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Short-range ordering (SRO) in multi-principal element alloys influences material properties such as strength and corrosion. While some degree of SRO is expected at equilibrium, predicting the kinetics of its formation is challenging. We present a simplified isothermal concentration-wave (CW) model to estimate an effective relaxation time of SRO formation. Estimates from the CW model agree to within a factor of five with relaxation times obtained from kinetic Monte Carlo (kMC) simulations when above the highest ordering instability temperature. The advantage of the CW model is that it only requires mobility and thermodynamic parameters, which are readily obtained from alloy mobility databases and Metropolis Monte Carlo simulations, respectively. The simple parameterization of the CW model and its analytical nature makes it an attractive tool for the design of processing conditions to promote or suppress SRO in multicomponent alloys.

Diffusion involving atom transport from one location to another governs many important processes and behaviors such as precipitation and phase nucleation. The inherent chemical complexity in compositionally complex materials poses challenges for modeling atomic diffusion and the resulting formation of chemically ordered structures. Here, we introduce a neural network kinetics (NNK) scheme that predicts and simulates diffusion-induced chemical and structural evolution in complex concentrated chemical environments. The framework is grounded on efficient on-lattice structure and chemistry representation combined with artificial neural networks, enabling precise prediction of all path-dependent migration barriers and individual atom jumps. To demonstrate the method, we study the temperature-dependent local chemical ordering in a refractory NbMoTa alloy and reveal a critical temperature at which the B2 order reaches a maximum. The atomic jump randomness map exhibits the highest diffusion heterogeneity (multiplicity) in the vicinity of this characteristic temperature, which is closely related to chemical ordering and B2 structure formation. The scalable NNK framework provides a promising new avenue to exploring diffusion-related properties in the vast compositional space within which extraordinary properties are hidden.

Abstract Purpose To compare the morphometry of paraspinal muscles in patients with degenerative spondylolisthesis (DS), isthmic spondylolisthesis (IS), and healthy individuals. Methods Thirty-seven pairs of DS patients were selected using propensity score matching with IS patients, while 37 healthy individuals matched for age, sex, and BMI were selected as controls. The relative cross-sectional area (rCSA), and relative functional cross-sectional area (rfCSA) of paraspinal muscles were measured, and the degree of fatty infiltration (FI) was calculated. Based on occupational differences, the patients were also divided into worker and farmer groups, and the same measurements were taken on them. Results At the L3/L4 level, the multifidus (MF) FI was greater in the DS and IS groups than in the control group, the erector spinae (ES) rfCSA was higher in the IS group than in the DS and control groups. At the L4/L5 level, MF rfCSA was smaller in the DS and IS groups than in the control group; ES rfCSA was higher in the IS group than in the DS and control groups. At the L5/S1 level, MF rfCSA was smaller in the DS and IS groups than in the control group; ES rfCSA was higher in the IS group than in the DS group. At the L3/L4, L4/L5 level, MF rfCSA were higher in the worker group than in the farmer group (p

IntroductionAdult diffuse hepatic hemangiomatosis (DHH) is an extremely rare disease. Consequently, its characteristics are poorly understood. Herein, we report a case of adult DHH involving both liver lobes but without extrahepatic involvement. To the best of our knowledge, this the largest reported adult DHH to date.Case presentationA 51-year-old man was admitted due to abdominal distension and dyspnea. Physical examination revealed marked liver enlargement. Color Doppler, plain and contrast-enhanced computed tomography, and contrast-enhanced magnetic resonance imaging revealed a hepatic lesion sized 35.1 × 32.1 × 14.1 cm occupying nearly the entire abdominal and pelvic cavities. Diagnosis was established by liver puncture biopsy. The patient exhibited clinical signs of portal hypertension and hypersplenism, but remains free of serious DHH-related complications. He is followed up regularly, with proactive evaluation for future liver transplantation.ConclusionThis case will contribute to the current knowledge on the clinical and imaging features of this rare entity.

As an emerging concept, metaverse has attracted extensive attention from industry, academia and scientific research field. The combination of agriculture and metaverse will greatly promote the development of agricultural informatization and agricultural intelligence, provide new impetus for the transformation and upgrading of agricultural intelligence. Firstly, to expound feasibility of the application research of metaverse in agriculture, the basic principle and key technologies of agriculture metaverse were briefly described, such as blockchain, non-fungible token, 5G/6G, artificial intelligence, Internet of Things, 3D reconstruction, cloud computing, edge computing, augmented reality, virtual reality, mixed reality, brain computer interface, digital twins and parallel system. Then, the main scenarios of three agricultural applications of metaverse in the fields of virtual farm, agricultural teaching system and agricultural product traceability system were discussed. Among them, virtual farm is one of the most important applications of agricultural metaverse. Agricultural metaverse can help the growth of crops and the raising of livestock and poultry in the field of agricultural production, provide a three-dimensional and visual virtual leisure agricultural experience, provide virtual characters in the field of agricultural product promotion. The agricultural metaverse teaching system can provide virtual agricultural teaching similar to natural scenes, save training time and improve training efficiency by means of fragmentation. Traceability of agricultural products can let consumers know the production information of agricultural products and feel more confident about enterprises and products. Finally, the challenges in the development of agricultural metaverse were summarized in the aspects of difficulties in establishing agricultural metaverse system, weak communication foundation of agricultural metaverse, immature agricultural metaverse hardware equipment and uncertain agricultural meta universe operation, and the future development directions of agricultural metaverse were prospected. In the future, researches on the application of metaverse, agricultural growth mechanism, and low power wireless communication technologies are suggested to be carried out. A rural broadband network covering households can be established. The industrialization application of agricultural meta universe can be promoted. This review can provide theoretical references and technical supports for the development of metaverse in the field of agriculture.