Trend In Direction Research Articles

Territorial spatial vulnerability assessment based on PSO-BP neural network: A case study in Shenzhen, China

Studies on vulnerability, a fairly new research paradigm inspired by global environmental change, are expanding to support scientific decision-making for developing sustainable, resilient territorial space at the regional level. The goal of this research is to reveal the vulnerability of a human-environment coupled system and its interaction mechanisms amidst a changing environment. This study started with the vulnerability scoping diagram (VSD) conceptual model and built up a research framework of territorial spatial vulnerability according to the three structural elements of ecological protection, agricultural production and urban construction. Following the requirements for intelligent computing, we introduced particle swarm optimization and BP neural network learning algorithms to evaluate the vulnerability of Shenzhen's territory. We also introduced flow cytometry to analyze the mechanism of Shenzhen's territorial spatial vulnerability driven by human and natural forces. The results showed that the territorial spatial vulnerability of Shenzhen was low under various functional orientations. Among them, ecological protection-oriented territorial spatial vulnerability was high in the west and low in the east and followed an inverted U-shaped trend in the north-south direction. Agricultural production-oriented territorial spatial vulnerability was high in the east and low in the west, high in the north and low in the south. Urban construction-oriented territorial spatial vulnerability was high in the west and low in the east, high in the north and low in the south. Under the complex orientation of the gigantic human-environment coupled system, the vulnerability of territory was symmetrical and balanced in the north-south direction and fluctuated with an overall declining trend in the east-west direction. In vulnerability, ecological protection, agricultural production and urban construction systems independently accounted for 35.642%, 38.209%, and 26.149% of the territorial spatial vulnerability, respectively.

Improving the spaceborne GNSS-R altimetric precision based on the novel multilayer feedforward neural network weighted joint prediction model

Global navigation satellite system-reflection (GNSS-R) sea surface altimetry based on satellite constellation platforms has become a new research direction and inevitable trend, which can meet the altimetric precision at the global scale required for underwater navigation. At present, there are still research gaps for GNSS-R altimetry under this mode, and its altimetric capability cannot be specifically assessed. Therefore, GNSS-R satellite constellations that meet the global altimetry needs to be designed. Meanwhile, the matching precision prediction model needs to be established to quantitatively predict the GNSS-R constellation altimetric capability. Firstly, the GNSS-R constellations altimetric precision under different configuration parameters is calculated, and the mechanism of the influence of orbital altitude, orbital inclination, number of satellites and simulation period on the precision is analyzed, and a new multilayer feedforward neural network weighted joint prediction model is established. Secondly, the fit of the prediction model is verified and the performance capability of the model is tested by calculating the R2 value of the model as 0.9972 and the root mean square error (RMSE) as 0.0022, which indicates that the prediction capability of the model is excellent. Finally, using the novel multilayer feedforward neural network weighted joint prediction model, and considering the research results and realistic costs, it is proposed that when the constellation is set to an orbital altitude of 500 km, orbital inclination of 75° and the number of satellites is 6, the altimetry precision can reach 0.0732 m within one year simulation period, which can meet the requirements of underwater navigation precision, and thus can provide a reference basis for subsequent research on spaceborne GNSS-R sea surface altimetry.

Patterns and processes in the history of body size in turritelline gastropods, Jurassic to Recent

AbstractBody size is an important trait with implications for energy use and ecology as well as generation time and evolutionary rates. Turritelline gastropods are widely distributed through geologic time and space, making them an excellent group for evaluating macroevolutionary patterns. To evaluate the pattern of body-size change in turritelline gastropods, we compiled a dataset of shell lengths of 316 species of turritelline gastropods spanning the Jurassic to Recent. Type specimens were almost always significantly larger than specimen distributions from the same species. We found that turritelline gastropod size was inversely correlated with latitude, a trend likely driven by the Neogene–Recent diversification of small-bodied Southern Hemisphere taxa. A time series model was applied to distinguish among three possible macroevolutionary patterns: unbiased random walk (no directional trend), biased random walk (directional trend), and stasis (no net change). We determined that turritelline gastropods have experienced stasis in body size throughout their evolutionary history, adding to the growing literature documenting directionless body-size trends in marine invertebrate clades. Stasis of geographically widespread clades may be the result of ecological variability across the environmental range occupied by the group or differential diversification into opposing environments. Turritelline life-history patterns, especially their reproductive strategy that combines a short life span and decline in growth rate around 1 year of age to reallocate energy to reproduction, might circumvent selection for longevity and larger size, while further decrease in minimum size is likely limited by feeding efficiency and anti-predatory defense. The expectation that species or clades should continue to evolve to occupy larger size classes conflicts with the evolutionary advantages of small size, which in turritelline gastropods include high generational turnover and larger population sizes that yield opportunities for genetic variance.

Autonomous Trajectory Tracking Integrated Control of Unmanned Surface Vessel

Trajectory tracking control of unmanned surface vessels (USVs) has become a popular topic. Regarding the problem of ship collision avoidance encountered in trajectory tracking, more attention needs to be paid to the algorithm application, namely the characteristics of flexibility and accessibility. Thus, a fusion framework of field theoretical planning and a model predictive control (MPC) algorithm is proposed in this paper to obtain a realizable collision-free tracking trajectory, where the trajectory smoothness and collision avoidance constraints under a complex environment need to be considered. Through the designed fast matching (FM) method based on the electric field model, the algorithm gains the direction trend of collision avoidance planning and then combines it with a flexible distance to reconstruct the architecture of the MPC and constraint system, generating the optimal trajectory tracking controller. The new algorithm was tested and validated for several situations, and it can potentially be developed to advance collision-free trajectory tracking navigation in multivessel situations.

Trends in Lake Erie zooplankton biomass and community structure during a 25-year period of rapid environmental change

Zooplankton play a key role in aquatic ecosystems, providing potential top-down control on phytoplankton and linking primary production to higher trophic levels. Thus, knowledge of zooplankton dynamics is fundamental to any assessment of the impacts of human driven rapid environmental change on lakes. Lake Erie has undergone eutrophication since the 1990s, resulting in summer harmful cyanobacterial blooms, dominated by Microcystis aeruginosa, since approximately 2003 in the western basin (WB) and 2008 in the central basin (CB). The effect of eutrophication on zooplankton in Lake Erie is unclear; few studies have characterized trends in zooplankton biomass and community structure during this period of rapid change. We used the Lake Erie Plankton Abundance Study (LEPAS) zooplankton dataset to analyze interannual trends in the dynamics of eight major zooplankton groups in the WB and CB during 1995–2020. In both basins, we found directional change in zooplankton biomass and community structure. These directional trends in zooplankton biomass overlaid approximate five-year cycles in nearly all taxa, potentially linked to the El Niño Southern Oscillation. Eutrophication was associated with an increase in the summer biomass of total zooplankton, calanoids, and large cladocerans but surprisingly, not cyclopoids, rotifers or small cladocerans. The surprisingly positive or neutral effect of eutrophication and M. aeruginosa on zooplankton biomass may be due to a combination of bottom-up (e.g. concurrent increases in more edible algae) and top-down (e.g. changes in planktivory) forces.

Recent Advances in the Efficient Synthesis of Useful Amines from Biomass-Based Furan Compounds and Their Derivatives over Heterogeneous Catalysts

Bio-based furanic oxygenates represent a well-known class of lignocellulosic biomass-derived platform molecules. In the presence of H2 and different nitrogen sources, these versatile building blocks can be transformed into valuable amine compounds via reductive amination or hydrogen-borrowing amination mechanisms, yet they still face many challenges due to the co-existence of many side-reactions, such as direct hydrogenation, polymerization and cyclization. Hence, catalysts with specific structures and functions are required to achieve satisfactory yields of target amines. In recent years, heterogeneous catalytic synthesis of amines from bio-based furanic oxygenates has received extensive attention. In this review, we summarize and discuss the recent significant progress in the generation of useful amines from bio-based furanic oxygenates with H2 and different nitrogen sources over heterogeneous catalysts, according to various raw materials and reaction pathways. The key factors affecting catalytic performances, such as active metals, supports, promoters, reaction solvents and conditions, as well as the possible reaction routes and catalytic reaction mechanisms are studied and discussed in depth. Special attention is paid to the structure–activity relationship, which would be helpful for the development of more efficient and stable heterogeneous catalysts. Moreover, the future research direction and development trend of the efficient synthesis for bio-based amines are prospected.

Hydrochemical variations and driving mechanisms in a large linked river-irrigation-lake system

A linked river-irrigation-lake system exhibits intricate and dynamic hydrochemical variations, closely related to changes in natural conditions and anthropogenic activities. However, little is known about the sources, migration and transformation of hydrochemical composition, and the driving mechanisms, in such systems. In this study, the hydrochemical characteristics and processes in the linked Yellow River-Hetao Irrigation District-Lake Ulansuhai system were studied, based on a comprehensive hydrochemical and stable isotope analysis of water samples collected during spring, summer, and autumn. The results showed that the water bodies in the system were weakly alkaline with a pH range of 8.05–8.49. The concentrations of hydrochemical ions showed an increasing trend in the water flow direction. Total dissolved solids (TDS) were less than 1000 mg/L (freshwater) in the Yellow River and the irrigation canals, and increased to more than 1800 mg/L (saltwater) in the drainage ditches and Lake Ulansuhai. The dominant hydrochemical types varied from SO4•Cl–Ca•Mg and HCO3–Ca•Mg types in the Yellow River and the irrigation canals to Cl–Na type in the drainage ditches and Lake Ulansuhai. The ion concentrations in the Yellow River, the irrigation canals, and the drainage ditches were highest during summer, while ion concentrations in Lake Ulansuhai were highest during spring. The hydrochemistry of the Yellow River and the irrigation canals was mainly affected by rock weathering, while evaporation was the principal controlling factor in the drainage ditches and Lake Ulansuhai. Water-rock interactions including the dissolution of evaporites and silicates, the precipitation of carbonates, and cation exchange were the main sources of hydrochemical compositions in this system. Anthropogenic inputs had a low impact on the hydrochemistry. Therefore, greater attention should be paid in future to hydrochemical variations, especially salt ions, in the management of linked river-irrigation-lake system water resources.

Crop production in Türkiye: trends and driving variables

Climate change and a rapidly increasing population boost the pressure on Türkiye’s cropping systems to increase crop production in order to meet rising food demand. It is unknown whether and in which direction trends and variability in harvested area and yield separately affect crop production in Türkiye. The objective of this study was to (1) quantify the long-term (2004–2020) trends of planting/harvested areas, yield and crop production for the 16 vital annual crops in Türkiye, (2) quantify the separate contribution of harvested area and yield on crop-specific production variability and (3) the potential of water and temperature-based remote sensing variables on capturing the variability of harvested areas and yield. The harvested area of the most grown crops (10 out of 16) such as wheat and barley showed a declining trend. However, the yield trend was increased for all of the study crops, which in some cases overcompensated for the decline in the harvested area on crop production. The harvested area showed a more robust explanatory power for production variability than yield except for the crops with higher breeding investments and subsidized by authorities such as wheat and sugar beet. The water-related remote sensing variables and combination of water and temperature variables largely explained the variability of the harvested area in Türkiye. In order to stabilize crop production in Türkiye, better and more efficient water management plans are crucial.

Long term spatiotemporal trends and health risk assessment of remotely sensed PM2.5 concentrations in Nigeria

PM2.5 is an important indicator reflecting air quality variations. Currently, environmental pollution related issues have become more severe that significantly threaten human health. The current study is an attempt to analyze the spatio-dynamic characteristics of PM2.5 in Nigeria based on the directional distribution and trend clustering analysis from 2001 to 2019. The results indicated that PM2.5 concentration increased in most of the Nigerian states, particularly in mid-northern and southern states. The lowest PM2.5 concentration in Nigeria is even beyond the interim target-1 (35 μg/m3) of the WHO. During the study period, the average PM2.5 concentration increased at a growth rate of 0.2 μg/m3/yr from 69 μg/m3 to 81 μg/m3. The growth rate varied from region to region. Kano, Jigawa, Katsina, Bauchi, Yobe, and Zamfara experienced the fastest growth rate of 0.9 μg/m3/yr with 77.9 μg/m3 mean concentration. The median center of the national average PM2.5 moved toward the north indicating the highest PM2.5 concentration in northern states. The Saharan desert dust is the dominant source of PM2.5 in northern areas. Moreover, agricultural practices and deforestation activities along with low rainfall increase desertification and air pollution in these regions. Health risks increased in most of the mid-northern and southern states. The extent of ultra-high health risk (UHR) areas corresponding to the 8×104−7.3×106 μg⋅person/m3 increased from 1.5% to 2.8%. Mainly Kano, Lagos, Oyo, Edo, Osun, Ekiti, southeastern Kwara, Kogi, Enugu, Anambra, Northeastern Imo, Abia, River, Delta, northeastern Bayelsa, Akwa Ibom, Ebonyi, Abuja, Northern Kaduna, Katsina, Jigawa, central Sokoto, northeastern Zamfara, central Borno, central Adamawa, and northwestern Plateau are under UHR areas.

Impact of the Thompson method on breastfeeding exclusivity and duration: Multi-method design

BackgroundHow hospital clinicians facilitate breastfeeding in the first 48–72 h is critical to breastfeeding exclusivity and duration. Mothers who discharge hospital directly breastfeeding are more likely to continue exclusively breastfeeding at 3-months. ObjectiveTo assess the impact of facility-wide implementation of a physiological breastfeeding method (the Thompson method) on direct breastfeeding at hospital discharge and exclusive breastfeeding at 3-months of age. DesignMulti-method design using interrupted time series analysis and surveys. Setting(s)An Australian tertiary maternity hospital. Participants13,667 mother-baby pairs (interrupted time series analysis) and 495 postnatal mothers (surveys). MethodsThe Thompson method includes cradle position and hold, alignment of mouth-to-nipple, baby-led connection and seal, maternal fine-tuning for symmetry, and leisurely duration. We used a large pre-post implementation dataset and conducted interrupted time series analysis using a 24-month baseline period (January 2016 – December 2017); and a 15-month post-implementation period (April 2018 – June 2019). We recruited a sub-sample of women to complete surveys at hospital discharge and 3-months postpartum. Surveys were primarily used to measure impact of Thompson method on exclusive breastfeeding at 3-months, compared with a baseline survey conducted in same setting. ResultsFollowing implementation of the Thompson method, the declining trend in direct breastfeeding at hospital discharge was significantly averted by 0.39% each month relative to baseline (95% CI: 0.03% to 0.76%; p = 0.037). While the 3-month exclusive breastfeeding rate in the Thompson group was 3 percentage points higher than the baseline group; this result did not reach statistical significance. However, a subgroup analysis of women who discharged hospital exclusively breastfeeding revealed the relative odds of exclusive breastfeeding at 3-months in the Thompson group was 0.25 (95% CI: 0.17 to 0.38; p < 0.001), significantly better than the baseline group (Z = 3.23, p < 0.01) where the relative odds was only 0.07 (95% CI: 0.03 to 0.19; p < 0.001). ConclusionsImplementation of the Thompson method for well mother-baby pairs improved direct breastfeeding trends at hospital discharge. For women who discharged hospital exclusively breastfeeding, exposure to the Thompson method reduced the risk of exclusive breastfeeding discontinuation by 3-months. The positive impact of the method was potentially confounded by partial implementation and a parallel rise in birth interventions which undermine breastfeeding. We recommend strategies to strengthen clinician buy-in to the method, and future research using a cluster randomised trial design. Tweetable abstractFacility-wide implementation of the Thompson method improves direct breastfeeding at hospital discharge and predicts breastfeeding exclusivity at 3-months.

Geostatistical and geoarchaeological study of Holocene floodplains and site distributions on the Sha‐Ying River Basin, Central China

AbstractGeostatistics has become a powerful method for investigating complex spatial variations of prehistoric settlements in floodplains and other geomorphological settings. A geoarchaeological drilling program that covers most of the Sha‐Ying River Basin provides a rare opportunity with unusually detailed environmental data to contest and develop the geostatistics method, which proves to be essential, in combination with archaeological data, to understand long‐term (9000–2500 B.P.) patterns of human inhabitation and adaption to volatile floodplain environments in eastern Central China. We analysed the variography and multivariate ordination of the borehole data and explored the complexities of landform evolution, with reference to sedimentation processes and soil development in the floodplain of the Sha‐Ying River. The recurrent impact of river floods on regional landforms is manifested by spatial‐autocorrelated properties over distances up to 10 km, sometimes with directional trends. We then developed a model of landform evolution through kriging and compared the model with detailed reconstruction of archaeological settlement patterns. Our results illustrate long‐term socio‐environmental dynamics by which human communities first populated and then adapted in diverse ways to the changing floodplain environments from the early to middle Holocene. This improved method will have far‐reaching implications for future studies on similar geomorphological settings across vast floodplains of Central China and other global regions.

Diversity of protist genera in periphyton of tufa-depositing karstic river

PurposeIn aquatic ecosystems, protists play a crucial role and cover numerous ecological functions. The karstic Krka River (Croatia) is a unique hotspot for high diversity of aquatic organisms, especially protists. The main objective of the present study was to obtain a detailed overview of the protist community structure in the periphyton of the Krka River and to determine the differences in protist diversity along the river.MethodsProtist diversity was detected by amplicon sequencing of the hypervariable region V9 of the 18S rRNA gene, using the universal eukaryotic primer pair.ResultsThe three main groups of protists were as follows: Ciliophora, Cercozoa, and Bacillariophyta. In terms of abundance of protist OTUs, the shade plot revealed an evident difference from the upstream to downstream river section, which increased between locations from Krka spring to Skradinski buk. Diversity was explored using measures of alpha and beta diversity. Alpha diversity showed an increasing trend in the downstream direction of the river. The location effect, or clustering/grouping of samples by location, was confirmed by the PERMANOVA permutation test of beta diversity.ConclusionThe combination of alpha and beta diversity can help provide deeper insight into the study of diversity patterns, but also point out to decline in species diversity and allow for effective ways to protect aquatic karst habitats in future management.

Modelling spatial–temporal expansion of Lilongwe City using Shannon’s entropy model through semi-dynamic environmental mapping and analysis

This study involves analysis of the urban spatial–temporal expansion of Lilongwe City from 1973 to 2020 using Shannon’s entropy model through time-series satellite mapping. Landsat images from 1973 to 2020 in a nearly 10-year interval are used to determine spatial–temporal land use/cover changes. The city is zoned into 1 km concentric rings and four pie sections to determine both directional and spatial urban expansion trends while Shannon’s entropy model is employed to determine the degree of dispersity of the city’s sprawl. A linear regression model incorporating population as an explanatory variable is then applied to predict the spatial expansion trends for Lilongwe City. Results show that the built-up area in Lilongwe City expanded by 465.4% (9.9% per year) from 1973 to 2020, making it the second-largest land use/cover type in the city, after vegetation. Consequently, vegetation cover decreased by − 32.7% (− 0.7% per year) during the same period. High relative entropy indices (> 0.9) obtained from Shannon’s entropy model indicate a dispersed urban development for the city during the entire period of study. The North-West quadrant of the city has the highest proportion of urban expansion while the North-East quadrant has the lowest proportion, in a relative sense. Regression model predictions show that the city will most likely continue to expand by the year 2023 and then increase exponentially by the year 2033, due to high population growth. The results of this study will assist city authorities to control the expansion of the city and anticipate patterns for future urban sprawl.

Rapidly changing speciation and extinction rates can be inferred in spite of nonidentifiability

The birth-death model is commonly used to infer speciation and extinction rates by fitting the model to phylogenetic trees with exclusively extant taxa. Recently, it was demonstrated that speciation and extinction rates are not identifiable if the rates are allowed to vary freely over time. The group of birth-death models that have the same likelihood is called a congruence class, and there is no statistical evidence to favor one model over the other. This issue has led researchers to question if and what patterns can reliably be inferred from phylogenies of only extant taxa and whether time-variable birth-death models should be fitted at all. We explore the congruence class in the context of several empirical phylogenies as well as hypothetical scenarios. For these empirical phylogenies, we assume that we inferred the true congruence class. Thus, our conclusions apply to any empirical phylogeny for which we robustly inferred the true congruence class. When we summarize shared patterns in the congruence class, we show that strong directional trends in speciation and extinction rates are shared among most models. Therefore, we conclude that the inference of strong directional trends is robust. Conversely, estimates of constant rates or gentle slopes are not robust and must be treated with caution. Interestingly, the space of valid speciation rates is narrower and more limited in contrast to extinction rates, which are less constrained. These results provide further evidence and insights that speciation rates can be estimated more reliably than extinction rates.

Prediction of Energy Production Level in Large PV Plants through AUTO-Encoder Based Neural-Network (AUTO-NN) with Restricted Boltzmann Feature Extraction

In general, reliable PV generation prediction is required to increase complete control quality and avoid potential damage. Accurate forecasting of direct solar radiation trends in PV power production could limit the influence of uncertainties on photovoltaics, enhance organizational dependability, and maximize the utilization factor of the PV systems for something such as an energy management system (EMS) of microgrids. This paper proposes an intelligent prediction of energy production level in large PV plants through AUTO-encoder-based Neural-Network (AUTO-NN) with Restricted Boltzmann feature extraction. Here, the solar energy output may be projected using prior sun illumination and meteorological data. The feature selection and prediction modules use an AUTO encoder-based Neural Network to improve the process of energy prediction (AUTO-NN). Restricted Boltzmann Machines (RBM) can be used during a set of regulations for development-based feature extraction. The proposed model’s result is evaluated using various constraints. As a result, the proposed AUTO-NN achieved 58.72% of RMSE (Root Mean Square Error), 62.72% of nRMSE (Normalized Root Mean Square Error), 48.04% of MaxAE (Maximum Absolute Error), 48.66% of (Mean Absolute Error), and 46.76% of (Mean Absolute Percentage Error).

The direct admission trend: How states, schools, and students are working to flip college enrollment

Direct admissions might be the hottest new trend in higher education.

Morphological Continua Make Poor Species: Genus-Wide Morphometric Survey of the European Bee Orchids (Ophrys L.).

Despite (or perhaps because of) intensive multidisciplinary research, opinions on the optimal number of species recognised within the Eurasian orchid genus Ophrys range from nine to at least 400. The lower figure of nine macrospecies is based primarily on seeking small but reliable discontinuities in DNA 'barcode' regions, an approach subsequently reinforced and finessed via high-throughput sequencing studies. The upper figure of ca. 400 microspecies reflects the morphological authoritarianism of traditional taxonomy combined with belief in extreme pollinator specificity caused by reliance on pollination through pseudo-copulation, enacted by bees and wasps. Groupings of microspecies that are less inclusive than macrospecies are termed mesospecies. Herein, we present multivariate morphometric analyses based on 51 characters scored for 457 individual plants that together span the full morphological and molecular diversity within the genus Ophrys, encompassing 113 named microspecies that collectively represent all 29 mesospecies and all nine macrospecies. We critique our preferred morphometric approach of accumulating heterogeneous data and analysing them primarily using principal coordinates, noting that our conclusions would have been strengthened by even greater sampling and the inclusion of data describing pseudo-pheromone cocktails. Morphological variation within Ophrys proved to be exceptionally multidimensional, lacking strong directional trends. Multivariate clustering of plants according to prior taxonomy was typically weak, irrespective of whether it was assessed at the level of macrospecies, mesospecies or microspecies; considerable morphological overlap was evident even between subsets of the molecularly differentiable macrospecies. Characters supporting genuine taxonomic distinctions were often sufficiently subtle that they were masked by greater and more positively correlated variation that reflected strong contrasts in flower size, tepal colour or, less often, plant size. Individual macrospecies appear to represent morphological continua, within which taxonomic divisions are likely to prove arbitrary if based exclusively on morphological criteria and adequately sampled across their geographic range. It remains unclear how much of the mosaic of subtle character variation among the microspecies reflects genetic versus epigenetic or non-genetic influences and what proportion of any contrasts observed in gene frequencies can be attributed to the adaptive microevolution that is widely considered to dictate speciation in the genus. Moreover, supplementing weak morphological criteria with extrinsic criteria, typically by imposing constraints on geographic location and/or supposed pollinator preference, assumes rather than demonstrates the presence of even the weakest of species boundaries. Overall, it is clear that entities in Ophrys below the level of macrospecies have insufficiently structured variation, either phenotypic or genotypic, to be resolved into discrete, self-circumscribing ("natural") entities that can legitimately be equated with species as delimited within other less specialised plant genera. Our search for a non-arbitrary (meso)species concept competent to circumscribe an intermediate number of species has so far proven unsuccessful.

The direct admission trend: How states, schools, and students are working to flip college enrollment

Direct admissions might be the hottest new trend in higher education.

The Clustering Characteristics and Driving Mechanisms of Tourist Preference for 5A Scenic Spots from the Dynamic Spatio-Temporal Perspective: A Case of Jiangsu in Eastern Coastal Area of China

In the era of tourism 4.0, the subjective preferences and experiences of tourists directly affects the future development of scenic spots. Among them, 5A scenic spots represent China’s world-class boutique tourist scenic ranking, which pays more attention to humanization and detailing, and better reflect tourists’ general psychological demand for tourist attractions. Therefore, it becomes an important scientific issue to explore the spatial and temporal characteristics of 5A tourists’ preferences and their deeper reasons. China’s eastern coastal provinces have played a very important role in promoting regional tourism culture, promoting regional economic development, and building a strong coastal province. Taking Jiangsu as an example, this study introduces the standard deviation ellipse and kernel density estimation to explore the characteristics and trends of tourist preference clustering in 5A scenic spots and their internal and external driving mechanisms from 2012–2021, which is based on a new perspective of geotemporal dynamic analysis. The empirical results show that: (1) the network attention of 5A scenic spots in Jiangsu generally showed a “barb-type” trend in 2012–2021, the highest network attention is concentrated in April and October, accounting for 82%, and tourists pay the most attention to cultural relics scenic spots, peaking on Sunday; (2) the tourist preference for 5A scenic spots in Jiangsu shows a relative clustering distribution pattern in general, with a slightly higher clustering trend in the northwest-southeast direction than in the northeast-southwest direction. Furthermore, the nucleus of the density values range from 0 to 115.43, showing the spatial pattern of “one belt and two cores”; (3) the internal driving factors include the types, the culture nature, the characteristics nature, the spatial proximity, and the infrastructure of scenic spots, and the external driving factors include geographical location, industrial development policy, climate comfort, economic development level, traffic accessibility, and the impact of COVID-19 epidemic. On this basis, this study puts forward feasible suggestions for improving scenic area management and increasing the reception capacity, so as to provide fine scientific guidelines for the high-quality development of 5A scenic spots in Jiangsu and provide reference for further enhancing the attractiveness of 5A scenic spots and their synergistic development in the eastern coastal provinces.

Recovery and stress of control center dispatchers in the first waves of the SARS-CoV-2 pandemic.

Control center dispatchers (CCDs) are exposed to high levels of work-related mental stress, which are exacerbated by the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. The aim of this study was to comparatively analyze the recovery and stress state of CCDs during the first and second waves of the SARS-CoV‑2 pandemic. A total of 490 CCDs (n = 440, t1 and n = 50, t2) with amean age of 42.26 ± 8.79years participated directly at the end of the first wave from June to August 2020 (t1) and during the second wave between January and February 2021 (t2) of the SARS-CoV‑2 pandemic. The short form (EBF-24/A; test form S2) of the Kallus recovery-stress questionnaire (EBF) was applied. Over the course of the two survey phases, the dimensions strain significantly increased (t1: 2.47 ± 1.08 vs. t2: 3.12 ± 0.93points, p < 0.001) and recovery significantly decreased (t1: 3.03 ± 0.94 vs. t2: 2.50 ± 0.81points, p < 0.001). Significant to highly significant differences were present in the EBF dimensions of the two waves in the majority of cases, even when taking the waves into account. For the variable "recovery in the social field", amedium effect was noticeable in the corrected model (η2 = 0.064). The SARS-CoV‑2 pandemic illustrates that the stress experience increased from the first to the second waves, and the recovery of CCDs decreased. These data provide adirectional trend as the pandemic is ongoing, and stress and strain situations in control centers may continue to worsen. Immediate health promotion and prevention measures are essential.