Two new species of Scytinostroma (Russulales, Basidiomycota) in Southwest China

Two new species of Scytinostroma viz. S. acystidiatum and S. macrospermum, are described from southwest China. Phylogeny based on ITS + nLSU dataset demonstrates that samples of the two species form two independent lineages and are different in morphology from the existing species of Scytinostroma. Scytinostroma acystidiatum is characterized by resupinate, coriaceous basidiomata with cream to pale yellow hymenophore, a dimitic hyphal structure with generative hyphae bearing simple septa, the absence of cystidia, and amyloid, broadly ellipsoid basidiospores measuring 4.7–7 × 3.5–4.7 μm. Scytinostroma macrospermum is characterized by resupinate, coriaceous basidiomata with cream to straw yellow hymenophore, a dimitic hyphal structure with generative hyphae bearing simple septa, numerous cystidia embedded or projecting from hymenium, and inamyloid, ellipsoid basidiospores measuring 9–11 × 4.5–5.5 μm. The differences between the new species and morphologically similar and phylogenetically related species are discussed

Optimizing the Placement of Non-Functional Pads on Signal Vias using Multiple Reflection Analysis

In this study, the effects of using non-functional pads to optimize the performance of high-speed signal vias are investigated based on multiple reflection analysis. The non-functional pads on signal vias introduce more capacitive coupling and are possible to improve the response of the via structure if the original via has relatively larger impedance compared to the system reference impedance. The effectiveness of the non-functional pad optimization is validated through a numerical example, and the eye diagram of the via structure without and with non-functional pads are compared. The eye opening becomes 5.4 times larger after the via optimization using non-functional pads

AIGC Empowering Telecom Sector White Paper_chinese

In the global craze of GPT, people have deeply realized that AI, as a transformative technology and key force in economic and social development, will bring great leaps and breakthroughs to the global industry and profoundly influence the future world competition pattern. As the builder and operator of information and communication infrastructure, the telecom sector provides infrastructure support for the development of AI, and even takes the lead in the implementation of AI applications. How to enable the application of AIGC (GPT) and implement AIGC in the telecom sector are questions that telecom practitioners must ponder and answer. Through the study of GPT, a typical representative of AIGC, the authors have analyzed how GPT empowers the telecom sector in the form of scenarios, discussed the gap between the current GPT general model and telecom services, proposed for the first time a Telco Augmented Cognition capability system, provided answers to how to construct a telecom service GPT in the telecom sector, and carried out various practices. Our counterparts in the industry are expected to focus on collaborative innovation around telecom and AI, build an open and shared innovation ecosystem, promote the deep integration of AI and telecom sector, and accelerate the construction of next-generation information infrastructure, in an effort to facilitate the digital transformation of the economy and society

Multi-Objective Personalized Product Retrieval in Taobao Search

In large-scale e-commerce platforms like Taobao, it is a big challenge to retrieve products that satisfy users from billions of candidates. This has been a common concern of academia and industry. Recently, plenty of works in this domain have achieved significant improvements by enhancing embedding-based retrieval (EBR) methods, including the Multi-Grained Deep Semantic Product Retrieval (MGDSPR) model [16] in Taobao search engine. However, we find that MGDSPR still has problems of poor relevance and weak personalization compared to other retrieval methods in our online system, such as lexical matching and collaborative filtering. These problems promote us to further strengthen the capabilities of our EBR model in both relevance estimation and personalized retrieval. In this paper, we propose a novel Multi-Objective Personalized Product Retrieval (MOPPR) model with four hierarchical optimization objectives: relevance, exposure, click and purchase. We construct entire-space multi-positive samples to train MOPPR, rather than the single-positive samples for existing EBR models.We adopt a modified softmax loss for optimizing multiple objectives. Results of extensive offline and online experiments show that MOPPR outperforms the baseline MGDSPR on evaluation metrics of relevance estimation and personalized retrieval. MOPPR achieves 0.96% transaction and 1.29% GMV improvements in a 28-day online A/B test. Since the Double-11 shopping festival of 2021, MOPPR has been fully deployed in mobile Taobao search, replacing the previous MGDSPR. Finally, we discuss several advanced topics of our deeper explorations on multi-objective retrieval and ranking to contribute to the community.Comment: 9 pages, 4 figures, submitted to the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Minin

The importance of NOx control for peak ozone mitigation based on a sensitivity study using CMAQ‐HDDM‐3D model during a typical episode over the Yangtze River delta region, China.

In recent years, ground-level ozone (O3) has been one of the main pollutants hindering air quality compliance in China's large city-clusters including the Yangtze River Delta (YRD) region. In this work, we utilized the process analysis (PA) and the higher-order decoupled direct method (HDDM-3D) tools embedded in the Community Multiscale Air Quality model (CMAQ) to characterize O3 formation and sensitivities to precursors during a typical O3 pollution episode over the YRD region in July 2018. Results indicate that gas-phase chemistry contributed dominantly to the ground-level O3 although a significant proportion was chemically produced at the middle and upper boundary layer before reaching the surface via diffusion process. Further analysis of the chemical pathways of O3 and Ox formation provided deep insights into the sensitivities of O3 to its precursors that were consistent with the HDDM results. The first-order sensitivities of O3 to anthropogenic volatile organic compounds (AVOC) were mainly positive but small, and temporal variations were negligible compared with those to NOx. During the peak O3 time in the afternoon, the first- and second-order sensitivities of O3 to NOx were significantly positive and negative, respectively, suggesting a convex response of O3 to NOx over most areas including Shanghai, Hangzhou, Nanjing and Hefei. These findings further highlighted an accelerated decrease in ground-level O3 in the afternoon corresponding to continuous decrease of NOx emissions in the afternoon. Therefore, over the YRD region including its metropolises, NOx emission reductions will be more important in reducing the afternoon peak O3 concentration compared with the effect of VOC emission control alone

6G Network Operation Support System

6G is the next-generation intelligent and integrated digital information infrastructure, characterized by ubiquitous interconnection, native intelligence, multi-dimensional perception, global coverage, green and low-carbon, native network security, etc. 6G will realize the transition from serving people and people-things communication to supporting the efficient connection of intelligent agents, and comprehensively leading the digital, intelligent and green transformation of the economy and the society. As the core support system for mobile communication network, 6G OSS needs to achieve high-level network automation, intelligence and digital twinning capabilities to achieve end-to-end autonomous network operation and maintenance, support the operation of typical 6G business scenarios and play a greater social responsibility in the fields of environment, society, and governance (ESG).This paper provides a detailed introduction to the overall vision, potential key technologies, and functional architecture of 6G OSS . It also presents an evolutionary roadmap and technological prospects for the OSS from 5G to 6G.Comment: 103 pages, 20 figures, 52 references (chinese version

Study of the beneficial effects of green light on lettuce grown under short-term continuous red and blue light-emitting diodes

Red and blue light are the most important light spectra for driving photosynthesis to produce adequate crop yield. It is also believed that green light may contribute to adaptations to growth. However, the effects of green light, which can trigger specific and necessary responses of plant growth, have been underestimated in the past. In this study, lettuce (Lactuca sativa L.) was exposed to different continuous light (CL) conditions for 48 h by a combination of red and blue light-emitting diodes (LEDs) supplemented with or without green LEDs, in an environmental-controlled growth chamber. Green light supplementation enhanced photosynthetic capacity by increasing net photosynthetic rates (Pn), maximal photochemical efficiency (Fv/Fm), electron transport for carbon fixation (JPSII) and chlorophyll content in plants under the CL treatment. Green light decreased malondialdehyde and H2O2 accumulation by increasing the activities of superoxide dismutase (SOD; EC 1.15.1.1) and ascorbate peroxidase (APX; EC 1.11.1.11) after 24 h of CL. Supplemental green light significantly increased the expression of photosynthetic genes LHCb and PsbA from 6 to 12 h, and these gene expression were maintained at higher levels than those under other light conditions between 12 and 24 h. However, a notable down-regulation of both LHCb and PsbA was observed during 24 to 48 h. These results indicate that the effects of green light on lettuce plant growth, via enhancing activity of particular components of antioxidantive enzyme system and promoting of LHCb and PsbA expression to maintain higher photosynthetic capacity, alleviated a number of the negative effects caused by CL

A simulation study on the measurement of D0-D0bar mixing parameter y at BES-III

We established a method on measuring the \dzdzb mixing parameter $y$ for BESIII experiment at the BEPCII $e^+e^-$ collider. In this method, the doubly tagged $\psi(3770) \to D^0 \overline{D^0}$ events, with one $D$ decays to CP-eigenstates and the other $D$ decays semileptonically, are used to reconstruct the signals. Since this analysis requires good $e/\pi$ separation, a likelihood approach, which combines the $dE/dx$, time of flight and the electromagnetic shower detectors information, is used for particle identification. We estimate the sensitivity of the measurement of $y$ to be 0.007 based on a $20fb^{-1}$ fully simulated MC sample.Comment: 6 pages, 7 figure