esa-sceva/satcom-chunk-collection huggingface dataset:
# Multi-Domain Communication Systems and Networks: A Tensor-Based Approach
## 1 Introduction
In our work, we consider a multi-linear tensor framework that reveals the latent trade-off that exists between multiple domains. The proposed tensor formulation also leads to joint domain signal processing to control and combat interference across all domains. In [9], a multi-domain extension to [PERSON]'s criterion for zero interference is introduced. In this work, we explore the addition of controlled inter-domain interference to manipulate the spectrum and cross-spectrum of the transmitted tensor signals in the form of tensor partial response signaling (TPRS). The objective of this paper is two-fold. Firstly, it presents original contributions in the form of TPRS and it reveals the domain trade-off in communication systems via a tensor information theoretic perspective. Secondly, in order to convey a more holistic state-of-the-art picture, we also present an overview of closely related tensor concepts and techniques used in communications from recent literature. Essentially, the primary goals of this paper can be briefly summarized as follows:  
* Propose a general tensor framework using the [PERSON] product to model multi-domain communication systems with examples. * Develop tensor partial response signaling for addition of controlled inter- and intra-tensor domain interference for the purpose of spectral and cross-spectral shaping. * Reveal the trade-off between multiple domains and develop a multi-domain beamforming approach through an information theoretic analysis of the tensor channel. * Provide a review of some related tensor applications in communications found in literature to further motivate the tensor perspective. The organization of this paper is as follows: In Section 2, we present a generic system model using the [PERSON] product for a multi-domain communication system where the channel is characterized using a higher order tensor. Several examples from multi-carrier, multi-antenna, and multi-user systems are presented which can be modeled using the proposed framework. In Section 3, we develop the notion of TPRS as a signal processing technique to control the spectrum and cross-spectrum of transmitted signals. In addition, we present a brief review of other tensor-based signal processing techniques found in the literature. Section 4 presents an information theoretic analysis of the tensor channel, a few numerical examples that illustrate the trade-off behavior between domains, and a multi-domain beamforming approach for MIMO Generalized Frequency Division Multiplexing (GFDM). The paper is concluded in Section 5.
# Design and Implementation of a Smart Traffic Signal Control System for Smart City Applications
## 3 Smart Traffic Control System
### Emergency Vehicle Signal Preemption Scenario  
To illustrate the STSC system process, we take the EVSP scenario as an example to discuss in detail the state transition, control algorithms, and information flow among STSC system components. As shown in Figure 4, the EVSP scenarios have seven stages and two state transitions from RSU detecting approaching EV to EV leaving. RSU switches from pre-time mode to EVSP mode if it is the host RSU. The RSU then begins the whole EVSP processes and switches back to pre-time mode after traffic signal compensation, which is designed for compensating the crossing traffic flows stopped by signal preemption.  
In Figure 4, assuming an EV is on duty and approaches to the intersection from the south, the RSU receives the EV message broadcasted from the OBU. Once the EV entering the 802.11p signal coverage range, seven stages will be done to complete the emergency vehicle signal preemption process including detected EV, determined host RSU, traffic signal guarding mode, EV preemption control, EV leaving, signal switch, and traffic flow compensation, then the system state switches back to the original state. Each phase has a specific control algorithm to deal with, which are discussed in the following sections.  
Figure 4: Emergency vehicle signal preemption (EVSP) scenario.
# Research Progress of Polysaccharide-Gold Nanocomplexes in Drug Delivery
## Abbreviations  
* APSs &astragalus polysaccharide
* ARE & antioxidant response element
* ASP &angelica sinensis polysaccharide
* AuNCs &gold nanoclusters
* AuNFs &gold nanoflowers
* AuNPs &gold nanoparticles
* AuNRs &gold nanorods
* AuNSs &gold nanoshells
* BB &Brust-Schiffrin
* BMP-2 &bone morphogenetic protein 2
* CAO &carrageenanan oligosaccharides
* CAT &catalase
* CDT &chemodynamic therapy
* CH &chitosan
* CPPs &cell-penetrating peptides
* CPT &cephalexin
* CPT-11 &irinotecan hydrochloride
* Cs-AuNPs &chitosan capped gold nanoparticles
* CT &computed tomography
* CYP &chinese yam polysaccharides
* DARA &aldehyde/catechol-functionalized hyaluronic acid
* DDS &drug delivery systems
* DNA &deoxyribonucle acid
* DOX & doxorubicin
* DPPH &1,1-Diphenyl-2-picrylhydrazyl radical
* EGFR &epidermal growth factor receptor
* EPI &epirubicin
* EPR &enhanced permeability and retention effect
* EPS & extracellular polysaccharides
* FA & folic acid
* GC &glycol chitosan
* GEM & gemcitabine
* GK &gum karaya
* GOx &glucose oxidase
* GSH & glutathione
* GSH-Px &glutathione peroxidase
* HA & hyaluronic acid
* HACD &cyclodextrin-grafted hyaluronic acid
* HBV &hepatitis B virus
* HECS &hydroxyethyl chitosan
* HER2 &human epidermal growth factor receptor 2
* HIV &human immunodeficiency virus
* HPV &human papillomavirus virus
* HyNA &hyaluronan nanoassembly
* IL-6 & interleukin-6
* iNOS &inducible nitric oxide synthase
* ITME &immunosuppressive tumor microenvironment
* LNT &lentin
* LSPR &local surface plasmonic resonance
* MCF-7 &Michigan Cancer Foundation-7
* MDR & multidrug-resistant
* MMP2 &matrix metalloproteinase-2
* M-M2 pep &M2 pep fusion peptide
* M2-TAMs &M2-type tumor-associated macrophages
# SARAC4N: Socially and Resource-Aware Caching in Clustered Content-Centric Networks
## 2 Literature Review
### Location-Based Caching  
Location-based caching strategies aim to store data at specific nodes across the network to optimize retrieval latency. Several techniques have emerged in this category. Hash-Routing applies hash functions on data identifiers to direct requests toward specific caches, while Cooperative In-Network Caching (CIC) distributes content in equal portions across multiple routers to increase availability and balance load. ProbCache introduces a probabilistic content placement approach along the request path to minimize redundancy. Techniques like Breadcrumbs offer best-effort retrieval by tracking the content path, and the Chunk Caching Location and Searching Scheme (CLS) retains a historical footprint of content access to guide future retrievals. While these methods improve local accessibility and reduce repeated data fetching, they are inherently static and lack adaptability to dynamic social behaviors, node interactions, and real-time resource availability. Moreover, they do not consider node importance or network centrality in cache decisions. These limitations highlight the need for socially and resource-aware strategies like SARAC4N that adapt caching based on both network topology and contextual relevance.  
While location-based caching enhances content accessibility by strategically positioning data across specific nodes, it often lacks adaptability in dynamic network conditions. Techniques like Hash-Routing and CIC assume static or semi-static paths, which may result in underutilized caches or inefficient redirection under node failures. Moreover, these methods rarely account for node-level resource availability or contextual relevance of content. SARAC4N overcomes these limitations by integrating social awareness and real-time resource monitoring, allowing content to be cached not just at fixed locations but at socially and resource-optimal nodes, ensuring both resilience and efficiency.
## 3 Results  
### Identification and Selection of Study Sites  
The applications of interested farmers to participate in the project were 23 in 2017 and 30 in 2018. In 2017, most requests were from the Sardinian southwest region, called 'Sulcis-Iglesiente', while in 2018 the applications came from the rest of Sardinia without the prevalence of any area (Figure 1a).  
Cross referencing these data with the georeferenced information available in the DBSS and SIRA systems [35; 36], 18 candidates sites were selected. Based on the results of the first fast chemical analyses of the soil samplings made in candidate sites, (data not shown) eight candidates were chosen (Figure 1b).  
The sites where the metal contents resulted above the contamination threshold established by the Legislative Decree 152/2006 [44] were considered \"potentially polluted\". Furthermore, the selection of candidate study sites was also made based on the presence of uncontaminated sites in adjacent areas available as \"control\".  
Starting with the 53 applications from farmer who expressed an interest in participating in the project, eight planned experimental sites, that were highly polluted (3), moderately polluted (2) and non-polluted (3), were chosen for the project (Figure 1b). In fact, at the end of the selection phase, only three farmers signed up to join the CANOPAES project. The first farmer decided to participate in conducting three fields, hereafter named Site 2 and Site 3 (both polluted) and Site 4 (not polluted or control). Another farmer participated with a not polluted field (hereafter Site 5). Afterwards a farmer, that was interested in the project, but could not participate until 2019 due to administrative problems, was able to conduct an experimental field (hereafter named Site 1) that was moderately polluted. Finally, two other selected farmers who should have cultivated sites 6, 7 and 8 decided not to participate anymore.  
For these reasons in this study the soils were described for all the 5 sites.
# Real-Time Simulation and Sensor Performance Evaluation of Space-Based Infrared Point Target Group
## 4 Simulation Experiments and Validation  
### Parameter Design  
#### 4.1.1 Walker Constellation Design  
Walker constellations are based on the \(T/P/F\) for distributing the satellites in a constellation [38]. \(T\) is the total number of satellites in the constellation, \(P\) is the number of planes, and F is an interplane phasing designation. The right ascension of the ascending nodes (RAAN) and the mean anomaly of the \(j\)th satellites on the \(i\)th plane are described by Equations (9) and (10).  
\[\Omega_{ij}=2\pi(i-1)/P, \tag{9}\]  
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**Infrared Magnitude** & **Band A** & **Band B1** & **Band B2** & **Band C** & **Band D** & **Band E** \\ \hline
0 & 510.651 & 444.097 & 658.514 & 113.509 & 61.359 & 40.000 \\
1 & 203.285 & 176.790 & 262.147 & 45.187 & 24.426 & 15.924 \\
2 & 80.925 & 70.378 & 104.358 & 17.988 & 9.724 & 6.339 \\
3 & 32.215 & 28.017 & 41.543 & 7.161 & 3.871 & 2.524 \\
4 & 12.825 & 11.153 & 16.538 & 2.851 & 1.541 & 1.005 \\
5 & 5.105 & 4.439 & 6.584 & 1.135 & 0.614 & 0.400 \\
6 & 2.032 & 1.768 & 2.621 & 0.452 & 0.244 & 0.159 \\ \hline \end{tabular}
\end{table}
Table 2: Dynamic range of infrared magnitude of MSX catalog.  
\[M_{ij}=2\pi(j-1)/S+2\pi(i-1)/N \tag{10}\]  
where \(S\) is the number of satellites per plane, \(\Omega\) is the RAAN, and \(M\) is the mean anomaly. In the experiment, we built a Space Tracking and Surveillance System (STSS)-like Walker satellite constellation [39; 40] with four satellite orbital planes and seven satellites in each plane. The main parameters of this constellation are presented in Table 3. The chain analysis reveals the participation of 10 satellites in the simulation scenario's imaging process for the target. Given that the STK scenario imposes a constraint on the quantity of infrared sensors, extraneous satellites were eliminated before the simulation calculation.
## 2 Materials and Methods
### Statistical Analysis  
#### 2.3.1 Extraction of Feature Quantity and Analysis Method  
Figure 1 shows the analysis method employed in this study. Using the recorded elbow joint angle and movement time, we calculated the peak velocity, peak angle ratio,  
Figure 2: The SAMO therapeutic arm motion evaluation and training system in the present study. (**a**) Actuator and control driver unit. (**b**) Display and application for controller with data correction. (**c**) The right-arm robot unit. Three modes of spasticity, rigidity, and relaxation can be switched by the controller application. Elbow joint torque is converted from voltage values of wire-bound actuators. Elbow angle data are estimated from the rotation angle of pulleys tethered to actuators. The endoskeleton of an arm robot is constructed of aluminum alloy, while the outer skin and hand are made from synthetic resin. The spastic, rigid, and relaxed modes are reproduced by adjusting and driving wire-coupled actuators using an application program. In this study, two SAMOs were used: SAMO-A for evaluation and SAMO-B for training. The panel displays SAMO-A. Among the structures and systems of SAMO-A and SAMO-B, (**a,c**) are slightly different. Regarding (**a**), SAMO-A exhibits a “sticky” movement when moving the elbow joint, resembling the movement of muscle tension in stroke patients, but SAMO-B exhibits a mechanical movement akin to a gear. This is slightly different from the movement of muscle tension in stroke patients. Regarding (**c**), SAMO-A has a simplified structure to efficiently express the stroke patient’s muscle tone pathology, but SAMO-B has a structure that imitates human bones.  
and movement time during flexion and extension as features of the therapeutic motion techniques and used them as analysis items. The peak angle ratio during flexion and extension was calculated by dividing the peak angle recorded during each therapeutic motion task by the peak physical angle of SAMO. The peak physical flexion angle and peak extension angle of SAMO were measured as calibration data before measurement. The movement time was defined as the interval from the onset of the exercise to the end of the exercise. The onset of the exercise was defined as the value when the average resting angular velocity for 3 s before the task was continuously exceeded for \(\geq\)50 ms. The end of the exercise was defined as the time when the joint angle became constant after the completion of elbow flexion and extension. To clarify the effect of practice due to differences in practice methods, the peak velocity, peak angle ratio, and movement time during elbow joint flexion and extension were compared between and within the two groups before and after practice using a repeated measures two-way ANOVA. Thereafter, multiple comparisons were performed using the Bonferroni method.
## 4 Coordinated Control Example and Simulation
### Coordinated Control Example
#### 4.1.3 Delay Calculation  
After generating 178 sets of examples, the delays of vehicles in both directions of the arterial road were calculated by the above-mentioned single conversion standard and multi-conversion standard delay calculation methods. The average delays of buses and cars were calculated by the single conversion standard. The standard included two types: by-vehicle and by-bus-line, in which the average delay of cars and buses were calculated by vehicles, and the average delay of cars and buses on each line were calculated by bus lines.
# Advanced Progress of Optical Wireless Technologies for Power Industry: An Overview
## 2 Classification and Progress of Power Industry Optical Wireless Communications
### Modulation Methods of Hybrid Optical Wireless Communications
#### 2.2.2 Hybrid Optical Wireless System in NOMA Mode
Among them, the home gateway assumes the function of connecting with external network or external personal consumption terminal. The controlled terminal in the home network is called network appliance. Each communications unit is interconnected by PLC bus and gateway to realize independent two-way communications. The test results of this system show that 22,953 instructions are sent through the network transmitter for testing, and the network receiver can correctly receive 22,829 instructions, and the correct transmission rate of system instructions is 99.46%, meeting the basic requirements of actual use [50].
# Nanofiber-Based Materials for Persistent Organic Pollutants in Water Remediation by Adsorption
## 5 Adsorbent Regenerability  
Two studies reported the adsorbent desorption and recyclability capacity for further use in the industry, and are reviewed below.  
Nylon 6-Poly(pyrrole) core-shell nanofibers have been investigated for atrazine desorption and adsorbent regenerability [41]. The desorption procedure consisted of successive washing in methanol and deionized water for 5 min each to elute atrazine, followed by air-drying of nanofibers at room temperature. With this procedure, Nylon-Poly(pyrrole) nanofibers demonstrated the same capacity of 2.77 mg/g over five cycles, with a slight decrease of 0.2 mg/g in adsorption capacity observed at the 6 th cycle (Table 4, \(N3\)) [41]. With an adsorption plateau reached after 5 h and a desorption procedure estimated around 3 h, such an adsorbent has a life-span of 37 h at its maximal efficiency. Electrostatic interaction and \(\pi\)-\(\pi\) stacking of electrons had been identified as the two adsorption mechanisms at stake in the uptake of Atrazine by Nylon-Poly(pyrrole) nanofibers [41]. Although absorption of Atrazine would be a recyclability limitation, the methanol wash procedure might also imply methanol adsorption.  
Manganese oxide-cellulose fiber nanocomposites were investigated for the desorption of Toxaphene (Table 16, \(N1\)). Desorption rates were shown to be of 12%, 13% and 25%, respectively, at pH 3, 7, and 11 [111]. The preferential affinity for alkaline pH could suggest the reversibility of the adsorption reaction. Indeed, cellulose and manganese oxide (MnO\({}_{2}\)) were reported in the literature to have an isoelectric point of 2.5 and below 5.1, respectively [119; 120]. At pH 11, both components of the adsorbent material therefore carry a strong negative surface charge, while the decreasing protonation of Toxaphene with increasing pH could suggest that both adsorbent and adsorbate carry a negative surface charge, hence the desorption. However, the desorption protocol followed was not reported [111].
## 7 Summary and Perspective  
The studies reviewed above suggest that tanshinones possess broad range anti-cancer potential through anti-proliferation, pro-apoptosis, anti-angiogenesis, induction of differentiation, and inhibition of adhesion, migration, invasion and metastasis. Tanshinones may also exert their inhibitory actions through modulating of inflammatory and immune responses, inhibiting telomerase, interacting with DNA minor groove and activating p53 tumor suppressor, or regulating specific pathways such as AR (e.g., TIIA, CT) or STAT3 (e.g., CT). Tanshinones can sensitize cancer cells to apoptosis by current therapeutic drugs. Identification of AR pathway as a target of selected tanshinones provides scientific basis for developing new tanshinone-based agents for prostate cancer in the future.  
Cancer-related clinical studies in China suggested potential benefit of tanshinone-containing formulas for cancer patients, yet most of these studies had serious limitations, such as small sample size, absence of necessary control groups, lack of randomization and blinding in trial designs, poorly defined dose-formulation information and content of tanshinones used. Well-designed clinical studies to validate the efficacy of tanshinones in cancer patients await significant efforts to overcome major challenges.  
One challenge is the poor water-solubility and bioavailability of natural tanshinones. The chemical modification approaches discussed above have resulted in improved water solubility in all cases and improved anti-cancer efficacy in some instances such as ATA [116], but inactivated apoptosis potency in others such as STS [301,302]. The ongoing pharmaceutical approach through nanoparticle- or lipid-based delivery formulation may help to improve the delivery and bioavailability of tanshinones. Structure-activity relationship (SAR) investigations have produced some insights into the chemical basis of bioactivities of tanshinones. Computational approaches with defined molecular targets (e.g., STAT3 and CT) combined with cell culture assays are necessary to improve the knowledge of molecular targets. Testing the efficacy of defined tanshinone compounds or their combinations in relevant animal cancer models will be a key to pave the way for clinical translational work.
## 2 Materials and Methods  
### Sampling Area, Plant and Soil Sampling Procedure  
The experiments were conducted on sites (Figure 2) with no direct addition of PTEs in 2019. The plots were in Vatin (49\({}^{\circ}\)31\({}^{\prime}\)03.3\({}^{\prime\prime}\) N 15\({}^{\circ}\)58\({}^{\prime}\)31.9\({}^{\prime\prime}\) E) and Troubsko (49\({}^{\circ}\)10\({}^{\prime}\)14.8\({}^{\prime\prime}\) N 16\({}^{\circ}\)29\({}^{\prime}\)50.2\({}^{\prime\prime}\) E). The two sites belong to research field stations; Vatin is under management of Mendel University in Brno and Troubsko is managed by Agricultural Research Ltd. White sweet clover (_M. albus_) was sown in an amount of 12.0 kg/ha, at a depth of 0.02 m, i.e., 5.85 million individuals/ha. The sowing rate was based on [PERSON] et al. [32]. Plants were not treated with any pesticide. When the adult white sweet clover was 1 year old, four samples of aerial biomass and four samples of underground biomass were collected at the beginning of butonization (formation of flower buds) at BBCH 51 [33]. Soil samples of 100 g in weight were then collected from four places on the plot, and were taken to the laboratory for the determination of some parameters of aerial biomass, underground biomass, and soil.  
Experimental plots in Vatin were located on Cambisol sandy loam, in the central part of Bohemian-Moravian Highland. Climatological parameters were as follows: a mean annual temperature of 7 \({}^{\circ}\)C and mean annual total precipitation amount of 658 mm (long-term mean 1981-2010), and the av. altitude was 540 m a.s.l. Experimental plots in Troubsko were located on Haplic Luvisol in the South Moravia region with an average altitude of 287 m a.s.l., mean annual temperature 8.9 \({}^{\circ}\)C, and total precipitation 525 mm (long term mean 1981-2010).