esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Status and Application
### Repeat-Pass Interference
#### 3.1.3 Sbas-InSAR  
In 2002, [PERSON] et al. [51] proposed the Small Baseline Subset (SBAS) method. By selecting short time-space baseline interferograms, the SBAS method limited the decoherence problem caused by long time-space baselines [52]. Compared with PS-InSAR technology, the SBAS method selects more interferograms for calculation. Based on the interferogram phase of the high coherence points in the time series, a deformation model is established. As shown in Figure 8[53], the overall average deformation velocity map during the study period was obtained through SBAS-InSAR analysis. This map reveals that the D-InSAR technology can only present the local information of the deformation condition of the Sierra Negra crater. In fact, from Figure 8c, the terrain change situation on the north side of the volcano can be clearly observed, and the displacement is approximately a few centimeters. Due to the existence of correlated observations in the interferogram phase, the Singular Value Decomposition (SVD) method is adopted to solve the deformation information and elevation correction amount. This method requires multi-view processing of SAR data, so it is mostly used in large-scale surface subsidence surveys [54; 55; 56; 57; 58; 59; 60].  
In conclusion, D-InSAR, SBAS-InSAR, and PS-InSAR are all used to obtain surface deformation information, but there are differences in application range, accuracy, and data processing. Table 3 shows the details.
## 1 Introduction
Additionally, the grain industry is reluctant to use inert dusts as grain protectants over the fact that the recommended dosages of DEs and zeolites can sufficiently reduce the grain bulk density, an extensively used grading factor that affects the grain prices [15]. In contrast, there are limited published data for the use of inert materials as surface treatments, i.e., in walls, floor etc., despite the fact that most of the insecticidal formulations that are now registered in stored product protection are for this use and not as admixture with grains. More than two decades ago, [PERSON] and [PERSON] [22] combined DEs with heat treatment in a flour mill and found that the occurrence of DEs could drastically accelerate insect mortality of the confused flour beetle, _Tribolium confusum_ [PERSON] (Coleoptera: Tenebrionidae) that is caused by elevated temperatures. Similar results have been reported by [PERSON] [23] in the case of this combination for the red flour beetle, _Tribolium castaneum_ ([PERSON]) (Coleoptera: Tenebrionidae). [PERSON] et al. [24] found that zeolites can be effective as a surface treatment against the maize weevil, _Stiophilus zeamais_ [PERSON] (Coleoptera: Curculinotidae). As the cases of resistance to conventional insecticides not only by the aforementioned species but also by other major stored product pests such as the lesser grain borer, _Rhyzopertha domitica_ ([PERSON]) (Coleoptera: Bostrychidae), are constantly increasing [25; 26; 27], the utilization of inert dust applications on stored product protection has gained distinct attention for their vital importance in resistant pest management strategies. Thus, the evaluation of these materials as surface or crack and crevice treatments in storage and processing facilities becomes even more important, in order to illustrate if eventually DEs and zeolites can play a viable role as insecticides that can be used for this purpose. Recently, [PERSON] and [PERSON] [28] found that certain DE deposits from Greece were very effective as grain protectants against several beetle pests at concentrations that were comparable with those of commercial DE formulations. In addition to these DEs, the same surveillance indicated that there is a zeolite formulation that could be effective for this purpose. Based on the above, and taking into account the scarcity of data for the application of DEs and zeolites in surfaces, the aim of the present study was to evaluate these specific Greek deposits for this purpose under a range of factors, such as the target species, the concentration, the exposure interval and the type of surface.
# Overview of an Experimental Program for Development of Yield Surfaces Tracing Method
## 2 Materials and Methods
### Test Specimens and Materials  
The presented experimental method employs thin-walled tubular test specimens (TS) for the testing under combined axial and torsional loading. Figure 1 shows a technical drawing of a TS used for the current YS tracing experiment. TSs were manufactured using conventional machining technologies. The central bore hole was manufactured within a three-stage process starting with rough drilling, followed by precise lathe knife machining, and careful surface finishing using a special reamer.  
The relatively high length at both end sections prevents sliding of the TS when subjected to intensive loadings. The TS is clamped in hydraulically actuated grips with V-serrated jaw faces. The end sections are filled/reinforced with steel pin inserts. The design of the TS's central section provides the cross-section with sufficient stiffness preventing buckling and the occurrence of other instabilities possibly associated with the complex loading modes and intensities.  
Two conventional non-alloyed ferritic steel grades were investigated in this work. The first grade, P250 GH (W. Nr. 1.0460, or C22G2) is designated for applications on weldable parts of pressure vessels and piping exposed to elevated temperatures. The second grade, S235 JR (W. Nr. 1.0122), belongs to a group of ordinary weldable steels commonly used for less demanding parts of structures as halls, bridges, cranes, etc. The composition of these alloys is shown in Tables 1 and 2, respectively. Some preliminary results on the initial YSs tracing of alternative ferritic steels can be found in previously reported work [1]. Current results are particularly enriched by the measurement of subsequent yield surfaces.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline
**C** & **Mn** & **Si** & **P** & **S** & **Cr** & **Ni** & **Mo** & **Al** & **Ti** \\ \hline
0.19 & 0.82 & 0.18 & 0.011 & 0.006 & 0.17 & 0.090 & 0.020 & 0.023 & 0.0017 \\ \end{tabular}
\end{table}
Table 1: Contents of alloying elements (wt%) in P250 GH steel investigated in the present work, as-stated by inspection certificate.  
Figure 1: Technical drawing of thin-walled tubular TS.
## 5 Quality Attribute Outcomes
### Privacy and Security
#### 5.1.4 Encryption and Anonymity  
Blockchains can utilize encryption to protect sensitive data, making it accessible only to authorized parties. In [PERSON] et al. [24], a mobile health app for behavioral tracking employs encryption to secure users' geolocation and activity data, ensuring that only authorized entities can view or use the data.
## 4 APSP and Routing Tables  
We first describe an algorithm for the APSP problem with routing tables in the qCCM, for which we combine an algorithm of [7] with a routing table computation from [17]. For this, we reduce APSP with routing tables to triangle finding by utilizing _distance products_, as demonstrated in [12].
# A Ku-Band Bi-Directional Transmit and Receive IC in 0.13 \(\upmu\)m CMOS Technology
## 2 Design of Ku-Band Bi-Directional Transmit and Receive IC
### Ku-Band 6-Bit Digital Step Attenuator  
The block diagram of the Ku-band 6-bit digital step attenuator is shown in Figure 6. The attenuator is designed with T-type resistive networks. The attenuation steps of 2, 4, 8, and 16 dB are controlled by steering the signal paths between the reference paths and the T-shape resistive network path using the DPDT switches. The 0.5 and 1 dB attenuation  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multicolumn{2}{c}{**Parameter**} & **11.25\({}^{\circ}\)** & **22.5\({}^{\circ}\)** & **45\({}^{\circ}\)** & **90\({}^{\circ}\)** & **180\({}^{\circ}\)** \\ \hline \multirow{2}{*}{HPF (BPF)} & L\({}_{1}\) (pH) & 177 & 221 & 1420 & 898 & 915 \\ \cline{2-6}  & C\({}_{2}\) (pF) & 1.2 & 0.57 & 2.1 & 0.62 & 0.62 \\ \hline \multirow{2}{*}{LPF} & L\({}_{2}\) (pH) & 156 & 229 & 176 & 287 & 287 \\ \cline{2-6}  & C\({}_{2}\) (fF) & 74 & 118 & 102 & 146 & 146 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Design parameters of the phase shifting filter networks.  
Figure 4: Schematics of the phase shifting elements of (**a**) \(11.25^{\circ}\) and \(22.5^{\circ}\), (**b**) \(45^{\circ}\) and \(90^{\circ}\), (**c**) \(180^{\circ}\).  
Figure 5: Schematic of the phase shifting elements of \(5.6^{\circ}\) and \(2.8^{\circ}\).  
Figure 3: Schematics of (**a**) the SPDT switch, and (**b**) the DPDT switch.  
states are designed with a switched shunt resistor to reduce the insertion loss and chip size. Additionally, the 0.5 and 1 dB attenuation states are designed as tuning bits to compensate for the amplitude error. The attenuation variation range is 31.5 dB with an attenuation resolution of 0.5 dB.
## 3 Related Work
Hence, the self-coexistence mechanism needs to be enforced to mitigate the effects of interference in the network performance. More recently, in [13] and [14], the authors evaluate the suitability of the IEEE 802.15.4 g-2012 physical layers for environmental and smart building applications, respectively, showing that SUN-OFDM is affected by multi-path fading and external interference in a similar way as OQPSK-DSSS. Based on these results, in [15], the authors conclude that the SUN-OFDM physical layer alone does not yield the robustness required for industrial applications and, thus, they recommend to add channel hopping techniques to combat its effects.
# Establishment and Numerical Analysis of Rolling Force Model Based on Dynamic Roll Gap
###### Abstract  
Applying mathematical models and numerical methods is crucial for describing and simulating the metal cold-rolling process, wherein the accurate prediction of rolling force is an effective way to improve the quality of rolled sheets. This paper considers key influencing parameters such as friction lubrication, stress, tension, and roll-flattening radius during the rolling process and establishes a calculation model for the friction coefficient and roll-flattening radius. By considering the coupling effect of the dynamic roll gap on rolling force, a rolling force model for non-steady-state friction lubrication during the rolling process is obtained. The correctness of the proposed model is verified by comparing it with industrial measurement results. The influences of the friction coefficient, stress, tension before and after rolling, and roll-flattening radius on rolling force are quantitatively studied. The results show that the rolling force increases with an increase in the friction coefficient. When the friction coefficient exceeds 0.2, the rate of increase slows down, approaching dry friction conditions. The rolling force increases linearly with stress but decreases with increasing tension before and after rolling. The rolling force model, considering the roll-flattening radius, provides numerical calculation results that are closer to an industrial measured rolling force. This work contributes to a better understanding of the mechanism behind the improvement of the cold rolling process.  
cold rolling process; rolling force model; dynamic roll gap; numerical analysis +
Footnote †: journal: Applied sciences
## 4 Conclusions  
In summary, a new spectroscopy method for detecting AFB1 concentration based FRET with CdSe/ZnS QDs has been developed. The FRET between AFB1 and CdSe/ZnS QDs causes a change in the fluorescence intensity and fluorescence lifetime. However, fluorescence intensity was weak and has large fluctuations, so the fluorescence lifetimes were used to estimate AFB1 concentration. The results of AFB1 detection in maize showed that the AFB1 concentration detection by FRET was consistent with the results detected by the HPLC method. The application in real sample suggests that this approach shows the promising prospect for the rapid screening of AFB1 in food.  
Conceptualization, T.B.N., T.B.V., C.S.T., and H.H.L.T.; data curation, T.B.N., C.S.T., H.H.L.T., and N.T.V.T.; formal analysis, T.B.N., H.M.P., and C.S.T.; investigation, T.B.N., T.B.V., H.M.P., C.S.T., H.H.L.T., and N.T.V.T.; methodology, T.B.N. and T.B.V.; project administration, T.B.V.; resources, T.B.N., C.S.T., H.H.L.T., and N.T.V.T.; validation, C.S.T., H.H.L.T., and N.T.V.T.; writing--original draft, T.B.N. and T.B.V. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Vietnam Academy of Science and Technology under the Program of development in Physics 2020: \"Application of time-resolved fluorescence spectroscopy and fluorescence resonance energy transfer (FRET) for assays detection toxin/antibiotics in food\" and by the International Center of Physics under the auspices of UNESCO through project number ICP.2019.07.  
The authors declare no conflict of interest.
## 2 Study Area and Data
### Data
#### 2.2.1 Weather Data  
The Digital Forecast is the weather forecast information provided by the Korea Meteorological Administration at 5 km resolution every 3 h based on the Unified Model Regional Data Assimilation and Prediction System numerical forecast model. It forecasts weather conditions hourly for the first two hours and with the three-hour interval after that up to two days (48 h). Digital Forecast provides basic meteorological products including temperature, precipitation, relative humidity, wind direction, and wind speed. The real-time Digital Forecast data are post-processed by Observation Data Analysis Module (ODAM) utilizing the in-situ observations [33]. In this study, the ODAM data were used for forest fire risk modeling. Among the products from Digital Forecast, relative humidity, temperature, and wind speed that affect forest fire occurrences were used in this study [1; 34].
###### Abstract  
Global navigation satellite system (GNSS) has been widely used in many fields due to their low cost and high positioning accuracy. Because of the open frequency of navigation signals, the low power of navigation signals, and the growing reliance of many modern wireless systems on satellite-based navigation, GNSS performance may be easily affected by interference signals. Monitoring and troubleshooting of interference sources are important means to guarantee the normal use of satellite navigation applications and are an important part of GNSS operation in complex electromagnetic environments; however, traditional angle of arrival (AOA) algorithms cannot efficiently operate with coherent signals, so a decoherence-based orientation scheme is proposed to optimize the AOA algorithm. Furthermore, a joint AOA and time difference of arrival (TDOA) interference localization algorithm is proposed for problems such as the lack of accuracy in a single interference source localization algorithm. Numerical simulation results show that decoherence-based AOA localization can be well applied to various interference signals, and the accuracy of the joint AOA and TDOA interference localization algorithm is higher than that of single-method interference localization. In addition, the physical verification further verifies the usability and reliability of the GNSS interference source positioning algorithm proposed in this paper.  
decoherence direction finding; joint interference locating; AOA; TDOA; least squares 2025  
19 June 2025  
20 June 2025
# New Orthogonal Transforms for Signal and Image Processing
## 5 Proposed Orthogonal Transform and Its Modifications  
### One-Dimensional (1D) Transform  
Let us consider a discrete one-dimensional signal represented by an \(N\)-element vector \(X(n)=[x_{1}\ x_{2}\ \ldots\ x_{N}]\), \(N=2^{n}\).  
A 1D orthogonal Transform based on the matrix \(A(n)\) defined earlier has the form:  
\[\begin{split}\text{Forward Transform:}&\quad S(n)=A(n) \cdot X(n)\\ \text{Inverse Transform:}&\quad X(n)=\frac{1}{C} \cdot A(n)\cdot S(n)\end{split} \tag{23}\]  
where  
\(S(n)\)--vector of spectral components.  
\(X(n)\)--vector of 1D signal.  
\(A(n)\)--transform matrix defined by Equation (15).  
\(C\)--constant defined by Equation (16).  
As was shown, the transform matrix \(A(n)\) is symmetric and orthogonal and \(A^{T}=A^{-1}\). Therefore, the forward transform (FT) differs from the inverse transform (IT) only by the constant \(C\). Another more detailed form of the FT can be written as follows:  
Figure 2: Approximated signal for different \(N\) and \(a=\frac{1}{2}\).  
\[\text{FT:}\begin{bmatrix}S_{1}\\ S_{2}\\ \vdots\\ S_{N}\end{bmatrix}=\begin{bmatrix}A(n-1)&A(n-1)\cdot a^{2(n-1)}\\ A(n-1)\cdot a^{2(n-1)}&-A(n-1)\end{bmatrix}\begin{bmatrix}x_{1}\\ x_{2}\\ \vdots\\ x_{N}\end{bmatrix} \tag{24}\]  
\[\text{IT:}\begin{bmatrix}x_{1}\\ x_{2}\\ \vdots\\ x_{N}\end{bmatrix}=\frac{1}{C}\cdot\begin{bmatrix}A(n-1)&A(n-1)\cdot a^{2(n-1)} \\ A(n-1)\cdot a^{2(n-1)}&-A(n-1)\end{bmatrix}\begin{bmatrix}S_{1}\\ S_{2}\\ \vdots\\ S_{N}\end{bmatrix}\]  
for \(A(0)=a^{k},\;k=1,\;2,\;3,\;\ldots\)  
We generally assume that \(k=1\). Generally, we also assume that the parameter \(a\
eq 0\) is any real number within the interval \((-\infty,+\infty)\). For a particular case \(a=1\) the transform (24) becomes the 1D Walsh-Hadamard transform.
# Experimental Evaluation of Thermal Performance and Durability of Thermally-Enhanced Concretes
## 3 Results and Discussion
### Resistance to Freeze-Thaw Cycles  
The relative dynamic modulus of elasticity (RDME) measured at 300 freeze-thaw cycles is presented in Figure 9. It is clear that all specimens had sufficient freeze-thaw resistance of RDME (more than 97% compared to 0 cycles) regardless of the use of insulating materials. Pop-out or cracks on all specimens were not observed in up to 300 cycles. From the test results, it can be known that all specimens have enough voids to absorb the volume expansion due to the freezing of pore water. Thus, tested specimens showed negligible reductions of RDME. In this study, the minimum air content, except the reference specimen, having no insulating materials was 4.9%. Thus, it is recommended that thermally-enhanced concrete with insulating materials should have at least 5% air content in fresh concrete using an air-entraining agent.  
Figure 9: Experimental observations of concrete relative dynamic modulus of elasticity relative dynamic modulus of elasticity (RDME) measured at 300 freeze-thaw cycles.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Coarse Aggregate Type**} & \multirow{2}{*}{**Labels**} & \multirow{2}{*}{**Insulation Materials**} & \multicolumn{2}{c}{**Average Carbonation Depth (mm)**} \\ \cline{4-5}  & & & **7 Days** & **28 Days** & **56 Days** \\ \hline \multirow{4}{*}{Normal (N)} & NN & None & 4.6 & 5.7 & 10.1 \\  & ND & Diatomite & 8.6 & 12.9 & 18.6 \\  & NH & Hollow micro-sphere & 8.9 & 17.9 & 21.7 \\  & NM & Micro-form agent & 7.6 & 13.5 & 20.9 \\ \hline \multirow{4}{*}{Light (L)} & LM & None & 2.5 & 5.1 & 8.2 \\  & LD & Diatomite & 8.6 & 13.9 & 18.2 \\  & LH & Hollow micro-sphere & 9.2 & 16.0 & 20.9 \\  & LM & Micro-form agent & 8.7 & 11.3 & 16.8 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Average carbonation rates.
## 3 System Function Realization
### Binocular Camera Accurate Distance Measurement  
A binocular camera consists of two cameras separated by a baseline distance, capturing the object in 2D images. The object's distance is calculated by measuring the pixel disparities. The Bouguet polar line correction method is used to ensure that the imaging origin coordinates of the left and right camera views are consistent, the optical axes of the two cameras are parallel, the left and right imaging planes are coplanar, and the polar lines are aligned. Using the internal parameters, rotation, and translation matrices from camera calibration, the camera views are adjusted and aligned through rotation and translation.  
By observing the object through a binocular lens and calculating the parallax \(d\), combined with parameters such as the baseline distance b and angle of view of two cameras, the three-dimensional coordinates of the object can be calculated using the principle of triangulation, and then the distance \(D\) of the object can be calculated using Equation (6). (_f_ is the focal length of the cameras; \(X\), \(Y\), and \(Z\) are the global coordinates of the object; and \(x_{l}\), \(x_{r}\), \(y_{l}\), and \(y_{r}\) are the projection coordinates of the object in the left and right cameras.) The schematic diagram of the binocular ranging principle is shown in Figure 9a.  
\[\frac{D}{f}=\frac{X}{x_{l}}=\frac{X-b}{x_{r}}=\frac{Y}{y_{l}}=\frac{Y}{y_{r}},D =\frac{f\times b}{x_{l}-x_{r}}=\frac{f\times b}{d} \tag{6}\]  
Initially, binocular camera calibration is conducted to derive the internal and external parameter matrices essential for rectifying the binocular camera system. Subsequently, the image captured by the binocular camera and the target's bounding box pixel coordinates, as ascertained by the YOLOv8 algorithm, are input into the system. The image undergoes conversion to grayscale, and distortion is rectified utilizing the calibrated internal and external parameter matrices. Thereafter, the Semi-Global Block Matching (SGBM) algorithm is engaged to perform stereo matching, which ascertains just the pixel parallax at the target's bounding boxes. Armed with these data, the target's real-world distance is computed employing Equation (6). Finally, the calculated world distance of the target is output. The flow chart of the binocular ranging algorithm is shown in Figures 9b and 10.  
Figure 9: The schematic diagram and flow chart of the monocular ranging algorithm. (**a**) Algorithm schematic diagram (f is the focal length of the cameras; X, Y, and Z are the global coordinates of the object; xl, xx, yl, and yr are the projection coordinates of the object in the left and right cameras; D is the distance of the object; and b is the baseline distance); (**b**) algorithm flow chart.
## 5 Evaluation of Major Design Codes Based on Results of FE Analysis
### Influence of Bridge Type  
The Chinese code provides the same formulae for calculating the critical axial force for the three different types of arch bridges. The Japanese code assumes a different \(\varphi\)-value in Equation (6) to obtain the different effective lengths of arch rib for the three types of bridges, which then affects the allowable axial compression stress \(\sigma_{\alpha}\). Although the \(\varphi\)-value has a large effect on \(\sigma_{\alpha}\) when the arch rib is slender, the influence of the \(\varphi\)-value in this study is negligible since the slenderness ratio of the arch rib is comparatively small. For these reasons, the effect of bridge type on normalized critical axial force according to the Chinese and Japanese codes should be contrary to that discussed in relation to the FE results in Section 4. This can be seen in Figures 14-16. In the Eurocode, the positive effect of the horizontal component of tension in the hangers and the negative effect of the horizontal component of compression in the columns on the out-of-plane buckling of the arch ribs, as shown in Figure 17, are considered. Since the hanger and column lengths are treated as positive and negative values, respectively, when calculating the \(h_{r}\)-value for different types of arch bridges, the \(h_{r}\)-values for through and half-through type arch bridges are little different, while the \(h_{r}\)-value for a deck-type bridge is smaller. For this purpose, the critical axial force for a through-type arch bridge is only slightly different from that for a half-through type arch bridge. Moreover, this conclusion is quite similar to the FE analysis results when the stiffness ratio is relatively large. Although the critical axial force for a through-type bridge is larger than that for a half-through type bridge in the FE analysis results when the stiffness ratio is relatively small, the critical axial force according to the Eurocode is much larger than that by FE analysis. For these reasons, the normalized critical axial force given by the Eurocode for through and half-through type bridges is almost the same, while the critical axial force for a deck-type bridge is much smaller.