bluuebunny/crossref_metadata_2025_split huggingface dataset:
Seismic performance loss evaluation of reinforced concrete frame structure based on updatable damage model
Authors: Li Zuohua , Lu Jianfeng , Teng Jun 
Published: March 2024

AbstractAs structural seismic damage develops, the internal force transfer and damage weight relationship of component are constantly changing, and the fixed weighted coefficient is adopted by the traditional weighted method, which cannot reflect the changes in the structural damage state. The structure is a network formed by connecting a large number of components, and the network state undergoes complex changes with the development of component damage. In this paper, a novel method for component damage transfer to structural seismic performance loss is proposed using network shortest paths. First, a directed weighted complex network based on force transfer direction and component stiffness is constructed for reinforced concrete (RC) frame structures. Then, the component damage is calculated by the degradation of its stiffness and is used to update the weight distribution of the damage network. Finally, the structural performance loss is evaluated by the degradation of damage network efficiency. Results show that the proposed method with an updated component weight relationship is able to reflect the true loss of structural performance according to the finite element dynamic elastic‐plastic analysis of RC frame structures. For the structural performance loss degree (none, slight, moderate, severe, complete), the proposed method and the weighted method both exhibit high accuracy (number correctly classified/total number of samples) when structural performance loss is none, severe, or complete loss. The accuracy of the proposed method is significantly higher than that of the weighted method when structural performance loss is slight and moderate loss, with 58.1% and 84.2% improvement, respectively. For structural typical damage modes (global, local, and weak layer damage mode), the proposed method and the weighted method both exhibit high accuracy when structures exhibit global damage mode. The accuracy of the proposed method is significantly higher than that of the weighted method when structures exhibit local and weak layer damage mode. The accuracy of the proposed method is stable at 95.2%, while the accuracy of the weighted method is 76.2% and 70.2%, respectively. Overall, the weighted method exhibits high accuracy when structural performance loss is less than slight loss or greater than moderate loss, while the proposed method exhibits high accuracy throughout the entire process of structural performance loss, especially in moderate loss.
Nonresilience curve: A new tool for use in resilience assessment
Authors: Wang Cao 
Published: March 2024

AbstractResilience assessment is a widely used method to evaluate the ability of an object (e.g., an individual structure, or a system consisting of multiple interacting structures) to withstand, recover from, and adapt to disruptive events. This paper proposes a novel concept of “nonresilience curve,” which measures the nonresilience (complement of resilience) of an object of interest conditional on a specific hazard intensity. It is by nature an extension of the well‐established fragility curves, integrating the multiple damage states of a posthazard object. The applicability of the proposed nonresilience curve to individual structures and systems (including series systems, parallel systems, and more general and complicated systems) has been demonstrated in this paper. It is also preliminarily shown that the shape of the cumulative distribution function of a lognormal distribution is suitable to approximate the nonresilience curve, if only limited data points associated with the target nonresilience curve are available. Since the nonresilience curve is a function of the hazard intensity measure (IM), one can estimate the nonresilience of an object in a fully probabilistic manner by additionally taking into account the uncertainty associated with the IM. The proposed nonresilience curve can be further extended to formulate nonresilience surface, which is a joint function of both the IM and the available resource that supports the posthazard recovery process. The nonresilience curve is promising to be adopted in engineering practice for resilience assessment and resilience‐based design of civil structures and infrastructure systems.
Seismic motion incoherency effects on SSSI responses of nuclear buildings
Authors: Wang Dongyang , Sun Xiaoying , Liu Ziqiao , Yang Jianhua 
Published: March 2024

AbstractThe spatial variation of ground motion may significantly aggravate the seismic damage of large‐scale structures such as nuclear buildings. Establishing the seismic wave field with spatial features is the basis and key to seismic analysis of large‐scale complex structures. For the nuclear island buildings, which are arranged close to each other, the influence of structure–soil–structure interaction (SSSI) and incoherent motion on the structural seismic response should be considered. Taking a domestic nuclear power project as an example, the seismic response analyses under incoherent seismic motion and coherent seismic motion are carried out respectively. The seismic motion incoherency effects on the nuclear island buildings on the common raft and the adjacent seismic category I structure are explored by comparing the results of the in‐structure response spectrum (ISRS) at key elevations. The results indicate that the seismic motion incoherency does not change the trend of the response spectrum curve and the dominant frequency. Both the peak acceleration and zero‐period acceleration of ISRS are changed to some extent. Overall, seismic motion incoherency has a more significant impact on the ISRS of nuclear buildings with smaller volumes.
Community detection in the human connectome: Method types, differences and their impact on inference
Authors: Brooks Skylar J. , Jones Victoria O. , Wang Haotian , Deng Chengyuan , Golding Staunton G. H. , Lim Jethro , Gao Jie , Daoutidis Prodromos , Stamoulis Catherine 
Published: March 2024

AbstractCommunity structure is a fundamental topological characteristic of optimally organized brain networks. Currently, there is no clear standard or systematic approach for selecting the most appropriate community detection method. Furthermore, the impact of method choice on the accuracy and robustness of estimated communities (and network modularity), as well as method‐dependent relationships between network communities and cognitive and other individual measures, are not well understood. This study analyzed large datasets of real brain networks (estimated from resting‐state fMRI from = 5251 pre/early adolescents in the adolescent brain cognitive development [ABCD] study), and = 5338 synthetic networks with heterogeneous, data‐inspired topologies, with the goal to investigate and compare three classes of community detection methods: (i) modularity maximization‐based (Newman and Louvain), (ii) probabilistic (Bayesian inference within the framework of stochastic block modeling (SBM)), and (iii) geometric (based on graph Ricci flow). Extensive comparisons between methods and their individual accuracy (relative to the ground truth in synthetic networks), and reliability (when applied to multiple fMRI runs from the same brains) suggest that the underlying brain network topology plays a critical role in the accuracy, reliability and agreement of community detection methods. Consistent method (dis)similarities, and their correlations with topological properties, were estimated across fMRI runs. Based on synthetic graphs, most methods performed similarly and had comparable high accuracy only in some topological regimes, specifically those corresponding to developed connectomes with at least quasi‐optimal community organization. In contrast, in densely and/or weakly connected networks with difficult to detect communities, the methods yielded highly dissimilar results, with Bayesian inference within SBM having significantly higher accuracy compared to all others. Associations between method‐specific modularity and demographic, anthropometric, physiological and cognitive parameters showed mostly method invariance but some method dependence as well. Although method sensitivity to different levels of community structure may in part explain method‐dependent associations between modularity estimates and parameters of interest, method dependence also highlights potential issues of reliability and reproducibility. These findings suggest that a probabilistic approach, such as Bayesian inference in the framework of SBM, may provide consistently reliable estimates of community structure across network topologies. In addition, to maximize robustness of biological inferences, identified network communities and their cognitive, behavioral and other correlates should be confirmed with multiple reliable detection methods.
Altered intersubject functional variability of brain white‐matter in major depressive disorder and its association with gene expression profiles
Authors: Gai Qun , Chu Tongpeng , Li Qinghe , Guo Yuting , Ma Heng , Shi Yinghong , Che Kaili , Zhao Feng , Dong Fanghui , Li Yuna , Xie Haizhu , Mao Ning 
Published: March 2024

AbstractMajor depressive disorder (MDD) is a clinically heterogeneous disorder. Its mechanism is still unknown. Although the altered intersubject variability in functional connectivity (IVFC) within gray‐matter has been reported in MDD, the alterations to IVFC within white‐matter (WM‐IVFC) remain unknown. Based on the resting‐state functional MRI data of discovery (145 MDD patients and 119 healthy controls [HCs]) and validation cohorts (54 MDD patients, and 78 HCs), we compared the WM‐IVFC between the two groups. We further assessed the meta‐analytic cognitive functions related to the alterations. The discriminant WM‐IVFC values were used to classify MDD patients and predict clinical symptoms in patients. In combination with the Allen Human Brain Atlas, transcriptome‐neuroimaging association analyses were further conducted to investigate gene expression profiles associated with WM‐IVFC alterations in MDD, followed by a set of gene functional characteristic analyses. We found extensive WM‐IVFC alterations in MDD compared to HCs, which were associated with multiple behavioral domains, including sensorimotor processes and higher‐order functions. The discriminant WM‐IVFC could not only effectively distinguish MDD patients from HCs with an area under curve ranging from 0.889 to 0.901 across three classifiers, but significantly predict depression severity (r = 0.575, p = 0.002) and suicide risk (r = 0.384, p = 0.040) in patients. Furthermore, the variability‐related genes were enriched for synapse, neuronal system, and ion channel, and predominantly expressed in excitatory and inhibitory neurons. Our results obtained good reproducibility in the validation cohort. These findings revealed intersubject functional variability changes of brain WM in MDD and its linkage with gene expression profiles, providing potential implications for understanding the high clinical heterogeneity of MDD.
Tissue‐resident memory T cells in immunotherapy and immune‐related adverse events by immune checkpoint inhibitor
Authors: Xiong Hao , Shen Zhu 
Published: March 2024

AbstractTissue‐resident memory T cells (TRM) are a specialized subset of T cells that reside in tissues and provide long‐term protective immunity against pathogens that enter the body through that specific tissue. TRM cells have specific phenotype and reside preferentially in barrier tissues. Recent studies have revealed that TRM cells are the main target of immune checkpoint inhibitor immunotherapy since their role in cancer immunosurveillance. Furthermore, TRM cells also play a crucial part in pathogenesis of immune‐related adverse events (irAEs). Here, we provide a concise review of biological characteristics of TRM cells, and the major advances and recent findings regarding their involvement in immune checkpoint inhibitor immunotherapy and the corresponding irAEs.
Reliability of the carousel simulator for assessing labor cervical dilation in medical obstetrics education
Authors: Sartorao‐Filho Carlos Izaias , Sartorao Ana Luisa Varrone , Terribile Diogo Coutinho , Barbosa Angelica Mercia Pascon , Rudge Marilza Vieira da Cunha 
Published: March 2024

AbstractObjectiveTo determine the reliability of the Carousel simulator in medical education for obstetric examinations. Cervical dilation examination training in pregnant women exposes patients to additional uncomfortable and health‐risk procedures, a gold standard, and does not objectively evaluate the medical student's competence.MethodWe studied the reliability of training internship medical students in obstetrics. Participating students were assigned to take the examination of digital assessment of the cervical dilation on the simulator. Classes performed 12 consecutive randomly blind predetermined cervical dilation examinations using the Carousel simulator. The exact answer and the answer with certainty within ±1 cm were registered and analyzed. Incorrect or outlier answers were considered with a cutoff of ≥2 cm from the dilation. A dispersion graph for each centimeter of dilation simulation was constructed.ResultsSixty‐six medical obstetricians took part, performing 396 examinations. Thus, we observed 49 outliers (12.37%) in simulated assessments. According to the analysis, we did not observe outliers from dilation 1 to 4 cm; dilation 7 to 9 cm had a higher index of outlier measurements. We did not consider any dilation simulation dispersion graphic as a null correlation. A strong correlation was seen in the dilation 1 to 6 cm and the dilation 10 cm. The dilations 7, 8, and 9 cm showed a weak correlation.ConclusionThe Carousel simulator model is a reliable method for student learning. The simulator is an essential study tool capable of reducing the embarrassment and possible harm caused by the excessive and repetitive number of in vivo digital vaginal examinations. Novel studies are proposed to improve the simulator device and method, mainly to estimate the adequate repetitions and training needed before in vivo practice.
Enhanced charge transport in 2D inorganic molecular crystals constructed with charge‐delocalized molecules
Authors: Wu Jie , Zeng Yan , Feng Xin , Ma Yiran , Li Pengyu , Li Chunlei , Liu Teng , Liu Shenghong , Zhao Yinghe , Li Huiqiao , Jiang Lang , Yi Yuanping , Zhai Tianyou 
Published: March 2024

AbstractOutstanding charge transport in molecular crystals is of great importance in modern electronics and optoelectronics. The widely adopted strategies to enhance charge transport, such as restraining intermolecular vibration, are mostly limited to organic molecules, which are nearly inoperative in 2D inorganic molecular crystals currently. In this contribution, charge transport in 2D inorganic molecular crystals is improved by integrating charge‐delocalized Se8 rings as building blocks, where the delocalized electrons on Se8 rings lift the intermolecular orbitals overlap, offering efficient charge transfer channels. Besides, α‐Se flakes composed of charge‐delocalized Se8 rings possess small exciton binding energy. Benefitting from these, α‐Se flake exhibits excellent photodetection performance with an ultrafast response rate (~5 μs) and a high detectivity of 1.08 × 1011 Jones. These findings contribute to a deeper understanding of the charge transport of 2D inorganic molecular crystals composed of electron‐delocalized inorganic molecules and pave the way for their potential application in optoelectronics.
The role of dynamic interplay exists between sympathetic and parasympathetic nerve in gastric tumorigenesis
Authors: Chen Diqun , Li Xunjun , Wang Yiyun , Li Xinxin , Zhang Hongxia , Zhang Lina , Yang Jia , Tan Haoyang , Xie Yingxin , Liuzhou Yingyi , Qiu Jiayun , Shi Miao , Zhang Feiran , Zhong Wu , Xi Kexing , Fang Chuanfa , Balde Alpha Ibrahima , Yu Jiang , Chen Tao 
Published: March 2024

AbstractRecent research underscores the significance of the nervous system in tumor progression. Nonetheless, understanding the intricate roles of nerves in gastric tumorigenesis remains limited. Our study aims to elucidate nerve alterations, associated key genes, and signaling pathways during gastric tumorigenesis. We enroll 257 patients with gastric precancerous lesions (GPLs) from four national cohorts. Utilizing immunohistochemistry and digital analysis, we quantified the densities of sympathetic and parasympathetic nerves, as well as Schwann cells in patient slides. We collected three mRNA expression profiles of GPL samples from the gene expression omnibus database and assessed them for nerve expression signatures, differentially expressed genes, enriched pathways, and the immune microenvironment. Parasympathetic nerve and Schwann cell densities display a progressive increase, while sympathetic nerve exhibits an inverse trend along the precancerous spectrums. Notably, CD8+ T cells, natural killer cells, and antigen‐presenting cells (APC) co‐inhibition decrease, while epithelial‐mesenchymal transition increases significantly from early to late premalignancy. Several key nerve‐regulating genes (NTRK3, MYBL2, NRP1, BCL2, CCND1, VEGFA, PLXNA2, ADRB2), and pathways (mitogen‐activated protein kinase [MAPK]/ERK, PI3K/AKT, Wnt) emerge as potential contributors to precancerous progression. Our study reveals a dynamic relationship between sympathetic and parasympathetic nerves, characterized by a gradual increase in parasympathetic nerve and Schwann cell density, contrasting with an inverse trend in sympathetic nerve across precancerous spectrums. Targeting the interaction between tumor cells and nerves, including sympathetic and parasympathetic nerves, has emerged as a promising strategy for the prevention and treatment of gastric cancer.
How do spin‐scaled double hybrids designed for excitation energies perform for noncovalent excited‐state interactions? An investigation on aromatic excimer models
Authors: Hancock Amy C. , Giudici Erica , Goerigk Lars 
Published: March 2024

AbstractTime‐dependent double hybrids with spin‐component or spin‐opposite scaling to their second‐order perturbative correlation correction have demonstrated competitive robustness in the computation of electronic excitation energies. Some of the most robust are those recently published by our group (M. Casanova‐Páez, L. Goerigk, J. Chem. Theory Comput. 2021, 20, 5165). So far, the implementation of these functionals has not allowed correctly calculating their ground‐state total energies. Herein, we define their correct spin‐scaled ground‐state energy expressions which enables us to test our methods on the noncovalent excited‐state interaction energies of four aromatic excimers. A range of 22 double hybrids with and without spin scaling are compared to the reasonably accurate wavefunction reference from our previous work (A. C. Hancock, L. Goerigk, RSC Adv. 2023, 13, 35964). The impact of spin scaling is highly dependent on the underlying functional expression, however, the smallest overall errors belong to spin‐scaled functionals with range separation: SCS‐ and SOS‐PBEPP86, and SCS‐RSX‐QIDH. We additionally determine parameters for DFT‐D3(BJ)/D4 ground‐state dispersion corrections of these functionals, which reduce errors in most cases. We highlight the necessity of dispersion corrections for even the most robust TD‐DFT methods but also point out that ground‐state based corrections are insufficient to completely capture dispersion effects for excited‐state interaction energies.
Allogeneic hematopoietic cell transplantation for acute myeloid leukemia with BCR::ABL1 fusion
Authors: Mizuno Shohei , Takami Akiyoshi , Kawamura Koji , Harada Kaito , Masayoshi Masuko , Yano Shingo , Ito Ayumu , Ozawa Yukiyasu , Ouchi Fumihiko , Ashida Takashi , Nawa Yuichiro , Ichinohe Tatsuo , Fukuda Takahiro , Atsuta Yoshiko , Yanada Masamitsu 
Published: March 2024

AbstractBCR::ABL1 fusion is found in < 1% of de novo acute myeloid leukemia (AML) cases and confers a poor prognosis. This Japanese nationwide survey analyzed patients with AML (n = 22) and mixed phenotype acute leukemia (MPAL) (n = 10) with t(9;22) or BCR::ABL1 who underwent allogeneic hematopoietic cell transplantation (allo‐HCT) between 2002 and 2018. The 3‐year overall survival (OS) rates were 81.3% and 56.0%, respectively (p = 0.15), and leukemia‐free survival (LFS) rates were 76.2% and 42.0%, respectively (p = 0.10) in patients with AML and MPAL. The relapse rates were 9.5% and 14.0% (p = 0.93), and the non‐relapse mortality (NRM) rates were 14.3% and 44.0%, respectively (p = 0.10) in patients with AML and MPAL. One in 17 patients with AML, with pre‐transplant tyrosine kinase inhibitors (TKI), and three in five patients with AML, without pre‐transplant TKI, did not achieve complete remission (CR) before allo‐HCT (p = 0.024). Among the 20 patients with known disease status after allo‐HCT, 95.0% were in hematological or molecular CR. None of the four patients who received post‐transplant TKI for prophylaxis or measurable residual disease relapse experienced hematological relapse.
In conclusion, our results suggest that pre‐transplant TKI could improve disease status before allo‐HCT. Moreover, allo‐HCT resulted in high OS, high LFS, low relapse, and low NRM rates in patients with AML with BCR::ABL1.
Association between protein intake and muscle wasting in critically ill children: A prospective cohort study
Authors: Tume Lyvonne N. , Simons Christopher , Latten Lynne , Huang Chao , Comfort Paul , Compton Vanessa , Wagh Anand , Veale Archie , Valla Frederic V. 
Published: March 2024

AbstractBackgroundSurvival from pediatric critical illness in high‐income countries is high, and the focus now must be on optimizing the recovery of survivors. Muscle mass wasting during critical illness is problematic, so identifying factors that may reduce this is important. Therefore, the aim of this study was to examine the relationship between quadricep muscle mass wasting (assessed by ultrasound), with protein and energy intake during and after pediatric critical illness.MethodsA prospective cohort study in a mixed cardiac and general pediatric intensive care unit in England, United Kingdom. Serial ultrasound measurements were undertaken at day 1, 3, 5, 7, and 10.ResultsThirty‐four children (median age 6.65 [0.47–57.5] months) were included, and all showed a reduction in quadricep muscle thickness during critical care admission, with a mean muscle wasting of 7.75%. The 11 children followed‐up had all recovered their baseline muscle thickness by 3 months after intensive care discharge. This muscle mass wasting was not related to protein (P = 0.53, ρ = 0.019) (95% CI: −0.011 to 0.049) or energy intake (P = 0.138, ρ = 0.375 95% CI: −0.144 to 0.732) by 72 h after admission, nor with severity of illness, highest C‐reactive protein, or exposure to intravenous steroids. Children exposed to neuromuscular blocking drugs exhibited 7.2% (95% CI: −0.13% to 14.54%) worse muscle mass wasting, but this was not statistically significant (P = 0.063).ConclusionOur study did not find any association between protein or energy intake at 72 h and quadricep muscle mass wasting.