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We report a simple, effective, and universal lattice reconstruction approach to improve the quality of perovskite films by using nonpolar solvents with high Gutmann donor numbers (DNs). We find that high-DN nonpolar solvents, for instance, ethyl acetate, can interact with perovskite precursors. Such a solvent can make the perovskite lattice more ordered and “harder” and promote the formation of heterostructures with low-dimensional perovskite impurities and residual solvent molecules. As a result, the lattice-reconstructed perovskite films exhibit reduced defect densities and suppressed ion migration. The resultant mixed-halide blue perovskite light-emitting diodes (PeLEDs) show greatly enhanced tolerance to high driving current densities and voltages, demonstrating high brightness, outstanding color stability and low efficiency roll-off. Our work provides a deep understanding of the interactions between nonpolar solvents and perovskites and offers useful guidelines for further development of high-power PeLEDs.

Graphical Abstract:

With the rapid development of energy-based seismic design, probabilistic seismic hazard analysis (PSHA) in terms of the input energy spectrum, EI, has become increasingly important. Generally, implementing EI-based PSHA requires a ground-motion prediction equation (GMPE) for EI. However, although a GMPE for EIcan be constructed in regions with abundant earthquake data based on regression analyses, it is difficult to obtain in regions lacking strong ground-motion records. Therefore, this study proposes a new approach for performing EI-based PSHA in regions with limited earthquake data. Instead of using a GMPE for EIdirectly, a model of Fourier amplitude spectrum (FAS) is adopted, which can be determined using a small number of earthquake data with small-to-moderate magnitudes. Then, the EIof the ground motion is obtained from FAS based on the relationship between EIand FAS. Furthermore, to calculate the annual intensity exceedance rate within the proposed framework of adopting the FAS model, a highly efficient method, namely, the moment method, is applied. Several numerical examples indicate that the proposed approach not only is suitable for regions lacking strong ground-motion records but also performs very efficiently in calculating the annual intensity exceedance rate.

Perovskite materials (ABO3) possess a wealth of elements selectable and exhibit a diverse range of octahedral transformations. The emergence of high-entropy perovskite ceramics provides a fresh perspective for advancing the field of wave-absorbing materials. In this study, we concentrate on the wet chemical synthesis of a high-entropy perovskite oxide, Sr(Cr0.2Mn0.2Fe0.2Co0.2Ni0.2)O3, and investigate its crystal structure, microstructure, chemical composition, magnetic properties, and microwave absorbing capabilities. The results indicate that when sintered at a temperature of 1,350 °C, the sample achieves a minimum reflection loss of −54.0 dB at a frequency of 9.68 GHz, accompanied by a maximum effective absorption bandwidth (EAB) of 7.44 GHz at the thickness of 1.8 mm. The high-entropy design of the B-site induces distortions of oxygen vacancy and octahedral structure of the perovskite material. This leads to the fine tuning of its dielectric and magnetic properties, thereby endowing perovskite with excellent electromagnetic wave absorption capabilities. Consequently, perovskite emerges as a promising new electromagnetic wave absorption material with significant potential.

A key challenge for achieving high-efficient DNA strand displacement reaction (SDR) with existing technologies is the inferior kinetic performance due to the alternately cumbersome conjunction and dissociation of dsDNA. In this work, a novel multidriven SDR collaborated by toehold initiator, strand towing, and click chemistry is engineered. The invasion strand (O) endows the hybridization with a basal strand (M) in dsDNA for releasing a displacement strand (P), which can be significantly boosted by the towing of a helper strand and impetus from the click reaction. Accordingly, the hybridization rate and dissociation extent of P can be largely improved and showed a desiring displacement rate close to 6-fold compared with the traditional method, providing a newly high-efficient SDR strategy for potential application in biosensing, clinical diagnostics, and DNA nanotechnology. In view of this, a practical biosensing platform by combining the multidriven SDR (MSDR) with waste-free DNA multi-cycle amplification is constructed for the rapid and ultrasensitive electrochemical detection of cancer-related miRNA-21. The substantial output DNA as an invasion strand (O) from target-triggered waste-free DNA multicycle can high-efficiently release a signal probe (Fc)-labeled displacement strand (P) on an electrode by using the proposed MSDR, obtaining a low detection limit below 106.8 aM.

The repair of critical-sized bone defects remains a major challenge for clinical orthopedic surgery. Here, we develop a surface biofunctionalized three-dimensional (3D) porous polyether–ether–ketone (PEEK) scaffold that can simultaneously promote osteogenesis and regulate macrophage polarization. The scaffold is created using polydopamine (PDA)-assisted immobilization of silk fibroin (SF) and the electrostatic self-assembly of nanocrystalline hydroxyapatite (nano-HA) on a 3D-printed porous PEEK scaffold. The SF/nano-HA functionalized surface provides a bone-like microenvironment for osteoblastic cells’ adhesion, proliferation, mineralization and osteogenic differentiation. Moreover, the biofunctionalized surface can effectively drive macrophages polarization from the pro-inflammatory M1 phenotype to the anti-inflammatory M2 phenotype. Integrin β1-specific cell-matrix binding and the activation of Ca2+receptor-mediated signaling pathway play critical roles in the regulation of macrophage polarization. Compared with the as-printed scaffold, the SF/nano-HA functionalized porous PEEK scaffold induces minimal inflammatory response, enhanced angiogenesis, and substantial new bone formation, resulting in improved osseointegration in vivo. This study not only develops a promising candidate for bone repair but also demonstrates a facile surface biofunctionalization strategy for orthopedic implants to improve osseointegration by stimulating osteogenesis and regulating immunity.

Based on the high-quality observation data and the numerical simulation, the evolution characteristics of internal solitary waves (ISWs) and the load on the suspend submerged body are studied on the continental shelf and slope separately. The observed ISWs exhibit the first mode depression ISWs. The amplitudes of ISWs on the shelf and slope areas reach 50 m and 80 m, respectively. The upper layer velocity in the westward direction is about 0.8 m/s on the continental shelf and 0.9 m/s on the continental slope during the passing through of ISWs. The lower layer is dominated by the eastward compensating flow. In the vertical direction, the water in front of the wave flows downward, while the water behind the wave flows upward, and the maximum vertical velocity exceeds 0.2 m/s. Numerical simulation results show that the larger the amplitude of ISWs, the larger the load on the submerged body. The force on the submerged body by ISWs is dominated by the vertical force, and the corresponding maximum vertical forces on the continental shelf and slope are −25 kN and −27 kN. The submerged body is subjected to a large counterclockwise moment and the sudden change of the moment will also cause the submerged body to capsize. This paper not only gives a deeper understanding of the characteristics of ISWs from the deep continental slope to the shallow continental shelf, but also has a certain guiding value for the prediction of ISWs and for marine military activities.

According to the established prediction model of internal solitary wave loads on FPSO in the previous work, the lumped mass model and the movement equations of finite displacement in time domain, the dynamic response model of interaction between internal solitary waves and FPSO with mooring lines were established. Through calculations and analysis, time histories of dynamic loads of FPSO exerted by internal solitary waves, FPSO’s motion and dynamic tension of mooring line were obtained. The effects of the horizontal pretension of mooring line, the amplitude of internal solitary wave and layer fluid depth on dynamic response behavior of FPSO were mastered. It was shown that the internal solitary waves had significant influence on FPSO, such as the large magnitude horizontal drift and a sudden tension increment. With internal solitary wave of −170 m amplitude in the ocean with upper and lower layer fluid depth ratio being 60:550, the dynamic loads reached 991.132 kN (horizontal force), 18067.3 kN (vertical force) and −5042.92 kN·m (pitching moment). Maximum of FPSO’s horizontal drift was 117.56 m. Tension increment of upstream mooring line approached 401.48 kN and that of backflow mooring line was −140 kN. Moreover, the loads remained nearly constant with different pretension but increased obviously with the changing amplitude and layer fluid depth ratio. Tension increments of mooring lines also changed little with the pretension but increased rapidly when amplitude and layer fluid depth ratio increased. However, FPSO’s motion increased quickly with not only the horizontal pretension but also the amplitude of internal solitary wave and layer fluid depth ratio.

Anomaly-based network intrusion detection systems (NIDSs) are essential for ensuring cybersecurity. However, the security communities realize some limitations when they put most existing proposals into practice. The challenges are mainly concerned with (i) fine-grained unknown attack detection and (ii) ever-changing legitimate traffic adaptation. To tackle these problem, we present three key design norms. The core idea is to construct a model to split the data distribution hyperplane and leverage the concept of isolation, as well as advance the incremental model update. We utilize the isolation tree as the backbone to design our model, named FOSS, to echo back three norms. By analyzing the popular dataset of network intrusion traces, we show that FOSS significantly outperforms the state-of-the-art methods. Further, we perform an initial deployment of FOSS by working with the Internet Service Provider (ISP) to detect distributed denial of service (DDoS) attacks. With real-world tests and manual analysis, we demonstrate the effectiveness of FOSS to identify previously-unseen attacks in a fine-grained manner.

Due to the finite bandwidth of practical wireless systems, one multipath component can manifest itself as a discrete pulse consisting of multiple taps in the digital delay domain. This effect is called channel leakage, which complicates the multipath parameter estimation. In this study, we propose a new algorithm to estimate multipath parameters, including delay, angle of arrival (AOA), and angle of departure (AOD) of leaked channels. This is accomplished by leveraging the knowledge of pulse shaping functions, a technique that can be applied to enhance the precision of WiFi sensing. More specifically, we formulate the channel impulse response (CIR) between a transmit and a receive antenna as a linear combination of a set of overcomplete basis vectors, each corresponding to a different delay. Considering the limited number of paths in physical environments, we formulate the multipath parameter estimation as a group sparse recovery problem. We develop a two-stage approach based on variational expectation maximization (VEM) to solve the formulated problem. In the first stage, we estimate the sparse vectors and determine the number of physical paths and their associated delay parameters from the positions of the nonzero entries. In the second stage, we use Newton’s method to estimate the AOA and AOD of each path. The Cramér-Rao lower bound (CRLB) for multipath parameter estimation is derived for performance evaluation. Simulation results show that our algorithm can achieve superior estimation accuracy in multipath parameters compared to two benchmarking schemes and approach the CRLB.

IMPORTANCE: The X chromosome has remained enigmatic in Alzheimer disease (AD), yet it makes up 5% of the genome and carries a high proportion of genes expressed in the brain, making it particularly appealing as a potential source of unexplored genetic variation in AD. OBJECTIVES: To perform the first large-scale X chromosome–wide association study (XWAS) of AD. DESIGN, SETTING, AND PARTICIPANTS: This was a meta-analysis of genetic association studies in case-control, family-based, population-based, and longitudinal AD-related cohorts from the US Alzheimer’s Disease Genetics Consortium, the Alzheimer’s Disease Sequencing Project, the UK Biobank, the Finnish health registry, and the US Million Veterans Program. Risk of AD was evaluated through case-control logistic regression analyses. Data were analyzed between January 2023 and March 2024. Genetic data available from high-density single-nucleotide variant microarrays and whole-genome sequencing and summary statistics for multitissue expression and protein quantitative trait loci available from published studies were included, enabling follow-up genetic colocalization analyses. A total of 1 629 863 eligible participants were selected from referred and volunteer samples, 477 596 of whom were excluded for analysis exclusion criteria. The number of participants who declined to participate in original studies was not available. MAIN OUTCOME AND MEASURES: Risk of AD, reported as odds ratios (ORs) with 95% CIs. Associations were considered at X chromosome–wide (P < 1 × 10−5) and genome-wide (P < 5 × 10−8) significance. Primary analyses are nonstratified, while secondary analyses evaluate sex-stratified effects. RESULTS: Analyses included 1 152 284 participants of non-Hispanic White, European ancestry (664 403 [57.7%] female and 487 881 [42.3%] male), including 138 558 individuals with AD. Six independent genetic loci passed X chromosome–wide significance, with 4 showing support for links between the genetic signal for AD and expression of nearby genes in brain and nonbrain tissues. One of these 4 loci passed conservative genome-wide significance, with its lead variant centered on an intron of SLC9A7 (OR, 1.03; 95% CI, 1.02-1.04) and colocalization analyses prioritizing both the SLC9A7 and nearby CHST7 genes. Of these 6 loci, 4 displayed evidence for escape from X chromosome inactivation with regard to AD risk. CONCLUSION AND RELEVANCE: This large-scale XWAS of AD identified the novel SLC9A7 locus. SLC9A7 regulates pH homeostasis in Golgi secretory compartments and is anticipated to have downstream effects on amyloid β accumulation. Overall, this study advances our knowledge of AD genetics and may provide novel biological drug targets. The results further provide initial insights into elucidating the role of the X chromosome in sex-based differences in AD.

With the increasing security concerns of the satellite network due to the broadcasting nature and the inherent openness of satellite-terrestrial communications, the satellite spectrum and terrestrial node resource trading based cooperation in cognitive satellite terrestrial networks (CSTNs) has gained a lot attention. However, the existing literature has not well considered the fairness issue in resource trading, which may cause cooperation failure between the satellite and terrestrial networks when their own benefits are impaired. To tackle this issue, in this paper we propose a two-layer hierarchical game framework for a multi-terrestrial base stations (BSs) CSTN scenario to guarantee the fairness of resource trading between the satellite and terrestrial networks and thus achieve a win-win situation for both networks. Specifically, a coalition formation game is adopted to study the cooperative behaviors among the terrestrial BSs. Herein, we propose a distributed merge-and-split based coalition formation algorithm to determine the coalition structure, of which the stability, convergence, and complexity are theoretically investigated. Moreover, a Stackelberg game is introduced to model the competition between the satellite and terrestrial BSs, where the satellite acts as the leader and the terrestrial BSs act as the followers. The Stackelberg equilibrium (SE) for the Stackelberg game is derived based on the backward induction method. We then design a distributed algorithm to obtain the coalition structure and SE for the proposed two-layer hierarchical game framework. Finally, simulations are presented to validate our theoretical results.

In this paper, we investigate multi-user modular extremely large-scale multiple-input multiple-output (XL-MIMO) communication systems, where modular extremely large-scale uniform linear array (XL-ULA) is deployed at the base station (BS) to serve multiple single-antenna users. By exploiting the unique modular array architecture and considering the potential near-field propagation, we develop sub-array based uniform spherical wave (USW) models for distinct versus common angles of arrival/departure (AoAs/AoDs) with respect to different sub-arrays/modules, respectively. Under such USW models, we analyze the beam focusing patterns at the near-field observation location by using near-field beamforming. The analysis reveals that compared to the conventional XL-MIMO with collocated antenna elements, modular XL-MIMO can provide better spatial resolution by benefiting from its larger array aperture. However, it also incurs undesired grating lobes due to the large inter-module separation. Moreover, it is found that for multi-user modular XL-MIMO communications, the achievable signal-to-interference-plus-noise ratio (SINR) for users may be degraded by the grating lobes of the beam focusing pattern. To address this issue, an efficient user grouping method is proposed for multi-user transmission scheduling, so that users located within the grating lobes of each other are not allocated to the same time-frequency resource block (RB) for their communications. Numerical results are presented to verify the effectiveness of the proposed user grouping method, as well as the superior performance of modular XL-MIMO over its collocated counterpart with densely distributed users.

Electronic countermeasure (ECM) technology plays a critical role in modern electronic warfare, which can interfere with enemy radar detection systems by noise or deceptive signals. However, the conventional active jamming strategy incurs additional hardware and power costs and has the potential threat of exposing the target itself. To tackle the above challenges, we propose a new intelligent reflecting surface (IRS)-aided radar spoofing strategy, where IRS is deployed on the surface of a target to help eliminate the signals reflected towards the hostile radar to shield the target, while simultaneously redirecting its reflected signal towards a surrounding clutter to generate deceptive angle-of-arrival (AoA) sensing information for the radar. The IRS’s reflection coefficients are optimized to maximize the received signal power at the radar from the direction of the selected clutter subject to the constraint that its received power from the direction of the target is lower than a given detection threshold. We first solve this non-convex optimization problem using the semidefinite relaxation (SDR) method. A lower-complexity solution is further proposed to reduce computational burden. Simulation results validate the efficacy of our proposed IRS-aided spoofing system as compared to various benchmark schemes.

Six-dimensional movable antenna (6DMA) is an effective solution for enhancing wireless network capacity through the adjustment of both 3D positions and 3D rotations of distributed antenna surfaces. Although freely positioning/rotating 6DMA surfaces offer the greatest flexibility and thus highest capacity improvement, its implementation may be challenging in practice due to the drastic architecture change required for existing base stations (BSs), which predominantly adopt fixed-position antenna (FPA) arrays (e.g., sector antenna arrays). Thus, we introduce in this letter a new BS architecture called hybrid fixed and movable antennas (HFMA), which consists of both conventional FPA arrays and position/rotation-adjustable 6DMA surfaces. For ease of implementation, we consider that all 6DMA surfaces can rotate along a circular track above the FPA arrays. We aim to maximize the network capacity via optimizing the rotation angles of all 6DMA surfaces based on the users’ spatial distribution. Since this problem is combinatorial and its optimal solution requires prohibitively high computational complexity via exhaustive search, we propose an alternative adaptive Markov Chain Monte Carlo based method to solve it more efficiently. Finally, we present simulation results that show significant performance gains achieved by our proposed design over various benchmark schemes.

In this article, automatic machine learning (ML) technology and global optimization algorithms have been combined to achieve a fast and high-performance extended interaction oscillator (EIO) design. An EIO model is manually designed to give a comparison. The manually designed EIO model can predict an output power of 7.9 kW with an efficiency of 15.8%. The data to train ML models are generated with CST-MATLAB co-simulation. During dataset creation, some EIO models are derived from high-output-power models by changing voltage and current parameters. By adding these derived models into dataset, power gradients over current and voltage are decreased. This is the key to the success of the whole project. Particle swarm optimization (PSO) and genetic algorithm (GA) are tested and compared to achieve the EIO fast design. PSO algorithm performs better than GA for relatively fixed searching directions and less randomness. An EIO optimized by PSO can predict an output power of 11.9 kW. The EIO electronic efficiency is 19.3%, which is 3.5% higher than that of the manually designed oscillator.

The mobility scattering mechanisms in the ultra-thin-body (UTB) Ge-OI p- and n-MOSFETs have been systematically investigated. It is found that the ${E} _{\text {eff}}^{-{2}}$ dependence is confirmed for the hole mobility in Ge-OI pMOSFETs, while the electron mobility exhibits an unusually strong dependence on ${E} _{\text {eff}}$ ( $\propto {E} _{\text {eff}}^{-{4}}\text {)}$ . The $\mu _{\text {ph}}$ exhibits an ${E} _{\text {eff}}^{\,{-{0}.{3}}}$ dependence for both holes and electrons, along with a temperature dependence of $\sim {T} ^{\,{-{1}.{8}}}$ . The $\mu _{\text {total}}$ is measured at different depletion layer carrier densities ( ${N} _{\text {depl}}\text {)}$ , revealing that $\mu _{\text {Coulomb}}$ increases with the rise of ${N} _{\text {depl}}$ . Specially, $\mu _{\text {Coulomb}}$ exhibits ${N} _{\text {depl}}^{{0}.{5}}$ and ${N} _{\text {depl}}^{{1}.{8}}$ dependencies for electrons and holes, respectively. Consequently, more pronounced mobility degradation has been confirmed in UTB Ge-OI nMOSFETs than in UTB Ge-OI pMOSFETs. These findings suggest universal carrier scattering mechanisms for both holes and electrons in UTB Ge-OI channels, which are valuable for understanding carrier transport in thin-channel Ge devices for future advanced technology nodes.

The grid-forming control is a promising solution to address the instability issues induced by the voltage source inverters (VSIs) based on grid-following control under weak grid conditions. Nonetheless, the placement of VSIs based on grid-forming control (GFM-VSIs) and its capacity configuration method have not been theoretically revealed. To fill this gap, this article proposes the placement and capacity configuration strategies for GFM-VSIs based on participating factor (PF) and power flow analysis. By establishing the unified αβ-frame complex-valued node admittance model, the active node with the largest PF is chosen as the placement of GFM-VSIs. It is revealed that the system stability can be guaranteed even if the active power reference of GFM-VSIs is set to 0, thereby, the system stability can be improved by implementing the GFM-based static synchronous compensator (GFM-STATCOM). Furthermore, the optimal capacity of GFM-STATCOM under different control strategies is obtained by the power flow analysis within the stability constraints as the active node type is determined after accessing GFM-STATCOM. The proposed method is performed based on the three-machine test system, and the hardware-in-the-loop and physical experiments validate the theoretical analysis.

The oncogenic potential of chromosome 8q22 copy number gain in liver cancer remains to be depicted. Here, we report that ZNF706, encoded by a gene mapped to chromosome 8q22, is a C2H2-type zinc finger protein. However, the biological function and mechanism of ZNF706 have been poorly investigated. Clinically, ZNF706 expression was elevated in hepatocellular carcinoma (HCC), and high ZNF706 expression was associated with unfavorable survival in HCC patients. Functional experiments revealed that ZNF706 knockdown inhibited HCC progression both in vitro and in vivo. RNA sequencing (RNA-seq) and chromatin immunoprecipitation-based deep sequencing (ChIP-seq) revealed that mechanistically, ZNF706 is a crucial ferroptosis regulator and that SLC7A11 is a critical target of ZNF706. In addition, ZNF706 knockdown inhibited SLC7A11 expression, increased lipid peroxidation, and promoted ferroptosis. Further analysis revealed that ZNF706 is a novel direct target transcriptionally activated by MYC in HCC cells. Importantly, MYC depletion reduced SLC7A11-mediated redox homeostasis, and this effect was reversed by ZNF706 reexpression. Collectively, our data demonstrate that ZNF706 is a potential oncogene in liver cancer and functions as a ferroptosis regulator by modulating SLC7A11 expression, constituting a potential therapeutic target for HCC.

To realize the online control of fuel cell/supercapacitor hybrid power system, a new method called equivalent power consumption (EPC) is proposed in this article. This method proposes a new equivalent coefficient, which optimizes the calculation accuracy of electro-hydrogen conversion of the hybrid power system. To further realize the optimal power distribution of the hybrid system, the cost function of the entire hybrid system is constructed and solved. By using the optimal analytical solution of the hybrid system, the online control is finally realized. The test results of the RT-LAB platform show that the proposed method has significant advantages in both power consumption and fluctuation rate compared with commonly used methods. In addition, this method has also been further improved to fit the operation of trams on actual long-distance routes, whose results demonstrates the effectiveness of the proposed method and the stable operation under complex conditions.

Leaves are the main organ for photosynthesis and organic synthesis in cotton. Leaf shape has important effects on photosynthetic efficiency and canopy formation, thereby affecting cotton yield. Previous studies have shown that LMI1(LATE MERISTEM IDENTITY1) is the main gene regulating leaf shape. In this study, the LMI1gene was inserted into the 35S promoter expression vector, and cotton plants overexpressing LMI1(OE) were obtained through genetic transformation. Statistical analysis of the biological traits of the T1and T2populations showed that compared to the wild type (WT), OE plants had significantly larger leaves, thicker stems and significantly greater dry weight. Furthermore, plant sections of the main vein and petiole showed that the numbers of cells in those tissues of OE plants were significantly greater. In addition, RNA-seq analysis revealed the differential expression of genes related to gibberellin synthesis and NACgene family (genes containing the NAC domain) between the OE and WT plants, suggesting that LMI1is involved in secondary wall formation and cell proliferation, which promotes stem thickening. Moreover, Gene Ontology (GO) analysis revealed enrichment in the terms of calcium ion binding, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed enrichment in the terms of fatty acid degradation, phosphatidylinositol signal transduction system, and cAMP (cyclic adenosine monophosphate) signal pathway. These results suggested that LMI1OE plants are responsive to gibberellin hormone signals, and have altered messenger signals (cAMP, Ca2+) which amplify this function, to promote stronger aboveground vegetative growth. This study found the LMI1greatly increased the vegetative growth in cotton, which is the basic requirement for higher yield.

(±)-Salvicatone A (1), a C27-meroterpenoid featuring a unique 6/6/6/6/6-pentacyclic carbon skeleton with a 7,8,8a,9,10,10a-hexahydropyren-1 (6H)-one motif, was isolated from the roots and rhizomes of Salvia castaneaDiels f. tomentosaStib. Its structure was characterized by comprehensive spectroscopic analyses along with computer-assisted structure elucidation, including ACD/structure elucidator and quantum chemical calculations with 1H/13C NMR and electronic circular dichroism. Biogenetically, compound 1was constructed from decarboxylation following [4 + 2] Diels–Alder cycloaddition reaction between caffeic acid and miltirone analogue. Bioassays showed that (−)-1and (+)-1inhibited nitric oxide production in lipopolysaccharide-induced RAW264.7 macrophage cells with an IC50value of 6.48 ± 1.25 and 15.76 ± 5.55 μM, respectively. The structure-based virtual screening based on the pharmacophores in ePharmaLib, as well as the molecular docking and molecular dynamics simulations study, implied that (−)-1and (+)-1may potentially bind to retinoic acid receptor-related orphan receptor C to exert anti-inflammatory activities.

Sc2CO2MXene has potential applications in energy storage and optoelectronics due to its superior structure and excellent properties. The electronic properties, quantum capacitance, and photocatalytic activity of Cr-doped Sc2CO2under strain are studied by the density functional theory. Cr doping makes the system produce magnetism. The spin-down states of Sc2CO2–Cr under strain are direct semiconductors, while their spin-up states are indirect semiconductors. Sc2CO2–Cr under +5, −5, −3, and −2% strains in an aqueous system are suitable for cathode material. A large voltage drastically modulates the type of electrode materials. Sc2CO2–Cr under strains from 0 to +2% can perform the oxygen evolution reaction at an alkaline environment, while the Sc2CO2–Cr system under strain is a good for CO2photocatalysis at pH 0 and 7.

The ecological environment of the Yellow River Basin has become more fragile under the combined action of natural and manmade activities. However, the change mechanisms of ecological vulnerability in different sub-regions and periods vary, and the reasons for this variability are yet to be explained. Thus, in this study, we proposed a new remote sensing ecological vulnerability index by considering moisture, heat, greenness, dryness, land degradation, and social economy indicators and then analyzed and disclosed the spatial and temporal change patterns of ecological vulnerability of the Yellow River Basin, China from 2000 to 2022 and its driving mechanisms. The results showed that the newly proposed remote sensing ecological vulnerability index had a high accuracy, at 86.36%, which indicated a higher applicability in the Yellow River Basin. From 2000 to 2022, the average remote sensing ecological vulnerability index of the Yellow River Basin was 1.03, denoting moderate vulnerability level. The intensive vulnerability area was the most widely distributed, which was mostly located in the northern part of Shaanxi Province and the eastern part of Shanxi Province. From 2000 to 2022, the ecological vulnerability in the Yellow showed an overall stable trend, while that of the central and eastern regions showed an obvious trend of improvement. The gravity center of ecological vulnerability migrated southwest, indicating that the aggravation of ecological vulnerability in the southwestern regions was more severe than in the northeastern regions of the basin. The dominant single factor of changes in ecological vulnerability shifted from normalized difference vegetation index (NDVI) to temperature from 2000 to 2022, and the interaction factors shifted from temperature∩NDVI to temperature∩precipitation, which indicated that the global climate change exerted a more significant impact on regional ecosystems. The above results could provide decision support for the ecological protection and restoration of the Yellow River Basin.

By transmitting task-related information only, semantic communications yield significant performance gains over conventional communications. However, the lack of mature semantic theory about semantic information quantification and performance evaluation makes it challenging to perform resource allocation for semantic communications, especially when multiple tasks coexist in the network. To cope with this challenge, we propose a quality-of-experience (QoE) based semantic-aware resource allocation method for multi-task networks in this paper. First, semantic entropy is defined to quantify the semantic information for different tasks, and the relationship between semantic entropy and Shannon entropy is analyzed. Then, we develop a novel QoE model to formulate the semantic-aware resource allocation in terms of semantic compression, channel assignment, and transmit power. The compatibility of the formulated problem with conventional communications is further demonstrated. To solve this problem, we decouple it into two subproblems, and solve them by a developed deep Q-network (DQN) based method and a proposed low-complexity matching algorithm, respectively. Finally, simulation results validate the effectiveness and superiority of the proposed method, as well as its compatibility with conventional communications.

Movable antenna (MA) is a new technology with great potential to improve communication performance by enabling local movement of antennas for pursuing better channel conditions. In particular, the acquisition of complete channel state information (CSI) between the transmitter (Tx) and receiver (Rx) regions is an essential problem for MA systems to reap performance gains. In this paper, we propose a general channel estimation framework for MA systems by exploiting the multi-path field response channel structure. Specifically, the angles of departure (AoDs), angles of arrival (AoAs), and complex coefficients of the multi-path components (MPCs) are jointly estimated by employing the compressed sensing method, based on multiple channel measurements at designated positions of the Tx-MA and Rx-MA. Under this framework, the Tx-MA and Rx-MA measurement positions fundamentally determine the measurement matrix for compressed sensing, of which the mutual coherence is analyzed from the perspective of Fourier transform. Moreover, two criteria for MA measurement positions are provided to guarantee the successful recovery of MPCs. Then, we propose several MA measurement position setups and compare their performance. Finally, comprehensive simulation results show that the proposed framework is able to estimate the complete CSI between the Tx and Rx regions with a high accuracy.

A conventional principal component analysis (PCA) frequently suffers from the disturbance of outliers, and thus, spectra of extensions and variations of PCA have been developed. However, all the existing extensions of PCA derive from the same motivation, which aims to alleviate the negative effect of the occlusion. In this article, we design a novel collaborative-enhanced learning framework that aims to highlight the pivotal data points in contrast. As for the proposed framework, only a part of well-fitting samples are adaptively highlighted, which indicates more significance during training. Meanwhile, the framework can collaboratively reduce the disturbance of the polluted samples as well. In other words, two contrary mechanisms could work cooperatively under the proposed framework. Based on the proposed framework, we further develop a pivotal-aware PCA (PAPCA), which utilizes the framework to simultaneously augment positive samples and constrain negative ones by retaining the rotational invariance property. Accordingly, extensive experiments demonstrate that our model has superior performance compared with the existing methods that only focus on the negative samples.

Immunoglobulin A nephropathy is a complex autoimmune disease with various underlying causes and significant clinical heterogeneity. There are large individual differences in its development, and the etiology and pathogenesis are still poorly understood. While it is known that immunobiological factors play a significant role in the pathophysiology of immunoglobulin A nephropathy, the specific nature of these factors has yet to be fully elucidated. Numerous investigations have verified that CD4+and CD8+T lymphocytes are involved in the immunopathogenesis of immunoglobulin A nephropathy. Furthermore, certain data also point to γδT cells’ involvement in the pathophysiology of immunoglobulin A nephropathy. By thoroughly examining the mechanisms of action of these T cells in the context of immunoglobulin A nephropathy, this review sheds light on the immunopathogenesis of the disease and its associated factors. The review is intended to provide reference value for the future research in this field and promising treatment clues for clinical patients.This review demonstrates the immunological correlation between T cells and immunoglobulin A nephropathy, providing guidance for future diagnosis and precise individualized treatment of immunoglobulin A nephropathy.

The purpose of this study was to determine the causal effect of statins on osteoarthritis (OA) risk using Mendelian randomization (MR). Single nucleotide polymorphism–based genome‐wide association analyses of statins were collected from the UK Biobank and FinnGen dataset, and OA data were collected from the UK Biobank and Arthritis Research UK Osteoarthritis Genetics (arcOGEN) study. Two‐sample MR analyses were performed using the inverse‐variance weighted (IVW) technique. MR‐Egger, weighted median, and weighted mode served as supplementary analyses. MR‐Egger regression, Cochran's Q test, and Mendelian Randomization Pleiotropy Residual Sum and Outlier analysis were performed as sensitivity analyses. Hydroxymethylglutaryl‐coenzyme A reductase (HMGCR) expression and OA risk were evaluated using summary data–based MR (SMR). MR analyses consistently supported a causal connection between statin use and OA risk. A causal effect was observed for atorvastatin (IVW: β = −2.989, P= 0.003) and rosuvastatin (IVW: β = −14.141, P= 0.006) treatment on hip OA. Meta‐analysis showed the association between atorvastatin and knee OA was statistically significant (odds ratio 0.15; P= 0.004). Simvastatin use exhibited a protective effect against knee (IVW: β = −1.056, P= 0.004) and hip OA (IVW: β = −1.405, P= 0.001). Statin medication showed a protective effect on hip OA (IVW: β = −0.054, P= 0.013). HMGCR correlated significantly with a reduced risk of knee OA (β = −0.193, PSMR= 0.017), rather than hip OA (β = 0.067, PSMR= 0.502), which suggested that statins' protective effect on OA may not be related to its lipid‐lowering effect. This MR study provides compelling evidence that statin treatment may be a protective factor for OA. Further research is required to clarify its underlying mechanism.

Compared to the traditional modular multilevel converter and alternative arm converter, the hybrid multilevel converter (HMC) exhibits superiority in terms of cost and volume. In the HMC, the pulse width of the direction switch (DS) is conventionally utilized to maintain capacitor voltage balancing (CVB). However, this method has certain limitations, including a restricted range of modulation indices and the inability to support pure reactive power operation. To address these drawbacks, a new CVB method based on the phase angle of the DS is proposed in this article. Compared to the traditional method, the proposed method enables the HMC to achieve a full range of modulation index and four-quadrant operation. Additionally, it demonstrates improved performance in terms of SM capacitance and capacitor voltage ripple, especially under severe grid voltage sags and low power factors. A comparative analysis is conducted between two CVB methods, focusing on the SM number, switch number, and SM capacitance. Furthermore, a unified control strategy considering asymmetrical and symmetrical grid voltage sags is proposed for these two CVB methods. Finally, the effectiveness and superiority of the proposed CVB methods are verified by simulation and experimental testing.

High-pressure die casting (HPDC) is one of the most popular mass production processes in the automotive industry owing to its capability for part consolidation. However, the nonuniform distribution of mechanical properties in large-sized HPDC products adds complexity to part property evaluation. Therefore, a methodology for property prediction must be developed. Material characterization, simulation technologies, and artificial intelligence (AI) algorithms were employed. Firstly, an image recognition technique was employed to construct a temperature-microstructure characteristic model for a typical HPDC Al7Si0.2Mg alloy. Moreover, a porosity/microstructure-mechanical property model was established using a machine learning method based on the finite element method and representative volume element model results. Additionally, the computational results of the casting simulation software were mapped with the porosity/microstructure-mechanical property model, allowing accurate prediction of the property distribution of the HPDC Al-Si alloy. The AI-enabled property distribution model developed in this study is expected to serve as a foundation for intelligent HPDC part design platforms in the automotive industry.

Precipitation is a common phenomenon that occurs during heat treatments. There is internal stress around the precipitate owing to the lattice misfit between the precipitate and matrix. This internal stress has a significant influence not only on the precipitation kinetics but also on the material properties. The misfit stress can be obtained by numerically solving the mechanical equilibrium equations. However, this process is complex and time-consuming. We developed a new approach based on deep learning to accelerate the solution process. The training data were first generated by a phase-field model coupled with elastic mechanical equilibrium equations, which were solved using the finite difference method. The obtained precipitate morphologies and corresponding stress distributions were input data for training the physics-informed (PI) UNet model. The well-trained PI-UNet model can then be applied to predicting stress distributions with the precipitate morphology as the input. Prediction accuracy and efficiency are discussed in this study. The results showed that the PI-UNet model was an appropriate approach for quickly predicting the misfit stress between the precipitate and matrix.

• A novel ZnO photosensitizer mediated by Ni-doped and oxygen vacancy double defect structure. • Enhanced photogenerated electron–hole pair separation and photocatalytic efficiency. • Excellent antibacterial properties based on ROS damage and ATP synthesis inhibition. • Outstanding wound healing performance by tissue regeneration and anti-inflammatory. • A great biomedical application merit for combating the drug resistance challenge. The use of zinc oxide (ZnO) photosensitizers (PSs)-mediated photodynamic therapy (PDT) against bacterial wound infections is greatly restricted by diminished photocatalytic efficiency caused by the rapid recombination of photogenerated electrons and holes. In this work, ZnO PSs with a Ni-doped/oxygen vacancy and a protective carbon shell were successfully synthesized by calcinating a Ni-doping zeolitic imidazolate framework-8 precursor. The double-defect structure and the carbon-based substrates significantly promoted the efficiency of photogenerated electron–hole pair separation, meanwhile, the 3 % Ni doping endows it with great photocatalytic performance as elucidated by photodegradation assays of methylene blue (MB) and density functional theory (DFT) calculations, reinforcing the generation of reactive oxygen species (ROS) by ZnO and showing obvious advantages in antibacterial properties. As the enhanced photogenerated electron transfer and the ROS damage underwent localized accumulation, the PSs disturbed the bacterial membrane integrity and caused bacterial ATP synthesis inhibition, further leading to bacterial lysis and promoting bacterial deaths. Additionally, the PSs showed outstanding efficacy in eradicating bacterial biofilms. Simultaneously, the significantly enhanced PDT antibacterial performance of the PSs in vivo could initiate wound tissue repair and trigger anti-inflammatory reactions by significantly regulating the expression levels of regeneration- and inflammation-related genes or proteins. Furthermore, the PSs consistently exhibited favorable compatibility both in vitro and in vivo. In summary, this study offers evidence of the remarkably efficient and biologically safe performance of Ni-ZnO@C PSs, with antibacterial properties advancing wound healing, both in controlled laboratory environments and living organisms, further underscoring their substantial potential for biomedical applications. [Display omitted] [ABSTRACT FROM AUTHOR]

• Effect of MEG conductivity and axial Ocfp gradient on power property is explored. • A continuous power output from SC-(50 %/25 %) MEG with a p mo of 27.37 µW/cm2. • Reusable SC-(50 %/25 %) MEG has good environment adaptability. Moist-electric generation, a green and environmentally friendly energy harvesting technology, is undoubtedly one of the effective methods to alleviate energy shortages and environmental damage. However, the lack of fiber-like moist-electric generators (MEGs) that combine continuous power generation and high electrical output performance has constrained the development of moist-electric in the fields of flexible wearable and self-power supplies. In this work, sodium alginate (SA)/multi-walled carbon nanotubes (MWCNT) fibers with axial heterogeneous (axi-he) of oxygen-containing functional groups (Ocfgs) are prepared through a mold forming method in assistance with the coagulation process. The interaction between axi-he MEG and moisture is investigated by analyzing the electrical signal changes of dried MEG under moisture stimulation. The maximum output voltage and current of axi-he MEG can reach 0.35 V and 1.92 µA under the stimulation of moisture. Based on the regulation of Ocfgs, axi-he MEG has a continuous high moist-electric performance and environmental adaptability. The maximum output power density (P mo) of axi-he MEG with a length of only 2 cm can reach 27.37 µW cm–2 at RH = 90 %, which exceeds most of the MEGs reported in literature. Meanwhile, a continuous output voltage of 0.33–0.37 V for more than 15 h can be obtained from this axi-he MEG. Thus, the axi-he MEG from Ocfg distribution design and mold forming method provides a new way of clean energy generation using moisture from the ambient environment, exhibiting enormous potential in energy supply for Internet of Things (IoT) devices. [Display omitted] [ABSTRACT FROM AUTHOR]

Electrochemical impedance spectroscopies of different solid-solid contact states in all-solid-state lithium batteries are simulated through finite element method, which afford quantitative rules for diagnosing the actual solid-solid contacts from electrochemical impedance spectroscopy results.

Hybrid multilevel converters have gained more popularity due to their unique superiority. Thus, the T2C-HB converter is adopted in this article which consists a T-type converter (T2C) and three H-bridge (HB) cells. This hybrid converter combines the advantages of these two topologies and can output the same voltage level by adopting fewer switching devices compared with other multilevel converters. However, due to the high switching frequency of the HB switches, they may fail in practice which will cause serious deterioration in the output waveform and compromise the reliability of the entire system. Thus, a fault-tolerant control method based on floating capacitor voltage balance is proposed in this article. First, based on the level-shifted pulse width modulation (LS-PWM) method, the fault-tolerant control is accomplished by modifying the three-phase reference voltage. Second, a strategy which bypasses the HB equivalently when the absolute value of output voltage exceeds the peak value of the dc-link voltage is proposed to balance the floating capacitor voltage. Besides, the three-phase reference voltage is modified again utilizing the similar idea in order to balance the line voltage. Consequently, the line voltage remains unchanged during postfault operation and the floating capacitor voltage can restore balance without excessive fluctuation. Finally, the feasibility and correctness of the proposed method are verified by simulation and experimental results.

Hybrid multilevel converters have gained more popularity due to their unique superiority. Thus, the reduced switch hybrid multilevel (RSHMC) converter is adopted in this article which consists three H-bridge cells and a Vienna rectifier. The RSHMC converter combines the advantages of these two topologies and can output higher voltage level by adopting fewer switching devices compared with other multilevel converters. However, the Vienna rectifier of the RSHMC converter has the inherent current zero-crossing distortion (CZCD) problem, which will increase the total harmonic distortion of the grid-side current. Thus, a modulation method based on phase disposition-pulsewidth modulation is proposed to eliminate the CZCD of the RSHMC converter by selecting redundant switching states. Besides, in order to ensure the normal operation of the RSHMC converter, the proposed modulation method can also realize the voltage balance control of the floating capacitor and the neutral point which is also realized by selecting the switching states to charge or discharge. Consequently, the RSHMC converter can operate normally with balanced voltage and without CZCD after adopting the proposed modulation method. Finally, the feasibility and correctness of the proposed modulation method are verified by simulation and experimental results.

Flying-capacitor (FC) five-level topology with lower total blocking voltage is a potential topology in the medium-voltage application. Still, under high modulation indexes, conventional modulation methods cannot guarantee the stability of the FC voltage, resulting in increased volume and capacity of passive components and limiting its application. To achieve capacitor voltage balance at various modulation indexes with a modulation method, this article proposes a hybrid virtual SPWM method that modifies the carrier and modulation waves based on conventional SPWM, achieving FC voltage balance under full-modulation and full-frequency conditions. Due to the advantage of the topology without neutral point voltage control, HVSPWM can be seamlessly switched to the hybrid virtual DPWM, which can achieve different control objectives while satisfying the stability of the FC voltage. The proposed method has the same expansion capability as the topology, meeting the requirements of the future development. The effectiveness of the proposed method is verified by the simulations and experiments.

Low yields of crops, especially rice, are caused by climate change and environmental stress concerns such as drought, temperature fluctuations, and salinity in arid and semi-arid locations around the globe. Rice is one of the essential crops for human consumption and one of the most commonly farmed cereals on the planet earth, but its growth is severely retarded by excessive salt, which influences rice development and production, leading to economic loss. Salt stress induces osmotic stress and ionic toxicity in rice by altering the environment, leading to water deprivation and accumulation of toxic ions, thereby triggering specific physiological and molecular responses in the rice plants. Many factors may affect rice production and cereal quality via its interaction with salinity. This review focuses on some influential factors (photosynthesis, osmosis, micro and macronutrients, microbial flora, rice growth, development, and genes) that may reduce rice production in saline soils. The review also describes the responsive mechanism of rice to salinity and the genetic susceptibility of rice. In light of the challenges posed by the growing global population and limited agricultural land, it is imperative to consider the influential factors discussed in this review, along with genetic susceptibility to improve rice production in terms of quantity and quality under saline soil conditions.

High-quality phase-pure formamidinium lead triiodide (FAPbI3) perovskite film needs to be fabricated under strict control of the surrounding atmosphere, which becomes more rigorous when large-area FAPbI3film is involved, leading to high-performance FAPbI3perovskite solar cells and modules predominantly carried out in an inert gas-filled atmosphere. In this work, we propose a scalable printing strategy for the large-area high-quality phase-pure FAPbI3film under a high-humidity atmosphere (up to 75% ± 5% relative humidity) by regulating the perovskite precursor ink with a functional perfluoroalkylsulfonyl quaternary ammonium iodide. This approach decreases the energy barriers of cubic phase formation and heterogeneous nucleation, thereby regulating the FAPbI3crystallization. The printed photovoltaic small-area cells and large-area modules achieved remarkable power conversion efficiencies of 24.37% and 22.00%, respectively. Specifically, the unencapsulated device exhibits superior operational stability with T90 > 1,060 h, ambient stability with T90 > 2,020 h, and thermal stability with T90 > 2,350 h.

Direct dehydrogenation of carboxylic acids to their unsaturated counterparts represents a valuable transformation for complex molecule synthesis, which, however, has been challenging to achieve. In addition, the current carbonyl desaturation methods are almost all based on oxidative conditions. Here we report an Ir-catalyzed redox-neutral transfer dehydrogenation approach to directly convert carboxylic acids to either α,β- or β,γ-unsaturated counterparts. These reactions avoid using oxidants or strong bases, thus, tolerating various functional groups. The combined experimental and computational mechanistic studies suggest that this transfer hydrogenation reaction involves directed C–H oxidative addition, β-H elimination, and dihydride transfer to an alkene acceptor with C(sp3)–H reductive elimination as the turnover-limiting step.

In this paper, Ti3C2TxMXene/Cu–Bi bimetallic sulfide (Ti3C2Tx/BiCuS2.5) composites were prepared by a simple in situdeposition method for electrocatalytic nitrogen reduction reaction (eNRR). Compared to Ti3C2Tx/Bi2S3and Ti3C2Tx/CuS, the eNRR performance of Ti3C2Tx/BiCuS2.5is significantly improved. The results show that Ti3C2Tx/BiCuS2.5exhibits a NH3yield of 62.57 μg h–1mg–1cat.in 0.1 M Na2SO4at −0.6 V vs reversible hydrogen electrode, and the Faradaic efficiency (FE) reaches 67.69%, which is better than that of Ti3C2Tx/CuS (NH3yield: 52.26 μg h–1mg–1cat., FE: 34.15%) and Ti3C2Tx/Bi2S3(NH3yield: 54.04 μg h–1mg–1cat., FE: 37.38%). According to density functional theory calculations, the eNRR at the Ti3C2Tx/BiCuS2.5surface is the alternating pathway. The 1H NMR experiment of 15N proves that the N of NH3generated in the experiment originates from N2passed during the experiment.

Terephthalic polyesters are important engineering plastics and can crystallize into multiple crystal phases, including the mesophase in processing. However, the formation process and structural characteristics for the unique long-range ordered mesophase of terephthalic polyesters are still not well understood. Herein, we investigated the crystal polymorphism, crystallization kinetics, phase transition, and mechanical properties of a medium-chain terephthalic polyester, poly(hexamethylene terephthalate) (PHT). A new long-range ordered mesophase (named as the δ phase) is discovered for PHT during quiescent melt crystallization at a low crystallization temperature (Tc= 10–30 °C). However, the α and β crystal phases are crystallized at a medium (40–80 °C) and high (90–130 °C) Tc, respectively. The mesomorphic δ phase has a long-range order with a layered structure and inclined chain packing, which shows faster chain relaxation and smaller lamellar thickness than the α and β phases. The mesomorphic δ phase is metastable and converts into the stable β phase upon heating or high-temperature annealing. Mechanical properties of PHT can be well tuned by crystal polymorphs. The mesomorphic δ phase of PHT has good transparency and ductility, while the α and β phases possess a higher yield strength and modulus. This work provides an in-depth understanding of the mesophase formation and complex crystal polymorphism of terephthalic polyesters.

We present an optical parametric amplifier (OPA), pumped by an Yb fiber laser system, for efficiently generating mid-infrared femtosecond optical pulses over a wide wavelength tuning range of 3.5- $16~\mu $ m. Our scheme starts with two cascaded BBO OPA stages for providing high-power pulses at 1.09- $1.47~\mu $ m with ~200 fs pulse duration, which are used as the seed source for a subsequent mid-infrared OPA based on a BaGa4Se7 (BGSe) crystal. Therefore, with a moderate parametric gain of 4-6 from the final-stage BGSe OPA, a quantum conversion efficiency of higher than 24% is obtained for the mid-infrared idler wave over the full wavelength tuning range at 3.5- $16~\mu $ m. We expect that the source would be useful for applications in mid-infrared spectroscopy.

Aluminum is an attractive alternative fuel, but it burns very inefficiently due to the formation of a dense Al2O3layer which prevents O2from diffusion to the surface of Al particles. In previous experiments, the combustion of millimeter-sized Al (mAl) particles in the fluidized bed has achieved a substantial increase in the combustion efficiency, but further improvements are still needed. In this study, the effects of reaction atmosphere on the fluidized combustion of mAl particles were investigated. The experiments with different O2/H2O/CO2concentrations were conducted. The experimental results indicate that the combustion efficiency of mAl particles in fluidized bed increases as the mole fraction of O2, H2O or CO2increases, and the highest combustion efficiency can reach 38.7%. After the analysis of the oxide film on the surface of aluminum particles, it was found that it is easier to generate the unstable θ-Al2O3under CO2atmosphere, and it is easier to generate the unstable γ-Al2O3and θ-Al2O3under H2O atmosphere. The unstable Al2O3film is more likely to be abraded in the fluidized bed, which leads to the effective improvement of the combustion efficiency.

Due to numerous advantages of thyristors, such as low conduction loss and low cost, using thyristors to design solid-state circuit breakers (SSCBs) to protect dc microgrids has become increasingly popular. However, the majority of existing bidirectional thyristor-based SSCBs (TCBs) have one or more following drawbacks: high conduction loss, lack of operating current interrupting ability, low current breaking reliability, unsuitable for fast-reclosing protection, and the need to use ample thyristors. To address these problems, a new bidirectional TCB is proposed in this article. First, the proposed method could break both bidirectional operating and fault currents reliably by actively turning on its auxiliary thyristors. Second, the conduction loss of the proposed TCB is extremely low. Third, the proposed TCB can realize fast-reclosing protection function by masterly using an LC resonant circuit, which would ensure a safe restart of dc microgrids after a fault. Finally, the proposed TCB is very economical since only one additional set of auxiliary parallel thyristors is needed. Thus, all the above merits are making the proposed TCB a promising candidate for protecting dc microgrids. The parameter design guidelines, scaled-down experimental results, and comparative studies of the proposed TCB are also presented.

In this paper, we consider a challenging secure wireless sensing scenario where a legitimate radar station (LRS) intends to detect a target at unknown location in the presence of an unauthorized radar station (URS). We aim to enhance the sensing performance of the LRS and in the meanwhile prevent the detection of the same target by the URS. Under this setup, conventional stealth-based approaches such as wrapping the target with electromagnetic wave absorbing materials are not applicable, since they will disable the target detection by not only the URS, but the LRS as well. To tackle this challenge, we propose in this paper a new target-mounted IRS approach, where intelligent reflecting surface (IRS) is mounted on the outer/echo surface of the target and by tuning the IRS reflection, the strength of its reflected radar signal in any angle of departure (AoD) can be adjusted based on the signal’s angle of arrival (AoA), thereby enhancing/suppressing the signal power towards the LRS/URS, respectively. To this end, we propose a practical protocol for the target-mounted IRS to estimate the LRS/URS channel and waveform parameters based on its sensed signals and control the IRS reflection for/against the LRS/URS accordingly. Specifically, we formulate new optimization problems to design the reflecting phase shifts at IRS for maximizing the received signal power at the LRS while keeping that at the URS below a certain level, for both the cases of short-term and long-term IRS operations with different dynamic reflection capabilities. To solve these non-convex problems, we apply the penalty dual decomposition method to obtain high-quality suboptimal solutions for them efficiently. Finally, simulation results are presented that verify the effectiveness of the proposed protocol and algorithms for the target-mounted IRS to achieve secure wireless sensing, as compared with various benchmark schemes.

This paper investigates an intelligent reflecting surface (IRS) enabled multiuser integrated sensing and communications (ISAC) system, which consists of one multi-antenna base station (BS), one IRS, multiple single-antenna communication users (CUs), and one target at the non-line-of-sight (NLoS) region of the BS. The IRS is deployed to not only assist the communication from the BS to the CUs, but also enable the BS’s NLoS target sensing based on the echo signals from the BS-IRS-target-IRS-BS link. We consider two types of targets, namely the extended and point targets, for which the BS aims to estimate the complete target response matrix and the target’s direction-of-arrival (DoA) with respect to the IRS, respectively. To provide full degrees of freedom for sensing, we consider that the BS sends dedicated sensing signals in addition to the communication signals. Accordingly, we model two types of CU receivers, namely Type-I and Type-II CU receivers, which do not have and have the capability of canceling the interference from the sensing signals, respectively. Under each setup, we jointly optimize the transmit beamforming at the BS and the reflective beamforming at the IRS to minimize the Cramér-Rao bound (CRB) for target estimation, subject to the minimum signal-to-interference-plus-noise ratio (SINR) constraints at the CUs and the maximum transmit power constraint at the BS. We present efficient algorithms to solve the highly non-convex SINR-constrained CRB minimization problems, by using the techniques of alternating optimization, semi-definite relaxation, and successive convex approximation. Numerical results show that the proposed design achieves lower estimation CRB than other benchmark schemes, and the sensing signal interference cancellation at Type-II CU receivers is beneficial when the number of CUs is greater than one.

Both passive and active intelligent reflecting surfaces (IRSs) can be deployed in complex environments to enhance wireless network coverage by creating multiple blockage-free cascaded line-of-sight (LoS) links. In this paper, we study a multi-passive/active-IRS (PIRS/AIRS) aided wireless network with a multi-antenna base station (BS) in a given region. First, we divide the region into multiple non-overlapping cells, each of which may contain one candidate location that can be deployed with a single PIRS or AIRS. Then, we show several trade-offs between minimizing the total IRS deployment cost and enhancing the signal-to-noise ratio (SNR) performance over all cells via direct/cascaded LoS transmission with the BS. To reconcile these trade-offs, we formulate a joint multi-PIRS/AIRS deployment problem to select an optimal subset of all candidate locations for deploying IRS and also optimize the number of passive/active reflecting elements deployed at each selected location to satisfy a given SNR target over all cells, such that the total deployment cost is minimized. However, due to the combinatorial optimization involved, the formulated problem is difficult to be solved optimally. To tackle this difficulty, we first optimize the reflecting element numbers with given PIRS/AIRS deployed locations via sequential refinement, followed by a partial enumeration to determine the PIRS/AIRS locations. Simulation results show that our proposed algorithm achieves better cost-performance trade-offs than other baseline deployment strategies.