esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### STL vs. MTL Performance Comparison  
We further examined the comparative performance of STL versus MTL, as well as the impact of the number and combination of tasks on predictive performance within the MTL framework. Specifically, Task 1 corresponds to Clinical Frailty Scale (CFS) prediction, Task 2 to hospital length of stay prediction, and Task 3 to mortality prediction. In this context, STLNFM refers to the Neural Factorization Machine (NFM) model trained independently on a single task, whereas MTLNFM refers to models jointly trained on multiple tasks. The experimental results are illustrated in Figure 3. Overall, MTLNFM consistently outperformed STLNFM across all prediction tasks. Notably, in hospital length of stay prediction, the 2-task MTLNFM model (involving two related tasks) achieved an average performance improvement of 2.5% over the single-task counterpart, while the 3-task MTLNFM model yielded a further improvement of 4.4%. These findings reinforce our hypothesis that MTL facilitates knowledge sharing across related tasks, leading to more robust and generalizable representations. Moreover, we observed that the joint modeling of CFS and mortality resulted in higher predictive accuracy compared to the combination of hospital length of stay and mortality, suggesting a stronger correlation between frailty and mortality outcomes. This highlights the importance of task selection and correlation in the design of effective MTL models. Additionally, the superior performance of the 3-task MTLNFM model over its 2-task variants shows that incorporating multiple, well-aligned tasks can further enhance model learning and prediction quality. Additional results and analysis related to Figure 3 are provided in Supplementary Materials S2.
## 4 Conclusions  
This study analyzed the performance of bolt connectors for honeycomb sandwich plates. Different connector designs were compared by carrying out experimental tests and finite element simulation. The main findings of the study can be summarized as follows:  
1. The failure of a high strength bolt connector is driven by severe stress concentration and minor bending deformation of the bolt. Connection plate and pad openings are oxidized and the excessive total displacement causes the failure of the joint. The ordinary bolt connector fails because stress concentration on bolt shear surface causes excessive deformation. Self-tapping bolt connector failure mechanisms are intermediate between those observed for high-strength and self-tapping bolt connectors. The high-strength bolt connector has the highest shear capacity followed by ordinary bolt and self-tapping bolt connectors. Hence, high strength connectors are preferred although ordinary bolts also may be utilized.
2. Finite element simulations are in agreement with experimental data of load-displacement curves that were reproduced with less than 3.6% difference in terms of load-displacement curves. The present model can hence turn useful in designing new connection systems for aluminum sandwich structures. The geometry of the connector was optimized by setting the bolt hole-edge distance equal to 1.5 times the bolt diameter.
3. Numerical results validated by experimental data were fitted to obtain a very simple formula that predicts the connector's ultimate shear load bearing capacity. The new approach is less conservative than Chinese standards as it accounts for the contribution of the sandwich wall thickness to shear load capacity. This may be the starting point for future revisions of design specifications that should be used for a new honeycomb sandwich structural system.  
This study was supported by the Natural Science Foundation of China under Grant No. 51578136.  
[PERSON] and [PERSON] conceived and designed the experiments; [PERSON] performed the experiments; [PERSON] and [PERSON] analyzed the data; [PERSON] and [PERSON] contributed reagents/materials/analysis tools; [PERSON] wrote the paper.  
The authors declare no conflict of interest.
# Wildfire Monitoring Based on Energy Efficient Clustering Approach for FANETS
## 3 Proposed Methodology
### Metrics Used by Our Proposed Algorithm
#### 3.1.3 Degree Difference  
The node's stability as a cluster head increases with its node degree. The degree of a node is the number of connections that it has to other nodes in the network. Where Di is node i's practical degree and Max\({}_{D}\) is its maximum degree, we define degree difference D\({}_{D}\) as \(\mid\) Di-Max\({}_{D}\)\(\mid\). Node I will performs better as a cluster head if the value of D\({}_{D}\) is smaller.
# Application of a DC Distribution System in Korea: A Case Study of the LVDC Project
## 1 Introduction  
The share of DC power consumption in PCs, TVs, DC buildings, Internet Data Centers (IDCs), and DC homes is expected to increase. In particular, EPRI in the United States estimates that digital devices will account for 50% of the world's total DC load in 2020. In addition, due to the expansion of renewable energy, such as photovoltaics (PV) generation and fuel cells, there is a need for a new high-quality electricity service, such as DC distribution service technology. In existing AC distribution systems, the power conversion to DC was required to take advantage of the distributed resources or the DC consumers, which resulted in additional cost and power losses. However, in the case of DC distribution systems, the power conversion step can be omitted to enable a more efficient and economical operation, compared to the existing AC distribution system, when the DC distributed resources and DC consumers are connected [1]. Previous studies have confirmed the economics of the Direct Current (DC) distribution system [2]. In addition, the DC distribution system can effectively control voltage using the power conversion device instead of the transformer, and it can limit the fault current in case of an accident at the load side and prevent accidents from spreading to the main grid. However, there are still difficulties for DC distribution system operation and there is insufficient research on connecting with the actual grid system. The accurate detection and location of fault resultsin fast restoration of the system are needed [3]. In previous studies, the lab test was performed prior to applying the DC distribution to the actual grid system, confirming the tremendous potential of the DC distribution system [4]. In this paper, the DC distribution was applied to the actual grid system and confirmed the possibility of its commercialization. The construction of a demonstration area has been verified by simulations and field tests. Also IMD, the DC distribution fault detecting system, has been installed and its operating algorithms are proposed.
## 2 Principle of the Measurement Mechanism
### Measuring Mechanism for Measuring Two Vertical Parallel Surfaces  
Figure 5 shows the measuring mechanism for measuring the positional relation of two vertical parallel surfaces. Contact lines \(A\) and \(B\) are fixed, and the detection line \(C\) is movable. The length of contact lines \(A\) and \(B\) are 70 mm, and detection line \(C\) is 50 mm. The contact line \(A\), \(B\), and detection line \(C\) are ground after processing, and the processing accuracy grade is IT3.  
During the detection process, the fixed contact lines \(A\) and \(B\) move in one surface, the variable contact line \(C\) moves in another detection surface, and the contact lines \(A\), \(B\) and the detection line \(C\) form a caliper. Under the clamping action of the caliper, the spring generates tension and compression with the shape contour of the measured surface. At the same time, the fluctu  
Figure 4: The positional relation between contact line \(A\) and detection line \(C\): (**a**). Contact line \(A\) and detection line \(C\) are collinear; (**b**). Contact line \(A\) and detection line \(C\) are not collinear.  
Figure 5: Measuring mechanism for measuring two vertical parallel surfaces.  
laser receiving plate along the guide rail, and the laser displacement sensor detects the weak change of the laser receiving plate and records the change through the computer.  
As shown in Figure 5(a), according to Table 1, start measuring range is 50 mm. When the surface where the contact line \(A\) and the detection line \(C\) are located are absolutely parallel and the surfaces are absolutely smooth, the detection data is a fixed value and is defined as the initial value \(X_{1}\). When the shape contours of the two surfaces are considered, the position of the detection line \(C\) may change, as shown in Figure 5(b). At this time, fluctuating measurements will be generated, and the difference between the measurements and the initial value is the displacement of the detection line \(C\) relative to the contact line \(A\).
# Dual-Band MIMO Antenna for 5G/WLAN Mobile Terminals
## 3 Antenna Analysis  
In order to investigate the dual band operating mechanism, a parametric study of single antenna element has been carried out by the electromagnetic simulator HFSS. Since the geometry of the four antenna elements are identical, the parameters of Ant. 1 are used for analysis.  
Figure 2 exhibits the surface current and electric field distributions of the proposed Ant. 1. The 3.5 GHz surface current is concentrated on the right side of the individual antenna element toward the center of the substrate, while the electric field is reversed toward the outside of the substrate. However, the surface current at 5.5 GHz is concentrated to the left side of the individual antenna element, while the electric field is directed toward the interior of the substrate. These two resonant positions result in dual-band and wideband characteristics.  
Figure 3 shows the simulated S\({}_{11}\) of Ant. 1 as functions of L\({}_{1}\) and H\({}_{3}\), respectively. The value of L\({}_{1}\) can be effectively employed to shift the resonance frequencies of both the lower and higher frequency bands. Eventually, both the N78 (3.3-3.8 GHz) band and IEEE 802.11 ac (5.15-5.875 GHz) band can be covered. As shown in Figure 4, the higher resonance of Ant. 1 can also be optimized by the value of H\({}_{3}\), which is the length of the open-loop ring.  
Figure 1: Geometry of the proposed MIMO antenna system in millimeters. (**a**) Prospective view; (**b**) single antenna element.  
Figure 2: The surface current and electric field distributions of the proposed antenna at (**a**) 3.5 GHz; (**b**) 5.5 GHz.  
Figure 5 shows the simulated application scenario when Ant. 3 is excited. Due to the high permittivity and high loss characteristic of the hand, it is necessary to investigate the effect of the hand on the antenna performance.  
Figure 6 shows simulated coefficients when the device is held in single hand. To cover both the N78 (3.3-3.8 GHz) band and IEEE 802.11 ac (5.15-5.875 GHz) bands, the reflection coefficients are lower than \(-8.5\) dB. The transmission coefficients are lower than 14 dB.  
Figures 7 and 8 show simulated electric field distributions and 3D radiation patterns when the device is held in a single hand, respectively.  
Figure 4: Simulated S\({}_{11}\) of Ant. 1 with different values of H\({}_{3}\).  
Figure 3: Simulated S\({}_{11}\) of Ant. 1 with different values of L\({}_{1}\).  
Figure 5: Simulated application scenario when the device is held in a single hand.  
Figure 6: Simulated coefficients when the device is held in single hand: (**a**) reflection coefficient; (**b**) transmission coefficient; (**c**) realized peak gains; (**d**) total efficiency.
# Robust Quadratic Optimal Control for Discrete-Time Linear Systems with Non-Stochastic Noises
## 3 Robust Optimal Control Strategy
### Estimation of True State Feasible Set  
For the unknown-but-bounded noises, set-membership filtering can provide a true state feasible set which contains the true states all the time. In addition, the filtering gain can be obtained off-line with small computation burden.  
According to set-membership filtering theory, assuming that at instant \(k-1\) the true state feasible set is \(\Omega(\hat{x}(k-1),P(k-1))\), where \(\hat{x}(k-1)\) is the center of state feasible set, \(P(k-1)\) is used to define its shape.  
At instant \(k\), the true states \(x(k)\) belong to the optimal ellipsoidal feasible set \(\Omega(\hat{x}(k),P(k))\), the center \(\hat{x}(k)\) and the matrix \(P(k)\) can be updated as follows,  
\[\hat{x}(k) = \hat{x}(k|k-1)+K(k)\delta(k), \tag{7}\] \[\hat{x}(k|k-1) = A(k-1)\hat{x}(k-1)+B(k-1)u(k-1),\] (8) \[K(k) = P(k|k-1)C^{T}(k)[C(k)P(k|k-1)C^{T}(k)+q_{k}^{-1}V(k)]^{-1},\] (9) \[P(k|k-1) = (p_{k}^{-1}+1)A(k-1)P(k-1)A^{T}(k-1)+(p_{k}+1)W(k-1),\] (10) \[P(k) = \hat{p}_{k}\{[I-K(k)C(k)]P(k|k-1)[I-K(k)C(k)]^{T}+q_{k}^{-1}K(k)V( k)K^{T}(k)\},\] (11) \[\beta_{k} = 1+q_{k}-\delta^{T}(k)[q_{k}^{-1}V(k)+C(k)P(k|k-1)C^{T}(k)]^{-1} \delta(k),\] (12) \[\delta(k) = y(k)-C(k)\hat{x}(k|k-1). \tag{13}\]  
The scalar parameters \(p_{k}>0\) and \(q_{k}>0\) are selected to make the sizes of ellipsoidal sets \(\Omega(\hat{x}(k|k-1),P(k|k-1))\) and \(\Omega(\hat{x}(k),P(k))\) to be minimized respectively. There are two common criteria to optimize size of the ellipsoid. One is Minimum-trace criterion, and the other is Minimum-volume criterion [13]. In this paper, we adopt the latter one and \(p_{k}\) satisfies  
\[\sum_{i=1}^{n}\frac{1}{\gamma_{i}^{(p)}+p_{k}}=\frac{n}{p_{k}(p_{k}+1)},\]where \(\gamma_{i}^{(p)}\) denote the eigenvalues of matrix \(A(k-1)P(k-1)A^{T}(k-1)W^{-1}(k)\) and \(n\) is the dimension of the state. \(q_{k}\) satisfies  
\[\sum_{i=1}^{n}\frac{\gamma_{i}^{(q)}}{1+q_{k}\gamma_{i}^{(q)}}=n\frac{\beta_{k} ^{{}^{\prime}}(q_{k})}{\beta_{k}(q(k))},\]  
where \(\gamma_{i}^{(q)}\) denote the eigenvalues of matrix \(P(k|k-1)C^{T}(k)V^{-1}(k)C(k)\), \(\beta_{k}(q_{k})\) is given by (12) and \(\beta_{k}^{{}^{\prime}}(q_{k})\) is the derivative of \(\beta_{k}(q_{k})\) with respect to \(q_{k}\).
## 3 Method
### Evaluation of 15-min Walkability to Elderly Care Facilities
#### 3.3.1 Machine Learning-Based Analysis of Facility Importance Weights
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**First Level Indicators** & **Second Level Indicators** & **First-Level Weight** & **Local Weight** & **Global Weight** \\ \hline \multirow{4}{*}{Catering} & Chinese Restaurant & & 0.58565 & 0.17109 \\  & Dessert and beverage & & 0.33632 & 0.09825 \\  & Fast restaurant & & 0.06644 & 0.01941 \\  & Bakery & & 0.01159 & 0.00339 \\ \hline \multirow{4}{*}{Shopping} & Supermarket & & 0.12869 & 0.02416 \\  & Shopping mall & & 0.00025 & 0.00005 \\  & Convenience store & & 0.68406 & 0.12842 \\  & Integrated market & & 0.17449 & 0.03276 \\  & Bird and flower market & & 0.01251 & 0.00235 \\ \hline \multirow{4}{*}{Transportation} & Resident & 0.01332 & & 0.01332 \\  & Bus station & & 0.96038 & 0.04183 \\  & Subway station & & 0.03962 & 0.00173 \\ \hline \multirow{4}{*}{Medical care} & General hospital & & 0.16530 & 0.02604 \\  & Specialized hospital & & 0.02918 & 0.00460 \\  & Clinic & & 0.36262 & 0.05713 \\  & Pharmacy & & 0.44290 & 0.06978 \\ \hline \multirow{2}{*}{Leisure} & Park and square & & 0.23619 & 0.00187 \\  & Landscape & & 0.76381 & 0.00095 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The weight of amenities is calculated by random forest in rural areas. Notably, medical service facilities maintain prominent weighting across both urban and rural contexts, highlighting the urgent demand for healthcare management and medical support among elderly populations. This phenomenon primarily stems from two interrelated factors: 1. The elderly population generally experiences compromised health status with elevated prevalence of chronic diseases and underlying health conditions; 2. Functionally impaired seniors constitute a substantial proportion of institutional care residents, demonstrating heightened dependency on medical services. Consequently, urban planners and policymakers should prioritize spatial configurations that ensure either immediate proximity to medical facilities or integrated co-location strategies when determining elderly care facility locations. Such deliberate spatial planning would effectively safeguard seniors' access to essential medical care and nursing support services. Figure 3 shows the service function of different facilities in urban and township areas.
## 2 Modeling and Optimization Method
### BSCN Model and Optimization  
#### 2.2.1 Conceptual Model of the BSCN  
In Figure 5, in the conventional straight cone nozzle inlet section L1 and outlet section L3 of the internal flow channel surface, according to a specific uniform rule, a circular groove was added as a bionic unit. The inner pipe of the conventional straight cone nozzle changed from the original smooth flow channel to the bionic non-smooth surface structure, thus forming the BSCN.  
As shown in Figure 5, the inlet section L1 and outlet section L3 of the conventional straight cone nozzle were circular tubes. The BSCN model was proposed based on the bionic non-smooth surface drag reduction theory, which can effectively improve the kinematic and dynamic characteristics of fluid flow along the pipe wall to a certain extent.  
Figure 5: Concept diagram of BSCN.
## 3 Results  
### Mineralogy, Microtextures  
Bulk XRD analysis suggests that the main mineral phases are identical in all 70 samples (a representative diffractogram is shown as a Supplementary Figure S1). Cancrinite (20-50 m/m\(\%\)), goethite (10-30 m/m\(\%\)), and hematite (20-30 m/m\(\%\)) are the predominant phases. Various amounts of calcite (5-20\(\%\) m/m\(\%\)) with minor (>5 m/m\(\%\)) boehmite, gibbsite, anatase, dolomite, and illite are present in all samples. Based on the low baseline, the proportion of the amorphous material can be estimated as low as <5\(\%\). Raman spectroscopy revealed the majority of hematite, goethite, and gibbsite in each sample while rutile, anatase, ilmenite, titanomagnetic, magnetite, zircon and monazite were identified in several samples, basically in the coarse (>20 microns) fraction (Figure 2).  
Figure 2: Typical mineral grains of the studied red mud. (**a**) ilmenite (coarse grain fraction) (**b**) hematite (coarse grain fraction), (**c**) goethite (coarse grain fraction), (**d**) gibbsite (coarse grain fraction), (**e**) anatase in the matrix, (**f**) zircon in the matrix.  
A combined evaluation of SEM-BSE images and EDS data shows that the coarsest grains in all studied red mud samples are not individual mineral grains of the above list, but spherical aggregates of them. As they are enriched in both Fe and Al, these spherical grains are thought to be aggregates of fine-crystalline goethite, hematite, and carcinrite (Figure 3).
# A Noncontact Method for Calibrating the Angle and Position of the Composite Module Array
###### Abstract  
Freeform surface is one of the research focuses in the measurement field. A composite module is composed of a plane and rotating paraboloid. The composite module array can identify 21 geometric errors of the machine tool in a wide range, which is composed of several composite modules. Eliminating the error of the array itself is of great significance for improving measurement accuracy. For this reason, this paper proposed a noncontact method for calibrating the angle and position of the composite module array. This paper used a self-developed angle sensor to access corresponding information and established the mathematical model according to the freeform surface's geometric characteristics to achieve calibration. In addition, the influence of array placement error on calibration was analyzed. The experimental results showed that the angle repeatability was within 0.4\({}^{\prime\prime}\) around the X-axis and within 0.3\({}^{\prime\prime}\) around the Y-axis, and the position repeatability was within 0.4\(\upmu\)m in the X direction and within 0.7\(\upmu\)m in the Y direction. The measurement comparison experiments with high-precision laser interferometer and uncalibrated array verified the correctness of the experimental results. This method provides an important reference for practical application and freeform surface array calibration, and creates conditions for the implementation of machine tool error detection.  
Keywords:freeform surface; composite module array; angle sensor; calibration method; 2-D angle; 2-D position; array placement error +
Footnote †: journal: Applied sciences
# Effect of Leaf Grade on Taste and Aroma of Shaken Hunan Black Tea
## 3 Results
### Analysis of Aroma Compounds
#### 3.3.3 OAV Analysis of Volatile Compounds  
The contribution of volatile components to the aroma is influenced by both their quantity in the sample and their odor activity value (OAV). Generally, volatile components with an OAV \(\geq 1\) are deemed to have a significant impact on the overall aroma [28]. To investigate the variations in the aroma of Hunan black tea at different grades, a total of 63 differential volatile components were analyzed using OAV. Among these, 16 important aroma components were identified, with geraniol having the highest OAV, ranging from 69.68 to 203.29. According to odor orientation, the 16 significant aroma components were categorized into 10 floral, fruity, and sweet volatile components, as well as 6 volatile components of other aroma types (Table 5).  
Geraniol, jasmone, \(\beta\)-myrcrene, citral, and trans-\(\beta\)-ocimene possess sweet and fruity odor characteristics, and their concentrations in Hunan black tea decreased with decreasing grades when subjected to shaking, aligning with the findings of the sensory evaluation of the aroma (Grade 1 to Grade 4: tender-sweet aroma to sweet aroma and pure aroma) [29]. Hence, the presence of geraniol, jasmonone, \(\beta\)-myrcrene, citral, and trans-\(\beta\)-ocimene significantly contributes to the variations in the sweet aroma of different grades of Hunan black tea when subjected to shaking. Furthermore, the floral odor attributes of methyl jasmonate, indole, and nerolidol are noteworthy, as their concentrations in Hunan black tea exhibit a pattern of initially increasing and subsequently decreasing with decreasing grades, aligning with the outcomes of the sensory evaluation of aroma. Consequently, methyl jasmonate, indole, and nerolidol emerge as pivotal aroma active components that account for the distinctions observed among the various grades of shaken Hunan black tea [30; 31].  
The fragrance of geraniol exhibited a refined and pleasant rosy and sweet scent, and it demonstrated the highest OAV in first-grade black tea with agitation, suggesting its significance as a crucial aroma-active compound. Furthermore, geraniol also serves as a significant aroma component in various other tea varieties, including green tea, white tea, and oolong tea [32; 33; 34]. Methyl jasmonate, primarily derived from the metabolic pathway of linelenic acid, plays a pivotal role as a floral component in shaken Hunan black tea with agitation and serves as an endogenous signaling molecule in the plant's defense response [35]. Indole, a compound formed by the fusion of pyrrole and benzene, emits a potent fecal scent at elevated concentrations; however, when significantly diluted, it emanates a floral fragrance. Moreover, indole serves as a significant floral constituent in black and oolong tea [27; 36; 37].