esa-sceva/satcom-chunk-collection huggingface dataset:
# Structural Evolution of Polyimide-Derived Carbon during Phosphoric Acid Activation
## 3 Results and Discussion
### Copper Binding  
Figure 10 shows the pH dependence of copper binding by polyimide-derived carbons obtained with (H\({}_{3}\)PO\({}_{4}\) series) and without phosphoric acid (Thermal series). Adsorption of copper ions on all studied adsorbents increases with an increase in the pH of the solution. The increase in copper adsorption with increasing pH occurs due to the deprotonation of surface functional groups and the formation of surface complexes with copper ions [76; 77; 78; 79; 80]. Carbon obtained without phosphoric acid shows very small adsorption of copper at pH < 5.3 and follows the precipitation curve at higher pHs. This behavior is expected since carbon obtained without phosphoric acid does not have surface groups capable of dissociation at pH less than 5-6.  
On the contrary, the adsorption of copper on polyimide-derived carbon obtained with phosphoric acid is significant even at a very low pH (Figure 10). This carbon exhibits noticeably greater copper adsorption than the cation-exchange resin with carboxylic groups KB-4 (an analog of Amberlite IRC 86), which has a very high cation exchange capacity of 10 mmol/g. Adsorption of copper on the carbon is even greater than that on the very acidic cation exchange resin KU-23 containing sulfo groups (analog to Amberlyst-15) with a cation exchange capacity of 4.5 mmol/g. Despite having a lower cation-exchange capacity of 2.5 mmol/g, phosphorus-containing carbon removes more copper than ion-exchange  
Figure 10: Copper binding by polyimide-derived carbons obtained with (H\({}_{3}\)PO\({}_{4}\)-series) and without (Thermal-series) phosphoric acid at 800 \({}^{\circ}\)C. Copper binding by ion-exchange resins with carboxyl (KB-4) and sulfo groups (KU-23) is provided for comparison.  
resins. This shows that phosphorus-containing carbon has a higher affinity for copper ions than ion-exchange resins.  
It is worth noting that polyimide-derived carbon obtained with phosphoric acid exhibits significant copper uptake at pH values lower than PZC (pH < 2.3), i.e., when the surface of carbon is positively charged, and therefore cation adsorption should be hindered. This phenomenon has been reported previously for the adsorption of Cd(II), Hg(II), and Cr(III) and has been explained as being due to an ion exchange reaction between the delocalized protonated \(\pi\)-electrons of the graphene layer of carbon (-Cr-H\({}_{3}\)O\({}^{+}\)) and the metal cation [81; 82; 83; 84; 85]. The high adsorption capacity of polyimide-derived carbon obtained with phosphoric acid in an acidic environment indicates its potential for the extraction of heavy metal ions from acidic solutions, as well as its use as an enterosorbent for detoxification of the body from toxic metals in the acidic environment of the stomach.
## 3 Evaluation Index System for Core Abilities of Distributed PV-Generation Projects
### Investment and Earning Ability  
The index is set to explore the benefit-earning ability via traditional financial and techno-economic indicators, such as net present value (_NPV_), internal rate of return (_IRR_), static payback period (_T_), return on equity (_ROE_) and return on investment (_ROI_). The calculation of each indicator is shown as follows.  
1. Net present value (_NPV_). _NPV_ is a basic economic indicator to describe the project's profit during the construction and operation period. It is the sum of differentials between cash inflows and outflows in every year. It can be calculated by Equation (1). \[NPV=\sum_{t=0}^{n}\left[\left(CI-CO\right)_{t}\times\left(1+i_{0}\right)^{-t}\right]\] (1) In Equation (1), _CI_ stands for the annual cash inflow; _CO_ is the annual cash outflow; \(t\) represents the construction and operation period and \(i_{0}\) is the basic discount rate.
2. Effective rate of return. Compared with internal rate of return (_IRR_), the rationality of the effective rate of return can be determined. When effective rate of return is bigger than internal rate of return, this means the effective rate of return is acceptable and valuable. _IRR_ can be calculated by Equation (2). \[NPV=\sum_{t=0}^{n}\left[\left(CI-CO\right)_{t}\times\left(1+IRR\right)^{-t} \right]=0\] (2)  
Figure 4: Evaluation index system for core abilities of distributed PV-generation project.  
In Equation (2), \(IRR\) is the rate of return which makes the net cash flows zero. \(IRR\) can be also named as expected rate of return. As it is greater than \(IRR\), \(NPV\) is better.
3. Static payback period (\(T\)). T stands for the return ability of investment. If \(T\) is smaller, the ability is better. A static payback period can be calculated via Equation (3). \[T=t_{\left(\sum\left(CI-CO\right)>0\right)}-1+\frac{\left|CI-CO\right|_{t-1}}{ \left(CI-CO\right)_{t}}\] (3) In Equation (3), \(t_{\left(\sum\left(CI-CO\right)>0\right)}\) stands for the year \(t\) when the accumulative net flows are more than 0 for the first time. \(\left|CI-CO\right|_{t-1}\) is the absolute value of net cash flow in the year \(t-1\), and \(\left(CI-CO\right)_{t}\) is the net cash flow in the year \(t\). In general, \(T\) should be shorter than the \(T_{0}\) calculated by basic discount rate \(i_{0}\).
4. Return on equity (\(ROE\)). \(ROE\) stands for the earning ability of equity. It can be measured through Equation (4). \[ROE=\frac{NP}{ANW}\times 100\%\] (4) where \(NP\) stands for net profits, \(ANW\) is the average net worth.
5. Return on investment (\(ROI\)). \(ROI\) equals pre-tax profits divided by total investment. The calculation method is shown in Equation (5). \[ROI=\frac{PP}{TI}\times 100\%\] (5) where \(PP\) stands for pre-tax profit, \(TI\) is the total investment.
## Materials and Methods
### Solid Phase Microextraction  
Fibers and a manual SPME device were obtained from Supelco Co. (Bellefonte, PA, USA). Fibers tested for extraction of the volatile components were as follows: poly(dimethylsiloxane) (PDMS) 100 \(\upmu\)m, carboxen/PDMS (CAR/PDMS) 85 \(\upmu\)m and divinylbenzene/CAR/PDMS (DVB/CAR/PDMS) 50/30 \(\upmu\)m. Before use, fibers were conditioned as recommended by the manufacturer. To study the influence of ethanol (EtOH) content on the extraction, the model mixture was diluted with deionized water. The EtOH contents (\(v/v\)) studied here were as follows: 40% (undiluted mixture), 10%, 5%. To study the influence of NaCl on the extraction, the following conditions were tested: no salt or 10% NaCl (\(w/v\)), accordingly. Next, 13 mL of sample were then placed in a 40 mL amber vial closed by a polytetrafluoroethylene (PTFE)/silicone septum (Supelco). A water bath was used to control the temperature (20 \({}^{\circ}\)C, 30 \({}^{\circ}\)C, 45 \({}^{\circ}\)C and 60 \({}^{\circ}\)C tested) and the sample was conditioned for 5 min before extraction. Each analysis was carried out in triplicate. After exposure, the fiber was thermally desorbed into a GC and left in the injection port (equipped with a 0.75 mm i.d. inlet liner) for 5 min. The injector was set at the temperature recommended by the manufacturer and operated in splitless mode for 5 min.
# Improved Color Attenuation Prior for Single-Image Haze Removal
## 2 Related Works
### Hazy Particle Map  
Using median filters in [PERSON] et al.'s dehazing algorithm [16] causes halo artifacts because the standard median filtering is not appropriate for image regions containing edges. This problem can be resolved efficiently using mHMF rather than the standard median filter (SMF), as proposed by [PERSON] et al. [24]. mHMF first computes the medians of three windows: cross, diagonal, and square. Then, the median of these three is selected as the final output. Thus, in flat image regions, mHMF functions in a similar way to SMF and smoothly estimates the hazy particle map (HPM) corresponding to the airlight. The information from the cross and diagonal windows helps mHMF to better preserve the image edges, however, in the abrupt regions with depth discontinuities, resulting in reduced halo artifacts.  
Additionally, a sophisticated adaptive tone remapping algorithm [31] also is used, as opposed to the simple tone remapping method used by [PERSON] et al. [16]. As a result, this algorithm is a significant improvement upon the fast haze removal using median filters, and its hardware design presented by [PERSON] et al. [35] provides an efficient means of handling large images in real time. An issue arising from the assumption that the atmospheric light is pure white (\(A=1\)) after local white balance is that noticeable background noise may occur in the dehazed image.
## 2 Method  
The work presented in this paper aims to determine the impact of boundary conditions and model input on the output of an LCC calculation, concerning the renovation of a multi-family building located in Denmark. To do so, first, the origin and key details of the applied baseline are presented. Thereafter, Section 2.1 describes the applied LCC calculation method, whereas Sections 2.1.1 and 2.1.2 depict boundary conditions and building-related model inputs, respectively. The local sensitivity of each model input is determined by performing OAT variation method as in [16; 18] and further described in Section 2.2. The five most sensitive parameters to the output, found via the OAT method, are further applied in the global sensitivity analysis. Global sensitivity consists of simultaneous variation of inputs [15; 16; 17; 24], where the method applied in this paper includes Monte Carlo (MC) method with Sobol sampling, described in Section 2.3. Finally, the sensitivity of the different parameters is analyzed using regression methods, described in Section 2.4. Figure 1 illustrates the approach used to define the input parameters and quantify their sensitivity.  
For this study, the case building investigated in [28; 29] is used as a starting point for the analysis. The building has been operational since 1949 and houses 66 apartments with a total heated floor area of 5250 m\({}^{2}\). The existing source of heating and DHW is a District Heating (DH) substation. The primary energy demand of the building in its existing condition, determined by the Danish compliance tool BE18, accounts for 130 kWh/m\({}^{2}\) per year [28]. The selected renovation package, represented in the baseline model, achieved approximately 40% energy savings and consists of the installation of new windows (energy class B); replacement of the circulation pump for DHW; re-insulation of the external wall, attic slab, and pipe networks for distribution of heating and DHW; and 110 kWp roof-mounted Photovoltaic (PV) system [18].  
As indicated previously, the baseline is suited to three different energy supply systems for space heating and DHW. The scenario with a new DH substation considers costs related to replacing the existing sub-station. In the other two scenarios, the existing DH substation is replaced with a heat pump (HP) and natural gas boiler. Switching from DH to natural gas or HP as a supply source accounts for removing the DH sub-station and incorporating gas  
Figure 1: Diagram of sensitivity study applied in this paper.  
boiler or ground-source HP, respectively. Thereby, each of the three models have common (renovation package-related) and individual (system-related) input parameters.
# Estimating Forest Carbon Stock Using Enhanced ResNet and Sentinel-2 Imagery
## 3 Methodology
### Enhanced ResNet Architecture
#### 3.2.4 Model Efficiency  
The Enhanced ResNet contains approximately 13.2 million parameters, striking a practical balance between model complexity and computational efficiency. While incorporating both multiscale residual blocks and channel attention modules increases its representational capacity compared to the standard ResNet-18, the architecture remains lightweight enough to be deployed in real-world remote sensing scenarios. From a computational perspective, the model avoids deepening the network unnecessarily. Instead, it leverages architectural innovations--such as parallel convolutions and efficient squeeze-and-excitation units--that add only a modest overhead in terms of parameters and FLOPs (floating-point operations). These components selectively enrich feature representations without incurring the high memory costs typically associated with deeper or transformer-based architectures.  
The use of global average pooling and a single linear regression head further contributes to model compactness. Unlike dense fully connected layers commonly used in high-capacity models, this design significantly reduces overfitting risk and ensures smooth convergence during training, even with moderate-sized ground truth datasets. Moreover, the model is compatible with standard hardware, including mid-range GPUs and edge devices, making it feasible for large-scale inference on satellite images or integration into operational forest monitoring systems. This is particularly important for applications in developing regions or mountainous forest zones, where computational resources may be limited.  
In summary, the Enhanced ResNet achieves high predictive performance without sacrificing efficiency, making it well-suited for scalable carbon stock estimation in remote sensing workflows that demand both accuracy and deployability.
# Using Explainable AI (XAI) for the Prediction of Falls in the Older Population
## 4 Discussion
### All Falls and Syncope  
Judging by the feature importance scores (\(\geq\)0.1), the model would suggest that if a clinician was interested in predicting any future falls or syncope over a six year period, the most important features to consider would be whether a fall had occurred in the last year and their age. The highest SHAP feature importance score was also for whether a fall had occurred in the last year, which was followed by their sex (being female had a positive impact on model output), and a fear of falling. In keeping with the literature [28; 29], higher age values tended to contribute positively to the model, with the opposite being generally true; however, the SHAP plot allowed us to appreciate a degree of heterogeneity (i.e., with some older--more red--participants having a negative impact, and some younger participants --more blue--having a positive impact). This interesting nuance that is evidenced by XAI is helpful for reminding clinicians that despite it having average effects, individual disagreements with the norm are not uncommon. Previous falls have also been highlighted in the literature as being predictive of future falls [26], and the top importance of them having had a fall in the last year in our model resonates with the top clinical recommendation by NICE that older people who are in contact with healthcare professionals should be asked routinely whether they have fallen in the past year [4].  
The fact that female sex contributed towards the prediction of all falls and syncope is consistent with the literature, which suggests that women are more prone to falls than men [30; 31]. The SHAP summary plot demonstrated that there was little deviation over the SHAP values of sex between the samples, thereby suggesting that there was little variability amongst samples of the contribution of the sex feature towards the final output. This contrasted with the features such as having had a fall in last year, where a large variance in the SHAP values could be seen. This suggests that the importance of this feature to the prediction that is makes may differ from person to person.  
There was also a general trend where the absence of a binary feature which was represented by a blue spot on the summary plot had a lesser impact on the model output as compared to the presence of the feature. This may be observed on the SHAP summary plot as larger absolute SHAP values for the red dots in comparison to the corresponding blue ones. It may be suggested that the presence of a feature is much more relevant to the prediction of a fall, rather than its absence. A clear example of this is being on Z-drugs, as is highlighted in the literature [32].
# A Network Analysis-Based Approach for As-Built BIM Generation and Inspection
## 2 Literature Review
### As-Built BIM  
Ensuring the accuracy of the as-built model is a critical task for enabling as-built BIM functions throughout the building lifecycle, and most practical problems arise due to mismatching and inaccurate final as-built BIM. [PERSON] et al. [24] developed a management system for the as-built BIM to support its inspection and modification during project closeout, while [PERSON] and [PERSON] [25] proposed an automated approach for the shape and pose updating of BIM elements to reflect as-built conditions during the on-site construction phase. Furthermore, as-built BIM proves advantageous for building analysis in special scenarios, such as earthquakes [26]. As-built BIM accounts for the actual construction processes, material deviations, and modifications made during construction, providing a realistic foundation for seismic analysis. [PERSON] et al. [27] developed a BIM-based inspection framework utilising computer vision methods for post-earthquake building inspections. Moreover, employing as-built BIM to perform comparative analyses of structures before and after earthquakes significantly enhances seismic design and improves building stability [28].  
Current as-built comparison methods are mostly achieved through the element-by-element approach, which requires the utilisation of the element-matching approach. Common detected-content, vision, and IFC-enabled approaches have been widely explored by previous researchers. [PERSON] et al. [29] presented a visual inspection method based on the integration of the autonomous localisation algorithm and an aerial sensor system, while [PERSON] [30] developed an accuracy evaluation method for as-built BIM from photographs taken by commercial cameras. IFC acquired more attention because of its versatility in the BIM field; [PERSON] et al. [31] achieved the updating of BIM object information by retrieving the semantics from IFC files and discrepancy analysis automatically. [PERSON] et al. [32] investigated the common patterns and structures of IFC files collected in practice, while [PERSON] et al. [33] designed software for the automatic comparison of different IFC documents, which are based on the content and hierarchical structure analysis of IFC files.  
Though the element-based method has gained popularity among current researchers, the underlying logic of the element-matching approach is sensitive to the change in Globally Unique Identifiers (GUID), which results in the loss of valuable information concerning the integrity and correlation of building structures. Therefore, the introduction of network-based matching approaches from other research fields will bring significant benefits to the B&C industry. The concept of a network is commonly utilised in the linguistics field and biology engineering for text matching [34; 35] or biological network exploration [36; 37]. Neural network-based approaches are usually utilised as supplementary methods for network analysis and comparison, which depends on frequent parameter tuning and massive computing resources.
## 5 Experimental Results
### Comparative Analysis
#### 5.2.5 Impact of Reliability  
Reliability is defined as the measure of the total number of packets successfully transmitted and received in the network during a certain period of time. It proves the efficiency of a mechanism in the long run. The reliability of the proposed MiA-CODER mechanism is compared with that of other approaches in terms of simulation time. It is found that the packet transmission and reception rate increase with the increase in the simulation time. For a mechanism to be stated as highly reliable, the number of transmitted packets, number of received packets and number of control packets should be high. The reliability of an approach is affected by the coverage holes which are formed in the network. The reliability of the proposed MiA-CODER mechanism is analyzed both before and after coverage hole repair.
## 2 Related Work  
Several studies addressed the problem of cache deployment in telecommunication networks with the objective of maximizing the benefits of caching. For example, [10,11] address the problem focusing on offloading traffic to guarantee a more energy-efficient VoD-content distribution; and reference [12] presents an intelligent, content placement approach considering a trade-off between size of caches and network bandwidth. These works, however, consider static network scenarios. Moreover, they either assume the location or assume the dimensions of the cache are given and do not account for an investment budget to deploy caches. Other works, such as [13,14], qualitatively evaluate the impact of content caching inside telecommunication networks in terms of cost and throughput improvement; however, no budget-constraint is considered in these studies. Recent works, such as [15], investigated the content placement problem for resilience against link-cut attacks in a data center network.  
Similarly to our work, [16] solves the cache deployment optimization problem considering a trade-off between the cost of the cache deployment and that of bandwidth and energy resources in a static scenario while meeting end-user performance requirements. In our work, however, the problem is significantly different, as we aim to jointly find the locations and dimensions of the caches at the various hierarchical network levels that minimize the overall network resource consumption. Moreover, we consider a dynamic network scenario where both the number of VoD content requests (and the VoD content requested) are not known a priori. Furthermore, [17] presents an optimization model whose objective is to decide where to deploy caches, in order to minimize costs and maximize the bandwidth saved, but in a hierarchical tree network. In our work the problem is different, since we consider ring-based hierarchical metro networks.  
Complementing our work, prior works have investigated real time operations of content-delivery networks via aspects such as load balancing [2]. While such works consider the cache deployment as a given, in our work we focus on the cache-deployment planning phase and then perform simulations under dynamic VoD traffic to capture network limitations, such as link bandwidth.
## 1 Introduction
The literature lacks a comprehensive criterion that considers multiple factors. This study addresses these gaps by developing a unified performance metric using Lagrange interpolation, combining components such as distance, delay, trust, and energy into a single measure. The primary contribution of this research includes the following:  
* Unified Performance Metric: A single performance metric developed using Lagrange interpolation integrates multiple factors, such as energy, delay, distance, and trust. This metric will comprehensively evaluate the performance of CWGO and other algorithms with various rounds and sensor node configurations. * Evaluation Across Wireless Technologies and Node Configurations: This study builds on our previous research by comparing the proposed CWGO algorithm to others, such as E-CERP, EECHIGOWO, DUCISCA, and DE-SEP, both bot static and dynamic sensor nodes for different wireless communication technologies (Wi-Fi, Zigbee, LoRa, and BLE). The remainder of this paper is organized as follows: Section 2 introduces the proposed algorithm and evaluation method. Section 3 shows simulation results, Section 4 discusses these results in detail, and Section 5 concludes the study with recommendations for further improvement.