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With the rapid development of society, a wide variety of consumer applications are increasingly emerging. At the same time, the involvement of intelligent technologies such as deep learning, reinforcement learning, and quantum computing is empowering consumer applications by driving them to be smarter, more secure, and digitized. Among them, the underwater field is an important application direction, such as equipment overhaul, scientific research, resource exploration, and so on. This paper targets the detection, optimization, and inference tasks in underwater applications, aiming to design efficient and safe solution algorithms for them using new techniques. First, we establish an underwater mission scenario, using time-varying current data to create a 3D ocean environment model, which can satisfy the requirements of different underwater applications. Second, a safe and efficient underwater object detection algorithm is designed, which constructs a deep neural network to extract valid information from redundant environments. Finally, a path planning algorithm for underwater unmanned equipment clusters is developed to solve the optimization decision problem through deep reasoning computation. We carry out a series of comparative experiments, which adequately prove that the algorithm proposed in this paper has good superiority, can cope with the interference of different intensities of ocean currents, and ensures the operational effect of the cluster formation.

Graphdiyne (GDY) multilayers show stacking-style-dependent physical properties; thus, controlling the stacking style of nanostructures is crucial for utilizing their electrical, optical, and transport properties in electro-optical devices. Herein, we report the assemblies of nanographdiynes decorated with substituents with different steric hindrances to adjust the stacking style. We show that the π-stacked aggregates were influenced by peripheral substituents and the substrate. Steric hexaterphenyl-substituted nanoGDY scaffolds led to dimer structures stacked in the AB-3 configuration with a twist angle of 26.01° or the AB-1 configuration with an in-plane shift along one diyne link. With the interval replacement of steric substituents with long C12 alkyl chains, nanoGDYs were stacked in the AB-2 configuration to decrease the steric congestion, eventually leading to one-dimensional (1D) nanofibrous aggregates. Self-assembly in the presence of substrates can result in ABC-stacked nanoGDYs, which endowed us with the possibility of using nanoGDY as the template for GDY growth in a homogeneous reaction. High-resolution transmission electron microscopy (HRTEM), powder X-ray diffraction (PXRD), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and near-infrared–ultraviolet–visible (NIR–UV–vis) absorption spectroscopy indicate that the crystalline GDY prepared in this way is a 1.18 eV bandgap semiconductor.

The Tactile Internet (TI) allows operators to have an immersive experience in a remote environment. During this process, users generate a large amount of demonstration data containing tactile information. It is important to reasonably use user-generated data to improve the intelligence of Tactile Internet applications without infringing on user privacy. In order to use only user-generated datasets for learning without expensive environment interaction, conservative policy estimation in offline reinforcement learning is introduced in this brief to ensure the convergence of reinforcement learning algorithms. In addition, the dataset composed of different user behavior data has the characteristics of multimodal distribution, where the same state corresponds to different actions. The offline reinforcement learning algorithm is used to reconstruct and learn the user’s behavior under the framework of federated learning, and the diffusion model is introduced to model the multimodal distribution caused by different user preference. Based on this, we propose a federated diffusion Q-learning (FDQL) algorithm and verify the effectiveness of the algorithm in the d4rl dataset. Experimental results demonstrate that the FDQL algorithm performs efficiently within the federated learning framework, effectively capturing users’ multimodal behaviors and achieving state-of-the-art results.

In recent years, with the expanding scope of the Intelligent Cyber-Physical Transportation Systems (ICTS), Autonomous Underwater Vehicle (AUV) has also become a hot product in this field that consumers are paying attention to. Consumer-level AUVs have a broad consumer market for underwater detection and search and rescue due to their small size, autonomy, flexibility, and long endurance. The formation of multiple AUVs can complete more diverse and complex tasks. However, consumers can only communicate with AUVs when they float to the surface, which poses a tough challenge to AUV’s formation control. This paper proposes an AUV On-board Control Scheme (AUV-OCS) based on multi-agent reinforcement learning and cloud computing technology to serve consumer-level AUVs, in which the local perception information preprocessed by each AUV is uploaded to the cloud center for data fusion in real-time and a centralized value function is designed to optimize the global decision. The experimental results show that the proposed AUV-OCS can effectively control the AUV cluster to complete underwater task in a predetermined formation for consumers with an average task success rate of 97.4%, and has a certain collision avoidance ability.

The aerodynamic benefits of non-smooth surfaces, such as drag reduction, are well-established, but accurately simulating their effects poses significant challenges due to increased modeling complexity and computational demands. This paper introduces an enhanced simulation method tailored for analyzing the near-wall flow fields of non-smooth surfaces. By developing a modified wall function, the proposed method replicates the flow characteristics of non-smooth surfaces on smooth walls, thereby simplifying the simulation process. The results demonstrate a marked improvement in computational efficiency, with a reduction in simulation time by more than 20%, without compromising accuracy. This approach offers a robust and efficient tool for aerodynamic optimization in engineering applications.

Smartphone addiction among child users is becoming a severe global social problem. Uncontrolled and unsupervised use of smartphones by children has posed a significant threat to the health and property of both children and their parents. Automatic identification of child users on smartphones can be an effective way to alleviate this problem. Unfortunately, existing works usually require additional input devices like cameras for face biometrics or additional applications for users’ specific touch-interaction behavior to identify child users, leading to poor user experience and privacy concerns. This paper develops a novel, implicit and continuous system, named ChildShield, for child identification on smartphones. Specifically, our system providing a built-in data acquisition service can automatically and real-timely collect users’ behavioral data in a non-conscious and privacy-preserving manner. We build a large-scale database by collecting users’ operations in 5 complex and popular mobile game applications on 12 different models of smartphones from 1875 subjects. Based on the feature extracted from multi-finger interaction data in realistic and complex usage scenarios, ChildShield can learn the discriminative behavioral patterns for accurate child identification using the specifically designed deep learning-based classifiers. Then when a child user is identified, the pre-setting subsequent operation like Enable Kids Mode in ChildShield can be executed to provide a protective shield for children. The effectiveness of ChildShield is validated on the created database. Our approach significantly outperforms existing methods, achieves an EER of 4.38% for child identification, and performs an even lower EER of 2.12% for the younger age group.

Major depressive disorder, a prevalent and severe psychiatric condition, necessitates development of new and fast-acting antidepressants. Genetic suppression of astrocytic inwardly rectifying potassium channel 4.1 (Kir4.1) in the lateral habenula ameliorates depression-like phenotypes in mice. However, Kir4.1 remains an elusive drug target for depression. Here, we discovered a series of Kir4.1 inhibitors through high-throughput screening. Lys05, the most potent one thus far, effectively suppressed native Kir4.1 channels while displaying high selectivity against established targets for rapid-onset antidepressants. Cryogenic-electron microscopy structures combined with electrophysiological characterizations revealed Lys05 directly binds in the central cavity of Kir4.1. Notably, a single dose of Lys05 reversed the Kir4.1-driven depression-like phenotype and exerted rapid-onset (as early as 1 hour) antidepressant actions in multiple canonical depression rodent models with efficacy comparable to that of (S)-ketamine. Overall, we provided a proof of concept that Kir4.1 is a promising target for rapid-onset antidepressant effects.

Behavioral biometrics has been widely investigated and deployed in real world scenarios for human authentication. However, there has been almost nil attempt to identify behavior patterns in a cross-scenario setting, which is common in practice and needs urgent attention. This paper defines and investigates cross-scenario behavioral biometrics authentication using keystroke dynamics. A novel system called CrossBehaAuth is presented for extending keystroke dynamics-based behavior authentication to new scenarios and extensive problems. We design a temporal-aware learning mechanism based deep neural network for cross-scenario keystroke dynamics authentication. This mechanism selectively learns and encodes temporal information for efficient behavioral pattern transfer in cross-scenario settings. A local Gaussian data augmentation approach is proposed to increase the diversity of behavioral data and therefore, further improve the performance. We evaluate the proposed approach on two publicly available datasets. The extensive experimental results confirm the efficacy of our CrossBehaAuth for cross-scenario keystroke dynamics authentication. Our approach significantly improves the authentication accuracy in cross-scenario settings and even achieves comparable performance on single-scenario authentication tasks. In addition, our approach shows its generalizability and advantages in both single and cross scenario keystroke dynamics authentication.

In this study, the decomposed fast and slow responses of clouds to an abruptly quadrupled CO2concentration (approximately 1139 ppmv) in East Asia (EA) are obtained quantitatively by using a general circulation model, BCC–AGCM2.0. Our results show that in the total response, the total cloud cover (TCC), low cloud cover (LCC), and high cloud cover (HCC) all increased north of 40°N and decreased south of 40°N except in the Tibetan Plateau (TP). The mean changes of the TCC, LCC, and HCC in EA were −0.74%, 0.38%, and −0.38% in the total response, respectively; 1.05%, −0.03%, and 1.63% in the fast response, respectively; and −1.79%, 0.41%, and −2.01% in the slow response, respectively. By comparison, we found that changes in cloud cover were dominated by the slow response in most areas in EA due to the changes in atmospheric temperature, circulation, and water vapor supply together. Overall, the changes in the cloud forcing over EA related to the fast and slow responses were opposite to each other, and the final cloud forcing was dominated by the slow response. The mean net cloud forcing (NCF) in the total response over EA was −1.80 W m−2, indicating a cooling effect which partially offset the warming effect caused by the quadrupled CO2. The total responses of NCF in the TP, south China (SC), and northeast China (NE) were −6.74 W m−2, 6.11 W m−2, and −7.49 W m−2, respectively. Thus, the local effects of offsetting or amplifying warming were particularly obvious.

Herein, we synthesized different kinds of citric acid based CDs from low-cost citric acid and used them for culturing Italian lettuce. Since they all used citric acid as a precursor, some similarities were observed in terms of optical properties, morphologies, and chemical compositions. In comparison to the control group, they were able to increase the fresh weight of lettuce by 25.53% (CA-CDs), 33.25% (EDA-CDs), and 39.5% (Mg,N-CDs) respectively. Moreover, the three CDs can enhance the nutrient qualities of lettuce. After evaluating the promotion effect of three kinds of CDs on the growth and nutritional qualities of lettuce, we found that the promotion effect of Mg,N-CDs was the best among the three. The results of PAM chlorophyll fluorescence imaging indicate that Mg,N-CDs can promote photosynthesis, thereby increasing weight and accumulating nutrients. This work provides guidance for designing CDs for agricultural production.

Dear Editor, This letter presents an inspection method for process monitoring of underwater oil transportation via multiple autonomous underwater vehicles (AUV). To improve the adaptability of our method in practice, we introduce the dynamic complex ocean current data to the previously mentioned case by using regional ocean modeling system (ROMS) for the first time, and elaborately design AUV's local information, as well as the deep reinforcement learning (DRL) tuple $(S_{t}, A_{t}, R_{t}, S_{t+l})$. Specifically, according to the local information of each AUV, including captured pipeline image, ocean current velocity, position coordinates and pose angles, an agent can be well trained to control the AUV for underwater oil pipeline tracking through vision-hydrology-motion-based soft actor critic (VHM-SAC) mechanism. Experimental results show that the proposed method can provide stable oil pipeline tracking performance in dynamic complex underwater environment.

Graphdiyne(GDY), a new carbon allotrope composed of sp-sp2carbon atoms, has attracted increased attention in recent years. It has a direct band gap of 0.46–1.22 eV, high charge carrier mobility and lower work function compared to most of the typical semiconductors, which ensure successful hybridization with other semiconductors(e.g., TiO2, g-C3N4). This review aims at discussing recent achievements of GDY and its analogues applied in photocatalytic and photoelectrochemical(PEC) reactions. Meanwhile, some challenges and new perspectives of opportunities in developing catalysts and electrodes based on GDY and its analogues are also discussed.

The improvement of the accuracy of simulated cloud-related variables, such as the cloud fraction, in global climate models (GCMs) is still a challenging problem in climate modeling. In this study, the influence of cloud microphysics schemes (one-moment versus two-moment schemes) and cloud overlap methods (observation-based versus a fixed vertical decorrelation length) on the simulated cloud fraction was assessed in the BCC_AGCM2.0_CUACE/Aero. Compared with the fixed decorrelation length method, the observation-based approach produced a significantly improved cloud fraction both globally and for four representative regions. The utilization of a two-moment cloud microphysics scheme, on the other hand, notably improved the simulated cloud fraction compared with the one-moment scheme; specifically, the relative bias in the global mean total cloud fraction decreased by 42.9%–84.8%. Furthermore, the total cloud fraction bias decreased by 6.6% in the boreal winter (DJF) and 1.64% in the boreal summer (JJA). Cloud radiative forcing globally and in the four regions improved by 0.3%–1.2% and 0.2%–2.0%, respectively. Thus, our results showed that the interaction between clouds and climate through microphysical and radiation processes is a key contributor to simulation uncertainty.

This study aimed to assess the effect of inbreeding on production traits using a long-term closed-line population recorded for residual feed intake (RFI). The study first used data from a previously reported population to determine the appropriate period of divergent selection for RFI. The results showed that RFI had similar moderate heritability estimates (0.28–0.34) during the fast-growing period (7–12 wk), and RFI at 7 to 10 wk had the highest heritability (0.34). Therefore, divergent selection was performed in a Chinese broiler population for RFI at 7 to 10 wk; the total sample size from generations zero (G0) to 13 was 9050. The divergence between the 2 lines increased steadily throughout generations, resulting in G13 with average RFI values of 304.55 in high RFI (HRFI) males, −160.31 in low RFI (LRFI) males, 296.30 in HRFI females and −157.55 in LRFI females. The feed intake (FI) and feed conversion ratio were almost higher in HRFI broilers than in LRFI broilers, and the magnitude of the difference in FI increased from approximately 4% for both sexes in G1 to approximately 33% in G13. Body weight gain was irregular from G1 to G13 and higher in LRFI broilers than in HRFI broilers after G10. Indeed, the HRFI broilers consumed more food, but they were lighter than LRFI broilers. In G13, LRFI males had heavier slaughter weight, longer cecum length, more white blood cells (WBC), red blood cells (RBC) and hemoglobin (HGB), but triglycerides, lower dressed percentage, percentage of half eviscerated yield, and eviscerated yield than HRFI males. LRFI females had a higher percentage of breast muscle and gizzard yield, longer cecum length, and more WBCs, RBCs and HGB but less abdominal fat and serum total cholesterol than HRFI females. This study was the first to verify that long-term divergent selection for RFI in Chinese broiler chickens is positive and beneficial.

Graphdiyne, a sp- and sp2-hybridized 2D π-conjugated carbon material with well-dispersed pores and unique electronic properties, was well investigated and applied in catalysis, electronics, optics, and energy storage and conversion. Graphdiyne fragments with conjugation in 2D can provide in-depth insights for understanding the intrinsic structure–property relationships of graphdiyne. Herein, an atomic precise wheel-shaped nanographdiyne composed of six dehydrobenzo [18] annulenes ([18]DBAs, the smallest macrocyclic unit of graphdiyne), was realized through the sixfold intramolecular Eglinton coupling in the hexabutadiyne precursors obtained by the sixfold Cadiot–Chodkiewicz cross-coupling of hexaethynylbenzene. Its planar structure was revealed by X-ray crystallographic analysis. The full cross-conjugation of the six 18π electron circuits yields the π-electron conjugation along the giant π core. This work provides a realizable method for the synthesis of future graphdiyne fragments with different functional groups and/or heteroatom doping, as well as the study of the unique electronic/photophysical properties and aggregation behavior of graphdiyne.

The hydrodynamic damping characteristics of elastic rotating propeller blades are investigated theoretically and experimentally. Firstly, the modal hydrodynamic damping ratio of propeller blade rotating in water is theoretically predicted based on the cantilever plate theory. Then, a series of tests are designed to determine the mechanical, acoustic radiation and hydrodynamic damping of the first-order bending mode of the rotating blade. During the hydrodynamic damping test, the bending vibration of the blade is excited by the rotation-induced turbulence and measured by two strain gauges attached to the blade root. The results show that the theoretical prediction is in good agreement with the experimental results. The hydrodynamic damping increases linearly with the rotational speed of the propeller. Theoretical analysis also shows that the modal hydrodynamic damping ratio of the first-order bending mode is much larger than that of higher-order bending modes. The hydrodynamic damping decays exponentially with the increase of frequency ratio while increases slightly with the increase of propeller advance ratio which represents the ratio of free stream fluid speed to the propeller tip speed.

High-performance frontal analysis (HPFA) and high-perfon-ance liquid chromatography (HPLC) were incorporated in an on-line coupled column system for the enantioselective determination of unbound fenoprofen (FP) concentrations in the state of a protein binding equilibrium following direct sample injection. This system consists of a "restricted access" type column for HPFA and al-acid glycoprotein-immobilized silica column for chiral separation. When a 80-μL portion of a sample solution containing 50 or 90μg/mL FP and 300 or 550,μM human serum albumin (HSA) was directly injected into the HPFA column, FP gave a trapezoidal peak exhibiting a plateau region. The concentration in the plateau range was equal to the unbound FP concentration in the initial sample solution. By the delivery of a 90-μL portion of the eluent in this plateau region into the chiral separation column, the unbound concentrations of FP enantiomers were determined. The results agreed with those obtained by the conventional ultrafil-tration-HPLC method. The precision was also confirmed by the within-run and day-to-day reproducibilities (CV<9.95%, n=5). It was found that the binding between FP and HSA is stereoselective, and S-FP binds with HSA more strongly than R-FP.

The metabolic requirements of hematopoietic stem cells (HSCs) change with their cell cycle activity. However, the underlying role of mitochondria remains ill-defined. Here we found that, after mitochondrial activation with replication, HSCs irreversibly remodel the mitochondrial network and that this network is not repaired after HSC re-entry into quiescence, contrary to hematopoietic progenitors. HSCs keep and accumulate dysfunctional mitochondria through asymmetric segregation during active division. Mechanistically, mitochondria aggregate and depolarize after stress because of loss of activity of the mitochondrial fission regulator Drp1 onto mitochondria. Genetic and pharmacological studies indicate that inactivation of Drp1 causes loss of HSC regenerative potential while maintaining HSC quiescence. Molecularly, HSCs carrying dysfunctional mitochondria can re-enter quiescence but fail to synchronize the transcriptional control of core cell cycle and metabolic components in subsequent division. Thus, loss of fidelity of mitochondrial morphology and segregation is one type of HSC divisional memory and drives HSC attrition.

Hematopoietic stem cells (HSC) have extensive regenerative potential but limited self-renewal ability. The repopulation potential is gradually lost with HSC divisions and during stress hematopoiesis. Hence, we hypothesize that activation or inactivation of signaling pathways or other mechanisms, inherently occurring during HSC activation into cycle, drives their progressive functional decline. To address this, we used single cell RNA-sequencing and compared the transcriptome of HSCs [Lin-c-Kit+Sca-1+CD48-CD150+] that is expressed upon exit from quiescence and the one that is inherited by daughter cells upon HSC division. We compared HSCs with full self-renewal activity to HSCs that have lost self-renewal activity [i.e. before (NT-HSC) and after transplantation (T-HSC), respectively]. Analysis of the data was performed using unsupervised methods, namely iterative clustering and guide-gene selection (ICGS), [Olsson et al, Nature, 2016] and principal component (PCA) analysis. Each revealed that genes categorized in mitochondrial organization were dramatically upregulated in activated NT-HSC and remained highly expressed in their daughter cells. Remarkably, ICGS revealed at least 2 distinct regulatory states within T-HSC; one that clustered within NT-HSC, and another one that was clearly separated from NT-HSC. The latter was exclusively comprised of daughter T-HSCs, and quite unexpectedly was demarcated by a lack of expression of mitochondrial genes along with changes in expression of genes related to cytoskeleton organization. Using EGFP-mitochondria reporter mice; which labels mitochondria regardless of their membrane potential and activated state, we found that NT-HSC had 4-fold higher mitochondrial content than progenitors. High resolution confocal imaging indicated that mitochondria were punctuated and the network was dispersed in the entire cell volume in NT-HSC. However, in T-HSCs, mitochondria formed one or a few larger aggregates. Mitochondrial membrane potential was also severely reduced in T-HSC in vivo, indicating that HSC accumulate dysfunctional mitochondria after replicative stress during stress hematopoiesis. During cell division, in vitro, mitochondria were unequally distributed to daughter cells of single T-HSC division [one daughter cell had more aggregated mitochondria], whereas mitochondria were equally partitioned during division of NT-HSC, suggesting that HSC lose mitochondrial quality control after replicative stress. Further, mitochondria aligned along the microtubule network in NT-HSC but not in T-HSC. Mitochondrial morphology and distribution are maintained through regulated cycles of fission and fusion, which is essential for maintaining a functional organelle and for equal mitochondrial inheritance during division. We found that the mitochondrial fission protein Drp1, which normally accumulated and wrapped around mitochondria in NT-HSC during cell activation, failed to do so in T-HSCs, perhaps due to impaired mitochondrial-cytoskeleton association. Genetic loss of Drp1 caused severe mitochondrial aggregation in HSCs, and impaired HSC self-renewal and repopulation ability in competitive transplant studies, indicating that accumulation of aggregated and dysfunctional mitochondria causes HSC functional defects. To understand whether HSCs accumulated abnormal mitochondrial morphology with divisional history during homeostatic conditions, we used the GFP label-retaining H2B mouse model. Remarkably, mitochondria were well dispersed and homogeneously distributed in GFP labeled-retaining HSCs (i.e. HSC that had not divided), while HSCs with history of cell division (no GFP) had larger and more compact aggregates. Hence, once HSCs exit from quiescence, they irreversibly accumulate dysfunctional mitochondria over the course of divisions due to lack of mitochondrial quality control mechanisms, which drives gradual heterogeneity and loss of self-renewal ability. Thus, HSCs use mitochondrial architecture to remember their divisions, in turn affecting their self-renewal ability. Therefore, drugs or pharmacological inhibitors targeting mitochondrial organization or its quality can be new therapeutic approach to improve HSC function following transplantation.

No relevant conflicts of interest to declare.