esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Dependence of the Kaiser Effect on the Loading Strain Rate
When the loading strain rate is high (\(l_{\rm sr}\geq 10^{-4}\) s\({}^{-1}\)), the AE rate is higher, and the AE number increases abruptly in a short time. The slope of the cumulative quantity of AEs-monitoring time relationship is large and increases rapidly. The reasons for the effect of loading strain rate on the Kaiser effect can be explained as follows. First, as the loading strain rate ascends, growth of the existing microcracks and new cracks are accelerated, accompanied by gradually enlarged internal damage. More AEs are generated and a higher AE rate is induced. Additionally, a large quantity of AEs occurs earlier, which facilitates the appearance of the Kaiser effect. Second, the red sandstone is compactly structured. Under a low loading strain rate, the stress between the internal particles is continuously transferred and adjusted so that initial damage and microcracks within the rock could be sufficiently developed, which gives rise to a low strength of the rock specimen. With a high loading strain rate, it is found that the stress between the particles inside the rock specimen cannot be quickly transferred and adjusted in the yielding process. Thus, the rock strength is increased as the loading strain rate increases [35; 36; 37]. Consequently, both \(\sigma_{\rm AE}\) and the \(FR\) increase, which promotes the possible appearance of the Kaiser effect. Figure 11: _Cont._
# Comprehensive Energy Demand Response Optimization Dispatch Method Based on Carbon Trading
## 5 Optimal Dispatch Model of Integrated Energy Demand Response Based on Carbon Trading
### Objective Function  
The goal of economic dispatch of the integrated energy system is to achieve the lowest operating cost while meeting the demand for electricity, gas, and heat in the system. The objective function of the model can be expressed as  
\[\text{min}C=C_{coal}+C_{W}+C_{IDR}+C_{gas}+F_{C} \tag{25}\]  
where \(C_{coal}\) is the cost of generating electricity for conventional units, including the cost of generating electricity from coal-fired units and gas turbines, \(C_{W}\) is the cost of generating electricity from wind turbines, \(C_{IDR}\) is the demand response cost, \(C_{gas}\) is the cost of purchased natural gas, and \(F_{C}\) is the cost of carbon trading.  
The power generation cost of a conventional unit can be expressed as  
\[C_{coal}=\sum_{t=1}^{24}\sum_{j=1}^{J}\Bigl{(}a_{1}P_{C,j,t}^{2}+b_{1}P_{C,j,t }+c_{1}\Bigr{)} \tag{26}\]  
where \(a_{1}\), \(b_{1}\), and \(c_{1}\) are the cost coefficients of the coal-fired units, and \(P_{C,j,t}\) is the generating power of the \(j\)-th coal-fired unit at time \(t\).  
The cost of wind turbine generation can be expressed as  
\[C_{W}=\sum_{t=1}^{T}K_{W}P_{W,j,t} \tag{27}\]  
where \(P_{W,j,t}\) indicates that the output \(K_{W}\) of the \(j\)-th wind farm at the time \(t\) is the operation and maintenance cost coefficient of wind power.  
The demand response cost can be expressed as  
\[C_{IDR}=\sum_{t=1}^{T}p_{e}\Bigl{|}L_{e,t}^{load}-L_{e,t}^{expect}\Bigr{|}+\sum _{t=1}^{T}p_{g}\Bigl{|}L_{g,t}^{load}-L_{g,t}^{expect}\Bigr{|} \tag{28}\]  
where \(p_{e}\) and \(p_{g}\) are the demand response compensation coefficients of the electric load and gas load, respectively; \(L_{e,t}^{expect}\) and \(L_{g,t}^{expect}\) are the predicted values of the electric load and gas load; and \(L_{e,t}^{load}\) and \(L_{g,t}^{load}\) are the response values of the electrical load and gas load demand.  
The cost of the purchased natural gas \(C_{gas}\) can be expressed as  
\[C_{gas}=p_{gas}\sum_{t=1}^{T}L_{out,t} \tag{29}\]  
where \(L_{out,t}\) is the purchased natural gas volume at time \(t\), and \(P_{gas}\) is the price of natural gas.
# Food and Drinking Water as Sources of Pathogenic Protozoans: An Update
## 12 _Cystoisospora belli_
### Epidemiology of C. belli  
In a study investigating the prevalence of _C. belli_ in resected human gallbladder in a large cohort, the parasite was identified in 9.7% of specimens in a retrospective analysis and 27.3% of specimens in a prospective study, and this organism appeared more prevalent among immunocompetent humans than previously recognized. Therefore, it was proposed that _C. belli_ might be conceived as a commensal organism with a latent presence in the gallbladder, giving rise to symptoms in case of pronounced immunodeficiency or immunosuppression [20].  
In a cross-sectional study involving 156 children suffering from diarrhea or abdominal discomfort in Sulaimaniyah, Iraq, _C. belli_ oocysts, missed by the direct wet mount technique, were detected in 26.92% of cases with the modified ZN staining method. The highest infection rate, 15.38%, was found among male children aged 4-6 years, who lived in an urban area (23.08%) and assumed bottled water (15.38%) [277].  
Vegetables are the main food source of _C. belli_. This was the parasite with the highest contamination rate (16.67%) and mean density (13 ocysts/g) in a study on wet markets and supermarkets of San Jose City, Philippines [278] and the most frequent among parasites contaminating fruit preparations (tamarind water, sliced fruits, and fruit juice) sold in schools in Dhaka City, Bangladesh [279].
# Supervised Learning-Based Image Classification for the Detection of Late Blight in Potato Crops
###### Abstract  
This article presents the application of supervised learning and image classification for the early detection of late blight disease in potato using convolutional neural network and support vector machine SVM. The study was realized in the Boyaca department, Colombia. An initial dataset is created with the acquisition of a large number of images directly from the crops. These images are pre-processed in order to extract the main characteristics of the late blight disease. A classification model is developed to identify the potato plants as healthy or infected. Several performance, efficiency, and quality metrics were applied in the learning and classification tasks to determine the best machine learning algorithms. Then, an additional data set was used for validation, image classification, and detection of late blight disease in potato crops in the department of Boyaca, Colombia. The results obtained in the AUC curve show that the CNN trained with the data set obtained an AUC equal to 0.97; and the analysis through SVM obtained an AUC equal to 0.87. Future work requires the development of a mobile application with advanced features as a technological tool for precision agriculture that supports farmers with increased agricultural productivity.  
classification; image processing; mobile app; precision agriculture; supervised learning +
Footnote †: journal: Medical  
approach can be accurately applied in different geographical areas from where the original dataset was acquired.
###### Abstract  
In this study, a rotor-bearing-runner system (RBRS) considering multiple nonlinear factors is established, and the complex nonlinear dynamic behavior of the coupling system is studied. The effects of excitation current, radial stiffness, and friction coefficient on dynamic characteristics are analyzed by numerical simulation. The research results show that the dynamic properties of the coupling system caused by different nonlinear factors are interactional. With the changes of different parameters, the RBRS presents multiple motion states, including periodic-n, quasi-periodic, and chaotic motion. The increase of the excitation current \(I_{j}\) has a certain inhibitory effect on the response amplitude of the system and makes the motion state of the system more complex, the chaotic motion wider, and the jump discontinuity enhanced. With the increase of radial stiffness \(k_{r}\), the motion complexity of the coupling system increases, the chaotic region increases, the response amplitude increases, and the vibration intensity increases. With the increase of the friction coefficient \(\mu\), the chaotic region increases first and decreases, the different motions alternate frequently, and the response amplitude gradually increases. This study can not only help to understand the dynamic characteristics of RBRS, but also help the stable operation of the generator set.  
RBRS; nonlinear dynamics; mechanical-electromagnetic-rubbing coupling; hydraulic turbine; stability +
Footnote †: journal: Applied Sciences
## 3 Results and Discussion
### Hysteresis Loops  
The hysteresis loops of all the specimens are shown in Figure 8, where the longitudinal rebar yielding point, cover concrete spalling, and longitudinal rebar fracture point are marked. Figure 8 depicts the hysteresis loops of specimens BMRC1 and NEWRC1. It can be observed that the change of materials had a notable impact on the shape of the hysteresis loops as the latter's area was narrow and small in all the NEWRC specimens, thereby dissipating less energy compared to BMRC1. The peak lateral load of BMRC1 was 305.45 kN, whereas the peak lateral load of NEWRC1 was 332.45 kN, which was 9% larger than that of BMRC1.  
In Figure 8, the hysteresis loop of specimens NEWRC1, NEWRC2, and NEWRC3 are also presented. The longitudinal rebar buckling in NEWRC2 and NEWRC3 was observed at an early stage compared to NEWRC1, leading to shear strength degradation. The peak lateral loads of NEWRC2 and NEWRC3 were 12.3% and 4.35% lower than NEWRC1, respectively, indicating that the spacing of transverse reinforcement had a marginal impact on the overall peak lateral load but had a significant impact on the rebar buckling and shear strength degradation.  
Moreover, also in Figure 8, the hysteresis loop of NEWRC1 and NEWRC4 is presented. Due to the doubled axial compression ratio, the peak lateral load of NEWRC4 was 364 kN, i.e., 10% larger than NEWRC1, while the peak drift ratio was smaller than NEWRC1. As the drift ratio level increased, more severe shear strength degradation was observed in NEWRC4.  
When considering Figure 8, the hysteresis loop of NEWRC1 and NEWRC5 is presented. The peak lateral load of NEWRC5 was 337.5 kN, i.e., 1.5% larger than NEWRC1. However, it is worth noting that both the specimens showed similar hysteresis loop shapes regardless of HSR transverse reinforcement strength replacement with NSR.  
Also, in Figure 8, the hysteresis loop of NEWRCF is shown. The hysteresis response and energy dissipation were found to be satisfactory. The force-displacement response was elastic during the initial stage and gradually shifted towards an inelastic response at higher drift ratios. The peak lateral load recorded was 1087 kN, corresponding to a 2% drift ratio. The buckling of the longitudinal rebar was observed around a 6% drift ratio, due to which the specimen's load-bearing capacity and dissipated energy decreased gradually.  
Figure 8: _Cont._
# A Survey of Autonomous Vehicles: Enabling Communication Technologies and Challenges
## 5 Different VANET Technologies Based on Transmission Range
### Medium-Range Communication Technologies
#### 5.2.2 Applications  
DSRC technology enables various applications in V2V communication and V2I communication. Some applications are discussed below.  
* Traffic Safety: DSRC technology can be used to improve traffic safety [162]. It allows vehicles to detect the barriers and to avoid collision accidents on the roads [35]. With the help of DSRC, the vehicle can detect a sharp curve and warn other cars [27]. If an accident happens on the road, the vehicles can transmit an alert message to other vehicles to avoid collisions [28].
* Traffic Management System: DSRC can help establish a traffic management system which includes highway fleet management, safe overtaking, etc. [40]. The vehicles can safely overtake and maintain a desired gap during lane changes [30]. If a particular vehicle wants to change its lane, it will send the request to other vehicles for lane change [14]. Therefore, the vehicle can perfectly manage the traffic using DSRC communication.
* Vehicle Management: DSRC can be used to identify registered vehicles and provide an automatic pass to them. Hence, trespassing with a non-registered vehicle can be blocked [31].
## 2 Basic Principle, Experimental Setup and Results  
This section consists of two subsections. First, a brief explanation of the principle of operation of the MPF used in this experiment is given. Next, the experimental description of the transmission of the digital signals using the filtered microwave band pass windows at 2.1 GHz and 4.2 GHz as electrical carriers is presented.
# Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles
## 3 Delay Tolerant Network Protocols
### Protocol Comparison  
The key differences between the protocols are highlighted in Table 1. If a protocol is replication-aware it indicates that there is a fixed number of copies (replications) within the network and it will not exceed this by making any new copies. Reputation awareness is based upon the data a node retains about other vehicles. In this instance it is concerning how likely a node is to deliver the message to the destination node. If its reputation is better (more likely to deliver the message) then the node will provide the message to it. Social awareness allows nodes to communicate a social status between them, passing data about other nodes to the wider network. This can be done as a part of updating the vector values and changes the likelihood of a vehicle receiving the message. Resource awareness  
Figure 2: Diagram of how the MaxProp protocol works [32].  
protocols consider the resources available to the node and will manage the messages it is carrying based upon the capacity of each vehicle.  
```
start while True do ifContacted Nodethen ExchangeSummaryVector() UpdateDeliveryProbabilities() SortPackets() ifBlack Holethen Drop Messages elseifGreyHolethen ifDropping Messagesthen Drop Messages else ifNext node does not have messagesthen ifNext node is destinationthen Forward messages ifNext node has greater probability of deliverythen Forward Messages with lowest hop count end if else ifNext node does not have messagesthen ifNext node is destinationthen Forward messages ifNext node has greater probability of deliverythen Forward Messages with lowest hop count end
```  
**Algorithm 4** Black and Grey Hole MaxProp Router
## 3 Aircraft Low Altitude Operation Scene
### Low-Altitude Operation Scenarios Supporting Modern Logistics  
With the development of e-commerce, people gradually increased their dependence on logistics services, while the requirements for logistics services also gradually increased. In the past, the traditional logistics mode is more vulnerable to humans, weather, roads, and other aspects of impact, resulting in adverse results and affecting the development of the logistics industry. At present, aircraft are mostly used in cross-regional logistics operations. In a single city, the current use of aircraft for logistics transmission still needs to be developed. The use of aircraft in the city has specific height requirements, and in order to reduce the operating cost at low altitudes, most of them use unmanned aerial vehicles. UAV avionics systems need to focus on radio altitude, network communication, remote monitoring functions, and the development of ground network base stations.
## 4 Experiments and Results
### Abnormal Detection Results
Based on practical considerations, if abnormal  
Figure 11.2 Partial anomaly detection results for the PEMS04 dataset. Figure 11.3 Partial anomaly detection results for the dataset. data is detected both at the beginning and end of a short data collection period, the data measured during this short period is most likely also abnormal. Thus, the situation where two anomalous data points within a short time frame have a large discrepancy, and the data between these points is also classified as abnormal, aligns better with real-world scenarios. This analysis further validates that the anomaly detection method proposed in this paper has higher accuracy.
## 3 Results
### Influence of ASA and/or Anti-Fas Ab Treatment on DCs Phenotype  
DCs were harvested and subjected to flow cytometry phenotypic analysis, which revealed that the number of CD11c+, HLA-DR+, CD80+ and CD83+ DCs was altered in a cell line dependent manner (Figure 7). Lysates derived from HCT116 cells pretreated with ASA and anti-Fas Ab induced more significant changes of DCs' proportions in comparison to HT29-derived lysates. Only the proportion of CD11c+ DCs extended over the level caused by LPS (Figure 7A,B). We could observe the relevantly increased proportion of activated DCs after incubation with lysates prepared with CRC cells incubated with ASA and/or anti-Fas Ab in comparison to control unstimulated cells (iDCs). There were some exceptions, for instance, anti-Fas Ab when used alone often kept the DCs status on the same level as iDCs (Figure 7B,D,E).  
Figure 6: The length [\(\upmu\)m] of DCs expanded from monocytes and incubated for 24 h with LPS or lysates of HCT116 and HT29 cells expanded for 10 days in spherical forms with agonistic anti-Fas antibody (200 ng/mL) and/or aspirin ASA) (2.2 mM or 1.8 mM for HCT116 or HT29, respectively), or 5-FU (50 \(\upmu\)M) in comparison to immature unstimulated DCs (iDCs). DCs incubated with lysates prepared from cancer cells not treated are defined as CONTROL in the Figure. Boxes and whiskers represent min-max, lines–median values. The LPS–stimulated median value of DCs’ length was set on Y-axis. Statistically significant differences were assessed by Kruskal-Wallis test followed by Dunn’s test as a post hoc procedure. (* \(p\) < 0.05 vs iDCs, * p < 0.05 ASA vs ASA/ anti-Fas antibody, # \(p\) < 0.05 vs LPS, \(n\) = 60–80 of each option). Three independent experiments were performed.  
The effect of 5-FU-treated CRC cells on DCs was found very diverse, in some experimental options the proportion of DCs with studied markers was elevated (Figure 7A,C), in other cases-decreased after in vitro modification (Figure 7E,F,H) in comparison to iDCs.  
Figure 7: The effect of cancer cell lysates or LPS on the proportions of CD11c+ (**A**,**B**), HLA-DR+ (**C**,**D**), CD80+ (**E**,**F**) and CD83+ (**G**,**H**) DCs. Data are presented as mean fluorescence intensity (MFI) related to sustained control. Lysates used in these analyses were collected from cultures of HCT116 and HT29 CRC cell lines expanded for 10 days in spherical forms with agonistic anti-Fas antibody (200 ng/mL) and/or aspirin (ASA) (2.2 mM or 1.8 mM for HCT116 or HT29, respectively), or 5-FU (50 uM). The value of LPS–timulated DCs was set on Y-axis with continuous line. DCs incubated with lysates prepared from cancer cells not treated are defined as CONTROL in the Figure. Bars and whiskers represent median \(\pm\) interquartile range. Statistically significant differences assessed by Kruskal-Wallis test were followed by Dunn’s test as a post hoc procedure or U Mann-Whitney test. (* \(p<\) 0.05 vs iDCs, # \(p<\) 0.05 vs LPS). Three independent experiments were performed. M.
# Energy Efficient Constellation for Wireless Connectivity of IoT Devices
## 1 Introduction  
Internet of things (IoT), mobile computing (MC), pervasive computing (PC), wireless sensor networks (WSNs), and, most recently, cyber-physical systems (CPS) are the promising research areas for the future smart world [1; 2]. However, as technology and solutions progress in each of these fields, connectivity and energy consumption are always two of the most hard tasks to be handled [3; 4; 5; 6; 7].  
Both the 5G and the next generation 6G wireless systems aim at dramatically increasing the throughput and latency performances, but also require to address low-power low-rates internet of things (IoT) devices with unseen energy efficiency targets. The desired efficiency requires substantial improvements at all layers. At the physical layer, orthogonal frequency division multiplexing (OFDM) modulation will be likely substituted by the promising filter-bank multi-carrier [8], which breaks the constraints imposed by DFT on the carrier modulating pulse shape. Signal constellation is also a potential field of improvements. As IoT concept spreads, the operational situations where sporadic transmission of burst data become more frequent. Efficient ways to exploit the discontinuity of radio sources may be of interest for several factors, ranging from energy efficiency to reduced radio interference. This work proposes a physical layer approach to burst transmissions management, where the signalling overhead is replaced by a contained increment of error ratio. This tradeoff is analysed in the paper, identifying the operational contexts where the proposed solution is convenient.
## 2 Related Work  
### Technology Acceptance Models  
Technology acceptance models are used to explain how people utilize or accept a particular technology. Intention to use can be considered a predictor of behavior, according to [PERSON] technology acceptance model (TAM) [10]. The TAM is based on [PERSON]'s theory of reasoned action [11], in which behavioral intention is defined as an individual's subjective probability of performing a particular behavior [11; 12]. According to [PERSON], there are three factors that affect technology acceptance: perceived usefulness and ease of use, as well as attitude toward using. Over the years, there have been several extensions of the TAM to improve the predictive accuracy of technology use [13]. The most inclusive model is the unified theory of acceptance and use of technology (UTAUT), which integrates elements from eight different technology acceptance models [14]. It is common to adopt the TAM and the UTAUT to assess the intention of older people to adopt new technologies. [PERSON] et al. [15], for example, formulated a questionnaire based on the TAM to evaluate a mobile health application for hypertension monitoring in order to improve user engagement. However, relevant psychological factors, as well as theories regarding aging, which are crucial in the actual employment of technologies, were not considered in these technology acceptance models. [PERSON] et al. [16] developed an instrument, the Technology Usage Inventory (TUI), which includes key psychological factors to better reflect accessibility, usability and acceptability and is thus intended for older adults. [PERSON] [17] investigated the relationship between usability and mental workload and found that these are two non-overlapping constructs that can be used together to improve the prediction of human performance.
# The Development of a Spaceborne SAR Based on a Reflector Antenna
## 2 Principles and Classification of Reflector Antennas
### Types and Characteristics of Reflector Antennas
#### 2.2.3 Elliptical Reflector Antennas  
Elliptical reflector antennas use an ellipsoidal surface to focus signals, differing from parabolic reflectors by having two distinct focal lengths in orthogonal directions (azimuth and range). As shown in Figure 4a, rays from one focal point reflect to the other, enabling dual-focus operation. The reflector surface is as follows:  
\[Z=\frac{x^{2}}{4 Fa}+\frac{y^{2}}{4 Fr} \tag{13}\]  
where \(Fa\) and \(Fr\) are the focal lengths in the \(x\) and \(y\) directions, respectively.  
Figure 3: Parabolic cylindrical reflector antenna: (**a**) basic configuration; (**b**) beam direction.  
The ellipsoidal geometry enables beam shaping, improved gain distribution, enhanced directivity, and sidelobe control. Although less common in spaceborne SAR systems, elliptical reflectors are valuable for applications requiring custom beam patterns or multi-beam scanning.  
In spaceborne SAR systems, elliptical reflector antennas are mostly used in conjunction with one-dimensional linear phased array feeds. As shown in Figure 4b, the phased array feed is placed on the azimuth focus \(F_{1}\); for the range direction, it is located at the forward out-of-focus position. Elliptical reflector antennas offer dual-focus operation, making them suitable for applications requiring shaped or multi-beam coverage, such as wide-swath monitoring. However, the complex geometry imposes challenges in surface accuracy control and mechanical deployment.