Detailed Distribution Research Articles

Fine mesh pin-by-pin analysis of IPWR equilibrium core

Detailed fine mesh reactor physics simulations are warranted for reactor cores in order to estimate the important safety parameters such as detailed pin power distribution in the core and local pin peaking factors. A pin-by-pin reactor analysis code HEXPIN has been developed to perform 3D reactor core analysis with a pincell size mesh. HEXPIN uses the conventional two step calculation methodology for performing reactor calculations. India is developing a 2700 MWth/900 MWe Indian Pressurized Water Reactor (IPWR) for developing indigenous capability for commercial light water technology. It uses enriched uranium oxide fuel. The batch refueling scheme is adopted for fuel cycle management. A fine mesh pin-by-pin analysis of equilibrium core of IPWR has been performed using HEXPIN code system. The pin homogenised parametric cross section library, required for HEXPIN calculation, has been generated using lattice burn up code EXCEL. The equilibrium core calculation has been performed by a set of repeated calculations till a converged core configuration is achieved. The present paper gives the methodology and brief results of the analysis.

Distribution Pattern of Metastatic Lymph Nodes in 870 Cases of Nasopharyngeal Carcinoma: A Clue for Individualized Elective Prophylactic Neck Irradiation

We aimed to explore a potential individualized elective prophylactic neck irradiation (iEPNI) to optimize the current strategy by investigating the distribution of metastatic lymph nodes (LNs) in nasopharyngeal carcinoma (NPC). Magnetic resonance imaging (MRI) and clinical data of 870 non-distant metastatic NPC patients admitted to the Hunan Cancer Hospital between January 2019 and December 2019 were reviewed. All patients were staged using the 8th TNM staging system, and the LNs location was assigned based on the 2013 guidelines. According to the distribution patterns of the LNs in NPC, the intra-regional lymphatic drainage levels were categorized into the following three stations: Station 1st of level VIIa and II; Station 2nd of level III and Va; and Station 3rd of level IV, Vb, and Vc. Other levels were defined as extra-regional areas. The incidence of LNs metastasis was 822/870 (94.5%), including 198 cases of unilateral metastasis and 624 cases of bilateral metastasis. Among the 870 patients, the most frequently involved intra-regional lymphatic drainage was level IIb (87.1%), followed by level VIIa (80.0%), IIa (61.8%), Va (30.6%), IV (21.4%), Vb (8.9%), and Vc (1.1%). In the extra-regional areas, the detailed LNs distribution was: level Ia (0.2%), level Ib (7.7%), level VI (0.1%), level VIIb (5.6%), level VIII (5.5%), level IX (0.3%), and level X (0.2%). The rates of LNs metastasis in Station 1st, Station 2nd, and Station 3rd were 820/870 (94.3%), 532/870 (61.1%), and 199/870 (22.9%), respectively. Only 4 patients were considered to be skipping metastasis among the three stations (4/870, 0.5%). Additionally, in 203 patients with unilateral Station 1st LNs metastasis, there were 86 (42.4%) and 37 (18.2%) patients with ipsilateral Station 2nd and Station 3rd metastasis, respectively, and 3 (1.5%) and 1 (0.5%) patients with contralateral Station 2nd and Station 3rd LNs metastasis, respectively. LNs spread from Station 1st to Station 3rd successively with rare skipping metastasis. A potential iEPNI strategy of prophylactical neck irradiation to the ipsilateral latter node-negative station might be feasible, which is detailed as follows: irradiation to Station 1st in patients with no LNs metastasis, irradiation to Station 2nd in patients with only Station 1st metastasis, and irradiation to Station 3rd in patients with Station 2nd metastasis but without Station 3rd metastasis. Further prospective investigations are expected to validate the strategy.

Exploring a Low-Cost Valorization Route for Amazonian Cocoa Pod Husks through Thermochemical and Catalytic Upgrading of Pyrolysis Vapors.

Ecuador as an international leader in the production of cocoa beans produced more than 300 000 tons in 2021; hence, the management and valorization of the 2 MM tons of waste generated annually by this industry have a strategic and socioeconomic value. Consequently, appropriate technologies to avoid environmental problems and promote sustainable development and the bioeconomy, especially considering that this is a megadiverse country, are of the utmost relevance. For this reason, we explored a low-cost pyrolysis route for valorizing cocoa pod husks from Ecuador's Amazonian region, aiming at producing pyrolysis liquids (bio-oil), biochar, and gas as an alternative chemical source from cocoa residues in the absence of hydrogen. Downstream catalytic processing of hot pyrolysis vapors using Mo- and/or Ni-based catalysts and standalone γ-Al2O3 was applied for obtaining upgraded bio-oils in a laboratory-scale fixed bed reactor, at 500 °C in a N2 atmosphere. As a result, bimetallic catalysts increased the bio-oil aqueous phase yield by 6.6%, at the expense of the organic phase due to cracking reactions according to nuclear magnetic resonance (NMR) and gas chromatography-mass spectrometry (GC-MS) results. Overall product yield remained constant, in comparison to pyrolysis without any downstream catalytic treatment (bio-oil ∼39.0-40.0 wt % and permanent gases 24.6-26.6 wt %). Ex situ reduced and passivated MoNi/γ-Al2O3 led to the lowest organic phase and highest aqueous phase yields. The product distribution between the two liquid phases was also modified by the catalytic upgrading experiments carried out, according to heteronuclear single-quantum correlation (HSQC), total correlation spectroscopy (TOCSY), and NMR analyses. The detailed composition distribution reported here shows the chemical production potential of this residue and serves as a starting point for subsequent valorizing technologies and/or processes in the food and nonfood industry beneficiating society, environment, economy, and research.

Born to Be Wide: The Distribution of Wide Binaries in the Field and Soft Binaries in Clusters

Most stars, binaries, and higher-multiplicity systems are thought to form in stellar clusters and associations that later dissociate. Very wide binaries can be easily disrupted in clusters due to dynamical evaporation (soft binaries) and/or tidal disruption by the gravitational potential of the cluster. Nevertheless, wide binaries are quite frequent in the field, where they can sometimes play a key role in the formation of compact binaries and serve as tools to study key physical processes. Here we use analytic tools to study the dynamical formation of soft binaries in clusters and their survival as field binaries following cluster dispersion. We derive the expected properties of very wide binaries both in clusters and in the field. We analytically derive their detailed distributions, including the wide binary fraction as a function of mass in different cluster environments, binary mass functions and mass ratios, and the distribution of their orbital properties. We show that our calculations agree well in most aspects with the results of N-body simulations but show some different binary fraction dependence on the cluster mass. We find that the overall fraction of wide binaries scales as , where N ⋆ is the size of the cluster, even for non-equal-mass stars. More massive stars are more likely to capture wide companions, with most stars above 5 M ⊙ likely to capture at least one stellar companion, and formation of triples is found to be frequent.

Detailed Inventory and Spatial Distribution Analysis of Rainfall-Induced Landslides in Jiexi County, Guangdong Province, China in August 2018

In recent years, with the intensification of climate change, the occurrence of heavy rain events has become more frequent. Landslides triggered by heavy rainfall have become one of the common geological disasters around the world. This study selects an extreme rainfall event in August 2018 in Jiexi County, Guangdong province, as the research object. Based on high-resolution remote sensing images before and after the event, visual interpretation is conducted to obtain a detailed distribution map of rainfall-induced landslides. The results show that a total of 1844 rainfall-induced landslides were triggered within Jiexi County during this rainfall event. In terms of triggered scale, the total area of the landslides is 3.3884 million m2, with the largest individual landslide covering an area of 22,300 m2 and the smallest one covering an area of 417.78 m2. The landslides are concentrated in the northeastern, central, and southwestern parts of the study area, consistent with the distribution trend of rainfall intensity. To investigate further the influence of the regional environment on landslide distribution, this study selects eight influencing factors, including elevation, slope aspect, slope angle, topographic wetness index (TWI), topographic relief, lithology, distance to river, and accumulated rainfall. The landslide number density (LND) and landslide area percentage (LAP) are used as evaluation indicators. Based on statistical analysis using a data analysis platform, the relationship between landslide distribution and influencing factors triggered by this event is revealed. The results of this study will contribute to understanding the development law of regional rainfall-induced landslides and provide assistance for disaster prevention and mitigation in the area. The research results show that the elevation range of 100–150 m is the high-risk zone for landslides. In addition, this study has verified previous findings that slopes in the southeast direction are more prone to landslides. The steeper the slope, the more significant its influence on landslide development. When the topographic wetness index (TWI) is less than 4, landslides tend to have a high-density distribution. Greater variation in terrain relief is more likely to trigger landslides. The instability of lithology in Mesozoic strata is the main cause of landslides. The farther away from the water system, the fewer landslides occur. An increase in cumulative rainfall leads to an increase in both the number and area of landslides.

Development of a large-area alpha imaging detector for hand and foot monitors

— This paper describes the development of a large-area imaging detector capable of measuring the detailed distribution of alpha particles on hands and feet for use in entry/exit control monitors in decommissioning sites such as the Fukushima Daiichi Nuclear Power Plant. The detector was developed using a commercially available ZnS(Ag) scintillator and an electron multiplying CCD camera. The effectiveness of the detector was evaluated by measuring several types of radiation sources, and the results showed that it was possible to detect the position of alpha particles in a very short time, and contamination levels of up to 11 Bq/cm2 could be visualized. As a result of the minimal detectable surface activity concentration evaluations, 2.0 min or more is required to achieve 4 Bq/cm2, and 25.0 min or more is required to achieve 0.4 Bq/cm2. The field of view of the detector was also checked, and it was confirmed that the setup had a field of view that could cover most of the hand and the sole of the shoe. This detector is expected to be useful for preventing internal uptake and decontamination.

Modelling potential distribution of Tuta absoluta in China under climate change using CLIMEX and MaxEnt

AbstractThe Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) originated in South America and is a major pest of the economically critical solanaceous crops. It is devastating to tomatoes, attacking mainly the leaves, stems, flowers and fruits of tomato plants, and can cause up to 100% damage. T. absoluta invaded China in 2017 and expanded rapidly, severely impacting the tomato industry. To illustrate the detailed potential distribution of T. absoluta in China, we used CLIMEX and MaxEnt models to predict the potential distribution of this pest using historical and future climate data. CLIMEX predicts a wider potential distribution area for T. absoluta in China than MaxEnt, which suggests that most of China is suitable for its distribution, except for the Tarim Basin in southern Xinjiang, western Inner Mongolia and northwestern Gansu. Both models accurately predicted the known distribution of T. absoluta in the provinces of Yunnan and Guangxi, and the predictions by both models suggest the total distribution range of T. absoluta in China is to increase slightly with future changes in climate temperature. These predictions will help understand the influence of climate change on the potential distribution of T. absoluta in China and thus provide a theoretical foundation for developing early monitoring, quarantine and control strategies.

ChinaWheatYield30m: a 30 m annual winter wheat yield dataset from 2016 to 2021 in China

Abstract. Generating spatial crop yield information is of great significance for academic research and guiding agricultural policy. Existing public yield datasets have a coarse spatial resolution, spanning from 1 to 43 km. Although these datasets are useful for analyzing large-scale temporal and spatial change in yield, they cannot deal with small-scale spatial heterogeneity, which happens to be the most significant characteristic of the Chinese farmers' economy. Hence, we generated a 30 m Chinese winter wheat yield dataset (ChinaWheatYield30m) for major winter-wheat-producing provinces in China for the period 2016–2021 with a semi-mechanistic model (hierarchical linear model, HLM). The yield prediction model was built by considering the wheat growth status and climatic factors. It can estimate wheat yield with excellent accuracy and low cost using a combination of satellite observations and regional meteorological information (i.e., Landsat 8, Sentinel 2 and ERA5 data from the Google Earth Engine (GEE) platform). The results were validated using in situ measurements and census statistics and indicated a stable performance of the HLM based on calibration datasets across China, with a correlation coefficient (r) of 0.81 and a relative root mean square error (rRMSE) of 12.59 %. With regards to validation, the ChinaWheatYield30m dataset was highly consistent with in situ measurement data and statistical data (p<0.01), indicated by an r (rRMSE) of 0.72** (15.34 %) and 0.69** (19.16 %). The ChinaWheatYield30m is a sophisticated dataset with both high spatial resolution and excellent accuracy; such a dataset will provide basic knowledge of detailed wheat yield distribution, which can be applied for many purposes including crop production modeling and regional climate evaluation. The ChinaWheatYield30m dataset generated from this study can be downloaded from https://doi.org/10.5281/zenodo.7360753 (Zhao et al., 2022b).

Aerosol Optical Depth Retrieval for Sentinel-2 Based on Convolutional Neural Network Method

Atmospheric aerosol significantly affects the climate environment and public health, and Aerosol Optical Depth (AOD) is a fundamental optical characteristic parameter of aerosols, so it is important to develop methods for obtaining AOD. In this work, a novel AOD retrieval algorithm based on a Convolutional Neural Network (CNN) method that could provide continuous and detailed aerosol distribution is proposed. The algorithm utilizes data from Sentinel-2 and Aerosol Robotic Network (AERONET) spanning from 2016 to 2022. The CNN AOD data are consistent with the AERONET measurements, with an R2 of 0.95 and RMSE of 0.049 on the test dataset. CNN demonstrates superior performance in retrieving AOD compared with other algorithms. CNN retrieves AOD well on high reflectance surfaces, such as urban and bare soil, with RMSEs of 0.051 and 0.042, respectively. CNN efficiently retrieves AOD in different seasons, but it performs better in summer and winter than in spring and autumn. In addition, to study the relationship between image size and model retrieval performance, image datasets of 32 × 32, 64 × 64 and 128 × 128 pixels were created to train and test the CNN model. The results show that the 128-size CNN performs better because large images contain rich aerosol information.

Rabbits (Oryctolagus cuniculus) increase caecal calcium absorption at increasing dietary calcium levels.

Hindgut fermenting herbivores from different vertebrate taxa, including tortoises, and among mammals some afrotheria, perissodactyla incl. equids, several rodents as well as lagomorphs absorb more calcium (Ca) from the digesta than they require, and excrete the surplus via urine. Both proximate and ultimate causes are elusive. It was suggested that this mechanism might ensure phosphorus availability for the hindgut microbiome by removing potentially complex-building Ca from the digesta. Here we use Ussing chamber experiments to show that rabbits (Oryctolagus cuniculus) maintained on four different diets (six animals/diet) increase active Ca absorption at increasing Ca levels. This contradicts the common assumption that at higher dietary levels, where passive uptake should be more prevalent, active transport can relaxand hence supports the deliberate removal hypothesis. In the rabbits, this absorption was distinctively higher in the caecum than in the duodenum, which is unexpected in mammals. Additional quantification of the presence of two proteins involved in active Ca absorption (calbindin-D9K CB; vitamin D receptor, VDR) showed higher presence with higher dietary Ca. However, their detailed distribution across the intestinal tract and the diet groups suggests that other factors not investigated in this study must play major roles in Ca absorption in rabbits. Investigating strategies of herbivores to mitigate potential negative effects of Ca in the digesta on microbial activity and growth might represent a promising area of future research.

The Endangered Sardinian Grass Snake: Distribution Update, Bioclimatic Niche Modelling, Dorsal Pattern Characterisation, and Literature Review.

The Sardinian grass snake, Natrix helvetica cetti, is an endangered endemic snake subspecies with a restricted and highly fragmented geographic distribution. Information on its ecology and detailed geographic distribution are scarce and may negatively impact on its conservation status. Therefore, a literature review on its taxonomy, morphology, ecology, and conservation is presented here. Moreover, field records from the authors, citizen science and the existing literature provide an updated geographic distribution highlighting its presence within 13 new and 7 historic 10 × 10 km cells. Bioclimatic niche modelling was then applied to explore patterns of habitat suitability and phenotypic variation within N. h. cetti. The geographic distribution of the species was found to be positively correlated with altitude and precipitation values, whereas temperature showed a negative correlation. Taken together, these outcomes may explain the snake's presence, particularly in eastern Sardinia. In addition, analysis of distribution overlap with the competing viperine snake (N. maura) and the urodeles as possible overlooked trophic resources (Speleomantes spp. and Euproctus platycephalus) showed overlaps of 66% and 79%, respectively. Finally, geographical or bioclimatic correlations did not explain phenotypic variation patterns observed in this highly polymorphic taxon. Perspectives on future research to investigate N. h. cetti's decline and support effective conservation measures are discussed.

Analysis of Injuries and Cause of Death in Fatal Accidents with Farm Tractors

Abstract Farm tractor accidents are a frequent cause of death for people in agricultural field of work. The aim of this study was to evaluate the characteristics of the fatal farm tractor accidents, as well as the most significant types of injuries and causes of death. Research is based on epidemiological criteria of subjects, traffic participation, cause of death, distribution of injury, outliving period and toxicological details. The study included 22 (4.2%) farm tractor related fatalities out of all 525 subjects who died from sustained injuries or complications of the injuries sustained in road traffic accidents. The highest number of deaths was reported in men in 95.5%. The highest percentage died of bleeding out (41%), while in 18% of cases, complications that occurred during the outliving period were the cause of death. Analyzing injuries through organ systems, it is observed that the highest number of farm tractor drivers had a chest injury (90%), and the most common chest injury was a rib fracture (82%). When determining the outliving period, the highest number of fatal farm tractor drivers died at the scene of accidents (68.2%). Of all of the subjects, 32% were under the influence of alcohol, while 23% had blood alcohol concentration level greater than 0.5 ‰. The high mortality of farm tractor drivers can be reduced by introducing a mandatory rollover protective structures system and the use of a seat belt in farm tractors with cabs, which would reduce the possibility of the driver falling out of the farm tractor seat and additional injuries due to rollover.

Advances in the Co-Simulation of Detailed Electrical and Whole-Building Energy Performance

This article describes recent co-simulation advances for the simultaneous modeling of detailed building electrical distribution systems and whole-building energy performance. The co-simulation architecture combines the EnergyPlus® engine for whole-building energy modeling with a new Modelica library for building an electrical distribution system model that is based on harmonic power flow. This new library allows for a higher-fidelity modeling of electrical power flows and losses within buildings than is available with current building electrical modeling software. We demonstrate the feasibility of the architecture by modeling a simple, two-zone thermal chamber with internal power electronics converters and resistive loads, and we validate the model using experimental data. The proposed co-simulation capability significantly expands the capabilities of building electrical distribution system models in the context of whole-building energy modeling, thus enabling more complex analyses than would have been possible with individual building performance simulation tools that are used to date.

A new species of Jacaena Thorell, 1897 (Araneae: Liocranidae) from Guiyang, southwestern China.

A new species belonging to the liocranid genus Jacaena Thorell, 1897, J. guiyang sp. nov., is described from southwestern China. A detailed description, diagnosis, photographs, and distribution map of the new species are given. DNA barcodes of the species were obtained and confirmed matching of the sexes, and are available for future use.

A Machine Learning Framework for Quantifying Chemical Segregation and Microstructural Features in Atom Probe Tomography Data.

Atom probe tomography (APT) is ideally suited to characterize and understand the interplay of segregation and microstructure in modern multi-component materials. Yet, the quantitative analysis typically relies on human expertise to define regions of interest. We introduce a computationally efficient, multi-stage machine learning strategy to identify compositionally distinct domains in a semi-automated way, and subsequently quantify their geometric and compositional characteristics. In our algorithmic pipeline, we first coarse-grain the APT data into voxels, collect the composition statistics, and decompose it via clustering in composition space. The composition classification then enables the real-space segmentation via a density-based clustering algorithm, thus revealing the microstructure at voxel resolution. Our approach is demonstrated for a Sm-(Co,Fe)-Zr-Cu alloy. The alloy exhibits two precipitate phases with a plate-like, but intertwined morphology. The primary segmentation is further refined to disentangle these geometrically complex precipitates into individual plate-like parts by an unsupervised approach based on principle component analysis, or a U-Net-based semantic segmentation trained on the former. Following the composition and geometric analysis, detailed composition distribution and segregation effects relative to the predominant plate-like geometry can be readily mapped from the point cloud, without resorting to the voxel compositions.

Artificial grassland mapping using artificial grassland detection index of vegetation growth in the Three-River Headwaters region

Mapping the spatial distribution of artificial grassland for ecological restoration is of great significance for evaluating its secondary degradation and negative consequences, such as nonpoint source pollution of water bodies in the Three-River Headwaters (TRH) region. Because of the numerous challenges faced in obtaining ground training samples caused by adverse natural conditions, inclement cloudy weather and spectral similarity between natural and artificial grassland, commonly used classification or temporal-profile extraction methods have proven ineffective in identifying artificial grasslands. To overcome these challenges, we present a novel artificial grassland detection index for mapping their distribution using optical images with a resolution of 10 ∼ 30 m, along with their corresponding quality control data based on the Google Earth Engine cloud computing platform. The index is calculated using the ratio of the normalized difference vegetation index during the sowing and emergence period and the growth peak period of artificial grassland. A case study was conducted in Maqin County in the TRH region covering an area of 1.35 × 104 km2 from 2017 to 2021. Our proposed method demonstrated high accuracy and achieved a favorable balance between commission errors and omission errors. Over the study period, the average overall accuracy and Cohen's kappa were 96.2% and 0.91, respectively; with average precision, recall, and F1-score of artificial grassland being 89.6%, 99.2%, and 94.0%, respectively. The proposed method exhibited excellent robustness for the critical threshold used, with the average overall accuracy, F1-score, precision, and recall of artificial grassland between 2017 and 2021 consistently exceeding 90% for threshold values ranging from 1.5 to 2.0 throughout the study period. These findings suggest that our proposed method is capable of efficiently and accurately obtaining the detailed spatiotemporal distribution of artificial grassland in the TRH region. Moreover, the method also meets the pressing requirement for the rapid acquisition of detailed spatiotemporal distribution of artificial grassland across the Qinghai-Tibet Plateau.

Vanilla cameroniana (Orchidaceae, Vanilloideae), a new species from French Guiana and new records from the Guiana Shield

In this study, a new species of Vanilla from French Guiana is described with detailed illustrations, photographs, and distribution. Vanilla cameroniana honors Kenneth M. Cameron, a distinguished professor at the University of Wisconsin-Madison, for his contributions to our understanding of the subfamily Vanilloideae. The new species is placed within Vanilla subgenus Xanata, due to its distinctive penicillate callus and lip margins connate to the column. Vanilla cameroniana can be distinguished from V. appendiculata, a morphologically similar species by the broader leaves up to 12 cm wide (vs. 5.9 cm), axillary inflorescence (vs. apical), narrow linear petals, 0.2–0.3 cm wide (vs. narrowly lanceolate, 0.5–0.8 cm), unlobed lip (vs. trilobed), and sub-quadrate apex (vs. sub-acute) with a trullate-shaped structure close to the apex made of short appendages (vs. long lombricoid appendages). Detailed morphological comparisons are provided for other superficially similar species. Additionally, based on herbarium collections V. sprucei, and V. dressleri are newly recorded from the Guiana Shield, and a geographic range expansion is proposed for Vanilla corinnae. Our findings highlight the importance of conservation efforts of fragile ecosystems such as swamps in the Guiana Shield.

Elevated light-frame wood residential building physical and numerical modeling of damage due to hurricane overland surge and waves

An experimental program of a 1:6 scale elevated wood frame shear-wall residential building was developed to model the damage progression of buildings subjected to increasing hurricane surge depth and wave conditions until collapse. This paper presents testing and system identification methods used to characterize structural engineering properties of the physical model that accumulated damage during hydrodynamic testing under increasing surge depth and wave heights. Methods used include (a) quasi-static lateral load-deformation testing, (b) out-of-water dynamic structural characterization testing under free vibration, ambient vibration, and forced vibration, conducted on the test specimen prior to hydrodynamic testing, (c) in-water dynamic structural characterization during hydrodynamic testing, (d) quantification of accumulated damage in hydrodynamic testing through observed changes in the laser scan point cloud data of the specimen, and (e) finite element model updating. The accumulated damage in the test specimen is correlated to changes in modal features (frequency, damping, and mode shapes) assessed using two output-only system identification (SID) methods. In addition, finite volume numerical models are used to determine detailed pressure distributions on the test specimen which are coupled with finite element (FE) models that are updated, in a phased manner, to understand the contribution of structural and nonstructural components on the modeled stiffness and strength of the physical model. Lastly, the impact of the damage on the modal features of the physical model of the building and their sensitivity to FE model assumptions are presented.

Distribution of macrophages in the developing cochlea of the common marmoset, a primate model animal.

Macrophages are essential immune cells in the cochlea that contribute to inflammation, tissue repair, and homeostasis. They also play an important role in local cochlear immunity. The developmental immigration and maturation of macrophages in the cochlea have been investigated and are considered essential for normal hearing acquisition. Most of our current knowledge regarding cochlear development is based on rodent models because of the ethical challenges of using human fetal samples for research. However, inter-species differences between rodents and humans have been reported. In this study, we used a primate animal model to investigate the distributions of macrophages in the developing cochlea. The common marmoset (Callithrix jacchus), a small monkey species that inhabits the New World, was used as the model. We investigated the distribution of macrophages in the developing cochlea of the common marmoset by performing immunohistochemical analyses of cochlear tissue from common marmoset embryos at different development stages. We revealed detailed distribution changes in the macrophages of a primate animal model cochlea. This observation indicates that most of the changes in the general distribution of macrophages were well preserved between rodents and this primate. The distribution changes observed in the common marmoset were also compatible with observations in the human fetus; although, observations in the human fetus are limited. Our observations in this study also revealed several differences between common marmosets and rodents. The time course of immunological development and maturations established in this study will aid in the study of the primate-specific developmental biology of the inner ear. These observations may eventually lead to new therapeutic strategies for hearing loss in humans. In addition, understanding the immunological steady-state of the cochlea may help in the study of age- and genetic-induced hearing loss and in the design of regenerative therapies.

Sinking into the ocean? Climate change risks and second home planning

Second homes are essential resources for tourism and recreation. Climate change is projected to transform tourism geographies and threaten economic and recreational activities. Based on building and housing register data and national models for climate change hazards, this paper investigates whether second homes in Denmark are potentially affected. Five different hazards are used to describe climate risk based on the RCP8.5 scenario: sea level rise, storm surge events, coastal erosion, flooding from watercourses, and terrestrial groundwater. It is estimated that between 2020 and 2070 a significant number of second homes will potentially be affected by one or more of these hazards, with terrestrial groundwater being the most frequent. GIS-analysis shows the detailed geographical distribution of the affected second homes, while regional grouping highlights the most affected regions. A compound risk analysis demonstrates that a significant proportion (approximately 25%) of the Danish second homes will be affected by either one or more hazards. The analysis thereby highlights how amenity rich geographies are threatened by climate change, which could cause these areas to become risk prone. This provides a background for discussing the implications for land use policy of transforming geographies. The article highlights a need for strategic planning and active engagement with second to protect the recreational potential of second homes and local economies in coastal zones.