A Deep‐Learning Approach to the Dynamics of Landau–Zenner Transitions

Traditional approaches to the dynamics of the open quantum systems with high precision are often resource intensive. How to improve computation accuracy and efficiency for target systems is an extremely difficult challenge. In this work, combining unsupervised and supervised learning algorithms, a deep-learning approach is introduced to simulate and predict Landau–Zenner dynamics. Data obtained from multiple Davydov (Formula presented.) Ansatz with a low multiplicity of four are used for training, while the data from the trial state with a high multiplicity of ten are adopted as target data to assess the accuracy of prediction. After proper training, our method can successfully predict and simulate Landau–Zenner dynamics using only random noise and two adjustable model parameters. Compared to the high-precision dynamics data from multiple Davydov (Formula presented.) Ansatz with a multiplicity of ten, the error rate falls below 0.6%.Ministry of Education (MOE)Accepted versionThe authors gratefully acknowledge the support of the Singapore Ministry of Education Academic Research Fund (Grant Nos. 2018-T1-002-175 and 2020-T1-002- 075)). K. Sun would also like to thank the Natural Science Foundation of Zhejiang Province (Grant No. LY18A040005) for partial support. L.L. Gao acknowledges the support of the Graduate Scientific Research Foundation of Hangzhou Dianzi University

Profiles of Urine Samples Taken from Ecstasy Users at Rave Parties: Analysis by Immunoassays, HPLC, and GC-MS

The abuse of the designer amphetamines such as 3,4-methylenedioxymethamphetamine (MDMA, Ecstasy) is increasing throughout the world. They have become popular drugs, especially at all-night techno dance parties (Raves), and their detection is becoming an important issue. Presently, there are no MDMA- or MDA-specific immunoassays on the market, and detection of the designer amphetamines is dependent upon the use of commercially available amphetamine assays. The success of this approach has been difficult to assess because of the general unavailability of significant numbers of samples from known drug users. The objectives of the present study are to characterize the drug content of urine samples from admitted Ecstasy users by chromatographic methods and to assess the ability of the available amphetamine/methamphetamine immunoassays to detect methylenedioxyamphetamines. We found that, when analyzed by high-performance liquid chromatography with diode-array detection (HPLC-DAD), 64% of 70 urine samples (by gas chromatography-mass spectrometry [GC-MS]: 88% of 64 urine samples) obtained from Rave attendees contained MDMA and/or 3,4-methylenedioxyamphetamine (MDA) alone or in combination with amphetamine, methamphetamine, or other designer amphetamines such as 3,4-methylenedioxyethylamphetamine (MDEA). This suggests that the majority of the Ravers are multi-drug users. At the manufacturer's suggested cutoffs, the Abbott TDx Amphetamine/Methamphetamine II and the new Roche HS Amphetamine/MDMA assays demonstrated greater detection sensitivity for MDMA than the other amphetamine immunoassays tested (Abuscreen OnLine Hitachi AMPS, Abuscreen OnLine Integra AMPS, Abuscreen OnLine Integra AMPSX, CEDIA AMPS, and EMIT II AMPS). There is 100% agreement between each of the two immunoassays with the reference chromatographic methods, HPLC-DAD and GC-MS, for the detection of methylenedioxyamphetamine

The circadian rhythms regulated by Cx43-signaling in the pathogenesis of Neuromyelitis Optica

IntroductionNeuromyelitis Optica (NMO) is an inflammatory demyelinating disease of the central nervous system (CNS). NMO manifests as selective and severe attacks on axons and myelin of the optic nerve and spinal cord, resulting in necrotic cavities. The circadian rhythms are well demonstrated to profoundly impact cellular function, behavior, and disease. This study is aimed to explore the role and molecular basis of circadian rhythms in NMO.MethodsWe used an Aquaporin 4(AQP4) IgG-induced NMO cell model in isolated astrocytes. The expression of Cx43 and Bmal1 were detected by real-time PCR and Western Blot. TAT-Gap19 and DQP-1105 were used to inhibit Cx43 and glutamate receptor respectively. The knockdown of Bmal1 were performed with the shRNA containing adenovirus. The levels of glutamate, anterior visual pathway (AVP), and vasoactive intestinal peptide (VIP) were quantified by ELISA kits.ResultsWe found that Bmal1 and Clock, two essential components of the circadian clock, were significantly decreased in NMO astrocytes, which were reversed by Cx43 activation (linoleic acid) or glutamate. Moreover, the expression levels of Bmal1 and Clock were also decreased by Cx43 blockade (TAT-Gap19) or glutamate receptor inhibition (DQP-1105). Furthermore, adenovirus-mediated Bmal1 knockdown by shRNA (Ad-sh-Bmal1) dramatically decreased the levels of glutamate, AVP, and VIP from neurons, and significantly down-regulated the protein level of Cx43 in NMO astrocytes with Cx43 activation (linoleic acid) or glutamate treatment. However, Bmal1 knockdown did not alter these levels in normal astrocytes with Cx43 blockade (TAT-Gap19) or glutamate receptor inhibition (DQP-1105).DiscussionCollectively, these results suggest that Cx43-glutamate signaling would be a critical upstream regulator that contributes to the NMO-induced rhythmic damage in SCN astrocytes

Recommended high performance telescope system design for the TianQin project

China is planning to construct a new space-borne gravitational-wave (GW) observatory, the TianQin project, in which the spaceborne telescope is an important component in laser interferometry. The telescope is aimed to transmit laser beams between the spacecrafts for the measurement of the displacements between proof-masses in long arms. The telescope should have ultra-small wavefront deviation to minimize noise caused by pointing error, ultra-stable structure to minimize optical path noise caused by temperature jitter, ultra-high stray light suppression ability to eliminate background noise. In this paper, we realize a telescope system design with ultra-stable structure as well as ultra-low wavefront distortion for the space-based GW detection mission. The design requirements demand extreme control of high image quality and extraordinary stray light suppression ability. Based on the primary aberration theory, the initial structure design of the mentioned four-mirror optical system is explored. After optimization, the maximum RMS wavefront error is less than lamda/300 over the full field of view (FOV), which meets the noise budget on the telescope design. The stray light noise caused by the back reflection of the telescope is also analyzed. The noise at the position of optical bench is less than 10-10 of the transmitted power, satisfying the requirements of space gravitational-wave detection. We believe that our design can be a good candidate for TianQin project, and can also be a good guide for the space telescope design in any other similar science project

Sharing Economy in Local Energy Markets

With an increase in the electrification of end-use sectors, various resources on the demand side provide great flexibility potential for system operation, which also leads to problems such as the strong randomness of power consumption behavior, the low utilization rate of flexible resources, and difficulties in cost recovery. With the core idea of 'access over ownership', the concept of the sharing economy has gained substantial popularity in the local energy market in recent years. Thus, we provide an overview of the potential market design for the sharing economy in local energy markets (LEMs) and conduct a detailed review of research related to local energy sharing, enabling technologies, and potential practices. This paper can provide a useful reference and insights for the activation of demand-side flexibility potential. Hopefully, this paper can also provide novel insights into the development and further integration of the sharing economy in LEMs.</p

Dietary Modulation of Gut Microbiota Contributes to Alleviation of Both Genetic and Simple Obesity in Children

Gut microbiota has been implicated as a pivotal contributing factor in diet-related obesity; however, its role in development of disease phenotypes in human genetic obesity such as Prader–Willi syndrome (PWS) remains elusive. In this hospitalized intervention trial with PWS (n = 17) and simple obesity (n = 21) children, a diet rich in non-digestible carbohydrates induced significant weight loss and concomitant structural changes of the gut microbiota together with reduction of serum antigen load and alleviation of inflammation. Co-abundance network analysis of 161 prevalent bacterial draft genomes assembled directly from metagenomic datasets showed relative increase of functional genome groups for acetate production from carbohydrates fermentation. NMR-based metabolomic profiling of urine showed diet-induced overall changes of host metabotypes and identified significantly reduced trimethylamine N-oxide and indoxyl sulfate, host-bacteria co-metabolites known to induce metabolic deteriorations. Specific bacterial genomes that were correlated with urine levels of these detrimental co-metabolites were found to encode enzyme genes for production of their precursors by fermentation of choline or tryptophan in the gut. When transplanted into germ-free mice, the pre-intervention gut microbiota induced higher inflammation and larger adipocytes compared with the post-intervention microbiota from the same volunteer. Our multi-omics-based systems analysis indicates a significant etiological contribution of dysbiotic gut microbiota to both genetic and simple obesity in children, implicating a potentially effective target for alleviation