esa-sceva/satcom-chunk-collection huggingface dataset:
# Optimal Collision-Free Grip Planning for Biped Climbing Robots in Complex Truss Environment
## 3 Computation of Operational Regions for Negotiating Obstacles
### Constraints
#### 4.2.2 Collision Avoidance during Transitions  
Potential collision must be also taken into account when BiCRs perform transitions. As a result, it is necessary to extract the potential obstacle members before solving the grip optimization model, in order to guarantee safe transitions.  
Figure 9 shows our strategy to find all the potential obstacles \({}^{j}\mathcal{O}_{t}\). Supposing BiCRs transit from _Member 1_ to _Member 2_, a conservative _Sphere \(\Omega\)_ is constructed based on the operational region \(\mathfrak{R}_{t}\) for transiting. The center \(P_{C}\) of _Sphere \(\Omega\)_ coincides with the center point of a set of \(T_{1}\) and \(T_{3}\) joint center  
Figure 8: The relationship between moving distance (on a member) and minimum climbing steps.  
points corresponding to the boundary configurations. While the radius \(r_{\Omega}\) of _Sphere_\(\Omega\) is set as the furthest distance between its center and the gripping points. Thus, this sphere space covers the range where potential collision may happen during transition. Obstacle members are then found out by carrying out intersection checks between the sphere and each truss member. Taking the case in Figure 9 for example, _Member_**4**, _Member_ 5 and _Member_ 6 will be extracted as the potential obstacles.
## 4 Numerical Results
### Analysis
#### 4.1.1 Pivot Radius  
The pivot radius might be intuitively designed for the pad-pivot friction moment because it is directly related to the amount of the friction moment, as shown in Equation (2). The selected pivot radius ranged from 0.01 m to 0.02 m. As can be seen in Figure 7, a larger pivot radius indicates a higher dynamic eccentricity of the friction-induced instability. On the contrary, the large size of the pivot delayed the occurrence of the Hopf bifurcation marginally; and became more pronounced in the form of a subcritical type of Hopf bifurcation. As the disc had unbalance eccentricity, the response appears to have a Neimark-Sacker (N-S) bifurcation in the high speed range. This results in the quasi-periodic motion suddenly changing to a 1/3 sub-synchronous response, and vice-versa.  
Figure 6: Poincaré sections of orbits: (**a**) 1\(\tau\) periodic solution, (**b**) quasi periodic or aperiodic solution.  
Figure 7: Effect of pivot radius (\(R_{\rm pvt}\) = 0.01 m, 0.015 m, 0.02 m) on the rotorbynamic bifurcation induced by pad-pivot friction on the TPJB system (\(m_{\rm p}\) = 1/2, \(\chi_{\rm p}\)/\(\chi\) = 0.5, L/D = 0.5): (**a**) Fully balanced; (**b**) \(e_{\rm immb}\) = 0.05 C\({}_{\rm b}\); (**c**) \(e_{\rm immb}\) = 0.10 C\({}_{\rm b}\); (**d**) \(e_{\rm immb}\) = 0.20 C\({}_{\rm b}\).
# Characterization of Tropical Cyclone Intensity Using the HY-2B Scatterometer Wind Data
## 1 Introduction
[6] shows, though, that the ASCAT high and extreme winds can be made consistent with the extreme winds from the airborne Stepped-Frequency Microwave Radiometer (SFMR), which is calibrated with dropsonde data, by applying an appropriate high-wind rescaling, which may be useful in estimating the TC intensity following the tropical cyclone community standards. Regarding the rapid increase of satellite scatterometer missions in China [21; 22], it becomes more realistic to monitor the TC evolution (notably the TC center locations) based on the joint wind observations from the virtual scatterometer constellation. In particular, the recent HY-2C and -2D satellites are operated in inclined orbits [22], which can provide nearly six-hourly regional wind observations together with the sun-synchronous HY-2B satellite. Since all the HSCATs are operated in a Ku-band microwave frequency with conically scanning pencil beams, this paper intends to estimate the TC intensity using an alternative parameter to the maximum HSCAT-derived wind speed. [PERSON] and [PERSON] [23] constructed a comprehensive statistical climatology of the TC size (e.g., the azimuthally averaged radius of 17-m/s winds, R17) and strength (i.e., the average wind speed in the cyclonic circulation), and found that the correlation between TC size and strength is strong. [PERSON] and [PERSON] [24] proposed a new concept, namely TC fullness, to quantitatively measure the storm wind structure and to evaluate the TC intensity. Though both studies indicated that the direct correlation between R17 and the maximum sustained wind speed (MSW) of the best-track data is relatively low (~0.3), the wind radii information (R17) can be used to derive new parameters (e.g., TC fullness) that are more correlated with MSW, hence R17 is essential in the estimation of TC intensity. As such, this paper aims at improving estimates of the TC center location and R17 using scatterometer data, using best-track information on storm intensity and evolution as the reference. Section 2 describes the datasets used in this study. Section 3 presents the methods of data preparation and derivation of essential parameters, e.g., the TC center location and the TC wind radii (R17). The relation between wind radii and TC intensity is examined in Section 4. Finally, the main conclusions are summarized and discussed in Section 5.
## 2 Experimental Set-Up  
### Moving Model Test Rig  
To provide insights into the aerodynamic issues of high-speed railways and obtain aerodynamic characteristics of railway-related vehicles and infrastructures, a moving model test rig was developed in the National engineering laboratory for high-speed railway construction at Central South University, Changsha, China [38]. The moving model test rig has a 34 m long double track and consists of three parts: acceleration, test, and deceleration sections. On the other hand, crosswind is one of the prerequisites of exploration, therefore, the moving mode test rig needs a necessary qualification from the crosswind. The wind tunnel of Central South University (CSU) implementation of the strategy for the high-speed railway under crosswind has provided an arena and adequate condition. The moving model test rig spreads over the low-speed test section along both sides of the chamber plotting a moving train & infrastructure system across the wind tunnel. Thus, the moving model test rig can be combined with a wind tunnel to study the high-speed railway aerodynamics under crosswind effects.  
As shown in Figure 1, a schematic diagram of the moving model rig, the acceleration and deceleration parts are located on both sides, and the available test part as 12 m long across the wind tunnel's test section. The low-speed section had a dimension of 12 m wide, 3.5 m height, and 18 m long. A 1/16.8 scaled model of a Fuxing HST, which is an HST in operation throughout China, was used in the experiment. The maximum corresponding Reynolds number (Re) of the experimental model was 4.91 \(\times\) 10\({}^{5}\), based on the train model height as 0.227 m and train speed \(U_{t}\). For the present experiments, a constant crosswind can be generated using the wind tunnel during the investigation.
# Adaptive Multi-Grained Buffer Management for Database Systems
## 4 Performance Evaluation
### I/Os  
Figure 4a shows the I/Os for all algorithms with a varying hybrid ratio. First, MG-Buffer causes more I/Os when meeting many \(WQs\), compared with page-grained buffers (e.g., LRU, LIRS, CFLRU, and CFDC). This is because MG-Buffer loses the benefits of spatial locality. Furthermore, MG-Buffer incurs more additional I/Os when writing incomplete dirty pages. Compared to MG-Buffer, AMG-Buffer can distinguish pages by clustering rates to choose the page-grained buffer or tuple-grained buffer, which alleviates these problems. For different hybrid ratios, compared with others, AMG-Buffer can achieve the least I/Os. Figure 4b shows the I/Os under different buffer sizes. When the buffer size is less than 128 MB, MG-Buffer incurs more I/Os than traditional ones and AMG-Buffer reduces I/O costs by up to 13% (32 MB) and 23% (64 MB) than others. When the buffer size is larger than or equals 128 MB, both AMG-Buffer and MG-Buffer have fewer I/Os than LRU, CFLRU and CFDC due to caching more hot tuples, but AMG-Buffer reduces I/Os by 29% (128 MB) and 15% (256 MB) compared to MG-Buffer. Figure 4c shows the write I/Os of all algorithms under different read/write ratios. Both AMG-Buffer and MG-Buffer have fewer write I/Os than LRU, CFLRU, and CFDC and are friendly to SSDs. When we set the read ratio to 20% (R20), 50% (R50), and 80% (R80), AMG-Buffer reduces write I/Os by up to 39%, 37% and 38%, respectively, compared to traditional ones. All results demonstrate that AMG-Buffer can retain the benefit of both the tuple-grained and the page-grained buffer management policy.
## 4 Discussion  
In this study, we isolated a polyketide compound, (\(\pm\))-differolide, from the desert-inhibiting _Streptomyces aaidamensis_. Although, (\(\pm\))-differolide has been known for decades, its bioactivity has not been demonstrated before. In this study, we show its radical scavenging activity against DPPH for the first time. Researchers have been convinced for a long time that extreme _Streptomyces_-derived NPs with their structure-activity relationship (SAR) may be a highly promising source for future development of drugs against bacterial infections, especially against multidrug-resistant bacteria [6]. Many polyketides have been confirmed to have antioxidant activity. For example, rhizophols A [21], ascomindones A [22], and hexaricin F/G [23] exhibited DPPH radical scavenging activity. This indicates that (\(\pm\))-differolide is precisely the antioxidant that may enable _S. aaidamensis_ to survive in the niche. Considering the adaptation strategy of _Streptomyces_ to different extreme conditions [24], it is possible to generate diverse biologically active compounds. These types of NPs should also attract a greater research interest. Here, we showed that it is feasible to isolate NPs with antioxidant activity from the desert _Streptomyces_.  
Although the yield of (\(\pm\))-differolide in _S. aaidamensis_ is not very low (10 mg/L), considering the application value of its biological activity, it is necessary to synthesize the compound in large quantities. To explore the biosynthesis gene cluster of (\(\pm\))-differolide, we used a comparative genomics approach in this study. The method has been successfully applied to finding biosynthetic gene clusters of target compounds in multiple strains [25; 26]. It is also demonstrated here that the method enables rapid deduction of biosynthetic pathways for compounds for which no biosynthetic pathways have been reported. Biosynthesis of (\(\pm\))-differolide has been verified in this study, providing a basis for its development as an antioxidant medicine.  
Conceptualization, Y.W. and T.C.; methodology, W.Z. and X.Y.; software, K.J.; validation, W.Z., G.L. and T.C.; data curation, Y.W., X.Y. and S.W.; writing--original draft preparation, Y.W.; writing--review and editing, W.Z. and T.C.; supervision, T.C.; project administration, T.C.; funding acquisition, W.Z., G.L. and T.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the West Light Foundation of The Chinese Academy of Sciences(xbzg-zdsys-202105), the National Key R&D Program of China (2019 YFE0121100), and the Scientific Project of Gansu Province, China (20 YF3 WA007, 18 JR2 TA019, 20 JR5 RA548). And the APC was funded by the West Light Foundation of The Chinese Academy of Sciences(xbzg-zdsys-202105).  
Not applicable.  
The data presented in this study are available in the submitted article.  
The authors are grateful to [PERSON] from Shanghai Jiao Tong University for cooperation in laboratory support, and to [PERSON] from Fudan University for providing laboratory facilities including HR-LC-MS.  
The authors declare no conflict of interest.
## 3 Typology of the Building Stock, Market Segments and Economics of Refurbishing
### The Economics of Refurbishing
#### 3.1.2 Costs of Reducing Energy Consumption in Swedish Building Stock  
In Sweden, the building stock comprises 2.1 million buildings of which 165,000 are multifamily housing, 1.89 million are detached housing and 47,000 are commercial and public buildings [16], see Table 6. Boverket [16] provides a cost estimate for reducing energy consumption in the building stock by 50% in 2050, relative to 1995. By implementing technically feasible energy saving measures in the most cost-effective order, the cost expressed as net present value would be about 217 billion \(\epsilon\), excluding transaction costs [18]. The results were based on a calculation period of 40 years; costs calculated as annuities of investment and maintenance costs in 2009 prices. The marginal cost curves clearly illustrate the law of diminishing returns [28], see Figure 3.  
The estimated cost for _residential housing_ (detached and multifamily housing) was about 371 \(\epsilon\)/m\({}^{2}\) and about 132 \(\epsilon\)/m\({}^{2}\) for commercial and public buildings. Prerequisites for favorable total economy should on average be greater in commercial and public buildings.  
A collaborative study by Boverket and the Swedish Energy Agency (2013) [12] suggest that gradual energy upgrades added to regular maintenance and renovations cycles together with current incentives will yield energy reductions of 26%-40% by 2050. On total economy, the study concludes that profitability will ultimately depend on assumptions about discount rates, returns, economic lifespan, whether the property owner is located in a strong or weak market and on the calculation method included and used for projections. This conclusion is similar to other findings [29, 30, 31, 32].  
Figure 3: The solid curve shows the reduction of energy demand per annum (x-axis) and the cost for material and labour, in billion \(\epsilon\) per annum (y-axis) for residential buildings left, and commercial and public buildings right. The dashed curve signifies that the total cost for the building owner is higher. From: [PERSON] (2010) [18] (Figures 1 and 2).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Building Stock** & **Detached** & **Multifamily** & **Detached** & **Multifamily** \\
**by Construction** & **Housing–Number** & **Housing–Number** & **Housing–Heated Floor** & **Housing–Heated Floor** \\
**Year, Sweden** & **of Buildings in** & **of Buildings in** & **Area/Million m\({}^{2}\) (\%)** & **Area/Million m\({}^{2}\) (\%)** \\ \hline \(-\)1960 & 846 (45\%) & 77 (47\%) & 146 (48\%) & 99 (41\%) \\
1961–1975 & 500 (26\%) & 32 (20\%) & 82 (27\%) & 76 (32\%) \\
1976–1985 & 313 (17\%) & 12 (7\%) & 44 (15\%) & 14 (6\%) \\
1986–1995 & 154 (8\%) & 31 (19\%) & 19 (6\%) & 38 (16\%) \\
1996–2005 & 77 (4\%) & 12 (7\%) & 11 (4\%) & 11 (5\%) \\ \hline Total & 1888 (100\%) & 165 (100\%) & 301 (100\%) & 238 (100\%) \\ \hline \hline \end{tabular}
\end{table}
Table 6: Building stock typology in Sweden, Source: Boverket (2010); [16, 17].
# Data-Driven Modeling of Low Frequency Noise Using Capture-Emission Energy Maps
## 1 Introduction  
In nanoscale CMOS devices, the stochastic behavior of a few defects can have a significant impact on the reliability of devices and their circuits [1; 2; 3; 4; 5; 6; 7; 8]. The negative bias temperature instability (NBTI) is among the most critical reliability issues and can be described by capture-emission energy (CEE) maps [3; 4; 5; 9; 10; 11; 12; 13; 14; 15]. Accurately modeling the NBTI relies on a combined methodology comprising thorough CEE maps and efficient models. However, CEE maps are limited by the stress-recovery measurement window [9; 10; 14; 15; 16; 17]. An accurate estimation of the parameters of CEE distribution is crucial to enable full lifetime calculation of NBTI without measurement time extrapolation. The kinetics of defects responsible for NBTI has been explained by the random capture-emission process of charge carriers caused by oxide traps [9; 10; 11; 12; 13; 14; 15; 18; 19]. Moreover, it has been found that the recoverable component of NBTI and random telegraph signal (RTS) noise are due to same defects [19; 20; 21; 22; 23; 24; 25]. The discrete fluctuations of RTSs with widely distributed time or energy scales are the main source of low frequency (\(1/f\)) noise in nanoscale MOSFETs [20; 21; 26; 27; 28; 29]. For the statistical analysis and rigorous modeling of noise behavior, it is crucial to incorporate the distribution of defects based on CEE maps, including large signal AC operations [27; 28; 29; 30]. In particular, since the static random-access memory (SRAM) cell is a highly scaled device, the threshold voltage variation due to RTS is a major source of degradation in SRAM characteristics [30]. In the CEE map framework, the time-dependent variability of degradation such as NBTI and noise is reproduced under different bias and duty cycle conditions. In this study, CEE-based noise models are newly presented to allow a quantitative prediction for RTS and \(1/f\) noise. The models utilize a Gaussian mixture model (GMM) for enlarging the capture-emission energy window and clustering the recoverable component from the fitted CEE map.
# Calibrating the Attack to Sensitivity in Differentially Private Mechanisms
## 4 Adversarial Classification in Gaussian Mechanisms
### A Statistical Threshold-First-Order Statistics  
Next, we present a statistical trade-off between the privacy budget of the Gaussian mechanism and the adversary's advantage.  
**Theorem 6**.: _The adversary avoids being correctly detected by the defender with the largest possible power of the test \(\bar{\beta}=1-\beta\) and the best critical region of size \(\alpha=1-\bar{\alpha}\) for positive bias, if the following inequality holds_  
\[\Delta\mu\leq\Big{(}Q^{-1}(\alpha)-Q^{-1}(\bar{\beta})\Big{)}\sigma_{z} \tag{60}\]  
_where \(Q(.)\) denotes the Gaussian \(Q\)-function defined as \(\Pr[T>t]\) and for \(\sigma_{z}=\frac{\sqrt{2}\cdot s\cdot 5\cdot\log(1.25/\delta)}{\epsilon}\). By analogy, for negative bias, we have_  
\[\Delta\mu\geq\Big{(}Q^{-1}(\bar{\alpha})-Q^{-1}(\beta)\Big{)}\sigma_{Z} \tag{61}\]  
Proof.: Likelihood ratio function \(\Lambda\) to choose between \(Y-\sum_{i}^{n}X_{i}\) and \(Y-\sum_{i}^{n}X_{i}-X_{a}\) results in \(z>\tilde{k}\) where \(\tilde{k}=\frac{\sigma_{z}^{2}\log k}{\Delta\mu}+\frac{\mu_{1}+\mu_{0}}{2}\) by setting \(p_{0}\) and \(p_{1}\) as Gaussian distributions with respective location parameters \(\mu_{0}\) and \(\mu_{1}\) and the mutual scale parameter \(\sigma_{z}\). Probability of rejecting \(H_{0}\) in case of an attack is derived using this condition as  
\[\alpha=\begin{cases}Q\Big{(}\frac{\sigma_{z}\log k}{\Delta\mu}+\frac{\Delta \mu}{2\sigma_{z}}\Big{)}\ \Delta\mu>0,\\ 1-Q\Big{(}\frac{\sigma_{z}\log k}{\Delta\mu}+\Delta\mu/(2\sigma_{z})\Big{)} \end{cases} \tag{62}\]  
where \(Q(.)\) denotes the Gaussian Q-function defined as \(\Pr[T>t]\) for standard Gaussian random variables. The threshold of the critical region \(k\) for \(\Delta\mu>0\) is obtained as a function of the probability of false-alarm as \(k=\exp\Big{\{}\frac{\Delta\mu}{\sigma_{z}}\big{(}Q^{-1}(\alpha)-\Delta\mu/2 \sigma_{z}\big{)}\Big{\}}\). The second threshold for negative bias can be obtained similarly. The defender fails to detect the attack if \(Y<k+q(\mathbf{X})\), where \(q(.)\) is the noiseless query output. By analogy, for \(\Delta\mu<0\), the attack is not detected if the DP output exceeds \(\tilde{k}+q(\mathbf{X})\) where \(\tilde{k}=\exp\Big{\{}\frac{\Delta\mu}{\sigma_{z}}\Big{(}Q^{-1}(\bar{\alpha} )-\frac{\Delta\mu}{2\sigma_{z}}\Big{)}\Big{\}}\). The power of the test for both cases is obtained as follows  
\[\bar{\beta}=\begin{cases}Q\big{(}Q^{-1}(\alpha)-\Delta\mu/\sigma_{z}\big{)}, \text{ for }\Delta\mu>0,\\ 1-Q\big{(}Q^{-1}(\bar{\alpha})-\Delta\mu/\sigma_{z}\big{)}\text{ for }\Delta\mu<0. \end{cases} \tag{63}\]  
Rewriting (62) and (63), we obtain (60) and (61).
# Efficient MIMO Signal Predistortion for Secrecy-Enhancing
## 2 Related Works
### O-STBC for Real-Numbered Signals  
Even though the full-rate O-STBC scheme for complex-numbered signals only exists for the two transmit antennae system [13], it is well known that it can be designed for more than two transmit antennae for real-numbered signals, such as pulse-amplitude modulation (PAM) [12]. The encoding matrices of the full-rate O-STBC schemes for \(p\) time periods and \(N_{T}\) transmit antennae, \(\mathbf{X}_{N_{T}}\) of size \(p\times N_{T}\), can be found in the literature [12]; here we provide the following examples for \(N_{T}=4\) and \(8\):  
\[\mathbf{X}_{4}=\begin{bmatrix}x_{1}&x_{2}&x_{3}&x_{4}\\ -x_{2}&x_{1}&-x_{4}&x_{3}\\ -x_{3}&x_{4}&x_{1}&-x_{2}\\ -  
periods. Therefore, they can offer the full-diversity of \(N_{T}\) due to the orthogonality as well as full-rate [12].  
Assuming the signal vector \(\mathbf{x}\) is transmitted using \(\mathbf{X}_{N_{T}}\) via \(N_{T}\) transmit antennae, the received signal vector can be expressed as:  
\[\mathbf{y}=\mathbf{X}_{N_{T}}\mathbf{h}+\mathbf{n}, \tag{6}\]  
where \(h_{k}\) is the complex channel gain from the \(k\)-th transmit antenna to the receiver and \(\mathbf{n}\) is an AWGN vector. Then, the above (6) can be equivalently expressed by:  
\[\mathbf{y}=\mathbf{H}_{\text{C},N_{T}}\mathbf{x}+\mathbf{n}, \tag{7}\]  
where \(\mathbf{H}_{\text{C},N_{T}}\) is a complex-numbered channel matrix and is therefore not an orthogonal matrix. For example, the \(\mathbf{H}_{\text{C},4}\) corresponding to the encoding matrix, \(\mathbf{X}_{4}\) of (4) can be given by:  
\[\mathbf{H}_{\text{C},4}=\begin{bmatrix}h_{1}&h_{2}&h_{3}&h_{4}\\ h_{2}&-h_{1}&h_{4}&-h_{3}\\ h_{3}&-h_{4}&-h_{1}&h_{2}\\ h_{4}&h_{3}&-h_{2}&-h_{1}\end{bmatrix}. \tag{8}\]  
Even though the above \(\mathbf{H}_{\text{C},N_{T}}\) with complex elements does not have full-orthogonality, a linear decoding can be performed for real number signal detection as follows:  
\[\hat{\mathbf{x}} =\frac{1}{\sum_{k=1}^{N_{T}}||h_{k}||^{2}}\mathbf{H}_{\text{C},N _{T}}^{H}\mathbf{y} \tag{9}\] \[=\frac{1}{\sum_{k=1}^{N_{T}}||h_{k}||^{2}}(\mathbf{H}_{\text{C},N _{T}}^{H}\mathbf{H}_{\text{C},N_{T}}\mathbf{x}+\mathbf{H}_{\text{C},N_{T}}^{H} \mathbf{n}),\]  
where \(\hat{\mathbf{x}}\) is the estimated result of \(\mathbf{x}\). This is because the diagonal elements of the Gram matrix, \(\mathbf{H}_{\text{C},N_{T}}^{H}\mathbf{H}_{\text{C},N_{T}}\), are pure real numbers, while the off-diagonal elements are pure imaginary numbers which do not affect the real number signal detection.
# Detailed Design and Aerodynamic Performance Analysis of a Radial-Inflow Turbine
## 1 Introduction
In other similar works with preliminary design of the RI turbine, we cannot find a detailed design approach for all components of a typical RI turbine (Volute, stator and rotor) [16; 17; 18; 19; 20]. In this study, we redesign the radial-inflow turbine applied in the air cycle machines at Amikabir University of Technology to achieve higher efficiency such that the coefficient of performance of ACM is improved. To achieve this goal, first, a preliminary design approach has been developed based on the various available methods. Second, a method is applied to the detailed aerodynamic design of the turbine rotor blades based on Aungier [7] and then the detailed design of volute is established. After finalizing the turbine geometry, unsteady 3D simulations using ANSYS CFX are performed to compute the aerodynamic performances of the turbine, including the mass flow rate map, efficiency map, temperature drop and streamlines through the rotor and nozzle.