Dual-species Bose-Einstein condensates of 7^{7}Li and 133^{133}Cs

We report the creation of dual-species Bose-Einstein condensates (BECs) of $^{7}$Li and $^{133}$Cs. These BECs are formed in a bichromatic optical dipole trap created with 1550-nm and 780-nm laser beams. During the production process, an external magnetic field of 886~G is applied to adjust the scattering lengths to $a_{\rm{Cs}} = 123a_0$, $a_{\rm{Li}} = 484a_0$, and $a_{\rm{LiCs}} = 248a_0$. These scattering lengths allow for efficient evaporation and sympathetic cooling. The dual-species BECs are typically produced with $1.5\times 10^4$ Cs atoms and $6.0\times 10^3$ Li atoms. This quantum degenerate mixture of Li and Cs provides an ideal platform for exploring phenomena such as polarons and Efimov trimers, as well as for creating ground-state LiCs molecules.Comment: 9 pages, 9 figure

Proportional and Preemption-enabled Traffic Offloading for IP Flow Mobility:Algorithms and Performance Evaluation

IP Flow Mobility (IFOM) enables a user equipment to offload data traffic at the IP flow level. Although the procedure of IFOM-based flow offloading has been specified by 3GPP, how many IP flows should be offloaded and when offloading should be performed are not defined. Consequently, IP flows may be routed to a target access network which has a strong signal strength but with backhaul congestion or insufficient access capability. In this paper, we propose two algorithms, referred to as proportional offloading (PO), and proportional and preemption-enabled offloading (PPO), respectively, for IP flow offloading in hybrid cellular and wireless local area networks. The PO algorithm decides an optimal proportion of IP flows which could be offloaded by considering available resources at the target access network. In the PPO algorithm, both service continuity and network utilization are taken into consideration. Furthermore, a detailed analytical model is developed in order to evaluate the behavior of the proposed algorithms. The analytical model is validated through extensive simulations. The results show that by dynamically adjusting the percentage of traffic flows to be offloaded, PO can reduce blocking probability and increase resource utilization. PPO further improves the performance at the cost of slightly higher offloading overhead

Distributed Training Large-Scale Deep Architectures

Scale of data and scale of computation infrastructures together enable the current deep learning renaissance. However, training large-scale deep architectures demands both algorithmic improvement and careful system configuration. In this paper, we focus on employing the system approach to speed up large-scale training. Via lessons learned from our routine benchmarking effort, we first identify bottlenecks and overheads that hinter data parallelism. We then devise guidelines that help practitioners to configure an effective system and fine-tune parameters to achieve desired speedup. Specifically, we develop a procedure for setting minibatch size and choosing computation algorithms. We also derive lemmas for determining the quantity of key components such as the number of GPUs and parameter servers. Experiments and examples show that these guidelines help effectively speed up large-scale deep learning training

Assessment of the genetic basis of rosacea by genome-wide association study.

Rosacea is a common, chronic skin disease that is currently incurable. Although environmental factors influence rosacea, the genetic basis of rosacea is not established. In this genome-wide association study, a discovery group of 22,952 individuals (2,618 rosacea cases and 20,334 controls) was analyzed, leading to identification of two significant single-nucleotide polymorphisms (SNPs) associated with rosacea, one of which replicated in a new group of 29,481 individuals (3,205 rosacea cases and 26,262 controls). The confirmed SNP, rs763035 (P=8.0 × 10(-11) discovery group; P=0.00031 replication group), is intergenic between HLA-DRA and BTNL2. Exploratory immunohistochemical analysis of HLA-DRA and BTNL2 expression in papulopustular rosacea lesions from six individuals, including one with the rs763035 variant, revealed staining in the perifollicular inflammatory infiltrate of rosacea for both proteins. In addition, three HLA alleles, all MHC class II proteins, were significantly associated with rosacea in the discovery group and confirmed in the replication group: HLA-DRB1*03:01 (P=1.0 × 10(-8) discovery group; P=4.4 × 10(-6) replication group), HLA-DQB1*02:01 (P=1.3 × 10(-8) discovery group; P=7.2 × 10(-6) replication group), and HLA-DQA1*05:01 (P=1.4 × 10(-8) discovery group; P=7.6 × 10(-6) replication group). Collectively, the gene variants identified in this study support the concept of a genetic component for rosacea, and provide candidate targets for future studies to better understand and treat rosacea

The Hamiltonian boundary term and quasi-local energy flux

The Hamiltonian for a gravitating region includes a boundary term which determines not only the quasi-local values but also, via the boundary variation principle, the boundary conditions. Using our covariant Hamiltonian formalism, we found four particular quasi-local energy-momentum boundary term expressions; each corresponds to a physically distinct and geometrically clear boundary condition. Here, from a consideration of the asymptotics, we show how a fundamental Hamiltonian identity naturally leads to the associated quasi-local energy flux expressions. For electromagnetism one of the four is distinguished: the only one which is gauge invariant; it gives the familiar energy density and Poynting flux. For Einstein's general relativity two different boundary condition choices correspond to quasi-local expressions which asymptotically give the ADM energy, the Trautman-Bondi energy and, moreover, an associated energy flux (both outgoing and incoming). Again there is a distinguished expression: the one which is covariant.Comment: 12 pages, no figures, revtex

Challenges in biogas production from anaerobic membrane bioreactors

© 2016 Spectacular applications of anaerobic membrane bioreactors (AnMBRs) are emerging due to the membrane enhanced biogas production in the form of renewable bioresources. They produce similar energy derived from the world's depleting natural fossil energy sources while minimizing greenhouse gas (GHG) emissions. During the last decade, many types of AnMBRs have been developed and applied so as to make biogas technology practical and economically viable. Referring to both conventional and advanced configurations, this review presents a comprehensive summary of AnMBRs for biogas production in recent years. The potential of biogas production from AnMBRs cannot be fully exploited, since certain constraints still remain and these cause low methane yield. This paper addresses a detailed assessment on the potential challenges that AnMBRs are encountering, with a major focus on many inhibitory substances and operational dilemmas. The aim is to provide a solid platform for advances in novel AnMBRs applications for optimized biogas production

Photon-induced conduction modulation in SiO 2 thin films embedded with Ge nanocrystals

The authors report the photon-induced conduction modulation in Si O2 thin films embedded with germanium nanocrystals (nc-Ge). The conduction of the oxide could be switched to a higher- or lower-conductance state by a ultraviolet (UV) illumination. The conduction modulation is caused by charging and discharging in the nc-Ge due to the UV illumination. If the charging process is dominant, the oxide conductance is reduced; however, if the discharging process is dominant, the oxide conductance is increased. As the conduction can be modulated by UV illumination, it could have potential applications in silicon-based optical memory devices. © 2007 American Institute of Physics.published_or_final_versio