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Because of COVID-19, factories are facing many difficulties, such as shortage of workers and social alienation. How to improve production performance under limited labor resources is an urgent problem for global manufacturing factories. This work studies an energy-efficient job-shop scheduling problem with limited workers. Those workers can have multiskills. A many-objective model with five objectives, that is: 1) makespan; 2) total tardiness; 3) total idle time; 4) total worker cost; and 5) total energy, is built. To solve this many-objective optimization problem (MaOP), a novel fitness evaluation mechanism (FEM) based on fuzzy correlation entropy (FCE) is adopted. Two construction methods for reference points are proposed to build the bridge between MaOP and a fuzzy set. Based on FCE and cluster methods, an environmental selection mechanism (ESM) is proposed to achieve a balance between solution convergence and diversity. With the proposed FEM and ESM, two many-objective evolutionary algorithms are proposed to solve MaOP. The effect of FCE-based FEM and ESM on the performance of algorithms is verified via experiments. The proposed algorithms are compared with four well-known peers to test their performance. The extensive experimental results show that they are very competitive for the considered many-objective scheduling problem.

In the context of new retail and personalized, small-batch, distributed collaborative production, orders arrive in real time, and each workshop needs to organize production lines based on suborders in real time under the constraints of smart contracts. However, the existing cloud centralized scheduling method has very high calculation and communication costs when inserting orders in real time, and the fully reactive edge scheduling method is difficult to meet the various order-level requirements of customers. Therefore, this article proposes a real-time edge scheduling model that considers real-time trial insertion of orders based on order-level requirements. Further, a real-time edge adjustment method to eliminate fluctuations is proposed. The proposed strategies were implemented using the lightest methods, avoiding cascading effects, to apply to the edge. Experimental results show that proposed strategies have significant advantages in order-level indicators such as customer satisfaction and have slightly better performance in workshop-level indicators such as resource utilization, energy consumption, and makespan.

In this paper, the problem of non-fragile H ∞ control for uncertain active suspension systems (ASSs) with time-delay is investigated via a fuzzy control approach in the finite frequency domain. Firstly, considering the variation of sprung and unsprung masses, a Takagi-Sugeno (T-S) fuzzy model is constructed to describe the nonlinear suspension dynamics based on a typical quarter-automobile ASS model. Meanwhile, the input delays and gain perturbations of the actuator are considered to approximate the real physical device situations in the control systems. Secondly, through combining Lyapunov stability theory, generalized Kalman-Yakubovich-Popov (GKYP) lemma with the further universalization of the strict S-procedure, a sufficient condition is presented to ensure that the resulted closed-loop system is asymptotically stable and satisfies the desired finite frequency H ∞ performance simultaneously. Furthermore, the existing conditions of the fuzzy controller are given as a convex optimization problem in terms of a set of linear matrix inequality (LMI) constraints. Finally, numerical simulations are implemented to examine the effectiveness and performance advantages of the proposed control approach.

SummaryIn conventional wellbore-integrity analysis, the cement sheath’s initial state of stress and transient thermoporoelastic effects are often neglected. However, the initial state of stress is prerequisite information for accurately predicting the safe operating conditions that prevent a cemented well from being damaged. In addition, transient thermoporoelastic effects can have a profound effect on when damage will occur. In this paper, we propose a model that includes these effects to predict the safe operating pressures and temperatures that will prevent cement-sheath failure. For the initial state of stress, we proposed an empirical model using measurements. Subsequent stress changes are evaluated by a fully coupled transient thermoporoelastic model to analyze the mechanical behavior of the cement sheath. We predict the safe operating envelope (SOE) for shear, tensile, and debonding cement-sheath failures caused by pressure and temperature perturbations after the cement sets. Our model predicts that pore pressure is a key factor for cement failure, especially for rapid temperature changes. If the formation is low permeability, the transient pore pressures are amplified, causing the risk of damage to increase. Compared with conventional thermoelastic models, the thermoporoelastic model predicts a smaller SOE when heating the internal casing fluid and a larger envelope when cooling the internal casing fluid. Finally, the heating rate was considered with respect to field applications. The heating rate was also considered, and slower heating/cooling rates can prevent damage to the cement sheath. Finally, the thermoporoelastic model was applied to explain several laboratory and field experiments and achieved good matches.

This paper proposes a static-output-feedback based robust fuzzy wheelbase preview control algorithm for uncertain active suspensions with time delay and finite frequency constraint. Firstly, a Takagi-Sugeno (T-S) fuzzy augmented model is established to formulate the half-car active suspension system with consideration of time delay, sprung mass variation and wheelbase preview information. Secondly, in view of the resonation between human's organs and vertical vibrations in the frequency range of 4-8 Hz, a finite frequency control criterion in terms of $H_{\infty}$ norm is developed to improve ride comfort. Meanwhile, other mechanical constraints are also considered and satisfied via generalized $H_{2}$ norm. Thirdly, in order to maintain the feasibility of the controller despite of some state variables are not online-measured, a two stage approach is adopted to derive a static output feedback controller. Finally, numerical simulation results illustrate the excellent performance of the proposed controller.

This article presents a novel adaptive-event-trigger-based fuzzy nonlinear lateral dynamic control algorithm for autonomous electric vehicles under insecure communication networks. The integration of path following control and direct yaw moment control is considered to acquire a better lateral dynamic performance. To effectively tackle inherent nonlinearities of lateral dynamics, the Takagi–Sugeno fuzzy model approach is employed to approximate the nonlinear lateral dynamics. To avoid the infeasibility of state-feedback control due to the immeasurability of sideslip angle, a fuzzy output feedback control strategy is proposed via a useful transformation. To improve resource utilization of the band-limited communication networks, an adaptive event-triggered communication mechanism is proposed to save communication resource. Moreover, to enhance the robustness of the proposed controller, the insecure communication link is considered, which is described by the Bernoulli random distributed process. Finally, simulation results show the proposed adaptive-event-trigger-based fuzzy controller not only can save communication resource, but also achieve the perfect control performance.

In this research effort, an innovative magneto-rheological variable stiffness and damping torsional vibration absorber (MR-VSDTVB) is proposed, and independent variable damping control and independent variable stiffness control are adopted to suppress the torsional vibration of the transmission system. MR-VSDTVB, based on semi-active control principle, exhibits a compact structure and integrates with magneto-rheological technology. First, the concept of MR-VSDTVB is discussed, and the output torque characteristic of MR-VSDTVB is analytically developed. Then, a prototype is fabricated and tested. A transmission system with MR-VSDTVB is proposed to verify the MR-VSDTVB's effectiveness. The structure and inherent characteristics of the transmission system are analyzed theoretically. Finally, an experimental setup of transmission system with MR-VSDTVB is built. Experimental results indicate that when torsional stiffness of MR-VSDTVB changes, a frequency shift phenomenon occurs; moreover, when torsional damping of MR-VSDTVB changes, the response amplitude of the experimental setup changes regularly; And finally, the on-off control test validates the effectiveness of semi-active control on the torsional vibration suppression of the transmission system. The above results verify the effectiveness of MR-VSDTVB in suppressing the torsional vibration of the transmission system. These findings are expected to expand the application of magneto-rheological technology and variable stiffness and variable damping technology in torsional vibration of transmission systems.

To avoid the limitation of conventional vehicle magnetorheological (MR) suspension, a variable damping and inertia device is applied in the vehicle suspension with MR technology. A semi-active adaptive MR inerter (AMRI) is discussed. A quarter car suspension model with an AMRI installed in parallel with a double-ended MR damper (D-MRD) is considered. First, the vehicle suspension with variable damping and inertia is analyzed. The prototype of D-MRD and MR variable inertia flywheel (MRVIF) are fabricated and tested respectively. Then, the control model of D-MRD and MRVIF is developed on the basis of test data. An improved Fuzzy PID controller for the semi-active suspension with D-MRD and AMRI is formulated. Numerical simulation is investigated to validate the proposed variable damping and inertia device. The results demonstrate that the performance of the semi-active suspension with D-MRD and AMRI can achieve much better ride comfort than the semi-active suspension with only D-MRD or AMRI.

In this work, we propose a fault detection strategy for wireless sensor networks (WSNs) called Trend Correlation based Fault Detection strategy (TCFD). This strategy can detect the faulty sensor nodes through analyzing the trend correlation and the median value of neighboring nodes. On this basis, aiming to avoid the excessive routing overhead caused by over-frequent fault detection, a fault detection self-starting mechanism is designed based on the cubic exponential smoothing method. Since the detection results in TCFD are determined by historical data at consecutive times and do not rely on the comparison of instantaneous sensed values at a single moment, it can significantly reduce the impact of fault detection time on detection accuracy. The simulation results have indicated that compared with referenced strategies, the proposed TCFD can obtain better fault detection accuracy for four common fault types of sensor nodes; in the case where the real fault rate of the network reaches 0.5, at least 70% of the faulty nodes can be detected by TCFD and the false alarm rate can still be kept below 30%; with the help of fault detection self-starting mechanism, the response time of sensor nodes to faults can be significantly shortened.

The Co3O4 decorated TiO2 nanotube arrays(NTAs) coatings are fabricated by the combination of anodization and impregnating methods. It is found that the introduction of Co3O4 can reduce the diffraction intensity of (101) plane of the TiO2 and accelerate the separation of photogenerated electron/hole pairs. In addition, the open circuit potential(OCP) and the corrosion potential of 304 stainless steel(304SS) with or without Co3O4 decorated TiO2 NTAs were measured under visible light, which indicated the 304SS coupled with Co3O4 decorated TiO2 NTAs had better anticorrosion performance than that of the 304SS or the 304SS coupled with pure TiO2 NTAs. The enhancement of the cathodic protection performance of the Co3O4 decorated TiO2 NTAs can be ascribed to the matched energy levels and strong interaction between Co3O4 and TiO2 NTAs, and the improvement of light absorption.

In the emerging wearable world, a plethora of smart devices are being designed to facilitate our daily life. More activities, such as student learning, desk office work, or driving are requiring human beings to spend a significant portion of their daily life sitting on a chair. As a result, there is increasing interest in the development of technologies that monitor and support seated users. The most iconic examples of this are the smart chair and the smart cushion. To prompt users to maintain healthy sitting posture and to encourage them to have a short break after prolonged sitting, several studies focus on the detection, monitoring, and analysis of sitting postures. The smart cushion, in particular, is a very promising device in this context because it is noninvasive and can be conveniently deployed on the seat or backrest, making an ordinary chair, sofa, or even a car seat suddenly smart. This article reviews our previous research studies and the results related to sitting posture recognition using the smart cushion. We will show that very diversified applications can be enabled, spanning medical applications (e.g., back pain or pressure ulcers avoidance) and even human communication (body language detection).

With the further development of the Deep Space Networking (DSN), more and more satellites and space probes will be put into space which makes the DSN more diverse and complex. We argued that Information Centric Networking (ICN) may be a suitable architecture for the DSN. In this paper, a publish-subscribe networking architecture based on ICN is proposed for future manned deep space exploration network. It adopts the publish-subscribe mechanism and decouples the control plane and data plane logically. In the proposed architecture, the improvement of routing is made to tolerant the long propagation delay and frequent link disruptions of deep space. And the multi-source transmission is considered to deal with the large amount of data in the future manned deep space exploration network. We evaluated the feasibility of the architecture and the performance of the protocol stack, the improved routing mechanism and the multi-source transmission. The results indicate that Publish-Subscribe Networking (PSN) can cope with the harsh transmission conditions, and the multi-source transmission can reduce the delivery time of data. It enables the network to allocate and share resources more efficiently and keeps the network well managed.

Reasonable hydrophobic anode is deemed to be a promising electrode for photoelectrocatalytic degradation of wastewater. In this study, the C3N4-modified Ti/PbO2 electrode with tunable hydrophobic characteristics is fabricated by a facile electrodeposition process. It is found that the introduction of C3N4 into the PbO2 films changed the morphology, surface hydrophilicity, and hydrophobicity of the electrode, which promotes the photoelectrochemical active areas, generating efficiency of hydroxyl radicals. In addition, introducing C3N4 into PbO2 coating can enhance oxygen evolution potential and carrier density of PbO2. Photoelectrocatalytic degradation experiments show that the addition of C3N4 can further improve the catalytic performance of PbO2 and there exists a significant photoelectric synergism in photoelectrocatalytic process. These results demonstrate that the combination of reasonable surface hydrophobic characteristics and photoelectrocatalytic is a prospective approach for wastewater treatment.

Despite the long-term use and recent development of keratin materials, the mechanism of their solubilization is still not well understood beyond the breakage of disulfide bonds due to the complexit...

Next generation global navigation satellite systems (GNSSs) will embrace intersatellite links capability as an enabler of navigation and data transfer. However, platform restrictions will require of suitable contact plan design (CPD) schemes, which have been traditionally assumed centralized . After discussing the requirements of distributed CPD, we propose a first scheme in this class. Simulation results on the BeiDou GNSS prove that satisfactory metrics can be obtained enabling valuable and real autonomy for future GNSSs.

Flame-retardant epoxy (EP) resin/cyanate ester (CE) composites were prepared with 9,10-dihydro-9-oxa-10-phosphaphenanthrene 10-oxide (DOPO) and wollastonite (Wo). The combustion behavior of the flame-retardant EP/CE composites was investigated by limiting oxygen index (LOI), UL-94, and cone calorimeter tests. It is found that the EP/CE composite containing 7 wt% DOPO and 3 wt% Wo (sample 7DO/3Wo/EP/CE) exerts the best flame retardancy (LOI 35.5% and UL-94 V-0 rating). The peak heat release rate and total heat release of sample 7DO/3Wo/EP/CE increase slightly, while total smoke release decreases about 14% compared with the EP/CE composite containing 10 wt% DOPO (sample 10DO/EP/CE). Thermal studies indicate that the glass transition temperature and temperature at 5% mass loss of sample 7DO/3Wo/EP/CE are higher than that of sample 10DO/EP/CE. Moreover, the mechanical properties of EP/CE composites were investigated.

Nanozymes are inorganic nanoparticles that mimic the enzyme-like properties in redox reactions, processing both unique properties of nanomaterials and a catalytic function. Because of high catalytic activity, stability and multifunctionality, nanozyme are of increasingly wide interest in the fields of environmental science and technology. In this article, we review the most recent advances of nanozyme research for environmental pollutant detection and treatment. Nanozymes can be used to detect ions, molecules and organic compounds both qualitatively and quantitatively. They have also been applied for destruction multi-drug resistant bacteria and the degradation of various organic pollutants. Despite the apparent potential of nanozymes in environmental science and technology, current research and application is still limited, and so future challenges and research prospects have been highlighted.

The incessant diffusion of smart wearable devices and Body Area Networks (BANs) systems is pushing more and more researches on human activity recognition. Previous studies usually adopted fixed time window or chose an optimal window size depending on the characteristics of the activity. In this paper, we propose an adaptive time window-based algorithm of activity recognition, which addresses the problem of different types of activities having different time duration that usually causes poor recognition results. Multivariate Gaussian Distribution (MGD) method was used to detect the signal difference between each determined time window and the defined activity characteristics, and we more accurately define the time window size for each activity. To evaluate the proposed algorithm, we focused on the activities performed by wheelchair users in their daily life, so as to provide them with better healthcare services. We construct two different datasets, respectively considering static and dynamic wheelchair user activities on different ground surfaces. Then, we use time window expansion and contraction method to determine and dynamically adjust the window size for each activity. Different comparison criteria such as recognition precision and F-score were used to evaluate our algorithm. Experiment results revealed that, according to F-score, the proposed algorithm performs 15.3% better than traditional methods in static conditions. In dynamic scenarios we observed 6.4% and 24.5% improvements on flat and rough floors, respectively.

Bad weather conditions (such as fog, haze) seriously affect the visual quality of images. According to the scene depth information, physical model-based methods are used to improve image visibility for further image restoration. However, the unstable acquisition of the scene depth information seriously affects the defogging performance of physical model-based methods. Additionally, most of image enhancement-based methods focus on the global adjustment of image contrast and saturation, and lack the local details for image restoration. So, this paper proposes a single image defogging method based on image patch decomposition and multi-exposure fusion. First, a single foggy image is processed by gamma correction to obtain a set of underexposed images. Then the saturation of the obtained underexposed and original images is enhanced. Next, each image in the multi-exposure image set (including the set of underexposed images and the original image) is decomposed into the base and detail layers by a guided filter. The base layers are first decomposed into image patches, and then the fusion weight maps of the image patches are constructed. For detail layers, the exposure features are first extracted from the luminance components of images, and then the extracted exposure features are evaluated by constructing gaussian functions. Finally, both base and detail layers are combined to obtain the defogged image. The proposed method is compared with the state-of-the-art methods. The comparative experimental results confirm the effectiveness of the proposed method and its superiority over the state-of-the-art methods.

Multicolor-tunable materials have attracted extensive interest due to their unique advantages in applications of lighting and displays. In this paper, energy transfer from Ce3+ to Tb3+ occurred and the effective energy transfer efficiency (ηETE) of Ce3+-Tb3+ has been calculated to be as high as 36%. To obtain multicolor-tunable emissions, Eu3+ ions were successfully introduced into Ce3+–Tb3+ codoped Sr3La6(SiO4)6 samples. Furthermore, an energy transfer process from Ce3+ to Eu3+ ions has also been demonstrated by an energy transfer bridge of Tb3+. Meanwhile, we achieved the precise adjustment of purple, green, orange and red emissions of Sr3La6(SiO4)6: Ce3+, Tb3+, and Sr3La6(SiO4)6: Ce3+, Tb3+, Eu3+. In addition, Sr3La6(SiO4)6: Ce3+, Tb3+, Eu3+ phosphors exhibited a good thermal stability: their integrated emission intensities at 450 K still kept more than 90% of their initial intensity at room temperature. Therefore, these results might provide a novel multicolor-tunable phosphor for lighting and display application.

Tb3+ is a typical green emitting luminescence center in inorganic compounds. However, the absorption of Tb3+ is very weak in ultraviolet spectral region (from 240 to 400 nm). Ce3+ is often used as a sensitizer to transfer energy to Tb3+. In this paper, Ce3+ and Tb3+ were co-doped into a novel aluminates-borates LaAl2.03B4O10.54. Ce3+ can absorb UV light (from 240 to 340 nm) and transfer absorbed energy to co-doped Tb3+ effectively and bring bright green emission of Tb3+. The crystal structure and fluorescence spectra of phosphors, the efficiency of energy transfer between Ce3+ and Tb3+, decay dynamics, the thermal stability and internal quantum efficiency of luminescence have been investigated in detail. These results indicate that the color tunable LaAl2.03B4O10.54: Ce3+, Tb3+ phosphor is a potential green-emitting material. Especially, analysis about the relationship of the doping concentration of luminescence centers and thermal stability of luminescence points out a feasible way to enhance the thermal stability of luminescence in the future.

One of the main problems of large-scale wind power access to the power system is the fault ride-through (FRT) ability of wind turbine generator (WTG) at present. A fast-reactive current control (FR...

This paper investigates the problem of fuzzy finite-frequency output feedback control for nonlinear active suspension systems with time delay and output constraints. Firstly, as the physical suspension systems always exist the phenomenon of sprung and un-sprung mass variation and time delay, the Takagi-Sugeno (T-S) fuzzy model is adopted to represent the nonlinear uncertain active suspension system with uncertainties and time delay. Secondly, since the human body is much more sensitive to vertical vibrations between 4 and 8 Hz, a finite-frequency control criterion is formulated for the controller deign with consideration of time delay and output constraints. Other mechanical constraints such as suspension travel, tire dynamic deflection and actuator saturation are also considered. Thirdly, on a practical point of view, not all the states are online measurable. Hence, a novel fuzzy static output feedback (SOF) controller is proposed by applying the parallel-distributed compensation (PDC) scheme. The sufficient conditions for deriving the fuzzy SOF controller are obtained in terms of linear matrix inequalities (LMIs). Finally, numerical simulations on a quarter-car suspension model are conducted to validate the effectiveness and applicability of the proposed fuzzy SOF controller.

High brightness and precise adjustment of luminescence colour of phosphors are two main targets in the research of phosphor-converted white LEDs. However, few feasible strategy can be employed to achieve the multicolor-tunable luminescence under the premise of maintaining high quantum efficiency. Here, we demonstrate a high-efficiency energy-transfer process from Tb3+ to Eu3+ ions with a higher luminescent quantum efficiency (64.5% and 53.4%, respectively), and green-red multicolor emission in Lu2GeO5 host via varying the doping content of Tb3+ and Eu3+ ions. Besides, Lu2GeO5:Tb3+, Lu2GeO5: Eu3+ and Lu2GeO5: Tb3+, Eu3+ all exhibit weak thermal quenching which ensures the stable use of white LED device in the high temperature environment. This paper provides a novel multicolor-tunable phosphor with high brightness, efficient energy transfer and weak thermal quenching, which presents a potential application for UV-converted white LEDs.

Research hotspots about Ce3+-Tb3+ and Ce3+-Mn2+ codoped multicolor-tunable materials, has grown rapidly and is still growing. However, few feasible strategies can be employed to achieve the multicolor-tunable luminescence under the premise of maintaining high QE. In this paper, KSrLu(PO4)2:0.25Ce presents a high luminescence efficiency with approximately 78% quantum efficiency. Furthermore, Ce3+-Tb3+ and Ce3+-Mn2+ codoped optimal samples give a green and red luminescence, which corresponds to a high 61% and 55% quantum efficiency due to a high energy transfer efficiency of Ce3+→Tb3+ and Ce3+→Mn2+. Besides, we achieved the precise adjustment of blue, green, orange and pink emissions of KSrLu(PO4)2:Ce3+, Tb3+, Mn2+ samples. Meanwhile, KSrLu(PO4)2:Ce3+, Tb3+ and KSrLu(PO4)2:Ce3+, Mn2+ phosphors present a weak thermal quenching: their integrated emission intensity at 500K still keep more than 80% of their initial intensity at room temperature. Therefore, the results might provide a novel multicolor-tunable phosphor for backlight display application.

Design and preparation of novel advanced carbon materials with unique architecture and functional groups is of great significance. Herein, a spongy acetylenic carbon material (SACM) was prepared through mechanochemical reaction of CaC2 and chlorinated rubber in a planetary ball mill at ambient temperature. Its composition and structure were characterized, and its electrochemical properties and adsorption performance for Hg2+ were studied. The SACM is composed of submicron spongy aggregates with high carbon content (81.8%) and specific area (503.9 m2·g−1), rich porosity and acetylenic groups. The SACM exhibits excellent adsorption for Hg2+ with saturated adsorption amount being 157.1 mg·g−1, which is superior to conventional carbon materials. Further, it exhibits good electrochemical performance with low equivalent series resistance (0.50 Ω), excellent cycling stability and ideal double layer capacitive behavior. This paper provides a novel and universal synthesis method of spongy carbon materials, and better results can be expected through tuning the pore structure, graphitization degree, and heteroatoms of the target carbon materials.

A comprehensive learning particle swarm optimizer (CLPSO) embedded with local search (LS) is proposed to pursue higher optimization performance by taking the advantages of CLPSO’s strong global search capability and LS’s fast convergence ability. This paper proposes an adaptive LS starting strategy by utilizing our proposed quasi-entropy index to address its key issue, i.e., when to start LS. The changes of the index as the optimization proceeds are analyzed in theory and via numerical tests. The proposed algorithm is tested on multimodal benchmark functions. Parameter sensitivity analysis is performed to demonstrate its robustness. The comparison results reveal overall higher convergence rate and accuracy than those of CLPSO, state-of-the-art particle swarm optimization variants.

Dielectric barrier discharge (DBD) plasma in situ generates reactive species (e*, OH, O, H, H2O2, O3, etc.), UV irradiation and local high temperature. These physiochemical effects can non-selectively destroy aqueous organic contaminants, but the energy efficiency of DBD plasma for water decontamination can be further improved. Persulfate ( S 2 O 8 2 - , PS) and ferrous ions (Fe2+) were employed for enhancing the degradation of p-nitrophenol (PNP). An addition of both S 2 O 8 2 - ( OH and SO 4 · - through Fenton-like reactions and PS activation process. Moreover, the tertiary system of plasma/PS/Fe2+ (81.1%) presented higher PNP degradation efficiency after 50 min treatment than discharge plasma alone (34.8%) and the binary systems of plasma/PS (63.6%), plasma/Fe2+ (69.6%) and PS/Fe2+ (13.7%). However, an excessive addition of S 2 O 8 2 - (2.5–3.6 mM) and Fe2+ (36–360 µM) had unobvious or even harmful influence on PNP degradation, possibly due to the enhanced recombination or consumption of OH and SO 4 · - by radical side reactions. The effect of radical scavengers on PNP degradation indicates that OH was the most important radical species in plasma system for PNP degradation, but SO 4 · - was also very important for PNP degradation when PS was present in solution. Besides Fe2+ and the heat effect from discharge plasma, the electrons produced by electric discharge may also be one of the important contributors to the activation of PS.

A novel method is presented for the synthesis of Ti2SC powder by heating FeS2/Ti/TiC mixtures. The phase evolution of Ti2SC was explored in detail with X-ray diffraction, thermo-gravimetry/differential scanning calorimetry, and scanning electron microscopy analysis. It was found that FeS2 began to decompose into activated FeS and released molecular state sulphur at around 500 °C. Subsequently, FeS and Ti underwent a reaction that formed Fe and TiS at 700 °C. Finally, the reaction of both TiS and TiC to form a Ti2SC phase could be triggered at 900 °C. It was confirmed that the Ti2SC phase was obtained with only trace impurity of TiC remaining after acid treatment by microwave hybrid heating of 1.1FeS2/2Ti/2TiC mixtures at 1 300 °C for 3 min. The fine powder with a mean diameter of approximately 1 μm was mainly composed of quasi-spherical particles. Compared to the conventional method, Ti2SC powder was synthesised at a temperature some 300 °C lower and required only 10 % of the heating time.

The development of high drug loading and sustained release nanoparticles by simple and economical methods is significant for the treatment of diseases. Amorphous calcium carbonate (ACC) is an ideal drug delivery system because of its excellent pH responsiveness, biocompatibility and biodegradability. In this work, ACC nanoparticles were successfully precipitated in ethanol–calcium solutions using ammonium carbonate as the internal source of CO2, which exhibited a relatively narrow size distribution in range of 10–200 nm. The microscopic morphology, amorphous characters, porous structure and thermal behavior of resultants were investigated by electron microscopy, Fourier-transform infrared spectroscopy, Brunauer–Emmett–Teller and thermogravimetric analysis, respectively. In vitro drug release assay showed that ACC nanoparticles had high loading capacity of curcumin (Cur) and favorable drug release properties. Furthermore, ACC-Cur showed excellent abilities to scavenge free radicals, protect Cur stability and damage A549 cells, providing a broadened space for the applications of this material in the fields of biomedical or food.

The static anisotropic elastic properties of shales can be measured by performing uniaxial compression on core specimens with bedding planes of different inclination angles (or anisotropy angles). However, these measurements differ when different numbers of specimens are tested, mainly because of the heterogeneity of shales. This study aimed to quantify the uncertainties of the anisotropic elastic properties of a shale when testing different numbers of specimens with distinct anisotropic angles. Three sets of room-dried core samples were prepared, and each set consisted of seven specimens with incremental anisotropic angles of 15°. Uniaxial compression measurements were used to determine the anisotropic elastic properties for a given number (2–7) of specimens in each set. The results indicated that the uncertainties of the determined anisotropic elastic properties decreased monotonically as the number of measurements was increased. The results also suggested that at least five specimens with different anisotropic angles should be tested in order to obtain accurate elastic properties (uncertainty

Accelerating and regulating collagen formation during wound healing repair is key issues for skin regeneration. Insulin can promote the healing of damaged skin by stimulating cellular migration and angiogenesis. Here, human hair keratin-conjugated insulin was synthesized to enhance full-thickness skin regeneration based on the excellent wound healing and hemostatic effects of keratin and the collagen deposition regulation ability of insulin. The insulin-conjugated keratin (Ins-K) was synthesized through the EDC/NHS reaction, which can supply a sustained release of insulin. The Ins-K hydrogel displayed similar water absorption, porosity and rheology properties to those of the keratin hydrogel. However, the Ins-K hydrogel shows a stronger hemostatic ability than the keratin hydrogel group, with a stronger wound healing effect found for the Ins-K hydrogel in the early regeneration stage (first 2 weeks) than for the keratin hydrogel treatment, resulting in smoother skin tissues at an excision section realized by regulating transforming growth factor β1 (TGF-β1) and hydroxyproline (HYP) expression. The results demonstrate that keratin promotes hemostasis and wound healing after insulin conjugation, which highlights the potential of keratin-based materials in tissue regeneration applications.

6-Phosphogluconate dehydrogenase (6PGD) is a key enzyme that converts 6-phosphogluconate into ribulose-5-phosphate with NADP+ as cofactor in the pentose phosphate pathway (PPP). 6PGD is commonly upregulated and plays important roles in many human cancers, while the mechanism underlying such roles of 6PGD remains elusive. Here we show that upon EGFR activation, 6PGD is phosphorylated at tyrosine (Y) 481 by Src family kinase Fyn. This phosphorylation enhances 6PGD activity by increasing its binding affinity to NADP+ and therefore activates the PPP for NADPH and ribose-5-phosphate, which consequently detoxifies intracellular reactive oxygen species (ROS) and accelerates DNA synthesis. Abrogating 6PGD Y481 phosphorylation (pY481) dramatically attenuates EGF-promoted glioma cell proliferation, tumor growth and resistance to ionizing radiation. In addition, 6PGD pY481 is associated with Fyn expression, the malignancy and prognosis of human glioblastoma. These findings establish a critical role of Fyn-dependent 6PGD phosphorylation in EGF-promoted tumor growth and radiation resistance., 6-phosphogluconate dehydrogenase is commonly upregulated in cancers. Here, the authors show that activation of EGFR induces phosphorylation of this enzyme at Y481 to activate the pentose phosphate pathway, which consequently reduces ROS and accelerates DNA synthesis to promote tumor growth and radioresistance.

How to shorten time delay and enhance delivery ratio in sparse settings is still an open issue in the study of opportunistic networks. Most proposals are trying to deal with this issue by introducing infrastructures; however, although related research has been proved to be useful in improving the routing performance of the network, there is still room for further improvement. In this paper, inspired by the powerful message synchronization capability of wireless sensor networks (WSNs), we propose a new opportunistic network framework called WON that introduces WSNs into the opportunistic network. With the support of WSNs, low latency delivery and high delivery ratio can be achieved. To make the best use of WSNs, we present a comprehensive routing mechanism that is able to cover all the message-forwarding activities (i.e., mobile-to-mobile, mobile-to-stationary, stationary-to-mobile and stationary-to-stationary) in WON. To tackle the challenging issues caused by constrained energy and storage space, we develop a storage management scheme and a message control scheme. The experimental results show that WON can improve the success ratio while lowering the latency compared with the existing architectures. Furthermore, it is shown that WON is a highly effective solution for the rapid deployment of a low-latency communication network in the disaster-relief scenarios.

Delay/disruption tolerant networking (DTN) [1] is proposed as an internetworking architecture for reliable data delivery despite a long propagation delay and/or lengthy link disruptions. DTN targets challenging networking environments where traditional networking protocols such as the terrestrial Transmission Control Protocol/Internet Protocol (TCP/IP) typically do not work effectively. The challenging problem of mission control and data delivery in space communications is a typical application scenario of the DTN technology. Reliable and highly efficient data delivery of DTN relies heavily on the bundle protocol (BP) [2]. BP is intended to establish an overlay network that is able to withstand intermittent data link connectivity in the delivery of DTN data units, termed bundles. BP adopts a store-and-forward mechanism and a custody transfer option for transmission reliability.

Wireless sensor networks have been widely used in industrial IoT contexts due to their useful support during the production monitoring and risk pre-warning. However, complicated and extremely variable industrial environments call for higher communication stability and reliability to guarantee timely transmission of monitored data. Considering mobile intelligences such as Automated Guided Vehicles (AGVs), within industrial scenarios, we propose a solution based on hybrid (fixed and mobile) industrial wireless sensor networks featured with a task-oriented model. The proposal includes a heuristic modeling method adopted to assign tasks from definite orders which will be sent to the controller, and a collaborative routing algorithm exploiting the AGVs mobility on specific trajectories. Experiments have shown that, using mobility features of the AGVs, the integrated solution can promptly repair the network when a node and the relative link fail or the detected quality is low, significantly reducing the energy consumption of wireless nodes and data communication delay, thus improving the overall throughput and reliability of industrial IoT systems.

Phosphate-stabilized amorphous calcium carbonate (ACCP) has excellent biocompatibility, bioactivity, and biodegradability, and can be easily synthesized and stored. However, unmodified ACCP, as a controlled drug release carrier, decomposes rapidly in an acidic environment and highly depends on the system's pH value, which can not meet the need for long-term release of active substances, thus limiting its application scope. To realize the specific pH responsiveness of ACCP nanoparticles, we designed and synthesized monodisperse sodium alginate/ACCP (Alginate/ACCP) composite nanoparticles in this paper. After ultrasonic treatment, nanoparticles with an average particle size less than 200 nm could form stable water dispersion that could be dispersed for up to 10 d. Based on the specific pH sensitivity of sodium alginate, the drug-controlled release performance of composite nanoparticles and the therapeutic effect of drug-loaded nanoparticles on A549 cancer cells were studied. The results indicated that under the same pH condition, the curcumin (Cur) release rate of composite nanoparticles gradually decreased with sodium alginate addition. When the dosage of sodium alginate was 1.0 mg ml-1, the cumulative drug release rate of nanoparticles in 40 h was only about 35%. Besides, the drug-loaded nanoparticles showed the excellent killing ability of cancer cells, and the survival rate of cancer cells decreased in a concentration-dependent manner. Therefore, through reasonable optimization design, we can synthesize composite nanoparticles with excellent sustained-release properties to provide a new strategy for cancer cells' long-term treatment.

With the construction of interconnected power grid and the rapid development of clean energy, the frequency problem of power system is becoming increasingly prominent. The problem of ultra-low frequency oscillation affects the stability of system frequency. In order to analyze the frequency regulation characteristics of the system, it is necessary to study the local active power control link and stability calculation model of the hydropower plant computer monitoring system. In this paper, the influence of the local active power control link of the monitoring system on the system frequency small signal stability is studied, and the model is built in the simulation program. Through the simulation of 4-machine-2 regional power grid, the influence characteristics of local active power control on frequency dynamic damping level are verified. In the example of large power grid, the coordination between the local active power control of the monitoring system and the speed regulation system of hydropower units is comprehensively considered, the suggestion of coordination of multi-level frequency modulation resources to system frequency regulation is put forward.

Cell-Free massive multiple-input multiple-output (MIMO), which is expected to become one of the core technologies of the B5G and 6G, has attracted more and more researchers' attention. This paper considers a Cell-Free Massive MIMO system with multiple antennas at access points (AP) and a single antenna at users. At the same time, this system applies AP selection technology. To reduce pilot contamination, this paper proposes a new pilot assignment algorithm based on weighted counting, which uses the user's prior geographic information to maximize the pilot reuse weighted distance, and also considers pilot power control in the pilot training phase and AP power control in the downlink phase to verify system performance. Simulation results show that the algorithm can significantly improve system performance.

Particle swarm optimization (PSO) attracts much attention due to its ability in solving complex practical engineering problems effectively. To further improve its performance, a heterogeneous particle swarm optimizer (HPSO) is proposed in this work. Five widely used benchmark functions are selected to test its efficiency. Furthermore, five state-of-the-art improved PSO variants are selected for a comparisons purpose. The results demonstrate that HPSO is better than the other five algorithms. A logistics problem in aircraft manufacturing is then studied and solved. The results show HPSO's superiority over its tested PSO variants.

Wellbore integrity analysis should consider the cement setting process in a confined downhole environment, noting that cement is initially a liquid that becomes a solid. In our study, the state of stress of cement specimens is measured during cure from a liquid to a solid at laboratory simulated downhole conditions. We apply accurate control of axial stress, confining pressure, and pore pressure inside cement specimens during the entire setting process combined with strain gauges mounted on the outer surface of the steel pipe to measure the cement's state of stress during the setting process. The setup allows multiple experimental conditions to be investigated, including constant axial stress, constant axial displacement, drained and undrained conditions. Different controlling conditions represent different field scenarios since the process of cement setting in the downhole situations is a highly complex process that depends on the in-situ condition, formation lithology, cement slurry composition, mud cake composition, drill bit type, etc. In this work, the Class-G cement slurry is cured under constant axial stress, confining pressure, and undrained conditions. This represents a field condition where the top of the cement can drop during setting, the vertical component of cement weight is not significantly affected by bonding, and the formation is quite impermeable with a very difficult fluid exchange between formation and cement. Our results show that under such a scenario, no significant pressure drop occurs after seven days of the setting process, and the cement initial total stress is close to its hydrostatic pressure.

Uncertainty of data is inherent in many important applications. Effectively extracting valuable information to enable better decisions is important but not a trivial task over uncertain data. We have witnessed a great deal of significant researches for this purpose, such as top-k queries, skyline queries and dominated top-k queries. As for uncertainty, the common challenge that those researches face is to answer the ranking methods in consideration of user's function score and probability. In this paper, we propose a novel ranking method to select reliable and worthy results. In our method the coordinated and balanced degree of score and probability is also an evaluation target. After constructing of balance degree, we design the balanced dominating top-k query semantic and effective algorithms to identify the top-k answers. Comprehensive experiments with both real and synthetic data sets demonstrate the effectiveness and efficiency of our proposed approach.

In recent years, the individualized demand of customers brings small batches and diversification of orders towards enterprises. The application of enabling technologies in the factory, such as the industrial Internet of things (IIoT) and cloud manufacturing (CMfg), enhances the ability of customer requirement automatic elicitation and the manufacturing process control. The job shop scheduling problem with a random job arrival time dramatically increases the difficulty in process management. Thus, how to collaboratively schedule the production and logistics resources in the shop floor is very challenging, and it has a fundamental and practical significance of achieving the competitiveness for an enterprise. To address this issue, the real-time model of production and logistics resources is built firstly. Then, the task entropy model is built based on the task information. Finally, the real-time self-adaption collaboration of production and logistics resources is realized. The proposed algorithm is carried out based on a practical case to evaluate its effectiveness. Experimental results show that our proposed algorithm outperforms three existing algorithms.

Most chemotherapeutic drugs commonly suffer from low aqueous solubility that can potentially limit drugs absorption. Drug nanomerization is an advanced approach to overcoming their poor water-solubility. In this study, class I hydrophobin recombinant HGFI (rHGFI)-based curcumin (Cur) nanoparticles (rHGFI-Cur) were prepared by freeze-drying method. The rHGFI-Cur nanocomposites were characterized by contact angle, transmission electron microscopy, fluorescence microscopy and dynamic light scattering. The results showed that rHGFI could lead to the wettability conversion and stability improved of Cur in water. X-ray photoelectron spectroscopy and Fourier transform infrared suggested that rHGFI could non-covalently bind to Cur to render them hydrophilic through hydrophobic forces. Additionally, drug release and cytotoxicity assays illustrated that rHGFI-Cur nanoparticles could facilitate Cur release and exhibited higher cytotoxicity than free Cur for human esophageal cancer cells TE-1. Thus, it suggested that rHGFI has a great potential application for hydrophobic drug delivery without toxicity.[Formula: see text].

This article proposes a novel improved adaptive event-triggered (AET) control algorithm for networked Takagi-Sugeno (T-S) fuzzy systems with asynchronous constraints. First, taking the limited bandwidth of the network into consideration, an improved AET mechanism is proposed to save the communication resource. Superior to the existing event-triggered mechanism, the improved AET scheme introduces two adjusting parameters, which further contribute to the economization of the communication resource. Second, with consideration of asynchronous premise variables, a reconstructed approach is applied to synchronize the time scales of membership functions of the fuzzy system and the fuzzy controller. Third, to derive a less conservative sufficient condition for the controller design, a new augmented Lyapunov-Krasovskii functional with event-triggered information and triple integral terms is constructed. Meanwhile, by applying a Bessel-Legendre inequality and extended reciprocally convex matrix inequality together, a new control algorithm is derived with less conservatism. Finally, simulations on a cart-damper-spring system are implemented to evaluate and verify the performance and advantages of the proposed algorithm.

A novel magneto-rheological variable stiffness and damping torsional vibration absorber (MR-VSDTVB) is proposed, fabricated and tested. According to the test data, the control model of MR-VSDTVB is established. Meanwhile, the analysis of the multi-degree-of-freedom model of the powertrain system provides the key frequency and the rotating velocity of the torsional vibration control of the powertrain system and further determines the installation position and structural parameters of MR-VSDTVB. Besides, a human-simulated intelligent controller (HSIC) is developed and numerical simulation of the powertrain system with MR-VSDTVB is carried out. Ultimately, the results verify the effectiveness of the powertrain system with MR-VSDTVB and the semi-active HSIC algorithm on the torsional vibration control.

With the increasing rate of traffic accidents, driving safety has attracted attentions of researchers from academy and industry. Nowadays, most of the traffic accidents are related to abnormal driving operations. This chapter proposes a novel method aiming to recognize the basic driving operations. The method uses smart cushion for data collection and deep neural network (DNN) algorithm for classification. In particular, the proposed method can recognize five driving operations: normal driving, stepping on the brakes, stepping on the accelerator, stepping on the clutch, rotating the steering wheel. A smart cushion that contains four pressure sensors is used to collect the driving-operations-related data. The defined processing workflow involves: (1) a preprocessing phase where a digital filter is used for data noise reduction; (2) a feature extraction phase based on a sliding time window technique able to extract time-based features; (3) a merging phase where features are combined together; (4) a phase where principal component analysis is executed before classification to reduce high-dimensionality of combined features; (5) application of the defined DNN for classification. Using our proposed DNN, basic driving operations can be therefore recognized. The experimental results show that the proposed driving operations recognition method achieves an average recognition accuracy rate of about 97%.

In this paper, the runaway transient process in a bulb turbine has been investigated by adopting commercial CFD code ANSYS CFX, and transient characteristics in the process have been examined and analyzed in detail. The results show that the predicted maximal runaway rotational speed and flow rate of the turbine are in close agreement with experimental data. During transient process, both the flow rate and rotational speed are rising with time, leading to an increase in both axial and circumferential velocities at the runner outlet. The velocity ratio between them has been diminished greatly at the draft tube inlet, inducing a spiral vortex rope growing with time. The cavitation will shorten the duration and reduce the maximal rotational speed of the runaway process. The runner blade pressure surface is much more critical to cavitation than the suction surface. The amplitude of pressure fluctuation in the runaway process is increasing in the main flow direction. Furthermore, the amplitude of pressure fluctuation reaches up to over 100% of the working head in the draft tube, considerably threatening the safe operation of the turbine.

In the study, amorphous calcium phosphate (ACP) nanoparticles were prepared by the coprecipitation method to optimize release profile of curcumin (Cur) and avoid burst releases, which were used to overcome the weakness of Cur, such as poor chemical stability and bioavailability. To find the best preparation condition, the influence of reaction concentration, temperature, time and pH on crystal phase of the samples was investigated by XRD and FTIR. The results showed that amorphous calcium phosphate (ACP) was obtained, when pH value and the concentration of PO43− were 8 and 0.024 mM, prepared at 30 °C for 10 min. In vitro drug release assay, ACP nanoparticles showed high loading capacity of Cur and favorable pH-responsive drug release properties. Furthermore, the Cur-load ACP nanoparticles showed an excellent ability to scavenge free radical and damage A549 cells, resulting in a high antioxidant properties and low cell viability. Therefore, the as-prepared nanoparticles have promising applications in the food and biomedical fields.

In a smart factory environment, a much larger amount of data are transmitted in the workshop networks bringing big challenges to data transfer capability and energy usage efficiency. In the workshop, two main networks, i.e., wired/wireless fieldbus networks and wireless sensor networks, are usually used to collect and transmit data separately; thus, this paper proposes a mobile and hierarchical data transmission architecture to integrate these two networks also taking advantages from the existing mobile intelligence in smart factories, such as automatic guided vehicles (AGVs), to implement a novel data and materials delivery scheme well suited for modern industrial wireless sensor networks (IWSNs). Simulation experiments demonstrated how the proposed approach, running within the IWSN, significantly increases data delivery efficiency along with achieving better energy usage, by 4 times, with respect to the separated networks without any mobile intelligence support.