Enhanced thermoelectric properties of atomic-layer-deposited Hf:Zn16O/18O superlattice films by interface-engineering

This study examines three novel approaches for enhancing the thermoelectric (TE) properties of atomic-layer-deposited (ALD) ZnO thin films: 1) Hf-doping, which preserved the crystallinity of ZnO and provided effective phonon scattering owing to Hf's similar atomic radius to and large mass difference with Zn, leading to high power factor (PF) and low thermal conductivity (κ); 2) controlling the distribution of Hf into an alternating scattered phase/clustered phase superlattice, which balanced the high PF of the scattered phases with the low κ of the clustered phases, while providing significant energy-filtering effect to raise the Seebeck coefficient; 3) introducing ¹⁸O/¹⁶O periodicity into the Hf:ZnO films—by alternately using H₂¹⁶O and H₂¹⁸O as oxidants in the ALD processes, which further suppressed κ without compromising PF. The combination of the three approaches resulted in a maximum improvement in ZT of ~1600% over that of the undoped ZnO.     

Calorimetric study of ytterbium orthovanadate YbVO4 polycrystalline ceramics

The heat capacity of ytterbium orthovanadate was first measured by adiabatic calorimetry in the temperature range T?=?12.28–344.06?K. No obvious anomalies were observed on the curve obtained. The values of standard thermodynamic functions in the temperature range T?=?0–400 K were calculated. Based on low-temperature calorimetry data obtained, previously published data on the high-temperature heat capacity of ytterbium orthovanadate were corrected. The anomalous contribution to heat capacity for YbVO₄ was compared with the data known for YbPO₄.     

Fully solution-processed and multilayer blue organic light-emitting diodes based on efficient small molecule emissive layer and intergrated interlayer optimization

Efficient and fully solution-processed blue organic light-emitting diodes (OLEDs) based on fluorescent small-molecule and methanol/water soluble conjugated polymer as electron-injection material are reported. The emitting layer is 3,6-bis(9,9,9′,9′-tetrakis (6-(9H-carbazol-9-yl)hexyl)-9H,9′H-[2,2′-bifluoren]-7-yl)dib-nzo[b, d]thiophene 5, 5-dioxide (OCSoC) with a blue-fluorescent small-molecule, and a methanol/water soluble polymer poly[(9,9-bis(30-(N,N-dimethylamino)propyl)-2,7-fluorene)-alt-2,7-(9,9-dioctyl-fluorene)] (PFN) acted as electron-injection layer (EIL). All the organic layers are spin-coated from solution. The multilayer device structure with emitting layer/electron-injection layer is achieved by solution-processed method without the dissolution problem between layers. The performances of the devices show that the maximum luminous efficiency of the multilayer device is increased about 43%, compared to the single-layer device. PFN acting as the EIL material plays a key role in the improvement of the device performance when used in solution-processed small-molecule OLEDs.     

LTE系统多小区上行联合功控算法

针对传统的小区内开环功率控制算法通常以提升本小区的吞吐量性能为目标，忽略了当前小区用户对邻小区用户同频干扰的问题，为提升边缘用户性能的同时兼顾系统整体性能，提出了一种LTE系统小区间上行联合功率控制（UJPC）算法。该算法采用单基站三扇区为系统模型，以最优化系统吞吐量比例公平函数为目标，首先根据最小信干噪比（SINR）约束值和用户最大发射功率这两个约束条件得到相应的数学优化模型，然后采用连续凸近似的方法求解优化问题得出各个基站所管辖的小区内所有用户的最优发射功率。仿真结果表明，与基准的开环功控方案相比，联合功控方案在保证系统平均频谱利用率的情况下能够较大幅度地提高小区边缘频谱利用率，其最佳性能增益能达到50%。     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Development of LTCC micro-hotplate with PTC temperature sensor for gas-sensing applications

Low temperature co-fired ceramic (LTCC) micro-hotplates show wide applications in gas sensors and micro-fluidic devices. It is easily structured in three-dimensional structures. This paper presents the low power consumption micro-hotplates which were developed with PTC (positive temperature coefficient) temperature sensor and inter-digitated electrodes. The paper presents two different structures for micro-hotplate with platinum as a heating element. The PTC temperature sensor using two different materials viz. PdAg and platinum paste are developed with micro-hotplates. The simulation has been achieved through COMSOL for LTCC and alumina micro-hotplates. The temperature variation with power consumption has been measured for the developed LTCC micro-hotplates. The change in resistance of PTC temperature sensors was measured with micro-hotplate temperature. The aim of this study was to place a temperature sensor with the gas sensor module to measure and control the temperature of micro-hotplate. A SnO₂ sensing layer is coated on LTCC micro-hotplate using screen printing and characterized for the sensing of carbon monoxide gas (CO). This study will be beneficial for designing hotplates based on LTCC technology with low power consumption and better stability of temperature for gas-sensing applications.     

综放工作面防治水技术应用实践

为解决21000工作面采空区及顶板涌水问题,根据工作面出水点的不同情况,采取了集水器导水、老塘设挡水堰截水、挖排水沟疏水等多项治水措施,经统计排水量达33~42m3/h,有效控制了水情,确保了工作面正常生产。     

Active disturbance rejection based trajectory linearization control for hypersonic reentry vehicle with bounded uncertainties

This paper investigates a novel compound control scheme combined with the advantages of trajectory linearization control (TLC) and alternative active disturbance rejection control (ADRC) for hypersonic reentry vehicle (HRV) attitude tracking system with bounded uncertainties. Firstly, in order to overcome actuator saturation problem, nonlinear tracking differentiator (TD) is applied in the attitude loop to achieve fewer control consumption. Then, linear extended state observers (LESO) are constructed to estimate the uncertainties acting on the LTV system in the attitude and angular rate loop. In addition, feedback linearization (FL) based controllers are designed using estimates of uncertainties generated by LESO in each loop, which enable the tracking error for closed-loop system in the presence of large uncertainties to converge to the residual set of the origin asymptotically. Finally, the compound controllers are derived by integrating with the nominal controller for open-loop nonlinear system and FL based controller. Also, comparisons and simulation results are presented to illustrate the effectiveness of the control strategy.     

Dhh1 is a member of the SESA network

The correct separation of chromosomes during mitosis is necessary to prevent genetic instability and aneuploidy, which are responsible for cancer and other diseases, and it depends on proper centrosome duplication. In a recent study, we found that Smy2 can suppress the essential role of Mps2 in the insertion of yeast centrosome into the nuclear membrane by interacting with Eap1, Scp160, and Asc1 and designated this network as SESA (S my2, E ap1, S cp160, A sc1). Detailed analysis showed that the SESA network is part of a mechanism which regulates translation of POM34 mRNA. Thus, SESA is a system that suppresses spindle pole body duplication defects by repressing the translation of POM34 mRNA. In this study, we performed a genome-wide screening in order to identify new members of the SESA network and confirmed Dhh1 as a putative member. Dhh1 is a cytoplasmic DEAD-box helicase known to regulate translation. Therefore, we hypothesized that Dhh1 is responsible for the highly selective inhibition of POM34 mRNA by SESA.     

Automated classification of simulated wind field patterns from multiphysics ensemble forecasts

In this study, we have proposed an automated classification approach to identify meaningful patterns in wind field data. Utilizing an extensive simulated wind database, we have demonstrated that the proposed approach can identify low‐level jets, near‐uniform profiles, and other patterns in a reliable manner. We have studied the dependence of these wind profile patterns on locations (eg, offshore vs onshore), seasons, and diurnal cycles. Furthermore, we have found that the probability distributions of some of the patterns depend on the underlying planetary boundary layer schemes in a significant way. The future potential of the proposed approach in wind resource assessment and, more generally, in mesoscale model parameterization improvement is touched upon in this paper.