Qwen Technical Report

Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling natural language processing tasks that were previously thought to be exclusive to humans. In this work, we introduce Qwen, the first installment of our large language model series. Qwen is a comprehensive language model series that encompasses distinct models with varying parameter counts. It includes Qwen, the base pretrained language models, and Qwen-Chat, the chat models finetuned with human alignment techniques. The base language models consistently demonstrate superior performance across a multitude of downstream tasks, and the chat models, particularly those trained using Reinforcement Learning from Human Feedback (RLHF), are highly competitive. The chat models possess advanced tool-use and planning capabilities for creating agent applications, showcasing impressive performance even when compared to bigger models on complex tasks like utilizing a code interpreter. Furthermore, we have developed coding-specialized models, Code-Qwen and Code-Qwen-Chat, as well as mathematics-focused models, Math-Qwen-Chat, which are built upon base language models. These models demonstrate significantly improved performance in comparison with open-source models, and slightly fall behind the proprietary models.Comment: 59 pages, 5 figure

Iron Accumulation with Age, Oxidative Stress and Functional Decline

Identification of biological mediators in sarcopenia is pertinent to the development of targeted interventions to alleviate this condition. Iron is recognized as a potent pro-oxidant and a catalyst for the formation of reactive oxygen species in biological systems. It is well accepted that iron accumulates with senescence in several organs, but little is known about iron accumulation in muscle and how it may affect muscle function. In addition, it is unclear if interventions which reduced age-related loss of muscle quality, such as calorie restriction, impact iron accumulation. We investigated non-heme iron concentration, oxidative stress to nucleic acids in gastrocnemius muscle and key indices of sarcopenia (muscle mass and grip strength) in male Fischer 344 X Brown Norway rats fed ad libitum (AL) or a calorie restricted diet (60% of ad libitum food intake starting at 4 months of age) at 8, 18, 29 and 37 months of age. Total non-heme iron levels in the gastrocnemius muscle of AL rats increased progressively with age. Between 29 and 37 months of age, the non-heme iron concentration increased by approximately 200% in AL-fed rats. Most importantly, the levels of oxidized RNA in gastrocnemius muscle of AL rats were significantly increased as well. The striking age-associated increase in non-heme iron and oxidized RNA levels and decrease in sarcopenia indices were all attenuated in the calorie restriction (CR) rats. These findings strongly suggest that the age-related iron accumulation in muscle contributes to increased oxidative damage and sarcopenia, and that CR effectively attenuates these negative effects

Zigzag edge ferromagnetism of triangular-graphene-quantum-dot-like system

The magnetic susceptibility of a triangular-graphene-quantum-dot-like system was examined by using the determinant quantum Monte Carlo method. We focused on three kinds of zigzag edge quantum dots or rings, namely the triangular graphene quantum ring, twist bilayer triangular graphene quantum dot, and twist bilayer triangular graphene quantum ring. The triangular-graphene-quantum-dot-like system exhibits robust edge ferromagnetic behavior, which is independent of size, monolayer or bilayer, and dot or ring shape, according to the unbiased numerical results. At half filling, the edge magnetic susceptibility is increased by on-site interaction, especially in low temperature region. Applications of this system in spintronics may benefit from the robust edge ferromagnetic behavior.Comment: 6 pages, 7 figure

An Optical Fiber Sensor Coated with Electrospinning Polyvinyl Alcohol/Carbon Nanotubes Composite Film

A fiber-optics tapered sensor that is covered by an electrospinning polyvinyl alcohol (PVA) nanofiber film, is demonstrated to measure humidity and temperature simultaneously. A section multi-mode fiber (MMF) was sandwiched between two leading-in and out single mode fibers (SMFs), which was further tapered down to 29 μm to promote the humidity sensitivity of the sensor. A thin layer of electrospinning PVA nanofiber film was uniformly coated on the MMF taper region by electrospinning technology. In order to promote the humidity sensitivity and mechanical strength of electrospinning nanofibers, the carbon nanotubes (CNTs) were mixed into PVA to formed PVA/CNTs composite nanofiber film. A Fiber Bragg Grating (FBG) was cascaded with the humidity sensing fiber to monitor the ambient temperature simultaneously. The addition of CNTs effectively eliminated the cracks on the electrospinning nanofiber and made it more uniform and smoother. As experimental results show, the humidity sensitivity of the sensor with PVA/CNTs film was 0.0484 dB/%RH, an improvement of 31.16% compared to that of the sensor with PVA film, for which sensitivity is 0.0369 dB/%RH. The nanofiber humidity-sensitive film constructed using electrospinning had a satisfactory humidity response, special 3D structure and extensive application prospect

Discovery of a novel lipid metabolism-related gene signature to predict outcomes and the tumor immune microenvironment in gastric cancer by integrated analysis of single-cell and bulk RNA sequencing

Abstract Gastric cancer (GC) is a pressing global clinical issue, with few treatment options and a poor prognosis. The onset and spread of stomach cancer are significantly influenced by changes in lipid metabolism-related pathways. This study aimed to discover a predictive signature for GC using lipid metabolism-related genes (LMRGs) and examine its correlation with the tumor immune microenvironment (TIME). Transcriptome data and clinical information from patients with GC were collected from the TCGA and GEO databases. Data from GC samples were analyzed using both bulk RNA-seq and single-cell sequencing of RNA (scRNA-seq). To identify survival-related differentially expressed LMRGs (DE-LMRGs), differential expression and prognosis studies were carried out. We built a predictive signature using LASSO regression and tested it on the TCGA and GSE84437 datasets. In addition, the correlation of the prognostic signature with the TIME was comprehensively analyzed. In this study, we identified 258 DE-LMRGs in GC and further screened seven survival-related DE-LMRGs. The results of scRNA-seq identified 688 differentially expressed genes (DEGs) between the three branches. Two critical genes (GPX3 and NNMT) were identified using the above two gene groups. In addition, a predictive risk score that relies on GPX3 and NNMT was developed. Survival studies in both the TCGA and GEO datasets revealed that patients categorized to be at low danger had a significantly greater prognosis than those identified to be at high danger. Additionally, by employing calibration plots based on TCGA data, the study demonstrated the substantial predictive capacity of a prognostic nomogram, which incorporated a risk score along with various clinical factors. Within the high-risk group, there was a noticeable abundance of active natural killer (NK) cells, quiescent monocytes, macrophages, mast cells, and activated CD4 + T cells. In summary, a two-gene signature and a predictive nomogram have been developed, offering accurate prognostic predictions for general survival in GC patients. These findings have the potential to assist healthcare professionals in making informed medical decisions and providing personalized treatment approaches

A New Method for In-Situ Characterization of Solid-State Batteries Based on Optical Coherence Tomography

With the in-depth study of solid-state batteries (SSBs), various in situ and ex situ characterization technologies have been widely used to study them. The performance and reliability of SSBs are limited by the formation and evolution of lithium dendrites at the interfaces between solid electrodes and solid electrolytes. We propose a new method based on optical coherence tomography (OCT) for in situ characterization of the internal state of solid-state batteries. OCT is a low-loss, high-resolution, non-invasive imaging technique that can provide real-time monitoring of cross-sectional images of internal structures of SSBs. The morphology, growth, and evolution of lithium dendrites at different stages of cycling under various conditions can be visualized and quantified by OCT. Furthermore, we validate and correlate the OCT results with scanning electron microscopy (SEM) and XPS, proving the accuracy and effectiveness of the OCT characterization method. We reveal the interfacial phenomena and challenges in SSBs and demonstrate the feasibility and advantages of OCT as a powerful tool for in situ and operando imaging of battery interfaces. This study provides new insights into the mechanisms and factors that affect SSB performance, safety, and lifetime, and suggests possible solutions for improvement and application in the field of applied energy

Methyl Salicylate Lactoside Protects Neurons Ameliorating Cognitive Disorder Through Inhibiting Amyloid Beta-Induced Neuroinflammatory Response in Alzheimer’s Disease

Neuroinflammatory reactions mediated by microglia and astrocytes have been shown to play a key role in early progression of Alzheimer’s disease (AD). Increased evidences have demonstrated that neurons exacerbate local inflammatory reactions by producing inflammatory mediators and act as an important participant in the pathogenesis of AD. Methyl salicylate lactoside (MSL) is an isolated natural product that is part of a class of novel non-steroidal anti-inflammatory drugs (NSAID). In our previous studies, we demonstrated that MSL exhibited therapeutic effects on arthritis-induced mice and suppressed the activation of glial cells. In the current study, we investigated the effects of MSL on cognitive function and neuronal protection induced by amyloid-beta peptides (Aβ) and explored potential underlying mechanisms involved. Amyloid precursor protein (APP) and presenilin 1 (PS1) double transgenic mice were used to evaluate the effects of MSL through behavioral testing and neuronal degenerative changes. In addition, copper-injured APP Swedish mutation overexpressing SH-SY5Y cells were used to determine the transduction of cyclooxygenase (COX) and mitogen-activated protein kinase (MAPK) pathways. Our results indicated that at an early stage, MSL treatment ameliorated cognitive impairment and neurodegeneration in APP/PS1 mice. Moreover, in an in vitro AD model, MSL treatment protected injured cells by increasing cell viability, improving mitochondrial dysfunction, and decreasing oxidative damage. In addition, MSL inhibited the phosphorylated level of c-Jun N-terminal kinase (JNK) and p38 MAPK, and suppressed the expression of COX-1/2. As a novel NSAIDs and used for the treatment in early stage of AD, MSL clearly demonstrated cognitive preservation by protecting neurons via a pleiotropic anti-inflammatory effect in the context of AD-associated deficits. Therefore, early treatment of anti-inflammatory therapy may be an effective strategy for treating AD