OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement

The introduction of large language models has significantly advanced code generation. However, open-source models often lack the execution capabilities and iterative refinement of advanced systems like the GPT-4 Code Interpreter. To address this, we introduce OpenCodeInterpreter, a family of open-source code systems designed for generating, executing, and iteratively refining code. Supported by Code-Feedback, a dataset featuring 68K multi-turn interactions, OpenCodeInterpreter integrates execution and human feedback for dynamic code refinement. Our comprehensive evaluation of OpenCodeInterpreter across key benchmarks such as HumanEval, MBPP, and their enhanced versions from EvalPlus reveals its exceptional performance. Notably, OpenCodeInterpreter-33B achieves an accuracy of 83.2 (76.4) on the average (and plus versions) of HumanEval and MBPP, closely rivaling GPT-4's 84.2 (76.2) and further elevates to 91.6 (84.6) with synthesized human feedback from GPT-4. OpenCodeInterpreter brings the gap between open-source code generation models and proprietary systems like GPT-4 Code Interpreter

Interaction between microbiota and immunity and its implication in colorectal cancer

Colorectal cancer (CRC) is one of the leading causes of cancer-related death in the world. Besides genetic causes, colonic inflammation is one of the major risk factors for CRC development, which is synergistically regulated by multiple components, including innate and adaptive immune cells, cytokine signaling, and microbiota. The complex interaction between CRC and the gut microbiome has emerged as an important area of current CRC research. Metagenomic profiling has identified a number of prominent CRC-associated bacteria that are enriched in CRC patients, linking the microbiota composition to colitis and cancer development. Some microbiota species have been reported to promote colitis and CRC development in preclinical models, while a few others are identified as immune modulators to induce potent protective immunity against colitis and CRC. Mechanistically, microbiota regulates the activation of different immune cell populations, inflammation, and CRC via crosstalk between innate and adaptive immune signaling pathways, including nuclear factor kappa B (NF-κB), type I interferon, and inflammasome. In this review, we provide an overview of the potential interactions between gut microbiota and host immunity and how their crosstalk could synergistically regulate inflammation and CRC, thus highlighting the potential roles and mechanisms of gut microbiota in the development of microbiota-based therapies to prevent or alleviate colitis and CRC

Diagnostic potential of structural neuroimaging for depression from a multi-ethnic community sample

Background At present, we do not have any biological tests which can contribute towards a diagnosis of depression. Neuroimaging measures have shown some potential as biomarkers for diagnosis. However, participants have generally been from the same ethnic background while the applicability of a biomarker would require replication in individuals of diverse ethnicities. Aims We sought to examine the diagnostic potential of the structural neuroanatomy of depression in a sample of a wide ethnic diversity. Method Structural magnetic resonance imaging (MRI) scans were obtained from 23 patients with major depressive disorder in an acute depressive episode (mean age: 39.8 years) and 20 matched healthy volunteers (mean age: 38.8 years). Participants were of Asian, African and Caucasian ethnicity recruited from the general community. Results Structural neuroanatomy combining white and grey matter distinguished patients from controls at the highest accuracy of 81% with the most stable pattern being at around 70%. A widespread network encompassing frontal, parietal, occipital and cerebellar regions contributed towards diagnostic classification. Conclusions These findings provide an important step in the development of potential neuroimaging-based tools for diagnosis as they demonstrate that the identification of depression is feasible within a multi-ethnic group from the community. Declaration of interests C.H.Y.F. has held recent research grants from Eli Lilly and Company and GlaxoSmithKline. L.M. is a former employee and stockholder of Eli Lilly and Company

PyPose: A Library for Robot Learning with Physics-based Optimization

Deep learning has had remarkable success in robotic perception, but its data-centric nature suffers when it comes to generalizing to ever-changing environments. By contrast, physics-based optimization generalizes better, but it does not perform as well in complicated tasks due to the lack of high-level semantic information and the reliance on manual parametric tuning. To take advantage of these two complementary worlds, we present PyPose: a robotics-oriented, PyTorch-based library that combines deep perceptual models with physics-based optimization techniques. Our design goal for PyPose is to make it user-friendly, efficient, and interpretable with a tidy and well-organized architecture. Using an imperative style interface, it can be easily integrated into real-world robotic applications. Besides, it supports parallel computing of any order gradients of Lie groups and Lie algebras and $2^{\text{nd}}$-order optimizers, such as trust region methods. Experiments show that PyPose achieves 3-20$\times$ speedup in computation compared to state-of-the-art libraries. To boost future research, we provide concrete examples across several fields of robotics, including SLAM, inertial navigation, planning, and control

PyPose v0.6: The Imperative Programming Interface for Robotics

PyPose is an open-source library for robot learning. It combines a learning-based approach with physics-based optimization, which enables seamless end-to-end robot learning. It has been used in many tasks due to its meticulously designed application programming interface (API) and efficient implementation. From its initial launch in early 2022, PyPose has experienced significant enhancements, incorporating a wide variety of new features into its platform. To satisfy the growing demand for understanding and utilizing the library and reduce the learning curve of new users, we present the fundamental design principle of the imperative programming interface, and showcase the flexible usage of diverse functionalities and modules using an extremely simple Dubins car example. We also demonstrate that the PyPose can be easily used to navigate a real quadruped robot with a few lines of code

Effects of Sensor Location on Dynamic Load Estimation in Weigh-in-Motion System

In recent years, weigh-in-motion systems based on embedded sensor networks have received a lot of attention. However, how to improve the accuracy of multi-sensor weigh-in-motion (WIM) systems while keeping costs low remains a challenge. In this paper, a numerical simulation method is presented to analyze the relationship between sensor location and the accuracy of static weight estimation. The finite element model of a WIM system is developed, which consists of three parts: a pavement model, a moving load model and two types of sensor models. Analysis of simulation results shows that the ability of sensing dynamic load is closely related to the installation depth of sensors and pavement material. Moreover, the distance between the moving wheel and sensors has a great impact on estimating performance. Gaussian curve fitting could be used to reduce weighing error within a limited range. Our work suggests that much more attention should be paid to the design of the sensor layout of a WIM system

MANAGING UNCERTAINTY ON EWOM: A COMPARISON STUDY BETWEEN COMMERCIAL AND THIRD PARTY WEBSITES

This study utilizes elaboration likelihood model (ELM) as the theoretical foundation, to explore the effects of information comprehensiveness, argument strength, consistency and quantity on eWOM (electronic word-of-mouth) readers’ information adoption intention in two types of websites (commercial and third party), we collect 278 data from one commercial and one third party website, the results find, in general, all of these four determinant factors can significant affect information adoption intention; however, their effects will be modified in different websites, this finding indicates that people do perceive different level of uncertainties in different websites, and they will utilize different signals to alleviate their information uncertainty concerns. The theoretical and practical implications of this study are also introduce

Results of Medial Patellofemoral Ligament Reconstruction with and without Tibial Tubercle Transfer in Patellar Instability: A Systematic Review and Meta‐Analysis

The optimal surgical intervention for lateral patellar instability remains a topic of controversy despite satisfactory clinical outcomes and low re‐dislocation rates reported in numerous studies following medial patellofemoral ligament reconstruction (MPFLR) with and without tibial tubercle transfer (TTT). The purpose of this systematic review and meta‐analysis is to investigate the hypothesis that combining MPFLR with TTT provides reduced complication rates and improved clinical outcomes to isolated MPFLR in patients with lateral patellar instability. We conducted a comprehensive systematic review and meta‐analysis of comparative trials involving MPFLR with and without TTT, sourcing data from PubMed, the Cochrane Library, Embase, and Web of Science. The primary clinical outcomes analyzed included the Kujala score, the Lysholm score, complication rates, and the Caton–Deschamps index (CDI). Random or fixed effects were used for the meta‐analysis. Postoperatively, there were no significant differences observed in the Kujala and Lysholm scores between MPFLR and MPFLR + TTT (p = 0.053). At the final follow‐up, the CDI had decreased 0.015 (95% CI −0.044, 0.013; p = 0.289) points in the MPFLR group, with no statistical significance. In contrast, the MPFLR + TTT group demonstrated a significant decrease of 0.207 (95% CI −0.240, −0.174; p = 0.000) points in CDI. Notably, the complication rate was higher in the MPFLR + TTT group compared to the MPFLR‐only group (RR = 2.472; 95% CI 1.638, 3.731; p = 0.000). Both MPFLR and MPFLR + TTT procedures yield significant improvements in the Kujala and Lysholm scores. However, the MPFLR + TTT approach results in an apparent improvement in CDI and corrects patellar maltracking, particularly in cases involving high tibial tuberosity‐trochlear groove (TT‐TG) (>20 mm) or patella alta (CDI > 1.2), while MPFLR alone cannot. It is essential to consider the higher complication rate of MPFLR + TTT, which suggests that MPFLR alone may be sufficient for patients without high TT‐TG or patella alta

Experimental Research on Controllability and Emissions of Jet-Controlled Compression Ignition Engine

Low-temperature combustions (LTCs), such as homogeneous charge compression ignition (HCCI), could achieve high thermal efficiency and low engine emissions by combining the advantages of spark-ignited (SI) engines and compression-ignited (CI) engines. Robust control of the ignition timing, however, still remains a hurdle to practical use. A novel technology of jet-controlled compression ignition (JCCI) was proposed to solve the issue. JCCI combustion phasing was controlled by hot jet formed from pre-chamber spark-ignited combustion. Experiments were done on a modified high-speed marine engine for JCCI characteristics research. The JCCI principle was verified by operating the engine individually in the mode of JCCI and in the mode of no pre-chamber jet under low- and medium-load working conditions. Effects of pre-chamber spark timing and intake charge temperature on JCCI process were tested. It was proven that the combustion phasing of the JCCI engine was closely related to the pre-chamber spark timing. A 20 °C temperature change of intake charge only caused a 2° crank angle change of the start of combustion. Extremely low nitrogen oxides (NOx) emission was achieved by JCCI combustion while keeping high thermal efficiency. The JCCI could be a promising technology for dual-fuel marine engines