Superfluid and magnetic states of an ultracold Bose gas with synthetic three-dimensional spin-orbit coupling in an optical lattice

We study ultracold bosonic atoms with the synthetic three-dimensional spin-orbit (SO) coupling in a cubic optical lattice. In the superfluidity phase, the lowest energy band exhibits one, two or four pairs of degenerate single-particle ground states depending on the SO-coupling strengths, which can give rise to the condensate states with spin-stripes for the weak atomic interactions. In the deep Mott-insulator regime, the effective spin Hamiltonian of the system combines three-dimensional Heisenberg exchange interactions, anisotropy interactions and Dzyaloshinskii-Moriya interactions. Based on Monte Carlo simulations, we numerically demonstrate that the resulting Hamiltonian with an additional Zeeman field has a rich phase diagram with spiral, stripe, vortex crystal, and especially Skyrmion crystal spin-textures in each xy-plane layer. The obtained Skyrmion crystals can be tunable with square and hexagonal symmetries in a columnar manner along the z axis, and moreover are stable against the inter-layer spin-spin interactions in a large parameter region.Comment: 9 pages, 4 figures; title modified, references and discussions added; accepted by PR

Text2Bundle: Towards Personalized Query-based Bundle Generation

Bundle generation aims to provide a bundle of items for the user, and has been widely studied and applied on online service platforms. Existing bundle generation methods mainly utilized user's preference from historical interactions in common recommendation paradigm, and ignored the potential textual query which is user's current explicit intention. There can be a scenario in which a user proactively queries a bundle with some natural language description, the system should be able to generate a bundle that exactly matches the user's intention through the user's query and preferences. In this work, we define this user-friendly scenario as Query-based Bundle Generation task and propose a novel framework Text2Bundle that leverages both the user's short-term interests from the query and the user's long-term preferences from the historical interactions. Our framework consists of three modules: (1) a query interest extractor that mines the user's fine-grained interests from the query; (2) a unified state encoder that learns the current bundle context state and the user's preferences based on historical interaction and current query; and (3) a bundle generator that generates personalized and complementary bundles using a reinforcement learning with specifically designed rewards. We conduct extensive experiments on three real-world datasets and demonstrate the effectiveness of our framework compared with several state-of-the-art methods

Closed-form Approximation for Performance Bound of Finite Blocklength Massive MIMO Transmission

Ultra-reliable low latency communications (uRLLC) is adopted in the fifth generation (5G) mobile networks to better support mission-critical applications that demand high level of reliability and low latency. With the aid of well-established multiple-input multiple-output (MIMO) information theory, uRLLC in the future 6G is expected to provide enhanced capability towards extreme connectivity. Since the latency constraint can be represented equivalently by blocklength, channel coding theory at finite block-length plays an important role in the theoretic analysis of uRLLC. On the basis of Polyanskiy's and Yang's asymptotic results, we first derive the exact close-form expressions for the expectation and variance of channel dispersion. Then, the bound of average maximal achievable rate is given for massive MIMO systems in ideal independent and identically distributed fading channels. This is the study to reveal the underlying connections among the fundamental parameters in MIMO transmissions in a concise and complete close-form formula. Most importantly, the inversely proportional law observed therein implies that the latency can be further reduced at expense of spatial degrees of freedom

Amino acid Formula induces Microbiota Dysbiosis and Depressive-Like Behavior in Mice

Amino acid formula (AAF) is increasingly consumed in infants with cow\u27s milk protein allergy; however, the long-term influences on health are less described. In this study, we established a mouse model by subjecting neonatal mice to an amino acid diet (AAD) to mimic the feeding regimen of infants on AAF. Surprisingly, AAD-fed mice exhibited dysbiotic microbiota and increased neuronal activity in both the intestine and brain, as well as gastrointestinal peristalsis disorders and depressive-like behavior. Furthermore, fecal microbiota transplantation from AAD-fed mice or AAF-fed infants to recipient mice led to elevated neuronal activations and exacerbated depressive-like behaviors compared to that from normal chow-fed mice or cow\u27s-milk-formula-fed infants, respectively. Our findings highlight the necessity to avoid the excessive use of AAF, which may influence the neuronal development and mental health of children

Long-term storage modifies the microRNA expression profile of cryopreserved human semen

The global practice of cryopreservation of human semen is commonplace in Assisted Reproductive Technology (ART) labs and sperm banks. However, information on the effects of long-term cryopreservation on semen is limited to clinical data summaries and descriptions. For this study, we prepared 4 semen specimens of fresh semen, 4 specimens cryostored for at least 1 year, 3 specimens cryostored for at least 5 years, 4 specimens cryostored for at least 10 years, and 3 specimens cryostored for at least 15 years. Total RNA was extracted from each sample, amplified, labeled, and mapped to the known primary microRNA (miRNA) in the miRBase database, enabling the prediction of novel miRNAs. We found that cryopreservation can lead to changes in miRNA expression, and with the increase in storage time, these changes became more pronounced. Meanwhile, the expression of let-7d-3p, let-7c-5p and let-7i-3p miRNAs changed dynamically over cryostorage time in frozen-thawed human sperm. Furthermore, we analyzed the time-dependent dynamics of cryostorage-expressed miRNAs and their target mRNAs and found that half of the target genes were expressed in oocytes. These intersection genes were mainly enriched in cancer and cytoskeletal signaling pathways. Our findings showed that the miRNA expression profile of cryopreserved human semen is modified by long-term storage. Furthermore, as the storage time increases, the impact on human sperm becomes more pronounced in terms of miRNAs, which may have an effect on subsequent fertilization and embryonic development