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Aiming to investigate whether a fresh produce e‐tailer should implement the strategy of advance selling considering the behavior of consumers' risk aversion, we build a two‐stage newsvendor decision‐making model and further explore how the advance selling value is affected by factors, such as the freshness‐keeping cost and the effect of demand information updating on reducing demand uncertainty. The results indicate that adopting advance selling strategy benefits the e‐tailer or not depends on consumer risk aversion and the effect of demand information updating on reducing demand uncertainty. The increasing effect of demand information updating on reducing demand uncertainty is conducive to improving the value of advance selling, and the freshness‐keeping cost may increase or decrease the value of advance selling. Besides, adopting the strategy of advance selling may benefit both the e‐tailer and the consumers under certain conditions. [ABSTRACT FROM AUTHOR]

Detection of vector magnetic fields at nanoscale dimensions is critical in applications ranging from basic material science and fundamental physics to information storage and medical diagnostics. So far, nanoscale vector magnetic field sensing is achieved solely by exploiting a single nitrogen‐vacancy (NV) center in a diamond, by evaluating the Zeeman splitting of NV spin qubits by using the technique of an optically‐detected magnetic resonance. This protocol requires a complex optical setup and expensive detection systems to detect the photoluminescence light, which may limit miniaturization and scalability. Here, a simple approach with all‐electric operation to sensing a vector magnetic field at 200 × 200 nm2 dimensions is experimentally demonstrated, by monitoring a stochastic nanomagnet's transition probability from a metastable state, excited by a driving current due to spin‐orbit torque, to a settled state. [ABSTRACT FROM AUTHOR]

This paper considers a fresh produce supply chain in which a retailer sources alternative produce from two competing suppliers. The suppliers make efforts to preserve product freshness, while the retailer, with demand forecast information, can share it with none, one or both of the suppliers strategically. By constructing a multistage game model, the optimal demand information sharing strategy in the supply chain is explored. The results show that the retailer has the willingness to disclose demand information only when the freshness elasticity is high. Significantly, with the improvement of the freshness elasticity, the retailer will transform from sharing information with both suppliers to one supplier. The suppliers are always willing to accept the information disclosed by the retailer. However, complete transparency of demand information may hurt the supply chain under certain conditions. To improve the supply chain performance, the retailer can charge both suppliers for information fees and adjust from sharing information with no suppliers to both suppliers with a relatively low freshness elasticity. Conversely, the retailer can change from sharing information with both suppliers to sharing information with one supplier through a charging contract with a relatively high freshness elasticity. [ABSTRACT FROM AUTHOR]

Analog arithmetic operations are the most fundamental mathematical operations used in image and signal processing as well as artificial intelligence (AI). In‐memory computing (IMC) offers a high performance and energy‐efficient computing paradigm. To date, in‐memory analog arithmetic operations with emerging nonvolatile devices are usually implemented using discrete components, which limits the scalability and blocks large scale integration. Here, a prototypical implementation of in‐memory analog arithmetic operations (summation, subtraction and multiplication) is experimentally demonstrated, based on in‐memory electrical current sensing units using spin‐orbit torque (SOT) devices. The proposed structures for analog arithmetic operations are smaller than the state‐of‐the‐art complementary metal oxide semiconductor (CMOS) counterparts by several orders of magnitude. Moreover, data to be processed and computing results can be locally stored, or the analog computing can be done in the nonvolatile SOT devices, which are exploited to experimentally implement the image edge detection and signal amplitude modulation with a simple structure. Furthermore, an artificial neural network (ANN) with SOT devices based synapses is constructed to realize pattern recognition with high accuracy of ≈95%. [ABSTRACT FROM AUTHOR]

Effects of endophytes infection on bacterial and fungal communities in soil have been extensively studied. However, how the presence of Epichloë endophytes and environmental factors influence the nitrifying genes abundance of ammonia‐oxidizing archaea (amoA‐AOA) and bacteria (amoA‐AOB), and denitrifying genes abundances of N reduction (nirS and nirK) and nitrous oxide reduction (nosZ) in soil is unclear. In the study, the copy number of 16S rRNA, 18S rRNA, amoA‐AOB, amoA‐AOA, nirS, nirK, and nosZ genes in rhizosphere soils of drunken horse grass [Achnatherum inebrians (Hance) Keng] with the infected (E+) and uninfected (E–)endophyte five ecotypes after 3 yr field cultivation were investigated using quantitative polymerase chain reaction (PCR). The effects of A. inebrians in geographic source on plant growth, soil fertility, and microbial community was greater than in different endophyte status. The copy number of the 16S rRNA, amoA‐AOA, nirK, and nosZ genes from different ecotypes (Qinghai, QH; and Tianzhu, TZ) were significantly affected by Epichloë endophyte. The copy number of the 16S rRNA, 18S rRNA, amoA‐AOB. amoA‐AOA, nirS, nirK, and nosZ genes positively related to soil pH, moisture, C/N ratio, and soil ammonium nitrogen (NH4+), and soil organic carbon (SOC) contents. Endophyte infection significantly increased plant biomass of A. inebrians from QH ecotype. Plant total chlorophyll and soil nitrate nitrogen (NO3–) were the main factor for the Epichloë endophyte and ecotype to affect plant dry weight. Further studies are required to confirm the regulation of soil NO3– as an important factor in Epichloë endophyte affecting plant growth and the soil microbial community structure in relation to N cycling. [ABSTRACT FROM AUTHOR]

Litter decomposition plays a key role in nutrient cycling across ecosystems. The presence of Epichloë endophytes in grass plants affects litter decomposition. The overall effects of leaf litter containing Epichloë endophytes on the chemical and biological properties in non‐rhizosphere soils have not previously been examined. The current study is aimed to understand the effect of direct incorporation of leaf litter from Epichloë endophyte‐infected perennial ryegrass (Lolium perenne) on soil chemical characteristics, and fungal and bacterial biodiversity. Firstly, fresh leaf litter of the endophyte Epichloë festucae var. lolii‐infected (E+) and endophyte‐free (E−) L. perenne were incorporated into the soil, and then samples were collected from E+ and E− litter incorporated soil at T0, T1, T2 and T3 (0, 120, 240 and 360 days) for chemical and sequencing analyses. The Epichloë‐containing leaf litter incorporation changed the soil microbial environment by enhancing the soil organic carbon (SOC), total nitrogen (TN), total phosphorus, NH4+–N and NO3−–N contents, and acidifying soil pH. The endophyte had stronger effects on soil bacteria than soil fungi when the litter was determined with and without the endophyte. Litter containing the Epichloë endophyte significantly increased the absolute abundance of the 16S rRNA gene and relative abundances of the Actinobacteria, Nitrospirae and Gemmatimonadetes, while significantly decreasing the relative abundances of the Planctomycetes and Rokubacteria and the diversity in soil bacteria community. There was no significant effect of endophyte‐containing leaf litter incorporation on the absolute abundance and diversity of the soil fungal community except the increment in the relative abundance of Rozellomycota. Soil pH and the SOC‐to‐TN ratio (C:N) were the main factors influencing the soil bacterial community, and the presence of E. festucae var. lolii was directly and positively related to the soil bacterial diversity. The current study established that Epichloë endophyte‐infection altered the abundance and diversity of the soil bacterial community by affecting leaf litter quality and increasing soil chemical properties after litter incorporation. Highlights: Soil microbial habitat was changed by leaf litter with Epichloë endophyte incorporation.Litter containing endophytes increased the absolute abundance of the 16S rRNA gene.Epichloë endophytes altered the diversity of bacteria during litter incorporation.The response of soil bacteria to a litter containing endophytes was greater than that of soil fungi. [ABSTRACT FROM AUTHOR]

This article reports the complete chloroplast genome of Achnatherum inebrians, a poisonous herb that is widely distributed in the rangelands of Northern China. The genome is 137 714 bp in total and consists of a large single‐copy (81 758 bp) region and small single‐copy (12 682 bp) region separated by a pair of inverted repeats (21 637 bp). The genome contains 130 genes, including 84 protein‐coding genes, 38 tRNA genes and 8 ribosomal RNA genes, and the guanine + cytosine content is 36.17%. We subsequently performed comparative analysis of complete genomes from A. inebrians and other Poaceae‐related species from GenBank. Thirty‐eight simple sequence repeats were identified, further demonstrating rapid evolution in Poaceae. Finally, the phylogenetic trees of 37 species of Poaceae and 2 species of Amaranthaceae were constructed by using maximum likelihood and Bayesian inference methods, based on the genes of the complete chloroplast genome. We identified hotspots that can be used as molecular markers and barcodes for phylogenetic analysis, as well as for species identification. Phylogenetic analysis indicated that A. inebrians is a member of the genus Stipa rather than Achnatherum. [ABSTRACT FROM AUTHOR]