Comparison of Volatile Compounds in Two Brandies Using HS-SPME Coupled with GC-O, GC-MS and Sensory Evaluation

The aim of this study was to compare the volatile compounds between Changyu XO and Hennessy XO. Sensoryevaluation was performed by a panel of tasters. Qualitative and semi-quantitative analysis was achieved byheadspace solid phase micro-extraction (HS-SPME), coupled with gas chromatography-mass spectrometry (GCMS)and gas chromatography-olfactometry (GC-O). A total of 160 volatile compounds were identified in the twobrands of brandy. Of these, 118 compounds were common to both Changyu XO and Hennessy XO; 18 compoundswere specific to Changyu XO and 24 were specific to Hennessy XO. A total of 85 aroma compounds responsiblefor brandy flavour were identified by GC-O, of which 68 were common to both brands, while seven and tenwere specific to Changyu XO and Hennessy XO, respectively. The study provided detailed information aboutthe compounds responsible for the characteristic flavour of specific brandies. According to statistical analysis,significant differences were recorded between Changyu XO and Hennessy XO. Most volatile compounds inChangyu XO occurred at lower concentrations than those in Hennessy XO. Based on sensory evaluation analysis,the floral, alcohol and rancid aroma descriptors achieved higher scores in Changyu XO and Hennessy XO, whilethe lime aroma seemed specific to Hennessy XO. Herb and almond aromas were specific to Changyu XO

Cross-layer design for mission-critical IoT in mobile edge computing systems

In this paper, we establish a cross-layer framework for optimizing user association, packet offloading rates, and bandwidth allocation for mission-critical Internet-of-Things (MC-IoT) services with short packets in mobile edge computing (MEC) systems, where enhanced mobile broadband (eMBB) services with long packets are considered as background services. To reduce communication delay, the fifth generation new radio is adopted in radio access networks. To avoid long queueing delay for short packets from MC-IoT, processor-sharing (PS) servers are deployed at MEC systems, where the service rate of the server is equally allocated to all the packets in the buffer. We derive the distribution of latency experienced by short packets in closed form, and minimize the overall packet loss probability subject to the end-to-end delay requirement. To solve the nonconvex optimization problem, we propose an algorithm that converges to a near optimal solution when the throughput of eMBB services is much higher than MC-IoT services, and extend it into more general scenarios. Furthermore, we derive the optimal solutions in two asymptotic cases: communication or computing is the bottleneck of reliability. The simulation and numerical results validate our analysis and show that the PS server outperforms first-come-first-serve servers

Joint compression and deadline optimization for wireless federated learning

Federated edge learning (FEEL) is a popular distributed learning framework for privacy-preserving at the edge, in which densely distributed edge devices periodically exchange model-updates with the server to complete the global model training. Due to limited bandwidth and uncertain wireless environment, FEEL may impose heavy burden to the current communication system. In addition, under the common FEEL framework, the server needs to wait for the slowest device to complete the update uploading before starting the aggregation process, leading to the straggler issue that causes prolonged communication time. In this paper, we propose to accelerate FEEL from two aspects: i.e., 1) performing data compression on the edge devices and 2) setting a deadline on the edge server to exclude the straggler devices. However, undesired gradient compression errors and transmission outage are introduced by the aforementioned operations respectively, affecting the convergence of FEEL as well. In view of these practical issues, we formulate a training time minimization problem, with the compression ratio and deadline to be optimized. To this end, an asymptotically unbiased aggregation scheme is first proposed to ensure zero optimality gap after convergence, and the impact of compression error and transmission outage on the overall training time are quantified through convergence analysis. Then, the formulated problem is solved in an alternating manner, based on which, the novel joint compression and deadline optimization (JCDO) algorithm is derived. Numerical experiments for different use cases in FEEL including image classification and autonomous driving show that the proposed method is nearly 30X faster than the vanilla FedSGD algorithm, and outperforms the state-of-the-art schemes

Gene expression time delays & Turing pattern formation systems

The incorporation of time delays can greatly affect the behaviour of partial differential equations and dynamical systems. In addition, there is evidence that time delays in gene expression due to transcription and translation play an important role in the dynamics of cellular systems. In this paper, we investigate the effects of incorporating gene expression time delays into a one-dimensional putative reaction diffusion pattern formation mechanism on both stationary domains and domains with spatially uniform exponential growth. While oscillatory behaviour is rare, we find that the time taken to initiate and stabilise patterns increases dramatically as the time delay is increased. In addition, we observe that on rapidly growing domains the time delay can induce a failure of the Turing instability which cannot be predicted by a naive linear analysis of the underlying equations about the homogeneous steady state. The dramatic lag in the induction of patterning, or even its complete absence on occasions, highlights the importance of considering explicit gene expression time delays in models for cellular reaction diffusion patterning

Controllable Laser Ion Acceleration

In this paper a future laser ion accelerator is discussed to make the laser-based ion accelerator compact and controllable. Especially a collimation device is focused in this paper. The future laser ion accelerator should have an ion source, ion collimators, ion beam bunchers, and ion post acceleration devices [Laser Therapy 22, 103(2013)]: the ion particle energy and the ion energy spectrum are controlled to meet requirements for a future compact laser ion accelerator for ion cancer therapy or for other purposes. The energy efficiency from the laser to ions is improved by using a solid target with a fine sub-wavelength structure or a near-critical density gas plasma. The ion beam collimation is performed by holes behind the solid target or a multi-layered solid target. The control of the ion energy spectrum and the ion particle energy, and the ion beam bunching would be successfully realized by a multistage laser-target interaction

Alterations to nuclear architecture and genome behavior in senescent cells.

The organization of the genome within interphase nuclei, and how it interacts with nuclear structures is important for the regulation of nuclear functions. Many of the studies researching the importance of genome organization and nuclear structure are performed in young, proliferating, and often transformed cells. These studies do not reveal anything about the nucleus or genome in nonproliferating cells, which may be relevant for the regulation of both proliferation and replicative senescence. Here, we provide an overview of what is known about the genome and nuclear structure in senescent cells. We review the evidence that nuclear structures, such as the nuclear lamina, nucleoli, the nuclear matrix, nuclear bodies (such as promyelocytic leukemia bodies), and nuclear morphology all become altered within growth-arrested or senescent cells. Specific alterations to the genome in senescent cells, as compared to young proliferating cells, are described, including aneuploidy, chromatin modifications, chromosome positioning, relocation of heterochromatin, and changes to telomeres

Genome-wide association study of heart rate and its variability in Hispanic/Latino cohorts

Background Although time–domain measures of heart rate variability (HRV) are used to estimate cardiac autonomic tone and disease risk in multiethnic populations, the genetic epidemiology of HRV in Hispanics/Latinos has not been characterized. Objective The purpose of this study was to conduct a genome-wide association study of heart rate (HR) and its variability in the Hispanic Community Health Study/Study of Latinos, Multi-Ethnic Study of Atherosclerosis, and Women's Health Initiative Hispanic SNP-Health Association Resource project (n = 13,767). Methods We estimated HR (bpm), standard deviation of normal-to-normal interbeat intervals (SDNN, ms), and root mean squared difference in successive, normal-to-normal interbeat intervals (RMSSD, ms) from resting, standard 12-lead ECGs. We estimated associations between each phenotype and 17 million genotyped or imputed single nucleotide polymorphisms (SNPs), accounting for relatedness and adjusting for age, sex, study site, and ancestry. Cohort-specific estimates were combined using fixed-effects, inverse-variance meta-analysis. We investigated replication for select SNPs exceeding genome-wide (P <5 × 10–8) or suggestive (P <10–6) significance thresholds. Results Two genome-wide significant SNPs replicated in a European ancestry cohort, 1 one for RMSSD (rs4963772; chromosome 12) and another for SDNN (rs12982903; chromosome 19). A suggestive SNP for HR (rs236352; chromosome 6) replicated in an African-American cohort. Functional annotation of replicated SNPs in cardiac and neuronal tissues identified potentially causal variants and mechanisms. Conclusion This first genome-wide association study of HRV and HR in Hispanics/Latinos underscores the potential for even modestly sized samples of non-European ancestry to inform the genetic epidemiology of complex traits

Identification of common genetic risk variants for autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.Peer reviewe