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High-entropy alloys (HEAs) have aroused extensive attention in the field of catalysis. However, due to the integration of multiple active sites in HEA, it exhibits excessive adsorption behavior resulting in difficult desorption of active species from the catalyst surfaces, which hinders the catalytic efficiency. Therefore, adjusting the adsorption strength of the active site in HEA to enhance the catalytic activity is of great importance. By introducing rare-earth (RE) elements into the high-entropy alloy, the delocalization of 4f electrons can be achieved through the interaction between the multimetal active site and RE, which benefits to regulate the adsorption strength of the HEA surface. Herein, the RE Ce-modified hexagonal-close-packed PtRuFeCoNiZn-Ce/C HEAs are synthesized and showed an excellent electrocatalytic activity for hydrogen evolution reaction and oxygen evolution reaction with ultralow overpotentials of 4, 7 and 156, 132 mV, respectively, to reach 10 mA cm–2in 0.5 M H2SO4and 1.0 M KOH solutions, and the assembled water electrolysis cell only requires a voltage of 1.43 V to reach 10 mA cm–2, which is much better than the performance of PtRuFeCoNiZn/C. Combined with the results of in situattenuated total reflection infrared spectroscopy and density functional theory (DFT), the fundamental reasons for the improvement of catalyst activity come from two aspects: (i) local lattice distortion of HEA caused by the introduction of RE with large atomic radius induces 4f orbital electron delocalization of RE elements and enhances electron exchange between RE and active sites. (ii) The electronegativity difference between the RE element and the active site forms a surface dipole in HEA, which optimizes the adsorption of the active intermediate by the HEA surface site. This study provides an insightful idea for the rational design of high-performance HEA- and RE-based electrocatalysts.

The bond coat of thermal barrier coatings (TBCs) often experiences internal crack nucleation and propagation due to insufficient strain tolerance, leading to premature failure during service. To address this issue, a composite laser-induced texture composed of both concave and convex features is engraved on the bond coat to prolong the service life of the TBC system. The influence of laser parameters, including laser power and pulse width parameters, on the microstructure and mechanical properties of the modified bond coat is investigated. The microstructure and composition of the TBCs are characterized by laser scanning confocal microscope, scanning electron microscopy and X-ray diffraction. The microhardness, fracture toughness and wettability of the laser-textured and unengraved TBCs are evaluated. The results reveal that the surface texture transitions from a spherical crown to a volcano-shaped morphology as the laser pulse width increases. For different laser parameters, when the power and pulse width are 150 W and 2000 μs respectively, laser-induced volcano-shaped micro-texture array providing superior adhesive properties and a highly active coating, enhances surface solid-liquid wettability. Microscopic observations show that laser texturing effectively suppresses internal pores and cracks inside the coating, and refines grain structure. Furthermore, the mechanical properties of the NiCoCrAlY coating were altered following laser texturing. The hardness of the coating increased by 41.8 %, the elastic modulus decreased by 13.2 %, and the fracture toughness was improved.

The development of efficient and stable catalysts for hydrogen production from electrolytic water in a wide pH range is of great significance in alleviating the energy crisis. Herein, Pt nanoparticles (NPs) anchored on the vacancy of high entropy rare earth oxides (HEREOs) were prepared for the first time for highly efficient hydrogen production by water electrolysis. The prepared Pt-(LaCeSmYErGdYb)O showed excellent electrochemical performances, which require only 12, 57, and 77 mV to achieve a current density of 100 mA cm–2in 0.5 M H2SO4, 1.0 M KOH, and 1.0 M PBS environments, respectively. In addition, Pt-(LaCeSmYErGdYb)O has successfully worked at 400 mA cm–2@ 60 °C for 100 h in 0.5 M H2SO4, presenting the high mass activity of 37.7 A mg–1Ptand turnover frequency (TOF) value of 38.2 s–1@ 12 mV, which is far superior to the recently reported hydrogen evolution reaction (HER) catalysts. Density functional theory (DFT) calculations have revealed that the interactions between Pt and HEREO have optimized the electronic structures for electron transfer and the binding strength of intermediates. This further leads to optimized proton binding and water dissociation, supporting the highly efficient and robust HER performances in different environments. This work provides a new idea for the design of efficient RE-based electrocatalysts.

Non-uniform sampling two-dimensional convolution (NUSC) maps spatially sampling data with irregular distribution to a regular grid by convolution. As the data scale and growth rate continue to increase, accelerating NUSC with the heterogeneous computing platform is a feasible way. However, the complex hardware architecture and storage hierarchy of the heterogeneous computing platform poses a challenge to programming and performance tuning. Therefore, this paper proposes a heterogeneous parallel programming model and runtime framework named AutoNUSC. For the programming difficulties of NUSC in heterogeneous computing environments, AutoNUSC abstracts and encapsulates the parallel execution process of NUSC. Task scheduling, data division, node communication, fault-tolerant recovery, and other parallelization tasks are managed by AutoNUSC. For the performance tuning issues of NUSC, this paper implements performance optimization strategies for AutoNUSC, including vectorization, memory access optimization, data reuse, etc. The experiments show that AutoNUSC effectively reduces the workload of users in developing NUSC applications in heterogeneous computing environments. Performance acceleration of up to 339 times is achieved within a single node compared to the serial program. AutoNUSC can efficiently perform task scheduling and fault-tolerant recovery across multiple nodes, with desirable scalability and robustness.

The article analyzes influence of domestication on the trait complex of einkorn wheat. The presence of genetically very close forms—two wild (Triticum monococcumL. subsp. aegilopoides(Link) Thell., Triticum urartuTumanian ex Gandilyan) and two cultivated (T. monococcumL. subsp. monococcum, T. monococcumsubsp. sinskajae(Filat. and Kurkiev) Valdés and H.Scholz) in the einkorn gene pool makes it a convenient object for studying effect of domestication. This study establishes three main traits that define the essence of the "domestication syndrome": increase in seed size, absence of spontaneous ear brittleness, ease of grain threshing (decrease in hullness) in cultivated einkorns compared to wild ancestral forms. It was found that during the transition from wild to cultivated einkorn, stem height and upper internode length decreased but the indices of plant development rate, weight of kernels per ear and 1000 kernel weight increased. At the same time, the traits related to the potential productivity—weight of whole spike and spikelet number in ear—did not change whereas indicators of this potential realization (actual productivity)—kernel number per spike and spike length—have decreased. Multivariate analysis of the einkorns characteristics identified two main components that generally explain 78% of variability. Clustering of the einkorn accessions according to 10 traits made it possible to divide the accessions into groups of differential significance for breeding. Suggestions for the rational use of einkorn wheat accessions in breeding were formulated. In cultivated eincorn, the traits are more correlated than in the wild ones, indicating greater physiological homeostaticity of wild ancestral species and less homeostaticity of cultivated einkorn.

Pyrolysis is a promising thermochemical conversion technology, which can convert biomass and cellulose into value-added products. Herein, a new approach of oxalic acid-assisted staged fast pyrolysis (OASFP) of cellulose was developed, achieving the coproduction of 1,4:3,6-dianhydro-α-d-glucopyranose (DGP), furfural (FF), and formic acid (FA) in separated pyrolysis stages. The lab-scale tests demonstrated that a selectivity of 71.6% and a yield of 31.5 wt % for FA in the aqueous phase, as well as a selectivity of 55.6% and a yield of 1.2 wt % for FF in the organic phase, were achieved in the primary pyrolysis stage under the optimized conditions (primary pyrolysis temperature of 220 °C and cellulose-to-oxalic acid (OA) ratio of 1:3). During the subsequent secondary pyrolysis process at 400 °C, the decomposition of the solid residue achieved a yield of 7.2 wt % and a selectivity of 32.7% for DGP. The interaction between OA and cellulose during the primary pyrolysis stage was essential for DGP generation. The formation mechanism of major products and the role of OA were revealed based on experiments and density functional theory calculations. In total, the OASFP of cellulose offers new possibilities and opportunities for biomass utilization.

Cancer is the second leading cause of human mortality and has rapidly become a major global issue. According to traditional Chinese medicine (TCM) theory, the primary pathogenesis of cancer is the deficiency of "vital Qi". Licorice (Gancao in Chinese, GC) one of the oldest and the most frequently used herbs for tonifying Qi, is commonly integrated with other Chinese medicines to treat cancer in TCM clinical practice. GC extract, or its chemical components, are often utilized in cancer treatment. However, the molecular mechanisms underlying GC's therapeutic effects on cancer remain unclear. Our current study aimed to elucidate these mechanisms from the perspective of network pharmacology and experimental validation.

To address the limited wear resistance attributed to the insufficient initial mechanical properties observed in high manganese steel (HM) wear behavior, we introduced nitrogen (N) to modulate precipitation behavior, thereby elevating material mechanical properties and wear resistance, and this was further enhanced through aging treatments. Due to the nitrogen addition, the precipitates transformed from MC to M(C, N), concurrently triggering a substantial increase and refinement in precipitates. As a result, nitrogenous high manganese steel (NHM) exhibited improved strength, toughness, and work-hardening capacity. The enhancements amounted to 67–77 MPa in yield strength and 5.3–9.3 % in elongation, with these improvements becoming more pronounced after extending the aging treatment. Under impact abrasive wear conditions, the NHM demonstrated the development of a stable work-hardened layer. The NHM hardened layer rapidly reached a depth of 4–6 mm, effectively resisting abrasive embedding and suppressing matrix abrasion. This transitioned the primary wear mechanisms from cutting and plowing to plastic deformation and micro-spalling. Additionally, NHM's great uniformity and toughness-plasticity played a crucial role in preventing the initiation and propagation of fatigue cracks and fatigue sheds.

The corrosion caused by marine organisms adhering to the wall surface is one of the main reasons for the failure of ships and equipment, and leads to shortened life and increased maintenance costs, and this has seriously affected the development of the national economy. Therefore, it is very important to develop a new composite material to protect the metal substrate from biological corrosion. In this article, a superhydrophobic surface was prepared by simply spraying silicone rubber emulsion containing hydrophobic SiO2nanoparticles onto a graphene silicone rubber (GSR) pre-coated substrate (SiO2-GSR). The antifouling ability was investigated under laboratory conditions and real marine environments, and the results show that the SiO2-GSR coating has good antiadhesion effect and longer antifouling ability. The anticorrosion performance was evaluated by electrochemistry methods, and the SiO2-GSR has good corrosion resistance ability. Additionally, the SiO2-GSR film still exhibited a strong antifouling and anticorrosion ability after immersed in marine environment for 6 months. Therefore, SiO2-GSR can be applied to the maritime field as an effective antifouling and anticorrosion coating.

Most IoT systems involve IoT devices, communication protocols, remote cloud, IoT applications, mobile apps, and the physical environment. However, existing IoT security analyses only focus on a subset of all the essential components, such as device firmware or communication protocols, and ignore IoT systems’ interactive nature, resulting in limited attack detection capabilities. In this work, we propose Iota, a logic programming-based framework to perform system-level security analysis for IoT systems. Iota generates attack graphs for IoT systems, showing all of the system resources that can be compromised and enumerating potential attack traces. In building Iota, we design novel techniques to scan IoT systems for individual vulnerabilities and further create generic exploit models for IoT vulnerabilities. We also identify and model physical dependencies between different devices as they are unique to IoT systems and are employed by adversaries to launch complicated attacks. In addition, we utilize NLP techniques to extract IoT app semantics based on app descriptions. Iota automatically translates vulnerabilities, exploits, and device dependencies to Prolog clauses and invokes MulVAL to construct attack graphs. To evaluate vulnerabilities’ system-wide impact, we propose three metrics based on the attack graph, which provide guidance on hardening IoT systems. Evaluation on 127 IoT CVEs (Common Vulnerabilities and Exposures) shows that Iota's exploit modeling module achieves over 80% accuracy in predicting vulnerabilities’ preconditions and effects. We apply Iota to 37 synthetic smart home IoT systems based on real-world IoT apps and devices. Experimental results show that our framework is effective and highly efficient. Among 27 shortest attack traces revealed by the attack graphs, 62.8% are not anticipated by the system administrator. It only takes 1.2 seconds to generate and analyze the attack graph for an IoT system consisting of 50 devices.

The thermal conductivity (TC) of graphene-based/metal composites is currently not satisfactory because of the existence of large interfacial thermal resistance between graphene and metal originating from the strong scattering of phonons. In this work, 6063Al-alloy-based reduced graphene oxide (rGO) composite with strong covalent bonds interface was prepared via self-assembly, reduction, and electrophoresis-deposition processes by using 3-aminopropyl triethoxysilane (APTS) as a link agent. Structural characterizations confirmed the successful construction of strong Al-O-Si-O-C covalent bonds in the as-prepared 6063Al-Ag-APTS-rGO composite, which can promote the transfer of phonons in the interface. Benefiting from the unique structure, 6063Al-Ag-APTS-rGO (214.1 W/mK) showed obviously higher cross-plane TC than 6063Al (195.6 W/mK). Comparative experiments showed that 6063Al-Ag-APTS-rGO has better cross-plane TC than 6063Al/Ag/APTS/rGO (196.6 W/mK) prepared via physical mixing of stirring process, evidencing the significance of electrophoresis-deposition (EPD) process on constructing strong covalent bonds for improving the heat dissipation performance. Besides, the effects of different rGO contents and test temperature on the TC of the composites and their corrosion resistance were also discussed. This work demonstrated a feasible strategy for the construction of metal–carbon interface composite with improved thermal performance.

The oxygen excess ratio (OER) is closely coupled with the entire efficiency of proton exchange membrane fuel cell (PEMFC). However, it is challenging to apply OER regulations owing to unpredictability and frequent load fluctuations. This article employs a feedforward model predictive control to track the optimal OER and reduce the detrimental effect of external current. According to the simulation outcomes, the proposed control performs superior in terms of integral absolute error, disturbance rejection, and tracking trajectory in OER tracking with variable external current than the conventional model predictive control.

Photothermal therapy (PTT) has emerged as a promising approach for treating bacterial infections. However, achieving a high photothermal conversion efficiency (PCE) of photothermal agents (PTAs) remains a challenge. Such a problem is usually compensated by the use of a high-intensity laser, which inevitably causes tissue damage. Here, we present a universal strategy to enhance PCE by regulating the molecular aggregation states of PTAs within thermoresponsive nanogels. We demonstrate the effectiveness of this approach using aggregation-induced emission (AIE) and aggregation-caused quenching (ACQ) PTAs, showing significant enhancements in PCE without the need for intricate molecular modifications. Notably, the highest PCEs reach up to 80.9% and 64.4% for AIE-NG and ACQ-NG, respectively, which are nearly 2-fold of their self-aggregate counterparts. Moreover, we elucidate the mechanism underlying PCE enhancement, highlighting the role of strong intermolecular π−π interactions facilitated by nanogel-induced volume contraction. Furthermore, we validate the safety and efficacy of this strategy in in vitroand in vivomodels of bacterial infections at safe laser power densities, demonstrating its potential for clinical translation. Our findings offer a straightforward, universal, and versatile method to improve PTT outcomes while minimizing cytotoxicity, paving the way for enhanced treatment of bacterial infections with safe PTT protocols.

The state perception of the digital twin (DT) relies on various sensors in the physical body, which generate massive data, and data transmission is an essential intermediate bridge between the physical bodies and the twins. In a mechanical DT system (MDTS), vibration is an important feature that reflects the physical body state, and vibration data generated by mechanical vibration sensors are extremely large, which results in data transmission latency. Therefore, this study proposes a fusion codec method for reducing data transmission and enhancing data transfer efficiency in MDTS; compared to traditional single-sensor data compression methods, the approach proposed data fusion codec (DFC) achieves an exceptionally low compression ratio (CRO) and superior data reconstruction accuracy. First, the transformed coefficients are classified by the screening principle and different quantization bits are designed to quantize the classified coefficients differently according to the mapping interval values, which initially reduce data bits. Based on the quantized data, the fusion of different vibration sensor data is achieved through bytes fusion to decrease the overall data information entropy. To further decline bytes redundancy, the bit fusion method is proposed. Furthermore, the fused data structure is designed to implement the codec of the fused data on the physical body and the twin body of MDTS, respectively. Finally, the performance-related parametric and comparative experiments are implemented separately based on the DFC, and the experimental results demonstrate effectiveness and superiority.

Purpose: This systematic review and meta-analysis was conducted to evaluate the usefulness of deep learning (DL) models for aorta segmentation in computed tomography (CT) images. Methods: Adhering to 2020 PRISMA guidelines, we systematically searched PubMed, Embase, and Web of Science for studies published up to March 13, 2024, that used DL models for aorta segmentation in adults’ chest CT images. We excluded studies that did not use DL models, involved nonhuman subjects or aortic diseases (aneurysms and dissections), or lacked essential data for meta-analysis. Segmentation performance was evaluated primarily in terms of Dice scores. Subgroup analyses were performed to identify variations related to geographical location and methodology. Results: Our review of 16 studies indicated that DL models achieve high segmentation accuracy, with a pooled Dice score of 96%. We further noted geographical variations in model performance but no significant publication bias, according to the Egger test. Conclusion: DL models facilitate aorta segmentation in CT images, and they can therefore guide accurate, efficient, and standardized diagnosis and treatment planning for cardiovascular diseases. Future studies should address the current challenges to enhance model generalizability and evaluate clinical benefits and thus expand the application of DL models in clinical practice.

We propose a framework in which multiple entities collaborate to build a machine learning model while preserving privacy of their data. The approach utilizes feature embeddings from shared/per-entity feature extractors transforming data into a feature space for cooperation between entities. We propose two specific methods and compare them with a baseline method. In Shared Feature Extractor (SFE) Learning, the entities use a shared feature extractor to compute feature embeddings of samples. In Locally Trained Feature Extractor (LTFE) Learning, each entity uses a separate feature extractor, and models are trained using concatenated features from all entities. As a baseline, in Cooperatively Trained Feature Extractor (CTFE) Learning, the entities train models by sharing raw data. Secure multi-party algorithms are utilized to train models without revealing data or features in plain text. We investigate the trade-offs among SFE, LTFE, and CTFE in regard to performance, privacy leakage (using an off-the-shelf membership inference attack), and computational cost. LTFE provides the most privacy, followed by SFE, and then CTFE. Computational cost is lowest for SFE and the relative speed of CTFE and LTFE depends on network architecture. CTFE and LTFE provide the best accuracy. We use three different datasets for evaluations.

The accurate estimation of 6D pose remains a challenging task within the computer vision domain, even when utilizing 3D point cloud data. Conversely, in the manufacturing domain, instances arise where leveraging prior knowledge can yield advancements in this endeavor. This study focuses on the disassembly of starter motors to augment the engineering of product life cycles. A pivotal objective in this context involves the identification and 6D pose estimation of bolts affixed to the motors, facilitating automated disassembly within the manufacturing workflow. Complicating matters, the presence of occlusions and the limitations of single-view data acquisition, notably when motors are placed in a clamping system, obscure certain portions and render some bolts imperceptible. Consequently, the development of a comprehensive pipeline capable of acquiring complete bolt information is imperative to avoid oversight in bolt detection. In this paper, employing the task of bolt detection within the scope of our project as a pertinent use case, we introduce a meticulously devised pipeline. This multi-stage pipeline effectively captures the 6D information with regard to all bolts on the motor, thereby showcasing the effective utilization of prior knowledge in handling this challenging task. The proposed methodology not only contributes to the field of 6D pose estimation but also underscores the viability of integrating domain-specific insights to tackle complex problems in manufacturing and automation.

Due to the propagation of traffic congestion from upstream to downstream links and the uncertainty of path choice behaviours, travel times between different links, particularly adjacent links, are highly correlated in a typical period from day to day. To improve the estimation accuracy of both the mean and covariance of link travel times, a novel measurement is proposed to optimize the locations of multi-type traffic sensors for link travel time estimation. Multi-source data from different types of traffic sensors can be integrated to better estimate link travel time in an entire road network. In practice, the allocation of multi-type traffic sensors is constrained by the total financial budget and should be optimized in accordance with measurement errors and the cost ratio. Numerical examples of synthetic and real road networks are conducted to demonstrate the applications and merits of the proposed multi-type sensor location model with covariance effects.

Quinoline‐based fibroblast activation protein (FAP) inhibitor (FAPI)‐based positron emission tomography (PET) imaging and radioligand therapy (RLT) are being investigated for use in a wide variety of diseases, and recent results have been promising. This review summarizes the current status of FAPI radiopharmaceuticals in PET imaging of malignant tumors and benign conditions and compares their diagnostic efficacy with 18F‐fluorodeoxyglucose. In addition, we summarize the previously published FAP‐targeted RLT data and discuss its current clinical use and future potential. Our qualitative summary can inform future research directions, medical guidelines, and optimal clinical decision‐making. FAP is considered a promising target for radioligand therapy because of high FAP tracer uptake in tumors and low expression of FAP in healthy tissues. FAP‐targeting agents ensure uptake in the tumor stroma and the cross‐fire effect of the radionuclides (alpha‐ or beta‐emitting) delivers a tumoricidal dose of radiation. These agents may revolutionize radionuclide therapy and theranostics in the future.

The Triticum-Aegilopscomplex provides ideal models for the study of polyploidization, and mitochondrial genomes (mtDNA) can be used to trace cytoplasmic inheritance and energy production following polyploidization. In this study, gapless mitochondrial genomes for 19 accessions of five Triticumor Aegilopsspecies were assembled. Comparative genomics confirmed that the BB-genome progenitor donated mtDNA to tetraploid T. turgidum(genome formula AABB), and that this mtDNA was then passed on to the hexaploid T. aestivum(AABBDD). T urartu(AA) was the paternal parent of T. timopheevii(AAGG), and an earlier Ae. tauschii(DD) was the maternal parent of Ae. cylindrica(CCDD). Genic sequences were highly conserved within species, but frequent rearrangements and nuclear or chloroplast DNA insertions occurred during speciation. Four highly variable mitochondrial genes (atp6, cob, nad6, and nad9) were established as marker genes for Triticumand Aegilopsspecies identification. The BB/GG-specific atp6and cobgenes, which were imported from the nuclear genome, could facilitate identification of their diploid progenitors. Genic haplotypes and repeat-sequence patterns indicated that BB was much closer to GG than to Ae. speltoides(SS). These findings provide novel insights into the polyploid evolution of the Triticum/Aegilopscomplex from the perspective of mtDNA, advancing understanding of energy supply and adaptation in wheat species.

A novel 4H-silicon carbide power heterojunction tunneling transistor (4H-SiC power HETT) structure is proposed and demonstrated by the calibrated process and characteristic simulation, featuring a low specific ON-resistance ( ${R} _{ \mathrm{\scriptscriptstyle ON},\text {sp}}$ ) of 1.56 $\text{m}\Omega \cdot \text { cm}^{{2}}$ , 1460 V breakdown voltage (BV), and a low forward voltage drop ( ${V} _{\text {F}}$ ) of 1.4 V reaching the level of the junction barrier Schottky barrier diode (JBS) diode. The N+ type polycrystalline silicon (Poly-Si) is utilized to form the heterojunction with the 4H-SiC epi-layer. Owing to the unique cell structure of 4H-SiC power HETT, the cell pitch is reduced to $3~\mu \text{m}$ for significantly improving the tunneling current density. Moreover, the 0.3- $\mu \text{m}$ shallow gate trench and the Al2O3 high- ${k}$ dielectric further enhance the gate-controlled heterojunction tunneling characteristic. The parasitic heterojunction body diode with a heterojunction barrier of 0.7 eV provides a ${V} _{\text {F}}$ of 1.4 V and the unipolar freewheeling current without bipolar degradation issues. The P region sustains a high avalanche breakdown and effectively shields the electric field ( ${E}$ ) under the shallow gate trench and the heterojunction interface, leading to good gate reliability and low reverse leakage current. The simulation results show that the 4H-SiC power HETT has potential to approach the ideal performances of the SiC material and replace the conventional SiC power MOSFETs.

The unit-cell-size comparable ultrathin nanowires(UCNWs) with typical cross-sectional dimension of around one nanometer, comparable to the unit-cell-size of inorganic materials, exhibit unique properties different from traditional nanomaterials. However, their facile and general synthesis is still a great challenge, since it not only demands the anisotropic growth in one direction, but also needs to completely restrict the growth in the other two dimensions. In this review, we summarize and introduce a strategy to prepare UCNWs using nanoclusters as synthons, which is promising to be a general synthesis method for UCNWs. We start with the introduction to the definition and characteristics of UCNWs. Subsequently, the key problems of UCNWs synthesis are analyzed from the perspective of thermodynamics and the strategy of using nanoclusters as synthons is proposed. Then, the related works about synthesis of UCNWs using magic-size clusters(MSCs) and polyoxometalate(POM) clusters as synthons are introduced and carefully discussed. Finally, challenges and opportunities are also elaborately discussed. This review is anticipated to provide a panoramic sketch and future directions toward the general synthesis of UCNWs.

Enduring surface technologies draw much attention to improving friction performance and prolonging the lifespan of multi-alternative contact pairs. Laser surface texturing is smart to modify effectively the microscopic surface geometries and mechanical performances for the service's improvement of friction pair. This study explored the formation mechanisms and morphology evolution of hierarchical microtextures, with a focus on the thermal field and phase transformation resulting from the laser heating effect on the alloy surface. The controlling variates of laser machining were analyzed considering their influences on microtextures' height and diameter, the pulse numbers are 3 times and 1.7 times of the unit laser power, 81 times and 82.5 times of the unit pulse width. We contributed to the development of laser manufacturing techniques for creating hierarchical microtextures' controllable morphology and smart surface design for tribology engineering and energy management applications.

The immunotherapy of deep solid tumors in the human body, such as liver cancer, still faces great challenges, especially the inactivation and insufficient infiltration of immune cells in solid tumor microenvironment. Natural killer (NK) cells are gaining ever-increasing attention owing to their unique features and are expected to play an important role in the liver cancer immunotherapy. However, NK cells are severely insufficient and inactivated in solid liver tumor due to the highly immunosuppressive intratumor microenvironment, resulting in poor clinical therapeutic efficacy. Herein, we propose a mild magnetocaloric regulation approach using a magnetogenetic nanoplatform MNPs@PEI-FA/pDNA (MPFD), which is synthesized by loading a heat-inducible plasmid DNA (HSP70-IL-2-EGFP) on polyethyleneimine (PEI)- and folic acid (FA)-modified ZnCoFe2O4@ZnMnFe2O4magnetic nanoparticles (MNPs) to promote the proliferation and activation of tumor-infiltrating NK cells under magnetic manipulation without the limitation of penetration depth for orthotopic liver cancer immunotherapy. The magnetothermally responsive MPFD serves as a magnetism-heat nanotransducer to induce the gene transcription of IL-2 cytokine in orthotopic liver tumor for NK cell proliferation and activation. Both in vitroand in vivoresults demonstrate that the remote mild magnetocaloric regulation (∼40 °C) by MPFD initiates the HSP70 promoter to trigger the overexpression of IL-2 cytokine for subsequent secretion, leading to in situexpansion and activation of tumor-infiltrating NK cells through the IL-2/IL-2 receptor (IL-2R) pathways and the resulting prominent tumor inhibition. This work not only evidences the great potential of magnetogenetic nanoplatform but also reveals the underlying proliferation and activation mechanism of NK cells in liver cancer treatment by magnetogenetic nanoplatform.

To solve the ongoing problems of micro-alloyed Hadfield's steel, insufficient hardness and excessive deformation in the early working period, expensive alloying elements like Ti, Nb, and V have been utilized. However, traditional long-time, single-stage aging exacer-bates vanadium to assemble at the edge of initial precipitates, which diminishes estimated effects. For this, here we report the tremendous impact of retrogression and re-aging process (RRA) in this steel by booming the V (C, N) mean sized in 11 nm. The procedure enhances the micro-hardness, yielding strength, tensile strength, and impact-wear resistance for more than 27.4%, 29.5%, 22.2%, and 51.5%, respectively. Moreover, the wear mechanism of RRA samples has been investigated in that micro-sized precipitates surrounded by numerous nano V (C, N) stick in the matrix and hinder the abrasive embedding consistently, thus decreasing the micro-cutting and micro-plowing. This new process maximizes the utilization of costly and nonrenewable vanadium and magnifies the impact-wear resistance under either mild or medium-intensity working conditions.

Cemented paste backfill (CPB) has been a practical approach for mining waste management, underground goaf treatment, and green mining. Strength deterioration because of high sulfide content (SC) is a severe challenge for sulfide-rich CPB. To investigate the influence of rice straw (RS) on the strength of sulfide-rich CPB, RS was utilized as an inhibitor of strength deterioration. RS dosage (RSD), RS length (RSL), and sulfide content (SC) were chosen as the factors, and two stages of the experiment were carried out. It was found that high SC produced pores, cracks, and loose microstructure of CPB, resulting in the strength deterioration of sulfide-rich CPB. The 90-day uniaxial compressive strength (90 d-UCS) was the maximum of the UCS of sulfide-rich CPB. The hydration products and microstructural characteristics observed by XRD and scanning electron microscopy (SEM) illustrated that RS has the effect of bridging and water retention. Accordingly, adding RS improved the long-term strength of sulfide-rich CPB. The optimal RSD, RSL, and SC for 90 d-UCS of sulfide-rich CPB were obtained through the response surface methodology approach. The optimal conditions within the experimental range of this study for maximum 90 d-UCS of CPB with high SC (17 wt%) were RSD of 0.032 wt% and RSL of 0.28 cm, producing a 90 d-UCS of 5.14 MPa.