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Production plans based on Material Requirement Planning (MRP) frequently fall short in reflecting actual customer demand and coping with demand fluctuations, mainly due to the rising complexity of the production environment and the challenge of making precise predictions. At the same time, MRP is deficient in effective adjustment strategies and has inadequate operability in plan optimization. To address material management challenges in a volatile supply-demand environment, this paper creates a make-to-stock (MTS) material production planning model that is based on customer demand and the demand-driven production planning and control framework. The objective of the model is to optimize material planning output under resource constraints (capacity and storage space constraints) to meet the fluctuating demand of customers. To solve constrained optimization problems, the demand-driven material requirements planning (DDMRP) management concept is integrated with the grey wolf optimization (GWO) algorithm and proposed the DDMRP-GWO algorithm. The proposed DDMRP-GWO algorithm is used to optimize the inventory levels, shortage rates, and production line capacity utilization simultaneously. To validate the effectiveness of the proposed approach, two sets of customer demand data with different levels of volatility are used in experiments. The results demonstrate that the DDMRP-GWO algorithm can optimize the production capacity allocation of different types of parts under the resource constraints, enhance the material supply level, reduce the shortage rate, and maintain a stable production process.

In multi-stage machining-assembly production, collaborative scheduling for multiple production lines can effectively improve the execution efficiency of production planning and increase the effective output of the production system. In this paper, a production scheduling mathematical model was constructed for the collaborative scheduling problem of machining-assembly multi-production lines with kitting constraints, with the optimization objectives of minimizing assembly completion time and tardiness time. For the scheduling model, the product assembly process is constrained by the machining sequence of the jobs on the machining lines. Only by collaborating on the production scheduling schemes of the machine line and the assembly line as a whole can the output efficiency of the product on the assembly line be improved. An improved hybrid multi-objective optimization algorithm named SMOEA/D is designed to solve this scheduling model. The algorithm uses adaptive parents’ selection and mutation rate strategies and integrates the Tabu search strategy for the search process in the solution space when the solution of the sub-problem has not been improved after specified search generations, to improve the local search ability and search accuracy of MOEA/D algorithm. To verify the performance of the SMOEA/D algorithm in solving machining-assembly collaborative scheduling problems in production systems with different resource configurations and scales, two sets of numerical experiments were designed, corresponding to situations where the number of operations on each production line is equal or unequal. The running results of the proposed algorithm were compared with three other well-known multi-objective algorithms. The comparison results indicate that the SMOEA/D algorithm is effective and superior for solving such problems.

Restenosis formation is initiated from intimal hyperplasia when arterial stretch and injury exist. In this study, we examined the role of CDKN1A-interacting zinc finger protein 1 (CIZ1) in neointimal hyperplasia in injured arteries. CIZ1 protein was up-regulated, and p21Cip1/Waf1 (p21) was down-regulated in the neointimal hyperplasia from a mouse femoral artery wire-injury model. In vitro, proliferation and migration were reduced in vascular smooth muscle cells transformed with Ciz1-shRNA lentiviral particles. In addition, p21 expression is increased, and MMP9 expression is decreased in vascular smooth muscle cells with CIZ1 knockdown. These data imply that CIZ1 might be a novel repressor of neointimal lesion formation caused by interventional therapy.

Neuropeptide Y (NPY) signaling plays an essential role in gating the pruritic afferent information in the spinal cord. Recent studies revealed that the aging process down-regulated the expression of NPY in the central nervous system. We propose that the lack of spinal NPY may be involved in certain types of pruritus in the elderly population. This study was designed to investigate the role of NPY in aging-induced itch using the senile mouse model. The expression of NPY in the spinal dorsal horn was compared between young (2 months old) and aged (24 months old) mice. Western blotting and immunohistochemistry showed that the expression of NPY was significantly reduced in the spinal dorsal horn in aged mice. In addition, a neuronal maker of apoptosis, TUNEL, was detected in the NPY positive neurons only in the aged spinal cord. Behavioral assay indicated that light mechanical stimulus evoked significantly more scratching in the aged than in the young mice, whereas chemical-evoked itch and pain-related behaviors were not altered. Intrathecal injection of either NPY or LP-NPY, a NPY receptor 1 (NPY1R) agonist, significantly alleviated the mechanically evoked itch in aged mice without altering the responses to chemical pruritogens. Our study suggested that downregulation of spinal NPY in the aged mice might play a role in the higher incidence of the mechanically evoked itch than that in the young mice. Therapies targeting the NPY system might serve as a potential strategy for alleviating the pruritic symptoms among the elderly population.

Intraoperative hypothermia is very common and leads to memory decline. The hippocampus is responsible for memory formation. As a functional core area, the cornu ammonis 1 (CA1) region of the hippocampus contains abundant blood vessels and is susceptible to ischemia. The aim of the study was to explore vascular function and neuronal state in the CA1 region of rats undergoing intraoperative hypothermia. The neuronal morphological change and activity-regulated cytoskeleton-associated protein (Arc) expression were evaluated by haematoxylin-eosin staining and immunofluorescence respectively. Histology and immunohistochemistry were used to assess vascular function. Results showed that intraoperative hypothermia inhibited the expression of vascular endothelial growth factor and endothelial nitric oxide synthase, and caused reactive oxygen species accumulation. Additionally, the phenotype of vascular smooth muscle cells was transformed from contractile to synthetic, showing a decrease in smooth muscle myosin heavy chain and an increase in osteopontin. Ultimately, vascular dysfunction caused neuronal pyknosis in the CA1 region and reduced memory-related Arc expression. In conclusion, neuronal disorder in the CA1 region was caused by intraoperative hypothermia-related vascular dysfunction. This study could provide a novel understanding of the effect of intraoperative hypothermia in the hippocampus, which might identify a new research target and treatment strategy.

Solar-powered unmanned aerial vehicles usually fly at high altitudes, and they are mainly powered by the photocells covering the body of unmanned aerial vehicles. Considering that the solar vector cannot be affected by the disturbing magnetic field and harmful acceleration, a unit solar vector solving method based on photovoltaic array is proposed in this paper. The photocells with different installation angles are selected to form the photovoltaic array. The solar vector is solved by the least-squares method on the basis of normalization by using the output currents of the photovoltaic array. For eliminating the influence of faults and reflected light on the solving of the solar vector, an adaptive least-squares unit solar vector solving method is proposed. In addition, a solar vector measuring device is designed in order to verify the effectiveness of the proposed methods. By employing the structural advantages of the device, the current generated by the reflected light of the sky can be solved according to the currents generated by all photocells of this device. Thus, the solved current generated by the reflected light of the sky is more accurate. Moreover, strapdown inertial navigation system/solar vector/global positioning system integrated navigation Kalman filtering algorithm is proposed, in which the adaptive least-squares unit solar vector solving method is applied to the measurement update of the filter. The effectiveness of the methods proposed in this paper is illustrated by some numerical and physical simulations.

The attitude measurement systems composed of magnetic, angular rate and gravity sensors in the navigation system of an unmanned aerial vehicle are vulnerable to disturbed magnetic field observations. In this paper, an anti-interference integrated navigation federal Kalman filter is designed with fusing the information of microelectromechanical-system-based strapdown inertial navigation system, gravity field, geomagnetic field and solar vector (direction of sun). The filter works in the mode of fusion reset or no reset according to environmental conditions or manual setting. In addition, the characteristic is discovered that disturbed magnetic field observations can interfere with the state estimation covariance matrixes of quaternions, which in turn affect the fusion update of estimated quaternions in no reset mode of the federal filter. In order to eliminate the effect of magnetic field observations on the attitude information of pitch and roll angles, a method of correction update for a yaw angle component in quaternions using the magnetometer is designed, and an Euler angle information fusion method is developed by constructing a pseudo-covariance matrix of Euler angels in fusion update of the filter. Thus, when there exist disturbed magnetic field observations and the filter is in no reset mode, the estimated pitch and roll angles of the main filter after fusion update are not affected, and the yaw angle estimation errors of the main filter decrease relative to the estimation errors of the sub-filter which is corrected by a magnetometer. The effectiveness of the algorithm is illustrated by a numerical simulation and a semi-physical simulation.

Increasing productivity and efficiency in factories with make-to-order (MTO) production systems have attracted growing interest of academia and industry. In MTO companies, efficient order release and schedule are essential for succeeding in today’s marketplace. However, dynamic demand of customers and constrained resources make it difficult to achieve, as well as limiting the profits. Thus, to overcome the problem of order releasing and multi-item scheduling considering the capacity constrained resources investigated, a heuristic approach is proposed based on the drum-buffer-rope (DBR) method. The proposed heuristic is tested on different types of problems based on due date tightness and demand of products. The performance of the proposed heuristic is compared with other famous heuristic methods in literature. End results indicate that the proposed heuristic based on the DBR method outperforms against the other competitors, and it gives more significant results when optimal buffer size is adopted.

Intraoperative hypothermia is a common complication during operations and is associated with several adverse events. Postoperative cognitive dysfunction (POCD) and its adverse consequences have drawn increasing attention in recent years. There are currently no relevant studies investigating the correlation between intraoperative hypothermia and POCD. The aim of this study was to assess the effects of intraoperative hypothermia on postoperative cognitive function in rats undergoing exploratory laparotomies and to investigate the possible related mechanisms. We used the Y-maze and Morris Water Maze (MWM) tests to assess the rats’ postoperative spatial working memory, spatial learning, and memory. The morphological changes in hippocampal neurons were examined by haematoxylin-eosin (HE) staining and hippocampal synaptic plasticity-related protein expression. Activity-regulated cytoskeletal-associated protein (Arc), cyclic adenosine monophosphate-response element-binding protein (CREB), S133-phosphorylated CREB (p-CREB [S133]), α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor 1 (AMPAR1), and S831-phosphorylated AMPAR1 (p-AMPAR1 [S831]) were evaluated by Western blotting. Our results suggest a correlation between intraoperative hypothermia and POCD in rats and that intraoperative hypothermia may lead to POCD regarding impairments in spatial working memory, spatial learning, and memory. POCD induced by intraoperative hypothermia might be due to hippocampal neurons damage and decreased expression of synaptic plasticity-related proteins Arc, p-CREB (S133), and p-AMPAR1 (S831).

This paper investigates the nonidentical parallel production line scheduling problem derived from an axle housing machining workshop of an axle manufacturer. The characteristics of axle housing machining lines are analyzed, and a nonidentical parallel line scheduling model with a jumping process operation (NPPLS-JP), which considers mixed model production, machine eligibility constraints, and fuzzy due dates, is established so as to minimize the makespan and earliness/tardiness penalty cost. While the physical structures of the parallel lines in the NPPLS-JP model are symmetric, the production capacities and process capabilities are asymmetric for different models. Different from the general parallel line scheduling problem, NPPLS-JP allows for a job to transfer to another production line to complete the subsequent operations (i.e., jumping process operations), and the transfer is unidirectional. The significance of the NPPLS-JP model is that it meets the demands of multivariety mixed model production and makes full use of the capacities of parallel production lines. Aiming to solve the NPPLS-JP problem, we propose a hybrid algorithm named the multi-objective grey wolf optimizer based on decomposition (MOGWO/D). This new algorithm combines the GWO with the multi-objective evolutionary algorithm based on decomposition (MOEA/D) to balance the exploration and exploitation abilities of the original MOEA/D. Furthermore, coding and decoding rules are developed according to the features of the NPPLS-JP problem. To evaluate the effectiveness of the proposed MOGWO/D algorithm, a set of instances with different job scales, job types, and production scenarios is designed, and the results are compared with those of three other famous multi-objective optimization algorithms. The experimental results show that the proposed MOGWO/D algorithm exhibits superiority in most instances.

Stressed plants and polymer production can emit many unsaturated volatile organic esters (UVOEs). However, secondary organic aerosol (SOA) formation of UVOEs remain unclear, especially under complex ambient conditions. In this study, we mainly investigated ethyl methacrylate (EM) ozonolysis. Results showed that a substantial increase in secondary H2SO4 particles promoted SOA formation with increasing SO2. An important reason was that the homogeneous nucleation of more H2SO4 at high SO2 level provided greater surface area and volume for SOA condensation. However, increased primary H2SO4 with seed acidity enhanced EM uptake, but reduced SOA formation. This was ascribed to the fact that the ozonolysis of more adsorbed EM was hampered with the formation of surface H2SO4 at higher particle acidity. Moreover, the increase in secondary H2SO4 particle via homogeneous nucleation favored to the oligomerization of oxidation products, whereas the increasing of primary H2SO4 with acidity in the presence of seed tended to promote the functionalization conversion products. This study indicated that the role of increased H2SO4 to EM-derived SOA maybe not the same under different ambient conditions, which helps to advance our understanding of the complicated roles of H2SO4 in the formation of EM-derived SOA. [ABSTRACT FROM AUTHOR]

The J2 effect is the dominating perturbation for satellite formation flying missions. In this paper, a linearized satellite relative motion model considering J2 perturbation and eccentricity was derived first. Then, a real-time fuel-optimal continuous low-thrust control approach was proposed for satellite formation control in eccentric orbits on the basis of the developed linear J2 dynamic model. This optimal control problem was converted into a mathematical programming problem by the application of the Legendre pseudospectral method, which makes real-time optimal control feasible. Finally, comprehensive simulation results validated the proposed linearized J2 model and formation control approach. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the design of a fuel-optimal maneuver strategy to reconfigure satellite formation using a low-thrust propulsion system. We cast it as an optimization problem with a desired final satellite formation configuration subject to collision avoidance constraints on the paths of the chief and all deputy satellites. The satellite terminal orbit states corresponding to this desired formation configuration are ensured by imposing an energy-matching condition and final geometry configuration constraints in the problem formulation. In addition, we adopt our recently developed relative satellite kinematics model to accurately describe relative satellite orbit geometry in the presence of J2 effects. The resulting nonlinear optimal control problem is converted into a nonlinear programming problem by the application of the Legendre pseudospectral method and is then solved by using a sparse nonlinear optimization software named TOMLAB/SNOPT. Simulation results demonstrate the efficiency of our proposed method in designing fuel-optimal maneuvers for a wide class of satellite formation problems. [ABSTRACT FROM AUTHOR]

The article focuses on a study which establishes the J2 dynamics of the reference satellite S0 in the local rotating frame. It notes the study's use of two Cartesian coordinate frames. According to the authors, they use the Lagrangian formulation to develop the relative dynamics of the member satellite Sj. The equation for the kinetic energy per unit mass of the satellite Sj is also presented.

In the paper, the stable full-state tracking problem is investigated for nonholonomic wheeled mobile robots under output-tracking control laws. Dynamics of such wheeled mobile robots are nonholonomic and pose challenging problems for control design and stability analysis. The dynamics formulated in terms of full-state tracking errors offer some properties that allow better understanding of the internal and zero dynamics of the tracking-error system and more insights to the trajectory tracking stability. Output functions are chosen as virtual reference points for various types of wheeled mobile robots in aid of output controller designs. Sufficient conditions are derived to ensure the stable full-state trajectory tracking under output-tracking control laws. A type (1,1) mobile robot of car-like configuration is studied in detail and further numerical analysis provides more results which are beyond the reach of analytical means. An example and simulation results are presented to confirm the theory and observations. [ABSTRACT FROM PUBLISHER]