keyword
https://read.qxmd.com/read/38534860/a-two-layer-self-organizing-map-with-vector-symbolic-architecture-for-spatiotemporal-sequence-learning-and-prediction
#1
JOURNAL ARTICLE
Thimal Kempitiya, Damminda Alahakoon, Evgeny Osipov, Sachin Kahawala, Daswin De Silva
We propose a new nature- and neuro-science-inspired algorithm for spatiotemporal learning and prediction based on sequential recall and vector symbolic architecture. A key novelty is the learning of spatial and temporal patterns as decoupled concepts where the temporal pattern sequences are constructed using the learned spatial patterns as an alphabet of elements. The decoupling, motivated by cognitive neuroscience research, provides the flexibility for fast and adaptive learning with dynamic changes to data and concept drift and as such is better suited for real-time learning and prediction...
March 13, 2024: Biomimetics
https://read.qxmd.com/read/38531903/cancer-incidence-trends-in-new-york-state-and-associations-with-common-population-level-exposures-2010-2018-an-ecological-study
#2
JOURNAL ARTICLE
Haokun Yuan, Rebecca D Kehm, Josephine M Daaboul, Susan E Lloyd, Jasmine A McDonald, Lina Mu, Parisa Tehranifar, Kai Zhang, Mary Beth Terry, Wan Yang
The impact of common environmental exposures in combinations with socioeconomic and lifestyle factors on cancer development, particularly for young adults, remains understudied. Here, we leveraged environmental and cancer incidence data collected in New York State at the county level to examine the association between 31 exposures and 10 common cancers (i.e., lung and bronchus, thyroid, colorectal, kidney and renal pelvis, melanoma, non-Hodgkin lymphoma, and leukemia for both sexes; corpus uteri and female breast cancer; prostate cancer), for three age groups (25-49, 50-69, and 70-84 year-olds)...
March 26, 2024: Scientific Reports
https://read.qxmd.com/read/38531712/resilience-and-vulnerability-distinct-concepts-to-address-global-change-in-forests
#3
REVIEW
Judit Lecina-Diaz, Jordi Martínez-Vilalta, Francisco Lloret, Rupert Seidl
Resilience and vulnerability are important concepts to understand, anticipate, and manage global change impacts on forest ecosystems. However, they are often used confusingly and inconsistently, hampering a synthetic understanding of global change, and impeding communication with managers and policy-makers. Both concepts are powerful and have complementary strengths, reflecting their different history, methodological approach, components, and spatiotemporal focus. Resilience assessments address the temporal response to disturbance and the mechanisms driving it...
March 25, 2024: Trends in Ecology & Evolution
https://read.qxmd.com/read/38531357/spatial-patterning-controls-neuron-numbers-in-the-drosophila-visual-system
#4
JOURNAL ARTICLE
Jennifer A Malin, Yen-Chung Chen, Félix Simon, Evelyn Keefer, Claude Desplan
Neurons must be made in the correct proportions to communicate with the appropriate synaptic partners and form functional circuits. In the Drosophila visual system, multiple subtypes of distal medulla (Dm) inhibitory interneurons are made in distinct, reproducible numbers-from 5 to 800 per optic lobe. These neurons are born from a crescent-shaped neuroepithelium called the outer proliferation center (OPC), which can be subdivided into specific domains based on transcription factor and growth factor expression...
March 19, 2024: Developmental Cell
https://read.qxmd.com/read/38528343/where-the-small-things-are-modelling-edge-effects-on-mouse-lemur-population-density-and-distribution-in-northwestern-madagascar
#5
JOURNAL ARTICLE
Fernando Mercado Malabet, Malcolm Ramsay, Coral Chell, Bertrand Andriatsitohaina, Ute Radespiel, Shawn Lehman
Edge effects result from the penetration to varying depths and intensities, of abiotic and biotic conditions from the surrounding non-forest matrix into the forest interior. Although 70% of the world's forests are within 1 km of a forest edge, making edge effects a dominant feature of most forest habitats, there are few empirical data on inter-site differences in edge responses in primates. We used spatially explicit capture-recapture (SECR) models to determine spatial patterns of density for two species of mouse lemurs (Microcebus murinus and Microcebus ravelobensis) in two forest landscapes in northwestern Madagascar...
March 25, 2024: American Journal of Primatology
https://read.qxmd.com/read/38527809/dissociable-contributions-of-the-medial-parietal-cortex-to-recognition-memory
#6
JOURNAL ARTICLE
Seth R Koslov, Joseph W Kable, Brett L Foster
Human neuroimaging studies of episodic memory retrieval routinely observe the engagement of specific cortical regions beyond the medial temporal lobe. Of these, medial parietal cortex (MPC) is of particular interest given its distinct functional characteristics during different types of retrieval tasks. Specifically, while recognition and autobiographical recall tasks are both used to probe episodic retrieval, these paradigms consistently drive distinct spatial patterns of response within MPC. However, other studies have emphasized alternate MPC functional dissociations in terms of brain network connectivity profiles or stimulus category selectivity...
March 25, 2024: Journal of Neuroscience
https://read.qxmd.com/read/38526888/breast-cancer-classification-from-digital-pathology-images-via-connectivity-aware-graph-transformer
#7
JOURNAL ARTICLE
Kang Wang, Feiyang Zheng, Lan Cheng, Hong-Ning Dai, Qi Dou, Jing Qin
Automated classification of breast cancer subtypes from digital pathology images has been an extremely challenging task due to the complicated spatial patterns of cells in the tissue micro-environment. While newly proposed graph transformers are able to capture more long-range dependencies to enhance accuracy, they largely ignore the topological connectivity between graph nodes, which is nevertheless critical to extract more representative features to address this difficult task. In this paper, we propose a novel connectivity-aware graph transformer (CGT) for phenotyping the topology connectivity of the tissue graph constructed from digital pathology images for breast cancer classification...
March 25, 2024: IEEE Transactions on Medical Imaging
https://read.qxmd.com/read/38524798/modeling-the-spatial-patterns-of-antenatal-care-utilization-in-nigeria-with-inference-based-on-p%C3%A3-lya-gamma-mixtures
#8
JOURNAL ARTICLE
Osafu Augustine Egbon, Ezra Gayawan
Despite the vast advantages of making antenatal care visits, the service utilization among pregnant women in Nigeria is suboptimal. A five-year monitoring estimate indicated that about 24% of the women who had live births made no visit. The non-utilization induced excessive zeroes in the outcome of interest. Thus, this study adopted a zero-inflated negative binomial model within a Bayesian framework to identify the spatial pattern and the key factors hindering antenatal care utilization in Nigeria. We overcome the intractability associated with posterior inference by adopting a Pólya-Gamma data-augmentation technique to facilitate inference...
2024: Journal of Applied Statistics
https://read.qxmd.com/read/38523306/applying-common-spatial-pattern-and-convolutional-neural-network-to-classify-movements-via-eeg-signals
#9
JOURNAL ARTICLE
Sepideh Zolfaghari, Tohid Yousefi Rezaii, Saeed Meshgini
Developing an electroencephalography (EEG)-based brain-computer interface (BCI) system is crucial to enhancing the control of external prostheses by accurately distinguishing various movements through brain signals. This innovation can provide comfortable circumstances for the populace who have movement disabilities. This study combined the most prospering methods used in BCI systems, including one-versus-rest common spatial pattern (OVR-CSP) and convolutional neural network (CNN), to automatically extract features and classify eight different movements of the shoulder, wrist, and elbow via EEG signals...
March 24, 2024: Clinical EEG and Neuroscience: Official Journal of the EEG and Clinical Neuroscience Society (ENCS)
https://read.qxmd.com/read/38523107/impact-of-different-grade-roads-on-ecological-networks-a-case-study-of-fuzhou-city-china
#10
JOURNAL ARTICLE
Ding-Yi Jia, Rong-Peng Guo, Wei-Guo Qiu, Zhi-Long Wu, Sen Lin, Xi-Sheng Hu
The expansion of roads exacerbates the fragmentation of ecological networks and obstructs landscape connectivity. Scientific analysis of the impacts of different grades of roads on landscape connectivity and ecological networks is crucial for guiding road planning and ecological conservation. Based on the data of 2020 road network, land cover types, and digital elevation models, we used morphological spatial pattern analysis and circuit theory to construct ecological networks within different species dispersal distances (1, 3, 5, 10 km) in Fuzhou...
February 2024: Ying Yong Sheng Tai Xue Bao, the Journal of Applied Ecology
https://read.qxmd.com/read/38523104/ecosystem-service-tradeoff-and-synergistic-relationship-in-the-yellow-river-delta-high-efficiency-eco-economic-zone
#11
JOURNAL ARTICLE
Chang Lu, Xue-Qin Cai, Can-Shu Hao, Yu-Zhen Liu, Zhi-Yu Wang, Ya-Nan Ma
Exploring the tradeoff and synergy relationship among ecosystem services in the Yellow River Delta High-Efficiency Eco-Economic Zone is of great practical significance for regional ecosystem service function zoning and high-quality development. Using the InVEST model, spatial auto-correlation and trade-off synergism (ESTD) model, we analyzed the spatial and temporal variations of five ecosystem services (habitat quality, carbon storage, soil conservation, water conservation, and water purification), as well as their trade-off and synergistic relationships at the township scale from 2000 to 2020...
February 2024: Ying Yong Sheng Tai Xue Bao, the Journal of Applied Ecology
https://read.qxmd.com/read/38523094/spatial-distribution-pattern-and-correlation-of-dominant-populations-in-the-shrub-layer-of-fengshui-forest-in-leizhou-peninsula-china
#12
JOURNAL ARTICLE
Cai Chen, Guang-da Tang, Xiao-Quan Dong, Song-Jun Xu
To elucidate the spatial patterns of understory species in fragmented forests adjacent to human settlements, we examined the spatial distribution and intraspecific correlations of three dominant species Mallotus philippensis , Dasymashalon trichophorum , and Psychotria rubra by employing point pattern analysis, which were the top three in terms of importance value in the shrub layer of Fengshui forest in Leizhou Peninsula, Guangdong. The results showed that all the three species were mainly aggregated at the scale of 0-25 m, especially for young trees...
February 2024: Ying Yong Sheng Tai Xue Bao, the Journal of Applied Ecology
https://read.qxmd.com/read/38521404/individual-differences-in-the-neural-representation-of-cooperation-and-competition
#13
JOURNAL ARTICLE
G G Knyazev, A N Savostyanov, A V Bocharov, A E Saprigyn
Much evidence links the Big Five's agreeableness to a propensity for cooperation and aggressiveness to a propensity for competition. However, the neural basis for these associations is unknown. In this functional magnetic resonance imaging study, using multivariate pattern analysis of data recorded during a computer game in which participants were required to construct target patterns either in cooperation or in competition with another person, we sought to determine how individual differences in neural representations of cooperative and competitive behavior relate to individual differences in agreeableness and aggressiveness...
March 21, 2024: Neuroscience Letters
https://read.qxmd.com/read/38521267/predicting-particulate-matter-nitrogen-dioxide-and-ozone-across-great-britain-with-high-spatiotemporal-resolution-based-on-random-forest-models
#14
JOURNAL ARTICLE
Jiaxin Chen, Shengqiang Zhu, Peng Wang, Zhonghua Zheng, Su Shi, Xinyue Li, Chang Xu, Kexin Yu, Renjie Chen, Haidong Kan, Hongliang Zhang, Xia Meng
In Great Britain, limited studies have employed machine learning methods to predict air pollution especially ozone (O3 ) with high spatiotemporal resolution. This study aimed to address this gap by developing random forest models for four key pollutants (fine and inhalable particulate matter [PM2.5 and PM10 ], nitrogen dioxide [NO2 ] and O3 ) by integrating multiple-source predictors at a daily level and 1-km resolution. The out-of-bag R2 (root mean squared error, RMSE) between predictions from models and measurements from monitoring stations in 2006-2013 was 0...
March 21, 2024: Science of the Total Environment
https://read.qxmd.com/read/38520364/thalamic-contributions-to-psychosis-susceptibility-evidence-from-co-activation-patterns-accounting-for-intra-seed-spatial-variability-%C3%AE-caps
#15
JOURNAL ARTICLE
Farnaz Delavari, Corrado Sandini, Nada Kojovic, Luigi F Saccaro, Stephan Eliez, Dimitri Van De Ville, Thomas A W Bolton
The temporal variability of the thalamus in functional networks may provide valuable insights into the pathophysiology of schizophrenia. To address the complexity of the role of the thalamic nuclei in psychosis, we introduced micro-co-activation patterns (μCAPs) and employed this method on the human genetic model of schizophrenia 22q11.2 deletion syndrome (22q11.2DS). Participants underwent resting-state functional MRI and a data-driven iterative process resulting in the identification of six whole-brain μCAPs with specific activity patterns within the thalamus...
April 2024: Human Brain Mapping
https://read.qxmd.com/read/38517095/revealing-early-spatial-patterns-of-cellular-responsivity-in-fiber-reinforced-microenvironments
#16
JOURNAL ARTICLE
Saitheja A Pucha, Maddie Hasson, Hanna Solomon, Gail E McColgan, Jennifer L Robinson, Sebastián L Vega, Jay M Patel
Due to responses to reviewer comments, we are slightly above the word limit for the abstract. The revised version is included in the main manuscript text. Please let us know if this is an issue, and we can revise to try to get under the word limit. Thank you.
March 22, 2024: Tissue Engineering. Part A
https://read.qxmd.com/read/38515959/prediction-of-tuberculosis-from-lung-tissue-images-of-diversity-outbred-mice-using-jump-knowledge-based-cell-graph-neural-network
#17
JOURNAL ARTICLE
Vasundhara Acharya, Diana Choi, BüLENT Yener, Gillian Beamer
Tuberculosis (TB), primarily affecting the lungs, is caused by the bacterium Mycobacterium tuberculosis and poses a significant health risk. Detecting acid-fast bacilli (AFB) in stained samples is critical for TB diagnosis. Whole Slide (WS) Imaging allows for digitally examining these stained samples. However, current deep-learning approaches to analyzing large-sized whole slide images (WSIs) often employ patch-wise analysis, potentially missing the complex spatial patterns observed in the granuloma essential for accurate TB classification...
2024: IEEE Access: Practical Innovations, Open Solutions
https://read.qxmd.com/read/38514500/optimizing-motion-imagery-classification-with-limited-channels-using-the-common-spatial-pattern-based-integrated-algorithm
#18
JOURNAL ARTICLE
Shishi Chen, Xugang Xi, Ting Wang, Hangcheng Li, Maofeng Wang, Lihua Li, Zhong Lü
The extraction of effective classification features from electroencephalogram (EEG) signals in motor imagery is a popular research topic. The Common Spatial Pattern (CSP) algorithm is widely employed in this field. However, the performance of the traditional CSP method depends significantly on the choice of a specific frequency band and channel number of EEG data. Furthermore, inter-class variance among these frequency bands and the limited number of available EEG channels can adversely affect the CSP algorithm's ability to extract meaningful features from the relevant signal frequency bands...
March 22, 2024: Medical & Biological Engineering & Computing
https://read.qxmd.com/read/38513859/comprehensive-risk-assessment-of-typhoon-disasters-in-china-s-coastal-areas-based-on-multi-source-geographic-big-data
#19
JOURNAL ARTICLE
Zhenkang Wang, Nan Xia, Xin Zhao, XianKai Ji, Jiechen Wang
Typhoons can bring substantial casualties and economic ramifications, and effective prevention strategies necessitate a comprehensive risk assessment. Nevertheless, existing studies on its comprehensive risk assessment are characterized by coarse spatial scales, limited incorporation of geographic big data, and rarely considering disaster mitigation capacity. To address these problems, this study combined multi-source geographic big data to develop the Comprehensive Risk Assessment Model (CRAM). The model constructed 17 indicators from 4 categories of factors, including exposure, vulnerability, hazard, and mitigation capacity...
March 19, 2024: Science of the Total Environment
https://read.qxmd.com/read/38513587/land-use-simulation-for-synergistic-pollution-and-carbon-reduction-scenario-analysis-and-policy-implications
#20
JOURNAL ARTICLE
Luyan Wu, Yanhu He, Qian Tan, Yanhui Zheng
Simulations of sustainable land use and management are required to achieve targets to reduce pollution and carbon emissions. Limited research has been conducted on synergistic pollution and carbon reduction (SPCR) in land-use simulations. This study proposed a framework for land-use simulation focused on SPCR. The non-dominated sorting genetic algorithm (NSGA-Ⅱ) and the entropy weight-based technique for order of preference by similarity to an ideal solution (TOPSIS) were used to optimize the land-use structure according to minimum net carbon, nitrogen, and phosphorus emissions...
March 20, 2024: Journal of Environmental Management
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