Spatial Patterns Research Articles

Spatiotemporal patterns and surveillance artifacts in maternal mortality in the United States: a population-based study

Reports of high and rising maternal mortality ratios (MMR) in the United States have caused serious concern. We examined spatiotemporal patterns in cause-specific MMRs, in order to obtain insights into the cause for the increase. The study included all maternal deaths recorded by the Centers for Disease Control and Prevention from 1999 to 2021. Changes in overall and cause-specific MMRs were quantified nationally; in low-vs high-MMR states (i.e., MMRs <20 vs≥26 per 100,000 live births in 2018-2021); and in California vs Texas (populous states with low vs high MMRs). Cause-specific MMRs included those due to unambiguous causes (e.g., selected obstetric causes such as pre-eclampsia/eclampsia) and less-specific/potentially incidental causes (e.g., "other specified pregnancy-related conditions", chronic hypertension, and malignant neoplasms). MMRs increased from 9.60 (n=1543) in 1999-2002 to 23.5 (n=3478) per 100,000 live births in 2018-2021. The temporal increase in MMRs was smaller in low-MMR states (from 7.82 to 14.1 per 100,000 live births) compared with high-MMR states (from 11.1 to 31.4 per 100,000 live births). MMRs due to selected obstetric causes decreased to a similar extent in low-vs high-MMR states, whereas the increase in MMRs from less-specific/potentially incidental causes was smaller in low- vs high-MMR states (MMR ratio (RR) 5.57, 95% CI 4.28, 7.25 vs 7.07, 95% CI 5.91, 8.46), and in California vs Texas (RR 1.67, 95% CI 1.03, 2.69 vs 10.8, 95% CI 6.55, 17.7). The change in malignant neoplasm-associated MMRs was smaller in California vs Texas (RR 1.21, 95% CI 0.08, 19.3 vs 91.2, 95% CI 89.2, 94.8). MMRs from less-specific/potentially incidental causes increased in all race/ethnicity groups. Spatiotemporal patterns of cause-specific MMRs, including similar reductions in unambiguous obstetric causes of death and variable increases in less-specific/potentially incidental causes, suggest misclassified maternal deaths and overestimated maternal mortality in some US states. This work received no funding.

Employing stable isotopes to reveal temporal trajectories of water travelling through the soil–plant-atmosphere continuum

The spatiotemporal patterns of water travelling through the soil–plant-atmosphere continuum (SPAC) have received much attention due to the frequency of extreme weather and water scarcity. However, the interconnections and transboundary transport of specific compartments within the hydrologic cycle are poorly understood. We portrayed the propagation paths of water isotope signals by analyzing isotopes of precipitation, soil water, and xylem water. The isotope sine curves analysis method was improved to quantify water transfer efficiency, mean transmission time from precipitation to soil (MTT1), mean transmission time from soil to trees (MTT2), mean residence time within soil (MRTSW), and mean residence time within tree xylems (MRTXY). The temporal trajectory of water traveling through SPAC was depicted, and its influencing factors and intrinsic mechanisms were explored. Our results showed that (1) water isotopes were blocked when crossing water pools (precipitation, soil water, and xylem water) and the transfer efficiency was progressively weaker (85.5 %→13.5 %). (2) The MTT1 was significantly and positively correlated with soil porosity (Spearman correlation coefficient, 0.551). Its spatiotemporal pattern (0.8–15.9d) indicated that the transport and mixing of soil water involved two modes: displacement flow and bypass flow. The MTT2 (−13.2d–4.3d) of Platycadus orientalis was in general smaller than that of Quercus variabilis (−4.7d–11.5d). (3) The MRT (35.2d–343.8d) was influenced by a combination of soil physicochemical properties, root distribution, and tree morphological traits. Our study shows that connectivity between pools is better reflected with transfer efficiency. Comparing MTT and MRT of P. orientalis and Q. variabilis, tree hydrodynamic processes were quantified, and P. orientalis was more sensitive to seasonal moisture variability. Additionally, our study improved the understanding of the “black box” within the hydrological interface of plant-soil interactions.

Slow-fast dynamics in non-linear enzyme cascades gives rise to spatial multiscaling.

Slow-fast dynamics in a well-mixed biological system is known to be associated with functional modularity with temporal hierarchy of processes. Yet, the significance of slow-fast dynamics in spatially distributed reaction-diffusion systems remains to be clarified.We assessed such systems with slow-fast dynamics, such as blood coagulation and predator-prey models to identify spatial patterns with independent parametric regulation, and performed their reaction-rate based sensitivity analysis with the help of computational one-dimensional reaction-diffusion models.In blood coagulation, spatial distribution of fibrin had two scales: a larger region with a high and almost constant fibrin concentration (corresponding to solid blood clot) and a narrow transition zone, where fibrin concentration decayed to zero (semi-liquid clot). Slow variables (e.g., the concentration of the coagulation factor IXa) regulated the clot size (large scale), while fast variables (e.g., concentrations of thrombin and factor Xa) regulated the thickness of the gel-to-liquid transition zone (small scale). Analysis of the simplified model of blood coagulation, composed only of factor X and IX activation, and of the predator-prey model confirmed this finding to be sufficiently general, and revealed that the limitation of fast enzyme production (due to precursor depletion or to kinetics with saturation) was crucial for this multi-scaling. Independent regulation of spatial scales also required species with slow kinetics to be upstream from species with fast kinetics.The shared slow-fast dynamics of the examined systems endow them with the ability to form spatial patterns, representing a new mechanism complementing the Turing-type and the Positional Information type pattern formation.

Resting state of human brain measured by fMRI experiment is governed more dominantly by essential mode as a global signal rather than default mode network

Resting-state of the human brain has been described by a combination of various basis modes including the default mode network (DMN) identified by fMRI BOLD signals in human brains. Whether DMN is the most dominant representation of the resting-state has been under question. Here, we investigated the unexplored yet fundamental nature of the resting-state. In the absence of global signal regression for the analysis of brain-wide spatial activity pattern, the fMRI BOLD spatiotemporal signals during the rest were completely decomposed into time-invariant spatial-expression basis modes (SEBMs) and their time-evolution basis modes (TEBMs). Contrary to our conventional concept above, similarity clustering analysis of the SEBMs from 166 human brains revealed that the most dominant SEBM cluster is an asymmetric mode where the distribution of the sign of the components is skewed in one direction, for which we call essential mode (EM), whereas the second dominant SEBM cluster resembles the spatial pattern of DMN. Having removed the strong 1/f noise in the power spectrum of TEBMs, the genuine oscillatory behavior embedded in TEBMs of EM and DMN-like mode was uncovered around the low-frequency range below 0.2 Hz.

Optimization of territorial ecological space under the constraint of ecosystem service externalities

Ecosystem services are dynamic, following specific paths between regions and generating externalities. However, research on these externalities and the mechanisms within ecological networks remains limited. The quantification, spatial patterns, and evolution of these externalities are still unclear and need further study. Utilizing land use, topography, precipitation, and socio-economic data from 2010 and 2020, the study aims to quantify the externalities of ecosystem services and analyze their spatial distribution and network transmission characteristics within the Territorial Ecological Space (TES) of Jintan District. Using the InVEST model, we assessed the externalities of ecosystem services and integrated these with an ecological network model to reveal the impact of network structure on the flow of externalities. We propose an ecological space optimization plan with various scenarios, offering a reference for regional ecological space optimization. Key findings indicate that ecosystem service externalities exist and display spatial differentiation, with ecological source areas and corridors participating in the flow and dissipation of these services. Based on these findings, an ecological space optimization plan is proposed, consisting of multiple scenarios, which offers a reference for regional ecological space optimization. The study contributes to the sustainable management of ecological spaces by providing new insights and methodological advancements, particularly in the context of optimizing ecological spatial structures and ensuring regional ecological security. By elucidating the spatial dynamics and network transmission of ecosystem service externalities, this research supports informed decision-making in ecological conservation and land use planning.

Evaluation of consumer-grade wireless EEG systems for brain-computer interface applications.

With the growing popularity of consumer-grade electroencephalogram (EEG) devices for health, entertainment, and cognitive research, assessing their signal quality is essential. In this study, we evaluated four consumer-grade wireless and dry-electrode EEG systems widely used for brain-computer interface (BCI) research and applications, comparing them with a research-grade system. We designed an EEG phantom method that reproduced µV-level amplitude EEG signals and evaluated the five devices based on their spectral responses, temporal patterns of event-related potential (ERP), and spectral patterns of resting-state EEG. We discovered that the consumer-grade devices had limited bandwidth compared with the research-grade device. A late component (e.g., P300) was detectable in the consumer-grade devices, but the overall ERP temporal pattern was distorted. Only one device showed an ERP temporal pattern comparable to that of the research-grade device. On the other hand, we confirmed that the activation of the alpha rhythm was observable in all devices. The results provide valuable insights for researchers and developers when it comes to selecting suitable EEG devices for BCI research and applications.

Molecular characterization, spatio-temporal expression patterns of crtc2 gene and its immune roles in yellow catfish (Pelteobagrus fulvidraco)

cAMP response element binding (CREB) protein 2 (CRTC2) is a transcriptional coactivator of CREB and plays an important role in the immune system. Thus far, the physiological roles of Crtc2 in teleost are still poorly understood. In this study, the crtc2 gene was identified and characterized from yellow catfish (Pelteobagrus fulvidraco; therefore, the gene is termed as pfcrtc2), and its evolutionary and molecular characteristics as well as potential immunity-related roles were investigated. Our results showed that the open reading frame of pfcrtc2 was 2,346 bp in length, encoding a protein with 781 amino acids. Gene structure analysis revealed its existence of 14 exons and 13 introns. A phylogenetic analysis proved that the tree of crtc2 was clustered into five groups, exhibiting a similar evolutionary topology with species evolution. Multiple protein sequence alignment demonstrated high conservation of the crtc2 in various vertebrates with similar structure. Syntenic and gene structural comparisons further established that crtc2 was highly conserved, implying its similar roles in diverse vertebrates. Tissue distribution pattern detected by quantitative real-time PCR showed that the pfcrtc2 gene was almost expressed in all detected tissues except for eyes, with the highest expression levels in the gonad, indicating that Crtc2 may play important roles in various tissues. In addition, pfcrtc2 was transcribed at all developmental stages in yellow catfish, showing the highest expression levels at 12 h after fertilization. Finally, the transcriptional profiles of crtc2 were significantly increased in yellow catfishes injected with Aeromonas hydrophila or Poly I:C, which shared a consistent change pattern with four immune-related genes including IL-17A, IL-10, MAPKp38, and NF-κBp65, suggesting pfCrtc2 may play critical roles in preventing both exogenous bacteria and virus invasion. Anyway, our findings lay a solid foundation for further studies on the functions of pfcrtc2, and provide novel genetic loci for developing new strategies to control disease outbreak in teleost.

Spatial Distributions and Edge Relationships of Plant Communities in Coastal Barrens in Nova Scotia, Canada

Coastal barrens support varied vegetation that includes wetlands, dwarf shrublands, and small patches of forest. Forest expansion, sea-level rise and recreational trails affect plant communities but spatial vegetation patterns within barrens are unknown. Using high-resolution multispectral aerial imagery, we classified plant communities and other land cover types using 500m x 500m landcover maps at three coastal barrens sites on the Atlantic coast of Nova Scotia, Canada. Community patches were compared using size and shape metrics; shared edge length identified adjacent communities. Community distributions were modelled using environmental variables such as elevation and distance to coast. Forty distinct plant communities were detected, with shrublands (37.5% total area), dwarf shrublands (23.3%) and bog wetlands (13.9%) the most abundant. Average patch size was 9.2 m2; average patch density was 951 patches/ha, indicating fine scale community variability. Recreational vehicle trails occurred primarily in bog wetlands. Dwarf shrublands and some wetland types were closest to the coastline; taller shrublands and tree islands occurred further from the coast. Edge relationships revealed a vegetation height gradient across the forest-barren ecotone: tree islands were mostly adjacent to tall shrub communities, followed by progressively shorter vegetation. Topographic variability and distance to coast were important predictors of community distribution. Edge relationships among communities allowed identification of those most at risk from trail disturbance, forest expansion and coastal squeeze.

Functional preference and spatial response of urban renewal entities in Beijing

In the process of rapid urban renewal, quantitative research on functional preferences and spatial layout norms of multi-type urban renewal entities is crucial for optimizing spatial governance and promoting orderly control of urban renewal. We investigate urban renewal in Beijing from 2006 to 2021 using directional distribution, spatial autocorrelation, and hotspot analysis. The findings are as follows: (1) The functional preference of each type of entity differs. While most private companies and other profit-oriented entities concentrate on producer services and residential functions, policy-oriented entities dominate the urban regeneration of public service activities. (2) Every entity shows a significant agglomeration characteristic, yet exhibits a differentiated spatial response pattern. Those entities with stronger leasing ability prefer the central zone while others are the opposite. (3) Diverse types of entities have differentiated spatiotemporal evolutions. The spatial directional divergence of state-owned enterprises and scientific research institutes has increased between 2006 and 2021. This is mainly influenced by the policy of relieving Beijing of nonessential functions. However, the rest entities show a balanced spatial development trend with the difference in each direction becoming smaller. Furthermore, the center of gravity of profit-oriented entities has shifted from the suburbs to the central zone due to a combination of administrative and market forces, whereas the center of gravity of policy-oriented entities tends to move outward from the central zone.

Sustainable Development of Urban Agglomerations around Lakes in China: Achieving SDGs by Regulating Ecosystem Service Supply and Demand through New-type Urbanization

The mechanism through which New-type Urbanization (NU), as a new direction in urban development, influences the Sustainable Development Goals (SDGs) by regulating the Ecosystem Services (ES) supply and demand remains to be determined. It is particularly true in urban agglomerations around lakes, characterized by severe human-land conflicts, where socio-economic development is closely linked to water. We selected China’s urban agglomerations around lakes as the study area. We investigated the spatio-temporal heterogeneity of NU and the Ecosystem Service Supply and Demand Ratio (ESDR) from 2000 to 2018. We specifically focused on the dynamic trends of SDG 2 (Zero Hunger), SDG 13 (Climate Action), and SDG 15 (Life on Land). Furthermore, we utilized Structural Equation Modeling (SEM) to reveal the direct effects and indirect pathways through which NU influences the achievement of SDGs in the study area, emphasizing the differentiated performance of this mechanism across various urban agglomerations around Lakes. The results indicated that the ESDR has a particularly evident downward trend in urban centers along lakes, rivers, and road networks in spatial terms. The level of NU in urban agglomerations around lakes has increased by about 50% overall. It geographically exhibits three main spatial distribution patterns: “diffusion along the lake,” “homogeneous distribution,” and “diffusion along the river.” NU directly inhibits the achievement of SDGs but indirectly promotes the improvement of ESDR for food production and soil conservation, thereby indirectly facilitating the achievement of SDG 2 and SDG 15, but has an inhibitory effect on SDG 13. By regulating ESDR, NU is most effective in achieving SDGs in the urban agglomerations around Poyang Lake and Dongting Lake but has a significant inhibitory effect on the urban agglomeration around Hongze Lake. This research provides quantitative evidence for the urban planning shift, terrestrial ecosystem function restoration, and SDGs achievement in urban agglomerations around lakes. It also offers new insights from China for the sustainable urban construction of urban agglomerations around lakes worldwide.

Continuous measurement of the dynamics of residential indoor and outdoor NO2 and the contributions to human exposure

In residential environment, NO2 is an important air pollutant. Yet, the dynamics of indoor NO2 and source contributions to human exposure are not well understood. Here, we conducted a continuous NO2 measurement in and out of eight households in Guangzhou, China. Paired high time-resolution NO2 data sets indoors (kitchen, living room) and outdoors (balcony) were obtained with NO2 monitors. We summarized the indoor and outdoor NO2 levels, identified temporal variation patterns, analyzed indoor-outdoor relationships, and quantified source contributions to indoor NO2 exposure. Indoor NO2 were overall higher than outdoor NO2, and in most cases, the highest NO2 levels were observed in the kitchen. NO2 in the kitchen was characterized by multiple spikes associated with use of gas stoves, while NO2 in the living room was also elevated but the peaks were generally smaller. The indoor-outdoor correlations were stronger in winter than in summer, and were stronger in nighttime than daytime. The sources contributing to indoor NO2 were separated with a conceptual model. Overall, the outdoor NO2 source contributed 73% – 76% of the NO2 in the kitchen, and 76% – 85% in the living room. The source pattern was quite different: outdoor NO2 sources were present indoors all the time; by contrast, indoor NO2 sources were present sporadically but with a very high contribution. This has important implication to the exposure assessment that indoor NO2 sources lead to short-term high exposure, and deserves attention regarding acute health effects.

Divergent responses of forest canopy height to environmental conditions across China

As major components of terrestrial ecosystems, forest ecosystems play an important role in sequestering carbon and hence mitigating climate change. Canopy height is a crucial factor characterizing the structure and function of forest ecosystems, yet the driving mechanism of forest canopy height receives less attentions in China. Here, we utilize the satellite-based forest canopy height product with several environmental and climate factors (e.g. forest age, temperature, etc.) to delineate the spatial distributions of forest canopy height and its drivers in China at 1 km spatial resolution during the period of 2014 to 2018. The random forest is employed for identifying the dominant factors at province level, while Shapley additive explanations (SHAP) analysis is further incorporated at pixel-level to dig into the specific contributions of each driver. The results show that forest age primarily dominates the spatial distributions of forest canopy height across different forest ecosystems of China, followed by mean annual precipitation, soil type, and aspect. SHAP analysis further indicates that other factors, such as soil moisture and wind speed, also play critical roles to shape the spatial patterns of forest canopy height in China, which could not be revealed from province-level random forest analyses. Such results emphasize the priority of incorporating SHAP analysis with random forest to advance our understanding of forest canopy height distributions and benefit future projections. Our study highlights the necessity to characterize the spatial heterogeneity of forest canopy height, which is critical for accurate estimations of forest and even terrestrial carbon sink in China, facilitating the achievement of the goal of “carbon peak in 2030 and carbon neutrality in 2060”.

Relationship between MRI brain-age heterogeneity, cognition, genetics and Alzheimer’s disease neuropathology

Brain ageing is highly heterogeneous, as it is driven by a variety of normal and neuropathological processes. These processes may differentially affect structural and functional brain ageing across individuals, with more pronounced ageing (older brain age) during midlife being indicative of later development of dementia. Here, we examined whether brain-ageing heterogeneity in unimpaired older adults related to neurodegeneration, different cognitive trajectories, genetic and amyloid-beta (Aβ) profiles, and to predicted progression to Alzheimer's disease (AD). Functional and structural brain age measures were obtained for resting-state functional MRI and structural MRI, respectively, in 3460 cognitively normal individuals across an age range spanning 42-85 years. Participants were categorised into four groups based on the difference between their chronological and predicted age in each modality: advanced age in both (n=291), resilient in both (n=260) or advanced in one/resilient in the other (n=163/153). With the resilient group as the reference, brain-age groups were compared across neuroimaging features of neuropathology (white matter hyperintensity volume, neuronal loss measured with Neurite Orientation Dispersion and Density Imaging, AD-specific atrophy patterns measured with the Spatial Patterns of Abnormality for Recognition of Early Alzheimer's Disease index, amyloid burden using amyloid positron emission tomography (PET), progression to mild cognitive impairment and baseline and longitudinal cognitive measures (trail making task, mini mental state examination, digit symbol substitution task). Individuals with advanced structural and functional brain-ages had more features indicative of neurodegeneration and they had poor cognition. Individuals with a resilient brain-age in both modalities had a genetic variant that has been shown to be associated with age of onset of AD. Mixed brain-age was associated with selective cognitive deficits. The advanced group displayed evidence of increased atrophy across all neuroimaging features that was not found in either of the mixed groups. This is in line with biomarkers of preclinical AD and cerebrovascular disease. These findings suggest that the variation in structural and functional brain ageing across individuals reflects the degree of underlying neuropathological processes and may indicate the propensity to develop dementia in later life. The National Institute on Aging, the National Institutes of Health, the Swiss National Science Foundation, the Kaiser Foundation Research Institute and the National Heart, Lung, and Blood Institute.

Nonlinear Radiative Response to Patterned Global Warming due to Convection Aggregation and Nonlinear Tropical Dynamics

Abstract Climate responses to global warming exhibit large dependence on the spatial pattern of sea surface temperature (SST) changes. A Green’s function (GF) approach—predicting the global climate response to a complex SST pattern change as the linear superposition of the response to finite-area SST perturbations evaluated in isolation—has been used to systematically evaluate and understand the top of atmosphere (TOA) radiation response to patterned warming. However, in general, the linear GF approach fails for TOA radiation reconstruction under future global warming scenarios in coupled models. Here, we show that the linear superposition of global mean TOA radiation responses to large SST warming perturbations at multiple patches (the GF approach prediction) overestimates the actual response to simultaneous multipatch perturbation. This is because the linear superposition overestimates tropical large-scale convection aggregation strengthening upon localized heating that enhances longwave radiative cooling, which is further explained by the overestimation of circulation response and associated horizontal water vapor transport. The nonadditivity of TOA radiation response is caused by the nonadditivity of convection aggregation, ultimately rooted in nonlinear tropical dynamics. We also demonstrate that the prediction error of the GF approach grows with decreasing patch size (equivalently, increasing patch number). We conclude that using the GF approach to predict future climate change could overestimate longwave radiative cooling and underestimate (effective) climate sensitivity. Numerical experiments may be used to identify specific perturbation patterns where the errors are smaller than the signal. Our research also highlights that an increase in the degree of large-scale convection aggregation has a nonlinear and negative feedback for mean warming.

Poleward Migration of the Latitude of Maximum Tropical Cyclone Intensity—Forced or Natural?

Abstract Past studies have shown a significant observed poleward trend in the latitude at which tropical cyclones reach their lifetime maximum intensity (LMI), especially in the northwest Pacific basin. Given the brevity of the historical record, it remains difficult to separate the forced trend from internal variability of the climate system. A recently developed tropical cyclone downscaling model is used to downscale the Community Earth System Model, version 2 (CESM2), preindustrial control simulation. It is found that the observed trend in the latitude at which tropical cyclones reach their LMI in the northwest Pacific is very unlikely to be caused by internal variability. The same downscaling model is then used to downscale CESM2 simulations under historical forcing. The resulting trend distribution shows a significant poleward migration of tropical cyclone LMI even after regressing out both natural variability and the part of the forced warming pattern that projects onto natural variability. The results indicate that the observed poleward migration of the latitude at which tropical cyclones reach their LMI in the northwest Pacific basin is likely to be, at least in part, forced. However, the magnitude of the projected poleward trend in climate models can be significantly modulated by the simulated spatial pattern of ocean warming. This highlights how discrepancies between models and observations, with regard to projected changes to the equatorial zonal sea surface temperature gradient under anthropogenic forcing, can lead to large uncertainties in projected changes to the LMI latitude of tropical cyclones. Significance Statement Observations in the northwest Pacific basin show that the latitude at which tropical cyclones are at their most intense has been trending northward in the recent half century. These changes are important since tropical cyclones could bring hazardous weather to coastal areas that are poorly equipped to handle them. Here, we show that natural variations in Earth’s climate are very unlikely to explain the observed poleward trend in the latitude that tropical cyclone reach their maximum intensity. We find that it is much more likely that the observed trend is forced by human-related emissions, though the spatial pattern of warming in response to greenhouse emissions can have significant impacts on the magnitude of the trend.

Distinct mechanisms for online and offline motor skill learning across human development.

The human central nervous system (CNS) undergoes tremendous changes from childhood to adulthood and this may affect how individuals at different stages of development learn new skills. Here, we studied motor skill learning in children, adolescents, and young adults to test the prediction that differences in the maturation of different learning mechanisms lead to distinct temporal patterns of motor learning during practice and overnight. We found that overall learning did not differ between children, adolescents, and young adults. However, we demonstrate that adult-like skill learning is characterized by rapid and large improvements in motor performance during practice (i.e., online) that are susceptible to forgetting and decay over time (i.e., offline). On the other hand, child-like learning exhibits slower and less pronounced improvements in performance during practice, but these improvements are robust against forgetting and lead to gains in performance overnight without further practice. The different temporal dynamics of motor skill learning suggest an engagement of distinct learning mechanisms in the human CNS during development. In conclusion, adult-like skill learning mechanisms favor online improvements in motor performance whereas child-like learning mechanisms favors offline behavioral gains. RESEARCH HIGHLIGHTS: Many essential motor skills, like walking, talking, and writing, are acquired during childhood, and it is colloquially thought that children learn better than adults. We investigated dynamics of motor skill learning in children, adolescents, and young adults. Adults displayed substantial improvements during practice that was susceptible to forgetting over time. Children displayed smaller improvements during practice that were resilient against forgetting. The distinct age-related characteristics of these processes of acquisition and consolidation suggest that skill learning relies on different mechanisms in the immature and mature central nervous system.

ChatKG: Visualizing time-series patterns aided by intelligent agents and a knowledge graph

Line-chart visualizations of temporal data enable users to identify interesting patterns for the user to inquire about. Using Intelligent Agents (IA), Visual Analytic tools can automatically uncover explicit knowledge related information to said patterns. Yet, visualizing the association of data, patterns, and knowledge is not straightforward. In this paper, we present ChatKG, a novel visual analytics strategy that allows exploratory data analysis of a Knowledge Graph that associates temporal sequences, the patterns found in each sequence, the temporal overlap between patterns, the related knowledge of each given pattern gathered from a multi-agent IA, and the IA’s suggestions of related datasets for further analysis visualized as annotations. We exemplify and informally evaluate ChatKG by analyzing the world’s life expectancy. For this, we implement an oracle that automatically extracts relevant or interesting patterns, populates the Knowledge Graph to be visualized, and, during user interaction, inquires the multi-agent IA for related information and suggests related datasets to be displayed as visual annotations. Our tests and an interview conducted showed that ChatKG is well suited for temporal analysis of temporal patterns and their related knowledge when applied to history studies.

The Characteristics of Everyday Life Safety Incidents among Vulnerable Groups

As society diversifies, everyday life safety incidents have emerged as a major social concern. Consequently, support measures for vulnerable groups who are less capable of responding to such accidents are increasingly necessary. This study is intended to diagnose the causes of everyday life safety incidents among vulnerable groups and establish preventive measures by analyzing the spatial, temporal, and variable characteristics of these accidents. The study’s findings reveal distinct spatial patterns and monthly and hourly trends in the occurrence of everyday life safety incidents, with a significant relationship between the age of the vulnerable persons and the accident type. The results of this study are expected to 1) contribute to the development of preventive measures tailored to different vulnerable groups and 2) inform regional safety policies.

A Systematic Literature Review on The Role of LSTM Networks in Capturing Temporal Dependencies in Data Mining Algorithms

Data mining plays a crucial role in extracting meaningful insights from large and complex data sets, with broad applications in sectors like finance, health care, and market analysis. Traditional techniques—such as classification, clustering, association rule mining, regression, and anomaly detection—are effective for analyzing structured data but struggle with sequential data due to the challenges of modeling temporal dependencies. Long Short Term Memory (LSTM) networks, a specialized form of Recurrent Neural Networks (RNNs), provide a solution to these challenges. By incorporating memory cells and gating mechanisms, LSTM effectively manage long-term dependencies and address issues like vanishing and exploding gradients. This paper reviews the impact of LSTM networks on data mining, analyzing over 60 key publications. By synthesizing concepts and recent advancements, the review underscores how LSTMs enhance the ability of data mining algorithms to capture and predict temporal patterns, reflecting current research trends and innovations

Validating the place of Underutilized Indigenous Vegetable (UIV) Marketers: A case of Agrarian Communities, Southwestern Nigeria

Over the years, staple crops have faced several challenges, and a step away from over-reliance on them is very important to achieve food security in Nigeria. Indeed, underutilized vegetables are usually indigenous ancient crops that are still used reasonably in local, national, and even international communities. Hence, this study validates the spatial pattern and network of underutilized indigenous vegetable (UIV) marketers in Ondo State, southwestern, Nigeria with emphasis on fluted pumpkin (Telfaria occidentalis), African eggplant (Solanum macrocarpon) and Amaranth (Amaranthus virides). A multi-stage sampling technique was used to select a total of 120 UIV marketers from 5 villages. Primary data were collected and gathered using structured questionnaires and responses from the interview were coded and analyzed with STATA and UCINET. The study further examines the factors influencing the performance of the UIV marketers and determines the predictors driving association membership using multiple linear regression and binary logistic regression, respectively. The analysis results revealed that the majority (90.83%) of the UIVs marketers are female with a large proportion of the marketers within the age range of 51-60 years. The primary occupation of most of the respondents is trading (51.67%). From the regression results, belonging to a vegetable association is not statistically significant and thus it can be concluded that being a member of a vegetable association does not affect the income of the marketers. This is in sync with the information gathered from the focus group interviews that the association only serve as a medium to get firsthand information on price, product quality, and vegetables demanded. However, from social network analysis, it can also be concluded that the major actors involved in UIV marketing are interrelated and that they transfer information between themselves with the association being the common ground for such exchange. The study recommends that the government should consciously push for the wide acceptance of vegetable cultivation and provide good network roads in rural areas.