esa-sceva/satcom-chunk-collection huggingface dataset:
# Mycobacterial Biofilm: Mechanisms, Clinical Problems, and Treatments
## 4 Clinical Problems
### Biofilm-Associated Infections  
Some infections are closely and even directly associated with mycobacterial biofilm and many of them are caused by biomaterials. In Chinese and European cities, mycobacteria account for the largest proportion of bacteria that exist in urban air [72]. They also emerge in hospital water systems and some medical devices, which can lead to nosocomial infections [73; 74]. Nearly half of hospital-acquired infections occur in patients who have received foreign body implantation, such as catheters, cardiac pacemakers, joint prostheses, and prosthetic heart valves, all of which are suitable for biofilm formation [75]. Many rapid-growing mycobacterium species, like _Mycobacterium fortuitum_ and _M. chelonae_, are a menace to public health, colonizing and forming biofilm in intravascular catheters and consequently causing bloodstream infections. Removing the catheters is usually required to end the infections [74]. [PERSON] and colleagues used _M. avium_, _Mycobacterium intracellulare_, _M. abscessus_, and six different kinds of materials (polpropylene, acrylic, silicon, glass, titanium, and steel) to analyze NTM biofilm formation on medical devices. The results showed that these mycobacteria tend to form biofilm around air-liquid interface areas, and materials are factors that influence the amount of biofilm formation [76].  
Another example of biofilm-related infections in hospitals is the infection of _M. Chimera_ on heater-cooler units (HCUs). _M. Chimera_ is a member of the _M. avium_ complex, which grows slowly [77]. HCUs are vital for maintaining a patient's blood temperature during cardiac operations. However, the water tank inside these devices may be contaminated by microorganisms like _M. Chimera_ and its biofilms, making HCUs a place that produces and releases _M. Chimera_ bioaerosols, which can reach surgical sites and the surrounding environment [78; 79]. Measures have been proposed to decontaminate HCUs, but the existence of biofilm makes the process even more challenging [80]. Patients receiving cardiothoracic surgeries always suffer from an increased risk of _M. Chimera_ infection [73], which has high mortality and requires reoperation to be eliminated [81].
###### Abstract  
In the modern technological world, there are several key factors in the construction of sensor networks. These include maximizing the coverage and minimizing the cost of the network. Like any information system, the sensor network must also meet the conditions of survivability. This is why the development of a method for assessing the survivability of the sensor network is also a key factor. The purpose of this study is to develop a method to establish the maximum coverage of the territory of the sensor network at minimum cost with the ability to assess the survivability of the network. Coverage maximization while minimizing the network's cost is achieved by finding the optimal pair of values of the coverage radius and the level of the intersection of coverage areas. These values are found by solving a nonlinear multicriteria optimization problem with the use of the genetic algorithm. The designed method for estimating the survivability of sensor networks takes into account not only the importance of network components but also the bandwidth of the network elements. The result of using the proposed methods is a set of Pareto optimal pairs of values of the radii of coverage and the value of the intersection of the coverage areas. In the case of network survivability assessment, the result, in addition to the percentage assessment, is a set of vulnerable sensors and network communication channels. The proposed network survivability estimation method improved the estimation accuracy by 18% compared to methods used in previous works.  
sensors; sensor networks; area coverage; sensor network cost; sensor network survivability +
Footnote †: journal: Applied  
Article
# Air Traffic Simulation Framework for Testing Automated Air Traffic Control Solutions +
## 2 Proposed Architecture Framework
### Operational Modes
#### 2.3.1 Data Collection Mode  
The foundational mode of the simulation environment is designed for the collection and storage of raw ADS-B data from a specified airspace. Each data point is timestamped using the UNIX format, ensuring the unique identification and chronological sequencing. This data recording capability is embedded in all subsequent operational modes, while also serving as in the primary function of this standalone mode. The ability to utilize pre-recorded historical data mitigates risks associated with disruptions in live ADS-B feeds, thereby enhancing simulation reliability. Moreover, it facilitates repeatable simulations by allowing consistent traffic scenarios to be replayed under varying parameter settings while preserving real-world data fidelity.  
Given the growing interest in data science applications in ATM, the availability of large quantities of traffic datasets are essential. Aircraft trajectory prediction and optimization are among the most prominent use cases, often utilizing machine learning approaches. However, as shown in [26], small changes in input data can mislead deep neural networks, resulting in incorrect predictions due to adversarial attacks. This is a significant concern for safety-critical applications. Moreover, while data-driven regression models can achieve high accuracy, they are particularly vulnerable to such adversarial attacks [27]. By functioning as a standalone data collection module, the proposed framework provides a reliable and robust source of training and validation data for machine learning models. Beyond trajectory prediction, recorded traffic data can support a wide range of data-driven ATM applications. For instance, the machine learning methods described in [28] utilize ADS-B data for flow management optimization.
# Analysis and Evaluation of Performance Gains and Tradeoffs for Massive MIMO Systems
## 6 Conclusions  
The main performance gains in a multi-cell massive MIMO system (array gain, multiplexing gain and spatial diversity gain) are discussed for first time at this work taking into account the effect of pilot contamination on massive MIMO system through these gains. These gains mirror the energy efficiency, spectral efficiency and channel reliability with its effect on the performance of massive MIMO systems. Fundamental tradeoffs among these gains are studied and the present work concludes that all gains cannot be maximized at the same time due to non-orthogonal interference among cells. Our simulation results discussed the effect of pilot interference on the tradeoff between energy efficiency and spectral efficiency. In addition, a comparison is made between imperfect and perfect CSI on array gain and multiplexing gain. Still massive MIMO outperforms because of unlimited number of antennas that makes it powerful to any interference.  
This work was supported in part by National High Technology Research and Development Program (2015 AA015901). I would like to express my grateful and thankful to the Chinese Scholarship Council (CSC) for support and give me the opportunity to study at China.  
[PERSON] and [PERSON] are conceived and worked together to achieve this work, [PERSON] wrote the paper and [PERSON] supervised it.  
The authors declare no conflict of interest.
## 2 Results
### Selectivity Studies
#### 2.3.1 Cross-Reactivity Tests
The very high uptake of **19**, equivalent or higher than **1**, could be attributed to multipoint H-bonding interactions with the MAA FM by virtue of its NH and OH groups, which are H donor/acceptor species, leading to potentially greater binding affinity. Furthermore, analyte **19** is the only test target containing an amine unit that is not part of a ring system, which could mean greater fluxionality, resulting in better orientation within the binding cavity. The semi-covalent MIPs (E16\({}_{\text{MIPCHCI3}}\) and T**16\({}_{\text{MIPCHCI3}}\)) showed a cross-reactivity trend that is similar to the self-assembly MIPs, except for analyte **17**, which recorded high levels of cross-reactivity (XRF's 0.64 and 0.85 for E**16\({}_{\text{MIPCHCI3}}\) and T**16\({}_{\text{MIPCHCI3}}\), respectively) in contrast to its behaviour towards the self-assembly MIPs. Note that the post-polymerisation cleavage of the carbothioate linker of **16** (Figure 5) to release the template moiety leaves a phenol functionality within the cavity capable of interacting with **1** or other complementary analytes. The XRFs for **19** and **20** are slightly lower than those observed with the self-assembly MIPs, thus suggesting a less favourable affinity to the imprinted cavities containing the phenol functionality than with the MAA carboxyl unit. The unexpected high cross-reactivity with **17** could possibly be due to its benzoyl group, which is similar in structure and size to the benzyl group of **1**, that could easily fit the imprinted cavities and interact with the phenol group by pi-pi stacking.
## 1 Introduction
This sensor is simple with respect to its structure and has here been found sensitive towards temperature. A Bragg, or a non-Bragg, band gap can be generated when the incident THz wave frequency matches the geometry of the periodic waveguide. By introducing a cylindrical defect in the middle of the periodic structure of the metal tube, the original periodicity will be destroyed. As a result, a defect state will be generated in the former forbidden band. By analyzing the mode components of the defect state, it has here been found that the Bragg defect state consists of almost all first-order modes, while the non-Bragg defect state (NBDS) is dominated by second-order modes. Furthermore, the bandwidth of the NBDS is found to be much narrower (when compared with the Bragg defect state), which makes it more sensitive to changes in ambient temperature. Gold foil's thermo-optic effect has been studied for a long time. [PERSON] et al. studied the thermally induced multiple photon energy modulations in the surface plasmon of a gold foil [35; 36]. The gold waveguide can undergo thermal expansion and contraction, and it propagates the terahertz beam without any leakage. References [37; 38] describe in detail the dielectric properties and temperature modulations of gold materials using the Drude model. These characteristics of gold materials, and gold waveguides, are important for the development of a THz thermal sensor in the present study (i.e., by using a periodically corrugated gold waveguide). In the following section (Section 2), the NBDS will be introduced in a periodic metal waveguide by using a defect beyond the traditional Bragg defect state. In addition, the development of the temperature-modified Drude model will be presented in Section 3, where the thermal sensing of the proposed waveguide structure will also be discussed. In Section 4, the optimization of the waveguide geometry will be presented, and the corresponding sensing performances will be discussed in further detail. Finally, the major results will be summarized in Section 5.
# PCCAU-Net: A Novel Road Extraction Method Based on Coord Convolution and a DCA Module
## 1 Introduction
### Related Works
At the same time, he improved the cross-entropy function and proposed an adaptive loss function in order to effectively solve the problem of road and non-road areas in training samples [26]. Models like SENet [27] and CCNet [28] incorporate attention mechanisms capable of enhancing semantic segmentation accuracy. Novel attention-based networks, such as CSANet [29], capture long-range dependencies at a lower computational cost. Various other approaches, like HA-RoadFormer [30] and MSFANet [31], further enrich feature representations by leveraging long-range dependencies or multi-spectral data, thereby mitigating the impact of noise and redundant features. [PERSON] [32] effectively obtained pixel values and optimized prediction results by combining residual blocks and attention. [PERSON] [33] proposed a global context-aware and batch-independent network, using a global context-aware network embedded in the encoder-decoder structure to extract complete and continuous road networks. [PERSON] [34] proposed a dual-task end-to-end convolutional neural network, using cumulative convolution and a pyramid scene-parsing pool module, expanding the network reception field, integrating multi-level features, and obtaining richer road information. [PERSON] [35] proposed a new context-enhanced and self-attention capsule feature pyramid network, which integrates context enhancement and self-attention modules, uses multi-scale context attributes and channel information feature enhancement, and enhances the robustness of feature representation. However, existing methods often fall short in adequately fusing multi-scale features [36] and in contextual modeling across encoding and decoding phases [37], thereby limiting their learning capability and attention optimization for road extraction tasks. The development of more effective algorithms for remote sensing image processing remains an area of active research.
# Multi-Modality Cardiovascular Imaging Assessment in Fabry Disease
## 2 Diagnosis: Maximal Wall Thickness and LV Hypertrophy  
### Transthoracic echocardiography  
Transthoracic echocardiography (TTE) is a readily available and accessible imaging modality that is widely used for screening, assessment, and monitoring of cardiac involvement in FD by determining systolic and diastolic function, left ventricular (LV) mass, LV wall thickness (LVWT), presence of left ventricular outflow tract obstruction (LVOTO), and the presence of valvular heart disease [4]. In those with confirmed 'classical' variant FD (in whom leucocyte enzyme activity is less than 5%), Fabry-specific therapy is considered at the point of diagnosis of the phenotype [5]. In those with 'later onset' variants, TTE imaging triggers the initiation of ERT or OCT in patients with a maximum wall thickness (MWT) >12 mm in males and >11 mm in females [6], or an increase in LV mass above the normal range for age and sex (see Figure 1). American and European guidelines on chamber quantification specify that measurements of wall thickness and mass should be performed using 2D echocardiography [7]. Specifically, linear measurements of wall thickness should be obtained by 2D echocardiographic images to avoid oblique sections of the LV (see Figure 1). For LV mass, 2D area-length or truncated ellipsoid techniques are recommended where LV mass is to be measured in an individual over time, especially in cases when LV geometry may be abnormal, as in FD. Unfortunately, recent data have emphasized how highly variable these 2D techniques are, even when used by internationally recognized experts. In a study analysing the measurements of 70 experienced readers from across the world, using 2D images that were in the majority graded as good quality, intramodality inter-reader percentage variability was large (range \(-\)59% to 117% (SD 20%)) [8]. Furthermore, the variability of measuring LV mass using 2D methods is also high, both significantly over-estimating LV mass and with wide inter-observer variability, such that measures can differ to the order of 9-10 g [9]. The advent of 3D echocardiography has made this the technique of choice, mainly because it is the only echocardiographic technique that directly measures myocardial volume. Although data consistently support the use of 3D compared to 2D techniques both in terms of accuracy and reproducibility, variability remains a problem, with 95% limits of agreement in measurement of LV mass still as high as 28%, and inter (7%) and intra-observer (8%) variability much greater than expected [10]. With technical improvements in spatial and temporal resolution that can achieve whole heart, single beat high resolution 3D datasets, this variability is falling to the extent that with semi-automated analysis, variability of repeated measures is below 5% [11]. With artificial intelligence (AI) increasingly used for analysis of data, and technical developments in cardiac ultrasound, it is likely that accuracy will compete with cardiovascular magnetic resonance (CMR) imaging.
# High-Resolution Radio Observations of Five Optically Selected Type 2 [PERSON]
## 3 Observational Data  
### EVN Observations  
We observed the five selected targets (Table 1) with the EVN at 1.7 and 5 GHz, to attempt the detection of mas-scale compact radio components in these LLAGNs. The observations were carried out on 5 June 2015 (5 GHz) and 15 June 2015 (1.7 GHz) under the project code EP093. The total bandwidth of 128 MHz was divided into eight intermediate frequency channels (IFs) containing thirty-two 500-kHz wide spectral channels each, in both left and right circular polarizations. The following 13 radio observatories participated in the experiments: Jodrell Bank Mk2 25-m (Great Britain), Westerbork 25-m (The Netherlands), Effelsberg 100-m (Germany), Medicina 32-m, Noto 32-m (Italy), Onsala 25-m (Sweden), Sheshan 25-m (China), Torun 32-m (Poland), Yebes 40-m (Spain), Svetloe 32-m, Zelenchuckskaya 32-m, Badary 32-m (Russia), and Hartebeesthoek 26-m (South Africa). The data were recorded at 1024 Mbit s\({}^{-1}\) rate and correlated at JIVE. We applied the technique of phase referencing [30] and subsequently pointed the radio telescopes to a nearby bright compact calibrator source and the given target, in a repeated 5-min cycle. Within each cycle, \(\sim\) 3.5 min was spent on the weak target source. The delay, rate, and phase solutions derived for the phase-reference calibrators (J0741+3112, J0956+5753, J1015+0109, J1024\(-\)0052, and J1440+0157) could later be interpolated and applied to the corresponding target source data, to allow for longer coherent integration and thus an improved sensitivity for the weaker LLAGNs. The calibrator-target separations were 0.87\({}^{\circ}\), 0.31\({}^{\circ}\), 1.65\({}^{\circ}\), 0.57\({}^{\circ}\), and 1.57\({}^{\circ}\), respectively. The total on-source integration time for each target was \(\sim\)80 min.
# Influence of Fatigue and Defensive Pressure on Three-Point Jump-Shot Kinematics in Basketball
## 4 Discussion
### Combined Effect of Fatigue and Defense  
The most significant changes in kinematic parameters were observed in the condition combining both fatigue and defensive pressure (CON4). In this scenario, players demonstrated the highest jump height and maintained relatively high shooting accuracy (51%). The elevated jump height in CON4 may be a response to the combined challenge of fatigue and defense, with players likely using the extra elevation to counterbalance the defensive player's position. This finding underscores the adaptability of skilled players, who are capable of modifying their techniques to sustain performance under demanding conditions [38].  
However, the reduction in horizontal displacement in CON4 suggests that while players were able to jump higher, their overall forward movement was constrained, likely due to fatigue. This could have implications for shot selection during games, where players may need to rely more on vertical movement when fatigued, particularly under defensive pressure.
## 4 Proposed Architecture
### Overall Design Architecture  
As can be seen in Figure 12, the overall architecture is divided into Control Plane, Data Plane, kernel space, and hardware. FRR, as a control plane, and VPP + DPDK, as a data plane, are located in user space. However, the Network Interface Card (NIC) is completely in control of DPDK, therefore, the kernel will not be able to see or manipulate it [14; 55]. The main details of this architecture should be mentioned, including Zebra and Router plugins. As shown in Figure 12, Zebra is used in FRR as a software-routing protocol to send messages between VPLS nodes. In fact, Zebra is used to manage the route and forwarding tables in VPLS, as well as routing messages sent between VPLS nodes. In addition, Zebra, as a routing protocol independent of the VPLS protocol, uses protocols such as OSPF or BGP as routing protocols for the network. In other words, Zebra manages routing tables between VPLS using an OSPF or BGP protocol and then sends these tables to VPP so that VPP can send VPLS messages between VPLS nodes. The router plugin is also a tool used in VPP and it allows users to implement a VPLS service on one or more routers using this tool. This tool allows users to set routing parameters, such as default routes or routing protocols, for VPLS.  
One of the advantages of the proposed architecture compared to existing hierarchical structures is that VPLS establishes communication between different devices directly without the need for layer three (routing). In other words, VPLS, using bridging technology, allows different devices in a local network to be seen as a single network independently of each other. In VPLS using VPP and FRR, this local network is managed using routing protocols such as OSPF or BGP. This method is simpler, less expensive, and does not require more powerful processing devices than the hierarchical structure. Also, the implementation of VPLS with VPP and FRR allows traffic between devices in a local network to be sent  
Figure 11: FRR Architecture [18].  
directly without the addition of intrusive routing protocols and at high speed. While in a hierarchical structure, traffic is transferred to another layer through routing protocols, and this can reduce network performance.