Cr/Fe超薄膜/酸化物量子井戸における電圧制御磁気異方性とスピン依存共鳴トンネル効果

筑波大学 (University of Tsukuba)201

Cr/Fe超薄膜/酸化物量子井戸における電圧制御磁気異方性とスピン依存共鳴トンネル効果

筑波大学 (University of Tsukuba)201

The relationship between metabolic rate and sociability is altered by food-deprivation

Individuals vary in the extent to which they associate with conspecifics, but little is known about the energetic underpinnings of this variation in sociability. Group-living allows individuals to find food more consistently, but within groups, there can be competition for food items. Individuals with an increased metabolic rate could display decreased sociability to reduce competition. Long-term food deprivation (FD) may alter any links between sociability and metabolic rate by affecting motivation to find food. We examined these issues in juvenile qingbo carp Spinibarbus sinensis, to understand how FD and metabolic rate affect sociability. Like many aquatic ectotherms, this species experiences seasonal bouts of FD. Individuals were either: (i) food-deprived for 21 days; or (ii) fed a maintenance ration (control). Fish from each treatment were measured for standard metabolic rate (SMR) and tested for sociability twice: once in the presence of a control stimulus shoal and once with a food-deprived stimulus shoal. Control individuals ventured further from stimulus shoals over a 30-min trial, while food-deprived fish did not change their distance from stimulus shoals as trials progressed. Control fish with a higher SMR were least sociable. Well-fed controls showed decreased sociability when exposed to food-deprived stimulus shoals, but there was evidence of consistency in relative sociability between exposures to different shoal types. Results contrast with previous findings that several days of fasting causes individuals to decrease associations with conspecifics. Prolonged FD may cause individuals to highly prioritize food acquisition, and the decreased vigilance that would accompany continuous foraging may heighten the need for the antipredator benefits of shoaling. Conversely, decreased sociability in well-fed fish with a high SMR probably minimizes intraspecific competition, allowing them to satisfy an increased energetic demand while foraging. Together, these results suggest that FD – a challenge common for many ectothermic species – can affect individual sociability as well as the attractiveness of groups towards conspecifics. In addition, the lack of a link between SMR and sociability in food-deprived fish suggests that, in situations where group membership is linked to fitness, the extent of correlated selection on metabolic traits may be context-dependent

Sparsity for Ultrafast Material Identification

Mid-infrared spectroscopy is often used to identify material. Thousands of spectral points are measured in a time-consuming process using expensive table-top instrument. However, material identification is a sparse problem, which in theory could be solved with just a few measurements. Here we exploit the sparsity of the problem and develop an ultra-fast, portable, and inexpensive method to identify materials. In a single-shot, a mid-infrared camera can identify materials based on their spectroscopic signatures. This method does not require prior calibration, making it robust and versatile in handling a broad range of materials

Fatigue reliability assessment of small sample excavator working devices based on Bootstrap method

To evaluate the fatigue reliability of the excavator working device, the fatigue tests of 2 sets of moving arm and bucket rod of medium-sized excavators with self-weight of 26000 kg were carried out. The virtual augmented sample method (VASM) combined with Bootstrap method was used to analyze the reliability of the excavator working device under extreme small samples, and the interval and point estimations of life parameters were obtained. Based on the lognormal distribution of the excavator working device, the reliability evaluation model of the excavator working device was esTablelished, and reliability indexes, such as reliability function, failure distribution function, inefficiency function, reliable life and so on, were obtained. And the results of fatigue safety life under different confidence and reliability were calculated. The evaluation results show that the average failure time of the excavator working device is 5885 hours under the confidence of 75%, which provides an important reference for the design, the safety inspection and maintenance decision of the excavator working device

Genetic variants of DNA repair genes predict the survival of patients with esophageal squamous cell cancer receiving platinum-based adjuvant chemotherapy

Additional file 2: Table S2. Stratified univariate analysis of DFS and OS between LG* and HG* in Chinese ESCC patients

TableGPT: Towards Unifying Tables, Nature Language and Commands into One GPT

Tables are prevalent in real-world databases, requiring significant time and effort for humans to analyze and manipulate. The advancements in large language models (LLMs) have made it possible to interact with tables using natural language input, bringing this capability closer to reality. In this paper, we present TableGPT, a unified fine-tuned framework that enables LLMs to understand and operate on tables using external functional commands. It introduces the capability to seamlessly interact with tables, enabling a wide range of functionalities such as question answering, data manipulation (e.g., insert, delete, query, and modify operations), data visualization, analysis report generation, and automated prediction. TableGPT aims to provide convenience and accessibility to users by empowering them to effortlessly leverage tabular data. At the core of TableGPT lies the novel concept of global tabular representations, which empowers LLMs to gain a comprehensive understanding of the entire table beyond meta-information. By jointly training LLMs on both table and text modalities, TableGPT achieves a deep understanding of tabular data and the ability to perform complex operations on tables through chain-of-command instructions. Importantly, TableGPT offers the advantage of being a self-contained system rather than relying on external API interfaces. Moreover, it supports efficient data process flow, query rejection (when appropriate) and private deployment, enabling faster domain data fine-tuning and ensuring data privacy, which enhances the framework's adaptability to specific use cases.Comment: Technical Repor