Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation

Knowledge-intensive tasks (e.g., open-domain question answering (QA)) require a substantial amount of factual knowledge and often rely on external information for assistance. Recently, large language models (LLMs) (e.g., ChatGPT), have demonstrated impressive prowess in solving a wide range of tasks with world knowledge, including knowledge-intensive tasks. However, it remains unclear how well LLMs are able to perceive their factual knowledge boundaries, particularly how they behave when incorporating retrieval augmentation. In this study, we present an initial analysis of the factual knowledge boundaries of LLMs and how retrieval augmentation affects LLMs on open-domain QA. Specially, we focus on three primary research questions and analyze them by examining QA performance, priori judgement and posteriori judgement of LLMs. We show evidence that LLMs possess unwavering confidence in their capabilities to respond to questions and the accuracy of their responses. Furthermore, retrieval augmentation proves to be an effective approach in enhancing LLMs' awareness of knowledge boundaries, thereby improving their judgemental abilities. Additionally, we also find that LLMs have a propensity to rely on the provided retrieval results when formulating answers, while the quality of these results significantly impacts their reliance. The code to reproduce this work is available at https://github.com/RUCAIBox/LLM-Knowledge-Boundary

Prevalence and Predictors of Loss of Wild Type BRCA1 in Estrogen Receptor Positive and Negative BRCA1-Associated Breast Cancers

Introduction: The majority of breast cancers that occur in BRCA1 mutation carriers (BRCA1 carriers) are estrogen receptor-negative (ER-). Therefore, it has been suggested that ER negativity is intrinsic to BRCA1 cancers and reflects the cell of origin of these tumors. However, approximately 20% of breast cancers that develop in BRCA1 carriers are ER-positive (ER+); these cancers are more likely to develop as BRCA1 carriers age, suggesting that they may be incidental and unrelated to BRCA1 deficiency. The purpose of this study was to compare the prevalence of loss of heterozygosity due to loss of wild type (wt) BRCA1 in ER+ and ER- breast cancers that have occurred in BRCA1 carriers and to determine whether age at diagnosis or any pathologic features or biomarkers predict for loss of wt BRCA1 in these breast cancers. Methods: Relative amounts of mutated and wt BRCA1 DNA were measured by quantitative polymerase chain reaction performed on laser capture microdissected cancer cells from 42 ER+ and 35 ER- invasive breast cancers that developed in BRCA1 carriers. BRCA1 gene methylation was determined on all cancers in which sufficient DNA was available. Immunostains for cytokeratins (CK) 5/6, 14, 8 and 18, epidermal growth factor receptor and p53 were performed on paraffin sections from tissue microarrays containing these cancers. Results: Loss of wt BRCA1 was equally frequent in ER+ and ER- BRCA1-associated cancers (81.0% vs 88.6%, respectively; P = 0.53). One of nine cancers tested that retained wt BRCA1 demonstrated BRCA1 gene methylation. Age at diagnosis was not significantly different between first invasive ER+ BRCA1 breast cancers with and without loss of wt BRCA1 (mean age 45.2 years vs 50.1 years, respectively; P = 0.51). ER+ BRCA1 cancers that retained wt BRCA1 were significantly more likely than those that lost wt BRCA1 to have a low mitotic rate (odds ratio (OR), 5.16; 95% CI, 1.91 to ∞). BRCA1 cancers with loss of wt BRCA1 were more likely to express basal cytokeratins CK 5/6 or 14 (OR 4.7; 95% CI, 1.85 to ∞). Conclusions: We found no difference in the prevalence of loss of wt BRCA1 between ER+ and ER- invasive BRCA1-associated breast cancers. Our findings suggest that many of the newer therapies for BRCA1 breast cancers designed to exploit the BRCA1 deficiency in these cancers may also be effective in ER+ cancers that develop in this population

Critical role of multidimensional biodiversity in contributing to ecosystem sustainability under global change

The 21st century has seen an acceleration of global change, including climate change, elevated carbon dioxide, nitrogen deposition, and land-use intensification, which poses a significant threat to ecosystem functioning. Nevertheless, studies on the relationship between biodiversity and ecosystem functioning (BEF) have consistently demonstrated that biodiversity enhances ecosystem functioning and its stability, even in variable environmental conditions. These findings potentially indicate the critical role of biodiversity in promoting sustainable provisioning of ecosystem functioning under global change. Our paper provides a comprehensive review of current BEF research and the response of BEF to multiple global change factors. We demonstrate that (1) assessing the effects of biodiversity on ecosystem functioning requires consideration of multiple dimensions of diversity, such as diversity across multiple trophic levels (plants, animals, and microbes), multiple facets (taxonomy, functional traits, and phylogeny), and multiple spatial scales (local, regional, and landscape scales). (2) The interaction of multiple global change factors may lead to a greater reduction in biodiversity and ecosystem functioning than a single global change factor. (3) Multidimensional biodiversity regulates the response of ecosystem functioning to global change factors, indicating that high levels of multidimensional biodiversity can mitigate the negative impacts of global change on ecosystem functioning. Overall, we emphasize that recognizing the importance of multidimensional biodiversity is critical for sustaining ecosystem functioning. Therefore, prioritizing conservation efforts to maintain and enhance all dimensions of biodiversity is essential to address the challenges of future global change

Extraction of Information about Individual Trees from High-Spatial-Resolution UAV-Acquired Images of an Orchard

The extraction of information about individual trees is essential to supporting the growing of fruit in orchard management. Data acquired from spectral sensors mounted on unmanned aerial vehicles (UAVs) have very high spatial and temporal resolution. However, an efficient and reliable method for extracting information about individual trees with irregular tree-crown shapes and a complicated background is lacking. In this study, we developed and tested the performance of an approach, based on UAV imagery, to extracting information about individual trees in an orchard with a complicated background that includes apple trees (Plot 1) and pear trees (Plot 2). The workflow involves the construction of a digital orthophoto map (DOM), digital surface models (DSMs), and digital terrain models (DTMs) using the Structure from Motion (SfM) and Multi-View Stereo (MVS) approaches, as well as the calculation of the Excess Green minus Excess Red Index (ExGR) and the selection of various thresholds. Furthermore, a local-maxima filter method and marker-controlled watershed segmentation were used for the detection and delineation, respectively, of individual trees. The accuracy of the proposed method was evaluated by comparing its results with manual estimates of the numbers of trees and the areas and diameters of tree-crowns, all three of which parameters were obtained from the DOM. The results of the proposed method are in good agreement with these manual estimates: The F-scores for the estimated numbers of individual trees were 99.0% and 99.3% in Plot 1 and Plot 2, respectively, while the Producer’s Accuracy (PA) and User’s Accuracy (UA) for the delineation of individual tree-crowns were above 95% for both of the plots. For the area of individual tree-crowns, root-mean-square error (RMSE) values of 0.72 m2 and 0.48 m2 were obtained for Plot 1 and Plot 2, respectively, while for the diameter of individual tree-crowns, RMSE values of 0.39 m and 0.26 m were obtained for Plot 1 (339 trees correctly identified) and Plot 2 (203 trees correctly identified), respectively. Both the areas and diameters of individual tree-crowns were overestimated to varying degrees

A Study of Real-Time Scheduling Algorithms in Cluster Environment Based on Machine Learning

Machine Learning is on the rise and is transforming industries across the board, from climate forecasting to stock price evaluation. In this study, we explore the use of machine learning in real-Time scheduling algorithms for cluster environments. Using the \u27GWA-T-4 Auver Grid\u27 dataset, we predict burst times of processes with an accuracy of over 87%. We then compare the performance of the FCFS and SJF scheduling algorithms using these predictions, and find that while SJF performs better, it is better suited for short processes, while FCFS is better for longer ones. Our results provide insight into the potential of machine learning in the realm of real-Time scheduling algorithms for cluster environments

In Situ Chemical Modification with Zwitterionic Copolymers of Nanofiltration Membranes:Cure for the Trade-Off between Filtration and Antifouling Performance

Breaking the trade-off between filtration performance and antifouling property is critical to enabling a thin-film nanocomposite (TFC) nanofiltration (NF) membrane for a wide range of feed streams. We proposed a novel design route for TFC NF membranes by grafting well-defined zwitterionic copolymers of [2-(methacryloyloxy)ethyl]dimethyl-(3-sulfopropyl)ammonium hydroxide (SBMA) and 2-aminoethyl methacrylate hydrochloride (AEMA) on the polyamide surfaces via an in situ surface chemical modification process. The successful grafting of a zwitterionic copolymer imparted the modified NF membranes with better surface hydrophilicity, a larger actual surface area (i.e., nodular structures), and a thinner polyamide layer. As a result, the water permeability of the modified membrane (i.e., TFC-10) was triple that of the pristine TFC membrane while maintaining high Na2SO4 rejection. We further demonstrated that the TFC-10 membrane possessed exceptional antifouling properties in both static adsorption tests and three cycles of dynamic protein and humic acid fouling tests. To recap, this work provides valuable insights and strategies for the fabrication of TFC NF membranes with simultaneously enhanced filtration performance and antifouling property.</p

Hydrothermal Synthesis Au-Bi2Te3 Nanocomposite Thermoelectric Film with a Hierarchical Sub-Micron Antireflection Quasi-Periodic Structure

In this work, Au-Bi2Te3 nanocomposite thermoelectric film with a hierarchical sub-micron antireflection quasi-periodic structure was synthesized via a low-temperature chemical route using Troides helena (Linnaeus) forewing (T_FW) as the biomimetic template. This method combines chemosynthesis with biomimetic techniques, without the requirement of expensive equipment and energy intensive processes. The microstructure and the morphology of the Au-Bi2Te3 nanocomposite thermoelectric film was analyzed by X-ray diffraction (XRD), field-emission scanning-electron microscopy (FESEM), and transmission electron microscopy (TEM). Coupled the plasmon resonances of the Au nanoparticles with the hierarchical sub-micron antireflection quasi-periodic structure, the Au-Bi2Te3 nanocomposite thermoelectric film possesses an effective infrared absorption and infrared photothermal conversion performance. Based on the finite difference time domain method and the Joule effect, the heat generation and the heat source density distribution of the Au-Bi2Te3 nanocomposite thermoelectric film were studied. The heterogeneity of heat source density distribution of the Au-Bi2Te3 nanocomposite thermoelectric film opens up a novel promising technique for generating thermoelectric power under illumination

Seed nutrient is more stable than leaf in response to changing multiple resources in an alpine meadow

Abstract Background It has been long thought that nitrogen (N), phosphorus (P) concentrations and their ratios (N:P) in metabolically active or functional organs (i.e., leaves) are less responsive to environmental changes. Little attention, however, has been paid to the reproductive organs—seeds, while seeds may maintain their nutrients more stable for the evolutionary fitness of next generation. Methods Here, we conducted a field experiment of N, P addition and drought in an alpine meadow, aiming to compare the difference of leaf and seed nutrients and stoichiometric ratios in response to these resource treatments and their interactions. Four dominant species were selected among grass and forb functional groups, including Elymus nutans, Deschampsia caespitosa, Artemisia roxburghiana and Polygonum viviparum. Results Under natural conditions, leaf N and P concentrations were consistently lower than seed among species. However, leaf nutrients were much more sensitive than seed nutrients to N and P addition. Specifically, N or P addition accordingly increased leaf N or P concentration by 22.20–44.24% and 85.54–93.61%, while only enhanced seed N or P concentration by 5.15–17.20% and 15.17–32.72%, respectively. Leaf N or P concentration was significantly reduced by P or N addition, but seed nutrients remained unchanged. In contrast, drought did not change both organ nutrients. Similarly, nutrient addition and drought had synergistic interactions on leaf nutrients, but not on seed nutrients. Conclusions This study highlights that seed nutrient concentrations could be more stable than metabolically active leaf organ when facing multidimensional resource changes. This complements the traditional view on the ‘Stable Leaf Nutrient Hypothesis’ with the involvement of reproductive organs. The less responsiveness of seed nutrients suggests the adaptive strategy to ensure the success of next generations and long-term plant demographic stability

Single-cell sequencing: A promising approach for uncovering the characteristic of pancreatic islet cells in type 2 diabetes

Single-cell sequencing is a novel and rapidly advancing high-throughput technique that can be used to investigating genomics, transcriptomics, and epigenetics at a single-cell level. Currently, single-cell sequencing can not only be used to draw the pancreatic islet cells map and uncover the characteristics of cellular heterogeneity in type 2 diabetes, but can also be used to label and purify functional beta cells in pancreatic stem cells, improving stem cells and islet organoids therapies. In addition, this technology helps to analyze islet cell dedifferentiation and can be applied to the treatment of type 2 diabetes. In this review, we summarize the development and process of single-cell sequencing, describe the potential applications of single-cell sequencing in the field of type 2 diabetes, and discuss the prospects and limitations of single-cell sequencing to provide a new direction for exploring the pathogenesis of type 2 diabetes and finding therapeutic targets

108 m Underwater Wireless Optical Communication Using a 490 nm Blue VECSEL and an AOM

Advanced light sources in the blue-green band are crucial for underwater wireless optical communication (UWOC) systems. Vertical-external-cavity surface-emitting lasers (VECSELs) can produce high output power and good beam quality, making them suitable for UWOC. This paper presents a 108 m distance UWOC based on a 100 mW 490 nm blue VECSEL and an acousto-optic modulator (AOM). The high-quality beam, which is near diffraction-limited, undergoes relatively small optical attenuation when using a conventional avalanche photodiode (APD) as the detector and employing 64-pulse position modulation (PPM). At the time-slot frequency of 50 MHz, the bit error rate (BER) of the UWOC was 2.7 × 10−5. This is the first reported AOM-based UWOC system with a transmission distance over 100 m. The estimated maximum transmission distance may be improved to about 180 m by fully utilizing the detection accuracy of the APD according to the measured attenuation coefficient of the blue VECSEL used. This type of UWOC system, composed of a high-beam-quality light source and a conventional detector, make it more closely suited to practical applications