Design of microstrip-line coupled kinetic inductance detectors for near infrared astronomy

Kinetic inductance detectors (KID) have great potential in astronomical observation, such as searching for exoplanets, because of their low noise, fast response and photon counting characteristics. In this paper, we present the design process and simulation results of a microstrip line coupled KIDs array for near-infrared astronomical observation. Compared with coplanar waveguide (CPW) feedlines, microstrip feedlines do not require air bridges, which simplify fabrication process. In the design part, we mainly focus on the impedance transforming networks, the KID structure, and the frequency crosstalk simulations. The test array has a total of 104 resonators with 8 rows and 13 columns, which ranges from 4.899~GHz to 6.194~GHz. The pitch size is about 200~$\mu$m and the frequency crosstalk is less than 50~kHz in simulation

Increased human pressures on the alpine ecosystem along the Qinghai-Tibet Railway

Construction of the Qinghai-Tibet Railway (QTR) increased the links between inland China and the Qinghai-Tibet Plateau (QTP). The QTR accelerated surrounding tourism, boosted the local economy and led to rapid development of livestock raising. To assess how distance from the railway and different regions has influenced the impact of the QTR on the alpine ecosystem, human footprint maps were produced to indicate human pressures, and the normalized difference vegetation index (NDVI), an index of vegetation greenness, was used to characterize the growth of alpine vegetation. The construction and operation of the QTR have increased human pressures, while the establishment of nature reserves has effectively reduced human pressures. The QTR contributes significantly to the increased human pressures in the Tibetan region compared with the Qinghai region and exerts negative impacts on alpine vegetation. Although the warmer and wetter climate trend has proven beneficial in enhancing alpine vegetation greenness, the declining trend of alpine vegetation has been stronger in regions with more intensive human pressures, especially in the grazing areas and the tourist areas around Lhasa. These results suggest that the impact of the QTR on alpine vegetation in Tibet is greater than that in Qinghai and that the spatial extent of the indirect impact of the QTR in Tibet is confined to approximately 30 km from the railway. These results will provide guidance and a theoretical basis for the protection of the alpine environment on the QTP under intensified anthropogenic influence

Are the shoreline and eutrophication of desert lakes related to desert development?

Desert lakes are unique ecosystems found in oases within desert landscapes. Despite the numerous studies on oases, there are no reports regarding the spatiotemporal distribution and causes of eutrophication in the desert lakes that are located at the edge of the Linze Oasis in northwestern China. In this study, the seasonal shoreline and eutrophication of a desert lake were monitored using an unmanned aerial vehicle (UAV) and water sampling during three crop growth stages. The spatial extents of the shoreline and algal blooms and the chromophoric dissolved organic matter (CDOM) absorption coefficient were derived through UAV images. The desert lake shoreline declined during the crop growing stage, which exhibited the largest water demand and began to expand after this stage. The estimated CDOM absorption coefficient measurements and classified algal bloom area showed seasonal variations that increased from spring to late summer and then decreased in autumn. The first two crop growth stages accounted for most of the water and fertilizer requirements of the entire growth period, which may have contributed to large amounts of groundwater consumption and pollution and resulted in peak eutrophication of the lake in the second growth stage. However, the CDOM absorption coefficient of the third stage was not well correlated with that of the first two stages, suggesting that the lake may be affected by the dual effects of groundwater and precipitation recharge in the third stage. These results indicate that the water quality of desert lakes may be affected by agricultural cultivation. The agricultural demands for water and fertilizer may change the spatiotemporal changes in water quality in the lake, especially in the middle and early stages of crop growth

QTL Mapping of Six Spike and Stem Traits in Hybrid Population of Agropyron Gaertn. in Multiple Environments

Most Agropyron Gaertn. species are excellent sources of forage. The derivative lines of wheat-Agropyron cristatum show elite agronomic traits, and some are valuable for wheat breeding. The species of Agropyron Gaertn. was mainly recognized by the spike morphology in traditional taxon. Six traits, including spike length (SL), ear stem length (ESL), the second internodes length (SIL), spikelet number per spike (SNS), floret number per spikelet (FNS), and grain number per spikelet (GNS), are vital to morphology studies and also influences the forage crop yield. To elucidate the genetic basis of spike and stem traits, a quantitative trait locus (QTL) analysis was conducted in a cross-pollinated (CP) hybrid population derived from a cross between two diverse parents, Agropyron mongolicum Keng Z2098 and A. cristatum (L.) Gaertn. Z1842, evaluated across three ecotopes (Langfang, Changli, and Guyuan of Hebei, China) over 3 years (from 2014 to 2016). Construction of a high-density linkage map was based on 1,023 single-nucleotide polymorphism (SNP) markers, covering 907.8 cM of the whole Agropyron genome. A total of 306 QTLs with single QTL in different environments explaining 0.07–33.21% of the phenotypic variation were detected for study traits. Seven major-effect QTLs were identified, including one for ESL on chromosome 3, one for SIL on chromosome 5, three for SL (two on chromosome 2 and one on chromosome 4), and two for SNS on chromosomes 3 and 7. Also, seven stable QTLs, including four for ESL, one for SL, one for GNS, and one for FNS, were mainly mapped on chromosomes 2, 3, 4, 5, and 7, respectively, elucidating 0.25–14.98% of the phenotypic variations. On the use of Agropyron CP hybrid population to identify QTL determining spike and stem traits for the first time, these QTLs for six traits would provide a theoretical reference for the molecular marker-assisted selection in the improvement of forage and cereal crop species

Chemo‐ and mechanosensing by dendritic cells facilitate antigen surveillance in the spleen*

Spleen dendritic cells (DC) are critical for initiation of adaptive immune responses against blood-borne invaders. Key to DC function is their positioning at sites of pathogen entry, and their abilities to selectively capture foreign antigens and promptly engage T cells. Focusing on conventional DC2 (cDC2), we discuss the contribution of chemoattractant receptors (EBI2 or GPR183, S1PR1, and CCR7) and integrins to cDC2 positioning and function. We give particular attention to a newly identified role in cDC2 for adhesion G-protein coupled receptor E5 (Adgre5 or CD97) and its ligand CD55, detailing how this mechanosensing system contributes to splenic cDC2 positioning and homeostasis. Additional roles of CD97 in the immune system are reviewed. The ability of cDC2 to be activated by circulating missing self-CD47 cells and to integrate multiple red blood cell (RBC)-derived inputs is discussed. Finally, we describe the process of activated cDC2 migration to engage and prime helper T cells. Throughout the review, we consider the insights into cDC function in the spleen that have emerged from imaging studies

Research on Sustainable Reuse of Urban Ruins Based on Artificial Intelligence Technology: A Study of Guangzhou

In recent years, with the continuous deepening of the urbanization process, the problem of urban ruins (URs) has become prominent. This significantly affects the happiness of residents around the URs, the overall image of the city, and the environment, and it has become an important issue in urban construction. At present, the types of urban ruins mainly include industrial ruins, abandoned urban buildings, and war sites. Generally, methods such as demolition and reconstruction of original buildings or upgrading and transformation are used to reuse URs, and some of them have achieved fruitful results. However, the current renovation of URs is based on fragmented renovation strategies for different URs without a systematic and universally applicable renovation methodology. With the development of artificial intelligence, technologies such as Generative Adversarial Network (GAN), Easy DL, and Natural Language Processing (NLP) can provide technical support for urban ruin reconstruction, from design to operation. Specifically in the present study, the ten representative URs in Guangzhou are first evaluated by the Analytic Hierarchy Process and then combined with AI methods, such as the adversarial generative networks and big data applications, into the reuse design of URs. Finally, a complete research system is established to implement URs’ projects, which provides a clearer systematic planning strategy for the reuse of URs in the future

Research on Sustainable Reuse of Urban Ruins Based on Artificial Intelligence Technology: A Study of Guangzhou

In recent years, with the continuous deepening of the urbanization process, the problem of urban ruins (URs) has become prominent. This significantly affects the happiness of residents around the URs, the overall image of the city, and the environment, and it has become an important issue in urban construction. At present, the types of urban ruins mainly include industrial ruins, abandoned urban buildings, and war sites. Generally, methods such as demolition and reconstruction of original buildings or upgrading and transformation are used to reuse URs, and some of them have achieved fruitful results. However, the current renovation of URs is based on fragmented renovation strategies for different URs without a systematic and universally applicable renovation methodology. With the development of artificial intelligence, technologies such as Generative Adversarial Network (GAN), Easy DL, and Natural Language Processing (NLP) can provide technical support for urban ruin reconstruction, from design to operation. Specifically in the present study, the ten representative URs in Guangzhou are first evaluated by the Analytic Hierarchy Process and then combined with AI methods, such as the adversarial generative networks and big data applications, into the reuse design of URs. Finally, a complete research system is established to implement URs’ projects, which provides a clearer systematic planning strategy for the reuse of URs in the future