Showing papers by "University of Macau published in 2016"
TL;DR: In this paper, the authors present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macro-autophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes.
For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy.
Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.
5,187 citations
TL;DR: This review focuses on the biotransformation of polyphenols by gut microbiota, modulation of gut microbiota bypolyphenols, and the effects of these two-way mutual interactions on polyphenol bioavailability, and ultimately, human health.
Abstract: As of late, polyphenols have increasingly interested the scientific community due to their proposed health benefits. Much of this attention has focused on their bioavailability. Polyphenol–gut microbiota interactions should be considered to understand their biological functions. The dichotomy between the biotransformation of polyphenols into their metabolites by gut microbiota and the modulation of gut microbiota composition by polyphenols contributes to positive health outcomes. Although there are many studies on the in vivo bioavailability of polyphenols, the mutual relationship between polyphenols and gut microbiota is not fully understood. This review focuses on the biotransformation of polyphenols by gut microbiota, modulation of gut microbiota by polyphenols, and the effects of these two-way mutual interactions on polyphenol bioavailability, and ultimately, human health.
527 citations
TL;DR: The mechanism by which EMT contributes to drug resistance in cancer cells is described and new advances in research in EMT-associated drug resistance are summarized.
Abstract: Epithelial–mesenchymal transition (EMT) is known to play an important role in cancer progression, metastasis and drug resistance. Although there are controversies surrounding the causal relationship between EMT and cancer metastasis, the role of EMT in cancer drug resistance has been increasingly recognized. Numerous EMT-related signaling pathways are involved in drug resistance in cancer cells. Cells undergoing EMT show a feature similar to cancer stem cells (CSCs), such as an increase in drug efflux pumps and anti-apoptotic effects. Therefore, targeting EMT has been considered a novel opportunity to overcome cancer drug resistance. This review describes the mechanism by which EMT contributes to drug resistance in cancer cells and summarizes new advances in research in EMT-associated drug resistance.
514 citations
TL;DR: A two-dimensional Logistic-adjusted-Sine map (2D-LASM) is proposed that has better ergodicity and unpredictability, and a wider chaotic range than many existing chaotic maps.
496 citations
TL;DR: An observer-based adaptive consensus tracking control strategy is developed for a class of high-order nonlinear multiagent systems, of which each follower agent is modeled in a semi-strict-feedback form.
Abstract: Combined with backstepping techniques, an observer-based adaptive consensus tracking control strategy is developed for a class of high-order nonlinear multiagent systems, of which each follower agent is modeled in a semi-strict-feedback form By constructing the neural network-based state observer for each follower, the proposed consensus control method solves the unmeasurable state problem of high-order nonlinear multiagent systems The control algorithm can guarantee that all signals of the multiagent system are semi-globally uniformly ultimately bounded and all outputs can synchronously track a reference signal to a desired accuracy A simulation example is carried out to further demonstrate the effectiveness of the proposed consensus control method
455 citations
TL;DR: A specific novel *L-PSO algorithm is proposed, using genetic evolution to breed promising exemplars for PSO, and under such guidance, the global search ability and search efficiency of PSO are both enhanced.
Abstract: Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanistic parallel superposition and research has shown that construction of superior exemplars in PSO is more effective. Hence, this paper first develops a new framework so as to organically hybridize PSO with another optimization technique for “learning.” This leads to a generalized “learning PSO” paradigm, the *L-PSO. The paradigm is composed of two cascading layers, the first for exemplar generation and the second for particle updates as per a normal PSO algorithm. Using genetic evolution to breed promising exemplars for PSO, a specific novel *L-PSO algorithm is proposed in the paper, termed genetic learning PSO (GL-PSO). In particular, genetic operators are used to generate exemplars from which particles learn and, in turn, historical search information of particles provides guidance to the evolution of the exemplars. By performing crossover, mutation, and selection on the historical information of particles, the constructed exemplars are not only well diversified, but also high qualified. Under such guidance, the global search ability and search efficiency of PSO are both enhanced. The proposed GL-PSO is tested on 42 benchmark functions widely adopted in the literature. Experimental results verify the effectiveness, efficiency, robustness, and scalability of the GL-PSO.
413 citations
TL;DR: In order to stabilize a class of uncertain nonlinear strict-feedback systems with full-state constraints, an adaptive neural network control method is investigated and it is proved that all the signals in the closed-loop system are semiglobal uniformly ultimately bounded and the output is well driven to follow the desired output.
Abstract: In order to stabilize a class of uncertain nonlinear strict-feedback systems with full-state constraints, an adaptive neural network control method is investigated in this paper. The state constraints are frequently emerged in the real-life plants and how to avoid the violation of state constraints is an important task. By introducing a barrier Lyapunov function (BLF) to every step in a backstepping procedure, a novel adaptive backstepping design is well developed to ensure that the full-state constraints are not violated. At the same time, one remarkable feature is that the minimal learning parameters are employed in BLF backstepping design. By making use of Lyapunov analysis, we can prove that all the signals in the closed-loop system are semiglobal uniformly ultimately bounded and the output is well driven to follow the desired output. Finally, a simulation is given to verify the effectiveness of the method.
404 citations
TL;DR: This Review outlines recent advances in the field of protein assembly and summarizes several strategies, including biotechnological strategies, chemical strategies, and combinations of these approaches, for manipulating proteins to self-assemble into desired nanostructures.
Abstract: Nature endows life with a wide variety of sophisticated, synergistic, and highly functional protein assemblies. Following Nature’s inspiration to assemble protein building blocks into exquisite nanostructures is emerging as a fascinating research field. Dictating protein assembly to obtain highly ordered nanostructures and sophisticated functions not only provides a powerful tool to understand the natural protein assembly process but also offers access to advanced biomaterials. Over the past couple of decades, the field of protein assembly has undergone unexpected and rapid developments, and various innovative strategies have been proposed. This Review outlines recent advances in the field of protein assembly and summarizes several strategies, including biotechnological strategies, chemical strategies, and combinations of these approaches, for manipulating proteins to self-assemble into desired nanostructures. The emergent applications of protein assemblies as versatile platforms to design a wide variety ...
386 citations
TL;DR: The rational design of a NMOF composed by hafnium (Hf(4+)) and tetrakis (4-carboxyphenyl) porphyrin (TCPP) is reported, which shows efficient clearance from the mouse body, minimizing concerns regarding their possible long-term toxicity.
349 citations
TL;DR: Using whole-genome sequencing, this work proposes an evolutionary scenario where the Satellite chromosome arose by a rare recombination event about 500,000 years ago and resolved the enigma of how such complex phenotypic differences can have a simple genetic basis.
Abstract: Leif Andersson and colleagues report the genome sequence of the ruff, a bird species with three male morphs with different reproductive strategies. Satellite and faeder morphs differ from the common independent morph by a 4.5-Mb inversion that occurred approximately 3.8 million years ago, and multiple genetic changes within this inverted region are associated with the satellite and faeder morphs. The ruff is a Palearctic wader with a spectacular lekking behavior where highly ornamented males compete for females1,2,3,4. This bird has one of the most remarkable mating systems in the animal kingdom, comprising three different male morphs (independents, satellites and faeders) that differ in behavior, plumage color and body size. Remarkably, the satellite and faeder morphs are controlled by dominant alleles5,6. Here we have used whole-genome sequencing and resolved the enigma of how such complex phenotypic differences can have a simple genetic basis. The Satellite and Faeder alleles are both associated with a 4.5-Mb inversion that occurred about 3.8 million years ago. We propose an evolutionary scenario where the Satellite chromosome arose by a rare recombination event about 500,000 years ago. The ruff mating system is the result of an evolutionary process in which multiple genetic changes contributing to phenotypic differences between morphs have accumulated within the inverted region.
327 citations
TL;DR: Flower-like copper cobaltite (CuCo2O4) nanosheets anchored on graphite paper have been synthesized using a facile hydrothermal method followed by a postannealing treatment and exhibit enhanced capacitance compared with previously reported supercapacitor electrodes.
Abstract: Flower-like copper cobaltite (CuCo2O4) nanosheets anchored on graphite paper have been synthesized using a facile hydrothermal method followed by a postannealing treatment. Supercapacitor electrodes employing CuCo2O4 nanosheets exhibit an enhanced capacitance of 1131 F g–1 at a current density of 1 A g–1 compared with previously reported supercapacitor electrodes. The CuCo2O4 electrode delivers a specific capacitance of up to 409 F g–1 at a current density of as high as 50 A g–1, and a good long-term cycling stability, with 79.7% of its specific capacitance retained after 5000 cycles at 10 A g–1. Furthermore, the as-prepared CuCo2O4 nanosheets on graphite paper can be fabricated as electrodes and used as enzymeless glucose sensors, which exhibit good sensitivity (3.625 μA μM–1 cm–2) and an extraordinary linear response ranging up to 320 μM with a low detection limit (5 μM).
TL;DR: This survey comprehensively compares each scheme in terms of accuracy, cost, scalability, and energy efficiency, and takes a first look at intrinsic technical challenges in both categories and identifies several open research issues associated with these new challenges.
Abstract: With the marvelous development of wireless techniques and ubiquitous deployment of wireless systems indoors, myriad indoor location-based services (ILBSs) have permeated into numerous aspects of modern life. The most fundamental functionality is to pinpoint the location of the target via wireless devices. According to how wireless devices interact with the target, wireless indoor localization schemes roughly fall into two categories: device based and device free. In device-based localization, a wireless device (e.g., a smartphone) is attached to the target and computes its location through cooperation with other deployed wireless devices. In device-free localization, the target carries no wireless devices, while the wireless infrastructure deployed in the environment determines the target’s location by analyzing its impact on wireless signals. This article is intended to offer a comprehensive state-of-the-art survey on wireless indoor localization from the device perspective. In this survey, we review the recent advances in both modes by elaborating on the underlying wireless modalities, basic localization principles, and data fusion techniques, with special emphasis on emerging trends in (1) leveraging smartphones to integrate wireless and sensor capabilities and extend to the social context for device-based localization, and (2) extracting specific wireless features to trigger novel human-centric device-free localization. We comprehensively compare each scheme in terms of accuracy, cost, scalability, and energy efficiency. Furthermore, we take a first look at intrinsic technical challenges in both categories and identify several open research issues associated with these new challenges.
TL;DR: This study demonstrates the use of NMOPs as a potential photothermal agent, which features excellent tumor-targeted imaging and therapeutic functions, together with rapid renal excretion behavior, the latter of which would be particularly important for future clinical translation of nanomedicine.
Abstract: Nanoscale metal-organic particles (NMOPs) are constructed from metal ions and organic bridging ligands via the self-assembly process. Herein, we fabricate NMOPs composed of Mn(2+) and a near-infrared (NIR) dye, IR825, obtaining Mn-IR825 NMOPs, which are then coated with a shell of polydopamine (PDA) and further functionalized with polyethylene glycol (PEG). While Mn(2+) in such Mn-IR825@PDA-PEG NMOPs offers strong contrast in T1-weighted magnetic resonance (MR) imaging, IR825 with strong NIR optical absorbance shows efficient photothermal conversion with great photostability in the NMOP structure. Upon intravenous injection, Mn-IR825@PDA-PEG shows efficient tumor homing together with rapid renal excretion behaviors, as revealed by MR imaging and confirmed by biodistribution measurement. Notably, when irradiated with an 808 nm laser, tumors on mice with Mn-IR825@PDA-PEG injection are completely eliminated without recurrence within 60 days, demonstrating the high efficacy of photothermal therapy with this agent. This study demonstrates the use of NMOPs as a potential photothermal agent, which features excellent tumor-targeted imaging and therapeutic functions, together with rapid renal excretion behavior, the latter of which would be particularly important for future clinical translation of nanomedicine.
TL;DR: WiHear is presented, which enables Wi-Fi signals to “hear” people talks within the radio range without deploying any devices and can simultaneously “ hear’ multiple people's talks leveraging MIMO technology.
Abstract: Recent literature advances Wi-Fi signals to “see” people's motions and locations. This paper asks the following question: Can Wi-Fi “hear” our talks? We present WiHear, which enables Wi-Fi signals to “hear” our talks without deploying any devices. To achieve this, WiHear needs to detect and analyze fine-grained radio reflections from mouth movements. WiHear solves this micro-movement detection problem by introducing Mouth Motion Profile that leverages partial multipath effects and wavelet packet transformation. Since Wi-Fi signals do not require line-of-sight, WiHear can “hear” people talks within the radio range. Further, WiHear can simultaneously “hear” multiple people's talks leveraging MIMO technology. We implement WiHear on both USRP N210 platform and commercial Wi-Fi infrastructure. Results show that within our pre-defined vocabulary, WiHear can achieve detection accuracy of 91 percent on average for single individual speaking no more than six words and up to 74 percent for no more than three people talking simultaneously. Moreover, the detection accuracy can be further improved by deploying multiple receivers from different angles.
TL;DR: A novel fuzzy adaptive tracking controller is constructed via backstepping technique, which guarantees that the tracking error converges to a neighborhood of the origin in the sense of probability and all the signals in the closed-loop system remain bounded in probability.
Abstract: In this paper, a fuzzy adaptive approach for stochastic strict-feedback nonlinear systems with quantized input signal is developed. Compared with the existing research on quantized input problem, the existing works focus on quantized stabilization, while this paper considers the quantized tracking problem, which recovers stabilization as a special case. In addition, uncertain nonlinearity and the unknown stochastic disturbances are simultaneously considered in the quantized feedback control systems. By putting forward a new nonlinear decomposition of the quantized input, the relationship between the control signal and the quantized signal is established, as a result, the major technique difficulty arising from the piece-wise quantized input is overcome. Based on fuzzy logic systems’ universal approximation capability, a novel fuzzy adaptive tracking controller is constructed via backstepping technique. The proposed controller guarantees that the tracking error converges to a neighborhood of the origin in the sense of probability and all the signals in the closed-loop system remain bounded in probability. Finally, an example illustrates the effectiveness of the proposed control approach.
TL;DR: F fuzzy logic system is introduced to approximate the unknown nonlinear dynamics, and adaptive high-gain observer is designed to estimate the unmeasured states and it is proved that all the signals in the multiagent systems are semiglobally uniformly ultimately bounded.
Abstract: In this paper, the consensus tracking control problem of second-order multiagent systems with unknown nonlinear dynamics, immeasurable states, and disturbances is investigated. The nonlinear dynamics in multiagent systems do not satisfy the matched condition. In this paper, fuzzy logic system is introduced to approximate the unknown nonlinear dynamics, and adaptive high-gain observer is designed to estimate the unmeasured states. Based on backstepping approach and Lyapunov theory, a new adaptive fuzzy distributed controller is proposed for each agent only using the information of itself and its neighbors. Then the consensus tracking is achieved under the designed distributed controller. Moreover, it is proved that all the signals in the multiagent systems are semiglobally uniformly ultimately bounded, and the consensus tracking error converges to a small neighborhood of the origin that can be designed as small as possible. Finally, the simulation result illustrates the effectiveness of the designed controller.
TL;DR: In this paper, vertically stacked bilayer spinel heterostructures constructed from hierarchical CuCo2O4/MnCo 2O4 on graphite paper were used as highly capable supercapacitor electrodes.
Abstract: Cobaltite systems with spinel structures are promising cathode materials for next-generation high-performance electrochemical capacitors because of their high electrochemical stability. However, increasing the mass loading of active materials without sacrificing the geometry of the nanostructures remains a challenge. In this study, we propose vertically stacked bilayer spinel heterostructures constructed from hierarchical CuCo2O4/MnCo2O4 on graphite paper as highly capable supercapacitor electrodes. A two-step hydrothermal method with post annealing treatment is used in the preparation of the heterostructures. The CuCo2O4/MnCo2O4 electrode delivers a remarkable specific capacitance of 1434 F g−1 at 0.5 A g−1, considerable high-rate capability (810 F g−1 at 15 A g−1), and an excellent cycling stability, maintaining 81.4% at 10 A g−1 after 5000 cycles. An electrochemical capacitor device operating at 1.6 V is also constructed using CuCo2O4/MnCo2O4 and graphene as positive and negative electrodes, respectively. The device shows a high energy density of 42.1 W h kg−1 at a power density of 400 W kg−1, as well as good cycling stability (88.4% retention after 10 000 cycles). The concept of stacking heteronanostructures can potentially enrich the electrochemical performance of metal oxides for next-generation electrochemical capacitors.
TL;DR: Attitude toward MOOCs and perceived behavioral control were significant determinants of intention to use them and Autonomous motivation was an antecedent for all three core constructs of the TPB, while controlled motivation acted as an antecesent only for subjective norms.
Abstract: At the start of a teaching revolution, Massive Open Online Courses (MOOCs) represent the latest stage in distance education, and offer open educational resources to students around the globe. With their growing popularity, this study examines the factors that influence students' decisions to use MOOCs. To integrate the theory of planned behavior (TPB) and the self-determination theory (SDT) as a research framework, 475 university students in China participated in a survey on the five constructs hypothesized to explain their intention to use MOOCs for learning. Data were analyzed using structural equation modeling. The results showed that attitude toward MOOCs and perceived behavioral control (PBC) were significant determinants of intention to use them. Autonomous motivation was an antecedent for all three core constructs of the TPB, while controlled motivation acted as an antecedent only for subjective norms. Implications of the findings are discussed. Attitude toward MOOCs significantly predicts the intention to use them.Perceived behavioral control (significantly predicts the intention to use MOOCs.Autonomous motivation was an antecedent for all three core constructs of TPB.Controlled motivation acted as an antecedent only for subjective norms.
TL;DR: It is suggested that, when watching videos that induce an emotional response, men often have more intense emotional experiences, whereas women have higher emotional expressivity, particularly for negative emotions.
Abstract: The present study investigated gender differences in both emotional experience and expressivity. Heart rate (HR) was recorded as an indicator of emotional experience while the participants watched 16 video clips that induced eight types of emotion (sadness, anger, horror, disgust, neutrality, amusement, surprise, and pleasure). We also asked the participants to report valence, arousal, and motivation as indicators of emotional expressivity. Overall, the results revealed gender differences in emotional experience and emotional expressivity. When watching videos that induced anger, amusement, and pleasure, men showed larger decreases in HR, whereas women reported higher levels of arousal. There was no gender difference in HR when the participants watched videos that induced horror and disgust, but women reported lower valence, higher arousal, and stronger avoidance motivation than did men. Finally, no gender difference was observed in sadness or surprise, although there was one exception-women reported higher arousal when watching videos that induced sadness. The findings suggest that, when watching videos that induce an emotional response, men often have more intense emotional experiences, whereas women have higher emotional expressivity, particularly for negative emotions. In addition, gender differences depend on the specific emotion type but not the valence.
TL;DR: This work presents a meta-analysis of the putative mechanisms behind the Evolutionary Relationship of the Putative SmCPS1- and SmC PS2- Gene Clusters and co-Expression Analysis of CYPs with SmCps1 and 437 Putative CYPs in the S. miltiorrhiza Genome.
TL;DR: In this article, a mesoscopic hole transporter with active areas of 31 cm2 and 70 cm2 with power conversion efficiencies of 10.46% and 10.74% was fabricated using scalable printing processes.
Abstract: Monolithic perovskite modules with active areas of 31 cm2 and 70 cm2 and with power conversion efficiencies (PCE) of 10.46% and 10.74%, respectively, were fabricated using scalable printing processes. An ambient stability of more than 2000 h with less than a 5% reduction in efficiency is demonstrated. The electrical quality of the mesoscopic hole transporter and its facilitation of efficient infiltration is paramount.
TL;DR: A novel lightweight feature selection is proposed designed particularly for mining streaming data on the fly, by using accelerated particle swarm optimization (APSO) type of swarm search that achieves enhanced analytical accuracy within reasonable processing time.
Abstract: Big Data though it is a hype up-springing many technical challenges that confront both academic research communities and commercial IT deployment, the root sources of Big Data are founded on data streams and the curse of dimensionality. It is generally known that data which are sourced from data streams accumulate continuously making traditional batch-based model induction algorithms infeasible for real-time data mining. Feature selection has been popularly used to lighten the processing load in inducing a data mining model. However, when it comes to mining over high dimensional data the search space from which an optimal feature subset is derived grows exponentially in size, leading to an intractable demand in computation. In order to tackle this problem which is mainly based on the high-dimensionality and streaming format of data feeds in Big Data, a novel lightweight feature selection is proposed. The feature selection is designed particularly for mining streaming data on the fly, by using accelerated particle swarm optimization (APSO) type of swarm search that achieves enhanced analytical accuracy within reasonable processing time. In this paper, a collection of Big Data with exceptionally large degree of dimensionality are put under test of our new feature selection algorithm for performance evaluation.
TL;DR: In this paper, the authors examine how host country institutional development influences innovation performance of internationalized emerging market enterprises (EMEs), and they find that although host-country institutional development on average enhances innovation performance, such effects are more pronounced for EMEs with strong absorptive capacity and for those diversifying into a larger number of countries.
TL;DR: Li et al. as mentioned in this paper reported a 3D hierarchical porous flower-like NiAl-LDH grown on nickel foam (NF) through a liquid-phase deposition method as a high-performance binder-free electrode for energy storage.
TL;DR: This paper studies an adaptive neural control for nonlinear multiple-input multiple-output systems in interconnected form and removes an important assumption imposed on the previous works that the bounds of the parameters in PI hysteresis are known.
Abstract: This paper studies an adaptive neural control for nonlinear multiple-input multiple-output systems in interconnected form The studied systems are composed of ${N}$ subsystems in pure feedback structure and the interconnection terms are contained in every equation of each subsystem Moreover, the studied systems consider the effects of Prandtl–Ishlinskii (PI) hysteresis model It is for the first time to study the control problem for such a class of systems In addition, the proposed scheme removes an important assumption imposed on the previous works that the bounds of the parameters in PI hysteresis are known The radial basis functions neural networks are employed to approximate unknown functions The adaptation laws and the controllers are designed by employing the backstepping technique The closed-loop system can be proven to be stable by using Lyapunov theorem A simulation example is studied to validate the effectiveness of the scheme
TL;DR: In this paper, a 1D core-shell structure BaTiO3@Al2O3 nanofibers (BT@Al 2O3 nfs) was synthesized via coaxial electrospinning.
Abstract: Inorganic/polymer nanocomposites, using one-dimensional (1D) core–shell structure BaTiO3@Al2O3 nanofibers (BT@Al2O3 nfs) as fillers and poly(vinylidene fluoride) (PVDF) as the polymer matrix, have been prepared. The core–shell structure BT@Al2O3 nfs have been synthesized via coaxial electrospinning. The breakdown strength (Eb) and discharged energy density of the nanocomposites can be significantly improved by creating an insulating Al2O3 shell layer with moderate dielectric constant on the surfaces of BT nanofibers to form a moderate interfacial area. The Al2O3 shell layer could effectively confine the mobility of charge carriers, which reduces energy loss by reducing the Maxwell–Wagner–Sillars (MWS) interfacial polarization and space charge polarization between the fillers and the polymer matrix. As a result, the nanocomposite films filled with 5 vol% BT@Al2O3 nfs exhibit a excellent discharge energy density of 12.18 J cm−3 at 400 MV m−1, which is ≈254% over bare PVDF (4.8 J cm−3 at 350 MV m−1) and ≈1015% greater than the biaxially oriented polypropylenes (BOPP) (≈1.2 J cm−3 at 640 MV m−1). The work here indicates that this promising state-of-the-art method of preparing high energy density nanocomposites can be used in the next generation of dielectric capacitors.
TL;DR: A new feature input space is proposed and an LBP-like descriptor that operates in the local line-geometry space is defined, thus proposing a new image descriptor, local line directional patterns (LLDP).
TL;DR: Results displayed that the α-GOM2 may be utilized as an potential adsorbent for removing and separating Th(IV)/U(VI) ions from aqueous solutions.
TL;DR: This paper investigates a practical variant of the vehicle routing problem (VRP), called VRP with simultaneous delivery and pickup and time windows (VRPSDPTW), in the logistics industry and shows that MOLS outperforms MOMA in most of instances.
Abstract: This paper investigates a practical variant of the vehicle routing problem (VRP), called VRP with simultaneous delivery and pickup and time windows (VRPSDPTW), in the logistics industry. VRPSDPTW is an important logistics problem in closed-loop supply chain network optimization. VRPSDPTW exhibits multiobjective properties in real-world applications. In this paper, a general multiobjective VRPSDPTW (MO-VRPSDPTW) with five objectives is first defined, and then a set of MO-VRPSDPTW instances based on data from the real-world are introduced. These instances represent more realistic multiobjective nature and more challenging MO-VRPSDPTW cases. Finally, two algorithms, multiobjective local search (MOLS) and multiobjective memetic algorithm (MOMA), are designed, implemented and compared for solving MO-VRPSDPTW. The simulation results on the proposed real-world instances and traditional instances show that MOLS outperforms MOMA in most of instances. However, the superiority of MOLS over MOMA in real-world instances is not so obvious as in traditional instances.
TL;DR: In this article, the authors comprehensively review the recent development on novel strategies to design photocatalysts and novel nanomaterials for efficient production of hydrogen is comprehensively reviewed based on fundamental principles, including codoping, hydrogenation, defect engineering, sensitization, formation of heterojunction, metal decoration, band-edge-state modification, and novel designs of cell structures.
Abstract: As an energy carrier, hydrogen has been extensively studied to satisfy the increasing demand on green energy. Efficiently producing hydrogen from water under sunlight is one of the challenging and important topics in hydrogen energy technology. Photocatalyst plays a critical role for the photo-production of hydrogen from water. It is essential to design novel photocatalysts with enhanced efficiency for the increasing demand on energy. In this paper, recent development on novel strategies to design photocatalysts and novel nanomaterials for efficient production of hydrogen is comprehensively reviewed based on fundamental principles. The strategies, including codoping, hydrogenation, defect engineering, sensitization, formation of heterojunction, metal decoration, band-edge-states modification, and novel designs of cell structures (tandem cell), are systematically discussed. Nanomaterials, including oxides (such as TiO 2 , Ta 2 O 5 , Fe 2 O 3 and SrTiO 3 ) and nitrides (such as GaN, graphitic carbon nitride, and Ta 2 N 3 ), are investigated. It is shown that these strategies can generally apply to all of materials, such as oxide and nitride semiconductors. It is believed that maximal conversion efficiency could be achieved by optimizing the electronic structures of photocatalysts and engineering the structures of cells.