esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Derivation of the **pdfs** Assigned to Aliquot Mass and to Analyte Mass  
The mass concentration of an analyte in a subsample is considered a random continuous variable, denoted as \(\mathbf{R}\), defined as the ratio of analyte mass, denoted as \(\mathbf{Y}\), to the aliquot mass, denoted as \(\mathbf{X}\). Both \(\mathbf{X}\) and \(\mathbf{Y}\) masses are considered random continuous variables. According to standard laboratory procedures, an aliquot is taken from a commitment sample and carefully weighed for analytical measurement. The laboratory practice under the ISO EN 17025 standard imposed high exactness for the aliquot mass measurement [30]. The uncertainty of a laboratory weighing is less than \(10^{-2}\) g for masses of several grams. In such a case, a triangular probability density function (pdf) can be assigned to the \(\mathbf{X}\) mass [26].  
\[\mathbf{f}_{\mathbf{X}}(\mathbf{x})=\left\{\begin{array}{l}\frac{\mathbf{x}-\mathbf{m}+\mathbf{a}}{ \mathbf{a}^{2}};\mathbf{x}\in[\mathbf{m}-\mathbf{a};\mathbf{m}]\\ \frac{\mathbf{x}+\mathbf{m}+\mathbf{a}}{\mathbf{a}^{2}};\mathbf{x}\in[\mathbf{m};\mathbf{m}+\mathbf{a}]\\ \mathbf{0};\mathbf{x}\
otin[\mathbf{m}-\mathbf{a};\mathbf{m}+\mathbf{a}]\end{array}\right. \tag{1}\]  
where \(\mathbf{m}\) is the mean mass of the aliquot and \(\mathbf{a}\) is the largest weighing error.  
The analyte mass \(\mathbf{Y}\) is considered a random variable whose value in a sample of \(\mathbf{X}\) mass is unknown and very difficult to establish through experimental trials. The ISO 98-3 standard [25] recommends assigning a uniform \(\mathbf{pdf}\) in cases where no reliable information about a random variable exists. In this respect, a uniform \(\mathbf{pdf}\) is assigned to the analyte mass \(\mathbf{Y}\) contained in an aliquot.  
\[\mathbf{f}_{\mathbf{Y}}(\mathbf{y})=\left\{\begin{array}{l}\frac{1}{b}:\mathbf{y}\in[\mathbf{0},\mathbf{b}]\\ \mathbf{0};\mathbf{y}\
otin[\mathbf{0},\mathbf{b}]\end{array}\right. \tag{2}\]  
where \(\mathbf{b}\) is the maximum mass of the analyte in an aliquot.
# Effective Blind Frequency Offset Estimation Scheme for BST-OFDM Based HDTV Broadcast Systems
## 4 Proposed Estimation Scheme
### Computational Complexity  
Let us now consider the computational load of the estimation schemes. To make a parallel between the conventional and proposed estimation schemes, we consider the situation where the conventional scheme uses \(N_{f}=N_{p}\) explicit pilots, although in practice the number of explicit CPs is very small compared to that of TMCC signals. Table 2 shows the complexity of the conventional and proposed estimation schemes. The complexity of the estimation methods is compared with respect to the number of real floating point operations (flops). We assume that a complex multiplication is counted as six flops [26]. With this provision, the number of real flops needed to jointly get the estimate is \(10N_{a}N_{f}+3N_{f}\) for the conventional scheme, whereas the proposed scheme requires \(6N_{a}(2N_{p}-1)+3N_{p}-1\) real flops.
## 5 Conclusions  
In this paper, we propose a compressive beamforming method in the Fourier domain based on Stolt's f-k migration. This framework combines the advantages of beamforming in the Fourier domain and compressed sensing theory to provide a higher transmission rate and better image quality during tele-ultrasound imaging, especially for ultrasound cardiac imaging. Therefore, compared with DAS and beamformers with compressed sensing in the temporal domain, this framework improves contrast and lateral resolution of the ultrasound image while reducing data load during transmission and beamforming. Moreover, the method compresses data load by cutting down the number of transducer elements, which does not require too much memory for measurement matrix during sparsity and compression. Our work illustrates that the compressive beamforming on  
Figure 11: The time required to acquire one ultrasound image after averaging.  
lateral wavenumber is a competitive method which is especially useful to increase data transfer speed and imaging speed.  
Conceptualization, X.Z. and Y.J.; methodology, X.Z.; software, N.W.; data curation, Y.X.; writing--original draft preparation, X.Z.; writing--review and editing, Y.J. and Y.C. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the National Natural Science Foundation of China (Grant NO. 21927803), National Key Research and Development Program of China (Grant NO. 2019 YFC0120500), Jiangsu Science and Technology Project (Grant NO. BZ2021037), the Funds of Youth Innovation Promotion Association, Chinese Academy of Sciences (Grant NO. Y201961 and 20A122062 ZY), Suzhou Science and Technology Project (Grant NO. SS202062), Key R&D program of Jiangsu Province (Grant NO. BE2021659), Suzhou science and technology plan project (Grant NO. SZS201903).  
The animal study protocol was approved by the Suzhou Institute of Biomedical Engineering and Technology (Chinese Academy of Sciences) Institutional Animal Ethics Committee (SibetAEC) (protocol code: 2021-B22).  
Not applicable.  
The authors declare no conflict of interest.
###### Abstract  
The friction-type high-strength bolted (FHSB) T-stub connection has been widely used in steel structures, due to their good fatigue resistance and ease of installation. While the current studies on FHSB T-stub connections mainly focus on the structural behaviors under both shear and tensile force, no research has been reported on the mechanical responses of the connections under the combined effects of shear and compression. To make up for this gap, this paper presents a novel FHSB T-stub connection, which is simple in structure, definite in load condition, and easy to construct. Static load tests were carried out on 21 specimens under different shear-compression ratios, and the finite-element (FE) models were created for each specimen. The failure modes, initial friction loads and ultimate strengths of the specimens were compared in details. Then, 144 FE models were adopted to analyze the effects of the friction coefficient, shear-compression ratio, bolt diameter and clamping force on the initial friction load and ultimate strength. The results showed that the FHSB T-stub connection under shear and compression mainly suffers from bolt shearing failure. The load-displacement curve generally covers the elastic, yield, hardening and failure stage. If the shear-compression ratio is small and the friction coefficient is large, its curve only contains the elastic and failure stage. The friction coefficient and shear-compression ratio have great impacts on the initial friction load and ultimate strength. For every 1 mm increase in bolt diameter, the initial friction load increased by about 10%, while the ultimate strength increased by about 8.5%. For each 10% increase/decrease of the design clamping force, the initial friction load decreases/increases by 7.8%, while the ultimate load remains basically the same. The proposed formula of shear capacity and self-lock angles of FHSB T-stub connection can be applied to the design of CSS-enhanced prestressed concrete continuous box girder bridges (PSC-CBGBs) and diagonal bracing.  
T-stub connection; high-strength bolted (HSB) connection; shear and compression; initial friction load; ultimate strength; finite element method (FEM) +
Footnote †: journal: Applied  
Article
# 5G Cross-Border Operation for Connected and Automated Mobility: Challenges and Solutions
## 3 Selected Use Cases
### High-Definition Mapping
#### 3.2.3 What Are the Benefits of 5G Compared to 4G for High-Definition (HD) Mapping?  
Seamless availability of the autonomous and automated driving functionality is key for acceptance of such functionality. This is especially true in a fully autonomous car, where outages of the functionality would cause passengers incapable of driving the car themselves to be stuck. In order to get such seamless availability, it is important to have accurate maps--in particular the dynamic, fast changing parts like accidents, road closures, etc.--available anytime and everywhere. Such an order of magnitude of availability cannot be achieved with today's communication networks that are lacking full area coverage. Similarly, seamless connectivity across country or operator borders is far from available in today's networks.  
Smarter and optimized techniques are provided by 5G for managing its resources. For example, a reliable prediction of the availability of connectivity is another feature missing from today's networks. A function like Quality of Service Prediction that is currently discussed for 5G is essential to allow the aforementioned availability always and everywhere.  
Future traffic scenarios might involve a very high density of autonomous vehicles (e.g., in urban areas or on highways), and high definition map updates might have to be provided for many vehicles at once. This leads to new requirements for high-capacity or novel data distribution capabilities in downlink (e.g., efficient multicast) which are not available in 4G and below.  
Furthermore, the quality--in the sense of being both geographically accurate and up-to-date--of the HD map is highly correlated with the number of sensing vehicles that participate in the map generation. This means that, even though the amount of data for individual cars might be small enough to be covered by 4G networks, the number of contributing communication units likely causes data traffic that goes beyond the capacity of today's networks.
# Thermal and Mechanical Behavior of Elastomers Incorporated with Thermoregulating Microcapsules
###### Abstract  
Polyurethane (PU) is one of the principal polymers in the global plastic market thanks to its versatility and continuous improvement. In this work, PU elastomeric materials having thermoregulating properties through the incorporation of microcapsules (mSD-(LDPE: EVA-RT27)) from low-density polyethylene and vinyl acetate containing paraffin\({}^{\text{\textregistered}}\)RT27 as PCM were produced. Elastomers were synthesized while varying the molar ratio [NCO]/[OH] between 1.05 and 1.1 and the microcapsule (MC) content from 0.0 to 20.0 wt.%. The successful synthesis of the PUs was confirmed by IR analyses. All the synthesized elastomers presented a structure formed by a net of spherical microparticles and with a minimum particle size for those with 10 wt.% MC. The density and tensile strength decreased with the MC content, probably due to worse distribution into the matrix. Elastomer E-1.05 exhibited better structural and stability properties for MC contents up to 15 wt.%, whereas E-1.1, containing 20 wt.% MC, revealed mechanical and thermal synergy effects, demonstrating good structural stability and the largest latent heat. Hence, elastomers having a large latent heat (8.7 l/g) can be produced by using a molar ratio [NCO]/[OH] of 1.1 and containing 20 wt.% mSD-(LDPE: EVA-RT27).  
Keywords:polyurethane elastomers; microencapsulated PCMs; thermal properties; mechanical properties +
Footnote †: journal: Applied Sciences
## 2 Materials and Methods
### In Situ Measurements
#### 2.2.3 Leaf Chlorophyll Fluorescence and Photosynthesis Rates  
Leaf chlorophyll fluorescence and photosynthesis rates of two major species (i.e., _Pinus massonia_ and _Pinus elliotti_) were measured on a wooden platform of 14 m height next to the flux tower. An open gas exchange system (LI-6400 XT, LI-COR Inc., Lincoln, NE, USA) with an integrated leaf chamber fluorometer (LCF) (LI-6400-40, LI-COR Inc., Lincoln, NE, USA) was used to simultaneously measure the leaf chlorophyll fluorescence and photosynthesis rates. Meanwhile, some environmental variables at the leaf level were measured, including the PAR incident on the leaves (PAR\({}_{\text{leaf}}\)), leaf temperature and leaf humidity. We randomly selected 3 clusters of the upper canopy needles of each species for in situ measurement every month during the 2017 growing season, namely 21 April, 22 May, 1 July, 22 July, 31 August, 24 September, 23 October and 25 November. When we used LI-6400 XT to measure, the cluster of needles was flattened and they covered the entire leaf chamber to avoid measurement errors caused by overlapping leaves or gaps between leaves [33].  
The selected needles were wrapped in tin foil for at least 30 min [34] before the dark-adapted measurements at around 8:00. Then, they were measured once an hour for light-adapted measurements till 17:00. After being placed in the dark for at least 30 min,the leaves were shined on by a weak red light from the LCF and the initial minimum fluorescence (F\({}_{\rm o}\)) was detected. Net photosynthetic rate (P\({}_{\rm net}\), \(\mu\)mol m\({}^{-2}\) s\({}^{-1}\)) of the leaves was recorded together with the measurements of F\({}_{\rm o}\). The P\({}_{\rm net}\) under dark-adapted light ambient was regarded as dark respiration. Next, when the leaves were exposed to a saturating pulse, the fluorescence immediately rose to an initial maximal level (F\({}_{\rm m}\)) [26]. After the dark-adapted process, all leaves were exposed to ambient light to prepare for the light-adapted process. In this process, LCF provided an actinic light at an intensity equal to the ambient light. Then, the steady-state fluorescence (F\({}_{\rm s}\)) and P\({}_{\rm net}\) were recorded once they fluctuated in allowed ranges after the leaves were illuminated for 20-30 min. The P\({}_{\rm net}\) was quantified under an ambient-synchronized light intensity (i.e., PAR\({}_{\rm leaf}\)) and CO\({}_{2}\) level, except for the first measurement under a dark-adapted light ambient. Then, the leaf apparent photosynthesis (P\({}_{\rm apparent}\)) was calculated as the sum of dark respiration and P\({}_{\rm net}\) at a given ambient light intensity [35].
# Torque Characteristic Analysis of a Transverse Flux Motor Using a Combined-Type Stator Core
## 5 Influence of Structure Parameters on Torque Density  
As high torque density is the most attractive advantage of transverse flux motor, the torque density of CS-TFM should be calculated, and the influence of structure parameters on torque density should be analyzed in order to find a useful optimized method for future design process.  
Figure 10: The torque of CS-TFM: (**a**) single-phase torque; and (**b**) total torque.  
Figure 9: The cogging torque of CS-TFM: (**a**) waveform; and (**b**) harmonic components.  
The total volume of motor can be expressed as:  
\[V=S\cdot l_{a}=\frac{3\pi}{4}D_{\text{out}}^{2}l_{\text{a}}. \tag{22}\]  
Then, the torque density of CS-TFM can be deduced as:  
\[\rho=\frac{T}{V}=\frac{4\sqrt{2}\mu_{0}pkDa_{\text{a}}I_{\text{m}}N \textit{I}}{\pi D_{\text{out}}^{2}l_{\text{a}}\left(h_{\text{m}}+\delta\right)}. \tag{23}\]  
The relationship between pole-pitch and air-gap diameter can be written as:  
\[\tau_{\text{m}}=\frac{\pi D_{\text{a}}}{2p}. \tag{24}\]  
Then, the torque density of CS-TFM can be expressed as:  
\[\rho=\frac{2\sqrt{2}\mu_{0}kDa_{\text{a}}^{2}I_{\text{m}}N\textit{I}}{D_{\text {out}}^{2}l_{\text{a}}\tau_{\text{m}}\left(h_{\text{m}}+\delta\right)}. \tag{25}\]  
From Equation (25), the main influencing factors of torque density are the pole-pitch \(\tau_{\text{m}}\), the thickness of permanent magnet \(h_{\text{m}}\), the air-gap length \(\delta\) and the field modulated factor \(k\). When the out diameter \(D_{\text{out}}\), the air-gap diameter \(D_{\text{a}}\) and the axial length of motor \(l_{\text{a}}\) are kept as constant, the volume of motor \(V\) is a constant. Thus, the torque density corresponds with average torque, and the influence of structure parameters on average torque is analyzed by 3D FEM.
# Challenges and Solution Directions of Microservice Architectures: A Systematic Literature Review
## 5 Identified Challenges and Solution Directions
### RQ2. What Are the Identified Solution Directions?
#### 5.2.1 Service Discovery  
The authors [I] propose a new approach that uses information-centric networking (ICN) to find a solution to latency and overhead problems of the service discovery mechanism. They make the service discovery process in MSA easier by using information-centric network concepts. Since it is possible to offer a simple discovery process that decreases the number of service name records, name-based routing, and hierarchical naming are used. Study [J] presents multiple decision guidance models that can be used when deciding on an eligible microservice infrastructure. In this paper, there are multiple decision guidance models with their own design options addressing the fault tolerance and service discovery area. For each of the models, they provide specific infrastructure technologies to implement design options. Study [AF] provides a novel solution architecture to solve scalability and workload problems of service discovery in mega-scale systems. The authors focus on the idea that service description data can be broken into dynamic and static properties. They propose an architecture subdivided into two independent, interconnected processing levels for static and dynamic query parts. Both processing levels consist of interconnected peers which allow scaling of the registry dynamically. Study [M] proposes a mechanism to optimize service discovery operation in stateful microservices. Scalability and efficient usage of infrastructure resources are the main aspects of this study. The authors claim that an efficient and scalable routing mechanism is needed to figure these problems out. The proposed model has been validated with two experiments and it has been observed that there was an increase in scalability and a decrease in the usage of infrastructure resources.
# A Hybrid Intelligent Approach to Predict Discharge Diagnosis in Pediatric Surgical Patients
###### Abstract  
Computer-aided diagnosis is a research area of increasing interest in third-level pediatric hospital care. The effectiveness of surgical treatments improves with accurate and timely information, and machine learning techniques have been employed to assist practitioners in making decisions. In this context, the prediction of the discharge diagnosis of new incoming patients could make a difference for successful treatments and optimal resource use. In this paper, a computer-aided diagnosis system is proposed to provide statistical information on the discharge diagnosis of a new incoming patient, based on the historical records from previously treated patients. The proposed system was trained and tested using a dataset of 1196 records; the dataset was coded according to the International Classification of Diseases, version 10 (ICD10). Among the processing steps, relevant features for classification were selected using the sequential forward selection wrapper, and outliers were removed using the density-based spatial clustering of applications with noise. Ensembles of decision trees were trained with different strategies, and the highest classification accuracy was obtained with the extreme Gradient boosting algorithm. A 10-fold cross-validation strategy was employed for system evaluation, and performance comparison was performed in terms of accuracy and F-measure. Experimental results showed an average accuracy of 84.62%, and the resulting decision tree learned from the experience in samples allowed it to visualize suitable treatments related to the historical record of patients. According to computer simulations, the proposed classification approach using XGBoost provided higher classification performance than other ensemble approaches; the resulting decision tree can be employed to inform possible paths and risks according to previous experience learned by the system. Finally, the adaptive system may learn from new cases to increase decisions' accuracy through incremental learning.  
computer-aided diagnosis; pediatrics; support vector machines; decision trees; CART; DBSCAN; XGBoost; AdaBoost; gradient boosting; voting ensemble; random bagging +
Footnote †: journal: Applied Sci.
## 3 A Review of Evaluation Criteria
### Evaluation Measures Related to Lifetime of Network  
The evaluation metric \"lifetime of the network\" has a strong dependence on the nodes' battery capacity. As such, the network lifetime has been a critical concern in WSN research. While numerous energy-efficient protocols have been proposed to prolong the network lifetime, various definitions of network lifetime have also been used for the different scenarios and protocols. The lifetime of a sensor network is most commonly defined as the time to the first sensor node failure. However, this definition is seemingly over-pessimistic in many envisaged deployment scenarios, such as habitat monitoring, forest fire detection _etc._[16]. While other definitions exist, there has not been any consensus on which quantitative lifetime definition is most useful. The various \"network lifetime\" definitions proposed and used in the literature include:  
* Time till the first sensor node failure [17; 18; 19; 20].
* Time till certain percentage of sensor nodes failure, or surviving nodes in the network (falls below a given application-dependent threshold) [21; 22].
* Time till the network becomes disjoint; network partitions emerge [23].
* Time till size of the largest connected component drop below a threshold [24].
* Time till the packet delivery rate falls below a certain threshold [25].
* Time till all the sensor nodes dies [26].
* Time till number of errors exceeds a threshold [27].
* Time till the number of packets that can be (successfully/correctly) delivered by the network falls below a threshold [28].
## 4 Result and Discussion
### Packet Delivery Ratio  
The ratio of the total number of packages sent from the sender node to the total number of packages received at the destination is what is meant when someone uses the term \"package delivery ratio\". A comparison of the DEELB analysis with other approaches, including EEFO, DEERA, ELBS, and DESTS, is shown in Table 8 and Figure 9. The PDR for 10 nodes for the DEELB method was 89.97%, whereas the PDR for earlier processes such as the EEFO, DEERA, ELBS, and DEBTS processes was 78.34%, 88.32%, 72.32%, and 82.76%, respectively. The PDR of the suggested technique was 93.65% with 50 nodes, compared to the other current methods' range of 74.21% to 89.29%.
###### Abstract  
Astrophotonics is the application of photonic technologies to channel, manipulate, and disperse light from one or more telescopes to achieve scientific objectives in astronomy in an efficient and cost-effective way. Utilizing photonic advantage for astronomical spectroscopy is a promising approach to miniaturizing the next generation of spectrometers for large telescopes. It can be primarily attained by leveraging the two-dimensional nature of photonic structures on a chip or a set of fibers, thus reducing the size of spectroscopic instrumentation to a few centimeters and the weight to a few hundred grams. A wide variety of astrophotonic spectrometers is currently being developed, including arrayed waveguide gratings (AWGs), photonic echelle gratings (PEGs), and Fourier-transform spectrometer (FTS). These astrophotonic devices are flexible, cheaper to mass produce, easier to control, and much less susceptible to vibrations and flexure than conventional astronomical spectrographs. The applications of these spectrographs range from astronomy to biomedical analysis. This paper provides a brief review of this new class of astronomical spectrographs.  
astrophotonics; arrayed waveguide gratings; echelle gratings; single-mode; near-IR; photonic lanterns +
Footnote †: journal: Applied Physics Letters