esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Concepts and Problems  
### Log Parsing  
To gain insight into the operation of computer software, programmers carry out a specific programming practice, namely logging. With the use of commands that print out specific attributes of the given software at a specific time, developers create log files. The output of a print command is usually represented by a single line in the log file, which could be also called a log entry. These entries are frequently raw, which means they are not structured, since there is no restriction about what a developer can write. A typical log line is the combination of multiple pieces of information, such as the Sequence Number, which identifies the message; the Timestamp, which shows when the event took place; the Module on which the event took effect; and the free-text Message. Figure 1 is a snippet from our working data.  
The message consists of words or tokens, which are separated by spaces. The tokens can either belong to the constant part or to the parameter part of the message. The constant tokens are identical at every occurrence of the given event type, while parameter tokens can be different. For example, in the second line of the example shown in Figure 1 \"NPU\" and \"Software\" are constants, while \"CXP9029630.4\" and \"R9D3925\" are parameters.  
With log parsing, we allocate each log entry, \(e\), to its corresponding event type. Formally, a structured log parser assigns each entry in the list, \(e_{1},e_{2},\ldots,e_{N}\), of log lines representing the log to a single event type \(M\), where \(M\) are unique message types that were created by \(P\) distinct processes [8]. While log parsers are powerful instruments in log processing, they cannot be used in all cases. The parser does not have, in advance, the information about entry types and processes that generate the entries, and it has to deduce all this information using classifiers called 'template miners'. Pre- and post-processing of the data, such as deleting duplicates or using regex, are also indispensable. For example, regex can be used to remove not unnecessary fields like sequence numbers [22].
## 6 Threats to Validity  
While the findings suggest that hybrid-based interaction enhances the user experience through adaptability, several limitations related to external, construct, and internal validity must be acknowledged.  
1. External Validity:  
The sample size and participant selection could restrict the generalizability of the findings, given that data were gathered from a particular educational context. Although the sample size aligns with practical constraints and is comparable to similar studies, future research should involve larger and more diverse participant groups to increase the applicability of the findings across broader contexts.  
This limitation was mitigated by including a variety of question complexities, variations in student specialization and year of study, and multiple chatbot interaction modes. However, future studies should expand to include a wider range of educational settings and cultural backgrounds to validate the framework's applicability across diverse contexts.  
2. Construct Validity:  
This study relied on the CUQ and UES-SF metrics, which, while validated, may not fully capture the adaptability of chatbot systems without modality-switching features. The focus on usability, engagement, efficiency, and effectiveness does not address deeper cognitive dimensions such as critical thinking or knowledge retention. To address this, qualitative feedback was analyzed alongside quantitative metrics, providing a richer understanding of the user experience. Future research should incorporate metrics targeting cognitive engagement and learning outcomes to enhance the framework's adaptability to broader educational contexts.  
3. Internal Validity:  
The cross-sectional design of this study limits insights into adaptive responses and long-term changes in user behavior. This was mitigated by observing the participants across various task types, which helped control immediate behavioral variance. Future studies should adopt longitudinal designs to monitor sustained patterns of engagement and adaptability, offering a more nuanced understanding of long-term interactions with chatbots.  
Additionally, the PCA-based weighting approach for the composite metric introduces a potential limitation, as it may reflect sample-specific variance patterns. Although consistency was verified across interaction modes and question complexities, the absence of formal sensitivity analyses or bootstrap validation remains a limitation. Future studies should incorporate these techniques to enhance the robustness and reliability of the derived weights.
# Telerehabilitation--A Viable Option for the Recovery of Post-Stroke Patients
## 7 The Acceptability, Accessibility and Usability of Telerehabilitation  
Some patients may consider TR inferior to conventional face-to-face rehabilitation and be reluctant to accept it [11; 41]. Being, for many, a new approach, researchers were confronted with skepticism from patients and their families, while therapists have the mission to persuade users about the new concept and its advantages [36].  
In order to accept different new technologies as part of their recovery process, patients need to trust their therapist and be open to novelty. The presence of fear that the devices are too fragile and that they may get damaged during exercises can decrease acceptability for patients unfamiliar with technology [9]. The teletherapy system should fulfill some basic requirements such as assuring user safety, being user-friendly, not needing frequent technical maintenance, and requiring minimal home reorganization and investment [13].  
One study based on questionnaires distributed to patients, caregivers and healthcare professionals found that the possibility of using the e-rehabilitation program on different devices (phone, tablet and computer) was considered positively for accessibility. Another preference of patients and caregivers was small and easy to use devices [45]. Researchers also noted the patients' preference for the application interface. The most suitable interface is a calm interface without bright, fast-moving images [9]. The existence of user support in any form was also stated as being a priority [45], including in the transition period from conventional therapy to the new therapy [9]. Another identified factor that counted for the acceptance of rehabilitation through technology was the way the devices fit into patients' homes [9].  
Teletherapy solves the problem of transportation and has few restraints on location and time of performance, therefore improving accessibility of rehabilitation services [12].
## 2 Methods
### Sentinel-1 Data Acquisition and Processing
To generate Sentinel-1 InSAR coherence imagery, we used the Alaska Satellite Facility (ASF) Hybrid Pluggable Processing Pipeline (HyP3) tool [71], which contains modified Copernicus Sentinel data 2021, processed by ESA). Sentinel-1 InSAR pairs were selected using the ASF SAR baseline tool to maintain the shortest possible temporal and perpendicular baselines (i.e., the greatest degree of temporal and spatial similarity between image acquisitions). We developed a selection protocol for the InSAR pairs ordered through HyP3, where the image with the later acquisition time in the InSAR pair was matched most closely to ground biomass sampling. Once image pairs were selected, we used the HyP3 tool to generate interferograms with embedded Gamma software, performing an interferogram generation with a 10 \(\times\) 2 window size (smallest possible window size). The Sentinel-1 interferogram and associated InSAR coherence images output from this process resulted in a pixel size of approximately 40 m, meaning that the destructive biomass sampling of small plots (0.57 m\({}^{-2}\)) was unlikely to significantly impact coherence estimation. As the backscatter imagery produced using GEE, polarimetric decomposition imagery, and InSAR coherence imagery were derived from the same Sentinel-1 images, their incidence angles were identical for a single image, and nearly identical for an InSAR pair. It is also important to note that the incidence angle of observation for the Sentinel-1 image time series was consistent over our study sites, exhibiting a spatiotemporal mean incidence angle of 41.31 degrees, with temporal standard deviation of 0.08 degrees, and a spatial standard deviation of 0.15 degrees.
## 3 Results
### Study Characteristics and Participant Details  
This systematic review included fifteen observational studies investigating the relationship between personality traits, pain perception, attitude, satisfaction, compliance, and quality of life in orthodontics. These studies varied in methodology, including cross-sectional [51; 52; 53; 54; 55; 56; 57; 58] and longitudinal [59; 60; 61; 62; 63; 64; 65] designs. Sample sizes ranged from small groups of 22 participants to larger cohorts of up to 1037 participants. The age range varied across studies, with some focusing on adolescents [51; 52; 53; 55; 58; 59; 61; 65] and others including young adults [51; 56; 57; 58; 63; 65] and adults [54; 58; 60; 62; 64; 65]. The gender distribution was relatively balanced in most studies, with a slight predominance of female participants in some cases [53; 54; 55; 56; 58; 60; 62; 64; 65]. The studies utilized various validated tools to assess personality traits, including the Neuroticism Extraversion Openness Five-Factor Inventory  
Figure 1: Articles selection process summarized by PRISMA Flowchart.  
(NEO-FFI) [51; 52; 54; 56; 57; 59; 62; 63; 64; 65], Modified Big Five Inventory (BFI)-10 [53; 58], Brief Symptom Inventory (BSI) and Narcissistic Vulnerability Scale (NVS) [60], Basic Personality Traits Inventory (BPTI) [55], 16 Personality Factors-Adolescent Personal Questionnaire (16 PF-APQ) [61], and Temperament Questionnaire (EAS-C) [59].  
Outcomes measured included oral health-related quality of life (OHRQoL) [54; 55; 60; 62], pain perception [51; 52; 57; 60; 63], patient satisfaction [56], compliance with orthodontic treatment [58; 61; 65], attitude toward orthodontic treatment [51; 52; 57; 63; 64], and willingness to undergo treatment [53]. Across the selected studies, various validated instruments were employed to assess key orthodontic outcomes. Patient satisfaction was measured using the Dental Impact on Daily Living (DIDL) questionnaire [56] or an online questionnaire for the aesthetic perception of orthodontic appliances [64]. Cooperation during treatment was measured with scales such as the Orthodontic Patient Cooperation Scale (OPCS) [61] or by a questionnaire designed for this purpose [58]. Compliance was also objectively monitored using electronic sensors to track appliance wear time [59]. The patients' willingness to accept various treatment options was evaluated with a questionnaire designed for this purpose [53]. Pain perception and treatment attitudes were commonly quantified using visual analog scales (VASs) marked at 10 mm intervals [51; 52; 57; 63]. Oral health-related quality of life (OHRQoL) was assessed using instruments like the Oral Health Impact Profile-14 (OHIP-14) [54; 62] and the Health-Related Quality of Life (HRQOL) questionnaire [60], while treatment need was determined using indices such as the Index of Orthodontic Treatment Need (IOTN) [65] or a combination of the Index of Complexity, Outcome, and Need (ICON), and the Child Perceptions Questionnaire (CPQ) [55].
## 3 Results
### Detailed Analysis of Developments in Selected Specialties
#### 3.7.2 Teledermatology  
The evolution of teledermatology demonstrates the integration of virtual tools accelerated by COVID-19, encompassing diagnosis, management, and patient care. Initially, Reflectance confocal microscopy with cloud-based telemedicine was assessed for dermatological consultations [84]. During COVID-19 (2020-2022), the pandemic has accelerated the adoption of teledermatology through virtual conferences [85]. Research has explored COVID-19's impact on atopic dermatitis [86] and its efficacy in skin cancer screening [87]. Reviews have evaluated melanoma management through teledermatology [88], while the role of mobile telecdermoscopy in skin cancer management has been analyzed [89]. Surveys have shown a growing acceptance of AI and telemedicine among dermatologists [90], and studies have reported positive patient experiences during COVID-19 restrictions [91]. The role of teledermatology in managing sexually transmitted infections was examined during the pandemic [92]. Early teledermatology used advanced diagnostics for remote consultation [87; 92; 93]. COVID-19 has expanded teledermatology into clinical care and education, particularly in skin cancer screening. Mobile telecdermoscopy [89] and virtual conferences [85] have become essential remote tools. Healthcare professionals are increasingly accepting of AI and telemedicine. Teledermatology has proven to be effective for chronic conditions and patient access during social distancing. Its expansion to sexually transmitted infections has broadened in scope. The reviews have highlighted the benefits and limitations of these approaches.
## 3 Numerical Studies
### Four-Layer Framework Structure  
A four-layer framework structure is subjected to external load excitation in this section to validate the effectiveness of the proposed method. The floor is assumed to be rigid, and the mass of the columns is neglected. The mass and stiffness of each floor are shown in Figure 8a. The mass and stiffness of each floor are 10 t and 1000 kN/m, respectively. Rayleigh damping is used in this case, with a damping ratio of 5%, and the damping coefficient is obtained from the first two natural frequencies. It is assumed that the system's mass is mainly concentrated on the floors, and the external load \(F(t)\) is applied at the top of the structure. The form of the external load \(F(t)\) is shown in Figure 8b, and the displacement response of each floor within 1 s is analyzed. According to the D'Alembert principle, for a multi-degree-of-freedom structure subjected to external load action, the equation of motion can be expressed as follows:  
\[M\ddot{u}(t)+Cu(t)+Ku(t)=F(t). \tag{21}\]  
In the equation, \(M\), \(C\), and \(K\) represent the mass, damping, and stiffness matrices, respectively. The system utilizes Rayleigh damping with a damping ratio of 5%. \(F(t)\) is the external load, following the function \(F(t)=-\sin(5\pi\times t)\times 1000\) kN.  
The loss function considers the initial conditions of displacement and velocity. Therefore, the loss function for this numerical example can be expressed as follows:  
\[Loss=Loss_{1}+\lambda_{1}\sum_{i=1}^{4}Loss_{u}(u_{i}(0),0)+\lambda_{2}\sum_ {i=1}^{4}Loss_{v}(\dot{u}_{i}(0),0). \tag{22}\]
# Experimental Study of Imbibition Characteristics of Silica Sol in Coal-Measure Mudstone Matrix
###### Abstract  
Coal-measure mudstone is a typical dual-porosity media, and grouting in a matrix system is dominantly controlled by the imbibition effect for silica sol. This paper studies the imbibition effect using mudstone in the Huaibei mining area and silica sol as grouting material as an example. Groutability, driving force, and diffusion difficulty affecting the imbibition effect were tested by a mercury porosimeter, nanoparticle size analyzer, optical contact-angle measuring device, surface tension meter, and rotary viscosity meter. After finely grinding a mudstone sample, a pressureless imbibition process was conducted through nuclear magnetic resonance equipment for 216 h to study colloid spontaneous migration and phase characteristics. Results show that silica sol absorption rate follows a power function and that the spectrograms of \(T_{2}\) are distributed in a triple peak pattern, with a tendency to move to the right of vertex time. The paper lays a theoretical and experimental foundation for field grouting in the coal mine.  
imbibition effect; silica sol; coal-measure mudstone +
Footnote †: journal: Applied Sciences
## 4 Methods and Results  
In this experiment, TOC was predicted by using 158 groups of measured data and corresponding logging data. The traditional \(\Delta\)logR method and neural network method were compared and optimized in M3 and M5\({}_{6-10}\) layers. On this basis, it determines that the complicated lithologic TOC interpretation in the study area is applicable to the linear model or nonlinear model. Calculation results were evaluated by the determination coefficient (R\({}^{2}\)), mean absolute error (MAE), mean relative error (MRE) and root-mean-square error (RMSE). The calculation effect is better if R\({}^{2}\) approaches to 1 and MAE, MRE and RMSE approach to 0.
# HCLE: Hybrid Clustering Approach for Extending WBAN Lifetime
## 3 Preliminaries
### Performance Metrics
#### 3.4.2 Network Throughput  
Network throughput is an important performance metric in WBANs, as it measures the successful reception of packets at the sink, particularly when dealing with vital patient data. The goal is to minimize the packet drop ratio and maximize data reception at the sink to ensure reliable transmission of important healthcare information [4; 25]. The choice of routing protocol is essential for improving the network throughput, as it should be designed to optimize throughput in low-power and resource-constrained WBAN environments. By designing efficient and reliable routing protocols, congestion can be avoided, packet loss can be minimized, and data reception at the sink can be maximized, ultimately enhancing network throughput.
# The Long and Winding Road to Cardiac Regeneration
## 4 Biomaterials
### Synthetic Biomaterials
#### 4.1.4 Poly(lactic-co-glycolic acid) (PLGA)  
Poly(lactic-co-glycolic acid) (PLGA) is a biodegradable and biocompatible polymer widely used in various biomedical applications. It is derived from a combination of lactic acid and glycolic acid, making it an ideal material for tissue engineering and drug delivery systems [207].  
PLGA's physical features include its tunable mechanical properties, degradation rate, and surface characteristics. It can be easily synthesized into different forms such as fibers, films, and scaffolds, allowing for customization based on specific tissue engineering requirements.  
When it comes to cellular effects, PLGA has shown excellent biocompatibility, with minimal cytotoxicity. Its degradation products, lactic acid, and glycolic acid are naturally occurring metabolites that can be easily metabolized by cells, minimizing any adverse effects [208].  
PLGA provides mechanical support for cell attachment and proliferation while allowing for nutrient and oxygen diffusion. The porous structure of PLGA scaffolds facilitates cell infiltration and extracellular matrix deposition, promoting tissue regeneration.  
Numerous studies have investigated the use of PLGA in cardiac tissue engineering. Researchers have explored its potential for cardiac patch development, enabling the regeneration of damaged myocardium [209]. Additionally, PLGA has been incorporated into three-dimensional constructs, promoting the formation of functional cardiac tissues that mimic native heart structures [210].
# Enhanced Multicast Repair Fast Reroute Mechanism for Smart Sensors IoT and Network Infrastructure
## 5 Enhancements for M-Rep
### Multiple Failures
The second part between R4 (S2) \(\rightarrow\) R5 \(\rightarrow\)D was constructed for the multicast flow (S, G + 1). Figure 8: The EM-REP principle at multiple failures at different times. In the proposed solution, it is necessary to deal only with failures that have already occurred on the alternative route created by the EM-REP mechanism. Failures that occur outside of the alternative path do not affect or interfere with the path created and should not be addressed.
# DOW-PR DOlphin and Whale Pods Routing Protocol for Underwater Wireless Sensor Networks (UWSNs)
###### Abstract  
Underwater Wireless Sensor Networks (UWSNs) have intrinsic challenges that include long propagation delays, high mobility of sensor nodes due to water currents, Doppler spread, delay variance, multipath, attenuation and geometric spreading. The existing Weighting Depth and Forwarding Area Division Depth Based Routing (WDFAD-DBR) protocol considers the weighting depth of the two hops in order to select the next Potential Forwarding Node (PFN). To improve the performance of WDFAD-DBR, we propose DOlphin and Whale Pod Routing protocol (DOW-PR). In this scheme, we divide the transmission range into a number of transmission power levels and at the same time select the next PFNs from forwarding and suppressed zones. In contrast to WDFAD-DBR, our scheme not only considers the packet upward advancement, but also takes into account the number of suppressed nodes and number of PFNs at the first and second hops. Consequently, reasonable energy reduction is observed while receiving and transmitting packets. Moreover, our scheme also considers the hops count of the PFNs from the sink. In the absence of PFNs, the proposed scheme will select the node from the suppressed region for broadcasting and thus ensures minimum loss of data. Besides this, we also propose another routing scheme (whale pod) in which multiple sinks are placed at water surface, but one sink is embedded inside the water and is physically connected with the surface sink through high bandwidth connection. Simulation results show that the proposed scheme has high Packet Delivery Ratio (PDR), low energy tax, reduced Accumulated Propagation Distance (APD) and increased the network lifetime.  
underwater wireless sensor networks (UWSNs); dolphin and whale pods routing (DOW-PR); end-to-end delay (E2 ED); potential forwarding nodes (PFNs); suppressed nodes +
Footnote †: journal: Sensors