Search

To ensure the users’ immersive experience in cross-modal communication, overcoming the end-to-end (E2E) latency through prediction has attracted attention and shown its superiority. However, existing prediction schemes encounter formidable challenges in the presence of multi-modal signals, primarily to adapt and satisfy the prediction requirements of diverse multi-modal services, as well as to fully exploit and effectively utilize the correlation features of multi-modal signals for precise prediction. To this end, this work presents a flexible prediction scheme for low-latency cross-modal communication. Specifically, we first propose an adaptive prediction-aware cross-modal communication framework, which reduces the delay by predicting and transmitting the future multi-modal signals in advance, and flexibly adjusts the prediction horizon to satisfy the prediction accuracy of different multi-modal services. Next, we design an information gain-assisted graph attention (IGGA) method for cross-modal signal prediction, which leverages the graph attention block to extract the intra-modal, inter-modal spatial and temporal correlation features, and effectively optimize and utilize these features with the information gain (IG), thereby facilitating precise cross-modal signal prediction. Finally, numerical experiments conducted on a self-built dataset, a public dataset, and a multi-modal acupuncture platform demonstrate the superiority of the proposed scheme in low-latency cross-modal communication.

Studies have increasingly focussed on the relationship between periodontitis (PD) and preeclampsia (PE). However, conclusions have not been consistent, and it is unclear whether any causal relationship exists between them and whether causality is bidirectional. This study employed Mendelian randomisation (MR) analysis to investigate the potential bidirectional causal relationship between PD and PE.

Metal–organic frameworks (MOFs) have emerged as a highly promising platform for various sensing applications due to their tunable structures and functionalities. In the present work, a Eu3+-doped mixed-ligand MOF, namely, the Eu3+@UiO-66-IPA, exhibited excellent luminescent properties and high fluorescence stability in aqueous media, displaying dual-emission peaks under 395 and 615 nm excitation that were readily visible to the naked eye. Importantly, the presence of fluoride ions (F–) promoted the “antenna effect” between the ligand and the Eu3+centers, which significantly enhanced the emission intensity of the Eu3+characteristic peak. In addition, the addition of F–also inhibited the quenching effect of high-energy O–H bonds existing in the aqueous environment. Notably, Eu3+@UiO-66-IPA demonstrated exceptional selectivity for F–over a range of competing anions, with a remarkable limit of detection as low as 0.22 μM. The developed Eu3+-doped mixed-ligand MOF system offers a highly promising strategy for the simple and accurate sensing of F–in practical applications.

With countries proposing the goal of carbon neutrality, the clean transformation of energy structure has become a hot and trendy issue internationally. Renewable energy generation will account for the main proportion, but it also leads to the problem of unstable electricity supply. At present, large-scale energy storage technology is not yet mature. Improving the flexibility of coal-fired power plants to suppress the instability of renewable energy generation is a feasible path. Thermal energy storage is a feasible technology to improve the flexibility of coal-fired power plants. This article provides a review of the research on the flexibility transformation of coal-fired power plants based on heat storage technology, mainly including medium to low-temperature heat storage based on hot water tanks and high-temperature heat storage based on molten salt. The current technical difficulties are summarized, and future development prospects are presented. The combination of the thermal energy storage system and coal-fired power generation system is the foundation, and the control of the inclined temperature layer and the selection and development of molten salt are key issues. The authors hope that the research in this article can provide a reference for the flexibility transformation research of coal-fired power plants, and promote the application of heat storage foundation in specific coal-fired power plant transformation projects.

With the increasing demand for energy and worsening environmental issues, the application of photothermal materials has been widely explored due to their high energy conversion capabilities and environmental friendliness. In this work, metal–carbon fiber composites were prepared and subjected to photothermal and water evaporation performance tests alongside pure metals and pyrolytic phenolic resin materials. The results show that the addition of metals effectively improved the photothermal efficiency by narrowing the molecular energy gaps of the materials, indicating a strong synergistic enhancement effect between metals and carbon materials. This study provides a theoretical basis for the design of high-performance photothermal conversion materials.

The possible mechanism of metal toxicity is oxidative stress and mitochondrial DNA damage. However, the association between environmental metal exposure and mitochondrial DNA damage and the potential mediators remain unclear. In this study, a total of 155 participants from general population were enrolled. In 2016, we measured participants’ blood and urinary chromium, cadmium, manganese, and lead concentrations, serum malondialdehyde (MDA) concentration, urinary 8-hydroxy-2 deoxyguanosine (8-OHdG) concentration, serum activity of superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px). In 2018, we measured participants’ serum mitochondrial DNA polymerase γ (mtDNApolγ) activity, serum mitochondrial transcription factor A (mtTFA) activity, and mitochondrial DNA copy number (mtDNACN). We used general liner regression model and mediation analysis to explore the associations and potential mediation effects, respectively. Blood cadmium was associated with GSH-Px (βDoubling increase= 12.48), blood lead was associated with SOD (βDoubling increase= 5.41), and blood chromium was associated with mtDNApolγ (βDoubling increase=  − 0.54; βTertile 3 vs 1=  − 0.24) and mtDNACN (βDoubling increase=  − 0.22). Urinary cadmium was associated with mtDNApolγ (βTertile 3 vs 1= 0.22) and 8-OHdG (βDoubling increase= 0.24). We did not find a significant mediation effect of oxidative stress on the association between metal exposure and mtDNA damage, but we found that mtDNApolγ accounted for 16% of the association between blood Cr and mtDNACN (P= 0.1). The findings suggest that metal exposure was associated with oxidative stress and mtDNA damage, and mtDNA transcription replicase might mediate the association between metal exposure and mtDNA damage.

In this paper, we study symbol-level precoding (SLP) design for time-domain peak-to-average power ratio (PAPR) reduction in a multi-user MISO-OFDM transmission through the idea of constructive interference (CI). Specifically, we design the precoded transmit signals that minimize the symbol-level transmit power subject to per-antenna time-domain PAPR constraint and CI condition, using the knowledge of both data information and channel state information (CSI), based on which a non-convex problem is established. This non-convex problem is transformed into a convex one by the vectorization and relaxation method. For the relaxed problem, we employ Lagrangian method and Karush-Kuhn-Tucker (KKT) conditions to obtain a closed-form expression on the precoded signals as a function of the Lagrangian multipliers. Subsequently, we study the dual problem and obtain the optimal Lagrangian multipliers via the proposed alternating iterative algorithm. We further consider the practical communication scenario with imperfect CSI, where the original CI constraint is transformed into a probabilistic constraint in order to achieve robustness against statistically CSI errors. Numerical results validate that the proposed low-complexity algorithm achieves an enhanced performance over existing methods in terms of transmit power, PAPR and computation complexity, both in ideal perfect CSI and practical imperfect CSI cases.

We propose a parallel constructive interference (CI)-based symbol-level precoding (SLP) approach for massive connectivity in the downlink of multiuser multiple-input single-output (MU-MISO) systems, with only local channel state information (CSI) used at each processor unit and limited information exchange between processor units. We explore and reveal the separability of the SLP model. By reformulating the power minimization (PM) SLP problem and exploiting the separability of the corresponding reformulation, the original problem is decomposed into several parallel subproblems via the ADMM framework with closed-form solutions, leading to a substantial reduction in computational complexity. The sufficient condition for guaranteeing the convergence of the proposed approach is derived, based on which an adaptive parameter tuning strategy is proposed to accelerate the convergence rate. To avoid the large-dimension matrix inverse operation, an efficient algorithm is proposed by employing the standard proximal term and by leveraging the singular value decomposition (SVD). Furthermore, a prox-linear proximal term is adopted to fully eliminate the matrix inversion, and a parallel inverse-free SLP (PIF-SLP) algorithm is finally obtained. Numerical results validate our derivations above, and demonstrate that the proposed PIF-SLP algorithm can significantly reduce the computational complexity compared to the state-of-the-arts.

Background/Objectives: Bariatric surgery, as indicated for treatment of morbid obesity, has been studied in association with short term effects on ocular pathology. However, effects of surgery on postoperative disease incidence is largely unknown. Subjects/Methods: In this retrospective cohort study, the TriNetX United States Collaborative Network national database, was queried for patients with an ICD-10 code for morbid obesity and a procedural code for bariatric surgery. Patients were propensity score matched across baseline demographics at the time of surgery and compared to those presenting with an ICD10 code for morbid obesity with no records of a procedural code for bariatric surgery, identifying 42,408 patients per cohort. New diagnoses or procedural codes found after the surgical index date for diabetic retinopathy, age-related macular degeneration, glaucoma, low vision, and blindness along with pertinent treatment metrics were monitored. Results: Bariatric surgery was found to be associated with reduced future risk of diabetic retinopathy (RR: 0.283; 95% CI: 0.252–0.319), macular edema (RR: 0.224; 95% CI: 0.170–0.297), vitreous hemorrhage (RR: 0.459; 95% CI: 0.323–0.653), ocular hypertension (RR: 0.387; 95% CI: 0.387–0.487), glaucoma (RR: 0.360; 95% CI: 0.326–0.399), use of ocular pressure lowering medications (RR: 0.565; 95% CI: 0.496–0.644), age-related macular degeneration (RR: 0.628; 95% CI: 0.447–0.882), cataract surgery (RR: 0.524; 95% CI: 0.448–0.612), and low vision and blindness (RR: 0.328; 95% CI: 0.294–0.365) compared to patients not surgically managed. Conclusions: The present analysis comprising a large US cohort of patients suggests that bariatric surgery is associated with a decreased risk of future ocular morbidity and mortality.

We present an integrated filter on silicon photonics with wide free-spectral-range and sub-nm bandwidth, which is particularly suitable for programmable photonic circuit with arbitrary spectral responses. The unique feature is that its extinction ratio, namely the transmission coefficient within the bandwidth, can be independently controlled from 0 to 1 without affecting the rest optical span. Thus, a series of such building blocks with varying center wavelengths can be concentrated to form a programmable photonic circuit that can generate arbitrary spectral responses with easy control logic. The notch filter is a Mach–Zenhder-Interferometer with narrowband contra-directional couplers (CDC) and the filter performance is greatly enhanced compared with previous results. The bandwidth is reduced by a factor of 4 and the device length is only one third of previous demonstration.

This paper addresses the constructive interference (CI) precoding problem under per-antenna power constraint (PAPC) in the downlink of multi-user multiple-input single-output (MU-MISO) systems. In this setup, we extend the phase rotation metric and symbol scaling metric of CI precoding under sum power constraint (SPC) to the scenario of PAPC. Against SPC, the scenario of PAPC represents a practical constraint acknowledging that each antenna would have its dedicated power amplifier. Nevertheless, the optimization problem of CI-PAPC precoding becomes more challenging than that under SPC. By analyzing the KKT conditions and leveraging the generalized matrix inverse theory, we obtain a closed-form structure of the CI-PAPC precoder as a function of introduced variables, which facilitates a low-complexity solver. Since the power constraint of each antenna is not always active under PAPC, existing iterative schemes under CI-SPC are no longer applicable. Therefore, the primal-dual interior point method (IPM) is employed to solve the simplified problem with reduced complexity and fast convergence. Simulation results verify our mathematical derivations and demonstrate that our proposed method can reduce the complexity of solving CI-PAPC problem while preserving the error-rate performance, which promotes the practical implementation of CI precoding in real PAPC scenarios.

Pattern reconfigurable multiple-input multiple-output (PR-MIMO) can manipulate the wireless channel according to different communication requirements. In this paper, we discuss the potential of constructive interference (CI)-based symbol-level precoding (CI-SLP) in PR-MIMO communication systems. The joint design problem that optimizes the SLP strategy and the radiation pattern of PR-MIMO for phase-shift keying (PSK) modulation is formulated to maximize the worst serviced user’s communication quality. Since the optimization variables are softly-coupled, we employ the alternating optimization framework to decompose the joint design problem into the SLP design sub-problem and the pattern design sub-problem. We simplify the pattern design sub-problem and propose an interior-point algorithm, where a sequential optimization-based scheme is further proposed as a sub-optimal solution with low complexity. Furthermore, the discussion is extended to quadrature amplitude modulation (QAM) modulated systems, where a special stopping criterion is proposed to guarantee the performance gain of the proposed scheme. The practical realization of the designed reconfigurable antenna array is also discussed, where we propose a design scheme using programmable metasurface antennas based on time-division switching to enable quick and adaptive pattern reconfiguration. Numerical results demonstrate that the radiation pattern configurability can further enhance the benefit of SLP over conventional precoding approaches.

In this paper, we present an innovative symbol-level precoding (SLP) approach for a wideband multi-user multi-input multi-output (MU-MIMO) downlink integrated sensing and communications (ISAC) system employing faster-than-Nyquist (FTN) signaling. Our proposed technique minimizes the minimum mean squared error (MMSE) for the sensed parameter estimation while ensuring the communication per-user quality-of-service through the utilization of constructive interference (CI) methodologies. While the formulated problem is non-convex in general, we tackle this issue using proficient minorization and successive convex approximation (SCA) strategies. Numerical results substantiate that our FTN-ISAC-SLP framework can increase communication throughput by up to 20% while reducing sensing MMSE by about 1 dB.

This paper investigates the utilization of simultaneously transmitting and reflecting RIS (STAR-RIS) in supporting joint physical layer security (PLS) and covert communications (CCs) in a multi-antenna millimeter wave (mmWave) system, where the base station (BS) communicates with both covert and security users while defeating eavesdropping by wardens with the help of a STAR-RIS. Specifically, analytical derivations are performed to obtain the closed-form expression of warden’s minimum detection error probability (DEP). Furthermore, the asymptotic result of the minimum DEP and the lower bound of the secure rates are derived, considering the practical assumption that BS only knows the statistical channel state information (CSI) between STAR-RIS and the wardens. Subsequently, an optimization problem is formulated with the aim of maximizing the average sum of the covert rate and the minimum secure rate while ensuring the covert requirement and quality of service (QoS) for legal users by jointly optimizing the active and passive beamformers. Due to the strong coupling among variables, an iterative algorithm based on the alternating strategy and the semi-definite relaxation (SDR) method is proposed to solve the non-convex optimization problem. Simulation results indicate that the performance of the proposed STAR-RIS-assisted scheme greatly surpasses that of the conventional RIS scheme, which validates the superiority of STAR-RIS in simultaneously implementing PLS and CCs.

In this paper, we study the interference exploitation precoding in the presence of distortion from nonlinear power amplifiers (PAs) in multi-user multiple-input single-output (MU-MISO) downlink communication systems. We consider the memoryless polynomial model of nonlinear PAs, which is incorporated into the symbol-level precoding (SLP) design to allow the PA nonlinearities in the constructive interference (CI) exploitation. The optimization problem that aims to enhance the signal-to-interference-plus-noise ratio (SINR) without investing additional transmit signal power is formulated for both PSK and QAM signaling. Since the original optimization problem is nonconvex, we first introduce auxiliary variables to transform the optimization problem and adopt the alternating optimization framework for the new optimization problem. For non-convex subproblems, additional auxiliary variables are introduced and several approximations are employed to transform the problem into a semidefinite programming (SDP) form, where the semidefinite relaxation (SDR) method is adopted to obtain feasible solutions. In order to reduce the computational cost of the iterative algorithm, we further propose a low-complexity algorithm for the original PA-aware SLP optimization problem. Numerical results verify the superiority of our proposed PA-aware SLP approach in the presence of nonlinear PAs in the MU-MISO downlink in terms of the error-rate performance over the state-of-the-art.

Gatemon qubits are the electrically tunable cousins of superconducting transmon qubits. In this work, we demonstrate the full coherent control of a gatemon qubit based on hole carriers in a Ge/Si core/shell nanowire, with the longest coherence times in group IV material gatemons to date. The key to these results is a high-quality Josephson junction obtained using a straightforward and reproducible annealing technique. We demonstrate that the transport through the narrow junction is dominated by only two quantum channels, with transparencies up to unity. This novel qubit platform holds great promise for quantum information applications, not only because it incorporates technologically relevant materials, but also because it provides new opportunities, like an ultrastrong spin–orbit coupling in the few-channel regime of Josephson junctions.

To reconcile the contradictory wettability requirements for the reduction and oxidation half-reactions in overall CO2photoreduction, an alternately hydrophobic catalyst is constructed through selectively hydrophobic modification and a charge-carrier-guided strategy.

When shield tunneling is performed in water-rich silt and fine sand strata, the grout becomes runny when diluted by groundwater. After dilution, the filling effect of the grout is not significant, and the level of surface settlement is very high. In this study, based on bidding section 04 of Tianjin Metro Line 11, traditional grouting materials were selected to conduct response surface method (RSM) tests. The purposes of the RSM analysis were to analyze the interactions between materials and their influences on grout performance and to optimize the grout mix ratio. Various admixtures were compared to assess the effects of different admixtures and compositions on the dispersion resistance and flow performance of the grout. Finally, a shield synchronous grouting test system was developed, and a similar indoor grouting simulation test was performed to analyze the influences of the different admixtures on the filling effects and to determine a reasonable grout mix ratio. The following three results were obtained. (1) The RSM was suitable for grout performance prediction and grout mix ratio optimization, and hydroxyethyl cellulose could improve the grout performance and increase the bond performance between the cementing material and aggregate. (2) Admixture incorporation enhancement could improve the grout utilization rate and increase the diffusion distance at the top of the tunnel, which would be conducive to filling the gap at the tail end of the shield. (3) The optimal preparation scheme of grout in water-rich fine sand formations included a water–binder ratio of 0.72, cement–sand ratio of 0.80, fly ash content of 5%, bentonite content of 14.94%, and admixture content of 0.8%–0.9%

RNA N6-methyladenosine (m6A), as the most abundant modification of messenger RNA, can modulate insect behaviors, but its specific roles in aggregation behaviors remain unexplored. Here, we conducted a comprehensive molecular and physiological characterization of the individual components of the methyltransferase and demethylase in the migratory locust Locusta migratoria. Our results demonstrated that METTL3, METTL14and ALKBH5were dominantly expressed in the brain and exhibited remarkable responses to crowding or isolation. The individual knockdown of methyltransferases (i.e., METTL3and METTL14) promoted locust movement and conspecific attraction, whereas ALKBH5knockdown induced a behavioral shift toward the solitary phase. Furthermore, global transcriptome profiles revealed that m6A modification could regulate the orchestration of gene expression to fine tune the behavioral aggregation of locusts. In summary, our in vivocharacterization of the m6A functions in migratory locusts clearly demonstrated the crucial roles of the m6A pathway in effectively modulating aggregation behaviors.

High-temperature annealing is widely recognized as an effective way to improve the durability of Pt/C cathode catalysts used in proton exchange membrane fuel cells (PEMFCs), yet systematic studies on its effects on PEMFC performance are still lacking. Herein, we explore the effect of high-temperature annealing on the PEMFC performance, based on a thorough comparative analysis of Pt/C catalysts annealed at temperatures ranging from 500–900°C. Our results reveal that high-temperature annealing not only enhances the catalyst durability but also substantially increases Pt utilization, which in turn drives the increase in mass activity and the enhancement of low-current-density performance. Based on an array of electrochemical and physical characterization results, we infer that the increased utilization of Pt might stem from nanoparticle migration induced by high-temperature annealing, leading to closer proximity between Pt nanoparticles and ionomers. This reduced distance potentially enhances the accessibility of protons to the Pt nanoparticles, thereby improving the Pt utilization.

The hierarchical porous lattice implant with microscopic porosity, which resembles the original human bone structure, has significant potential application value. The microscopic porosity in the hierarchical porous lattice implant plays a crucial role in transporting nutrients and promoting tissue regeneration. However, it is difficult to fabricate microscopic pores smaller than 200 μm by powder bed fusion (PBF) processes due to the limitations of the laser spot size. In this study, the preparation of a hierarchical porous lattice implant with microscopic porosity is proposed by coupling structure design with the high scanning speed - short hatch spacing (HSSH) process formation. The structure-versus-process relationship is used to control the size and distribution of the microscopic pores, which meets the requirements of modulus and high biocompatibility. This proposed process breaks the inherent law where the higher the porosity, the higher the modulus of the lattice for the same lattice type. The modulus and porosity of the hierarchical porous implants could be flexibly tuned over a wide range (0.1–1.8 GPa and 63–84 %, respectively). The microscopic porosity is mainly distributed near the contour of the core rod, and the macroscopic porosity and microscopic porosity are approximately 73.70 % and 8.22 %, respectively. The problem of large errors in fitting the hierarchical porous lattice modulus calculation model according to the Gibson-Ashby equation has been solved. The mechanism of microscopic porosity formation was also analyzed. Furthermore, this method has the advantage of universal applicability, providing a feasible way for the development and application of porous materials.

Closed pores play a crucial role in improving the low-voltage (<0.1 V) plateau capacity of hard carbon anodes for sodium-ion batteries (SIBs). However, the lack of simple and effective closed-pore construction strategies, as well as the unclear closed-pore formation mechanism, has severely hindered the development of high plateau capacity hard carbon anodes. Herein, we present an effective closed-pore construction strategy by one-step pyrolysis of zinc gluconate (ZG) and elucidate the corresponding mechanism of closed-pore formation. The closed-pore formation mechanism during the pyrolysis of ZG mainly involves (i) the precipitation of ZnO nanoparticles and the ZnO etching on carbon under 1100 °C to generate open pores of 0.45–4 nm and (ii) the development of graphitic domains and the shrinkage of the partial open pores at 1100–1500 °C to convert the open pores to closed pores. Benefiting from the considerable closed-pore content and suitable microstructure, the optimized hard carbon achieves an ultrahigh reversible specific capacity of 481.5 mA h g–1and an extraordinary plateau capacity of 389 mA h g–1for use as the anode of SIBs. Additionally, some in situ and ex situ characterizations demonstrate that the high-voltage slope capacity and the low-voltage plateau capacity stem from the adsorption of Na+at the defect sites and Na-cluster formation in closed pores, respectively.

On Earth, high-speed rotating blades and rotors experience hypergravity, which is mainly derived from centrifugal force. Aluminum alloys are widely used in high-speed rotating machines. In particular, 7075 aluminum has excellent properties, providing it with great potential for application in high-temperature rotating parts. In this work, the cracking behavior and microstructural evolution characteristics of high-speed rotating blades under different stresses were studied. A specifically designed instrument and blades with multiple necks were assembled, and the stress was tuned by adding weight to the blade tip. Each rotating blade cracked on its root neck, indicating that the gradient hypergravitational force decreased from the root to the tip. The degree of high-temperature cracking obviously increased with a sawtooth-like tip, but the degree of low-temperature cracking did not obviously increase with a smooth tip. A comparison under a constant uniaxial force required a greatly increased ultimate cracking strength that was approximately 10–18 times greater than that under hypergravitational force at the same temperature. Force analysis indicated that the coupling of hypergravitational forces in the normal direction and torsional forces in the tangential direction accelerated cracking. A uniaxial force caused grains to extend along the blade direction. However, a tangential force cut these extended grains to accelerate cracking and grain refining. In this study, real-world simulated service conditions for commercial alloys rotating at high speeds and a new understanding of the mechanical properties of alloys under various severe conditions were provided.

A 38-year-old male patient was diagnosed as acute non-ST-segment elevation myocardial infarction on Apr 21st 2021 and he received percutaneous transluminal coronary angioplasty for RCA via transradial artery access. He sought for second percutaneous coronary intervention in our center for frequently exertional angina on Sep 13th 2021. Proximal right radial artery pulsation can not be touched in physical examination, indicating right radial artery occlusion (RAO). Distal transradial access was applied and RAO was confirmed via angiography. With balloon pre-dilation, the guidewire and guiding catheter crossed the occlusion and coronary intervention was successfully completed. A Reewarm 2.5 × 220 mm paclitaxel drug-coated balloon (Endovastec, China) was released at 12 atm in radial arterial lesion with 90 s. Pulsation of radial artery can be well palpated 24 h after PCI. No oral anticoagulant was added. The right radial artery remained patent after 8-month and 14-month follow-up and there was no abnormal sensation or obstacle of right hand.

AbstractFacility location and resource allocation play an essential role in the operational management of mobile health clinics (MHCs) as optimization of both can help medical service providers improve their service coverage under limited resources. In this paper, we consider the issue of maximizing the coverage of immunization services provided by MHCs in vulnerable communities such as school zones and census tracts. Since demand in communities overlaps with neighboring communities, this leads to the so-called mobile facility location with overlapped demand (MFL-OD). To capture the overlapped demand in different communities, we introduce a novel integer programming model with linear and bilinear constraints (BLCIP) and show that the BLCIP model is NP-hard. A polynomial-time approximation algorithm is proposed for the BLCIP, and the approximation ratio of the obtained solution is estimated. We implement the proposed model and approximation algorithm for a case study in the Houston Independent School District and its associated communities. Preliminary experiments demonstrate the efficacy of the proposed model and the efficiency of the proposed approximation method.

Ferromagnetic (FM) semiconductors combine the advantages of semiconductors (e.g., logic devices) and magnetic materials (e.g., memories) and have garnered increasing amounts of attention for more than half a century. However, the development of FM semiconductors faces challenges due to the scarcity of suitable candidates and their low Curie temperature. Traditionally, ferromagnetism is observed in transition metal compounds with octahedral coordination. In contrast, tetrahedral coordination compounds, with smaller crystal field splitting and weaker antiferromagnetic (AFM) direct exchange, hold promise as potential candidates for high-temperature ferromagnets but remain largely unexplored. In this work, we propose that high-temperature FM semiconductors can be realized in tetrahedral coordination superlattices (SLs). On the basis of first-principles calculations, we systematically investigated a series of MX/TMX (MX denotes group 12–16, 13–15 or 14–14 tetrahedral semiconductors, TM denotes a 3d transition metal, X denotes the ligand) SL. Among them, SiC/CrC SL emerges as a stable FM semiconductor with an indirect band gap of 0.363 eV and a high Curie temperature (TC) of ∼935 K. Furthermore, the distributions of the Cr atomic layer and interlayer magnetic couplings are explored. A uniaxial-pressure-induced AFM-to-FM phase transition is predicted. These discoveries present novel opportunities for realizing high-temperature FM semiconductors in tetrahedral coordination SLs, offering potential advancements in future spintronic applications.

To simultaneously yield superior evaporation rate and output voltage in solar-driven interfacial evaporators, the synergetic integration of phase change materials and photothermal materials in 3D interfacial evaporators has been proposed. This integration strategy provides additional insights for exploring next-generation solar-driven power generation and water evaporation devices.

Atomic structure prediction and associated property calculations are the bedrock of chemical physics. Since high-fidelity ab initio modeling techniques for computing the structure and properties can be prohibitively expensive, this motivates the development of machine-learning (ML) models that make these predictions more efficiently. Training graph neural networks over large atomistic databases introduces unique computational challenges, such as the need to process millions of small graphs with variable size and support communication patterns that are distinct from learning over large graphs, such as social networks. We demonstrate a novel hardware–software codesign approach to scale up the training of atomistic graph neural networks (GNN) for structure and property prediction. First, to eliminate redundant computation and memory associated with alternative padding techniques and to improve throughput via minimizing communication, we formulate the effective coalescing of the batches of variable-size atomistic graphs as the bin packing problem and introduce a hardware-agnostic algorithm to pack these batches. In addition, we propose hardware-specific optimizations, including a planner and vectorization for the gather-scatter operations targeted for Graphcore’s Intelligence Processing Unit (IPU), as well as model-specific optimizations such as merged communication collectives and optimized softplus. Putting these all together, we demonstrate the effectiveness of the proposed codesign approach by providing an implementation of a well-established atomistic GNN on the Graphcore IPUs. We evaluate the training performance on multiple atomistic graph databases with varying degrees of graph counts, sizes, and sparsity. We demonstrate that such a codesign approach can reduce the training time of atomistic GNNs and can improve their performance by up to 1.5× compared to the baseline implementation of the model on the IPUs. Additionally, we compare our IPU implementation with a Nvidia GPU-based implementation and show that our atomistic GNN implementation on the IPUs can run 1.8× faster on average compared to the execution time on the GPUs.

Oxidation is one of the main failure modes of superalloys, and the initial oxidation of a superalloy provides clues for its failure analysis. NiCo-based superalloys exhibit superior mechanical properties, but their oxidation behaviour is still debatable, especially in terms of the ratio of Ni/Co. Here, we show the effect of the Ni/Co ratio on the initial oxidation behaviour at the nanoscale by in situenvironmental transmission electron microscopy (ETEM), which provides the initial microstructural changes in the γ/γ′ structure-based alloy. The results indicate that Ni-rich alloys exhibit better structural stability at high temperatures than Ni-deficient alloys. A high content of Ni promotes the formation of a dense oxide layer, inhibits the oxidation rate, and improves the oxidation resistance. This result will help to elucidate the basic process of oxide formation in NiCo-based single-crystal superalloys and provide ideas for improving their oxidation resistance for alloy design.

Ferromagnetic (FM) semiconductors with intrinsic spontaneous net magnetizations and semiconductivity show great potential in future spintronic applications such as low-energy-cost random access memories. However, room-temperature FM semiconductors have not yet been discovered, which hinders their practical applications. In this work, using first-principles calculations, we show that Curie temperature (TC) of the conventional FM semiconducting spinels ACr2X4(A = Cd, Zn, Hg; X = S, Se, Te) can be significantly increased via partially replacing the Cr by W ions. The alloyed structures of ACr1.5W0.5X4are predicted to be intrinsic room-temperature FM semiconductors with diverse electronic bandgaps. Among them, CdCr1.5W0.5Se4shows TCof ∼310 K, which is more than doubled that (∼150 K) of the pristine CdCr2Se4. These findings provide a new route to realize room-temperature FM semiconductors, which will be of great interest for the development of spintronics.

In miniature ion trap mass spectrometry, achieving a balance between isolation resolution and efficiency is a formidable challenge. The presence of absorption curves causes target ions to inadvertently absorb energy from AC signal components near their resonant frequencies. To mitigate this issue, SAM–SFM waveforms introduce a parameter known as the decreasing factor. Unlike SWIFT waveforms, SAM–SFM’s spectral profile intentionally departs from a rectangular window, adopting an arch-shaped excitation window to minimize the impact on target ions and improve ion isolation efficiency. SAM–SFM waveforms have the advantage of low computational complexity, enabling real-time computation using an embedded FPGA technology. Regardless of any parameter changes, the FPGA can consistently guarantee waveform output within 1 μs. This not only enhances throughput but also eliminates the need for a PC in miniature mass spectrometry devices. The performance of SAM–SFM has been validated on an improved “Brick” miniature ion trap mass spectrometer. Comparative experiments with SWIFT waveforms confirm the lossless unit-mass isolation capabilities of SAM–SFM. This waveform has the capability to simultaneously isolate multiple target ions, even allowing for the lossless isolation of ions with lower abundance within isotopic clusters, albeit at the cost of requiring extended isolation durations.

Synapse-based artificial neural networks (ANNs) are hopeful in overcoming the von Neumann bottleneck since they can process and store data simultaneously. Here, we present an artificial synaptic device based on a ferroelectric BaTiO3thin film with a robust weight update and diverse plasticity for ANNs. Specifically, the potentiation and depression effects strongly depend on the spike polarity, amplitude, number, and rate. Moreover, four types of spike timing-dependent plasticities (STDP) and two types of Bienenstock–Cooper–Munro (BCM) learning rules with sliding frequency thresholds are obtained. For BCM learning rules, a normal one with potentiation at a high frequency and depression at a low frequency is obtained under a positive bias and an abnormal one with depression at a high frequency and potentiation at a low frequency is achieved at a negative bias. Furthermore, an ANN is enabled with a recognition accuracy of 92.18%. These results are essential for potential applications of ferroelectric artificial synapses for ANNs.

Body-centred cubic refractory multi-principal element alloys (MPEAs), with several refractory metal elements as constituents and featuring a yield strength greater than one gigapascal, are promising materials to meet the demands of aggressive structural applications1–6. Their low-to-no tensile ductility at room temperature, however, limits their processability and scaled-up application7–10. Here we present a HfNbTiVAl10alloy that shows remarkable tensile ductility (roughly 20%) and ultrahigh yield strength (roughly 1,390 megapascals). Notably, these are among the best synergies compared with other related alloys. Such superb synergies derive from the addition of aluminium to the HfNbTiV alloy, resulting in a negative mixing enthalpy solid solution, which promotes strength and favours the formation of hierarchical chemical fluctuations (HCFs). The HCFs span many length scales, ranging from submicrometre to atomic scale, and create a high density of diffusive boundaries that act as effective barriers for dislocation motion. Consequently, versatile dislocation configurations are sequentially stimulated, enabling the alloy to accommodate plastic deformation while fostering substantial interactions that give rise to two unusual strain-hardening rate upturns. Thus, plastic instability is significantly delayed, which expands the plastic regime as ultralarge tensile ductility. This study provides valuable insights into achieving a synergistic combination of ultrahigh strength and large tensile ductility in MPEAs.

Three-dimensional printing is a revolutionary strategy to fabricate dental implants. Especially, 3D-printed dental implants modified with nanoscaled titanium oxide layer (H-SLM) have impressively shown quick osseointegration, but the accurate mechanism remains elusive. Herein, we unmask a domino effect that the hydrophilic surface of the H-SLM facilitates blood wetting, enhances the blood shear rate, promotes blood clotting, and changes clot features for quick osseointegration. Combining computational fluid dynamic simulation and biological verification, we find a blood shear rate during blood wetting of the hydrophilic H-SLM 1.2-fold higher than that of the raw 3D-printed implant, which activates blood clot formation. Blood clots formed on the hydrophilic H-SLM demonstrate anti-inflammatory and pro-osteogenesis effects, leading to a 1.5-fold higher bone-to-implant contact and a 1.8-fold higher mechanical anchorage at the early stage of osseointegration. This mechanism deepens current knowledge between osseointegration speed and implant surface characteristics, which is instructive in surface nanoscaled modification of multiple 3D-printed intrabony implants.

Concentrated on the marine surface vessel (MSV) with input saturation, model uncertainties and unknown disturbances, this paper proposes the error-constrained line-of-sight guidance-based prescribed performance dual event-triggered path following control (ECLOS-PPDETPFC) strategy which applies the dual relative threshold event-triggered mechanism (ETM) to both guidance and controller of the MSV path following. We apply the prescribed performance function (PPF) as the bounds of asymmetric modified barrier Lyapunov function (AMBLF) to construct the prescribed performance asymmetric modified barrier Lyapunov function (PPAMBLF). In guidance, event-triggered error-constrained line-of-sight (ETECLOS) is constructed by relative threshold ETM and AMBLF to reduce the calculation pressure and keep position errors within the constraint range; In controller, prescribed performance event-triggered path following control (PPETPFC) is based on the relative threshold ETM and PPAMBLF, which makes the heading error meet the prescribed performance requirements, while reducing the loss of actuator. At the same time, the adaptive auxiliary systems are used to compensate the influence of input saturation, radial basis function neural networks (RBFNNs) and adaptive laws are used to approximate the model uncertainties and composite disturbances. According to the Lyapunov stability theory, all signals are semi-globally uniformly ultimately bounded (SGUUB) and the Zeno phenomenon is avoided. Finally, the comparative experiment shows the effectiveness and superiority of the designed control strategy. • This paper proposes the error-constrained line-of-sight guidance-based prescribed performance dual event-triggered path following control (ETECLOS-PPETPFC) strategy. • This control strategy applies the dual relative threshold event-triggered mechanism (ETM) to both guidance and controller of the MSV path following, which can reduce controller calculation pressure and actuator loss. • This control strategy can reduce the update frequency of guidance heading angle and controller. • This control strategy can not only constrain the errors of MSV position, but also make the heading error meet the prescribed performance requirements. [ABSTRACT FROM AUTHOR]

Monoatomic-layered carbon materials, such as graphene1and amorphous monolayer carbon2,3, have stimulated intense fundamental and applied research owing to their unprecedented physical properties and a wide range of promising applications4,5. So far, such materials have mainly been produced by chemical vapour deposition, which typically requires stringent reaction conditions compared to solution-phase synthesis. Herein, we demonstrate the solution preparation of free-standing nitrogen-doped amorphous monolayer carbon with mixed five-, six- and seven-membered (5-6-7-membered) rings through the polymerization of pyrrole within the confined interlayer cavity of a removable layered-double-hydroxide template. Structural characterizations and first-principles calculations suggest that the nitrogen-doped amorphous monolayer carbon was formed by radical polymerization of pyrrole at the α, β and N sites subjected to confinement of the reaction space, which enables bond rearrangements through the Stone–Wales transformation. The spatial confinement inhibits the C–C bond rotation and chain entanglement during polymerization, resulting in an atom-thick continuous amorphous layer with an in-plane π-conjugation electronic structure. The spatially confined radical polymerization using solid templates and ion exchange strategy demonstrates potential as a universal synthesis approach for obtaining two-dimensional covalent networks, as exemplified by the successful synthesis of monolayers of polythiophene and polycarbazole.

Weakly coupled resonators (WCRs) predicated on the mode localization phenomenon have found widespread utility in the topological design of high-performance sensors. However, the pronounced nonlinearity derived from the loci veering around the zero point imposes a significant constraint on the measurement range of mode-localized sensors. This article introduces a novel single-port readout circuit aimed at realizing full-scale linear sensing for mode-localized sensors. In our proposed methodology, we employ not only the conventional frequency closed-loop control but also introduce an amplitude closed-loop system incorporating automatic gain control (AGC). This AGC-based approach is utilized to maintain the amplitude product of resonant units at a standardized value. Consequently, we can consider the difference of squared amplitudes as the sensor output, which serves to effectively capture and characterize the fluctuations in external input signals. Furthermore, we have applied our proposed readout circuit to test a prototype of a micro-electro-mechanical system (MEMS) mode-localized accelerometer. The experimental results unequivocally affirm that the tested accelerometer prototype achieves linear sensing throughout the entire measurement range. Remarkably, it demonstrates a mechanical sensitivity of 0.1182/g, coupled with a maximum nonlinearity of -6.54%, and a bias stability of 19.23 mg, alongside a noise floor of $1.022\times 10^{-4}$ V/Hz $^{1/2}$ . These outcomes align closely with the output metric based on the subtraction of reciprocal amplitude ratios (SRARs). Our proposed methodology not only facilitates full-scale linear sensing for mode-localized sensors but also streamlines the signal extraction process, all while preserving the electromechanical performance. This advancement holds significant promise for the expansion of the application landscape for mode-localized sensors.

Ultrasound image acquisition in conventional transesophageal echocardiography (TEE) requires complex manual operation of the probe in the esophagus based on the interpretation of ultrasound images and in-depth knowledge of the cardiac anatomy. In this work, we formulate the TEE probe guidance task as a reinforcement learning (RL) problem, and present the first learning-based solution to 3-DOF control of a TEE probe based on the ultrasound image feedback, named RL-TEE, in order to mimic the visual search and navigation strategies of expert echocardiographers. The probe-tissue interaction in TEE is carefully modeled in our framework by considering both the requirements for navigation towards the standard views and compliance in the esophageal environment. Furthermore, we propose a hybrid deep Q-network model that augments a convolutional neural network backbone with self-attention mechanisms to better capture spatial information in ultrasound images to guide navigation decisions. The presented methods are preliminarily validated in a TEE simulation environment built with data from 25 subjects to acquire four standard views of the heart. Our results show that the proposed method can effectively learn to accurately and compliantly guide the probe movement for TEE standard view acquisition tasks and has a good generalization ability to unseen patient data. Note to Practitioners—The motivation of this paper is to realize 3-DOF movement guidance of a TEE probe to acquire the standard views of the heart based on the real-time images, which can be applied to existing robotic control systems or used to assist novice echocardiographers in TEE examination, thereby relieving operator workload and improving ease of use. This paper suggests a novel approach that uses the deep RL technique to achieve automatic interpretation of TEE images and intelligent guidance of the probe movement. The RL framework is designed to take into account both the navigation efficiency and compliance with the esophageal environment for the targeted intracorporeal application. A hybrid deep Q-network model that augments a convolutional neural network with attention mechanisms is designed to better capture spatial information from ultrasound images to predict the probe movement. The effectiveness of the framework is preliminarily validated in extensive experiments in a simulation environment built with real patient data. The proposed method can be applied in clinical use to provide real-time TEE probe guidance for novice echocardiographers, and can be integrated with a robotic system to fully automate the TEE acquisition, thereby relieving the doctors from tedious manual operation to focus on the diagnosis and treatment.

Background: It remains unclear what factors significantly drive racial disparity in cancer survival in the United States (US). We compared adjusted mortality outcomes in cancer patients from different racial and ethnic groups on a population level in the US and a single-payer healthcare system. Patients and Methods: We selected adult patients with incident solid and hematologic malignancies from the Surveillance, Epidemiology, and End Results (SEER) 2011–2020 and Veteran Affairs national healthcare system (VA) 2011–2021. We classified the self-reported NIH race and ethnicity into non-Hispanic White (NHW), non-Hispanic Black (NHB), non-Hispanic Asian Pacific Islander (API), and Hispanic. Cox regression models for hazard ratio of racial and ethnic groups were built after adjusting confounders in each cohort. Results: The study included 3,104,657 patients from SEER and 287,619 patients from VA. There were notable differences in baseline characteristics in the two cohorts. In SEER, adjusted HR for mortality was 1.12 (95% CI, 1.12–1.13), 1.03 (95% CI, 1.03–1.04), and 0.91 (95% CI, 0.90–0.92), for NHB, Hispanic, and API patients, respectively, vs. NHW. In VA, adjusted HR was 0.94 (95% CI, 0.92–0.95), 0.84 (95% CI, 0.82–0.87), and 0.96 (95% CI, 0.93–1.00) for NHB, Hispanic, and API, respectively, vs. NHW. Additional subgroup analyses by cancer types, age, and sex did not significantly change these associations. Conclusions: Racial disparity continues to persist on a population level in the US especially for NHB vs. NHW patients, where the adjusted mortality was 12% higher in the general population but 6% lower in the single-payer VA system.

Long timescale Molecular Dynamics (MD) simulation of small molecules is crucial in drug design and basic science. To accelerate a small data set that is executed for a large number of iterations, high-efficiency is required. Recent work in this domain has demonstrated that among COTS devices only FPGA-centric clusters can scale beyond a few processors. The problem addressed here is that, as the number of on-chip processors has increased from fewer than 10 into the hundreds, previous intra-chip routing solutions are no longer viable. We find, however, that through various design innovations, high efficiency can be maintained. These include replacing the previous broadcast networks with ring-routing and then augmenting the rings with out-of-order and caching mechanisms. Others are adding a level of hierarchical filtering and memory recycling. Two novel optimized architectures emerge, together with a number of variations. These are validated, analyzed, and evaluated. We find that in the domain of interest speed-ups over GPUs are achieved. The potential impact is that this system promises to be the basis for scalable long timescale MD with commodity clusters.

Deep cross-media hashing provides an efficient semantic representation learning solution for large-scale cross-media retrieval. The existing methods only consider the inter-media or intra-media semantic association learning, ignore the guiding of semantic structure information, and have weak reasoning ability for implicit fine-grained semantic associations. To tackle this problem, we propose a novel structures aware fine-grained contrastive adversarial hashing method for cross-media retrieval. A novel cross-media contrastive adversarial hash network is constructed for the first time, which integrates the cross-media and intra-media contrastive learning and multi-modal adversarial learning, aiming at maximizing the semantic association between different modalities, and improving the semantic discrimination and consistency of cross-media unified hash representation, thereby the inter-media and intra-media semantic preserving ability can be well enhanced; A fine-grained cross-media semantic feature learning method based on fine-grained semantic reasoning with transformers is proposed, which captures fine-grained salient features of different modalities for semantic association learning, and enhances the reasoning ability of fine-grained implicit semantic association; A semantic label graph convolutional network guided cross-media semantic association learning strategy is proposed, which makes full use of semantic structure information to enhance the learning ability of implicit cross-media semantic associations. Extensive experiments on several large-scale cross-media benchmark datasets demonstrate that the proposed method outperforms the state-of-the-art methods.

We propose a novel Sagnac interferometric intrusion localization system based on a rhombic optical path differential bias configuration for localization detection of intrusion signals. In contrast to the intricate multipath detection architecture employed in traditional Sagnac intrusion localization systems, the proposed system described in this article achieves comparable results through the utilization of a single detection optical path. This represents an improvement in terms of system simplicity and efficiency. The rhombic optical path differential bias Sagnac intrusion localization system has the advantages of simple structure, low cost, and optimized demodulation method. By combining the spectral analysis of the phase signal with the first-order null-frequency point method and the “Twice-FFT” algorithm, the intrusion location measurement of low- and high-intensity intrusion signals is achieved, respectively. Based on the findings presented in this article, it has been demonstrated that the system put forward in this study effectively achieves localized detection of intrusion signals. Furthermore, it exhibits the potential to possess the capability to discern the specific type of intrusion. According to the results presented in this study, the maximum standard deviation observed for intrusion localization of low-frequency signals is a mere 11 m. In addition, the maximum standard deviation observed for intrusion localization of high-frequency signals does not surpass 20 m.

Motivated by the need of modeling and inference for high-order integer-valued threshold time series models, this paper introduces a pth-order two-regime self-excited threshold integer-valued autoregressive (SETINAR(2, p)) model. Basic probabilistic and statistical properties of the model are discussed. The parameter estimation problem is addressed by means of conditional least squares and conditional maximum likelihood methods. The asymptotic properties of the estimators, including the threshold parameter, are obtained. A method to test the nonlinearity of the underlying process is provided. Some simulation studies are conducted to show the performances of the proposed methods. Finally, an application to the number of people suffering from meningococcal disease in Germany is provided.

D-Psicose, as a low-calorie rare sugar, has attracted a lot of attention in recent years for alternating to sucrose. The anti-obesity effect of D-psicose has been extensively confirmed in previous studies, however, the impact of D-psicose on colitis remains vague. Here, we firstly evaluated the effect of the D-psicose prophylactic intervention on dextran sulfate sodium-induced colitis in C57BL/6 mice. The pathological symptoms, inflammatory cytokines levels, gut microbiota composition, short chain fatty acids (SCFAs) production and colonic barrier integrity were comprehensively evaluated. The results confirmed that D-psicose intervention aggravated colitis, characterized by the exacerbation of colon shortening, increase of colonic inflammatory infiltration, and marked exaltation of disease activity indices and IL-6, IL-1β and TNF-α levels. Further, the dysfunction of gut microbiota was identified in the psicose group. The abundance of pro-inflammatory bacteria Lachnospiraceae_NK4A136_group was significantly up-regulated while the abundance of probiotics Akkermansiaand Lactobacilluswere significantly down-regulated in the psicose group compared to the model group. Moreover, the production of SCFAs was suppressed in the psicose group, accompanied by a decrease in the level of mucin 2 (Muc-2). Collectively, the underlying mechanism of the exacerbation of colitis by D-psicose intervention might be attributed to microbiota dysfunction accompanied by the reduction of SCFAs, which leads to the damage of the mucosal barrier and the intensification of inflammatory invasion.

Automatic Vehicle Identification (AVI) technology has been widely used for real-time path travel time estimation. For a study path equipped with AVI sensors at both ends, the difference between the timestamps of vehicles entering and leaving the path is AVI data. In urban areas, there can be several alternative routes and vehicle entry/exit points for the study path. Consequently, invalid AVI data occur that fall outside the scope of the travel time of the study path. Some AVI technologies based on identification information of vehicles can match vehicles precisely. However, for cities like Hong Kong with concerns of privacy issues, only commercial vehicle data can be collected. Under this scenario, the resultant AVI data are accurate but with few valid samples in a relatively short time interval due to the unavailability of private car data. The estimation accuracy of path travel times on a real-time basis will then be affected significantly by the existence of invalid AVI data. In this paper, a novel unsupervised algorithm is proposed to filter out real-time invalid AVI data efficiently although there is no ground truth available for training purposes. It is tested and compared with other benchmark algorithms on two selected paths in the Hong Kong urban road network. It is found that the proposed unsupervised algorithm can still filter limited but accurate AVI data with satisfactory performance. Sensitivity tests with ground truth are also conducted with different sampling rates. Some insightful findings are given for filtering AVI data under various scenarios.