spatial diversity
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Abstract Regarding climate change, the world’s most discussed issue for the last few decades, countries like Bangladesh are always noteworthy due to its susceptibility resulting from its geography, hazard proneness, and socioeconomic condition. Thus, this aimed to justify the hypothesis that Bangladesh has spatial diversity in sectors of Climate Change Vulnerability (CCV) by identifying the sectors of vulnerability and visualizing the spatial distribution of vulnerability through multivariate geospatial analysis in the GIS environment. For an integrated assessment of CCV, 38 indicators (socio-economic and biophysical) have been incorporated in the IPCC framework in raster form. Test statistics have shown Kiser-Meyer-Olkin (KMO) value is 0.73 and the p-value of Bartlett’s sphericity is 0. The principal component analysis resulted in 6 principal components with 73.52% total explained variance. Sectors of CCV are the Climatic extreme event vulnerability (PC1), Meteorological shift vulnerability (PC2), Infrastructure and demographic vulnerability (PC3), Ecological vulnerability (PC4), Flood vulnerability (PC5), and Economic vulnerability (PC6) with Cronbach’s alpha 0.90, 0.81, 0.88, 0.72, 0.72, and 0.66 respectively. Among 3 clusters (Jenk’s Natural break) of weighted averaged indices, the highly vulnerable cluster has shown that the PC1 has the highest magnitude with a score of 0.53–0.87, while the PC5 has the highest spatial coverage with 24 districts. The present study however is a new edition in climate vulnerability assessment in Bangladesh since it encompasses multivariate spatial analysis to demonstrate countrywide CCV. This study should be an important tool for setting adaptation and mitigation strategies from the root level to policymaking platforms of Bangladesh.

A signal processing approach combining beamforming with mask-informed speech enhancement was assessed by measuring sentence recognition in listeners with mild-to-moderate hearing impairment in adverse listening conditions that simulated the output of behind-the-ear hearing aids in a noisy classroom. Two types of beamforming were compared: binaural, with the two microphones of each aid treated as a single array, and bilateral, where independent left and right beamformers were derived. Binaural beamforming produces a narrower beam, maximising improvement in signal-to-noise ratio (SNR), but eliminates the spatial diversity that is preserved in bilateral beamforming. Each beamformer type was optimised for the true target position and implemented with and without additional speech enhancement in which spectral features extracted from the beamformer output were passed to a deep neural network trained to identify time-frequency regions dominated by target speech. Additional conditions comprising binaural beamforming combined with speech enhancement implemented using Wiener filtering or modulation-domain Kalman filtering were tested in normally-hearing (NH) listeners. Both beamformer types gave substantial improvements relative to no processing, with significantly greater benefit for binaural beamforming. Performance with additional mask-informed enhancement was poorer than with beamforming alone, for both beamformer types and both listener groups. In NH listeners the addition of mask-informed enhancement produced significantly poorer performance than both other forms of enhancement, neither of which differed from the beamformer alone. In summary, the additional improvement in SNR provided by binaural beamforming appeared to outweigh loss of spatial information, while speech understanding was not further improved by the mask-informed enhancement method implemented here.

Aim. Our task was to examine the relationship between the SARS–CoV–2 arrival and the number of confi rmed COVID–19 cases in the fi rst wave (period from March 4 to May 22, 2020 (unoffi cial data)), and socio–economic variables at the powiat (county) level.Methods. We were using simple statistical techniques such as data visualisation, correlation analysis, spatial clustering and multiple linear regression.Results. We showed that immigration and the logarithm of general mobility was the best predictor of SARS–CoV–2 arrival times, while emigration, industrialisation and air quality explain most of the size of the epidemic in poviats. On the other hand, infection dynamics is driven to a lesser extent by previously postulated variables such as population size and density, income or the size of the elderly population.Conclusions. Our analyses could support Polish authorities in preparation for the second wave of infections and optimal management of resources as we have provided a proposition of optimal distribution of human resources between poviats. Although this isa retrospective analysis of the initial phase of the epidemic, similar patterns could repeat in case of new variants of SARS–CoV–2 or new respiratory disease for immunologically naive populations.

Cooperative spectrum sensing improves the sensing performance of secondary users by exploiting spatial diversity in cognitive radio networks. However, the cooperation of secondary users introduces some overhead also that may degrade the overall performance of cooperative spectrum sensing.  The trade-off between cooperation gain and overhead plays a vital role in modeling cooperative spectrum sensing.  This paper considers overhead in terms of reporting energy and reporting time. We propose a cooperative spectrum sensing based coalitional game model where the utility of the game is formulated as a function of throughput gain and overhead. To achieve a rational average throughput of secondary users, the overhead incurred is to be optimized. This work emphasizes on optimization of the overhead incurred. In cooperative spectrum sensing, the large number of cooperating users improve the detection performance, on the contrary, it increases overhead too. So, to limit the maximum coalition size we propose a formulation under the constraint of the probability of false alarm. An efficient fusion center selection scheme and an algorithm to select eligible secondary users for reporting are proposed to reduce the reporting overhead. We also outline a distributed cooperative spectrum sensing algorithm using the properties of the coalition formation game and prove that the utility of the proposed game has non-transferable properties.  The simulation results show that the proposed schemes reduce the overhead of reporting without compromising the overall detection performance of cooperative spectrum sensing.

Abstract. Knowledge of the processes driving debris-flow fan evolution are critical in the support of efforts to mitigate related hazards, reduce risk to populations and infrastructure, and reconstruct the history of sediment dynamics in mountainous areas. Research on debris-flow fan development has focused on topographic controls, debris-flow volume and rheology, and the sequence of occurrence of debris flows. While these items have explained a great deal about fan formation and specifically avulsion and runout mechanisms, there is a need to further investigate other properties as they relate to debris-flow fan formative process. Here, we examined the role of debris-flow grain-size distribution on fan formation. Flume experiments were employed to examine the morphology of debris-flow fans that resulted from flows with mono- or multi-granular sediment composition with the same average grain size. All other flow characteristics were held constant. The mono-granular flows formed a symmetric-like fan morphology because there was little avulsion during the formation process. The multi-granular flows produced fans with an asymmetric morphology. Avulsions occurred on both lateral extents of the fan during the early stages of fan development and caused the runout direction to shift produce the fan asymmetry. Grain-size distribution was closely related to spatial diversity in fan morphology and stratigraphy.

The degree of connectivity among populations influences their ability to respond to natural and anthropogenic stressors. In marine systems, determining the scale, rate, and directionality of larval dispersal is therefore, central to understanding how coral metapopulations are interconnected and the degree of resiliency in the event of a localized disturbance. Understanding these source-sink dynamics is essential to guide restoration efforts and for the study of ecology and evolution in the ocean. The patterns and mechanisms of connectivity in the deep-sea (>200 m deep) are largely understudied. In this study, we investigated the spatial diversity patterns and metapopulation connectivity of the octocoral Paramuricea biscaya throughout the northern Gulf of Mexico (GoM). Paramuricea biscaya is one of the most abundant corals on the lower continental slope (between 1,200 and 2,500 m) in the GoM. The 2010 Deepwater Horizon oil spill (DWH) directly impacted populations of this species and thus are considered primary targets for restoration. We used a combination of seascape genomic analyses, high-resolution ocean circulation modeling, and larval dispersal simulations to quantify the degree of population structuring and connectivity among P. biscaya populations. Evidence supports the hypotheses that the genetic diversity of P. biscaya is structured by depth, and that larval dispersal among connected populations is asymmetric due to dominant ocean circulation patterns. Our results suggest that there are intermediate unsampled populations in the central GoM that serve as stepping stones for dispersal. The data suggest that the DeSoto Canyon area, and possibly the West Florida Escarpment, critically act as sources of larvae for areas impacted by the DWH oil spill in the Mississippi Canyon. This work illustrates that the management of deep-sea marine protected areas should incorporate knowledge of connectivity networks and depth-dependent processes throughout the water column.

Abstract. The current volume, National Atlas of Hungary – Society, is Part 3 of the series. It presents the special world of Hungarian society and, according to the availability of data, also that of the Carpatho–Pannonian Area. By combining the tools of statistics, geography and cartography, the maps present the spatial structure accompanied by numerous graphs, photos, texts and infographics.The present volume of the National Atlas, Society, contributes to a much deeper understanding of processes and a better understanding of the relationships between phenomena through the presentation of the spatial diversity of demographic and social processes in historical perspective. This is a significant record of the period also showing the challenges that Hungarian society faces at the end of the second decade of the 21st century. This addition to the National Atlas of Hungary – with its extensive body of knowledge presented in this work – is an important document of great benefit not only togeographers but also to historians, economists, politicians, and all other interested parties.

Abstract Background: Brain metastases (BMs) are the most common central nervous system (CNS) malignant tumors, with rapid disease progression and extremely poor prognosis. The heterogeneity between primary tumors and BMs leads to the divergent efficacy of the adjuvant therapy response to primary tumors and BMs. However, the extent of heterogeneity between primary tumors and BMs, and the evolutionary process remains little known. Methods: To deeply insight the extent of inter-tumor heterogeneity at single-patient level and the process of these evolutions, we retrospectively analyzed a total of 26 tumor samples from 11 patients with matched primary tumors and BMs. One patient underwent four times brain metastatic lesion surgery with diverse locations and one operation for the primary lesion. The genomic and immune heterogeneity between primary tumors and BMs was evaluated by utilizing the whole-exome sequencing (WESeq) and immunohistochemical analysis.Results: In addition to inheriting genomic phenotype and molecular phenotype from the primary tumors, massive unique genomic phenotype and molecular phenotype were also observed in BMs, which revealed unimaginable complexity of tumor evolution and extensive heterogeneity among lesions at single-patient level. Our study also verified that the expression level of immune checkpoints-related molecule Programmed Death-Ligand 1 (PD-L1) (P = 0.0013) and the density of tumor-infiltrating lymphocytes (TILs) (P = 0.0248) in BMs were significantly lower than that in paired primary tumors. Additionally, tumor microvascular density (MVD) and tumor invasiveness were also differed between primary tumors and paired BMs, indicating that temporal and spatial diversity profoundly contributes to the evolution of BMs heterogeneity.Conclusion: We verified the significance of temporal and spatial factors to the evolution of tumor heterogeneity by multi-dimensional analysis of matched primary tumors and BMs, which also provided novel insight for formulating individualized treatment strategies of BMs.

Changes in land management methods constantly occur, caused by natural, economic, social and demographic conditions. This paper aims to determine changes in set-asides and fallow land in Poland, in the years 1990-2020, and determine the spatial diversity of this phenomenon. The study was based on available statistical data for the studied period. The study shows that, before 2004, the share of fallow land was much more significant. After Poland acceded to the European Union, land left without cultivation decreased considerably with a simultaneous increase in the area of land used for agriculture. The results show that the share and number of hectares of fallow area decreased. The provinces of Kujawsko-Pomorskie, Opole and Wielkopolskie were characterized by the lowest percentage of fallow land in the agricultural area of the province. In contrast, the provinces of Podkarpackie, Lubuskie, Świętokrzyskie, Małopolskie, Śląskie and Warmińsko-Mazurskie had the highest percentage of fallow land.