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To develop a predicting model of child-bearing-aged women' spontaneous abortion (SA) by co-infections of TORCH and reproductive tract, in order to provide a reference tool for accurately predicting the risk of SA and guide the early prevention, diagnosis and treatment of SA. A prospective cohort study was designed based on 218 958 child-bearing-aged women following up in Hebei province in China from 2010 to 2017. Multivariable logistic regression analysis was used to select candidate predictive variables. Fisher's discriminant analysis was performed to build a predictive model, and the validity of the model was evaluated. The incidence rate of SA was 2.4%. Multivariable logistic regression analysis showed that age (OR = 3.507), adverse pregnancy history (OR = 1.509), co-infections status of Candida and HBsAg (OR

Background Guben Zhike decoction (GBZKD) is derived from the experience of Professor Enxiang Chao, an esteemed master of Chinese medicine, while treating chronic obstructive pulmonary disease (COPD). GBZKD reinforces the healthy qi and consolidates defensive qi. This study explored the efficacy and potential mechanism of action of GBZKD in a COPD mouse model using proteomics. Methods A COPD mouse model was established through cigarette smoke exposure and intranasal lipopolysaccharide administration. The model was verified through lung function test and lung histopathological observation. Label-free quantitative proteomics was used to detect the lung tissue proteins of mice from the GBZKD, COPD, and control groups. Results GBZKD markedly improved the lung function and associated pathological conditions in the COPD mouse model. Proteomic analysis identified 4316 proteins, of which 3696 were quantitative proteins. We highlighted 287 and 184 proteins with significant regulatory roles in the lung tissues of COPD mice and GBZKD-treated mice, respectively. These proteins participated in multiple functions, including complement/coagulation cascade, immune response, and metabolic pathways. Conclusion GBZKD exhibits multitarget and multipathway therapeutic effects in a COPD mouse model.

Background: The vehicle pose detection plays an important role in monitoring vehicle behavior and the parking situation. The real-time detection of vehicle pose with high accuracy is of great importance. Objective: The goal of the work is to construct a new network to detect the vehicle angle based on the regression Convolutional Neural Network (CNN). The main contribution is that several traditional regression CNNs are combined as the Multi-Collaborative Regression CNN (MCR-CNN), which greatly enhances the vehicle angle detection precision and eliminates the abnormal detection error. Methods: Two challenges with respect to the traditional regression CNN have been revealed in detecting the vehicle pose angle. The first challenge is the detection failure resulting from the conversion of the periodic angle to the linear angle, while the second is the big detection error if the training sample value is very small. An MCR-CNN is proposed to solve the first challenge. And a 2- stage method is proposed to solve the second challenge. The architecture of the MCR-CNN is designed in detail. After the training and testing data sets are constructed, the MCR-CNN is trained and tested for vehicle angle detection. Results: The experimental results show that the testing samples with the error below 4° account for 95% of the total testing samples based on the proposed MCR-CNN. The MCR-CNN has significant advantages over the traditional vehicle pose detection method. Conclusion: The proposed MCR-CNN cannot only detect the vehicle angle in real-time, but also has a very high detection accuracy and robustness. The proposed approach can be used for autonomous vehicles and monitoring of the parking lot.

The Seebeck effect converts thermal gradients into electricity. As an approach to power technologies in the current Internet-of-Things era, on-chip energy harvesting is highly attractive, and to be effective, demands thin film materials with large Seebeck coefficients. In spintronics, the antiferromagnetic metal IrMn has been used as the pinning layer in magnetic tunnel junctions that form building blocks for magnetic random access memories and magnetic sensors. Spin pumping experiments revealed that IrMn Néel temperature is thickness-dependent and approaches room temperature when the layer is thin. Here, we report that the Seebeck coefficient is maximum at the Néel temperature of IrMn of 0.6 to 4.0 nm in thickness in IrMn-based half magnetic tunnel junctions. We obtain a record Seebeck coefficient 390 (±10) μV K−1 at room temperature. Our results demonstrate that IrMn-based magnetic devices could harvest the heat dissipation for magnetic sensors, thus contributing to the Power-of-Things paradigm., Antiferromagnetic materials are potentially useful for spintronic applications. Here, the authors report high thermoelectric power value of 390 μV/K Seebeck coefficient in IrMn-based half magnetic tunnel junctions at room temperature.

Object detection is a crucial task of autonomous driving. This paper addresses an effective algorithm for pedestrian detection of the panoramic depth map transformed from the 3D-LiDAR data. Firstly, the 3D point clouds are transformed into panoramic depth maps, and then the panoramic depth maps are enhanced. Secondly, the grounds of the 3D point clouds are removed. The remaining point clouds are clustered, filtered and projected onto the previously generated panoramic depth maps, and new panoramic depth maps are obtained. Finally, the new panoramic depth maps are jointed to generate depth maps with different sizes, which are used as input of the improved PVANET for pedestrian detection. The 2D image of the panoramic depth map applied to the proposed algorithm is transformed from 3D point cloud, effectively containing the panorama of the sensor, and is more suitable for the environment perception of autonomous driving. Compared with the detection algorithm based on RGB images, the proposed algorithm cannot be affected by light, and can maintain the normal average precision of pedestrian detection at night. In order to increase the robustness of detecting small objects like pedestrians, the network structure based on the original PVANET is modified in this paper. A new dataset is built by processing the 3D-LiDAR data and the model trained on the new dataset perform well. The experimental results show that the proposed algorithm achieves high accuracy and robustness in pedestrian detection under different illumination conditions. Furthermore, when trained on the new dataset, the model exhibits average precision improvements of 2.8–5.1 % over the original PVANET, making it more suitable for autonomous driving applications.

Although nanoscale deformation, such as nanostrain in iron-chalcogenide (FeSexTe1−x, FST) thin films, has attracted attention owing to its enhancement of general superconducting properties, including critical current density (Jc) and critical transition temperature, the development of this technique has proven to be an extremely challenging and complex process thus far. Herein, we successfully fabricated an epitaxial FST thin film with uniformly distributed nanostrain by injection of a trace amount of CeO2 inside an FST matrix using sequential pulsed laser deposition. By means of transmission electron microscopy and geometric phase analysis, we verified that the injection of a trace amount of CeO2 forms nanoscale defects, with a nanostrained region of tensile strain (ezz ≅ 0.02) along the c-axis of the FST matrix. This nanostrained FST thin film achieves a remarkable Jc of 3.5 MA/cm2 under a self-field at 6 K and a highly enhanced Jc under the entire magnetic field with respect to those of a pristine FST thin film. The maximum amount of current that can be carried by iron-based superconductors can be improved by introducing deliberate defects during fabrication. Iron–selenium–tellurium thin films have recently been identified as high-temperature superconductors that may pass large quantities of current. Sanghan Lee from the Gwangju Institute of Science and Technology in South Korea and co-workers have now used lasers to deposit small amounts of cerium oxide atoms between layers of an iron–selenium–tellurium thin film. The cerium oxide particles create defects, such as selenium-deficient sites, that slightly strain the crystal lattice and let more current move through the film. Mapping these nanostrain effects with electron microscopy enabled the team to find conditions needed to enhance superconductivity while minimizing cerium oxide by-products. To enhance supercurrent of iron-chalcogenide (FST) superconductor thin films, we induced nanostrain in FST thin films. The nanostrain was generated around nanoscale defects which were formed by the inserted a trace amount of oxide artificially inside FST matrix during the growth of FST thin film using sequential pulsed laser deposition. In particular, the critical current density (Jc) of the nanostrained FST thin films was significantly improved without dominant degradation of critical transition temperature.

Excessive synthetic nitrogen (N) applications, high mineral N accumulation and low N use efficiency (NUE) are current issues in intensively cultivated winter wheat production system impeding the sustainable development of agriculture in China. To solve these problems, soil accumulated N in the top 1 m of the soil profile before sowing (Nsoil), returned straw-N from the previous maize crop (Nstraw) and fertilizer N application (Nfertilizer) should be comprehensively considered N supply sources in N management. As such, the objective of this research was to determine the optimal total N supply (TNsupply) level needed to meet crop requirements while minimizing environmental impacts. A 9-year on-farm experiment was conducted in accordance with a split-plot design involving two different fertilizer management systems (main treatments) and three N application strategies (sub treatments). Extensive TNsupply levels (ranging from 61 kg ha−1 to 813 kg ha−1) were detected, and relative yield (RY), N input and N output in response to the TNsupply were measured. The relationships between TNsupply and RY, N input, and N output strongly fit linear-plateau, linear, and linear-plateau models, respectively. The minimum TNsupply levels needed to achieve the maximum RY and N output were 325 and 392 kg ha−1, respectively. On the basis of N supply capacity, the TNsupply was removed from the growing system by 61% (N input). As the N input increased past 209 kg ha−1, the NUE declined, at which point the TNsupply reached 433 kg ha−1. Therefore, the suitable TNsupply should range from 325 kg ha−1 (ensuring a total N supply for high yield and N uptake) to 433 kg ha−1 (obtaining a relatively higher NUE and less N loss to the environment). The TNsupply was highlighted to be an indicator for use in N management recommendations. Considering the average high N accumulation in winter wheat production systems, N management should essentially take into account the consumption of Nsoil, the levels of Nstraw and the minimum application of Nfertilizer to obtain high yields while minimizing environmental impacts under suitable TNsupply levels.

Chicken plumage colour is a complex trait controlled by many genes. Herein, through Rhode Island Red (RIR) and White Leghorn (WL) F1 cross populations, the segregation of plumage color was observed in females, showing white in males, and dark red (DR) and light yellow (LY) in females. The white has been found to be caused by dominant white alleles (I) and the DR phenotype is attributed to a sex-linked recessive silver allele (S∗S). LY is a derived feather colour phenotype and the genetic mechanism of this is unclear. In order to explore the genetic basis for LY, we randomly selected 40 DR and 39 LY chickens for paired-end sequencing. Through the use of association analysis, we found the LY phenotype is caused by a 7.6 kb non-coding deletion near the SOX10 gene. This mutation has been reported to be responsible for dark brown plumage in chicken, and subsequent diagnostic PCR tests showed that the length of the long-range non-coding deletion is 7.6 kb instead of 8.3 kb as previously reported.

A dynamic thermal environment meeting human health requirements can be created with natural wind simulated by artificial means. Simulating natural wind can provide an innovative air-conditioning mode that reduces the energy consumption of air-conditioning systems and avoids the body-resistance decrease and body-temperature regulation mechanism failure that limit the traditional steady air-conditioning mode. In this paper, new methods for simulating natural wind are presented in which the controllable fluctuation of mechanical wind is improved to make its characteristics more similar to those of natural wind. Experiments carried out to verify the effectiveness of these mechanical-wind methods are reported. A self-operated air supply device improving the fluctuation of the air supply is proposed, which can increase the value of the characteristic parameter β (the negative slope of the double-logarithmic power spectrum curve) to 1.2 when the wind speed is greater than 1 m/s. With a second proposed device based on the gas-washing process, this value can reach 1.4 when the wind speed is greater than 0.5 m/s. In summary, this paper provides simple solutions for simulating natural wind.

In this study, we designed and synthesized a novel battery-type electrode featuring three-dimensional (3D) hierarchical ZnO@Ni x Co1−x(OH) y core/shell nanowire/nanosheet arrays arranged on Ni foam substrate via a two-step protocol including a wet chemical process followed by electro-deposition. We then characterized its composition, structure and surface morphology by X-ray diffraction, energy-dispersive X-ray spectrometry (EDS), X-ray photoelectron spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy, EDS elemental mapping. Our electrochemical measurements show that the ZnO@Ni0.67Co0.33(OH) y electrode material exhibited a noticeably high specific capacity of as much as 255 (mA·h)/g at 1 A/g. Additionally, it demonstrated a superior rate capability, as well as an excellent cycling stability with 81.6% capacity retention over 2000 cycles at 5 A/g. This sample delivered a high energy density of 64 W·h/kg and a power density of 250 W/kg at a current density of 1 A/g. With such remarkable electrochemical properties, we expect the 3D hierarchical hybrid electrode material presented in this work to have promising applications for the next generation of energy storage systems.

In high-rise residential buildings, channeling in the flue between stories can spread pollutants and airborne diseases. To avoid this issue, it is necessary to use an airflow balance device, which will greatly increase the flow resistance. Based on a centralized exhaust shaft, this paper proposed a novel cycloidal guide confluence flue tee. The resistance characteristics of the flue tee were analyzed at different flow ratios and duct aspect ratios. The quantitative effects of the forward flow resistance decreased and those of the backward flow resistance increased after the guide vane was installed. The performances of the traditional tee and novel tee were tested and verified by performing full-scale experiments under the same duct aspect ratio and different flow ratios. The ranges of the decrease in forward resistance and increase in backward resistance were 44.07–196.97% and 4.30–171.20%, respectively. Under the same flow ratio and different duct aspect ratios, the ranges of the decrease in forward resistance and increase in backward resistance were 17.30–99.90% and 2.23–27.40%, respectively. The results of this work will provide a new perspective on resistance reduction and anti-channeling flue tee shape design in ventilation and air conditioning systems.

Floor-standing air conditioners (FSACs) have been widely used in civil and office buildings due to their high cooling capacity and easy installation in recent years. Increasing attention has been given to reducing the draft sensation of FSACs. This study introduces a new form of smart terminal for air conditioners that can be automatically adjusted by identifying the positions of humans in the room. The smart terminal has certain practical value given its simple structure and relatively low cost. A target air supply evaluation index for regional thermal comfort evaluation named the air velocity target value is proposed. A computational fluid dynamics model is established, and an orthogonal experiment of 4 factors and 4 levels is designed. The optimal parameters of the terminal are further determined through a series of optimization steps. The effect of the smart terminal is validated with numerical simulation and experimental measures, and the local velocities of the occupied zone are mostly below 0.3 m/s, showing that the draft level in the room is acceptable. Compared with the case of an air conditioner only, the air velocity target value of the room with a smart terminal decreases by 21.3%–63.3%. Compared with other existing manually controlled terminals purchased online, the smart terminal satisfies the minimum air velocity target value in the occupied zone. This study can also be used to guide the positioning and setting of air supplies for different positions of humans in a room under other air distributions.

The fan energy consumption caused by the resistance of representative local components, including diffusers, accounts for 10% of building energy consumption. This proportion increases with more stringent requirements for building functionality, intelligence and comfort. This study introduces a high-efficiency diffuser based on a normalized evaluation index of jet length and resistance. The resistance reduction mechanism is analyzed based on the principle of entropy increase. A comprehensive performance evaluation index, the air diffuser effective index (ADEI), is put forward to describe the resistance and jet length of the diffuser. The preliminary results show that compared with the round diffuser, the novel diffuser can mitigate the fluid deformation, weaken the strength of the airflow vortex and reduce the conversion of mechanical energy to internal energy. The jet length and flow resistance of the novel diffuser are respectively 7% longer and 47% lower than those of the round diffuser. The proposed ADEI of the novel diffuser is 56% smaller than the round diffuser.

The Seebeck effect converts thermal gradients into electricity. As an approach to power technologies in the current Internet-of-Things era, on-chip energy harvesting is highly attractive, and to be effective, demands thin film materials with large Seebeck coefficients. In spintronics, the antiferromagnetic metal IrMn has been used as the pinning layer in magnetic tunnel junctions that form building blocks for magnetic random access memories and magnetic sensors. Spin pumping experiments revealed that IrMn Néel temperature is thickness-dependent and approaches room temperature when the layer is thin. Here, we report that the Seebeck coefficient is maximum at the Néel temperature of IrMn of 0.6 to 4.0 nm in thickness in IrMn-based half magnetic tunnel junctions. We obtain a record Seebeck coefficient 390 (±10) μV K

Different microgrid (MG) users possess different preferences, which effectively stimulates the energy management needs of MG. Based upon different preferences, this paper proposes a battery management strategy in MG for personalized customer requirements, aiming to lower the cost of electricity and stabilize the state of charge (SOC) of energy-storage devices. Firstly, the Long Short Term Memory (LSTM) algorithm is used to predict the user’s load power and generation power of renewable energy, followed by the construction of a corresponding reward function for different preferences of users. Secondly, according to the prediction, the Deep Deterministic Policy Gradient (DDPG) algorithm is used to carry out massive and intensive trainings on the decision model. Furthermore, the L2 regularization correction is introduced to avoid over-fitting during neural network training. Then, based on the predicted power data for the forecast day, an optimal control strategy of battery that meets the needs of differently preferred users is obtained. Finally, comparative experiments have been conducted in four scenarios for economic user, conservative user, compromised user, and user who did not adopt a decision-making framework. The results show that the battery management strategy proposed in this paper can meet the needs of differently preferred users, among whom, the profit of compromised user using the framework has increased by 55.19% and the fluctuation range of SOC have decreased by 67.05% compared with user who did not adopt the decision-making framework.

Vehicle navigation is widely used in path planning of self driving travel, and it plays an increasing important role in people's daily trips. Therefore, path planning algorithms have attracted substantial attention. However, most path planning methods are based on public data, aiming at different driver groups rather than a specific user. Hence, this study proposes a personalized path decision algorithm that is based on user habits. First, the categories of driving characteristics are obtained through the investigation of public users, and the clustering results corresponding to the category space are obtained by log fuzzy C-means clustering algorithm (LFCM) based on the driving information contained in the log trajectories. Then, the road performance personalized quantization algorithm evaluation is proposed to evaluate roads from the user’s field of vision. Finally, adaptive ant colony algorithm is improved and used to validate the path planning based on the road performance personalized values. Results show that the algorithm can meet the personalized requirements of the user path selection in the path decision.

Recent years have witnessed a rapidly growing interest in exploring the use of spin waves for information transmission and computation toward establishing a spin-wave-based technology that is not only significantly more energy efficient than the CMOS technology, but may also cause a major departure from the von-Neumann architecture by enabling memory-in-logic and logic-in-memory architectures. A major bottleneck of advancing this technology is the excitation of spin waves with short wavelengths, which is a must because the wavelength dictates device scalability. Here, we report the discovery of an approach for the excitation of nm-wavelength spin waves. The demonstration uses ferromagnetic nanowires grown on a 20-nm-thick Y3Fe5O12 film strip. The propagation of spin waves with a wavelength down to 50 nm over a distance of 60,000 nm is measured. The measurements yield a spin-wave group velocity as high as 2600 m s−1, which is faster than both domain wall and skyrmion motions., Short-wavelength spin waves with high group velocity are one of the key ingredients for the spin-wave based memory-logics. Here the authors demonstrate the propagation of spin waves with wavelength down to 50 nm and group velocity up to 2600 m s−1 using ferromagnetic nanowires grown on a thin Y3Fe5O12 film strip structure.

Understanding the changes in soil potassium (K) and crop yield under K fertilization and straw return is important for proper K fertilizer management. A field experiment involving a wheat (Triticum aestivum L.)–maize (Zea mays L.) rotation was conducted to study the effects of long-term (20-year) K fertilization and straw return on soil K and crop yield in north-central China. Fertilization treatments included: nitrogen and phosphorus fertilizers (NP), NP plus wheat straw (NPS), NP and K fertilizers (NPK), and NPK plus wheat straw (NPKS). Annual soil K budget increased with increasing K inputs (including fertilizer K and straw K) in the order of NP

Fabrication of epitaxial FeSexTe1−x thin films using pulsed laser deposition (PLD) enables improving their superconducting transition temperature (Tc) by more than ~40% than their bulk Tc. Intriguingly, Tc enhancement in FeSexTe1−x thin films has been observed on various substrates and with different Se content, x. To date, various mechanisms for Tc enhancement have been reported, but they remain controversial in universally explaining the Tc improvement in the FeSexTe1−x films. In this report, we demonstrate that the controversies over the mechanism of Tc enhancement are due to the abnormal changes in the chalcogen ratio (Se:Te) during the film growth and that the previously reported Tc enhancement in FeSe0.5Te0.5 thin films is caused by a remarkable increase of Se content. Although our FeSexTe1−x thin films were fabricated via PLD using a Fe0.94Se0.45Te0.55 target, the precisely measured composition indicates a Se-rich FeSexTe1−x (0.6 x 0.8) as ascertained through accurate compositional analysis by both wavelength dispersive spectroscopy (WDS) and Rutherford backscattering spectrometry (RBS). We suggest that the origin of the abnormal composition change is the difference in the thermodynamic properties of ternary FeSexTe1−x, based on first principle calculations.

In order to make up for the deficiency of traditional single diagnosis in rolling element bearing fault diagnosis application, eliminate a large amount of redundant information and improve the classification effect of the aliasing mode, based on comprehensive analysis of the respective advantages of fuzzy set and tree search, this paper presents a joint rolling bearing fault diagnosis method based on tree-inspired feature selection and FS-DFV (Fuzzy Set and Dependent Feature Vector). The dependent feature vectors (DFV) can dig deeper the essential differences of the faults and improve the fault accuracy. By establishing the heuristic tree model, the tree type heuristic feature search strategy is designed, and the excellent feature selection criteria based on the density clustering with noise are proposed, and the conventional feature selection model is improved. In addition, fuzzy set are used to process the problem of extracting aliasing patterns in the DFV, and fuzzy membership is used to guide subsequent feature extraction of the alias modes. The proposed method is compared with the other four fault diagnosis methods. The experimental results show that the proposed method can effectively improve the diagnostic efficiency of the rolling bearing.

With the aim of increasing the grain crop yield and the level of soil nutrition in the fluvo-aquic soil in North China, the effects of long-term application of K fertilizers and straw returning on crop yield and soil nutrient supplying capacity were investigated in the long-term K localization experiment (1992–2009). The results revealed that wheat and maize responded to K fertilizer in an identical manner and the average yield of wheat and maize for 17 years were NPKSr > NPK > NPSr > NP. Application of K fertilizer on the basis of NP fertilizers could increase the yield of wheat and maize while the grain and straw yields in each treatment were significantly higher for maize than for wheat. The yield of wheat and maize was increased by 6.74% and 22.32% respectively when applied with NPK fertilizers compared to NP fertilizers. With the NPSr fertilizing mode, the yield of wheat and maize was increased by 2.84% and 10.62% compared to the NP mode respectively. The NPKSr fertilizing mode gave the best yield for wheat and maize, resulting in 10.34% and 23.81% increase respectively compared to the NP mode. The yield stability of wheat was significantly higher than that of maize. Under the condition of long-term fertilization, the K uptaken by wheat and maize was degressive by the sequence of NPKSr > NPSr > NPK > NP, mainly deposited in the straw but not in the grain. In this work, the soil natural ability for applying K was gradually reduced as the planting years proceeded and the changes were fitted by linear equations. The natural supply ability of K element in land planted wheat was higher than that in land planted maize.

Y3Fe5O12 (YIG) is a promising candidate for spin wave devices. In the thin film devices, the interface between YIG and substrate may play important roles in determining the device properties. Here, we use spherical aberration-corrected scanning electron microscopy and spectroscopy to study the atomic arrangement, chemistry and electronic structure of the YIG/Gd3Ga5O12 (GGG) interface. We find that the chemical bonding of the interface is FeO-GdGaO and the interface remains sharp in both atomic and electronic structures. We provide an efficient method to study the interface chemical bonding, and these results give necessary information for understanding the properties of interface and also for atomistic calculation.

To observe the impact of Xinkeshu on top of standard medication on psychological stress-related emotional and biophysiological parameters in patients with mental stress-induced myocardial ischemia (MSIMI).A randomized controlled clinical trial was conducted on 40 patients with MSIMI and patients were randomized into treatment group (n = 21) and control group (n = 19) by random number table method. Patients in the treatment group received Xinkeshu (12 capsules/d) on top of standard therapy, and the control group received placebo on top of standard therapy. Serum homocysteine (Hcy), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), left ventricular ejection fraction (LVEF) and left ventricular fractional shortening (LVFS) were compared between the groups at baseline and after 8 weeks therapy.(1) Baseline data were similar between the 2 groups (all P0.05). (2) After 8 weeks, LVFS was significantly increased (from (34.62 ± 5.76)% to (35.90 ± 4.99) %, P = 0.027) and serum Hcy (from (18.08 ± 1.81) µmol/L to (16.06 ± 10.10) µmol/L), PHQ-9 (from 8.14 ± 3.98 to 6.28 ± 2.87) and GAD-7 (from 9.52 ± 4.98 to 6.48 ± 3.84) were significantly reduced in treatment group (all P0.05) compared to baseline. In the control group, only GAD-7 was significantly reduced (from 8.89 ± 5.06 to 6.74 ± 4.80, P = 0.003) after 8 weeks therapy compared to baseline (P0.05) while other parameters remained unchanged (all P0.05).Xinkeshu on the top of standard therapy can improve the emotional state and left ventricular systolic function in patients with MSIMI.

Time management is the study to use time scientifically by deploying skills, techniques and means, and maximizing time value to help individuals or organizations efficiently complete tasks and achieve goals. University professor as a body is an important force in teaching and research. In order to ensure high-quality teaching, productive research, we should establish appropriate service systems to help professors save time and improve efficiency. Time management is the main point of penetration in this research. The responsibilities and missions of professors in universities are the main points of concern. The responsibilities for universities to improve the quality of time management for professors were analyzed. Suggestions and counter measures used to economize time and to improve efficiency for professors with better service were proposed. Through introducing the concept and methods of time management for professor-service into the system, one can greatly improve the service quality, optimize professors’ time allocation, increase work efficiency.