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Objectives: The COVID-19 pandemic impacted food systems, health systems and the environment globally, with potentially greater negative effects in many lower-middle income countries (LMICs) including Indonesia. The purpose of this qualitative study was to investigate the potential impacts of the COVID-19 pandemic on diets, health and the marine environment in Indonesia, based on the perspectives of a multidisciplinary group of informants. Methods: We conducted remote in-depth interviews with 27 key informants from many regions of Indonesia, who are either healthcare providers, nutrition researchers or environmental researchers. Interview question guides were developed based on a socio-ecological framework. We analyzed the data using a qualitative content analysis approach. Results: Informants suggested that while the COVID-19 brought increased awareness about and adherence to good nutrition and health behaviors, the impact was transitory. Informants indicated that healthy food options became less affordable, due to job losses and reduced income, suggesting a likely increase in food insecurity and obesity. Environmental researchers described higher levels of marine pollution from increase in hygienic wastes as well as from plastic packaging from food orders. Conclusions: Our findings reveal perceptions by informants that the increased awareness and adherence to health behaviors observed during the pandemic was not sustained. Our results also suggest that the pandemic may have exacerbated the double-burden paradox and marine pollution in Indonesia. This study offers information for generating hypotheses for quantitative studies to corroborate our findings and inform policies and programs to mitigate the long-term impacts of the COVID-19 on diets, health, and the marine environment in Indonesia. 

Public health agencies routinely collect time-referenced records to describe and compare foodborne outbreak characteristics. Few studies provide comprehensive metadata to inform researchers of data limitations prior to conducting statistical modeling. We described the completeness of 103 variables for 22,792 outbreaks publicly reported by the United States Centers for Disease Control and Prevention’s (US CDC’s) electronic Foodborne Outbreak Reporting System (eFORS) and National Outbreak Reporting System (NORS). We compared monthly trends of completeness during eFORS (1998–2008) and NORS (2009–2019) reporting periods using segmented time series analyses adjusted for seasonality. We quantified the overall, annual, and monthly completeness as the percentage of outbreaks with blank records per our study period, calendar year, and study month, respectively. We found that outbreaks of unknown genus (n = 7401), Norovirus (n = 6414), Salmonella (n = 2872), Clostridium (n = 944), and multiple genera (n = 779) accounted for 80.77% of all outbreaks. However, crude completeness ranged from 46.06% to 60.19% across the 103 variables assessed. Variables with the lowest crude completeness (ranging 3.32–6.98%) included pathogen, specimen etiological testing, and secondary transmission traceback information. Variables with low (<35%) average monthly completeness during eFORS increased by 0.33–0.40%/month after transitioning to NORS, most likely due to the expansion of surveillance capacity and coverage within the new reporting system. Examining completeness metrics in outbreak surveillance systems provides essential information on the availability of data for public reuse. These metadata offer important insights for public health statisticians and modelers to precisely monitor and track the geographic spread, event duration, and illness intensity of foodborne outbreaks. 

ABSTRACT The rapid expansion of food and nutrition information requires new ways of data sharing and dissemination. Interactive platforms integrating data portals and visualization dashboards have been effectively utilized to describe, monitor, and track information related to food and nutrition; however, a comprehensive evaluation of emerging interactive systems is lacking. We conducted a systematic review on publicly available dashboards using a set of 48 evaluation metrics for data integrity, completeness, granularity, visualization quality, and interactivity based on 4 major principles: evidence, efficiency, emphasis, and ethics. We evaluated 13 dashboards, summarized their characteristics, strengths, and limitations, and provided guidelines for developing nutrition dashboards. We applied mixed effects models to summarize evaluation results adjusted for interrater variability. The proposed metrics and evaluation principles help to improve data standardization and harmonization, dashboard performance and usability, broaden information and knowledge sharing among researchers, practitioners, and decision makers in the field of food and nutrition, and accelerate data literacy and communication. 

Abstract The Jiangmen Underground Neutrino Observatory (JUNO) is a large-scale neutrino experiment with multiple physics goals including determining the neutrino mass hierarchy, the accurate measurement of neutrino oscillation parameters, the neutrino detection from supernovae, the Sun, and the Earth, etc. JUNO puts forward physically and technologically stringent requirements for its central detector (CD), including a large volume and target mass (20 kt liquid scintillator, LS), a high-energy resolution (3% at 1 MeV), a high light transmittance, the largest possible photomultiplier (PMT) coverage, the lowest possible radioactive background, etc. The CD design, using a spherical acrylic vessel with a diameter of 35.4 m to contain the LS and a stainless steel structure to support the acrylic vessel and PMTs, was chosen and optimized. The acrylic vessel and the stainless steel structure will be immersed in pure water to shield the radioactive background and bear great buoyancy. The challenging requirements of the acrylic sphere have been achieved, such as a low intrinsic radioactivity and high transmittance of the manufactured acrylic panels, the tensile and compressive acrylic node design with embedded stainless steel pad, and one-time polymerization for multiple bonding lines. Moreover, several technical challenges of the stainless steel structure have been solved: the production of low radioactivity stainless steel material, the deformation and precision control during production and assembly, and the usage of high-strength stainless steel rivet bolt and of high friction efficient linkage plate. Finally, the design of the ancillary equipment such as the LS filling, overflowing, and circulating system was done. 

Abstract We explore the decay of bound neutrons in the JUNO liquid scintillator detector into invisible particles (e.g.,$$n\rightarrow 3 \nu $$ $n\to 3\nu$or$$nn \rightarrow 2 \nu $$ $nn\to 2\nu$), which do not produce an observable signal. The invisible decay includes two decay modes:$$ n \rightarrow { inv} $$ $n\to \mathrm{inv}$and$$ nn \rightarrow { inv} $$ $nn\to \mathrm{inv}$. The invisible decays ofs-shell neutrons in$$^{12}\textrm{C}$$ $_{}^{12}\text{C}$will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino$${\bar{\nu }}_e$$ ${\overline{\nu }}_e$, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are$$\tau /B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, \textrm{years}$$ $\tau /B(n\to \mathrm{inv})>5.0\times {10}^{31}\text{years}$and$$\tau /B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, \textrm{years}$$ $\tau /B(nn\to \mathrm{inv})>1.4\times {10}^{32}\text{years}$. 

Abstract The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose neutrino experiment under construction in South China. This paper presents an updated estimate of JUNO’s sensitivity to neutrino mass ordering using the reactor antineutrinos emitted from eight nuclear reactor cores in the Taishan and Yangjiang nuclear power plants. This measurement is planned by studying the fine interference pattern caused by quasi-vacuum oscillations in the oscillated antineutrino spectrum at a baseline of 52.5 km and is completely independent of the CP violating phase and neutrino mixing angleθ₂₃. The sensitivity is obtained through a joint analysis of JUNO and Taishan Antineutrino Observatory (TAO) detectors utilizing the best available knowledge to date about the location and overburden of the JUNO experimental site, local and global nuclear reactors, JUNO and TAO detector responses, expected event rates and spectra of signals and backgrounds, and systematic uncertainties of analysis inputs. We find that a 3σmedian sensitivity to reject the wrong mass ordering hypothesis can be reached with an exposure of about 6.5 years × 26.6 GW thermal power. 

Abstract The physics potential of detecting⁸B solar neutrinos will be exploited at the Jiangmen Underground Neutrino Observatory (JUNO), in a model-independent manner by using three distinct channels of the charged current (CC), neutral current (NC), and elastic scattering (ES) interactions. Due to the largest-ever mass of¹³C nuclei in the liquid scintillator detectors and the expected low background level,⁸B solar neutrinos are observable in the CC and NC interactions on¹³C for the first time. By virtue of optimized event selections and muon veto strategies, backgrounds from the accidental coincidence, muon-induced isotopes, and external backgrounds can be greatly suppressed. Excellent signal-to-background ratios can be achieved in the CC, NC, and ES channels to guarantee the observation of the⁸B solar neutrinos. From the sensitivity studies performed in this work, we show that JUNO, with 10 yr of data, can reach the 1σprecision levels of 5%, 8%, and 20% for the⁸B neutrino flux, ${\sin }^2{\theta }_{12}$, and $\mathrm{\Delta }{m}_{21}^2$, respectively. Probing the details of both solar physics and neutrino physics would be unique and helpful. In addition, when combined with the Sudbury Neutrino Observatory measurement, the world's best precision of 3% is expected for the measurement of the⁸B neutrino flux. 

Abstract This paper presents an energy resolution study of the JUNO experiment, incorporating the latest knowledge acquired during the detector construction phase. The determination of neutrino mass ordering in JUNO requires an exceptional energy resolution better than 3% at 1 MeV. To achieve this ambitious goal, significant efforts have been undertaken in the design and production of the key components of the JUNO detector. Various factors affecting the detection of inverse beta decay signals have an impact on the energy resolution, extending beyond the statistical fluctuations of the detected number of photons, such as the properties of the liquid scintillator, performance of photomultiplier tubes, and the energy reconstruction algorithm. To account for these effects, a full JUNO simulation and reconstruction approach is employed. This enables the modeling of all relevant effects and the evaluation of associated inputs to accurately estimate the energy resolution. The results of this study reveal an energy resolution of 2.95% at 1 MeV. Furthermore, this study assesses the contribution of major effects to the overall energy resolution budget. This analysis serves as a reference for interpreting future measurements of energy resolution during JUNO data collection. Moreover, it provides a guideline for comprehending the energy resolution characteristics of liquid scintillator-based detectors.