esa-sceva/satcom-chunk-collection huggingface dataset:
# Mitigating Urban Congestion: A Cooperative Reservation Framework for Automated Vehicles
## 3 Infrastructure Map Recognition
### Control Area Definition  
In Figure 3 the idea behind this notation can be found. In Figure 3a, a four-way intersection is depicted, while in Figure 3b, a roundabout is shown. As can be seen, for each relevant traffic emplacement, Entry (Pink), Survey (Green), and Exit (Blue) _Control Areas_ are generated, marked as colorized polygons constructed from the lane geometry information. From each _Control Area_, the conflict zones (Red squares) are defined, where the compatibility between incoming vehicles and the allocated resources are checked. Note that, for the sake of clarity, not all relevant areas are drawn in Figure 3.  
On the other hand, the allocation of resources is defined based on compatibility using _Survey Clusters_, where a cluster is a tuple of three items: _Entry_, _Exit_ and _Survey_ lanes. Each item is a _control area_ defined by a set of unique roads, recognized by the ID provided in the HD Map. Each _Exit_ and _Entry_ area contains the Exit and Entry point, respectively, in local coordinates of the infrastructure map and global GNSS coordinates from a known ENU origin. At start-up, each _cluster_ found in the traffic emplacement is constructed from a map intersection lane by assigning each control area mentioned and computing the Entry and Exit points found in the logical connections of roads.  
The relevant roads chosen for this process are included within an arbitrary radius from the GNSS position reported by the localization module of the infrastructure set of sensors. All roads that are not inside this radius are not surveyed and are excluded from the internal map. Hereinafter, each _control area_ is inflated with a polygon to check for the object intersection so that the system knows how many vehicles are located inside each _cluster_, providing a matching mechanism to track with respect to the map new incoming vehicles. It is worth mentioning that the generation of the cluster is dependent on the emplacement; therefore, the automatic recognition tool implemented is expected to render different results depending on the HD Map information. For intersections, the system  
Figure 3: Surveillance areas for each respective traffic emplacement.  
searches automatically for intersection-type lanes within the radius provided. For the roundabouts, the system searches for entries adjacent to an intersection lane whose distance is minimal.
# Preparation Techniques of TiO\({}_{2}\) Nanofluids and Challenges: A Review
## 2 Preparation Methods
### Single Step Method
#### 2.1.1 Vapor Deposition  
[PERSON] and [PERSON] [38] developed the vapor deposition (VDP) method in 2001, and this is the most used single step method in recent decades. As shown in Figure 3, a thin layer of base fluid is formed on the vessel wall under the action of the centrifugal force of the rotating disc. The material is heated and evaporated in a container filled with an inert gas at low pressure. Nanofluid is obtained when the vapors of the raw material are condensed via interaction with a thin film of swirling water and settle in the base fluid.  
Figure 1: Classification of preparation methods.  
Figure 3: Schematic diagram of vapor deposition method.  
Figure 2: Single step method.  
The pulsed wire evaporation (PWE) method is an improved single-step vapor deposition method used to prepare nanoparticles with higher thermal characteristics. Experimental apparatus is comprised of four central components: an evaporation/condensation chamber, a high voltage dc power supply, a capacitor bank and a high voltage gap switch. A thin wire of titanium that is induced in the reaction chamber is evaporated into the plasma within a few microseconds when the pulsed high voltage drives through the wire. The inner wall of the reaction chamber is covered with base fluid and a nozzle spray system in which the exploited wire nanoparticles are condensed by direct contact with the base fluid without any surface contamination. [PERSON] et al. [39] prepared ethylene glycol based TiO\({}_{2}\) nanofluid by using the pulsed wire evaporation method. Pure titanium nanowire with a diameter and length of 0.5 mm and 100 mm, respectively, was used during experimentation. Ethylene-glycol, comprising nanoparticles of size less than 100 nm were successfully prepared with enhanced thermal conductivity. Results showed that the thermal conductivity of the prepared nanofluids was enhanced by increasing the volume concentration of nanoparticles but no particular effect with temperature variation was noticed.  
The vapor deposition method is mostly used in the preparation of nanofluids but is also less commonly employed in the case of TiO\({}_{2}\) nanofluids because it required a higher temperature to evaporate the material placed in the evaporation chamber. The VDP technique was further extended by introducing the laser ablation method and sub-merged arc method that removes the limitation of evaporating the materials, which requires higher temperature during the preparation process.
###### Abstract  
This paper proposes a coordinated active-reactive power optimization model for an active distribution network with energy storage systems, where the active and reactive resources are handled simultaneously. The model aims to minimize the power losses, the operation cost, and the voltage deviation of the distribution network. In particular, the reactive power capabilities of distributed generators and energy storage systems are fully utilized to minimize power losses and improve voltage profiles. The uncertainties pertaining to the forecasted values of renewable energy sources are modelled by scenario-based stochastic programming. The second-order cone programming relaxation method is used to deal with the nonlinear power flow constraints and transform the original mixed integer nonlinear programming problem into a tractable mixed integer second-order cone programming model, thus the difficulty of problem solving is significantly reduced. The 33-bus and 69-bus distribution networks are used to demonstrate the effectiveness of the proposed approach. Simulation results show that the proposed coordinated optimization approach helps improve the economic operation for active distribution network while improving the system security significantly.  
active distribution network; dynamic coordinated optimization; distribution generation; energy storage system; mixed integer second-order cone programming Article
## 3 Results
### HMSIW CP Slot Antenna  
The fabricated HMSIW RHCP slot array antenna is shown in Figure 9. The dimension including the bottom metal layer was \(143.8\times 10.1\times 0.254\) mm\({}^{3}\) (\(11.46\lambda_{0}\times 0.80\lambda_{0}\times 0.0202\lambda_{0}\)). It comprised a pair of \(-45^{\circ}\) and \(+45^{\circ}\) LP antennas, a circular polarizer, and a 180\({}^{\circ}\) transmission line. As depicted in Figure 10, the circular polarizer was realized using two parallel-connected 0201 flip chip resistors of 100 \(\Omega\) for the 50 \(\Omega\) termination at port 4, to reduce the parasitic effect on the K-band application. The input signal was excited at port 1 and divided by the designed circular polarizer into two signals with the relative phases of \(0^{\circ}\) and \(90^{\circ}\) at ports 2 and 3, respectively (Figures 9 and 10). Both signals at ports 2 and 3 propagated on the transmission lines with the relative phases of \(0^{\circ}\) and \(180^{\circ}\), respectively (Figure 9), and excited the \(-45^{\circ}\) and \(+45^{\circ}\) LP antennas with the relative phases of \(0^{\circ}\) and \(270^{\circ}\), respectively. Consequently, an RHCP radiation pattern was formed. When port 1 was 50 \(\Omega\) terminated, and port 4 was used as the input port, an LHCP radiation pattern was generated.  
The fabricated circular polarizer provided the gain imbalance and isolation of less than 0.4 dB and more than 21.4 dB, respectively, and the HMSIW RHCP slot array antenna has a wide 15-dB BW, as shown in Figure 11. The radiation patterns of the HMSIW RHCP slot array antenna were measured with Friis radio link formula and compact antenna test range and shown in Figure 12. Friis radio link formula is expressed as follows:  
\[P_{r} = \frac{G_{t}G_{r}\lambda^{2}}{(4\pi R)^{2}}P_{t}, \tag{4}\]  
where \(P_{r}\), \(P_{t}\), \(G_{t}\), \(G_{r}\), and \(\lambda\) are the received power, transmit power, transmit antenna gain, receive antenna gain, operating wavelength, and a distance between both antennas, respectively. The simulated results are based on an ideal circular polarizer. The HMSIW RHCP slot array antenna provides a gain of 8.57 dBic, an axial ratio (AR) of 3.4 dB, a half-power beamwidth (HPBW) of 5\({}^{\circ}\), a side-lobe level of 8.4 dB, and a co-to-cross-pol ratio of 12.3-20.1 dB within the HPBW at the frequency of 23.9 GHz in measurement. The discrepancies between the simulated and measured gains would be mainly attributed to the performance of the fabricated circular polarizer, manufacturing tolerances, and conductor and dielectric losses in the K-band.
## 2 Theoretical Background and Related Work
### Sensing Technology and Soft Computing Applications  
The rapid advancement of wearable technology has led to a shift from purely physiological monitoring to emotional awareness and social interaction. According to Gartner's [31] market research, this evolution reflects the growing recognition of the need to integrate social and emotional elements into technological solutions for the elderly.  
Project Jacquard [32] represents a significant breakthrough in soft sensing technology integration. By successfully incorporating touch control functionalities into traditional fabrics, while maintaining their original textures and wearing experiences, it demonstrates the feasibility of seamless technology integration. This project's success lies in three key aspects: (1) material properties--maintaining the warmth, comfort, and flexibility of traditional textiles; (2) interaction design--developing natural operation methods with immediate feedback; (3) technical integration--achieving the seamless integration of technology within daily objects.  
[PERSON] et al. [24] systematically reviewed various sensing technologies for elderly care applications, particularly focusing on fall detection and activity monitoring. Their analysis of both wearable sensors and environmental sensors provides valuable insights into the technical requirements for elderly-centered design. They emphasize that successful sensing technology must balance sensitivity and comfort, particularly when integrated into daily objects.  
The application of capacitive sensing in soft materials presents unique challenges and opportunities. Research has shown that careful consideration of the material properties and sensor placement is crucial in maintaining both functionality and user comfort. This is particularly important for elderly users, where comfort and familiarity with materials can significantly impact technology acceptance.  
[PERSON] and [PERSON] [33] discovered that emotional touch interaction does not only exist between humans but can also be effectively established between humans and digital devices through appropriate design. This finding opens up new possibilities for interaction design, particularly in applications requiring an emotional connection. Their research supports our work's emphasis on human-centered design thinking.
## 3 Methodology
### Overview  
The overall framework of the proposed bio-key generation mechanism via deep learning is shown in Figure 2. It mainly consists of the enrollment stage and reconstruction stage. (1) In the enrollment stage, we use a random binary code generator comprised of \(RNG\) to produce the binary code \(K\), and then train a biometrics mapping network to learn the mapping between the original biometric data and random binary code. Specifically, this network includes two components: feature extraction and binary code mapping. Next, the elements of the binary code are shuffled by using a random permutation module to yield a permuted code \(K_{R}\) as the bio-key, meanwhile, the generated permutation vector (PV) is stored in the database. Finally, \(K\) and \(K_{R}\) are encoded to generate auxiliary data (AD) via a fuzzy commitment encoder. Therefore, the PV and AD are only stored in the database during the enrollment process. (2) In the reconstruction stage, a query image is input to the trained network model to generate the corresponding binary code \(K^{*}\). Subsequently, we obtain the stored PV and AD from the database. Next, the query permuted code \(K_{R}\)\({}^{*}\) is generated from the predicted binary code by utilizing the random permutation module with PV. Finally, the bio-key \(K_{R}\) is decoded with the help of AD when the query image is close to the registered biometric image. Otherwise, the bio-key cannot be restored. In the next section, we describe the biometrics mapping network in detail.
## 4 Conclusions  
The catalyst, magnetized activated carbon (MPHAC), was successfully synthesized, and its simultaneous use with persulfate (PS) through the MPHAC/PS system increased the removal efficiency of 4-CP from water, thanks to the simultaneous adsorption and degradation processes. The initial solution pH, catalyst dose and PS dose exerted significant effects on the 4-CP removal. The obtained optimal conditions (MPHAC dose: 1250 mg/L, PS dose: 350 mg/L, and a solution pH of 5) for an initial 4-CP concentration of 100 mg/L and a contact time of 60 min, resulted in a 99.5% removal factor of 4-CP from water. The catalyst has a high stability, and after five successive cycles, the 4-CP removal efficiency decreased by only 10%. The possible mechanism and pathway, in addition to how adsorption and degradation processes affect the removal of 4-CP from the MPHAC/PS system, investigated possible intermediaries created during the reaction. Given the above explanations and the excellent removal of 4-CP from water by the MPHAC/PS system, it can be concluded that the MPHAC/PS system is a type of Fenton-like process that can be used to remove organic compounds, such as phenolic compounds.  
Figure 10: Possible pathway of 4-CP removal by the MPHAC/PS system.  
**Author Contributions:** The individual contributions are provided as follows. Methodology and investigation, S.H. and E.T.; Writing-original draft preparation, S.H., E.T. and M.M.A.; Conceptualization, A.F., E.T. and M.K.; Supervision and project administration, A.F. and E.T.; Writing-review and editing, A.F. and M.K. All authors have read and agreed to the published version of the manuscript.  
Present study funded by the Isfahan University of Medical Sciences (IUMS) of Iran, under Project No. 298169.  
**Data Availability Statement:** Not applicable.  
This study was financially supported by the Isfahan University of Medical Sciences (IUMS) of Iran, under Project No. 298169, with ethical code #IR.MUI.RESEARCH.REC.1398.636.  
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
# Reviews on Corrugated Diaphrags in Miniature Fiber-Optic Pressure Sensors
## 3 The Mechanical Properties of Diaphrags
### Mechanical Properties of the FD  
The deflection of a flat circular diaphragm with clamped edges responding to homogeneous pressure \(P\) is shown in Figure 4, where \(\omega_{0}\), \(R_{d}\) and \(h_{d}\) are the center deflection, the radius and the thickness of the diaphragm, respectively.  
1. Without initial stress  
The deflection of the circular clamped diaphragm without initial stress can be calculated from [41]  
\[P=5.33\frac{E}{(1-v^{2})}\frac{h_{d}^{4}}{R_{d}^{4}}\frac{\omega_{0}}{h_{d}}+2.83\frac{E}{(1-v^{2})}\frac{h_{d}^{4}}{R_{d}^{4}}\frac{\omega_{0}^{3}}{h_{d}^{ 3}}, \tag{2}\]  
where \(E\) and \(v\) are the [PERSON]'s modulus, the Poisson's ratio of the diaphragm, respectively.  
2. With initial stress  
The deflection of the circular diaphragm with clamped edges and initial stress can be calculated by [42]  
\[P=5.33\frac{E}{(1-v^{2})}\frac{h_{d}^{4}}{R_{d}^{4}}\frac{\omega_{0}}{h_{d}}+4 \frac{h_{d}^{2}}{R_{d}^{2}}\frac{\omega_{0}}{h_{d}}\sigma+2.83\frac{E}{(1-v^{2 })}\frac{h_{d}^{4}}{R_{d}^{4}}\frac{\omega_{0}^{3}}{h_{d}^{3}}, \tag{3}\]  
where \(\sigma\) is the initial stress of the diaphragm.  
Figure 4: The deflection of a flat circular diaphragm with clamped edges.  
Figure 3: Schematic of phase demodulation system.  
According to the elastic mechanics, when the central deflection is less than 30% of the diaphragm's thickness, that is, no larger than 20% of the diameter of the diaphragm [17], the small deflection theory could be adopted and the cubic terms of \(\omega_{0}\) in Equations (2) and (3) can be neglected. In this case, the homogeneous pressure \(P\) is linearly related to the center deflection \(\omega_{0}\), and the mechanical sensitivity of the FD with initial stress can be obtained as  
\[S_{m(FD)}=\frac{d\omega_{0}}{dP}=\frac{R_{d}^{2}}{4h_{d}\Big{[}\sigma+\frac{5. 33}{4(1-v^{2})}\frac{R_{d}^{2}}{E_{d}^{2}}\Big{]}}, \tag{4}\]  
In Equation (4), it can be seen that the mechanical sensitivity of the FD depends on the initial stress in the diaphragm, and the smaller the initial stress, the higher the sensitivity. The initial stress of the diaphragm can be reduced by controlling the parameters of the diaphragm deposition process. However, due to the limitations of the manufacturing technology, it is difficult to control the initial stress of the diaphragm accurately [42].
## 5 Results and Discussion  
The test samples have been measured with the methodology described above. The following sections show the results relative to the diffusers tested inside Room A and Room B.  
Measurement Results Undertaken inside Room A--Semi-Anechoic Room Facility at the SCM Group of Rimini  
Diffusing panels made of two different materials (MDF and plywood) and reflecting panels are illustrated in Figure 7. The measurements of diffusing panels were repeated for different configurations, considering the panel in the horizontal and vertical orientation with a reflecting panel as the back. The analysis was carried out to evaluate the acoustic behavior and differences between diffusing panels made of MDF and plywood.  
Figure 7: Diffusing panels made of MDF (**a**), plywood (**b**), and reflecting panel (**c**) tested inside the semi-anechoic chamber in SCM company in Rimini (Room A).  
The graphs shown in Figure 8 represent the variation at the mid-frequencies range of sound pressure levels measured for the four panel's configurations. From the results, it is possible to see that there is a slight difference between diffusing panels made of MDF and plywood and between the vertical and horizontal orientations.  
Figure 9 reports the matching between numerical and experimental data for the Horizontal plywood and MDF panels. From the graphs, it is possible to note that the reflected energy captured by the side microphones (microphone 1 and 25) is far more than expected. Indeed, there is a slight difference between the sound pressure levels recorded by the central microphones and the lateral ones. This is not due to the ability of the panel to reflect a lot of lateral energy, but it might be caused by the small dimensions of Room A that have influenced the measurements, causing reflections able to slant the results. Therefore, we have verified that the semi-anechoic chamber in Rimini is not suitable for detecting the diffusion measurements and ensuring the free field conditions.  
Figure 8: Results for the four panel’s configurations tested inside Room A at mid-frequencies.
# Development Characteristics and Mechanism of Crack in Expansive Soil under Wet-Dry Cycling
## 4 Experimental Study on Mechanical Properties of Expansive Soil under Wetting-Drying Cycles  
### Sample Design and Method  
Based on the results of the wet-dry cycle experiments conducted on expansive soil, medium and highly expansive soil samples were selected. These samples had a compaction degree of 90% and initial water content of 35% and 40%, respectively. A ZJ-type four-joint strain-controlled direct shear test device was utilized to conduct quick shear tests under different wet-dry cycling conditions, with a shear rate of 0.8 mm/min. Previous studies indicate that the shear strength test results of expansive soil under high normal stress conditions tend to be higher. For the case of instability in expansive soil slopes, it can be concluded that the failure mode is mostly shallow landslides, and the force acting on the slip surface generally falls within the range of 50 kPa. Therefore, in the experiments, normal stresses of 5 kPa, 10 kPa, 30 kPa, and 50 kPa were applied to each group of specimens, respectively.  
During the experiment, the expansive soil specimens, subjected to different numbers of wet-dry cycles, were placed in a vacuum saturation apparatus. After being saturated for 24 h, the specimens were considered fully saturated, and were then transferred to the direct shear test apparatus for shear tests. The experiment aimed to determine the attenuation law of strength parameters of expansive soil under different wet-dry cycling conditions, as well as establish a quantitative relationship between shear strength indicators and crack quantification indicators for different normal stress and wet-dry cycle numbers. These data will serve as a reference for understanding the instability mechanism of expansive soil slopes under wet-dry cycling conditions.
## 2 Material and Methods
### Column Mode Adsorption Experiment  
The fixed-bed column used comprised a 2.5 cm inner diameter pyrex glass tube. At the bottom of the column, a stainless steel sieve was attached followed by a layer of glass beads in order to provide a uniform flow of the solution through the column. A known quantity (56 g) of the resin was packed in the column to yield the desired bed height (12 cm). MBR treated water solutions were pumped upward through the column at a desired filtration velocity (2.5 m/h) controlled by a peristaltic pump. The effluents at the outlet of the column were collected at regular time intervals and the major anions present in MBR treated water such as nitrate, phosphate and sulphate concentrations were measured. At the pH of 7.0-7.5 of the MBR treated water there could have been appreciable concentrations of carbonate and bicarbonate in the influent solutions due to absorption of CO\({}_{2}\) from air but the removal of these anions was not studied.  
The breakthrough curves show the loading behaviour of phosphate to be removed from solution in a fixed-bed column. These are usually expressed in terms of adsorbed nitrate, phosphate and sulphate concentrations (C\({}_{\mathrm{ad}}\)), inlet nitrate, phosphate and sulphate concentrations (C\({}_{0}\)), outlet nitrate, phosphate and sulphate concentrations (C\({}_{\mathrm{t}}\)) or normalised concentrations defined as the ratio of outlet nitrate, phosphate and sulphate concentrations to inlet nitrate, phosphate and sulphate concentrations (C\({}_{\mathrm{t}}\)/C\({}_{0}\)) as a function of time. The maximum column adsorption capacity, q\({}_{\mathrm{total}}\) (mg/g) is equal to the area under the plot of the adsorbed phosphate-P concentration, C\({}_{\mathrm{ad}}\) (C\({}_{\mathrm{ad}}\) = C\({}_{0}\) - C\({}_{\mathrm{t}}\)) (mg/L) _versus_ effluent collection time (t, min) and was calculated from Equation (3):  
\[\mathrm{q}_{\mathrm{total}}=\frac{\mathrm{Q}}{1000}\int_{\mathrm{t=0}}^{ \mathrm{t=total}}\mathrm{C}_{\mathrm{ad}}\;\mathrm{dt} \tag{3}\]  
Equilibrium uptake q\({}_{\mathrm{eq}}\) (mg/g) or maximum adsorption capacity of the column is defined by Equation (4) as the total amount of adsorbed nitrate, phosphate and sulphate concentrations (q\({}_{\mathrm{total}}\)) per g of adsorbent (M) at the end of the total flow time:  
\[\mathrm{q}_{\mathrm{eq}}=\frac{\mathrm{q}_{\mathrm{total}}}{\mathrm{M}} \tag{4}\]