A Birandom Job Search Problem with Risk Tolerance

This paper considers a novel class of birandom job search problem, in which the job offers are sampled by the job searcher from a finite job set with equivalent probability and their wages are characterized as independent but maybe not identically nonnegative random variables. The job searcher knows the job offer's wage distribution when he samples the job offer. Since the offered wage is a random variable and the reservation wage is a deterministic number, it is meaningless to make comparison directly. In order to rank the random wage and the reservation wage and provide decision support, a risk tolerance criterion is designed, and the job searcher then accepts or rejects the sampled job offer depending on whether the risk tolerance criterion is met or not. Since the offered wages are random variables and the search process is random, it's impossible to obtain the job searcher's real return; in this case, its expected value can be calculated via birandom theory. Simultaneously, some propositions on the expected return as well as the average search times are also studied which may provide some valuable suggestions to the job searcher. Numerical examples are given to illustrate the decision process of the risk tolerance-based birandom job search problem

Population structure of Coilia nasus in the Yangtze River revealed by insertion of short interspersed elements

AbstractCoilia nasus is found in the Yangtze River and the coastal waters of China, Korea, and Japan. Two ecotypes (anadromous and freshwater-resident populations) are distributed throughout the Yangtze River basin based on their ecology and behavior, but relatively little is known about the population structure of this species. Analysis of short interspersed element (SINE) insertions, which vary among individuals, has been acknowledged to provide a unique way to study population divergence. SINEs isolated from C. nasus were characterized, and this enabled analysis of the SINE insertion pattern in six populations distributed throughout the Yangtze River basin. In all populations, four SINE loci displayed individual polymorphism, and two SINE loci showed a stochastic loss in all individuals of two resident populations. The correlation between genetic and geographic populations indicated a degree of genetic isolation in this species. In contrast with Coilia grayii and Coilia mystus, two SINE loci appeared only in C. nasus. Sequencing analysis indicated that the high insertion variability of SINEs was attributed mainly to the tails, which contained various repeat copies. The results in this study will be useful for sustainable management of fishery resources and conservation of this species

The haplotype-resolved T2T reference genome highlights structural variation underlying agronomic traits of melon

Melon (Cucumis melo L.) is an important vegetable crop that has an extensive history of cultivation. However, the genome of wild and semi-wild melon types that can be used for the analysis of agronomic traits is not yet available. Here we report a chromosome-level T2T genome assembly for 821 (C. melo ssp. agrestis var. acidulus), a semi-wild melon with two haplotypes of ~373 Mb and ~364 Mb, respectively. Comparative genome analysis discovered a significant number of structural variants (SVs) between melo (C. melo ssp. melo) and agrestis (C. melo ssp. agrestis) genomes, including a copy number variation located in the ToLCNDV resistance locus on chromosome 11. Genome-wide association studies detected a significant signal associated with climacteric ripening and identified one candidate gene CM_ac12g14720.1 (CmABA2), encoding a cytoplasmic short chain dehydrogenase/reductase, which controls the biosynthesis of abscisic acid. This study provides valuable genetic resources for future research on melon breeding.This work was supported by funding from the Agricultural Science and Technology Innovation Program (CAAS-ASTIP-2016-ZFRI-06), the China Agriculture Research System (CARS-25-2023-G6), the Key Research and Development Program of Hainan (ZDYF2021XDNY164), the European Research Council (ERC-NectarGland, 101095736), the 111 Project (B17043) and Henan Province Science and Technology Research Project (232102110185).info:eu-repo/semantics/acceptedVersio

Identification of Plant Messenger RNA Polyadenylation Sites Using Length-Variable Second Order Markov Model

In this paper we adopted a length-variable second order Markov model to identify plant messenger RNA poly(A) sites, and provided a common method that only relies on the experimental sequences. The efficacy of our model is showed up to 92% sensitivity and 79% specificity. This method is particularly suitable for the prediction of the poly(A) site which is lack of biological priori knowledge and has poor conservative signal characteristic, as well as for the identification of the alternative poly(A) sites in different genetic regions. Compared with other algorithms, generalized hidden Markov model needed the signal distributions and AdaBoost required the construction of signal features around the sites, our model is more versatile

Climatic warming in China during 1901-2015 based on an extended dataset of instrumental temperature records

Monthly mean instrumental surface air temperature (SAT) observations back to the nineteenth century in China are synthesized from different sources via specific quality-control, interpolation, and homogenization. Compared with the first homogenized long-term SAT dataset for China by Cao et al. (2013), which contained 18 stations mainly located in the middle and eastern part of China, the present dataset includes homogenized monthly SAT series at 32 stations, with an extended coverage especially towards western China. Missing values are interpolated by using observations at nearby stations including those from neighboring countries. Cross validation shows that the mean bias error (MBE) is generally small and falls between 0.45°C and -0.35°C. Multiple homogenization methods and available metadata are applied to assess the consistency of the time series and to adjust inhomogeneity biases. The homogenized annual mean SAT series show a range of trends between 1.1 and 4.0°C/century in northeastern China, between 0.4 and 1.9°C/century in southeastern China, and between 1.4 and 3.7°C/century in western China to the west of 105E (from the beginning years of the stations to 2015). The unadjusted data include unusually warm records during the 1940s and hence tend to underestimate the warming trends at a number of stations. The mean SAT series for China based on the Climate Anomaly Method shows a warming trend of 1.56°C/century during 1901-2015, larger than those based on other currently available datasets

PCR and Magnetic Bead-Mediated Target Capture for the Isolation of Short Interspersed Nucleotide Elements in Fishes

Short interspersed nucleotide elements (SINEs), a type of retrotransposon, are widely distributed in various genomes with multiple copies arranged in different orientations, and cause changes to genes and genomes during evolutionary history. This can provide the basis for determining genome diversity, genetic variation and molecular phylogeny, etc. SINE DNA is transcribed into RNA by polymerase III from an internal promoter, which is composed of two conserved boxes, box A and box B. Here we present an approach to isolate novel SINEs based on these promoter elements. Box A of a SINE is obtained via PCR with only one primer identical to box B (B-PCR). Box B and its downstream sequence are acquired by PCR with one primer corresponding to box A (A-PCR). The SINE clone produced by A-PCR is selected as a template to label a probe with biotin. The full-length SINEs are isolated from the genomic pool through complex capture using the biotinylated probe bound to magnetic particles. Using this approach, a novel SINE family, Cn-SINE, from the genomes of Coilia nasus, was isolated. The members are 180–360 bp long. Sequence homology suggests that Cn-SINEs evolved from a leucine tRNA gene. This is the first report of a tRNALeu-related SINE obtained without the use of a genomic library or inverse PCR. These results provide new insights into the origin of SINEs

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

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