esa-sceva/satcom-chunk-collection huggingface dataset:
# A SAR-Based Index for Landscape Changes in African Savannas
## Materials and Methods
### Index of Landscape Change
We chose a hexagon grid with a diameter of 1 km as a unit of analysis which aggregates the NR values of inherent LULC classes according to their spatial proportions within the grid cells. We chose hexagons as spatial units because they are suitable to represent nearest neighbor areas in a regular structure and, compared to rectangles, reduce sampling bias at their edges. Additionally, they are reported to support visual inspection of spatial patterns [105]. These NR values can then pairwise be compared per grid cell in order to retrieve its percentage increase or decrease of resources for different time increments. An example for the calculation of the NRD\({}_{w}\) is given in Figure 3.  
Figure 4 shows the design of the study: Based on the eight SAR images eight LULC classifications have been derived. The weighted index for Natural Resource Depletion is then calculated per image pair. The result is shown as an example for the first image pair of 2007 and 2008. This map indicates the spatial distribution of changes as well as their estimated impact on natural environment. Figure 4: Left: Design of the approach: Each classified image delivers aggregated values of natural resources. Right: Changes between the years are expressed as weighted Natural Resource Depletion (NRD\({}_{w}\)), demonstrated for the period between 2007 and 2008. Figure 3: Calculation of the weighted Natural Resource Depletion Index (NRD\({}_{w}\)).
###### Abstract  
Energy consumption, because of population development, is progressively increasing. For this reason, new sources of energy are being developed, such as that produced from the combustion of biomass. However, this type of renewable energy has one main disadvantage, the production of waste. Biomass bottom ash is a residue of this industry that currently has not much use. For this reason, this research evaluates its use as a filler in bituminous mixtures, since this sector also has a significant impact on the environment, as it requires large quantities of raw materials. With this objective, first, the physical and chemical properties of biomass bottom ashes were evaluated, verifying their characteristics for their use as filler. Subsequently, bituminous mixtures were conformed with biomass bottom ash as filler, and their physical and mechanical properties were analyzed through particle loss and Marshall tests. The results of these tests were compared with those obtained with the same type of mixture but with conventional and ophite aggregates. This study confirmed that biomass bottom ash was viable for use as a filler, creating mixtures with a higher percentage of bitumen, better mechanical behavior, and similar physical properties. In short, more sustainable material for roads was obtained with waste currently condemned to landfill.  
biomass bottom ash; energy production; waste-to-energy; discontinuous grading; bitumen emulsion; bituminous mixture; filler; circular economy; sustainable construction +
Footnote †: journal: Applied Sciences
## 3 The Modeling and Simulation Architecture
### Security  
In our approach, we considered minimal characteristics related to the security of the data processed in the simulation processes, to provide similarity to a real environment. Some protocols and technologies were selected to maintain the security of data transfer and storage.  
The EMQ broker guarantees the authentication of MQTT clients with client ID, username/password, IP address, and even HTTP cookies [32]. Confluent provides transport layer security (TLS) encryption, simple authentication and security layer (SASL) authentication, and authorization via access control lists (ACLs) [33].  
Regarding data storage, MongoDB facilitates authentication through the salted challenge response authentication mechanism (SCRAM) and x.509 certificate authentication. Additionally, MongoDB employs role-based access control (RBAC) to govern access to a MongoDB system and supports transport layer security and secure sockets layer to encrypt all of MongoDB's network traffic [34].  
On the other hand, some of the components of our system are supported on the Google cloud infrastructure whose security is designed in layers that include physical components and data centers, secure communication between services, protected access to services from the Internet, etc. [35] Additionally, K8s also provides some possibilities to configure node, container, and pod security [36].
## 1 Introduction
In general, to achieve optimum yields regardless of the substrate used, plants must be supplied with an adequate amount of a nutrient solution to compensate for high evapotranspiration rates and to ensure an adequate source of nutrients, along with the draining of excess amounts of nutrients and ensuring the availability of oxygen to the root system to avoid the accumulation of salt in the root zone [17; 18; 19]. Plants exposed to high concentrations of salt experience osmotic stress, which leads to water deficits and unhealthy growth. These factors negatively affect the physiological and metabolic processes of plants, such as photosynthesis, respiration, and cell division [20; 21; 22; 23]. The accumulation of sodium (Na\({}^{+}\)) and chloride (Cl\({}^{-}\)) in plants prevents the intake of nutrients (K\({}^{+}\), Ca\({}^{++}\), Mg\({}^{++}\), and NO\({}^{3-}\)) and leads to reductions in vegetative growth and yield [24; 25]. Crops that can be hydroponically grown with saline water are limited to salt-tolerant and moderately salt-tolerant species, such as tomato, asparagus, cucumber, rose, and carnation. Even among salt-tolerant species, varietal differences may exist. Varietal trials need to be conducted to determine the most tolerant varieties. The salt tolerance of a variety, its stage of development, the frequency of irrigation, and the addition of deficit nutrients are several factors to be considered when using saline water. Tomato plants have been reported to be a moderately salt-tolerant crop [26; 27; 28]. In previous research, salt stress was found to result in reduced growth and yield. However, salt stress produced fruits of better quality, which fetched higher market prices [29; 30; 31; 32]. Tomato has been characterizedas salt-sensitive and reported to be more susceptible to high salinity (8.7 dS m\({}^{-1}\)) at an early stage of development than in late growth stages [31]. However, [PERSON] et al. [33] observed that the effects of salt stress could be fully revocable by discharging excess amounts of salt from tomato roots, provided that the plant parts have not attained the rapid growth stage at a salinity level of 9.0 dS m\({}^{-1}\). Therefore, this study aimed (i) to assess the effects of salinity on three tomato cultivars grown under hydroponic conditions on perlite substrate by examining the morphological features (plant height, stem diameter, and leaf area), mineral concentrations in plant tissues (chlorophyll, Na\({}^{+}\), Ca\({}^{2+}\), and K\({}^{+}\)), fruit size, and yield, and (ii) to evaluate the effect of grafting for alleviating the effects of salinity and the water use efficiency (WUE) of these tomato crops, induced by three salinity levels (EC values of \(\sim\)2.5, \(\sim\)6.0, and \(\sim\)9.0 dS m\({}^{-1}\)) and four nutrient solutions (N1-N4).
# A Simple Unsupervised Knowledge-Free Domain Adaptation for Speaker Recognition
## 1 Introduction
(4) Using the resulting LDA matrix to transform speaker embedding vectors of speech from the target domain, compensating for potential distributional distortion. We refer to this clustering-based full-rank LDA model as _C-LDA_. In theory, the full-rank LDA does not alter the discrimination capacity of the embedding vectors; instead, it aims to discover a new set of coordinates where both within-class variance and between-class variance align along the coordinate axes. This enables speaker vectors, after the LDA transform, to be suitable for cosine scoring. Therefore, C-LDA should  
Figure 1: The t-SNE plot visualizes the speaker vectors of CN-Celeb1 extracted by a model pre-trained on VoxCeleb. Each color represents a speaker. be viewed as an embedding normalization approach. It is important to note that C-LDA does not require any knowledge of the system and the source data, making it _knowledge-free_. Interestingly, this simple linear transform, derived without reference to any prior knowledge, yields notably good performance, even outperforming approaches that require full or partial knowledge and significant computation. In summary, the contribution of this paper is three-fold:  
1. We introduced a novel speaker recognition adaptation approach called C-LDA. This method is simple (involving a linear transform), unsupervised (utilizing clustering without human labels), and knowledge-free (requiring no knowledge of models and source data). These characteristics make it highly suitable for real-world applications. 2. It was demonstrated that the C-LDA adaptation is highly effective and even outperforms the more complex front-end and back-end approaches in both multi-domain and single-domain adaptation scenarios. Additionally, the performance of C-LDA is robust against the setting of hyperparameters. 3. The success of C-LDA further demonstrated our hypothesis that domain mismatch faced by speaker recognition systems based on deep models is primarily attributed to distributional distortion in the embedding space, rather than a decrease in discriminability.
# Potential of Advanced Consolidants for the Application on Sandstone
## 3 Results and Discussion
### Application of the Consolidants on the Sandstone
#### 3.3.3 Mechanical Testing in Macroscale  
Due to the treatment with octylamine-catalyzed SiGel consolidants, there is a systematic decrease in the surface area (Table 6), which is in agreement with the smooth and uncracked character of the xerogels. Sample SiGel ZnO-oa/d exhibited an anomalous behaviour with a ten-fold increase in the surface area and formation of microporosity. The surface of the KSE OH-treated sample is comparable with the untreated sample, even if it should decrease due to the filling of pores, especially of the finer ones. The reasonable explanation is a cracking of the xerogel inside the pores, which created an additional surface area. The performance of the SP FX consolidant, characterized by an increase in the surface area and formation of micropores, is comparable with the SiGel ZnO-oa/d. Using the DAP consolidants, there was only a limited decrease in the surface area, which is in agreement with the very low dry matter yield for these samples. Compared to the untreated sandstone, the drilling resistance for the treated samples increased (Table 6). However, this increase depended substantially on the consolidant used. Regarding the consolidant SiGel-oa without nanoparticles, only a very limited increase in the force was observed. However, importantly, the stone retained its cohesion after weathering, as the resistance force decreased only by 21%. Concerning the SiGels containing SiO\({}_{2}\) nanoparticles, some modification effect of their surface was observed. The surface coating with octyl-groups decreased the resistance force in comparison with the other two types of particles. Moreover, SiGel SiO\({}_{2}\)-octyl-oa exhibited low durability. The reason is probably the practically complete coverage of the SiO\({}_{2}\) particles with octyl-groups. The performance of SiGel containing TiO\({}_{2}\) nanoparticles was slightly better than that of both commercial products, exhibiting higher durability. Interestingly, the SiGel containing ZnO nanoparticles, catalyzed by both amine and organometallic compounds, exhibited an exceptionally high resistance force, even after the weathering treatment. This performance might be due to the unusual micro-mesoporous texture of the xerogel and the solubility of the ZnO nanoparticles. A reaction occurred between the zinc ions and the xerogel-formed ions during the course of the sol-gel process. Similar reactions can be expected during the process of accelerated weathering. Finally, both HAP samples exhibited a reasonable degree of consolidation and excellent durability. The BET surface areas measured after the weathering treatment partially correlated with the resistance force. Samples with a small surface area after the weathering treatment (less than 1 m
## 2 Project Overview  
A water conservancy project tunnel in Xinjiang is located in the denuded, structurally complex hilly region on the southern slope of Mount Taishan, with elevations ranging from 650 to 800 m above sea level. The tunnel, with a diameter of 7.8 m, is being constructed using an open-type TBM. The total excavation length of the TBM is 26.5 km, divided into three sections: Sections 1-3. The surrounding terrain is relatively flat, with minor height variations (10-20 m, locally up to 70 m), and the area features a desert landscape with exposed bedrock.  
The primary lithologies in the exposed strata include gneiss, tuffaceous sandstone, bi-otite plagioclase gneiss, biotite plagioclase schist, and Late Variscan (y33b) granite. During the design phase, exploration data revealed four significant erosion gullies (referred to as Gully 1 through Gully 4) on the tunnel's roof in Sections 2 and 3. Notably, when the TBM passed through Gully 1, the surrounding rock was highly fractured, leading to the cutter head becoming stuck. This situation pointed to the presence of fault zones where the cave roof forms a gully, posing significant safety hazards, including the risk of TBM equipment damage and the jamming of the cutter head and shield body.  
Additionally, the section of the tunnel in the erosion gully area (Gully 1) is located within an erosion-affected low hill region of the Altai Mountains, where bedrock is largely exposed. The section is characterized by faults that can potentially impact tunnel stability. A total of ten faults (f120, f56, f121, f122, f158, f123, f124, f125, f126, and f159) were identified, with the most significant being fault f56. This fault exhibits a fracture zone width of 6-12 m and a strike of 55\({}^{\circ}\)NW/\(\angle\)80\({}^{\circ}\). The fault extends over a distance of 15-18 m and has a considerable impact on tunnel stability. Other smaller faults, ranging from 0.3 to 5 m in fracture zone width, have moderate effects on stability.  
In Sections Gully 2 and Gully 3, nine additional faults (f43, f106, f107, f108, f109, f110, f111, f112, and f113) were identified. Among these, faults f111 and f55 are of particular concern, with fracture zones 5-10 m wide, a strike of 55\({}^{\circ}\)NW/\(\angle\)70\({}^{\circ}\), and orientations 85\({}^{\circ}\) to the tunnel axis. These faults extend over 12-19 m, contributing to tunnel stability issues. Other smaller faults, with fracture zones 2-3 m wide and lengths between 10 and 36 m, also affect stability. To ensure construction progress and mitigate the risks associated with these fault zones, detailed explorations of Gully 2 through Gully 4 were conducted, with the results summarized in Table 1. The geological profile of the erosion gullies and fault zones is illustrated in Figure 1. Crossing these fault zones remains a critical challenge to maintaining the safety and efficiency of the TBM operation.
# A Study on a Radio Source Location Estimation System Using High Altitude Platform Stations (HAPS)
## 2 Methods for Estimating the Location of Radio Transmission Sources
### Estimation Method Using the Beamformer Method
Using the estimated direction of arrival, the radio wave source is estimated by triangulation, as shown in Figure 5:9 However, in the case of multiple incoming radio waves, if the main lobe of the antenna pattern shown in Figure 5 faces a certain radio wave while the side lobes (in the direction of relatively high gain) coincide with the direction of other radio waves, the output voltage will include not only one wave but also other waves, and it is not guaranteed that the evaluation function may always have a peak in the desired direction of arrival. In addition, when radio waves with almost similar arrival angles are incident, it may not be possible to distinguish the two waves when scanning with the main lobe having a wide angle of arrival, as shown in \[y(t)=\mathbf{W}^{H}\mathbf{X}(t) \tag{5}\]0 In such cases, the angular resolution of location estimation by the Beamformer method becomes low, and the peak value may not accurately represent the power of the signal. In fact, as shown in [14] which studied the direction of arrival estimation using the Beamformer method in a multipath environment, the estimation accuracy is degraded depending on the number of arriving waves. There is also the Capon method, which directs the main lobe in one direction while at the same time attempting to reduce the output contribution from other directions. However, all of these methods use the main lobe of the antenna pattern, and the angular resolution of the estimation is limited. Therefore, it is difficult to apply the Beamformer method to the scenarios of ground emitters in urban areas where many radio waves arrive.
# Evolution of V2X Communication and Integration of Blockchain for Security Enhancements
## 5 Issues and Challenges in 5G and Edge-Based V2X
### Resource Scaling  
Resource scaling is one of the main functionalities of cloud or MEC computing. It denotes the process of edge/cloud resources being dynamically allocated, such as CPU and memory. This function plays a crucial role, as it leverages the necessary dynamics and elasticity of the network. While considering the 5G Key Performance Indicators (KPIs), such as throughput, latency, reliability massive machine communication, etc., it is important to determine the effects and usefulness of the current resource scaling strategies on V2X network performance.  
Most of the above mentioned issues in 5G and edge based MEC in V2X can be solved by integrating Blockchain technology. The blockchain can solve the issues that are related to data integrity, transparency, traceability, and data privacy. The blockchain provides data integrity by using the Merkle Tree. Similarly, DAG and blockchain records the data in immutable manner and ensures that the data are trustable and the records cannot be altered, modified, or deleted. The data availability issue can be solved by storing the data temporarily at the local MEC servers and then utilizing the pre-fetch methods related with the cache. The interoperability issues can be handled using automation tools that are used to handle user side operations related to the cloud service application. The automation tools consists of adapters that works with several cloud services provided by various cloud service providers [49]. The latency can be reduced by integrating 5G networks with high bandwidth MEC, using Virtualized Network Functions (VNF) and implementing efficient offloading algorithms for controlling and managing traffic flow from vehicular nodes to the MEC servers. The distribution of wireless resources in edge computing should be dynamically adjusted without any centrally controlled manager to ensure high QoS. Blockchain is well suited to such instances by offering distributed ledgers to update resources in a fully automated and reliable manner. A research work in used blockchain to build a decentralized resource distribution system that overcomes the weakness of previous systems based on centralized techniques. The scaling issue can be tackled by using vertical and horizontal scaling architecture. In a vertical architecture, several mini resource pools are positioned at the selected edge locations and an efficient task offloading mechanisms is used for locally processing data on the edge device. The scaling issue can be tackled using vertical and horizontal scaling architecture. In vertical architecture, several mini resource pools are positioned at the selected edge locations and an efficient task offloading mechanisms is used for processing data locally on the edge device. Similarly, the horizontal scaling architecture is based on Opportunistic Edge Computing (OEC) [50] that owns the computing resources in a distributed fashion and lease the resources to the system based on short contracts.
## 3 Quantitative Analysis: Overview of Selected Studies
In this context, robust numerical solvers and domain-specific heuristics contribute to capturing fluid-structure interactions and potential failure modes. Additionally, multi-stage optimization frameworks [40; 41] enable planners to manage sequential decision-making tasks, such as reconfiguring transport routes or scheduling downtimes in a manner that balances short-term production goals with long-term reliability and sustainability. Figure 6: Frequency of key terms in abstracts. The chart illustrates the most common keywords, with “Condition Monitoring” leading the list, followed by terms like “Data Mining” and “Predictive Maintenance”. Moreover, specialized studies such as \"aviation engine monitoring\" [42, 43] provide insight into how high-risk, safety-critical methodologies from the aerospace industry can be adapted to the harsh realities of both open-pit and underground mining. Similarly, \"intelligent instrumentation\" [44, 45] reflects the growing intersection between hardware advancements (e.g., miniaturized sensor nodes, low-power wireless modules) and sophisticated analytics. Collectively, these cross-sectoral adoptions indicate that mining is not an isolated field but rather part of a broader transition towards Industry 4.0 and intelligent industrial systems [46, 47, 48, 49, 50]. In mining, these external influences translate into new sensor fusion strategies, more precise fault detection, and opportunities for real-time control, effectively reimaging conventional maintenance practices. The following subsections further explore the identified thematic clusters. Each subsection links the quantitative results from bibliometric and keyword analyses with qualitative perspectives on methodological advancements, domain-specific challenges, and key application areas. This layered perspective clarifies how contemporary research is addressing the unique demands of predictive maintenance in mining, shaped by extreme conditions, high capital investments, and the imperative of operational continuity and safety.