Spatial distribution of cultural ecosystem services demand and supply in urban and suburban areas: a case study from Shanghai, China

In the urban ecosystem, the demand for cultural ecosystem services (CES) has greatly increased, and the imbalance of CES supply and demand has been prominent. This paper integrated multi-source data to analyze and visualize the spatial differences in CES demand and supply capacity between Shanghai urban center and suburbs. Based on the geo-tagged photo data, the spatial distribution differences of the four types of CES demand, Recreation & tourism services (RTS) demand, Aesthetic services (AS) demand, Heritage & cultural services (HCS) demand, and Spiritual & religious services (SRS) demand, were analyzed. Residents and tourists had a strong demand for recreation and tourism, and the spatial agglomeration effect was the most obvious. Overall, CES demand was more concentrated in urban center, while the spatial distribution of suburbs was relatively discrete. At the same time, there were under supply areas of CES near the Huangpu River in urban center and suburbs. Results from bivariate Moran's I method showed: 1) there was a significant positive spatial correlation between CES demand and CES supply capacity in urban center; 2) CES supply had a positive external impact on CES demand; and 3) the increase in CES supply capacity can promote the growth of CES demand

Monopolar and dipolar relaxation in spin ice Ho2_2Ti2_2O7_7

When degenerate states are separated by large energy barriers, the approach to thermal equilibrium can be slow enough that physical properties are defined by the thermalization process rather than the equilibrium. The exploration of thermalization pushes experimental boundaries and provides refreshing insights into atomic scale correlations and processes that impact steady state dynamics and prospects for realizing solid state quantum entanglement. We present a comprehensive study of magnetic relaxation in Ho$_2$Ti$_2$O$_7$ based on frequency-dependent susceptibility measurements and neutron diffraction studies of the real-time atomic-scale response to field quenches. Covering nearly ten decades in time scales, these experiments uncover two distinct relaxation processes that dominate in different temperature regimes. At low temperatures (0.6K<T<1K) magnetic relaxation is associated with monopole motion along the applied field direction through the spin-ice vacuum. The increase of the relaxation time upon cooling indicates reduced monopole conductivity driven by decreasing monopole concentration and mobility as in a semiconductor. At higher temperatures (1K<T<2K) magnetic relaxation is associated with the reorientation of monopolar bound states as the system approaches the single-spin tunneling regime. Spin fractionalization is thus directly exposed in the relaxation dynamics

LRRTM3 Interacts with APP and BACE1 and Has Variants Associating with Late-Onset Alzheimer's Disease (LOAD)

Leucine rich repeat transmembrane protein 3 (LRRTM3) is member of a synaptic protein family. LRRTM3 is a nested gene within α-T catenin (CTNNA3) and resides at the linkage peak for late-onset Alzheimer’s disease (LOAD) risk and plasma amyloid β (Aβ) levels. In-vitro knock-down of LRRTM3 was previously shown to decrease secreted Aβ, although the mechanism of this is unclear. In SH-SY5Y cells overexpressing APP and transiently transfected with LRRTM3 alone or with BACE1, we showed that LRRTM3 co-localizes with both APP and BACE1 in early endosomes, where BACE1 processing of APP occurs. Additionally, LRRTM3 co-localizes with APP in primary neuronal cultures from Tg2576 mice transduced with LRRTM3-expressing adeno-associated virus. Moreover, LRRTM3 co-immunoprecipitates with both endogenous APP and overexpressed BACE1, in HEK293T cells transfected with LRRTM3. SH-SY5Y cells with knock-down of LRRTM3 had lower BACE1 and higher CTNNA3 mRNA levels, but no change in APP. Brain mRNA levels of LRRTM3 showed significant correlations with BACE1, CTNNA3 and APP in ∼400 humans, but not in LRRTM3 knock-out mice. Finally, we assessed 69 single nucleotide polymorphisms (SNPs) within and flanking LRRTM3 in 1,567 LOADs and 2,082 controls and identified 8 SNPs within a linkage disequilibrium block encompassing 5′UTR-Intron 1 of LRRTM3 that formed multilocus genotypes (MLG) with suggestive global association with LOAD risk (p = 0.06), and significant individual MLGs. These 8 SNPs were genotyped in an independent series (1,258 LOADs and 718 controls) and had significant global and individual MLG associations in the combined dataset (p = 0.02–0.05). Collectively, these results suggest that protein interactions between LRRTM3, APP and BACE1, as well as complex associations between mRNA levels of LRRTM3, CTNNA3, APP and BACE1 in humans might influence APP metabolism and ultimately risk of AD.© 2013 Lincoln et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Improved Anti-Collision Algorithm for the Application on Intelligent Warehouse

As an important part of economic development, warehousing logistics also needs to be transformed and upgraded in order to adapt to the development of the new situation. The RFID reader records the related information of the goods to improve the efficiency of warehouse operation by identifying the RFID tags attached to the goods in batches. This paper also proposes an improved group-based anti-collision algorithm (GMQT) to solve the problem of tag collision in the process of Radio Frequency Identification (RFID) identification. The simulation results show that the GMQT algorithm improves the recognition efficiency of the system. The algorithm has the advantages of small data transmission and stable performance; in particular, the recognition efficiency is not affected by the number of tags

A review on passive and active strategies of enhancing the safety of lithium-ion batteries

Lithium-ion battery (LIB) becomes the dominant candidate for electric vehicles (EVs) and energy storage systems (ESSs); nevertheless, as its popularization, the number of safety (fire) accidents regarding with LIB thermal runaway increases, undermining the public confidence. Safety turns into one of the main concerns in the widespread usage of LIBs. In this review paper, various faults in LIBs which have a potential risk leading to safety accidents are scrutinized firstly, followed by the presentation of recent progress in strategies of improving the safety of LIBs. Faults in large-scale LIB-based systems like EVs and ESSs for power grids include battery faults, sensor faults and actuator faults. The battery faults can be triggered by mechanical abuse, electrical abuse, thermal abuse as well as aging or degradation. This paper classifies the safety strategies into active safety strategies and passive safety strategies. Passive safety strategies pursue inherent safety in LIBs via material modification and alleviate the hazard level of faults through taking timely countermeasure like fire suppression or extinguishment once the LIB fire accident occurs. On the contrary, the active safety strategies aim to prevent the abuse conditions from developing into uncontrollable thermal runaway or fire accidents by effective state estimation and monitoring, fault diagnosis and early warning, thermal management, equalization technology, etc. (c) 2021 Elsevier Ltd. All rights reserved

A novel entropy-based fault diagnosis and inconsistency evaluation approach for lithium-ion battery energy storage systems

Detection and diagnosis of faults at the early stage, as well as inconsistency monitoring and control are of extreme importance for operating Li-ion batteries (LIBs) safely and reliably, handling performance degradation and cell unbalancing, and avoiding accidents like thermal runaway (TR). In this work, a general procedure based on multi-level Shannon entropy algorithms is put forward to perform fault diagnosis as well as inconsistency evaluation for LIB-based energy storage systems (ESSs). More specifically, the cell-level Shannon entropy algorithm is used to detect faults by comparing Shannon entropies of different LIB cells in each module while the module-level and cluster-level Shannon entropy algorithms are used to evaluate the overall inconsistency among LIB cells in each module and in each cluster respectively. The proposed approach is then applied in a large-scale LIB-based ESS (1 MW/2 MWh). Through simulated data, the availability of the cell-level Shannon entropy algorithm to detect small changes in gradual faults is testified while the module-level and the cluster-level Shannon entropy algorithms are demonstrated to be effective for assessing inconsistences of LIBs in every module and in every cluster respectively, by comparing results of the normal case with those from two cases each with a different faulty LIB cell at the early stage of internal short circuit (ISC)

Domain Decomposition Strategy for Pin-wise Full-Core Monte Carlo Depletion Calculation with the Reactor Monte Carlo Code

Because of prohibitive data storage requirements in large-scale simulations, the memory problem is an obstacle for Monte Carlo (MC) codes in accomplishing pin-wise three-dimensional (3D) full-core calculations, particularly for whole-core depletion analyses. Various kinds of data are evaluated and quantificational total memory requirements are analyzed based on the Reactor Monte Carlo (RMC) code, showing that tally data, material data, and isotope densities in depletion are three major parts of memory storage. The domain decomposition method is investigated as a means of saving memory, by dividing spatial geometry into domains that are simulated separately by parallel processors. For the validity of particle tracking during transport simulations, particles need to be communicated between domains. In consideration of efficiency, an asynchronous particle communication algorithm is designed and implemented. Furthermore, we couple the domain decomposition method with MC burnup process, under a strategy of utilizing consistent domain partition in both transport and depletion modules. A numerical test of 3D full-core burnup calculations is carried out, indicating that the RMC code, with the domain decomposition method, is capable of pin-wise full-core burnup calculations with millions of depletion regions

Improved Anti-Collision Algorithm for the Application on Intelligent Warehouse

As an important part of economic development, warehousing logistics also needs to be transformed and upgraded in order to adapt to the development of the new situation. The RFID reader records the related information of the goods to improve the efficiency of warehouse operation by identifying the RFID tags attached to the goods in batches. This paper also proposes an improved group-based anti-collision algorithm (GMQT) to solve the problem of tag collision in the process of Radio Frequency Identification (RFID) identification. The simulation results show that the GMQT algorithm improves the recognition efficiency of the system. The algorithm has the advantages of small data transmission and stable performance; in particular, the recognition efficiency is not affected by the number of tags

The Spatial Distribution, Influencing Factors, and Development Path of Inbound Tourism in China—An Empirical Analysis of Market Segments Based on Travel Motivation

According to China&rsquo;s tourism statistics, the inbound tourism market is composed of eight types of travel motivations (sightseeing, leisure, business meeting (business-m), visiting relatives and friends (visiting-rf), shopping, religious worship (religious-w), culture and sports (culture-s), and health care (health-c)), and the spatial distribution of each type of travel motivation is significantly different. Four inbound sub-markets (foreigners, Hong Kong, Macao, and Taiwan) were selected as our research object. Through empirical analysis of the variable elasticity of eight different inbound motive market segments, we found that the sensitivities (elasticity) of the influencing factors (traffic conditions (traffic-c), destination image (destination-i), industry structure (industry-s), infrastructure, consumer price index (CPI), resource endowment (resource-e), and dressing index (ICL)) are different. Therefore, investment options in the target market can have differential treatment based on the rate of marginal return on investment. In accordance with the characteristics of different market segments, we suggest more feasible development paths and countermeasures, providing a decision-making basis for the accurate development of the inbound tourism market