esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
Given the limited adoption of EVs to date, we can assume those consumers that are buying such cars are early adopters with the possibility to recharge on a daily basis. In this case, however, the full potential of such batteries will potentially only be addressed in rare cases. Thus, the respective EV will have to move a 'dead mass' for most of the time, diminishing its inherent environmental impact due to high energy consumption, a higher manufacturing impact and higher tyre and road wear [41]. Another solution might be a roll-out of fast-chargers and, parallel to this, the development of battery chemistries that can be charged at higher currents. Although this option creates a lesser burden for the EV user in terms of charging time, the challenge remains to limit the impact of charging rates >50 kW have on the cycle-life of the respective battery packs. Moreover, fast-chargers put a substantial strain on the available power grid [42; 43], if they are not coupled to a local storage system, consisting of second-life batteries or supercapacitors that are charged when power demand is low. For these reasons, a concept of in-life modularity is proposed in this paper, consisting of a range-extender trailer that can be connected to an EV. Both a petrol generator and a battery pack trailer are shown in Figure 2.  
Ideally, this concept consists of a trailer fitted with an extra battery pack, allowing the EV's battery to be used in a charge-sustaining mode for an additional 300 km. Whereas extra range is typically required to cover long distances over highways, this range-extender concept (from now on abbreviated to 'ReX') could complement fast-charging stations located near highways and would be offered on a rental basis, to avoid a high upfront cost for its sporadic use. As an intermediate towards the ideal situation, a petrol generator could serve as a power source for a generator to supply energy to the EV. As battery costs continue to decrease with increased production and a further fine-tuning of the production process, the petrol generator could be phased-out on the short to mid-term to maximize the environmental potential of in-life range modularity. Therefore, the objective of the presented paper is first to assess the environmental impact of this setup considering both climate change and air quality, by comparing a 40 kWh EV + ReX trailer combination to a range of mid-sized family cars. These are based on either petrol, diesel, petrol hybrid, or petrol PHEV powertrains. Also, the comparison is made with four existing EV models, characterized by battery capacities of 30, 60, and 90 kWh, respectively. The main focus is on the results for a petrol generator and a 50 kWh battery trailer, which are discussed in relation to the PHEV and the 90 kWh EV, as these are the technologies we expect to compete in the coming decade.
## 3 Results and Discussion
### Impedance-Based Immunoassay  
In order to test the sensing performance of the sensor, IgG solutions of five different concentrations: 0.001 ng, 0.01 ng, 0.1 ng, 1 ng, and 10 ng were sequentially incubated on the biofunctional electrode for 30 min. After each incubation, the electrode was washed with 1\(\times\)PBS and dried with a nitrogen gun. Then the redox solution, containing [Fe(CN)\({}_{6}\)]3-/4- was added into the acrylic tank and the EIS spectrum was read. When immunoassay was performed, the Nyquist diagram showed an obvious semicircle. The range of R\({}_{\text{ct}}\) was between 500 k and 2.5 M, indicating the immune response of IgG on the electrode, which strongly limited the charge transfer between [Fe(CN) 6]3-/4-. In addition, the range of R\({}_{\text{ct}}\) was smaller than the previously reported range of 3 M-7 M. The reason for this difference is that our cross-finger electrode area (5.628 mm\({}^{2}\)) is larger than the previously reported electrode area (0.5 mm\({}^{2}\)) [18]. Figure 4b shows the changes in the Nyquist plot at different concentrations. We have intuitively observed that, the diameter of the Nyquist diagram semicircle has gradually increased with the rise of incubation antigen IgG concentration, revealing the increase of impedance. As described in Section 3.3, we extracted the charge transfer resistance R\({}_{\text{ct}}\) for each test. Here, we consider the blocking step as the zero point, that is, \(\Delta\)R = R\({}_{\text{ct}}\) (IgG) - R\({}_{\text{ct}}\) (Blocking). This standardized \(\Delta\)R can truly reflect the IgG concentration.  
Figure 5 shows the relationship between normalized resistance \(\Delta\)R and concentration C. in the range of 0.01 ng-10 ng/mL. With higher IgG concentration, the logarithm of \(\Delta\)R and concentration presents a linear regression with a high determination coefficient R\({}_{2}\) = 0.991. When the concentration drops to 1 pg/mL, the impedance data cannot read correctly, indicating that the concentration is below the lowest detection line of the system. It can be seen in the Figure that the linear detection interval of the biosensor is 0.01 ng/mL-10 ng/mL, and the linear regression equation in this interval is:  
\[\Delta\text{R}=567.79\log_{10}[\text{C}]+1243.2, \tag{2}\]  
The minimum detection limit is about 0.01 ng/mL. The above shows that our miniature interdigital gold electrode based on PEN flexible material is suitable for the manufacture of high-performance immunosensors.  
Figure 5: The response trend line of the immunosensor.
# Joint Hybrid Beamforming Design for Millimeter Wave Amplify-and-Forward Relay Communication Systems
## 4 Hybrid Beamforming Design for FD AF Relay Systems  
In this section, a more common case in practical applications is further considered, where the FD AF relay communication system operates with CSI unavailable.
# Planar Array Diagnostic Tool for Millimeter-Wave Wireless Communication Systems
## 3 Compressed Sparse Recovery Methods
### Mixed \(\ell_{1}/\ell_{2}\) Norm  
The radiating aperture's position and dimensions can also be taken. The solution \(X\) is grouped into \(G\) groups \(X^{g}\), which corresponds to the individual radiating element's aperture \(g\). For a faulty element, all regions of discretization \(x_{k}^{g}\) in the aperture will be faulty (nonzero). Let vector \(X\) of dimension \(M\ \times\ N\) be divided into \(G\) non-overlapping groups depicted \(X^{g}\) of size \(N_{g}\), such as \(\sum_{g=1}^{G}N_{g}=MN\). Hence, the mixed \(\ell_{1}/\ell_{2}\) norm is given as  
\[\lVert X\rVert_{1,2}=\sum_{g=1}^{G}\lVert X^{g}\rVert_{2}=\sum_{g=1}^{G} \sqrt{\left\lvert x_{1}^{g}\right\rvert^{2}+\ldots+\left\lvert x_{N_{g}}^{g} \right\rvert^{2}}. \tag{8}\]  
The mixed \(\ell_{1}/\ell_{2}\) norm has similar behavior to \(\ell_{1}\) norm on vector \(\lVert X^{1}\rVert_{2}\),..., \(\lVert X^{g}\rVert_{2}\),..., \(\lVert X^{G}\rVert_{2}\); it, therefore, induces group sparsity at the radiating aperture level. The regularized inversion problem is then expressed as  
\[\min_{X}\lVert\mathbf{X}\rVert_{1,2}\quad\text{subject to }\lVert\mathbf{y}-\mathbf{AX} \rVert_{2}\leq\epsilon. \tag{9}\]
## 4 Software
### Components
#### 4.1.3 Solace PubSub+
The term _message_, in the technological context, refers to the technology that allows computer systems to share information without the need for direct links or knowledge of each other's location. In the most basic operations, the sending of messages requires 5 components:  
* **Publisher**: the entity that sends or publishes the message (also called a producer);
* **Message**: what the publisher wants to say to the subscriber. Messages often contain events, but can also carry queries, commands, and other information;
* **Subscriber**: the ultimate receiver of the message (also called a consumer);
* **Topic**: used when the message is intended to be consumed by more than one subscriber;
* **Queue**: used when the message is intended to be consumed by at most one subscriber. These components are architecturally organized as illustrated in Figure 4.
## 5 Conclusions  
This study proposed a relationship-based Ambient Detection model to achieve reliable object recognition even under visual complexity and occlusion during concrete-pouring operations. Comparative experiments with the YOLOv11 model confirmed that the proposed method significantly improves recognition performance by embedding distance, attribute, and spatial relationships in the detection pipeline.  
(T1) The complete framework outperformed the baseline, raising accuracy from 81.03% to 93.10%, and lowering the misdetection and complete-failure rates to 1.72% and 5.17%, respectively.  
(T2) A rigorously defined ROI and closed-form scores for all three relationships (\(D_{R},S_{R},A_{R}\)) enabled deterministic weight computation.  
(T3) The model's robustness was further evidenced by an ablation study and a McNemar test showing a statistically significant performance gap in 232 field images.  
(T4) Processing time inevitably increased from 45 ms to 65 ms per image because the three relationship scores must be calculated; however, the 44% overhead is a reasonable trade-off for the 12% accuracy gain. Future work will focus on lightweight optimization device inference to satisfy stricter real-time constraints.  
(T5) Limitations such as the uniform 1.5 m neck-height assumption (\(\approx\)\(\pm\)7% height-error) and the single-trade dataset will be addressed through adaptive scaling, depth sensing, and cross-trade validation.  
In summary, relationship-based Ambient Detection substantially mitigates boundary ambiguity and visual-similarity errors, fulfilling all five research tasks and thereby confirming the initial hypothesis that contextual cues markedly enhance detection reliability in concrete-pouring scenarios.  
Conceptualization, S.Y. and H.K.; methodology, S.Y. and H.K.; validation, S.Y. and H.K.; investigation, S.Y.; writing--original draft preparation, S.Y.; writing--review and editing, S.Y. and H.K. All authors have read and agreed to the published version of the manuscript.  
This research was by a grant (RS-2022-00143493) from a Digital-Based Building Construction and Safety Supervision Technology Research Program funded by Ministry of Land, Infrastructure and Transport of Korean Government.  
The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of DANKOOK UNIVERSITY (DKU 2020-09-027, date of approval 14 September 2020).  
Written informed consent has been obtained from the patient(s) to publish this paper.  
All data, models, or code generated or used during the study are available from the corresponding author by request.  
The authors declare no conflicts of interest.
## 3 Application and Results
### Crack-Pattern Profiles  
Figures 5 and 6 show the typical crack patterns for both BTC and BTD, respectively. It should be noted that these tests were conducted under quasi-static conditions. In Figure 5, it can be clearly seen that a crack branching existed near the loading points at the boundaries in the BTC, although the fracture approximately passed through the centre of the discs. Therefore, it was inferred that the local concentrated load led to the shear failure of concrete at the boundaries. Meanwhile, through an observation of the crack-pattern profiles of the BTD in Figure 6, it was found that the cracks at the centre of discs in the BTD were significantly finer and straighter compared with the BTC. The crack branching was located at the loading points in the BTD, while several fine cracks occurred at the contacting boundary.  
Figure 4: The time-history analysis of the loading response with BTC (**a**) and BTD (**b**) boundaries. Note that three tests were conducted for the BTC and BTD. These tests are referred to as BTC-01, 02, and 03 for BTC, and BTD-01, 02, and 03 for BTD.  
Figure 5: The final crack-pattern profiles of BTC: front views (**a**–**c**), back views (**d**–**f**), and side views at the loading point (**g**–**i**) of BTC-01 (left), BTC-02 (middle), and BTC-03 (right) tests.
# A Review of Photothermal Detection Techniques for Gas Sensing Applications
## 3 Fiber-Based Photothermal Gas Sensors
### Spatial Gas Sample Localization in an Fiber-Based PTS Sensor  
Some practical applications of laser-based gas spectrometers e.g., at gas or oil processing plants, require to exactly localize the position of a gas leak [27; 28; 29]. This requires using open-path gas sensing techniques where the laser beam is transmitted in air and only the back reflected or scattered light is gathered for analysis [30; 31]. Standard open-path absorption-based implementations of gas sensors do not allow to precisely define the position of the gas particles being measured, as the registered signal is averaged over the entire length of the interaction between the gas sample and the laser beam. This problem was also addressed in Reference [24]. The proposed configuration of a PTS spatially resolved gas detection is presented in Figure 5.  
In this unique configuration, the PTS-induced RI modulation is probed similarly as in the configuration shown in Figure 4--using a fiber-based Mach-Zehnder interferometer working at 1.55 \(\upmu\)m. Here, the _pump_ laser was not collinearly aligned with the _probe_ laser beam. Instead, the collimator outputting the 2 \(\upmu\)m radiation was mounted on a mechanized optical rail and aligned to cross the _probe_ beam at an angle (see Figure 5). By moving the stage, the _pump_ beam could be positioned at a given  
Figure 5: (a) PAS configuration for spatially resolved measurement. AOM—acousto optical modulator, PD—photodiode. Gas cell filled with pure CO\({}_{2}\) at atmospheric pressure was placed in the optical path of the fiber-based 1.55 \(\upmu\)m Mach-Zehnder interferometer. (b) By scanning the position of the _probe_ beam, a clear PT signal was registered only at a point, where the 2 \(\upmu\)m beam intersected the gas-filled cell. Reprinted with permission from [24] C The Optical Society.  
point along the path-length of the _probe_ beam with high precision, with only one intersection point. The proof-of-concept experiment was carried out by inserting a transparent gas cell filled with pure CO\({}_{2}\) into the path-length of the _probe_ beam. In this configuration, the PTS signal was registered only at a certain position of the _pump_ beam, where it coincided with the CO\({}_{2}\)-filled gas cell. This experiment proved that appropriately designed PTS sensors are capable of resolving the position of the measured gas sample with reasonable precision.
## 2 Motivation and General Problem Statement
### General Problem Statement
For example, if \(f(\mathbf{x})\) represents the system's reliability at a design point \(\mathbf{x}\), then \(f^{*}(\mathbf{x}^{\text{low}},\mathbf{x}^{\text{up}})\) represents the system's reliability within the box-shaped solution space \([\mathbf{x}^{\text{low}},\mathbf{x}^{\text{up}}]\). It is intuitive that the degrees of freedom in the Equation (2) are \(\mathbf{x}^{\text{low}}\) and \(\mathbf{x}^{\text{up}}\), rather than the design parameters themselves. If \(f^{*}(\mathbf{x}^{\text{low}},\mathbf{x}^{\text{up}})\) can be explicitly expressed by \(\mathbf{x}^{\text{low}}\) and \(\mathbf{x}^{\text{up}}\), the Equation (2) can be solved easily. In fact, these two scenarios are more common in most engineering problems: Firstly, it is not possible to explicitly express \(f^{*}(\mathbf{x}^{\text{low}},\mathbf{x}^{\text{up}})\) as a function of \(\mathbf{x}^{\text{low}}\) and \(\mathbf{x}^{\text{up}}\), although the performance function \(f(\mathbf{x})\) is analytically known. Secondly, the performance function \(f(\mathbf{x})\) is a black box and is produced by numerical simulations; therefore, the explicit expression of \(f^{*}(\mathbf{x}^{\text{low}},\mathbf{x}^{\text{up}})\) does not exist. Therefore, a sampling-based method that can be applied to both analytically unknown \(f^{*}(\mathbf{x}^{\text{low}},\mathbf{x}^{\text{up}})\) and black-box \(f(\mathbf{x})\) is anticipated. Solving the Equation (2) presents two main challenges. The first is determining how to compute the box-constrained global optimization sub-problem \(\min_{\mathbf{x}\in[\mathbf{x}^{\text{low}},\mathbf{x}^{\text{up}}]}f(\mathbf{x})\). The calculation accuracy has a great influence. In general, overestimation could mean that an unfeasible solution space is wrongly identified as a feasible one, and underestimation could lead to a feasible solution space being incorrectly identified as unfeasible. Moreover, in order to handle the black-box performance function, the calculation method should not rely on the specific form of the function \(f(\mathbf{x})\). In other words, the calculation of \(\min_{\mathbf{x}\in[\mathbf{x}^{\text{low}},\mathbf{x}^{\text{up}}]}f(\mathbf{x})\) requires high accuracy and wide applicability. The second challenge is determining how to optimize multiple objectives without the use of gradients. The robustness optimization problems described in [16; 18; 19; 20] aim to identify the most robust box-shaped solution space that fulfills design requirements. In contrast, the Equation (2) in this paper considers both enhancing the robustness and optimizing the performance of the box-shaped solution space. In other words, the Equation (2) demands that the performance of the box-shaped solution space not only meets design requirements but also achieves optimality. **Remark 1**. : _If the performance requirement is \(f_{i}(\mathbf{x})\leq f_{i}^{u}\), for example, the system cost in Section 2.1, the Equation (2) sets \(f_{i}(\mathbf{x})=-f_{i}(\mathbf{x})\) and \(f_{i}^{l}=-f_{i}^{u}\)._
## 5 Experiments
### Intention Recognition
#### 5.1.3 Performance Analysis  
The performance analysis of the accuracy and loss graphs demonstrates the model's effectiveness during training and validation phases. The accuracy curve shows a steady improvement, reaching values close to 100%, indicating the model's proficiency in learning to classify intentions correctly. The loss curve, on the other hand, steadily decreases, reflecting the model's improved capability to minimize errors.
## 3 Study Area, Data Sources, and Data Description  
Al-Ahsa is located in the Eastern Province of Saudi Arabia and is bordered by the Persian Gulf to the east. The area extends from 29\({}^{\circ}\)20\({}^{\prime}\) N in Kuwait to the southernmost point of the Gulf of Bahrain at 25\({}^{\circ}\)10\({}^{\prime}\) N (Figure 1). The area is well known for its agricultural output, historic buildings, and palm trees. It is one of Saudi Arabia's largest regions, and has a vibrant culture and history. The area is also home to several historical attractions, such as the Qara Mountain Caves, which are thought to be more than 7000 years old and are home to prehistoric rock art. UNESCO has recently listed it as a heritage site in Saudi Arabia. The Al-Ahsa region was selected for this study since previous research has shown a high rate of traffic crashes in Al-Ahsa, with 31.9% of all crashes in the Eastern Province occurring in this city between 2009 and 2016. Dammam, Hafr Al-Batin, Qatif, Jubail, Dhahran, and Khobar are the next cities in terms of the number of crashes, with crash rates below 5% in other cities (Figure 2) [37]. These findings indicate that Al-Ahsa is particularly susceptible to traffic crashes in the Eastern Province. Although Al-Ahsa possesses significant potential to thrive as an international tourist attraction because of its recognition as a UNESCO-listed heritage site and a Guinness World Record, its high crash rate may put this at risk, necessitating immediate action. During the period of October 2014 to May 2018, the Road Safety Authority in Dammam provided data on traffic crashes in Al-Ahsa. The data revealed that around 8% of fatal and 30% of serious injury incidents were due to crashes between cars. Fatal crashes refer to those which involve at least one death, while serious injury crashes refer to those crashes in which at least one of the victims is hospitalized, without involving any deaths. The data provided by the Road Safety Authority also included the classification of crashes on the bases mentioned above. Another significant type of crash was vehicle overturning, which contributed to 6.5% of fatal and injury events. Pedestrians were also shown to be vulnerable, as they were involved in 12.5% of injury incidents and 2% of fatal crashes. Although some types of crashes, such as crashes with road guardrails, parked vehicles, motorcyclists, and permanent objects, have low fatality rates, they still pose a risk of harm, as illustrated in Figure 3. Therefore, further analysis and actions are needed to address the issue of traffic crashes in Al-Ahsa.  
Figure 1: (**a**) Location of the study area (Al-Ahsa) in Saudi Arabia; (**b**) distribution of traffic crashes in the study area (adapted from [8]).  
Figure 2: The percentage of road crashes in different cities of the eastern region of Saudi Arabia (adapted from [8]).
# Model Modification of the Soil-Water Characteristic Curve of Unsaturated Weak Expansive Soil
## 6 Correction of the Soil-Water Characteristic Curve by the Mercury Intrusion Test  
### SWCC Three-Parameter Model Fitting  
The movement of the water phase in unsaturated soil depends on soil particle size, mineral composition, pore distribution characteristics, temperature, and embossing degree. In some cases, for example, when soil moisture is affected by one or more factors, the SWCC is the only curve of soil moisture-base suction. However, it cannot be deduced from theoretical analysis according to the basic properties of soil. The movement of the water phase in unsaturated soil depends on soil particle size, mineral composition, pore distribution characteristics, temperature, and compaction degree.  
Considering the existing typical SWCC equations, including V-G, F-X, the Gardner model, etc., the formula is complex, and there are many parameters. In order to explore the influence of mudstone compaction degree (dry density) on the SWCC, based on the test data obtained by filter paper method, the nonlinear fitting analysis of soil water characteristic test results was carried out by using origin software. Through multiple model selection attempts, it was found that the three-parameter model can express the data more accurately:  
\[\theta=\alpha+\beta ln(\psi+\gamma) \tag{9}\]