Effect of Vent Mode on the Differential Pressure Pre-cooling Efficiency of Layered Peaches

The objective of this study was to explore the effect of the vent mode of corrugated boxes universally used in the market on the precooling performance of layered peaches and to determine the functional relationship between the precooling environmental parameters and the precooling efficiency and the optimal vent mode under different differential pressure pre-cooling working conditions in order to realize the rapid energy-saving precooling of peaches after harvest. A numerical model of heat and mass transfer during differential pressure precooling with circular and rectangular vents (abbreviated as CV and RV, respectively) was established based on computational fluid dynamics. By comparing and analyzing the experimental and simulated data, it was found that the maximum root mean square error and mean absolute percentage error between the two vent designs were 0.799 ℃ and 6.6%, respectively, which fully verified that this numerical model had high prediction accuracy. Through in-depth exploration of the temperature and flow field distribution in different vent modes, it was found that CV exhibited inferior precooling uniformity when compared with RV. Nevertheless, CV demonstrated a notable reduction in precooling time by 30%–40% and a decrease in fan energy consumption by 50%. Additionally, their relationships with differential pressure were described by. Based on these obtained results, the precooling quality of peaches could be improved by using RV, and the precooling cost could be reduced by using CV. To simultaneously achieve these two goals, the diameter of CV should be greater than 35 mm. This study provides a theoretical reference for the reasonable selection of vent parameters and accurate monitoring of fruit precooling performance in small and medium-sized orchards

Proof-of-work consensus by quantum sampling

Since its advent in 2011, boson-sampling has been a preferred candidate for demonstrating quantum advantage because of its simplicity and near-term requirements compared to other quantum algorithms. We propose to use a variant, called coarse-grained boson-sampling (CGBS), as a quantum Proof-of-Work (PoW) scheme for blockchain consensus. The users perform boson-sampling using input states that depend on the current block information, and commit their samples to the network. Afterward, CGBS strategies are determined which can be used to both validate samples and to reward successful miners. By combining rewards to miners committing honest samples together with penalties to miners committing dishonest samples, a Nash equilibrium is found that incentivizes honest nodes. The scheme works for both Fock state boson sampling and Gaussian boson sampling and provides dramatic speedup and energy savings relative to computation by classical hardware.Comment: 21 pages, 6 figures (v2 fixes typos, add references

Full-length transcriptome sequencing reveals the molecular mechanism of monoterpene and sesquiterpene biosynthesis in Cinnamomum burmannii

Essential oil of Cinnamomum burmannii is rich in monoterpenes and sesquiterpenes and is widely used in cosmetics and medicines. Knowledge about the enzymes that catalyze the formation of monoterpenes and sesquiterpenes in C. burmannii is insufficient. Therefore, anatomy observation of C. burmannii at the four developmental stages (7 days, CBS1; 14 days, CBS2; 21 days, CBS3, and 28 days, CBS4) were conducted to elucidate the origins of essential oil production. Twelve full-length transcriptomes of C. burmannii leaves at the four stages were generated using Oxford Nanopore Technologies. GC-MS analysis revealed 15 monoterpene and sesquiterpenes dramatically increased from CBS1 to CBS4. A weighted correlation network analysis (WGCNA) in association and differentially expressed genes across four developmental stages were performed. A total of 44 differentially expressed genes (DEGs) were involved in terpenoid syntheses during leaf development. Among them, the DEGs of the mevalonate acid (MVA) pathway were predominantly expressed at CBS1, while those of the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway showed increased expression from CBS2 to CBS4. Besides, fourteen genes were associated with monoterpene synthesis and nine with sesquiterpene synthesis. Functions of these DEGs were further predicted with regard to gene expression profile and phylogenetic relationship with those characterized in previous studies. In addition, 922 long noncoding RNAs (lncRNAs) were detected, of which twelve were predicted to regulate monoterpene and sesquiterpene biosynthesis. The present study provided new insights the molecular mechanisms of monoterpenoid and sesquiterpenoid syntheses of C. burmannii

Neutrino Physics with JUNO

The Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton multi-purposeunderground liquid scintillator detector, was proposed with the determinationof the neutrino mass hierarchy as a primary physics goal. It is also capable ofobserving neutrinos from terrestrial and extra-terrestrial sources, includingsupernova burst neutrinos, diffuse supernova neutrino background, geoneutrinos,atmospheric neutrinos, solar neutrinos, as well as exotic searches such asnucleon decays, dark matter, sterile neutrinos, etc. We present the physicsmotivations and the anticipated performance of the JUNO detector for variousproposed measurements. By detecting reactor antineutrinos from two power plantsat 53-km distance, JUNO will determine the neutrino mass hierarchy at a 3-4sigma significance with six years of running. The measurement of antineutrinospectrum will also lead to the precise determination of three out of the sixoscillation parameters to an accuracy of better than 1\%. Neutrino burst from atypical core-collapse supernova at 10 kpc would lead to ~5000inverse-beta-decay events and ~2000 all-flavor neutrino-proton elasticscattering events in JUNO. Detection of DSNB would provide valuable informationon the cosmic star-formation rate and the average core-collapsed neutrinoenergy spectrum. Geo-neutrinos can be detected in JUNO with a rate of ~400events per year, significantly improving the statistics of existing geoneutrinosamples. The JUNO detector is sensitive to several exotic searches, e.g. protondecay via the $p\to K^++\bar\nu$ decay channel. The JUNO detector will providea unique facility to address many outstanding crucial questions in particle andastrophysics. It holds the great potential for further advancing our quest tounderstanding the fundamental properties of neutrinos, one of the buildingblocks of our Universe

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO