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Abstract Vaccine hesitancy (VH) is an issue for healthcare students, influenced by safety concerns and misinformation. The need for better communication training and understanding sociocultural factors in VH was highlighted in a European University Alliance seminar. Practical exercises like simulation role-playing, interprofessional collaboration, and digital literacy may improve vaccine education.

Abstract Precipitation channelled down tree stems (stemflow) or into drip points of ‘throughfall’ beneath trees results in spatially concentrated inputs of water and chemicals to the ground. Currently, these flows are poorly characterised due to uncertainties about which branches redirect rainfall to stemflow or throughfall drip points. We introduce a graph theoretic algorithm that ‘prunes’ quantitative structural models of trees (derived from terrestrial LiDAR) to identify branches contributing to stemflow and those contributing to throughfall drip points. To demonstrate the method's utility, we analysed two trees with similar canopy sizes but contrasting canopy architecture and rainfall partitioning behaviours. For both trees, the branch ‘watershed’ area contributing to stemflow (under conditions assumed to represent moderate precipitation intensity) was found to be only half of the total ground area covered by the canopy. The study also revealed significant variations between trees in the number and median contribution areas of modelled throughfall drip points (69 vs. 94 drip points tree−1, with contributing projected areas of 28.6 vs. 7.8 m2 tree−1, respectively). Branch diameter, surface area, volumes and woody area index of components contributing to stemflow and throughfall drip points may play a role in the trees' differing rainfall partitioning behaviours. Our pruning algorithm, enabled by the proliferation of LiDAR observations of canopy structure, promises to enhance studies of canopy hydrology. It offers a novel approach to refine our understanding of how trees interact with rainfall, thereby broadening the utility of existing LiDAR data in environmental research.

Research on the growth mindset interventions (GMIs) on nonacademic outcomes is burgeoning. The present systematic review aims to evaluate the effects of GMIs on social-emotional outcomes among school-aged children and adolescents. Using the PRIMSA guidelines, our search across three electronic databases (PsycINFO, ERIC, and PubMed) yielded an initial identification of 1057 records. Inclusion criteria include publication format, language, participant age range, and intervention purpose, focus and components. Risk of bias was analyzed at the study level using a list of research quality indicators and across studies by comparing nonpeer reviewed versus peer reviewed publications. Our final sample yielded 13 papers including 14 studies. The findings from these studies were extracted to examine research quality, sample characteristics, intervention content, and intervention effects of the GMIs. Results showed despite that study quality, samples, and intervention designs varied, core components of the interventions were highly similar. Intervention effect results suggest that mindsets can be changed toward a growth orientation through brief GMIs, and effectiveness of GMIs on social-emotional outcomes is promising, especially in reducing depressive symptoms and aggressive reactions to perceived social exclusion. Research gaps and future directions, and implications for school psychologists and other mental health professionals are discussed.

Human Papillomavirus (HPV) vaccine coverage was

The last decade has seen substantial advances in the capacity to record behaviour and neural activity in humans in real-world settings, to simulate real-world situations in laboratory settings and to apply sophisticated analyses to large-scale data. Along with these developments, a growing number of groups has begun to advocate for real-world neuroscience and cognitive science. Here, we review the arguments and the available methods for real-world research and outline an overarching framework that embeds key ideas proposed in the literature integrating them into a cyclic process of ‘bringing the lab to the real world’ (recording behavioural and neural activity in real-world settings) and ‘bringing the real-world to the lab’ (manipulating the environments in which behaviours occur in the laboratory) that combines exploratory and confirmatory research and is interdisciplinary (including those sciences concerned with the natural, built or virtual environment). We highlight the benefits brought by this framework emphasizing the greater potential for novel discovery, theory development and human-centred applications to the environment.

Abstract Human interaction is immersed in laughter; though genuine and posed laughter are acoustically distinct, they are both crucial socio-emotional signals. In this novel study, autistic and non-autistic adults explicitly rated the affective properties of genuine and posed laughter. Additionally, we explored whether their self-reported everyday experiences with laughter differ. Both groups could differentiate between these two types of laughter. However, autistic adults rated posed laughter as more authentic and emotionally arousing than non-autistic adults, perceiving it to be similar to genuine laughter. Autistic adults reported laughing less, deriving less enjoyment from laughter, and experiencing difficulty in understanding the social meaning of other people’s laughter compared to non-autistic people. Despite these differences, autistic adults reported using laughter socially as often as non-autistic adults, leveraging it to mediate social contexts. Our findings suggest that autistic adults show subtle differences in their perception of laughter, which may be associated with their struggles in comprehending the social meaning of laughter, as well as their diminished frequency and enjoyment of laughter in everyday scenarios. By combining experimental evidence with first-person experiences, this study suggests that autistic adults likely employ different strategies to understand laughter in everyday contexts, potentially leaving them socially vulnerable in communication.

BackgroundDespite clinical suspicion, most non-invasive ischemia tests for coronary artery disease (CAD) reveal unremarkable results. Patients with a coronary artery calcium score (CACS) of zero rarely have an abnormal positron emission tomography (PET) and could be deferred from further testing. However, most patients have some extent of coronary calcification.ObjectivesCACS percentiles could be useful to exclude abnormal perfusion in patients with CACS >0, but data from patients with 82Rb PET are lacking. The aim of this study was to assess the diagnostic utility of CACS percentiles in comparison to zero calcium and absolute CACS classes.MethodsConsecutive patients with suspected CAD (n = 1,792) referred for 82Rb PET were included and analyzed for abnormal PET (SSS ≥4) and relevant ischemia (>10% myocardium). Test characteristics were calculated.ResultsThe mean age was 65 ± 11 years, 43% were female, and typical angina was reported in 21%. Abnormal PET/relevant ischemia (>10%) were observed in 19.8%/9.3%. Overall, the sensitivity/negative predictive value (NPV) of a 90.9% in all age groups.ConclusionIn patients >50 years, the 10%). They could be used to extend the scope of application of CACS 0 by 8%–10% to 32%–34% overall of patients who could be deferred from further testing.

The Dark Energy Spectroscopic Instrument (DESI) survey will measure spectroscopic redshifts for millions of galaxies across roughly $14,000 \, \mathrm{deg}^2$ of the sky. Cross-correlating targets in the DESI survey with complementary imaging surveys allows us to measure and analyze shear distortions caused by gravitational lensing in unprecedented detail. In this work, we analyze a series of mock catalogs with ray-traced gravitational lensing and increasing sophistication to estimate systematic effects on galaxy-galaxy lensing estimators such as the tangential shear $\gamma_{\mathrm{t}}$ and the excess surface density $\Delta\Sigma$. We employ mock catalogs tailored to the specific imaging surveys overlapping with the DESI survey: the Dark Energy Survey (DES), the Hyper Suprime-Cam (HSC) survey, and the Kilo-Degree Survey (KiDS). Among others, we find that fiber incompleteness can have significant effects on galaxy-galaxy lensing estimators but can be corrected effectively by up-weighting DESI targets with fibers by the inverse of the fiber assignment probability. Similarly, we show that intrinsic alignment and lens magnification are expected to be statistically significant given the precision forecasted for the DESI year-1 data set. Our study informs several analysis choices for upcoming cross-correlation studies of DESI with DES, HSC, and KiDS.

Abstract Background The systems approach has been used to evaluate higher education and explores inputs, transformation process, and outputs of a system that is also influenced by environmental factors such as COVID-19. The COVID-19 pandemic shifted many college students to different learning modes, changing their university experience. This study evaluated dietetics students’ education experiences and characteristics in the latter period (spring 2022) of the COVID-19 pandemic using the systems approach. Methods Researchers developed and distributed an electronic survey to all 215 US-based Didactic Program in Dietetics (DPD) directors during March to May 2022 to forward to their students. Researchers calculated descriptive statistics for variables related to inputs, transformation process, and outputs in the systems approach. Results Respondents (n = 341) represented 51 DPDs in 31 states in the United States. Overall, DPD students (88.5%) were mostly or very satisfied with their choice of majoring in dietetics. Most (84.0%) planned to earn the RDN credential. Nearly half (46.9%) of DPD students were somewhat or extremely concerned about their readiness to continue their dietetics education path due to the pandemic-related learning conditions. Most students (43.6%) reported dissatisfaction with asynchronous remote instruction in laboratory courses. DPD students’ GPAs remained consistent within the range of 3.75-4.0 from Fall 2019 (43.2%) to Spring 2022 (44.5%). The most important expectations of professors moving forward were to communicate effectively (97.3%), employ cultural humility (93.8%), eliminate discrimination in the classroom (93.6%), provide lecture slides (89.7%), and be flexible and accommodating (88.7%). Conclusions DPD students emerged from COVID-19 with new perspectives and expectations for their university learning experience. Future research should explore the perspectives of DI directors, preceptors, and employers of COVID-19 era DPD graduates.

Abstract Inflammation is one of the suggested pathways linking exposure to neighbourhood air pollution and greenspace to psychological distress. Yet, inflammation has not been tested formally as a mediating factor in an adult human sample. Using data from 6813 adults participating in Understanding Society, the present study examines longitudinally the joint role of the two neighbourhood‐level exposures in psychological distress and the mediating role of inflammation. Annual concentrations of nitrogen dioxide and availability of greenspace in participants' neighbourhoods across England and Wales were examined. Psychological distress was measured with the General Health Questionnaire. Inflammation was assessed with C‐reactive protein and fibrinogen. A structural equation model path analysis showed that, in fully adjusted models, an increase in the amount of greenspace in one's neighbourhood was related to lower psychological distress 4 years later, but inflammation did not mediate this relationship. Neighbourhood‐level air pollution, specifically nitrogen dioxide, was not associated with psychological distress. Read the free Plain Language Summary for this article on the Journal blog.

The ambient atmospheric environment affects the growth and spread of wildland fires, whereas heat and moisture released from the fires and the reduction of the surface drag in the burned areas can significantly alter local atmospheric conditions. Observational studies on fire–atmosphere interactions have used instrumented towers to collect data during prescribed fires, but a few towers in an operational-scale burn plot (usually > 103 m2) have made it extremely challenging to capture the myriad of factors controlling fire–atmosphere interactions, many of which exhibit strong spatial variability. Here, we present analyses of atmospheric turbulence data collected using a 4 × 4 array of fast-response sonic anemometers during a fire experiment on a 10 m × 10 m burn plot. In addition to confirming some of the previous findings on atmospheric turbulence associated with low-intensity surface fires, our results revealed substantial heterogeneity in turbulent intensity and heat and momentum fluxes just above the combustion zone. Despite the small plot (100 m2), fire-induced atmospheric turbulence exhibited strong dependence on the downwind distance from the initial line fire and the relative position specific to the fire front as the surface fire spread through the burn plot. This result highlights the necessity for coupled atmosphere–fire behavior models to have 1–2 m grid spacing to resolve heterogeneities in fire–atmosphere interactions that operate on spatiotemporal scales relevant to atmospheric turbulence. The findings here have important implications for modeling smoke dispersion, as atmospheric dispersion characteristics in the vicinity of a wildland fire are directly affected by fire-induced turbulence.

Abstract Support for vaccine decision-making requires a tailored approach taking into account psychological antecedents of vaccine acceptance. We aimed at validating an extended 7C-model of antecedents in three different target population groups (healthcare workers [n = 3870], parents [n = 2002] and adolescents [n = 7118]) and two vaccinations (COVID-19, HPV) in France. We performed a secondary analysis of questionnaires collecting sociodemographic characteristics, attitudes and knowledge on vaccination, and vaccine status and intention. We used standard psychometric techniques to validate a first and second order latent structure, and evaluated their association with vaccine intentionality in three levels (refusal, indecision, acceptance). In all populations, the 7C-model yielded a very good model fit (CFI and TLI > 0.90) and, in comparison with non-nested and nested 5C-models, significantly improved the model performance (Ω2, p

Abstract Introduction Despite various efforts to improve human papillomavirus (HPV) vaccine coverage in France, it has always been lower than in most other high‐income countries. The health authorities launched in 2018 the national PrevHPV research programme to (1) co‐develop with stakeholders and (2) evaluate the impact of a multicomponent complex intervention aimed at improving HPV vaccine coverage amongst French adolescents. Objective To describe the development process of the PrevHPV intervention using the GUIDance for rEporting of intervention Development framework as a guide. Methods To develop the intervention, we used findings from (1) published evidence on effective strategies to improve vaccination uptake and on theoretical frameworks of health behaviour change; (2) primary data on target populations' knowledge, beliefs, attitudes, preferences, behaviours and practices as well as the facilitators and barriers to HPV vaccination collected as part of the PrevHPV Programme and (3) the advice of working groups involving stakeholders in a participatory approach. We paid attention to developing an intervention that would maximise reach, adoption, implementation and maintenance in real‐world contexts. Results We co‐developed three components: (1) adolescents' and parents' education and motivation using eHealth tools (web conferences, videos, and a serious video game) and participatory learning at school; (2) general practitioners' e‐learning training on HPV using motivational interviewing techniques and provision of a decision aid tool and (3) easier access to vaccination through vaccination days organised on participating middle schools' premises to propose free of charge initiation of the HPV vaccination. Conclusion We co‐developed a multicomponent intervention that addresses a range of barriers and enablers of HPV vaccination. The next step is to build on the results of its evaluation to refine it before scaling it up if proven efficient. If so, it will add to the small number of multicomponent interventions aimed at improving HPV vaccination worldwide. Patient or Public Contribution The public (adolescents, their parents, school staff and health professionals) participated in the needs assessment using a mixed methods approach. The public was also involved in the components' development process to generate ideas about potential activities/tools, critically revise the successive versions of the tools and provide advice about the intervention practicalities, feasibility and maintenance.

In 2000, Seligman and Csikszentmihalyi published the highly influential “Positive Psychology: An Introduction” in American Psychologist, and with it, they advocated for a strengths-based approach for helping people live a “good life”. Building on that work, positive psychology was further conceptualized as consisting of meta-psychological and practical aspects. The meta-psychological constitutes the aims or “grand vision” of what positive psychology stands for, whereas the practical constitutes the “nuts-and-bolts” elements that should be focused on in developing interventions. In the present commentary, we build on this previous work to propose a “positive psychology pragmatic framework” to develop strengths-based interventions (SBIs) for use with special student populations; in this case, students with special needs and P-3 and gifted students. Relatedly, we review the empirical and theoretical/conceptual literature relevant to the use of SBIs within each subpopulation as well as discuss some characteristics that make each subpopulation unique. Consequently, to the highest degree possible, we advocate for integrating intrapersonal, interpersonal, contextual/environmental, systemic, and developmental factors in developing SBIs and we make specific recommendations for future research through the lens of this proposed framework.

Abstract Background Elimination of mother-to-child transmission of hepatitis B virus (HBV) requires infant immunoprophylaxis and antiviral prophylaxis for pregnant women with high viral loads. Since real-time polymerase chain reaction (RT-PCR), a gold standard for assessing antiviral eligibility, is neither accessible nor affordable for women living in low-income and middle-income countries (LMICs), rapid diagnostic tests (RDTs) detecting alternative HBV markers may be needed. To inform future development of the target product profile (TPP) for RDTs to identify highly viremic women, we used a discrete choice experiment (DCE) and elicited preference and trade-off of healthcare workers (HCW) in Africa between the following four attributes of fictional RDTs: price, time-to-result, diagnostic sensitivity, and specificity. Methods Through an online questionnaire survey, we asked participants to indicate their preferred test from a set of two RDTs in seven choice tasks with varying levels of the four attributes. We used mixed multinomial logit models to quantify the utility gain or loss generated by each attribute. We attempted to define minimal and optimal criteria for test attributes that can satisfy ≥ 70% and ≥ 90% of HCWs, respectively, as an alternative to RT-PCR. Results A total of 555 HCWs from 41 African countries participated. Increases in sensitivity and specificity generated significant utility and increases in cost and time-to-result generated significant disutility. The size of the coefficients for the highest attribute levels relative to the reference levels were in the following order: sensitivity (β = 3.749), cost (β = -2.550), specificity (β = 1.134), and time-to-result (β = -0.284). Doctors cared most about test sensitivity, while public health practitioners cared about cost and midwives about time-to-result. For an RDT with 95% specificity, costing 1 US$, and yielding results in 20 min, the minimally acceptable test sensitivity would be 82.5% and the optimally acceptable sensitivity would be 87.5%. Conclusions African HCWs would prefer an RDT with the following order of priority: higher sensitivity, lower cost, higher specificity, and shorter time-to-result. The development and optimization of RDTs that can meet the criteria are urgently needed to scale up the prevention of HBV mother-to-child transmission in LMICs.

BackgroundNon-participation in mental health studies is an under-explored but very important topic. Investigating reasons for non-participation holds promise for the planning of future study designs and recruitment strategies. This study aimed at investigating reasons for children and adolescents (C&A) not participating in a school-based mental health research project.MethodsData collection took place within the school-based recruitment of a large-scale multi-site project (“ProHEAD—Promoting Help-seeking using E-technology for Adolescents”) in Germany. Participants were N = 534 C&A aged ≥ 12 years attending secondary schools. The present cross-sectional study analyzed anonymous survey data of C&A who themselves or whose parents, respectively, did not provide written consent to participate in the mental health research project. The questionnaire consisted of 14 items covering potential reasons for non-participation, and four free text fields. Besides descriptive statistics, free text field answers were analyzed using qualitative content analysis.ResultsStudents indicated an average of M = 2.94 (SD = 1.75) reasons for their non-participation in the project. In the descriptive analysis of indicated items, the three most frequently reported reasons for non-participation included students reporting to not be concerned by the topic “mental health” (n = 290, 54.3%), not having returned the consent form to the teacher (n = 175, 32.8%), and not having time for participation (n = 149, 27.9%). In the qualitative content analysis, the most frequently assigned categories were organizational reasons (n = 216, 57.1%), general disinterest in study participation (n = 139, 36.8%), and personal attitudes toward the topic “mental health” (n = 84, 22.2%), such as not being concerned with the topic “mental health” (n = 23, 6.1%) or being too concerned with the topic “mental health” (n = 16, 4.2%).ConclusionThe study provides unique insights into reasons for C&A and their caregivers not participating in a large federally funded mental health research project. The results suggest that in order to increase participation rates, stigma should be reduced, parents as well as teachers should be involved where possible, and the use of incentives might be helpful. The study highlights the importance of assessing reasons for non-participation, especially in online intervention studies on mental health.

Abstract Much research focuses on increasing carbon storage in mineral-associated organic matter (MAOM), in which carbon may persist for centuries to millennia. However, MAOM-targeted management is insufficient because the formation pathways of persistent soil organic matter are diverse and vary with environmental conditions. Effective management must also consider particulate organic matter (POM). In many soils, there is potential for enlarging POM pools, POM can persist over long time scales, and POM can be a direct precursor of MAOM. We present a framework for context-dependent management strategies that recognizes soils as complex systems in which environmental conditions constrain POM and MAOM formation.

Young people with child welfare experience face significant barriers in accessing and completing post-secondary education. Barriers to post-secondary education often include various system-level factors related to access to college or university, including lack of high school completion, lack of institutional knowledge and familiarity with academic culture, low educational attainment and expectation bias, first in family to attend post-secondary, and financial constraints. These barriers can have lifelong consequences for these individuals, their families, and communities, including economic, social, and legal impacts. While tuition waiver programs are interventions aimed at addressing financial considerations, additional barriers to post-secondary education for this population continue to persist. Our research team undertook a scoping review to better understand the barriers facing former youth in care (FYIC) and how tuition waiver programs can address these challenges. Particularly, the aim of this scoping review was to understand how well Canada, as a signatory on the Sustainable Development Goals (SDGs), is achieving its commitment to addressing SDG 4, Quality Education, noting that tuition waiver programs for FYIC are a growing trend aimed at advancing SDG 4. This scoping review followed the methodology as described by Arksey and O'Malley (2005) and a total of 58 peer-reviewed articles met the inclusion criteria. These articles describe the variable requirements for acceptance into a tuition waiver program as well as the differing types of supports offered in tuition waiver programs aimed at FYIC.

Abstract Background HPV vaccine coverage in France remained lower than in most other high-income countries. Within the diagnostic phase of the national PrevHPV program, we carried out a mixed methods study among school staff to assess their knowledge, beliefs and attitudes regarding HPV, HPV vaccine and vaccination in general, and regarding schools’ role in promoting HPV vaccination. Methods Middle school nurses, teachers and support staff from four French regions participated between January 2020 and May 2021. We combined: (i) quantitative data from self-administered online questionnaires (n = 301), analysed using descriptive statistics; and (ii) qualitative data from three focus groups (n = 14), thematically analysed. Results Less than half of respondents knew that HPV can cause genital warts or oral cancers and only 18% that no antiviral treatment exists. Almost 90% of the respondents knew the existence of the HPV vaccine but some misunderstood why it is recommended before the first sexual relationships and for boys; 56% doubted about its safety, especially because they think there is not enough information on this topic. Schools nurses had greater knowledge than other professionals and claimed that educating pupils about HPV was fully part of their job roles; however, they rarely address this topic due to a lack of knowledge/tools. Professionals (school nurses, teachers and support staff) who participated in the focus groups were unfavourable to offering vaccination at school because of parents’ negative reactions, lack of resources, and perceived uselessness. Conclusions These results highlight the need to improve school staff knowledge on HPV. Parents should be involved in intervention promoting HPV vaccination to prevent their potential negative reactions, as feared by school staff. Several barriers should also be addressed before organizing school vaccination programs in France.

The A–B transition in superfluid 3He is a pure experimental model system to study first-order phase transitions in the early Universe. Tian et al. observe the path dependence of the supercooling of the A phase in a wide parameter range and provide explanations for the heterogeneous nucleation of the B phase.

Abstract Despite improved surveillance capacities and WHO recommendations for subdistrict analysis, routine epidemic surveillance of acute bacterial meningitis in the African meningitis belt remains largely limited to the district level. We evaluated the appropriateness and performance of analyses at higher spatial resolution. We used suspected meningitis surveillance data at health centre (HC) resolution from Burkina Faso from 14 health districts spanning years 2004–2014 and analysed them using spatio-temporal statistics and generative models. An operational analysis compared epidemic signals at district and HC-level using weekly incidence thresholds. Eighty-four percent (N = 98/116) of epidemic clusters spanned only one HC-week. Spatial propagation of epidemic clusters was mostly limited to 10–30 km. During the 2004–2009 (with serogroup A meningitis) and 2010–2014 (after serogroup A elimination) period, using weekly HC-level incidence thresholds of 100 and 50 per 100,000 respectively, we found a gain in epidemic detection and timeliness in 9 (41% of total) and 10 (67%), respectively, district years with at least one HC signal. Individual meningitis epidemics expanded little in space, suggesting that a health centre level analysis is most appropriate for epidemic surveillance. Epidemic surveillance could gain in precision and timeliness by higher spatial resolution. The optimal threshold should be defined depending on the current background incidence of bacterial meningitis.

We present the Ly α Continuum Analysis Network (LyCAN), a convolutional neural network that predicts the unabsorbed quasar continuum within the rest-frame wavelength range of 1040–1600 Å based on the red side of the Ly α emission line (1216–1600 Å). We developed synthetic spectra based on a Gaussian mixture model representation of nonnegative matrix factorization (NMF) coefficients. These coefficients were derived from high-resolution, low-redshift ( z < 0.2) Hubble Space Telescope/Cosmic Origins Spectrograph (COS) quasar spectra. We supplemented this COS-based synthetic sample with an equal number of DESI Year 5 mock spectra. LyCAN performs extremely well on testing sets, achieving a median error in the forest region of 1.5% on the DESI mock sample, 2.0% on the COS-based synthetic sample, and 4.1% on the original COS spectra. LyCAN outperforms principal component analysis (PCA) and NMF-based prediction methods using the same training set by 40% or more. We predict the intrinsic continua of 83,635 DESI Year 1 spectra in the redshift range of 2.1 ≤ z ≤ 4.2 and perform an absolute measurement of the evolution of the effective optical depth. This is the largest sample employed to measure the optical depth evolution to date. We fit a power law of the form $\tau {(z)={\tau }_{0}(1+z)}^{\gamma }$ to our measurements and find τ _0 = (2.46 ± 0.14) × 10 ^−3 and γ = 3.62 ± 0.04. Our results show particular agreement with high-resolution, ground-based observations around z = 2, indicating that LyCAN is able to predict the quasar continuum in the forest region with only spectral information outside the forest.

The Dark Energy Spectroscopic Instrument (DESI) is a revolutionary instrument designed for precise measurements of cosmic distances and the investigation of dark energy. DESI utilizes 5000 optical fibers to simultaneously measure the spectra of distant objects and aims to measure 40 million galaxies and quasars in a 5 yr survey. One of the critical challenges to DESI’s success was ensuring that the fiber system was not only highly efficient but also delivered a highly stable beam enabling more reliable sky subtraction for measurements of faint objects. We achieved this stability by minimizing the stress on the fiber system during the manufacture and operation of the telescope and fiber positioning robots. We installed the DESI fiber system on the 4 m Mayall telescope with ≥99% of fibers intact, and the instrument has delivered superb optical performance throughout the initial years of the DESI survey, including ≥90% average throughput when injected with a focal ratio of ∼ f /3.9 as delivered by the primary focus corrector, excluding fiber absorption losses. The design of DESI required multiple innovations to achieve these requirements, such as cleaved fibers bonded with a UV-curing epoxy to glass ferrules in the focal plane and fusion splicing instead of physical connectors. In this paper, we describe the development, delivery, and installation of the fiber system, the innovations that made the state-of-the-art performance possible, and the key lessons learned that could benefit future projects.

We present a computationally efficient galaxy archetype-based redshift estimation and spectral classification method for the Dark Energy Survey Instrument (DESI) survey. The DESI survey currently relies on a redshift fitter and spectral classifier using a linear combination of principal component analysis–derived templates, which is very efficient in processing large volumes of DESI spectra within a short time frame. However, this method occasionally yields unphysical model fits for galaxies and fails to adequately absorb calibration errors that may still be occasionally visible in the reduced spectra. Our proposed approach improves upon this existing method by refitting the spectra with carefully generated physical galaxy archetypes combined with additional terms designed to absorb data reduction defects and provide more physical models to the DESI spectra. We test our method on an extensive data set derived from the survey validation (SV) and Year 1 (Y1) data of DESI. Our findings indicate that the new method delivers marginally better redshift success for SV tiles while reducing catastrophic redshift failure by 10%–30%. At the same time, results from millions of targets from the main survey show that our model has relatively higher redshift success and purity rates (0.5%–0.8% higher) for galaxy targets while having similar success for QSOs. These improvements also demonstrate that the main DESI redshift pipeline is generally robust. Additionally, it reduces the false-positive redshift estimation by 5%−40% for sky fibers. We also discuss the generic nature of our method and how it can be extended to other large spectroscopic surveys, along with possible future improvements.

The Dark Energy Spectroscopic Instrument (DESI) completed its 5 month Survey Validation in 2021 May. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This paper describes the public release of those spectra, the catalogs of derived properties, and the intermediate data products. In total, the public release includes good-quality spectral information from 466,447 objects targeted as part of the Milky Way Survey, 428,758 as part of the Bright Galaxy Survey, 227,318 as part of the Luminous Red Galaxy sample, 437,664 as part of the Emission Line Galaxy sample, and 76,079 as part of the Quasar sample. In addition, the release includes spectral information from 137,148 objects that expand the scope beyond the primary samples as part of a series of secondary programs. Here, we describe the spectral data, data quality, data products, Large-Scale Structure science catalogs, access to the data, and references that provide relevant background to using these spectra.

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg ^2 over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI was evaluated during a 5 month survey validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar Milky Way Survey (MWS), Bright Galaxy Survey (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the 5 yr program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a One-Percent Survey conducted at the conclusion of SV covering 140 deg ^2 using the final target selection algorithms with exposures of a depth typical of the main survey. The SV indicates that DESI will be able to complete the full 14,000 deg ^2 program with spectroscopically confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval z < 1.1, 0.39% over the redshift interval 1.1 < z < 1.9, and 0.46% over the redshift interval 1.9 < z < 3.5.

Seasonal influenza vaccination rates remain low, and contribute to preventable influenza cases, hospitalizations, and deaths in the US. While numerous interventions have been implemented to increase vaccine uptake, there is a need to determine which interventions contribute most to vaccine willingness, particularly among age groups with vaccination rates that have plateaued at suboptimal levels. This study aimed to quantify the relative effect of multiple interventions on vaccine willingness to receive influenza vaccine in three age groups using a series of hypothetical situations with different behavioral interventions.We assessed the relative impact of four categories of interventions: source of vaccine messages, type of vaccination messages, vaccination incentives, and ease of vaccine access using a discrete choice experiment. Within each category, we investigated the role of four different attributes to measure their relative contribution to willingness to be vaccinated by removing one option from each of the intervention categories. Among the 1,763 Minnesota residents who volunteered for our study, participants expressed vaccine willingness in over 80% of the scenarios presented. Easy access to drop-in vaccination sites had the greatest impact on vaccine willingness in all age groups. Among the younger age group, small financial incentives also contributed to high vaccine willingness.Our results suggest that public health programs and vaccination campaigns may improve their chances of successfully increasing vaccine willingness if they offer interventions preferred by adults, including facilitating convenient access to vaccination and offering small monetary incentives, particularly for young adults.

Improvements in computational and experimental capabilities are rapidly increasing the amount of scientific data that are routinely generated. In applications that are constrained by memory and computational intensity, excessively large datasets may hinder scientific discovery, making data reduction a critical component of data-driven methods. Datasets are growing in two directions: the number of data points and their dimensionality. Whereas dimension reduction typically aims at describing each data sample on lower-dimensional space, the focus here is on reducing the number of data points. A strategy is proposed to select data points such that they uniformly span the phase-space of the data. The algorithm proposed relies on estimating the probability map of the data and using it to construct an acceptance probability. An iterative method is used to accurately estimate the probability of the rare data points when only a small subset of the dataset is used to construct the probability map. Instead of binning the phase-space to estimate the probability map, its functional form is approximated with a normalizing flow. Therefore, the method naturally extends to high-dimensional datasets. The proposed framework is demonstrated as a viable pathway to enable data-efficient machine learning when abundant data are available.

BackgroundThe COVID-19 pandemic has had an impact on nearly all people. Vaccines provide an effective tool to combat the pandemic, however, vaccination hesitancy remains an issue. This study aims to investigate (a) students' attitudes toward the pandemic, (b) potential differences in attitudes between university students and the general population, and (c) to examine predictors of vaccination intention in both samples.MethodsIn this cross-sectional study data from two research projects were analyzed and compared. First, attitudes toward the COVID-19 pandemic in German university students were assessed within a cross-sectional anonymous online survey (March-April 2021, N = 5,639) and analyzed quantitatively and also qualitatively (free text field answers examined positive and negative aspects of the pandemic). Second, data from a cross-sectional survey within the COVID-19 Snapshot Monitoring project (COSMO; 29th wave of data collection, December 2020, N = 1,387) in the German general population was analyzed. Both samples, were compared in sharedly used variables, regarding attitudes toward the pandemic and vaccination intention, and factors associated with vaccination (logistic regression analyses).ResultsIn comparison to the general population, university students were significantly more likely to report being worried about/thinking about the coronavirus and to perceive the coronavirus as overrepresented in the media (all p < 0.001). University students reported a more supportive attitude toward vaccinations in general (students: M = 4.57, SD = 0.85; general population: M = 3.92, SD = 1.27) and a significantly higher vaccination intention (students: n = 4,438, 78.7%; general population: n = 635, 47.7%) than the general population (p < 0.001). Regression analyses revealed that in university students, vaccination intention was significantly predicted by not having children, a supporting attitude toward vaccinations in general, the belief that the coronavirus is overrepresented in the media, and less thinking about/worrying about the coronavirus (all p < 0.05). In the general population, vaccination intention was significantly associated with male gender, higher age, not having children, a supporting attitude toward vaccinations in general, and the belief that the coronavirus is overrepresented in the media (p < 0.05). The qualitative analysis among university students revealed that the most frequently stated positive aspect of the pandemic was to be more flexible due to digitalization (n = 1,301 statements, 22.2%) and the most frequently stated negative aspect was restriction in social life (n = 3,572 statements, 24.2%).ConclusionThe results indicate differences in the attitudes toward the pandemic between university students and the general population. In addition, differences regarding factors associated with vaccination intention were found in both samples. These results could be important to be considered when designing and targeting vaccination campaigns aiming at informing different population or age groups.Study registrationDRKS00022424.

BackgroundVolumetric measurements of fetal brain maturation in the third trimester of pregnancy are key predictors of developmental outcomes. Improved understanding of fetal brain development trajectories may aid in identifying and clinically managing at-risk fetuses. Currently, fetal brain structures in magnetic resonance images (MRI) are often manually segmented, which requires both time and expertise. To facilitate the targeting and measurement of brain structures in the fetus, we compared the results of five segmentation methods applied to fetal brain MRI data to gold-standard manual tracings.MethodsAdult women with singleton pregnancies (n = 21), of whom five were scanned twice, approximately 3 weeks apart, were recruited [26 total datasets, median gestational age (GA) = 34.8, IQR = 30.9–36.6]. T2-weighted single-shot fast spin echo images of the fetal brain were acquired on 1.5T and 3T MRI scanners. Images were first combined into a single 3D anatomical volume. Next, a trained tracer manually segmented the thalamus, cerebellum, and total cerebral volumes. The manual segmentations were compared with five automatic methods of segmentation available within Advanced Normalization Tools (ANTs) and FMRIB’s Linear Image Registration Tool (FLIRT) toolboxes. The manual and automatic labels were compared using Dice similarity coefficients (DSCs). The DSC values were compared using Friedman’s test for repeated measures.ResultsComparing cerebellum and thalamus masks against the manually segmented masks, the median DSC values for ANTs and FLIRT were 0.72 [interquartile range (IQR) = 0.6–0.8] and 0.54 (IQR = 0.4–0.6), respectively. A Friedman’s test indicated that the ANTs registration methods, primarily nonlinear methods, performed better than FLIRT (p < 0.001).ConclusionDeformable registration methods provided the most accurate results relative to manual segmentation. Overall, this semi-automatic subcortical segmentation method provides reliable performance to segment subcortical volumes in fetal MR images. This method reduces the costs of manual segmentation, facilitating the measurement of typical and atypical fetal brain development.

Ionic pseudopotentials are widely used in classical simulations of materials to model the effective potential due to the nucleus and the core electrons. Modeling fewer electrons explicitly results in a reduction in the number of plane waves needed to accurately represent the states of a system. In this work, we introduce a quantum algorithm that uses pseudopotentials to reduce the cost of simulating periodic materials on a quantum computer. We use a qubitization-based quantum phase estimation algorithm that employs a first-quantization representation of the Hamiltonian in a plane-wave basis. We address the challenge of incorporating the complexity of pseudopotentials into quantum simulations by developing highly-optimized compilation strategies for the qubitization of the Hamiltonian. This includes a linear combination of unitaries decomposition that leverages the form of separable pseudopotentials. Our strategies make use of quantum read-only memory subroutines as a more efficient alternative to quantum arithmetic. We estimate the computational cost of applying our algorithm to simulating lithium-excess cathode materials for batteries, where more accurate simulations are needed to inform strategies for gaining reversible access to the excess capacity they offer. We estimate the number of qubits and Toffoli gates required to perform sufficiently accurate simulations with our algorithm for three materials: lithium manganese oxide, lithium nickel-manganese oxide, and lithium manganese oxyfluoride. Our optimized compilation strategies result in a pseudopotential-based quantum algorithm with a total Toffoli cost four orders of magnitude lower than the previous state of the art for a fixed target accuracy.

The paper deals with the peculiarities of the German-language pedagogical discourse, in particular teachers’ oral speech. Pedagogical discourse as a type of institutional discourse is characterised by a pronounced cultural component related to the differences in educational systems, traditions and modern practices of communicative interaction between teachers and students. The aim of the study is to analyse teachers’ evaluative and facilitative strategies which are implemented in the speech acts of criticism and praise. The examples under review are borrowed from German-language speech resources that teachers in German schools are recommended to use in class. To thematically differentiate between the objects of praise and criticism of students the article is based on contextual analysis, which helps to describe the speech acts of praise and censure, using the procedure of detecting teachers’ intention. The analysis of the grammatical and syntactic construction of the utterances makes it possible to determine the linguistic means of implementing praise and criticism in the German-language teacher discourse and to identify the corpus of linguistic means whose main function is to increase or decrease the semantic and emotional significance of the utterance components.

Half-cell gas diffusion electrode (GDE) setups have recently been shown to allow characterization of oxygen reduction reaction (ORR) catalysts at fuel cell relevant current densities and potentials while offering the advantage of fast screening and requiring only minimal sample usage. Most recently, publications suggesting best practices for GDE half-cell characterization have highlighted key challenges in running GDE experiments and have presented measurement protocols that allow excellent Inter-lab comparability. This step can be seen as the cornerstone for broad-based utilization of GDE half-cells. However, what is still missing, is an understanding of what limits the maximum achievable current density in GDE measurements. In this study we highlight the influence of various setup parameters (electrode area, electrolyte concentration, as well as size and position of the counter electrode) on the maximum achievable current density in an automated GDE setup. Furthermore, we present the metrics that need to be considered when adapting the electrochemical protocol for recording ORR polarization curves at higher current densities. The findings observed in this study are not limited to testing the ORR, but can be transferred to any other electrocatalytic reaction tested in a half-cell GDE at high current densities.

Abstract Background Equine degenerative suspensory ligament desmitis (DSLD) is a systemic connective tissue disorder first identified in Peruvian Paso horses but afflicting other horse breeds as well. Inappropriate accumulation of proteoglycans in connective tissues, most prominently in tendons and ligaments, leads to progressive and debilitating lameness and pain. It is largely unknown what drives the overproduction of proteoglycans, but our previous studies suggest involvement of bone morphogenetic protein 2 (BMP2), a member of the transforming growth factor-β (TGFβ) family, impacting synthesis of proteoglycans. To identify potential players in pathogenesis of DSLD a new approach utilizing next generation sequencing was undertaken. Methods Next generation sequencing was performed using RNA extracted from skin biopsies of six control Peruvian Pasos and six horses with DSLD (4 Peruvian Pasos and 2 warmbloods). The CuffDiff result sets were validated with algorithms used to run them. This was based on the determined false discovery rates derived from the P values adjusted for multiple testing for any given result. Results Bioinformatics analysis of transcriptomes revealed differential expression of over 1500 genes, including increased expression of genes for several growth factors (most prominently BMP2, FGF5, CTGF, many members of the EGF family), and mediators of signaling (Fos, Myc, MAPK system), and keratins. Two genes encoding for enzymes involved in synthesis of hyaluronan were also overexpressed. Gene expression was decreased for protein cores of many proteoglycans, several growth factors, most collagens, and many peptides with immune function. Conclusions The overexpression of BMP2 correlates well with our previous data. However, the decrease in expression of numerous proteoglycans was unexpected. A mutation in a gene of a less characterized proteoglycan and/or glycosyltransferase with subsequent increased production of hyaluronan and/or a proteoglycan(s) undetected in our study could account for the systemic proteoglycan deposition. Decreased collagen gene expression indicates abnormal connective tissue metabolism. The increased expression of keratin genes and FGF5 supports reports of skin abnormalities in DSLD. Underexpression of immune function genes corresponds with lack of inflammation in DSLD tissues. Finally, though the proteoglycan and/or glycosaminoglycan abundant in DSLD has not been identified, we validated our previous data, including overexpression of BMP2, and systemic nature of DSLD due to disturbed metabolism of the extracellular matrix.

Superfluid 3He under confinement can be used as a model system for topological quantum matter, but few related measurements are reported. Here, the authors report on the thermal conduction of helium-3 in a micro-fabricated channel with unanticipated effects in both the normal and superfluid states.

Dopamine neurons are proposed to signal the reward prediction error in model-free reinforcement learning algorithms. Here, the authors show that when given during an associative learning task, optogenetic activation of dopamine neurons causes associative, rather than value, learning.

Background: We previously conducted a single-profile discrete choice experiment to elicit preferences of adolescents around HPV vaccine communication, finding that only half of participants made variable choices (non-uniform respondents) from which preferences were elicited. In this paper we provide a framework to evaluate post-choice certainty information to elicit preferences even among respondents who uniformly accepted (serial demanders) or refused (serial non-demanders) hypothetical vaccination scenarios. Methods: During an in-class online questionnaire among 1458 French adolescents aged 13–15 years old, we collected certainty levels (0–10) after decisions on nine hypothetical scenarios, including four vaccination attributes: information on vaccine-preventable disease type, on vaccine safety, on potential for indirect protection and on vaccine coverage. We developed a vaccine eagerness scale (ranging from −10 to 10), by combining information on the binary decision (accept vs. refuse the hypothetical vaccine) and the decision certainty level. We used random effects linear regressions to evaluate attributes’ impact on vaccine eagerness. Sensitivity analyses were performed taking into account low response quality, assessed as invariant certainty and low response time. Results: Attributes’ impact on decision certainty were similar between serial demanders (N = 659) and non-uniform respondents (N = 711): mentioning a positive benefit-risk balance significantly decreased certainty to accept (coefficient −0.93), while information on 80% coverage in other countries (+0.33) and potential for disease elimination (+0.09) increased it. Among serial non-demanders, significant attribute impacts were observed only after exclusion of low-quality responses (N = 31): a potential for disease elimination (coefficient: +0.24) and 80% coverage in other countries (+0.42) significantly increased certainty of refusing vaccination. Combining decision and certainty into a vaccine eagerness indicator allowed analysing preferences in the full sample, including “hesitant” respondents, who were sensitive to the content of the vaccination profile. Conclusion: Choice certainty informs on respondents’ preferences in single-profile discrete-choice experiments, in particular among those with uniform responses.

Introduction Vaccination is an effective and safe strategy to prevent Human papillomavirus (HPV) infection and related harms. Despite various efforts by French authorities to improve HPV vaccine coverage (VC) these past few years, VC has remained far lower than in most other high-income countries. To improve it, we have coconstructed with stakeholders a school-based and primary care-based multicomponent intervention, and plan to evaluate its effectiveness, efficiency and implementation through a cluster randomised controlled trial (cRCT).Methods and analysis This pragmatic cRCT uses an incomplete factorial design to evaluate three components applied alone or in combination: (1) adolescents and parents’ education and motivation at school, using eHealth tools and participatory learning; (2) general practitioners’ training on HPV using motivational interviewing techniques and provision of a decision aid tool; (3) free-of-charge access to vaccination at school. Eligible municipalities (clusters) are located in one of 14 preselected French school districts and must have only one secondary school which enrols at least 2/3 of inhabitants aged 11–14 years. A randomisation stratified by school district and deprivation index allocated 90 municipalities into 6 groups of 15. The expected overall sample size estimate is 41 940 adolescents aged 11–14 years. The primary endpoint is the HPV VC (≥1 dose) among adolescents aged 11–14 years, at 2 months, at the municipality level (data from routine databases). Secondary endpoints include: HPV VC (≥1 dose at 6 and 12 months; and 2 doses at 2, 6 and 12 months); differences in knowledge, attitudes, behaviours, and intention among adolescents, parents and general practitioners between baseline and 2 months after intervention (self-administered questionnaires); incremental cost-effectiveness ratio. Implementation measures include dose, fidelity, adaptations, reached population and satisfaction (activity reports and self-administered questionnaires).Ethics and dissemination This protocol was approved by the French Ethics Committee ‘CPP Sud-Est VI’ on 22 December 2020 (ID-RCB: 2020-A02031-38). No individual consent was required for this type of research; all participants were informed of their rights, in particular not to participate or to oppose the collection of data concerning them. Findings will be widely disseminated (conference presentations, reports, factsheets and academic publications).Trial registration number NCT04945655.

Silicon is widely used in the semiconductor industry and has recently become very attractive as a lithium ion battery anode due to its high capacity. However, volume changes associated with repeated lithiation–delithiation cycles expose fresh silicon surfaces to the electrolyte, causing irreversible side reactions. Moreover, silicon suffers from a poor electronic conductivity at a low lithium content. Carbon impurities originating at synthesis or resulting from subsequent contact with other electrode components are often neglected. However, atomistic simulations reveal that dissolved carbon decreases the local potential energy surface by drawing the electron density from silicon to form polar covalent C–Si bonds that are stronger than the non-polar covalent Si–Si bonds they replace. This leads to a higher density and elastic stiffness, regardless of the interstitial lithium concentration. Substitutional carbon also reduces the mobility of silicon self-vacancies and interstitial lithium by increasing their diffusion barriers by 24.7 and 27.3 kJ mol−1, respectively. Moreover, the [carbon, silicon vacancy] complex is basically stable, while the [carbon, lithium] complex is found to become stable against both single defects at a spacing of 4.72 Å. The minimum energy paths ultimately demonstrate that both the interstitialcy and dissociative mechanisms are mainly responsible for carbon diffusion in silicon.

BackgroundThere is a critical need to identify the drivers of willingness to receive new vaccines against emerging and epidemic diseases. A discrete choice experiment is the ideal approach to evaluating how individuals weigh multiple attributes simultaneously. We assessed the degree to which six attributes were associated with willingness to be vaccinated among university students in Uganda.MethodsWe conducted a single-profile discrete choice experiment at Makerere University in 2019. Participants were asked whether or not they would be vaccinated in 8 unique scenarios where attributes varied by disease risk, disease severity, advice for or against vaccination from trusted individuals, recommendations from influential figures, whether the vaccine induced indirect protection, and side effects. We calculated predicted probabilities of vaccination willingness using mixed logistic regression models, comparing health professional students with all other disciplines.FindingsOf the 1576 participants, 783 (49.8%) were health professional students and 685 (43.5%) were female. Vaccination willingness was high (78%), and higher among health students than other students. We observed the highest vaccination willingness for the most severe disease outcomes and the greatest exposure risks, along with the Minister of Health's recommendation or a vaccine that extended secondary protection to others. Mild side effects and recommendations against vaccination diminished vaccination willingness.InterpretationOur results can be used to develop evidence-based messaging to encourage uptake for new vaccines. Future vaccination campaigns, such as for COVID-19 vaccines in development, should consider acknowledging individual risk of exposure and disease severity and incorporate recommendations from key health leaders.

Mental health and well-being in adolescence are associated with many short- and long-term outcomes. The evidence suggests that greenspace may play a role in adolescents' mental well-being, but we do not know much about the specifics of this link. In this paper, we investigated the role of other factors in the association. In a cross-sectional study, we investigated the role of neighbourhood greenspace in emotional and behavioural outcomes in 11-year-old urban adolescents participating in the UK Millennium Cohort Study (n = 4,534). We used linear regression models to test for an association of greenspace with self-esteem, happiness, positive mood, negative mood, and antisocial behaviour. We also investigated effect modification/moderation by garden access, physical activity, and perceived area safety. We did not find a main effect of greenspace, but we did find interaction effects. First, in adolescents without a garden, higher levels of greenspace were associated with lower levels of self-esteem and positive mood. Second, in adolescents who reported lower levels of physical activity, higher levels of greenspace were associated with lower levels of negative mood. Third, in adolescents who perceived their areas to be unsafe, higher levels of greenspace were associated with higher levels of antisocial behaviour. Our findings suggest that merely more greenspace in the neighbourhood may not be sufficient to promote the mental well-being of urban adolescents in the UK. However, greenspace does seem to have an influence under certain conditions which should be investigated further in future studies.

This paper examines wage premiums – the difference in this case in wages between public and private sector employees – in administrative and nonadministrative jobs at different levels of the public sector and various sectors of private industry. The comparisons can then be used to determine how potential savings could be realized through cuts to public sector compensation. The public sector generally pays better than the private sector in Alberta, although the high-paying oil and gas industry in the province means the wage gap is not radically large and is even negative in some cases.

The underlying transcriptional and cellular events mediating the reduction of dendritic spines on medium spiny neurons of the nucleus accumbens (NAc) remains unknown. Here, authors demonstrate that heroin self-administration negatively regulates the actin-binding protein drebrin in the NAc, which is shown to be transcriptionally repressed by the histone modifier HDAC2, and that overexpression of drebrin is sufficient to decrease drug seeking and increase dendritic spine density

BackgroundThe Eliminate Yellow fever Epidemics (EYE) strategy was launched in 2017 in response to the resurgence of yellow fever in Africa and the Americas. The strategy relies on several vaccination activities, including preventive mass vaccination campaigns (PMVCs). However, to what extent PMVCs are associated with a decreased risk of outbreak has not yet been quantified.Methods and findingsWe used the self-controlled case series (SCCS) method to assess the association between the occurrence of yellow fever outbreaks and the implementation of PMVCs at the province level in the African endemic region. As all time-invariant confounders are implicitly controlled for in the SCCS method, this method is an alternative to classical cohort or case-control study designs when the risk of residual confounding is high, in particular confounding by indication. The locations and dates of outbreaks were identified from international epidemiological records, and information on PMVCs was provided by coordinators of vaccination activities and international funders. The study sample consisted of provinces that were both affected by an outbreak and targeted for a PMVC between 2005 and 2018. We compared the incidence of outbreaks before and after the implementation of a PMVC. The sensitivity of our estimates to a range of assumptions was explored, and the results of the SCCS method were compared to those obtained through a retrospective cohort study design. We further derived the number of yellow fever outbreaks that have been prevented by PMVCs. The study sample consisted of 33 provinces from 11 African countries. Among these, the first outbreak occurred during the pre-PMVC period in 26 (79%) provinces, and during the post-PMVC period in 7 (21%) provinces. At the province level, the post-PMVC period was associated with an 86% reduction (95% CI 66% to 94%, p < 0.001) in the risk of outbreak as compared to the pre-PMVC period. This negative association between exposure to PMVCs and outbreak was robustly observed across a range of sensitivity analyses, especially when using quantitative estimates of vaccination coverage as an alternative exposure measure, or when varying the observation period. In contrast, the results of the cohort-style analyses were highly sensitive to the choice of covariates included in the model. Based on the SCCS results, we estimated that PMVCs were associated with a 34% (95% CI 22% to 45%) reduction in the number of outbreaks in Africa from 2005 to 2018. A limitation of our study is the fact that it does not account for potential time-varying confounders, such as changing environmental drivers of yellow fever and possibly improved disease surveillance.ConclusionsIn this study, we provide new empirical evidence of the high preventive impact of PMVCs on yellow fever outbreaks. This study illustrates that the SCCS method can be advantageously applied at the population level in order to evaluate a public health intervention.

BackgroundTo adapt communications concerning vaccine prevention, we studied knowledge, beliefs and practices around meningitis risk and prevention in a young adult population in Burkina Faso in 2016, 5 years after the MenAfriVac® mass campaign and one year before the vaccine's inclusion in the infant immunization schedule.MethodsIn a representative sample of the population aged 15 to 33 years (N = 220) in Bobo-Dioulasso, Burkina Faso, study nurses administered a standardized paper questionnaire consisting of predominantly open questions, collecting information on meningitis risk factors and prevention, and on exposure to dry air and kitchen fire smoke. We identified themes and analyzed their frequency. We created a meningitis knowledge score (range 0 to 4) based on pre-defined best responses and analyzed the determinants of knowledge score levels ≥2 (basic score) and ≥3 (high score) using multivariate logistic regression.ResultsBiomedically supported facts and good practices were known by the majority of participants (eg vaccine prevention, 84.5%). Younger women aged 15-20 years had a higher frequency of low scores DiscussionThis study shows a gender gap in knowledge of meningitis risk and prevention, largely due to education-level inequalities. Women below 21 years had particularly low levels of knowledge and may need interventions outside schools and perinatal care. Our study suggests a strong adherence to local understandings of and practices around meningitis risk and prevention, which should be taken into account by vaccination promotion.

The Dark Energy Spectroscopic Instrument (DESI) embarked on an ambitious 5 yr survey in 2021 May to explore the nature of dark energy with spectroscopic measurements of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the baryon acoustic oscillation method to measure distances from the nearby universe to beyond redshift z > 3.5, and employ redshift space distortions to measure the growth of structure and probe potential modifications to general relativity. We describe the significant instrumentation we developed to conduct the DESI survey. This includes: a wide-field, 3.°2 diameter prime-focus corrector; a focal plane system with 5020 fiber positioners on the 0.812 m diameter, aspheric focal surface; 10 continuous, high-efficiency fiber cable bundles that connect the focal plane to the spectrographs; and 10 identical spectrographs. Each spectrograph employs a pair of dichroics to split the light into three channels that together record the light from 360–980 nm with a spectral resolution that ranges from 2000–5000. We describe the science requirements, their connection to the technical requirements, the management of the project, and interfaces between subsystems. DESI was installed at the 4 m Mayall Telescope at Kitt Peak National Observatory and has achieved all of its performance goals. Some performance highlights include an rms positioner accuracy of better than 0.″1 and a median signal-to-noise ratio of 7 of the [O ii ] doublet at 8 × 10 ^−17 erg s ^−1 cm ^−2 in 1000 s for galaxies at z = 1.4–1.6. We conclude with additional highlights from the on-sky validation and commissioning, key successes, and lessons learned.