esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
Environmental thresholds use a similar concept of the \"degree of vegetation stress\" or \"accumulation of stress factors\" to identify environmental stress loads that are critical for ecosystem failure or ecostype conversion [42]. Detecting significant temporal patterns in ecosystem performance is especially challenging because of the substantial [43, 44] and increasing role of fire disturbance [3] and insect damage [4, 20]. Interannual weather variations [19], often related to the PDO [23] also confound the temporal patterns in performance. To reduce the complex response of ecosystem performance to these factors [3], we used ecosystem models that account for variations of weather in moderate resolution satellite imagery and built upon the methodology of previously successful efforts [5, 39] that tracked forest fire succession and grazing effects in the central United States [40]. Similar approaches that detrend spectral responses for weather and site conditions to assess range condition and management effects have been applied in Africa [45, 46, 47] and Australia [48]. The separation of climate and human influences through this approach combined with entropy analysis was also proposed by [PERSON] _et al_. [49] as a method to identify causes of change. Our objectives were to (1) evaluate boreal forest performance departures from expected conditions in the Yukon River Basin over the 2000-2008 period; (2) separate the influence of weather on performance to reveal disturbance; (3) assess successional dynamics of ecosystem performance following fire using a chronosequence; and (4) model future equilibrium (non-disturbed) ecosystem performance in 2040 and 2070..
# Spatial Sound Rendering Using Intensity Impulse Response and Cardioid Masking Function
###### Abstract  
This study presents a new technique for creating spatial sounds based on a convolution processor. The main objective of this research was to propose a new method for generating a set of impulse responses that guarantee a realistic spatial experience based on the fusion of amplitude data acquired from an omnidirectional microphone and directional data acquired from an intensity probe. The advantages of the proposed approach are its versatility and easy adaptation to playback in a variety of multi-speaker systems, as well as a reduction in the amount of data, thereby simplifying the measurement procedure required to create any set of channel responses at the post-production stage. This paper describes the concept behind the method, the data acquisition method, and the signal processing algorithm required to generate any number of high-quality channel impulse responses. Experimental results are presented to confirm the suitability of the proposed solution by comparing the results obtained for a traditional surround 5.1 recording system and the proposed approach. This study aims to highlight the potential of intensity impulse responses in the audio recording and virtual reality industries.  
room acoustics; room impulse responses; sound intensity; spatial sound; spatialization Article
# Towards 6G Satellite-Terrestrial Networks: Analysis of Air Mobility Operations
## 7 Conclusions  
The link budget analysis achieved a positive link margin for the given data, indicating successful communication between the transmitter and the UAM vehicle. The effect of velocity and altitude on various link parameters and quality of service metrics i.e., latency, were also studied. This study was done while considering different weather attenuations. A loss model was formulated, taking all the losses into account.  
In the second part, a study on mobility and handover analysis was carried out for a UAM vehicle moving on a straight-line path, using the entropy method and considering three base stations. The signal strength at the UAV from three ground base stations and one satellite base station along the flight path was studied. It was observed that the satellite connection could provide 6G connectivity for only about 250 km on the ground at a time instant. Hence, a larger number of satellites would be required in orbit to provide a 6G terrestrial network to the whole world. The number would depend on the type of service the 6G network aimed to provide.  
This work contributes to the virtual knowledge bank for researchers working toward the successful implementation of robust communication systems for urban air mobility (UAM). This study highlights the effects of altitude and weather on communication systems. It also proves a methodology for signal handover using the entropy method. This study will be useful for use cases involving UAVs in remote areas, such as medical deliveries, mapping, etc.
## 2 Background and Related Work
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Title** & **Year** & **Method Used** \\ \hline Toward Optimal Load Prediction and Customizable Autoscaling Scheme for Kubernetes [12] & 2023 & GRU \\ \hline Intelligent Microservices Autoscaling Module Using Reinforcement Learning [13] & 2023 & RL \\ \hline High Concurrency Response Strategy based on Kubernetes Horizontal Pod Autoscaler [14] & 2023 & custom formula \\ \hline Proactive Horizontal Pod Autoscaling in Kubernetes Using Bi-LSTM [15] & 2023 & Bi–LSTM \\ \hline Container Scaling Strategy Based on Reinforcement Learning [16] & 2023 & RL \\ \hline Autoscaling Based on Response Time Prediction for Microservice Application in Kubernetes [10] & 2022 & ML \\ \hline Traffic-Aware Horizontal Pod Autoscaler in Kubernetes-Based Edge Computing Infrastructure [17] & 2022 & custom formula \\ \hline Horizontal Pod Autoscaling Based on Kubernetes with Fast Response and Slow Shrinkage [18] & 2022 & custom formula \\ \hline K-AGRUED: A Container Autoscaling Technique for Cloud-based Web Applications in Kubernetes & 2022 & GRU \\ Using Attention-Based GRU Encoder-Decoder [19] & 2022 & LSTM–GRU \\ \hline LP-HPA:Load Predict-Horizontal Pod Autoscaler for Container Elastic Scaling [20] & 2022 & LSTM–GRU \\ \hline DScaler: A Horizontal Autoscaler of Microservice Based on Deep Reinforcement Learning [21] & 2022 & RL \\ \hline HANSEL: Adaptive Horizontal Scaling of Microservices Using Bi-LSTM [22] & 2021 & Bi–LSTM \\ \hline Development of QoS-Aware Agents with Reinforcement Learning for Autoscaling of Microservices on The Cloud [23] & 2021 & RL \\ \hline Deep Learning-Based Autoscaling Using Bidirectional Long Short-Term Memory for Kubernetes [24] & 2021 & Bi–LSTM \\ \hline Adaptive Scaling of Kubernetes Pods [9] & 2020 & custom formula \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Scientific papers with converging topics.
# Dynamic Workload Management System in the Public Sector: A Comparative Analysis
## 2 Related Work and Contributions
#### Advancing Workforce Management Through ANFIS: Contributions Beyond Existing Research  
Building upon these studies, our research contributes to the field by integrating Adaptive Neuro-Fuzzy Inference System (ANFIS) into a dynamic workload management framework for the public sector. While previous studies have extensively explored factors such as motivation ([PERSON] et al., 2014) [4], compensation ([PERSON] et al., 2014) [5], employee engagement ([PERSON], 2014) [6], and intellectual capital ([PERSON], 2011) [7] in shaping performance, our approach focuses on quantifying employee capability using machine learning-driven workload metrics. Additionally, research leveraging Artificial Neural Networks (ANNs) ([PERSON] & [PERSON], 2010; [PERSON] et al., 2017; [PERSON] et al.,2023) [12; 13; 15] has demonstrated their effectiveness in modeling complex workforce dynamics. However, our study advances this by employing ANFIS, which not only captures non-linear relationships but also integrates fuzzy logic for greater interpretability in employee capability assessment. Furthermore, while past research has applied ANFIS in various domains, such as manufacturing performance ([PERSON], 2023) [20], education quality assessment ([PERSON] et al., 2020) [22], and organizational cohesion ([PERSON] et al., 2022) [24], our study is among the first to implement ANFIS in dynamic workload distribution within the public sector, addressing critical gaps in real-time task allocation and resource optimization. This research, therefore, complements existing work by providing a novel AI-driven approach to workforce management, moving beyond static evaluations toward a real-time, data-driven optimization model.
## 3 Modal Discretization
Under the small deformation assumption, the transformation matrix \(\mathbf{A}_{b,\ ri}\) and \(\mathbf{A}_{ri,\ b}\) are approximately identity matrices, which makes the angular momentum vector of the gyroscopes  
\[\overset{\rightarrow}{\mathbf{J}}_{ri}=\mathbf{A}_{b,ri}\cdot\mathbf{J}_{ri} \cdot\mathbf{A}_{ri,b}\approx\mathbf{J}_{ri}=\text{diag}(J_{ri}^{x}\,J_{ri}^{y }\,J_{ri}^{z}) \tag{19}\]  
On the other hand, the generalized active force due to the nominal stiffness of the structure is  
\[\mathbf{F}^{A}=\mathbf{\Lambda}_{b}\mathbf{\tau}_{b} \tag{20}\]  
where the stiffness matrix is defined as the diagonal array constituted by the square of the circular frequencies of the beam without any attachments,  
\[\mathbf{\Lambda}_{b}=diag(\omega_{1}^{2},\ldots,\omega_{i}^{2},\ldots,\omega_{m }^{2}) \tag{21}\]Substituting Equations (17) and (20) into [PERSON]'s Equation  
\[\mathbf{F}_{i}^{I}+\mathbf{F}_{i}^{A}=0 \tag{22}\]  
and neglecting the angular accelerations of the gyroscopes, one obtains the final ordinary differential equation governing the generalized displacement  
\[\mathbf{E}_{a}\tilde{\boldsymbol{\tau}}_{b}+\mathbf{G}\tilde{\boldsymbol{\tau} }_{b}+\boldsymbol{\Lambda}_{b}\boldsymbol{\tau}_{b}=0 \tag{23}\]  
where the skew-symmetric gyroscopic matrix \(\mathbf{G}\) is  
\[\mathbf{G}=\sum\mathbf{G}_{i},\ \mathbf{G}_{i}=(\mathbf{R}_{ri}^{2T}\mathbf{R}_{ ri}^{3}-\mathbf{R}_{ri}^{3T}\mathbf{R}_{ri}^{2})J_{ri}^{x}\boldsymbol{\Omega}_{i} \tag{24}\]  
The superscript numbers in Equation (24) denote the row number of the corresponding matrix. The gyroscopic term expressed in the generalized coordinate in Equation (23) plays a key role, which leads to frequency bifurcation and complex modes. The linear gyroscopic ordinary governing Equation (23) can be solved numerically and the natural frequencies and complex modes can be obtained by transferring the generalized variables back into physical deformations via relations (1) and (2).
# Development of Multi-Channel Seismic-Electrical Combined Rolling Coverage Measurement System
###### Abstract  
Electrical and seismic exploration are two widely used geophysical methods in geological surveys. They reflect different geophysical properties of underground rocks, but each method can only provide information from a single perspective of the rock structure's physical parameters. As a result, relying on a single geophysical method can lead to ambiguous interpretations. To address this issue, this paper presents the development of a multi-functional, high-power, multi-channel, rolling, fast measurement system for combined electrical and seismic exploration. The system features the following capabilities: it can be used simultaneously for both electrical and seismic exploration; it supports high-power operation, with a transmission power of up to 10 kW during electrical exploration; it includes multiple measurement channels for rolling measurement and data acquisition, with a sampling rate of up to 100 ksps, significantly improving work efficiency and expanding the frequency range. The distance between channels can be selected from 1 to 20 m, greatly enhancing the system's adaptability to various environments. Additionally, we have designed accompanying upper-level software that not only stores data internally but also displays waveforms in real-time on a computer for monitoring and control. The experimental results demonstrate that the instrument operates stably and meets the requirements for field exploration.  
geophysical instruments; seismic-electrical combined exploration; multi-functional; high power; rolling coverage measurement Article
# Effects of Achilles Tendon Moment Arm Length on Insertional Achilles Tendonopathy
## 4 Discussion
In addition, any measurements of the moment arm length before and after surgery using the suture bridge technique have not been reported to date. As a surgical treatment for IAT, the calcaneal wedge osteotomy takes the influence of the moment arm into account and aims to reduce stress on the insertion of the Achilles tendon by shortening the calcaneus length and slightly lifting the insertion of the Achilles tendon [30]. The suture bridge technique used in the present study has also been reported to have good long-term outcomes [17; 31]. This method can treat various pathological conditions that influence IAT with minimal invasion [31]. Furthermore, by comparing the preoperative andpostoperative data in this study, the postoperative Achilles tendon moment arm was found to be shortened. On the other hand, the force applied to the Achilles tendon was significantly increased in individuals with IAT compared to healthy individuals. This indicates that this method may not reduce the force applied to the Achilles tendon. Rather, it may reduce the length displacement of the Achilles tendon by reducing the Achilles tendon moment arm, thereby reducing the energy applied to the Achilles tendon. There are three limitations to this study. First, the number of cases was small. The study needs to proceed with an increased number of cases, and proper statistical analysis needs to be performed. Secondly, the Achilles tendon insertion is an area, but for the sake of simplicity, it was considered to be a point. Performing 3D analyses allows more precise analyses, and we will need to investigate the area of the Achilles tendon insertion. Third, the moment arm measurement method used in this study was the static evaluation. An X-ray or MRI scan is required to measure the Achilles tendon moment arm after the reconstruction of Achilles tendon insertion using the suture bridge technique. However, it is difficult to measure the dynamic change of the moment arm before and after surgery with the measurement methods reported to date. Therefore, a new measurement method needs to be developed for measuring a dynamic moment arm using X-ray or ultrasonic waves in the future.
# Beyond Prompt Chaining: The TB-CSPN Architecture for
## 7 Comparative Analysis
Figure 7 shows a qualitative comparison of the features of the TB-CSPN and OpenAI Cookbook agent frameworks across six dimensions: agent composition, execution semantics, guard logic, backend flexibility, traceability, and production readiness. TB-CSPN demonstrates strong formalism and modularity, particularly through its use of Petri net-based agent coordination, verifiable thresholds, and openness to heterogeneous AI backends. TB-CSPN excels in interpretability and supports traceable, role-specific workflows involving supervisors, consultants, and worker agents. In contrast, the OpenAI Cookbook prioritizes rapid deployment and LLM-centric collaboration, offering high usability and production maturity. However, it relies heavily on prompt engineering and lacks formal verification capabilities. Its agent composition is modular, yet it is constrained by message-passing patterns and tight coupling with the OpenAI stack. Overall, TB-CSPN prioritizes explainability, compositionality, and agentic rigor, while LangGraph and LangSmith excel in tool maturity and developer accessibility. This juxtaposition highlights the broader tension between formalism and usability in the evolution of agentic AI architectures. The comparative implementations and benchmarking methodologies used in this analysis are available in the public repository, enabling independent validation of these architectural trade-offs in production scenarios. Figure 7: Qualitative comparison of TB-CSPN and OpenAI Cookbook frameworks across six core agentic AI dimensions. TB-CSPN demonstrates superior formalism and modularity through Petri net coordination and verifiable thresholds, while OpenAI Cookbook prioritizes rapid deployment and production maturity. The comparison highlights the trade-off between formal rigor (TB-CSPN) and practical accessibility (OpenAI Cookbook).
# An Ultra-Wideband Vivaldi Antenna System for Long-Distance Electromagnetic Detection
## 3 Verification and Discussion
### Analysis of the Test Results  
The TDT test results are shown in Figure 12. The peak point one was at 17.65 ns--5.295 m, because two antennae were coupled. The peak point two is at 202.3 ns--60.69 m, where the signal was reflected by the target. In Figure 11, L2 is the distance between the transmitting antenna and the target, and L2 is the distance between the receiving antenna and the target. The measured L2 was 30.31 m, and the measured L1 was 30.2 m with w = 4.2 m. Undoubtedly, the measured L1 + L2 = 60.51 m. Considering the electromagnetic wave travel difference, which is determined by the difference between the cable port and the electromagnetic wave feed port, thus, the tested L1 + L2 = 59.6 m.  
Figure 11: Experimental schematic.  
Figure 10: Photos of the proposed antennas. (**a**) Wide beam transmitting antenna. (**b**) Narrow beam receiving antenna.  
The actual and tested position map of the target are plotted in Figure 13. The two blue square dots at the bottom are the transmitting antenna and the receiving antenna. The coordinates (3.278, 30.13) is the measured target point, and (3.138, 29.86) is the estimated result point of the test. It can be seen from the results that the error of the coordinate values of x and y of this test result are both less than 0.3 m, which meets the actual application requirements.
# Lossless Compression of Large Aperture Static Imaging Spectrometer Data +
## 3 Compression Scheme
### The CCSDS-123 Standard  
To facilitate an improved understanding of the experimental results, the CCSDS-123 algorithm is briefly described in this section.
## 5 Implementation  
The experiment of this study establishes a hybrid attack detection system based on the FDD in SDN. It is implemented in Java, deployed on OpenDayLight, which is a popular open-source SDN controller, and obtains flow information through OpenDayLight's REST APIs so that it will not introduce additional loading overhead to the controller. There are two main modules in this system: (1) the Target Link Selection Module (TSM) and (2) the Service Performance Module (SPM).  
The TSM is responsible for calculating which links will be selected as target links. It also calculates the link weight using Formula (1) in [21]. The TSM obtains all flows through the target area in the network to sort those links by link weight from high to low weight. On the other hand, it also needs to know the switch and link positions in the topology and consider the topology and link weight together to the target links. The primary REST APIs used by the TSM mainly include APIs1 and APIs2 to receive all switch flow tables, where APIs1 and APIs2 are as follows:  
* APIs1: /restconf/operational/network-topology:network-topology;
* APIs2: /restconf/operational/opendaylight-inventory:nodes/node/switch/table.  
The SPM applies a chi-square test to evaluate the differentiation between input and output flows to obtain SP in the target link. If a significant difference exists, the system will send an alert that indicates the target area is under attack to the network manager. The SDN controller can obtain all the information from the network depending on the OpenFlow protocol. This implementation will focus on the SDN controller.  
The SDN controller obtains the topology of the network, such as the link between the switch and the switch, the link between the switch and the node, or the link between the switch and the controller, so we can use this API to determine all the distributions and positions of the links in the network. The SDN controller obtains the flow table from the links. The TSM obtains flows that pass the target area to calculate the link weight of each link, and the SPM obtains input and output flows that pass through the target area.
# Antimicrobial Effect of Submicron Complex Oxide Particles CsTeMoO\({}_{6}\) under Visible Light
## 3 Results  
### Characterization of CsTeMoO\({}_{6}\)  
The CsTeMoO\({}_{6}\) compound was obtained and described according to previous works [22; 23]. The study of the crystal structure, thermal properties and electronic structure showed that it belongs to the \(\beta\)-pyrochlore structure type and has absorption lines inside the band gap (3.1 eV) at \(\sim\)2 and 2.6 eV, which corresponds to the visible light range. The obtained electron band diagram for CsTeMoO\({}_{6}\) has been confirmed by photocatalytic experiments: absorption of photons with an energy of \(\sim\)2 eV leads to the formation of electron-hole pairs, which lead to oxidation reactions of organic substances, which is shown by the example of the photodecomposition of methylene blue and methyl orange [22]. Figure 1 shows the powder X-ray diffraction pattern of the resulting CsTeMoO\({}_{6}\) sample, which can be indexed in the cubic system with the space group \(Fd\overline{3}m\)[23].  
A comparison of the obtained X-ray diffraction pattern with the theoretical pattern, calculated from the single crystal X-ray diffraction data for this compound, indicated the monophasic nature of the powder. Impurity phases were not detected within the sensitivity of the method. The results of measuring the elemental composition showed a homogeneous distribution for the Cs, Te, Mo and O elements over the powder and correspond to the stoichiometric ratio of 11.50 at % (L\(\alpha\), Cs), 10.44 at % (L\(\alpha\), Te), 11.60 at % (L\(\alpha\), Mo) and 66.46 at % (K\(\alpha\), O) within the sensitivity of the method (\(\sim\)0.1 at %). The particle size distribution was calculated according to the Fraunhofer theory (Figure 2).  
Figure 1: The powder X-ray diffraction pattern of the CsTeMoO\({}_{6}\) compound.  
Figure 2: SEM photo and volume distribution of particles by size of CsTeMoO\({}_{6}\) powder.  
The average particle size of the CsTeMoO\({}_{6}\) powder dispersed in a planetary mill was 670 nm, with the maximum particle size distribution at 300 nm (Figure 2). The particle size distribution was unimodal, and the SEM results showed that micron agglomerates of smaller particles predominantly represented the powder.