esa-sceva/satcom-chunk-collection huggingface dataset:
# Using Coherent Hemodynamic Spectroscopy Model to Investigate Cardiac Arrest
## 2 Methodology
### Experimental Setup, Cardiac Arrest, and CPR  
Female pigs (6-9 weeks old, 33-39 kg) were fasted overnight before being sedated with an intramuscular injection of ketamine (20 mg/kg; \"Ketalean\", Bimeda-MTC Animal Health, Cambridge, ON, Canada). After sedation, the pigs were intubated and maintained under anesthesia with continuous isoflurane (1-3% mixed with oxygen). Ventilation was supported using an Ohmeda ventilator (Ohio Medical Products, Madison, WI, USA) with settings adjusted to stabilize physiological parameters such as pH (7.35-7.45), \(\text{PCO}_{2}\) (35-45 mm Hg), and \(\text{PO}_{2}\) (>100 mm Hg). To prevent hypovolemia, normal saline (NS) was administered intravenously through a cannulated ear vein at a rate of 2-4 mL/kg/h. Electrocardiogram (ECG) leads were attached, and defibrillation patches (Zoll Medical, Inc., Chelmsford, MA, USA) were applied to monitor the cardiac activity. Aortic and right atrial pressures were continuously monitored via femoral artery catheters (Mikro-Tip Transducer; Millar Instruments, Houston, TX, USA), providing real-time data to detect the onset of cardiac arrest (VF) [15]. The intra-experimental and post-death blood samples were taken for the blood gas analyses.  
Before inducing VF, the administration of anesthetic gases was halted for 15 min, and the animals were sedated with propofol and fentanyl to minimize any anti-arrhythmic effects from the anesthetic gases. VF was then induced by burst pacing at a frequency of at least 300 Hz with a 10 mV pulse, using a pacing catheter (AM-2200, AD Instruments, Castle Hill, Australia) inserted into the right ventricle. CPR was initiated after 2 min of VF, consisting of chest compressions at a rate of 100 per minute using an automatic piston device (LUCAS; Physio-Control Inc./Jolife AB, Lund, Sweden). Mechanical ventilation was maintained at a rate of 10 breaths per minute with pure oxygen using the Ohmeda ventilator(Ohio Medical Products, Madison, WI). An intravenous bolus of 0.015 mg/kg of epinephrine in NS (0.1 mg/mL concentration) was administered after 2 min of CPR, followed by a 10 mL NS flush, with additional doses given every 4 min for a total of three doses. Additionally, a continuous infusion of NS equivalent to the volume of epinephrine was started after 2 min of CPR and continued for a total duration of 12 min.  
All experimental protocols adhered to the guidelines for reporting in vivo experiments [16]. Ethical approval was obtained from the Animal Care Committee of St. Michael's Hospital (Toronto, ON, Canada), and all procedures were conducted in accordance with the Guide for the Care and Use of Laboratory Animals as outlined by the U.S. National Institutes of Health (NIH Publication number 85-23, revised 1996).
## 3 Results
### Statistical Hypothesis Testing Results  
Table 1 includes the results of the main statistical hypothesis testing (\(p\)-values) for each impact point tested at 5 m/s together with the mean and SD of the PLA and HIC for each shell stiffness group. Since all \(p\)-values are much higher than the significance level (0.05), the statistical analysis could not find any significant difference in PLA or HIC variables between the two shell groups at 5 m/s. Therefore, shell stiffness was not found to have an effect on the impact performance of the helmets tested at 5 m/s.  
The same analysis was repeated for the data obtained in the drop tests at 8.2 m/s. As above, Table 2 includes the mean and SD of the PLA and HIC for each shell group together with the \(p\)-value for each impact point tested. In this case, PLA was significantly higher for the soft shell group (\(p\)-value = 0.0381) but only when the testing point was the P location. These results suggest that the effective PLA and HIC values provided by the helmet in drop tests are influenced by other parameters different from the shell stiffness alone.
## 4 Results
### Effect of Nozzle Configuration Under Different Ambient Pressures and Constant Pressure Drop  
Figure 8 shows the influence of nozzle configuration on the rock erosion performance of the SC-CO\({}_{2}\) jet under four ambient pressures and constant nozzle pressure drop, \(\Delta P\). In this group of experiments, \(\Delta P\) was set constant as 30 MPa, and the fluid temperature was set constant as 330 K. The standoff distances increased from 1 to 10. The ambient pressure was sequentially set at 2, 10, 18, and 26 MPa.  
Figure 7: Effect of nozzle configuration on rock erosion volume of the SC-CO\({}_{2}\) jet under different ambient pressures and constant inlet pressure: (**a**) 2 MPa; (**b**) 10 MPa; (**c**) 18 MPa; (**d**) 26 MPa.  
As is illustrated in Figure 8, the ambient pressure has a significant effect on the erosion ability of all the jets discharging from different nozzles though the \(\Delta P\) remains constant. The maximum erosion volume for the three nozzles increases when the ambient pressure is increased from 2 to 10 MPa. Then the further increase of ambient pressure reduces the maximum erosion volume. This suggests that, when the ambient pressure is below the critical pressure 7.38 MPa, the increasing ambient pressure can enhance the rock erosion ability of the SC-CO\({}_{2}\) jet, which is attributed to the increasing density and diffusivity of SC-CO\({}_{2}\) fluid with the increasing ambient pressure. The increase of ambient pressure above the critical pressure can weaken the erosion capability because of the growing fluid resistance [11]. Moreover, when compared to the convergent nozzle, the maximum erosion volumes of the Laval-1 nozzle show an increment of 29.5%, 21.8%, 19.3%, and 16.4%, corresponding to ambient pressures of 2, 10, 18, and 26 MPa, respectively; while those of the Laval-2 nozzle show an increment of 54.6%, 49.2%, 45.6%, and 36.7%, respectively. These data suggest that, when \(\Delta P\) is constant, the enhancement of rock erosion ability of the SC-CO\({}_{2}\) jet caused by the Laval nozzles decreases with the increase of ambient pressure. Besides, it can be observed in the figure that the optimal standoff distances for the three nozzles at ambient pressure of 2 MPa are significantly shorter than that at ambient pressures of 10, 18, and 26 MPa.
# Localization of a BLE Device Based on Single-Device RSSI and DOA Measurements
## 5 Single Scanner-Based DoA Estimation
### Navigation towards the Target BLE Beacon  
The DOA of the BLE beacon signal for two scanning locations that are a small distance (\(d_{\mathrm{ss}}\)) apart is represented by \(\hat{\theta}\). The user can employ this estimation and move in the direction of \(\hat{\theta}\) to take further measurements until they get closer to the BLE beacon. An illustration of navigating towards the BLE beacon by taking measurements at multiple locations can be seen in Figure 5. For this research, we assume that users can physically look for and find the BLE beacon when they are 1 m away.  
Figure 4: Space–time data processing and fusion method for reliable estimation of the RSS profile over heading direction.  
The RSS value received by the scanner is dependent on the transmission power that is set at the BLE beacon. The scanner can receive high RSS values from a distant beacon if the transmission power of the beacon is high. To create a balance between range and power consumption, we set the transmission power of the BLE beacon as 10 dBm. After conducting multiple experiments, we determined the baseline of RSS values to be 65 dBm, which can help identify if the BLE beacon is within 1 m. The scanner device will notify the user that the BLE beacon is nearby when the RSS values are consistently higher than the determined baseline.
# Meso-Scale Simulation of Concrete Based on Fracture and Interaction Behavior
## 2 Finite Element Modeling Method
### Interfacial Transitional Zones (ITZs) and Mortar Internal Interface (MII) Model  
The ITZs and MII are modeled by eight-node three-dimensional cohesive elements (CH3D8). Cohesive elements only allow separation in one specific direction (Figure 3). Therefore, cracks can only propagate along the boundaries of particle elements, which may lead to mesh sensitivity [35]. In the case of control computing cost, the fine and irregular mesh is generated to provide more path choices for the crack propagation and to reduce the mesh sensitivity to some extent [36]. The geometrical (constitutive) thickness of cohesive elements is set to zero to maintain the original geometrical partition. The quadratic nominal stress criterion is adopted to define the beginning of an element's degradation, which is presented as follows:  
\[\left(\frac{t_{n}}{t_{n}^{0}}\right)^{2}+\left(\frac{t_{s}}{t_{s}^{0}}\right) ^{2}+\left(\frac{t_{t}}{t_{t}^{0}}\right)^{2}=1 \tag{4}\]  
Figure 2: Aggregate generation in polar coordinates.  
where \(t_{n}^{0}\), \(t_{s}^{0}\) and \(t_{t}^{0}\) represent the maximum allowable nominal stresses in normal and two shear directions, respectively. Likewise, \(t_{n}\), \(t_{s}\) and \(t_{t}\) represent the values of the nominal tensile stress and nominal shear stresses in two directions, respectively.  
In this paper, linear damage evolution is selected to describe the traction-separation law, for its excellent computing efficiency and high accuracy [37].  
Damage evolution is defined based on the mode I and II fracture energies, which are obtainable from the experiments. Since the model is two-dimensional, the out-of-plane shear failure mode will not happen, and the fracture energy in mode III is not taken into account. Different types of concrete shear experiments have shown that the mode II fracture energy of concrete is about 20 to 25 times larger than mode I fracture energy [22; 38; 39]. The findings are used in the present research.  
Since crack propagation paths are meandering curves at the meso-scale, mixed-mode (I + II) fractures are more general than pure mode I or II fractures in concrete failure. The Benzeggagh-Kenane (B-K) fracture criterion [40] is applied to define the mixed-mode fracture energy. It is given by:  
\[G^{C}=G_{n}^{C}+\left(G_{s}^{C}-G_{n}^{C}\right)\left\{\frac{G_{s}}{G_{n}+G_{s }}\right\}^{\eta} \tag{5}\]  
where \(G^{C}\) is mixed-mode fracture energy, \(G_{n}^{C}\) and \(G_{s}^{C}\) are mode I and II fracture energies, \(G_{s}\) is the sum of shear strain energies in two directions, \(G_{n}\) is strain energy in the normal direction, and \(\eta\) is the material parameter. Since tearing mode fracture will not happen in the 2D models, \(G_{s}\) is equal to in-plane shear energy. \(G_{n}\) and \(G_{s}\) of a cohesive element are computed based on the deformation history at integration points in computation, which also relates to the damage evolution of the element [31]. The quadratic nominal stress criterion and mixed-mode fracture criterion are shown in Figure 4.
## 2 Overview of the Proposed Method  
As the relation between the halftone pattern of color plane and the contone value of a specific color plane is a complex nonlinear, a lot of nonexistent values could not be estimated accurately in the building color LUT. In view of the same color halftone patterns corresponding to the similar values of the R, G, B planes as shown in Figure 1, we propose a novel color inverse halftoning method,which uses all common patterns to estimate the nonexistent values in the color LUT. The common pattern is defined as those halftone patterns which have the same halftone patterns in each color table, while their corresponding contone values are not empty. Figure 1 shows the overall framework of the proposed method.  
As shown in Figure 1a, the first step of the color inverse halftoning is to separate a color halftone image into different color component images, such as R, G, B images, while the second step is to get  
Figure 1: The framework of our proposed color inverse halftoning method by multi-color components correlation, (**a**) the process of inverse halftoning, (**b**) the creation of color look-up table (LUT).  
the contone value from the pre-computed LUT. In order to remove the artifacts in the smooth areas of the obtained continuous image, a low-pass filter is introduced for this purpose. Figure 1b gives the generation of color LUT. In a similar way to Reference [14], we first use sample images to build an initial lookup table for each color component, and then estimate the nonexistent values using ELM.  
Compared to the method in reference [14], there are two different aspects of the proposed method as shown in Figure 1b. The first is that the halftone values of all color components are used to estimate nonexistent values. For nonexistent values, we only use those items which have the same halftone patterns in each color component table where their contone values are not empty. The other is that ELM is employed to establish the relation between halftone patterns and their corresponding contone values. A discriminative feature of the proposed method is the introduction of a common pattern, because common patterns can describe the strong relation of color components.
# Experimental Study of Explosion Mitigation by Deployed Metal Combined with Water Curtain
## 3 Results
### Free Field  
The initial overpressure and the maximum impulse obtained through the control gauge for all experiments are presented in Tables 2 and 3, respectively. These measurements showed that there was rather good reproducibility. The side-on overpressure was estimated with [PERSON]'s and [PERSON]'s formula [12]. The detonation of 2 kg of C4 generates an overpressure of 0.8 bar at a distance of 5 m. The measured values were consistent with this value. Figure 13 presents the overpressure measured on the wall for one test of each configuration. Two or three experiments were conducted for each configuration. Table 2 gives the initial overpressure value obtained in all the tests. According to [PERSON]'s and [PERSON]'s formula [12], the detonation of 2 kg of C4 generates a reflected overpressure of 2.6 bar at a distance of 4.8 m. The measured values were consistent with this value. The overpressure was reduced when one plate was located in front of the wall, in the order of 32-47%. Adding a second plate on the shock wave path led to a stronger attenuation. The initial overpressure was reduced by about 62-66%. When a water film was used, the reflected overpressure on the wall was reduced even more, especially in the case of the one-plate configuration. The reduction of overpressure was about 69-71% and 66-74% for one-plate configurations and two-plate configurations, respectively. The setup using a water wall alone was also evaluated and the reflected overpressure on the wall was not modified. Figure 14 presents the impulse measured on the wall for one test of each configuration and Table 3 gives the maximum impulse values obtained for all tests. The results were similar to those observed for overpressure. \begin{table}
\begin{tabular}{c c c c c} \hline
**Type of Plate** & **Number of Plates** & **Overpressure (Bar)** & **Attenuation (\%)** & **Impulse (Bar\(\cdot\)s)** & **Attenuation (\%)** \\ \hline no plate & - & 22.82 & - & 0.0032 & - \\ no plate & - & 19.48 & - & 0.0040 & - \\ no plate & - & 15.61 & - & 0.0035 & - \\ no plate & - & 15.65 & - & 0.0037 & - \\ no plate & - & 15.73 & - & 0.0034 & - \\ expanded metal & 1 & 9.36 & 48 & 0.0011 & 70 \\ expanded metal & 1 & 7.71 & 57 & 0.0012 & 65 \\ expanded metal & 1 & 10.89 & 39 & 0.0013 & 63 \\ expanded metal & 1 & 10.30 & 42 & 0.0015 & 59 \\ expanded metal & 2 & 4.46 & 75 & 0.0003 & 93 \\ expanded metal & 2 & 4.50 & 75 & 0.0005 & 87 \\ expanded metal & 2 & 5.86 & 67 & 0.0005 & 87 \\ expanded metal & 2 & 4.46 & 75 & 0.0003 & 93 \\ \hline \end{tabular}
\end{table} 
Table 1: Initial reflected overpressure and maximum impulse collected by the sensor inserted in the wall and located 50 mm downstream from the perforated plates for all experiments. The difference from the mean value obtained with the reference tests (no plate) is also given. Figure 12: Reflected pressure (**a**) and impulse (**b**) measured on the wall positioned 50 mm behind either one or two expanded metal plates. One reference test, which was performed without plates, is also shown.
# Whole-Genome Alignment: Methods, Challenges, and Future Directions
## 1 Introduction
Despite the importance of WGA, aligning whole genomes is non-trivial due to the sheer size of genomes, their complex evolutionary histories, and the computational demands of alignment algorithms [8]. For instance, the human genome consists of approximately 3 billion base pairs, posing significant computational challenges such as execution time, memory usage, and management of genomic rearrangements [9]. A multitude of algorithms have been developed over the years to address these challenges [10]. Each algorithm offers a unique approach to WGA and has its specific strengths and weaknesses in terms of computational efficiency, scalability, and alignment accuracy [11]. Therefore, a comprehensive understanding of these algorithms is crucial for researchers when choosing the most suitable tool for their specific tasks [3]. This study aims to provide a comprehensive review of prevalent WGA algorithms, highlighting their algorithmic aspects, methodological underpinnings, and the current challenges they face. We focus on three primary classes of algorithms: suffix tree-based methods, anchor-based methods, and graph-based methods, with an emphasis on recent advancements, including algorithms such as SibeliaZ and BubbZ [4] and innovative methods like PlusV [12] and MAGOT [13]. Our goal is to offer a balanced, comprehensive, and critical view of the current landscape of WGA algorithms, assisting researchers in their choice of suitable algorithms for specific applications. In the following sections, we delve into the classification of WGA algorithms, their algorithmic aspects, recent advancements, and the challenges in whole-genome alignment. We hope that this review will serve as a valuable guide for researchers and practitioners in the field of bioinformatics, genomics, and computational biology [14].
# Research on Multicore Key-Value Storage System for Domain Name Storage
## 4 Evaluation
### Synchronous Method Test  
To test the throughput and the hit rate of different synchronization methods, we conducted experimental tests on three methods: synchronous, asynchronous, and non-synchronous. The way of synchronization means that each operation of each cached sub-table is immediately synchronized to all other sub-tables and the total table. The asynchronous mode refers to the periodic synchronization strategy we propose. Non-synchronization means that each sub-table operates independently on its own core and does not need to be synchronized to any other sub-tables. This is equivalent to a single-core operation. We use our cache replacement method in the experiment. In the experiment, the total size of the cache is 8 GB, and the cache is tested with 17 GB of unique domain names.  
Table 1 shows the insert latency and hit rate of three different synchronization methods. As can be seen from Table 1, the one main multi-proxy approach has a much higher hit rate than the single operation approach does. However, the single operation method has a high throughput. Except when the cache space is sufficient, the asynchronous method is better than the single operation method. Compared with the asynchronous method, the synchronous method has no obvious advantage in the hit rate, but the throughput is very low. Therefore, we believe that our periodic asynchronous synchronization method is the best method.
### Preparation of Composites Based on [M(Salen)] and Carbon Nanomaterials
#### 2.2.2 Features of the Formation of [M(Salen)]/Carbon Nanotubes and [M(Salen)]/Graphene Composites
In the studies referred to, it was mainly MWCNTs that were used as the carbon material, with the preparing composites serving as materials for energy storage. However, this method of composite preparation leads to polymer growth primarily on the outer surface of the carbon nanomaterial, which ultimately restricts the access of the electrolyte to a significant portion of the pores. This restriction leads to a decrease in conductivity at the \"carbon nanomaterial-metal salen\" interfaces, resulting in a deterioration of the electrochemical properties [61]. To overcome this limitation, a technique of carbon nanomaterial presoaking in a metal-salen monomer's highly concentrated solution is utilized to adsorb the complex both on the surface and in the volume of the pores. This technique was first applied to composites of poly-[Ni(Salten)]/porous carbon, poly-[Ni(Salen)]/porous carbon, poly-[Ni(S-CH\({}_{3}\)O-Salen)]/porous carbon [47,115], and subsequently to composites of poly-[Ni(CH\({}_{3}\)-Salen)]/SWCNTs [6] and poly-[Ni(Salen)]/ MWCNTs [116]. The prepared material can then be transferred to a low concentration monomer solution or a solution without monomers for electrochemical polymerization. At the adsorption step, the degree of pore filling in the carbon nanomaterial can be regulated. Afterwards, it can be dried for long-term storage without the loss of the monomeric metal-salen component. An alternative method involves codepositing polymer and carbon material from a mixture of a monomer solution in an electrolyte and a suspension of carbon material, followed by the formation of a composite coating on a conductive electrode [58]. Poly-[Ni(Salen)]/MWCNTs [9], poly-[Ni(3-CH\({}_{3}\)O-Salen)]/graphene [114], and poly-[Ni(3-CH\({}_{3}\)O-Salen)]/N-FLG (nitrogen-doped few-layer graphene) [37] composite films were synthesized using this method. However, this approach has a number of disadvantages associated both with obtaining a uniform dispersion of carbon nanomaterials and with the reproducibility of the structure and, accordingly, the characteristics of the composite. Therefore, to prepare poly-[M(Salen)]/SWCNTs (or MWCNTs) and poly-[M(Salen)]/graphene composites with a uniformly distributed polymer layer on the carbon material surface and pores, as well as high interfacial adhesion at the \"polymer-carbon material\" interfaces, predeposition of carbon material on the conducting electrode, additional functionalization of the surface of the carbon material, and subsequent soaking in a concentrated monomer solution are required steps. As a result, synergistic effects of the two phases may occur, leading to an improvement in a number of properties of the composite and the creation of new functionality. Figure 6: Schematic representation of the formation of [M(Salen)]/carbon nanotubes and [M(Salen)]/graphene composites. Local Atomic and Electronic Structure of [M(Salen)] Complexes, Their Polymers, and Composites with Carbon Nanostructures: X-ray Spectroscopic Data