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The return of crop residues to cultivated fields has numerous agronomic and soil quality benefits and, therefore, the areal extent of crop residue cover (CRC) could provide a rapid measure of the sustainability of agricultural production systems in a region. Recognizing the limitations of traditional CRC methods, a new method is proposed for estimating the spatial and temporal distribution of maize residue cover (MRC) in the Jilin Province, NE China. The method used random forest (RF) algorithms, 13 tillage indices and 9 textural feature indicators derived from Sentinel-2 data. The tillage indices with the best predictive performance were STI and NDTI (R2of 0.85 and 0.84, respectively). Among the texture features, the best-fitting was Band8AMean-5∗5 (R2of 0.56 and 0.54 for the line-transect and photographic methods, respectively). Based on MSE and InNodePurity, the optimal combination of RF algorithm for the line-transect method was STI, NDTI, NDI7, NDRI5, SRNDI, NDRI6, NDRI7 and Band3Mean-3∗3. Likewise, the optimal combination of RF algorithm for the photographic method was STI, NDTI, NDI7, SRNDI, NDRI6, NDRI5, NDRI9 and Band3Mean-3∗3. Regional distribution of MRC in the Jilin Province, estimated using the RF prediction model, was higher in the central and southeast sections than in the northwest. That distribution was in line with the spatial heterogeneity of maize yield in the region. These findings showed that the RF algorithm can be used to map regional MRC and, therefore, represents a useful tool for monitoring regional-scale adoption of conservation agricultural practices.

Prognostics and health management technology for industrial equipment heavily relies on the accurate prediction of the remaining useful life (RUL). As commonly used RUL prediction approaches, the conventional convolutional neural network, and long-short term memory network are not only difficult to realize the extraction process of spatio-temporal features, but also cannot reflect the difference between the data at different moments in the RUL prediction results. Aimed to deal with these problems, a self-attention mechanism network integrating spatio-temporal feature extraction (SAMN-STFE) is proposed to predict RUL, which can deliver higher weight to the significant moments. In detail, feature selection and noise reduction are performed on the data picked up by the multiple sensors during the working process. The self-attention mechanism network assigns corresponding weights to different time points in the time window. Afterward, the spatial features are extracted by one-dimensional convolutional neural network. The temporal features are extracted by bidirectional long short-term memory networks. Ultimately, the trained SAMN-STFE can be utilized for online RUL prediction. To validate the proposed approach for predicting RUL, the dataset of aircraft turbofan engines, furnished by NASA Ames Prediction Center is employed. Experimental results represent that the proposed approach has excellent RUL prediction performance.

The unsatisfactory treatment outcome of Alzheimer’s disease (AD) can be attributed to two primary factors, the intricate pathogenic mechanisms leading to restricted treatment effectiveness against single targets and the hindered drug accumulation in brain due to blood–brain barrier obstruction. Therefore, we developed a carrier-free nanomodulator (NanoDS) through the self-assembly of donepezil and simvastatin for direct nose-to-brain delivery. This approach facilitated a rapid and efficient traversal through the nasal epithelial barrier, enabling subsequent drug release and achieving multiple therapeutic effects. Among them, donepezil effectively ameliorated the symptoms of AD and restored synaptic plasticity. Simvastatin exerted a neurotrophic effect and facilitated the clearance of amyloid-β aggregation. At the same time, NanoDS demonstrated effective anti-inflammatory and antioxidative stress effects. This therapy for AD is approached from both symptomatic and etiological perspectives. In the treatment of FAD4Ttransgenic mice, it highly improved spatial memory impairment and cognitive deficits while restoring the homeostasis of brain microenvironment. Collectively, our study presented a paradigm for both achieving efficient brain delivery and offering pleiotropic therapies for AD.

AbstractThe metaverse is hyped as revolutionizing advertising, but practitioners remain cautious. Knowledge of “why” advertisers are or are not adopting the metaverse is limited, because they have not been asked. Through 48 interviews with advertising executives, this research elucidates a complex ecosystem with four affordances (novel advertising space, immersive experiences, specific audience targeting, and communicating brand innovativeness) and four disaffordances (limited reach, anticipated lack of return on investment, lack of requisite technical expertise, and poor interoperability) that underpin adoption. These are shaped by consumers’ and decision makers’ (dis)affordances, as well as by contextual factors such as industry norms. The authors offer an advertising-context-specific definition of the metaverse and questions to guide practitioners’ adoption.

Flow chemistry coupled with microreactor technology represents a contemporary advancement in the chemical industry. This approach integrates chemical synthesis, organic chemistry, and green chemistry, offering enhanced safety for hazardous chemical operations. In the present study, the continuous flow synthesis and separation of diazoacetate ethyl ester (EDA) in a microchannel reactor were investigated using glycine ethyl ester hydrochloride (GEE), sodium nitrite, and acetic acid as starting materials, with 1,2-dichloroethane utilized as an extractant. Response surface analysis (RSM) was adopted to determine appropriate test design factors and levels using single-factor experiments as a basis, and a model was constructed by means of the Box–Behnken Design (BBD) central combination principle. The effects of reaction temperature (5–15 °C), GEE to acetic acid molar ratio (1: 2.8–3.2), residence time (90–150 s), and GEE to sodium nitrite molar ratio (1: 1.0–1.2) were investigated, examining the interactions among these factors to determine their combined effects on the yield of the diazotization process. The optimal process conditions for synthesizing ethyl diazoacetate in a microchannel reactor were determined: n(GEE):n(sodium nitrite):n(acetic acid) = 1:1.154:3.069, reaction temperature of 9.82 °C, and residence time of 135.18 s. The yield of GEE diazonium salt under such conditions was predicted to be 95.02%. The results reveal that the residence time significantly affected the yield of the product. Additionally, a three-dimensional computational fluid dynamics model was developed for the microchannel reactor to predict flow patterns and micromixing efficiency during the iodate–iodide reaction. As demonstrated, velocity, path lines, and concentration distributions inside the reactor could be visualized by examining the effects of Re, volumetric flow ratio (R), and initial H+concentration on micromixing efficiency (representative of the segregation index XS). XSdecreased with increasing Reor decreasing Ror initial H+concentrations. The control system for the integrated continuous flow preparation of EDA, which integrates continuous production, extraction, and separation, provides a novel approach for industrial production.

This article proposes an online estimation strategy for reducing parameter identification errors in surface-mounted permanent magnet synchronous linear motor (SPMSLM) at low speeds. The strategy is based on injecting signals into dual axis, enabling full-speed domain parameter identification. First, sensitivity analysis is conducted on resistance, inductance, and flux linkage concerning speed and torque, revealing significant parameter identification errors in traditional voltage model-based methods under low-speed and low-current conditions. Next, the impact of sampling noise on parameter identification is analyzed when the sampling signal is small. Subsequently, an identification strategy is proposed that simultaneously injects signals in both the d-q and $\alpha $ - $\beta $ axes to accurately estimate resistance and inductance at low speed and low current. Finally, experiments were conducted on an SPMSLM, and the results indicated that the proposed method significantly reduces identification errors caused by low signal-to-noise ratio during low speeds.

The total synthesis and structural elucidation of the antimicrobial sactipeptide enteropeptin A is reported. Enteropeptin A contains a thioaminoketal group with an unassigned stereochemical configuration that is embedded in a highly unusual thiomorpholine ring. In this synthesis, a linear peptide containing a dehydroamino acid and a pendant cysteine residue is subjected to Markovnikov hydrothiolation by a dithiophosphoric acid catalyst. This cyclization reaction forms the central thiomorpholine ring found in the enteropeptins. Both diastereomers at the unassigned thioaminoketal stereocenter of enteropeptin A were prepared, and their comparison to an authentic standard allowed for the unambiguous stereochemical assignment of the natural product to be of the D configuration. This inaugural total synthesis of enteropeptin A represents the first total synthesis of a sactipeptide reported to date. Moreover, the strategy disclosed herein serves as a general platform for the synthesis of stereochemically defined thiomorpholine-containing peptides, which may enable the discovery of new cyclic peptide antibiotics.

The simultaneous removal of multi-VOCs (C3H6O/C6H6/C7H8/C8H10) and NO/SO2by catalytic ozonation on the CoOx-CrOx/γ-Al2O3(SCC) catalyst was studied on a laboratory scale and in industrial field testing, respectively. It was discovered that the removal efficiencies of aromatic VOCs gradually increased as the excess ozone ratio (λ), the ratio of the actual number of moles of ozone to the theoretical number, increased. With the help of a wet scrubbing system, multi-VOCs and SO2can be completely removed. The removal efficiency of NO remained above 95%, and the NO2selectivity was only 2%. The applicability of the SCC catalyst at lower temperatures was verified by achieving conversion efficiencies of multiple pollutants of more than 80% at 50 °C, with the scrubbing system. In an industrial field-scale test performed in a textile mill in Anhui Province, China, it was proven that in the absence of catalyst assistance, VOCs with high molecular weight were gradually degraded and small molecules such as methanol, formaldehyde, and formic acid were generated more. Coupled with the SCC catalyst, at λ = 3, the concentrations of almost all major VOC pollutants could be degraded to <3 ppm. Analyzed by XRD, O2-TPD, H2-TPR, XPS, and ICP-OES characterizations, the excellent activity and stability of the SCC catalysts are attributed to the good dispersion of metal oxides, strong intermetallic interactions, excellent reducibility, rapid redox cycles of Cr3+/Cr6+and Co2+/Co3+, and abundant chemisorbed oxygen. The slight deactivation of the SCC catalysts utilized continuously in the textile mill may be related to the loss of active Cr6+and Co2+. The results show that the combination of catalytic ozonation technology and the wet scrubbing system can realize the efficient and simultaneous removal of multiple pollutants, providing an experimental and practical basis for further industrial application.

Biological materials exhibit fascinating mechanical properties for intricate interactions at multiple interfaces to combine superb toughness with wondrous strength and stiffness. Recently, strong interlayer entanglement has emerged to replicate the powerful dissipation of natural proteins and alleviate the conflict between strength and toughness. However, designing intricate interactions in a strong entanglement network needs to be further explored. Here, we modulate interlayer entanglement by introducing multiple interactions, including hydrogen and ionic bonding, and achieve ultrahigh mechanical performance of graphene-based nacre fibers. Two essential modulating trends are directed. One is modulating dynamic hydrogen bonding to improve the strength and toughness up to 1.58 GPa and 52 MJ/m3, simultaneously. The other is tailoring ionic coordinating bonding to raise the strength and stiffness, reaching 2.3 and 253 GPa. Modulating various interactions within robust entanglement provides an effective approach to extend performance limits of bioinspired nacre and optimize multiscale interfaces in diverse composites.

Depression, as a common mental illness, has become a significant public health issue, and the recurrence rate for patients with depression who have been treated is relatively high. In this study, a mental health monitoring system based on wearable sensing wristbands with sensors for voice, activity, and heart rate has been developed. Using this system, we perform a therapeutic monitoring study for hospitalized patients with depression and healthy controls to investigate multimodal changes before, during, and after a course of treatment. The obtained results demonstrate that there are significant changes in multimodal features such as audio short-time energy and angular velocity shape skewness with the remission of depressive symptoms. According to Mikels’ emotion wheel, a day’s data for subjects is defined as three types of emotional units and the emotional state of each emotional unit is recognized as positive or negative emotions. With this, emotion-sensing-graphs guided by Mikels’ emotion wheel theory are constructed. The analysis of emotion-sensing-graphs reveals that the same emotions are more closely linked to each other and the average degree and proportion of positive emotion nodes after a course of treatment have increased significantly. Finally, an emotion-sensing-graph graph convolutional network (ESG-GCN) model fused three types of emotion-sensing-graphs with emotion labels has been developed to assess the levels of depression, thereby monitoring the changes in depressive symptoms. Compared with classical machine learning models, the accuracy, F1 score, and recall rate of the model perform best and the model achieves a verification accuracy of 0.83.

A study on CFRP spiral milling was conducted by investigating the material removal mechanism of carbon fibre reinforced polymer/plastic (CFRP) during milling, The milling process of CFRP is simplified as oblique cutting, and a three-dimensional finite element simulation model for microscopic-level oblique cutting is established. The accuracy of the model is validated through experimental verification. It has been discovered that when the fibre-cutting angle is 0°, fibre fracture occurs in bending mode. Compared to orthogonal cutting, CFRP exhibits poorer surface quality under 45° edge angle conditions due to the different support provided by back fibres. The degree of damage on the non-cutting side is more severe than that on the cutting side due to this difference in support role. As the cutting angle increases, damage depth decreases on non-cutting sides while increasing on cuttings sides; however, machining parameters have no effect on fibre fracture.

Point cloud registration is crucial for various applications such as robotics and urban planning, yet it remains challenging due to issues such as noise, variable resolutions, and uncertainties in the initial pose. The normal distribution transform (NDT) algorithm has become a standard approach for registering point scans, but its application to large-scale scenes faces significant challenges due to inherent limitations. These include computational complexity, susceptibility to noise interference, limited adaptability to varying voxel resolutions, and substantial initial pose deviations. To address these issues, we propose the multiscale iterative NDT (MI-NDT) through a meticulously designed multiscale iterative optimization framework. The MI-NDT algorithm voxelizes the reference scan into multiscale voxels based on the optimal flatness ratio criterion. At each scale, the classic NDT algorithm computes the pose of the source scan. The pose obtained from coarse voxels serves as input for the next optimization step on finer voxels. This iterative refinement continues until the finest voxel level, where the resulting pose corresponds to the optimal translation parameters. The experimental results demonstrate the effectiveness of the MI-NDT algorithm in terms of registration accuracy and robustness. Comparative experiments with existing algorithms show significant improvements in accuracy, especially under varying voxel resolutions and noise levels. Moreover, the algorithm exhibits enhanced tolerance to initial pose deviations, enabling successful registration even with poor initial poses.

Artemisia annuais an anti-fever herbal medicine first described in traditional Chinese medicine 1,000 years ago. Artemisinin, the extract of A. annua, and its derivatives (dihydroartemisinin (DHA), artemether, and artesunate) have been used for the treatment of malaria with substantial efficacy. Recently, DHA has also been tested for the treatment of lupus erythematosus, indicating that it may function to balance the immune response in immunocompromised individuals. In the present study, the regulatory effect of artemisinin on the murine immune system was systematically investigated in mice infected with two different protozoan parasites (Toxoplasma gondiiand Plasmodium berghei). Our results revealed that the mouse spleen index significantly increased (spleen enlargement) in the healthy mice after DHA administration primarily due to the generation of an extra number of lymphocytes and CD8+T lymphocytes in both the spleen and circulation. DHA could increase the proportion of T helper cells and CD8+T cells, as well as decrease the number of splenic and circulatory B cells. Further, DHA could reduce the production of proinflammatory cytokines. Our study revealed that apart from their anti-parasitic activity, artemisinin and its derivatives can also actively modulate the immune system to directly benefit the host.

Modern smart TVs often communicate with their remote controls (including the smartphone simulated ones) using multiple wireless channels (e.g., Infrared, Bluetooth, and Wi-Fi). However, this multi-channel remote control communication introduces a new attack surface. An inherent security flaw is that remote controls of most smart TVs are designed to work in a benign environment rather than an adversarial one, and thus wireless communications between a smart TV and its remote controls are not strongly protected. Attackers can leverage such a flaw to abuse the remote control communication and compromise smart TV systems. In this paper, we propose EvilScreen, a novel attack that exploits ill-protected remote control communications to access protected resources of a smart TV or even control the screen. EvilScreen exploits a multi-channel remote control mimicry vulnerability present in today smart TVs. Unlike other attacks, which compromise the TV system by exploiting code vulnerabilities or malicious third-party apps, EvilScreen directly reuses commands of different remote controls, combines them together to circumvent deployed authentication and isolation policies, and finally accesses or controls TV resources remotely. We evaluated eight mainstream smart TVs and found that they are all vulnerable to EvilScreen attacks, including a ${\sf Samsung}$Samsung product adopting the ISO/IEC security specification.

The heterogeneity of CARM1 controls first cell fate bias during early mouse development. However, how this heterogeneity is established is unknown. Here, we show that Carm1mRNA is of a variety of specific exon-skipping splicing (ESS) isoforms in mouse two-cell to four-cell embryos that contribute to CARM1 heterogeneity. Disruption of paraspeckles promotes the ESS of Carm1precursor mRNAs (pre-mRNAs). LincGET, but not Neat1, is required for paraspeckle assembly and inhibits the ESS of Carm1pre-mRNAs in mouse two-cell to four-cell embryos. We further find that LincGETrecruits paraspeckles to the Carm1gene locus through HNRNPU. Interestingly, PCBP1 binds the Carm1pre-mRNAs and promotes its ESS in the absence of LincGET. Finally, we find that the ESS seen in mouse two-cell to four-cell embryos decreases CARM1 protein levels and leads to trophectoderm fate bias. Our findings demonstrate that alternative splicing of CARM1 has an important role in first cell fate determination.

White light-emitting low-dimensional organic-inorganic hybrid lead halide perovskite materials have been considered as candidates for next generation of light sources because of the potential in daily lighting acting as white light emitters or phosphors. However, due to the instability of perovskite materials in water, the underwater application scenario has not been well developed. In this work, we report a method employing an ultraviolet (UV)-polymerizable acrylic monomer to wrap a low dimensional white light emitting perovskite single crystal ([DMEDA]PbBr4) powders in the polymer matrix. We investigate the exciton dynamics in this composite material by transient absorption spectra. More importantly, white light-emitting devices (WLEDs) are manufactured employing this composite material as phosphor excited by UV-LED. Thanks to the protection of the polymer matrix, the stability against the water of this WLED is very good allowing the devices to work underwater for many days. This strategy in this work illustrates a facile way for the application of white light emitting low dimensional perovskite single crystals in WLEDs.

Phase separation inside mammalian cells regulates the formation of the biomolecular condensates that are related to gene expression, signalling, development and disease. However, a large population of endogenous condensates and their candidate phase-separating proteins have yet to be discovered in a quantitative and high-throughput manner. Here we demonstrate that endogenously expressed biomolecular condensates can be identified across a cell’s proteome by sorting proteins across varying oligomeric states. We employ volumetric compression to modulate the concentrations of intracellular proteins and the degree of crowdedness, which are physical regulators of cellular biomolecular condensates. The changes in degree of the partition of proteins into condensates or phase separation led to varying oligomeric states of the proteins, which can be detected by coupling density gradient ultracentrifugation and quantitative mass spectrometry. In total, we identified 1,518 endogenous condensate proteins, of which 538 have not been reported before. Furthermore, we demonstrate that our strategy can identify condensate proteins that respond to specific biological processes.

Motivated by applications in DNA-based storage and communication systems, we study deletion and insertion errors simultaneously in a burst. In particular, we study a type of error named $t$ -deletion- $s$ -insertion-burst ( $(t,s)$ -burst for short) which is a generalization of the (2, 1)-burst error proposed by Schoeny et al. Such an error deletes $t$ consecutive symbols and inserts an arbitrary sequence of length $s$ at the same coordinate. We provide a sphere-packing upper bound on the size of binary codes that can correct a $(t,s)$ -burst error, showing that the redundancy of such codes is at least $\log (n-t+2)+t-1$ . For $t\geq 2s$ , an explicit construction of binary $(t,s)$ -burst correcting codes with redundancy $\log n+(t-s-1)\log \log n+O_{t}(1)$ is given, where $O_{t}(\cdot)$ suppresses factors that depend only on $t$ . Additionally, we construct a binary (3, 1)-burst correcting code with redundancy at most $\log n+9$ , which is optimal up to an additive constant.

The unstable flow phenomenon in injection molding and the resulting flow marks adversely affect the application of polymer products. Therefore, it is important and necessary to study the unstable flow to clarify the generation mechanism of the flow marks. In this work, the development of unstable flow in injection molding of the polypropylene/polyolefin elastomer (PP/POE) blend was investigated through short shot injection molding experiments. The results show that the melt flows stably at the early stage, and then, the flow front of the melt begins to fluctuate along the thickness direction, resulting in the formation of an unstable flow of the melt and periodic concave and convex regions on the surface of short shot samples. The relationship between the generation of flow marks and the development of unstable flow was also clarified, that is, the convex and concave regions formed during the filling process evolve into the cloudy and glossy regions of the flow marks, respectively. Since the melts in different regions experience different shear and thermal histories, the orientation degree of the dispersed phase and the crystal in the cloudy region is higher than that in the glossy region, while the glossy region has a higher crystallinity and lamellar thickness. Ultimately, a more refined unstable flow model for the generation mechanism of flow marks was proposed..

Parenting has a significant impact on adolescent well-being, particularly subjective psychological well-being. This study investigated the relationship between parenting and adolescents’ subjective psychological well-being in fragile families and whether immigration background moderated these associations, using data from the Fragile Families and Child Wellbeing Study (FFCW) Wave 6 (age 15). The main finding of this study showed that parental monitoring, nonviolent discipline, and parent–child closeness were positively associated with adolescents’ subjective psychological well-being. In contrast, harsh parenting and parenting stress were negatively associated with this outcome. Regression models with interactions indicated that immigration background exacerbated the associations of parental monitoring and parenting stress with adolescents’ subjective psychological well-being. These findings indicate that more policy efforts and parenting interventions are needed to strengthen the positive functioning of adolescents in fragile families. It is also recommended that these policies and interventions become more culturally sensitive in response to the unique challenges that immigrant families face.

ABSTRACTAiming at the defects that wireless sensor network is vulnerable to intrusion attacks and affects communication performance, a WSN intrusion detection method based on deep data mining is presented. The network traffic capture tool is used to capture the data stream of the wireless sensor network, and the captured data stream is cleaned and normalized. An improved deep sparse autoencoder is used to extract WSN intrusion features from the normalized data stream. The extracted intrusion features are taken as the initial data of K-means clustering, to optimize the k-means clustering algorithm (KMCA) by genetic algorithm. The reasonable initial center point searched by the genetic algorithm is taken as the input parameter of the improved KMCA. The proposed method can detect internal attacks, external attacks and other intrusion behaviors in wireless sensor networks, and the false detection rate is less than 1%.

In order to selectively oxidize benzyl alcohol, a novel noble metal catalyst based on polymer ionic liquids with a core–shell structure was created. First, polymer ionic liquid microspheres (PILMs) were prepared by free radical polymerization. Second, the in situ adsorption of Au nanoparticles on the surface of PILMs was accomplished, thanks to the strong electrostatic interaction between N atoms and metal ions on the diazole ring of PILMs. Additionally, the introduction of Al(OH)3prevented the aggregation of Au nanoparticles and promoted the catalytic reaction. Finally, the PILM/Au/Al(OH)3catalyst with a core–shell structure was formed. The effectiveness of the PILM/Au/Al(OH)3catalyst was assessed by varying the catalyst’s type, quantity, amount of Au, amount of H2O2, temperature, and reaction time. After five cycles of experiments, the catalyst was effective and reusable. In addition, the potential catalytic mechanism of the catalyst in the oxidation of benzyl alcohol was proposed.

Pectate lyase (PL) holds significant potential for applications in various industries. However, the existing PL was unable to adapt to thermo-alkaline industrial environments. In this work, a PL from Caldicellulosiruptor besciiDSM 6725 (hereafter, CbPelD) was studied to disclose its structural and biochemical properties. CbPelD consisted of a putative signal peptide sequence, a short linker region, and a catalytic domain (PelD-II), along with an exoacting β-fructofuranosidase domain (PelD-I). In molecular dynamics simulation, PelD-II demonstrated significantly higher activity and thermal stability compared to other truncated enzymes of CbPelD. The optimal pH and temperature for PelD-II were 10.0 and 60 °C, respectively, with the specific activity increasing by 164–223% in the presence of Ca2+or Ni2+. The exotype PelD-II exhibited efficient degradation of polygalacturonic acid (PGA) into unsaturated galacturonic acid (uG1), digalacturonic acid (uG2), and trigalacturonic acid (uG3). In the bioscouring assay, PelD-II exhibited a significant increase in the wetted fabric area to 6.072 ± 0.684 cm2, which was about 7.9 times higher than untreated fabric. Scanning electron microscopy further revealed that treatment with PelD-II resulted in a smoother fiber surface, providing direct visual confirmation of the enzyme’s action. These results highlight the potential of PelD-II for applications in the textile industries.

Soil polycyclic aromatic hydrocarbons (PAHs) and cadmium (Cd) pollution poses severe threats to environment security. Previous studies have reported that both nanoparticles and humic acid (HA) have ability to phytoremediate of pyrene/Cd in soil. Here, pot experiments were conducted to investigate the effects of TiO2NPs and humic acid addition on the applicability Hylotelephium spectabileof remediation for pyrene-Cd co-contaminated soil and the corresponding plant growth. The results show that TiO2NPs with HA can mitigate the damage to plant physiology. TiO2NPs-HA is more suitable to be applied on composite soil where Cd pollution is dominant and pyrene pollution is light. Furthermore, the coating of TiO2NPs with HA enhances the availability of Cd and expands root xylem, allowing roots to absorb and accumulate Cd in large quantities finally. This study aims to establish a theoretical foundation for the implementation of sedum plant in remediating soil contaminated with multiple pollutants.

Congenital deficiency or extensive cervical injury leads to female genital tract obstruction and cervical laxity, resulting in infertility or miscarriage. Current clinical approaches could be conducted to restore the continuity of cervix. However, full-thickness and large-scale cervical regeneration with complete structural and functional restoration have not been reported. In this study, we fabricated a double-layered collagen membrane (CM) scaffold based on decellularized extracellular matrix. Each layer was adapted to support the growth of epithelial cells and stromal cells, respectively. Further, the thickness and folded “sandwich” structure were tailored to match the cervical structure. When transplanted into rabbit full-thickness and total ectocervix excision models, only CM scaffold groups enabled the regeneration of neo-ectocervix tissue, including epithelium, stroma and muscular layers after 3 and 6 months. The neo-ectocervix regenerated by CM scaffolds exhibited significantly higher expression of secretory glands and estrogen receptors, more secretion of neutral and acidic mucins, showing functional maturity of regenerated epithelium. Notably, CM scaffolds supported the regeneration of stroma and muscular layers. The mechanical strength of neo ectocervix was comparable to that of normal ectocervix. CM scaffolds demonstrate good biocompatibility, support different cell growth, and enhance superior regeneration of epithelium, stromal and muscular tissue, confirming its construction capacity as new strategies for addressing cervical deficiency and damage.

Coiled-coil domain containing 3 (CCDC3) was previously shown to regulate liver lipid metabolism as a secretory protein. Here, we report an unexpected intracellular role of CCDC3 as a tumor suppressor in breast cancer (BrC). Bioinformatics datasets analysis showed that CCDC3 is under-expressed in BrCs, while its higher levels are correlated with higher overall survival and lower relapse of cancer patients, and CCDC3 is positively correlated with p53 and its target genes. Ectopic CCDC3 markedly suppressed proliferation, colony formation, and xenograft tumor growth by augmenting p53 activity in BrC cells. Depletion of endogenous CCDC3 by CRISPR-Cas9 increased proliferation and drug resistance of BrC cells by alleviating 5-Fluorouracil (5-FU)-induced p53 level and activity. Mechanistically, CCDC3 bound to the C-termini of p53 and MDM2, consequently stabilizing p53 in the nucleus and impairing MDM2 recruitment of p53 to the 26S proteosome without inhibiting p53 ubiquitination. p53 induced CCDC3 expression by binding to its promoter in BrC cells. Our results unveil a unique mechanism underlying CCDC3 activation of p53 in a positive feedback fashion to suppress BrC growth.

Cell models can express a variety of cell information, including mechanical properties, electrical properties, and chemical properties. Through the analysis of these properties, we can fully understand the physiological state of cells. As such, cell modeling has gradually become a topic of great interest, and a number of cell models have been established over the last few decades. In this paper, the development of various cell mechanical models has been systematically reviewed. First, continuum theoretical models, which were established by ignoring cell structures, are summarized, including the cortical membrane droplet model, solid model, power series structure damping model, multiphase model, and finite element model. Next, microstructural models based on the structure and function of cells are summarized, including the tension integration model, porous solid model, hinged cable net model, porous elastic model, energy dissipation model, and muscle model. What’s more, from multiple viewpoints, the strengths and weaknesses of each cell mechanical model have been analyzed in detail. Finally, the potential challenges and applications in the development of cell mechanical models are discussed. This paper contributes to the development of different fields, such as biological cytology, drug therapy, and bio-syncretic robots.

Poly(A)-tail-mediated post-transcriptional regulation of maternal mRNAs is vital in the oocyte-to-embryo transition (OET). Nothing is known about poly(A) tail dynamics during the human OET. Here, we show that poly(A) tail length and internal non-A residues are highly dynamic during the human OET, using poly(A)-inclusive RNA isoform sequencing (PAIso-seq). Unexpectedly, maternal mRNAs undergo global remodeling: after deadenylation or partial degradation into 3ʹ-UTRs, they are re-polyadenylated to produce polyadenylated degradation intermediates, coinciding with massive incorporation of non-A residues, particularly internal long consecutive U residues, into the newly synthesized poly(A) tails. Moreover, TUT4 and TUT7 contribute to the incorporation of these U residues, BTG4-mediated deadenylation produces substrates for maternal mRNA re-polyadenylation, and TENT4A and TENT4B incorporate internal G residues. The maternal mRNA remodeling is further confirmed using PAIso-seq2. Importantly, maternal mRNA remodeling is essential for the first cleavage of human embryos. Together, these findings broaden our understanding of the post-transcriptional regulation of maternal mRNAs during the human OET.

Heart rate is an important physiological indicator of the human body. It can evaluate the activity of the heart and the degree of fatigue. It can be further used to assess emotions by monitoring heart-rate changes and voice recording or breathing. Single-lead or multilead equipment is often used to monitor electrocardiogram (ECG) in medical treatment. However, it brings inconvenience to daily life to record the heart rate from a free-living natural environment. Due to the subject’s voluntary or involuntary movement, it is difficult to collect ideal photoplethysmography (PPG) signal by using wearable device (WD) as it is continually interfered by the motion artifacts (MAs). These MAs seriously affect the calculation and online monitoring of the heart rate. This article proposes a WD with real-time online fusion learning for heart PPG tracking. In particular, it proposes a recursive least-squares algorithm to fuse three-axis acceleration signals to remove MAs from PPG signals. In order to further determine the heart-rate frequency range and select the appropriate spectrum peak, a decision tree spectrum interval estimation method is proposed to provide prior information for PPG signal spectrum tracking, so as to optimize the spectrum peak estimation. The performance of the proposed device, which is an integrated Internet of Things with wearable platform, has been shown to be robust to natural and unpredictable situations. The experimental results have confirmed that the proposed method can adaptively track the PPG signal with high accuracy.

Permutation codes and multi-permutation codes have been widely considered due to their various applications, especially in flash memory. In this paper, we consider permutation codes and multi-permutation codes against a burst of stable deletions. In particular, we propose a construction of permutation codes correcting a burst stable deletion of length $s$ , with redundancy $\log n+ 2\log \log n+O(1{)}$ . Compared to the previous known results, our improvement relies on a different strategy to retrieve the missing symbol on the first row of the array representation of a permutation. We also generalize our constructions for multi-permutations and the variable length burst model. Furthermore, we propose a linear-time encoder with optimal redundancy for single stable deletion correcting permutation codes.

In order to achieve the low-cost position detection of modular permanent magnet synchronous linear motor (MPMSLM), three switching Hall sensors space 120° apart are designed. Two groups of Hall detection board are installed to ensure the position detection is effective throughout the process. The motor speed and electrical angle are extracted from Hall signals using Taylor expansion. In addition, a sliding mode observer (SMO) is designed to estimate the back EMF. Then, the information of SMO and Hall sensors is integrated by vector tracking observer. Eventually, a closed-loop speed control system based on sliding mode vector tracking observer is established. The experiments are carried out on the linear segment of MPMSLM. The results show that the proposed method can estimate motor speed and electrical angle accurately at the full-speed range.

Solid-state nanopores, inspired by biological nanopores, have the advantages of good mechanical properties, stability, and easy modification. They have attracted wide attention in the fields of sequencing, sensing, molecular sieving, nanofluidic devices, nanoelectrochemistry, and energy conversion. Because of the ion/molecule transport characteristic of the pore, the research on solid-state nanopores mainly focuses on the functional modification of its inner wall. In recent years, the outer surface of nanopores has also attracted the attention of researchers, and the functional elements on the outer surface have the functions of anti-interference and ionic signal enhancement. In this perspective, we review research progress of inner wall and outer surface distinguished solid-state nanopores, highlight their processing and advantages, summarize their functions and applications in sensing, and give insight into further research.

Internet of Things (IoT) devices expect a secure communication method or protocol with communication performance that matches the network bandwidth in a public network. With the advancement of network bandwidths, such as through wireless technology 5G, encryption and decryption throughput can be the performance bottleneck of IoT communication security, as IoT devices have limited computing power. As a result, it is a challenge for IoT devices to obtain the required level of security and communication performance. In this article, we improve the encryption and decryption performance with a lightweight cipher algorithm called uBlock for IoT devices. By using sequential circuits, the encryption and decryption throughput can reach the 1 Gb/s level with 90 nm technology in our simulation environment. We can expect a more than two fold improvement in the performance with better nanotechnology from hardware vendors. Our proposed solution can achieve the required level of security and communication performance with a little power consumption.

A Ru/Mo/Mo2C sheet-structured composite electrocatalyst was synthesized through a meticulous methodology involving etching pretreatment, impregnation, and subsequent calcination. This work delves into the intricacies of how the incorporation of Ru and the application of etching pretreatment influence the compositional makeup, morphological characteristics, electronic configuration, and, most notably, the hydrogen evolution reaction (HER) performance of the catalyst within the context of water electrolysis. Specifically, it was observed that the introduction of Ru catalyzed the formation of Mo and Mo2C phases, while the etching pretreatment played a pivotal role in augmenting the specific surface area of the catalyst, thereby facilitating the availability of an enriched landscape of active sites and modifying the electronic coupling between Ru and Mo species. Electrochemical evaluations revealed that the optimized E-Ru/Mo/Mo2C-3 catalyst exhibited remarkable HER kinetics, manifested by a minimal overpotential of 39.7 mV at a benchmark current density of 10 mA cm−2and a favorable Tafel slope of 14.5 mV dec−1in an alkaline medium. This comprehensive investigation offers profound insights into the rational design of metal-organic framework (MOF)-derived electrocatalysts, paving the way for the development of highly efficient HER catalysts tailored for water electrolysis applications.

Ni-Co nano-alloys confined by in-situ formed N-doped porous carbon overlayer have been prepared through chelation of metal cations with citric acid and urea followed by carbonization for hydrodeoxygenation of 5-hydroxymethylfurfural (HMF) into 2, 5-dimethylfuran (DMF). The results indicated that the Ni-Co nano-alloys were formed and homogeneously distributed within the N-doped porous carbon overlayer. The electronic effect of the Ni-Co nano-alloys significantly boosted hydrodeoxygenation activity of the Co2Ni1@NC catalyst and simultaneously inhibited further hydrogenation and opening of furan ring. The N-doped porous carbon overlayer around Ni-Co nano-alloys not only facilitated to disperse and stable Ni-Co nano-alloys through strong metal-support interaction, but also protected the Ni-Co nano-alloys from aggregation. Therefore, the Co2Ni1@NC catalyst offered superior catalytic performance with the HMF conversion of 100 % and DMF selectivity of 93.0 %. Moreover, the Co2Ni1@NC catalyst displayed excellent stability without significant activity loss after five recycles due to the spatial confinement of N-doped carbon overlayer.

The immunomodulatory potential of dihydroartemisinin (DHA) has recently been highlighted; however, the potential mechanism remains to be clarified. Single-cell RNA sequencing was explored in combination with cellular and biochemical approaches to elucidate the immunomodulatory mechanisms of DHA. In this study, we found that DHA induced both spleen enlargement and rearrangement of splenic immune cell subsets in mice. It was revealed that DHA promoted the reversible expansion of effective regulatory T cells and interferon-γ+cytotoxic CD8+T cells in the spleen via induction of superoxide dismutase 3 (SOD3) expression and increased phosphorylation of c-Jun N-terminal kinases (JNK) and its downstream activator protein 1 (AP-1) transcription factors. Further, SOD3 knockout mice were resistant to the regulatory effect of DHA. Thus, DHA, through the activation of the SOD3-JNK-AP-1 axis, beneficially regulated immune cell heterogeneity and splenic immune cell homeostasis to treat autoimmune diseases.

Purpose: Green energy as a transportation supply trend is irreversible. In this paper, a highway energy supply system (HESS) evolution model is proposed to provide highway transportation vehicles and service facilities with a clean electricity supply and form a new model of a source-grid-load-storage-charge synergistic highway-PV-WT integrated system (HPWIS). This paper aims to improve the flexibility index of highways and increase CO2emission reduction of highways. Design/methodology/approach: To maximize the integration potential, a new energy-generation, storage and information-integration station is established with a dynamic master–slave game model. The flexibility index is defined to evaluate the system ability to manage random fluctuations in power generation and load levels. Moreover, CO2emission reduction is also quantified. Finally, the Lianhuo Expressway is taken as an example to calculate emission reduction and flexibility. Findings: The results show that through the application of the scheduling strategy to the HPWIS, the flexibility index of the Lianhuo Expressway increased by 29.17%, promoting a corresponding decrease in CO2emissions. Originality/value: This paper proposed a new model to capture the evolution of the HESS, which provides highway transportation vehicles and service facilities with a clean electricity supply and achieves energy transfer aided by an energy storage system, thus forming a new model of a transportation energy system with source-grid-load-storage-charge synergy. An evaluation method is proposed to improve the air quality index through the coordination of new energy generation and environmental conditions, and dynamic configuration and dispatch are achieved with the master–slave game model.

Three β-diketiminato proligands incorporating a thiophene or tetrahydrofuran heterocyclic group, H2L1, H2L2, and HL3(MeC(NDipp)CHC(Me)N(CH2)n-2-(HCG), HCG = C4H2S, n= 2, L1; n= 1, L2; HCG = C4H7O, n= 1, L3; Dipp = 2,6-iPr2C6H3), have been developed. Unusual N,N,Ctridentate β-diketiminato rare-earth metal monoalkyl complexes L1RE(CH2SiMe3)(thf) (RE = Y (1a), Er (1b), Yb (1c), Lu (1d), thf = tetrahydrofuran) and L2Yb(CH2SiMe3)(thf) (2c) were achieved unexpectedly by the reactions of RE(CH2SiMe3)3(thf)2with H2L1and H2L2, respectively. In this process, the C–H bond activation of the thiophene ring occurred. In sharp contrast, the treatment of RE(CH2SiMe3)3(thf)2with a tetrahydrofuran-functionalized β-diketiminato proligand HL3, under the same conditions, gave five-coordinate N,N,Otridentate β-diketiminato rare-earth metal dialkyl complexes L3RE(CH2SiMe3)2(RE = Y (3a), Er (3b), and Yb (3c)). In addition, their unique catalytic performances have been described. The monoalkyl complexes exhibited high efficiency toward the dimerization of various aldehydes, providing a wide range of carboxylic esters in good to high yields under mild conditions. The dialkyl complexes could promote the head-to-head dimerization of terminal alkynes to afford conjugated 1,4-disubstituted enynes with excellent regio- and stereoselectivity (up to 100% Z-selectivity). More importantly, a rare type of rare-earth metal complexes [{L3RE(μ-C≡CPh)}2(μ-η2:η2-PhCCCCPh)] (RE = Y (6a), Er (6b)) containing two bridging alkynyl groups and a Z-butatrienediyl fragment were isolated and characterized by the reaction of N,N,Otridentate rare-earth metal dialkyls with phenylacetylene, which is unarguably responsible for the outcome of Z-configured enynes during alkyne dimerization.

A novel, efficient and economical process of cyclohexanol (CHOL) production based on cyclohexene esterification–hydrogenation has become a research hotspot in recent years. Wherein, hydrogenation of cyclohexyl acetate (CHA) derived from the esterification of cyclohexene with acetic acid is a crucial step. Combining the advantages of metal complexes and heterogeneous catalysts, the robust Cu(i) coordinated amino-functionalized poly(ionic liquid)s (PILs-Cu(i)) were, in this research, synthesized for use in the mild and highly selective hydrogenation of CHA to CHOL. The results of FT-IR, UV-vis, BET, XPS and SEM-EDS confirmed that the Cu(i) was dominant in the PILs-Cu(i), and was homogeneously and stably coordinated on the amino-functionalized poly(ionic liquid)s. Benefiting from that, the PILs-Cu(i) was endowed with an unprecedented performance in the mild and highly selective hydrogenation of CHA to CHOL. Specifically, 95.6% CHA conversion with 96.6% selectivity of CHOL, and 97.0% selectivity of ethanol was obtained under extremely mild conditions of 80 °C and 2 MPa H2. Furthermore, no significant activity loss was observed over the PILs-Cu(i) after recycling for at least five times, delivering excellent stability and reusability.

Poly(A) tails are added to the 3′ ends of most mRNAs in a non-templated manner and play essential roles in post-transcriptional regulation, including mRNA export, stability and translation. Measuring poly(A) tails is critical for understanding their regulatory roles in almost every aspect of biological and medical studies. Previous methods for analyzing poly(A) tails require large amounts of input RNA (microgram-level total RNA), which limits their application. We recently developed a poly(A) inclusive full-length RNA isoform-sequencing method (PAIso-seq) at single-oocyte-level sensitivity (a single mammalian oocyte contains ~0.5 ng of total RNA) based on PacBio sequencing that enabled accurate measurement of the poly(A) tail length and non-A residues within the body of poly(A) tails along with the full-length cDNA, providing the opportunity to study precious in vivo samples with very limited input material. Here, we describe a detailed protocol for PAIso-seq library preparation from single mouse oocytes or bulk oocyte samples. In addition, we provide a complete bioinformatic pipeline to perform the analysis from the raw data to downstream analysis. The minimum time required is ~14.5 h for PAIso-seq double-stranded cDNA preparation, 2 d for PacBio sequencing in HiFi mode and 8 h for the initial data analysis.

ABSTRACTDendritic cells (DCs) form a sentinel network to induce protective immunity against pathogens or self-tolerance. mRNA stability is an important part of the post-transcriptional regulation (PTR) that controls the maturation and function of DCs. In this review, we summarize the effects of TTP-mediated regulation of mRNA stability in DCs, focusing on DC maturation and antigen presentation, T cell activation and differentiation, immune tolerance and inflammation. We also discuss the potential DC-based immune treatment for HIV+patients through regulation of mRNA stability. This review proposes the regulation of mRNA stability as a novel immune therapy for various inflammatory diseases, such as arthritis and dermatitis.

In order to handle the problem of frequency fluctuations caused by load disturbances in multi-area interconnected power systems, a sliding mode control strategy for hybrid energy storage system has been designed by combining interval observer and disturbance reconstruction technology. The hybrid energy storage system composed of a battery and a super capacitor has been used to improve the performance of load frequency control systems. Using the load frequency control model of the multi-area interconnected power system, the interval observers are designed for each area to get the information about interval bounds of the system state in each area online. Then, the load disturbance in each area is reconstructed online using the estimation information of system state, and a sliding mode controller based on interval disturbance reconstruction is designed for power consumption and storage of the hybrid energy storage system, so as to stabilize the power grid frequency. Simulation results have shown that the proposed control strategy can effectively suppress the frequency and tie-line power fluctuations caused by load disturbances, and ensure the reliability and stability of the power system.