esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion  
### Feature of Shear Band in Architected Metamaterials  
When it comes to the deformation pattern, shear band found in P-0 structure has much in common with slip band in single crystals. For P-0 structure, the localized plastic deformation at the nodes adjacent to the diagonal results in the formation of shear band and the subsequent rotation of unit  
Figure 7: Deformation behavior and failure mode of four structures under compression.  
cells (see Section 3.2), which leads to the highly localized deformation along the diagonal when the structure is loaded beyond the elastic limit. This sort of shear band has also been observed in samples with a variety of lattice structures such as BCC, BCC-Z and FCC-Z (similar to BCC, FCC micro-lattice but with vertical pillars), in which the deformation localization was found to be accorded with internal node movement [44]. The phenomenon is similar to the slip band along particular direction as shown in Figure 8, when single crystals are loaded beyond the yield point and undergo strain localization [27].  
In addition, the plastic deformation in single crystals is generated by a dominant slip mode of dislocations, and a step with the width of a Burgers vector is formed [27]. During the process the strain becomes localized and stress for further deformation starts to decrease. Similarly, as the strain increases when the architected metamaterial is compressed, a diagonal deformation pattern occurs which can be regarded as the result of node movement along the same direction, with the width of a strut length. The movements of node also result in repeated decrease and increase of the stress.  
However, shear band (in architected metamaterial) and slip band (in single crystals) differ in the way of translating macroscopic shear. In single crystals, strong interactions exist between neighboring atoms which are deemed rigid, hence atomic bonds form plastic hinges which simply allow axial compression at the atoms, resulting in continuous zones of plastic deformation. In contrast, when external stress is loaded on architected metamaterials, the highly concentrated strains around the nodes could generate new plastic hinges near the center of the struts, which lead to the rigid body rotations of strut intersections, corresponding to the localized deformation and collapse behaviors of materials.  
The analysis demonstrates that the P-0 structure with completely periodic arrangement of microstructures is roughly similar to single crystals in its deformation mode, however it is still distinct because of the attempt to mimic crystallographic microstructures at a macroscale level.
# Assessment Analysis of Flood Susceptibility in Tropical Desert Area: A Case Study of Yemen
## 1 Introduction
This study is valuable since it is the first time proposed models are being used in a tropical desert area of Yemen to assess flood susceptibility. The models can also be used to analyze other disasters, such as earthquakes, landslides, and other natural disasters. Additionally, this study contributes significantly to the global effort to mitigate the risk of natural disasters, notably in Yemen. The model's performance and validation of the FFS maps are assessed using the confusion matrix and AUROC. The results of this study may be helpful to legislators and city planners for sustainable land use and infrastructure planning.
# Low-Power Wake-Up Receivers for Resilient Cellular Internet of Things
###### Abstract  
Smart Cities leverage large networks of wirelessly connected nodes embedded with sensors and/or actuators. Cellular IoT, such as NB-IoT and 5G RedCap, is often preferred for these applications thanks to its long range, extensive coverage, and good quality of service. In these networks, wireless communication dominates power consumption, motivating research on energy-efficient yet resilient and robust wireless systems. Many IoT use cases require low latency but cannot afford high-power radios continuously operating to accomplish this. In these cases, wake-up receivers (WURs) are a promising solution: while the high-power main radio (MR) is turned off/idle, a lightweight WUR is continuously monitoring the RF channel; when it detects a wake-up sequence, the WUR will turn on the MR for subsequent communications. This article provides an overview of WUR hardware design considerations and challenges for 4G and 5G cellular IoT, summarizes the recent 3 GPP activities to standardize NB-IoT and 5G wake-up signals, and presents a state-of-the-art WUR chip.  
wake-up receiver; low-power receiver; Internet of Things; cellular communication; NB-IoT; 5G; 3 GPP; energy efficiency +
Footnote †: journal: Information  
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# Automatic Identification System for Rock Microseismic Signals Based on Signal Eigenvalues
### Technical Route  
In this paper, the comprehensive analysis method of multiple parameters is used to analyze the difference between rock blasting signals and rock fracture signals. The technology roadmap is shown in Figure 1. The specific analysis methods are as follows:  
1. The differences between the maximum amplitude value and the signal duration of the collected original rock blasting signals and the rock fracture signals are directly analyzed.
2. Using Symlets8 wavelet, three layers of decomposition layers are selected to denoise the original microseismic signal. The Hilbert-Huang transform is used to process the microseismic signal after noise reduction, and the differences between the microseismic signal of rock blasting and the microseismic signals of rock fractures in the main frequency of the signal are analyzed.  
3. The ensemble empirical simulation decomposition method is used to decompose the microseismic signal into 8 layers after noise reduction, and the differences between the energy proportion of the rock blasting microseismic signals and the rock fracture microseismic signals in terms of total energy proportion after different decompositions are analyzed.
4. The fractal box dimension method is used to analyze the differences in fractal box dimension distribution between rock blasting vibration signals and rock fracture microseismic signals after noise reduction.
5. According to the above analysis results, an automatic identification model of microseismic signals based on the BP neural network is established, and the model is trained and tested.
# A 28-nm CMOS Low-Power/Low-Voltage 60-GHz LNA for High-Speed Communication
###### Abstract  
This paper presents a wideband low-power/low-voltage 60-GHz low-noise amplifier (LNA) in a 28-nm bulk CMOS technology. The LNA has been designed for high-speed millimeter-wave (mm-wave) communications. It consists of two pseudo-differential amplifying stages and a buffer stage included for 50-Ohm on-wafer measurements. Two integrated input/output baluns guarantee both simultaneous 50-ohm input-noise/output matching at input/output radio frequency (RF) pads. A power-efficient design strategy is adopted to make the LNA suitable for low-power applications, while minimizing the noise figure (_NF_). Thanks to the adopted design strategy, the post-layout simulation results show an excellent trade-off between power gain and 3-dB bandwidth (\(BW_{\text{3 dB}}\)) with 13.5 dB and 7 GHz centered at 60 GHz, respectively. The proposed LNA consumes only 11.6 mA from a 0.9-V supply voltage with an _NF_ of 8.4 dB at 60 GHz, including the input transformer loss. The input 1 dB compression point (\(IP_{\text{1 dB}}\)) of \(-\)15 dBm at 60 GHz confirms the first-rate linearity of the proposed amplifier. Human body model (HBM) electrostatic discharge (ESD) protection is guaranteed up to 2 kV at the RF input/output pads thanks to the input/output integrated transformers.  
low-noise amplifier (LNA); integrated transformers; baluns; noise figure (_NF_); electro-static discharge (ESD) protection; millimeter-wave (mm-wave) applications Article
# Performance Evaluation of Open-Source Serverless Platforms for Kubernetes
### Background  
Serverless is described in detail by [1; 2]; in summary, it is an execution model for cloud applications that abstracts away concrete servers. This means that developers do not know exactly which machine their code will be run on. Furthermore, serverless applications are composed of serverless functions that usually handle a single task and become active when invoked through a certain type of event. Serverless functions are commonly embedded into function environments to form function images (commonly container images). These images can then be used to create function instances, which are usually just container instances. Depending on the current amount of incoming load for a serverless function, the serverless platform can automatically scale the number of active function instances by starting new instances or terminating existing ones and load balancing the incoming requests among all active instances.  
Kubernetes fits well with serverless, as it provides all the necessary technologies and could itself even be considered as accidentally serverless. Installing a serverless platform, such as OpenFaa5 or Nuclio, on top of Kubernetes adds workflows for creating serverless functions, uploading them to the platform and adding endpoints that invoke them. Moreover, the serverless platforms provide templates for function environments that must be used to build function images. As Python and Javascript are the most popular programming languages for building serverless functions (See DataDog State of Serverless 2021: [[https://www.datadoghq.com/state-of-serverless/](https://www.datadoghq.com/state-of-serverless/)]([https://www.datadoghq.com/state-of-serverless/](https://www.datadoghq.com/state-of-serverless/)) accessed on 27 May 2022), most serverless platforms offer well-developed templates for these languages. C/C++ is far less popular for serverless computing, and only few serverless platforms offer dedicated support for it, meaning that users must often fall back on general-purpose templates, if any are available.
## 5 Limitations  
This work presents some limitations. First, our method was based on a microscopy set-up with linearly polarized light. Although linear polarization has been widely used for collagen fibers quantification [35], only collagen fibers oriented at a certain angle with respect to the polarizer can be enhanced, which leads to partial underestimation of collagen content. To overcome this limitation, acquisition of linearly polarized light images at different angles of rotation may be performed [36], or, alternatively, our framework may be adapted to model a circularly polarized light configuration [9; 10]. Second, we did not assess the accuracy of our method in comparison with samples of known collagen content nor with respect to analytical methods for collagen assessment. Third, our proof-of-concept application was limited to cardiac samples of right atrial appendage specimens from cardiac surgery patients. In future studies, the validation of our approach should be extended to include the analysis of different tissue types and the comparison with other collagen estimation techniques.
# Through-Wire Microstrip-to-Empty-Substrate-Integrated-Waveguide Transition at Ka-Band
## 2 Design Method  
As is was exposed in [9] for the X-band, the through-wire transition consists of three layers (Figure 1): the upper one is used for the microstrip feeding and the top cover of the ESIW, the central one is used to implement the ESIW, and the bottom one is used as bottom cover for the ESIW. The power transfer between the microstrip and the ESIW is carried out with a metallic filament passed through via holes and tin soldered to the upper and bottom layers. It is also necessary to mechanize a circular gap in the bottom of the top layer to avoid short circuiting the microstrip with the upper conductor of the ESIW (which is also the ground of the microstrip), creating a isolated pad from the microstrip ground. This structure has a great impact on the impedance matching of microstrip and ESIW lines, which makes it necessary to carefully optimize pad and gap dimensions.  
As through-wire transition was first proposed in the X-band, it is necessary to validate the design procedure and the transition at upper frequencies. To accomplish that, the procedure and equations shown in [9] were used to design both transition at the Ku- and Ka-bands. For that, the width and length of the microstrip transformer (\(w_{trans}\) and \(d\)), the width of the coupling gap (\(gap\)), the diameters of the circular pads of the upper layer (\(pad_{T}\) and \(pad_{B}\)), the diameter of the via hole for the filament (\(d_{hole}\)), the diameter of the filament (\(d_{cable}\)), and the distance between the ESIW initial short circuit and the filament (\(L\)) were carefully calculated. After that, a final optimization in CST Studio Suite was carried out for all the design parameters (\(w_{trans}\), \(d\), \(gap\), \(pad_{T}\), \(pad_{B}\) and \(L\)) to obtain the final dimensions for each transition, which are shown in Table 1 jointly with those obtained in the X-band.
## 5 Use Case: Dynamic Radio/MEC Resource Allocation and Slicing Management in High Mobility Scenarios  
After confirming the effectiveness of the federated approach in the proposed solution and its advantages in terms of scalability and training process efficiency, this section introduces the application of the system in a use case with a realistic scenario.
# Data Conversion Strategies for Effective Aviation Technical Support as a Service
## 3 Results
### Extended Decision-Making Model for Optimal ATSaaS Architecture Selection  
Selecting the optimal architecture for ATSaaS platform requires a comprehensive evaluation of multiple criteria beyond just cost. To address this, a decision-making model is introduced in this section, using a multi-criteria decision-making (MCDM) approach. This model considers essential factors such as cost, performance, reliability, security, flexibility and scalability, control and management, and sustainability. By integrating a weighted scoring system, the model enables a structured comparison of centralized and decentralized architectures, providing a robust framework for stakeholders to identify the architecture that best aligns with their operational priorities and long-term goals.
## 3 Results and Discussion
### CO Release, Drug Release, and Chemical Images of Loaded CF's
The chemical maps of the selected vibrations show the following features. Consistently with images reported in Figure 3 the asymmetric \(\gamma\)(Si-O-Si) band shows the highest intensity  
Figure 4: Top left: UV-visible spectra of reduced Mb in the presence of CF and CF-12. Insert shows the splitting of the protein Q band (red line) characteristic of carboxymyoglobin (Mb-CO). Bottom Left: IR spectra (2200–700 cm\({}^{-1}\) range) of isolated CF-12 before (black) and after (red) exposure to a buffered solution of reduced Mb. The tentative assignment of major peaks are based on reference [72]. Right: MCT detector generated chemical images of single CF-12 valves exposed to a buffered aqueous solution of reduced myoglobin. (**A**): Optical image; (**B**): chemical mapping of the Si-O-Si stretching vibration at 1100 cm\({}^{-1}\); (**C**): chemical mapping of the residual symmetric C\(\equiv\)O stretching mode of B\({}_{12}\)-ReCORM-2 at 2010 cm\({}^{-1}\); (**D**): overlay of (**B**) and (**C**); (**E**) and (**F**): 3D surface representations of chemical maps shown in (**B**) and (**C**), respectively. in the central region of the diatom valve and lower intensity on the girdle band. Once again, the roughness of the valve surface can be fully appreciated in the 3D surface representations of the chemical map (Figure 4E). The residual intensity of the weak 2010 cm\({}^{-1}\) absorption is highest in the girdle band. This is most evident in the 3D surface representations (Figure 4F) of the vibration. We note once again here that these vibrations also contain the Si-O-Si overtone modes. Thus the observed vibrations in hydrated CF-12 are most likely be due to an overlap of both residual v(CO) Re-C\(\equiv\)O stretching vibrations and Si-O-Si overtone modes. Having established that following chemisorption of ReCORM-2 and B\({}_{12}\)-ReCORM-2 on _Coscinodiscus_ frustules the molecules retain their CO-releasing ability, we finally studied CF-1 and CF-12 drug release profiles. The addition of PBS buffer to solid samples of CF-1 and CF-12 initiated drug release, which was monitored by ICP-OES (Re content). As shown in Figure 5, after 1 h of incubation ca. 90% of the drug contents were released from the frustules. The release occurred very rapidly, in particular for ReCORM-2, and was steadily sustained afterward. Examination of the relative profiles of drug discharge indicates that, within experimental error, ReCORM-2 is more rapidly released than B\({}_{12}\)-ReCORM-2 in the first 20 min of incubation, but then similar concentrations of Re metal are measured afterward.
## 3 Results  
We enrolled a sample of 400 pediatric dentistry patients for this cross-sectional, baseline study. This represents 80% of the parents of children who are age-eligible for the HPV vaccine and were receiving care at our clinics.  
Of the 400 pediatric patients included in the analysis, 182 (45.5%) had completed the HPV vaccine series, whereas 218 (54.5%) had not. Vaccine uptake differed significantly by age and gender but showed no significant variation by race/ethnicity, primary language, or insurance type (Table 1). Completion rates rose steadily with age (\(p\) < 0.001): only 24% of children aged 9-11 years (19/79) were up to date, compared with 45% of those aged 11-14 years (93/205) and 60% of adolescents aged 15-18 years (70/116). Gender was also associated with vaccination status (\(p\) = 0.03); females accounted for 59.3% of the vaccinated cohort but only 48.6% of the incompletely vaccinated group, whereas males showed the opposite pattern (40.7% vs. 51.4%). By contrast, completion rates did not differ across racial/ethnic categories (\(p\) = 0.95); Latino/Hispanic patients formed the largest subgroup in both vaccinated (59.3%) and unvaccinated (59.6%) cohorts. Primary language likewise showed no association with vaccination status (\(p\) = 0.65), with English speakers representing approximately three-fifths of each group and Spanish speakers about one-quarter. Insurance type was not a significant correlate (\(p\) = 0.14); Medicaid covered roughly two-thirds of all patients irrespective of vaccination status, while the proportions of commercially insured and uninsured children were comparable between groups. Taken together, these data identify younger adolescents (particularly those aged 9-11 years) and male patients as priority groups for chair-side HPV vaccine promotion in the dental setting (Table 1).  
Among the 172 parents who declined chair-side HPV vaccination, the most frequently cited barrier was a preference for having the vaccine administered in a physician's office (75/172, 43.6%), followed by indecision (35/172, 20.3%) and unspecified \"other\" reasons (25/172, 14.5%) (Figure 2). Concerns about potential side-effects or risks accounted for 14 respondents (8.1%), whereas religious objections were reported by nine respondents (5.2%). Three low-prevalence barriers--waiting for additional information, distrust of the vaccine or provider, and lack of time despite having decided to vaccinate--were each endorsed by four respondents (2.3%). Only two parents (1.2%) indicated a belief that vaccines are ineffective. These data demonstrate that most resistance to chair-sidevaccination stems from site-of-care preferences or indecision rather than safety worries or vaccine skepticism.
## 3 Model Architecture
### Alignment with Cybersecurity Standards  
The RC model and P-R-A-L framework are designed to align with global and national cybersecurity standards, ensuring compatibility and enhancing practical adoption. Specific mappings include the following:  
* NIST SP 800-37 PDR Cycles: The P dimension corresponds to the Prepare and Protect phases, focusing on preemptive threat mitigation. R aligns with the Detect and Respond phases, emphasizing system endurance under attack. A maps to Respondand Recover, prioritizing rapid restoration, while L connects to Identify and Prepare for long-term adaptation through learning.
* GB/T 44862-2024: The four dimensions (P, R, A, L) directly map to the standard's capability domains of Prevention, endurance, recovery, and adaptation. Indicators within the P-R-A-L framework serve as evidence and quantifiable means to meet the standard's requirements for dynamic risk control and resilience assessment.
* MITRE ATT&CK Threat Taxonomy: Indicators in the P dimension, such as \"threat hunting behavior library\" and \"attacker intent inference\", and in the R dimension, such as \"dynamic attack containment\", directly leverage MITRE's tactics and techniques for mapping and quantification. Additionally, the computation of \(\sigma\) incorporates attack cost (\(C_{attack}\)) metrics aligned with ATT&CK's adversarial behavior models to quantify real-time threat entropy.
## 2 The Proposed Pedestrian Attributes Recognition Method
### Loss Function Design  
In this paper, a sigmoid cross entropy-based loss function is adopted in the proposed model. Sigmoid is a kind of S-type function [13; 14], and can represent the classification results in the form of output probability. Therefore, it can handle the multi-classification problem at the output of the neural network, and meet the requirements of pedestrian attributes recognition. As shown in Equation (1), where \(p_{n,l}\) is the output probability of the lth attribute of the nth sample.  
\[p_{n,l}=1/(1+\exp(-x_{n,l})) \tag{1}\]  
Figure 2: An example of a pedestrian image and labels in the PETA dataset.  
Because the proposed model recognizes multiple attributes of the pedestrian sample simultaneously, it is essentially a multi-label recognition for pedestrians. Therefore, it is necessary to determine the relationship among attributes and consider the loss comprehensively. The overall sigmoid cross-entropy loss function is adopted in this paper, as shown in Equation (2).  
\[Loss_{sigmoid}=-\frac{1}{N}\sum_{n=1}^{N}\sum_{l=1}^{L}\left(y_{n,l}\ln(p_{n,l })+(1-y_{n,l})\ln(1-p_{n,l})\right) \tag{2}\]  
The distribution of the samples is not balanced in the pedestrian datasets. In order to solve this problem, a positive sample scale index factor is introduced to the loss function to comprehensively determine the loss value of each attribute, and deal with the severe imbalance distribution of attributes. \(w_{l}\) represents the weight of the loss of the lth attribute, and the loss function with the positive sample scale factor added can be expressed by Equation (3).  
\[Loss_{our}=-\frac{1}{N}\sum_{n=1}^{N}\sum_{l=1}^{L}w_{l}(y_{n,l}\ln(p_{n,l})+( 1-y_{n,l})\ln(1-p_{n,l})) \tag{3}\]  
where \(p_{l}\) is the proportion of the positive sample of the lth attribute in the training set, and \(w_{l}\) can be calculated using the following equation:  
\[w_{l}=\exp(-p_{l}/\sigma^{2}) \tag{4}\]  
In this paper, the value of \(\sigma\) in Equation (4) is set to 1.
## 2 Materials and Methods
### Characterization Techniques  
#### 2.2.1 Fourier Transform Infrared Spectrometry (FT-IR)  
ATR-FTIR spectra of the dried powder samples were recorded on FTIR spectrophotometer (Jasco Europe s.r.l. Cremella, Italy) equipped with an ATR (attenuated total reflectance) attachment with horizontal ZnSe crystal (Jasco PRO400S). The spectra resolution was 4 cm\({}^{-1}\), and scans were repeated 100 times. The appropriate amount of the samples was placed on the ZnSe crystal and then the FTIR spectrum was measured in the range of 4000-500 cm\({}^{-1}\).