E(5)E(5)-like emerging γ\gamma-softness in 82^{82}Kr

Recently the interacting bosom model with $SU(3)$ higher-order interactions was proposed by one of the authors, wherein unexpected $\gamma$-softness can be emerged in this new model. This stimulates further discussion on the connections of the new $\gamma$-softness and the realistic $\gamma$-soft nuclei. In this paper, $E(5)$-like $\gamma$-softness arises when the $SU(3)$ fourth-order interaction $\hat{C}_{2}^{2}[SU(3)]$ is considered. And the corresponding transitional behaviors are similar to that from the $U(5)$ limit to the $O(6)$ limit in previous IBM-1, which provides a novel perspective for understanding the new model. Low-lying spectra, $B(E2)$ values between the low-lying states and quadrupole moment of the first $2_{1}^{+}$ state are investigated. Experimental data of the $E(5)$-like nucleus $^{82}$Kr are compared with the calculated theoretical results, where the calculated low-lying level energies and the associated $B(E2)$ values fit very well with the experimental data

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

New approaches to estimate microbial diversity of alcoholic fermentation

La fermentació alcohòlica la realitza una comunitat microbiana complexa, on els llevats vínics juguen un paper important. En els darrers anys, hi ha hagut un creixent interès per millorar complexitat del vi mitjançant fermentacions controlades quer utilitzaven no només S. cerevisiae sinó també soques seleccionades de llevats no-Saccharomyces. La investigació sobre la viabilitat dels llevats i les interaccions tenen un paper fonamental per entendre la diversitat de llevats en la fermentació mixta. En aquesta tesi, les tècniques independents de cultiu que es van aplicar per a l'anàlisi directa de mostres de vins inclouen la seqüenciació massiva, fluorescència per hibridació in situ (FISH) en combinació amb microscòpia i citometria de flux, RT-qPCR i EMA-DGGE. Aquestes tècniques independents de cultiu permeten una ràpida identificació i / o quantificació dels diferents llevats del vi. Aquestes tècniques han estat utilitzades en fermentacions espontànies a la regió del Priorat, i H. uvarum i Starm. bacillaris van ser les dues principals espècies de llevats no-Saccharomyces aïllades. H. uvarum o Starm. bacillaris perden gradualment la seva cultivabilitat quan els mostos es van inocular amb S. cerevisiae, però es podien quantificar cèl•lules de llevats en estat viable però no cultivable. La pèrdua de cultivabilitat dels no Saccharomyces va ser induïda principalment per alguns metabòlits secretats per S. cerevisiae, però els canvis en altres metabòlits principals també van influir. Aquesta interacció de llevat no Saccharomyces amb S. cerevisiae era específica d’espècie i soca.La fermentación alcohólica es llevada a cabo por una comunidad microbiana compleja, donde las levaduras del vino juegan un papel importante. En los últimos años, ha habido un creciente interés para mejorar la complejidad del vino en fermentaciones controladas utilizando no sólo S. cerevisiae sino también algunas cepas seleccionadas de levaduras no-Saccharomyces. La investigación sobre la viabilidad de las levaduras y las interacciones tienen un papel fundamental para entender la diversidad de levaduras en fermentaciones mixtas. En esta tesis, se aplicaron técnicas independientes de cultivo para el análisis de muestras de vinos directa incluyendo la secuenciación masiva, fluorescencia por hibridación in situ (FISH) en combinación con microscopía y citometría de flujo, RT-qPCR y EMA-DGGE. Estas técnicas independientes de cultivo permiten una rápida identificación y / o cuantificación de las distintas levaduras del vino. Estas técnicas han sido utilizadas para el análisis de fermentaciones espontáneas en la región del Priorat, siendo las especies H. uvarum y Starm. bacillaris las dos principales especies de levaduras no-Saccharomyces. H. uvarum o Starm. bacillaris pierden gradualmente su cultivabilidad cuando los mostos se inocularon con S. cerevisiae, pero las levaduras se pudieron cuantificar en estado viable pero no cultivable. La pérdida de cultivabilidad de las especies no Saccharomyces fue inducida principalmente por algunos metabolitos secretados por S. cerevisiae, pero los cambios en otros metabolitos principales también influyen. Esta interacción entre levaduras no Saccharomyces con S. cerevisiae es especie y cepa dependiente.Alcoholic fermentation is driven by complex microbial community, where wine yeasts play an important role. In recent years, there has been growing interest to enhance wine complexity by controlled fermentations using not only S. cerevisiae but also together with some selected non-Saccharomyces yeast strains. Research on yeast viability and interaction has a fundamental role to understand the diversity of yeast in mixed fermentations. In this thesis, culture-independent techniques were developed and applied for direct wine sample analysis including massive sequencing, fluorescence in situ hybridization (FISH) combined with microscopy and flow cytometry, RT-qPCR and EMA-DGGE. These culture-independent techniques enable fast identification and/or quantification of different wine yeasts. These techniques have been used during spontaneous fermentation in Priorat region, and H. uvarum and Starm. bacillaris where the two main non-Saccharomyces yeast species detected. H. uvarum or Starm. bacillaris gradually lost their culturability when musts were inoculated with S. cerevisiae, but quantifiable yeast cells existed in viable but non-culturable state. The culturability loss of non-Saccharomyces was mainly induced by some metabolites secreted from S. cerevisiae, but changes in other main metabolites also had some effect. This interaction of non-Saccharomyces yeast with S. cerevisiae showed the specificity of species and strains

Effects of food concentration and photoperiod on egg production, female life expectancy and population dynamics of the paracalanid copepod, Bestiolina amoyensis

The paracalanid copepod, Bestiolina amoyensis, is a widely distributed species occurring in subtropical inshore waters across the Pacific Ocean. Its small size, herbivorous feeding habit, and high adaptability make the species one of the most promising candidates as potential live feed for hatchery larval rearing. This study investigated effects of different feeding density of microalgae Isochrysis spp. (1 × 105, 2 × 105, 3 × 105, 4 × 105, and 5 × 105 cells ml–1) and photoperiod (8L:16D, 12L:12D, and 16L:8D) on productivity-related parameters, including egg production, female life expectancy and population dynamics of B. amoyensis. Results showed that total egg output over female lifespan, final population size and intrinsic rate of population of 12L:12D photoperiod treatments were always the highest among three photoperiod conditions, especially at the food concentration of 4 × 105 cells ml–1, indicating B. amoyensis had high reproductive performance and the population was in a more stable status. The number of nauplii from 4 × 105 cells ml–1 algal concentration treatment accounted for 75% of the population, and the ratio of females to males approaching 1:1 when photoperiod was 12L:12D; female life expectancy was 10.5 ± 0.6 days. In conclusion, our results showed that Isochrysis spp. is a suitable feed for B. amoyensis with an optimal concentration at 4 × 105 cells mL–1; the optimal photoperiod for B. amoyensis rearing is 12L:12D. The relatively long reproductive lifespan and high intrinsic population increase rate make B. amoyensis a good candidate to develop culture techniques for hatchery larval rearing

Suppression of Gluconeogenic Gene Expression by LSD1-Mediated Histone Demethylation

Aberrant gluconeogenic gene expression is associated with diabetes, glycogen storage disease, and liver cancer. However, little is known how these genes are regulated at the chromatin level. In this study, we investigated in HepG2 cells whether histone demethylation is a potential mechanism. We found that knockdown or pharmacological inhibition of histone demethylase LSD1 causes remarkable transcription activation of two gluconeogenic genes, FBP1 and G6Pase, and consequently leads to increased de novo glucose synthesis and decreased intracellular glycogen content. Mechanistically, LSD1 occupies the promoters of FBP1 and G6Pase, and modulates their H3K4 dimethylation levels. Thus, our work identifies an epigenetic pathway directly governing gluconeogenic gene expression, which might have important implications in metabolic physiology and diseases

Automated Prompting for Non-overlapping Cross-domain Sequential Recommendation

Cross-domain Recommendation (CR) has been extensively studied in recent years to alleviate the data sparsity issue in recommender systems by utilizing different domain information. In this work, we focus on the more general Non-overlapping Cross-domain Sequential Recommendation (NCSR) scenario. NCSR is challenging because there are no overlapped entities (e.g., users and items) between domains, and there is only users' implicit feedback and no content information. Previous CR methods cannot solve NCSR well, since (1) they either need extra content to align domains or need explicit domain alignment constraints to reduce the domain discrepancy from domain-invariant features, (2) they pay more attention to users' explicit feedback (i.e., users' rating data) and cannot well capture their sequential interaction patterns, (3) they usually do a single-target cross-domain recommendation task and seldom investigate the dual-target ones. Considering the above challenges, we propose Prompt Learning-based Cross-domain Recommender (PLCR), an automated prompting-based recommendation framework for the NCSR task. Specifically, to address the challenge (1), PLCR resorts to learning domain-invariant and domain-specific representations via its prompt learning component, where the domain alignment constraint is discarded. For challenges (2) and (3), PLCR introduces a pre-trained sequence encoder to learn users' sequential interaction patterns, and conducts a dual-learning target with a separation constraint to enhance recommendations in both domains. Our empirical study on two sub-collections of Amazon demonstrates the advance of PLCR compared with some related SOTA methods