Search

Flow field design is critical to improving the overall performance of high-temperature proton exchange membrane fuel cells. Adding baffles in the flow channel has been proven to be effective in enhancing mass transfer. In this study, fuel cells with different baffle numbers, heights, and arrangements are numerically simulated to investigate the effects of reactant velocity, concentration distribution, and pressure drop on mass transfer and output performance. The results show that baffles are beneficial in improving cell performance, especially under high current density. With the increase in baffle number and height, the concentration of the reactant at the outlet decreases and the output power increases with the increase in pressure drop. The net power density growth rate is defined to characterize the cell performance. A lower pressure drop reduces the pumping power loss generated during reactant transfer, resulting in a staggered baffle structure with the highest net power density of 4329.65 W/m2. Compared with the traditional and parallel baffle channels, this value is improved by about 11.74% and 4.83%, respectively. Therefore, the optimized baffle channel can enhance the mass transfer, reduce the pumping power, and further improve the cell performance, providing an effective guide for the optimal design and development direction of the orientated flow channel.

Scientific communication holds a pivotal role within research institutions. This study establishes three distinct categories of indicators, tailored to the unique attributes of these institutions, aiming to assess their performance in scientific communication. Employing a rigorous two-stage data envelopment analysis (DEA) approach, we meticulously calculate output efficiency, feedback efficiency, and overall efficiency. Subsequently, we cluster the efficiency outcomes and delve into the factors that influence them. Drawing from the clustering insights and identified influencing factors, we formulate targeted scientific communication strategies tailored to the needs of these research institutions.

In this paper, we consider a multiperiod, two-location inventory system with unknown demand distributions and perishable products. Products can be transshipped from the location with excess inventory to the other with excess demand to better fulfill customer demand. The demand distributions are assumed to follow a family of parametric distributions and can only be learned on the fly. To address the challenge, we propose a data-driven inventory management algorithm called DD2LI that achieves a good performance in terms of regret. This algorithm, DD2LI, employs maximum likelihood estimation to approximate the unknown parameter and determines the order quantity based on these estimations. In addition, we emphasize a key assumption that tightens regret bound. Finally, we test the effectiveness of our proposed algorithm by conducting numerical experiments for two scenarios.

In this paper, we formulate Subcarrier Assignment and Discrete Power Allocation for multi-UAV millimeter-wave cooperative Orthogonal Frequency Division Multiple Access (OFDMA) networks as a joint optimization problem considering the heterogeneous user data rate quality-of-service (QoS) requirements. The formulated joint optimization problem, named Discrete Power and Subcarrier Allocation (DPSA), is a nonconvex and mixed-integer nonlinear programming (MINP) problem, making it NP-hard to solve. We then transform the DPSA into the Subcarrier and Power Resource Efficient Cooperative Potential Game (SRECPG) based on game theory which facilitates distributed execution. We analyze the conditions under which a Nash Equilibrium (NE) exists in the SRECPG and provide rigorous proof of its existence. Furthermore, to enhance computational efficiency, we propose a BR-SSO algorithm based on better response dynamics. BR-SSO dramatically reduces the computational burden compared to the best response dynamics based on local exhaustive search (BRLES) while still ensuring convergence to a NE. Through extensive simulations, we demonstrated the effectiveness of the proposed SRECPG and BR-SSO algorithms. The results show significant improvements in throughput, fairness, and QoS guarantees compared to the baseline schemes. Our approach offers valuable insights into the design of efficient resource allocation schemes for multi-UAV millimeter-wave networks with varying QoS demands.

BackgroundWomen with atypical hyperplasia (AH) is associated with a higher risk of future breast cancer. However, whether AH found at margins in patients with breast-conserving surgery (BCS) after neoadjuvant chemotherapy (NAC) needs re-excision is not well-defined. The aim of the present study was to evaluate the impact of AH at the surgical margins on the local recurrence and survival outcomes in breast cancer patients treated with NAC and BCS.MethodsA retrospective analysis comparing patients who treated with NAC and BCS with AH at the margins to those without AH was performed.Results598 patients were included in this study. The 5-year rates of ipsilateral breast tumor recurrence (IBTR) were 4.6% and 6.2% in patients with and without AH, respectively. No significant differences were observed among the two groups in terms of IBTR, DMFS, or OS. HER2 overexpressing breast cancer patients with severe AH at margins have a significantly higher risk of IBTR compared to those without severe AH.ConclusionOur study suggests that the presence of AH at the surgical margins of BCS in patients who received NAC does not appear to increase the risk of ipsilateral breast cancer. Therefore, there is no need for surgeons to routinely perform additional re-excision of AH found at the margins of BCS in these patients. However, selective re-excision should be considered in certain cases, particularly in patients with HER2 overexpression.

Ampacity is an important parameter in power cable operation. In order to provide a reference for the operation of ultra-high voltage cables laid in tunnel,a three-dimensional geometric model is established to simulate the thermal-fluid coupling by COMSOL Multiphysics according to the actual cable tunnel structure and internal cable arrangement. The distribution of temperature and wind velocity under different operating modes and environmental conditions is analyzed based on finite element method. The ampacity of tunnel ultra-high voltage cables is calculated. It is observed that the highest temperature appears at the conductor. The temperature decreases gradually along the radial direction of cable. Temperature and wind velocity at the exit are increased compared to the entrance. With the increase of current,the influence of cable heating on ambient temperature also increases. The steady-state load capacity of cable for double-loop or four-loop laying is higher than that for eight-loop laying. Cable surface temperature decreases with increasing ventilation rate.

Abstract Background Axillary vein/subclavian vein (AxV/SCV) and Internal jugular vein (IJV) are commonly used for implantable venous access port (IVAP) implantation in breast cancer patients for chemotherapy. Previous research focused on comparison of complications while patient comfort was ignored. This study aims to compare patient comfort, surgery duration and complications of IVAP implantation between IJV and AxV/SCV approaches. Methods Two hundred forty-eight breast cancer patients were enrolled in this randomized controlled study from August 2020 to June 2021. Patients scheduled to undergo IVAP implantation were randomly and equally assigned to receive central venous catheters with either AxV /SCV or IJV approaches. All patients received comfort assessment using a comfort scale table at day 1, day 2 and day 7 after implantation. Patient comfort, procedure time of operation as well as early complications were compared. Results Patient comfort was significantly better in the AxV/SCV group than that of IJV group in day 1 (P

Abstract The feature map is a characteristic of high computational efficiency, but it is seldom used in path planning due to its lack of expression of environmental details. To solve this problem, a global path planning algorithm based on the feature map is proposed based on the directionality of line segment features. First, the robot searches the path along the direction of the target position but turns to search in the direction parallel to the obstacle, which it approaches until the line between the robot and the target position does not intersect with obstacles. Then it turns to the target position, keep searching the path. Meanwhile, the problems of the direction selection of turning point, corner point and obstacle circumvention in the searching process are analysed and corresponding solutions are put forth. Finally, a path optimisation algorithm with variable parameters is proposed, making the optimised path shorter and smoother. Simulation experiments demonstrate that the proposed algorithm is superior to A* algorithm in terms of computation time and path length, especially of the computation efficiency. The cover image is based on the Research Article A global path planning algorithm based on the feature map by Peng Liu et al., https://doi.org/10.1049/csy2.12040.

With the rise of satellite-as-a-service subscriptions as technology improves, our paper examines how satellite operators (SOs) can choose between traditional channels for selling satellites, satellite-as-a-service (SataaS), and dual-channel strategies. In the space supply chain, commercial satellites display several distinct characteristics that differentiate them from other physical commodities in traditional supply chains, most notably their exposure to significant launch risks. In addition, SataaS suffers from the risk of secure data transmission. However, the emergence of novel technologies such as blockchain technology (BCT) could help to mitigate such risks. Therefore, our study analyzes the optimal strategy among the sell, SataaS, and dual-channel approaches for SOs by considering the above distinctive characteristics in the case without blockchain and the case with blockchain. Our paper reveals the existence of a dual-channel strategy that generates the highest profit for the SO and yields the highest consumer utility when launch success is high and when SataaS fixed costs are low. When the launch success rate is very high, the dual-channel strategy transforms into a pure sell strategy. After the adoption of BCT, when the cost of BCT is low, the SO’s profit is enhanced in all three sales channels compared to the case without blockchain. Notably, in SataaS as well as in the dual-channel approach, the adoption of BCT always improves consumer utility compared to the case without blockchain. However, in the sell channel, the consumer benefits depend on the relatively low cost of blockchain customization.

The Ca-based organic framework (Ca-SINAP-1) loaded with silver was successfully prepared, which has a certain γ-ray irradiation resistance of 50 kGy. X-ray diffraction, scanning electron microscopy, Brunauer-Emmett-Teller specific surface area analysis, and pore volume analysis were used to characterize the sample and its Xe adsorption capacity. The results showed that loading of silver on the sample surface did not change the original structure of Ca-SINAP-1. However, the Xe uptake reached a maximum of 3.29 mmol/g and the Xe/Kr separation coefficient was 10.71 when silver loading was 0.93%. With increasing AgNO3 concentration in ethanol, the Xe adsorption quantity decreased because excess silver loading blocked the channels, and thus prevented Xe adsorption. The good irradiation resistance and high Xe/Kr selectivity make Ca-SINAP-1 a potential material for treating radioactive off-gas emitted from molten salt reactors.

In this paper, a novel compact, dual-polarized, dual-broadband shared-aperture antenna array unit consisting of one lower-band (LB) element and four upper-band (UB) elements underneath is proposed for 5G mobile communications. L-shaped parasitic branches are introduced in the LB to broaden the bandwidth while reducing the mutual coupling between the LB element and UB elements. Compared with the traditional lower-band dipole, the proposed LB element has far less influence on the electric field of the UB array, thus preserving their radiation patterns. To verify its performance, the antenna array unit is fabricated and experimentally demonstrated to achieve the bandwidth of 32.7% (0.69–0.96 GHz) in the LB and 45.5% (1.7–2.7 GHz) in the UB with a voltage standing wave ratio (VSWR) of lower than 1.5. High port isolation and stable radiation patterns are attained in both the LB and UB as required for dual-band base station antennas.

Transcranial magnetic stimulation (TMS) has been proved to be effective in the treatment of many kinds of mental diseases. However, the clicking noise produced by the pulse current with large amplitude and short duration in the TMS coil may damage the hearing of patients. The heat produced by the high-frequency pulse current in the coil also reduces the efficiency of TMS equipment. A multi-objective waveform optimization method to improve heat and noise problems at the same time is presented. By analyzing the current waveforms of TMS, the relationship between the current and the vibration energy/Joule heating is established. Taking the Joule heating and the vibration energy as the optimization objectives, exceeding the same amount of neuronal membrane potential as the limiting condition, the Pareto fronts of different current models are obtained by applying the multi-objective particle swarm optimization algorithm (MOPSO). Therefore, the corresponding current waveforms are inversely deduced. A ringing suppression cTMS (RS-cTMS) proof-of-principle experimental platform is constructed. The feasibility of the proposed method is validated through experiments. The results show that the optimized current waveforms can greatly reduce the vibration and heating of the coil compared with the conventional full-sine, recified sine and half-sine waveforms, thus reducing the pulse noise and prolonging the using time of the equipment. The optimized diversified waveforms also provide a reference for the diversity of TMS.

WSN is one of the most efficient technologies in intelligent communication and because of its advantages, this technology has been utilized in various applications. By using WSNs, different types of data can be collected and analyzed in wide environments. The high variety of applications and types of data available in this network can cause several challenges about heterogeneous data routing. This research, presents a Fuzzy Model for Content-Centric Routing (FMCCR) in WSN to solve these challenges. The performance of FMCCR is based on two basic steps: "topology control", and "data transmission through content-centric and fuzzy logic-based routing algorithm". In the first step of FMCCR, the network topology is constructed. In the second step of the proposed method, data transmission paths are determined based on network topology and content type, and data transmission is performed. The performance of FMCCR has been evaluated in a simulation environment and the results have been compared with previous algorithms. The results show that FMCCR reduce energy consumption and improve the traffic load distribution in the network in addition to increasing the network lifetime. According to the results, FMCCR can increase network lifetime at least 10.74% and at the same time, deliver at least 88.1% more packets through the network, compared to previous methods. These results, prove the efficiency of the proposed method for using in real-world scenarios.

The impact of human resource management (HRM) on corporate growth is a crucial research topic, especially for growth-oriented firms. This paper aims to study how different payment policies (such as recruitment and dismissal strategies and payment plans) affect the human resource market system. Based on the HRM characteristics of growth-oriented firms, we develop an agent-based model to simulate the decision-making and interaction behaviors of firms and workers. The system performance is measured by six indicators: the average profit, the profit Gini coefficient, the average output of firms, the average payment, the payment Gini coefficient, and the employment rate of workers. According to the simulation results and statistical analysis, the recruitment plan is the only key factor that significantly impacts all performance indicators other than the employment rate, and companies should pay extra attention to such plans. This study also finds that the changing worker’s payment gap is influenced by industry growth and their abilities, and that the payment cap policy has a positive impact on the development of growth-oriented firms in the startup stage.

Blockchain technology, as a revolutionary technology that has emerged in recent years, holds significant potential for application in supply chain operations. This paper provides a systematic review of blockchain-based supply chain case studies. The existing literature primarily focuses on the food, agriculture, and pharmaceutical sectors, highlighting the advantages of blockchain technology in terms of traceability and transparency. However, there is a limited number of studies addressing the improvement of collaboration efficiency in supply chains, particularly within the realm of information technology enterprises. By conducting semi-structured interviews, we present a case study of Lenovo, a leading enterprise utilizing blockchain technology, to elucidate the advantages of using blockchain technology. Subsequently, it proposes a conceptual model for a blockchain-based information collaboration system and discusses the potential applications of blockchain technology in supply chain collaboration. Our study contributes to the existing work on blockchain applications to enhance supply chain collaboration.

We aimed to examine the effects of aerobic exercise training on renal function in spontaneously hypertensive rats (SHR) and elucidate their possible mechanisms. Adult male SHR and age-matched Wistar-Kyoto rats (WKY) were divided into four groups: WKY sedentary group, SHR sedentary group, low-intensity training group, and medium-intensity training group. Using molecular and biochemical approaches, we investigated the effects of 14-week training on renalase (RNLS) protein levels, renal function, and apoptosis and oxidative stress modulators in kidney tissues. In vitro, angiotensin II (Ang II)-induced human kidney proximal epithelial cells (HK-2) were treated with RNLS, and changes in apoptosis and oxidative stress levels were observed. Our results show that moderate training improved renal function decline in SHR. In addition, aerobic exercise therapy significantly increased levels of RNLS in the renal medulla of SHR. We observed in vitro that RNLS significantly inhibited the increase of Ang II-inducedapoptosis and oxidative stress levels in HK-2. In conclusion, aerobic exercise training effectively improved renal function in SHR by promoting RNLS expression in the renal medulla. These results explain the possible mechanism in which exercise improves renal injury in hypertensive patients and suggest RNLS as a novel therapy for kidney injury patients.

Abstract Background There is controversy regarding the efficacy of different treatment strategies for acute left malignant colonic obstruction. This study investigated the 5-year overall survival (OS) and disease-free survival (DFS) of several treatment strategies for acute left malignant colonic obstruction. Methods We searched for articles published in PubMed, Embase (Ovid), MEDLINE (Ovid), Web of Science, and Cochrane Library between January 1, 2000, and July 1, 2020. We screened out the literature comparing different treatment strategies. Evaluate the primary and secondary outcomes of different treatment strategies. The network meta-analysis summarizes the hazard ratio, odds ratio, mean difference, and its 95% confidence interval. Results The network meta-analysis involved 48 articles, including 8 (randomized controlled trials) RCTs and 40 non-RCTs. Primary outcomes: the 5-year overall survival (OS) and disease-free survival (DFS) of the CS-BTS strategy and the DS-BTS strategy were significantly better than those of the ES strategy, and the 5-year OS of the DS-BTS strategy was significantly better than that of CS-BTS. The long-term survival of TCT-BTS was not significantly different from those of CS-BTS and ES. Secondary outcomes: compared with emergency resection (ER) strategies, colonic stent-bridge to surgery (CS-BTS) and transanal colorectal tube-bridge to surgery (TCT-BTS) strategies can significantly increase the primary anastomosis rate, CS-BTS and decompressing stoma-bridge to surgery (DS-BTS) strategies can significantly reduce mortality, and CS-BTS strategies can significantly reduce the permanent stoma rate. The hospital stay of DS-BTS is significantly longer than that of other strategies. There was no significant difference in the anastomotic leakage levels of several treatment strategies. Conclusion Comprehensive literature research, we find that CS-BTS and DS-BTS strategies can bring better 5-year OS and DFS than ER. DS-BTS strategies have a better 5-year OS than CS-BTS strategies. Without considering the hospital stays, DS-BTS strategy is the best choice.

The water produced from the coalbed methane (CBM) wells contains abundant geochemical information, which is of great significance in evaluating the productivity of these wells. Based on the data of water produced from five CBM wells, geochemical characteristics of the produced water and its influence on the productivity of the wells are analyzed in Laochang Block. The results show that with the increase in the produced water of the five wells, δD and δ18O show a downward trend in general, reflecting that the influence of coal seams and surrounding rock on the produced water is weak, while the water–rock interaction of the Y-3 and Y-5 wells is more stable than that of the Y-1, Y-2, and Y-4 wells. Combining the water production characteristics of the Y-3 and Y-5 wells with better drainage and recovery effects, it is proposed that 0 ≤ σM < 0.3 and 0 ≤ σY < 600 or 0.7 < σM < 0.8 and 1,200 < σY < 1,300, and the fluctuation ranges of Ca2+, Mg2+, HCO3− and SO42− can provide a basis for quantitative characterization and evaluation of CBM well production.

As a biodegradable material,magnesium alloys has been attracted by more researchers, recently. Due to good biocompatibility, mechanical properties and biodegradable absorption charac-teristics, it has been honored as revolutionary biological materials. However, current bio-magnesium alloy still could not meet the requirements of clinical application, due to its shortcomings of rapid corrosion rate and local corrosion. In this paper, the progress of bio-magnesium alloy in improving the corrosion performance was reviewed from the aspects of high purity, alloying, heat treatment process and surface modification. The paper makes a prospect on how to develop the biodegradable materials with better corrosion performance in terms of adding non-toxic alloying elements, proper surface coating, advanced preparation technology and heat treatment process.

In this study, tensile tests at room temperature and observations of slip bands on the free surface of a nickel-based single-crystal thin plate with densely distributed film cooling holes were performed. The deformation of the slip system at the edge of the cooling hole and between the holes was analyzed. Numerical simulation predictions were conducted based on the plasticity theory of crystals, and the comparison with the experimental results showed good consistency. Based on the simulation and experimental results, the nucleation and propagation direction of the edge cracks were analyzed by means of crystallography. The results showed that the fracture surface was mainly attributed to slipping, and the slip traces were approximately in two directions, namely [011] and [01-1], both of which were 45° to the stress axis. The maximum values of the resolved shear stress around the cooling hole were attained at 82.5°, 112.5°, 247.5°, and 277.5°, which corresponded to τ2, τ8, τ10, and τ6.

For the United States and China, artificial intelligence (AI) algorithms, methods, and applications are considered key to a nation's economic competitiveness and security. This paper investigates funding by the U.S. National Science Foundation and National Natural Science Foundation of China from 2010 to 2019, including the key institutions and universities that received AI awards, and the key AI disciplines and applications of focus in the research. Comparisons between the U.S. National Science Foundation and the National Natural Science Foundation of China, including the number of published papers as a result of the awards, are also presented.

Petri nets (PNs) are widely used to model flexible manufacturing systems (FMSs). This paper deals with the performance optimization of FMSs modeled by Petri nets that aim to maximize the system’s performance under a given budget by optimizing both quantities and types of resources, such as sensors and devices. Such an optimization problem is challenging since it is nonlinear; hence, a globally optimal solution is hard to achieve. Here, we developed a genetic algorithm combined with mixed-integer linear programming (MILP) to solve the problem. In this approach, a set of candidate resource allocation strategies, i.e., the choices of the number of resources, are first generated by using MILP. Then, the choices of the type and the cycle time of the resources are evaluated by MILP; the promising ones are used to spawn the next generation of candidate strategies. The effectiveness and efficiency of the developed methodology are illustrated by simulation studies.

According to the characteristics of flexible job shop scheduling problems, a dual-resource constrained flexible job shop scheduling problem (DRCFJSP) model with machine and worker constraints is constructed such that the makespan and total delay are minimized. An improved African vulture optimization algorithm (IAVOA) is developed to solve the presented problem. A three-segment representation is proposed to code the problem, including the operation sequence, machine allocation, and worker selection. In addition, the African vulture optimization algorithm (AVOA) is improved in three aspects: First, in order to enhance the quality of the initial population, three types of rules are employed in population initialization. Second, a memory bank is constructed to retain the optimal individuals in each iteration to increase the calculation precision. Finally, a neighborhood search operation is designed for individuals with certain conditions such that the makespan and total delay are further optimized. The simulation results indicate that the qualities of the solutions obtained by the developed approach are superior to those of the existing approaches.

Fault detection is quite important for discrete event systems. We investigate K-codiagnosability of Petri nets in this paper under the framework that some local sites monitor the operation of the system using their own masks. They exchange information with a coordinator while do not communicate with each other. A fault is detected when there exists a site can diagnose it. We recall the notion of Modified Verifier Nets (MVNs), and prove that K-codiagnosability can be verified looking at some special cycles in the reachability or coverability graph of the MVN. In particular, the proposed approach is available for bounded and unbounded nets. Finally, we give an algorithm to compute the minimum value of K.

Mobile robots are extensively used to complete repetitive operations in industrial areas such as intelligent transportation, logistics, and manufacturing systems. This paper addresses the path planning problem of multi-type robot systems with time windows based on timed colored Petri nets. The tasks to be completed are divided into three different types: common, exclusive and collaborative. An analytical approach to plan a group of different types of mobile robots is developed to ensure that some specific robots will visit task regions within given time windows. First, a multi-type robot system and its environment are modeled by a timed colored Petri net. Then, some methods are developed to convert the task requirements that contain logic constraints and time windows into linear constraints. Based on integer linear programming techniques, a planning approach is proposed to minimize the total cost (i.e., total travel distance) of the system. Finally, simulation studies are investigated to show the effectiveness of the developed approach.

The automated manufacturing systems (AMS) can be regarded as a resource allocation system which can be abstracted as discrete event systems (DES) for analysis. Once an effective computational method is put forward to the DES, the corresponding real AMS, connected by networks or sensors, can be indirectly controlled. Supervisory control theory (SCT) of DES is developed with the intention of discovering the maximally permissible supervisor of AMS. The state-tree structure (STS) is an extension of SCT, whose application is mainly to solve the SCT state explosion of complicated AMS. The nonblocking supervisory control is investigated on the foundation of predicates in STS, of which the synthesis focuses on the states of the system but ignores the transition between events. In order to effectively solve the above problems, this paper puts forward a novel method based on state feedback control (SFBC) in the STS framework, by which the relation among events is discussed. First, following the definition of the SFBC for predicates, the algorithms to compute the SFBC under reachability, coreachability, and weak controllability are introduced. Second, it is proved that the nonblocking SFBC obtained by the proposed algorithm is equivalent to the one by computing predicates first, which ensures the satisfactory controllers for the supervisory control problems. To demonstrate the contribution of the proposed approach, which is designed considering the symmetry of the system behavior between the real system and its STS model, three examples are illustrated.

Automated guided vehicles (AGVs) are extensively used in many applications such as intelligent transportation, logistics, and industrial factories. In this paper, we address the path planning problem for an AGV system (i.e. a team of identical AGVs) with logic and time constraints using Petri nets. We propose a method to model an AGV system and its static environment by timed Petri nets. Combining the structural characteristics of Petri nets and integer linear programming technique, a path planning method is developed to ensure that all task regions are visited by AGVs in time and forbidden regions are always avoided. Finally, simulation studies are presented to show the effectiveness of the proposed path planning methodology.

Transcranial magnetic stimulation (TMS) has been widely used in scientific research and clinical application. In TMS, the stimulation coil generates a focusing induced electrical field in the intracranial target area to achieve neuromodulation. Since different disorders correspond to their specific target areas, in order to avoid non-target tissue being stimulated, the figure-of-eight (FOE) coil with good focusing performance is still the most commonly used magnetic coil. In this paper, the U-shaped coil with multi-parameters is introduced and optimized. The spatial distributions of the intracranial induced electrical field produced by the U-shaped coil are obtained using the finite-element method. Compared to the traditional FOE coil, the U-shaped coil not only has a great advantage in improving focalization but also is beneficial to obtain other improved characteristics. The mathematical relationship between the coil geometric parameters and the intracranial induced electrical field characteristics is analyzed under the constraint of fixed coil power loss. To further improve coil efficiency, the particle swarm optimization (PSO) is adopted to optimize the coil parameters. A real human head modeled as homogeneous and isotropic is occupied in this paper to verify our method, and a traditional FOE coil is used as the reference coil. We also checked the maximum induced charge density on the targeted plane generated by the optimized U-shaped coil to make sure that it will not cause induced neurologic damage.

Electrohydrodynamic jet 3D printing is an emerging and promising technology of microand nano-scale additive manufacturing with a low cost and high resolution, as well as a wide range of printed materials. However, due to the high printing speed and small standoff height between the nozzle and the substrate, it is especially difficult to directly observe and measure the printed patterns. Furthermore, there are many process parameters that affect the printing accuracy and quality, among which each parameter is coupling and interacting. This paper proposed a method of controlling the accuracy and quality of printed patterns based on the regulation of the shape and size of the Taylor cone by varying the process parameters. A theoretical model was then derived and established that describes the relationship between the line width printed with process parameters, printed material, and used substrate. Through the systematic experimental study, the influences and rules of the printing process parameters on the Taylor cone and printed patterns were revealed; Furthermore, the ideal jet printing window for the same nozzle was optimized. Finally, the feasibility and validity of the experimental results were demonstrated by the typical engineering cases, and a pattern of minimum line width of 3 μm was achieved with the nozzle diameter of 60 μm. The proposed method and experimental results provide a basis for further improving the accuracy, quality, and stability for electrohydrodynamic jet 3D printing, and the method offers a feasible solution for simplification and easy operation of actual 3D printing.

Timed event graphs are a subclass of Petri nets that are commonly applied for modeling and controlling manufacturing systems. In this paper, we investigate the problem of improving the performance of machines (servers) in timed event graphs in order to maximize the firing rate of a system. We show that the logic constraints on the cost of machines and the operation time of machines (firing delay of transitions) can be transformed into linear algebraic constraints. Furthermore, we formulate a mixed integer linear programming problem to maximize the firing rate of the net under a given budget for improving the performance of servers (decreasing the firing delay of transitions) that can provide an optimal solution. Finally, application to an assembly line is presented to show the effectiveness of the developed methodology.

The flotation separation of galena, sphalerite, and pyrrhotite was investigated with CCSL as a depressant. Flotation test results show that galena and sphalerite can float but pyrrhotite can barely float with CCSL as a depressant. The flotation tests also show that galena can be separated efficiently from pyrrhotite, and that sphalerite can be separated on the whole from pyrrhotite, but the separation efficiency of the former is much better. The X-ray photoelectron spectroscopy (XPS), IR spectrum, and Zeta potential analysis results indicate that the interaction of sodium acetate and pyrrhotite is not only physical absorption. The UV spectrum indicates that the decline in floatability of pyrrhotite is due to the hydrophilicity caused by CH3COO- being stronger than that caused by dixanthogen, and the xanthate adsorption on pyrrhotite is not prohibited by CH3COO-. The CH3COO- reacts not only with pyrrhotite, but also with H+ in water as a H-bond, so the pyrrhotite becomes hydrophilic.

The corrosion behavior of primid-curing solidified polyester powder coating defects in marine environment was investigated by CASS test, immersion test, electrochemical impedance spectroscopy (EIS) and scanning Kelvin probe (SKP). The results show that the primid-curing polyester powder coating has a small amount of blisters along the scratch edge, the maximu single side corrosion width is less than 0.5mm, and the surface adhesion is 0 after 240 hours' CASS test. The EIS map in 0.6mol/L NaCl solution exhibits that the corrosion rate of aluminu alloy is decreased with increasing immersion time and gradually stable. The scanning Kelvin spectrum reveals that the corrosion of the metal under the coating of the polyester powder is extended from scratch to the coating, the anode and the cathode are alternately changed, which leads to the expansion of the corrosion area.

Most existing deadlock prevention studies on flexible manufacturing systems (FMSs) resort to Petri nets (PNs) by designing controllers for them. PNs are an effective tool for analyzing and modeling the dynamic behavior of FMSs. As an important subclass of PNs, the system of simple sequential processes with resources (S3PR) can be used to model many FMSs. This paper proposes a novel resource configuration method based on structural analysis to ensure the liveness of an S3PR. The restrictive relation between the initial marking of the process idle places and a special PN structure called strongly connected characteristic resource sunnets (SCCRSs) is first explored by employing the corresponding relation between SCCRSs and their related strict minimal siphons. With the structural properties of SCCRSs, functions invoked to compute the configuration marking for the resource places in an SCCRS are established. Then, an algorithm for computing a configuration marking in an S3PR is developed, and a resource configuration tree is correspondingly generated according to the execution of the developed algorithm. Thus, the liveness of the configured system is ensured, while the siphon enumerations are avoided. It is shown that the computational complexity of the developed algorithm is polynomial, which is more efficient than other existing ones. Examples are finally provided to illustrate the mentioned results.

Transcranial magnetic stimulation (TMS) has been proved to be effective in the treatment of many psychiatric disorders, but the clicking noise produced by the large and short pulse current in the TMS coil may put negative effect to the hearing of patients. However, current researches on noise control of the TMS device are very limited. In this paper, by analyzing the actual noise signal of TMS, the mechanism of noise generation of the device is explained. According to the therapeutic schedule of TMS, an active noise control (ANC) strategy for TMS device with online identification, offline analysis, and real-time output is proposed. A finite element analysis model of noise propagation and noise control of the device is established. The strategy steps are as follows: the secondary pathway is constructed at first; during the first stimulation sequence, the coil noise received by the human ear is collected in real-time, and the noise is analyzed offline; the secondary signal is then produced to reduce the following noise in real-time. The simulation results show that the proposed ANC strategy for TMS can effectively reduce the noise with certain robustness.

Self-interacting proteins (SIPs), whose more than two identities can interact with each other, play significant roles in the understanding of cellular process and cell functions. Although a number of experimental methods have been designed to detect the SIPs, they remain to be extremely time-consuming, expensive, and challenging even nowadays. Therefore, there is an urgent need to develop the computational methods for predicting SIPs. In this study, we propose a deep forest based predictor for accurate prediction of SIPs using protein sequence information. More specifically, a novel feature representation method, which integrate position-specific scoring matrix (PSSM) with wavelet transform, is introduced. To evaluate the performance of the proposed method, cross-validation tests are performed on two widely used benchmark datasets. The experimental results show that the proposed model achieved high accuracies of 95.43 and 93.65% on human and yeast datasets, respectively. The AUC value for evaluating the performance of the proposed method was also reported. The AUC value for yeast and human datasets are 0.9203 and 0.9586, respectively. To further show the advantage of the proposed method, it is compared with several existing methods. The results demonstrate that the proposed model is better than other SIPs prediction methods. This work can offer an effective architecture to biologists in detecting new SIPs.

Rapidly increasing mobile data traffic have placed a significant burden on mobile Internet networks. Due to limited network capacity, a mobile network is congested when it handles too much data traffic simultaneously. In turn, some customers leave the network, which induces a revenue loss for the mobile service provider. To manage demand and maximize revenue, we propose a dynamic plan control method for the mobile service providers under connection-speed-restriction pricing. This method allows the mobile service provider to dynamically set the data plans’ availability for potential customers’ new subscriptions. With dynamic plan control, the service provider can adjust data network utilization and achieve high customer satisfaction and a low churn rate, which reflect high service supply chain performance. To find the optimal control policy, we transform the high-dimensional dynamic programming problem into an equivalent mixed integer linear programming problem. We find that dynamic plan control is an effective tool for managing demand and increasing revenue in the long term. Numerical evaluation with a large European mobile service provider further supports our conclusion. Furthermore, when network capacity or potential customers’ willingness to join the network changes, the dynamic plan control method generates robust revenue for the service provider.

Petri nets are an effective tool for analyzing and modeling the dynamic behavior of flexible manufacturing systems. Finite capacity systems of simple sequential processes with resources are an important subclass of Petri nets, for which this article gives a liveness characteristic analysis. First, an effective algorithm for deciding the liveness of finite capacity systems of simple sequential processes with resources is developed by analyzing the relation between the structural properties of resource subnets and the strict minimal siphons. Then, a liveness condition of finite capacity systems of simple sequential processes with resources is accordingly established. Based on the proposed liveness condition, an algorithm for configuring an initial marking for a finite capacity systems of simple sequential processes with resources is given, and therefore, a live finite capacity systems of simple sequential processes with resources net with a configured initial marking can be obtained, which avoids the siphon enumerations and the addition of any control actions. It is shown that the computational complexity of both the developed liveness deciding and the initial marking configuration algorithms is polynomial. Examples are finally provided to illustrate the mentioned results.