esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Time-Dependent Temperature Variation During the Whole Testing Process
Figure 7: Time-dependent temperature curves of TSs of different distances to UT along each row in the fluid circulation of -10 \({}^{\circ}\)C: (**a**) No.1 TSs; (**b**) No.2 TSs; (**c**) No.3 TSs; (**d**) No.4 TSs. Comparing the curves in Figure 6, it can be found that closer to UT, a higher maximum temperature can occur and the temperature increment is larger. In another aspect, at the same time during circulation, the slope of the curve is greater, i.e., the temperature gradient is larger and has a higher temperature increasing rate. That is why, except Array 5 TSs, in almost all graphs (Figure 6a-d), Array 2 TSs (2-1, 2-2, 2-3 and 2-4) approach stable temperature values first. Likewise, in Figure 7 in the winter temperature of \(-10\)\({}^{\circ}\)C, heat conduction behaved similarly. To better understand the heat influence on the temperature in soils along the depth, temperature variations of temperature sensors (TSs) in a same TS array number (such as TS 2-1, TS 2-2, TS 2-3, and TS 2-4) are also discussed and shown in Figures 8 and 9. They are located at the same distance to the U-tube but at different depths within the soils. Specifically, they are arranged in a column seen from the model elevation of Figure 4b and labeled as Array 1 TSs, Array 2 TSs, Array 3 TSs, and Array 4 TSs (such as Array 2 TSs includes TS 2-1, TS 2-2, TS 2-3, and TS 2-4). The temperature monitoring data indicated the very similar process on temperature variation along the depth just with very small amount change on temperature value. It proves that the vertical heat conduction is not much apparent than that in radial direction. In other words, the commonly-used assumption of one-dimensional thermal conduction theory in thermal parameters calculation is rational during the operation of GSHP system. Similarly, in Figure 9 of the winter case, temperature variations also show that radial heat conduction plays a role during the operation of the GSHP system. Figure 8d further shows that the presence of the heat source of UT did not create an apparent increase of temperature in Array5 TSs (5-1, 5-2, 5-3, and 5-4), which also proved the rationality of choosing the TS of 4-3 as a criterion remark point to analyze the thermal balance. The fifth temperature sensor array was regarded as the influence boundary of heat conduction in this model test. At least closer No.4 TSs can show the temperature variation during testing. Additionally, muddy clay is the most concerned soil layer so that TS 4-3 is selected. Moreover, seen from the final stable temperature values, both in summer and winter cases, temperatures could hardly get back to the initial values, and are all raised a little (about 0.5 \({}^{\circ}\)C). This irreversibility seems not to be a contingency because the temperature increment did occur in all the TSs. Figure 8: Time-dependent temperature curves of TSs of different distances to UT along each row in the fluid circulation of 50 \({}^{\circ}\)C: (**a**) Array 1 TSs; (**b**) Array 2 TSs; (**c**) Array 3 TSs; (**d**) Array 4 TSs.
## 4 Experiments
### Effect of Defense  
We evaluated how well existing defense methods could mitigate attacks using jailbreak prompts created by the proposed method. Most existing defenses (e.g., [17; 19; 20]) assume adversarial suffixes. However, the jailbreak prompts generated by the proposed method, including PAIR and manual jailbreak attacks, are written in natural language, making these defenses inapplicable. The only suitable defense approach for naturally-worded jailbreak prompts is the SR method [18], which was used in this study. Since the SR method is predicated on ChatGPT, GPT-3.5 was used as a representative example.  
The ASR for the proposed method, PAIR, and manual jailbreak attacks was determined both with and without defense (Figure 4). It was found that the manual jailbreak attack  
Figure 3: Distributions of \(\Delta w\) for jailbreak prompts created by the proposed method and PAIR for GPT-3.5 (**A**), GPT-4 (**B**), and Gemini-Pro (**C**).  
was significantly mitigated by the SR method, with the ASR decreasing from 51.3% to 35.9%, a value nearly equivalent to the baseline ASR with defense. This corresponded to a reduction rate of 30.0%. The result confirms the findings of prior research [18] that self-reminder is effective against manual jailbreak attacks. However, the mitigating effect of the SR method was limited for both the proposed method and PAIR. Specifically, for PAIR, the ASR decreased from 72.8% to 67.2% with defense, but the reduction rate was only 7.7%. For the proposed method, the ASR decreased from 81.0% to 75.4% with defense, but the reduction rate was even smaller at 6.9%, compared to PAIR.  
The effective mitigation of manual jailbreak attacks appears to be due to the distinctive prompts used for attack settings being easily recalled by the self-reminder mechanism. On the other hand, while the prompts for rewriting in PAIR are complex, the rewritten input prompts are relatively simple, and expressions that could evoke the attack setting are suppressed. This might make the self-reminder less functional, leading to a limited mitigating effect. The proposed method creates even shorter input prompts (Figure 3) than PAIR by simply rewriting the original input prompts into expressions that 'do not cause discomfort', thus containing almost no descriptions that would recall the attack setting. Therefore, the self-reminder becomes even less effective, further weakening its mitigating effect.
## 1 Introduction
### DGNSS on Earth  
In the field of terrestrial applications, differential GNSS techniques are used a lot through the creation of corrections for compensating atmospheric delays, satellite orbits and clock errors for both the GNSS pseudoranges in the field of DGNSS, [12; 13; 14], and of carrier phase in the field of Real Time Kinematic (RTK) for higher accuracy applications [14; 15]. In both techniques, the corrections are inferred by using a fixed reference station with a well-known location and are transmitted to the user via radio, cellular networks, or the internet. When the baseline length between the user and the reference station becomes long, as is mostly the case for space scenarios, the literature for terrestrial applications based on differential GNSS measurements focus on the spatial decorrelation of the atmospheric delays with the increasing baseline [16; 17; 18; 19]. Another type of collaborative positioning, known as DGNSS-Cooperative Positioning (CP), has been proven successful for terrestrial applications as well, such as in collaborative vehicle networks and mobile users [20; 21]. This technique does not rely on a fixed reference station but, instead, works between two moving GNSS receivers [22; 23]. The basic idea behind DGNSS-CP is to measure the relative distance between GNSS receivers by exchanging information about their respective pseudoranges to a common set of tracked GNSS satellites. More specifically, a user with poor GNSS visibility can share raw GNSS measurements through a communication link with another user to estimate their baseline vector. Subsequently, this relative distance can be used in the Position Velocity Time (PVT) solution estimation and improve the Dilution of Precision (DOP) of the positioning problem. Even when it is noisy and correlated to the other GNSS range measurements, this additional ranging information was proven to be beneficial in low visibility and high DOP scenarios [22].
## 3 Results and Discussion
### Hysteresis and Skeleton Curves  
The horizontal force-displacement hysteresis curves and skeleton curves of specimens at the vertex section are shown in Figure 8. It can be seen that the shapes of the hysteresis curves of the cast-in-place wall and the prefabricated walls were basically the same, and the hysteresis curves in the later stage of loading had a certain degree of pinching, which was mainly due to the development of concrete diagonal cracks and local crushing. With the increase of the loading displacement, the hysteresis curves gradually tended to be full, and the area of the positive hysteresis curves of the specimens were larger than that in the negative direction, indicating that the energy consumption in the positive direction was larger. It is obvious that the bearing capacity of the specimens LSW and LAPC-1 decreased significantly during the negative loading in the later stage, resulting in a larger enclosing area of the hysteresis loop. Comparing the failure phenomenon of straight-edge members of the LAPC-1 and LAPC-2 specimens, it was found that LAPC-1 did not actually set stirrups within 50 mm above the sleeve due to manufacturing errors, resulting in rapid failure of LAPC-1 after buckling of rebars during negative loading. Due to the restraint of stirrups, the buckling section of stirrups moved upward when LSW was damaged, and the bearing capacity of LAPC-2 still had a certain safety reserve in the ultimate state. Therefore, it was suggested that the distance between the first stirrup above the edge-member sleeve and the upper surface of the sleeve should not be greater than 50 mm.  
It can be seen from Figure 8d that the skeleton curve of each specimen before cracking was basically a straight line, and the skeleton curves of LSW and LAPC-1 were basically consistent. As the displacement increased, the load and stiffness values of the positive skeleton curve of LAPC-2 were greater than those of the other two specimens during positive loading, and the negative skeleton curve was basically consistent with the other two specimens before the yield displacement (at a displacement level of 16 mm). However, the ultimate bearing capacity and ultimate load displacement were larger than those of LSW and LAPC-1. In addition, during the positive loading, the bearing capacity of each specimen increased with the increase of displacement, while the bearing capacity gradually decreased after the peak load under negative loading, as shown in Figure 8d. This was  
Figure 7: Failure of the root and grouting joint of L-shaped shear walls under ultimate load: (**a**) root of specimens; and (**b**) grouting joint of prefabricated specimens.  
mainly caused by the asymmetric geometric property of the L-shaped shear wall. Larger compression capacity was provided in the L-shaped-edge member due to the larger concrete area and more rebars, which made the specimen fail to reach the peak load during the positive loading.
# Phase Offset Tracking for Free Space Digital Coherent Optical Communication System
## 2 System Model  
### Atmosphere Channel Model  
The optical signal through the atmosphere turbulence channel suffers from random fluctuations as a result of the distorted refractive index caused by time-varying temperatures and pressures. The probability density function (PDF) of the normalized optical irradiance \(I\) can be described by the log-normal model as [18]:  
\[f(I)=\frac{1}{\sqrt{2\pi\sigma_{l}^{2}}}\frac{1}{I}\text{exp}\left[-\frac{ \left(\ln I+\frac{\sigma_{l}^{2}}{2}\right)^{2}}{2\sigma_{l}^{2}}\right];\;I\geq 0 \tag{1}\]  
The key parameter \(\sigma_{l}^{2}\) of this PDF is the Rytov variance and for satellite-to-ground downlink it can be obtained as [19]:  
\[\sigma_{l}^{2}=2.25k^{7/6}\text{sec}^{11/6}(\zeta)\int_{h_{0}}^{H}C_{n}^{2}(h) (h-h_{0})^{5/6}dh \tag{2}\]  
Here, \(k=2\pi/\lambda\) is the wavenumber and \(\lambda\) is the optical wavelength. \(\zeta\) is the satellite zenith angle and \(h\) is the altitude of the satellite. \(h_{0}\) is the ground station altitude. The Hufnagel-Valley (H-V) model is employed to describe the refractive-index structure parameter \(C_{n}^{2}(h)\) as:  
\[C_{n}^{2}(h)=0.00594\Big{(}\frac{w}{27}\Big{)}^{2}\Big{(}10^{-5}h\Big{)}^{10} \text{exp}(-\frac{h}{1000})+2.7\times 10^{-16}\text{exp}(-\frac{h}{1500})+A \text{exp}(-\frac{h}{100}) \tag{3}\]  
where \(w\) and \(A\) are the rms windspeed and the nominal value of \(C_{n}^{2}(0)\). With the atmosphere turbulence getting stronger, \(\sigma_{l}^{2}\) increases. The PDF in (1) can be measured by another parameter named the scintillation index \(\sigma_{l}^{2}\), which is defined as [20]  
\[\sigma_{l}^{2}=E\Big{(}I^{2}\Big{)}-E^{2}(I)=\text{exp}(\sigma_{l}^{2})-1 \tag{4}\]  
We define a group of samples \(\boldsymbol{X}\) obeying the normalized log-normal distribution described as Equation (1), written as \(\boldsymbol{X}\sim L-N\big{(}1,\sigma_{l}^{2}\big{)}\) where 1 and \(\sigma_{l}^{2}\) are the mean value and Rytov variance of the samples respectively. Another group of samples \(\boldsymbol{Y}\) is defined as \(\boldsymbol{Y}=\ln(\boldsymbol{X})\). \(\boldsymbol{Y}\) obeys the zero-mean normal distribution with variance \(\sigma^{2}\) and it is written as \(\boldsymbol{Y}\sim N\big{(}0,\sigma^{2}\big{)}\). Changing the variance of \(\boldsymbol{Y}\) into \(\sigma^{\prime 2}\), we obtain \(\boldsymbol{Y}^{\prime}\sim N\big{(}0,\sigma^{\prime 2}\big{)}\). Then, calculating the logarithm of \(\boldsymbol{Y}^{\prime}\), a new group of samples \(\boldsymbol{X}^{\prime}\) obeying log-normal distribution with new Rytov variance \(\sigma_{l}^{\prime 2}\) is constructed and it can be written as \(\boldsymbol{X}^{\prime}\sim L-N\big{(}1,\sigma_{l}^{\prime 2}\big{)}\). Using this method, we obtain multiple groups of channel gain data with different Rytov variances and scintillation indexes based on a group of experience data. The data are shown in chapter 4 and used to verify the performance of the phase offset estimation algorithm.
## 2 Methodology
### Coarse-to-Fine Spatiotemporal Correlation Computation Scheme
#### 2.3.2 Fine Disparity Estimation  
Following the coarse disparity, \(d_{c}^{p}\), computation, the square area centred on the grid point in the disparity map is filled with the disparity of the grid point. Because the coarse disparity map has given the initial position of the fine-matching search, it is only necessary to calculate the fine disparity, \(d_{f}^{p}\), within the narrow search range of \([d_{f}^{\text{min}},d_{f}^{\text{max}}]\), which significantly reduces the matching search range. This means that the final disparity, \(d\), fits the condition, \(d=d_{c}^{p}+d_{f}^{p}\). Because the final disparity is determined by the result of fine matching, the selection of the fine matching window size directly determines the accuracy of 3D face reconstruction. To ensure measurement accuracy, a smaller correlation window is introduced in order to effectively reduce the computation cost.
## 1 Introduction
### Motivations and Contributions  
Motivated by the working mechanism of LEO constellation, we study a multiple nodes cooperative transmission for downlink LEO SATCOM. Recognizing there exists a huge beam gain difference between the beam-edge UT and the beam-center UT, two co-carrier cooperative transmission methods are proposed where the outage probability and ergodic sum-rate are further analyzed.  
The main contributions of the paper can be summarized as follows:  
* Recognizing that UTs located at the beam-edge area could be covered by multiple satellites, we propose two promising cooperative transmission methods. In the first method, UTs receive multiple signal paths from numerous LEO nodes and combine them without processing selection. In this scheme, the receiver directly demodulates the received signals. To fully utilize the signals from different satellites, we then study a selection combination (SC) method where the strongest signal path is selected to perform the demodulation procedure.
* As there exists a significant beam gain difference at the beam-edge area and the beam-center area, we develop a co-carrier transmission-aided scheme based on the two cooperative methods. In detail, the beam-edge and beam-center UTs share the same resource block where the signals for these two users would be superposed as one signal after modulation. To separate the two signals, SIC is applied at the receiver.
* In order to evaluate the performance of the new methods, we derive the expressions of the ergodic sum-rate and outage probability. Moreover, we further consider the processing expense of the SC algorithm. At last, simulation results confirm the performance of the work.
* Both the proposed methods are energy efficient. The received signal of the co-carrier-based direct combination (DC) method could be enhanced by combining signals from multiple satellites without increasing the transmit power, while the co-carrier-based SC scheme enables the UT access to the satellite with the best channel condition.  
The rest of the paper is organized as follows. Section 2 describes the system model of a cooperative LEO SATCOM. In Section 3, the DC and SC methods are proposed while the co-carrier transmission is studied as well. To evaluate the performance, expressions of ergodic sum-rate and outage probability are derived and analyzed theoretically in Section 4. The impact of processing expense of the SC method is also studied. Simulation results of the ergodic sum-rate and outage probability are presented and discussed in Section 5, and the paper is concluded in Section 6.  
_Notation:_ Vectors and matrices are presented by lowercase and uppercase bold letters, respectively. The transpose and Hermitian transpose are denoted by superscripts T and H, respectively. The statistical expectation and the probability are presented by \(\mathbb{E}[\cdot]\) and \(\mathbb{P}(\cdot)\), respectively. While \(\mathcal{CN}(a,b)\) denotes the distribution of circularly symmetric complex Gaussian (CSCG) random variables with mean \(a\) and covariance \(b\).
# Retrofit Fatigue Cracked Diaphrag Cutouts Using Improved Geometry in Orthotropic Steel Decks
## 1 Introduction
Furthermore, the cutout radius, diaphragm thickness, and the position of longitudinal ribs were taken into consideration, which affect the stress distribution and concentration around the diaphragm cutouts, due to the effects of bending and shearing, in-plane supports, asymmetrical loading, and relative longitudinal deformations [38; 39]. Based on studies conducted with cutout types (I), (II), (III), and (V), in which the spacing and thickness of diaphragms were taken into consideration, it was concluded that the design of the geometric dimensions of diaphragm cutouts has a great influence on the fatigue performance of the diaphragms [40; 41; 42]. However, previous studies were only limited to typical diaphragm cutouts in newly built bridges. Little research has been conducted on the retrofitting of diaphragm cutouts in as-built bridges that have developed fatigue cracks using atypical geometries. Diaphragm cutout retrofitting in as-built bridges should consider the geometry of the original shape, and the improved geometries generally are not the typical cutout type recommended by the related specifications. When changing the shape of diaphragm cutouts by cutting and grinding methods, the maximum stress of the diaphragm cutouts with a radius of 35 mm was reduced by 54.6% [5]. Another scheme shows that based on the crack length, the fatigue stress can be reduced by 20-29% if the cracks were cut using a combination of straight and arc sections [42]. In these above methods, stress reduction differs mainly because of the different cutting shapes used for the fatigue cracks in diaphragm cutouts. Given that the cutout geometry used to repair as-built bridges is different from that in newly built bridges, the retrofitting mechanisms and the actual effects of cutout repairs need to be analyzed and verified. This paper explores the stress concentration mechanisms around diaphragm cutouts using stress flow methods, based on an OSD in a suspension bridge that had developed fatigue cracks during its service period, after nine years of operation. Thereafter, some principles of optimization and retrofitting strategies of diaphragm cutouts were proposed to reduce stress concentration and eliminate short fatigue cracks. Repair schemes were designed on the basis of these optimization principles, and were carried out at a test segment of OSD with a length of 30 m in this bridge. Wheel loads were applied with standard trucks and stresses were measured during loading test on this bridge. The stress state on the original and retrofitted diaphragm cutouts were compared and analyzed. The retrofitting mechanisms and experimental data presented in this study can provide reference in the rehabilitation of OSDs with diaphragm cutout cracks.
# Game-Based Resource Allocation Mechanism in B5G HetNets with Incomplete Information
###### Abstract  
Ultra-dense and highly heterogeneous network (HetNet) deployments make the allocation of limited wireless resources among ubiquitous Internet of Things (IoT) devices an unprecedented challenge in 5G and beyond (B5G) networks. The interactions among mobile users and HetNets remain to be analyzed, where mobile users choose optimal networks to access and the HetNets adopt proper methods for allocating their own network resource. Existing works always need complete information among mobile users and HetNets. However, it is not practical in a realistic situation where important individual information is protected and will not be public to others. This paper proposes a distributed pricing and resource allocation scheme based on a Stackelberg game with incomplete information. The proposed model proves to be more practical by solving the problem that important information of either mobile users or HetNets is difficult to acquire during the resource allocation process. Considering the unknowability of channel gain information, the follower game among users is modeled as an incomplete information game, and channel gain is regarded as the type of each player. Given the pricing strategies of networks, users will adjust their bandwidth requesting strategies to maximize their expected utility. While based on the sub-equilibrium obtained in the follower game, networks will correspondingly update their pricing strategies to be optimal. The existence and uniqueness of Bayesian Nash equilibrium is proved. A probabilistic prediction method realizes the feasibility of the incomplete information game, and a reverse deduction method is utilized to obtain the game equilibrium. Simulation results show the superior performance of the proposed method.  
5G and beyond (B5G) heterogeneous networks (HetNets); resource allocation; game theory; incomplete information +
Footnote †: journal: Accepted: 21 February 2020; Published: 25 February 2020
## 2 System Architecture  
The data-collection and processing system, as shown in Figure 2, consists of three modules: (1) wearable devices integrating sensors acquiring physiological and other data; (2) SynCHubs handling data synchronization with the wearables; and (3) a local or cloud-based storage and analytics node (SAN). The SAN can transfer selected data and metrics to other networks or visualization resources (the optional fourth module).  
The architecture is modular and can be adapted to support multiple concepts of operations. There is no transmission of data to OEM cloud servers, and the system can operate with no connectivity to Internet.