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Taurine is a conditionally essential micronutrient and one of the most abundant amino acids in humans1-3. In endogenous taurine metabolism, dedicated enzymes are involved in the biosynthesis of taurine from cysteine and in the downstream metabolism of secondary taurine metabolites4,5. One taurine metabolite is N-acetyltaurine6. Levels of N-acetyltaurine are dynamically regulated by stimuli that alter taurine or acetate flux, including endurance exercise7, dietary taurine supplementation8 and alcohol consumption6,9. So far, the identities of the enzymes involved in N-acetyltaurine metabolism, and the potential functions of N-acetyltaurine itself, have remained unknown. Here we show that the body mass index associated orphan enzyme phosphotriesterase-related (PTER)10 is a physiological N-acetyltaurine hydrolase. In vitro, PTER catalyses the hydrolysis of N-acetyltaurine to taurine and acetate. In mice, PTER is expressed in the kidney, liver and brainstem. Genetic ablation of Pter in mice results in complete loss of tissue N-acetyltaurine hydrolysis activity and a systemic increase in N-acetyltaurine levels. After stimuli that increase taurine levels, Pter knockout mice exhibit reduced food intake, resistance to diet-induced obesity and improved glucose homeostasis. Administration of N-acetyltaurine to obese wild-type mice also reduces food intake and body weight in a GFRAL-dependent manner. These data place PTER into a central enzymatic node of secondary taurine metabolism and uncover a role for PTER and N-acetyltaurine in body weight control and energy balance.

We study the following generalized quasilinear Schrödinger equation:

In view of the fact that the current integrated port energy system (IPES) considers neither the time scale difference of refrigerated containers in port scheduling nor the impact of renewable energy and load uncertainty, this paper proposes a day-ahead and intra-day two-stage rolling optimization scheduling method for a container IPES. In day-ahead scheduling, based on the temperature rise process of refrigerated containers, a port cold chain energy demand model is established, which is combined with the logistics process after the arrival of refrigerated containers. Then, the day-ahead output values of each unit in the system are obtained with the goal of the lowest operating cost. In intra-day scheduling, a two-layer rolling model is proposed to obtain the adjusted output of the port energy equipment, which considers the prediction error of shore power load and renewable energy as well as the different response speeds of cooling, heating and power. The calculation results show that the collaborative optimization scheduling of refrigerated containers and the container IPES can effectively reduce the port operation cost and carbon emissions. The two-stage day-ahead and intra-day rolling optimization scheduling can improve the economy and stability of the system.

In modern ship degaussing systems, degaussing windings are mainly distributed based on the shape of ship bulkhead, which is difficult to ensure the degaussing effect of magnetic induction intensity of unit winding of each degaussing winding. In order to solve this problem, this paper introduces a tilted correlation screening in high-dimensional variable filter, which splits and recombines the original coils, and re-divides the original degaussing sections, so as to improve the degaussing efficiency of each coil. Aiming at the problem of sparse parameter vectors and multiple collinearity in the calculation of degaussing current after winding restructuring, this paper proposes a slant correlation screening and partial ridge regression algorithm. Through simulation, when the threshold is 0.73 and 0.91, the algorithm reduces 10.08% and 17.59% respectively compared with the least square method, while the residual root mean square error decreases by 10.45% and 12.17%. The simulation results show that the degaussing effect is significantly improved after the algorithm is adopted.

Integration of distributed generations into distribution networks has become one of the important features of new power systems. The integration of distributed generation and the uncertainty of power generation make the power flow in distribution networks complex and variable, which poses higher technical requirements for rapid fault location in distribution networks. However, existing intelligent optimization algorithms may encounter problems such as slow convergence speed and susceptibility to local optimization when solving the problem of fault section location in distribution networks. To address these challenges and problems, a rapid fault section location technology based on quantum ant colony algorithm (QACA) is proposed. First, a location mathematical model is constructed based on the state approximation idea and the minimum fault set theory. Then, an information self-correction method is proposed for the missing information uploaded by feeder terminal unit, and a hierarchical location model is proposed to shorten the location time. Afterwards, three improvement techniques are proposed to improve the QACA. The update mechanism of the quantum rotary gate is improved, the rotation angle is dynamically adjusted in the form of function control, and the elite strategy is introduced to accelerate the convergence speed of the algorithm. Finally, after the key parameters are determined, the effectiveness of the improved technique, the information self-correction method, and the hierarchical positioning model is verified. A comparison with 7 different algorithms indicates that the improved QACA can effectively locate the fault section, and has a fast convergence speed, great accuracy, and fault tolerance.

A method is proposed for determining the optimal temperature and magnetic field strength used to condition a sodium vapor cell for use in a sodium Double-Edge Magneto-Optic Filter (Na-DEMOF). The desirable characteristics of these filters are first defined and then analyzed over a range of temperatures and magnetic field strengths, using an IDL Faraday filter simulation adapted for the Na-DEMOF. This simulation is then compared to real behavior of a Na-DEMOF constructed for use with the Chu Research Group’s STAR Na Doppler resonance-fluorescence lidar for lower atmospheric observations.

We present the first coordinated study of a 1-h mesoscale gravity wave event detected simultaneously by a Na Doppler lidar at Boulder, CO (40.1°N, 105.2°W), and a Na Doppler lidar and an airglow temperature mapper (AMTM) at Logan, UT (41.7°N, 111.8°W) in the mesopause region on 27 Nov. 2013. The vertical and horizontal wavelengths are ~16.0±0.3 and 342.0±10.4 km, corresponding to vertical and horizontal phase speeds of ~4.4±0.1 and 95.0±3.0 m/s, respectively. The wave propagates from Logan to Boulder with an azimuth angle of ~138.1±1.7° clockwise from North. A uniqueness of this study is that the 1-h wave amplitudes on vertical winds have been quantified for the first time by the STAR Na lidar at Boulder. The GW polarization relation between vertical wind and temperature is evaluated. The intrinsic period of the wave is Doppler shifted to ~100 min by a background wind of 40 m/s, which is confirmed by USU lidar wind observations. This study illustrates a great potential of combining multiple instruments to fully characterize mesoscale gravity waves and inspect their intrinsic properties

Stunning new science discoveries including neutral thermospheric metal layers in the 100–200 km altitude from McMurdo lidar campaign and other world lidar observations have led to a new initiative in the middle and upper atmosphere science community—the very large-aperture lidar Observatory for Atmosphere Space Interaction Studies (OASIS). These discoveries and the recent technology breakthroughs in Fe and Na Doppler lidars are presented to illustrate the science drivers and technology foundations forming the basis for OASIS.