Search

Background: The incidence of rabies exposure is high and increasing in China, leading to an urgent demand of rabies post-exposure prophylaxis (PEP) clinics for the injured. However, the spatial accessibility and inequality of rabies-exposed patients to rabies PEP clinics is less known in China. Methods: Based on rabies exposure data, PEP clinic data, and resident travel origin-destination (OD) matrix data in Guangzhou City, China, we first described the incidence of rabies exposure in Guangzhou from 2020 to 2022. Then, the Gaussian two-step floating catchment area method (2SFCA) was used to analyze the spatial accessibility of rabies-exposed patients to rabies PEP clinics in Guangzhou, and the Gini coefficient and Moran's I statistics were utilized to evaluate the inequality and clustering of accessibility scores. Results: From 2020 to 2022, a total of 524,160 cases of rabies exposure were reported in Guangzhou, and the incidence showed a significant increasing trend, with an average annual incidence of 932.0/100,000. Spatial accessibility analysis revealed that the overall spatial accessibility scores for three scenarios (threshold of driving duration [d0] = 30 min, 45 min, and 60 min) were 0.30 (95% CI: 0.07, 0.87), 0.28 (95% CI: 0.11, 0.53) and 0.28 (95% CI: 0.14, 0.44), respectively. Conghua, Huangpu, Zengcheng and Nansha districts had the higher accessibility scores, while Haizhu, Liwan, and Yuexiu districts exhibited lower spatial accessibility scores. The Gini coefficient and Moran's I statistics showed that there were certain inequality and clustering in the accessibility to rabies PEP clinics in Guangzhou. Conclusions: This study clarifies the heterogeneity of spatial accessibility to rabies PEP clinics, and provide valuable insights for resource allocation to achieve the WHO target of zero human dog-mediated rabies deaths by 2030. [ABSTRACT FROM AUTHOR]

A metal catalyst free approach for regioselective ortho-chlorination of anilines has been developed using a secondary amine as the organocatalyst and sulfuryl chloride as the halogen source under mild conditions. A wide range of substrates were compatible with this catalytic system. In addition, this catalytic protocol has been applied to the efficient synthesis of bioactive compounds and modification of drug derivatives. Further studies indicated that the anionic trichloride species was responsible for the ortho-selectivity. [ABSTRACT FROM AUTHOR]

This study evaluated the performance of 23 models participating in Phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating snowfall variation across the Eurasian continent. The results show that the CMIP6 multi‐model ensemble (MME) can reasonably capture the climate means of snowfall indices for 1995–2014 period and has high pattern correlations with observations. However, most of CMIP6 models generally overestimate snowfall amounts, snowfall days and snowfall duration, and the overestimation is much clearer in spring. The performance of these models in simulating snowfall events with different grades (including light snowfall, moderate snowfall, heavy snowfall and snowstorm) becomes gradually poorer with higher snowfall levels. On the whole, the comprehensive model ranks implied that NorESM2‐MM, NorESM2‐LM and CESM2‐WACCM models showed the best performances. In addition, the CMIP6 MME outperforms individual models in terms of both spatial–temporal features and interannual variability; thus, the MME is used to project the snowfall change in the 21st century. Further evaluations show that by the end of this century, snowfall will decrease in most of Eurasia with an average value of 16.7% (31.3%) under the SSP2‐4.5 (SSP5‐8.5) scenarios, and snowfall days will decrease by 12.6 days (25.0 days); the snowfall duration will shorten further due to the first date of snowfall occurrence will postpone by 12.7 days (23.0 days) and the last date further advance by 15.0 days (26.7 days). Additionally, heavy snowfall, snowstorms and their number of days will increase over part of Northern Asia, the Tibetan Plateau and Central Asia, where the risk of snowfall extremes will increase. However, large inter‐model and scenario uncertainties also exist in the CMIP6 model projection of snowfall events, which requires further improvement. [ABSTRACT FROM AUTHOR]

The observed spatial–temporal variations in daily snowfall over the Eurasian continent from 1980 to 2019 are explored in this study. The results show that the snowfall amount and its number of days are mainly centred in the high latitudes and high terrain regions of the Eurasian continent (such as North Asia), while they are relatively small in Southern Europe, Central Asia and East Asia. During the past decades, a decreasing trend can be observed for snowfall amounts and the numbers of days over most regions of Eurasia, while increases are clear in terms of the mean intensity. In response to climate warming in recent decades, the first date of snowfall occurrence postponed and the ending date advanced across the Eurasian continent. Furthermore, the change characteristics of the different grades of snowfall are also investigated across this region, including light snowfall, moderate snowfall, heavy snowfall and snowstorm. The light snowfall and number of days show a decreasing tendency, which mainly results in a decrease in the total snowfall amount and number of days. However, the amounts of heavy snowfall and snowstorms and their numbers of days are significantly increased, implying that the Eurasian continent has experienced increased severe snowfall events during recent decades. [ABSTRACT FROM AUTHOR]

In this paper, a spoof surface plasmon polaritons (SPPs)-based multi-frequency splitter in the terahertz (THz) band is realized by designing different grating heights. The structure is composed of an incident aperture waveguide and a composite gratings structure placed on both sides of the incident aperture waveguide. The composite grating structure has different grating heights, which is used to transmit and guide THz waves of different frequencies in different directions. Simulation results show that a mixed incident light consisting of three frequencies, of 0.5 THz, 0.7 THz and 1 THz, can be effectively separated by this splitter. Furthermore, the function of the spoof SPPs switch can be realized by increasing the number of incident aperture waveguides. The simple structure and small size, means that this multi-frequency splitter and switch can be conveniently integrated into THz sensing or THz communication systems. [ABSTRACT FROM AUTHOR]

Data in the form of graphs are prevalent, ranging from biological and social networks to citation graphs and the Web. In particular, most real-world graphs are heterogeneous, containing objects of multiple types, which present new opportunities for many problems on graphs. Consider a typical proximity search problem on graphs, which boils down to measuring the proximity between two given nodes. Most earlier studies on homogeneous or bipartite graphs only measure a generic form of proximity, without accounting for different “semantic classes”—for instance, on a social network two users can be close for different reasons, such as being classmates or family members, which represent two distinct semantic classes. Learning these semantic classes are made possible on heterogeneous graphs through the concept of metagraphs. In this study, we identify metagraphs as a novel and effective means to characterize the common structures for a desired class of proximity. Subsequently, we propose a family of metagraph-based proximity, and employ a learning-to-rank technique that automatically learns the right parameters to suit the desired semantic class. In terms of efficiency, we develop a symmetry-based matching algorithm to speed up the computation of metagraph instances. Empirically, extensive experiments reveal that our metagraph-based proximity substantially outperforms the best competitor by more than 10 percent, and our matching algorithm can reduce matching time by more than half. As a further generalization, we aim to derive a general node and edge representation for heterogeneous graphs, in order to support arbitrary machine learning tasks beyond proximity search. In particular, we propose the finer-grained anchored metagraph, which is capable of discriminating the roles of nodes within the same metagraph. Finally, further experiments on the general representation show that we can outperform the state of the art significantly and consistently across various machine learning tasks. [ABSTRACT FROM AUTHOR]

Personalized PageRank (PPR) is a classic measure of the relevance among different nodes in a graph, and has been applied in numerous systems, such as Twitter's Who-To-Follow and Pinterest's Related Pins. Existing work on PPR has mainly focused on three general types of queries, namely, single-pair PPR, single-source PPR, and all-pair PPR. However, we observe that there are applications that rely on a new query type (referred to as batch one-hop PPR), which takes as input a set $S$ S of source nodes and, for each node $s \in S$ s ∈ S and each of $s$ s 's neighbor $v$ v , asks for the PPR value of $v$ v with respect to $s$ s . None of the existing PPR algorithms is able to efficiently process batch one-hop queries, due to the inherent differences between batch one-hop PPR and the three general query types. To address the limitations of existing algorithms, this paper presents Baton, an algorithm for batch one-hop PPR that offers both strong theoretical guarantees and practical efficiency. Baton leverages the characteristics of one-hop PPR to avoid unnecessary computation, and it incorporates advanced mechanisms to improve the cost-effectiveness of PPR derivations. Extensive experiments on benchmark datasets show that Baton is up to three orders of magnitude faster than the state of the art, while offering the same accuracy. [ABSTRACT FROM AUTHOR]

It is commonly accepted that psychological stress is closely associated with the occurrence and development of chronic orofacial pain. However, the pathogenesis underlying this process has not been fully elucidated. In the present study, we explored the role of N-methyl-D-aspartate receptors (NMDARs) and Jun N-terminal kinase (JNK) mediated intercellular communication between neurons and astrocytes in the spinal trigeminal nucleus caudalis (Vc) in the induction of masseter hyperalgesia by psychological stress in rats. We found that subjecting rats to 14 days of restraint stress (8 h/d) caused a significant decrease in body weight gain, behavioral changes and marked masseter hyperalgesia in the rats. We also found that exposure to restraint stress for 14 days caused the expression of pJNK in astrocytes in the Vc to significantly increase, and intrathecally infusing a JNK inhibitor significantly prevented restraint stress-induced masseter hyperalgesia in the rats. In addition, after exposure to restraint stress for 14 days, the stressed group exhibited a noticeably increased expression level of pNR2B in neurons in the Vc. Then, we intrathecally injected MK-801 (an NMDAR inhibitor) and ifenprodil (a selective NR2B subunit antagonist) and observed that the two types of inhibitors not only alleviated masseter hyperalgesia but also significantly inhibited the phosphorylation of JNK in the Vc after restraint stress; this indicates that the effect of NMDAR antagonists may influence the activation of astrocytic JNK. Furthermore, inhibitors of neuronal nitric oxide synthase (nNOS) activation and guanylate cyclase (GC) inhibitor could not only inhibit the expression of pJNK in the Vc, but also effectively alleviate masseter hyperalgesia induced by restraint stress. Taken together, our results suggest that NMDAR activation could increase JNK phosphorylation in astrocytes after restraint stress, which may depend on the nNOS-GC pathway. The intercellular communication between neurons and astrocytes in the Vc may play a key role in the induction of masseter muscle hyperalgesia by psychological stress in rats. [ABSTRACT FROM AUTHOR]

The identification of network motifs has important applications in numerous domains, such as pattern detection in biological networks and graph analysis in digital circuits. However, mining network motifs is computationally challenging, as it requires enumerating subgraphs from a real-life graph, and computing the frequency of each subgraph in a large number of random graphs. In particular, existing solutions often require days to derive network motifs from biological networks with only a few thousand vertices. To address this problem, this paper presents a novel study on network motif discovery using Graphical Processing Units (GPUs). The basic idea is to employ GPUs to parallelize a large number of subgraph matching tasks in computing subgraph frequencies from random graphs, so as to reduce the overall computation time of network motif discovery. We explore the design space of GPU-based subgraph matching algorithms, with careful analysis of several crucial factors (such as branch divergences and memory coalescing) that affect the performance of GPU programs. Based on our analysis, we develop a GPU-based solution that (i) considerably differs from existing CPU-based methods in how it enumerates subgraphs, and (ii) exploits the strengths of GPUs in terms of parallelism while mitigating their limitations in terms of the computation power per GPU core. With extensive experiments on a variety of biological networks, we show that our solution is up to two orders of magnitude faster than the best CPU-based approach, and is around $20$ times more cost-effective than the latter, when taking into account the monetary costs of the CPU and GPUs used. [ABSTRACT FROM PUBLISHER]

Alkyl azides and acyl azides were reduced to the corresponding amines and amides with zinc and ammonium chloride as reducing agent under mild conditions in good to excellent yield. [ABSTRACT FROM AUTHOR]