Age-Related Digital Divide during the COVID-19 Pandemic in China

China has adopted a variety of digital technologies to effectively combat the unprecedented COVID-19 pandemic. The massive utilisation of digital technologies, however, to a great extent, magnifies the age-related digital divide. This paper aims to examine the impacts of the age-related digital divide on older adults in the context of the COVID-19 pandemic. Cases of three age-related digital divide scenarios, including older people taking public transportation, seeking medical care, as well as conducting digital transactions, are collected from Chinese official news outlets. The results indicate that the COVID-19 pandemic accelerates the pace of digital technology utilisation but exacerbates the age-related digital divide. Such an age-related digital divide has largely excluded older adults from both the real society and the virtual society. Older adults’ personal attitudes and motivations, as well as education and income, governmental policies, and family and social supports, are all major contributors to the severe impacts of the age-related digital divide on old adults during the pandemic. More measures should be adopted to bridge the age-related digital divide and build a senior-friendly e-society.</jats:p

Maskless micro/nanofabrication on GaAs surface by friction-induced selective etching

In the present study, a friction-induced selective etching method was developed to produce nanostructures on GaAs surface. Without any resist mask, the nanofabrication can be achieved by scratching and post-etching in sulfuric acid solution. The effects of the applied normal load and etching period on the formation of the nanostructure were studied. Results showed that the height of the nanostructure increased with the normal load or the etching period. XPS and Raman detection demonstrated that residual compressive stress and lattice densification were probably the main reason for selective etching, which eventually led to the protrusive nanostructures from the scratched area on the GaAs surface. Through a homemade multi-probe instrument, the capability of this fabrication method was demonstrated by producing various nanostructures on the GaAs surface, such as linear array, intersecting parallel, surface mesas, and special letters. In summary, the proposed method provided a straightforward and more maneuverable micro/nanofabrication method on the GaAs surface

Friction-induced nanofabrication method to produce protrusive nanostructures on quartz

In this paper, a new friction-induced nanofabrication method is presented to fabricate protrusive nanostructures on quartz surfaces through scratching a diamond tip under given normal loads. The nanostructures, such as nanodots, nanolines, surface mesas and nanowords, can be produced on the target surface by programming the tip traces according to the demanded patterns. The height of these nanostructures increases with the increase of the number of scratching cycles or the normal load. Transmission electron microscope observations indicated that the lattice distortion and dislocations induced by the mechanical interaction may have played a dominating role in the formation of the protrusive nanostructures on quartz surfaces. Further analysis reveals that during scratching, a contact pressure ranged from 0.4Py to Py (Py is the critical yield pressure of quartz) is apt to produce protuberant nanostructures on quartz under the given experimental conditions. Finally, it is of great interest to find that the protrusive nanostructures can be selectively dissolved in 20% KOH solution. Since the nanowords can be easily 'written' by friction-induced fabrication and 'erased' through selective etching on a quartz surface, this friction-induced method opens up new opportunities for future nanofabrication

Fabrication mechanism of friction-induced selective etching on Si(100) surface

As a maskless nanofabrication technique, friction-induced selective etching can easily produce nanopatterns on a Si(100) surface. Experimental results indicated that the height of the nanopatterns increased with the KOH etching time, while their width increased with the scratching load. It has also found that a contact pressure of 6.3 GPa is enough to fabricate a mask layer on the Si(100) surface. To understand the mechanism involved, the cross-sectional microstructure of a scratched area was examined, and the mask ability of the tip-disturbed silicon layer was studied. Transmission electron microscope observation and scanning Auger nanoprobe analysis suggested that the scratched area was covered by a thin superficial oxidation layer followed by a thick distorted (amorphous and deformed) layer in the subsurface. After the surface oxidation layer was removed by HF etching, the residual amorphous and deformed silicon layer on the scratched area can still serve as an etching mask in KOH solution. The results may help to develop a low-destructive, low-cost, and flexible nanofabrication technique suitable for machining of micro-mold and prototype fabrication in micro-systems

Low-code LLM: Graphical User Interface over Large Language Models

Utilizing Large Language Models (LLMs) for complex tasks is challenging, often involving a time-consuming and uncontrollable prompt engineering process. This paper introduces a novel human-LLM interaction framework, Low-code LLM. It incorporates six types of simple low-code visual programming interactions to achieve more controllable and stable responses. Through visual interaction with a graphical user interface, users can incorporate their ideas into the process without writing trivial prompts. The proposed Low-code LLM framework consists of a Planning LLM that designs a structured planning workflow for complex tasks, which can be correspondingly edited and confirmed by users through low-code visual programming operations, and an Executing LLM that generates responses following the user-confirmed workflow. We highlight three advantages of the low-code LLM: user-friendly interaction, controllable generation, and wide applicability. We demonstrate its benefits using four typical applications. By introducing this framework, we aim to bridge the gap between humans and LLMs, enabling more effective and efficient utilization of LLMs for complex tasks. The code, prompts, and experimental details are available at https://github.com/moymix/TaskMatrix/tree/main/LowCodeLLM. A system demonstration video can be found at https://www.youtube.com/watch?v=jb2C1vaeO3E.Comment: Accepted as a Demo Track paper at NAACL 202

TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs

Artificial Intelligence (AI) has made incredible progress recently. On the one hand, advanced foundation models like ChatGPT can offer powerful conversation, in-context learning and code generation abilities on a broad range of open-domain tasks. They can also generate high-level solution outlines for domain-specific tasks based on the common sense knowledge they have acquired. However, they still face difficulties with some specialized tasks because they lack enough domain-specific data during pre-training or they often have errors in their neural network computations on those tasks that need accurate executions. On the other hand, there are also many existing models and systems (symbolic-based or neural-based) that can do some domain-specific tasks very well. However, due to the different implementation or working mechanisms, they are not easily accessible or compatible with foundation models. Therefore, there is a clear and pressing need for a mechanism that can leverage foundation models to propose task solution outlines and then automatically match some of the sub-tasks in the outlines to the off-the-shelf models and systems with special functionalities to complete them. Inspired by this, we introduce TaskMatrix.AI as a new AI ecosystem that connects foundation models with millions of APIs for task completion. Unlike most previous work that aimed to improve a single AI model, TaskMatrix.AI focuses more on using existing foundation models (as a brain-like central system) and APIs of other AI models and systems (as sub-task solvers) to achieve diversified tasks in both digital and physical domains. As a position paper, we will present our vision of how to build such an ecosystem, explain each key component, and use study cases to illustrate both the feasibility of this vision and the main challenges we need to address next

Mapping the path towards novel treatment strategies: a bibliometric analysis of Hashimoto’s thyroiditis research from 1990 to 2023

BackgroundHashimoto’s thyroiditis (HT), a common form of thyroid autoimmunity, is strongly associated with deteriorating clinical status and impaired quality of life. The escalating global prevalence, coupled with the complexity of disease mechanisms, necessitates a comprehensive, bibliometric analysis to elucidate the trajectory, hotspots, and future trends in HT research.ObjectiveThis study aims to illuminate the development, hotspots, and future directions in HT research through systematic analysis of publications, institutions, authors, journals, references, and keywords. Particular emphasis is placed on novel treatment strategies for HT and its complications, highlighting the potential role of genetic profiling and immunomodulatory therapies.MethodsWe retrieved 8,726 relevant documents from the Web of Science Core Collection database spanning from 1 January 1990 to 7 March 2023. Following the selection of document type, 7,624 articles were included for bibliometric analysis using CiteSpace, VOSviewer, and R software.ResultsThe temporal evolution of HT research is categorized into three distinct phases: exploration (1990-1999), rapid development (1999-2000), and steady growth (2000-present). Notably, the United States, China, Italy, and Japan collectively contributed over half (54.77%) of global publications. Among the top 10 research institutions, four were from Italy (4/10), followed by China (2/10) and the United States (2/10). Recent hotspots, such as the roles of gut microbiota, genetic profiling, and nutritional factors in HT management, the diagnostic dilemmas between HT and Grave’s disease, as well as the challenges in managing HT complicated by papillary thyroid carcinoma and type 1 diabetes mellitus, are discussed.ConclusionAlthough North America and Europe have a considerable academic impact, institutions from emerging countries like China are demonstrating promising potential in HT research. Future studies are anticipated to delve deeper into the differential diagnosis of HT and Grave’s disease, the intricate relationship between gut microbiota and HT pathogenesis, clinical management of HT with papillary thyroid carcinoma or type 1 diabetes, and the beneficial effects of dietary modifications and micronutrients supplementation in HT. Furthermore, the advent of genetic profiling and advanced immunotherapies for managing HT offers promising avenues for future research

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Spatial analysis and modeling of transport demand

Spatial characteristics of transportation demand have not received much attention in the past research. The objective of this research is to explore spatial characteristics of transportation demand and establish models to describe some of their key characteristics including activity space (AS) and vehicle kilometers traveled (VKT).Master of Engineering (CEE