River Network Patterns and Their Evolutionary Preconditions

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Image Restoration Combining the Second-Order and Fourth-Order PDEs

A noise removal technique using partial differential equations (PDEs) is proposed. It combines a second-order filter with a fourth-order filter. The combined method takes the advantage of both filters since it can preserve edges and at the same time avoid the blocky effects in smooth regions. The experimental results illustrate the effectiveness of the model in image restoration

Analyzing the farmers' pro-environmental behavior intention and their rural tourism livelihood in tourist village where its ecological environment is polluted.

This study examines farmers' intentions towards pro-environmental behavior in a famous tourist village in China called Guanshan, whose ecological environment is polluted. By adopting the empirically validated norm activation model (NAM) of Schwartz and merging it with Vroom's expectancy theory, the current research aims to develop a refined framework for understanding the formation of and predicting changes in pro-environmental intention. Field surveys were conducted in Guanshan, which resulted in sample data consisting of 275 valid responses collected by the research team. We develop a refined model, including six latent variables and 24 observational items. The structural equation modeling results show that the final model enjoys a better predictive accuracy of pro-environmental intention than does the original NAM. The study also discovers that the motivational force of expectancy theory significantly influences pro-environmental intention, whose motivational force comes from the impact of valence and expectancy. The pro-environmental intentions of farmers are mainly affected by the environmental personal norm and by a certain degree of personal expectancy. The improvement of farmers' pro-environmental intention needs be promoted in two approaches: the cultivation of personal environmental protection norms and the guidance of producing a desired expectation for pro-environmental intention

Stream networks and knickpoints in the Sanjiangyuan Region

Abstract: Stream networks and knickpoints in the Sanjiangyuan Region. The source area of the Lancang (Mekong), Yangtze and Yellow rivers is named in Chinese Sanjiangyuan (source of three rivers). Geographical characteristics of these rivers, and various rivers at the margin of the Qinghai-Tibetan Plateau (Jialing, Minjiang, Dadu, Yalong and Jinsha) are summarized from fi eld investigations along with digital elevation model (DEM) analyses and satellite images. Uplift of the Qinghai-Tibetan Plateau has resulted in an asymmetrical distribution of tributaries for stream networks at the margins of the plateau. Almost all tributaries join the trunk stream from the northwest. Three types of drainage network are evident: plume, nervation and dendritic. In general, plume networks have a large number of fi rst order streams. Nervation networks have a main stream and parallel tributaries. Dentritic networks are characrterized by continuous bifurcation and have a branch-like appearance. Most stream networks in the Sanjiangyuan region are of the nervation type. Several large knickpoints are evident along the longitudinal profi les of the Yellow and Yangtze Rivers. Channel aggradation immediately upstream of these knickpoints marks a transition in river processes from vertical bed evolution (i.e. incision) to horizontal channel adjustment (and associated braided and anabranching channels)

Research on Construction Quality Acceptance and Digital Archive Management System Based on BIM

By analyzing the existing problems and causes of the construction quality acceptance assessment of engineering projects, the idea of BIM-based construction quality inspection and assessment system architecture was proposed. Through the operation of the system, digital and paperless management of construction project archives was realized while the construction quality inspection and assessment was proceeded. Then it also analyzed the advantages of this system and put forward countermeasures to the possible problems during the operation process

Spatiotemporal variations of “triple-demic” outbreaks of respiratory infections in the United States in the post-COVID-19 era

Background: the US confronted a “triple-demic” of influenza, respiratory syncytial virus (RSV), and COVID-19 in the winter of 2022, leading to increased respiratory infections and a higher demand for medical supplies. It is urgent to analyze these epidemics and their spatial-temporal co-occurrence, identifying hotspots and informing public health strategies.Methods: we employed retrospective and prospective space-time scan statistics to assess the situations of COVID-19, influenza, and RSV in 51 US states from October 2021 to February 2022, and from October 2022 to February 2023, respectively. This enabled monitoring of spatiotemporal variations for each epidemic individually and collectively.Results: compared to winter 2021, COVID-19 cases decreased while influenza and RSV infections significantly increased in winter 2022. We found a high-risk cluster of influenza and COVID-19 (not all three) in winter 2021. In late November 2022, a large high-risk cluster of triple-demic emerged in the central US. The number of states at high risk for multiple epidemics increased from 15 in October 2022 to 21 in January 2023.Conclusions: our study offers a novel spatiotemporal approach that combines both univariate and multivariate surveillance, as well as retrospective and prospective analyses. This approach offers a more comprehensive and timely understanding of how the co-occurrence of COVID-19, influenza, and RSV impacts various regions within the United States. Our findings assist in tailor-made strategies to mitigate the effects of these respiratory infections

Stable and Reusable Electrochemical Biosensor for Poly(ADP-ribose) Polymerase and Its Inhibitor Based on Enzyme-Initiated Auto-PARylation

A stable and reusable electrochemical biosensor for the label-free detection of poly­(ADP-ribose) polymerase (PARP) is designed in this work. C-kit-1, a thiol-modified G-quadruplex oligonucleotide, is first self-assembled on a gold electrode surface. The G-quadruplex structure of c-kit-1 can specifically tether and activate PARP, resulting in the generation of negatively charged poly­(ADP-ribose) polymer (PAR). On the basis of electrostatic attraction, PAR facilitates the surface accumulation of positively charged electrochemical signal molecules. Through the characterization of electrochemical signal molecules, the label-free quantification of PARP is simply implemented. On the basis of the proposed method, selective quantification of PARP can be achieved over the linear range from 0.01 to 1 U with a calculated detection limit of 0.003U. Further studies also demonstrate the applicability of the proposed method to biosamples revealing the broad potential in practical applications. Furthermore, inhibitor of PARP has also been detected with this biosensor. Meanwhile, benefited from self-assembly on solid surface, this biosensor possesses two important features, i.e., reusability and stability, which are desirable in related biosensors