bluuebunny/crossref_metadata_2025 huggingface dataset:
An example of reflexive and ethical work on a geoscientific speculation bubble: the case of natural hydrogen
Authors: Marc Odin , Monnier Loïs , Coriat Mickael
Published: March 2024

Recently, in the context of intensifying calls for a rapid decarbonation of the economy and energy systems, there has been a growing interest in developing the use of hydrogen, either as a fuel or as an energy storage system. However, hydrogen production suffers from various drawbacks, due to its carbon footprint or cost, which has led the field of geosciences to renew its interest in the possibility to collect naturally occurring hydrogen (so called "white hydrogen"), found in gas reservoirs or in hydrothermal waters for example, or stimulate natural production of hydrogen before harvesting it (so called "orange hydrogen").Querying the Web of Science database, the average number of annual scientific publications including "natural hydrogen" in their title or abstract, was steady around 2 between 1984 and 2016, it was 6 over 2017-2019, 16 over 2020-2022 and reaching 27 in 2023, thus appearing to follow an exponential growth. Similarly in media in France we retrieved 37 articles mentioning "natural hydrogen" between 2010 and 2019, with terms such as "infancy", "pilot project" or "future energy?" , while there were 44 between 2020-2022 and 227 in 2023 alone, with terms such as "rush", "game changer", "revolution" or "bright hopes".This exponential growth and the rapid shift toward very enthusiastic vocabulary make us hypothesize that the rising interest in natural hydrogen is a process similar to an economic bubble, in which a commodities is over-valued during a transient period.In this work we will present reflexive work based on an analysis of the recent scientific literature and on associated media coverage, on basic comparisons between energy available from recent H2 fluxes or estimated reservoirs and from other renewable energy sources, and on semi-directive interviews of some geoscientist specialists of hydrogen.These elements allow us to confront this hypothesis and to gain insights on the intertwined effects that may favor the over-valuation of natural hydrogen. In particular, we also discuss reasons why geoscientists contribute, actively or not, to the growth of a speculative bubble, a mechanism generally associated with irrational market dynamics. We do so by exploring the potential roles of undeclared conflicts of interests, temptation to access facilitated research funding, lack of interdisciplinary analysis, and of the predominant belief that technological innovation or adjustments is needed and sufficient to address the ecological emergencies.
Refinements to harmonic tidal predictions in estuaries and shallow water.
Authors: Williams Joanne , Hibbert Angela
Published: March 2024

Harmonic analysis is used to predict tidal heights from observations or model data. The usual method is to fit tidal constituents, at frequencies informed by astronomical cycles. In most cases the higher harmonics of these frequencies are sufficient to provide a good model of the tide to within observational accuracy, and successfully predict tides for decades outside the observational period, even including double high and low water and seasonal variations.In shallow bays or estuaries the propagation of the tidal wave slows, leading to very slow draining of the water and much faster rise. The tidal waveform is closer to a saw-tooth shape than sinusoidal. So least-square fit of harmonics leads to Gibbs ringing artefacts around the discontinuity in slope just before the tide rises. These are often several tens of cm in the macrotidal regime of the UK, and complicate the assessment of surge modelling.Though the problem is not new, we are still seeking a consistent and universally applicable solution. In practice manual corrections are often applied at individual sites. Or with enough data, more harmonics can be fitted to minimise the false peaks, but at the risk of over-fitting. In this presentation we quantify the severity of this problem in UK estuarine sites, improvements using the response method, and the subsequent effect on total water level  for operational storm surge forecasting.
Geological risk analysis of geothermal developments in a sedimentary basin, Hungary
Authors: Markó Ábel , Tóthi Tamara , Szilágyi Imre , Mádl-Szőnyi Judit
Published: March 2024

In our research, we develop a novel methodology to evaluate the geological uncertainties of geothermal exploration in order to quantify them. The outcomes can be used as inputs when deciding on new geothermal investments. Adapted from the hydrocarbon industry probability of success is evaluated by estimating potential geological risk factors which can hinder geothermal production and reinjection, following the risk assessment scheme of petroleum play analysis.As a case study in a clastic geological environment, we test the methodology on the Zala Basin, a sedimentary subbasin of the Pannonian Basin, Hungary. Here, the Neogene (so-called Pannonian) sediments form one of the principal thermal water-reservoirs. Although the preliminary geothermal potential of the Zala region (SW Hungary) is assessed to be good, there is a need for more thorough analysis before starting new developments. As an example, heterogeneity of the deltaic and fluvial deposits poses geological risk. In our case study, we consider the risk of insufficient temperature, the absence of the appropriate aquifer formations, the bad quality of the aquifer i.e., the unfavourable distribution of the high permeable sandstone bodies, the insufficient permeability and flow rate as well as the potential risk of unsuccessful reinjection. This is done by combining and evaluating datasets from well data (lithology, well logs, well tests) and 3D seismic measurements. The goal of the assessment is to decide whether a future geothermal system can provide sufficient capacity, in the current case, for industrial or agricultural heat utilisation.The first author was supported, and the research was financed through the KDP-2021 Cooperative Doctoral Programme of the Ministry of Innovation and Technology (Hungary) from the source of the National Research, Development and Innovation Fund, grant number: KDP_2021_ELTE_C1789026. The study was funded by the National Multidisciplinary Laboratory for Climate Change, RRF-2.3.1-21- 2022-00014 project.
Realistic representation of forest harvesting for large-scale models – integrating harvest information from national forest inventories to LPJ-GUESS
Authors: Suvanto Susanne , Lindeskog Mats , Olin Stefan , Piltz Karl , Pugh Thomas A. M.
Published: March 2024

Harvesting of wood is one of the key processes of forest management, strongly impacting the structure and dynamics of European forests. This makes accounting for it crucial in any large-scale analysis of forest ecosystems. Yet, the representation of forest harvests in large-scale models is typically far from realistic, as the actual management regimes are not well described by simple rules or even by formal management guidelines.Here, we show an implementation of national forest inventory (NFI) -based forest harvesting regimes in a demographic vegetation model, LPJ-GUESS. In our approach, the probability of harvest in the model simulation is based on frequency of harvest events in the NFI data in forests with similar structure and geospatial location. Similarly, the characteristics of the harvest event (the percentage of the removed tree basal area and, in case of partial harvests, the tree size targeted in the harvest) are based on the observed harvest events in the data, and depend in the simulation on forest structure and location. This means that model simulations are dynamic, responding to the real state of the forest. We demonstrate this with several countries in Europe, for which we have earlier created NFI-based harvest regimes based on analysis of more than 180 000 forest plots. Forests are simulated with LPJ-GUESS with different forest harvesting set-ups, allowing us to compare the outcome of the suggested NFI-based harvest implementation to other approaches, including simplified clear-cut rules and density-based thinning (based on Reineke’s rule). In addition, the simulation results are compared to observational evaluation data.Moving from simple rule-based approaches to observed NFI-based harvest regimes can bring the model simulations closer to how forests are actually currently managed. Our approach blending big data and dynamics modelling has potential to both enable improved assessments of continental-scale carbon dynamics and provide a realistic reference to which potential future forest management changes can be compared to.
Using neural networks for predicting soil water storage based in situ soil moisture observations
Authors: Bischof Balazs , Zehe Erwin , Loritz Ralf
Published: March 2024

Previous studies have shown that Long-Short Term Memory networks (LSTMs) offer a large potential for data-based learning and hydrological predictions. This study focuses on exploring the largely untapped potential of such modeling approach using a large sample of in-situ soil moisture data based on Time-Domain Reflectometry (TDR) measurements, collected across the Attert experimental basins in Luxembourg. Soil moisture plays a critical role in various hydrological processes, influencing groundwater recharge, governing infiltration dynamics, and contributing significantly to the generation of overland flow. Additionally, it stands as a key determinant for the water supply essential for sustaining vegetation and agricultural crops. Here we introduce an LSTM model that has been trained on extensive long-term in-situ soil moisture observations with the objective of extrapolating the dynamics of soil moisture across spatial dimensions, temporal scales, and depths. A key challenge in this context is how to deal with multiscale variability of TDR observations, which arising from small scale variations in soil texture scales as well as larger scale spatial variability of physiographic and meteorological characteristics. Acknowledging, that this multiscale variability of soil moisture is difficult to disentangle by standard available predictors and their gradients, we place particular emphasis on data processing and understanding of such variability. This emphasis is crucial to mitigate potential confusion within the model, ensuring a more accurate representation of soil moisture dynamics. For this purpose, we evaluate the efficacy of LSTMs in capturing soil moisture dynamics, while concurrently aiming to clarify variability and address uncertainty. Furthermore, employing clustering techniques and network theory approaches, our aim is to discern systematic variability and patterns, considering model performance and the relationships within soil moisture measurement time series. As a result, we demonstrate the advantages of employing LSTMs to assess soil moisture dynamics at the catchment scale, while emphasizing the exploration of drawbacks and limitations inherent in purely data-based learning. This analysis provides a valuable guide for future modeling attempts, offering an opportunity to depict spatial and temporal variations in soil water storage. Such representations prove beneficial in the development of early-warning systems for potential dry events.
Colocated airborne observations from MOSAiC enable sea ice process understanding and new model parameterization development
Authors: Zampieri Lorenzo , Hutter Nils , Cocetta Francesco
Published: March 2024

State-of-the-art sea ice models struggle to accurately simulate historical sea ice thickness changes, which could be partially due to inadequate representation of dynamics and thermodynamic processes. High-resolution observations are fundamental tools for improving our understanding of the sea ice physical processes, validating numerical models, and ultimately formulating better sea ice parameterization. Winter observations collected during the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in winter 2019-2020 are unique tools for evaluating our models during the freezing season. However, a shortcoming of these observations is that they cannot be easily combined due to differences in measurement techniques and processing chain, impeding a comprehensive characterization of the sea ice system and limiting their diagnostic employment with models. Here, we present an advanced spatiotemporal colocation algorithm designed to integrate airborne measurements collected during multiple helicopter surveys, which provide a two-dimensional characterization of the sea ice surface temperature through infrared camera images and of the surface elevation through an airborne laser scanner at a resolution of approximately one meter over areas spanning several kilometers. The co-located temperature and elevation fields can be combined with boundary layer observations and ground-based transect surveys via drift correction approaches. These observations put in relation for the first time snow freeboard with the equilibrium skin temperature resulting from the surface energy balance while resolving small-scale thickness features (e.g., snow dunes, ridges, and refrozen leads). We will showcase how this innovative observational dataset enables multi-category sea ice model evaluation and the development of new parameterizations. 
Towards understanding aromatic SOA by studying the molecular level oxidations mechanisms of xylene isomers
Authors: Iyer Siddharth , Kumar Avinash , Barua Shawon , Zhao Jian , Savolainen Anni , Seal Prasenjit , Pichelstorfer Lukas , Roldin Pontus , Ehn Mikael , Rissanen Matti
Published: March 2024

Aromatic compounds like xylene contribute significantly to the formation of tropospheric secondary organic aerosol (SOA) that have strong implications on health and on climate. The sources of this class of molecules are primarily anthropogenic, but biogenic sources of aromatics can be significant too. To form SOA, the volatile xylene needs to oxidize into low volatility aerosol precursors with multiple oxygen containing polar functional groups called highly oxygenated organic molecules (HOMs). It does this through the autoxidation mechanism, which is a sequential process involving peroxy radicals where each intra-molecular reaction step such as an H-atom shift is followed quickly by O2 addition. While laboratory measurements using the sensitive chemical ionization mass spectrometer (CIMS) instrument indicate rapid conversion of xylene to HOM, this is unsupported by established oxidation mechanisms. This is due to the assumed stability of the crucial bicyclic peroxy radical (BPR), an intermediate that is intrinsic to aromatic oxidation in general. Recently, we showed that the BPR associated with toluene oxidation can be unstable, and its decomposition is pivotal to the subsequent autoxidation mechanism that leads to HOM. [1] Through investigating the autoxidation mechanisms of xylene in this work, we establish the importance of aromatic derived BPR decomposition to the formation of SOA. We combine theoretical modelling with sub-second HOM measurements using CIMS to develop the Aerosol Dynamics gas- and particle-phase chemistry model for laboratory CHAMber (ADCHAM) code [2] for xylene that is robust at reproducing the SOA mass yields we measure from our chamber experiments. We also show that the underlying autoxidation mechanisms are remarkably similar for many of the atmospherically dominant monocyclic aromatics, which opens the remarkable prospect of significantly improved model predictions of aromatic SOA even in the absence of theoretical and experimental data.[1] Iyer, S., Kumar, A., Savolainen, A. et al. Molecular rearrangement of bicyclic peroxy radicals is a key route to aerosol from aromatics. Nat. Commun. 14, 4984 (2023). https://doi.org/10.1038/s41467-023-40675-2[2] Roldin, P., Eriksson, A.C., Nordin, E.Z., Hermansson, E., Mogensen, D., Rusanen, A., Boy, M., Swietlicki, E., Svenningsson, B., Zelenyuk, A. and Pagels, J., 2014. Modelling non-equilibrium secondary organic aerosol formation and evaporation with the aerosol dynamics, gas-and particle-phase chemistry kinetic multilayer model ADCHAM. Atmospheric Chemistry and Physics, 14(15), pp.7953-7993.
Lesson Proposal for Climate Change in geography: Utilization of "Mystery" as a Learning Method
Authors: Yamauchi Hiromi
Published: March 2024

Miyagi Prefecture, in Japan, where my students and I live, faces the Pacific Ocean, named Sanriku east offing fishing ground, where we can see the "tidal current" where the Kuroshio and Oyashio currents meet. Therefore, both warm-water and cold-water fish species can be seen in the coastal waters. Miyagi Prefecture is also a place where different terrains intersect, such as the submerged coast of the Rias coast and the emergent coast of the coastal plain. Matsushima, one of the Three Views of Japan, is also a gift of such complex terrain. So, several fishing ports boasting some of the largest catches in Japan can be seen, and seafood is essential to our daily lives.One of the brokers at the Shiogama wholesale market has always said this in recent years, "The sea is strange lately, the kinds of fish that are usually landed are often not landed." This is corroborated by data from the Fisheries Agency and others. The catch of cold-water fish species such as salmon is decreasing, and the catch of warm-water fish species such as yellowtail and gazami-Japanese blue crab- is increasing. The rise in sea temperature in coastal waters since 2014 also corroborates this. In other words, climate change is having an impact on the status of seafood landings.On the other hand, this sea area has undergone significant crustal changes due to The 2011 off the Pacific coast of Tohoku Earthquake, and the seabed has been eroded by tsunamis, or conversely, inflow from land has been deposited on the seabed. As a result, the ecosystem of the seabed has changed significantly.It is impossible to learn all of this in the curriculum of high school social studies geography in Japan, and collaboration with other subjects such as science is necessary. However, not only that, but I propose to learn with students about the impact of climate change from changes in the ocean using the learning method "Mystery" that originated in the UK, which can capture the complex relationship between the global environment and human life. This is because geography is a subject to learn about “RELATIONSHIPS WITHIN PLACES: Humans and Environments”.
Performance evaluation of a high-precision timing receiver based on the BDS-3 PPP-B2b service
Authors: Lyu Daqian , Pan Jifei , Liu Fangzheng , Wang Jie
Published: March 2024

    The precise point positioning (PPP) timing service has been proposed in recent years and has been demonstrated to achieve sub-nanosecond accuracy. As an integral part of BDS-3, the PPP services via b2b signals (hereafter referred to as PPP-B2b) are provided by BDS-3 GEO satellites with better than decimeter-level accuracy for users around China. In this research, a high-precision timing receiver based on the BDS-3 PPP-B2b service has been established, which obtains the local clock offset with respect to Beidou Time (BDT) through PPP time transfer, and controls the local clock of the receiver according to the clock offset. The 1PPS output of the receiver clock is adjusted to the BDT.    First, the performance of the time transfer is evaluated. The experimental results of two links show that a level of 0.20 ns can be achieved with a convergence time of 20 minutes. Second, the timing performance of the receiver is examined using UTC(NTSC) as a reference. The timing accuracy is better than 0.2 ns in terms of standard daily deviation, and the frequency stability could reach about 2 × 10-14 in 1 day. Third, we compare the time synchronization performance between two receivers using rubidium and a crystal oscillator as the external clock, respectively. When the average time exceeds 10s, the time variance and the Allan variance of the scheme using rubidium clocks is better than the scheme using crystal oscillators.
What control reactions in unsaturated soils? On the dynamic effect of small-scale heterogeneity and (spatially variable) diffusion
Authors: Henri Christopher , Diamantopoulos Efstathios
Published: March 2024

Soils are complex systems where different physical, chemical and biological processes occurring simultaneously and interact in a non-linear way. This includes the diffusion process, which is known to be affected by the tortuosity, and therefore the water content. Additionally, the high degree of soil heterogeneity poses significant challenges in studying soil reactivity due to its high impact on mixing. In this study we evaluate the effect of a series of what we could be key controlling factors of effective reaction rates in soils at the plot scale: the degree of heterogeneity, the hydraulic structure, the reaction rate, the initial distribution of reactants, and the heterogeneity in the diffusion coefficient.We tackle this by explicitly simulating hypothetical biomolecular soil reaction (A+B → C) for different degrees of heterogeneity, different hydraulic structures, different reaction rates, different initial distribution of the reactants and different representation of diffusion. Results are evaluated in terms of effective reaction rates at the plot scale.The simulation results reveal that mixing conditions control reactions in unsaturated soils. Non-ideal reactivity due to mixing-limited conditions is not only a consequence of the simple presence of heterogeneity or even of its intensity. Instead, it results from (at least): the characteristics of heterogeneity, the Pe number, the Da number, the spatial distribution of the reactants. Interestingly, the spatial variability of the (tortuosity-dependent) diffusion coefficient appears to also have a significant effect on mixing conditions.  By these results, we illustrate the high complexity of reactive systems in unsaturated soils, which makes the use of average macroscopic reaction rates (as in most agriculture, environmental and geoengineering models) at least questionable.
Is temperate ice a good paleoclimatic archive? Insights from the Adamello temperate ice core (Italian Alps)
Authors: Baccolo Giovanni , Di Stefano Elena , Brugger Sandra O. , Brütsch Sabine , Jenk Theo , Eichler Anja , Delmonte Barbara , Maggi Valter , Schwikowski Margit
Published: March 2024

Glaciers are well known for providing valuable climatice and environmental information which are made available through the retrieval of ice cores. Not all glaciers are equal in this respect, however. The best sites to drill ice cores for paleoclimatic purposes are the cold portions of accumulation basins. The term cold, when referred to ice, indicates ice whose temperature is constantly below the pressure melting point. The importance of cold sites for ice core science is related to the fact that under cold conditions, the stratigraphic signals used for paleoclimatic reconstructions are best preserved because of the absence of meltwater.Because of climate change, cold portions of mountain glaciers are rapidly changing. The rise of atmospheric temperature is impacting the thermal properties of ice and firn, leading to their warming. As a consequence of this, many cold accumulation basins of high-altitude glaciers are turning to temperate and their mass balances are approaching negative values. This is posing issues on the ability of glaciers to preserve climatic and environmental signals. This is related to two distinct processes. At first, temperate ice, by definition contains a fraction of liquid water which can interfere with the preservation of chemical and physical signals. Secondarily, negative mass balances related to increased melt rates, imply the loss of upper ice layers, obliterating the most recent stratigraphic signals normally used for calibration with instrumental data.The possibility to retrieve reliable paleoclimatic records from mountain glaciers in the future, is thus questionable. This will only be possible if the ice core science community develops new methods and competencies to extract information from temperate ice addressing meltwater disturbances. To this aim, a 223 m long ice core was drilled in 2021 at the Adamello glacier, in the Italian Alps. At the drilling site (3100 m a.s.l.) the glacier has a negative mass balance and a temperate regime. Thus, the site is ideal to test to what extent temperate ice can be used as a paleoclimatic archive.To this aim, a set of paleoclimatic proxies has been investigated in the upper part of the ice core. We present here preliminary results. They show that while most of the analytes are significantly affected by meltwater percolation and regelation, some of them, in particular the less soluble ones, still exhibit a detectable seasonality. This has allowed to develop a chronology, estimate the age of surface ice and identify what proxies are best preserved in temperate ice.
Validation on the content of clay and organic matter of a digital soil map across Denmark - A median-soil texture perspective
Authors: Motevalli Alireza , Børgesen Christen Duus , Vangsø Iversen Bo , Pesch Charles
Published: March 2024

Detailed soil maps are an essential tool for water resource, land management and agricultural planning. However, due to different soil processes and variation in geology, soil textural properties vary in space at different scales challenging the development of accurate soil maps. Despite the advances in sampling and efforts to produce accurate maps, uncertainties remain at many scales. Therefore, by implementing error evaluation methods such as comparing predictions and observations, it is possible to understand the performance of digital soil maps. The aim of this work was to obtain the uncertainties of soil categories from a Danish national soil map (AC map) based on measured contents of soil texture and soil organic matter. The AC maps describes the horizon characteristics (soil texture, soil organic matter, soil horizon depths and bulk density) at three depths corresponding to the A (0-30 cm), B (30-70 cm), and C (70-120 cm) horizon. In addition, it combines information on soil classification (soil texture), geology at a depth of ca. 1.5 meters as well as the national geological region. The map has a spatial resolution of 250 meters in the A and B horizons and 500 meters in the C horizon. The analysis is based on 38,000 textural points for the A horizon, 7,000 points for the B horizon, and almost 1,700 points for the C horizon. Considering mean and medians of the content of clay and organic matter together with the observed data, the AC map was validated. The uncertainties of the AC map, statistical correlation coefficient (R2), root mean square error (RMSE), and the Nash-Sutcliffe efficiency (NSE) were used. The results showed that the AC map has an acceptable performance when predicting the clay content in the A horizon (R2 = 0.97, RMSE = 1.15%, and NSE = 0.91), B horizon (R2 = 0.95, RMSE = 1.85%, and NSE= 0.8), and C horizon (R2 = 0.74, RMSE = 5.32%, and NSE = 0.41, respectively. The performance of the prediction of organic matter content in the A horizon (R2 = 0.84, RMSE = 0.39%, and NSE = 0.65) and B horizon (R2 = 0.66, RMSE = 0.44%, and NSE = 0.32) horizons was acceptable as well. Also, the result of validation showed that the highest residual errors of AC maps for clay content and organic matter content has been related loamy (>15% clay) and peat soils. In conclusion, the AC maps, with its optimal accuracy especially in the A and B horizons, can be a suitable tool for use at variable scales in the analysis of crop growth and nitrate leaching modelling studies.Keywords: Soil texture, digital soil maps, soil variability, soil organic matter, clay, soil properties
High-Resolution Analysis of the 2023 Seismic Swarm Offshore Malta
Authors: Grigoli Francesco , Cesca Simone , Bocchini Gian Maria , D'Amico Sebastiani , Agius Matthew
Published: March 2024

In January-February 2023 a seismic sequence took place in the Central Mediterranean Sea,  ~90 km south of the island of Malta, and ~200 km from the coast of Sicily. The seismicity started in Mid January, in a region that experienced only sparse seismicity in the past. In the following days several M4+ events occurred. The largest earthquake, with moment magnitude Mw 5.3, took place a couple of weeks after the unrest onset, on January 30. The seismicity continued for several weeks, before fading down. Later seismicity was observed and still going on. This recent, unusual seismicity offers a unique opportunity to investigate seismogenic processes in this region with unprecedented detail. However, analyzing seismic sequences in offshore environments presents significant challenges due to the absence of optimal seismic monitoring conditions. These limitations compromise the effectiveness of conventional data analysis techniques, hindering the characterization of offshore seismic sequences. We tackled these limitations through the adoption of advanced, waveform-based seismic data analysis techniques that allow to investigate offshore seismic sequences, with the aim to provide insights into their origin. We combine full-waveform based detection and template matching methods to enhance the detection of events, advanced location techniques based on Distance Geometry Solvers (DGS), and probabilistic waveform-based methods for seismic source characterization. We combine the seismic source analysis for the 8 largest earthquakes in the sequence, with magnitude exceeding ML 4.5, with waveform-based and statistical analysis of the seismicity. About 500 events are identified. Their locations map a narrow lineament extending ~NW-SE. Full moment tensors for the largest events identify normal faulting mechanisms with a similar orientation, and shallow centroids of ~5 km depth. This result, combined with a waveform similarity analysis, suggests a predominant mechanism for the entire sequence. Using different seismicity indicators we classify the 2023 sequence as a seismic swarm. Indeed, the largest events in the sequence occur weeks after the unrest onset. Compared to previous seismicity, the sequence was outstanding in terms of maximum magnitude, seismicity rate and moment rate. While normal faulting earthquakes are not unusual in the Central Mediterranean, they differ from the few focal mechanisms previously proposed for the swarm focal region, which has important implications, considering that normal faulting earthquakes at shallow depth pose a tsunami hazard in the region.
It’s the little things that count – how microbial dynamics affect simulation results of the systemic soil model BODIUM
Authors: König Sara , Weller Ulrich , Reitz Thomas , Diel Julius , Wollschläger Ute , Vogel Hans-Jörg
Published: March 2024

Mechanistic simulation models are essential tools for predicting soil functions such as nutrient cycling, water filtering and storage, productivity, and carbon storage as well as the complex interactions between these functions. Most soil functions are driven or affected by soil microorganisms. Yet, biological processes are often neglected in soil function models or only implicitly considered in form of unspecific, effective rate parameters. This can be explained by the high complexity of the soil ecosystem with its dynamic and heterogeneous environment, and by the range of temporal and spatial scales at which these processes take place.We integrated different microbial processes and feedbacks into our systemic soil model BODIUM (König et al., 2023) and tested the sensitivity of soil functions such as productivity and nutrient cycling to these microbial aspects at the scale of soil profiles. This includes flexible C:N ratios, carbon use efficiency, nitrogen fixation, feedback with root exudation, and the dynamics of different functional groups such as fungi and bacteria. We observed a high sensitivity of our simulation outcomes to microbial parameters related to the microbial component, such as the exudation rate or fungal/bacterial resistance to environmental conditions. This shows the high relevance of microbial processes for soil functions at the field scale, but also indicates that the process description should be further improved.  In process-based models, a high sensitivity of parameters is often a sign for an instable process description relying too much on site-specific calibration instead of mechanistic understanding.We will discuss how to improve this, but also further extensions, including an approach that accounts for the spatial distribution of microorganisms within the pore space. König, S., Weller, U., Betancur-Corredor, B., Lang, B., Reitz, T., Wiesmeier, M., Wollschläger, U., & Vogel, H.-J. (2023). BODIUM—A systemic approach to model the dynamics of soil functions. European Journal of Soil Science, 74(5), e13411. https://doi.org/10.1111/ejss.134
A Self-learning Weight Calibration Based Residual Dense Network for Soil Moisture Downscaling
Authors: Wei Yingtao , Lin Liupeng , Li Jie , Feng Ruyi , Li Huifang
Published: March 2024

Soil moisture is a key state variable in the ecosystem. However, existing soil moisture products often cannot have both high spatial resolution and long time series. Therefore, it is important to downscale the soil moisture products for fine application. So far，the soil moisture downscaling methods can be summarized as satellite-based methods, model-based methods, and learning-based methods. Satellite-based methods can integrate the advantageous features of different satellite, but face challenging in practical applications due to spatiotemporal differences and cloud coverage. Model-based methods offer superior interpretability of physical processes, but the model parameters are difficult to obtain and cannot fully characterize the non-linear mapping relationship in real physical processes. Learning-based methods have the prominent ability to fit nonlinear relationship, while existing learning-based methods do not take the correlation and redundancy between various covariates into consideration, and the extraction of key features is insufficient. Hence, we proposed Self-learning Weight calibration based soil moisture Downscaling Network (SWDN) to couple the learning-based model with the weight calibration strategy for improving the products accuracy, as shown in Fig 1.The proposed SWDN constructs a complex mapping relationship model from multi-factor geoscience parameters to soil moisture. Under this framework, the residual dense connection network is adopted as the backbone for feature extraction and guides the reconstruction of soil moisture spatial information. The spatial weight and multi-factor weight self-learning modules are designed to adaptively calibrate feature weights of spatial direction and multi-factors, respectively. By updating parameters of above two modules, the weights of key features are enhanced and the weights of redundant features are weakened to achieve efficient extraction of discriminative features. Subsequently, under the assumption of scale invariance, model from geoscience parameters to soil moisture is fully trained on low spatial resolution data and applied on high spatial resolution geoscience parameters to generate high-precision soil moisture products. Experiments on the Western Continental United States dataset show that the proposed SWDN method exhibits superior performance with higher consistency with in-situ measurements and richer spatial texture information over the comparison methods. Compared to the state of the art downscaling methods, results demonstrate that the R and RMSE reach 0.44 and 0.077 , which improve 16% and 5% respectively. The maps of soil moisture distribution before and after downscaling are shown in Fig 2.Fig.1. The structure of the SWDN method for soil moisture downscaling.Fig.2. Mapping of SM distribution before and after downscaling on 2017.7.17. (a) Original SMAP; (b) BPNN downscaled SM; (c) DBN downscaled SM; (d) RDN downscaled SM;(e) SWDN downscaled SM.
3D LAND-MARINE PROPERTIES ADMINISTRATION IN THE CONTEXT OF SEA LEVEL RISE (SLR) – ISSUES & CHALLENGES
Authors: Abdul Rahman A. , Hassan M. I. , Musliman I. A. , Rashidan H. , Mutiarasari W. M. , Zamzuri A. , Buyuksalih G. , Gazioglu C. , Bayirhan I.
Published: March 2024

Abstract. The current scenario of understanding spatial objects with regards to land and marine environment seems lacking. Inevitably, the scenario in line with the global warming issues as being highly mentioned by world-bodies such as the United Nations (UN) on climate change, etc. Recently the statistics on earth surface temperature point towards high record temperatures that lead to sea-level rise and degradation of land surface area, in general. These situations caused other spatial objects (land and marine properties) to be affected by their physical properties’ changes (including geometries and locations). Thus, this paper attempts to review various aspects related to digital twins of land and marine spatial objects with respect to issues and challenges of multiple data acquisition techniques considering accuracy, data standard, seamless and integrated georeferenced data within the scenario as being reported in the 6th IPCC document. The situation warrants us to explore different types of land and marine properties (static and dynamic) where static properties are defined as immovable objects and vice versa for the dynamic environment. This paper also discusses on a brief experiment utilizing MERIT DEM (Multi-Error-Removed Improved-Terrain Digital Elevation Model), existing building footprints, simulated bathymetry, and land use datasets. The experiment reveals the prediction of the sea level rise according to the IPCC report. The gist of this paper to serve a motivation for our near-future research in the context of geospatial components and sea level rise (SLR).
RANDOMISED COMPRESSION RATIOS FOR EFFECTIVE LARGE POINT CLOUD PROCESSING USING COMPRESSIVE SENSING
Authors: Qiu Z. , Nagesh S. , Martínez-Sánchez J. , Arias P.
Published: March 2024

Abstract. Effectively navigating the intricacies of extensive 3D point cloud data in urban environments poses a series of formidable computational challenges. These challenges are primarily attributed to the substantial data volume and density inherent in urban settings, the presence of noise and inconsistencies within the collected data, and the constraints imposed by limited transmission bandwidth, which consequently impact storage requirements. This paper introduces an innovative methodology for handling large point cloud datasets, based on concepts from Sparse Signal Processing (SSP), also known as compressive sensing. The proposed approach integrates well known geometric data manipulation such as the Octree to work hand in hand with SSP, as unified method. Through experimental validation using the Santiago Urban Dataset (SUD), we demonstrate the effectiveness of our method in achieving high data fidelity, as measured by Peak Signal-to-Noise Ratio (PSNR) values reaching approximately 60 dB even at substantial compression ratios. Comparative analysis against traditional methods, including those implemented in the widely used Point Cloud Library (PCL), reveals the superior performance of our proposed methodology. The results underscore the robustness and efficiency of our approach, positioning it as a compelling alternative for compressing extensive 3D point cloud data. This has crucial implications for diverse applications, ranging from city planning to rapid and effective disaster response.
SPATIALLY AWARE LANDSLIDE SUSCEPTIBILITY PREDICTION USING A GEOGRAPHICAL RANDOM FOREST APPROACH
Authors: Teke A. , Kavzoglu T.
Published: March 2024

Abstract. Landslide susceptibility prediction practices have been increasingly reliant on non-geographically-oriented (i.e., aspatial) machine learning algorithms. While these approaches have exhibited increasing success, they have often faced criticism for their limited consideration of spatial autocorrelations and local variations across geographical space, thereby neglecting the concept of spatial non-stationarity. To fulfill the research gap, this work applies a geographical random forest (GRF) approach, contrasting it with the conventional random forest (RF) algorithm. To this end, the study area, encompassing the Lake Sapanca Basin and its surroundings, was subdivided into 4,452 slope-based mapping units. The effectiveness of both predictive models was then measured by using overall accuracy (OA) and area under the curve (AUC). The results revealed that the GRF (OA = 80.82% and AUC = 85.22%) outperformed the RF algorithm (OA = 75.34% and AUC = 82.50%) by approximately 5% in OA, and demonstrated a 3% improvement in AUC score. The Wilcoxon signed-rank test confirmed significant differences (95% level) between the predictions of both models. The slope parameter emerged as the globally most influential factor, but local interpretations disclosed notable variations in the importance of causative factors contingent upon location. For instance, the curvature parameter was the most important geospatial covariate in around one-third (34.23%) of the slope units, mostly concentrated in the northernmost zones of the study area. On the other hand, elevation was the most important factor for 14.67% of the slope units primarily located in the southern region.
ERROR ANALYSIS OF VISUAL ODOMETRY FOR A SMALL SIZE UNMANNED AERIAL VEHICLE
Authors: Bettemir Ö. H.
Published: March 2024

Abstract. Usage of small size Unmanned Aerial Vehicle (UAV) with autonomous flight capability became widespread at both civil and military applications because of its low costs and ease of use. However, inertial or GPS based positioning and orientation sensors can be disabled at battlefields and the UAV losses its path in a short time. Visual odometry becomes a solution for the aforementioned hassle. Real-time detection of ground control points, matching the same control points at the stereo pair images and correcting the position and orientation data with least square adjustment are the challenges of visual odometry. In this study, error analysis of position and orientation of a UAV flying through mountainous region which cannot obtain any augmenting data for position and orientation is conducted by error propagation law. The flight of UAV is simulated with exact initial position and orientation data. Optic images of ground obtained by nadir directed camera are georeferenced using the digital elevation model of the region, interior and exterior camera parameters. The digital elevation model is used to correct the relief displacement. The stereo-pair image is obtained when the UAV flies 200 m and image coordinates of the common control points are detected by colinearity equations. Position and orientation of UAV is corrected by least square adjustment and the process is repeated for each obtained image acquired at 200 m interval. The analysis revealed that the precisions of horizontal and vertical positioning becomes 75 and 200 meter, respectively. The precision of roll angle becomes worse than 0.5 degree, while the precisions of pitch and yaw angle are estimate to be better that 0.1 degree.
Chikki: Food from De-oiled Peanut Cake
Authors: Arun K Tyagi  , N. G. Shah  , M. Vinjamur
Published: March 2024

A “Tel-Ghani” (Indian traditional oil-expression unit) of about 150 kg/day of peanuts, yields about 5% less oil from peanuts than mechanical oil expeller, and is an important entrepreneurial activity in villages. De-oiled cake fetch low price as animal feed. Use of peanut cake in snack food as chikki was attempted for value addition to improve the economics of the Tel-Ghani. Preparation of the snack, technical specifications of processes involved, characterization of the snack in terms of colour, texture, and sorption isotherms to predict keeping quality and economic analysis are reported. Chikki made from ground deolied cakepowder containing 16.3 % residual oil and having added 20% jaggery, 12% sugar, 8% liquid glucose and 4% vanaspati ghee scored best in sensory evaluation. The product - chikki not only provides a protein-rich food, but also improves the economics of Tel-Ghani.
A study on clinical characteristics and management of anaphylaxis in Emergency Department
Authors: Duong Le Xuan
Published: March 2024

Objective: The aim of this study was to describe clinical features and outcome of patients with anaphylaxis at the Emergency Department - 108 Military Central Hospital in 2021. Subject and method: A cross-sectional, retrospective descriptive study of 146 anaphylaxis patients who came to Emergency Department - 108 Military Central Hospital in 2021. Result: Drug-induced anaphylaxis accounted for 65.8%, of which: Antibiotics accounted for 17.7%, vaccines accounted for 27.1%, contrast agents accounted for 10.4%. Common symptoms were: Mucocutaneous lesion (98.6%), respiratory (16.4%), digestive (6.8%), cardiovascular (4.8%), neurological disorders (2.1%). Anaphylaxis of grade I accounted for 76.7%, grade II accounted for 18.5%, grade III accounted for 4.8% and there was no anaphylaxis of grade IV. There was no statistically significant relationship between the degree of anaphylaxis and the entry of the allergen. The fluid transfusion counted for 100%, corticosteroid use (91.1%), dimedrol (84.2%), adrenaline (23.3%), oxygen therapy (13.7%) and invasive ventilation (0.7%). Conclusion: The main cause of anaphylaxis was drug-related, the most common symptom of anaphylaxis was manifestation of mucosal skin, the anaphylactic subjects were mainly grade I. Most of patients was complete recovery.
Clinical, paraclinical features and the surgery outcomes of chronic otitis media with cholesteatoma at 108 Military Central Hospital
Authors: Thao Nguyen Thi Phuong
Published: March 2024

Objective: To assess the clinical features and the surgery outcomes of chronic otitis media with cholesteatoma. Subjects and method: A retrospective, descriptive study was conducted on fifty-six patients underwent a surgery to remove cholesteatoma at the Ear, Nose and Throat (ENT) Department at 108 Military Central Hospital from January 2019 to September 2023. Result: Most of patients presented at the late stage with years of clinical symptoms: Otorrhea (92.9%), hearing loss (100%). One-third of the subjects had a severe to profound hearing loss. 89.3% had scutum and ossicles erosion on CT scan images. Cholesteatoma was found at epitympanum location most of the time (83.9%). Incus was the most likely to be eroded ossicle (83.9%). No significant hearing improvement was found postoperatively. No complications and no recurrences in a long-term follow up. Conclusion: Although most of patients presented at the late stage, our micro-surgery for cholesteatoma removal still had favorable outcomes.