Patterns of Grewia (Malvaceae) diversity across geographical scales in Africa and Madagascar.

BACKGROUND AND AIMS: Quantifying spatial species richness is useful to describe biodiversity patterns across broad geographical areas, especially in large, poorly known plant groups. We explore patterns and predictors of species richness across Africa in one such group, the palaeotropical genus Grewia L. (Malvaceae). METHODS: Grewia species richness was quantified by extracting herbarium records from GBIF and Tropicos and creating geographical grids at varying spatial scales. We assessed predictors of species richness using spatial regression models with 30 environmental variables. We explored species co-occurrence in Madagascar at finer resolutions using Schoener's index and compared species range sizes and International Union for Conservation of Nature status among ecoregions. Lastly, we derived a trait matrix for a subset of species found in Madagascar to characterize morphological diversity across space. KEY RESULTS: Grewia species occur in 50 countries in Africa, with the highest number of species in Madagascar (93, with 80 species endemic). Species richness is highest in Madagascar, with ≤23 Grewia species in a grid cell, followed by coastal Tanzania/Kenya (≤13 species) and northern South Africa and central Angola (11 species each). Across Africa, higher species richness was predicted by variables related to aridity. In Madagascar, a greater range in environmental variables best predicted species richness, consistent with geographical grid cells of highest species richness occurring near biome/ecoregion transitions. In Madagascar, we also observe increasing dissimilarity in species composition with increasing geographical distance. CONCLUSIONS: The spatial patterns and underlying environmental predictors that we uncover in Grewia represent an important step in our understanding of plant distribution and diversity patterns across Africa. Madagascar boasts nearly twice the Grewia species richness of the second most species-rich country in Africa, which might be explained by complex topography and environmental conditions across small spatial scales.

Segregation and the pandemic: The dynamics of daytime social diversity during COVID-19 in Greater Stockholm.

In this study, we set out to understand how the changes in daily mobility of people during the first wave of the COVID-19 pandemic in spring 2020 influenced daytime spatial segregation. Rather than focusing on spatial separation, we approached this task from the perspective of daytime socio-spatial diversity - the degree to which people from socially different neighbourhoods share urban space during the day. By applying mobile phone data from Greater Stockholm, Sweden, the study examines weekly changes in 1) daytime social diversity across different types of neighbourhoods, and 2) population groups' exposure to diversity in their main daytime activity locations. Our findings show a decline in daytime diversity in neighbourhoods when the pandemic broke out in mid-March 2020. The decrease in diversity was marked in urban centres, and significantly different in neighbourhoods with different socio-economic and ethnic compositions. Moreover, the decrease in people's exposure to diversity in their daytime activity locations was even more profound and long-lasting. In particular, isolation from diversity increased more among residents of high-income majority neighbourhoods than of low-income minority neighbourhoods. We conclude that while some COVID-19-induced changes might have been temporary, the increased flexibility in where people work and live might ultimately reinforce both residential and daytime segregation.

Efficient MIMO Configuration for Bi-Directional Vertical FSO Link with Multiple Beam Induced Pointing Error.

We proposed the statistical misalignment model and the power-efficient configuration of transceivers for bi-directional multi-input and multi-output (MIMO) based vertical free space optical (FSO) links. Spatial diversity based MIMO FSO systems could be used to mitigate atmospheric fading issues. However, the increased number of channels can cause additional pointing error in pointing, acquisition and tracking (PAT) systems. The statistical misalignment model for detecting misalignment error is derived from the multiple transceivers. For the bi-directional characteristics of non-terrestrial back-haul networks, transmission performance is down-leveled to the worse in the asymmetric MIMO configuration of transceivers. The symmetric structure can mitigate the effect of increased pointing error to improve transmission performance. The proposed technique can be applied to the design of power-efficient FSO systems for non-terrestrial wireless back-haul networks.

Semi-Supervised Nonnegative Matrix Factorization of Wide-Field Fluorescence Microscopic Images for Tissue Diagnosis.

This study tests the use of a constrained nonnegative matrix factorization (NMF) algorithm to explore the comparatively new field of chemometric microscopy to support tissue diagnosis. The algorithm can extract the spectral signature and the absolute concentration map of endogenous fluorophores from wide-field microscopic images. The resultant data distinguished normal and fibrous calvarial tissues, based on the changes in their spectral signatures. The absolute concentration map of endogenous fluorophores, nicotinamide adenine dinucleotide (NADH), flavin adenine dinucleotide (FAD), and lipofuscin were derived from microscopic images and compared with the fluorescence from pure fluorophores. While the absolute concentration of NADH increased, the same of FAD and lipofuscin decreased from a normal to fibrous calvarial condition. An increase in the optical redox ratio, possibly due to the metabolic changes during the development of fibrosis, was observed. Differentiating tissue types using the absolute concentration map was found to be considerably more precise than that achievable with relative concentration. The quantification of fluorophores with reference to the absolute concentration map can eliminate uncertainties due to system responses or measurement details, thereby generating more biologically apposite data. Wide-field microscopy augmented with a constrained NMF algorithm could emerge as an advanced diagnostic tool, potentially heralding the emergence of chemometric microscopy.

Doubling the Accuracy of Indoor Positioning: Frequency Diversity.

Determination of indoor position based on fine time measurement (FTM) of the round trip time (RTT) of a signal between an initiator (smartphone) and a responder (Wi-Fi access point) enables a number of applications. However, the accuracy currently attainable-standard deviations of 1-2 m in distance measurement under favorable circumstances-limits the range of possible applications. An emergency worker, for example, may not be able to unequivocally determine on which floor someone in need of help is in a multi-story building. The error in position depends on several factors, including the bandwidth of the RF signal, delay of the signal due to the high relative permittivity of construction materials, and the geometry-dependent "noise gain" of position determination. Errors in distance measurements have unusal properties that are exposed here. Improvements in accuracy depend on understanding all of these error sources. This paper introduces "frequency diversity," a method for doubling the accuracy of indoor position determination using weighted averages of measurements with uncorrelated errors obtained in different channels. The properties of this method are verified experimentally with a range of responders. Finally, different ways of using the distance measurements to determine indoor position are discussed and the Bayesian grid update method shown to be more useful than others, given the non-Gaussian nature of the measurement errors.

Compressive Sensing Based Radio Tomographic Imaging with Spatial Diversity.

Radio tomographic imaging (RTI) has emerged as a promising device-free localization technology for locating the targets with no devices attached. RTI deduces the location information from the reconstructed attenuation image characterizing target-induced spatial loss of radio frequency measurements in the sensing area. In cluttered indoor environments, RF measurements of wireless links are corrupted by multipath effects and thus less robust to achieve a high localization accuracy for RTI. This paper proposes to improve the quality of measurements by using spatial diversity. The key insight is that, with multiple antennae equipped, due to small-scale multipath fading, RF measurement variation of each antenna pair behaves differently. Therefore, spatial diversity can provide more reliable and strong measurements in terms of link quality. Moreover, to estimate the location from the image more precisely and make the image more identifiable, we propose using a new reconstruction regularization linearly combining the sparsity and correlation inherent in the image. The proposed reconstruction method can remarkably reduce the image noise and enhance the imaging accuracy especially in the case of a few available measurements. Indoor experimental results demonstrate that compared to existing RTI improvement methods, our RTI solution can reduce the root-mean-square localization error at least 47% while also improving the imaging performance.

Interference Range-Reduced Cooperative Multiple Access with Optimal Relay Selection for Large Scale Wireless Networks.

Cooperative communication improves the link throughput of wireless networks through spatial diversity. However, it reduces the frequency reuse of the entire network due to the enlarged link interference range introduced by each helper. In this paper, we propose a cooperative medium access control (MAC) protocol with optimal relay selection (ORS-CMAC) for multihop, multirate large scale networks, which can reduce the interference range and improve the network throughput. Then, we investigate the performance gain achieved by these two competitive factors, i.e., the spatial frequency reuse gain and spatial diversity gain, in large scale wireless networks. The expressions of maximum network throughput for direct transmissions and cooperative transmissions in the whole network are derived as a function of the number of concurrent transmission links, data packet length, and average packet transmission time. Simulation results validate the effectiveness of the theoretical results. The theoretical and simulation results show that the helper can reduce the spatial frequency reuse slightly, and spatial diversity gain can compensate for the decrease of the spatial frequency reuse, thereby improving the network throughput from the viewpoint of the whole network.

Community Composition and Diversity of Coastal Bacterioplankton Assemblages in Lakes Michigan, Erie, and Huron.

The Laurentian Great Lakes, including Lakes Superior, Michigan, Huron, Erie, and Ontario, located in the eastern part of North America are considered the largest of freshwater lakes in the world; however, very little is known about the diversity and distribution of indigenous microbial assemblages within these vast bodies of freshwater systems. Therefore, to delineate the microbial structure and community composition in these aquatic environments, combinations of high-throughput sequencing and fluorescent in situ hybridization (FISH) approaches were utilized to quantitatively characterize the occurrence, diversity, and distribution of bacterioplankton assemblages in six different sites located along the coastal regions of Lakes Michigan, Huron, and Erie. Phylogenetic examination showed a diverse bacterial community belonging to 11 different taxonomic groups. Pyrosequencing results revealed that the majority of the sequences were clustered into four main groups, i.e., Proteobacteria, Bacteriodetes, Actinobacteria, and Cyanobacteria, while fluorescent in situ hybridization also showed the numerical dominance of members of the Gammaproteobacteria and the Cytophaga-Flavobacterium in the six lake sites examined. Overall, the assemblages were shown to be quite diverse in distribution among the lake sites examined, comprising mostly of various heterotrophic populations, with the exception of the Lake Erie-Sandusky Bay site with more than 50% domination by autotrophic Cyanobacteria. This indicates that combinations of factors including water chemistry and various anthropogenic disturbances as well as the lake morphometric characteristics are probably influencing the community structure and diversity of the bacterial assemblages within the systems.

A Novel Device-Free Counting Method Based on Channel Status Information.

Crowd counting is of significant importance for numerous applications, e.g., urban security, intelligent surveillance and crowd management. Existing crowd counting methods typically require specialized hardware deployment and strict operating conditions, thereby hindering their widespread application. To acquire a more effective crowd counting approach, a device-free counting method based on Channel Status Information (CSI) is proposed. The wavelet domain denoising is introduced to mitigate environment noise. Furthermore, the amplitude or phase covariance matrix is extracted as the eigenmatrix. Moreover, both the spatial diversity and frequency diversity are leveraged to improve detection robustness. At the same experimental environment, the accuracy of the proposed CSI-based method is compared with a renowned crowd counting one, i.e., Electronic Frog Eye: Counting Crowd Using WiFi (FCC). The experimental results reveal an accuracy improvement of 30% over FCC.

Coherent and Noncoherent Joint Processing of Sonar for Detection of Small Targets in Shallow Water.

A coherent-noncoherent joint processing framework is proposed for active sonar to combine diversity gain and beamforming gain for detection of a small target in shallow water environments. Sonar utilizes widely-spaced arrays to sense environments and illuminate a target of interest from multiple angles. Meanwhile, it exploits spatial diversity for time-reversal focusing to suppress reverberation, mainly strong bottom reverberation. For enhancement of robustness of time-reversal focusing, an adaptive iterative strategy is utilized in the processing framework. A probing signal is firstly transmitted and echoes of a likely target are utilized as steering vectors for the second transmission. With spatial diversity, target bearing and range are estimated using a broadband signal model. Numerical simulations show that the novel sonar outperforms the traditional phased-array sonar due to benefits of spatial diversity. The effectiveness of the proposed framework has been validated by localization of a small target in at-lake experiments.

UCMAC: A Cooperative MAC Protocol for Underwater Wireless Sensor Networks.

This paper proposes a cooperative medium access control (MAC) protocol for underwater wireless sensor networks (UWSNs) named UCMAC, which fundamentally benefits from cooperative communication. In UCMAC, a source identifies cooperators and provides its destination with a list of the cooperators while also delineating their proximity to the destination. For erroneous reception of data packets, the destination then requests retransmission to the cooperators in a closest-one-first manner. A designated cooperator transmits the buffered data packet it has successfully overheard from the source or other cooperators. A signaling procedure and the various waiting times of the nodes are carefully designed to address the overheads that stem from cooperation. Through computer simulation, this paper evaluates UCMAC in terms of system throughput, latency, single-hop packet delivery ratio (PDR), and energy efficiency. The results show that UCMAC performs better than existing schemes, including MACA-U and CD-MACA.

Spatial Heterogeneity Analysis: Introducing a New Form of Spatial Entropy.

Distinguishing and characterizing different landscape patterns have long been the primary concerns of quantitative landscape ecology. Information theory and entropy-related metrics have provided the deepest insights in complex system analysis, and have high relevance in landscape ecology. However, ideal methods to compare different landscape patterns from an entropy view are still lacking. The overall aim of this research is to propose a new form of spatial entropy (Hs) in order to distinguish and characterize different landscape patterns. Hs is an entropy-related index based on information theory, and integrates proximity as a key spatial component into the measurement of spatial diversity. Proximity contains two aspects, i.e., total edge length and distance, and by including both aspects gives richer information about spatial pattern than metrics that only consider one aspect. Thus, Hs provides a novel way to study the spatial structures of landscape patterns where both the edge length and distance relationships are relevant. We compare the performances of Hs and other similar approaches through both simulated and real-life landscape patterns. Results show that Hs is more flexible and objective in distinguishing and characterizing different landscape patterns. We believe that this metric will facilitate the exploration of relationships between landscape patterns and ecological processes.

Diversity and distribution of bamboo-feeding true bugs in China.

The Bambusoideae subfamily, originating in the late Cretaceous, has evolved to include over 1500 species globally. Notably, China hosts the richest diversity of Bambusoideae, with 728 species documented. After a long period of coevolution, plenty of animals could feed on these plants rich in cellulose and lignin. As an important group of pests and participants in the ecosystem, bamboo-feeding true bugs (BFTBs, or bamboo-feeding Heteropteran insects) have attracted the attention of researchers. However, the diversity and distribution of BFTBs still lack systematic and generalized research. In this study, we reviewed the BFTBs in China and simulated the diversity pattern and the driving forces of this pattern. A list of 36 genera with 69 species of BFTBs in China was obtained through paper review and field surveys. And their bamboo-feeding habit had multiple independent origins. The spatial diversity pattern showed that the biodiversity hotspots of BFTBs are located in and around the tropics of southern China. Environmental driving force analysis showed that the minimum temperature of coldest month and annual precipitation were the dominant environmental factors shaping the spatial diversity of BFTBs. Our work quantified the diversity and distribution of BFTBs in China, providing fundamental data support for pest control and evolutionary research.

A high-dimensional, multi-transceiver channel state information dataset for enhanced human activity recognition.

Human Activity Recognition (HAR) has emerged as a critical research area due to its extensive applications in various real-world domains. Numerous CSI-based datasets have been established to support the development and evaluation of advanced HAR algorithms. However, existing CSI-based HAR datasets are frequently limited by a dearth of complexity and diversity in the activities represented, hindering the design of robust HAR models. These limitations typically manifest as a narrow focus on a limited range of activities or the exclusion of factors influencing real-world CSI measurements. Consequently, the scarcity of diverse training data can impede the development of efficient HAR systems. To address the limitations of existing datasets, this paper introduces a novel dataset that captures spatial diversity through multiple transceiver orientations over a high dimensional space encompassing a large number of subcarriers. The dataset incorporates a wider range of real-world factors including extensive activity range, a spectrum of human movements (encompassing both micro-and macro-movements), variations in body composition, and diverse environmental conditions (noise and interference). The experiment is performed in a controlled laboratory environment with dimensions of 5 m (width) × 8 m (length) × 3 m (height) to capture CSI measurements for various human activities. Four ESP32-S3-DevKitC-1 devices, configured as transceiver pairs with unique Media Access Control (MAC) addresses, collect CSI data according to the Wi-Fi IEEE 802.11n standard. Mounted on tripods at a height of 1.5 m, the transmitter devices (powered by external power banks) positioned at north and east send multiple Wi-Fi beacons to their respective receivers (connected to laptops via USB for data collection) located at south and west. To capture multi-perspective CSI data, all six participants sequentially performed designated activities while standing in the centre of the tripod arrangement for 5 s per sample. The system collected approximately 300-450 packets per sample for approximately 1200 samples per activity, capturing CSI information across the 166 subcarriers employed in the Wi-Fi IEEE 802.11n standard. By leveraging the richness of this dataset, HAR researchers can develop more robust and generalizable CSI-based HAR models. Compared to traditional HAR approaches, these CSI-based models hold the promise of significantly enhanced accuracy and robustness when deployed in real-world scenarios. This stems from their ability to capture the nuanced dynamics of human movement through the analysis of wireless channel characteristic from different spatial variations (utilizing two-diagonal ESP32 transceivers configuration) with higher degree of dimensionality (166 subcarriers).

Synergistic effects of succession and microtopography of moraine on the fungal spatial diversity in a glacier forefield.

Primary succession and microtopography result in environmental changes and are important processes influencing the community assembly of soil fungi in the Arctic region. In glacier forefields that contain a series of moraine ridges, both processes contribute synchronously to fungal spatial diversity. To reveal the synergistic effects of succession and microtopography, we investigated the fungal community structure and environmental variables in the moraines of the Arklio Glacier, Ellesmere Island. The study sites were established at four locations from the top to the bottom of the ridge slope within each of the three moraine ridges of different post-glacial ages. The location-dependent community composition was equally diverse in both the initial and later stages of succession, suggesting that successional time could alter the effects of microtopography on the fungal community. Moreover, our results suggest that fungal communities at different locations follow different successional trajectories, even if they have passed through the same time lapse. Such a synergistic effect of succession and microtopography of moraines does not allow for parallel changes in fungal communities among moraines or among locations, suggesting that the moraine series contributes substantially to fungal spatial diversity in the glacier forefield.

Environmental and topographic drivers of amphibian phylogenetic diversity and endemism in the Iberian Peninsula.

Understanding the ecological and evolutionary processes driving biodiversity patterns and allowing their persistence is of utmost importance. Many hypotheses have been proposed to explain spatial diversity patterns, including water-energy availability, habitat heterogeneity, and historical climatic refugia. The main goal of this study is to identify if general spatial drivers of species diversity patterns of phylogenetic diversity (PD) and phylogenetic endemism (PE) at the global scale are also predictive of PD and PE at regional scales, using Iberian amphibians as a case study. Our main hypothesis assumes that topography along with contemporary and historical climate are drivers of phylogenetic diversity and endemism, but that the strength of these predictors may be weaker at the regional scale than it tends to be at the global scale. We mapped spatial patterns of Iberian amphibians' phylogenetic diversity and endemism, using previously published phylogenetic and distribution data. Furthermore, we compiled spatial data on topographic and climatic variables related to the water-energy availability, topography, and historical climatic instability hypotheses. To test our hypotheses, we used Spatial Autoregressive Models and selected the best model to explain diversity patterns based on Akaike Information Criterion. Our results show that, out of the variables tested in our study, water-energy availability and historical climate instability are the most important drivers of amphibian diversity in Iberia. However, as predicted, the strength of these predictors in our case study is weaker than it tends to be at global scales. Thus, additional drivers should also be investigated and we suggest caution when interpreting these predictors as surrogates for different components of diversity.

Origami Microwave Imaging Array: Metasurface Tiles on a Shape-Morphing Surface for Reconfigurable Computational Imaging.

Origami is the art of paper folding that allows a single flat piece of paper to assume different 3D shapes depending on the fold patterns and the sequence of folding. Using the principles of origami along with computation imaging technique the authors demonstrate a versatile shape-morphing microwave imaging array with reconfigurable field-of-view and scene-adaptive imaging capability. Microwave/millimeter-wave based array imaging systems are expected to be the workhorse for sensory perception of future autonomous intelligent systems. The imaging capability of a planar array-based systems operating in complex scattering conditions have limited field-of-view and lack the ability to adaptively reconfigure resolution. To overcome this, here, deviations from planarity and isometry are allowed, and a shape-morphing computational imaging system is demonstrated. Implemented on a reconfigurable Waterbomb origami surface with 22 active metasurface panels that radiate near-orthogonal modes across 17-27 GHz, capability to image complex 3D objects in full details minimizing the effects of specular reflections in diffraction-limited sparse imaging with scene adaptability, reconfigurable cross-range resolution, and field-of-view is demonstrated. Such electromagnetic origami surfaces, through simultaneous surface shape-morphing ability (potentially with shape-shifting electronic materials) and electromagnetic field programmability, opens up new avenues for intelligent and robust sensing and imaging systems for a wide range of applications.

Realization of microbial community stratification for single-stage nitrogen removal in a sequencing batch biofilter granular reactor.

A permanent microbial stratified nitrogen removal system coupling anammox with partial nitrification (SNAP) in a sequencing batch biofilter granular reactor (SBBGR) was successfully constructed for the treatment of ammonia-rich wastewater. With a nitrogen loading rate of 0.1kgNm-3·d-1, the maximal ammonia and total nitrogen removal efficiencies could reach up to 96.08% and 84.86% on day 108, respectively. The pH, DO profiles revealed a switch of functional species (AOB and anammox) at a typical intermittent aeration cycle. qPCR and high throughput analyses certified a stable spatial microbial stratified community structure. Although, anammox preferred strict anaerobic environment while AOB needed oxygen, a special stratified community structure contributed to conquer this obstacle. Moreover, Bacteroidet, Chlorobi, OD1, Planctomycetes, and Proteobacteria were the dominant species in the SBBGR. Although we have predicted the possible pathways of nitrogen transformation, further studies are needed to validate the pathways in enzymology.

Associating spatial diversity features of radiologically defined tumor habitats with epidermal growth factor receptor driver status and 12-month survival in glioblastoma: methods and preliminary investigation.

We analyzed the spatial diversity of tumor habitats, regions with distinctly different intensity characteristics of a tumor, using various measurements of habitat diversity within tumor regions. These features were then used for investigating the association with a 12-month survival status in glioblastoma (GBM) patients and for the identification of epidermal growth factor receptor (EGFR)-driven tumors. T1 postcontrast and T2 fluid attenuated inversion recovery images from 65 GBM patients were analyzed in this study. A total of 36 spatial diversity features were obtained based on pixel abundances within regions of interest. Performance in both the classification tasks was assessed using receiver operating characteristic (ROC) analysis. For association with 12-month overall survival, area under the ROC curve was 0.74 with confidence intervals [0.630 to 0.858]. The sensitivity and specificity at the optimal operating point ([Formula: see text]) on the ROC were 0.59 and 0.75, respectively. For the identification of EGFR-driven tumors, the area under the ROC curve (AUC) was 0.85 with confidence intervals [0.750 to 0.945]. The sensitivity and specificity at the optimal operating point ([Formula: see text]) on the ROC were 0.76 and 0.83, respectively. Our findings suggest that these spatial habitat diversity features are associated with these clinical characteristics and could be a useful prognostic tool for magnetic resonance imaging studies of patients with GBM.

Single-Nucleotide Polymorphisms Reveal Spatial Diversity Among Clones of Yersinia pestis During Plague Outbreaks in Colorado and the Western United States.

BACKGROUND: In western North America, plague epizootics caused by Yersinia pestis appear to sweep across landscapes, primarily infecting and killing rodents, especially ground squirrels and prairie dogs. During these epizootics, the risk of Y. pestis transmission to humans is highest. While empirical models that include climatic conditions and densities of rodent hosts and fleas can predict when epizootics are triggered, bacterial transmission patterns across landscapes, and the scale at which Y. pestis is maintained in nature during inter-epizootic periods, are poorly defined. Elucidating the spatial extent of Y. pestis clones during epizootics can determine whether bacteria are propagated across landscapes or arise independently from local inter-epizootic maintenance reservoirs. MATERIAL AND METHODS: We used DNA microarray technology to identify single-nucleotide polymorphisms (SNPs) in 34 Y. pestis isolates collected in the western United States from 1980 to 2006, 21 of which were collected during plague epizootics in Colorado. Phylogenetic comparisons were used to elucidate the hypothesized spread of Y. pestis between the mountainous Front Range and the eastern plains of northern Colorado during epizootics. Isolates collected from across the western United States were included for regional comparisons. RESULTS: By identifying SNPs that mark individual clones, our results strongly suggest that Y. pestis is maintained locally and that widespread epizootic activity is caused by multiple clones arising independently at small geographic scales. This is in contrast to propagation of individual clones being transported widely across landscapes. Regionally, our data are consistent with the notion that Y. pestis diversifies at relatively local scales following long-range translocation events. We recommend that surveillance and prediction by public health and wildlife management professionals focus more on models of local or regional weather patterns and ecological factors that may increase risk of widespread epizootics, rather than predicting or attempting to explain epizootics on the basis of movement of host species that may transport plague.