Cross-domain bearing fault diagnosis using dual-path convolutional neural networks and multi-parallel graph convolutional networks.

Bearing fault diagnosis is significant in ensuring large machinery and equipment's safe and stable operation. However, inconsistent operating environments can lead to data distribution differences between source and target domains. As a result, models trained solely on source-domain data may not perform well when applied to the target domain, especially when the target-domain data is unlabeled. Existing approaches focus on improving domain adaptive methods for effective transfer learning but neglect the importance of extracting comprehensive feature information. To tackle this challenge, we present a bearing fault diagnosis approach using dual-path convolutional neural networks (CNNs) and multi-parallel graph convolutional networks (GCNs), called DPC-MGCN, which can be applied to variable working conditions. To obtain complete feature information, DPC-MGCN leverages dual-path CNNs to extract local and global features from vibration signals in both the source and target domains. The attention mechanism is subsequently applied to identify crucial features, which are converted into adjacency matrices. Multi-parallel GCNs are then employed to further explore the structural information among these features. To minimize the distribution differences between the two domains, we incorporate the multi-kernel maximum mean discrepancy (MK-MMD) domain adaptation method. By applying the DPC-MGCN approach for diagnosing bearing faults under diverse working conditions and comparing it with other methods, we demonstrate its superior performance on various datasets.

Nanomedicine revolutionizes epilepsy treatment: overcoming therapeutic hurdles with nanoscale solutions.

INTRODUCTION: Epilepsy, a prevalent neurodegenerative disorder, profoundly impacts the physical and mental well-being of millions globally. Historically, antiseizure drugs (ASDs) have been the primary treatment modality. However, despite the introduction of novel ASDs in recent decades, a significant proportion of patients still experiences uncontrolled seizures. AREAS COVERED: The rapid advancement of nanomedicine in recent years has enabled precise targeting of the brain, thereby enhancing therapeutic efficacy for brain diseases, including epilepsy. EXPERT OPINION: Nanomedicine holds immense promise in epilepsy treatment, including but not limited to enhancing drug solubility and stability, improving drug across blood-brain barrier, overcoming resistance, and reducing side effects, potentially revolutionizing clinical management. This paper provides a comprehensive overview of current epilepsy treatment modalities and highlights recent advancements in nanomedicine-based drug delivery systems for epilepsy control. We discuss the diverse strategies used in developing novel nanotherapies, their mechanisms of action, and the potential advantages they offer compared to traditional treatment methods.

Unusual cysteine modifications in natural product biosynthesis.

l-Cysteine is a highly reactive amino acid that is modified into a variety of chemical structures, including cysteine sulfinic acid in human metabolic pathways, and sulfur-containing scaffolds of amino acids, alkaloids, and peptides in natural product biosynthesis. Among the modification enzymes responsible for these cysteine-derived compounds, metalloenzymes constitute an important family of enzymes that catalyze a wide variety of reactions. Therefore, understanding their reaction mechanisms is important for the biosynthetic production of cysteine-derived natural products. This review mainly summarizes recent mechanistic investigations of metalloenzymes, with a particular focus on recently discovered mononuclear non-heme iron (NHI) enzymes, dinuclear NHI enzymes, and radical-SAM enzymes involved in unusual cysteine modifications in natural product biosynthesis.

A context-dependent perspective to understand the relation between parent-child physiological synchrony and child socioemotional adjustment.

Physiological synchrony is an important biological process during which parent-child interaction plays a significant role in shaping child socioemotional adjustment. The present study held a context-dependent perspective to examine the conditional association between parent-child physiological synchrony and child socioemotional adjustment (i.e., relationship quality with parents and child emotion regulation) under different (i.e., from highly unsupportive to highly supportive) emotional contexts. One hundred and fifty school-age Chinese children (Mage = 8.64 years, 63 girls) and their primary caregivers participated in this study. After attaching electrocardiogram (ECG) electrodes, parent-child dyads were instructed to complete a 4-minute conflict discussion task. Parent-child physiological synchrony was calculated based on the within-dyad association between parents' and children's respiratory sinus arrhythmia (RSA) levels across eight 30-second epochs. Parental emotional support, child relationship quality with parents, and child emotion regulation during the discussion task were coded by trained research assistants. Supporting our hypotheses, parental emotional support moderated the relations of parent-child RSA synchrony with both child relationship quality with parents and child emotion regulation. Furthermore, the Johnson-Neyman technique of moderation indicated that the associations between parent and child RSA synchrony and child socioemotional adjustment indicators shifted from negative to positive as the parental emotional support became increasingly high. Our findings suggest that parent-child physiological synchrony may not be inherently adaptive or maladaptive, highlighting the importance of understanding the function of parent-child physiological synchrony under specific contexts. RESEARCH HIGHLIGHTS: Physiological synchrony may not be inherently adaptive or maladaptive, and the meanings of parent-child physiological synchrony might be contingent on contextual factors. Parental emotional support moderated the relations between parent-child respiratory sinus arrhythmia (RSA) synchrony and child socioemotional adjustment indicators (i.e., child relationship quality with parents and child emotion regulation). More positive/less negative parent-child RSA synchrony was associated with better child socioemotional adjustment under a supportive emotional context, whereas with poorer child socioemotional adjustment under an unsupportive emotional context. These findings highlight the significance of considering the emotional context in physiological synchrony studies.

TpPa-1 COFs-Enhanced Zwitterion Hydrogel for Efficient Harvesting of Atmospheric Water.

Zwitterionic hydrogel, serving as carriers for hygroscopic salts, holds significant potential in atmospheric water harvesting. However, their further application is limited by structural collapse in high-concentration salt solution and poor photothermal conversion performance. Herein, the graded pore structure of poly-3-[dimethyl-[2-(2-methylprop-2-enoyloxy)ethyl]azaniumyl]propane-1-sulfonate (PDMAPS) zwitterionic hydrogel/TpPa-1 covalent organic frameworks (COFs)/LiCl composite (named as PCL composite hydrogel) is proposed, which leads to the accelerated diffusion effect for water molecules. As a result, the vapor adsorption capacity of the optimal composite hydrogel (PCL-42) reaches 2.88 g g-1 within 12 hours under conditions of 25 °C and 90 % RH. Simultaneously, the maximum temperature of PCL-42 composite could reach 53.9 °C after 9 minutes under a simulated solar intensity of 1.0 kW m-2, releasing 91 % of the adsorbed water in 3 hours, providing a promising prospect for efficient solar-driven atmospheric water harvesting. One cycle could collect 7.55 g of fresh water under outdoor conditions, and the maximum daily water production may reach 2.71 kg kg-1. The reason lies in that TpPa-1 COFs lead hydrogel to form a gradient pore structure, which may accelerate the transport of water molecules, increase the loading capacity of LiCl and enhance the photothermal property.

Covalent Organic Framework Ionomer Steering the CO2 Electroreduction Pathway on Cu at Industrial-Grade Current Density.

CO2 electroreduction holds great promise for addressing global energy and sustainability challenges. Copper (Cu) shows great potential for effective conversion of CO2 toward specific value-added and/or high-energy-density products. However, its limitation lies in relatively low product selectivity. Herein, we present that the CO2 reduction reaction (CO2RR) pathway on commercially available Cu can be rationally steered by modulating the microenvironment in the vicinity of the Cu surface with two-dimensional sulfonated covalent organic framework nanosheet (COF-NS)-based ionomers. Specifically, the selectivity toward methane (CH4) can be enhanced to more than 60% with the total current density up to 500 mA cm-2 in flow cells in both acidic (pH = 2) and alkaline (pH = 14) electrolytes. The COF-NS, characterized by abundant apertures, can promote the accumulation of CO2 and K+ near the catalyst surface, alter the adsorption energy and surface coverage of *CO, facilitate the dissociation of H2O, and finally modulate the reaction pathway for the CO2RR. Our approach demonstrates the rational modulation of reaction interfaces for the CO2RR utilizing porous open framework ionomers, showcasing their potential practical applications.

Data augmentation using continuous conditional generative adversarial networks for regression and its application to improved spectral sensing.

Machine learning-assisted spectroscopy analysis faces a prominent constraint in the form of insufficient spectral samples, which hinders its effectiveness. Meanwhile, there is a lack of effective algorithms to simulate synthetic spectra from limited samples of real spectra for regression models in continuous scenarios. In this study, we introduced a continuous conditional generative adversarial network (CcGAN) to autonomously generate synthetic spectra. The labels employed for generating the spectral data can be arbitrarily selected from within the range of labels associated with the real spectral data. Our approach effectively produced spectra using a small spectral dataset obtained from a self-interference microring resonator (SIMRR)-based sensor. The generated synthetic spectra were subjected to evaluation using principal component analysis, revealing an inability to discern them from the real spectra. Finally, to enhance the DNN regression model, these synthetic spectra are incorporated into the original training dataset as an augmentation technique. The results demonstrate that the synthetic spectra generated by CcGAN exhibit exceptional quality and significantly enhance the predictive performance of the DNN model. In conclusion, CcGAN exhibits promising potential in generating high-quality synthetic spectra and delivers a superior data augmentation effect for regression tasks.

Gradient Channel Segmentation in Covalent Organic Framework Membranes with Highly Oriented Nanochannels.

Covalent organic frameworks (COFs) offer an exceptional platform for constructing membrane nanochannels with tunable pore sizes and tailored functionalities, making them promising candidates for separation, catalysis, and sensing applications. However, the synthesis of COF membranes with highly oriented nanochannels remains challenging, and there is a lack of systematic studies on the influence of postsynthetic modification reactions on functionality distribution along the nanochannels. Herein, we introduced a "prenucleation and slow growth" approach to synthesize a COF membrane featuring highly oriented mesoporous channels and a high Brunauer-Emmett-Teller surface area of 2230 m2 g-1. Functional moieties were anchored to the pore walls via "click" reactions and coordinated with Cu ions to serve as segmentation functions. This led to a remarkable H2/CO2 separation performance that surpassed the Robeson upper bound. Moreover, we found that the functionalities distributed along the nanochannels could be influenced by functionality flexibility and postsynthetic reaction rate. This strategy paved the way for the accurate design and construction of COF-based artificial solid-state nanochannels with high orientation and precisely controlled channel environments.

Multiscale Dynamic Graph Representation for Biometric Recognition With Occlusions.

Occlusion is a common problem with biometric recognition in the wild. The generalization ability of CNNs greatly decreases due to the adverse effects of various occlusions. To this end, we propose a novel unified framework integrating the merits of both CNNs and graph models to overcome occlusion problems in biometric recognition, called multiscale dynamic graph representation (MS-DGR). More specifically, a group of deep features reflected on certain subregions is recrafted into a feature graph (FG). Each node inside the FG is deemed to characterize a specific local region of the input sample, and the edges imply the co-occurrence of non-occluded regions. By analyzing the similarities of the node representations and measuring the topological structures stored in the adjacent matrix, the proposed framework leverages dynamic graph matching to judiciously discard the nodes corresponding to the occluded parts. The multiscale strategy is further incorporated to attain more diverse nodes representing regions of various sizes. Furthermore, the proposed framework exhibits a more illustrative and reasonable inference by showing the paired nodes. Extensive experiments demonstrate the superiority of the proposed framework, which boosts the accuracy in both natural and occlusion-simulated cases by a large margin compared with that of baseline methods.

Hierarchical Microtubular Covalent Organic Frameworks Achieved by COF-to-COF Transformation.

Pore environment and aggregated structure play a vital role in determining the properties of porous materials, especially regarding the mass transfer. Reticular chemistry imparts covalent organic frameworks (COFs) with well-aligned micro/mesopores, yet constructing hierarchical architectures remains a great challenge. Herein, we reported a COF-to-COF transformation methodology to prepare microtubular COFs. In this process, the C3 -symmetric guanidine units decomposed into C2 -symmetric hydrazine units, leading to the crystal transformation of COFs. Moreover, the aggregated structure and conversion degree varied with the reaction time, where the hollow tubular aggregates composed of mixed COF crystals could be obtained. Such hierarchical architecture leads to enhanced mass transfer properties, as proved by the adsorption measurement and chemical catalytic reactions. This self-template strategy was successfully applied to another four COFs with different building units.

Metal-Organic Frameworks for Breakthrough Separation of 2-Butene Isomers with High Dynamic Selectivity and Capacity.

Developing porous sorbents represents a potential energy-efficient way for industrial gas separation. However, a bottleneck for reducing the energy penalty is the trade-off between dynamic adsorption capacity and selectivity. Herein, we showed this problem can be overcome by modulating the kinetic and thermodynamic separation behaviours in metal-organic frameworks for sieving 2-butene geometric isomers, which are desired for upgrading the raffinates to higher value-added end products. We found that the iron-triazolate framework can realize the selective shape screening of 2-butene isomers assisted by electrostatic interactions at the pore apertures. Further introducing uncoordinated N binding sites by ligand substitution lowered the gas diffusion barrier and greatly boosted the dynamic separation performance. In breakthrough tests under ambient conditions, trans-2-C4 H8 can be efficiently separated from cis-2-C4 H8 with a record capacity of 2.10 mmol g-1 with high dynamic selectivity of 2.39.

Experimental Investigation of Discharge Phenomena in Electrochemical Discharge Machining Process.

Electrochemical discharge machining (ECDM) is a promising non-traditional processing technology used to machine non-conductive materials, such as glass and ceramic, based on the evoked electrochemical discharge phenomena around the tool electrode. The discharge in ECDM is a key factor that affects the removal of material. Moreover, the discharge current is an important indicator reflecting the discharge state. However, the discharge characteristics remain an open topic for debate and require further investigation. There is still confusion regarding the distinction of the discharge current from the electrochemical reaction current in ECDM. In this study, high-speed imaging technology was applied to the investigation of the discharge characteristics. By comparing the captured discharge images with the corresponding discharge current, the discharge can be classified into three types. The observations of the discharge effect on the gas film indicate that a force was exerted on the gas film during the discharge process and the shape of the gas film was changed by the force. In addition, the energies released by different types of discharge were calculated according to the voltage and current waveforms. The discharge frequency was found to increase with the increase in applied voltage and the frequency of the second type of discharge was approximately equal to that of the third type when the applied voltage was higher than 40 V.

Co-designed metaoptoelectronic deep learning.

A metaoptical system is co-designed with electronic hardware to implement deep learning image recognition. The optical convolution block includes a reflective metasurface to perform one layer of a deep neural network. The optical and digital components are jointly optimized to perform an image classification task attaining 65% accuracy, which is close to the 66% accuracy of a fully-digital network where the optical block is replaced by a digital convolution layer.

Biallelic mutations in LSS in autosomal-recessive mutilating palmoplantar keratoderma.

Mutilating palmoplantar keratoderma (PPK) is a heterogeneous genetic disease that poses enormous challenges to clinical diagnosis and genetic counselling. Lanosterol synthase (LSS) gene encodes LSS involved in the biosynthesis pathway of cholesterol. Biallelic mutations in LSS were found to be related to diseases such as cataracts, hypotrichosis and palmoplantar keratoderma-congenital alopecia syndrome. The aim of this study was to investigate the contribution of the LSS mutation to mutilating PPK in a Chinese patient. The clinical and molecular characteristics of the patient were evaluated. A 38-year-old male patient with mutilating PPK was recruited in this study. We identified biallelic variants in the LSS gene (c.683C > T, p.Thr228Ile and c.779G > A, p.Arg260His). Immunoblotting revealed that the Arg260His mutant showed a significantly reduced expression level while Thr228Ile showed an expression level similar to that of the wild type. Thin layer chromatography revealed that mutant Thr228Ile retained partial enzymatic activity and mutant Arg260His did not show any catalytic activity. Our findings show the correlation between LSS mutations and mutilating PPK.

2D Covalent Organic Framework for Water Harvesting with Fast Kinetics and Low Regeneration Temperature.

Atmospheric water harvesting represents a promising technique to address water stress. Advanced adsorbents have been rationally designed to achieve high water uptake, yet their water sorption kinetics and regeneration temperature greatly limit water production efficiency. Herein, we demonstrated that 2D covalent organic frameworks (COFs), featuring hydrophobic skeleton, proper hydrophilic site density, and 1D open channels significantly lowered the water diffusion and desorption energy barrier. DHTA-Pa COF showed a high water uptake of 0.48 g/g at 30 % R.H. with a remarkable adsorption rate of 0.72 L/Kg/h (298 K) and a desorption rate of 2.58 L/Kg/h (333 K). Moreover, more than 90 % adsorbed water could be released within 20 min at 313 K. This kinetic performance surpassed the reported porous materials and boosted the efficiency for multiple water extraction cycles. It may shed light on the material design strategy to achieve high daily water production with low-energy input.

The Influence of Storage in Saline or Irradiation by Ultraviolet on Surface Hydrophilicity of Implant and Osseointegration: An Experimental Study in Rabbits.

Storage in aqueous solution or ultraviolet (UV) irradiation can retain or regain the hydrophilicity of titanium implant surface. In this study, 3 types of commercial titanium implants were used: ZBL (ZDI Bone Level), CEL (C-tech Esthetic Line), and modSLA (Straumann SLActive). ZBL and CEL implants were treated with UV irradiation for 4 hours. Surface characterization of the 4 groups (ZBL, ZBL-UV, CEL-UV, and modSLA) was evaluated by scanning electron microscopy and contact angle measurements. The in vivo bone response was evaluated by removal torque (RTQ) tests and histomorphometric analysis at 3, 6, and 12 weeks postimplantation. A total of 144 implants and 36 rabbits were used for experiments according to a previously established randomization sequence. The ZBL-UV, CEL-UV, and modSLA groups were hydrophilic, and nanostructures were observed on the modSLA implant surface. ModSLA achieved better RTQ value than ZBL at 12 weeks (P < .05). For histomorphometric analysis, ZBL-UV and CEL-UV implants showed higher bone area values in the cancellous bone zone at 6 weeks than did modSLA and ZBL implants (P < .05). In the cortical bone zone, all groups showed comparable bone-to-implant contact at all healing time points (P > .05). Both storage in saline and UV irradiation could retain or provoke hydrophilic surfaces and improve osseointegration. Compared with storage in saline, UV irradiation displayed slight advantages in promoting new bone formation in cancellous bone zone at an early stage.

Development of nonionic nanoemulsions to improve hydrophobic 9'-cis-bixin stability in acidic aqueous medium with in vitro cytosis and nanosafety evaluation.

Nonionic oil-in-water (O/W) nanoemulsion provides potential to stabilize hydrophobic bio-functional components in aqueous medium. Understanding safety of nanoemulsion droplets via investigating in vitro cell uptake and cellular substructural changes is important to achieve their practical applications. Herein, we developed a nonionic O/W nanoemulsion to stabilize representative bio-functional hydrophobic component of 9'-cis-bixin at pH 3-7 and ultraviolet (UV)-induced degradation at 365, 302, and 254 nm. In vitro cell uptake demonstrated that Caco-2 cells adequately enriched 9'-cis-bixin through fast uptake of nanoemulsion droplets within 15 min. However, excessive nanoemulsion droplets greatly decreased cell survival rate, which was due to the potential destruction of cellular substructures of mitochondria, nuclear membrane, and cell membrane. Lower nanoemulsion concentration provided no significant effects on Caco-2 cell survival. This work provided objective understanding on bio-functional component stability by nanoemulsion with in vitro safety evaluation.

Covalent organic framework-based porous ionomers for high-performance fuel cells.

Lowering platinum (Pt) loadings without sacrificing power density and durability in fuel cells is highly desired yet challenging because of the high mass transport resistance near the catalyst surfaces. We tailored the three-phase microenvironment by optimizing the ionomer by incorporating ionic covalent organic framework (COF) nanosheets into Nafion. The mesoporous apertures of 2.8 to 4.1 nanometers and appendant sulfonate groups enabled the proton transfer and promoted oxygen permeation. The mass activity of Pt and the peak power density of the fuel cell with Pt/Vulcan (0.07 mg of Pt per square centimeter in the cathode) both reached 1.6 times those values without the COF. This strategy was applied to catalyst layers with various Pt loadings and different commercial catalysts.

Biallelic Variants in Lanosterol Synthase (LSS) Cause Palmoplantar Keratoderma-Congenital Alopecia Syndrome Type 2.

Palmoplantar keratoderma-congenital alopecia syndrome type 2 is an autosomal recessive disorder with an unknown genetic basis. In this study, we identified biallelic variants in the LSS gene in two unrelated palmoplantar keratoderma-congenital alopecia syndrome type 2 cases (c.3G>A, p.Met1? and c.1025T>G, p.Ile342Ser in patient 1; c.1522G>T, p.Gly508Trp and c.428+42T>A in patient 2) presenting with additional clinical features, including early-onset cataracts, pseudoainhum, and agenesis of the corpus callosum. LSS encodes lanosterol synthase (LSS), which functions in the cholesterol biosynthesis pathway by converting (S)-2,3-oxidosqualene to lanosterol. The c.3G>A variant resulted in an alternative translation initiation at residue Met81, producing an N-terminal truncated protein (LSS-ΔN80), as shown by immunoblotting. The c.428+42T>A variant introduced a potential splicing site, leading to a premature stop codon. Ex vivo studies revealed downregulation of LSS in both patients. Remarkably decreased lanosterol levels were found in vitro in three LSS variants, LSS-ΔN80, p.Ile342Ser, and p.Gly508Trp, suggesting a loss of enzymatic activity. Transmission electron microscopy and immunofluorescence showed abnormal cornified envelope formation in the stratum corneum of the patients. Taken together, our findings indicate LSS as a causative gene for palmoplantar keratoderma-congenital alopecia syndrome type 2, which emphasizes the importance of the cholesterol synthesis pathway in human skin cornification.

Covalent Organic Frameworks with Record Pore Apertures.

The pore apertures dictate the guest accessibilities of the pores, imparting diverse functions to porous materials. It is highly desired to construct crystalline porous polymers with predesignable and uniform mesopores that can allow large organic, inorganic, and biological molecules to enter. However, due to the ease of the formation of interpenetrated and/or fragile structures, the largest pore aperture reported in the metal-organic frameworks is 8.5 nm, and the value for covalent organic frameworks (COFs) is only 5.8 nm. Herein, we construct a series of COFs with record pore aperture values from 7.7 to 10.0 nm by designing building blocks with large conformational rigidness, planarity, and suitable local polarity. All of the obtained COFs possess eclipsed stacking structures, high crystallinity, permanent porosity, and high stability. As a proof of concept, we successfully employed these COFs to separate pepsin that is ∼7 nm in size from its crudes and to protect tyrosinase from heat-induced deactivation.