esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Experimental Setup
### Chassis Dynamometer and Experimental Vehicle  
The test vehicle was operated on an EC system dynamometer as shown in Figure 1. This method is a device for measuring driving force generated from the driving wheels of the vehicle by using the EC method. When the roller is rotated by the car wheel, the flywheel of the belt-connected brake (PAU) is rotated. When a current is applied to the coil of the brake PAU, it is magnetized and becomes an electromagnet, and a magnetic field is formed. This magnetic field generates an eddy current in the flywheel and forms an electromotive force in the direction opposite to rotational direction, and acts as a brake to measure power of the experimental vehicle [15].  
The chassis power-measuring device used in this study conforms to the US BAR97 (Bureau of Automotive Repair) certification standard and supports IM 240 (Inspection & Maintenance Driving Cycle), ASM 2525 (Acceleration Simulation Mode), and CVS 75 (Constant Volume Sampler) modes, which are test modes of gasoline and LPG (Liquefied Petroleum Gas) vehicles according to current South Korean regulations. It also supports diesel vehicle test modes KD147, LugDown3, and NEDC (New European Driving Cycle).  
The TMED type hybrid vehicle is a domestic vehicle and uses a clutch between the engine and motor to control the engine. The engine uses only the motor when starting from stop state and low speed, and only the power of the engine with high efficiency at the constant speed with low load. In a state requiring a large output such as acceleration and gradeability, the engine and motor are used simultaneously to improve fuel economy. Table 1 shows specifications of the hybrid electric vehicle used in this study.  
Figure 1: TMED type parallel hybrid vehicle and chassis dynamometer.
# Mycobacterial Biofilm: Mechanisms, Clinical Problems, and Treatments
## 5 Treatments  
### Drugs Targeting Biofilm  
In the 20 th century, 12 to 13 chemical substances were validated as drugs that can fight TB, of which INH, rifampicin, ethanolutol, and pyrazinamide are first-line drugs usually used in combination. For instance, the combination of INH and pyrazinamide or rifampicin possesses the highest potency [89]. Patients with TB are always required to receive regular treatmentswith first-line drugs for a long period. Short-course chemotherapy has also been used to treat drug-sensitive tuberculosis [89]. However, owing to Mtb's waxy cell wall, slow growth rate, ability to form biofilm, and development of drug tolerance, clearing Mtb infections is challenging, requiring at least 6 months of treatment with traditional drugs [90]. Therefore, novel approaches and drugs with more efficiency, especially drugs that target Mtb biofilm, are urgently needed to cope with drug-resistant TB.  
The recalcitrance of biofilm is phenotypic and reversible [83]; therefore, chemical substances that can either impede biofilm formation or destroy the formed biofilm can make a great contribution to TB treatment (Figure 2). Many features are required for an ideal antib Biofilm agent. It should be able to kill bacterial cells rapidly to prevent them from transforming into biofilm phenotypes in advance, target slow-growing and non-growing cells, penetrate EPS or inhibit its generation, intervene in cell communication in biofilm, etc. [91]. However, it is nearly impossible to discover an agent with all of these features. It would be hopeful to find one that possesses some of these functions or to use them in combination. Here, we discuss a few newly developed antibofilm agents in detail. Their functions and mechanisms are briefly summarized in Table 2.  
Figure 2: Anti-TB treatments in mice based on antib biofilm agents. Three strategies have been reported in current years. (1) Some antib biofilm formation agents, such as DMNP, trehalose analogs, and IDR1018, inhibit Mtb biofilm formation, enhancing the bactericidal activity of traditional anti-TB drugs. (2) Nanoparticles carrying IDR-1018 and traditional anti-TB drugs were coated with the mucus-penetrating agent NAC. After inhalation, it can penetrate host mucus via NAC and reach the infection points, releasing IDR-1018 and anti-TB drugs to prevent biofilm formation and kill planktonic Mtb cells. (3) Nanoparticles carrying cellulase and traditional anti-TB drugs were injected into host blood, which released cellulase and anti-TB drugs with the assistance of ultrasound irradiation. The formed mycobacterial biofilms were destroyed by cellulase, which improved the efficiency of anti-TB drugs. This figure was created with BioRender.com (accessed on 19 June 2024).
## 2 Materials and Methods
### Development and Design Process of the Control System Hardware
#### 2.2.2 EMG Base Station  
The main purpose of the base station is to receive the sensor signal using a time-synchronised wireless protocol that minimises the data latency across sensors. The base station can receive data from 16 wireless sensors simultaneously. The base station is equipped with high-speed USB communication with the PC and has a 64-channel analogue output with an analogue output range of \(\pm\)5 V. It is capable of streaming data to the analysis software and of generating 16 EMG analogue channels for integration with other third-party data acquisition systems. EMG signals are provided by the 68 pin connectors of the base station through the analogue output connectors. EMG signals at these outputs are amplified by a factor of 909 (TRIGNOTM Wireless System User's Guide, 2014) [16]. The output analogue port EMG 1-16 moves through an SCSI I-to-II cable to be transferred to an eight-way connection to gather the reading of eight sensors. The delay of the base station is less than 500 us.
# The Use of Rapeseed Husks to Remove Acidic and Basic Dyes from Aquatic Solutions
## 1 Introduction
The residue from the oil pressing is the so-called rapeseed oil cake, containing the husk and crushed seed kernel. It is usually used as an additive to animal feedstuffs. Seed husks, which account for approximately 20% of rape seed weight [22], can be easily isolated from rapeseed cake. They consist of polysaccharides (cellulose, hemicellulose)--33%; lignin--26%; and proteins--18% [23; 24], which may suggest their potentially high usability in removing both acidic and basic dyes from aqueous solutions. This study examined the possibility of using rapeseed husks as an unconventional sorbent to remove dyes from aqueous solutions. To this end, sorption capacity of rapeseed husks was tested in respect of acidic dyes (Acid Red 18, Acid Yellow 23) and basic dyes (Basic Red 46, Basic Violet 10) popular in the industry.
# Distribution of Magnetic Flux Density under Stress and Its Application in Nondestructive Testing
## 3 Results, Analysis, and Discussion
### Experiments Results  
In this part, the measurement data obtained with the sensor are presented, and they were taken following the experimental procedure outlined in the Materials and Methods section. They provided a dataset for each applied load, where signals were acquired for the three X, Y, and Z directions.  
The collected experimental data are shown in Figure 3. The analysis of the magnetic flux density represented by Figure 3a is somewhat tricky and can lead to confusion if these data are analyzed in terms of \(B_{X}\), \(B_{Y}\), and \(B_{Z}\), and it is complex to evaluate the loading condition of the plate under study. In general, it is difficult to absolutize the magnetic field according to the in-situ state, on account of the geomagnetic field, the background, and the residues, so it is necessary to compare with the reference. To overcome this limitation, a differential magnetic flux density is used, and is computed by:  
\[\Delta B_{\alpha}=B_{\alpha,def}-B_{\alpha,0.00} \tag{5}\]  
where \(\alpha\) means the components X, Y, and Z; \(B_{\alpha,def}\) is the magnetic flux density at each deformation; and \(B_{\alpha,0.00}\) is the magnetic flux density without deformation.  
The back data (magnetic flux density without deformation) were subtracted from the magnetic flux to delete the bias, as presented in Figure 3b, and the resulting data were plotted in terms of \(\Delta B_{X}\), \(\Delta B_{Y}\), and \(\Delta B_{Z}\), which is particularly beneficial in making the changes visible; furthermore, the achieved data reveal the differences that are clearly visible, and show changes in the parameter's values over the surface of the plate, even in terms of amplitude for the applied load.
## 4 Discussion  
The stress distribution achieved by using Raman mapping showed that the residual stress did not increase continuously with the gradual rise in germanium content. The diameter of elemental germanium is larger than that of the silicon, and so is the lattice size of the Ge crystal. In the germanium-silicon layer prepared by reduced-pressure CVE, most silicon maintained its monocrystalline stage according to the Raman FWHM results (shown in Figure 7) and high-resolution TEM image (shown in Figure 7b,d). Therefore, some strain, and hence residual stress, was introduced into the buffer layer. The maximum residual tensile stress introduced by doping Ge in Si was 2.2 GPa, which did not induce any visible break or crack in each layer or interface, because of the birth and propagation of the dislocation, which was coincident with the GeSi alloy growth. Dislocation networks and dislocation loops helped to release the residual stress induced by the change in lattice dimension during the growth of a graded buffer layer where the germanium content increased gradually, which was positive for the reliability and stability of the \(\varepsilon\)-Si structure during its application.  
In the Ge\({}_{\mathrm{x}}\)Si\({}_{\mathrm{1-x}}\) layer, the germanium component started from zero at the Ge\({}_{\mathrm{x}}\)Si\({}_{\mathrm{1-x}}\)/C-Si interface and increased with a linear gradient (shown in Figure 3a), which resulted in a gradual change in lattice constant, avoided a sudden difference in lattice constant at the interface and reduced the mismatch strain and dislocation nucleation density compared with other growth methods. When the epitaxial Ge\({}_{\mathrm{x}}\)Si\({}_{\mathrm{1-x}}\) layer grew accompanied by a linear increase in Ge content, the mismatch strain relaxed gradually, and slowed down the extent of dislocation lines and the formation of dislocation networks. The dislocation lines stopped when the strain energy was released, which made the dislocation networks limited inside the Ge\({}_{\mathrm{x}}\)Si\({}_{\mathrm{1-x}}\) layer and unable to extend into the Ge\({}_{\mathrm{0.2}}\)Si\({}_{\mathrm{0.8}}\) and \(\varepsilon\)-Si. Thus, the growth of the gradient-graded component can be effective for confining dislocations within the buffer layer.  
As shown by the Raman results, the residual stress remained stable and the lattice quality improved inside the relaxed buffer layer. No obvious dislocation existed in this layer in the TEM images. These results proved that it was helpful to reduce the negative effect of germanium, and to improve the liability and performance of the microdevice based on strained-silicon technology.
## 1 Introduction
The emulator is capable of characterising key aspects of the UWAC channel, such as the signal's amplitude profile, attenuation, propagation loss, delay, Doppler spread, and shift. These aspects are critical for designing signal processing techniques, networking protocols, and extracting network topology in UWAC systems. Specifically, we,  
* Combine concepts of damped harmonic classical oscillators [19], Milne's oscillator [20], and acoustic wave equations to formulate a mathematical model for the propagation of acoustic signal through an underwater environment. * Integrate outputs of the mathematical model with wide sense stationary uncorrelated scattering (WSSUS) and SOS-based models for the synthetic generation of channel impulse responses, signal amplitudes, phase change profiles, Doppler frequencies, and the Doppler power spectral profile. * Develop a Simulink-based channel emulator platform that incorporates the oscillator-based mathematical model and WSSUS-based channel sample generation. * Use the developed channel emulator platform, and demonstrate (i) snapshots of channel samples for different scenarios and parameters and (ii) the performance of two example communication systems--(a) the differential \(M\)-ary phase shift keying (DMPSK)-orthogonal frequency division multiplexing (OFDM) system with 1/2-rate Turbo coding for single-transmit-single-receive scenarios; (b) a DMPSK-OFDM system with a 1/2-rate Turbo coding for multiple-transmit-multiple-receive scenarios. For some time now, it has been common practice to conduct measurement campaigns in specific scenarios for which underwater acoustic communications (UWAC) systems are designed. This trend can be attributed to several reasons; (i) UWAC is an emerging field in communications system design, and it is not as well-established as radio frequency (RF)-based communication systems for terrestrial scenarios. (ii) There is no typical UWAC scenario due to the diverse characteristics of the underwater medium and its vastness. (iii) Acoustic communication is not a widely prevalent signal carrier form compared to other technologies. However, throughout the years, emulation platforms for underwater scenarios, such as BELLHOP, have emerged, which can reliably approximate the communication scenario. On the other hand, the idea behind our work is to understand the physics of acoustic waves travelling through water and represent the interaction in a way that is similar to [PERSON]'s equations. [PERSON]'s equations or empirical channel models (such as the Rayleigh fading model) are good enough for designing robust radio frequency (RF) communication systems. Ray-tracing techniques in RF communications also provide detailed maps of specific scenarios; however, they are rarely used when designing general systems. Similarly, we believe that our physics-based simulation platform would be good enough to design reliable UWAC systems.
# Go Wider: An Efficient Neural Network for Point Cloud Analysis via Group Convolutions
## 4 Experiments
### Classification  
#### 4.1.1 Dataset  
We evaluate our classification model on the ModelNet40 benchmark [36]. It contains 9843 training models and 2468 testing models that are classified to 40 classes. We firstly uniformly downsampled all models to 1024 points from a total of 2048 points, and then normalized them into a sphere with radius one. Besides this, in order to improve the overall robustness, we further augmented the training data by means of rotations, by random scaling the sampled points, and by jittering the position of every point using Gaussian noise with zero mean and 0.01 standard deviation.
## 1 Introduction
To address this issue, a 3D EM model of the diode chip is established in HFSS software to accurately characterize the parasitic parameters. Based on the 3D EM model and the co-simulation method, by analyzing different surface channel widths and anode junction areas, the best frequency conversion efficiency can be obtained, thereby finally determining the dimension of the diode chip. The approach adopted in this paper is a combination of 3D full-wave EM simulation and harmonic balanced simulation. Measurements and results about the output capacity of the triplers and the noise temperature of the SHMs agree well with the simulation results.
# Global Resource Scheduling for Distributed Edge Computing
## 1 Introduction
This gap is particularly evident in the following aspects: Firstly, existing optimization models lack generality and a standardized mathematical definition for the global resource scheduling problem in edge computing. Secondly, current optimization scheduling methods need to adequately consider resource diversity and account for constraints on scheduling different qualities of resources. Thirdly, most research falls under static scheduling and needs to consider dynamic parameter changes adequately. Figure 1: The case of large-scale distributed resource migration and scheduling. To address these challenges, this paper introduces a global resource scheduling problem for distributed edge computing and presents a solution algorithm. The primary motivations for this paper include:  
1. Definition of the global resource scheduling problem: In contrast to existing research, this paper incorporates two factors into the optimization objective: resource prices and migration costs. Depending on different application scenarios, migration costs may include latency and load balancing. Innovative constraints, such as the price budget constraint, are introduced within the context of resource scheduling. The paper conducts a computational complexity analysis and proves that the problem is NP-Hard. 2. Ant colony optimization (ACO)-based adaptive dynamic scheduling algorithm: Recognizing the difficulty of solving NP-Hard problems in polynomial time, this paper proposes an ACO-based adaptive dynamic scheduling algorithm. ACO converges quickly and is less likely to get stuck in local optima. However, the method's performance is constrained by parameter settings, and ant colony optimization involves numerous parameters that could be challenging to set manually. Therefore, the paper leverages a particle swarm optimization (PSO) approach to optimize parameters during the ACO process, enhancing the reasonableness of parameter settings for each iteration. 3. Comparative analysis with general methods: The paper conducts a comparative analysis of the proposed algorithm with standard methods, including basic ACO algorithms, genetic algorithms (GA), and ACO-GA algorithms. The algorithms are compared in terms of accuracy and iteration cost. The remainder of this paper is organized as follows: Section 2 presents an overview of the relevant research work. Section 3 defines the global resource scheduling problem and analyzes its computational complexity. Section 4 introduces an adaptive dynamic scheduling algorithm based on the ant colony algorithm and utilizes particle swarm optimization for parameter optimization. Section 5 establishes an experimental platform and conducts a comparative analysis of algorithm performance. Finally, Section 6 provides a summary of the work presented in this paper.
## 3 Results and Discussion
### Durability Properties
#### 3.2.2 Sorptivity Coefficient (SC)  
SC can be defined as the absorption time rate of water by hydraulic cement concrete. It is one of the main properties of concrete for assessing its durability [61]. SC values are given in Figure 10. A similar trend like WA was observed for the results of SC with the varying incorporation levels of MAB and TMAB. For the same age and incorporation level of bentonite, TMAB mixes showed more resistance to sorptivity than MAB-added mixes. Since both WA and SC are functions of porosity and microstructural development of concrete, no significant difference in the results of SC and WA was observed with varying dosages of bentonite. After 180 days, almost all bentonite-added mixes showed higher resistance to sorptivity than CON, whereas after 28 days, up to 25% replacement of bentonite (either MAB or TMAB) with OPC lowered the sorptivity compared to the CON mix.  
Figure 9: Relationship between experimental values of compressive strength (f\({}_{c}\)) and water absorption.  
Similarly to WA, SC has a good relationship with compressive strength; see Figure 11. Both SC and compressive strength are inversely related to each other in an exponential equation; see Equation (3). Since microstructural development and density due to bentonite inclusion leads to reduction in volume and connectivity of pores, these developments can also improve the compressive strength of concrete. Therefore, permeability-related durability and strength parameters are inversely related to each other.  
\[\text{SC}\left(\text{mm}/\text{min}^{0.5}\right)=0.255\times\text{e}^{-0.019 \times f_{\text{c}}}\left(\text{for 7, 28, and 180 days, R}^{2}=0.85\right), \tag{3}\]  
where SC is sorptivity coefficient and f\({}_{\text{c}}\) (MPa) is cylindrical compressive strength of concrete.  
Figure 11: Relationship between experimental values of compressive strength (\(f_{\text{c}}\)) sorptivity coefficient (SC).  
Figure 10: Sorptivity coefficient (SC) test results at days 7, 28, and 180.
# Line Clipping in 3D: Overview, Techniques and Algorithms
## 5 The Proposed Method
### The Steps in Brief and the Pseudocode  
The steps of the algorithm are as follows:  
1. Check, if both endpoints of the line are outside the same side of the rectangular parallelepiped clipping region. If this is true then stop and draw nothing or else proceed to Step 2.
2. Compare each coordinate of each endpoint of the line along with the boundaries of the clipping region (left, right, top, bottom, near, and far). If a coordinate is outside the clipping boundary, then use the boundary coordinate instead and calculate the other coordinates of the endpoint, respectively.
3. Draw the clipped line between the two endpoints.
## 4 Discussion  
### Mechanical Equivalence of Quad-Helix and W-Arch  
The stiffness of the expander, which is equivalent to the bending stiffness of the wire, is proportional to the fourth power of the wire diameter [12]. When changing the wire diameter of the W-arch from 0.036 to 0.032 inches, its stiffness decreased to 62%, as calculated by \((0.032/0.036)^{4}=0.62\). This reduction in stiffness was comparable to that caused by incorporating the helix. Thus, the stiffness of the 0.032-inch W-arch was almost identical to that of the 0.036-inch quad-helix (Figure 5).  
On the other hand, the stress induced in the W-arch (614 MPa) was greater than that in the quad-helix (437 MPa), meaning that the safety margin for plastic deformation was reduced in the W-arch. However, the maximum equivalent stress in the W-arch (614 MPa) was still less than half of the yield stress of stainless steel (1500 MPa), and therefore, the W-arch could be activated without causing plastic deformation [13].  
The arm of the expander requires sufficient stiffness to expand the canine and premolars. If the stiffness is too low, the arm will be elastically deformed by the force applied from the teeth, impeding the desired expansion. Although the arm of the 0.032-inch W-arch was less stiff than that of the 0.036-inch quad-helix, it maintained enough stiffness to allow the desired expansion.  
The expansion patterns achieved by the 0.032-inch W-arch were almost identical to those of the 0.036-inch quad-helix (Figure 7 and Table 1). The deformation of the 0.032-inch W-arch was nearly the same as that of the 0.036-inch quad-helix (Figure 8). In the present simulations, there was no difference in arch-expanding ability between the two expanders. The W-arch can therefore be used in the same way as the quad-helix. From a mechanical standpoint, the W-arch, which has a simpler structure and is easier to fabricate, may be the preferred choice for slow expansion in clinical settings. However, the findings of the present FEM study should be validated by future clinical studies.