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A nuclear-localized cysteine desulfhydrase, LCD1, plays a crucial role in mediating endogenous hydrogen sulfide production in tomatoes. However, the mechanism underlying the nuclear localization of SlLCD1 is not yet fully understood. In this study, it was found that SlLCD1 specifically interacted with nuclear import receptor importin α3 (SlIMPA3). Furthermore, it was demonstrated that silencing SlIMPA3 through virus-induced gene silencing or introducing mutations in SlIMPA3via CRISPR/Cas9 significantly accelerated fruit ripening. Moreover, enhanced chlorophyll degradation, carotenoid accumulation, and premature upregulation of ripening-associated genes in the slimpa3mutant indicated SlIMPA3 to be a negative regulator of fruit ripening and leaf senescence. Besides, SlIMPA3deletion resulted in excessive hydrogen peroxide accumulation in fruits and leaves, potentially leading to premature leaf senescence and accelerated fruit ripening in the slimpa3mutant. SlIMPA3 exhibited pronounced nuclear localization with weak distribution in the cytoplasm. SlLCD1 showed specific nuclear localization; however, after GFP tagging in slimpa3-edited tomato leaves, it migrated to the cytoplasm, suggesting that SlIMPA3 mediated the nuclear localization of SlLCD1. SlLCD1 transient expression in slimpa3mutant fruits indicated that it did not inhibit tomato ripening following the SlIMPA3mutation. In summary, our study revealed that SlIMPA3 interacted with SlLCD1 to facilitate its nuclear entry. Mutations in SlIMPA3led to premature fruit ripening and leaf senescence, likely due to disrupted reactive oxygen species homeostasis resulting from SlLCD1 mislocalization in the slimpa3mutant.

Ionic skin can mimic human skin to sense both temperature and pressure simultaneously. However, a significant challenge remains in creating precise ionic skins resistant to external stimuli interference when subjected to pressure. In this study, we present an innovative approach to address this challenge by introducing a highly anisotropic nanofluidic ionic skin (ANIS) composed of carboxylated cellulose nanofibril (CNF)-reinforced poly(vinyl alcohol) (PVA) nanofibrillar network achieved through a straightforward one-step hot drawing method. The inherent anisotropic nanostructures endowed the ANIS with a modulus (20.9 ± 4.9 MPa) comparable to that of human cartilage and skin, alongside higher fracture energy (41.4 ± 0.3 kJ/m2) and fatigue threshold (1360 J/m2). Incorporating carboxylated CNF not only improves the negative potential but also increases the ionic conductivity of ANIS up to 0.001 S/cm, even at very low ionic concentration (1.0 × 10–6M). Furthermore, the ANIS exhibits pressure-independent temperature sensitivity due to its high deformation-resistant performance. Thus, this work introduces a facile strategy for fabricating ANIS with pressure-independent thermosensing properties, promising prospects for practical healthcare applications.

Oxidative pyrolysis eliminates the need for external heating in large-scale industrial applications by autothermal reactions. Heavy components in bio-oil (molecular weight >200 Da) tend to generate coke when heated, causing reactor blockages and catalyst deactivation. This research aimed to elucidate the effects of interactions among the three components of biomass on the generation of heavy components. Both oxidative pyrolysis with an oxygen concentration of 4 vol % and conventional experiments were conducted at 500 °C. The results showed that the interactions among the three components presented different effects on the formation of heavy components. The interactions between cellulose and hemicellulose promoted the formation of heavy components by enhancing the homogeneous oxidation of volatiles, e.g., increasing the content of heavy components (200–300 Da) by 103%. Similarly, the interactions between hemicellulose and lignin promoted the polymerization of volatiles during oxidative pyrolysis to generate heavy components, e.g., increasing the content of heavy components (O ≥ 4) by 71%. However, the interactions between cellulose and lignin promoted the decomposition of heavy components (≥300 Da, O ≥ 5) to generate those (<300 Da, O < 5).

Canonical correlation analysis (CCA) is a correlation analysis technique that is widely used in statistics and the machine-learning community. However, the high complexity involved in the training process lays a heavy burden on the processing units and memory system, making CCA nearly impractical in large-scale data. To overcome this issue, a novel CCA method that tries to carry out analysis on the dataset in the Fourier domain is developed in this article. Appling Fourier transform on the data, we can convert the traditional eigenvector computation of CCA into finding some predefined discriminative Fourier bases that can be learned with only element-wise dot product and sum operations, without complex time-consuming calculations. As the eigenvalues come from the sum of individual sample products, they can be estimated in parallel. Besides, thanks to the data characteristic of pattern repeatability, the eigenvalues can be well estimated with partial samples. Accordingly, a progressive estimate scheme is proposed, in which the eigenvalues are estimated through feeding data batch by batch until the eigenvalues sequence is stable in order. As a result, the proposed method shows its characteristics of extraordinarily fast and memory efficiencies. Furthermore, we extend this idea to the nonlinear kernel and deep models and obtained satisfactory accuracy and extremely fast training time consumption as expected. An extensive discussion on the fast Fourier transform (FFT)-CCA is made in terms of time and memory efficiencies. Experimental results on several large-scale correlation datasets, such as MNIST8M, X-RAY MICROBEAM SPEECH, and Twitter Users Data, demonstrate the superiority of the proposed algorithm over state-of-the-art (SOTA) large-scale CCA methods, as our proposed method achieves almost same accuracy with the training time of our proposed method being 1000 times faster. This makes our proposed models best practice models for dealing with large-scale correlation datasets. The source code is available at https://github.com/Mrxuzhao/FFTCCA.

Divergent synthesis of structurally different products from the same kinds of starting materials is highly synthetically useful but very challenging. Herein, we reported a base-mediated chemodivergent [4 + 1] and [2 + 1] cycloaddition of N-alkylpyridinium and enone under mild conditions, leading to furan-fused bicycles with high diastereoselectivity and spirobicycles, respectively, from moderate to high yields. N-Alkylpyridinium salts were modular nucleophilic transfer reagents and C1 synthons, which underwent tandem Michael addition to the α,β-unsaturated ketones and cyclization under the base conditions. Late-stage derivatization of 4-propyldicyclohexylanone from an important industrial raw of liquid crystal display (LCD) screens was realized. In vitro, compound 3fexhibited good activities against human colon cancer cells (HCT116) with IC50values in 9.82 ± 0.27 μM. Further biological evaluations investigated the mechanism of the effective inhibition of cell growth, including apoptosis ratio detection, cell cycle analysis, and migration capacity of HCT116 cells. In apoptosis effect studies, complex 3fincreased the percentage of apoptotic HCT116 cells to 26.8% (15 μM).

Background: Direct-acting oral anticoagulants (DOACs) have become the preferred drugs for managing venous thromboembolism (VTE). Despite their advantages over vitamin K antagonists such as warfarin, their use in obese patients remains controversial with many providers reluctant to switch patients managed on warfarin. Outcome research that opts to increase provider confidence when prescribing DOACs for patients with obesity will be invaluable.Objective: This investigation evaluated whether patients with a body mass index (BMI) 35 kg/m2or greater who were prescribed a DOAC had a higher risk for a recurrent VTE or bleed event relative to warfarin.Methods: The study was conducted in West Virginia which has the highest rate of obesity in the United States.Results: Of the total study population (1633), 2.3% (37) had a recurrent thrombotic event, 5.5% (89) had a major bleed event, and 10.7% (174) had some type of bleeding event. No individual patient characteristic was associated with recurrent thrombosis—including BMI. Older age, antiplatelet use, and taking a medication with a theoretical risk of increasing the effect of DOACs were associated with any and major bleeding events. The use of warfarin was associated with major bleeding events more frequently versus a DOAC. Body mass index was not a predictor for recurrent VTE or any bleed or major bleed events.Conclusions: These findings support the conclusion that DOACs are an appropriate and effective drug class for the management of VTE in patients with obesity.

In this work, a type of modified aluminum oxide-titanium dioxide composite filler (MAT) was employed as a high refractive index and wide electron band gap filler and incorporated into reversible cross-linked polyurethane (RCPU) with disulfide bonds to prepare passive radiative cooling coating. After modification by a 3-isocyanatopropyltrimethoxysilane coupling agent, the urethane and siloxane chains were found to covalently bond between aluminum oxide and titanium dioxide, which imparts the MAT filler a good dispersion level in the RCPU matrix. The as-prepared RCPU-MAT10 coating with 10 wt % of the MAT filler possessed desirable solar reflectance and thermal emittance in atmospheric transparency windows of 0.874 and 0.977, respectively, resulting in a subambient daytime cooling of 8.7 °C (solar light irradiation is 814 W/m2) and a nighttime cooling of 4.2 °C under outdoor environments. Taking advantage of the dynamic exchange feature of disulfide bonds, RCPU-MAT10 exhibited good recyclability behavior under heating (100 °C) for 10 min. More encouragingly, the recycling efficiency in passive radiative cooling performance for RCPU-MAT10 still remained above 95% after three cycles.

In the field of electrocatalysis, most of the electrodes have the problem of poor mechanical properties, which leads to the electrode can not be used on a large scale. At present, most bulk electrodes are used to study their mechanical properties due to their unique phase composition distribution and facile fabricate methods. But their novel properties in the field of electrocatalysts have not been fully developed. Multi-element bulk electrodes not only diversified the electronic states, but also build complex surface morphology by different dissolution rate between multi-phase distribution. In this paper, we synthesized the FeNiMo bulk electrode for oxygen evolution reaction (OER) with two-phase coexistence of Mo-doped face center cubic phase (FCC) and Mo-rich intermetallic compound (IMC) phase. During cyclic voltammetry activation, the surface reconstruction of Mo-rich IMC phases generated by ion leaching leaves Fe–Ni pore structures with more active area, which enhances OER performance. Meanwhile, the electron states get more diverse on the surface of remaining FCC phases due to Mo doping, which provides more suitable sites for four-step OER process. The FeNiMo electrode shows an ultra-low overpotential of 212 mV and 293.4 mV at a current density of 10 mA cm−2and 100 mA cm−2, respectively. Moreover, it can maintain stability at 100 mA cm−2for up to 72 h. This work provides a strategy for studying the relationship between phase composition and electrochemical performance of alloy bulk electrodes.

The solid-state reaction behavior of MgO−V2O5mixtures with different molar ratios was explored. The solubility of the solid-state reaction products (magnesium vanadates) in water at 25−55 °C was measured using the isothermal solution saturation method. The dissolution behavior and kinetics of the magnesium vanadates in dilute sulfuric acid were also investigated. The results showed that the molar ratio of MgO to V2O5and roasting temperature significantly influenced the phase transformation of the solid-state reaction product. MgV2O6exhibits the highest solubility in water, followed by Mg2V2O7and Mg3V2O8. The dissolution rate of magnesium vanadates in dilute sulfuric was significantly increased with the decrease of pH from 4.0 to 2.5 and the temperature increase from 30 to 70 °C. The dissolution of magnesium vanadate can be described using a second-order pseudo-homogeneous reaction model.

Grain refinement is a crucial technique for enhancing the mechanical properties and corrosion resistance of magnesium alloys. In this study, the addition of 0.3 wt% CaO and 0.3 wt% CaCO3successfully refined the AM60 alloy, resulting in a significant reduction in the average grain size from 326 μm to 96 μm (when adding CaCO3). The refined grain size of the as-cast AM60 alloy led to an increase in both tensile strength and yield strength to 118.2 MPa and 72.6 MPa, representing a respective increase of 35% and 23% compared to the alloy without the refiner. As results of EBSD, it is verified that the basal slip system (0001)<112‾0>has a higher Schmid factor after adding CaO, which indicates that this system has higher activity. The substitution reaction between CaO and Mg can produce synergistic effects from the solute effect of Ca and the nucleating effect of residual CaO, which play an important role in grain refinement. Due to the fine grain size and diffuse distribution of the second phase in the AM60-CaCO3alloy and the thermal decomposition of CaCO3, which consumes the aluminum element in the matrix, the content of the β-phase (Mg17Al12) is reduced. Consequently, this reduces the electric coupling effect between the β-phase and the magnesium matrix. The AM60-CaCO3alloy exhibited the most superior corrosion resistance, achieving a corrosion rate of only 1.01 mm y−1, representing a 48.9% reduction in corrosion rate compared to the AM60 alloy.

The metallurgical quality control of magnesium (Mg) and Mg alloys in melting process is required to ensure a satisfied mechanical and corrosion performance, while the typical used steel crucible introduces impurities and interfacial interaction during melting process. Therefore, a systematic study about impurities diffusion and interfacial interaction between molten Mg and steel is necessary. In the present study, the interfacial reaction between molten AZ91D Mg alloy and mild steel during melting process was investigated with the melting temperatures of 700 °C, 750 °C and 800 °C. The results show that Al(Fe, Mn) intermetallic layer is the intermetallic primarily formed at the interfaces of AZ91D melt and mild steel. Meanwhile, Al8(Mn, Fe)5is indexed between Al(Fe, Mn) and AZ91D. AlFe3C appears between the mild steel and Al(Fe, Mn) at 700 °C and 750 °C, but absent at 800 °C due to the increased solubility of carbon in Mg matrix. It is found that the growth of the intermetallic layer is controlled by diffusion mechanism, and Al and Mn are the dominant diffusing species in the whole interfacial reaction process. By measuring the thickness of different layers, the growth constant was calculated. It increases from 1.89(±0.03)×10−12m2·s−1at 700 °C to 3.05(±0.05)×10−12m2·s−1at 750 °C, and 5.18(±0.05)×10−12m2·s−1at 800 °C. Meanwhile, the content of Fe is linearly increased in AZ91D with the increase of holding time at 700 °C and 750 °C, while it shows a significantly increment after holding for 8 h at 800 °C, indicating holding temperature is more crucial to determine the Fe content of AZ91D than holding time.

Key message: Unreduced megagametophytes via second-division restitution were confirmed through heterozygosity analysis, and four candidate physical centromeres of rubber were located for the first time. Abstract: The evaluation of maternal heterozygosity restitution (MHR) is vital in identifying the mechanism of 2ngametogenesis and assessing the utilization value of 2ngametes. In this study, three full-sib triploid populations were employed to evaluate the MHR of 2nfemale gametes of rubber tree clone GT1 and to confirm their genetic derivation. The 2nfemale gametes of GT1 were derived from second-division restitution (SDR) and transmitted more than half of the parental heterozygosity. In addition, low recombination frequency markers were developed, and four candidate physical centromeres of rubber tree were located for the first time. The confirmation that 2nfemale gametes of rubber tree clone GT1 are derived from SDR provides insights into the molecular mechanisms of 2ngametogenesis. In addition, the identified centromere location will aid in the development of centromeric markers for the rapid identification of the 2ngametogenesis mechanism.

Hydrogel, recognized as a promising biomaterial for tissue engineering, possesses notable characteristics, including high water uptake, an interconnected porous structure, and excellent permeability. However, the intricate task of fabricating a hierarchically macro–micronanoporous structure, essential for providing adequate space for nutrient diffusion and cell growth within hydrogels, remains a formidable challenge. In response to these challenges, this study introduces a sustainable and straightforward three-dimensional (3D) foaming printing strategy to produce hierarchically macro–micronanoporous hydrogels (HPHs) without the utilization of porogens and post-etching process. This method entails the controlled generation of air bubbles within the hydrogels through the application of optimal mechanical stirring rates. Subsequent ultraviolet (UV) cross-linking serves to effectively stabilize the macropores within the HPHs. The resulting hierarchically macro–micronanoporous structures demonstrate a substantial improvement in the viability, adhesion, and proliferation of human umbilical vein endothelial cells (HUVECs) when incubated with the hydrogels. These findings present a significant advancement in the fabrication of hierarchically macro–micronanoporous hydrogels, with potential applications in the fields of tissue engineering and organoid development.

Photovoltaic arrays present multiple peaks characteristic under partial shading conditions (PSCs), bringing challenge of finding the global maximum power point (GMPP). Recently, the bio-inspired metaheuristics have been popularly applied to find the GMPP under PSCs, while they usually suffer from long convergence time and large power oscillations. Therefore, this paper proposes an improved white shark optimizer (IWSO) based MPPT algorithm under PSCs. The WSO algorithm is a novel metaheuristic and can find the GMPP quickly and accurately due to its flexibility and robustness. Furthermore, an improved method has been proposed, which dynamically adjusts the hierarchy in the white sharks during global exploration and local exploitation. Through this, the search scope for the GMPP is increased and the local exploitation is accelerated. To verify the performance and superiority of the IWSO based MPPT algorithm under PSCs, it is compared with existing metaheuristic based MPPT algorithms (particle swarm optimization, cuckoo search, grey wolf optimizer, and salp swarm optimization) by simulations and then evaluated by experiments. The proposed IWSO based MPPT algorithm shows excellent performance under different PSCs regarding tracking time, tracking efficiency and power oscillations.

Bio-oil is a major product from pyrolysis of biomass which serves as a carbon source to produce carbon material due to its high reactivity towards polymerization itself or cross-polymerization with other organic feedstocks. In this study, activation of polyaniline (PANI) mixed with wheat straw-derived bio-oil and K2C2O4at 800 °C was conducted, aiming to understand the effect of potential interactions of bio-oil with PANI on pore development of resulting activated carbon (AC). The results revealed cross-polymerization reactions between PANI and bio-oil during direct activation, which increased the yield of AC from 13.0% (calculated average) to 15.0%, the specific surface area from 1677.9 m2g−1(calculated average) to 1771.3 m2g−1, and the percentage of micropores from 94.3% to 97.1%. In addition, pre-polymerization of PANI and bio-oil at 200 °C before activation was also conducted. Such pretreatment could increase the AC yield from 13.0% to 23.3%, but the specific surface area decreased to 1381.8 m2g−1. The pre-polymerization formed the organics that were more resistant towards cracking/gasification, but introduced oxygen-rich functionalities. This made AC highly hydrophilic, rendering a much higher capability for adsorption of phenol despite the smaller specific surface area. Additionally, the AC with developed pore structures facilitated dispersion of nickel in Ni/AC and enhanced the catalytic activity for hydrogenation of o-chloronitrobenzene and vanillin.Keywords: Polyaniline; Bio-oil; Activation; Activated carbon; Pre-polymerization; Adsorption.

The micro-area characterization experiments like scanning Kelvin probe force microscope (SKPFM) and Kernel average misorientation have the defects of complex sample preparation and occasional errors in test results, which makes it impossible to accurately and quickly analyze the pitting behavior induced by inclusions in some cases, prompting attempts to turn to simulation calculation research. The method of calculating band structure and work function can be used to replace current-sensing atomic force microscopy and SKPFM to detect the potential and conductivity of the sample. The band structure results show that Al2O3inclusion is an insulator and non-conductive, and it will not form galvanic corrosion with the matrix. Al2O3inclusion does not dissolve because its work function is higher than that of the matrix. Moreover, the stress concentration of the matrix around the inclusion can be characterized by first-principles calculation coupled with finite element simulation. The results show that the stress concentration degree of the matrix around Al2O3inclusion is serious, and the galvanic corrosion is formed between the high and the low stress concentration areas, which can be used to explain the reason of the pitting induced by Al2O3inclusions.

Typical tomographic image reconstruction methods require that the imaged object is static and stationary during the time window to acquire a minimally complete data set. The violation of this requirement leads to temporal-averaging errors in the reconstructed images. For a fixed gantry rotation speed, to reduce the errors, it is desired to reconstruct images using data acquired over a narrower angular range, i.e., with a higher temporal resolution. However, image reconstruction with a narrower angular range violates the data sufficiency condition, resulting in severe data-insufficiency-induced errors. The purpose of this work is to decouple the trade-off between these two types of errors in contrast-enhanced computed tomography (CT) imaging. We demonstrated that using the developed data consistency constrained deep temporal extrapolation method (AIRPORT), the entire time-varying imaged object can be accurately reconstructed with 40 frames-per-second temporal resolution, the time window needed to acquire a single projection view data using a typical C-arm cone-beam CT system. AIRPORT is applicable to general non-sparse imaging tasks using a single short-scan data acquisition.

Diagnosability of a multiprocessor system is an important measure of the reliability of interconnection networks. System-level diagnosis is a primary strategy to identify the faulty processors in a multiprocessor system. Based on a sound assumption proposed by Zhu et al. recently, we proposed a new diagnosability named non-inclusion diagnosability and showed that the non-inclusion diagnosability tN(Qn)of the hypercube under the PMC model is 2n-2. That is, assume that if two vertex sets F1and F2are both consistent with a syndrome and F1⊂F2, then F2is not the faulty set which we are looking for; the faulty set Fis 1-step diagnosable if |F|⩽2n-2in Qnunder the PMC model.

Low-dose computed tomography (LDCT) imaging faces great challenges. Although supervised learning has revealed great potential, it requires sufficient and high-quality references for network training. Therefore, existing deep learning methods have been sparingly applied in clinical practice. To this end, this paper presents a novel Unsharp Structure Guided Filtering (USGF) method, which can reconstruct high-quality CT images directly from low-dose projections without clean references. Specifically, we first employ low-pass filters to estimate the structure priors from the input LDCT images. Then, inspired by classical structure transfer techniques, deep convolutional networks are adopted to implement our imaging method which combines guided filtering and structure transfer. Finally, the structure priors serve as the guidance images to alleviate over-smoothing, as they can transfer specific structural characteristics to the generated images. Furthermore, we incorporate traditional FBP algorithms into self-supervised training to enable the transformation of projection domain data to the image domain. Extensive comparisons and analyses on three datasets demonstrate that the proposed USGF has achieved superior performance in terms of noise suppression and edge preservation, and could have a significant impact on LDCT imaging in the future.

Multi-label classification remains a challenging task for high-dimensional data samples and their labels both increase the complexity of training models. In this paper, we propose a Robust Label and Feature Space Co-Learning method, referred to as RLFSCL, for multi-label classification. Different from traditional multi-label classification methods which focus on feature space learning through regression directly between data samples and labels, our proposed method can further learn robust low rank label space from this traditional regression method. Therefore, our RLFSCL can learn better low rank feature and label representations simultaneously in original noisy and high dimensional spaces. Experimental comparison on five benchmark datasets, including Rcv1s5, Cal500, and Corel16k4 shows that the proposed RLFSCL algorithm outperforms state-of-the-art multi-label classification methods. The code of RLFSCL is made available on https://github.com/JingChuanTang/RLFSCL.

Green growth policies aim to address both climate change and economic growth and are now prevalent throughout many economies. While green growth is sufficiently assessed in qualitative, case-study-based literature, quantitative and cross-country analyses are still limited. In response to this research deficit, our aim is twofold: (1) to develop a classification framework to quantitatively analyse green growth and (2) to identify key policy inputsand techno-economic or environmental outputsfor green growth through a novel taxonomy. We focus on the G7 countries, since they have, historically, tended to align their economic policies. We employ a machine-automated K-means clustering algorithm, as well as correlation analyses, to assess where green growth “win–wins,” or co-benefits to the economy and environment, might exist. Our findings suggest that enthusiasm should be tempered for public policy commitments for green growth; despite unified green growth policy in G7 countries—significant differences are observed for both policy inputs and environmental/economic outputs. As a result, we caution policymakers and researchers against drawing generalised conclusions about the effectiveness of green growth policies, even among highly developed economies. Finally, our research draws attention to data deficiencies which, evidently, reduce more robust assessment across countries and over time.

C-type lectins (CTLs) are an important family of pattern recognition receptors (PRRs) that regulate immune responses. The CTL5gene of the silkworm Bombyx moriL. (Lepidoptera: Bombycidae) encodes a protein comprised of 223 amino acids, containing a signal peptide and a carbohydrate recognition domain (CRD). Our previous study showed that CTL5 can facilitate the clearance of bacteria from larval hemocoel but the underlying mechanisms are unclear. In this study, we found that CTL5was mainly expressed in fourth-instar larvae, adult moths, and the larval epidermis. CTL5expression showed differential responses to both pathogenic stimuli and the molting hormone 20-hydroxyecdysone. The full-length (FL) and truncated (ΔN/ΔC/ΔNC) CTL5 recombinant proteins can bind to hemocytes, polysaccharides, bacteria, and spores of the entomopathogenic fungus Beauveria bassiana. Yeast 2-hybrid assays showed that the recombinant proteins can interact with integrin β2–β5 subunits. Recombinant proteins increased the phagocytic rate of hemocytes. Injection of recombinant CTL5 stimulated the expression of many immune genes in hemocytes, mainly antimicrobial peptides and immune signaling molecules. Additionally, transcriptomic sequencing of CTL5-stimulated hemocytes revealed 265 upregulated and 580 downregulated genes. Functional enrichment and the gene set enrichment analyses showed that differentially expressed genes were mainly enriched in innate immune responses and signaling. Our study suggests that CTL5 may act as an opsonin to enhance the clearance of pathogens by regulating both humoral and cellular responses.Graphical Abstract

Piezoelectric polymer films are forthcoming choices for self-powered portable flexible electronics due to instant mechanoelectrical transduction, ease of fabrication, and assembly for device integration. However, the low piezoelectricity of polymers in comparison with piezoelectric ceramics precludes their practical applications significantly. Here, we report an interesting method to fabricate piezoelectric poly(vinylidene fluoride) (PVDF) fiber mats with excellent piezoelectricity by collecting electrospun fibers using low-temperature electrolytes. Specifically, fiber collection assisted by liquid electrolytes enables the formation of piezoelectric PVDF crystals with zigzag conformation induced by strong solvent–electrolyte and dipole–ion interactions, as well as the immobilization of aligned dipoles at low temperature. Consequently, compared with conventional PVDF fibers collected by aluminum foils, those fiber mats electrospun using liquid electrolytes can generate an open-circuit voltage of 2.3 V under a pressure of 20 N at 1 Hz for an effective area of 1 cm2, showing a nearly eight-times improvement. In addition, the as-prepared piezoelectric fiber mats enable the conversion of mechanical energy into electricity with an instantaneous output power density of ∼16.2 mW/m2, which allows for self-powered sensing or energy harvesting. Such an electrospinning technology enables simple fabrication of high-performance piezoelectric polymer fiber mats with diverse surface microstructure for self-powered flexible electronics.