esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Microbial Community Analysis  
To gain a deeper insight into the impact that the activation procedures have on the microbial communities that thrive on the surface of the electrodes, the taxonomic composition of the anodic biofilms was analyzed (Figure 6). The genus _Geobacter_, a well-known exoelectrogen [20], was found in all three biofilms. Its relative abundance was much higher in the biofilms of the acetone- and DMF-activated electrodes compared to the control (control 4.9%, DMF 33.4%, acetone 52%). Thus, the activation procedures of the PLA/graphene electrodes seem to trigger a selection process in which diversity (in terms of the number of taxa) is lost in favor of a greater richness in the electroactive genera. This might explain (at least in part) the improved bioelectrochemical performance of acetone and DMF electrodes.
## 6 Numerical Results
### Probability of Error
#### 6.1.1 Probability of Error at the Relay  
Two sources are considered to be transmitting the signals (\(s_{1}\) and \(s_{2}\)) drawn from a one-dimensional integer lattice, _i.e._, \(n=1\) and \(\mathcal{L}=\mathbb{Z}\). There is one relay, which decodes the linear combination of these signals. The performance in terms of probability of error in decoding the linear combination of original signals at the relay is simulated. The additive noise at the relay node has a Gaussian distribution.  
In order to compare with the existent schemes, the baseline lattice network coding (LNC) scheme, which is used to practically implement CF in [3], is considered. To make a fair comparison, we have adjusted the power of the transmitters in the schemes with and without precoding, such that the total power available at the transmitters in both schemes is equal. We consider precisely the same channel as considered in [5], for the sake of comparison, given by \(\mathbf{h}=[\begin{array}{cc}-1.274&0.602\end{array}]\); however, the results are not sensitive to the choice of the channel gain vector.  
We observe in Figure 2 that the probability of error by the proposed IFP-based scheme has a gain of up to 2 dB over the existent baseline LNC.  
For comparison, we also plot the probability of error, which can be achieved when the channel gain vector is integral. In this case, the additional noise is the only source of error at the relay. Therefore, this indicates a lower bound of the probability of error for CF. Note that, with our proposed precoding, the only source of error at the relay is the additional noise. However, as shown in Figure 2, there is a gap between the proposed scheme and the lower bound. This gap is due to t required for precoding. More precisely, the proposed scheme requires more power at the transmitter to achieve the same probability of error as the CF with an integral channel.
## 3 System Model
### Simulation Set-Up/Network Model  
In this study, two different scenarios by changing the number of nodes were considered to analyze the performance of the WBAN network. We have considered 9 or 12 sensor nodes that are implanted in the human body. A static and rechargeable sink was placed at the center of the body, whose responsibility is to collect and forward all sensed data from all the sensor nodes to the external server or PDA. However, communication afar from the sink was not considered for this protocol. We assumed all the sensor nodes were homogeneous in terms of their computational power, sensing ability, initial energy level, and the temperature. The packet size considered in this work was of 296 bits. In order to analyze the performance, the proposed protocol was compared with the existing Multipath Ring Routing protocol. In our proposed protocol, the selection of the relay node was premeditated and is based on residual energy and temperature of the node. The simulation setup along with the energy values and temperature values are given in Table 4
# Vibration Analysis of Piezoelectric Cantilever Beams with Bimodular Functionally-Graded Properties
## 1 Introduction
The publication of this book marks that the idea of bimodular materials entered the field of vision of scholars from all over the world. Thereafter, bimodular problems for materials and structures have been investigated extensively [22; 23; 24; 25]. These works indicated that the bimodular effect of materials will modify, to some extent, the mechanical behaviors of structures. Unfortunately, due to the complexity in analysis, the bimodular effect of materials is often neglected. Although some works have been carried out to combine the functionally-graded properties with bimodular effect of materials, for example, [26], the existing works appear insufficient. In fact, not only pure functionally-graded materials but also functionally-graded piezoelectric materials may have a certain degree of bimodular effect. Simple neglect will inevitably lead to analytical errors, which could further influence the design application of the electromechanical devices based on piezoelectric effect. [PERSON] et al. [27] considered the bimodular effect during the analysis of functionally-graded piezoelectric materials and structures for the first time, and presented a two-dimensional analytical  
Figure 1: Constitutive model for bimodular materials: (**a**) nonlinear model under actual state; (**b**) bilinear model when \(E^{+}>E^{-}\); (**c**) bilinear model when \(E^{+}<E^{-}\). solution for a FGPM bimodular cantilever beam. Thereafter, aiming at the static problem of a bimodular FGPM cantilever, [PERSON] et al. [28] neglected some unimportant factors to derive the one-dimensional theoretical solution and, based on the model of tension-compression subarea, conducted a two-dimensional numerical simulation. However, the existing works appear insufficient since there is no dynamic solution to the corresponding problem. At present, for a cantilever-type structure which is extensively adopted in piezoelectric sensors devices, the bimodular functionally-graded effect on its vibration has not been investigated. In addition, for piezoelectric polymer elements, the vibration problem, due to flexible and lightweight characters of the elements, is particularly acute, which also deserves further research. In this paper, the free damping vibration problem of a piezoelectric cantilever beam with bimodular functionally-graded properties is analyzed by using analytical and numerical methods. The paper is organized as follows: In Section 2, the problem studied is briefly described and the constitutive relation for bimodular functionally-graded piezoelectric materials is presented. In Section 3, we derive the equivalent modulus of elasticity and obtain the analytical solution of the problem described. The numerical simulation for the problem is performed step by step in Section 4 and the corresponding comparisons and discussions are given in Section 5. Based on the results obtained in this study, some main conclusions are presented in Section 6.
## 5 Adaptive Scheduling Mechanism Based on Self-Similarity  
Experimental analysis in [17] shows that the inter-contact intervals has the distribution of self-similarity. In this paper, we proposed an Adaptive Scheduling Mechanism based on Self-Similarity (ASMSS) for efficient contact probing. Firstly, we use the _LMMSE_ predictor to predict the future inter-contact interval based on the contact history of nodes. Then, nodes can adaptively schedule the listening and sleeping states in each period based on the predicted result. The _LMMSE_ predictor is described as follows.  
Figure 2: Contact comparison between random working mechanism (**a**) and adaptive scheduling mechanism (**b**).
## 2 Materials and Methods
### Headspace-Solid Phase Microextraction (HS-SPME)  
Cider sample aliquots (10 mL), 2.6 g of NaCl (Sigma Aldrich, St. Louis, MO, USA), and internal standards were transferred to 20 mL, 22.5 \(\times\) 75 mm glass headspace vials (Sigma Aldrich) for solid phase microextraction (SPME). A volume of 30 \(\mu\)L of 4-methyl-2-propanol (0.80 g mL\({}^{-1}\)) and 1 \(\mu\)L ethyl heptanoate (0.87 g mL\({}^{-1}\)) were added as internal standards (Millipore Sigma, 99% and 98%, respectively). Tepepenes were semi-quantified by spiking 0.1 \(\mu\)L of 0.01 g mL\({}^{-1}\)\(\beta\)-myrcene-d6 in ethyl acetate (Axios Research, Washington, DC, USA) [20] into the cider samples after dry hopping. The structures of the internal standards are displayed in Figure 1A and the 8 classes of compounds that were semi-quantified by these internal standards are shown in Figure 1B. Ethyl hepatomaate was used for semi-quantification of ethyl esters, acetate esters, other esters, ketones, aldehydes, and volatile acids. 4-Methyl-2-propanol was used for higher alcohol semi-quantification. B-Myrcene-d6 was used to semi-quantifying three classes of terpenes that developed after the addition of hops (monoterpenes, terpenoids, and sesquiterpenes). Vials were then capped with 20 mm aluminum release seal PTFE/silicone liner cap (Sigma Aldrich) with a manual vial crimper. Vials were held in a 40 \({}^{\circ}\)C water bath for ten minutes for headspace equilibration. A conditioned DVB/CAR/PDMS 50/30 \(\mu\)m SPME fiber (Supelco, Bellefonte, PA, USA) was then exposed to the headspace for 30 min for volatile preconcentration. Samples were analyzed by GC-MS within 24 h of exposure and stored at 4 \({}^{\circ}\)C in the interim. SPME fibers were conditioned after every sample according to manufacturer recommendations.
## 4 Results and Discussion
### Automatic Recognition of Lexical Situation Types
#### 4.3.2 Classification Experiments Based on Embedding Vectors
To address this, we first extract a portion of data from the original training set, removing their situation type labels to construct a small unlabeled prediction set. The remaining data form a new training set, on which we train the FastText model and predict situation types on the prediction set. Subsequently, we manually evaluate the model's prediction accuracy to preliminarily assess the presence of overfitting tendencies. Additionally, we extract unlabeled verbs from dictionaries, collect commonly used colloquial words and create several more challenging small prediction sets without situation type labels. Utilizing the original FastText vector dataset as the training set, we conduct multiple rounds of prediction experiments to further evaluate the model for overfitting. The experimental results indicate that the model's accuracy on these small prediction sets is generally around 20% higher than the baseline, showing consistent performance with the classification experiments on the original complete dataset and no apparent signs of overfitting. This suggests that the FastText model exhibits good generalization capabilities in situation classification tasks, maintaining a relatively high level of accuracy, and also validates the effectiveness of the dataset we utilized. Furthermore, although other models have demonstrated good performance, they have not been able to achieve the accuracy of FastText word vectors. This indicates that there are indeed differences in the feature extraction capabilities and depth of contextual understanding among different models in the task of predicting situation types. Our objective is not to verify the correlation between the sophistication of models and prediction accuracy, but rather to select the optimized model capable of accurately identifying situation types. Taking all the above into consideration, we have decided to use the FastText vectors dataset as the training set and combine it with an ANN classifier to conduct automatic recognition of verb situation types in unknown language resources.
# Determination of Seed Volume Based on Selected Seed Dimensions
## 3 Results and Discussion  
### Experimental Material  
The accuracy with which the average geometric parameters of seeds are measured is determined by the standard error of the estimate [29], which is calculated based on sample size, the standard deviation of the analyzed trait, and the Student's t-distribution at a given level of significance. For the analyzed sample size (105 to 119 seeds) and the observed variations in seed dimensions, the standard error of the estimate for average seed dimensions did not exceed 0.1 mm.  
The basic seed dimensions and the calculated indicators are presented in Table 2. The results of [PERSON] and [PERSON]'s tests did not reveal non-normal distribution or heteroscedasticity. The sphericity index \(\Phi\) ranged from 0.510 (_Pseudotsuga menziesii_ ([PERSON].) [PERSON]) to 0.951 (_Cornu s macrophylla_ [PERSON]), and it differed significantly across the analyzed plant species. Considerable differences were also noted in the values of the aspect ratio, and the only homogeneous group was formed by the following pair of species: _Cotoneaster horizontalis_ [PERSON] and _Juniperus scopulorum_ [PERSON]. The aspect ratio was highest in _Cornu s macrophylla_ (0.960) and lowest in _Pseudotsuga menziesii_ (0.504). _Pseudotsuga menziesii_ had the longest seeds, with an average length of 6.93 mm, and a similar range of values (5-7 mm) was reported by [PERSON] et al. [30]. An analysis of average seed thickness and width revealed that _Pica abies_ (L.) [PERSON] was characterized by the smallest seeds, whereas _Cornu sanguinea_ L. was characterized by the largest seeds. _Pseudotsuga menziesii_ seeds resembled _Juniperus communis_ L. and _Cotoneaster horizontalis_ seeds in terms of thickness. Two groups of species with a similar average seed length were identified: _Juniperus communis_, _Juniperus scopulorum_ and _Pica abies_, and _Cotoneaster horizontalis_, _Cornu s macrophylla_, and _Pica abies_. The following pairs of species formed homogeneous groups based on seed width: _Pica abies_ and _Juniperus communis_, and _Juniperus scopulorum_ and _Tilia cordata_ Mill. Average seed volume ranged from 7.31 mm\({}^{3}\) (_Juniperus communis_) to 54.87 mm\({}^{3}\) (_Cornus sanguinea_). Similar values were reported by [PERSON] and [PERSON] [31]; therefore, the analyzed seeds can be regarded as representative of the evaluated species. The following pairs of species formed homogeneous groups based on seed volume: _Pica abies_ and _Juniperus communis_, and _Juniperus scopulorum_, _Pseudotsuga menziesii_, and _Tilia cordata_. In general, similar variations in the dimensions of the analyzed seed species were given in the literature [31; 32; 33].
# Swarm Robotics: A Perspective on the Latest Reviewed Concepts and Applications
## 6 Applications Using Swarm Robotics
### Space Exploration Tasks  
Space is a harsh environment. Thus, humans must rely on robots to perform autonomous tasks, given the difficulty and danger of exposing humans to space environments [162; 163; 164]. space applications of swarm robotics vary from exploration [165; 166] to the on-orbit structures assembly [167; 168]. On this matter, [PERSON] et al. [164] assessed how NASA approaches Swarm Robotics technologies. In their work, they study both the development process and present some proposed applications. For instance, they overview appliances to explore the asteroid belt, the Saturn rings, and provide moon landing bases. [PERSON] and [PERSON] [165] explore the computational methods to plan paths for robots performing collective tasks in the space environment. They apply the combination of Chaos, Particle Swarm Optimization (PSO) with Immune Network theory to create their algorithm. They tested it in simulated environments, performing successful planning to avoid obstacles and navigate. [PERSON] and [PERSON] [166] study the main individual rules to perform swarms' collective tasks. For this matter, they observe satellite reorganization tasks, such as collective changes in orbits for satellite arrays. They state that these tasks reach success as the composing individuals follow four rules: collision avoidance, group maintenance, neighbor alignment, and goal-reaching. In their study, [PERSON] et al. [167] evaluate on-orbit assembly tasks performed by autonomous swarm modules. In their research, they tested several features, such as docking and reconfiguration. Their examinations indicate that the proposed methods create a feasible swarm-based environment. [PERSON] et al. [168] propose a control scheme for spacecraft swarms. They perform mathematical modeling of the dynamical system of the swarm, providing predictability on the collective behavior. Finally, this model is used to impose control laws on each element composing the swarm, achieving typical behavior.
## 5 Results
### GPS Positioning Accuracy  
Although in general the positioning accuracy of the mobile mapping system is adequate for the considered task (ranging from 2 to 5 m), in several cases the system experienced problems in the geo-referencing of the images due to poor GPS signal reception. This problem, particularly present in the areas with a higher density of buildings and the presence of \"urban canyons,\" caused the misplacement of the survey path, with positioning errors ranging from a few meters to more than 30 m. Since this can affect the correct identification of the targeted building, in the offline analysis phase the operator was asked to evaluate whether the inconsistencies in the positioning would seriously hinder the analysis procedure itself. It has been noticed that, out of 1000 considered buildings, in around 120 cases (~12%) the image coordinates appeared misplaced (by visual judgment by the operator). In most of the cases the operator was still able to locate the targeted building despite the geo-referencing error. In 45 cases the operator could not retrieve the building in the exam, thus declaring the building as non-visible. Even though the impact of this issue in the preliminary testing was limited, affecting ~4.5% of the samples, the technological issue has to be addressed in the operational phase.
## 3 Distributed PV Storage Virtual Synchronous Generator System
### Bidirectional DC-DC (Chopper)  
The structure of the bidirectional DC-DC circuit can be divided into a non-isolated bidirectional DC-DC circuit and an isolated bidirectional DC-DC circuit. In this paper, the widely used non-isolated bidirectional DC-DC circuit topology was selected. Non-isolated bidirectional DC-DC circuits include bidirectional Buck/Boost circuits, bidirectional half-bridge circuits, bidirectional cuk circuits, and bidirectional sepk circuits. Among them, the bidirectional half-bridge topology is simple, low cost, and high efficiency. Therefore, this paper chose the bidirectional half-bridge circuit as the topology of bidirectional DC-DC. The structure and control of bidirectional DC-DC half-bridge topology were presented in Figure 10.  
where, \(P_{\text{PV}}\) is the power delivered by the PV array via MPPT, \(P_{\text{out}}\) is the power output from the PV storage system, and \(P_{\text{st}}\) is the power emitted by the energy storage system, and \(U_{\text{dc}}\) is the DC bus voltage, which tracks the DC bus voltage reference \(U_{\text{dc}}\)\({}^{*}\) through the DC voltage outer loop. \(P_{\text{PV}}\), \(P_{\text{out}}\) and \(P_{\text{st}}\) satisfy the relationship shown in Equation (20) without considering energy loss.  
\[P_{\text{out}}\ =\ P_{\text{PV}}+P_{\text{st}} \tag{20}\]  
When the system is stable, there was a power balance between power supply and demand, which is shown in Equation (21).  
\[P_{\text{out}}\ =\ P_{\text{Load}} \tag{21}\]  
where \(P_{\text{Load}}\) is the load demand power. A self-stable bidirectional DC-DC control scheme was designed to help to achieve a new power balance of the PV storage system through the control of energy storage when changes of the PV power output and load lead to an imbalance between power supply and demand (see Figure 11).  
When the power provided by the PV storage is less than the load required power, the switch signal S enables S1 and disables S2. Bidirectional DC-DC operates in boost mode, which increases the power \(P_{\text{st}}\) emitted by the energy storage system. When the power provided by the PV storage is more than the load required power, the switch signal S enables S1 and disables S2. Bidirectional DC-DC operates in buck mode, which decreases \(P_{\text{st}}\). Finally, a new power balance of \(P_{\text{out}}\ =\ P_{\text{PV}}+P_{\text{st}}\) is achieved. The above process is continuously circulated in the system and the power is adjusted in real time so that the PV storage system can play a role of peak shaving and valley filling under the premise of stable operation to meet the load requirements.  
Figure 10: Structure and control of bidirectional DC-DC.
## 1 Introduction
Our goal is to apply the properties of AAS to robot fault diagnosis and infer structural or functional abnormalities in robots. This method is similar to sonar or ultrasound imaging and is particularly suitable for systems where passive emission is insufficient or unreliable. In robotic applications, AAS enables fault diagnosis even when the robot is not in motion or when the faults do not result in prominent audible cues. The long-term vision of this research is to develop an autonomous self-diagnostic system for robots based on acoustic sensing. As an initial step toward this goal, the present study investigates whether component detachments--one type of externally observable structural fault--can be localized using only acoustic responses. This study builds upon the concept of active acoustic sensing to propose a novel fault diagnosis framework for robots. Rather than directly identifying specific fault types or internal functional failures, this study aims to evaluate whether structural anomalies such as component detachment can be acoustically localized. This represents a foundational step toward building a comprehensive self-diagnostic system based on acoustic sensing. To this end, sweep signals are applied to specific parts of a modular robot, and the resulting acoustic responses are analyzed to determine whether the location of the structural change can be correctly classified. Five classification algorithms--Support Vector Machine (SVM) [22; 23; 24; 25], Random Forest (RF) [26; 27; 28; 29; 30; 31], K-Nearest Neighbors (KNN) [32; 33; 34; 35; 36], XGBoost [37; 38; 39; 40], LightGBM [41; 42; 43], and Multi-Layer Perceptron (MLP) [44; 45; 46; 47]--are evaluated based on experimental data. The findings demonstrate that acoustic-based active sensing can be a reliable and accessible solution for robotic fault diagnosis, especially in scenarios where conventional diagnostic tools are impractical. Beyond its technical contributions, this research also addresses the broader need for scalable and cost-effective fault detection in the growing field of autonomous and modular robotics. As robotic platforms continue to proliferate across domains such as logistics, education, and home assistance, maintaining their mechanical integrity becomes increasingly critical. Traditional sensor-based approaches often require expensive instrumentation, specialized installation, or high-volume training data. In contrast, the proposed acoustic sensing approach is low-cost, non-invasive, and compatible with minimal hardware, making it a practical candidate for widespread deployment, particularly in environments with constrained resources. This paper is organized as follows: Section 2 describes the experimental platform, data collection procedures, and machine learning classifiers used in this study. Section 3 presents the classification results and analysis. Section 4 discusses the implications and limitations of the findings, while Section 5 concludes the paper and outlines future directions toward realizing self-diagnostic acoustic systems for robotic platforms.