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Urban railway tracks inevitably suffer damage due to the cyclic load of trains, necessitating structural health monitoring (SHM) with the primary purpose of damage detection. Recently, the ultra-weak fiber Bragg grating (UWFBG) monitoring system has been employed for long-term monitoring of urban railway tracks due to its ability to multiplex thousands of sensors on a single optical fiber. The vast amount of data collected imposes the importance of data-driven damage detection methods. Given the lack of labeled damage datasets, unsupervised learning methods are highlighted. This study proposes a damage detection method for urban railway tracks based on an unsupervised deep neural network, referred to as deep convolutional autoencoder (DCAE). The monitored data are first processed to the autocorrelation functions (ACFs) to be aligned across different channels, and then, the multichannel ACFs are used as the inputs of the DCAE model. Finally, the reconstruction error of the DCAE model is employed as the damage index, and field monitoring data are utilized to verify the proposed method. The results show that the proposed damage index is sensitive to track damage, and the precision of damage detection increases with the threshold of reconstruction error, reaching a peak at 1. The method also achieves a maximum F1 score of 0.90.

Directed Acyclic Graph (DAG)-based blockchain represents a paradigm shift from conventional blockchains, which has the potential to drastically improve throughput performance through concurrent storage and executions. In practice, however, existing DAG-based blockchains fail to deliver such promises, often with limited throughput, high conflicts, and security vulnerabilities under dynamic workloads. The root causes are their unawareness of the workload characteristics of different workload sizes and skewed access patterns. In this article, we propose MorphDAG, the first workload-aware DAG-based blockchain that can significantly enhance throughput without compromising security and achieve elastic scaling under realistic workloads. We derive the theoretically optimal degree of storage concurrency to achieve high throughput while retaining system security as the workload size changes, while enabling fine-grained concurrency adjustment that accommodates a Proof-of-Stake (PoS)-based consensus protocol. We develop a dual-mode transaction processing mechanism that effectively resolves the conflicts brought by skewed access. We implement a prototype of MorphDAG and evaluate under real-world workloads. Extensive evaluations demonstrate that MorphDAG improves end-to-end throughput by up to 2.3× and 2.4× over state-of-the-art DAG-based blockchain systems AdaptChain and OHIE, respectively.

• Through the combination of austenite reversion treatment (ART) and subsequent flash austenitizing (FA), nanoscale chemical heterogeneity was successfully introduced into a UHSS prior to the aging process. • The hard martensitic matrix strengthened by high-density dual-nanoprecipitates of Ni(Al,Mn) and (Mo,Cr)2C constrains the plastic deformation of soft retained austenite (RA) with relatively low fraction, and the presence of relatively stable nanoscale RA with adequate Mn and Ni enrichment leads to only a marginal loss in YS but keeps a persistent transformation-induced plasticity (TRIP) effect. • The newly-developed UHSS exhibits an ultrahigh yield strength (YS) of ∼ 1.7 GPa, an ultimate tensile strength (UTS) of ∼1.8 GPa, a large uniform elongation (UE) of ∼8.5 %, and a total elongation (TE) of ∼13. Nanoprecipitates and nanoscale retained austenite (RA) with suitable stability play crucial roles in determining the yield strength (YS) and ductility of ultrahigh strength steels (UHSSs). However, owing to the kinetics incompatibility between nanoprecipitation and austenite reversion, it is highly challenging to simultaneously introduce high-density nanoprecipitates and optimized RA in UHSSs. In this work, through the combination of austenite reversion treatment (ART) and subsequent flash austenitizing (FA), nanoscale chemical heterogeneity was successfully introduced into a low-cost UHSS prior to the aging process. This chemical heterogeneity involved the enrichment of Mn and Ni in the austenite phase. The resulting UHSS exhibited dual-nanoprecipitation of Ni(Al,Mn) and (Mo,Cr) 2 C and nanoscale austenite stabilized via Mn and Ni enrichment. The hard martensitic matrix strengthened by high-density dual-nanoprecipitates constrains the plastic deformation of soft RA with a relatively low fraction of ∼15 %, and the presence of relatively stable nanoscale RA with adequate Mn and Ni enrichment leads to a marginal loss in YS but keeps a persistent transformation-induced plasticity (TRIP) effect. As a result, the newly-developed UHSS exhibits an ultrahigh YS of ∼ 1.7 GPa, an ultimate tensile strength (UTS) of ∼1.8 GPa, a large uniform elongation (UE) of ∼8.5 %, and a total elongation (TE) of ∼13 %. The strategy of presetting chemical heterogeneity to introduce proper metastable phases before aging can be extended to other UHSSs and precipitation-hardened alloys. [Display omitted] [ABSTRACT FROM AUTHOR]

Regional variations in the evolution of the Tibetan Plateau have important implications for our understanding of crustal deformation processes. There have been few studies of the evolution of the NW margin of the plateau and its transition to the Pamir Mountains to the west. We focus on this region with a multi-technique detrital study of two sedimentary sections in the Tarim Basin. Our provenance data show that an appreciable component of the detrital material in the sedimentary sections was derived from the Songpan-Ganzi–Tianshuihai composite terrane, with some contribution from the Karakoram and/or West Qiangtang. Given the proximity of the West Kunlun terrane to the sedimentary sections under study, and its long history of exhumation, this terrane in all likelihood also contributed to the studied successions. Our thermochronological data record phases of exhumation in the hinterland in the Triassic, Early Cretaceous and Oligo-Miocene. Similar to the Pamir Mountains, the Triassic and Oligo-Miocene periods of exhumation are attributed to the Cimmerian and Himalayan orogenies, respectively. The Early Cretaceous signal may reflect the distal effects of the Lhasa–Qiangtang collision. Coevality with deformation in the Pamir Mountains suggests a coupled geodynamic system, with retro-arc deformation associated with Neotethyan subduction in the west and terrane accretion in the east. Supplementary material: Detailed analytical method, sample information, petrographic, geochronological and low-temperature thermochronological data are available at https://doi.org/10.6084/m9.figshare.c.7040686 [ABSTRACT FROM AUTHOR]

Optical pressure sensors have the advantage of being impervious to electromagnetic interference. However, it remains difficult to explore the quantitative relationship between the optical response and the exerted applied pressure. Here, for the first time, the quantitative relationship between the deformation of optical resonator and the applied pressure and the optical response characteristics of the structure are investigated in detail by finite element method, and an ultracompact optical pressure sensor with a high sensitivity ~10.2 nm/MPa is demonstrated. Simulation results show that the maximum deformation of the optical resonator is linearly related to the applied pressure and has a limit value at a fixed input pressure as the range of pressure applied increases. The results also imply that the external force can induce a redshift in the resonance wavelength in addition to generating intriguing phenomena like Fano resonance. These observations contribute to the enhancement and diversification of the optical response within the system. The special features of our suggested structure are applicable in optical property change detection under different pressures, chemical high-pressure experimental measurement, and study of chemical reaction kinetics process.

• Hierarchical porous carbon nanosheets embedded with metallic electrocatalyst nanoparticles were synthesized and applied to the separator modification of lithium-sulfur batteries. • Studying the connection between pore structure and Li-S electrochemical behavior revealed the importance of pore structures in polysulfides phase conversions. • The initial capacity of the cell with Ni-CNS separator is 960.7 mAh g−1 at 1 C, and the capacity remains 760.1 mAh g−1 after 300 cycles, with a capacity retention rate of 79.1% and an average capacity decay of 0.07% per cycle. The practical applications of lithium-sulfur (Li-S) batteries are hampered by the sluggish redox kinetics and polysulfides shuttle in the cyclic process, which leads to a series of problems including the loss of active materials and poor cycling efficiency. In this paper, the pore structures of carbon nanosheets based electrocatalysts were precisely controlled by regulating the content of water-soluble KCl template. The relationship between pore structures and Li-S electrochemical behavior was studied, which demonstrates a key influence of pore structure in polysulfides phase conversions. In the liquid-sloid redox reaction of polysulfides, the micropores and small mesopores (d < 20 nm) exhibited little impact, while the mesopores (d > 20 nm) and macropores played a decisive role. As a typical exhibition, the nickel-embedded carbon nanosheets (Ni-CNS) with a high content of large mesopores and macropores can aid Li-S batteries in exhibiting stable cycling performance (760.1 mAh g−1 at 1 C after 300 cycles) and superior rate capacity (847.8 mAh g−1 at 2 C). Furthermore, even with high sulfur loading (8 mg cm−2) and low electrolyte (E/S is around 6 µL mg−1), the high area capacity of 7.7 mAh cm−2 at 0.05 C could be achieved. This work can provide a guideline for the design of the pore structure of carbon-based electrocatalysts toward high-efficiency sulfur species redox reactions, and afford a general, controllable, and simple approach to constructing high performance Li-S batteries. [Display omitted] [ABSTRACT FROM AUTHOR]

Chinese chestnut (Castanea mollissimaBL.) is a well-known fruit tree that has been cultivated in East Asia for millennia. Leaves and buds of the plant can become seriously infested by the gall wasp Dryocosmus kuriphilus(GWDK), which results in gall formation and associated significant losses in fruit production. Herbivore-induced terpenes have been reported to play an important role in plant–herbivory interactions, and in this study, we show that upon herbivory by GWDK, four terpene-related compounds were significantly induced, while the concentrations of these four compounds in intact buds were relatively low. Among these compounds, (E)-nerolidol and (E, E)-α-farnesene have frequently been reported to be involved in plant herbivory defenses, which suggests direct and/or indirect functions in chestnut GWDK defenses. Candidate terpene synthase (TPS) genes that may account for (E)-nerolidol and (E, E)-α-farnesene terpene biosynthesis were characterized by transcriptomics and phylogenetic approaches, which revealed altered transcript levels for two TPSs: CmAFS, a TPS-g subfamily member, and CmNES/AFS, a TPS-b clade member. Both genes were dramatically upregulated in gene expression upon GWDK infestation. Furthermore, Agrobacterium tumefaciens-mediated transient overexpression in Nicotiana benthamianashowed that CmAFScatalyzed the formation of (E, E)-α-farnesene, while CmNES/AFSshowed dual (E)-nerolidol and (E, E)-α-farnesene synthase activity. Biochemical assays of the recombinant CmAFSand CmNES/AFSproteins confirmed their catalytic activity in vitro, and the enzymatic products were consistent with two of the major volatile compounds released upon GWDK-infested chestnut buds. Subcellular localization demonstrated that CmAFSand CmNES/AFSwere both localized in the cytoplasm, the primary compartment for sesquiterpene synthesis. In summary, we show that two novel sesquiterpene synthase genes CmAFSand CmNES/AFSare inducible by herbivory and can account for the elevated accumulation of (E, E)-α-farnesene and (E)-nerolidol upon GWDK infestation and may be implicated in chestnut defense against GWDK herbivores.

Remote sensing semantic segmentation is considered a key step in the intelligent interpretation of high-resolution remote sensing (HRRS) images, with widespread applications in fields such as hazard assessment, environmental monitoring, and urban planning. Recently, numerous deep learning-based semantic segmentation methods have emerged, achieving significant breakthroughs. However, the majority of current research still concentrates on representation learning in the visual feature space, with the potential of multimodal data sources yet to be fully explored. In recent years, the foundational visual language model, namely contrastive language-image pretraining (CLIP), has established a new paradigm in the visual field, demonstrating excellent generalization capabilities and deep semantic understanding across a variety of tasks. Inspired by prompt learning, we propose a prompting approach based on linguistic descriptions to enable CLIP to generate semantically distinct contextual information for remote sensing images. We introduce the SegCLIP network architecture, a novel framework specifically designed for semantic segmentation of HRRS images. Specifically, we have adapted CLIP to extract text information, thereby guiding the visual model in distinguishing among classes. Additionally, we have designed a cross-modal feature fusion (CFF) module that integrates linguistic and visual semantic features, ensuring semantic consistency across modalities. Finally, we have fully exploited the potential of text data and have used additional real text to refine ambiguous query features. Experimental evaluations confirm that the method exhibits superior performance on the LoveDA, iSAID, and UAVid public semantic segmentation datasets.

EGR4 (Early Growth Response 4) is a member of the EGR family, involving in tumorigenesis. However, the function and action mechanism of EGR4 in the pathogenesis of colorectal cancer (CRC) remain unclear. To address this, we assessed the prognosis of CRC based on EGR4 using the Kaplan-Meier plotter tool and tissue microarray. The abundance of immunoinfiltration was evaluated through ssGSEA, TISIDB, and TIMER. In vitro experiments involving knockdown or overexpression of EGR4 were performed, and RNA-sequencing was conducted to explore potential mechanisms. Furthermore, we used oxaliplatin and 5-fluorouracil to validate the impact of EGR4 on chemo-resistance. Pan-cancer analysis and tissue microarray showed that EGR4 was highly expressed in CRC and significantly correlated with an unfavorable prognosis. Moreover, EGR4 expression was associated with immunoinfiltration and cancer-associated fibroblasts in the CRC microenvironment. Functional enrichment demonstrated that high-expressional EGR4 were involved in chromatin and nucleosome assembly. Additionally, EGR4 promoted the proliferation of CRC cells. Mechanistically, EGR4 upregulated TNFα to activate the NF-κB signaling pathway, and its knockdown reduced p65 nuclear translocation. Importantly, combining shEGR4 with oxaliplatin and 5-fluorouracil significantly inhibited CRC proliferation. Taken together, these findings provide new insights into the potential prognosis and therapeutic targets of EGR4 in CRC.

Satellite communication plays a crucial role in supplementing blind areas and enhancing ubiquitous coverage, to meet the ubiquitous connectivity demands of the future 6G Internet of Things (IoT). As a vital means for integrated space-ground and the intelligent interconnectivity of everything in the future 6G system, Direct-to-Smartphone technology has emerged as a global development hotspot and got widespread attention. This paper analyzes various technical routes and numerous technological challenges of Direct-to-Smartphone technology, and innovatively proposes key technical solutions, such as air interface adapting to high-dynamics, spaceborne ultra-large array multi-beam antennas, on-demand scheduling of extremely narrow beams for random access (RA), and high-integration smartphone design. These solutions support to realize Direct-to-Smartphone technology to adapt the high-dynamic characteristic of Low Earth Orbit (LEO) satellites, provide all-area broadband service, satisfy high-performance and miniaturized. Finally, this paper outlines three potential development directions for Direct-to-Smartphone technology.

BackgroundThe visual outcome of open globe injury (OGI)-no light perception (NLP) eyes is unpredictable traditionally. This study aimed to develop a model to predict the visual outcomes of vitrectomy surgery in OGI-NLP eyes using a machine learning algorithm and to provide an interpretable system for the prediction results.MethodsClinical data of 459 OGI-NLP eyes were retrospectively collected from 19 medical centres across China to establish a training data set for developing a model, called ‘VisionGo’, which can predict the visual outcome of the patients involved and compare with the Ocular Trauma Score (OTS). Another 72 cases were retrospectively collected and used for human–machine comparison, and an additional 27 cases were prospectively collected for real-world validation of the model. The SHapley Additive exPlanations method was applied to analyse feature contribution to the model. An online platform was built for real-world application.ResultsThe area under the receiver operating characteristic curve (AUC) of VisionGo was 0.75 and 0.90 in previtrectomy and intravitrectomy application scenarios, which was much higher than the OTS (AUC=0.49). VisionGo showed better performance than ophthalmologists in both previtrectomy and intravitrectomy application scenarios (AUC=0.73 vs 0.57 and 0.87 vs 0.64). In real-world validation, VisionGo achieved an AUC of 0.60 and 0.91 in previtrectomy and intravitrectomy application scenarios. Feature contribution analysis indicated that wound length-related indicators, vitreous status and retina-related indicators contributed highly to visual outcomes.ConclusionsVisionGo has achieved an accurate and reliable prediction in visual outcome after vitrectomy for OGI-NLP eyes.

Cooperative positioning with multiple low earth orbit (LEO) satellites is promising in providing location-based services and enhancing satellite-terrestrial communication. However, positioning accuracy is greatly affected by inter-beam interference and satellite-terrestrial topology geometry. To select the best combination of satellites from visible ones and suppress inter-beam interference, this paper explores the utilization of flexible beam scheduling and beamforming of multi-beam LEO satellites that can adjust beam directions toward the same earth-fixed cell to send positioning signals simultaneously. By leveraging Cramér-Rao lower bound (CRLB) to characterize user Time Difference of Arrival (TDOA) positioning accuracy, the concerned problem is formulated, aiming at optimizing user positioning accuracy under beam scheduling and beam transmission power constraints. To deal with the mixed-integer-nonconvex problem, we decompose it into an inner beamforming design problem and an outer beam scheduling problem. For the former, we first prove the monotonic relationship between user positioning accuracy and its perceived signal-to-interference-plus-noise ratio (SINR) to reformulate the problem, and then semidefinite relaxation (SDR) is adopted for beamforming design. For the outer problem, a heuristic low-complexity beam scheduling scheme is proposed, whose core idea is to schedule users with lower channel correlation to mitigate inter-beam interference while seeking a proper satellite-terrestrial topology geometry. Simulation results verify the superior positioning performance of our proposed positioning-oriented beamforming and beam scheduling scheme, and it is shown that average user positioning accuracy is improved by 17.1% and 55.9% when the beam transmission power is 20 dBw, compared to conventional beamforming and beam scheduling schemes, respectively.

In recent years, recommender systems are crucially important for the delivery of personalized services that satisfy users’ preferences. With personalized recommendation services, users can enjoy a variety of recommendations such as movies, books, ads, restaurants, and more. Despite the great benefits, personalized recommendations typically require the collection of personal data for user modelling and analysis, which can make users susceptible to attribute inference attacks. Specifically, the vulnerability of existing centralized recommenders under attribute inference attacks leaves malicious attackers a backdoor to infer users’ private attributes, as the systems remember information of their training data (i.e., interaction data and side information). An emerging practice is to implement recommender systems in the federated setting, which enables all user devices to collaboratively learn a shared global recommender while keeping all the training data on device. However, the privacy issues in federated recommender systems have been rarely explored. In this paper, we first design a novel attribute inference attacker to perform a comprehensive privacy analysis of the GCN-based federated recommender models. The experimental results show that the vulnerability of each model component against attribute inference attack is varied, highlighting the need for new defense approaches. Therefore, we propose a novel adaptive privacy-preserving approach to protect users’ sensitive data in the presence of attribute inference attacks and meanwhile maximize the recommendation accuracy. Extensive experimental results on two real-world datasets validate the superior performance of our model on both recommendation effectiveness and resistance to inference attacks.

This article studies the short-circuit (SC) failure modes and mechanism of ohmic-gate GaN high electron mobility transistors (HEMTs) through experimental evaluation and numerical investigation. Two distinct SC failure modes of ohmic-gate GaN HEMT have been identified: gate–source SC failure and rapid thermal runaway failure. The SC capability and failure mode of ohmic-gate GaN HEMT are significantly influenced by both the dc bus voltage and gate injection current. Thermal–mechanical simulation and failure analysis techniques are used to identify two SC failure mechanisms: thermal–mechanical stress-induced structural failure and thermal breakdown of the gate GaN/AlGaN heterostructure. The gate injection current is found to be a crucial factor in improving the SC ruggedness of ohmic-gate GaN HEMT under high bus voltage SC conditions.

In most blockchain-based application scenarios, a complete application logic consists of multiple continuous transactions, in which the initiation of one transaction depends on the confirmation result of the previous one. This mandates that continuous transactions must be processed in the correct order. Unfortunately, existing chain-based blockchains fail to effectively support continuous transaction processing due to considerable latency in confirming continuous transactions. Recent studies shifted from chain-based blockchains to Directed Acyclic Graph (DAG) based blockchains, which reduced transaction confirmation latencies. However, DAG-based blockchains store transactions in an out-of-order manner that leads to unordered transaction processing. To address this challenge, we propose FLUID, a new DAG-based blockchain that supports continuous transaction processing while delivering high performance. The fundamental idea of FLUID is to design a transaction dependency tracking structure to ensure that continuous transactions can be processed in the correct order. FLUID utilizes a conflict resolution mechanism to provide instant confirmation and to support concurrent transaction processing with lower latencies. In addition, FLUID builds a checkpoint-based verification mechanism to achieve deterministic consensus on transaction processing results in the DAG. Extensive experiments demonstrate that our proposed FLUID can improve the throughput over state-of-the-art OHIE by 66% with two orders of magnitude lower latencies.

Tetracycline is a typical antibiotic commonly used in various industries which is eco-toxic and quickly causes bacterial resistance. Therefore, studying the efficient removal of tetracycline is necessary to protect the water environment. Herein, a novel Ce/Fe nanoparticle composite (1CCFO) was prepared by the sol–gel method and its removal effects of tetracycline under visible light were performed. The relationship between physicochemical properties of catalyst and photocatalytic degradation effects of tetracycline was analyzed based on a series of characterizations data such as X-ray diffraction (XRD), Raman spectroscopy, a vibrating sample magnetometer (VSM), scanning electron microscopy (SEM), Brunauer–Emmett–Teller (BET) method, X-ray photoelectron spectroscopy (XPS), and ultraviolet–visible (UV–Vis) spectroscopy. The results show that Ce/Fe photocatalyst possesses a large specific surface area, good visible light response, abundant oxygen vacancies and excellent redox performance, exhibiting good adsorption capacity, remarkable catalytic performance and stability. The optimal conditions for tetracycline removal were explored through orthogonal experiments. About 88% of tetracycline can be photodegraded in 1 h under optimal conditions. The possible decomposition pathways, main reactive oxygen species and suitable mechanism of the photocatalytic system were studied by liquid chromatography-mass spectrometry (LC-MS), an electron spin resonance (ESR) spectrometer and free radical quenching experiments. The results show that 1CCFO has an efficient degradation effect on tetracycline under visible light, which provides a feasible method to improve the performance of 1CCFO.

This article investigates the problem of the searches and time for stars identification, in which star magnitude, position noise, missing, or false star are considered. A novel star catalog based on angular distance, approximate longitude, and triangulation network is developed, which can accelerate the matching. The preliminary selection of stars is completed by magnitude and projection model. The final star catalog is constructed by Delaunay triangulation, magnitude, and angular distance. A longitude approximation model is proposed by star sensor visual axis and distance of the star on the image. The simulation results show that the proposed algorithm has anti-interference ability to the false star, missing star, and position noise. In addition, a semi-physical simulation experiment of trajectory rocket launch is created to demonstrate the effectiveness of the proposed matching method. Experimental results show that a single matching requires on average 2.1 searches, and the matching efficiency of the proposed method can be greatly improved compared with the existing algorithm.

The junction temperature is vital for the reliability evaluation and health management in silicon carbide (SiC) MOSFET applications. This article proposes a novel method to estimate the junction temperature under actual operating conditions, using the drain voltage falling edge time ( ${t_{f,\text {edge}}}$ ) as temperature-sensitive electrical parameters (TSEPs). Experimental results show that the proposed circuit can estimate the junction temperature with good linearity, high-temperature sensitivity, and load current independence. Furthermore, the proposed method is verified with the aged SiC MOSFET after the power cycling test. It shows a tiny impact of the bond wire degradation on the junction temperature estimation accuracy.

Obtaining cemented carbides with smaller WC grain size and better properties is key to their wider application. Ultrafine cemented carbides were prepared by using spark plasma sintering (SPS) with nano VC-Cr3C2as nanocomposite grain growth inhibitors (NGGIs) and multi-walled carbon nanotubes (MWCNTs) as reinforcing materials. The effects of NGGIs and MWCNTs on the microstructure and mechanical properties of alloys were evaluated. The results indicated that the specimens (0.5 wt % NGGIs and 0.4 wt % MWCNTs) prepared at 1350 °C for 8 min under a pressure of 50 MPa have enhanced mechanical properties (HV2520.85 kgf/mm2, KIC13.26 MPa m1/2) and a homogeneous microstructure. The grain size of WC is suppressed (the average grain size is 200–400 nm). NGGIs can prevent the dissolution of W and C in liquid Co, thereby inhibiting the growth of WC grains. The uniform dispersion of MWCNTs in WC matrix mobilizes their fiber-reinforcement effect. The combination of NGGIs, MWCNTs, and SPS can improve the mechanical properties and optimize the microstructure of the alloy.

Membrane fouling is a serious concern in cold-rolling wastewater treatment using electrodialysis (ED). In this study, a commonly used anion exchange membrane was selected, and the evolution of fouling behavior was evaluated by contact angle, atomic force microscope (AFM), scanning electron microscope-energy-dispersive X-ray spectrometer (SEM-EDS), X-ray photoelectron spectroscopy (XPS) and attenuated total refraction-Fourier transform infrared (ATR-FTIR). Furthermore, mechanism of hybrid pollution by organic and inorganic contaminants was presented. Representative regeneration methods were carried out to investigate the removal of pollutants. The results showed that compared with the uncontaminated ED, the electrical resistance of desalination compartment increased by 5.49% and 10.42% after 48 and 96 h contamination, respectively. Meanwhile, Cl–recovery rate decreased from 64.33% ± 0.02% (uncontaminated membrane) to 58.58% ± 0.10% (contaminated for 48 h) and 55.32% ± 0.52% (contaminated for 96 h). Results from SEM-EDS, AFM, XPS and FTIR revealed that the interaction between organic (dichloromethane, dichloroacetaldehyde, chloromethylsulfonyl chloride) and inorganic fouling (Fe2+) was the central factor in exacerbating membrane fouling, which resulted in more complicated fouling scenarios. It is recommended to remove chemical oxygen demand from membrane surface with 0.1% NaOH followed by 0.025% Na-SDS every 96 h to restore the permeability.

In view of the serious adverse reactions and clinical toxicity of first line therapy 5-fluorouracil and lack of small molecule therapeutics in colorectal cancer chemotherapy, a series of natural scaffold-based 3-arylindanone derivatives (9a–q) were designed, synthesized and evaluated as tubulin polymerization inhibitors targeting the colchicine site. The most potent colchicine binding site inhibitor (CBSI), (R)-9k, exhibited 14–38 times more dominant anti-proliferative activity against three colon cancer cell lines than 5-fluorouracil. Particularly, (R)-9kshowed higher selectivity against human normal cells compared with 5-fluorouracil and colchicine, and displayed negligible cardiotoxicity through hERG assessment. Furthermore, the binding of (R)-9kto the colchicine site was strongly supported by EBI competition assay and (R)-9kinhibited more tubulin polymerization than colchicine. Besides, the mechanism of action and binding modes of (R)-9kwere verified by molecular dynamics simulations and docking. Therefore, (R)-9kcould be regarded as a promising CBSI for colorectal cancer therapy.

Traditional evolutionary biology research mainly relies on sequence information to infer evolutionary relationships between genes or proteins. In contrast, protein structural information has long been overlooked, although structures are more conserved and closely linked to the functions than the sequences. To address this gap, we conducted a proteome-wide structural analysis using experimental and computed protein structures for organisms from the three distinct domains, including Homo sapiens(eukarya), Escherichia coli(bacteria), and Methanocaldococcus jannaschii(archaea). We reveal the distribution of structural similarity and sequence identity at the genomic level and characterize the twilight zone, where signals obtained from sequence alignment are blurred and evolutionary relationships cannot be inferred unambiguously. We find that structurally similar homologous protein pairs in the twilight zone account for ∼0.004%–0.021% of all possible protein pair combinations, which translates to ∼8%–32% of the protein-coding genes, depending on the species under comparison. In addition, by comparing the structural homologs, we show that human proteins involved in the energy supply are more similar to their E. colihomologs, whereas proteins relating to the central dogma are more similar to their M. jannaschiihomologs. We also identify a bacterial GPCR homolog in the E. coliproteome that displays distinctive domain architecture. Our results shed light on the characteristics of the twilight zone and the origin of different pathways from a protein structure perspective, highlighting an exciting new frontier in evolutionary biology.

Exhaust gas recirculation control (EGRC), an inlet air heating technology, can be utilized in combination with inlet/variable guide vane control (IGV/VGVC) and fuel flow control (FFC) to regulate the load, thereby effectively improving the part-load (i.e., off-design) performance of the gas turbine combined cycle (GTCC). In this study, the E-, F-, and H-Class EGR-GTCC design and off-design system models were established and validated to perform a comparative analysis of the part-load performance under the EGR-IGV-FFC and conventional IGV-FFC strategies in the E/F/H-Class GTCC. Results show that EGR-IGV-FFC has considerable potential for the part-load performance enhancement and can show a higher combined cycle efficiency than IGV-FFC in the E-, F-, and H-Class GTCCs. However, the part-load performance improvement in the corresponding GTCC was weakened for the higher class of the gas turbine because of the narrower load range of EGR action and the deterioration of the gas turbine performance. Furthermore, EGR-IGV-FFC was inferior to IGV-FFC in improving the performance at loads below 50% for the H-Class GTCC. The results obtained in this paper could help guide the application of EGR-IGV-FFC to enhance the part-load performance of various classes of GTCC systems.

Poor soil has become a serious global problem, threatening soil health and food security. Although returning sludge to soil in the form of coal char is an ideal method for soil improvement, the improvement of soil physical and chemical properties by different co-pyrolysis materials is not clear. We selected three co-pyrolysis species and sludge to prepare biochar, and studied their effects on soil improvement. The influences of different sludge-based biochar FeCl3(BC1), Na2SiO3(BC2), and Ca(H2PO4)2(BC3) on soil pH, cation exchange capacity (CEC), ammonium nitrogen, effective phosphorus, organic carbon, and the growth of Brassica chinensis Lthrough a pot experiment with three parallel were investigated. The results showed that all sludge-based biochar were beneficial to the growth of Brassica chinensis Land did not exceed the heavy metal standard in the soil (GB 1618-2018, Chinese Standard). In addition, the above-ground parts of Brassica chinensis Lmet the requirements of food safety (GB 2762-2017, Chinese Standard). BC3 was the most effective in increasing soil ammonium nitrogen, effective phosphorus, and organic carbon by 29.81%, 229.41%, and 25.12%, respectively. BC3 also increased plant yield and chlorophyll content by 54.5% and 27.9%, respectively. In addition, BC3 inhibited the migration of heavy metals to the above-ground and reduced the overall contamination level of heavy metals from 0.8467 to 0.3277. The human health risk assessment showed that the target hazard quotient (THQ) and total target hazard quotient (TTHQ) values were less than 1, indicating that the health risks associated with the consumption of Brassica chinensis L(heavy metal intake) were negligible.

Supercritical water gasification of waste hydrofluorocarbon refrigerants was an effective treatment technology, but there is a problem of high yield of fluorine-containing products with complex types. Plastic has the potential to provide sufficient H atoms as hydrogen donor to facilitate defluorination of fluorine-containing products. In this study, ReaxFF reactive molecular dynamic simulation and density functional theory calculation were used to investigate the supercritical water co-gasification (SCWCG) mechanism of R134a and low-density polyethylene (LDPE). The results showed that the decomposition of LDPE was the initial reaction of SCWCG, the generated radicals promoted the dissociation of R134a and H2O. The dominant SCWCG products were valuable hydrocarbons, H2, CO and HF. The present of LDPE promoted the defluorination reaction of fluorine-containing products from the dissociation of R134a, reduced the yield of fluorine-containing products, and greatly promoted the yields of H2, HF, CO and hydrocarbon products. 99 % of F atoms in R134a can be converted to HF, which indicated that plastics participating in supercritical water gasification of R134a has excellent defluorination effect. This study provided an efficient and potential route to conduct waste HFC refrigerants into valuable chemicals and fuels.

Background: SLC10A3, a gene upregulated in pan-cancer, lacks full understanding regarding its prognostic implications and association with immune infiltration in colorectal cancer (CRC). This study comprehensively analyzed SLC10A3 in CRC, evaluating its prognostic significance and influence on the tumor's immune microenvironment. Methods: Transcriptomic data from TCGA were obtained to compare SLC10A3 expression in both colorectal cancer (CRC) and normal tissues. Prognostic value was assessed for overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). DNA methylation patterns of SLC10A3 and correlation with DNA mismatch repair (MMR) were explored. Genetic alterations in SLC10A3 were scrutinized. The study also delved into the influence of SLC10A3 on the immune microenvironment of CRC, including immune cell infiltration and chemokines. Involvement of cancer-associated fibroblasts (CAFs) was explored. Methylation status of specific CpG islands in the SLC10A3 gene correlated with CRC patient prognosis. CRC tissue microarray was performed to verify the expression of SLC10A3 and its relationship with prognosis. Results: The research revealed that SLC10A3 is significantly upregulated in CRC and holds promise as a potential diagnostic marker. Elevated SLC10A3 expression was linked to poorer OS, DSS, and PFI. Methylation patterns of SLC10A3 displayed prognostic relevance, and genetic alterations in the gene were identified. SLC10A3 was shown to impact the immune microenvironment, with significant correlations observed between its expression and various immune cell types, chemokines, and markers associated with CAFs. Furthermore, an inverse relationship between SLC10A3 and MMR molecules was established. Methylation status of specific CpG islands within the SLC10A3 gene was associated with CRC patient prognosis. Tissue microarray showed that SLC10A3 was highly expressed in CRC and significantly correlated with poor prognosis. Conclusion: The study underscores the importance of elevated SLC10A3 in CRC, associating it with decreased survival and immune infiltration, proposing it as a diagnostic biomarker and appealing immunotherapy target, given its significant overexpression and influence on the immune microenvironment and prognosis through methylation patterns. Graphical Abstract:

A central issue in ecology is understanding what determines biodiversity in nature, particularly in biotic resource systems that typically lack cross-feeding. In this study, we demonstrate that by incorporating pairwise encounters among individuals of the same consumer species, a diverse array of consumer species can self-organize to coexist in a well-mixed system with one or a few biotic resource species. The coexistence modes may manifest as either stable steady states or self-organized oscillations. Notably, all coexistence states are robust to stochasticity, as confirmed by both stochastic simulation algorithms and individual-based modeling. Our model quantitatively illustrates species distribution patterns in various ecological communities and can be broadly used to explain biodiversity in many biotic resource systems. • Pairwise encounters enable breaking of competitive exclusion and foster biodiversity. • Species may self-organize to coexist in stable steady states or through oscillations. • Both self-organized coexistence modes are robust to stochasticity. • Our model explains species distribution patterns across diverse communities. [ABSTRACT FROM AUTHOR]

This paper investigates the practical predefined-time attitude cooperation control problem for a group of rigid spacecraft under an undirected communication graph. First, since the leader is accessible to only a subset of the group members, a distributed practical predefined-time state observer is proposed to estimate the leader's states by using a time-varying scaling function. Second, a distributed practical predefined-time attitude coordination controller is designed to guarantee that the attitude tracking errors of all follower spacecraft converge to the neighborhood of the origin within a preset time. Finally, the effectiveness of the proposed control law is demonstrated by illustrative numerical examples. [ABSTRACT FROM AUTHOR]

Graphical abstract: The latest inspiring progress of hollow-structured electromagnetic wave absorbers and their hybrids are summarized in detail including their merits, fabrication process, and absorption mechanisms.

Graphical abstract:

The nitrogen reduction reaction (NRR) using new and efficient electrocatalysts is a promising alternative to the traditional Haber-Bosch process. Nevertheless, it remains a challenge to design efficient catalysts with improved catalytic performance. Herein, various O-functional MXenes were investigated as NRR catalysts by a combination of density functional theory calculations and least absolute shrinkage and selection operator (LASSO) regression. Nb3C2OXhas been regarded as a promising catalyst for the NRR because of its stability, activity, and selectivity. The potential-determining step is *NH2hydrogenation to *NH3with a limiting potential of –0.45 V. Furthermore, viaLASSO regression, the descriptors and equations fitting the relationship between the properties of O-functional MXenes and NRR activity have been proposed. This work not only provides a rational design strategy for catalysts but also provides machine learning data for further investigation.

Background Death-associated protein kinase (DAPK) has a strong function of tumor suppression involving apoptosis regulation, autophagy, and metastasis inhibition. Hypermethylation of CpG islands in DAPK gene promoter region is one of the important ways to inactivate this tumor suppressor gene, which might promote lung carcinogenesis. However, the clinicopathological significance of the DAPK promoter hypermethylation in lung cancer remains unclear. In this study, we performed a meta-analysis trying to estimate the clinicopathological significance of DAPK promoter hypermethylation in non-small cell lung cancer (NSCLC).Methods A detailed literature search for publications relevant to DAPK gene promoter methylation and NSCLC was made in PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, CSTJ, Wanfang databases, and SinoMed (CBM). The random-effects model and fixed-effects model were utilized to pool the relative ratio based on the heterogeneity test in the meta-analysis.Results A total of 41 studies with 3348 patients were included. The frequency of DAPK methylation was significantly higher in NSCLC than in non-malignant control (odds ratio (OR) = 6.88, 95% confidence interval (CI):  4.17–11.35, P< 0.00001). The pooled results also showed that DAPK gene promoter hypermethylation was significantly associated with poor prognosis for overall survival in patients with NSCLC (hazard ratio: 1.23, 95% CI:1.01–1.52, P= 0.04). Moreover, DAPK gene promoter hypermethylation was significantly associated with squamous cell carcinoma (OR: 1.25, 95% CI: 1.01–1.54, P= 0.04) and smoking behavior (OR: 1.42, 95% CI: 1.04–1.93, P= 0.03) but not with TNM stage, tumor differentiation, age, or gender.Conclusion DAPK promoter hypermethylation might be a candidate diagnostic and prognostic tumor marker for NSCLC.

A Maxwellian display presents always-focused images to the viewer, alleviating the vergence-accommodation conflict (VAC) in near-eye displays (NEDs). Recently, many methods of improving its limited eyebox have been proposed, among which viewpoint replication has attracted a lot of attention. However, double-image, blind-area, and image-shift effects always happen in typical eyebox-replication Maxwellian NEDs when the eye moves between the replicated viewpoints, which prevents these NEDs from being applied more widely. In this Letter, we propose a method for designing a holographic Maxwellian NED system with continuous eyebox replication as well as flexible interval adjustment by changing the projection angles of the reconstructed images. Thus, holograms corresponding to the positions of different viewpoints are calculated to match the interval of the replicated viewpoints with the human pupil diameter, making it possible to eliminate or alleviate double-image or blind-area effects. Also, seamless viewpoint conversion in the eyebox is achieved by aligning the images of adjacent viewpoints on the retina via hologram pre-processing independently. These effects are verified successfully in optical experiments and have the potential to be applied in near-eye three-dimensional displays without VAC.

A simple and highly efficient porous composite viaa solvent evaporation method using g-C3N4and NiSO4was developed. It can super rapidly remove multiple organic dyes from water including rhodamine B (RhB), indigo carmine (IC), methylene blue (MB) and Congo red (CR) at room temperature and under sunlight. The optimal composite 50%NiCN was obtained by an orthogonal experiment, and it exhibited high removal ability towards the above four organic dyes up to 99.9% within 1 minute, even 96.9% in 2 seconds. The good stability of such a composite has been confirmed after five cycles and its possible degradation pathway was discussed. The dynamics of the photocatalytic degradation reaction were explored based on the structure of the organic dyes and the morphology of the photocatalyst by DFT calculations. In addition, simulation of the interactions between sunlight and the composite was performed by the field-only surface integral method. These two theoretical studies supply the reasonable explanation for this photocatalytic function in depth.

Background: Management of secondary glaucoma in nanophthalmos has always been challenging, especially for patients with extremely short axial length and extensive angle synechia. This case report discusses a nanophthalmic patient with secondary glaucoma and extensive angle synechia.Case presentation: A 60-year-old woman was referred to our hospital with uncontrolled intraocular pressure (IOP) in her left eye (LE). Slitlamp examination revealed small cornea and shallow anterior chamber (AC) in both eyes. Extensive angle synechia was seen on gonioscopy, and the IOP and axial length were 36 mmHg/15.79 mm in the left eye. She was diagnosed with nanophthalmos and secondary angle-closure glaucoma LE. Laser peripheral iridectomy (LPI) was performed, but the IOP LE remained elevated and uncontrolled on brinzolamide and brimonidine. The IOP LE was then normalized with the application of 2% pilocarpine. During the follow-up period, the AC of the LE showed progressive shallowing, and 5 months post LPI the IOP became uncontrollable. Goniosynechialysis combined with phacoemulsification, lamellar sclerectomy, sclerostomy, peripheral iridectomy, capsulotomy, and anterior vitrectomy were performed LE. Immediately after surgery, the AC deepened and the IOP stabilized. However, the IOP rose again post-surgically at 1 week and again at 2 months. A generally shallow AC and obstructed capsule hole were present. YAG laser capsulotomy was performed, and the IOP normalized and the AC deepened. Eighteen months after surgery, the IOP LE was 12 mmHg and the AC remained stable.Conclusion: Goniosynechialysis combined with multiple surgical procedures could be considered an alternative treatment regimen for nanophthalmos patients with secondary glaucoma and extensive angle synechia.

Human hippocampal volume has been separately associated with single nucleotide polymorphisms (SNPs), DNA methylation and gene expression, but their causal relationships remain largely unknown. Here, we aimed at identifying the causal relationships of SNPs, DNA methylation, and gene expression that are associated with hippocampal volume by integrating cross-omics analyses with genome editing, overexpression and causality inference. Based on structural neuroimaging data and blood-derived genome, transcriptome and methylome data, we prioritized a possibly causal association across multiple molecular phenotypes: rs1053218 mutation leads to cg26741686 hypermethylation, thus leads to overactivation of the associated ANKRD37gene expression in blood, a gene involving hypoxia, which may result in the reduction of human hippocampal volume. The possibly causal relationships from rs1053218 to cg26741686 methylation to ANKRD37expression obtained from peripheral blood were replicated in human hippocampal tissue. To confirm causality, we performed CRISPR-based genome and epigenome-editing of rs1053218 homologous alleles and cg26741686 methylation in mouse neural stem cell differentiation models, and overexpressed ANKRD37in mouse hippocampus. These in-vitro and in-vivo experiments confirmed that rs1053218 mutation caused cg26741686 hypermethylation and ANKRD37overexpression, and cg26741686 hypermethylation favored ANKRD37overexpression, and ANKRD37overexpression reduced hippocampal volume. The pairwise relationships of rs1053218 with hippocampal volume, rs1053218 with cg26741686 methylation, cg26741686 methylation with ANKRD37expression, and ANKRD37expression with hippocampal volume could be replicated in an independent healthy young (n= 443) dataset and observed in elderly people (n= 194), and were more significant in patients with late-onset Alzheimer’s disease (n= 76). This study revealed a novel causal molecular association mechanism of ANKRD37with human hippocampal volume, which may facilitate the design of prevention and treatment strategies for hippocampal impairment.

Graphical abstract: Incorporation of hydrothermally synthesized ZnO-RGO nanocomposites into waterborne epoxy coating significantly enhanced the corrosion resistance of the coatings for metal protection.

Photocatalytic production of hydrogen peroxide (H2O2) has received great attention as a promising route for sustainable solar fuel. In this work, we demonstrate that quantum dots (QDs) can be explored as a useful photocatalyst for high-efficiency photocatalytic production of H2O2under visible-light with a record-high concentration of 126 mmol L−1. By band structure and wavefunction engineering, QDs exhibit an enhanced stability in an oxidized and humid environment. An oil/water two-phase system is designed to realize spontaneous separation of the H2O2formed to the aqueous phase and of the organic by-products formed to the oil phase. By electron paramagnetic resonance (EPR) measurements, O2−radicals are generated from QDs in the oil phase and transferred to the water phase immediately. The results in this work show that QDs with a rational surface and structure design can serve as an outstanding photocatalyst for the production of H2O2under visible-light.

Gas turbines are increasingly and widely used, whose research and production reflect a country’s industrial capacity and level. Due to the changeable working environment, gas turbines usually work under the condition of simultaneous changes of ambient temperature, load and fuel. However, the current researches mainly focus on the change in single condition, and do not fully consider the simultaneous change in different conditions. On the basis of single condition, this paper further studies the dual off-design performance of gas turbines under three conditions: temperature-load, fuel-load and fuel-temperature. Firstly, the whole machine model of a gas turbine is established, in which the compressor model has the greatest impact on the performance of gas turbines. Therefore, this paper obtains a more accurate compressor model by combining the engineering modeling advantages of gPROMs and the powerful mathematical calculation ability of MATLAB neural network. Then, according to the established gas turbine model, the dual off-design performance is studied, which is mainly based on the parameter of output and efficiency. The result shows that the efficiency and power output of gas turbines will decrease with the increase of ambient temperature. With the decrease of fuel calorific value, power output and efficiency will increase. As the load decreases, the efficiency of the gas turbines will decrease, and these changes are consistent with the single off-design performance. However, when the fuel and temperature change simultaneously, only adjusting the IGV angle cannot avoid the surge when the temperature is above 30°C. At this time, it is necessary to adjust the extraction rate in order to ensure the safe and stable operation of gas turbines. Therefore, the research on dual off-design performance of gas turbines has an important significance for the peak shaving operation of gas turbines.

Trace water can trigger photocatalytic hydrogen peroxide production with a record-high concentration of 113 mmol/L in water and ethanol system. Trace water provides and transfers indispensable free protons to consume hydroperoxyl radicals in the system.

Using chaotic system for image encryption is a feasible and popular research interest. In this paper, a compound Sine-Piecewise Linear Chaotic Map is proposed to improve the chaotic characteristics of the original chaotic map. Compared with the original chaotic system, the proposed compound chaotic system has better dynamics performances, larger parameter space, which is more suitable for cryptographic applications. Furthermore, an image encryption algorithm based on this chaotic model and varying DNA coding is proposed. In this encryption algorithm, a novel method is provided to convert decimal numbers to binary numbers. Several numerical experiments show that the proposed encryption algorithm has good security performances, and is competitive with other chaos-based image encryption algorithms. [ABSTRACT FROM AUTHOR]

The erythropoietin receptor (EpoR) has traditionally been thought of as an erythroid-specific gene. Notably, accumulating evidence suggests that EpoR is expressed well beyond erythroid cells. However, the expression of EpoR in non-erythroid cells has been controversial. In this study, we generated EpoR-tdTomato-Cre mice and used them to examine the expression of EpoR in tissue macrophages and hematopoietic cells. We show that in marked contrast to the previously available EpoR-eGFPcre mice, in which a very weak eGFP signal was detected in erythroid cells, tdTomato was readily detectable in both fetal liver (FL) and bone marrow (BM) erythroid cells at all developmental stages and exhibited dynamic changes during erythropoiesis. Consistent with our recent finding that erythroblastic island (EBI) macrophages are characterized by the expression of EpoR, tdTomato was readily detected in both FL and BM EBI macrophages. Moreover, tdTomato was also detected in subsets of hematopoietic stem cells, progenitors, megakaryocytes, and B cells in BM as well as in spleen red pulp macrophages and liver Kupffer cells. The expression of EpoR was further shown by the EpoR-tdTomato-Cre–mediated excision of the floxed STOP sequence. Importantly, EPO injection selectively promoted proliferation of the EpoR-expressing cells and induced erythroid lineage bias during hematopoiesis. Our findings imply broad roles for EPO/EpoR in hematopoiesis that warrant further investigation. The EpoR-tdTomato-Cre mouse line provides a powerful tool to facilitate future studies on EpoR expression and regulation in various non-hematopoietic cells and to conditionally manipulate gene expression in EpoR-expressing cells for functional studies.

Background The diagnostic value of six tumor markers was investigated and the appropriate combinations of those tumor markers to discriminate small cell lung cancer was explored.Methods Patients suspected with lung cancer (1938) were retrospectively analyzed. Candidate tumor markers from carcinoembryonic antigen (CEA), squamous cell carcinoma-related antigen (SCC), cytokeratin 19 fragment 21-1 (CYFRA 21-1), neuron-specific enolase (NSE), tissue polypeptide antigen (TPA), and progastrin releasing peptide (ProGRP) were selected to construct a logistic regression model. The receiver operating characteristic curve was used for evaluating the diagnostic value of the tumor markers and the predictive model.Results ProGRP had the highest positive rate (72.3%) in diagnosed small cell lung cancer, followed by neuron-specific enolase (68.3%), CYFRA21-1 (50.5%), carcinoembryonic antigen (45.5%), tissue polypeptide antigen (30.7%), and squamous cell carcinoma-related antigen (5.9%). The predictive model for small cell lung cancer discrimination was established, which yielded the highest area under the curve (0.888; 95% confidence interval: 0.846–0.929), with a sensitivity of 71.3%, a specificity of 95.0%, a positive predictive value of 49.0%, and a negative predictive value of 98.0%.Conclusions Combining tumor markers can improve the efficacy for small cell lung cancer discrimination. A predictive model has been established in small cell lung cancer differential diagnosis with preferable efficacy.

A wind turbine (WT) is a complex system integrating mechanical and electrical controls, and WTs can be coupled and interact with each other. This paper established an electromechanical model of a WT drivetrain and explored the influence of the system parameters of the WT drivetrain on the dynamic response and current harmonics. The results show that the introduction of a generator produces an electromagnetic frequency component in the mechanical system and that the mechanical parameters directly determine whether the generator undergoes periodic motion, quasiperiodic motion or chaotic motion, which affects the power generation efficiency of a WT. The research results can be used as a reference for the mechanical design of WT drivetrains and the selection of generators.

Histone deacetylases (HDACs) are a group of enzymes that catalyze the removal of acetyl groups from histone and nonhistone proteins. HDACs have been shown to have diverse functions in a wide range of biological processes. However, their roles in mammalian erythropoiesis remain to be fully defined. This study showed that, of the 11 classic HDAC family members, 6 (HDAC1, -2, -3, and HDAC5, -6, -7) are expressed in human erythroid cells, with HDAC5 most significantly upregulated during terminal erythroid differentiation. Knockdown of HDAC5 by either short hairpin RNA or small interfering RNA in human CD34+ cells followed by erythroid cell culture led to increased apoptosis, decreased chromatin condensation, and impaired enucleation of erythroblasts. Biochemical analyses revealed that HDAC5 deficiency resulted in activation of p53 in association with increased acetylation of p53. Furthermore, although acetylation of histone 4 (H4) is decreased during normal terminal erythroid differentiation, HDAC5 deficiency led to increased acetylation of H4 (K12) in late-stage erythroblasts. This increased acetylation was accompanied by decreased chromatin condensation, implying a role for H4 (K12) deacetylation in chromatin condensation. ATAC-seq and RNA sequencing analyses revealed that HDAC5 knockdown leads to increased chromatin accessibility genome-wide and global changes in gene expression. Moreover, pharmacological inhibition of HDAC5 by the inhibitor LMK235 also led to increased H4 acetylation, impaired chromatin condensation, and enucleation. Taken together, our findings have uncovered previously unrecognized roles and molecular mechanisms of action for HDAC5 in human erythropoiesis. These results may provide insights into understanding the anemia associated with HDAC inhibitor treatment.

Foreground object segmentation is an important task with various applications in outdoor surveillance and navigation. Most existing methods focus on accuracy and therefore, are computationally expensive and low in speed, making them difficult to use in actual applications. In this study, we aim to address the issue of accuracy and efficiency trade-off. In particular, in contrast with existing methods that use fine-tuning routine on heavyweight pretrained models and/or optimization techniques to enhance results, we propose a lightweight end-to-end network that can be trained from scratch effectively and efficiently. First, long and short skip connections are used among convolutional blocks and within the bottleneck block. By doing so, information flow within the networks is enhanced during the training stage, and thus, the use rate of parameters in the model is increased, allowing a more compact and efficient network design. Second, we use feature fusions based on element-wise summing before each up-sampling layer to reduce the size of the decoder, accelerate the up-sampling process, and stabilize training convergence. Our proposed method is tested rigorously. In particular, we achieved 1000 times higher speed compared with state-of-the-art methods on CD2014 and SBI2015 datasets with comparable accuracy. [ABSTRACT FROM AUTHOR]

Double-spending is a potential flaw in cryptocurrencies. In recent years, double-spend attacks have caused severe economic damage to many Bitcoin consumers, thus double-spending problems have attracted wide attention. Studying related countermeasures and mitigations against such attacks is imperative. In this article, we briefly introduce a new form of combined attack: double-spending with a Sybil attack in the Bitcoin network and discuss how to mitigate it. We propose two mitigations such as charging an identity fee and setting a deadline to defend against this attack, and we evaluate the effect of these two mitigations through an economic analysis.