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Objective Arthrodesis, usage of metallic implants for internal fixation, is commonly employed as the primary treatment modality for Müller‐Weiss disease (MWD). Nevertheless, the efficacy of the current methods of fixation leaves room for improvement. Inadequate fixation strength and the risk of fixation failure are both critical concerns requiring attention. This study explored the clinical effects of implementing a modified fixation technique in talonavicular arthrodesis for the treatment of MWD. Methods A total of 14 cases diagnosed with MWD undergoing talonavicular (TN) arthrodesis from January 2021 toMarch 2023 were included in the retrospective study. The fixation method for fusion involved the use of screws, with additional support from the shape‐memory alloy (SMA) staple. Relevant clinical outcomes and complications were evaluated preoperatively and postoperatively. Paired‐samples t‐test was used for all data comparisons. Results Radiographic evidence confirmed solid fusion, and follow‐up evaluations showed satisfactory results in all cases. The American Orthopedic Foot and Ankle Society (AOFAS) scores were elevated from 32.21 ± 4.0 (range: 22–38) preoperatively to 86.5 ± 2.7 (range: 81–90) postoperatively (p

Lithium-ion batteries (LIBs) are widely used as important energy storage and energy supply devices. The porous design and heteroatomization modification of carbon-based anode materials are crucial for achieving high-capacity and reversible energy storage in LIBs. Sol-gel method and pyrolysis treatment were used to obtain silica/silver composite particles used as templates. Polyphosphazene-coated silica/silver composite composite carbon materials (SiO2/Ag@PZS-C) were synthesized through in-situ self-assembly and carbonization of polyphosphazene. The electrochemical behavior and lithium storage mechanism of SiO2/Ag@PZS-C was also studied. The results reveal that the composite exhibited high specific capacity, stable cycling and superior rate performance. The double modification of silver nanoparticles and polyphosphazene carbon significantly improves the conductivity of silica and reduces the volume change. Moreover, the carbon shell of polyphosphazene facilitated the formation of a stable solid electrolyte interface film (SEI), preventing direct contact between the active material and the electrolyte, thereby substantially enhancing lithium storage performance.

Abstract Background Currently, there are no optimal biomarkers available for distinguishing patients who will respond to immune checkpoint inhibitors (ICIs) therapies. Consequently, the exploration of novel biomarkers that can predict responsiveness to ICIs is crucial in the field of immunotherapy. Methods We estimated the proportions of 22 immune cell components in 10 cancer types (6,128 tumors) using the CIBERSORT algorithm, and further classified patients based on their tumor immune cell proportions in a pan-cancer setting using k-means clustering. Differentially expressed immune genes between the patient subgroups were identified, and potential predictive biomarkers for ICIs were explored. Finally, the predictive value of the identified biomarkers was verified in patients with urothelial carcinoma (UC) and esophageal squamous cell carcinoma (ESCC) who received ICIs. Results Our study identified two subgroups of patients with distinct immune infiltrating phenotypes and differing clinical outcomes. The patient subgroup with improved outcomes displayed tumors enriched with genes related to immune response regulation and pathway activation. Furthermore, CCL5 and CSF2 were identified as immune-related hub-genes and were found to be prognostic in a pan-cancer setting. Importantly, UC and ESCC patients with high expression of CCL5 and low expression of CSF2 responded better to ICIs. Conclusion We demonstrated CCL5 and CSF2 as potential novel biomarkers for predicting the response to ICIs in patients with UC and ESCC. The predictive value of these biomarkers in other cancer types warrants further evaluation in future studies.

Abstract Processing spatiotemporal data sources with both high spatial dimension and rich temporal information is a ubiquitous need in machine intelligence. Recurrent neural networks in the machine learning domain and bio-inspired spiking neural networks in the neuromorphic computing domain are two promising candidate models for dealing with spatiotemporal data via extrinsic dynamics and intrinsic dynamics, respectively. Nevertheless, these networks have disparate modeling paradigms, which leads to different performance results, making it hard for them to cover diverse data sources and performance requirements in practice. Constructing a unified modeling framework that can effectively and adaptively process variable spatiotemporal data in different situations remains quite challenging. In this work, we propose hybrid spatiotemporal neural networks created by combining the recurrent neural networks and spiking neural networks under a unified surrogate gradient learning framework and a Hessian-aware neuron selection method. By flexibly tuning the ratio between two types of neurons, the hybrid model demonstrates better adaptive ability in balancing different performance metrics, including accuracy, robustness, and efficiency on several typical benchmarks, and generally outperforms conventional single-paradigm recurrent neural networks and spiking neural networks. Furthermore, we evidence the great potential of the proposed network with a robotic task in varying environments. With our proof of concept, the proposed hybrid model provides a generic modeling route to process spatiotemporal data sources in the open world.

Abstract Background Oral cancer is one of the most common cancers in China and seriously threaten life and health of Chinese people. We analysed the trends and disparities of oral cancer mortality rates and the disease burden of oral cancer in China from 2006 to 2021 to provide a reference for its prevention and control. Methods Annual death data for oral cancer was gleaned from the China Death Surveillance Database. The age-standardized mortality rate (ASMR), annual percentage change (APC), and average APC (AAPC) were used to analyze the trend of mortality. Loss of life expectancy (LLE) and years of life lost (YLL) were adopted to assess disease burden. Results From 2006 to 2021, the overall ASMR of oral cancer lightly declined (AAPC: − 0.97%; 95% CI: − 1.89%, − 0.04%), and the similar trend was observed among females (AAPC: − 1.22%; 95% CI: − 1.89%, − 0.55%). The ASMR of males was 2.31–3.16 times higher than that of females per year. The median of LLE for overall, males and females caused by oral cancer from 2006 to 2021 were 0.05, 0.06 and 0.03 years, respectively. There was a decrease of standardized YLL rate from 2006 to 2021 for overall (AAPC: − 1.31%, 95% CI: − 2.24% ~ − 0.37%) and for female (AAPC: − 1.63%, 95% CI: − 2.30% ~ − 0.95%). ASMR in urban areas was 1.02–1.28 times higher than that in rural areas from 2006 to2011, but 0.85–0.97 times lower in urban areas than that in rural areas from 2018 to 2021. The disease burden was higher in urban areas than in rural areas in 2006, whereas the reverse was observed in 2021. Conclusions There are severe health gaps and disparities in trends between sexes and different areas in China. Males and rural populations need to be focused on targeted interventions for the main influencing factors.

Abstract Background Glycerophospholipids (GPLs) are essential for cell membrane structure and function. Sphingomyelin and its metabolites regulate cell growth, apoptosis, and stress responses. This study aimed to investigate lipid metabolism in patients experiencing sudden sensorineural hearing loss across all frequencies (AF-SSNHL). Methods The study included 60 patients diagnosed with unilateral AF-SSNHL, among whom 30 patients had a level of hearing improvement ≥ 15 dB after 6 months of follow-up. A propensity score-matched (2:1) control group was used. Liquid chromatography‒mass spectrometry based untargeted lipidomics analysis combined with multivariate statistics was performed to investigate the lipids change. The “lipidome” R package and weighted gene co-expression network analysis (WGCNA) were utilised to assess the lipids’ structural features and the association between lipids and hearing. Results Lipidomics successfully differentiated the AF-SSNHL group from the control group, identifying 17 risk factors, mainly including phosphatidylcholine (PC), phosphatidylethanolamine (PE), and related metabolites. The ratios of lysophosphatidylcholine/PC, lysophosphatidylethanolamine/PE, and lysodimethylphosphatidylethanolamine/PE were upregulated, while some glycerophospholipid (GPL)-plasmalogens were downregulated in the AF-SSNHL group, indicating abnormal metabolism of GPLs. Trihexosylceramide (d34:1), PE (18:1e_22:5), and sphingomyelin (d40:3) were significantly different between responders and nonresponders, and positively correlated with hearing improvement. Additionally, the results of the WGCNA also suggested that partial GPL-plasmalogens were positively associated with hearing improvement. Conclusion AF-SSNHL patients exhibited abnormally high blood lipids and pronounced GPLs metabolic abnormalities. Sphingolipids and GPL-plasmalogens had an association with the level of hearing improvement. By understanding the lipid changes, clinicians may be able to predict the prognosis of hearing recovery and personalize treatment approaches.

Abstract Aiming at the problem of efficient and reliable transmission for communication system in complex electromagnetic environment, an anti‐interference decision‐making method for communication waveform based on collaborative filtering (CF) is proposed here. The required minimum signal‐to‐noise ratio to meet a specific bit error rate is adopted as a key indicator to evaluate the performance of certain waveform–channel combinations. The main challenge that is solved is to predict transmission performance ratings that cannot be obtained in practice. With CF of waveform features and interference features, the missing training data can be accurately predicted. The convergence speed and prediction accuracy of the proposed algorithm are verified by simulation, and the influence of different feature quantities and different data deficiency degrees on the stability and accuracy of the algorithm is discussed.

Introduction Elderly patients are at a high risk of postoperative delirium (POD), leading to increased postoperative morbidity and mortality. The use of dexmedetomidine and depth of anaesthesia may influence POD. This study aims to determine the effects of dexmedetomidine infusion versus normal saline placebo during light versus deep anaesthesia on POD among elderly patients undergoing major non-cardiac surgery.Methods and analysis This prospective, multicentre, randomised, controlled, factorial trial will be conducted at three tertiary hospitals in Jiangsu, China. We will recruit a total of 420 patients who are at least 60 years old and undergoing major non-cardiac surgery (thoracic, abdominal, urology, orthopaedic and spine surgery) under general anaesthesia. Patients will be randomised (1:1:1:1) to receive one of four anaesthesia regimens: (1) dexmedetomidine and light anaesthesia, (2) dexmedetomidine and deep anaesthesia, (3) placebo and light anaesthesia or (4) placebo and deep anaesthesia. Dexmedetomidine will be infused at 0.5 µg/kg/h throughout surgery, and intraoperative bispectral index target will be 55 for light anaesthesia and 40 for deep anaesthesia. The primary outcome is the occurrence of POD during the first 7 days postoperatively or until hospital discharge, assessed using the 3-min Confusion Assessment Method two times per day. The secondary outcomes include days with POD, type of POD, pain scores at rest and on movement at 24 and 48 hours postoperatively, patient-controlled intravenous fentanyl consumption during 0–24 and 24–48 hours postoperatively, hypotension, bradycardia, postoperative nausea and vomiting, non-delirium complications, length of postoperative hospital stay, 30-day cognitive function and 30-day mortality. Data will be analysed on a modified intention-to-treat basis.Ethics and dissemination This trial was approved by the Ethics Committee of the First Affiliated Hospital of Soochow University and each participating centre. The trial results will be published in a peer-reviewed journal.Trial registration Chinese Clinical Trial Registry (ChiCTR2300073271)

Sensorineural hearing loss (SNHL) is the most common type of hearing loss worldwide. The primary mechanism is oxidative injury to the cochlea as a result of oxidative stress. Therefore, exploring antioxidant strategies is particularly important in addressing SNHL.Thioredoxin-interacting protein (TXNIP) is an upstream target of oxidative stress-induced damage, and the NOD-like receptor protein 3 (NLRP3) and NF-κB pathways may be the main downstream molecular pathways, but this has not been reported in SNHL. Therefore, we investigated the molecular mechanism and role of TXNIP in oxidative stress injury induced by H2O2 in the HEI-OC1 auditory cells. To induce oxidative stress, HEI-OC1 cells were treated with H2O2. The TXNIP expression was measured by western blotting and Immunofluorescence. Intracellular TXNIP was knocked down using small interfering RNAs (siRNAs). Cell viability was measured by CCK8, total intracellular reactive oxygen species (ROS) by DCFH-DA, mitochondrial ROS by Mito-SOX, NLRP3, pro-caspase-1, total p65 NF-κB, and phospho-p65 NF-κB expression were measured by western blotting. Statistical analyses were performed using one-way analysis of variance, and p

Abstract Pyroptosis may play an important role in the resistance of ovarian cancer (OC) to chemotherapy. However, the mechanism by which pyroptosis modulation can attenuate chemotherapy resistance has not been comprehensively studied in OC. Here, we demonstrated that RAS‐associated C3 botulinum toxin substrate 1 (RAC1) is highly expressed in OC and is negatively correlated with patient outcomes. Through cell function tests and in vivo tumor formation tests, we found that RAC1 can promote tumor growth by mediating paclitaxel (PTX) resistance. RAC1 can mediate OC progression by inhibiting pyroptosis, as evidenced by high‐throughput automated confocal imaging, the release of lactate dehydrogenase (LDH), the expression of the inflammatory cytokines IL‐1β/IL‐18 and the nucleotide oligomerization domain‐like receptor family pyrin domain‐containing 3 (NLRP3) inflammasome. Mechanically, RNA‐seq, gene set enrichment analysis (GSEA), coimmunoprecipitation (Co‐IP), mass spectrometry (MS), and ubiquitination tests further confirmed that RAC1 inhibits caspase‐1/gasdermin D (GSDMD)‐mediated canonical pyroptosis through the P21‐activated kinase 4 (PAK4)/mitogen‐activated protein kinase (MAPK) pathway, thereby promoting PTX resistance in OC cells. Finally, the whole molecular pathway was verified by the results of in vivo drug combination tests, clinical specimen detection and the prognosis. In summary, our results suggest that the combination of RAC1 inhibitors with PTX can reverse PTX resistance by inducing pyroptosis through the PAK4/MAPK pathway.

Objective: Hashimoto’s thyroiditis is an inflammatory disease, and research suggests that a low-carbohydrate diet may have potential anti-inflammatory effects. This study aims to utilize Dixon-T2-weighted imaging (WI) sequence for a semi-quantitative assessment of the impact of a low-carbohydrate diet on the degree of thyroid inflammation in patients with Hashimoto’s thyroiditis. Methods: Forty patients with Hashimoto’s thyroiditis were recruited for this study and randomly divided into two groups: one with a normal diet and the other with a low-carbohydrate diet. Antibodies against thyroid peroxidase (TPOAb) and thyroglobulin (TgAb) were measured for all participants. Additionally, thyroid water content was semi-quantitatively measured using Dixon-T2WI. The same tests and measurements were repeated for all participants after 6 months. Results: After 6 months of a low-carbohydrate diet, patients with Hashimoto’s thyroiditis showed a significant reduction in thyroid water content (94.84 ± 1.57% vs 93.07 ± 2.05%, P < 0.05). Concurrently, a decrease was observed in levels of TPOAb and TgAb (TPOAb: 211.30 (92.63–614.62) vs 89.45 (15.9–215.67); TgAb: 17.05 (1.47–81.64) vs 4.1 (0.51–19.42), P < 0.05). In contrast, there were no significant differences in thyroid water content or TPOAb and TgAb levels for patients with Hashimoto’s thyroiditis following a normal diet after 6 months (P < 0.05). Conclusion: Dixon-T2WI can quantitatively assess the degree of thyroid inflammation in patients with Hashimoto’s thyroiditis. Following a low-carbohydrate diet intervention, there is a significant reduction in thyroid water content and a decrease in levels of TPOAb and TgAb. These results suggest that a low-carbohydrate diet may help alleviate inflammation in patients with Hashimoto’s thyroiditis.

Abstract The strain clamps and leading wires are important components that connect conductors on overhead transmission lines and conduct current. During operation, poor contact between these components can cause abnormal overheating, leading to electric failures and threatening power system reliability. Recently, the use of unmanned aerial vehicles equipped with infrared thermal imagers for strain clamp and leading wire maintenance has become increasingly popular. Deep learning‐based image recognition shows promising prospects for intelligent fault diagnosis of overheating faults. A pre‐treatment method is proposed based on dynamic histogram equalisation to enhance the contrast of infrared images. The DeepLab v3+ network, loss function, and existing networks with different backbones are compared. The DeepLab v3+ network with ResNet101 and convolutional block attention module added, and the Focal Loss function achieved the highest performance with an average pixel accuracy of 0.614, an average intersection over union (AIoU) of 0.567, an F1 score of 0.644, and a frequency weighted intersection over union of 0.594 on the test set. The optimised Atrous rates has increased the AIoU by 12.91%. Moreover, an intelligent diagnosis scheme for evaluating the defect state of the strain clamps and leading wires is proposed and which achieves a diagnostic accuracy of 91.0%.

Abstract Objective Fluorine‐18‐fluorodeoxyglucose–positron emission tomography (FDG‐PET) is routinely used for presurgical evaluation in many epilepsy centers. Hypometabolic characteristics have been extensively examined in prior studies, but the metabolic patterns associated with specific pathological types of drug‐resistant epilepsy remain to be fully defined. This study was developed to explore the relationship between metabolic patterns or characteristics and surgical outcomes in type I and II focal cortical dysplasia (FCD) patients based on results from a large cohort. Methods Data from individuals who underwent epilepsy surgery from 2014 to 2019 with a follow‐up duration of over 3 years and a pathological classification of type I or II FCD in our hospital were retrospectively analyzed. Hypometabolic patterns were quantitatively identified via statistical parametric mapping (SPM) and qualitatively analyzed via visual examination of PET‐MRI co‐registration images. Univariate analyses were used to explore the relationship between metabolic patterns and surgical outcomes. Results In total, this study included data from 210 patients. Following SPM calculations, four hypometabolic patterns were defined including unilobar, multi‐lobar, and remote patterns as well as cases where no pattern was evident. In type II FCD patients, the unilobar pattern was associated with the best surgical outcomes (p = 0.014). In visual analysis, single gyrus (p = 0.032) and Clear‐cut hypometabolism edge (p = 0.040) patterns exhibited better surgery outcomes in the type II FCD group. Conclusions PET metabolic patterns are well‐correlated with the prognosis of type II FCD patients. However, similar correlations were not observed in type I FCD, potentially owing to the complex distribution of the epileptogenic region. Plain Language Summary In this study, we demonstrated that FDG‐PET was a crucial examination for patients with FCD, which was a common cause of epilepsy. We compared the surgical prognosis for patients with different hypometabolism distribution patterns and found that clear and focal abnormal region in PET was correlated with good surgical outcome in type II FCD patients.

In previous studies, the implementation of vegetation structure information remains underutilized during the assessment of burn severity. A PolSAR-based burn severity assessment model was proposed by incorporating polarimetric decomposition features. Based on coherence matrix, three polarimetric decomposition features (i.e. Entropy, Anisotropy, and Alpha) which might be related with some field variables of burn severity (e.g. percent foliage altered, percent change in cover, percent canopy mortality, and percent tree mortality) were extracted. Then, a sensitivity analysis of 20 PolSAR features was performed and a principal component analysis (PCA) was applied. Finally, the combination of polarimetric decomposition features and new PCA vectors were used as inputs and CBI values as outputs of random forest algorithm to assess burn severity. The Jinyun Mountain in the Chongqing municipality of China was used as study area and the C-band of dual-polarization SAR data acquired from Sentinel-1 satellite were used as remotely sensed data. The sensitivity analysis of PolSAR features showed that H, A, and α features exhibited higher correlations with CBI values, compared to SAR indices. For proposed model, the R was 0.60 and the RMSE was 0.55. This study offered a new research perspective for future investigations on PolSAR-based burn severity assessment of wildfires.

Backgroud Li-Fraumeni syndrome is a hereditary tumor syndrome characterized by an elevated risk of malignancy, particularly acute lymphoblastic leukemia (ALL), which can be caused by the heterozygous germline mutation. TP53 gene germline mutation is considered a potential risk factor and crucial prognostic parameter for acute leukemia development and diagnosis, but rarely occurs in adults, and its specific pathogenic significance in acute leukemia is unclear.Case presentation We describes a case of a 45-year-old woman diagnosed with ALL. Whole-exome sequencing approach identified one of the TP53 germline mutations from her bone marrow sample with possible pathogenic significance, c.848G>A (p.Arg283His) heterozygous missense mutation located on exon 8, which was further verified in her hair, oral mucous and nail samples. Family pedigree screening revealed that the same TP53 genetic variant was present in the patient's father and non-donor son, whereas not in the donor. Digital PCR observed that this point mutation frequency dropped post-transplantation but remained low during maintenance therapy when the patient was leukemia-free.Conclusion This suspected Li-Fraumeni syndrome case report with a likely pathogenic heterozygous TP53 variant expands the cancer genetic spectrum. Screening her family members for mutations facilitates identifying the optimal relative donor and avoids unnecessary treatment by monitoring TP53 germline mutations for minimal residual disease following hematopoietic stem cell transplantation. Its potential roles in hematological malignant tumor development and clinical pathogenic implications necessitate further probing.

Three-dimensional (3D) bioprinting techniques have emerged as the most popular methods to fabricate 3D-engineered tissues; however, there are challenges in simultaneously satisfying the requirements of high cell density (HCD), high cell viability, and fine fabrication resolution. In particular, bioprinting resolution of digital light processing-based 3D bioprinting suffers with increasing bioink cell density due to light scattering. We developed a novel approach to mitigate this scattering-induced deterioration of bioprinting resolution. The inclusion of iodixanol in the bioink enables a 10-fold reduction in light scattering and a substantial improvement in fabrication resolution for bioinks with an HCD. Fifty-micrometer fabrication resolution was achieved for a bioink with 0.1 billion per milliliter cell density. To showcase the potential application in tissue/organ 3D bioprinting, HCD thick tissues with fine vascular networks were fabricated. The tissues were viable in a perfusion culture system, with endothelialization and angiogenesis observed after 14 days of culture.

With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

This study investigates the propagation of dark Alfvén solitons in low-β magnetized plasma using Hall-magnetohydrodynamic (Hall-MHD) numerical simulations. The rational solution of the nonlinear Schrödinger equation (NLSE) is presented, which is proposed as an effective tool for studying dark envelope solitons in plasma. Our results show a high degree of agreement between numerical simulations and analytical solutions derived from the NLSE via the reductive perturbation method. This agreement validates our modeling and computational approach. In addition, the simulations confirm the existence of dark Alfvén solitons in magnetized plasma. This work demonstrates the effectiveness of Hall-MHD simulations in studying complex plasma phenomena, contributing to the broader understanding of soliton propagation in plasma environments.

Objective: The purpose was to explore the effects of traditional and non-traditional lipid parameters on Sudden Sensorineural Hearing Loss (SSNHL). Methods: The study included 452 patients diagnosed with SSNHL, among whom 206 patients had a level of hearing improvement ≥10 dB after one month of follow-up. A propensity score-matched (2:1) control group was used. Conditional and unconditional logistic regression were used to analyze the risk factors for SSNHL. Results: Patients with SSNHL had a higher risk of concomitant hypertension and elevated atherosclerogenic lipid levels, with apolipoprotein B and apolipoprotein E identified as independent risk factors for the onset of SSNHL. Additionally, the Lipid Comprehensive Index (LCI) was an independent risk factor for the degree of hearing loss. A positive linear correlation was revealed between triglyceride, non-high-density lipoprotein cholesterol, atherogenic index, Castelli risk index, atherogenic index of plasma, LCI and hearing loss. However, no linear relationship was observed between hearing gain and any lipid parameters. When Total Cholesterol (TC) was in the range of borderline high, the treatment effect was the best. However, the statistical significance disappeared upon adjusting for confounding factors. Conclusion: Patients with SSNHL exhibited markedly dysregulated lipid metabolism. Elevated serum lipid levels may be a causative factor in auditory impairment and can influence the extent of hearing loss. Promptly improving cochlear microcirculation may benefit patients with borderline elevated TC. Level of evidence: 4.

Online collaborative geographic experiments have many advantages in communication, resource sharing, and task coordination; thus, they play a vital role in comprehensive geographic problem solving for interdisciplinary experts. In these collaborative experiments, different experts usually possess different knowledge backgrounds and are responsible for specific tasks, making it difficult to fully understand the entire experimental process and implementation details, which may lead to different experimental ideas and actions, thus reducing the efficiency of the experiment. Therefore, it is necessary to record and trace information to help participants reach a consensus on the understanding of the experiment to support collaboration. However, most of the existing tracing strategies focus on the states of geographic experimental data but ignore the different interactions that impact the generation, flow, and use of these data. Limitations remain for existing strategies in terms of providing comprehensive insight into the geographic experiment process and its implementation details, especially when addressing the requirements of process understanding, error localization, and scheme sharing. Therefore, this study presents a strategy for tracing interactions in online collaborative geographic experiments. This strategy focuses on interactions and their types, structures, and dependencies during the geographic experiment process; designs three components for recording interaction information; and uses corresponding extraction methods to trace interaction information. To verify the feasibility of this strategy, it was implemented in an online prototype system, and a case study of aboveground forest biomass prediction under climate change was conducted with the prototype system. The results indicate that the proposed strategy can help enhance collaboration among different participants, thus effectively improving the performance of collaborative geographic experiments.

Abstract It is widely believed the brain-inspired spiking neural networks have the capability of processing temporal information owing to their dynamic attributes. However, how to understand what kind of mechanisms contributing to the learning ability and exploit the rich dynamic properties of spiking neural networks to satisfactorily solve complex temporal computing tasks in practice still remains to be explored. In this article, we identify the importance of capturing the multi-timescale components, based on which a multi-compartment spiking neural model with temporal dendritic heterogeneity, is proposed. The model enables multi-timescale dynamics by automatically learning heterogeneous timing factors on different dendritic branches. Two breakthroughs are made through extensive experiments: the working mechanism of the proposed model is revealed via an elaborated temporal spiking XOR problem to analyze the temporal feature integration at different levels; comprehensive performance benefits of the model over ordinary spiking neural networks are achieved on several temporal computing benchmarks for speech recognition, visual recognition, electroencephalogram signal recognition, and robot place recognition, which shows the best-reported accuracy and model compactness, promising robustness and generalization, and high execution efficiency on neuromorphic hardware. This work moves neuromorphic computing a significant step toward real-world applications by appropriately exploiting biological observations.

Driven by the IoT technology and smart sensors development in Industry 5.0, the digital twin as an innovative information technology brings new opportunities and challenges for intelligent maritime logistics management. This paper tries to present a systematic review on digital twin-empowered smart maritime logistics management by employing a bibliometric analysis framework under the Industry 5.0 era. The 3372 related publications from the Web of Science database are collected as research samples from 2003 to 2023. Besides, the VosViewer is adopted to perform the co-word and network analysis by visualizing interactive collaborations of published literature. Specifically, more than 3,000 articles on maritime logistics were reviewed to determine the research trajectories and main themes through same-word study and co-citation analysis. Results show that most publications on maritime logistics management are concentrated in China and the United States, where maritime logistics is developing towards digitization and informatization. In particular, Sustainability, Maritime Policy & Management, and Journal of Marine Science and Engineering are the most important journals focusing on maritime logistics management. Moreover, we hope this review study serves as a future direction on digital twin-empowered smart maritime logistics management practices for both researchers and practitioners.

Abstract Crane usage is pervasive on construction sites, however, it is associated with a notably high accident rate. The analyzing of crane accident risks is essential for accident prevention, control, and ensuring the safety of lifting operations. Hence, significant emphasis should be placed on understanding the interaction among various risk factors. This paper proposes a quantitative coupling method for human, machine, management, and environmental risk factors in crane accidents, leveraging Bayesian networks (BN) and the N-K model. Firstly, text mining technology and fault tree analysis are employed to analyze the causes of crane accidents and categorize the associate risk factors. Secondly, the types of risk coupling resulting from human, machine, management, and environmental risk factors are defined. Thirdly, the BN model is developed based on the analysis of crane accident risksand its N-K model. Fourthly, the parameters of the risk coupling nodes in the developed BN are determined based on the calculation results of the N-K model. Finally, for the risk coupling types with high coupling values and the first-level node and second-level node, the failure probability is analyzed through posterior probability and sensitivity analysis. The results indicate that factors related to man and management significantly impact crane accidents and warrant enhanced attention. The interplay among multiple risk factors significantly influences the probability of crane accidents, necessitating careful attention.

In a satellite communication system deployed with massive MIMO, when the number of users far exceeds the number of beams of the satellite, it is still difficult to satisfy the delay requirements of the satellite communication system even if the number of RF chains is increased, i.e., the number of concurrently serving users is increased.To address the above problems, it proposed a dynamic beam hopping (BH) scheme based on user grouping for communication service coverage.The proposed method utilized the sparsity of the angular domain channel distribution to adaptively divide user groups accorded to the beam direction where the user energy is maximum.The number of co-channel user groups was constrained by power and interference constraints, limiting the reduction of communication traffic delay, as power limitations on the satellite make the number of RF chains limited and increased the number of simultaneously served user groups increased the interference between user groups.So the BH scheme with beam cluster grouping was further proposed, when the beam clusters reduced the user delay by increased the number of users served at the same moment.Since the above problem was non-convex, it adopt a data-driven determinantal point process (DPP) learning method to simplify the beam scheduling in BH scheme.Simulation results showed that the dynamic BH algorithm based on user grouping could effectively reduce the average user delay by more than 52% compared with the single-beam scheme, also verifies the versatility of the DPP learning.

Abstract Various craniofacial syndromes cause skeletal malformations and are accompanied by neurological abnormalities at different levels, leading to tremendous biomedical, financial, social, and psychological burdens. Accumulating evidence highlights the importance of identifying and characterizing the genetic basis that synchronously modulates musculoskeletal and neurobehavioral development and function. Particularly, previous studies from different groups have suggested that neural EGFL-like-1 (Nell-1), a well-established osteochondrogenic inducer whose biopotency was initially identified in the craniofacial tissues, may also play a vital role in the central nervous system, particularly regarding neurological disorder pathologies. To provide first-hand behavior evidence if Nell-1 also has a role in central nervous system abnormalities, we compared the Nell-1-haploinsufficient (Nell-1 +/6R ) mice with their wild-type counterparts regarding their repetitive, social communication, anxiety-related, locomotor, sensory processing-related, motor coordination, and Pavlovian learning and memory behaviors, as well as their hippocampus transcriptional profile. Interestingly, Nell-1 +/6R mice demonstrated core autism spectrum disorder-like deficits, which could be corrected by Risperidone, an FDA-approved anti-autism, anti-bipolar medicine. Besides, transcriptomic analyses identified 269 differential expressed genes, as well as significantly shifted alternative splicing of ubiquitin B pseudogene Gm1821, in the Nell-1 +/6R mouse hippocampus, which confirmed that Nell-1 plays a role in neurodevelopment. Therefore, the current study verifies that Nell-1 regulates neurological development and function for the first time. Moreover, this study opens new avenues for understanding and treating craniofacial patients suffering from skeletal deformities and behavior, memory, and cognition difficulties by uncovering a novel bone-brain-crosstalk network. Furthermore, the transcriptomic analysis provides the first insight into deciphering the mechanism of Nell-1 in neurodevelopment.

The rise of computer-aided design and computer-aided manufacturing (CAD/CAM) and 3D printing technologies in orthodontics has revolutionized the development of customized labial and lingual bracket systems with a variety of materials, which offer potential advantages over traditional orthodontic brackets. To highlight the current state of knowledge regarding the mechanical and clinical properties of CAD/CAM and 3D-printed custom bracket systems, we conducted a comprehensive search across the PubMed, Embase, Cochrane Library, Web of Science, and Scopus databases to identify relevant articles published before April 2024. Mechanical (including fracture toughness, hardness, modulus of elasticity, frictional resistance, slot accuracy, torque transmission, and shear bond strength) and clinical (including treatment efficiency and duration, cost, and comfort) properties were compared between traditional and customized orthodontic bracket systems in the current review. Our findings suggest that customized brackets have the potential to increase bracket slot precision, reduce treatment time, and offer cost-efficiency. However, it is worth noting that the advantages and disadvantages of customized bracket systems vary depending on the bracket material and the manufacturing methods, warranting comprehensively controlled investigations in the future.

This paper presents a novel low-carbon binder formulated from fly ash (FA), ground granulated blast furnace slag, steel slag, and desulfurization gypsum as a quaternary solid waste-based material. It specifically examines the influence of FA content on the mechanical properties and hydration reactions of the quaternary solid waste-based binder. The mortar test results indicate that the optimal FA content is 10%, which yields a 28-day compressive strength 11.28% higher than that of the control group without FA. The spherical particles of fly ash reduce the overall water demand and provide a “lubricating” effect to the paste due to their continuous gradation, improving the fluidity of the slag-steel slag-gypsum cementitious materials. The micro test results indicate that fly ash has minimal effect on the early hydration products and process of the solid waste-based cementitious materials, but after 7 days, it continuously dissolves silicon-oxygen tetrahedrons or aluminum-oxygen tetrahedrons, consuming Ca2+ and OH− in the system. After 28 days, the amount of ettringite and C-(A)-S-H gel generated increases significantly. The pozzolanic activity of fly ash is mainly stimulated by the Ca(OH)2 from steel slag in the later hydration stage. Additionally, spherical fly ash particles can fill the voids in the hardened paste, reducing the formation of cracks and weak zones, and thereby contributing to a denser overall structure of the hydrated binder. The findings of this paper provide data support for the development of low-carbon cement-free binders using fly ash in conjunction with metallurgical slags, thereby contributing to the low-carbon advancement of the construction materials industry.

In recent years, academic research on perovskite solar cells (PSCs) has attracted remarkable attention, and one of the most crucial issues is promoting the power conversion efficiency (PCE) and operational stability of PSCs. Generally, modification of the electron or hole transport layers between the perovskite layers and electrodes via surface engineering is considered an effective strategy because the inherent structural defects between charge carrier transport layers and perovskite layers can be reshaped and modified by adopting the functional nanomaterials, and thus the charge recombination rate can be naturally decreased. At present, large amounts of available nanomaterials for surface modification of the perovskite films are extensively investigated, mainly including nanocrystals, nanorods, nanoarrays, and even colloidal quantum dots (QDs). In particular, as unique size-dependent nanomaterials, the diverse quantum properties of colloidal QDs are different from other nanomaterials, such as their quantum confinement effects, quantum-tunable effects, and quantum surface effects, which display great potential in promoting the PCE and operational stability of PSCs as the charge carriers in perovskite layers can be effectively tuned by these quantum effects. However, preparing QDs with a neat and desirable size remains a technical difficulty, even though the present chemical engineering is highly advanced. Fortunately, the rapid advances in laser technology have provided new insight into the precise preparation of QDs. In this review, we introduce a new approach for preparing the QDs, namely pulsed laser irradiation in colloids (PLIC), and briefly highlight the innovative works on PLIC-prepared QDs for the optimization of PSCs. This review not only highlights the advantages of PLIC for QD preparation but also critically points out the challenges and prospects of QD-based PSCs.