Search

Detecting oriented objects along with estimating their rotation information is one crucial step for image analysis, especially for remote sensing images. Despite that many methods proposed recently have achieved remarkable performance, most of them directly learn to predict object directions under the supervision of only one (e.g., the rotation angle) or a few (e.g., several coordinates) groundtruth (GT) values individually. Oriented object detection would be more accurate and robust if extra constraints, with respect to proposal and rotation information regression, are adopted for joint supervision during training. To this end, we propose a mechanism that simultaneously learns the regression of horizontal proposals, oriented proposals, and rotation angles of objects in a consistent manner, via naive geometric computing, as one additional steady constraint. An oriented center prior guided label assignment strategy is proposed for further enhancing the quality of proposals, yielding better performance. Extensive experiments on six datasets demonstrate the model equipped with our idea significantly outperforms the baseline by a large margin and several new state-of-the-art results are achieved without any extra computational burden during inference. Our proposed idea is simple and intuitive that can be readily implemented. Source codes are publicly available at: https://github.com/wangWilson/CGCDet.git.

Purpose: The present work attempts to propose a suspension vibration isolator with both diagonal dampers and inerters and investigates analytically its dynamic characteristics, laying the foundation for its engineering application. Methods: A dynamic equation of the suspension vibration isolator with both diagonal dampers and inerters is formulated in terms of dimensionless relative displacements. The harmonic balance method is used to calculate the steady-state responses to harmonic base excitations. The calculations yield the amplitude–frequency responses of the conventional suspension vibration isolator, and the suspension vibration isolators with diagonal dampers only and with both diagonal dampers and inerters, respectively. The outcomes are validated by the numerical solutions via direct integrations. The results in terms of dimensionless relative displacements are translated into those in terms of dimensionless absolute displacement for the practical sake. The backbone curves and the amplitude–frequency responses are examined for different system parameters. The stabilities and the transmissibility of the steady-state responses are determined. Results and Conclusion: The investigation shows that the diagonal inerter can reduce the peak responses of suspension vibration isolators and widen the vibration isolation frequency band.

Lossy image compression is a fundamental technology in media transmission and storage. Variable-rate approaches have recently gained much attention to avoid the usage of a set of different models for compressing images at different rates. During the media sharing, multiple re-encodings with different rates would be inevitably executed. However, existing Variational Autoencoder (VAE)-based approaches would be readily corrupted in such circumstances, resulting in the occurrence of strong artifacts and the destruction of image fidelity. Based on the theoretical findings of preserving image fidelity via invertible transformation, we aim to tackle the issue of high-fidelity fine variable-rate image compression and thus propose the Invertible Continuous Codec (I2C). We implement the I2C in a mathematical invertible manner with the core Invertible Activation Transformation (IAT) module. I2C is constructed upon a single-rate Invertible Neural Network (INN) based model and the quality level (QLevel) would be fed into the IAT to generate scaling and bias tensors. Extensive experiments demonstrate that the proposed I2C method outperforms state-of-the-art variable-rate image compression methods by a large margin, especially after multiple continuous re-encodings with different rates, while having the ability to obtain a very fine variable-rate control without any performance compromise.

Purpose: To improve the ability of energy harvester, a Helmholtz–Duffing oscillator with nonlinear capacitance is considered, which has an asymmetric characteristic. In this paper, we investigates the effect of potential function asymmetries on the dynamic behaviors under harmonic excitation. Method: The electromechanical coupling governing equations of Helmholtz–Duffing energy harvester is established. Then its dynamic response in the region of the primary resonance is sought by the harmonic balance method. Results: The performances of the presented asymmetric nonlinear primary resonance energy harvester and the linear stiffness system are compared. Results clearly demonstrate an improved bandwidth over a case which does not involve an asymmetric potential energy function. Conclusion: It is found that multiple-valued steady-state solutions of frequency-response equation can exist, indicating that the jump phenomenon occurs. Besides, the amplitude–frequency response curves have double-jumping phenomena by the bend, first to the left and then to the right. The influence of the stiffness parameters on the shape of the frequency-response curves is also discussed. It is observed that different shapes of frequency-response curves can exist. The approximate analytical outcomes are in good agreement with the numerical results.

Recently, a privacy-preserving technique called Privacy-Preserving Matrix Transformation (PPMT) is widely used to construct efficient privacy-preserving Verifiable (outsourced) Computation (VC) protocols for specific functions. This technique is first proposed and formalized by Salinas et al. in 2015, and it enjoys provable privacy and high efficiency. Although it seems that Salinas et al.'s PPMT scheme and the further modified scheme are elegant, we still need to take a step back and precisely discuss whether the PPMT schemes are suitable choices for VC protocols. Since Salinas et al. gave two concrete PPMT schemes to achieve the matrix-related VC in data protection and proved that their schemes are private (in terms of indistinguishability), and Zhou et al. devised a new type of PPMT scheme for the same purpose, we focus on exploring privacy of these three types of PPMT schemes. In this article, to achieve our object, we first propose the concept of a linear distinguisher and two constructions of the linear distinguisher algorithms. In particular, the linear distinguisher is a polynomial-time algorithm employed by an adversary to explore the privacy property of a cryptographic primitive. Then, we take these three PPMT schemes (including Salinas et al.'s original work, Yu et al.'s generalization and Zhou et al.'s variant) as targets and analyze their privacy property by letting an adversary make use of our linear distinguisher algorithms. The analysis results show that all these three types of transformations do not hold privacy even against passive eavesdropping (i.e., a ciphertext-only attack), and subsequently, the privacy-preserving VC protocols, based on any of these PPMT schemes, also do not hold the same privacy.

Text generation is a key component of many natural language tasks. Motivated by the success of generative adversarial networks (GANs) for image generation, many text-specific GANs have been proposed. However, due to the discrete nature of text, these text GANs often use reinforcement learning (RL) or continuous relaxations to calculate gradients during learning, leading to high-variance or biased estimation. Furthermore, the existing text GANs often suffer from mode collapse (i.e., they have limited generative diversity). To tackle these problems, we propose a new text GAN model named text feature GAN (TFGAN), where adversarial learning is performed in a continuous text feature space. In the adversarial game, GPT2 provides the “true” features, while the generator of TFGAN learns from them. TFGAN is trained by maximum likelihood estimation on text space and adversarial learning on text feature space, effectively combining them into a single objective, while alleviating mode collapse. TFGAN achieves appealing performance in text generation tasks, and it can also be used as a flexible framework for learning text representations.

To support secure data mining and privacy-preserving computation, partial access and selective computation on encrypted data are desirable. Functional encryption (FE) is a new paradigm of public-key encryption and allows authorized users to compute specific functions on encrypted data without knowing the data. However, in some FE schemes, a trusted central authority (CA) is required to generate secret keys for users according to the description of functions. In this paper, to reduce trust on the CA and protect users’ privacy, a privacy-preserving decentralized FE for inner product (PPDFEIP) scheme is proposed where multiple authorities co-exist and work independently without any interaction. Especially, to resist collusion attacks, all secret keys of the same user are tied to his/her global identifier (GID), but authorities cannot know any information of the GID even if they collaborate. We formalize the definition and security model of our PPFEIP scheme, and propose a concrete construction. Furthermore, the proposed scheme is implemented and evaluated. Finally, the security of our PPDFEIP scheme is reduced to well-known complexity assumptions. The novelty is to reduce trust on the CA, protect users’ privacy and enable authorized users to compute inner product on encrypted data without compromising confidentiality.

Single-image rain streaks’ removal has attracted great attention in recent years. However, due to the highly visual similarity between the rain streaks and the line pattern image edges, the over-smoothing of image edges or residual rain streaks’ phenomenon may unexpectedly occur in the deraining results. To overcome this problem, we propose a direction and residual awareness network within the curriculum learning paradigm for the rain streaks’ removal. Specifically, we present a statistical analysis of the rain streaks on large-scale real rainy images and figure out that rain streaks in local patches possess principal directionality. This motivates us to design a direction-aware network for rain streaks’ modeling, in which the principal directionality property endows us with the discriminative representation ability of better differing rain streaks from image edges. On the other hand, for image modeling, we are motivated by the iterative regularization in classical image processing and unfold it into a novel residual-aware block (RAB) to explicitly model the relationship between the image and the residual. The RAB adaptively learns balance parameters to selectively emphasize informative image features and better suppress the rain streaks. Finally, we formulate the rain streaks’ removal problem into the curriculum learning paradigm which progressively learns the directionality of the rain streaks, rain streaks’ appearance, and the image layer in a coarse-to-fine, easy-to-hard guidance manner. Solid experiments on extensive simulated and real benchmarks demonstrate the visual and quantitative improvement of the proposed method over the state-of-the-art methods.

Purpose: The effects of glue layers are regarded as the stiffness and damping of laminated circular plates. An energy harvester consisting of a concentrated mass and a piezoelectric laminated circular plate is investigated with the account for the glue layers. Methods: The resonant amplitudes and frequencies are determined via the frequency sweep experiments. To account the adhesive effects, the force surface method is employed to identify the restoring and damping force of the glued laminated plate in a simplified one and half degree-of-freedom system, and the resulting force is fitted by a combination of hyperbolic tangent and trigonometric functions. The model with the nonlinear restoring and damping force is analyzed via the harmonic balance method. The outcomes of the voltage-frequency response curves are supported by the experiment results. Results: The results show that only under small excitation the frequencies can be well predicted by the plate theory model without the glue layers and the differences increase with the excitation. The investigation reveals that the glue layers change mainly the stiffness rather than the damping. Conclusions: The model with the nonlinear restoring and damping force can predict the fundamental resonant amplitudes and frequencies measured by experiments well.

Combining a fog layer to aggregate and process data for smart grids is a straightforward approach, yet it inevitably leads to trust issues and audition difficulty. Most existing data-sharing architectures did not consider the copious meter–fog communication and fog–cloud bulk data transmission simultaneously, or they relay the trustworthiness of the fog nodes on a single center. In this article, we design a meter–fog–cloud-blockchain data-sharing architecture for smart grids where the fog nodes are not only data relay stations but also semitrusted local data processing points, and the dual blockchains are responsible for device key management and data integrity audit, respectively. Moreover, a certificateless aggregate signcryption between fog and smart meters is designed, and the data sharing between servers is based on an authenticated key agreement mechanism to achieve optimal efficiency overall. Detailed security proofs are demonstrated and performance results show the practicality and efficiency of our data-sharing scheme.

Temperature is a key factor affecting the safety of the Lithium-ion (Li-ion) battery. Therefore, real-time thermal fault diagnosis is becoming more and more prominent, as battery faults can lead to local overheating and thermal runaway in severe cases. This article proposes a Chebyshev–Galerkin-based thermal fault detection and localization framework for the pouch-type Li-ion battery under limited sensing. First, the Chebyshev function is used to construct the spatial basis functions with global and orthonormal properties. Under the time–space (T-S) separation framework, the time coefficients can be derived through the Galerkin method using six sensors. Then, by decomposing the time coefficients using the independent component analysis, the temporal and spatial reference statistics can be formed for real-time fault detection. Finally, considering the detected fault snapshots, the thermal fault location can be identified by finding the maximum contributed position through T-S synthesis. Simulations and experiments demonstrate the effectiveness of the proposed method.

Privacy-preserving Verifiable (outsourced) Computation (PVC) for face recognition is a significant research topic in the information security community. Recently, an efficient elementary matrices masking-based PVC protocol for face recognition has been published in IEEE Transactions on Dependable and Secure Computing (Ren et al. 2023). In this article, we analyze the privacy property of this protocol, and demonstrate that the output distribution of the problem generation algorithm in this protocol is not computationally indistinguishable from the uniform distribution over a matrix set, which breaks the original consequence (see Theorem 1). We introduce a formal definition of a privacy model for a PVC protocol and prove that the targeted PVC protocol does not hold privacy under this model. We then present experimental results to support our theoretical analyses.

Cancer therapies based on energy conversion, such as photothermal therapy (PTT, light-to-thermal energy conversion) and photodynamic therapy (PDT, light-to-chemical energy conversion) have attracted extensive attention in preclinical research. However, the PTT-related hyperthermia damage to surrounding tissues and shallow penetration of PDT-applied light prevent further advanced clinical practices. Here, we developed a thermoelectric therapy (TET) based on thermoelectric materials constructed p-n heterojunction (SrTiO3/Cu2Se nanoplates) on the principle of light-thermal-electricity-chemical energy conversion. Upon irradiation and natural cooling-induced the temperature gradient (35–45 oC), a self-build-in electric field was constructed and thereby facilitated charges separation in bulk SrTiO3and Cu2Se. Importantly, the contact between SrTiO3(n type) and Cu2Se (p type) constructed another interfacial electric field, further guiding the separated charges to re-locate onto the surfaces of SrTiO3and Cu2Se. The formation of two electric fields minimized probability of charges recombination. Of note, high-performance superoxide radicals and hydroxyl radicals’ generation from O2and H2O under catalyzation by separated electrons and holes, led to intracellular ROS burst and cancer cells apoptosis without apparent damage to surrounding tissues. Construction of bulk and interfacial electric fields in heterojunction for improving charges separation and transfer is also expected to provide a robust strategy for diverse applications.

We developed a 9.38‐inch transparent Micro‐LED display with 114 PPI and 70% transmittance. The prototype display shows high transmittance and high brightness through innovative pixel design layout and film layer stacking structure.

ABSTRACTIn the long process of human evolution, the Intestinal Bacteria has become intimately related to human health, producing many metabolites in the intestines that can affect cardiovascular disease. Today, the incidence of cardiovascular disease is rising, its treatment is becoming increasingly important, and new therapeutic targets are needed. Here we describe the effects of trimethylamine oxide (TMAO), lipid metabolism, phenolic compounds, indole sulfate (IS), oleuropein (OL), and hydroxytyrosol (HT) on atherosclerosis, heart failure, hypertension, and other cardiovascular diseases, as well as their mechanism of action. This study provides new ideas, new methods, and new directions for the treatment of cardiovascular disease.

We developed a 9.38‐inch transparent Micro‐LED display with 114 PPI and 70% transmittance. The prototype display shows high transmittance and high brightness through innovative pixel design layout and film layer stacking structure.

The attitude of spherical liquid-filled spacecraft is controlled based on the high-order fully actuated system approaches. The rigid-fluid coupling dynamic equation can be established in terms of the Euler angles of the spacecraft and the angular velocities of the liquid fuel. According to the dynamic equation, three kinds of input selections are presented. In the case of one control input, the dynamic equation is transformed into the third-order or the second-order differential equations of the Euler angle by the high-order fully actuated system approaches. Then a control law is designed to track the target. The effectiveness of the control law is demonstrated by numerical simulations.

Tumor hypoxia is a great physiological barrier for tumor treatment. The development of efficient detection and treatment methods for tumor hypoxia has great scientific and clinical significance. In this work, we investigated the potential of magnetotactic bacteria AMB-1 for magnetic resonance imaging (MRI)-guided magnetic hyperthermia treatment of hypoxic tumors. Our investigations reveal that AMB-1 bacteria can selectively migrate to the hypoxic regions of solid tumors due to their anaerobic characteristics, showing active deep tumor penetrability. Moreover, AMB-1 bacteria exhibit high MRI contrast and magnetic heating performances because of the excellent magnetic performance of their magnetosomes. In vivostudies demonstrate that AMB-1 can not only generate T2-weighted contrast signals in tumor tissue, but also efficiently ablate hypoxic solid tumors through the magnetic hyperthermia effect. We believe that this novel microbial therapy can be a potential weapon for hypoxic tumor treatment.

[Display omitted] Hydrogels with good antifouling and mechanical properties as well as biocompatibility have great application potential in the field of biomedicine. In this paper, a newly double network (DN) hydrogel was prepared based on zwitterionic material sulfobetaine methacrylate (SBMA) and natural polysaccharide, sodium alginate (SA). The PSBMA network is covalently crosslinked while the SA network is ionically crosslinked by Ca2+. The hybrid crosslinked double network structure endows the DN hydrogel with excellent mechanical properties (E = 0.19 ± 0.01 MPa, σ = 0.73 ± 0.03 MPa), fast self-recovery ability as well as excellent fatigue resistance. Moreover, the results show that the PSBMA/SA-Ca2+ DN hydrogel is biocompatible and resists the absorption of non-specific proteins and adhesion of microorganisms, such as cells and algae, exhibiting outstanding antifouling properties. These unique characteristics of PSBMA/SA-Ca2+ DN hydrogel make it a promising candidate for biomedical application, such as artificial connective tissues, implantable devices, and underwater equipment. [ABSTRACT FROM AUTHOR]

A nonlinear torsional absorber, which can overcome the influence of the fluid velocity on the natural frequency, is employed at the boundary to restrain the bending vibration of a pipe for the first time. By using the rotating angle at the end of the pipe, the bending vibration energy is pumped to the boundary absorber. The nonlinearly coupled pipe-absorber governing equations are obtained by the generalized Hamilton’s principle. Steady-state responses subjected to a basement excitation are discussed by the modal-correction-harmonic-balance-method. According to this method, the boundaries of the pipe are treated as the generalized governing equations. In this way, those nonlinearities and time-dependent terms in the boundary are involved in the response completely. A direct simulation method, called the differential quadrature element method (DQEM), is used to verify these analytical results. The investigation indicates that the nonlinear boundary absorber owns two outstanding advantages. The first one is that the natural characters remain the same and the absorber can capture the resonance of the pipe automatically. The second one is that the absorber works at all natural modes. Especially, by using the nonlinear damping, the absorber will not worsen the weak vibration in the non-resonance region. The parameters of the absorber are investigated to optimize the efficiency in detail. The result finds that good efficiency can be achieved with a tiny mass. Meanwhile, the efficiency becomes better as the damping increases. With the help of these investigations, the work provides a new strategy to protect pipes conveying fluids from being destroyed by the vibration.

As an emerging type of pollutant, microplastics have become a global environmental problem. Approximately, a fifth of the global burden of type 2 diabetes can be attributed to air particulate pollution. However, scientific knowledge remains limited about the effects of airborne nanoplastics (NPs) exposure on metabolic diseases. In this experiment, a whole-body exposure system was used to simulate the real atmospheric environment, and three exposure concentrations combined with the actual environmental concentration were selected to explore the effects of airborne NPs on metabolic diseases. Based on histological analyses, metabolic studies, gene expression, metabolites, and molecular signaling analyses, mice exposed to airborne NPs were observed to show a phenotype of systemic inflammation and complete insulin resistance featuring excessive drinking and eating, weight loss, elevated blood glucose, and decreased triglyceride levels. After airborne NPs exposure, mice were intolerant to glucose and tolerant to insulin. In addition, airborne NPs exposure could result in long-term irreversible hyperglycemia. Together, the research findings provide a strong basis for understanding the hazards of airborne nanopollution on metabolic disorders.

Because of their self-recovery ability and fatigue resistance, double-network (DN) hydrogels with hybrid ionical–covalent cross-linking have received wide attention. In this work, by a simple “one-pot” method, a novel kind of hybrid ionic–covalent chitosan/poly(sulfobetaine methacrylate) (CS/PSBMA) DN hydrogels was prepared. The hydrogels showed high tensile strength (2.0 MPa), strong elastic modulus (0.5 MPa), fast self-recovery ability as well as excellent fatigue resistance, high mechanical strength, and toughness retention rate after soaking in water for 24 h. Additionally, the mechanical properties of the DN gels were enhanced after stretch and relaxation because of the rearrangement of the CS network. More excitingly, because of the antifouling feature of PSBMA and the inherent antibacterial property of CS, the hybrid DN hydrogels demonstrated a “repel and kill” effect on microorganisms. The CS/PSBMA DN hydrogels may find potential applications in biomedical fields, such as artificial connective tissues, implantable devices, and wound dressing.

Timestamping services are used to prove that a data item existed at a given point in time. This proof is represented by a timestamp token that is created by a timestamping authority. ISO/ IEC 18014 specifies timestamping services and requires them to hold the following two properties: (1) The data being timestamped is not disclosed to the timestamping authority; hash values of the data are provided to the authority instead. (2) A timestamp token can be renewed; as a result, the validity duration of a timestamp token is not restricted by the lifetimes of underlying algorithms or policies. In this article, we review this standard and discover several issues: Due to inconsistent writing or information missing, a timestamping service following the standard specification may not be able to achieve these designed properties. We provide a solution to each issue.

Users accessing services are often required to provide personal information, for example, age, profession and location, in order to satisfy access polices. This personal information is evident in the application of e-ticketing where discounted access is granted to visitor attractions or transport services if users satisfy policies related to their age or disability or other defined over attributes. We propose a privacy-preserving electronic ticket scheme using attribute-based credentials to protect users’ privacy. The benefit of our scheme is that the attributes of a user are certified by a trusted third party so that the scheme can provide assurances to a seller that a user’s attributes are valid. The scheme makes the following contributions: (1) users can buy different tickets from ticket sellers without releasing their exact attributes; (2) two tickets of the same user cannot be linked; (3) a ticket cannot be transferred to another user; (4) a ticket cannot be double spent. The novelty of our scheme is to enable users to convince ticket sellers that their attributes satisfy the ticket policies and buy discounted tickets anonymously. This is a step towards identifying an e-ticketing scheme that captures user privacy requirements in transport services. The security of our scheme is proved and reduced to a well-known complexity assumption. The scheme is also implemented and its performance is empirically evaluated.

We report compounds 5(CG416) and 6(CG428) as two first-in-class tropomyosin receptor kinase (TRK) degraders that target the intracellular kinase domain of TRK. Degraders 5and 6reduced levels of the tropomyosin 3 (TPM3)-TRKA fusion protein in KM12 colorectal carcinoma cells and inhibited downstream PLCγ1 signaling at sub-nanomolar concentrations. Both degraders also degraded human wild-type TRKA with similar potency. Interestingly, both degraders, especially 6, showed selectivity for the degradation of endogenous TPM3-TRKA over ectopically expressed ATP/GTP binding protein-like 4 (AGBL4)-TRKB or ETS variant transcription factor 6 (ETV6)-TRKC fusion proteins in KM12 cells. Global proteomic profiling assays demonstrated that 5is highly selective for the intended target. TPM3-TRKA protein degradation induced by 5and 6was further confirmed to be mediated through cereblon and the ubiquitin-proteasome system. Compared with the parental TRK kinase inhibitor, both degraders exhibited higher potency for inhibiting growth of KM12 cells. Moreover, both 5and 6showed good plasma exposure levels in mice. Therefore, 5and 6are valuable chemical tool compounds for investigating the in vivofunction of TRK fusion during tumorigenesis. Our study also paves the way for pharmacological degradation of TRK.

Modeling of the parabolic distributed parameter system (DPS) with the Karhunen-Loéve (KL) method under sparse sensing will become very difficult because the information from the measurements is incomplete. A novel information completion and learning strategy is proposed for spatiotemporal modeling under sparse sensing. During the offline initialization phase, the initial full spatial basis functions (SBFs) are constructed first in the full sensing environment under the framework of time-space separation. Subsequently, during the normal operation phase of fewer sensors, the sparse SBFs are obtained and further used to complete the lost spatial information with the help of the initial full SBFs, which are then recursively calibrated by the incremental KL. By iteratively repeating these two steps, the sparse spatiotemporal output can be completed in a streaming data environment. Finally, the proper spatiotemporal model can be constructed through time-space synthesis. The experimental results of a nonlinear transport-reaction process on a catalytic rod demonstrate the effectiveness of the proposed method.

BRAF is among the most frequently mutated oncogenes in human cancers. Multiple small molecule BRAF kinase inhibitors have been approved for treating melanoma carrying BRAF-V600 mutations. However, the benefits of BRAF kinase inhibitors are generally short-lived. Small molecule-mediated targeted protein degradation has recently emerged as a novel pharmaceutical strategy to remove disease proteins through hijacking the cellular ubiquitin proteasome system (UPS). In this study, we developed thalidomide-based heterobifunctional compounds that induced selective degradation of BRAF-V600E, but not the wild-type BRAF. Downregulation of BRAF-V600E suppressed the MEK/ERK kinase cascade in melanoma cells and impaired cell growth in culture. Abolishing the interaction between degraders and cereblon or blocking the UPS significantly impaired the activities of these degraders, validating a mechanistic role of UPS in mediating targeted degradation of BRAF-V600E. These findings highlight a new approach to modulate the functions of oncogenic BRAF mutants and provide a framework to treat BRAF-dependent human cancers.

Purpose: An energy harvester of magnetic levitation is investigated under harmonic excitations. Methods: The governing equations of the harvester are derived according to the related laws of mechanics and electricity. The harmonic balance method is applied to evaluate the dynamic responses and energy harvesting performances. A parametric analysis is implemented to evaluate the effects of damping, electromagnetic parameters, and coupling coefficient. Results: The decrease of damping, coil length, and magnetic flux intensity improve energy harvesting and average power and broaden the bandwidth of the harvester. However, the displace amplitude response is decreased and the average power is increased with the increase of coupling coefficient. The numerical results also validate the theoretical predictions. Conclusions: Introducing the nonlinear magnetic force and optimizing the parameters can improve the effectiveness of energy harvesting. These results will assist the design of the energy harvester in the future.

Distributed thermal modeling of Lithium-ion batteries (LIBs) is critical for the safety of electric vehicles. Due to the installation and cost constraints, only limited sensors are allowed for practical applications. In this paper, a learning-based framework is proposed for online spatiotemporal modeling of distributed thermal processes in pouch-type LIBs under sparse sensing. It consists of two stages. In the offline learning stage under full sensing, the Karhunen–Loève (KL) decomposition is used to extract the full spatial basis functions (BFs). In the subsequent online modeling stage under sparse sensing, a spatial mapping filter is first designed to recover the missing spatial information using the initial full BFs, which are then dynamically updated by the incremental KL technique as the thermal process evolves. By iteratively repeating these two steps, the streaming sparse spatiotemporal output can be accurately completed. Finally, the typical KL-based time-space separation method can be used for online temperature prediction. The simulation results of the distributed thermal processes on a pouch-type cell and a LIB pack demonstrate the effectiveness of the proposed method.

This paper presents nonlinear energy sink with giant magnetostrictive-piezoelectric material for energy harvesting of the whole-spacecraft vibration reduction system. The whole-spacecraft vibration attenuation system can effectively reduce vibration and achieve self-tuning enhanced energy harvesting range. The open-circuit voltage generated at low frequency is affected by the magnetic field force, alternating magnetic field and relative displacement. In order to acquire a steady periodic solution of the energy harvesting system, a combination of the harmonic balance method and pseudo arc length continuation technique is used. The numerical outcomes are consistent with the analytical outcomes in a certain range, which also proves the accuracy and reliability of the results. The amplitude and voltage of the energy harvesting system are analyzed by parameters such as cubic stiffness, viscous damping, and external excitation acceleration. In addition, this paper provides a new idea for broadband energy harvesting.

A change in the metabolic flux of glucose from mitochondrial oxidative phosphorylation (OXPHOS) to aerobic glycolysis is regarded as one hallmark of cancer. However, the mechanisms underlying the metabolic switch between aerobic glycolysis and OXPHOS are unclear. Here we show that the M2 isoform of pyruvate kinase (PKM2), one of the rate-limiting enzymes in glycolysis, interacts with mitofusin 2 (MFN2), a key regulator of mitochondrial fusion, to promote mitochondrial fusion and OXPHOS, and attenuate glycolysis. mTOR increases the PKM2:MFN2 interaction by phosphorylating MFN2 and thereby modulates the effect of PKM2:MFN2 on glycolysis, mitochondrial fusion and OXPHOS. Thus, an mTOR-MFN2-PKM2 signaling axis couples glycolysis and OXPHOS to modulate cancer cell growth.

High-static-low-dynamic-stiffness (HSLDS) nonlinear isolators have proven to have an advantage over linear isolators, because HSLDS nonlinear isolators allow low-frequency vibration isolation without compromising the static stiffness. Previously, these isolators have generally been assumed to have linear viscous damping, degrading the performance of the isolator at high frequencies. An alternative is to use nonlinear damping, where the nonlinear behavior is achieved by configuring linear dampers so they are orthogonally aligned to the excitation direction. This report compares the performances of single-stage and two-stage isolators with this type of damping with the corresponding isolators containing only linear viscous damping. The results show that both isolators with linear viscous damping and nonlinear damping reduce the transmissibility around the resonance frequencies, but the results show that the isolators with nonlinear damping perform better at high frequencies.

A dual-sensitive drug delivery system (DDS) based on graphene oxide (GO) which is simultaneously loaded with proapoptotic peptides and anticancer drugs was rationally designed and fabricated for cancer synergetic therapy. Specifically, a kind of cell apoptosis peptide (KLAKLAK)2(KLA) was anchored on the surface of GO via a disulfide bond to obtain GO-SS-KLA. Then, the aromatic anticancer drug doxorubicin (DOX) was loaded on GO through π–π conjugation and hydrogen bonding interactions. Finally, bovine serum albumin (BSA) was used to coat the GO carrier to obtain a biological medium-stable GO-based DDS, DOX@GO-SS-KLA/BSA. The results show that KLA and DOX can be released responding to the reductive and pH stimulus inside the cells, respectively, and achieve a synergetic therapy for cancer. Moreover, the results of stability studies show that DOX@GO-SS-KLA/BSA could be stably dispersed in water for more than 8 days and in 10% fetal bovine serum for at least 6 days. The constructed DOX@GO-SS-KLA/BSA exhibits great potential as a drug carrier for co-delivery of various therapeutic agents.

In this paper, a novel kind of zwitterion modified graphene oxide (GO) for promoting stability and reducing aggregation of GO as a drug carrier was proposed and demonstrated. Specifically, the GO was functionalized with a kind of zwitterion based silane, 3-(dimethyl(3-(trimethoxysilyl)propyl)-ammonio)propane-1-sulfonate (SBS). After zwitterion modification, the SBS functionalized GO (GO-SB) shows significantly enhanced stability in both serum-free and serum-containing solution, especially after loading doxorubicin hydrochloride (DOX). According to drug release profiles, the drug-loaded GO-SB exhibits thermosensitive and sustained release behavior. Meanwhile, in vitrostudies show that the DOX loaded GO-SB could be easily internalized by HepG2 cells and exhibit obvious cytotoxicity on the cells. And, in vivostudies demonstrate that the GO-SB drug carrier is capable of being taken by the larvae of zebrafish and can be eliminated from the body within several days.