esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
To optimize the device's capabilities, we integrated high-quality spherically curved transducers that allow electronic steering of the focal point without physically moving the probe. This innovation improves depth and lateral resolution while increasing targeting  
Figure 3: Delivery of intense ultrasound energy at the (SMAS) layer to create thermal injury zones (TIZs). accuracy. Additionally, machine learning algorithms were utilized to make precise, real-time adjustments to the focal point based on tissue density, target depth, and patient movement. These enhancements ensure consistent accuracy and eliminate the need for continuous manual intervention during treatment. To assess the clinical efficacy of the improved More Young HIFU device, a comparative randomized clinical trial was conducted to compare its efficacy with 7D HIFU device. Fifty Chinese patients at Beijing Huanxin Medical Center, presenting with skin laxity in the jawline, midface, nasolabial folds, neck, and periorbital areas, were recruited for the study. Each patient underwent a detailed clinical evaluation of 14 skin parameters before and after treatment with both devices. Statistical analysis, performed using R software (version 4.2.3), provided a comprehensive assessment of the results, offering insights into the enhanced performance of the More Young HIFU device. This trial was not registered in a public registry because it was conducted as an academic, non-commercial investigation. Nevertheless, ethical approval was obtained from the Institutional Review Board, and all participants provided written informed consent before enrollment. Future improvements may include AI-guided treatment mapping, integration with multimodal imaging for better targeting, and development of personalized treatment algorithms based on individual skin types and elasticity profiles. The remainder of the paper is structured as follows: Section 2 describes the mechanism of action, model, and schematic design. Section 3 presents methods and statistical analysis. Section 4 discusses the results and outlines study limitations and future directions. The paper concludes in Section 6 with final remarks on clinical relevance and implications.
# Fuzzy Synthetic Evaluation of the Long-Term Health of Tunnel Structures
## 2 Determination of the Evaluation Methods and Ideas for the Tunnel Structural Health  
### Selection of Evaluation Method for Tunnel Structural Health  
Up to now, for the quantitative safety evaluation of tunnel structures in China, the formulas recommended in the Code for Design of Highway Tunnel [30] and the Code for Design of Railway Tunnel [31] have frequently been applied. Using the formulas, the stress status of a certain section of the tunnel structure can be obtained (the axial force and bending moment). Though this method can meet the requirements of the safety evaluation of the structure to a certain extent, as mentioned above, the health monitoring of a tunnel structure is a complex system, influenced by various factors such as the geological condition, the section types, and the construction method. The influencing factors include qualitative and quantitative indices, which are related and interact with each other. Thus, it is obviously inappropriate to evaluate the health status of the tunnel structure with the above simple quantitative evaluation method [3]. Moreover, many of these factors are coupled and interact with each other. It is difficult to obtain a reasonable evaluation using the common method of one-level fuzzy synthetic evaluation. The so-called one-level fuzzy synthetic evaluation means that, during the evaluating process, a number of influencing factors can be listed. Then each factor can be seen as a single evaluation factor. However, if the influencing factors of each factor in one-level fuzzy synthetic evaluation are further listed, then that makes it a two-level or multi-level fuzzy synthetic evaluation. Therefore, the method of multi-level fuzzy synthetic evaluation is more suitable to evaluate the health status of a tunnel structure. The steps of this method are illustrated in Figure 1.
## 3 Results and Preliminary Analysis  
### Results  
The strength performance of geomembrane, e.g., initial tangent modulus, secant modulus and offset modulus are expressed by tensile strength per unit width and corresponding tensile rate in both ASTM D4885-01 (Reapproved 2018) and the test procedures for geosynthetics (SL235-2012). The width used in the specification is the initial width of the specimen; however, the width gradually decreases in the axial tensile process. Therefore, the test methods do have certain limitations. The relationship between axial tension and displacement of the longitudinal and transverse specimens at all the testing temperatures are detailed in Figures 3 and 4, respectively. The studies show that the tensile strain at break of GEM is large (greater than 200%); affected by the internal space of the extreme temperature environment control box, the specimen fails to fracture, whereas the linear range of the relationship between tension and displacement can be obtained, which has no effect on the calculation of the initial modulus. It can be seen from the figure that at the same tensile displacement, the axial tension decreases with the increasing temperature, and the linear range of the relationship between force and displacement increases with the increasing temperature, that is, the higher the temperature, the greater the yield strength, and the smaller the tensile displacement.  
Figure 3: Relationship between axial tension and displacement of longitudinal specimen at (a) 0–60 \({}^{\circ}\)C; (b) \(-\)40–0 \({}^{\circ}\)C.  
Although the variation of mechanical properties of longitudinal specimen with temperature is consistent with that of the transverse specimen, there are certain differences at the same temperature. At the same tensile displacement, the axial tension of longitudinal specimen is higher than that of the transverse specimen. For example, with the tensile displacement of 80 mm at 4 \({}^{\circ}\)C, the axial tension of the longitudinal specimen is 11.0 kN, and that of the transverse specimen is 9.0 kN; at \(-40\)\({}^{\circ}\)C, the yield strength of the longitudinal specimen is 20 kN, and that of the transverse specimen is 17.5 kN.
## 3 Device Fabrication
### Inscription of the Sensing Structure  
We irradiated the fiber core with the infrared fs-laser pulses to fabricate the sensing structure within it. Inscription with fs-laser is becoming a powerful technique because the fiber does not need to be photosensitive [54]. The technique produces a highly localized RI change [55] through the high-intensity laser pulse interaction across a tiny region in a shorter time-frame that will result in high-resolution inscription [56]. The fabricated sensors are relatively stable at higher temperatures than conventional UV laser-based sensors [57] because the change of index occurs as a result of high intensity nonlinear multiphoton process, which allows sensors to be durable up to approximately the glass transition temperature (t\({}_{g}\)).  
The fiber taper (see Figure 7a) is first placed on the fs-laser micromachining set-up (from Newport Corp.) shown in Figure 8a, having a precise control of movement (motion control) in three dimensions (X, Y, and Z axes). Next, the fiber alignment is performed using a three-dimensional translation controller. The fs-laser pulses, emitted from the Ti:sapphire laser source (from Spectra-Physics), are focused onto the fiber core. Each pulse creates a grating plane. The laser parameters [58] are shown in Table 2. The fiber is moved along its main axis with a translational speed (\(\
u\)) to perform point-by-point writing (see Figure 8b). The period of a grating now depends on the translational speed (\(\
u\)) and laser repetition rate (l\({}_{fr}\)) as in Equation (9) [37]. In this way, the structure (total 7 mm in length), composed of two identical uniform FBG (each of 3 mm length) spaced apart by a small gap (1 mm), is directly inscribed within the core of the fiber waist.  
\[\Lambda=\frac{\
u}{I_{fr}} \tag{9}\]  
Figure 8: Inscription of sensing structure in fiber taper: (**a**) micromachining set-up; and (**b**) sensor writing.  
Figure 7: Adiabatic fiber taper: (**a**) schematic; and (**b**) microscopic view of fiber waist after taper.  
The fabrication was performed in a standard fiber, followed by the fiber taper, using uniform apodization (45:45); the translational velocity was 103.1 \(\upmu\)m/s for the design wavelength of 1547.04 nm. Figure 9 shows the spectrum of the FP fabricated in the adiabatic fiber taper, where P1 and P2 are the two peaks, and d1 is the dip wavelength of the spectrum. Each wavelength was tracked for the applied strain and temperature during the experiment.
## 2 Background  
### Flash Memory  
Flash memory includes NAND flash and NOR flash. Especially NAND flash has been extensively used as mass storage (e.g., SD/miniSD/microSD cards, MMC cards, UFS cards) due to its cheap price. Compared to conventional hard disk drives (HDD), the flash memory is electrically erasable and re-programmable and does not rely on mechanical components. Therefore, it usually has much higher I/O throughput and much lower noise compared to HDDs. The NAND flash is organized into blocks, each of which is typically a few hundred kilobytes in size. A flash block consists of pages, each of which is a few kilobytes in size. Typically, the I/O operations are performed on the basis of pages, while the erase operations are performed on the basis of blocks.  
Compared to traditional mechanical disk drives, NAND flash is different in nature: First, it uses an erase-then-write design, i.e., a flash memory cell needs to be erased first before it can be re-programmed. Therefore, to modify the data stored in a page, we need to erase the entire encompassing block. This, however, requires copying out valid data stored in this block, erasing the block, and writing the data back, leading to significant write amplification. To mitigate the write amplification, the flash memory typically uses an out-of-place update strategy (see Figure 1), i.e., when the OS performs an overwrite operation, the old data will be temporarily preserved in the flash memory, and the new data will be written to new locations. The data repairer component of our design will utilize this feature to restore external storage to a good historical state after malware detection. Second, each flash block only allows a limited number of program-erase (P/E) cycles, and if a flash block is programmed/erased too frequently, it will turn \"bad\" and is not able to reliably store data anymore. Therefore, to prevent a single flash block from being erased/programmed too frequently, wear leveling is introduced to distribute P/Es evenly across the entire flash. Third, reading/writing a flash memory cell too frequently may flip the bits stored in its nearby cells of the same block, leading to read/write disturb errors.
## 6 Conclusions  
A miniature laser diode interferometer (MLDI) was designed for the on-line measurement of the displacement of precision machines or measurement equipment. In order to reduce the size of the MLDI, a compact laser diode (LD) was adopted as the laser source of the MLDI. The factors that affect the measurement accuracy of the MLDI were first analyzed. The effects of the nonlinear errors caused by the installation errors and the manufacturing errors--along with the error caused by the unstable LD wavelength--on the measurement accuracy of the MLDI were investigated. An error sensitivity analysis of the installation errors was proposed. An algorithm was proposed to eliminate the nonlinear errors. In addition, an active wavelength stabilization method based on the laser wavelength meter was proposed to stabilize the stability of the LD wavelength. It has seen verified that the stability of the LD wavelength was improved from \(10^{-6}\) to \(10^{-7}\) by using the active wavelength stabilization method rather than the passive wavelength stabilization method during a long period of time. The measurement accuracy of the designed MLDI was improved from \(\pm\)800 nm to \(\pm\)200 nm after the nonlinear error compensation and the wavelength stabilization. The uncertainty analysis will be carried out in future work.  
Conceptualization, Y.C. and Z.W.; methodology, Y.C.; software, Y.L.; validation, Y.L. and Z.W.; formal analysis, Y.L. and C.L.; investigation, Y.L. and Z.W.; resources, C.L.; data curation, Y.L., C.L. and Z.W.; writing--original draft preparation, Y.C. and Z.W.; writing--review and editing, Y.C.; visualization, Y.L. and Z.W.; supervision, Y.C.; project administration, Y.C.; funding acquisition, Y.C. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Natural Science Foundation of China (Grant No. 51905078) and the National Key Research and Development Program of China (Grant No. 2018 YFB2001400).  
Not applicable.  
The data presented in this research are available on request from the corresponding author.  
The authors declare no conflict of interest.
## 1 Introduction
Due to the lack of the high-power amplification solution of the NIR laser (for example at 1553 nm), nonlinear frequency processes such as optical parameter oscillation (OPO) could be applied to build a wavelength converter by shifting the wavelength from 1 um to the desired wavelength as well as obtaining relative higher power [21]. Recently, a diamond Raman laser showed its ability in achieving a high power and a high conversion efficiency at the 1 st Stokes of the 1-um laser [22; 23], which implies the possibility to be applied in the 193-nm DUV laser generation because of its high Raman gain and large frequency shift. In this paper, we present a review on the current status of the high-power solid-state DUV lasers. The high-power DUV laser at 258 nm was generated by FHG from 1 um. The development of the 193-nm laser was demonstrated by stages of SFG. In order to scale the DUV laser power effectively, a new concept of the 193-nm DUV laser generation is presented based on the diamond Raman laser.
# Bridge Damping Extraction Method from Vehicle-Bridge Interaction System Using Double-Beam Model
## 5 Application  
In this section, a single-tower cable-stayed bridge with a span of 336 m is used as a case study to assess damping, as shown in Figure 12. The bridge was equipped with a bridge health monitoring system that monitored the structural response, environment, and vehicle loads. Using the bridge mid-span acceleration data, the damping ratio of the vehicle-bridge system was calculated, and the information about the vehicles on the bridge was obtained through the WIM system. The damping ratio of this bridge was then extracted using the method proposed in this paper.
# Highly Adaptive Reconfigurable Receiver Front-End for 5G and Satellite Applications
## 5 HARRF LNA Design  
In this work, two low-noise amplifiers (LNAs) are designed and fabricated using a \(0.15\,\mathrm{\SIUnitSymbolMicro m}\) gate length Indium Gallium Arsenide (InGaAs) pseudomorphic high electron mobility transistor (pHEMT) technology. The first LNA is an X-band LNA operating from \(8\,\mathrm{GHz}\) to \(12\,\mathrm{GHz}\), with a maximum bandwidth of \(4\,\mathrm{GHz}\), and a geometric center-design frequency of  
\[f_{c}=9.8\,\mathrm{GHz}, \tag{32}\]  
yielding a fractional bandwidth of  
\[\mathrm{Fractional\ Bandwidth}=\frac{4}{9.8}\approx 0.408\quad(\mathrm{or}\,40. 8\%). \tag{33}\]  
The second LNA operates in the K/Ka-band frequency range of \(23\,\mathrm{GHz}\) to \(28\,\mathrm{GHz}\), with a total bandwidth of \(5\,\mathrm{GHz}\), and a geometric center-design frequency of  
\[f_{c}=25.4\,\mathrm{GHz}, \tag{34}\]  
which provides a fractional bandwidth of  
\[\frac{5}{25.4}\approx 0.197\quad(\mathrm{or}\,19.7\%). \tag{35}\]  
Both LNAs use a three-stage cascade topology, with each transistor stage having separate gate and drain lines. The first stage of each LNA is carefully optimised for low noise figure (NF) and good input matching, whereas the subsequent stages are dedicated to ensuring high gain flatness and high output power. Both LNAs are designed to meet the criterion of unconditional stability as outlined in [15; 18].  
Unconditional stability for a two-port active device can be checked using the well-known Rollet stability factor \(K\) and the stability measure \(\Delta\), which are expressed as:  
\[K=\frac{1-|\Delta|^{2}}{2|S_{12}S_{21}|},\quad\Delta=S_{11}S_{22}-S_{12}S_{21}. \tag{36}\]  
For unconditional stability, the following conditions must be satisfied:  
\[K>1\quad\mathrm{and}\quad|\Delta|<1. \tag{37}\]
Anomalies in traffic flow data often indicate special situations, such as equipment failures or unexpected incidents within specific time periods. Failure to detect these anomalies in a timely and accurate manner may lead to severe consequences. Fast and effective anomaly detection helps identify potential issues early, minimizing unnecessary economic losses [4]. Therefore, efficiently extracting potential anomalies from data holds significant practical value. However, specialized anomaly detection methods for traffic flow data remain scarce. Existing studies often adopt a uniform detection approach without fully considering the varying needs of different domains. Moreover, many methods primarily focus on the spatio-temporal characteristics of traffic flow data while overlooking its frequency-domain features, limiting the exploration of periodic patterns. This single-dimensional analysis lacks specificity in handling traffic anomalies, making it challenging to accurately capture complex abnormal patterns. To achieve more precise anomaly detection in traffic flow data, this paper proposes a prediction-based anomaly detection method for traffic flow data with multi-domain feature extraction. The key innovations of this method are as follows:  
1. Optimizing the Prediction Model by Combining Data Characteristics This method not only focuses on the temporal characteristics of traffic flow data but also fully considers the spatial correlations between the data. By using different models to jointly learn both temporal and spatial features, it enables feature extraction in the time domain. Additionally, recognizing that traffic flow data often exhibits periodicity and may be subject to noise interference, this paper leverages the advantages of frequency-domain analysis (such as periodicity identification and noise suppression) to further explore the frequency-domain characteristics of the data. The model then learns its frequency-domain representation, achieving more comprehensive feature extraction. Experimental results show that prediction models that fully explore data features can significantly improve prediction accuracy. 2. Error Analysis and Threshold DeterminationPrediction-based methods are widely used in anomaly detection, relying on the difference between predicted and observed values to identify anomalies. However, determining an appropriate error threshold in existing methods often lacks adaptability and reliability. To address this issue, this paper introduces Chebyshev's inequality to establish a more scientific and rational threshold for error analysis, thereby enhancing the accuracy and robustness of anomaly detection.
###### Abstract
Seismic hazard is primarily related to the ground movement that is caused by earthquake occurrences. The goal of a seismic hazard assessment is to quantify the level of seismic hazard by computing ground motions and accounting for the associated epistemic uncertainties [47]. Ground motions can be expressed in terms of seismic intensity measures, such as Peak Ground Acceleration (PGA), Peak Ground Velocity (PGV), and spectral acceleration (S\({}_{\rm a}\)) values for each case study. PGA and PGV represent the maximum absolute acceleration and velocity that a Single Degree of Freedom (SDOF) system can experience while having infinite stiffness, which denotes a natural period of vibration equal to zero. On the other hand, a response spectrum displays the maximum S\({}_{\rm a}\) values of numerous SDOF systems with various natural vibration periods exposed to the same seismic input. Probabilistic Seismic Hazard Assessment (PSHA) is a reliable method for the computation of the aforementioned parameters, as it accounts for uncertainty through variability that is associated with seismic sources, ground motion prediction equations (GMPEs), and local site conditions [47; 48; 49; 50; 51]. PSHA uses an approach that incorporates a range of possible earthquake occurrences and their associated probabilities, providing a more comprehensive and realistic estimation of the seismic hazard [47; 48; 49; 50; 51]. There have been various seismic hazard assessment studies for the Greek territory [52; 53; 54; 55; 56; 57; 58; 59]. In this paper, we assess seismic hazard by computing PGA, PGV, and S\({}_{\rm a}\) values for the administrative region of Attica, including its islands, which is critical, as it composes 27% of the total population of the country [60].
## 1 Introduction  
Mainly, through a technical-economic analysis, the effects of an investment project are assessed together with the implementation profitability of the project throughout the entire lifetime. The analysis within the feasibility study is holistically performed, combining technical and economic aspects, on which the optimal solution is determined. The economic performance indicators are strictly dependent on the equipment of the technical solution and its characteristics. The calculations performed within the economic analysis, throughout a relatively long period of time, take into account considerations, premises, and a set of hypotheses compatible with the analysed project, which are lowering the uncertainty degree of the analysis.  
In the present paper, a comparative analysis from an economical perspective is performed for a hybrid thermal energy supply system with different operating scenarios, in order to identify the optimal solution.  
Defining and determining the financial-economic performance indicators associated with the proposed scenarios for the hybrid thermal energy supply system offers the possibility to identify the optimal operating scenario. For given conditions, this scenario will minimize the financial effort and risks while increasing the benefits.  
The main purpose of the project that will be implemented is to cover the thermal energy demand of a building from the campus of University Politehnica of Bucharest (UPB) using a hybrid thermal energy supply system based on renewable energy sources, and to inject the overproduction of heat into UPB's district heating network. Therefore, the following objectives are proposed:  
* Generate three forms of energy (electricity, heat, and cold) based on a hybrid renewable energy source (geothermal and solar), in which the electricity produced will cover at least the consumption of the thermal energy generation unit (on a yearly basis).
* Fully cover the heating and cooling demand for the target building (TB) using thermal energy produced from 100% renewable energy sources [1].
* The reintegration of the TB into the UPB heat distribution network (UPB DH) to inject the overproduction of heat.
* Develop a modular concept that will ease the process of replication and scaling.