Self-supervised learning is a new machine learning method that does not rely on manually labeled data, and learns from rich unlabeled data itself by designing agent tasks using the input data as supervision to obtain a more generalized representation for application in downstream tasks. However, the current self-supervised learning suffers from the problem of relying on the selection and number of negative samples and the problem of sample bias phenomenon after graph data augmentation. In this paper, we investigate the above problems and propose a corresponding solution, proposing a graph contrastive learning algorithm without negative samples. The model uses matrix sketching in the implicit space for feature augmentation to reduce sample bias and iteratively trains the mutual correlation matrix of two viewpoints by drawing closer to the distance of the constant matrix as the objective function. This method does not require techniques such as negative samples, gradient stopping, and momentum updating to prevent self-supervised model collapse. This method is compared with 10 graph representation learning algorithms on four datasets for node classification tasks, and the experimental results show that the algorithm proposed in this paper achieves good results. Full article

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. Full article

China has made notable advancements in the intelligent construction of coal mines. However, for longwall top coal caving (LTCC) mining faces, a key obstacle impeding the intelligent transition of the coal-cutting process is automated control. This paper focuses on the aforementioned issue and comprehensively considers the pre-, intra-, and post-coal-caving stages. In this work, diverse detection and monitoring technologies are integrated at various stages through a computer platform, facilitating the construction of an automated coal caving control system with self-perception, self-learning, self-decision-making, and self-execution capabilities. Key technologies include ground-penetrating radar-based top coal thickness detection, inertial navigation-based shearer positioning, tail beam vibration-based identification of coal and gangue, and magnetostrictive sensor-based monitoring of the tail beam and insert plate attitude. In this study, the 12309 working face of the Wangjialing Coal Mine was experimentally validated, and the efficacy of the aforementioned key technologies was assessed. The results demonstrated that the control requirements for automated coal caving are satisfied by the maximum errors. Automatic regulation of coal caving was realized through the implementation of this system, thereby facilitating initiation and cessation and yielding promising experimental outcomes. Overall, this system offers practical insights for intelligent construction in current LTCC mining faces and the sustainable development of coal resources. Full article

We present a systematic review of the methods developed for the synthesis of the aromathecin family of compounds (benz[⁶,⁷]indolizino[1,2-b]quinolin-11(13H)-ones) and their derivatives. These methods can be broadly classified into four categories based on the construction of pentacyclic structures: Category 1: by constructing a pyridone moiety (D-ring) on the pyrroloquinoline ring (A/B/C-ring), Category 2: by constructing a pyridine moiety (B-ring) on the pyrroloisoquinolone ring (C/D/E-ring), Category 3: by constructing an indolizidinone moiety (C/D-ring) in a tandem reaction, and Category 4: by constructing a pyrrolidine moiety (C-ring) on the isoquinolone ring (D/E-ring). Full article

Lactococcus lactis subsp. cremoris C60 is a probiotic strain of lactic acid bacteria (LAB) which induces various immune modifications in myeloid lineage cells. These modifications subsequently regulate T cell function, resulting in enhanced immunity both locally and systemically. Here, we report that C60 suppresses tumor growth by enhancing macrophage function via metabolic alterations, thereby increasing adenosine triphosphate (ATP) production in a murine melanoma model. Intragastric (i.g.) administration of C60 significantly reduced tumor volume compared to saline administration in mice. The anti-tumor function of intratumor (IT) macrophage was upregulated in mice administered with C60, as evidenced by an increased inflammatory phenotype (M1) rather than an anti-inflammatory/reparative (M2) phenotype, along with enhanced antigen-presenting ability, resulting in increased tumor antigen-specific CD8+ T cells. Through this functional modification, we identified that C60 establishes a glycolysis-dominant metabolism, rather than fatty acid oxidation (FAO), in IT macrophages, leading to increased intracellular ATP levels. To address the question of why orally supplemented C60 exhibits functions in distal places, we found a possibility that bacterial cell wall components, which could be distributed throughout the body from the gut, may induce stimulatory signals in peripheral macrophages via Toll-like receptors (TLRs) signaling activation. Thus, C60 strengthens macrophage anti-tumor immunity by promoting a predominant metabolic shift towards glycolysis upon TLR-mediated stimulation, thereby increasing substantial energy production. Full article

To accommodate the production and manufacture of complex and customized marine components and to avoid the empirical nature of process planning, machining operations can be automatically sequenced and optimized using ant colony algorithms. However, traditional ant colony algorithms exhibit issues in the context of machining process planning. In this study, an improved ant colony algorithm is proposed to address these challenges. The introduction of a tiered distribution of initial pheromones mitigates the blindness of initial searches. By incorporating the number of iterations into the expectation heuristic function and introducing a ‘reward–penalty system’ for pheromones, the contradictions between convergence speed and the tendency to fall into local optima are avoided. Applying the improved ant colony algorithm to the process planning of large container ship propeller shaft machining, this study constructs a ‘distance’ model for each machining unit and develops a process constraint table. The results show significant improvements in initial search capabilities and convergence speed with the improved ant colony algorithm while also resolving the contradiction between convergence speed and optimal solutions. This verifies the feasibility and effectiveness of the improved ant colony algorithm in intelligent process planning for ships. Full article

This review highlights recent advances in renal cell carcinoma (RCC) imaging. It begins with dual-energy computed tomography (DECT), which has demonstrated a high diagnostic accuracy in the evaluation of renal masses. Several studies have suggested the potential benefits of iodine quantification, particularly for distinguishing low-attenuation, true enhancing solid masses from hyperdense cysts. By determining whether or not a renal mass is present, DECT could avoid the need for additional imaging studies, thereby reducing healthcare costs. DECT can also provide virtual unenhanced images, helping to reduce radiation exposure. The review then provides an update focusing on the advantages of multiparametric magnetic resonance (MR) imaging performance in the histological subtyping of RCC and in the differentiation of benign from malignant renal masses. A proposed standardized stepwise reading of images helps to identify clear cell RCC and papillary RCC with a high accuracy. Contrast-enhanced ultrasound may represent a promising diagnostic tool for the characterization of solid and cystic renal masses. Several combined pharmaceutical imaging strategies using both sestamibi and PSMA offer new opportunities in the diagnosis and staging of RCC, but their role in risk stratification needs to be evaluated. Although radiomics and tumor texture analysis are hampered by poor reproducibility and need standardization, they show promise in identifying new biomarkers for predicting tumor histology, clinical outcomes, overall survival, and the response to therapy. They have a wide range of potential applications but are still in the research phase. Artificial intelligence (AI) has shown encouraging results in tumor classification, grade, and prognosis. It is expected to play an important role in assessing the treatment response and advancing personalized medicine. The review then focuses on recently updated algorithms and guidelines. The Bosniak classification version 2019 incorporates MRI, precisely defines previously vague imaging terms, and allows a greater proportion of masses to be placed in lower-risk classes. Recent studies have reported an improved specificity of the higher-risk categories and better inter-reader agreement. The clear cell likelihood score, which adds standardization to the characterization of solid renal masses on MRI, has been validated in recent studies with high interobserver agreement. Finally, the review discusses the key imaging implications of the 2017 AUA guidelines for renal masses and localized renal cancer. Full article

Yttrium-doped barium zirconate is a commonly used electrolyte material for Protonic Ceramic Fuel Cells (PCFC) due to its high protonic conductivity and high chemical stability. However, it is also known for its poor sinterability and poor grain boundary conductivity. In this work, in response to these issues, reactive magnetron sputtering was strategically chosen as the electrolyte deposition technique. This method allows the creation of a 4 µm tick electrolyte with a dense columnar microstructure. Notably, this technique is not widely utilized in PCFC fabrication. In this study, a complete cell is elaborated without exceeding a sintering temperature of 1350 °C. Tape casting is used for the anode, and spray coating is used for the cathode. The material of interest is yttrium-doped barium zirconate with the formula BaZr_0.8Y_0.2O_3−δ (BZY). The anode consists of a NiO-BZY cermet, while the cathode is composed of BZY and Ba_0.5Sr_0.5Co_0.8Fe_0.2O_3−δ (BSFC) in a 50:50 weight ratio. The electrochemical impedance spectroscopy analysis reveals a global polarization resistance of 0.3 Ω cm², indicating highly efficient interfaces between electrolytes and electrodes. Full article

Traditional video frame interpolation methods based on deep convolutional neural networks face challenges in handling large motions. Their performance is limited by the fact that convolutional operations cannot directly integrate the rich temporal and spatial information of inter-frame pixels, and these methods rely heavily on additional inputs such as optical flow to model motion. To address this issue, we develop a novel framework for video frame interpolation that uses Transformer to efficiently model the long-range similarity of inter-frame pixels. Furthermore, to effectively aggregate spatio-temporal features, we design a novel attention mechanism divided into temporal attention and spatial attention. Specifically, spatial attention is used to aggregate intra-frame information, integrating both attention and convolution paradigms through the simple mapping approach. Temporal attention is used to model the similarity of pixels on the timeline. This design achieves parallel processing of these two types of information without extra computational cost, aggregating information in the space–time dimension. In addition, we introduce a context extraction network and multi-scale prediction frame synthesis network to further optimize the performance of the Transformer. Our method and state-of-the-art methods are extensively quantitatively and qualitatively experimented on various benchmark datasets. On the Vimeo90K and UCF101 datasets, our model achieves improvements of 0.09 dB and 0.01 dB in the PSNR metrics over UPR-Net-large, respectively. On the Vimeo90K dataset, our model outperforms FLAVR by 0.07 dB, with only 40.56% of its parameters. The qualitative results show that for complex and large-motion scenes, our method generates sharper and more realistic edges and details. Full article

The author believes that the principles of statistical methods for vaccine safety can be divided into three categories: comparison of adverse event incidence rates between vaccinated and unvaccinated groups, analysis of incidentality in the vaccinated group, and a combination of both. The first category includes the cohort study; the second, the self-controlled risk interval design (SCRI); and the third, the self-controlled case series method. A single p-value alone should not determine a scientific conclusion, and analysis should be performed using multiple statistical methods with different principles. The author believes that using both the cohort study and the SCRI for analysis is the best method to assess vaccine safety. When the cohort study may not detect a significant difference owing to a low incidence rate of an adverse event in the vaccinated group or a high one in the unvaccinated group, the SCRI may detect it. Because vaccines must have a higher level of safety than the pharmaceuticals used for treatment, vaccine safety is advisable to be assessed using methods that can detect a significant difference even for any value of the incidence rate of an adverse event. The author believes that the analyses of COVID-19 vaccine safety have areas for improvement because the proportion of papers that used the cohort study and the SCRI was negligible. Full article

We propose a method for selecting the optimal set of weather features for wind energy prediction. This problem is tackled by developing a wrapper approach that employs binary differential evolution to search for the best feature subset, and an ensemble of artificial neural networks to predict the energy production from a wind plant. The main novelties of the approach are the use of features provided by different weather forecast providers and the use of an ensemble composed of a reduced number of models for the wrapper search. Its effectiveness is verified using weather and energy production data collected from a 34 MW real wind plant. The model is built using the selected optimal subset of weather features and allows for (i) a 1% reduction in the mean absolute error compared with a model that considers all available features and a 4.4% reduction compared with the model currently employed by the plant owners, and (ii) a reduction in the number of selected features by 85% and 50%, respectively. Reducing the number of features boosts the prediction accuracy. The implication of this finding is significant as it allows plant owners to create profitable offers in the energy market and efficiently manage their power unit commitment, maintenance scheduling, and energy storage optimization. Full article

Remote sensing techniques have become pivotal in monitoring algal blooms and population dynamics in freshwater bodies, particularly to assess the ecological risks associated with eutrophication. This study focuses on remote sensing methods for the analysis of 4 Italian lakes with diverse geological origins, leveraging water quality samples and data from the Sentinel-2 and Landsat 5.7–8 platforms. Chl-a, a well-correlated indicator of phytoplankton biomass abundance and eutrophication, was estimated using ordinary least squares linear regression to calibrate surface reflectance with chl-a concentrations. Temporal gaps between sample and image acquisition were considered, and atmospheric correction dedicated to water surfaces was implemented using ACOLITE and those specific to each satellite platform. The developed models achieved determination coefficients higher than 0.69 with mean square errors close to 3 mg/m³ for water bodies with low turbidity. Furthermore, the time series described by the models portray the seasonal variations in the lakes water bodies. Full article

Compared to adults without cancer, cancer survivors report poorer health-related quality of life (HRQOL), which is associated with negative treatment outcomes and increased healthcare use. Cancer-specialized physical and occupational therapy (PT/OT) could optimize HRQOL; however, the impact among survivors with non-breast malignancies is unknown. This retrospective (2020–2022), observational, study of medical record data of 12 cancer types, examined pre/post-HRQOL among cancer survivors who completed PT/OT. PROMIS^® HRQOL measures: Global Health (physical [GPH] and mental [GMH]), Physical Function (PF), and Ability to Participate in Social Roles and Activities (SRA) were evaluated using linear mixed effect models by cancer type, then compared to the minimal important change (MIC, 2 points). Survivors were 65.44 ± 12.84 years old (range: 19–91), male (54%), with a median of 12 visits. Improvements in GPH were significant (p < 0.05) for all cancer types and all achieved MIC. Improvements in GMH were significant for 11/12 cancer types and 8/12 achieved MIC. Improvements in PF were significant for all cancer types and all achieved the MIC. Improvements in SRA were significant for all cancer types and all groups achieved the MIC. We observed statistically and clinically significant improvements in HRQOL domains for each of the 12 cancer types evaluated. Full article

Bacterial leaf blight (BLB), among the most serious diseases in rice production, is caused by Xanthomonas oryzae pv. oryzae (Xoo). Xa23, the broadest resistance gene against BLB in rice, is widely used in rice breeding. In this study, the rice variety CBB23 carrying the Xa23 resistance gene was inoculated with AH28 and PXO99^A to identify differentially expressed genes (DEGs) associated with the resistance. Transcriptome sequencing of the infected leaves showed 7997 DEGs between the two strains at different time points, most of which were up-regulated, including cloned rice anti-blight, peroxidase, pathology-related, protein kinase, glucosidase, and other coding genes, as well as genes related to lignin synthesis, salicylic acid, jasmonic acid, and secondary metabolites. Additionally, the DEGs included 40 cloned, five NBS-LRR, nine SWEET family, and seven phenylalanine aminolyase genes, and 431 transcription factors were differentially expressed, the majority of which belonged to the WRKY, NAC, AP2/ERF, bHLH, and MYB families. Metabolomics analysis showed that a large amount of alkaloid and terpenoid metabolite content decreased significantly after inoculation with AH28 compared with inoculation with PXO99^A, while the content of amino acids and their derivatives significantly increased. This study is helpful in further discovering the pathogenic mechanism of AH28 and PXO99^A in CBB23 rice and provides a theoretical basis for cloning and molecular mechanism research related to BLB resistance in rice. Full article

The significant impact of Nb on ferrite transformation, both in terms of solute drag effect (SDE) and interphase precipitation, was investigated quantitatively. Ferrite transformation kinetics were characterized using thermal expansion experiments and theoretical calculations. The microstructures were characterized using high−temperature confocal laser scanning microscopy (CLSM), a field−emission scanning electron microscope (FESEM), and a transmission electron microscope (TEM). Under a higher driving force, interphase precipitations were observed in the sample with a higher Nb content. A three−dimensional (3D) reconstruction method was used to convert the two−dimensional (2D) image of interphase precipitation into a three−dimensional model for a more typical view. The SDE and interphase precipitation had opposite effects on the kinetics of ferrite transformation. A lower Nb content showed a strong contribution to the SDE, which delayed ferrite transformation. A higher concentration of Nb was expected to enhance the SDE, but the inhibition effect was eliminated by the interphase precipitation of NbC during interfacial migration. Both the experimental results and theoretical calculations confirmed this phenomenon. Full article

Primary mitochondrial diseases result from mutations in nuclear DNA (nDNA) or mitochondrial DNA (mtDNA) genes, encoding proteins crucial for mitochondrial structure or function. Given that few disease-specific therapies are available for mitochondrial diseases, novel treatments to reverse mitochondrial dysfunction are necessary. In this work, we explored new therapeutic options in mitochondrial diseases using fibroblasts and induced neurons derived from patients with mutations in the GFM1 gene. This gene encodes the essential mitochondrial translation elongation factor G1 involved in mitochondrial protein synthesis. Due to the severe mitochondrial defect, mutant GFM1 fibroblasts cannot survive in galactose medium, making them an ideal screening model to test the effectiveness of pharmacological compounds. We found that the combination of polydatin and nicotinamide enabled the survival of mutant GFM1 fibroblasts in stress medium. We also demonstrated that polydatin and nicotinamide upregulated the mitochondrial Unfolded Protein Response (mtUPR), especially the SIRT3 pathway. Activation of mtUPR partially restored mitochondrial protein synthesis and expression, as well as improved cellular bioenergetics. Furthermore, we confirmed the positive effect of the treatment in GFM1 mutant induced neurons obtained by direct reprogramming from patient fibroblasts. Overall, we provide compelling evidence that mtUPR activation is a promising therapeutic strategy for GFM1 mutations. Full article

Jets powered by AGN in the early Universe ($z\gtrsim 6$) have the potential to not only define the evolutionary trajectories of the first-forming massive galaxies but to enable the accelerated growth of their associated SMBHs. Under typical assumptions, jets could even rectify observed quasars with light seed formation scenarios; however, not only are constraints on the parameters of the first jets lacking, observations of these objects are scarce. Owing to the significant energy density of the CMB at these epochs capable of quenching radio emission, observations will require powerful, high angular resolution X-ray imaging to map and characterize these jets. As such, AXIS will be necessary to understand early SMBH growth and feedback. This White Paper is part of a series commissioned for the AXIS Probe Concept Mission; additional AXIS White Papers can be found at the AXIS website. Full article

Green mold, caused by Penicillium digitatum, is the major cause of citrus postharvest decay. Currently, the application of sterol demethylation inhibitor (DMI) fungicide is one of the main control measures to prevent green mold. However, the fungicide-resistance problem in the pathogen P. digitatum is growing. The regulatory mechanism of DMI fungicide resistance in P. digitatum is poorly understood. Here, we first performed transcriptomic analysis of the P. digitatum strain Pdw03 treated with imazalil (IMZ) for 2 and 12 h. A total of 1338 genes were up-regulated and 1635 were down-regulated under IMZ treatment for 2 h compared to control while 1700 were up-regulated and 1661 down-regulated under IMZ treatment for 12 h. The expression of about half of the genes in the ergosterol biosynthesis pathway was affected during IMZ stress. Further analysis identified that 84 of 320 transcription factors (TFs) were differentially expressed at both conditions, making them potential regulators in DMI resistance. To confirm their roles, three differentially expressed TFs were selected to generate disruption mutants using the CRISPR/Cas9 technology. The results showed that two of them had no response to IMZ stress while ∆PdflbC was more sensitive compared with the wild type. However, disruption of PdflbC did not affect the ergosterol content. The defect in IMZ sensitivity of ∆PdflbC was restored by genetic complementation of the mutant with a functional copy of PdflbC. Taken together, our results offer a rich source of information to identify novel regulators in DMI resistance. Full article

Background: There is a growing interest in bone tissue MRI and an even greater interest in using low-cost MR scanners. However, the characteristics of bone MRI remain to be fully defined, especially at low field strength. This study aimed to characterize the signal-to-noise ratio (SNR), T₂, and T₂* in spongy bone at 0.3 T, 1.5 T, and 3.0 T. Furthermore, relaxation times were characterized as a function of bone-marrow lipid/water ratio content and trabecular bone density. Methods: Thirty-two women in total underwent an MR-imaging investigation of the calcaneus at 0.3 T, 1.5 T, and 3.0 T. MR-spectroscopy was performed at 3.0 T to assess the fat/water ratio. SNR, T₂, and T₂* were quantified in distinct calcaneal regions (ST, TC, and CC). ANOVA and Pearson correlation statistics were used. Results: SNR increase depends on the magnetic field strength, acquisition sequence, and calcaneal location. T₂* was different at 3.0 T and 1.5 T in ST, TC, and CC. Relaxation times decrease as much as the magnetic field strength increases. The significant linear correlation between relaxation times and fat/water found in healthy young is lost in osteoporotic subjects. Conclusion: The results have implications for the possible use of relaxation vs. lipid/water marrow content for bone quality assessment and the development of quantitative MRI diagnostics at low field strength. Full article

Resveratrol could be applied in wound healing therapies because of its antioxidant, anti-inflammatory and antibacterial effects. However, the main limitation of resveratrol is its low aqueous solubility. In this study, resveratrol was included in hydroxypropyl-β-cyclodextrin complexes and further formulated in Pluronic F-127 hydrogels for wound treatment therapy. IR-spectroscopy and XRD analysis confirmed the successful incorporation of resveratrol into complexes. The wound-healing ability of these complexes was estimated by a scratch assay on fibroblasts, which showed a tendency for improvement of the effect of resveratrol after complexation. The antimicrobial activity of resveratrol in aqueous dispersion and in the complexes was evaluated on methicillin-resistant Staphylococcus aureus (MRSA), Escherichia coli, and Candida albicans strains. The results revealed a twofold decrease in the MIC and stronger inhibition of the metabolic activity of MRSA after treatment with resveratrol in the complexes compared to the suspended drug. Furthermore, the complexes were included in Pluronic hydrogel, which provided efficient drug release and appropriate viscoelastic properties. The formulated hydrogel showed excellent biocompatibility which was confirmed via skin irritation test on rabbits. In conclusion, Pluronic hydrogel containing resveratrol included in hydroxypropyl-β-cyclodextrin complexes is a promising topical formulation for further studies directed at wound therapy. Full article

Purpose: Hepatic Arteriography and C-Arm CT-Guided Ablation of liver tumors (HepACAGA) is a novel technique, combining hepatic–arterial contrast injection with C-arm CT-guided navigation. This study compared the outcomes of the HepACAGA technique with patients treated with conventional ultrasound (US) and/or CT-guided ablation. Materials and Methods: In this retrospective cohort study, all consecutive patients with hepatocellular carcinoma (HCC) or colorectal liver metastases (CRLM) treated with conventional US-/CT-guided ablation between 1 January 2015, and 31 December 2020, and patients treated with HepACAGA between 1 January 2021, and 31 October 2023, were included. The primary outcome was local tumor recurrence-free survival (LTRFS). Secondary outcomes included the local tumor recurrence (LTR) rate and complication rate. Results: 68 patients (120 tumors) were included in the HepACAGA cohort and 53 patients (78 tumors) were included in the conventional cohort. In both cohorts, HCC was the predominant tumor type (63% and 73%, respectively). In the HepACAGA cohort, all patients received microwave ablation. Radiofrequency ablation was the main ablation technique in the conventional group (78%). LTRFS was significantly longer for patients treated with the HepACAGA technique (p = 0.015). Both LTR and the complication rate were significantly lower in the HepACAGA cohort compared to the conventional cohort (LTR 5% vs. 26%, respectively; p < 0.001) (complication rate 4% vs. 15%, respectively; p = 0.041). Conclusions: In this study, the HepACAGA technique was safer and more effective than conventional ablation for HCC and CRLM, resulting in lower rates of local tumor recurrence, longer local tumor recurrence-free survival and fewer procedure-related complications. Full article