esa-sceva/satcom-chunk-collection huggingface dataset:
# Seismic Response Analysis of a Curved Bridge under Near-Fault and Far-Field Ground Motions
## 4 Test Results
### Displacement of Beam End  
Given that the tops of pairs 1, 3, and 4 are installed with a unidirectional sliding spot bearing, the bearing only produces tangential relative displacement, so the tangential displacement of the beam end is discussed in this part. Table 3 shows the beam end displacement of the curved bridge in the excitation of near-fault and FF ground motions. The beam end displacement is the largest in the excitation of NP ground motions and the smallest in the excitation of FF ground motions.  
When the connecting direction of the two abutments is the same as the EW-direction, due to the rotation of the curved bridge in the excitation of \(\rm X_{P}\), the first beam end has a large displacement. The beam end displacement in the excitation of \(\rm X_{P}+Y_{S}\), the curved bridge rotates significantly in the excitation of \(\rm X_{P}+Y_{S}\), the curved bridge rotates significantly in the excitation of \(\rm X_{P}\) ground motions, resulting in a large displacement at the first beam end. In the excitation of NF and FF ground motions, the displacement of the fourth beam end is significant. The displacement of beam end in the excitation of NP and NN ground motions is 2.26 and 1.18 times that in the excitation of FF ground motions, respectively.  
When the connecting direction of the two abutments is the same as the NS-direction, the curved bridge produces a small rotation in the plane, and the whole bridge model is mainly translational. Owing to the amplification effect of pier height, the beam end displacement at pier 4 is increased. In the excitation of \(\rm Y_{P}\), the beam end displacement for NP and NN ground motions is 1.76 and 1.10 times that for FF ground motions. In the excitation of \(\rm X_{S}+Y_{P}\), the beam end displacement for NP and NN ground motions is 1.62 and 1.12 times that under FF ground motions, respectively.  
The analysis shows that the motion state of the curved bridge affects its beam end displacement. Owing to the rotation generated by the curved bridge, the beam end of the curved bridge produces a large displacement at the lower pier, which increases the risk of the beam falling and a collision between the beam end and abutment. Anti-falling and anti-collision measures should be taken to reduce the damage caused by NP ground motions on curved bridges.
## 5 Role of sRNA in Quorum Sensing  
Bacteria regulate population density through a process known as quorum sensing (QS), which involves the production, release, accumulation, and detection of extracellular signaling molecules termed autoinducers (AIs) [15, 17, 226]. Quorum sensing enables bacterial communities to coordinate responses to chemical signals, promoting cooperative behaviors that enhance fitness [17, 227]. These include coordinated virulence, evading host immune responses, and establishing infections [228]. This mechanism is present in both Gram-positive and Gram-negative pathogens, though the signaling molecules triggering QS circuits differ between them. Gram-positive bacteria typically respond to processed oligopeptides [56], whereas Gram-negative bacteria respond to homoserine lactones as autoinducers [17]. Previous studies on _P. aeruginosa_[229], _S. aureus_[230], and _V. cholerae_[231] reveal that these pathogens use QS to regulate the production of virulence factors, including toxins, proteases, siderophores, and biofilm formation, which enhance their survival within the host. QS also facilitates immune evasion by regulating the expression of immunodulatory molecules, allowing bacteria to remain undetected until they reach a critical population density. Additionally, QS-mediated biofilm formation protects bacteria from antibiotics and immune clearance, contributing to chronic infections [52, 213]. Emerging evidence suggests that host organisms can interfere with QS through quorum quenching, a strategy in which the host degrades or inhibits bacterial signaling molecules to prevent infection. Understanding QS in host-pathogen interactions is essential for developing novel anti-virulence therapies that target bacterial communication without promoting antibiotic resistance.  
This section will explore the mechanism of quorum sensing and its role in bacterial pathogenesis and host-pathogen interactions, focusing on two Gram-negative representatives, _Vibrio_ sp. and _P. aeruginosa_, and one Gram-positive representative, _S. aureus_.
# Progress in Improving Photovoltaics Longevity
## 4 Results
### Mitigation Strategies for BIPV Longevity
The Net Present Value (NPV) index, estimated as the sum of present incoming (benefits) and outgoing (expenditures) cash flows over the lifetime of the investment, is dramatically increased by improving the longevity of the BIPV systems, as can be observed in Figure 7. Future design improvements should focus on mitigating heat and noise transmission, as well as corrosion. Ongoing research should aim to understand the impact of temperature on the electrical properties of BIPV modules, considering factors like material layers and installation angles while also comparing the long-term thermal and electrical performance of BIPV products with conventional building materials (2016). Table 11 summarizes the key aspects related to improving the longevity of BIPV, highlighting the material selection, thermal management, and operational practices, as well as future research directions necessary for enhancing the durability and efficiency of these systems in building applications. \begin{table}
\begin{tabular}{c c c c} \hline
**BIPV Longevity** & **Description** & **Key Features** & **References** \\
**Entance** & **Description** & & **Key Features** & **References** \\
**Strategy** & & & & \\ \hline \multirow{4}{*}{Material selection} & Selecting materials with high thermal stability and low moisture permeability is crucial for BIPV longevity. & – & Advanced encapsulants protect against environmental stressors - Flexible or laminated designs distribute mechanical loads better & [198; 199; 200] \\  & & & - Protective coatings enhance UV resistance and reduce water permeation & \\ \hline \multirow{4}{*}{Thermal management} & Effective thermal management strategies are essential for optimizing BIPV performance and lifespan. & – & Passive cooling methods like ventilated facades help regulate temperatures - Innovative cooling solutions can reduce temperature fluctuations significantly, improving lifespan by up to 21\% - Regular inspections are necessary to identify thermal stress issues early on \\ \cline
# Probabilistic Condition Monitoring of Azimuth Thrusters Based on Acceleration Measurements
## 3 Results and Discussion
### Discussion  
#### 3.3.1 Significance of Results  
Classification results show that the threshold (\(\alpha\)) had a significant effect on the classification accuracy when individual samples were classified. This is seen, for example, with the time domain feature set of thruster 1 while the accuracy varied between 56% (\(\alpha\) = 0.001) and 76% (\(\alpha\) = 0.1). The selection of the threshold is a trade-off between the number of false positives and false negatives. In general, the higher threshold limit (e.g., \(\alpha\) = 0.001) results in the lower the number of false positives, but also the number of false negatives grows. With the low threshold limit (\(\alpha\) = 0.1), the number of false positives increases and the number of false negatives decreases.  
In the light of this challenge, it could be useful to monitor the squared Mahalanobis distance in moving windows, as shown in Figure 11 or Figure 12, thus reducing the variation of the values used for inference. The use of moving mean or median is a standard approach in statistical process control [53]. Alternatively, a long enough segment of consecutive points on the other side of the threshold could indicate the change in condition, as was inferred in [15].  
The accuracy of the \"two distributions\" approach indicates that training separate models for normal and damaged conditions could be useful. However, the fault patterns in the signals should then be relatively fixed in the operational areas monitored, which is not certain, as indicated by the different patterns in Figures 13 and 14. In addition, the separation of the symptoms of superposed faults and other disturbances in signals is also required, unless it is probable that they occur together. Moreover, the correct labeling of each data sample in large data sets used for model training is often unrealizable without a robust automated approach to it.  
Therefore, the classification results are approximate and not a definitive proof of the performance of the methods. A predicted false negative, for example, could be a result of the fact that the sample does not contain characteristics of the defect even though the true label was set positive. This highlights the importance of a well-planned and executed sample selection to obtain significant results [54].
# Optimization of Wiring Harness Logistics Flow
## 3 Results and Discussion
### Methods for Production Waste Collection and Recycling in Wiring Harness Manufacturing
The production waste collection system implemented in the proposed configuration of the assembly line consists of placing the collection bins along the line, as shown in Figure 11.  
The collection bins are emptied regularly into centralized collection bins that are later prepared for transportation to recycling facilities. Figure 11: Integration of a waste collection system within the logistics flow of the hybrid assembly lines. Legend: Waste collection bin. Scrap recycling can be performed within an internal facility or by subcontracting to a specialized company. However, harness manufacturers have also been interested in developing new recycling methods that target production waste coming from wiring harness production. For example, Yazaki Corporation patented a method for recycling waste wire harnesses that took the wiring recycling process a step further. They conceived a method that allows the collection and reuse of magnesium hydroxide. This research's starting point was triggered by replacing vinyl chloride resin wire coating with non-halogen or low-halogen coating. The replacement was needed because it was discovered that vinyl chloride resin releases harmful hydrogen chloride gas, affecting human health. However, since the first usage of non-halogen or low-halogen fire-retardant resin composition as an electrical insulator and wire coating material, a new challenge has arisen regarding the recovery of the magnesium hydroxide, used as a fire retardant, that is found in the new resin type. A preparation step is required before applying the new recycling method, and the wire must be separated from connectors, clips, and protectors [30]. Many methods are applied in recycling wiring harness production waste; recovering as many elements as possible is mandatory for environmental protection and resource usage efficiency. Even though each recycling facility has its process and method, it can be observed that some phases of the recycling process tend to be common. The process mainly consists of removing and sorting the components of a wiring harness according to their material composition using different techniques, like cutting and shredding and applying different techniques to separate plastic from metal parts, such as electrostatic separation [31]. The main goal is to obtain materials with very similar technical characteristics to non-recycled materials, and to integrate them into the production cycle.
# A Literature Survey on Offline Automatic Algorithm Configuration
## 2 Literature Review
### [PERSON] et al. [9] proposed a naturally parallel gender-based genetic algorithm (GGA). Because genetic algorithms are inherently parallel, racing them against each other makes evaluating competitive individuals (the most time-consuming part of algorithm configuration) easier. In other terms, a tournament-based selection mechanism is used for testing the competitive population. They introduced the gender separation method to reduce the high evaluation cost for the genetic algorithm and apply different selection pressure to both genders. Additionally, new candidate configurations are generated by using different sub-populations and a specialized cross-over operator. GGA terminates when the runtime limit is achieved or when the average performance of the population is not further improved [14]. According to their report, parallel evaluation of configurations supports the configuration goal of minimizing algorithm run-time while producing an insignificant loss in performance. For the improvement of this study, they recommend selecting the most important component(s) of GGA for its performance. It can deal with both discrete and continuous parameters and give one best parameter configuration as an output. The GGA method is widely used in tuning literature, for example, in tuning solvers in SAT and mixed-integer programming [20], Max-SAT [21], and machine reassignment [22].  
GGA is extended to GGA++ by using surrogate models with population-based approaches in the study [23]. In GGA++, instead of using random recombination, they developed specialized surrogate models based on random forests and combined them with a genetic algorithm for finding the most promising offspring. After the experiments, model-based GGA outperformed other configurators such as GGA and SMAC for tuning two SAT solvers. [PERSON] et al. [24] suggested a Python tool that implements a distributed version of the GGA, PyDGGA, which maximizes the usage of parallel resources by simulatingfuture generations of the genetic algorithm even before the current generation is completely finished [24].
## 1 Introduction
In other similar fields, reference [19] proposes a rotating grayscale projection method, which obtains the grayscale edge image of the braided composite preform based on phase consistency and non-maximum suppression, and automatic measurement of surface weaving angle and pitch length is completed through gray image rotation projection and block segmentation; Reference [20] proposes a method that uses the 2D-DFT(two-dimensional discrete Fourier transform) to transform the image of a woven fiber into the frequency domain and achieves the measurement of the fiber weave angle using the rotational invariance of the phase. Through a thorough analysis of the above literature, the proposed various testing methods do not apply to the parameter testing of the coils in this paper. One reason is that the surface reflection of the wires used in this paper is serious and the pretreatment is more complicated; another reason is that these methods do not show better advantages for the detection of winding angle and spacing of coils. Based on the above reasons, this paper designs and verifies a coil parameter detection method to achieve automatic multi-parameter detection of coils during automatic winding. To a certain extent, it can reduce the manual involvement and enhance the automation of the whole production process. This method requires the use of an industrial camera to take  
Figure 1: The production process of high voltage primary coil. real-time pictures of the coil images during production and an image processing algorithm to achieve accurate identification of the winding process parameters. The rest of the article is organized as follows: Part 2 describes the composition of the winding quality inspection system. Part 3 describes in detail the overall inspection scheme and the implementation process of the winding angle detection method and the wire spacing detection method. Part 4 gives a discussion of the algorithmic experiments and results for angle and spacing.
# An Efficient Model-Based Clustering via Joint Multiple Sink Placement for WSNs
## 6 Conclusions  
This paper has dealt with the prevalent issues of high energy consumption, short network lifetime, and data transmission delay in a constrained IoT network. It has notably offered a complete analytical model that combines and resolves all mentioned issues using three aspects: clustering optimization, multiple sink placement, and data routing in heterogeneous WSNs.  
We have proposed a practical approach that computes Cp factors to select CHs and then constructs referred clusters, where each cluster has been assigned a specific sink according to a proposed architecture. Unlike existing methods that force each cluster to maintain one unchangeable CH, eventually leading to an enormous energy depletion of the CH nodes given the considerable distance between the cluster members' nodes and the CH, our suggested method ensures that no CH or intermediate node participates or transmits their data packets with less than an energy threshold and more than a distance threshold. Furthermore, the simulation results have showed that our proposed analytical model reduces the number of hops by more than 4% and increases the residual energy by more than 3% compared to other state-of-the-art algorithms. As a result, it outperforms them in terms of increasing the network's lifetime, decreasing energy consumption, and reducing data transmission delay using different amounts of sensor nodes.  
The proposed work can help researchers and developers build and create applications for highly compressed networks. In addition, applications such as smart farming, smart industry, and smart grids can leverage the data produced by the deployed sensors to develop new applications and services for users.  
To increase the extent of our contribution to sink placement, we plan to apply our approach in different environments, such as underwater wireless sensor networks (UWSNs). In this regard, we intend to resolve the fixed sink issue by investigating mobile sinks and to highlight potential trade-offs between performance and cost by corroborating the performance results with some further computational complexity analyses.  
Writing--original draft, S.B.; Writing--review & editing, A.Z., E.H.N. and A.B. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 1 Introduction
### Motivation  
The authors have chequered experiences of more than twenty-eight years as information warriors, teachers, and researchers and find that detecting the jamming conditions and using it to localize the jammer is a complex and costly affair with the existing technology. WSN have vast military applications for tactical battle field surveillance. However, the same cannot be done effectively because of its high vulnerability to jamming. The authors are motivated to convert this weakness of the WSN into its unique strength of detecting and localizing the jammer. We, therefore, take on the problem of jamming detection in this paper, as our first effort, towards exploiting the potential of WSN in hunting for the jammer in an information war.  
There is a special motivation to the approach to the problem too. The existing methods [1-6] of detecting the jamming conditions are node-centric, where the complete data collection, processing and decision making is done by individual nodes to arrive at a crisp decision of 'jammed' or 'not jammed'. This approach is not suitable in a hostile environment because, like wounded soldiers and damaged equipment who/which are graded according to the severity of the casualty/damage, the nodes too must be graded with different jamming indices as per the severity of jamming affecting them. This would make the employment and deployment of the WSN nodes, like any other battle resource, economic and flexible to suit different stages of the information warfare. The other serious drawback of the existing approaches is that the complete processing and decision making is done at the node level. This is not practicable as the WSN nodes are resource-starved and that because nodes may not be able to communicate with others during jamming. Therefore, the authors are motivated to change the approach from decision-making being node-centric to base-station-centric and from the decision being crisp-centric to fuzzy-centric.
## 2 Materials and Methods
### Data Processing
#### 2.2.4 Phenology Data  
Phenology data were fitted to EVI time series through the opensource software TIME-SAT 3.3 and extracted by the dynamic threshold method. The method mainly calculates phenological parameters by setting a specific ratio that exceeds the distance between the maximum and minimum values in the rising or falling stages of vegetation index. The thresholds of vegetation growth start and vegetation growth end are set at 30% and 15%, respectively [34].
# CI-UNet: Application of Segmentation of Medical Images of the Human Torso
## 1 Introduction
### Research Objectives  
In this paper, we design a deep learning algorithm CI-UNet, which can improve the accuracy of foreground target edge segmentation in medical images and the problem of partial organ undetectability. This study will finally be correlated with orthopedic spine images, and we used CI-UNet to perform scoliosis angle calculations in Guizhou residents of Guizhou Province, China. The research contributions and practical aspects of our proposed method can be summarized as follows:  
1. In the multi-organ segmentation task, image rotation and Cutout [37] data enhancement were performed for the insufficient amount of data in the dataset, and the effects of different rotation angles on the results of the dataset evaluation metrics and whether what level of Cutout data augmentation can better mitigate the problem of overfitting the dataset due to rotational data augmentation;
2. In the multi-organ experimental analysis, firstly, we increased the generalization ability of the network by modifying the backbone network and adding Transfer Learning. Secondly, the Polarized Self-Attention was added to the network to increase the overlap and localization ability of the prediction results with the actual labels. Finally, the network was fused with image information by adding an information aggregation module. The result of experiment showed that our designed CI-UNet achieves better results in evaluation metrics when compared with the current, more popular networks. At the same time, this paper has designed a scheme to cope with the imbalance in the Chaos dataset;
3. In the practical application of spine segmentation, we transposed the experience of multi-organ semantic segmentation experiments. Then, CI-UNet was applied to the spine dataset of the Guizhou branch of Beijing Jishuitan Hospital. CI-UNet was validated for semantic segmentation of 2 classification classes of X-ray spine images. From the perspective of practical applications, we are actively trying to provide computer-aided diagnostic applications for spinal disorders in Guizhou people.