Agents: An Open-source Framework for Autonomous Language Agents

Recent advances on large language models (LLMs) enable researchers and developers to build autonomous language agents that can automatically solve various tasks and interact with environments, humans, and other agents using natural language interfaces. We consider language agents as a promising direction towards artificial general intelligence and release Agents, an open-source library with the goal of opening up these advances to a wider non-specialist audience. Agents is carefully engineered to support important features including planning, memory, tool usage, multi-agent communication, and fine-grained symbolic control. Agents is user-friendly as it enables non-specialists to build, customize, test, tune, and deploy state-of-the-art autonomous language agents without much coding. The library is also research-friendly as its modularized design makes it easily extensible for researchers. Agents is available at https://github.com/aiwaves-cn/agents.Comment: Code available at https://github.com/aiwaves-cn/agent

The origin of ultrahigh piezoelectricity in relaxor-ferroelectric solid solution crystals

The discovery of ultrahigh piezoelectricity in relaxor-ferroelectric solid solution single crystals is a breakthrough in ferroelectric materials. A key signature of relaxor-ferroelectric solid solutions is the existence of polar nanoregions, a nanoscale inhomogeneity, that coexist with normal ferroelectric domains. Despite two decades of extensive studies, the contribution of polar nanoregions to the underlying piezoelectric properties of relaxor ferroelectrics has yet to be established. Here we quantitatively characterize the contribution of polar nanoregions to the dielectric/piezoelectric responses of relaxor-ferroelectric crystals using a combination of cryogenic experiments and phase-field simulations. The contribution of polar nanoregions to the room-temperature dielectric and piezoelectric properties is in the range of 50-80%. A mesoscale mechanism is proposed to reveal the origin of the high piezoelectricity in relaxor ferroelectrics, where the polar nanoregions aligned in a ferroelectric matrix can facilitate polarization rotation. This mechanism emphasizes the critical role of local structure on the macroscopic properties of ferroelectric materials

Research on a new power system development planning model based on two-tier planning

With the rapid development of the power industry, the safe and stable operation of the power system has become an important basis for safeguarding economic and social development. In order to adapt to the trend of rapid growth of new energy sources and the demand for transformation and upgrading of the power industry, the capacity allocation scheme of the power system needs to be constantly optimized and adjusted. To address the development planning of new power systems, a new power system development planning model based on two-layer planning is constructed, taking into account the operational output results of various types of units and the interaction between the configuration schemes. Through the analysis of the evolution of the power system in a region in the next 15 years, the development pattern of the new power system in different stages under the high, medium, and low scenarios of new energy development is optimally calculated to guide the development of the power system. The results show that the model can provide a quantitative reference for decision-making on energy policies and power strategies in the medium and long term

Real-space imaging of polar and elastic nano-textures in thin films via inversion of diffraction data

Exploiting the emerging nanoscale periodicities in epitaxial, single-crystal thin films is an exciting direction in quantum materials science: confinement and periodic distortions induce novel properties. The structural motifs of interest are ferroelastic, ferroelectric, multiferroic, and, more recently, topologically protected magnetization and polarization textures. A critical step towards heterostructure engineering is understanding their nanoscale structure, best achieved through real-space imaging. X-ray Bragg coherent diffractive imaging visualizes sub-picometer crystalline displacements with tens of nanometers spatial resolution. Yet, it is limited to objects spatially confined in all three dimensions and requires highly coherent, laser-like x-rays. Here we lift the confinement restriction by developing real-space imaging of periodic lattice distortions: we combine an iterative phase retrieval algorithm with unsupervised machine learning to invert the diffuse scattering in conventional x-ray reciprocal-space mapping into real-space images of polar and elastic textures in thin epitaxial films. We first demonstrate our imaging in PbTiO3/SrTiO3 superlattices to be consistent with published phase-field model calculations. We then visualize strain-induced ferroelastic domains emerging during the metal-insulator transition in Ca2RuO4 thin films. Instead of homogeneously transforming into a low-temperature structure (like in bulk), the strained Mott insulator splits into nanodomains with alternating lattice constants, as confirmed by cryogenic scanning transmission electron microscopy. Our study reveals the type, size, orientation, and crystal displacement field of the nano-textures. The non-destructive imaging of textures promises to improve models for their dynamics and enable advances in quantum materials and microelectronics

Age-related differences in risk factors, clinical characteristics, and outcomes for intracerebral hemorrhage

Background and purposeIntracerebral hemorrhage (ICH) is a severe form of stroke that remains understudied in the young adults. We aimed to investigate the clinical presentation, and risk factors associated with ICH in this age group and compare them to older patients.MethodsOur study included ICH patients admitted between March 2016 and December 2021 in the First Affiliated Hospital of Chongqing Medical University from our ongoing prospective cohort database. Demographic characteristics, etiology, risk factors, and clinical outcomes were compared between elderly and young patients. Furthermore, logistic regression analysis was employed to explore risk factors associated with the functional outcome at 3-months.ResultsWe selected 1,003 patients (mean age, 59.9 ±13.8 years old), 746 (74.4%) patients were aged >50 years. The logistic regression analysis showed young patients have a higher proportion of secondary ICH, higher white blood cell count and higher body mass index (BMI), but less diabetes mellitus. Of all patients, predictors of 3-month functional independence was first-ever ICH and age ≤50 years. The history of nephropathy and stroke, higher baseline NIHSS score, larger hematoma volume, and the presence of hydrocephalus were associated with poor outcomes. And the white blood cell count could significantly influence the prognosis among young ICH patients. Three-month functional outcome based on modified Rankin scale score was better in young patients than the elderly (OR, 1.232; 95% CI, 1.095–1.388; p < 0.001).ConclusionsThe highest incidence of ICH occurs in the age groups of 50–59 and 60–69. ICH in young adults had higher white blood cell and BMI compared to the elderly, and differs in etiological distribution. The young patients also had similar short-term mortality but more favorable functional outcomes than the elderly. Furthermore, NIHSS score and larger hematoma volumes were associated with poor outcome in all patients

A New Random Walk Simulation Model for Study of Diffusion Behavior of Single Particle Within Two-Dimensional Space

分子的扩散行为是微观化学的重要研究领域. 影响扩散行为的因素很多，但是目前各个因素的具体影响效果还不明确. 作者基于随机行走理论建立了分子在二维空间的扩散模型，依据此模型自主开发了模拟软件以及数据分析系统，并利用该模拟软件系统研究了势垒尧横向速度等因素对扩散行为的影响，验证了该模型的可靠性，证明根据该模型可以得到和实验尧理论相吻合的结果. 该软件有望成为模拟微观化学扩散行为的潜在平台，如电化学以及膜过滤过程中的扩散.Research on diffusion behaviors is of significant value in that it is closely related to transport phenomena in micro-chemistry. However, the effects of variables on diffusion are still unclear. Here, we developed and programmed a simulation methodology along with data analysis, which was capable to simulate the diffusion of a particle within twodimensional heterogeneous space in large timescale; the effects of periodically arranged impenetrable barriers of specific shape and lateral drifting velocity on diffusion behavior were studied. As well as standard mean square displacement analysis, a new method, the appearance probability distribution method, was introduced, which revealed whether the particle tended to be present at certain positions. This article introduced the construction of the simulation model and demonstrated the validity of the model. The results showed that our model fit qualitatively well with experiments and theories. The model was proved to be an excellent potential platform for simulating the diffusion behaviors in micro-chemistry, such as the diffusion process in electrochemistry as well as nanofiltration membrane.This work was supported by National Basic Research Program of China (973 Program, 2010CB732400), the National Natural Science Foundation of China (NSFC) (20821063, 20873063, 51071084, and 21273113), the Natural Science Foundation of Jiangsu Province (BK2010389).This work was supported by National Basic Research Program of China (973 Program, 2010CB732400), the National Natural Science Foundation of China (NSFC) (20821063, 20873063, 51071084, and 21273113), the Natural Science Foundation of Jiangsu Province (BK2010389).作者联系地址：南京大学 化学化工学院, 生命分析化学国家重点实验室, 江苏 南京 210008Author's Address: State Key Lab of A nalytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210008, China通讯作者E-mail：[email protected]

Proteomic-based stratification of intermediate-risk prostate cancer patients

Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management