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Sugarcane is an important economic crop in tropical and subtropical regions. Presawing planting is an important method for achieving automated and precise planting with sugarcane planting machines. The sawing process is a key stage in planting management, affecting not only the germination and survival rates of sugarcane, but also reflecting the mechanical performance of sawing. To reduce the peak sawing force and enhance the sawing surface quality of sugarcane seedlings, this study utilized a central composite experimental design method. Single-factor and multi-factor experiments were conducted with a specially designed sugarcane stalk sawing experimental rig to investigate the impact of factors such as the stalk diameter feeding speed, and sawing speed on the peak sawing force and sawing surface quality. Upon being developed and validated, multivariate mathematical regression models elucidated the relationships among these factors. The experimental results showed that the order of influence of each factor on the peak sawing force was the stalk diameter, feed speed, and sawing speed, while for the sawing surface quality, the sequence was the sawing speed, stalk diameter, and feed speed. Correspondingly, the determination coefficients for the peak sawing force and sawing surface quality prediction models were 0.9708 and 0.9675. With a maximum error of 7.6% for the peak sawing force and an average relative error of 7.1%, and a maximum error of 3.5% for the sawing surface quality and an average relative error of 2.83%, the calculated results from the regression models were in good agreement with the experimental findings. This indicates that the models are capable of quickly and accurately predicting the peak sawing force and sawing surface quality of sugarcane stalks under different conditions. The research findings provide valuable insights for the development and optimization of sugarcane stalk presawing equipment and related experimental studies. [ABSTRACT FROM AUTHOR]

We examine the immediate and bounce-back effects from six modern health crises that preceded Covid-19. Time-series models for a large cross-section of economies indicate that real GDP growth falls by around 2 percentage points in affected economies relative to unaffected economies in the year of the outbreak. Bounce-back in GDP growth is rapid and strong, especially when compared to non-health crises. Unemployment for less educated workers is higher and exhibits more persistence, and there is significantly greater persistence in female unemployment than male. Moreover, the negative initial effects of pandemics and bounce-back are economically contagious through international trade. The negative effects on GDP and unemployment are felt less in economies with larger first-year responses in government spending, especially on health care. Our estimates imply that the impact effect of the Covid-19 shock on world GDP growth is approximately four standard deviations worse than the average past pandemic. [ABSTRACT FROM AUTHOR]

As a core component of an aero-engine, the aerodynamic performance of the nacelle is essential for the overall performance of an aircraft. However, the direct design of a three-dimensional (3D) nacelle is limited by the complex design space consisting of different cross-section profiles and irregular circumferential curves. The deep manifold learning-assisted geometric multiple dimensionality reduction method combines autoencoders (AE) with strong capabilities for non-linear data dimensionality reduction and class function/shape function transformation (CST). A novel geometric dimensionality reduction method is developed to address the typical constraints of nacelle parameterization. Low-dimensional latent variables are extracted from the high-dimensional design space to achieve a parametric representation of 3D nacelle manifolds. Compared with traditional parametric methods, the proposed geometric dimensionality reduction method improves the accuracy and efficiency of geometric reconstruction and aerodynamic evaluation. A multi-objective optimization framework is proposed based on deep manifold learning to increase the efficiency of 3D nacelle design. The Pareto front curves under drag divergence constraints reveal the correlation between the geometry distribution and the surface isentropic Mach number distribution of 3D nacelles. This paper demonstrates the feasibility of the proposed geometric dimensionality reduction method for direct multi-objective optimization of 3D nacelles. [ABSTRACT FROM AUTHOR]

This article proposes a position detection method for a multi-to-one wireless power transmission (WPT) system for the first time and applies it to the position detection of a spherical motor. The traditional contact detection system has high friction resistance and poor rotor positioning accuracy. Although some noncontact measurement systems are not directly connected to the rotor, the structure or calculation of the measurement system is more complicated. To solve the abovementioned problems, this article proposes two structural topologies, which are evenly arranged on the upper part of the rotor and the receiving coil is placed on the rotor shaft. When the motor rotor rotates along with the three motion states of yaw, spin, and tilt, the receiving and multitransmitting coils will have an angular offset. The rotor position is obtained by a method of accurately estimating the mutual inductance. This method avoids complicated finite element calculations and saves a lot of time. Finally, the experiment verifies the above analysis and compares the data with the microelectromechanical system three-degree-of-freedom attitude detection method. This article provides insights into the position detection of spherical motors. This method simplifies the previous measurement system and obtains higher positioning accuracy. [ABSTRACT FROM AUTHOR]

This study examined Chinese university students' conceptualization of the meaning of work. One hundred and ninety students (93 male, 97 female) from Beijing, China, participated in the study. Prototype research methodology (J. Li, 2001) was used to explore the meaning of work and the associations among the identified meanings. Cluster analysis was used to organize the identified meanings into a structure consisting of lateral and hierarchical levels. The themes that emerged fell into 2 large categories named "ideal" and "reality." A series of superordinate-level and basic-level prototypes were found under each of these 2 categories. These prototypes reflected influences from both Chinese traditional and Western value orientations, as well as perceptions that are to be understood in the contemporary social and economic contexts of China. Implications for career development theory, research, and practice are discussed. (Contains 1 figure and 2 tables.)

This article proposes a rotor attitude estimation (RAE) method for spherical motors using the multiobject Kalman kernel correlation filter (MKKCF) algorithm in monocular vision. A permanent magnet spherical motor (PMSpM) is adopted as the research object, and a monocular area scan camera is equipped in the RAE system with a visual feature component mounted on top of the rotor output shaft. In the proposed MKKCF algorithm, the Kalman filter is used to enhance the robustness and accuracy of KCF tracker for each object. To simplify the proposed algorithm verification, a one-object tracking comparison is conducted among the KCF algorithm, the fast discriminative scale space tracking (FDSST) algorithm, and the Kalman KCF algorithm, and the results show that Kalman KCF tracker is more applicable for RAE. In addition, an RAE test bench is developed, and the MKKCF-based RAE method and the micro-electro-mechanical system (MEMS) (MPU9250) method are compared when estimating the rotor attitude. To set a benchmark, the contact rotor position measurement with encoders is used. The comparison results indicate that the MKKCF-based RAE method works with higher accuracy than the MEMS method. Finally, a closed-loop PMSpM control experiment is conducted by using the proposed MKKCF-based RAE method, and the practicability of the proposed method is proved. [ABSTRACT FROM AUTHOR]

A permanent magnet spherical motor (PMSpM) is a representative multiple degree-of-freedom electric apparatus. This paper proposes new analytical models for the PMSpM with stepped cylindrical permanent magnets (PMs). The research is not only to obtain the magnetic field and torque models of the PMSpM but also to yield a potential analytic tool for the spatial magnetic field and torque decomposition. The model decomposition aims to acquire a potential tool for the future research on PMSpM topology optimization and working mechanism. To achieve the two research targets above, the toroidal expansion method is used for magnetic field modeling, and the finite element method verification and experimental verification are conducted. Then, forces and torques are deduced from the Lorentz force law. In addition, a prototype PMSpM has been produced and the comparison studies of the air-gap flux density and torque among decomposed components are conducted using finite element analysis results and experimental results. It is concluded that the proposed analytical PMSpM models and the model decomposition method are proved. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive backstepping sliding mode control method based on a nonlinear disturbance observer (NDO) to solve the problem that the tracking performance of the motion system of a permanent magnet spherical motor (PMSpM) is degraded due to the influence of external nonlinear disturbance. First, the dynamic model of the PMSpM under the compound interference is established. Second, an NDO and an adaptive backstepping sliding mode controller are designed to compensate for the external disturbances and modeling uncertainties, and the stability of the closed-loop system using the proposed method is confirmed through the Lyapunov theorem. Then, compared with the results of proportion differentiation control and conventional sliding mode control, the simulation results show that the proposed method can significantly reduce input signal chattering and improve the trajectory tracking performance of the PMSpM. Finally, experimental results are provided to validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes a monolayer Halbach array based permanent magnet spherical motor (PMSpM) using cubic permanent magnets (PM). The research aims to provide a fast computing model to calculate the magnetic field for this PMSpM, which helps for future PMSpM optimization and control study. Three thickness equivalence principles are provided and compared for cubic PMs. The magnetic scalar potential is introduced, and the spherical harmonics expansion is implemented for rotor magnetic field analysis. Engineering revision is used to reduce the Legendre function deviation in polar angle direction. Torques and forces are deduced using the Lorentz force law, and relatively simple models of this PMSpM for both magnetic fields and torques are acquired. In addition, a prototype motor has been developed, and the analytic results of air-gap flux density and torque are compared with their finite element simulation and experimental results, which are proved consistent. It is concluded that the fundamental component of the spherical harmonics can be used to present the magnetic field model, which uses fewer integrals than the Biot-Savart law based solution, and the modeling results of the magnetic field flux density, forces and torques are in line with the expectations. The analytic models are proved correct. [ABSTRACT FROM AUTHOR]

In this paper, a sensorless rotor posture detection method based on the mutual inductance voltage of the stator coil is proposed to simplify the position detection element of a reluctance spherical motor. Firstly, the numerical relationship between the stator/rotor pole misalignment angle and the mutual inductance voltage of the stator coil is analyzed, which is used as the basis for judging the spatial position of the rotor. Secondly, an experimental platform is designed to verify the consistency between the calculated value and the experimental value of the mutual inductance voltage and to determine the appropriate excitation signal. Thirdly, based on the real-time voltages generated by the stator coil mutual inductance, an intelligent algorithm is used to invert the 3-DoF (degree-of-freedom) position angle of the spherical rotor combined with the motor structure constraints. The experimental results show that the detection method has a good on-line detection effect, and the population standard deviation is within 1.8° Therefore, the developed technique can be used for replacing the position detection method with sensors. [ABSTRACT FROM AUTHOR]

Foreign Direct Investment (FDI) and government spending are two important drivers of economic growth. We use Chinese city level data and document an inverse U shape relation between FDI and GDP growth. FDI's diminishing growth effect becomes more salient for cities with greater budget deficit or relying heavily on local corporate tax. When foreign firms account for sizable share of local capital formation in the economy, FDI significantly crowds out public spending. We attribute the inverse U shape of FDI and growth to both tax distortion and crowd-out effect. [ABSTRACT FROM AUTHOR]

We examine the immediate effects and bounce-back from six modern health crises: 1968 Flu, SARS (2003), H1N1 (2009), MERS (2012), Ebola (2014), and Zika (2016). Time-series models for a large cross-section of countries indicate that real GDP growth falls by around three percentage points in affected countries relative to unaffected countries in the year of the outbreak. Bounce-back in GDP growth is rapid, but output is still below pre-shock level five years later. Unemployment for less educated workers is higher and exhibits more persistence, and there is significantly greater persistence in female unemployment than male. The negative effects on GDP and unemployment are felt less in countries with larger first-year responses in government spending, especially on health care. Affected countries' consumption declines, investment drops sharply, and international trade plummets. Bounce-back in these expenditure categories is also rapid but not by enough to restore pre-shock trends. Furthermore, indirect effects on own-country GDP from affected trading partners are significant for both the initial GDP decline and the positive bounce back. We discuss why our estimates are a lower bound for the global economic effects of COVID-19 and compare contours of the current pandemic to the historical episodes. [ABSTRACT FROM AUTHOR]

In the last 20 years, humane education (HE) has undergone a paradigm shift from a simple animal welfare education model to a teacher-led positive education approach that cultivates kindness, love, and empathy in children and youth. While teachers' humane attitudes are considered a prerequisite for HE program success in school settings, their attitudes toward animals have received little attention to date. This study investigated pre-service teachers' humane attitudes toward animals and assessed whether and to what extent these attitudes are correlated with empathetic tendencies as well as variables such as gender and current and previous pet ownership. A total of 226 pre-service teachers in Hong Kong completed the Animal Attitude Scale (AAS) and the Davis Interpersonal Reactivity Index (IRI). The results showed that pre-service teachers showed moderate concern for the humane treatment of animals, and a difference in humane attitude was identified based on sex: female pre-service teachers tended to express more humane attitudes than their male counterparts. Moreover, pre-service teachers with greater tendencies toward warmth and compassion demonstrated a more welfare-oriented attitude toward animals. The results of the current study support using HE as a positive education approach and imply that the provision of training for pre-service teachers and teachers should be given higher priority by humane educators. Humane educators are recommended to recruit pre-service teachers as HE program instructors in their research projects. [ABSTRACT FROM AUTHOR]

Background/Aims: Integrin activation and lymphocyte migration to the vascular intima is a key event in early atherosclerosis. α4β7 integrin (LPAM-1) and its ligand, mucosal addressin cell adhesion molecule (MAdCAM-1) are known to play an important role in homing of activated lymphocytes to gut-associated lymphoid tissues. However, it is unclear whether α4β7 integrin is involved in the pathogenesis of atherosclerosis. Methods: The expressions of α4β7 integrin and its ligands in atherosclerosis plaques from 12 week high fat diet (HFD) fed ApoE-/- and C57BL/6 mice were examined using immunofluorescent and immunohistochemical assays, respectively. We also generated ApoE/β7 double deficient mice and compared atherosclerotic lesion development in β7+/+ApoE-/- and β7-/-ApoE-/- mice that were fed with HFD for 12 weeks. Results: We found an upregulation of α4β7 integrin and its ligands VCAM-1 and MAdCAM-1 at atherosclerosis plaques in Apolipoprotein E deficient (ApoE-/-) mice fed with HFD for 12 weeks. Over the 12 week HFD period, peripheral blood lymphocyte (PBL) expression of α4β7 integrin increased in parallel with aortic lesion size. A removal of α4β7 integrin by genetic deletion of the β7 chain in the ApoE-/- mouse resulted in a markedly decreased 12 week-HFD atherosclerotic plaque area. β7-/- ApoE-/- macrophages showed reduced acetylated and native LDL uptake and phagocytic activity, revealing possible roles for α4β7 at two distinct stages of macrophage dysfunction during atherogenesis. Finally, a reduced activity of integrin downstream signalling components focal adhesion kinase (FAK) and MAPK/ERK1/2 in macrophage indicates their possible engagement during α4β7 integrin signalling in atherosclerosis. Conclusions: Together our results reveal a critical role of α4β7 in diet-induced atherosclerosis in mouse. © 2014 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

To mirror an important aspect of ultra-high voltage network development, the remarkable amount of energy cost and carbon emissions of a typical ultra-high voltage transformer substation in China is revealed, in light of the hybrid method as the integration of input-output analysis and process analysis. By inclusively inventorying all the input items as products of the economy, the study differs from previous studies that simply treat the input items as some primary materials. The results show that the total energy cost and carbon emissions of 1000 kV transformer substation are 6.82E+09 MJ and 7.12E+05 t CO 2 eq., respectively. Equipment purchasing contributes more than 80% to the overall energy cost and carbon emissions, followed by construction engineering, additional service and installation engineering. From the sectoral perspective, Manufacture of equipment for power transmission and distribution and control sector (Sector 78) dominates the energy cost and carbon emissions induced by 1000 kV transformer substation, followed by Construction industry (Sector 95). The comparison and analysis between current research and previous studies in different countries and different voltages is clearly discussed. This study not only enhances our understanding about the impact of ultra-high voltage network on energy and environment, but also provides insights for energy conservation and low carbon development. [ABSTRACT FROM AUTHOR]

The C-C motif chemokine receptor 8 (CCR8) is a class A G-protein-coupled receptor that has emerged as a promising therapeutic target in cancer and autoimmune diseases. In the present study, we solved the cryo-electron microscopy (cryo-EM) structure of the human CCR8-G i complex in the absence of a ligand at 2.58 Å. Structural analysis and comparison revealed that our apo CCR8 structure undergoes some conformational changes and is similar to that in the CCL1-CCR8 complex structure, indicating an active state. In addition, the key residues of CCR8 involved in the recognition of LMD-009, a potent nonpeptide agonist, were investigated by mutating CCR8 and testing the calcium flux induced by LMD-009-CCR8 interaction. Three mutants of CCR8, Y113 3.32 A, Y172 4.64 A, and E286 7.39 A, showed a dramatically decreased ability in mediating calcium mobilization, indicating their key interaction with LMD-009 and key roles in activation. These structural and biochemical analyses enrich molecular insights into the agonism and activation of CCR8 and will facilitate CCR8-targeted therapy.

Peripheral artery disease is growing in global prevalence. Its most severe form, critical limb ischemia (CLI), is associated with high rates of limb loss, morbidity, and mortality. Neovascularization is the cornerstone of limb preservation in CLI. In the field of regenerative medicine, basic research and preclinical studies have been conducted using mesenchymal stem cells (MSCs) from adult tissues, including bone marrow and adipose tissue, to overcome clinical shortcomings. Adipose-derived stem cells (ASCs) display stable growth and proliferation kinetics and can differentiate into osteogenic, chondrogenic, adipogenic, myogenic or neurogenic lineages. ASCs are readily available from autologous adipose tissue, and have significant potential for tissue repair under conditions of myocardial infarction, heart failure, hind limb ischemia, and inflammation. This review highlights some of the key reports underlining the potential of ASCs, particularly in diseases involving neovascularization.