Search

The in-plane thermal conductivity of hexagonal boron nitride (h-BN) with varying thicknesses is a key property that affects the performance of various applications from electronics to optoelectronics. However, the transition of the thermal conductivity from two-dimensional (2D) to three-dimensional (3D) h-BN remains elusive. To answer this question, we have developed a machine learning interatomic potential within the neuroevolution potential (NEP) framework for h-BN, achieving a high accuracy akin to ab initio calculations in predicting its thermal conductivity and phonon transport from monolayer to multilayers and bulk. Utilizing molecular dynamics simulations based on the NEP, we predict the thermal conductivity of h-BN with a thickness up to ∼100 nm, demonstrating that its thermal conductivity quickly decreases from the monolayer and saturates to the bulk value above four layers. The saturation of its thermal conductivity is attributed to the little change in phonon group velocity and lifetime as the thickness increases beyond four layers. In particular, the weak thickness dependence of phonon lifetime in h-BN with a nanoscale thickness results from its extremely high phonon focusing along the in-plane direction. This research bridges the knowledge gap of phonon transport between 2D and 3D h-BN and will benefit the thermal design and performance optimization of relevant applications. [ABSTRACT FROM AUTHOR]

Chiral quantum dots (QDs) are promising materials applied in many areas, such as chiral molecular recognition and spin selective filter for charge transport, and can be prepared by facile ligand exchange approaches. However, ligand exchange leads to an increase in surface defects and reduces the efficiencies of radiative recombination and charge transport, which restricts further applications. Here, we investigate the light-induced photoluminescence (PL) enhancement in chiral L- and D-cysteine CdSe QD thin films, providing a strategy to increase the PL. The PL intensity of chiral CdSe QD films can be significantly enhanced over 100 times by continuous UV laser irradiation, indicating a strong passivation of surface defects upon laser irradiation. From the comparative measurements of the PL intensity evolutions in vacuum, dry oxygen, air, and humid nitrogen atmospheres, we conclude that the mechanism of PL enhancement is photo-induced surface passivation with the assistance of water molecules. [ABSTRACT FROM AUTHOR]

Developing high-performance cathode materials for intermediate-temperature solid oxide fuel cells (SOFCs) is crucial to advance SOFC technology. This study explores the application of an entropy engineering strategy to the A-site of ferrite spinel oxides to develop high-performance cathode materials. We synthesized a high-entropy spinel oxide, (Mg0.2Fe0.2Co0.2Ni0.2Cu0.2)Fe2O4, and compared its performance with its lower-entropy counterparts, CoFe2O4 and (Mg0.333Co0.333Ni0.333)Fe2O4. Experimental results and density functional theory (DFT) calculations revealed that (Mg0.2Fe0.2Co0.2Ni0.2Cu0.2)Fe2O4 exhibits superior electrochemical performance owing to its suitable electronic structure, diverse surface metal cations, and abundant surface oxygen vacancies. When applied as the cathode in an anode-supported SOFC, the cell achieves a peak power density of 787.15 mW cm−2 at 800 °C and demonstrates excellent long-term stability over 100 hours of operation. These findings highlight the potential of A-site entropy engineering as a promising approach to enhance the performance and stability of SOFC spinel oxide cathodes. [ABSTRACT FROM AUTHOR]

Sorafenib, an anticancer drug, has been shown to induce ferroptosis in cancer cells. However, resistance to sorafenib greatly limits its therapeutic efficacy, and the exact mechanism of resistance is not fully understood. This study investigated the role of N‐Acetyltransferase 10 (NAT10) in influencing the anticancer activity of sorafenib in nasopharyngeal carcinoma (NPC) and its molecular mechanism. NAT10 expression was significantly upregulated in NPC. Mechanistically, NAT10 promotes proteins of solute carrier family 7 member 11 (SLC7A11) expression through ac4C acetylation, inhibiting sorafenib‐induced ferroptosis in NPC cells. The combined application of sorafenib and the NAT10 inhibitor remodelin significantly inhibits SLC7A11 expression and promotes ferroptosis in NPC cells. In vivo knockout of NAT10 inhibited the growth of sorafenib‐resistant NPC. Our findings suggest that NAT10 inhibition might be a promising therapeutic approach to enhance the anticancer activity of sorafenib. [ABSTRACT FROM AUTHOR]

Uncontrollable interfacial side reactions generated from common aqueous electrolytes, just like the hydrogen evolution reaction (HER) and dendrite growth, have severely prevented the practical application of zinc‐ion batteries (ZIBs). Solid‐state ZIBs are considered to be an efficient strategy by adopting high‐quality solid‐state electrolytes (SSEs). Here, by confining deep eutectic electrolyte (DEE) into the nanochannels of metal‐organic framework (MOF)‐PCN‐222, a stable DEE@PCN‐222 SSE with internal Zn2+ transport channels was obtained. A distinctive ion‐transport network composed of DEE and PCN‐222 in the interior of DEE@PCN‐222 realizes the efficient Zn2+ conduction, contributing to high ionic conductivity of 3.13×10−4 S cm−1 at room temperature, low activation energy of 0.12 eV, and a high Zn2+ transference number of 0.74. Furthermore, experimental and theoretical investigations demonstrate that DEE@PCN‐222 with its unique channel structure could homogeneously regulate the Zn2+ distribution and effectively alleviate the side reactions. Highly reversible Zn plating/stripping performance of 2476 h can be realized by the SSE. The solid‐state ZIBs show a specific capacity of 306 mAh g−1 and display cycling stability of 517 cycles. This unique design concept provides a new perspective in realizing the high‐safety and high‐performance ZIBs. [ABSTRACT FROM AUTHOR]

Styrene-butadiene rubber (SBR) is an indispensable material in modern society, and the necessity for enhanced mechanical properties in SBR persists, particularly to withstand the rigors of challenging environmental conditions. To surmount the limitations of conventional cross-linking modes, mechanical bonds stabilized by host-guest recognition are incorporated as the cross-linking points of SBR to form mechanically interlocked networks (MINs). Compared with covalently cross-linked network, the representative MIN exhibits superior mechanical performance in terms of elongation (1392%) and breaking strength (4.6 MPa), whose toughness has surged by 17 times. Dissociation of host-guest recognition and subsequent sliding motion provide an effective energy dissipation mechanism, and the release of hidden length is also beneficial to enhance toughness. Furthermore, the introduction of the rotaxane cross-links made the network more pliable and possess damping and elastic properties, which can return to initial state with one minute rest interval. We aspire that this direct introduction method can serve as a blueprint, offering valuable insights for the enhancement of mechanical properties in conventional commercial polymer materials. [ABSTRACT FROM AUTHOR]

Uncontrollable interfacial side reactions generated from common aqueous electrolytes, just like the hydrogen evolution reaction (HER) and dendrite growth, have severely prevented the practical application of zinc‐ion batteries (ZIBs). Solid‐state ZIBs are considered to be an efficient strategy by adopting high‐quality solid‐state electrolytes (SSEs). Here, by confining deep eutectic electrolyte (DEE) into the nanochannels of metal‐organic framework (MOF)‐PCN‐222, a stable DEE@PCN‐222 SSE with internal Zn2+ transport channels was obtained. A distinctive ion‐transport network composed of DEE and PCN‐222 in the interior of DEE@PCN‐222 realizes the efficient Zn2+ conduction, contributing to high ionic conductivity of 3.13×10−4 S cm−1 at room temperature, low activation energy of 0.12 eV, and a high Zn2+ transference number of 0.74. Furthermore, experimental and theoretical investigations demonstrate that DEE@PCN‐222 with its unique channel structure could homogeneously regulate the Zn2+ distribution and effectively alleviate the side reactions. Highly reversible Zn plating/stripping performance of 2476 h can be realized by the SSE. The solid‐state ZIBs show a specific capacity of 306 mAh g−1 and display cycling stability of 517 cycles. This unique design concept provides a new perspective in realizing the high‐safety and high‐performance ZIBs. [ABSTRACT FROM AUTHOR]

This study presents dual-functional carbon-based poly(ether ether ketone) (PEEK) composites with enhanced thermal conductivity and electromagnetic interference shielding performance. A high-performance poly(p-phenylene benzobisoxazole) (PBO) polymer has been integrated within the composite to improve the thermal diffusion network. The composites comprising graphite nanosheets (GnPs) and multi-walled carbon nanotubes (MWCNTs)@PBO/PEEK exhibit outstanding in-plane thermal conductivity (TC) of 22.17 W m−1 K−1 at a filler loading of 19.31 vol%, representing a significant increase of 9540% and 1146% compared to pure PEEK and PBO@PEEK. Furthermore, the composites demonstrated exceptionally high electromagnetic interference shielding effectiveness (EMI SE) of 128.4 dB, with a total shielding efficiency of 99.99999999993%, which meets the aerospace shielding standard. The significant enhancement in TC and EMI is attributed to the π–π conjugation effect between carbon-based fillers and the main chains of PBO. According to the Agari and Foygel models, the addition of PBO establishes a robust and thermally conductive network, effectively reducing the heat flow barrier and facilitating the current tunneling effect. This study presents a straightforward and viable approach for developing thermally conductive and electromagnetic shielding bifunctional polymeric thermal management materials. [ABSTRACT FROM AUTHOR]

This study establishes the first core collection (CC) for Taiwanese Phalaenopsis orchids to preserve genetic diversity and key traits essential for breeding and research, thereby enhancing breeding efficiency without the need for a large maintained parent population. We examined 207 commercial orchid cultivars from ten nurseries, characterized by two phenotypes and genotypic data from eight simple sequence repeat markers. Multiple imputation was applied to estimate missing phenotypes, minimizing potential uncertainties and ensuring the reliability of population structure analysis. Weighted k-means clustering identified seven distinct clusters, highlighting substantial genetic diversity. We proposed a two-step phenotype and genotype strategy and modified genetic distance algorithms to effectively preserve both phenotypic and genetic diversity while retaining key features. Consequently, 22 core accessions were selected, distributed across seven clusters, and representing the orchid germplasm collection. Our evaluation revealed significant diversity preservation, particularly in distinct characteristics and rare features, outperforming other methodologies. Pedigree background analysis further confirmed the representativeness of the CC in maintaining diverse genetic materials. We emphasized the importance of evaluating the CC by detailing the criteria and statistical analyses used to ensure the quality, representativeness, and effectiveness of the selected accessions. This study contributes to orchid breeding, conservation efforts, and sustainable agricultural practices by providing a valuable and comprehensive resource. In conclusion, our research establishes a groundbreaking CC, offering insights into the genetic landscape of Taiwanese Phalaenopsis orchids and highlighting potential advancements in breeding commercially desirable varieties. [ABSTRACT FROM AUTHOR]

A large-scale integration of photovoltaic (PV) systems can degrade the stability of the power grid. Therefore, it is important to accurately predict the short-term output power generated from PV systems to achieve better grid power distribution and allocation. For this reason, a short-term PV power prediction model that uses the data collected from temperature sensors, irradiance sensors, and other relevant sensors was proposed, in which an improved dragonfly algorithm (IDA) was applied to optimize the support vector machine (SVM). First, the output power curves of PV systems under sunny, cloudy, and rainy conditions were analyzed to determine the input variables of the prediction model, which included temperature, relative humidity, and solar radiation intensity. Second, the original dragonfly algorithm in the optimization process was improved, and then, this IDA was utilized to optimize the parameters of SVM, enhancing the predictive capability of the model. Finally, the IDA-optimized SVM (IDA-SVM) model was applied to predict the PV output power. Test performance results demonstrated that the average absolute percentage errors of IDA-SVM were 2.42, 5.96, and 7.44% for sunny, cloudy, and rainy days, respectively, outperforming other comparative models. The performance results showed that the proposed model can not only improve the stability of PV integration, but also effectively increase the penetration rate of PV energy and enhance the reliability of power system operation. [ABSTRACT FROM AUTHOR]

The penetration of renewable energy resources for distribution networks can significantly impact the security of power supply systems. To improve the penetration efficiency, a hierarchical optimization planning for a distributed generation (DG) network using the improved sand cat swarm optimization (ISCSO) is proposed to determine the optimal location and capacity of DG into the distribution network. Firstly, the sensor is used to collect data, and the ISCSO algorithm is used to construct a complex nonlinear DG planning problem, thus reducing the impact of DG uncertainty. Second, a DG hierarchical planning model is established to select the optimal location and capacity of DG access to the distribution network. Finally, in the classical test system, the effectiveness of the proposed model is verified by setting up multiple cases. The test results confirm that the total annual cost and power loss of the DG system can be reduced by 13.1 and 40.5%, respectively. [ABSTRACT FROM AUTHOR]

The buried prestressed concrete cylinder pipe (PCCP) in mountainous areas easily suffers from geological disasters such as falling rocks, which result in leakage, pipe explosion and other structural safety issues. According to engineering practice, a "rock–soil-pipe" finite element model of buried PCCPs impacted by spherical falling rocks is established in this paper. The PCCP structural response to the impacts of falling rocks under different parameter settings is calculated. Taking the maximum plastic damage value of PCCP concrete cores as the evaluation index, an intelligent evaluation model of PCCP structural safety under falling rock impacts is built based on the Bayesian Optimization-Long Short-Term Memory (BO-LSTM) model. The constructed model is used to quickly predict the damage caused by falling rocks to the PCCP structure after the disaster. Meanwhile, the model provides support for the implementation of subsequent engineering measures. The study results show that the BO-LSTM-based intelligent evaluation model can accurately predict the PCCP structural damage caused by falling rock impacts, and it has practical application value. [ABSTRACT FROM AUTHOR]

G‐protein‐coupled receptor kinase 2 (GRK2) interacts with Gβγ and Gαq, subunits of G‐protein alpha, to regulate cell signalling. The second messenger inositol trisphosphate, produced by activated Gαq, promotes calcium release from the endoplasmic reticulum (ER) and regulates maturation‐promoting factor (MPF) activity. This study aimed to investigate the role of GRK2 in MPF activity during the meiotic maturation of porcine oocytes. A specific inhibitor of GRK2 (βi) was used in this study. The present study showed that GRK2 inhibition increased the percentage of oocyte arrest at the metaphase I (MI) stage (control: 13.84 ± 0.95%; βi: 31.30 ± 4.18%), which resulted in the reduction of the maturation rate (control: 80.36 ± 1.94%; βi: 65.40 ± 1.14%). The level of phospho‐GRK2 decreased in the treated group, suggesting that GRK2 activity was reduced upon GRK2 inhibition. Furthermore, the addition of βi decreased Ca2+ release from the ER. The protein levels of cyclin B and cyclin‐dependent kinase 1 were higher in the treatment group than those in the control group, indicating that GRK2 inhibition prevented a decrease in MPF activity. Collectively, GRK2 inhibition induced meiotic arrest at the MI stage in porcine oocytes by preventing a decrease in MPF activity, suggesting that GRK2 is essential for oocyte meiotic maturation in pigs. [ABSTRACT FROM AUTHOR]

Graph matching is a commonly used technique in computer vision and pattern recognition. Recent data-driven approaches have improved the graph matching accuracy remarkably, whereas some traditional algorithm-based methods are more robust to feature noises, outlier nodes, and global transformation (e.g. rotation). In this paper, we propose a graph neural network (GNN) based approach to combine the advantage of data-driven and traditional methods. In the GNN framework, we transform traditional graph matching solvers as single-channel GNNs on the association graph and extend the single-channel architecture to the multi-channel network. The proposed model can be seen as an ensemble method that fuses multiple algorithms at every iteration. Instead of averaging the estimates at the end of the ensemble, in our approach, the independent iterations of the ensembled algorithms exchange their information after each iteration via a 1 × 1 channel-wise convolution layer. Experiments show that our model improves the performance of traditional algorithms significantly. In addition, we propose a random sampling strategy to reduce the computational complexity and GPU memory usage, so that the model is applicable to matching graphs with thousands of nodes. We evaluate the performance of our method on three tasks: geometric graph matching, semantic feature matching, and few-shot 3D shape classification. The proposed model performs comparably or outperforms the best existing GNN-based methods. [ABSTRACT FROM AUTHOR]

Identifying and categorizing drilling-induced fractures is pivotal for understanding the mechanisms underlying wellbore instability, drilling fluid loss, and assessing reservoirs using imaging logging data. This study employs a linear elastic stress model around the wellbore, coupled with a tensile failure criterion, to establish a predictive framework for the orientation of drilling-induced fractures. It investigates how engineering parameters like wellbore trajectory and bottomhole pressure influence the distribution of principal stresses around the wellbore, as well as the angle and orientation of drilling-induced fractures relative to the wellbore axis, across various faulting scenarios. The results indicate that drilling-induced fractures exhibit structured arrangements and consistent patterns, often appearing at approximately 180° symmetric intervals and descending in similar orientations. This provides a theoretical basis for their systematic identification and classification. Under different stress conditions, these fractures can manifest as feather-like shapes, "J"-shaped, or transitional states between feather-like and "J"-shaped orientations, as well as "V"-shaped or "M"-shaped orientations. Accurate detection and classification of these fractures are essential for interpreting effective fractures, conducting thorough reservoir evaluations, and predicting appropriate drilling fluid densities to mitigate the wellbore failure risk. Moreover, this knowledge aids in effectively determining the magnitude and direction of in situ stress inversion. [ABSTRACT FROM AUTHOR]

The investigation focused on the precipitation behavior and mechanism during ferrite transformation in a Nb-alloyed steel, revealing a diverse range of NbC morphologies. The presence of interphase precipitation in regular sheet planes with three variants was attributed to a higher interfacial migration rate, while the non-uniform sheet spacing of interphase precipitation increased as the phase boundary approached. A qualitative analysis using the solute drag effect (SDE) model may potentially elucidate the non-uniform sheet spacing observed. [ABSTRACT FROM AUTHOR]

Background: Resistance training is often a part of the routine training regimen for competitive swimmers. However, due to the variety of resistance training methodology, the results can be inconsistent and sometimes unsatisfactory. Clear recommendations are still lacking at present. Aims: 1) Quantify the impact of resistance training on swimmers' upper limb maximum strength, front crawl performance and key technical parameters; 2) Find out the key technical parameters for improving front crawl performanceâ€"stroke rate or length; 3) Through subgroup analysis determine the best methodology of resistance training to enhance the front crawl. Methods: Systematic search in the PubMed, Embase, and Web of Science databases. Meta-analyses using the inverse-variance are performed to compare swimmers' upper limb maximum strength, front crawl performance and key technical parameters in resistance training and habitual aquatic training. A subgroup analysis was performed to examine whether the results were affected by the methodology of resistance training. Results: Thirteen studies (267 competitive swimmers) met the inclusion criteria. The results of meta-analysis showed that resistance training significantly improved upper limbs maximum muscle strength, and 25, 50, 100, and 200 m front crawl performance in competitive swimmers. And improvements in swimming performance may simply resulted from resistance training increasing stroke rate rather than stroke length. In addition, the results of subgroup analysis showed that only concurrent resistance training (CRT) and power training (PT) ultimately improved swimming performance by increasing the maximum muscle strength of the upper limbs. Conclusion: Resistance training significantly enhances competitive swimmers' upper limb strength and front crawl performance across various distances. The improvement in performance is likely attributed to an increased stroke rate rather than stroke length. In addition, CRT and PT are particularly effective, indicating the importance of selecting the appropriate methodology of resistance training for optimal swimming performance enhancement. [ABSTRACT FROM AUTHOR]

Exciton-driven strong light–matter interactions in two-dimensional materials have displayed their advantages in applications in optoelectronics and photonics. However, the large exciton binding energy prohibits the efficient separation of photoexcited electron–hole pairs and is unfavorable for the application of photoelectrics and photovoltaics. Here, based on density-functional theory with the many-body perturbation method, we study the evolution of quasiparticle band structure, exciton, and optical properties with biaxial strain in 2D Hittorf's phosphorene. The pristine and +1% strained Hittorf's phosphorene are direct-band-gap semiconductors with the valence band maximal and the conduction band minimal located at the X point. When strain is approaching +2%, the conduction band minimal changes from the X point to the Γ point, resulting in a transition to the indirect band gap. This kind of indirect band gap persists to +5%. For the optical gap, we observe a modulation threshold of 0.33 eV over a +5% strain range. It is revealed that a p–n junction with efficient electron–hole excitation and separation is naturally formed in inhomogeneously strained 2D membrane. The transition from direct-band-gap to indirect-band-gap semiconductor, the strongly enhanced exciton lifetime, and the spatial separation of photoexcited electron–hole pairs under a moderate electric field will further inhibit the recombination. Together with the efficient visible light absorption which guarantees the absorption of solar spectra, these findings provide an effective avenue toward solar energy harvesting. [ABSTRACT FROM AUTHOR]

Background: Gastroesophageal reflux disease (GERD) is a common condition characterized by the reflux of stomach contents into the esophagus. Despite its widespread prevalence worldwide, the causal link between GERD and various cancer risks has not been fully established, and past medical research has often underestimated or overlooked this relationship. Methods: This study performed Mendelian randomization (MR) to investigate the causal relationship between GERD and 19 different cancers. We leveraged data from 129,080 GERD patients and 473,524 controls, along with cancer-related data, obtained from the UK Biobank and various Genome-Wide Association Studies (GWAS) consortia. Single nucleotide polymorphisms (SNPs) associated with GERD were used as instrumental variables, utilizing methods such as inverse variance weighting, weighted median, and MR-Egger to address potential pleiotropy and confounding factors. Results: GERD was significantly associated with higher risks of nine types of cancer. Even after adjusting for all known risk factors—including smoking, alcohol consumption, major depression, and body mass index (BMI)—these associations remained significant, with higher risks for most cancers. For example, the adjusted risk for overall lung cancer was (OR, 1.23; 95% CI: 1.14–1.33), for lung adenocarcinoma was (OR, 1.18; 95% CI: 1.03–1.36), for lung squamous cell carcinoma was (OR, 1.35; 95% CI: 1.19–1.53), and for oral cavity and pharyngeal cancer was (OR, 1.73; 95% CI: 1.22–2.44). Especially noteworthy, the risk for esophageal cancer increased to (OR, 2.57; 95% CI: 1.23–5.37). Mediation analyses further highlighted GERD as a significant mediator in the relationships between BMI, smoking, major depression, and cancer risks. Conclusions: This study identifies a significant causal relationship between GERD and increased cancer risk, highlighting its role in cancer development and underscoring the necessity of incorporating GERD management into cancer prevention strategies. [ABSTRACT FROM AUTHOR]

SUMMARY: We examine auditor communication provisions (ACPs) in private loan agreements, which are private contracting mechanisms establishing communication between lenders and their borrowers' auditors. We provide evidence that lenders value auditor communications and often specify different types of ACPs that facilitate lender monitoring. With predictable variation across the different ACP types, ACPs are associated with larger loans, longer maturities, larger loan syndicates, more financial covenants, and greater slack in financial covenants. In examining audit effort implications for borrowers, we find that ACPs are associated with higher audit fees and longer audit report lags. This is consistent with auditors responding to the litigation risk ACPs impose. In samples where the risk of third-party litigation is greater, the association between ACPs and audit effort proxies is heightened, suggesting the increased litigation risk brought about by ACPs interacts with other audit client-specific risk factors. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: M42; D82; G21; G30; K40. [ABSTRACT FROM AUTHOR]

Development of potent and broad‐spectrum drugs against severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) remains one of the top priorities, especially in the cases of the emergence of mutant viruses and inability of current vaccines to prevent viral transmission. In this study, we have generated a novel membrane fusion‐inhibitory lipopeptide IPB29, which is currently under clinical trials; herein, we report its design strategy and preclinical data. First, we surprisingly found that IPB29 with a rigid linker between the peptide sequence and lipid molecule had greatly improved α‐helical structure and antiviral activity. Second, IPB29 potently inhibited a large panel of SARS‐CoV‐2 variants including the previously and currently circulating viruses, such as Omicron XBB.5.1 and EG.5.1. Third, IPB29 could also cross‐neutralize the bat‐ and pangolin‐isolated SARS‐CoV‐2‐related CoVs (RatG13, PCoV‐GD, and PCoV‐GX) and other human CoVs (SARS‐CoV, MERS‐CoV, HCoV‐NL63, and HCoV‐229E). Fourth, IPB29 administrated as an inhalation solution (IPB29‐IS) in Syrian hamsters exhibited high therapeutic and preventive efficacies against SARS‐CoV‐2 Delta or Omicron variant. Fifth, the pharmacokinetic profiles and safety pharmacology of IPB29‐IS were extensively characterized, providing data to support its evaluation in humans. In conclusion, our studies have demonstrated a novel design strategy for viral fusion inhibitors and offered an ideal drug candidate against SARS‐CoV‐2 and other coronaviruses. [ABSTRACT FROM AUTHOR]

Clavulina possesses important ecological and economic value and has attracted extensive attention from mycologists. Macrofungal diversity is high in China, but Clavulina species have not been thoroughly studied. In this study, based on morphological evidence and phylogenetic analyses of the nucleotide sequences of three loci (nrITS, nrLSU, and rpb2), three new species of Clavulina from North China were identified. Morphologically, Clavulina chengdeensis is characterized by its white to dirty white basidiomata with somewhat pale orange tips and somewhat wrinkled hymenium. Clavulina griseoviolacea is characterized by its gray to dark grayish violet basidiomata, with a sometimes-white stipe base, monopodial or irregularly polychotomous toward branch apices. Clavulina pallida is characterized by its white to pale cream white basidiomata with somewhat orange tips. Phylogenetically, the three new species form three independent branches with high support values in the phylogenetic tree. [ABSTRACT FROM AUTHOR]

Background: CT‐image segmentation for liver and hepatic vessels can facilitate liver surgical planning. However, time‐consuming process and inter‐observer variations of manual segmentation have limited wider application in clinical practice. Purpose: Our study aimed to propose an automated deep learning (DL) segmentation algorithm for liver and hepatic vessels on portal venous phase CT images. Methods: This retrospective study was performed to develop a coarse‐to‐fine DL‐based algorithm that was trained, validated, and tested using private 413, 52, and 50 portal venous phase CT images, respectively. Additionally, the performance of the DL algorithm was extensively evaluated and compared with manual segmentation using an independent clinical dataset of preoperative contrast‐enhanced CT images from 44 patients with hepatic focal lesions. The accuracy of DL‐based segmentation was quantitatively evaluated using the Dice Similarity Coefficient (DSC) and complementary metrics [Normalized Surface Dice (NSD) and Hausdorff distance_95 (HD95) for liver segmentation, Recall and Precision for hepatic vessel segmentation]. The processing time for DL and manual segmentation was also compared. Results: Our DL algorithm achieved accurate liver segmentation with DSC of 0.98, NSD of 0.92, and HD95 of 1.52 mm. DL‐segmentation of hepatic veins, portal veins, and inferior vena cava attained DSC of 0.86, 0.89, and 0.94, respectively. Compared with the manual approach, the DL algorithm significantly outperformed with better segmentation results for both liver and hepatic vessels, with higher accuracy of liver and hepatic vessel segmentation (all p < 0.001) in independent 44 clinical data. In addition, the DL method significantly reduced the manual processing time of clinical postprocessing (p < 0.001). Conclusions: The proposed DL algorithm potentially enabled accurate and rapid segmentation for liver and hepatic vessels using portal venous phase contrast CT images. [ABSTRACT FROM AUTHOR]

Treatment options for epidermal growth factor receptor (EGFR)-mutant advanced non-small cell lung cancer (NSCLC) following tyrosine kinase inhibitor (TKI) failure are limited, and platinum-based chemotherapy remains the main treatment. The development of effective immunotherapy for this disease has been challenging. In the present study, 37 patients with EGFR-mutant advanced NSCLC who were treated with programmed cell death-1 (PD-1) inhibitor-based combinations after TKI failure were reviewed. The total cohort had a median progression-free survival (mPFS) of 5.2 months (95% CI, 4.077-6.323 months) and a median overall survival (mOS) of 18.3 months (95% CI, 12.932-23.668 months). Patients with Eastern Cooperative Oncology Group performance-status (ECOG-PS) scores of 0 or 1 had longer mPFS than those with ECOG-PS scores of 2 (5.4 vs. 2.4 months; P=0.006). In addition, a PFS benefit was observed in patients with EGFR T790M-negative compared with EGFR T790M-positive tumors (mPFS 6.2 vs. 4.4 months; P=0.041). Patients treated with immunotherapy-based combinations as a front-line therapy had a longer mPFS than those in which the combinations were used as a late-line therapy (6.2 vs. 2.4 months; P<0.001). PD-1 inhibitor combined with chemotherapy and bevacizumab did not show a clear advantage over PD-1 inhibitor combined with chemotherapy alone (mPFS, 6.2 vs. 4.4 months; P=0.681), although it resulted in an improved overall response rate (ORR) and disease control rate. Notably, the 7 patients with a programmed cell death ligand-1 (PD-L1) tumor proportion score of ≥50% had an ORR of 100% and an mPFS of 8.3 months. Therefore, it is suggested that PD-1 inhibitor-based combinations should be a priority treatment option in selective populations, such as those with low ECOG-PS scores, T790M-negative status or high PD-L1 expression in EGFR-mutant NSCLC after TKI failure. The use of immunotherapy and chemotherapy in combination with antiangiogenic agents appears to be a promising combination therapy for such patients. [ABSTRACT FROM AUTHOR]

Background: Metabolic dysregulation is recognized as a significant hallmark of cancer progression. Although numerous studies have linked specific metabolic pathways to cancer incidence, the causal relationship between blood metabolites and lung cancer risk remains unclear. Methods: Genomic data from 29,266 lung cancer patients and 56,450 control individuals from the Transdisciplinary Research in Cancer of the Lung and the International Lung Cancer Consortium (TRICL-ILCCO) were utilized, and findings were replicated using additional data from the FinnGen consortium. The analysis focused on the associations between 486 blood metabolites and the susceptibility to overall lung cancer and its three major clinical subtypes. Various Mendelian randomization methods, including inverse-variance weighting, weighted median estimation, and MR-Egger regression, were employed to ensure the robustness of our findings. Results: A total of 19 blood metabolites were identified with significant associations with lung cancer risk. Specifically, oleate (OR per SD = 2.56, 95% CI: 1.51 to 4.36), 1-arachidonoylglyceropholine (OR = 1.79, 95% CI: 1.22 to 2.65), and arachidonate (OR = 1.67, 95% CI: 1.16 to 2.40) were associated with a higher risk of lung cancer. Conversely, 1-linoleoylglycerophosphoethanolamine (OR = 0.57, 95% CI: 0.40 to 0.82), ADpSGEGDFXAEGGGVR, a fibrinogen cleavage peptide (OR = 0.60, 95% CI: 0.47 to 0.77), and isovalerylcarnitine (OR = 0.62, 95% CI: 0.49 to 0.78) were associated with a lower risk of lung cancer. Notably, isoleucine (OR = 9.64, 95% CI: 2.55 to 36.38) was associated with a significantly higher risk of lung squamous cell cancer, while acetyl phosphate (OR = 0.11, 95% CI: 0.01 to 0.89) was associated with a significantly lower risk of small cell lung cancer. Conclusion: This study reveals the complex relationships between specific blood metabolites and lung cancer risk, highlighting their potential as biomarkers for lung cancer prevention, screening, and treatment. The findings not only deepen our understanding of the metabolic mechanisms of lung cancer but also provide new insights for future treatment strategies. [ABSTRACT FROM AUTHOR]

Developing highly efficient catalysts for carbon dioxide reduction reaction (CO2RR) is significant in producing useful chemicals and alleviating environmental pollution. Herein, a series of two-dimensional TM-PTC (TM = Sc-Zn, PTC = 1,2,3,4,5,6,7,8,9,10,11,12-perthiolated coronene) frameworks as CO2RR electrocatalysts are investigated based on the density functional method. The calculated results showed that the main product is CH4 for TM-PTC (TM = Sc-Mn). However, these catalysts can be poisoned by water molecules due to its strong adsorption on the catalyst surface. To solve the problem, we modified these catalysts by adding axial oxygen (TM-O-PTC). Our study showed that TM-O-PTC (TM = V, Cr) are good catalysts for CO2RR to produce CH4. We expected that this work could provide a useful strategy for developing high-performance CO2RR electrocatalysts. [ABSTRACT FROM AUTHOR]

A high proportion of new energy has become a prominent feature of modern power systems. Due to the intermittency, volatility, and strong randomness in wind power generation, an accurate and reliable method for the prediction of wind power is required. This paper proposes a modified stacking ensemble learning method for short-term wind power predictions to reduce error and improve the generalization performance of traditional single networks in tackling the randomness of wind power. Firstly, the base learners including tree-based models and neural networks are improved based on the Bagging and Boosting algorithms, and a method for determining internal parameters and iterations is provided. Secondly, the linear integration and stacking integration models are combined to obtain deterministic prediction results. Since the modified stacking meta learner can change the weight, it will enhance the strengths of the base learners and optimize the integration of the model prediction to fit the second layer prediction, compared to traditional linear integration models. Finally, a numerical experiment showed that the modified stacking ensemble model had a decrease in MAPE from about 8.3% to 7.5% (an absolute decrease of 0.8%) compared to a single learner for the 15 min look-ahead tests. Changing variables such as the season and predicting the look-ahead time showed satisfactory improvement effects under all the evaluation criteria, and the superiority of the modified stacking ensemble learning method proposed in this paper regarding short-term wind power prediction performance was validated. [ABSTRACT FROM AUTHOR]

Background: Microbial infection and colonization are frequently associated with disease progression and poor clinical outcomes in bronchiectasis. Identification of pathogen spectrum is crucial for precision treatment at exacerbation of bronchiectasis. Methods: We conducted a prospective cohort study in patients with bronchiectasis exacerbation onset and stable state. Bronchoalveolar lavage fluid (BALF) was collected for conventional microbiological tests (CMTs) and metagenomic Next-Generation Sequencing (mNGS). Bronchiectasis patients were monitored for documenting the time to the next exacerbation during longitudinal follow-up. Results: We recruited 168 eligible participants in the exacerbation cohorts, and 38 bronchiectasis patients at stable state at longitudinal follow-up. 141 bronchiectasis patients at exacerbation onset had definite or probable pathogens via combining CMTs with mNGS reports. We identified that Pseudomonas aeruginosa, non-tuberculous mycobacteria, Haemophilus influenzae, Nocardia spp, and Staphylococcus aureus were the top 5 pathogens with a higher detection rate in our cohorts via combination of CMTs and mNGS analysis. We also observed strong correlations of Pseudomonas aeruginosa, Haemophilus influenzae, non-tuberculous mycobacteria with disease severity, including the disease duration, Bronchiectasis Severity Index, and lung function. Moreover, the adjusted pathogenic index of potential pathogenic microorganism negatively correlated (r = -0.7280, p < 0.001) with the time to the next exacerbation in bronchiectasis. Conclusion: We have revealed the pathogenic microbial spectrum in lower airways and the negative correlation of PPM colonization with the time to the next exacerbation in bronchiectasis. These results suggested that pathogens contribute to the progression of bronchiectasis. [ABSTRACT FROM AUTHOR]

Objective: To examine the dose-response relationship between specific types of exercise for alleviating Timed up and Go (TUG) in Parkinson's disease PD. Design: Systematic review and Bayesian network meta-analysis. Data sources: PubMed, Medline, Embase, PsycINFO, Cochrane Library, and Web of Science were searched from inception until February 5th, 2024. Study analysis: Data analysis was conducted using R software with the MBNMA package. Effect sizes of outcome indicators were expressed as mean deviation (MD) and 95% confidence intervals (95% CrI). The risk of bias in the network was evaluated independently by two reviewers using ROB2. Results: A total of 73 studies involving 3,354 PD patients. The text discusses dose- response relationships in improving TUG performance among PD patients across various exercise types. Notably, Aquatic (AQE), Mix Exercise (Mul_C), Sensory Exercise (SE), and Resistance Training (RT) demonstrate effective dose ranges, with AQE optimal at 1500 METs-min/week (MD: -8.359, 95% CI: -1.398 to -2.648), Mul_C at 1000 METs-min/week (MD: -4.551, 95% CI: -8.083 to -0.946), SE at 1200 METs-min/week (MD: -5.145, 95% CI: -9.643 to -0.472), and RT at 610 METs-min/week (MD: -2.187, 95% CI: -3.161 to -1.278), respectively. However, no effective doses are found for Aerobic Exercise (AE), Balance Gait Training (BGT), Dance, and Treadmill Training (TT). Mind-body exercise (MBE) shows promise with an effective range of 130 to 750 METs-min/week and an optimal dose of 750 METs-min/week (MD: -2.822, 95% CI: -4.604 to -0.996). According to the GRADE system, the included studies' overall quality of the evidence was identified moderate level. Conclusion: This study identifies specific exercise modalities and dosages that significantly enhance TUG performance in PD patients. AQE emerges as the most effective modality, with an optimal dosage of 1,500 METs-min/week. MBE shows significant benefits at lower dosages, catering to patients with varying exercise capacities. RT exhibits a nuanced "U-shaped" dose-response relationship, suggesting an optimal range balancing efficacy and the risk of overtraining. These findings advocate for tailored exercise programs in PD management, emphasizing personalized prescriptions to maximize outcomes. [ABSTRACT FROM AUTHOR]

Background: Prostate cancer, characterized by its insidious onset and short overall survival, and has seen a rise in incidence over recent decades. This study aims to investigate the expression and molecular mechanism of lncRNA PTCSC3 (PTCSC3) in prostate cancer in order to develop new prognostic and therapeutic biomarkers. Methods: The level of PTCSC3 in serum and cell samples of prostate cancer was quantitatively measured using RT-qPCR assays. The correlation between the variation in PTCSC3 levels and clinical indicators of patients was evaluated. The survival status of the prostate cancer patients included in the study was evaluated using Kaplan-Meier curve and multivariable Cox analysis. The impact of PTCSC3 overexpression on cell growth and activity was revealed by CCK-8 and Transwell assays. The targeting relationship between PTCSC3 and miR-182-5p was determined by bioinformatics prediction and luciferase activity. Results: PTCSC3 was found to be downregulated in prostate cancer, and its low levels were associated with short overall survival in patients. It influenced the progression of prostate cancer by targeting miR-182-5p. Increasing PTCSC3 levels suppressed the proliferation, migration and invasion levels of cells, and miR-182-5p mimic counteracted PTCSC3's effects on cells. Conclusions: As a potential prognostic biological factor for prostate cancer, PTCSC3 may regulate the progression of prostate cancer by sponging miR-182-5p and affect the prognosis of patients. [ABSTRACT FROM AUTHOR]

Background: Subarachnoid hemorrhage (SAH) is a subtype of hemorrhagic stroke characterized by high mortality and low rates of full recovery. This study aimed to investigate the epidemiological characteristics of SAH between 1990 and 2021. Methods: Data on SAH incidence, mortality, and disability-adjusted life-years (DALYs) from 1990 to 2021 were obtained from the Global Burden of Disease Study (GBD) 2021. Estimated annual percentage changes (EAPCs) were calculated to evaluate changes in the age-standardized rate (ASR) of incidence and mortality, as well as trends in SAH burden. The relationship between disease burden and sociodemographic index (SDI) was also analyzed. Results: In 2021, the incidence of SAH was found to be 37.09% higher than that in 1990; however, the age-standardized incidence rates (ASIRs) showed a decreased [EAPC: -1.52; 95% uncertainty interval (UI) -1.66 to -1.37]. Furthermore, both the number and rates of deaths and DALYs decreased over time. It was observed that females had lower rates compared to males. Among all regions, the high-income Asia Pacific region exhibited the highest ASIR (14.09/100,000; 95% UI 12.30/100,000 − 16.39/100,000) in 2021, with an EPAC for ASIR < 0 indicating decreasing trend over time for SAH ASIR. Oceania recorded the highest age-standardized mortality rates (ASMRs) and age-standardized DALYs rates among all regions in 2021 at values of respectively 8.61 (95% UI 6.03 − 11.95) and 285.62 (95% UI 209.42 − 379.65). The burden associated with SAH primarily affected individuals aged between 50 − 69 years old. Metabolic risks particularly elevated systolic blood pressure were identified as the main risk factors contributing towards increased disease burden associated with SAH when compared against environmental or occupational behavioral risks evaluated within the GBD framework. Conclusions: The burden of SAH varies by gender, age group, and geographical region. Although the ASRs have shown a decline over time, the burden of SAH remains significant, especially in regions with middle and low-middle SDI levels. High systolic blood pressure stands out as a key risk factor for SAH. More specific supportive measures are necessary to alleviate the global burden of SAH. [ABSTRACT FROM AUTHOR]

Polymers are ideally utilized as damping materials due to the high internal friction of molecular chains, enabling effective suppression of vibrations and noises in various fields. Current strategies rely on broadening the glass transition region or introducing additional relaxation components to enhance the energy dissipation capacity of polymeric damping materials. However, it remains a significant challenge to achieve high damping efficiency through structural control while maintaining dynamic characteristics. In this work, we propose a new strategy to develop hyperbranched vitrimers (HBVs) containing dense pendant chains and loose dynamic crosslinked networks. A novel yet weak dynamic transesterification between the carboxyl and boronic acid ester was confirmed and used to prepare HBVs based on poly (hexyl methacrylate‐2‐(4‐ethenylphenyl)‐5,5‐dimethyl‐1,3,2‐dioxaborinane) P(HMA‐co‐ViCL) copolymers. The ABn ${{AB}_{n}}$ ‐type of macromonomers, the crosslinking points formed by the dynamic covalent connection via the associative exchange, and the weak yet dynamic exchange reaction are the three keys to developing high‐performance HBV damping materials. We found that P(HMA‐co‐ViCL) 20k‐40‐60 HBV exhibited ultrahigh energy‐dissipation performance over a broad frequency and temperature range, attributed to the synergistic effect of dense pendant chains and weak dynamic covalent crosslinks. This unique design concept will provide a general approach to developing advanced damping materials. [ABSTRACT FROM AUTHOR]

Polymers are ideally utilized as damping materials due to the high internal friction of molecular chains, enabling effective suppression of vibrations and noises in various fields. Current strategies rely on broadening the glass transition region or introducing additional relaxation components to enhance the energy dissipation capacity of polymeric damping materials. However, it remains a significant challenge to achieve high damping efficiency through structural control while maintaining dynamic characteristics. In this work, we propose a new strategy to develop hyperbranched vitrimers (HBVs) containing dense pendant chains and loose dynamic crosslinked networks. A novel yet weak dynamic transesterification between the carboxyl and boronic acid ester was confirmed and used to prepare HBVs based on poly (hexyl methacrylate‐2‐(4‐ethenylphenyl)‐5,5‐dimethyl‐1,3,2‐dioxaborinane) P(HMA‐co‐ViCL) copolymers. The ABn ${{AB}_{n}}$ ‐type of macromonomers, the crosslinking points formed by the dynamic covalent connection via the associative exchange, and the weak yet dynamic exchange reaction are the three keys to developing high‐performance HBV damping materials. We found that P(HMA‐co‐ViCL) 20k‐40‐60 HBV exhibited ultrahigh energy‐dissipation performance over a broad frequency and temperature range, attributed to the synergistic effect of dense pendant chains and weak dynamic covalent crosslinks. This unique design concept will provide a general approach to developing advanced damping materials. [ABSTRACT FROM AUTHOR]

Cryptococcus neoformans is at the top of the list of "most wanted" human pathogens. Only three classes of antifungal drugs are available for the treatment of cryptococcosis. Studies on antifungal resistance mechanisms are limited to the investigation of how a particular antifungal drug induces resistance to a particular drug, and the impact of stresses other than antifungals on the development of antifungal resistance and even cross-resistance is largely unexplored. The endoplasmic reticulum (ER) is a ubiquitous subcellular organelle of eukaryotic cells. Brefeldin A (BFA) is a widely used chemical inducer of ER stress. Here, we found that both weak and strong selection by BFA caused aneuploidy formation in C. neoformans, mainly disomy of chromosome 1, chromosome 3, and chromosome 7. Disomy of chromosome 1 conferred cross-resistance to two classes of antifungal drugs: fluconazole and 5-flucytosine, as well as hypersensitivity to amphotericin B. However, drug resistance was unstable, due to the intrinsic instability of aneuploidy. We found overexpression of AFR1 on Chr1 and GEA2 on Chr3 phenocopied BFA resistance conferred by chromosome disomy. Overexpression of AFR1 also caused resistance to fluconazole and hypersensitivity to amphotericin B. Furthermore, a strain with a deletion of AFR1 failed to form chromosome 1 disomy upon BFA treatment. Transcriptome analysis indicated that chromosome 1 disomy simultaneously upregulated AFR1, ERG11, and other efflux and ERG genes. Thus, we posit that BFA has the potential to drive the rapid development of drug resistance and even cross-resistance in C. neoformans, with genome plasticity as the accomplice. [ABSTRACT FROM AUTHOR]

Three distinct morphologies of Bi‐MOFs were innovatively employed as carriers, facilitating the formation of heterojunctions with BiPO4. Among these, the optimal photocatalytic performance was demonstrated by the type II heterojunction BiPO4/CAU‐17. Bi3+ competitively coordinated to crucially aid CAU‐17's transformation into a heterojunction, enhancing interfacial contact in BiPO4/CAU‐17. These photocatalysts effectively degraded dyes (RhB, MO, MB) and tetracycline (TC) under light exposure. RhB degradation was 3.33 times faster with BiPO4/CAU‐17 than BiPO4, 1.45 times faster than FCAU‐17, 1.36 times faster than FRCAU‐17, and 1.32 times faster than CAU‐17. Analyzing carrier density, Fermi level, and band structure through VB‐XPS, UV–VIS, and Mott–Schottky provided insights into enhanced separation of photoexcited electron–hole pairs. This study presents a novel approach to tackle the aggregation challenge of the wide‐bandgap material BiPO4 by using suitable MOFs as carriers. It offers valuable perspectives for the design and application of photocatalysts in environmental remediation. [ABSTRACT FROM AUTHOR]

Neuropeptide Y (NPY), a 36‐amino‐acid peptide, functions as a neurotransmitter in both the central and peripheral nervous systems by activating the NPY receptor subfamily. Notably, NPY analogs display varying selectivity and exert diverse physiological effects through their interactions with this receptor family. [Pro34]–NPY and [Leu31, Pro34]–NPY, mainly acting on Y1R, reportedly increases blood pressure and postsynaptically potentiates the effect of other vasoactive substances above all, while N‐terminal cleaved NPY variants in human body primary mediates angiogenesis and neurotransmitter release inhibition through Y2R. However, the recognition mechanisms of Y1R and Y2R with specific agonists remain elusive, thereby hindering subtype receptor‐selective drug development. In this study, we report three cryo‐electron microscopy (cryo‐EM) structures of Gi2‐coupled Y1R and Y2R in complexes with NPY, as well as Y1R bound to a selective agonist [Leu31, Pro34]–NPY. Combined with cell‐based assays, our study not only reveals the conserved peptide‐binding mode of NPY receptors but also identifies an additional sub‐pocket that confers ligand selectivity. Moreover, our analysis of Y1R evolutionary dynamics suggests that this sub‐pocket has undergone functional adaptive evolution across different species. Collectively, our findings shed light on the molecular underpinnings of neuropeptide recognition and receptor activation, and they present a promising avenue for the design of selective drugs targeting the NPY receptor family. [ABSTRACT FROM AUTHOR]

The utilization of optical antennas for active control of far-field radiation at the subwavelength scale is crucial in various scientific and technological applications. We propose a thermally tunable disk design of indium tin oxide (ITO) and aluminum gallium nitride ( Al 0.18 Ga 0.82 As ), enabling a switch between absorption and scattering. Furthermore, the control of far-field radiation pattern can be easily realized by combining ITO and Al 0.18 Ga 0.82 As to enhance or suppress emission. Our results demonstrate that hybrid structures can be dynamically tuned with temperature variations. In the proposed design, a frequency is achieved at the wavelength of 1240 nm. The thermal tunability of hybrid structures introduces new multifunctional possibilities for light manipulation, thereby enhancing the potential applications of new devices in the near-infrared range. [ABSTRACT FROM AUTHOR]

Cyberbullying is considered a major threat to adolescent anxiety. In this study, we aim to explore the simultaneous effects of cyberbullying victimization and perpetration on youth anxiety. Building on the childhood adversity model and the vulnerability‐stress model, we test the model wherein cyberbullying exposure is linked with cyberostracism, which in turn is expected to be associated with an increase in anxiety. We collected data from 1115 Chinese youth aged 11–19 years based on the stratified random sampling method. Structure equation modelling was conducted in Amos 26.0 to examine the proposed theoretical model. The findings suggested that compared with cyberbullying perpetration, the experience of cyberbullying victimization led to a significantly higher risk of youth anxiety. Multiple mediation analyses revealed that the three dimensions of cyberostracism, namely cyber direct excluded, cyber indirect excluded and cyber ignored, mediated the association of cyberbullying victimization and perpetration with youth anxiety. These results indicate that cyberostracism could be a risk factor for youth anxiety, thus providing new direction regarding intervention programs to reduce anxiety symptoms in adolescents. [ABSTRACT FROM AUTHOR]

Objective: Thoracolumbar fractures are one of the most common fractures in clinical practice. Surgical intervention is recommended to restore spinal alignment or decompress the nerves when there are unstable fractures or neurological injuries. However, after excessive forward thrust force restoration, facet joint dislocation often occurs between the upper vertebra and the fractured vertebra, which usually leads to unsatisfactory reduction outcomes. Herein, we propose a novel spinal facet joint toothed plate to assist in fracture reduction. The purpose of this study is to evaluate the effectiveness of the new spinal facet joint toothed plate in preventing facet joint dislocation, and its advantages compared to traditional pedicle screw‐rod decompression. Methods: A total of 26 patients in the toothed plate group and 93 patients in the traditional group who experienced thoracolumbar fracture with reduction were retrospectively included. Relevant patients' information and clinical parameters were collected. Furthermore, visual analogue scores (VAS) scores and Oswestry disability index (ODI) scores were also collected. Moreover, imaging parameters were calculated based on radiographs. Correlated data were analyzed by χ2 test and t test. Results: All patients in this study had no postoperative complications. Postoperative VAS scores and ODI scores (p < 0.001) were statistically significant (p < 0.001) in both groups compared with preoperative scores and further decreased (p < 0.001) at final follow‐up. In addition, the postoperative vertebral margin ratio (VMR) (p < 0.001) and vertebral angle of the injured vertebrae (p < 0.001) were significantly improved compared with the preoperative period. There were no significant differences in postoperative VAS scores and ODI scores between the two groups. However, toothed plate reduction significantly improved the VMR (p < 0.05) and vertebral angle (p < 0.05) compared with conventional reduction. Ultimately, the total screw accuracy was 98.72% (sum of levels 0 and I), with 100% screw accuracy in the segment related to the tooth plate in the tooth plate group. The dislocation rate was higher in the conventional group (6.45%) than in the new serrated plate repositioning group (0.00%). Conclusion: The facet toothed plate assisted reduction method prevents facet joint dislocation and improves fracture reduction compared to traditional reduction technique, hence it could be considered as a novel surgical strategy for thoracolumbar fracture reduction. [ABSTRACT FROM AUTHOR]

Foldamer is a scaled‐down version of coil spring, which can absorb and release energy by conformational change. Here, polymer networks with high density of molecular springs were developed by employing anion‐coordination‐based foldamers as the monomer. The coiling of the foldamer is controlled by oligo(urea) ligands coordinating to chloride ions; subsequently, the folding and unfolding of foldamer conformations endow the polymer network with excellent energy dissipation and toughness. The mechanical performance of the corresponding polymer networks shows a dramatic increase from P‐L2UCl (non‐folding), to P‐L4UCl (a full turn), and then to P‐L6UCl (1.5 turns), in terms of strength (2.62 MPa; 14.26 MPa; 22.93 MPa), elongation at break (70 %; 325 %; 352 %), Young's modulus (2.69 MPa; 63.61 MPa; 141.50 MPa), and toughness (1.12 MJ/m3; 21.39 MJ/m3; 49.62 MJ/m3), respectively, which is also better than those without anion centers and the non‐foldamer based counterparts. Moreover, P‐L6UCl shows enhanced strength and toughness than most of the molecular‐spring based polymer networks. Thus, an effective strategy for designing high‐performance anion‐coordination‐based materials is presented. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to develop a web‐based dynamic prediction model for postoperative nausea and vomiting (PONV) in patients undergoing gynecologic laparoscopic surgery. Methods: The patients (N = 647) undergoing gynecologic laparoscopic surgery were included in this observational study. The candidate risk‐factors related to PONV were included through literature search. Lasso regression was utilized to screen candidate risk‐factors, and the variables with statistical significance were selected in multivariable logistic model building. The web‐based dynamic Nomogram was used for model exhibition. Accuracy and validity of the experimental model (EM) were evaluated by generating receiver operating characteristic (ROC) curves and calibration curves. Hosmer–Lemeshow test was used to evaluate the goodness of fit of the model. Decision curve analysis (DCA) was used to evaluate the clinical practicability of the risk prediction model. Results: Ultimately, a total of five predictors including patient‐controlled analgesia (odds ratio [OR], 4.78; 95% confidence interval [CI], 1.98–12.44), motion sickness (OR, 4.80; 95% CI, 2.71–8.65), variation of blood pressure (OR, 4.30; 95% CI, 2.41–7.91), pregnancy vomiting history (OR, 2.21; 95% CI, 1.44–3.43), and pain response (OR, 1.64; 95% CI, 1.48–1.83) were selected in model building. Assessment of the model indicates the discriminating power of EM was adequate (ROC‐areas under the curve, 93.0%; 95% CI, 90.7%–95.3%). EM showed better accuracy and goodness of fit based on the results of the calibration curve. The DCA curve of EM showed favorable clinical benefits. Conclusions: This dynamic prediction model can determine the PONV risk in patients undergoing gynecologic laparoscopic surgery. [ABSTRACT FROM AUTHOR]

Deep learning models have been widely applied in the field of long-term forecasting has achieved significant success, with the incorporation of inductive bias such as periodicity to model multi-granularity representations of time series being a commonly employed design approach in forecasting methods. However, existing methods still face challenges related to information redundancy during the extraction of inductive bias and the learning process for multi-granularity features. The presence of redundant information can impede the acquisition of a comprehensive temporal representation by the model, thereby adversely impacting its predictive performance. To address the aforementioned issues, we propose a De-Redundant Multi-Period Hybrid Modeling Network (DPHM-Net) that effectively eliminates redundant information from the series inductive bias extraction mechanism and the multi-granularity series features in the time series representation learning. In DPHM-Net, we propose an efficient time series representation learning process based on a period inductive bias and introduce the concept of de-redundancy among multiple time series into the representation learning process for single time series. Additionally, we design a specialized gated unit to dynamically balance the elimination weights between series features and redundant semantic information. The advanced performance and high efficiency of our method in long-term forecasting tasks against previous state-of-the-art are demonstrated through extensive experiments on real-world datasets. [ABSTRACT FROM AUTHOR]

Bottle-brush polymers possessing densely grafted side chains have special properties that are distinct from linear macromolecules. Herein, an efficient method for preparing bottle-brush polymers based on a selective photoactivation strategy in the photoinduced electron/energy transfer reversible addition-fragmentation chain transfer (PET-RAFT) polymerization was developed. A methacrylate monomer 2-(2-(dodecylthiocarbonothioylthio)propionate)ethyl methacrylate (DTPEMA) containing a 2-(dodecylthiocarbonothioylthio)propionate (DTP) unit with a secondary R group was designed. Utilizing the unique selectivity of metal naphthalocyanine photocatalyst zinc 2,11,20,29-tetra-tert-butyl-2,3-naphthalocyanine (ZnTtBNc) toward trithiocarbonate with tertiary R group, the PET-RAFT polymerization of DTPEMA catalyzed by ZnTtBNc was performed under near infrared (NIR) light (λmax = 760 nm) irradiation at room temperature, using 4-cyano-4-[(dodecylsulfanylthiocarbonyl)-sulfanyl] pentanoic acid (CDTPA) with a tertiary R group as a chain transfer agent (CTA). Proton nuclear magnetic resonance (1H NMR) and gel permeation chromatography (GPC) results demonstrated that the DTP units in the side chains were inert during the polymerization. By grafting poly(methyl acrylate) (PMA) from PDTPEMA via thermal-initiated RAFT polymerization, well-defined P(DTPEMA-g-PMA) bottle-brush polymers could be afforded. Furthermore, the film prepared from the bottle-brush polymer exhibited excellent scratch self-healing property due to the interlocking of side chains. [ABSTRACT FROM AUTHOR]

Foldamer is a scaled‐down version of coil spring, which can absorb and release energy by conformational change. Here, polymer networks with high density of molecular springs were developed by employing anion‐coordination‐based foldamers as the monomer. The coiling of the foldamer is controlled by oligo(urea) ligands coordinating to chloride ions; subsequently, the folding and unfolding of foldamer conformations endow the polymer network with excellent energy dissipation and toughness. The mechanical performance of the corresponding polymer networks shows a dramatic increase from P‐L2UCl (non‐folding), to P‐L4UCl (a full turn), and then to P‐L6UCl (1.5 turns), in terms of strength (2.62 MPa; 14.26 MPa; 22.93 MPa), elongation at break (70 %; 325 %; 352 %), Young's modulus (2.69 MPa; 63.61 MPa; 141.50 MPa), and toughness (1.12 MJ/m3; 21.39 MJ/m3; 49.62 MJ/m3), respectively, which is also better than those without anion centers and the non‐foldamer based counterparts. Moreover, P‐L6UCl shows enhanced strength and toughness than most of the molecular‐spring based polymer networks. Thus, an effective strategy for designing high‐performance anion‐coordination‐based materials is presented. [ABSTRACT FROM AUTHOR]

This paper develops a distributed cooperative optimization model for multiple virtual power plant (VPP) operations based on multi-stage robust optimization and proposes a distributed solution methodology based on the combination of the alternating direction method of multipliers (ADMMs) and column-and-constraint generation (CCG) algorithm to solve the corresponding optimization problem. Firstly, considering the peer-to-peer (P2P) electricity transactions among multiple VPPs, a deterministic cooperative optimal operation model of multiple VPPs based on Nash bargaining is constructed. Secondly, considering the uncertainties of photovoltaic generation and load demand, as well as the non-anticipativity of real-time scheduling of VPPs in engineering, a cooperative optimal operation model of multiple VPPs based on multi-stage robust optimization is then constructed. Thirdly, the constructed model is solved using a distributed solution methodology based on the combination of the ADMM and CCG algorithms. Finally, a case study is solved. The case study results show that the proposed method can realize the optimal scheduling of renewable energy in a more extensive range, which contributes to the promotion of the local consumption of renewable energy and the improvement of the renewable energy utilization efficiency of VPPs. Compared with the traditional deterministic cooperative optimal operation method of multiple VPPs, the proposed method is more resistant to the risk of the uncertainties of renewable energy and load demand and conforms to the non-anticipativity of real-time scheduling of VPPs in engineering. In summary, the presented works strike a balance between the operational robustness and operational economy of VPPs. In addition, under the presented works, there is no need for each VPP to divulge personal private data such as photovoltaic generation and load demand to other VPPs, so the security privacy protection of each VPP can be achieved. [ABSTRACT FROM AUTHOR]

Creativity has been proven to be a core competitiveness in the twenty-first century. Although many experimental studies have confirmed that game learning can improve creativity, some studies have contrary results. Currently, there are very few, and primarily incomplete, meta-analyses integrating experimental studies of educational gaming's impact on creativity. The current meta-analysis included 29 articles from 2002 to 2022, containing 116 effect sizes and 4,159 student subjects. The results showed that the overall mean weighted effect size was 0.84, indicating that game learning significantly positively affected students' creativity compared with non-game learning. In addition, the mean effect size was moderated by digital content, teaching strategies, educational stages, publication sources, and class size but not by patterns, disciplines, and experiment duration. Accordingly, this study provides new insights and suggestions on improving creativity via game learning design and implementation as a reference for researchers, teachers, game designers, and developers in the field of creativity. [ABSTRACT FROM AUTHOR]