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ABSTRACTThe highly loaded design method of helium compressors can effectively solve the difficulty in compressing helium in High Temperature Gas-cooled Reactors (HTGR). But it also causes obviously different attack angle characteristics of blade surface loads in a highly loaded helium compressor compared to air compressors. This difference inevitably affects separation characteristics and flow loss within the compressor. In the current study, the effects of highly loaded design methods and changes in attack angle on the separation characteristics of the compressor cascade are analyzed by applying a numerical simulation method first. Then, the influence of Mach number on the loss characteristics of the cascade for a highly loaded helium compressor is systematically analyzed. Finally, the effect of differences in the material properties of working fluid on the separation characteristics is discussed. The results indicate that the proportion of secondary flow loss to the total loss in highly loaded compressor cascades is 2.46 times larger than that in conventionally loaded ones. While the properties of working fluid have an effect on the performance of the compressor cascade, their effects on the weight factor of vortex loss are highly limited.

Reducing production costs and energy consumption has always been the focus of industrial production today, which is driving the chemical industries from this old model towards developing sustainable processes with high efficiency and environmental protection. In this paper, three energy-saving and environment-friendly extractive distillation processes were designed and optimized to separate the methanol/water/toluene mixture. The extractive distillation process was improved by preheating the feed stream using a solvent circulation stream, the thermal energy utilization efficiency has been enhanced. Meanwhile, the process parameters were optimized by multi-objective genetic algorithm (MOGA) taking total annual cost (TAC), CO2emission (ECO2), and separation efficiency of extractive section (Eext) as objective functions. Compared with the existing process, the best separation process can reduce the TAC by up to 20.0 % and the ECO2by up to 30.0 %. In addition, the validity and rationality of the separation processes were verified by analyzing the influence of sensitive variables and exergy losses. This study provides a reference for the separation and energy saving of wastewater containing methanol and toluene.

This study explores the mechanisms enhancing phosphorus (P) release from sludge in anaerobic digestion (AD) with thermal hydrolysis pretreatment (THP) using sequential chemical extraction, X-ray absorption near-edge structure spectroscopy (XANES), 31P NMR, and multiomics. THP-treated sludge notably increased liquid-phase P by 53.8% over 3 days compared to sewage sludge (SS), identifying solid-phase Fe–P as the primary P source. The THP+AD also provided a higher abundance of bacteria that contributed to P release through multiple pathways (MPRPB), whereas SS+AD enriched some microbial species with single P release pathway. Moreover, species co-occurrence network analysis underlined the pivotal role of P-releasing bacteria in THP+AD, with 8 out of 16 keystones being P-releasers. Among the 63 screened genes that were related to P transformations and release, the poly beta-hydroxybutyrate (PHB) synthesis genes associated with polyphosphate bacteria-mediated P release were more abundant in THP+AD than in SS+AD. Furthermore, the upregulation of genes involved in methyl phosphonate metabolism in the THP-treated sludge enhanced the methane production potential of the AD process. These findings suggested that MPRPB were indeed the main contributors to P release, and enrichment in the THP+AD process enhanced their capability for P liberation.

Spin-crossover (SCO) materials that reversibly switch between high- and low-spin states have potential for the storage of spin state-relative information, and have gained much attention incorporating secondary physical properties, such as fluorescence and magneto-optical switching. In this study, we synthesized three octanuclear metal-organic cages (MOCs) using tetra-phenylethylene-based luminophores, aldehydes, and FeIIsalts, by subcomponent self-assembly approach, namely [Fe1]-[Fe3]. By controlling the ligand-field strength and guest encapsulation, we finely tuned their SCO properties. Among them, MOC [Fe2]displayed nearly complete SCO behavior in the solid state, which is rare for high-nuclearity complexes. We also demonstrated the coupling of SCO with fluorescence emission in these MOCs by using isostructural ZnIIcomplexes ([Zn1]-[Zn3]) as control experiments, for the first time. Theoretical calculations revealed the energy-transfer mechanism between fluorophores and SCO-active centers, which emphasizes the significant contribution of d-d transitions in the interplay between the occurrence of SCO and fluorescence emission.

The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated gene (Cas) system is continually optimized to achieve the most efficient gene editing effect. The Cas12iMax, a Cas12i variant, exhibits powerful DNA editing activity and enriches the gene editing toolbox. However, the application of Cas12iMaxin large domestic animals has not yet been reported. To verify the efficiency and feasibility of multiple gene editing in large animals, we generated porcine fibroblasts with simultaneous knockouts of IGF2, ANPEP, CD163, and MSTNvia Cas12iMaxin one step. Phenotypically stable pigs were created through somatic cell nuclear transfer technology. They exhibited improved growth performance and muscle quality. Furthermore, we simultaneously edited three genes in bovine fibroblasts. A knockout of MSTNand PRNPwas created and the amino acid Q-G in CD18was precisely substituted. Meanwhile, no off-target phenomenon was observed by sum-type analysis or off-target detection. These results verified the effectiveness of Cas12iMaxfor gene editing in livestock animals and demonstrated the potential application of Cas12iMaxin the field of animal trait improvement for agricultural production.

Metal halide perovskite (MHP) structures that exhibit polarized photoluminescence (PL) have attracted significant interest in fabricating light field regulation elements for display, imaging, and information storage applications. We report a three-dimensional direct lithography of heterostructures for controllable polarized PL inside glass by laser-induced localized temperature engineering. The heterostructures consisted of oriented periodic structures (OPSs) and MHP nanocrystals, and the mechanism for hierarchical distribution of heterostructures was illustrated. The patterning of heterostructures for manipulable polarized PL can be used for information encryption, wave-plate, and polarized micro-LEDs.

Polydatin, a glucoside of resveratrol, has shown protective effects against various diseases. However, little is known about its effect on hepatic ischemia-reperfusion (I/R) injury. This study aimed to elucidate whether polydatin protects liver against I/R-induced injury and to explore the underlying mechanism.

Acoustic ranging has been viewed as a promising Human-Computer Interaction (HCI) technology in many scenarios, such as Augmented Reality (AR)/Virtual Reality (VR) and smart appliances. Most ranging systems with distributed devices undergo an extra calibration process to remove the timing errors. However, the calibration process needs user intervention. Furthermore, it should assume that the clock drifts are linear and stable, which is disabled within tens of minutes. In this paper, we introduce a self-calibrated acoustic ranging system that achieves sub-millimeter accuracy on distributed asynchronous devices. Based on our theoretical timing model, we precisely cancel both the system delay and the nonlinear clock drift with carefully designed Orthogonal Frequency-Division Multiplexing (OFDM) ranging signals. Our synchronization scheme achieves a timing accuracy of 1.9 microseconds, which allows us to build large-scale virtual acoustic arrays. Based on such a calibration scheme, our localization system achieves a ranging error of $\text{0.39}\;mm$0.39mm within three meters in real-world experiments.

Al–Si–Cu–Ni–Mg–(Zr, Sr) alloys were prepared by permanent mold gravity casting. The effects of Zr and Sr on the microstructure and mechanical properties of cast Al-12Si-6Cu-1.5Ni-1.3Mg alloy at room temperature and high temperature were investigated systematically using X-ray diffractometer (XRD), ultra-depth-of-field metallographic microscope, scanning electron microscope (SEM), transmission electron microscope (TEM) and electronic universal testing machine. The experimental results show that the size of eutectic Si phase and Al–Cu–Ni phase is decreased with the addition of Zr, and it has little effect on the primary Si phase. The massive primary Si phase of the alloy with 0.1%Zr + 0.04%Sr addition disappears, and the eutectic Si phase changes from acicular to fibrous phase, which has little effect on the size of the Al–Cu–Ni phase. The ultimate tensile strength, yield strength and elongation of the alloy with 0.1%Zr + 0.04%Sr addition at room temperature are 360 MPa, 318 MPa and 4.2%, respectively. The ultimate tensile strength and elongation of the alloy with 0.1%Zr addition at high temperatures are 194 MPa, 4.3%, 117 MPa, 7.5% at 275 °C and 350 °C, respectively.

Abiotic d-proteins that selectively bind to natural l-proteins have gained significant biotechnological interest. However, the underlying structural principles governing such heterochiral protein–protein interactions remain largely unknown. In this study, we present the de novo design of d-proteins consisting of 50–65 residues, aiming to target specific surface regions of l-proteins or l-peptides. Our designer d-protein binders exhibit nanomolar affinity toward an artificial l-peptide, as well as two naturally occurring proteins of therapeutic significance: the D5 domain of human tropomyosin receptor kinase A (TrkA) and human interleukin-6 (IL-6). Notably, these d-protein binders demonstrate high enantiomeric specificity and target specificity. In cell-based experiments, designer d-protein binders effectively inhibited the downstream signaling of TrkA and IL-6 with high potency. Moreover, these binders exhibited remarkable thermal stability and resistance to protease degradation. Crystal structure of the designed heterochiral d-protein–l-peptide complex, obtained at a resolution of 2.0 Å, closely resembled the design model, indicating that the computational method employed is highly accurate. Furthermore, the crystal structure provides valuable information regarding the interactions between helical l-peptides and d-proteins, particularly elucidating a novel mode of heterochiral helix–helix interactions. Leveraging the design of d-proteins specifically targeting l-peptides or l-proteins opens up avenues for systematic exploration of the mirror-image protein universe, paving the way for a diverse range of applications.

Precise identification and quantification of amino acids is crucial for many biological applications. Here we report a copper(II)-functionalized Mycobacterium smegmatisporin A (MspA) nanopore with the N91H substitution, which enables direct identification of all 20 proteinogenic amino acids when combined with a machine-learning algorithm. The validation accuracy reaches 99.1%, with 30.9% signal recovery. The feasibility of ultrasensitive quantification of amino acids was also demonstrated at the nanomolar range. Furthermore, the capability of this system for real-time analyses of two representative post-translational modifications (PTMs), one unnatural amino acid and ten synthetic peptides using exopeptidases, including clinically relevant peptides associated with Alzheimer’s disease and cancer neoantigens, was demonstrated. Notably, our strategy successfully distinguishes peptides with only one amino acid difference from the hydrolysate and provides the possibility to infer the peptide sequence.

This paper presents a general framework for addressing sparse portfolio optimization problems using the mean-CVaR (Conditional Value-at-Risk) model and regularization techniques. The framework incorporates a non-negative constraint to prevent the portfolio from being too heavily weighted in certain assets. We propose a specific ADMM (alternating directional multiplier method) for solving the model and provide a subsequential convergence analysis for theoretical integrity. To demonstrate the effectiveness of our framework, we consider the ℓ1and SCAD (smoothly clipped absolute deviation) penalties as notable instances within our unified framework. Additionally, we introduce a novel synthesis of the CVaR-based model with ℓ1/ℓ2regularization. We explore the subproblems of ADMM associated with CVaR and the presented regularization functions, employing the gradient descent method to solve the subproblem related to CVaR and the proximal operator to evaluate the subproblems with respect to penalty functions. Finally, we evaluate the proposed framework through a series of parametric and out-of-sample experiments, which shows that the proposed framework can achieve favorable out-of-sample performance. We also compare the performance of the proposed nonconvex penalties with that of convex ones, highlighting the advantages of nonconvex penalties such as improved sparsity and better risk control.

In large-scale physics experiments, clock distribution and time synchronization over multigigabit serial links on one single optical fiber may benefit from the fixed-latency command distribution. For better portability, we make a new design of the off-the-shelf high-speed serial communication protocol Aurora 64B/66B, in which timing commands can be distributed with a fixed latency and clock can be distributed with a predictable phase. This design based on Aurora 64B/66B enables fixed-latency command distribution and fixed-phase clock distribution, with a jitter of few tens of picoseconds. It is available to all field-programmable gate arrays (FPGAs) which are supported in Aurora 64B/66B. The design concept used in our design to eliminate the latency variations in the 64B/66B synchronous gearbox can also be used in designs using the 64B/67B encoding and 10-Gb ethernet application.

Brain networks are built according to the structures or neural activities of different brain regions, which can be modeled as complex networks. Many studies exploit brains from the perspective of graph learning to diagnose the nerve diseases of brains. However, many of these algorithms are unable to automatically construct brain function topology based on electroencephalogram (EEG) and fail to capture the global features of multichannel EEG signals for whole-graph embedding. To address these challenging issues, we propose an attention-based whole-graph learning model for the diagnosis of brain diseases, namely, MAINS, which can adaptively construct brain functional topology from EEG signals and effectively embed multiple node features and the global structural features of brain networks into the whole-graph representations. We validated the model by conducting classification (diagnosis) experiments on real EEG datasets. Comprehensive experimental results demonstrate the superiority of the proposed approach over state-of-the-art methods.

Psychrophilic microalgae successfully survive in the extreme and highly variable polar ecosystems, which represent the energy base of most food webs and play a fundamental role in nutrient cycling. The success of microalgae is rooted in their adaptive evolution. Revealing how they have evolved to thrive in extreme polar environments will help us better understand the origin of life in polar ecosystems. We isolated a psychrophilic unicellular green alga, Microglenasp. YARC, from Antarctic sea ice which has a huge genome. Therefore, we predicted that gene replication may play an important role in its polar adaptive evolution. We found that its protein-coding gene number significantly increased and the duplication time was dated between 37 and 48 million years ago, which is consistent with the formation of the circumpolar Southern Ocean. Most duplicated paralogous genes were enriched in pathways related to photosynthesis, DNA repair, and fatty acid metabolism. Moreover, there were a total of 657 Microglena-specific families, including collagen-like proteins. The divergence in the expression patterns of the duplicated and species-specific genes reflects sub- and neo-functionalization during stress acclimation. Overall, key findings from this study provide new information on how gene duplication and their functional novelty contributed to polar algae adaptation to the highly variable polar environmental conditions.

One key property in recommender systems is the long-tail distribution in user-item interactions where most items only have few user feedback. Improving the recommendation of tail items can promote novelty and bring positive effects to both users and providers, and thus is a desirable property of recommender systems. Current novel recommendation methods over-emphasize the importance of tail items without differentiating the degree of users’ intent on popularity and often incur a sharp decline of accuracy. Moreover, none of existing studies has ever taken the extreme case of tail items, i.e., cold-start items without any interaction, into consideration. In this work, we first disclose the mechanism that drives a user's interaction towards popular or niche items by disentangling her intent into conformity influence (popularity) and personal interests (preference). We then present a unified end-to-end framework to simultaneously optimize accuracy and novelty targets based on the disentangled intent of popularity and that of preference. We further develop a new paradigm for novel recommendation of cold-start items which exploits the self-supervised learning technique to model the correlation between collaborative features and content features. We conduct extensive experiments on three real-world datasets. The results demonstrate that our proposed model yields significant improvements over the state-of-the-art baselines in terms of the trade-off between accuracy and novelty.

In this paper, we propose a Dynamic Speed Warping (DSW) algorithm to enable one-shot learning for device-free acoustic gesture signals performed by different users. The design of DSW is based on the observation that the gesture type is determined by the trajectory of hand components rather than the movement speed. By dynamically scaling the speed distribution and tracking the movement distance along the trajectory, DSW can effectively match gesture signals from different domains with a ten-fold difference in speeds. Our experimental results show that DSW can achieve a recognition accuracy of 97% for gestures performed by unknown users while only using one training sample of each gesture type from four training users.

Microplastics of size <25 μm possess globally transportable features, but the impact of precipitation on their transport remains unclear. Here, microplastics were detected in all 10 studied rainfalls in Beijing, with <25 μm microplastics present in 8 rainfalls. Interestingly, microplastic abundance (7590–136,778 items·m–3) was tentatively linked to maximum rainfall intensity, with <25 μm microplastics making up 39.6 (±27.5)% of the total count. The composition of <25 μm microplastics differed from that of larger microplastics, although both mainly comprised polystyrene, polyethylene, and polypropylene. The microplastic communities differed among rainfalls, suggesting that atmospheric transport is a highly dynamic process. The first rainfall exhibited the highest microplastic abundance and community diversity after long-term exposure to dry atmospheric environment. The deposited microplastics were unstable and highly fragmented according to the conditional fragmentation model. The wet deposition rate of the microplastics was calculated as 2–463 μg·m–2(146–8629 items·m–2) per rain, amounting to 25.44 tons per annum in Beijing. Although <25 μm microplastics represented a negligible proportion (0.00–1.24%) of the overall mass load of microplastics, their numerical abundance was high. Our results demonstrate that precipitation is an effective mechanism for removing airborne microplastics, which may enter urban soils and waters, exacerbate microplastic burdens in the environment, and cause potential risk for human health.

ABSTRACTTitanium slag obtained from electric-furnace smelting using ilmenite from Panzhihua contains predominately two phases: anosovite and augite. The mineral phase compositions in titanium slag can have severe effects on the leaching process and leaching efficiency. However, the precise role of the effect of mineral phases on the leaching efficiency is unclear. Here, we demonstrate that the formation of boundaries between mineral phases in titanium slag acts as resistance to slow down the leaching rate of titanium from titanium slag in sulphuric acid. We found the dissolution rate of augite phase was much slower than anosovite phase, and the surface area available for the titanium leaching from titania-rich anosovite phase was reduced due to the coexistence of augite and anosovite phases in titanium slag particles. Our results demonstrate that the formation of boundary structures of anosovite and augite phases is an important factor affecting the leaching efficiency of titanium slag.

Ocean warming (OW) and acidification (OA) are recognized as two major climatic conditions influencing phytoplankton growth and nutritional or toxin content. However, there is limited knowledge on the responses of harmful algal bloom species that produce toxins. Here, the study provides quantitative and mechanistic understanding of the acclimation and adaptation responses of the domoic acid (DA) producing diatom Pseudo-nitzschia multiseriesto rising temperature and pCO2using both a one-year in situ bulk culture experiment, and an 800-day laboratory acclimation experiment. Ocean warming showed larger selective effects on growth and DA metabolism than ocean acidification. In a bulk culture experiment, increasing temperature +4?°C above ambient seawater temperature significantly increased DA concentration by up to 11-fold. In laboratory when the long-term warming acclimated samples were assayed under low temperatures, changes in growth rates and DA concentrations indicated that P. multiseriesdid not adapt to elevated temperature, but could instead rapidly and reversibly acclimate to temperature shifts. However, the warming-acclimated lines showed evidence of adaptation to elevated temperatures in the transcriptome data. Here the core gene expression was not reversed when warming-acclimated lines were moved back to the low temperature environment, which suggested that P. multiseriescells might adapt to rising temperature over longer timescales. The distinct strategies of phenotypic plasticity to rising temperature and pCO2demonstrate a strong acclimation capacity for this bloom-forming toxic diatom in the future ocean.

Event building is an important task for data acquisition (DAQ) systems in high-energy physics experiments. D-Matrix is designed as a generic distributed stream processing DAQ platform, containing hardware description language (HDL)-based modules and software modules. In the D-Matrix system, the data transfer is abstracted into the form of a stream, and the event building is implemented through a cascade of various reusable stream processing modules. These stream processing modules will determine their work modes automatically based on a set of attributes, which describe the abstracted data stream characteristics, such as spatiotemporal organization and granularity. This article introduces the event building architecture, the physics data structure abstraction, and the algorithmic implementation of specific event building modules in the D-Matrix system. An application of the D-Matrix event building architecture in the CSR external-target experiment is presented in the end.

This study aims to predict the ash deposition rate on the windward and leeward sides of a tube in a two-dimensional computational domain of single row tube array. Based on particle viscosity criterion, an ash deposition model with considering the salt vapour condensation was developed and extended into computational fluid dynamics (CFD) calculation by user-defined function. The transport behaviour of ash particles was numerically described with the Lagrangian method under the effects of inertial force, turbulent eddy, Saffman's lift force, thermophoretic force and Brownian force. The results show that fine particles easily enter into the leeward part of tubes due to the combination effect of turbulent vortex and thermophoresis force. The ash deposition rate and the salt vapour condensation rate on the windward side of the first tube are equally important in the initial stage of ash deposition. While for other tubes downstream, the contribution of vapour condensation to the initially deposited mass is much greater than that of ash deposition. Ash deposition mass on the stagnation position of tubes is mainly from larger particles with the diameter over 10 μm and salt vapour condensation. [Received: September 18, 2021; Accepted: February 14, 2023]

Information-theoretic stealth attacks are data injection attacks that minimize the amount of information acquired by the operator about the state variables, while simultaneously limiting the Kullback-Leibler divergence between the distribution of the measurements under attack and the distribution under normal operation with the aim of controling the probability of attack detection. For Gaussian distributed state variables, attack construction requires knowledge of the second order statistics of the state variables, which is estimated from a finite number of past realizations using a sample covariance matrix. Within this framework, the attack performance is studied for the attack construction with the sample covariance matrix. This results in an analysis of the amount of data required to learn the covariance matrix of the state variables used on the attack construction. The ergodic attack performance is characterized using asymptotic random matrix theory tools and the variance of the attack performance is bounded. The ergodic performance and the variance bounds are assessed with simulations on IEEE test systems.

To improve the efficiency of innovative design and performances of a product, a self-commentary design method facing product-oriented innovation and fuzzy back end evaluation was proposed. Firstly, a functional structure mode of product was built on the basis of axiomatic design theory. The contradiction matrix must be built and the initial scheme should be redesigned by TRIZ conflict analysis method in order to be decoupled, and got product innovation program. Lastly, taking the lower extremity exoskeleton robot as an example, the structure was decoupled and optimised using Altium Designer (AD) and TRIZ theory. The performance of the lower extremities exoskeleton robot was evaluated quantificationally by using fuzzy analytic hierarchy process, which verified the feasibility and effectiveness of the decoupling design and fuzzy back end evaluation method for product innovation design and inspection.

Due to the structural inheritance, a uniform and refined as-cast microstructure is usually desirable for further thermomechanical processing of biodegradable Zn alloys. Considering the effectiveness of pulsed magnetic field (PMF) for structure refinement and homogenization, a high-voltage PMF was applied to the solidification process of Zn-Cu alloys with different compositions in this work. For Zn-1.5Cu alloy, a 6 kV PMF (i.e., a PMF generated by a discharge voltage of 6 kV) transformed the macrostructure from a mixture of coarse columnar and equiaxed η-Zn grains with an average size of 1437 ± 482 μm to homogeneously distributed fine equiaxed η-Zn grains with an average size of 454 ± 15 μm. For Zn-2.5Cu alloy, a 6 kV PMF changed the long dendritic primary ɛ-CuZn4particles into fine dot-like particles. Correspondingly, the coarse equiaxed η-Zn grains with an average size of 1895 ± 375 μm are transformed to fine equiaxed ones with an average size of 446 ± 46 μm due to the increase in amount of the primary ɛ-CuZn4particles as potent heterogeneous nucleation sites. For Zn-4.0Cu alloy, a 6 kV PMF causes segregation of the primary ɛ-CuZn4particles at the lower part of the specimen and intensifies the macrostructural inhomogeneity. For all the alloys, the most significant effect of the PMF on structure refinement and homogenization occurs in the early stage of solidification. The convection and Joule heat induced by the PMF in the melt are responsible for the structural transformation.

Ocean warming (OW) and acidification (OA) are recognized as two major climatic conditions influencing phytoplankton growth and nutritional or toxin content. However, there is limited knowledge on the responses of harmful algal bloom species that produce toxins. Here, the study provides quantitative and mechanistic understanding of the acclimation and adaptation responses of the domoic acid (DA) producing diatom Pseudo-nitzschia multiseriesto rising temperature and pCO2using both a one-year in situ bulk culture experiment, and an 800-day laboratory acclimation experiment. Ocean warming showed larger selective effects on growth and DA metabolism than ocean acidification. In a bulk culture experiment, increasing temperature +4 °C above ambient seawater temperature significantly increased DA concentration by up to 11-fold. In laboratory when the long-term warming acclimated samples were assayed under low temperatures, changes in growth rates and DA concentrations indicated that P. multiseriesdid not adapt to elevated temperature, but could instead rapidly and reversibly acclimate to temperature shifts. However, the warming-acclimated lines showed evidence of adaptation to elevated temperatures in the transcriptome data. Here the core gene expression was not reversed when warming-acclimated lines were moved back to the low temperature environment, which suggested that P. multiseriescells might adapt to rising temperature over longer timescales. The distinct strategies of phenotypic plasticity to rising temperature and pCO2demonstrate a strong acclimation capacity for this bloom-forming toxic diatom in the future ocean.