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Antiambipolar heterojunctions are regarded as a revolutionary technology in the fields of electronics and optoelectronics, enabling the switch between positive and negative transconductance within a single device, which is crucial for diverse logic circuit applications. This study pioneers a mixed-dimensional photodetector featuring antiambipolar properties, facilitated by the van der Waals integration of one-dimensional CdSxSe1–xnanowires and two-dimensional Te nanosheets. This antiambipolar device enables flexible control over carrier transport via gate voltage, thus paving new paths for future optoelectronic devices. Furthermore, by precisely managing the stoichiometry of the ternary alloy CdSxSe1–xnanowires, fine-tuning of the nanowire band structure is achieved. This allows for customizable heterojunction band alignment (Type I and Type II), enabling adjustable band alignment. Through sophisticated band engineering, optimal Type II band alignment is achieved at the CdSxSe1–x/Te interface, significantly enhancing the device’s photoelectric conversion efficiency through the synergistic effect of different dimensional materials. Exhibiting outstanding photoresponse across a broad spectral range from ultraviolet to near-infrared, especially under 450 nm illumination, the CdSxSe1–x/Te heterojunction photodetector demonstrates superior performance, including an impressive responsivity of 284 A W–1, a high detectivity of 1.07 × 1017Jones, an elevated external quantum efficiency of 7.83 × 104%, and a swift response time of 11 μs. Ultimately, this customizable antiambipolar photodetector lays a solid foundation for the advancement of next-generation optoelectronic technologies.

All-aqueous thermally regenerative battery (ATRB) is a promising electrochemical device for converting low-grade waste heat into electrical energy, while the low specific surface area of electrodes limits its performance. To improve the performance, the carbon nanotube/carbon cloth (CNT/CC) composite electrode with a highly specific surface area is proposed for ATRB in this study. The use of the CNT/CC composite electrodes induces a 37.4% higher maximum power density of ATRB (409.6 W/m2) compared with that of ATRB with the carbon cloth (CC) electrodes. The optimal CNT loading amount is determined to further enhance ATRB performance. Increasing the flow rate helps facilitate mass transfer, the optimal flow rate (50 mL/min) is selected considering the influence of the hydrodynamic loss. Concerning the expend application, a series stack of ATRB is constructed to successfully drive an electrochemical CO2reduction device, resulting in a comparable Faraday efficiency for the conversion of CO2to CO.

ABSTRACTThis research was undertaken to determine expression patterns of vacuolar processing enzyme (VPE) genes in four apple (Malus domestica(Suckow) Borkh) cultivars ‘Royal Gala (RG)’, ‘Golden Delicious (GD)’, ‘Ralls Janet (RJ)’ and ‘Fuji (FJ)’ during ripening. The results showed that GD and RG had higher respiration rate, ethylene production, content of malondialdehyde (MDA), relative electrical conductivity (REC) and VPE activity than RJ and FJ during ripening. A total of 17 MdVPEswere found to be expressed in four cultivars. These MdVPEsexhibited different expression patterns during ripening of four cultivars. Generally, MdVPEβ1, MdVPEγ2, MdVPEγ4and MdVPEδ7might be closely associated with ripening of all cultivars. MdVPEα6might have a role in the early period of ripening of ACS1–2/-2(1-Aminocyclopropane-1-carboxylate synthase) homozygous cultivars (RG, RJ and FJ). Our data here would be helpful in understanding the associations between MdVPEsand storage properties of different apple cultivars.

The human gut microbiota significantly impacts health, including liver conditions like liver cirrhosis (LC) and spontaneous bacterial peritonitis (SBP). Immunoglobulin A (IgA) plays a central role in maintaining gut microbial balance. Understanding IgA's interplay with gut microbiota and liver health is crucial. This study explores the relationship between fecal IgA levels, gut microbiota, and liver injury severity. A total of 69 LC patients and 30 healthy controls were studied. Fecal IgA levels were measured using ELISA, and IgA‐coated bacteria were quantified via flow cytometry. Microbiota diversity and composition were assessed through 16S rRNA sequencing. Liver injury severity was graded using the Child–Pugh score. Statistical analyses determined correlations. LC patients had higher fecal IgA levels than controls, correlating positively with liver injury severity. Microbiota diversity decreased with severity, accompanied by shifts in composition favoring pro‐inflammatory species. Ralstoniaabundance positively correlated with liver injury, whereas Faecalibacteriumshowed a negative correlation. Specific microbial markers for SBP were identified. Functional profiling revealed altered microbial functionalities in LC and SBP. Elevated fecal IgA levels, coupled with microbiota alterations, correlate with liver injury severity in LC patients. Modulating gut microbiota could be a promising strategy for managing liver‐related conditions. Further research is needed to understand underlying mechanisms and translate findings into clinical practice, potentially improving patient outcomes.

A high-temperature resistant air-coupled ultrasonic transducer (ACUT) was optimally designed with a single acoustic matching layer structure. The matching layer was prepared with an organosilicon substrate instead of traditional epoxy resin mixed with hollow glass microspheres. Acoustic performance tests showed that the matching layer achieved an acoustic impedance of 1.06 MRayl and an acoustic attenuation coefficient of 0.47 dB/mm. The ACUT was clamped with a prestressed bolt structure instead of an adhesive layer and encapsulated with a metal shell. Mechanical performance was tested before and after encapsulation, which resulted in varying degrees of reduction in mechanical quality factor and resonant frequency. The acoustic performance of the ACUT was compared to commercial transducers, and the results indicated 2.72 and 1.88 dB higher transmitting and receiving sensitivities than those of commercial transducers. The received amplitude increased by an additional 22% by adding an electrical impedance matching circuit between the excitation source and the transmitting transducer. High-temperature experiments revealed a linear decrease in the received signal amplitude with increasing temperature. The ACUT is finally calibrated for ambient flow rate calibration and high-temperature flow velocity calibration, respectively. The ambient flow rate calibration exhibited an error of only 1.9%, while the high-temperature flow velocity calibration demonstrated that temperature has a minimal impact on the precision of the ACUT.

In this study, a microwave slot-antenna loaded with complementary split ring resonator (CSRR) for wireless temperature-pressure detection in high-temperature environments was presented. To achieve the design of a miniaturized high-temperature sensor with multiple parameters, it is proposed to use an S11 to simultaneously monitor temperature and pressure parameters. Using resonant amplitude to monitor changes in environmental temperature and using resonant frequency to characterize changes in pressure, the sensitivity mechanisms for the temperature and pressure sensing are described in detail. The working principle of the temperature-pressure sensor is elaborated via circuit analysis and simulation optimization of high-frequency structure simulator (HFSS). The sensor was customized and fabricated on the high-temperature cofired ceramics (HTCC) using the 3-D co-firing and screen-printing technology. The as-prepared sensor can stably work at the ambient environment of $20~^{\circ }$ C– $800~^{\circ }$ C and 100–300 kPa, with a temperature sensitivity of 0.0133 dB/°C and a pressure sensitivity of 235 kHz/kPa at $800~^{\circ }$ C. The temperature compensation algorithm is proposed to achieve accurate acquisition of pressure signals in a high-temperature environment. The sensor has the potential for utilization in simultaneous temperature and pressure monitoring in harsh environments.

Video analytics at mobile edge servers offers significant benefits like reduced response time and enhanced privacy. However, guaranteeing various quality-of-service (QoS) requirements of dynamic video analysis requests on heterogeneous edge devices remains challenging. In this paper, we propose a scalable online video analytics scheme, called Novas, which automatically makes precise service configuration adjustments upon constant video content changes. Specifically, Novas leverages the filtered confidence sum and a two-window t-test to online detect accuracy fluctuations without ground truth information. In such cases, Novas efficiently estimates the performance of all potential service configurations through a singular value decomposition (SVD)-based collaborative filtering method. Finally, given the NP-hardness of the optimal scheduling problem, a heuristic scheduling strategy that maximizes the minimum remaining resources is devised to schedule the most suitable configurations to servers for execution. We evaluate the effectiveness of Novas through extensive hybrid experiments conducted on a dedicated testbed. Results show that Novas can achieve a substantial over 27$\times$× improvement in satisfying the accuracy requirements compared with existing methods adopting fixed configurations, while ensuring latency requirements. Moreover, Novas improves the goodput of the system by an average of 37.86% compared to existing state-of-the-art scheduling solutions.

Aqueous zinc-ion batteries (AZIBs) have garnered extensive attention as promising energy storage systems because of the advantages of low cost and high safety. However, severe parasitic reactions at the Zn anode surface pose a huge challenge for the practical application of AZIBs, especially the intricate hydrogen evolution reaction (HER) and Zn dendrite growth. Herein, zwitterionic taurine with isoelectric point property is introduced as an electrolyte additive to construct a passivation layer by adapting its net charge to the microenvironment variation for stabilizing the Zn anode. The experimental and theoretical results reveal that taurine can not only in-situform a hydrophobic and zincophilic layer on the Zn anode surface viathe chelation with Zn2+in the alkaline interfacial microenvironment, but also buffer the pH change dynamically, thus effectively suppressing the HER and Zn dendrite growth. As a consequence, the taurine-containing electrolyte enables a stable cycling of Zn anodes in symmetric Zn∥Zn cells for more than 1800 h under a deep plating/stripping condition (5 mA cm−2and 5 mAh cm−2). More encouragingly, the full cells coupled with the NH4V4O10cathode can also exhibit an excellent capacity retention of 89.8% after 1200 cycles. This efficient strategy with an environmental adaptive additive offers valuable insights for mitigating the side reactions to achieve practical AZIBs and beyond.

While the majority of knots are made from the metal-template approach, the use of entangled, constrained knotted loops to modulate the coordination of the metal ions remains inadequately elucidated. Here, we report on the coordination chemistry of a 140-atom-long cinquefoil knotted strand comprising five tridentate and five bidentate chelating vacancies. The knotted loop is prepared through the self-assembly of asymmetric “3 + 2” dentate ligands with copper(II) ions that favor five-coordination geometry. The formation of the copper(II) pentameric helicate is confirmed by X-ray crystallography, while the corresponding copper(II) knot is characterized by XPS and LR-/HR ESI-MS. Upon removal of the original template, the knotted ligand facilitates zinc(II) ions, which typically form four- or six-coordination geometries, resulting in the formation of an otherwise inaccessible zinc(II) metallic knot with coordinatively unsaturated metal centers. The coordination numbers and geometries of the zinc(II) cations are undoubtedly determined by X-ray crystallography. Despite the kinetically labile nature and high reversibility of the zinc(II) complex preventing the detection of 5-to-6 coordination equilibrium in solution, the effects on metal-ion coordination induced by knotting hold promise for fine-tuning the coordination of metal complexes.

Conducting/insulating inks have received significant attention for the fabrication of a wide range of additive manufacturing technology. However, current inks often demonstrate poor biocompatibility and face trade-offs between conductivity and mechanical stiffness under physiological conditions. Here, conductive/insulating bioinks based on two-dimensional materials are proposed. The conductive bioink, graphene (GR)-poly(lactic-co-glycolic acid) (PLGA), is prepared by introducing conductive GR into a degradable polymer matrix, PLGA, while the insulating bioink, boron nitride (BN)-PLGA, is synthesized by adding insulating BN. By optimizing the material ratios, this work achieves precise control of the electromechanical properties of the bioinks, thereby enabling the flexible construction of conductive networks according to specific requirements. Furthermore, these bioinks are compatible with a variety of manufacturing technologies such as 3D printing, electrospinning, spin coating, and injection molding, expanding their application range in the biomedical field. Overall, the results suggest that these conducting/insulating bioinks offer improved mechanical, electronic, and biological properties for various emerging biomedical applications.

With more flexible active sites and intermetal interaction, dual-atom catalysts (DACs) have emerged as a new frontier in various electrocatalytic reactions. Constructing a typical p-d orbital hybridization between p-block and d-block metal atoms may bring new avenues for manipulating the electronic properties and thus boosting the electrocatalytic activities. Herein, we report a distinctive heteronuclear dual-metal atom catalyst with asymmetrical FeSn dual atom sites embedded on a two-dimensional C2N nanosheet (FeSn–C2N), which displays excellent oxygen reduction reaction (ORR) performance with a half-wave potential of 0.914 V in an alkaline electrolyte. Theoretical calculations further unveil the powerful p-d orbital hybridization between p-block stannum and d-block ferrum in FeSn dual atom sites, which triggers electron delocalization and lowers the energy barrier of *OH protonation, consequently enhancing the ORR activity. In addition, the FeSn–C2N-based Zn–air battery provides a high maximum power density (265.5 mW cm–2) and a high specific capacity (754.6 mA h g–1). Consequently, this work validates the immense potential of p-d orbital hybridization along dual-metal atom catalysts and provides new perception into the logical design of heteronuclear DACs.

High-resolution range profile (HRRP) is increasingly employed in radar target recognition under intricate ground scenarios. Such scenarios demand recognizing the specific type of a target from a wide range of categories, a task known as fine-grained target recognition (FGTR), which involves numerous and potentially unbalanced categories. To tackle this, we propose a joint semantic-data guided hierarchical classification (SDHC) framework. It consists of a set of local classifiers organized in a tree hierarchy based on the joint semantic-data relationship. It allows the complex FGTR task to be simplified into multiple small-scale subtasks. Specifically, the proposed SDHC method focuses on tree hierarchy construction and local classifier training. We design the tree hierarchy based on a joint semantic-data similarity measure, which quantifies the data similarity between categories and incorporates semantic knowledge constraints. Following this, we deploy hierarchical feature selection on a multidimensional feature set, considering the contribution of features in each local classifier. Experimental results on measured data verify the effectiveness of the proposed method. Moreover, analysis results demonstrate the superiority of the hierarchical approach over flat methods.

Objective: To observe the effects of moxibustion on the levels of glucose-6-phosphate dehydrogenase (G6PD) and reduced nicotinamide adenine dinucleotide phosphate (NADPH) in the plasma and spleen and the CD4+T-cell number in the spleen of rats with adjuvant arthritis, thus to explore the mechanism in rheumatoid arthritis (RA) treatment with moxibustion by regulating the CD4+T-cell proliferation through G6PD-mediated pentose phosphate pathway. Methods: Twenty-seven male Sprague-Dawley rats were randomly divided into a blank group, a model group, and a moxibustion group, with 9 rats in each group. Incomplete Freund’s adjuvant was used to induce inflammation in the model group and the moxibustion group. The blank group and the model group were not intervened. In the moxibustion group, suspended moxibustion was performed at bilateral Zusanli (ST36), Guanyuan (CV4), and Ashi points for 30 min, once a day for 24 times in total. Hematoxylin-eosin staining was used to evaluate the histopathological changes of rat synovial tissue; the swelling degree of the rat toes was observed by measuring the toe volume; G6PD and NADPH in the spleen and plasma were detected by Western blotting and enzyme-linked immunosorbent assay. Flow cytometry was used to detect the CD4+T-cell number in the spleen. Results: Compared with the blank group, the levels of G6PD and NADPH in the plasma and spleen and the CD4+T-cell number in the spleen were significantly increased in the model group (P<0.01 or P<0.05). Compared with the model group, the NADPH level in the spleen and plasma and the CD4+T-cell number in the spleen in the moxibustion group decreased significantly (P<0.05 or P<0.01), and the G6PD level in the plasma decreased significantly (P<0.05), but there was no significant difference in the G6PD level in the spleen (P>0.05). Conclusion: Moxibustion can regulate immunity and improve joint synovial inflammation in RA. The mechanism may be that the G6PD-mediated pentose phosphate pathway reduces the production of metabolite NAPDH in CD4+T cells, thereby inhibiting the proliferation of naive CD4+T cells.

This paper establishes a widely applicable method for designing hollow-core anti-resonant fiber (HC-ARF) model based on geometric principles, which is feasible under practical manufacturing conditions and is defined by concise equations. We define this problem as a combinatorial optimization issue under the constraints of mixed integer nonlinearity. We iteratively refine the solution space through multiple steps, culminating in an integrated algorithm for automated modeling computation and data extraction. Through exhaustive calculation of models under limited conditions, we obtained multiple rigid HC-ARFs with low confinement loss (CL), low bend loss, and relatively high birefringence. The minimum CL is $\text{8.8}\times \text{10}^{-3}$ dB/m. At bending radius of 5 cm, the lowest bend loss is $\text{2.7}\times \text{10}^{-2}$ dB/m, and the highest birefringence is $\text{2.2}\times \text{10}^{-6}$. After statistical analysis, two key factors influencing single anti-resonance layer HC-ARF have been determined: the number and radius of the rings hold the primary importance, followed by the rings arrangement. Further study demonstrates that the proposed model design method can be applied to various optical fiber designs.

Uncertainty exists about whether lowering systolic blood pressure to less than 120 mm Hg is superior to that of less than 140 mm Hg, particularly in patients with diabetes and patients with previous stroke.

Relative permeability (RP) curves which provide fundamental insights into porous media flow behavior serve as critical parameters in reservoir engineering and numerical simulation studies. However, obtaining accurate RP curves remains a challenge due to expensive experimental costs, core contamination, measurement errors, and other factors. To address this issue, an innovative approach using deep learning strategy is proposed for the prediction of rock sample RP curves directly from mercury injection capillary pressure (MICP) measurements which include the mercury injection curve, mercury withdrawal curve, and pore size distribution. To capture the distinct characteristics of different rock samples' MICP curves effectively, the Gramian Angular Field (GAF) based graph transformation method is introduced for mapping the curves into richly informative image forms. Subsequently, these 2D images are combined into three-channel red, green, blue (RGB) images and fed into a Convolutional Long Short-Term Memory (ConvLSTM) model within our established self-supervised learning framework. Simultaneously the dependencies and evolutionary sequences among image samples are captured through the limited MICP-RP samples and self-supervised learning framework. After that, a highly generalized RP curve calculation proxy framework based on deep learning called RPCDL is constructed by the autonomously generated nearly infinite training samples. The remarkable performance of the proposed method is verified with the experimental data from rock samples in the X oilfield. When applied to 37 small-sample data spaces for the prediction of 10 test samples, the average relative error is 3.6%, which demonstrates the effectiveness of our approach in mapping MICP experimental results to corresponding RP curves. Moreover, the comparison study against traditional CNN and LSTM illustrated the great performance of the RPCDL method in the prediction of both Soand Swlines in oil–water RP curves. To this end, this method offers an intelligent and robust means for efficiently estimating RP curves in various reservoir engineering scenarios without costly experiments.

• Achieved optimal strength and ductility in Al-2.5Li-2Mg-1Cu-0.12Zr alloy with two-stage solution and 175 °C aging for 32 h. • Cu addition increased Al 2 CuMg and Al 3 Li, and restrained expansion of Al 3 Li-PFZ. • Thorough analysis of strengthening mechanism with Cu alloying and aging treatment. In this work, the effect of Cu addition and heat treatment schemes on the microstructural evolution, mechanical properties, and corresponding strengthening mechanism of cast Al-Li-Mg alloy were investigated. Results indicate that the dendritic segregation would be induced after the introduction of Cu, and a well-designed two-stage solution treatment could effectively dissolve secondary phases. With Cu addition, aging hardening responses of the alloys were accelerated, accompanied by a continuous increase in the volume fraction of both S'-Al 2 CuMg and Al 3 Li phases, which enhanced the precipitation strengthening effect. Furthermore, in Cu-containing alloys, both the coarsening of Al 3 Li phases and the expansion of Al 3 Li-precipitation free zones (PFZ) were inhibited during the aging process. However, severe strain accumulation was found at the interface between the coalesced S' phase and α-Al matrix, which reduced the ductility of the alloy. A good combination of strength and ductility (YS = 308 MPa, UTS = 428 MPa, EL = 5.0 %) was obtained in the Al-2.5Li-2Mg-1Cu-0.12Zr alloy aged at 175 °C for 32 h due to the narrowed Al 3 Li-PFZ and the synergistic strengthening of Al 3 Li and S' phase. This work is expected to provide guidelines for designing novel cast Al-Li alloys with wider applications. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: Three macrocyclic polyamine alkaloids with a 13-membered ring, named celafurine, celacarfurine, and celabenzine, isolated from Tripterygium wilfordiiHook.f., Celastraceae, were evaluated for their neuroprotective effects in an Alzheimer’s disease cell model, which was established by inducing human neuroblastoma SH-SY5Y cells with amyloid β-peptide (1-42). Celabenzine exhibited remarkable protective effects on SH-SY5Y cells induced by amyloid β-peptide (1-42) by increasing cell viability from 60 to 80%, and restored the morphology of damaged SH-SY5Y cells. Celabenzine significantly reduced the deposition of amyloid β-peptide (1-42) in SH-SY5Y cells probably via autophagy through upregulating the level of Beclin-1 and downregulating the level of LC 3-I. Graphical Abstract:

The global cold chain transportation system demands significant energy for low-temperature insulation and costly materials for mechanical support, driving the widespread use of nonrenewable petroleum and mineral-based resources. This study presents a sustainable solution in the form of structured wood, which offers thermal insulation and mechanical strength by microscopically reshaping cell walls and constructing complex three-dimensional shapes. The resulting corrugated wood boards (CWB) exhibit impressive characteristics, including ultralow thermal conductivity (∼0.09 W/m·K) and notable impact energy dissipation (∼80%), essential for cold chain storage and transportation. Additionally, they possess low density, exceptional structural stability, and mechanical strength (approximately 82 MPa per g/cm3and 1 MPa of specific bending and compressive strength), crucial for packaging containers and storage warehouses within the cold chain system. Through integration with high-fill insulation biobased polyurethane foam, the composite CWB achieves optimized insulation and thermal conductivity (∼0.06 W/m·K). With its low thermal conductivity, high mechanical strength, environmental advantages, and scalable manufacturing capabilities, this innovative wood-based material emerges as a promising sustainable option for both the cold chain transportation and construction sectors.

The redox transition between iron and its oxides is of the utmost importance in heterogeneous catalysis, biological metabolism, and geological evolution. The structural characteristics of this reaction may vary based on surrounding environmental conditions, giving rise to diverse physical scenarios. In this study, we explore the atomic-scale transformation of nanosized Fe3O4under ambient-pressure H2gas using in-situ environmental transmission electron microscopy. Our results reveal that the internal solid-state reactions dominated by iron diffusion are coupled with the surface reactions involving gaseous O or H species. During reduction, we observe two competitive reduction pathways, namely Fe3O4→ FeO → Fe and Fe3O4→ Fe. An intermediate phase with vacancy ordering is observed during the disproportionation reaction of Fe2+→ Fe0+ Fe3+, which potentially alleviates stress and facilitates ion migration. As the temperature decreases, an oxidation process occurs in the presence of environmental H2O and trace amounts of O2. A direct oxidation of Fe to Fe3O4occurs in the absence of the FeO phase, likely corresponding to a change in the water vapor content in the atmosphere. This work elucidates a full dynamical scenario of iron redox under realistic conditions, which is critical for unraveling the intricate mechanisms governing the solid–solid and solid–gas reactions.