esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
With the development of active distribution networks, the means of controlling such networks are becoming more abundant, and simultaneously, due to the intermittency of renewable energy and the randomness of the demand-side load, the operating uncertainty is becoming serious. To solve the problem of source-network-load coordination scheduling, a multiobjective scheduling model for an active distribution network (ADN) is proposed in this paper. The operating cost, renewable energy utilization rate, and user satisfaction are considered as the optimization objectives, and the distributed generation (DG) output power, switch number, and incentive price for the responsive load are set as the decision variables. Then the probabilistic power flow based on Monte Carlo sampling and the chance-constrained programming are used to deal with the uncertainty of the ADN. Moreover, the reference point-based many-objective evolutionary algorithm (NSGA3) is used to solve this nonlinear, multiperiod, and multiobjective optimization problem. The effectiveness of the proposed method is verified in the modified IEEE 33-bus distribution system. The results show that the proposed scheduling method can effectively improve the system status.  
active distribution network; distributed generation; energy storage systems; network reconfiguration; demand-side management; multiobjective optimization Article
# Effect of _Tinospora cordifolia_-Derived Phtocomponents on Cancer: A Systematic Review
## 4 Discussion  
Phytocomponents are natural components capable of exerting a therapeutic effect on disease entities, including cancer. Unlike conventional cytotoxic chemotherapeutic agents, phytocomponents have shown to inhibit cancer cells without eliciting systemic toxicity. _Tc_ is one such plant, whose phytocomponents have shown therapeutic value against several diseases, including cancer [3]. Thus, the present manuscript systematically reviewed the published literature to provide comprehensive data on the effect of _Tc_ on cancer based on both in vitro and in vivo experimental models. Assessment of the in vitro studies has shown _Tc_ to have a potent anti-carcinogenic property based on induction of apoptosis, cell cycle arrest, anti-migratory, anti-metastatic effect, upregulation of cellular senescence and cell  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**S. No.** & **Phytocomponents** & **Part in Use** & **Animals** & **Outcome** \\ \hline \multirow{4}{*}{6} & & & Freshwater air-breathing fish _Channa punctatus_ with & Non-cytotoxic, non-mutagenic, \\  & & & phenolic extract & DNA damage induction by & significant antioxidant \\  & & & nonionic surfactant & activity, genoprotective \\ \hline \multirow{4}{*}{10} & & & & \\  & [20] & & Stems & Swiss albino mice injected & \\  & [20] & & methanol and aqueous & with DMBA & Tumor inhibition \\ \hline \multirow{4}{*}{12} & & & & \\  & & & & \\  & & & extracts & & \\ \hline \multirow{4}{*}{13} & & & & \\  & & & & \\  & & & & \\  & & & & \\ \hline \multirow{4}{*}{14} & & & & & \\  & & & & \\  & & & & \\  & & & & & \\  & & & & & \\  & & & & \\ \hline \multirow{4}{*}{20} & & & & & \\  & & & & \\  & & & & \\  & & & & & \\  & & & & \\  & & & & & \\ \hline \multirow{4}{*}{21} & & & & & \\  & & & & & \\  & & & & \\  & & & & \\  & & & & \\  & & & & & \\  & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 2: _Cont._growth inhibition in cancer cells (Table 1). Assessment of in vivo studies has shown anti-carcinogenic properties in the form of apoptosis induction, decrease in the expression of proliferative markers, an overall reduction in disease burden, and recurrence rate, with a significant increase in the survival rate (Table 2).
# An Efficient Library for Reliability Block Diagram Evaluation
## 1 Introduction  
Reliability is defined as \"the ability of a system or component to perform its required functions under stated conditions for a specified period of time\" [1]. Reliability is often expressed through the usage of probability theory, i.e., it is defined as the probability that the system has successfully performed its required functions in time interval \([t_{0},t)\) given that it was correctly operating at time \(t_{0}\)[2].  
Reliability of a complex system is assessed by using a reliability model. Several reliability models have been developed. These models can be divided into the following two main categories:  
* **Combinatorial models**: they allow to efficiently evaluate reliability under the strong assumption of statistically independent components [3, 4]. These models include Reliability Block Diagrams (RBD) [5, 6], Fault Trees (FTs) [7, 8], Reliability Graphs (RGs) [9, 10] and Fault Trees with Repeated Events (FTREs) [8, 11].
* **State-space based models**: they allow for the modeling of several dependencies among failures, including statistical, time and space dependency, at the cost of a difficult tractability due to the state-space explosion [3, 4]. These models include Continuous Time Markov Chains (CTMCs) [12, 13], Stochastic Petri Nets (SPNs), Generalized Stochastic Petri Nets (GSPNs) and Stochastic Time Petri Nets (STPNs) [14, 15, 16, 17], Stochastic Reward Nets (SRNs) [18, 19] and Stochastic Activity Networks (SANs) [20, 21].  
The expressive power of state-space based models is obviously greater than the one of combinatorial models. On the other hand, expressive power varies among the different combinatorial models [22].  
All models that exploit both the usage of combinatorial and state-space based solutions for the quantitative evaluation are classified as hybrid models and are considered as the state-of-the-art approach to dependability evaluation [3]. Both Dynamic RBD (DRBD) [23, 24] and Dynamic FT (DFT) [25, 26, 27] are hybrid models, since they combine CTMC [13] evaluation with, respectively, RBD [6] and FT [8] quantitative analysis. Hierarchical models, i.e., models that combine the usage of different formalisms in order toanalyze the system at different levels, have been proposed in order to both exploit the benefits and to limit the drawbacks of combinatorial and state-space based models [3; 28; 29].  
This paper is structured as follows: Section 1 presents the context and motivation for this work; Section 2 recalls the definition of RBDs and the mathematics used to evaluate them; Section 3 describes the design and optimizations of the implemented RBD computation library; Section 4 presents the materials and the methods used to obtain the results; Section 5 evaluates the performance of the RBD computation library and discusses the results; finally, Section 6 concludes the paper with some final remarks.
# The Effect of Clamping Force on the Wear Behavior of a Steam Generator Tube
## 1 Introduction  
A steam generator (SG) is significant equipment in a pressurized water reactor nuclear power plant through which the heat generated by the nuclear reactor in the primary circuit is transferred to the secondary circuit. Steam generator tubes (SGTs) are the contact surface between the primary circuit medium and the secondary circuit medium, which requires high operational reliability. Once the SGT is damaged, it will cause the radioactive material in the primary circuit to overflow, posing a significant threat to the safety of the surrounding environment [1, 2].  
Affected by flow-induced vibration, SGTs will impact and rub against anti-vibration bars (AVBs) in the U-bend region [3]. Once the wear depth of the SGT reaches the limit value, the tube has to be plugged [4, 5, 6]. Many outages of nuclear power plant units caused by severe wear between AVBs and SGTs have been reported. Therefore, the influence of the AVB on wear behavior has attracted many researchers' attention.  
Clearances between AVBs and SGTs are designed below 0.1 mm [7]. However, the uncertainty of clearances due to insufficient manufacturing processes and unforeseen operating conditions will affect the wear behavior of the SGT. For example, the contact force or an unexpected large clearance between the AVB and the SGT will be generated [8].  
The clearance that exceeds a certain limit will cause the tube support to fail. A lot of research has been carried out on the effect of clearance on wear behavior. [PERSON] et al. [9] studied different modes of the SGT under different clearances between a tube and an AVB. [PERSON] et al. [10] used a straight tube to represent a u-shaped tube with the largest radius,studying the dynamic characteristics of a double-span tube by setting different parameters such as clearance and preload.  
Many scholars have carried out fretting wear experiments and finite element analysis to study the effect of contact force [11; 12; 13; 14; 15; 16]. Contact force is one of the most significant factors affecting the wear behavior of the SGT and can change the structural rigidity of the tube [17; 18].  
Contact force will change the sliding distance, and it is difficult to accurately illustrate the wear law with only a single variable. In this paper, contact force is represented by clamping force. The effect of clamping force on wear is measured by friction energy, which is affected by clamping force and sliding distance.  
Wear experiments are carried out in this study, combined with tube motion based on finite element analysis, to study the dynamic wear behavior of the tube under different clamping forces. Long tube specimens of 4 m length are used in this work. In addition, the natural frequency of the tube is presented.
###### Abstract  
In industrial fields dealing with high-temperature and high-pressure gas such as chemical, petrochemical, and offshore oil production plants, piping systems with valves are frequently used to protect the relevant system and equipment from being damaged by such gases. However, excessive noise is sometimes generated by the valve flow in the piping system, causing so-called acoustic induced vibration in the pipe wall. Therefore, it is of great importance to design the related system to avoid this phenomenon. In this study, a high-fidelity numerical procedure is proposed to assess the acoustic power generated by pressure relief devices in a pipe. The method consists of three sequential steps: high accuracy large eddy simulation, wavenumber-frequency transform, and duct acoustic theory. The critical nozzle is selected as a target system since it is commonly used as a flowmeter and thus there are a lot of relevant data for comparison. First, the steady Reynold-Averaged Navier-Stokes (RANS) solver is used to predict the flow rate of the two-dimensional axisymmetric critical nozzles, and its validity is confirmed by comparing the predicted results with the measured ones. There is good agreement between the two results. Then, a high accuracy Large Eddy Simulation (LES) technique is performed on the three-dimensional critical nozzle, and the steady-state RANS result is used as the initial condition to accelerate the convergence of the unsteady simulation. The validity of the unsteady LES results is also confirmed by comparing them with measured surface pressure data. The wavenumber-frequency transform is taken on the LES results, and the compressible surface pressure components matching the acoustical duct modes are identified in the wavenumber-frequency pressure diagram. The inverse wavenumber-frequency transform taken on the compressible pressure components leads to the acoustic power spectrum. These results reveal that the current numerical procedure can be used to more accurately predict the acoustic power generated by pressure relief device in the piping system.  
acoustic induced vibration (AIV); critical nozzle; wavenumber-frequency analysis; aerodynamic noise 1
## 1 Introduction
These approaches learn complex relationships from data and can capture intricate patterns in vehicle motion and environmental interactions. The advancement of deep learning [4] fields has significantly influenced trajectory imputation in autonomous vehicle systems. Deep learning techniques have demonstrated remarkable capabilities in capturing intricate patterns and dependencies within trajectory data, leading to enhanced prediction accuracy and robustness. Several key techniques have emerged that harness the strength of deep learning models. Recurrent neural networks (RNNs), particularly Gated Recurrent Units (GRUs) and long-short-term memory (LSTM), and several of LSTM's variants, like bidirectional LSTM (Bi-LSTM) [5], attention-based LSTM (AttLSTM) [6], stacked LSTM [7], convolutional LSTM (ConvLSTM) [8], LSTM with temporal convolutional networks (TCNs) [9], and peephole LSTM [10], have gained prominence in trajectory imputation tasks. As we stated earlier, despite advancements in trajectory prediction, accurately imputing pedestrian trajectories remains a significant challenge due to the inherent unpredictability of human movement. Traditional techniques like Kalman filters and particle filters have limitations in handling non-linear and non-Gaussian dynamics, while existing machine learning models often struggle with complex, crowded environments and missing data. There is a critical need for a robust trajectory imputation method that can effectively handle the erratic nature of pedestrian movement and provide accurate predictions in real time. Our research has made the following noteworthy contributions to this field of research:  
* We have explored the challenges and requirements specific to trajectory interpolation for autonomous vehicles, considering the real-time nature and safety criticality of autonomous driving systems. * We have utilized a masking process for converting complete trajectories into incomplete trajectories, which randomly eliminates a certain portion of points. This introduces more uncertainty and randomness, which ultimately enriches the training process. * We have examined the use of LSTM and GRU in the travel path restoration of pedestrians, taking into consideration their propensity for managing temporal dependencies and contextual interactions. * We have designed an encoder-decoder imputation model comprising LSTM blocks for the encoder and GRU blocks for the decoder. * We have evaluated the effectiveness of our model on a curated version of inD dataset, marking one of the earliest instances of research on this dataset for the trajectory imputation task. Section 2 provides an overview of the existing related literature. Section 3 identifies gaps in previous research. The dataset description and preprocessing methods are outlined in Section 4. Section 5 elaborates on the proposed methodology. The experimental results and a discussion are presented in Section 6. Finally, Section 7 presents the conclusions for the study and proposes avenues for future research. Moreover, Table 1 presents the symbols used in this paper.
# Research and Conceptual Design of Sensor Fusion for Object Detection in Dense Smoke Environments
## 1 Introduction
### Data Fusion  
#### 2.4.1 Overview  
The proposed system consists of a 3D ultrasonic sensor system, a thermal IR camera system, and an FMCW radar system. This means that each piece of information from each sensor system is measured in its own coordinate system. Therefore, this measured information must be transformed into a single global coordinate or common plane for sensor fusion. Since the information measured in each of the three types of sensor systems can be regarded as image information taken from different perspectives of the same object, such a transformation can be accomplished with the calibration methods covered by image transformation theory. Therefore, for this transformation, we estimate the homography matrix shown in Figure 8.  
Adopting the calibration method proposed in ref. [42; 43], we simply estimate the homography describing the transformation between the image plane and the radar plane or ultrasound plane, as shown in Figure 8. By using the calibration results and data mapping to the common plane, the proposed sensor system can visualize the information of objects, such as size and position, measured by the FMCW radar and 3D ultrasonic sensor system in an image sequence.
## 4 The Genesis of the Problem  
The choice between the USBL system and the method of dead reckoning based on the accuracy criterion is difficult. In some cases, the USBL system can be identified as being better (e.g., when measurements are carried out in small distances from the transceiver), while in others, the method of dead reckoning (e.g., immediately after updating coordinates by GNSS fixes). If a USBL system is selected, you give up additional COG and SOG. If you choose the DR method measurements \(r\), \(\alpha\), \(\beta\) (range, yaw, pitch) are not taken into account. It is certain that skilful use of a greater number of measurements can improve their accuracy [29].  
In the case of the NS BAUV, the different availability of measurements is assumed, i.e.,  
* at regular intervals of time and with high frequency--the course and speed determined by navigation devices installed on the BAUV (not less than once per second),
* at irregular intervals and with low frequency--the direction and distance to the Transceiver of the appointed USBL system and transmitted by hydro-modem (less than once per second--because of the difficulties in carrying out USBL system measurements and sending the results of these measurements by hydro-modem caused interference in the propagation of acoustic waves in the water).  
These parameters will then be used to determine the position coordinates using the extended Kalman filter (EKF).  
In its action, the filter may combine the various measurements (e.g., the course with the distance to a navigation mark), carried out at different time intervals, taking into account their errors--adjusted dynamically by the matrix of weights. Thanks to this mechanism, measurements which are obviously erroneous (e.g., carried out in the USBL system, on the border of its operation) can be firmly suppressed, and accurate measurements amplified (e.g., SOG and COG determined in a short period of time from the moment of updating the coordinates by GNSS fixes).  
However, will the coordinates obtained by the EKF method, a combination of parameter measurements of BAUV motion and the direction and distance of the USBL system, be more accurate than either the coordinate USBL system or the DR method in all cases?  
The rest of this article presents a study on the positioning accuracy of BAUV by the EKF method compared to the USBL and DR positioning system, aimed at finding answers to the above question.
## 4 Discussion
### Limitation and Prospects  
In terms of data and technology, scenarios' development always entails many limitations and uncertainties [66]. In our work, extrapolating the observed data to future projections would introduce errors under the four scenarios since fine-resolution and local projected meteorological data are rare and inaccessible in APTZNC. So, some down-scaling exercises with the Weather Research and Forecasting Model (WRF) or Statistical Down Scaling Model (SDSM) could be operated to localize large-scale climate conditions to the region context to improve the data accuracy and reduce uncertainty. In the land use allocation module, more socioeconomic factors, like emigration/immigration, could be integrated to address more influences of human activities, especially in the larger scale research. In our further study, employing a process-based ecosystem model, researching to compare (i) the synergy effects of climate and land use on ecosystem functions, and (ii) their relative contributions are proposed to better understand the response of ecosystems.
## 1 Introduction
The DInSAR technique can objectively and reliably solve some limitations of optical data: it works in the presence of clouds, and is also able to do so in the presence of snow, providing information on the activity level of the analyzed landform. However, there are some limitations that must be taken into account. The first is that it does not provide an exhaustive inventory. DInSAR provides Line of Sight (LOS) measurements, i.e., it measures the projection in the satellite-object line of the real displacement. This results in a negligible sensitivity to displacements perpendicular to the LOS, more or less in the North-South direction. The second limitation is SAR geometry. The visibility of a given landform depends on the slope and the aspect. Therefore, in any given satellite trajectory, there will be landforms that are not visible. However, this can be relatively solved by using the ascending and descending satellite trajectories. The last limitation is related to the sensitivity to minimum and maximum displacements. However, this limitation can be partially solved by using the multi-temporal analysis of interferometricpairs. Considering the advantages and limitations described above, the need to integrate optical and SAR data to provide exhaustive and reliable regional rock glacier inventories is worth noting. The region of the Central Andes (Southern Dry Andes) (Figure 1) has one of the densest concentrations of rock glaciers in the world [(20)]. Rock glaciers constitute some of the most significant evidence of mountain permafrost. They are lobate-to-tongue-shaped bodies of permanently supersaturated frozen detrital material with interstitial ice, ice lenses, and massive ice. In an active state, they are characterized by a downslope cohesive flow movement due to their ice content. The moving velocities range from a few centimetres to several meters per year. An inactive state implies that they have no movement, though they still contain frozen material [(21; 22)]. However, despite the climatic, paleoclimatic, mass wasting, and hydrological significance of these landforms in arid and semi-arid regions [(23; 24; 25)], their spatial distribution and dynamics are still not well known. This is particularly critical in the Dry Andes, where there are still areas for which there is no inventory of these landforms. In addition, surveys on surface dynamics are almost non-existent [(26; 27)]. This is a key issue that affects the development of populations located in the basins of these regions, where the water resources, necessary for human consumption and productive activities, are driven by cryogenic processes.