Small-scale Regions Research Articles

Human Mobility and Climate Change Adaptation in Small-Scale Farming Areas in Eastern Zimbabwe

Abstract This paper examines the role played by human mobility as a climate change adaptation strategy in Zimbabwe’s small-scale farming areas. Livelihoods in Zimbabwe’s small-scale farming areas are mostly agriculture-based and have long suffered from low levels of production. This is largely due to poor agroecological conditions and lack of agricultural investment, including income diversification projects from the central government. Recently, extreme climatic events in these areas have exacerbated food insecurity challenges, prompting many households to relocate. The findings of this study indicate that most households in the small-scale farming regions are resorting to either short- or long-term migration to areas that offer them food security. In these areas, poor households are forced to work on large commercial farms where they are paid in maize grain or trade their products for food to support their families. This paper argues that, if properly used together with other climate change policies promoted in Zimbabwe, human mobility can be an effective climate change adaptation strategy in small-scale farming areas.

Galaxy cluster mass density profile derived using the submillimetre galaxies magnification bias

Context. The magnification bias is a gravitational lensing effect that produces an increase or decrease in the detection probability of background sources near the position of a lense. The special properties of the submillimetre galaxies (SMGs; steep source number counts, high redshift, and a very low cross-contamination with respect to the optical band) makes them the optimal background sample for magnification bias studies. Aims. We want to study the average mass density profile of tens to hundreds of clusters of galaxies acting as lenses that produce a magnification bias on the SMGs, and to estimate their associated masses and concentrations for different richness ranges. The cluster richness is defined as R = L200/L* with L200 as the total r-band luminosity within the radius r200. Methods. The background sample is composed of SMGs observed by Herschel with 1.2 < z < 4.0 (mean redshift at ∼2.3) while the foreground sample is made up of galaxy clusters extracted from the Sloan Digital Sky Survey III with photometric redshifts of 0.05 < z < 0.8 (mean redshift at ∼0.38). Measurements are obtained by stacking the SMG–cluster pairs to estimate the cross-correlation function using the Davis-Peebles estimator. This methodology allows us to derive the mass density profile for a wide range of angular scales, ∼2 − 250 arcsec or ∼10 − 1300 kpc for z = 0.38, with a high radial resolution, and in particular to study the inner part of the dark matter halo (< 100 kpc). In addition, we also divide the cluster sample into five bins of richness and we analyse the estimated cross-correlation data using different combinations of the most common theoretical mass density profiles. Results. It is impossible to fit the data with a single mass density profile at all scales: in the inner part there is a clear excess in the mass density profile with respect to the outer part that we interpret as the galactic halo of the big central galaxy. As for the outer part, the estimated average masses increase with richness from M200c = 5.8 × 1013 M⊙ to M200c = 51.5 × 1013 M⊙ (M200c = 7.1 × 1013 M⊙ for the total sample). With respect to the concentration parameter, its average also increases with richness from C = 0.74 to C = 1.74 (C = 1.72 for the total sample). In the small-scale regions, the obtained average masses fluctuate around M200c = 3 − 4 × 1013 M⊙ with average concentration values of around C ∼ 4. Conclusions. The total average masses are in perfect agreement with the mass–richness relationship estimated from the cluster catalogue. In the bins of lowest richness, the central galactic halo constitutes ∼40% of the total mass of the cluster and its relevance decreases for higher richness values. While the estimated average concentration values of the central galactic halos are in agreement with traditional mass–concentration relationships, we find low concentrations for the outer part. Moreover, the concentrations decrease for lower richness values, probably indicating that the group of galaxies cannot be considered to be relaxed systems. Finally, we notice a systematic lack of signal at the transition between the dominance of the cluster halo and the central galactic halo (∼100 kpc). This feature is also present in previous studies using different catalogues and/or methodologies, but is never discussed.

Global and local fracture behavior in a brittle solid with a set of pre-existing small-scale cracks

For understanding the mechanics of complicated seismic activities, not only global observations of large-scale material behavior but also more local tracing of smaller-scale fractures is needed. In this study, therefore, by using the technique of dynamic photoelasticity, the evolution of fractures and waves is experimentally traced in a two-dimensional linear elastic brittle specimen that has a set of pre-existing small-scale parallel fracture regions. The small-scale fracture regions or cracks, modeling a large-scale geological normal fault plane, are prepared by a digital laser cutter. Our experimental observations with a high-speed video camera, together with finite difference numerical simulations, indicate that the global and local fracture behavior significantly depends on the initial inclination angle and distribution pattern of the set of parallel cracks. In the case of pre-existing cracks that are more vertically inclined with respect to the quasi-static external load applied by a tensile testing machine, the main fracture develops dynamically and then the secondary fractures appear at spatiotemporally remote distances from the main fracture. The secondary fractures extend also dynamically, into the direction opposite to the main fracture. On the other hand, in the case of smaller inclination angles, the main fracture tends to evolve quasi-statically. Nevertheless, in both cases, it is found that fracture can be arrested and jump without difficulties in a brittle solid having a number of small-scale cracks, which implies that such small-scale cracks may play an important part in the generation of a cluster of seismic events.

Research on Human Motion Analysis in Moving Scene Based on Timing Detection and Video Description Algorithm

Technical movement analysis requires specialized domain knowledge and processing a large amount of data, and the advantages of AI in processing data can improve the efficiency of data analysis. In this paper, we propose a feature pyramid network-based temporal action detection (FPN-TAD) algorithm, which is used to solve the problem that the action proposal module has a low recall rate for small-scale temporal target action regions in the current video temporal action detection algorithm research. This paper is divided into three parts. The first part is an overview of the algorithm; the second part elaborates the network structure and the working principle of the FPN-TAD algorithm; and the third part gives the experimental results and analysis of the algorithm.

Amalgamation: Social, technological, and legal entanglements in small-scale gold-mining regions in Colombia and Suriname

Popular and scholarly accounts often describe small-scale gold mining as a conflict-ridden economy that takes place in regions where state law is lacking. Our long-term ethnographic research in Colombia and Suriname has shown that stakeholder agendas in the goldfields, although often at variance, also come together in unexpected compromises and entanglements. We therefore propose to think of small-scale gold mining as an activity of not only conflict, but also of amalgamation; that is, as an activity that brings presumably adversary actors, labor practices, and governance systems together in temporary moments of conviviality. We present a three-pronged ethnographic analysis to sustain our proposition, thereby conceptualizing amalgamation as a social, technological, and legal phenomenon. First, we show that mining regions are characterized by social amalgamation; that is to say, by continuous compromises between the competing agendas of stakeholders. Second, we zoom in on technological amalgamation. We set out that technological differences that provoke hostility and conflict also have a more productive side, as miners employing various methods depend on each other in the process of gold extraction. And third, we provide illustrations of legal amalgamation that serve to highlight that the socio-political organization of small-scale gold mining, while largely happening outside the legal framework, comes into being through the symbolism and material infrastructure of the state.

A New Reconstruction of the Sun’s Magnetic Field and Total Irradiance since 1700

Abstract We model the Sun’s large-scale magnetic field and total solar irradiance (TSI) since 1700 by combining flux transport simulations with empirical relationships between facular brightening, sunspot darkening, and the total photospheric flux. The photospheric field is evolved subject to the constraints that (1) the flux emergence rate scales as the yearly sunspot numbers, and (2) the polar field strength at solar minimum is proportional to the amplitude of the following cycle. Simulations are performed using both the recently revised sunspot numbers and an average of these numbers and the Hoyt–Schatten group numbers. A decrease (increase) in the polar field strength from one cycle to the next is simulated either by increasing (decreasing) the poleward flow speed, or by decreasing (increasing) the average axial tilts of active regions; the resulting photospheric field evolution is very similar whichever parameter is varied. Comparisons between irradiance data and both the simulated and observed photospheric field suggest that TSI and facular brightness increase less steeply with the field strength at solar minimum than at other phases of the cycle, presumably because of the dominance of small-scale ephemeral regions when activity is very low. This relative insensitivity of the irradiance to changes in the large-scale field during cycle minima results in a minimum-to-minimum increase of annual TSI from 1700 to 1964 (2008) of 0.2 (0.06) W m−2, a factor of 2–3 smaller than predicted in earlier reconstructions where the relation between facular brightness and field strength was assumed to be independent of cycle phase.

Mapping trade-offs among urban fringe land use functions to accurately support spatial planning

The land use planning and management of urban fringe areas have become major governmental agendas under the background of continuing periurbanization processes. Quantifying land use functions (LUFs) and their interactions as rationales for spatial planning can aid in formulating a more effective and sustainable land use management system. Considering that most of the previous research on LUFs focused on large-scale regions, research on local-scale districts such as urban fringe is still limited. Therefore, the objective of this work is to map the spatial distribution of LUFs and their level of provision around an urban fringe area, so as to identify LUFs synergies and trade-offs in relation to urban expansion and environmental protection planning. To achieve this target, we have proposed an improved LUFs classification system that was suitable for small-scale regions. Fine scale multivariate datasets were used to meet the practical requirements of spatial planning. The urban fringe areas of Binzhou city in China was taken as a case study to quantify and analyze nine kinds of sub-land use functions. The interactions among LUFs and their cold-hot spots were measured through Spearman correlation analysis and bivariate local Moran's I respectively. The results demonstrated a heterogeneous spatial pattern of multiple LUFs and the diverse interactions among them. The social production function presented an obvious regional distribution, the residents’ living functions were greatly affected by the radiation of the urban central areas, and the ecological regulation functions were closely related to the land use types. According to the LUFs clustering results, we proposed two spatial planning-zoning schemes based on the land use function and human utilization intensity. The integrative approach and the proposal of functional zones developed in this paper are applicable to provide a new perspective for spatial planning and peri-urban land use management.

The Urban Characteristics of High Economic Resilient Neighborhoods during the COVID-19 Pandemic: A Case of Suwon, South Korea

Infectious diseases and pandemics, including the COVID-19 pandemic, have a huge economic impact on cities. However, few studies examine the economic resilience of small-scale regions within cities. Thus, this study derives neighborhoods with high economic resilience in a pandemic situation and reveals their urban characteristics. It evaluates economic resilience by analyzing changes in the amount of credit card payments in the neighborhood and classifying the types of neighborhoods therefrom. The study conducted the ANOVA, Kruskal–Wallis, and post hoc tests to analyze the difference in urban characteristics between neighborhood types. Accordingly, three neighborhood types emerged from the analysis: high-resilient neighborhood, low-resilient neighborhood, and neighborhood that benefited from the pandemic. The high-resilient neighborhood is a low-density residential area where many elderly people live. Neighborhoods that benefited are residential areas mainly located in high-density apartments where many families of parents and children live. The low-resilient neighborhood is an area with many young people and small households, many studio-type small houses, and a high degree of land-use mix.

Coupling a Global Heliospheric Magnetohydrodynamic Model to a Magnetofrictional Model of the Low Corona

Abstract Recent efforts coupling our Sun-to-Earth magnetohydrodynamics (MHD) model and lower-corona magnetofrictional (MF) model are described. Our Global Heliospheric MHD (GHM) model uses time-dependent three-component magnetic field data from the lower-corona MF model as time-dependent boundary values. The MF model uses data-assimilation techniques to introduce the vector magnetic field data from the Solar Dynamics Observatory/Helioseismic and Magnetic Imager, hence as a whole this simulation coupling structure is driven with actual observations. The GHM model employs a newly developed interface boundary treatment that is based on the concept of characteristics, and it properly treats the interface boundary sphere set at a height of the sub-Alfvénic lower corona (1.15 R ⊙ in this work). The coupled model framework numerically produces twisted nonpotential magnetic features and consequent eruption events in the solar corona in response to the time-dependent boundary values. The combination of our two originally independently developed models presented here is a model framework toward achieving further capabilities of modeling the nonlinear time-dependent nature of magnetic field and plasma, from small-scale solar active regions to large-scale solar wind structures. This work is a part of the Coronal Global Evolutionary Model project for enhancing our understanding of Sun–Earth physics to help improve space weather capabilities.

A numerical approach to address the acoustic stiffness in cavitating flows

A numerical approach based on preconditioning and dual-time stepping (DTS) is proposed to simulate cavitating flows at low Mach numbers. The methodology is based on a fully-compressible homogeneous mixture model and finite rate mass transfer as discussed in Gnanaskandan and Mahesh (2015). The method has shown promising results for capturing the large-scale cavitation in developed cavitation regimes (e.g. Bhatt and Mahesh, 2020; Gnanaskandan and Mahesh, 2016a). Small-scale vapor regions in the incipient cavitation, cavitation inception and wetted conditions are sensitive to free-stream nuclei content (e.g. Hsiao and Chahine, 2005; Bhatt and Mahesh, 2019, 2020). In these regimes, lower values of free-stream nuclei are necessary than what is typically prescribed in homogeneous mixture models that use a fully-compressible formulation. While important for the physical modeling, lower values of free-stream nuclei lead to acoustic stiffness. The goal of the present work is to present a numerical approach to enable such low free-stream nuclei calculations in an accurate manner and in a reasonable amount of time. The key aspects of the numerical approach are: (i) preconditioning applied to the cavitating flow equations in a fully-compressible (density-based) solver, (ii) modifications based on the all-speed Roe-type scheme to the characteristic-based filtering, and (iii) implementation in parallel and on unstructured grids that allow the simulation of complex problems. The numerical formulation of the time-derivative preconditioning matrix, the DTS framework, and modification to the shock-capturing are discussed. A proper conditioning of the preconditioned system of equations is obtained. The methodology is demonstrated for the unsteady flow over a cylinder under wetted and cavitation inception conditions, and LES of flow over a propeller under wetted conditions. Overall, a significant saving in total run-time as compared to the original solver is obtained, without compromising accuracy.

Carbon Emission Governance Zones at the County Level to Promote Sustainable Development

Low-carbon governance at the county level has been an important issue for sustainable development due to the large contributions to carbon emission. However, the experiences of carbon emission governance at the county level are lacking. This paper discusses 5 carbon emission governance zones for 1753 counties. The zoning is formed according to a differentiated zoning method based on a multi-indicator evaluation to judge if the governance had better focus and had formulated a differentiated carbon emission governance system. According to zoning results, there is 1 high-carbon governance zone, 2 medium-carbon governance zones, and 2 low-carbon zones. The extensive high-carbon governance zone and medium-carbon zones are key governance areas, in which the counties are mainly located in the northern plain areas and southeast coastal areas and have contributed 51.88% of total carbon emissions. This paper proposes differentiated governance standards for each indicator of the 5 zones. The differentiated zoning method mentioned in this paper can be applied to other governance issues of small-scale regions.

BrainSeg-Net: Brain Tumor MR Image Segmentation via Enhanced Encoder-Decoder Network.

Efficient segmentation of Magnetic Resonance (MR) brain tumor images is of the utmost value for the diagnosis of tumor region. In recent years, advancement in the field of neural networks has been used to refine the segmentation performance of brain tumor sub-regions. The brain tumor segmentation has proven to be a complicated task even for neural networks, due to the small-scale tumor regions. These small-scale tumor regions are unable to be identified, the reason being their tiny size and the huge difference between area occupancy by different tumor classes. In previous state-of-the-art neural network models, the biggest problem was that the location information along with spatial details gets lost in deeper layers. To address these problems, we have proposed an encoder–decoder based model named BrainSeg-Net. The Feature Enhancer (FE) block is incorporated into the BrainSeg-Net architecture which extracts the middle-level features from low-level features from the shallow layers and shares them with the dense layers. This feature aggregation helps to achieve better performance of tumor identification. To address the problem associated with imbalance class, we have used a custom-designed loss function. For evaluation of BrainSeg-Net architecture, three benchmark datasets are utilized: BraTS2017, BraTS 2018, and BraTS 2019. Segmentation of Enhancing Core (EC), Whole Tumor (WT), and Tumor Core (TC) is carried out. The proposed architecture have exhibited good improvement when compared with existing baseline and state-of-the-art techniques. The MR brain tumor segmentation by BrainSeg-Net uses enhanced location and spatial features, which performs better than the existing plethora of brain MR image segmentation approaches.

区块链技术在小型区域价值流转中的信任优化机制研究与应用

区块链技术在小型区域价值流转中的信任优化机制研究与应用

Sustainable development problems and countermeasures: A case study of the Qinghai-Tibet Plateau

The Qinghai-Tibet Plateau (QTP) is a region with unique and distinctive natural landscapes and cultural characteristics and presents a useful case to improve understanding of sustainable development for regions with extreme environments and unique social backgrounds. Research has been conducted for small-scale regions, however there has been insufficient exploration of the problems and countermeasures for sustainable development in Tibet. This study analyzes different functional zones (urbanized zones, agricultural zones, pastoral zones and ecological security zones) of the QTP. Then it develops a sustainable livelihood index (SLI) based on the sustainable livelihood analysis framework resulting in three main findings. First, sustainable livelihoods vary greatly across functional zones. The SLI for farmers and herdsmen in the urbanized zones is the highest, with a value of 3.57, followed by the agricultural zones of 3.07. In comparison, the SLI values in the ecological security zones and pastoral zones are 2.92 and 2.85, respectively, indicating that the two zones present challenges for sustainable development in the QTP. Second, all counties had few natural, social or physical assets, indicating the need to expand assets to achieve sustainable livelihoods. Finally, urbanized and agricultural counties had more robust livelihood strategies than ecological and pastoral counties. In light of these results, strategic options have been formulated to promote sustainable development. These options include: accelerating construction of the third pole national park group; establishing a pattern of green mining; promoting the biological resources industry; and initiating a carbon trading market in the QTP.

Monitoring Large-Scale Inland Water Dynamics by Fusing Sentinel-1 SAR and Sentinel-3 Altimetry Data and by Analyzing Causal Effects of Snowmelt

The warming climate is threatening to alter inland water resources on a global scale. Within all waterbody types, lake and river systems are vital not only for natural ecosystems but, also, for human society. Snowmelt phenology is also altered by global warming, and snowmelt is the primary water supply source for many river and lake systems around the globe. Hence, (1) monitoring snowmelt conditions, (2) tracking the dynamics of snowmelt-influenced river and lake systems, and (3) quantifying the causal effect of snowmelt conditions on these waterbodies are critical to understand the cryo-hydrosphere interactions under climate change. Previous studies utilized in-situ or multispectral sensors to track either the surface areas or water levels of waterbodies, which are constrained to small-scale regions and limited by cloud cover, respectively. On the contrary, in the present study, we employed the latest Sentinel-1 synthetic aperture radar (SAR) and Sentinel-3 altimetry data to grant a high-resolution, cloud-free, and illumination-independent comprehensive inland water dynamics monitoring strategy. Moreover, in contrast to previous studies utilizing in-house algorithms, we employed freely available cloud-based services to ensure a broad applicability with high efficiency. Based on altimetry and SAR data, the water level and the water-covered extent (WCE) (surface area of lakes and the flooded area of rivers) can be successfully measured. Furthermore, by fusing the water level and surface area information, for Lake Urmia, we can estimate the hypsometry and derive the water volume change. Additionally, for the Brahmaputra River, the variations of both the water level and the flooded area can be tracked. Last, but not least, together with the wet snow cover extent (WSCE) mapped with SAR imagery, we can analyze the influence of snowmelt conditions on water resource variations. The distributed lag model (DLM) initially developed in the econometrics discipline was employed, and the lagged causal effect of snowmelt conditions on inland water resources was eventually assessed.

CNN-Enhanced Graph Convolutional Network With Pixel- and Superpixel-Level Feature Fusion for Hyperspectral Image Classification

Recently, the graph convolutional network (GCN) has drawn increasing attention in the hyperspectral image (HSI) classification. Compared with the convolutional neural network (CNN) with fixed square kernels, GCN can explicitly utilize the correlation between adjacent land covers and conduct flexible convolution on arbitrarily irregular image regions; hence, the HSI spatial contextual structure can be better modeled. However, to reduce the computational complexity and promote the semantic structure learning of land covers, GCN usually works on superpixel-based nodes rather than pixel-based nodes; thus, the pixel-level spectral–spatial features cannot be captured. To fully leverage the advantages of the CNN and GCN, we propose a heterogeneous deep network called CNN-enhanced GCN (CEGCN), in which CNN and GCN branches perform feature learning on small-scale regular regions and large-scale irregular regions, and generate complementary spectral–spatial features at pixel and superpixel levels, respectively. To alleviate the structural incompatibility of the data representation between the Euclidean data-oriented CNN and non-Euclidean data-oriented GCN, we propose the graph encoder and decoder to propagate features between image pixels and graph nodes, thus enabling the CNN and GCN to collaborate in a single network. In contrast to other GCN-based methods that encode HSI into a graph during preprocessing, we integrate the graph encoding process into the network and learn edge weights from training data, which can promote the node feature learning and make the graph more adaptive to HSI content. Extensive experiments on three data sets demonstrate that the proposed CEGCN is both qualitatively and quantitatively competitive compared with other state-of-the-art methods.

Revision of the Oriental tiger beetle genus Heptodonta Hope, 1838 (Coleoptera: Cicindelidae).

This contribution aims to revise the taxonomy of the genus Heptodonta Hope, 1838, and provides a dichotomous key to the 15 species of this genus. Each species is described in detail with colour photographs of habitus and diagnostic characters. Information on distribution and biology of each species is provided. Heptodonta abasileia sp. nov., H. halensis sp. nov., H. horii sp. nov., H. schuelei sp. nov., H. tempesta sp. nov. and H. wiesneri sp. nov. are described. Heptodonta nigrosericea (W. Horn, 1930), stat. nov. is raised to species rank. Heptodonta ferrarii Gestro, 1893, syn. nov. and H. ferrarii shooki Wiesner, 1986, syn. nov. are placed into synonymy under H. pulchella (Hope, 1831). Heptodonta lumawigi Wiesner, 1980, syn. nov. is placed into synonymy under H. nigrosericea stat. nov. Females of H. vermifera W. Horn, 1908, and males of H. mindoroensis Cassola, 2000, are described for the first time. Lectotypes are designated for H. analis (Fabricius, 1801), H. arrowi W. Horn, 1900, H. ferrarii Gestro, 1893, H. hopei Parry, 1844, H. melanopyga (Schaum, 1862), H. nigrosericea (W. Horn, 1930), H. posticalis (White, 1844), H. pulchella (Hope, 1831), H. thongdii Fleutiaux, 1919, H. variipes (Chaudoir, 1850), H. vermifera W. Horn, 1908, and H. yunnana (Fairmaire, 1887). Holotype is designated by monotypy for H. eugenia Chaudoir, 1865. Regionally restricted records of two new species from the Philippine island Negros and one new species from the northeast Indian Garo Hills highlight the high conservation value of these rather small-scale regions.

CONAMAD: Birth cohort to quantify the effects of in-utero metals exposure on child development in an artisanal and small-scale gold mining region of the Amazon

Research quantifying in-utero trace metals exposure and health effects have been conducted primarily in developed regions. Given the global increase of artisanal scale gold mining (ASGM), there is a critical need to quantify in-utero exposure to trace metals and related health risks in populations living in ASGM environments, characterized by high prevalence of malnutrition, infectious disease, and poverty. We describe the design and initial results of CONAMAD, a birth cohort of multiparous women (18 and over) living in an ASGM region of Madre de Dios (MDD), Peru, whose long-term goal is to quantify in-utero toxic metals exposures and subsequent child health effects during the first two years of life. 270 mothers were enrolled during pregnancy across four zones representing differential economic and development activities in MDD. At enrollment, women averaged 28 years of age, 20 weeks gestational age, and 17% were of short stature (<1.45m). Half of all mothers lived near a major road and ~20% lived near mining or a gold shop, which varied by location (p<0.001). We obtained biomarkers from 215 mothers and their newborns at birth, including maternal and cord blood, hair samples, and placenta for exposure assessment. The median levels of mercury and lead in cord blood were 5.8 μg/L and 10.0 μg/L, respectively, while median levels in maternal blood were 3.4 μg/L and 13.3 μg/L, respectively (USEPA BMDL is 5.8 μg/L for blood Hg, 5 μg/dL for lead). USEPA assumes cord:maternal blood mercury ratio (Hgc:Hgm) to be equal when estimating reference doses for risk quantification; however, we find higher median Hgc:Hgm of 1.67 (10th to 90th percentile: 1.13-2.42) with 93% of cord blood Hg samples exceeding maternal blood levels. Results indicate that the developing fetus may have increased health risks if standard public health recommendations are followed by pregnant women in ASGM regions.

Macroscopic somatic clonal expansion in morphologically normal human urothelium.

Knowledge of somatic mutation accumulation in normal cells, which is essential for understanding cancer development and evolution, remains largely lacking. In this study, we investigated somatic clonal events in morphologically normal human urothelium (MNU; epithelium lining the bladder and ureter) and identified macroscopic clonal expansions. Aristolochic acid (AA), a natural herb-derived compound, was a major mutagenic driving factor in MNU. AA drastically accelerates mutation accumulation and enhances clonal expansion. Mutations in MNU were widely observed in chromatin remodeling genes such as KMT2D and KDM6A but rarely in TP53, PIK3CA, and FGFR3 KMT2D mutations were found to be common in urothelial cells, regardless of whether the cells experience exogenous mutagen exposure. Copy number alterations were rare and largely confined to small-scale regions, along with copy-neutral loss of heterozygosity. Single AA-associated clones in MNU expanded to a scale of several square centimeters in size.

The Effects of Oscillations and Collisions of Emerging Bipolar Regions on the Triggering of Solar Flares

Abstract The ability to predict the occurrence of solar flares in advance is important to humankind due to the potential damage they can cause to Earth’s environment and infrastructure. It has been shown in Kusano et al. that a small-scale bipolar region (BR), with its flux reversed relative to the potential component of the overlying field, appearing near the polarity inversion line (PIL) is sufficient to effectively trigger a solar flare. In this study we perform further 3D magnetohydrodynamic simulations to study the effect that the motion of these small-scale BRs has on the effectiveness of flare triggering. The effect of two small-scale BRs colliding is also simulated. The results indicate that the strength of the triggered flare is dependent on how much of the overlying field is disrupted by the BR. Simulations of linear oscillations of the BR showed that oscillations along the PIL increase the flare strength while oscillations across the PIL detract from the flare strength. The flare strength is affected more by larger amplitude oscillations but is relatively insensitive to the frequency of oscillations. In the most extreme case the peak kinetic energy of the flare increased more than threefold compared to a non-oscillating BR. Simulations of torsional oscillations of the BR showed a very small effect on the flare strength. Finally, simulations of colliding BRs showed the generation of much stronger flares as the flares triggered by each individual BR coalesce. These results show that significantly stronger flares can result from motion of the BR along the PIL of a sheared field or from the presence of multiple BRs in the same region.