Current Limitations Research Articles

Dipole momenta and compositeness of the τ lepton at Belle II

The large number of τ leptons available at the Belle II experiment makes it possible to study their properties and the extent of their compositeness. We propose a strategy that relies on three observables defined in terms of elements of the polarization density matrix of the produced τ pairs, which we obtain via quantum tomography. We find that these observables can explore values of the magnetic dipole moment down to 6.3×10−4, which is 2 orders of magnitude better than the current experimental limit, constrain the electromagnetic radius below 4.3×10−3 fm, and exclude an electric dipole moment larger than 1.7×10−17 e cm. The quoted limits are at the 95% confidence level (CL) and are obtained for a benchmark integrated luminosity of 1 ab−1 and a Monte Carlo estimate of the statistical sensitivity. Published by the American Physical Society 2024

A Perspective on graphene junctions for recognition tunneling

Biopolymer sequencing with graphene edge-based tunnel junctions has the potential to overcome current limitations with the third generation of sequencing based on biological nanopores. Detection of nucleotides via (recognition) tunneling with noble metal break junctions shows promising results; however, the bulky nature and a range of physical and chemical instabilities of the electrodes prevent advancing toward long-read sequencing with single base-calling accuracy. Graphene edges as tunnel electrodes may overcome these limitations, with the possibility to reach true single-molecule readout, thanks to their 2D nature. Currently, the development of graphene tunnel sequencers faces challenges in terms of targeted chemical functionalization of the graphene edge to enable recognition tunneling and the eventual integration in a nanopore configuration to realize long-read sequencing of biopolymers. Herein, we discuss the current developments that encourage active research toward graphene edge junctions for single-molecule detection, recognition, and sequencing applications with nucleotides and deoxyribonucleic acid as example.

Assessing the potential of BirdNET to infer European bird communities from large-scale ecoacoustic data

1.Passive acoustic monitoring has become increasingly popular as a practical and cost-effective way of obtaining highly reliable acoustic data in ecological research projects. Increased ease of collecting these data means that, currently, the main bottleneck in ecoacoustic monitoring projects is often the time required for the manual analysis of passively collected recordings. In this study we evaluate the potential and current limitations of BirdNET-Analyzer v2.4, the most advanced and generic deep learning algorithm for bird recognition to date, as a tool to assess bird community composition through the automated analysis of large-scale ecoacoustic data.2.To this end, we study 3 acoustic datasets comprising a total of 629 environmental soundscapes collected in 194 different sites spread across a 19° latitude span in Europe. We analyze these soundscapes using both BirdNET and manual listening by local expert birders, and we then compare the results obtained through the two methods to evaluate the performance of the algorithm both at the level of each single vocalization and for entire recording sequences (1, 5 or 10 min).3.Since BirdNET provides a confidence score for each identification, minimum confidence thresholds can be used to filter out identifications with low scores, thus retaining only the most reliable ones. The volume of ecoacoustic data used in this study did not allow us to estimate species-specific minimum confidence thresholds for most taxa, so we instead used and evaluated global confidence thresholds selected for optimized results when consistently applied across all species.4.Our analyses reveal that BirdNET identifications can be highly reliable if a sufficiently high minimum confidence threshold is used. However, the inevitable trade-off between precision and recall does not allow to obtain satisfactory results for both metrics at the same time. We found that F1-scores remain moderate (<0.5) for all datasets and confidence thresholds studied, and that acoustic datasets of extended duration seem to be currently necessary for BirdNET to provide a reliable and minimally comprehensive picture of the target bird community. We estimate, however, that the usage of species- and context-specific minimum confidence thresholds would allow to substantially improve the global performance benchmarks obtained in this study.5.We conclude that a judicious use of AI-based identifications provided by BirdNET can represent a powerful method to assist in the assessment of bird community composition through the automated analysis of ecoacoustic data, especially when applied to acoustic datasets of extended duration.

Synchrosqueezing Voices Through Deep Neural Networks for Horizon Interpretation

Horizon picking stands as a crucial element in reservoir characterisation, yet it remains a labour-intensive process. The manual interpretation of horizons across thousands of vertical seismic slices in a 3D seismic survey significantly further amplifies the time and effort invested in this task. While several automatic methods have been developed for extracting horizons in seismic images, their effectiveness can be compromised in the presence of interruptions in lateral continuity, such as faults and noise. Additionally, closely spaced horizons pose a challenge, making it even more difficult to accurately depict their exact locations. For tracking the horizon surfaces through a 3D seismic volume, it is necessary to exploit other seismic attributes extracted from the 3D seismic data. We proposed to use spectral voice components together with the original seismic amplitudes to track target horizon surfaces. We generated the time-frequency spectrum using a high-resolution method namely the synchrosqueezing wavelet transform (SWT) method, and the real part of the complex SWT spectrum is the voice component. We imported the spectral voice component and the seismic amplitude into a neural network. A framework of deep convolutional neural network (dCNN) was adopted for tracking horizon surfaces within a 3D seismic volume. We demonstrated this application on a field seismic dataset where closely spaced thin layers are within a complex faulted formation with noisy and low signal to noise ratio seismic data. The integration of amplitude and phase within the voice component attribute demonstrates its efficacy in enhancing the quality of the generated horizons, particularly when compared to using only seismic amplitude for this task. A field data example from the F3 dataset showcases the capability of our method in accurately delineating horizons across fault surfaces and in close proximity to unconformities. This surpasses the current limitations of existing horizon-picking methods.

Designing meaningful continuous representations of T cell receptor sequences with deep generative models

T Cell Receptor (TCR) antigen binding underlies a key mechanism of the adaptive immune response yet the vast diversity of TCRs and the complexity of protein interactions limits our ability to build useful low dimensional representations of TCRs. To address the current limitations in TCR analysis we develop a capacity-controlled disentangling variational autoencoder trained using a dataset of approximately 100 million TCR sequences, that we name TCR-VALID. We design TCR-VALID such that the model representations are low-dimensional, continuous, disentangled, and sufficiently informative to provide high-quality TCR sequence de novo generation. We thoroughly quantify these properties of the representations, providing a framework for future protein representation learning in low dimensions. The continuity of TCR-VALID representations allows fast and accurate TCR clustering and is benchmarked against other state-of-the-art TCR clustering tools and pre-trained language models.

Comparative analysis of time sweep testing evaluation methods for the fatigue characterisation of aged bitumen

Ageing of bitumen changes its stiffness related properties and is thought to have a considerable impact on its fatigue performance. Time sweep tests are a commonly used methodology to evaluate the fatigue performance of bitumen over the course of its lifetime. This study comparatively evaluated the fatigue performance of six aged bitumen samples using various commonly employed time sweep testing-based approaches, including conventional methods (50% reduction in complex modulus and peak in phase angle) and newer methods (peak in S × N and two dissipated-energy-based approaches). The statistical analysis of the results illustrated that although the trends of fatigue life versus ageing levels were similar, different methods had significantly varying results. It was generally seen that ageing increased stiffness and the calculated fatigue life of bituminous binders improved when commonly applied strain levels of 5% and 7.5% were used. This result demonstrates the need to develop more robust methods to fully capture the true fatigue related deterioration of aged binders in the future. Among all the methods, the peak in S × N approach was found to be the most efficient based on the criteria used in the study and was the recommended approach considering current limitations. It showed no apparent defects and had the best correlations with other methods when the applied strains were 5% and 7.5%.

Battery Electric Vehicles: Travel Characteristics of Early Adopters

Do U.S. households with battery electric vehicles (BEVs) drive less or more than U.S. households with internal combustion engine vehicles (ICEVs)? Answering this question is important to policymakers and transportation planners concerned with reducing vehicle miles traveled and the emissions of greenhouse gases from transportation. So far, this question has not been answered satisfactorily, possibly because of the relatively low number of EVs in the U.S. until recently, but also because of methodological issues. In this paper, we aim to fill this gap by analyzing data from the 2017 National Household Travel Survey (NHTS). We apply propensity score matching (PSM), a quasi-experimental method, to examine the differences in self-reported annual mileage and calculated daily mileage for various trip purposes among households with only BEVs (BEV-only), households with both BEVs and ICEVs (BEV+), and households without BEVs (non-BEV households). Our findings indicate that households with BEVs drive fewer annual miles than non-BEV households, but typically travel no less than they do for daily activities. This apparent discrepancy is likely due to taking fewer longer trips because the public charging infrastructure was still in its infancy in 2017, and its reliability was questionable. As technological progress is helping to overcome current battery limitations, policymakers may consider measures for fostering fast charging technologies while pondering new measures to fund both the charging infrastructure and the road network.

Empirical calibration method for the thermal simulation of Cu47Ti34Zr11Ni8 single tracks in laser powder bed fusion

AbstractBulk metallic glasses (BMGs) are materials that, due to their amorphous microstructure, offer a unique combination of high strength, hardness, and elasticity, making them attractive for various applications. Using laser powder bed fusion (PBF-LB/M) enables overcoming the current limitations of BMGs in size and shape imposed by traditional manufacturing methods such as casting. Despite its potential, challenges such as porosity, (nano-) crystallization, and impurities affect the mechanical performance of additively manufactured BMGs. This study focuses on the Cu–Ti-based alloy Vit101, known for its higher strength and improved cost-effectiveness compared to Zr-based BMGs. In-situ high-speed pyrometry and thermal simulations of single tracks are employed to enhance the understanding of processing and controlling the thermal cycling of Vit101. The proposed experimental calibration is performed through an off-axis integration of the pyrometer, allowing for in-situ temperature measurements. The acquired data show sufficient congruence with the simulated cooling profiles. Minimal cooling rates in the range of 104 K/s were measured and simulated above the glass transition temperature, indicating a large leeway for further development of glass-forming alloys. Scan track widths are evaluated for validation, resulting in minor deviations between 0.47% and 3.17%. However, challenges emerge at high scanning speeds, leading to higher deviations attributed to balling phenomena, which are not considered in the numerical model.

Quantitative profiling N1-methyladenosine (m1A) RNA methylation from Oxford nanopore direct RNA sequencing data

With the recent advanced direct RNA sequencing technique that proposed by the Oxford Nanopore Technologies, RNA modifications can be detected and profiled in a simple and straightforward manner. Majority nanopore-based modification studies were devoted to those popular types such as m6A and pseudouridine. To address current limitations on studying the crucial regulator, m1A modification, we conceived this study. We have developed an integrated computational workflow designed for the detection of m1A modifications from direct RNA sequencing data. This workflow comprises a feature extractor responsible for capturing signal characteristics (such as mean, standard deviations, and length of electric signals), a single molecule-level m1A predictor trained with features extracted from the IVT dataset using classical machine learning algorithms, a confident m1A site selector employing the binomial test to identify statistically significant m1A sites, and an m1A modification rate estimator. Our model achieved accurate molecule-level prediction (Average AUC = 0.9689) and reliable m1A site detection and quantification. To show the feasibility of our workflow, we conducted a study on in vivo transcribed human HEK293 cell line, and the results were carefully annotated and compared with other techniques (i.e., Illumina sequencing-based techniques). We believed that this tool will enabling a comprehensive understanding of the m1A modification and its functional mechanisms within cells and organisms.

Immunomodulatory Precision: A Narrative Review Exploring the Critical Role of Immune Checkpoint Inhibitors in Cancer Treatment

An immune checkpoint is a signaling pathway that regulates the recognition of antigens by T-cell receptors (TCRs) during an immune response. These checkpoints play a pivotal role in suppressing excessive immune responses and maintaining immune homeostasis against viral or microbial infections. There are several FDA-approved immune checkpoint inhibitors (ICIs), including ipilimumab, pembrolizumab, and avelumab. These ICIs target cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), programmed cell death protein 1 (PD-1), and programmed death ligand 1 (PD-L1). Furthermore, ongoing efforts are focused on developing new ICIs with emerging potential. In comparison to conventional treatments, ICIs offer the advantages of reduced side effects and durable responses. There is growing interest in the potential of combining different ICIs with chemotherapy, radiation therapy, or targeted therapies. This article comprehensively reviews the classification, mechanism of action, application, and combination strategies of ICIs in various cancers and discusses their current limitations. Our objective is to contribute to the future development of more effective anticancer drugs targeting immune checkpoints.

An Overview Analysis of Current Research Status in Iron Oxides Reduction by Hydrogen

This paper focuses on the study of current knowledge regarding the use of hydrogen as a reducing agent in the metallurgical processes of iron and steel production. This focus is driven by the need to introduce environmentally suitable energy sources and reducing agents in this sector. This theoretical study primarily examines laboratory research on the reduction of Fe-based, metal-bearing materials. The article presents a critical analysis of the reduction in iron oxides using hydrogen, highlighting the advantages and disadvantages of this method. Most experimental facilities worldwide employ their unique original methodologies, with techniques based on Thermogravimetric analysis (TGA) devices, fluidized beds, and reduction retorts being the most common. The analysis indicates that the mineralogical composition of the Fe ores used plays a crucial role in hydrogen reduction. Temperatures during hydrogen reduction typically range from 500 to 900 °C. The reaction rate and degree of reduction increase with higher temperatures, with the transformation of wüstite to iron being the slowest step. Furthermore, the analysis demonstrates that reduction of iron ore with hydrogen occurs more intensively and quickly than with carbon monoxide (CO) or a hydrogen/carbon monoxide (H2/CO) mixture in the temperature range of 500 °C to 900 °C. The study establishes that hydrogen is a superior reducing agent for iron oxides, offering rapid reduction kinetics and a higher degree of reduction compared to traditional carbon-based methods across a broad temperature range. These findings underscore hydrogen’s potential to significantly reduce greenhouse gas emissions in the steel production industry, supporting a shift towards more sustainable manufacturing practices. However, the implementation of hydrogen as a primary reducing agent in industrial settings is constrained by current technological limitations and the need for substantial infrastructural developments to support large-scale hydrogen production and utilization.

Sediment control and flow redistribution with submerged vanes: a review

ABSTRACT The most challenging issues in rivers include sediment management, outer bank erosion, intake choking, channel bed shoaling, and river meandering. This paper provides a concise review of the newly developed sediment and flow control technique known as the Iowa vane or submerged vane. Submerged vanes are small flow training structures designed to redistribute flow and sediment within the channel cross-section. The structural stability and economic feasibility of submerged vanes, which distinguish them from conventional methods such as dikes and groins, have inspired many researchers to study their use and efficiency in river management over many decades. Various hydrodynamic characteristics, such as flow structure, sediment motion, vortex generation, and scouring around submerged vanes and arrays of vanes, have been reviewed. Additionally, various vane parameters that influence these characteristics are also explained. This paper also underscores current limitations in understanding the flow and sediment behavior around submerged vanes, while also providing recommendations for future research in the field.

Microbial- and host immune cell-derived extracellular vesicles in the pathogenesis and therapy of periodontitis: A narrative review.

Periodontitis is a chronic inflammatory disease caused by dysbiotic biofilms and destructive host immune responses. Extracellular vesicles (EVs) are circulating nanoparticles released by microbes and host cells involved in cell-to-cell communication, found in body biofluids, such as saliva and gingival crevicular fluid (GCF). EVs are mainly involved in cell-to-cell communication,and may hold promise for diagnostic and therapeutic purposes. Periodontal research has examined the potential involvement of bacterial- and host-cell-derived EVs in disease pathogenesis, diagnosis, and therapy, but data remains scarce on immune cell- or microbial-derived EVs. In this narrative review, we first provide an overview of the role of microbial and host-derived EVs on disease pathogenesis. Recent studies reveal that Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans-derived outer membrane vesicles (OMVs) can activate inflammatory cytokine release in host cells, while M1 macrophage EVs may contribute to bone loss. Additionally, we summarised current invitro and pre-clinical research on the utilisation of immune cell and microbial-derived EVs as potential therapeutic tools in the context of periodontal treatment. Studies indicate that EVs from M2 macrophages and dendritic cells promote bone regeneration in animal models. While bacterial EVs remain underexplored for periodontal therapy, preliminary research suggests that P. gingivalis OMVs hold promise as vaccine candidates. Finally, we acknowledge the current limitations present in the field of translating immune cell derived EVs and microbial derived EVs in periodontology. It is concluded that microbial and host immune cell-derived EVs have a role in periodontitis pathogenesis and hence may be useful for studying disease pathophysiology, and as diagnostic and treatment monitoring biomarkers.

Study and Review of GupShup- A Chat Application

In the digital age, the demand for secure and private messaging platforms has surged, paralleling the exponential growth of online interactions. This research introduces Secure GupShup, a groundbreaking application designed to address the paramount concerns surrounding user privacy and data security. In an environment where information confidentiality is of utmost importance, Secure GupShup stands out by providing a feature-rich experience that includes private and public chat rooms, with a distinctive emphasis on security through the implementation of instant disappearing messages. The core innovation of Secure GupShup lies in its implementation of instant disappearing messages, a feature designed to augment user privacy. By ensuring that messages automatically vanish after a predetermined time, the application adds an extra layer of security, preventing unauthorized access to sensitive information. This not only grants users greater control over their conversations but also fosters an environment where information is transient, mitigating the risks associated with data retention. The research delves into the intricate architecture of Secure GupShup, exploring the amalgamation of cutting-edge encryption protocols and intuitive user interface design. The application's robust security measures, coupled with its user-friendly interface, position Secure GupShup as a formidable contender in the realm of secure communication applications. As the digital landscape continues to evolve, Secure GupShup signifies a pivotal step towards meeting the escalating demands for privacy and security in the realm of digital communication. The incorporation of end-to-end encryption protocols ensures that messages exchanged within Secure GupShup remain private and secure. Users can communicate confidently, knowing that their conversations are shielded from unauthorized access, providing a heightened level of privacy. The inclusion of disappearing messages adds an extra layer of security by automatically removing sensitive content after a designated time period. This feature not only protects user data from long-term exposure but also aligns with the evolving need for ephemeral communication in digital platforms. While acknowledging the current limitations, the proposed solutions aim to address these challenges and enhance the overall functionality of Secure GupShup. The outlined future work envisions continued improvements, embracing emerging technologies and user preferences to maintain Secure GupShup's position as a leading secure communication platform..

Harmonising light and structure: exploring ZnO/MOF composite photocatalysts for environmental remediations

Harmonising light and structure: exploring ZnO/MOF composite photocatalysts for environmental remediations

Near-Infrared-II Imaging Revealed Hypothermia Regulates Neuroinflammation Following Brain Injury by Increasing the Glymphatic Influx.

Advanced in vivo imaging techniques have facilitated the comprehensive visual exploration of animal biological processes, leading to groundbreaking discoveries such as the glymphatic system. However, current limitations of macroscopic imaging techniques impede the precise investigation of physiological parameters regulating this specialized lymphatic transport system. While NIR-II fluorescence imaging has demonstrated advantages in peripheral lymphatic imaging, there are few reports regarding its utilization in the glymphatic system. To address this, a noninvasive transcranial macroscopic NIR-II fluorescence imaging model is developed using a cyanine dye-protein coupled nanoprobe. NIR-II imaging with high temporal and spatial resolution reveals that hypothermia can increase the glymphatic influx by reducing the flow rate of cerebrospinal fluid. In addition, respiratory rate, respiratory amplitude, and heart rate all play a role in regulating the glymphatic influx. Thus, targeting the glymphatic influx may alter the trajectory of immune inflammation following brain injury, providing therapeutic prospects for treating brain injury with mild hypothermia.

Newborn Screening for Congenital Cytomegalovirus

What Is the Issue? Congenital cytomegalovirus (cCMV) is estimated to affect between 0.2% and 2.4% of newborns worldwide, and may cause long-term effects, including hearing loss and neurodevelopmental disability. Newborn screening for cCMV can identify affected neonates and provide an opportunity for early treatment, which may reduce any long-term effects from infection. We wanted to know if universal newborn screening is a clinically effective and cost-effective intervention for identifying and managing cCMV. What Did We Do? We identified and summarized published literature comparing the clinical effectiveness and cost-effectiveness of universal newborn screening with either targeted newborn screening or no screening for congenital cytomegalovirus in neonates. We also identified and summarized published, evidence-based guidelines that make recommendations concerning the use of newborn screening for congenital cytomegalovirus to help inform decisions considering the use of this intervention. An information specialist searched for peer-reviewed and grey literature sources published between January 1, 2014, and March 19, 2024. The search was limited to English-language documents. One reviewer screened articles for eligibility based on predefined criteria, critically appraised the included studies, and narratively summarized the findings. What Did We Find? Evidence from 1 prospective cohort study in the US found that, compared to universal newborn screening for cCMV, targeted newborn screening failed to identify a significant proportion of neonates who developed hearing loss associated with infection. Three cost-effectiveness evaluations concluded that universal newborn screening for cCMV was cost-effective when compared to targeted newborn screening or no screening. None of these analyses were specific to the Canadian context. While 1 of 3 evidence-based guidelines identified by this review makes a recommendation favouring universal newborn screening for cCMV, 2 evidence-based guidelines recommend against the implementation of universal newborn screening for cCMV (including 1 from the Canadian context), generally citing a lack of sufficient clinical evidence. What Does This Mean? The included cost-effectiveness studies and evidence-based guidelines in this report emphasize that limited clinical evidence is currently available to inform decision-making concerning newborn screening for cCMV. Jurisdictions where universal newborn screening for cCMV has been implemented provide an opportunity for clinical research to support and inform future decision-making. The current limitation of available clinical data describing newborn screening for cCMV will require decision-makers to draw from a broader set of inputs and sources than those available from empirical studies.

Propagation Mechanism and Suppression Strategy of DC Faults in AC/DC Hybrid Microgrid

Due to their efficient renewable energy consumption performance, AC/DC hybrid microgrids have become an important development form for future power grids. However, the fault response will be more complex due to the interconnected structure of AC/DC hybrid microgrids, which may have a serious influence on the safe operation of the system. Based on an AC/DC hybrid microgrid with an integrated bidirectional power converter, research on the interaction impact of faults was carried out with the purpose of enhancing the safe operation capability of the microgrid. The typical fault types of the DC sub-grid were selected to analyze the transient processes of fault circuits. Then, AC current expressions under the consideration of system interconnection structure were derived and, on this basis, we obtained the response results of non-fault subnets under the fault process, in order to reveal the mechanism of DC fault propagation. Subsequently, a current limitation control strategy based on virtual impedance control is proposed to address the rapid increase in the DC fault current. On the basis of constant DC voltage control in AC/DC hybrid microgrids, a virtual impedance control link was added. The proposed control strategy only needs to activate the control based on the change rate of the DC current, without additional fault detection systems. During normal operations, virtual impedance has a relatively small impact on the steady-state characteristics of the system. In the case of a fault, the virtual impedance resistance value is automatically adjusted to limit the change rate and amplitude of the fault current. Finally, a DC fault model of the AC/DC hybrid microgrid was built on the RTDS platform. The simulation and experimental results show that the control strategy proposed in this paper can reduce the instantaneous change rate of the fault state current from 19.1 kA/s to 2.73 kA/s, and the error between the calculated results of equivalent modeling and simulation results was within 5%. The obtained results verify the accuracy of the mathematical equivalent model and the effectiveness of the proposed current limitation control strategy.

Evaluation of minimally invasive esthetic crown lengthening using an open flap versus flapless surgical approach: A randomized controlled clinical trial.

Esthetic crown lengthening (ECL) is commonly advocated to treat patients with altered passive eruption (APE). Since the introduction of the minimally invasive surgical concept, a limited number of studies have investigated this technique in a standardized manner, with further studies required to verify the validity and predictability of the minimally invasive FL-technique. The current randomized trial compares a minimally invasive (ECL), using piezosurgery with flapless-approach (FL), versus an open-flap (OF) approach in the management of patients with APE Type 1B. Twenty-four patients diagnosed with APE Type 1B were randomly assigned into test (FL) with tunneling approach or control (OF) group with minimally invasive flap reflection (n = 12/group). Postoperative pain was assessed during the first 48 h. Gingival margin (GM) level relative to a custom-made stent (rGM) and patient satisfaction were assessed preoperative, immediately after surgery, at 3 and 6 months postsurgically. Postoperative swelling was reported for the first week postsurgically. Plaque index (PI), bleeding on probing (BoP), clinical attachment level (CAL), pocket depth (PD) and pink esthetic score (PES), were evaluated at baseline and 6 months. Linear regression analysis was conducted for pain. OF-group reported significantly higher pain and swelling scores than FL-group during the first 48 h (p < 0.05). FL-group showed no significant differences regarding rGM between 3 and 6 months, in contrast to OF-group, where a significant decrease in rGM was notable (p < 0.05). No significant differences in PI, BoP, CAL, PD, PES, and patient satisfaction scores were evident between groups (p > 0.05). Regression analysis demonstrated that treatment and gender were significant predictors for pain (p < 0.05). Within the current study's limitations, piezo-surgical ECL with FL-approach presented significantly lower postoperative pain, swelling, and early GM stability compared to OF-approach. Piezosurgical ECL with a FL-approach can be considered a predictable technique with advantages over the OF-approach in the management of patients with APE Type1B.

Strong Local Polarization Fluctuations Enabled High Electrostatic Energy Storage in Pb-Free Relaxors.

Electrostatic energy-storage ceramic capacitors are essential components of modern electrified power systems. However, improving their energy-storage density while maintaining high efficiency to facilitate cutting-edge miniaturized and integrated applications remains an ongoing challenge. Herein, we report a record-high energy-storage density of 20.3 J cm-3 together with a high efficiency of 89.3% achieved by constructing a relaxor ferroelectric state with strongly enhanced local polarization fluctuations. This is realized by incorporating highly polarizable, heterovalent, and large-sized Zn and Nb ions into a Bi0.5Na0.5TiO3-BaTiO3 ferroelectric matrix with very strong tetragonal distortion. Element-specific local structure analysis revealed that the foreign ions strengthen the magnitude of the unit-cell polarization vectors while simultaneously reducing their orientation anisotropy and forming strong fluctuations in both magnitude and orientation within 1-3 nm polar clusters. This leads to a particularly high polarization variation (ΔP) of 72 μC cm-2, low hysteresis, and a high effective polarization coefficient at a high breakdown strength of 80 kV mm-1. This work has surpassed the current energy density limit of 20 J cm-3 in bulk Pb-free ceramics and has demonstrated that controlling the local structure via the chemical composition design can open up new possibilities for exploring relaxors with high energy-storage performance.