esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Background and Related Work
### Hybrid Storage Structure  
The traditional high-performance database system is mainly based on hard disk drives (HDDs). Currently, HDD is still the main device used in storage systems. Although its capacity can be rapidly increased by increasing the number of disk slices and disk partitions, it still rapidly develops according to Moore's Law. Affected by this, the random-access performance of HDDs has not been significantly improved, which is a bottleneck. SSD is a new type of storage device that uses integrated circuits as a memory for the persistent storage of data. Compared with HDD, SSD yields outstanding read and write performance. However, SSD also has shortcomings, such as low capacity and high cost. Currently, no storage system comprising a single storage medium can meet the requirements of low cost and high query performance. Capacity, cost, sequential performance, random performance, and device life can together be considered as the primary indicators of the comprehensive level of the storage system. As shown in Figure 2, the range of requirements covered by a single storage medium is limited. If two storage media are integrated to form a hybrid storage system, such a system could conceivably utilize the strengths and avoid the weaknesses of each medium.  
Figure 1: SPARQL query types.  
To improve the storage and query efficiency, in addition to considering the storage device, it is essential to effectively access data. Therefore, an efficient storage system must guarantee excellent retrieval performance. Indexes are special-purpose data structures designed to accelerate data retrieval. Many researchers have conducted extensive research on indexes with respect to HDDs. Moreover, numerous methods have been suggested, most of which are based on popular B-trees [24], R-trees [6], linear [25], and scalable hashing [26]. These data structures can be directly used with SSDs. However, their performance is unsatisfactory because of several significant differences between integrated circuits and magnetic disks, such as asymmetric read-write latencies, out-of-place updates that must be erased before writing, and limited cell lifetime.
## 3 Results
### DED Additive Manufacturing
#### 3.2.2 Microstructure  
Samples were vertically cross-sectioned and examined for microstructural features. Analysis of the full-Co samples is included in Figures 7-9 while the Co-lean microstructural details are presented in Figures 10-12. There was low deviation between samples by this method and a representative microstructure of a full-Co sample is included below in Figure 7, and a representative microstructure of a Co-lean sample is included below in Figure 10. Throughout the cross-sections an equiaxed microstructure was prevalent with a finer grain \"skin\" (thickness of \(\sim\)200-260 \(\upmu\)m for full-Co), which was thinner than previous alnico DED builds, including the Co-lean in this study [16]. Increasing the grain aspect ratio along the vertical (build) direction is preferred, and would be beneficial towards increasing the magnetic remanence and energy product values.  
Investigation of any preferential grain orientation was performed for both compositions and the orientation information is presented in Figures 7 and 10 as an overlay of the grain orientation on a low magnification SEM micrograph. Quantitative orientation information in the form of pole figures (PF) and inverse pole figures (IPF) is included for each composition in Figures 8 and 11. According to the EBSD maps and IPF of the samples, there was no significant texture evident. Investigation of the microstructure present after the post-build SOQ process, the grain structure that persists during the MA and FHT processes, was conducted and is included in Figures 9 and 12. Note the uniform grain growth that occurs in both the Co-lean and full-Co compositions.  
Figure 6: Co-Lean DED samples 1–8 laid down horizontally for comparison. The left side of each sample was the point of connection to the build plate and the right side is the free end (top of the rod, i.e., build direction right). The left-hand scale bar represents 10 mm.  
Figure 7: SEM images of the DED full-Co alnico build sample C (build direction up) with corresponding EBSD map (**top**) and higher magnification image of a selected edge region (**bottom**).  
Figure 8: Orientation information from the region of DED sample C shown in Figure 7 with PFs for the [100], [110], and [111]-type planes (**top**) and IFFs for the sample X, Y, and Z directions (**bottom**). Of note is the lack of apparent texturing.  
Figure 9: Post SOQ microstructure of sample C, DED AM fabricated full-Co alnico.  
Figure 11: Orientation information from the region of the Co-lean sample 8 shown in Figure 10 with PFs for the [100], [110], and [111]-type planes (**top**) and IPFs for the sample X, Y, and Z directions (**bottom**). Of note is the lack of apparent texturing.  
Figure 10: SEM image of the DED Co-lean alnico build sample 8 (build direction up).
# Dual-Frequency Linear-to-Circular Polarization Converter for Ka-Band Applications
## 5 Conclusions  
This paper presents the realization and the measurement of a dual-band linear-to-circular polarization converter based on a multilayer printed circuit board (PCB). The converter consists of six substrate layers separated by five foam spacers. The three top layers are identical and contain an \(\mathrm{T}^{\prime}\)-type strip while the three layers on the bottom side are realized with three identical Jerusalem crosses (JC). An equivalent transmission line circuit model was used for the preliminary design of the unit cell which provides an initial estimate for further full-wave optimization. The output wave was converted to an LHCP signal in the lower band, and an RHCP signal in the upper band when transmitted through the proposed surface. A prototype was fabricated and measured. A close agreement was observed between simulated and measured results. The measured AR bandwidth was 12.5% and 8.7% in the K and Ka band respectively, with a maximum insertion loss of 0.5 dB.  
Conceptualization, F.G.; methodology, E.A.; software, E.A.; validation, F.G.; formal analysis, F.G.; investigation, F.G.; resources, F.G.; data curation, F.G.; writing--original draft preparation, E.A.; writing--review and editing, E.A.; visualization, F.G.; supervision, E.A.; project administration, E.A.; funding acquisition, E.A. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The study did not report any data.  
The authors declare no conflict of interest.
###### Abstract  
Pb-contaminated soil poses inherent risks for the spread of antibiotic resistance genes (ARGs). However, few reports have investigated the distribution of lead resistance genes (LRGs), particularly their role in ARGs dynamics during Pb-contaminated soil remediation. This study explored the mechanisms driving ARGs variation under different remediation strategies. The results indicated that an increase in the total abundance of ARGs after applying montmorillonite (Invite), the composite remediation agents of MgO and Ca(H\({}_{2}\)PO\({}_{4}\)) (MgO-Ca(H\({}_{2}\)PO\({}_{4}\))\({}_{2}\)), and the composite remediation agents of montmorillonite, MgO, and Ca(H\({}_{2}\)PO\({}_{4}\))\({}_{2}\) (Invite-MgO-Ca(H\({}_{2}\)PO\({}_{4}\))\({}_{2}\)). Bioelectrochemical systems (BES) effectively reduced ARGs abundance, and when combined with Invite-MgO-Ca(H\({}_{2}\)PO\({}_{4}\))\({}_{2}\), lowered the risk of ARGs proliferation linked to antibiotic deactivation. Changes in Pb concentration and pH reshaped microbial communities, impacting both LRGs and ARGs. To reduce the risk of ARGs proliferation and transmission during, various control strategies, such as modifying Pb stress, adjusting pH, and manipulating microbial community structure, have been proposed. The study provided theoretical foundation and practical strategies for controlling ARGs dissemination during the remediation of heavy metal-contaminated soil.  
bioelectrochemical system; lead-contaminated soil; antibiotic resistance genes; lead resistance genes; microbial community Article
## 5 Discussion
### Challenges and Practical Issues in Solar EVs  
Technological challenges exist for solar EVs, but efforts are being made to address them. Adopting solar EVs faces challenges such as low efficiency, limited energy storage, and infrastructure needs. As mentioned earlier, current PV cells have 20-25% efficiency, with ongoing research on multi-junction cells and perovskite materials to improve this. Perovskite cells are regarded as the future of VIPVs because they hold significant potential for achieving high efficiency, low cost, ultralow weight, and flexibility compared with those of silicon crystalline-based cells [14]. That is, perovskite cells can be attached to multiple sides of a vehicle. However, this technology still faces many technical challengesfor the mass production and commercialization of solar EVs due to limitations in longevity and reliability compared to large-scale silicon crystalline cell-based modules. Thus, if these issues are solved in the future, the PV potential of solar EVs could be significantly increased. Moreover, efforts should be made to include advanced battery technologies to increase storage capacity and designs that use lightweight materials to improve efficiency. Vehicles should be designed to be lightweight and aerodynamic, utilizing innovative design techniques to reduce weight and drag.  
There is more to discuss on the factors concerned with an estimation of the PV potential of a solar EV from a practical point of view. First, PV modules integrated into vehicles should exhibit exceptional durability to endure diverse operational conditions, including adverse weather phenomena and potential physical impacts. Any damage sustained by these modules could significantly impair the vehicle's capacity for power generation, thereby compromising its overall performance [14]. Second, PV modules experience a degradation rate of approximately 0.5% per year according to the published literature [46]. This study has not accounted for this degradation in potential calculations, as the estimates focused on the PV potential for a single trip or year. However, this degradation should be considered in analyses spanning multiple years. The third is the effect of vehicle design on the PV potential of a solar EV. VIPV systems vary in design, including curved PV modules with flat glass structures, lightweight flexible modules, and rigid lightweight modules. These differing geometries and weights lead to varied power generation efficiencies. Due to higher partial shading frequency compared to ground-mounted PV modules, more resilient electrical architectures, such as increasing the number of bypass diodes in series-connected cell modules, are recommended for EV applications [14]. The vehicle design factor will need to be considered when estimating the PV potential of solar EVs in the future.
# A Damage Model for Concrete under Fatigue Loading
## 4 Verification and Discussions
### Behaviors of Concrete under Fatigue Compression with Constant Amplitude  
In order to verify the effectiveness of the proposed model, the predictions are obtained using a calibration method similar to that in the literature [45] and compared with the experimental results. A series of experiments of concrete under fatigue compression with a constant amplitude are conducted and the results are reported in [57]. In this section, a typical result is selected for model verification. By using the definition in Equations (38-40), the calibrated parameters are obtained and listed as follows, \(E_{0}=32.3\) GPa, \(f_{\rm cu}^{-}=49.3\) MPa, \(A_{1}{}^{-}=0\), \(A_{2}{}^{-}=1\), \(\epsilon_{0}{}^{-}=1700.7\)\(\mu\varepsilon\), \(p^{-}=2.138\), \(A_{3}{}^{-}=1.864\), \(A_{4}{}^{-}=6.961\), \(A_{5}{}^{-}=2.702\), \(B_{1}=38.19\), \(B_{2}=-80.77\), and \(B_{3}=44.66\). Figure 8 illustrates the agreement of the predicted and the experimental results. In detail, initially, the three stages evolution of cyclic creep (i.e., the total fatigue strains and residual strains) of both the predicted and experimental results are coincidental (Figure 8a). Additionally, the proposed model is able to reproduce the stiffness degradation during fatigue life (Figure 8b).
## 3 Results  
BenPros Reduced the Expression of BPH Regulators in Testosterone-Induced LNCaP-LN3 Cells without Affecting Cell Viability  
The cytotoxicity of BenPros against LNCaP-LN3 cells was measured by MTT assay. LNCaP-LN3 cells were pre-treated with different concentrations (12.5, 25, 50, and 100 ug/mL) of BenPros for 24 h. There was no significant cytotoxicity following the treatment in our study (Figure 1A). In addition, treatment with 10 ng/mL of testosterone showedno cytotoxicity, and BenPros treatment exhibited no cytotoxicity, even in the presence of testosterone (Figure 1B).  
To investigate the regulatory ability of BenPros on BPH regulators, we performed Western blot analysis. As shown in Figure 1B, BenPros markedly inhibited the expression of AR, PSA, and 5 aR2 proteins in a dose-dependent manner, induced by testosterone in the LNCaP-LN3 cell line (androgen-sensitive prostate cancer cells).  
Figure 1: Effect of BenPros on cell viability and the expression of BPH regulators in LNCaP-LN3 cells. (**A**) Cell viability of LNCaP-LN3 cells treated with BenPros in the absence of testosterone treatment. (**B**) Cell viability in testosterone-treated LNCaP-LN3 cells. (**C**) Representative western blots of androgen receptor (AR), prostate-specific antigen (PSA) and 5\(\alpha\)-reductase type 2. Cells were pre-treated with BenPros in the presence of various concentrations for 30 min and treated with testosterone (10 ng/mL) for an additional 24 h. \(\beta\)-Actin was used as an internal standard in western blot. Blots are normalized to \(\beta\)-actin. Values are presented as the mean \(\pm\) standard deviation from three separate experiments. ***\(p\) < 0.001 vs. control; ***\(p\) < 0.01 and ***\(p\) < 0.001 vs. testosterone.  
BenPros Reduced the Elevated Levels of Inflammatory Cytokines in LPS-Induced Macrophages without Affecting Cell Viability  
The cytotoxicity of BenPros against RAW264.7 cells was measured by MTT assay. RAW264.7 cells were pre-treated with different concentrations (12.5, 25, 50, and 100 \(\upmu\)g/mL) of BenPros for 30 min and then treated with LPS (100 ng/mL) for an additional 24 h. As shown in Figure 2A, a high concentration of BenPros (50 and 100 \(\upmu\)g/mL) showed significant cytotoxicity in single treatment. However, in the presence of LPS, the treatment of 100 ng/mL LPS showed significant cytotoxicity (Figure 2B). Treatment with BenPros did not restore LPS-induced cytotoxicity, but there was no additional cytotoxicity.  
To investigate the anti-inflammatory effects of BenPros, we used LPS to stimulate the release of IL-6 and TNF-\(\upalpha\) from macrophages to mimic the inflammatory environment. After stimulation with LPS for 20 h, the secretion of IL-6 and TNF-\(\upalpha\) in the supernatant was significantly increased. However, the inflammatory cytokine levels were significantly decreased by the addition of BenPros. As shown in Figure 2C,D, IL-6 was more effectively reduced than TNF-\(\upalpha\). Furthermore, BenPros treatment alone did not affect the basal levels of IL-6 and TNF-\(\upalpha\) in macrophages.
## 3 Results  
Figure 2 presents results of feature selection on the number of sensors as input data using the Bayesian optimization method. For single LSTM, ANN-LSTM, RF-LSTM and SVM-LSTM models, 96, 96, 98 and 99 sensors were selected, respectively. Results of the objective function at the time when the sensor was selected were 14.49, 15.38, 6.53 and 4.94, respectively. Table 4 shows classification accuracies of ANN, RF, and SVM as motion classification models of the proposed algorithm. Based on confusion matrix results of 10-fold cross-validation, average accuracies of ANN, RF, and SVM were 83.54 \(\pm\) 4.48, 91.67 \(\pm\) 3.40, and 94.00 \(\pm\) 2.43%, respectively. There was a significant difference (_p_ < 0.01) between the accuracy of ANN, RF, and SVM models. In Table 5, RMSE, rRMSE, and R of each model were calculated to evaluate the performance of single LSTM, ANN-LSTM, RF-LSTM, and SVM-LSTM models. With the squat posture, rRMSE (%) results of single LSTM, ANN-LSTM, RF-LSTM, and SVM-LSTM were 9.38-18.64, 8.81-20.35, 8.06-16.33 and 8.44-14.03, respectively. With the stoop posture, rRMSE (%) values were 9.26\(\sim\)18.70, 9.59\(\sim\)18.36, 7.91\(\sim\)15.36 and 8.02-13.73, respectively. In both squat and stoop lifting tasks, the knee showed the highest rRMSE and a low correlation coefficient while the hip joint showed the lowest rRMSE with a high correlation coefficient. \begin{table}
\begin{tabular}{l c c c c} \hline \hline  & **1. ANN** & **2. RF** & **3. SVM** & **ANOVA** & **Post Hoc Test** \\ \hline \hline \multicolumn{1}{c}{Squark accuracy (\%)} & 87.06 \(\pm\) 9.11 & 91.36 \(\pm\) 7.16 & 92.84 \(\pm\) 6.00 & - & - \\ \multicolumn{1}{c}{Stoop accuracy (\%)} & 80.26 \(\pm\) 5.67 & 92.15 \(\pm\) 5.57 & 94.59 \(\pm\) 2.93 & - & - \\ \multicolumn{1}{c}{Total accuracy (\%)} & 83.54 \(\pm\) 4.48 & 91.67 \(\pm\) 3.40 & 94.00 \(\pm\) 2.43 & F = 16.1 (_p_ < 0.01) & 2, 3 \(>\) 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Symmetric lifting task posture classification accuracy for three classification models. Figure 2: **(a)** Selected optimal sensor location; **(b)** The progress of optimization using Bayesian optimization showing the objective function value for selecting optimal input feature.
# A Survey on Unmanned Surface Vehicles for Disaster Robotics: Main Challenges and Directions
## 4 Use of USVs in Environmental Disasters with Contaminants
### Chemical Hazards  
Although hydrocarbons can naturally occur at sea through seepages on the ocean floor, oil & gas in large quantities can bring environmental risks to water life and man-made constructions at sea. The presence of oil spills from natural sources is traditionally used to indicate the presence of underwater oil fields, a task which can even be performed by USVs [99; 94], resulting in substantial economic growth of a region. However, oil & gas spills are typical sources of environmental disasters [95; 96; 97], profoundly affecting water life and local economies. Environmental disasters involving oil pollution entail catastrophic consequences for marine habitat. They often spread out hundreds of nautical miles from the source of an incident and cause severe harm to the maritime environment [92], affecting birds, mammals, and mainland shorelines. Such disasters are even more destructive when harsh chemical solvents and cleaning materials are used. Studies from [PERSON] et al. [98] show that the most significant maritime environmental disasters were caused by oil spillage from ship collisions or grounding at sea.  
The recent history of oil spills has clearly shown their catastrophic effect on coastal ecosystems. Oil spills have been taking place at sea since the early days of offshore oil extraction and oil-carrying tankers [99]. The largest oil spill in the history of the petroleum industry occurred in 20 April 2010, with the Deepwater Horizon Macondo semi-submersible offshore drilling rig in the Gulf of Mexico: 210 million gallons of crude oil were released, affecting 180,000 km of ocean surface, where 39,000 personnel, 5000 vessels, and 110 aircraft were involved in cleaning, and over 700 km of booms were deployed [100]. In this disaster, autonomous marine robots played a pioneering role in fighting an oil spill [101]. Since then, many approaches using USVs have been studied to detect and mitigate the effects generated by such disaster, avoiding human exposure to hazardous conditions and reducing the cleanup labor costs. Table 3 presents the work that use USVs to deal with oil spill problems, where the papers are grouped by task-- \(NR\) means \"Not Reported\" to data not reported by the authors.
## 1 Introduction
### NIRF Coupling with ECT  
One of the most popular imaging modes in biomedical sciences for visualizing cells and tissues is fluorescence imaging [13]. NIRF (near-infrared fluorescence) imagers provide information on the distribution of the weak (relative to white-light reflectance) fluorescence signal arising from the excited fluorescent agents within the surgical field [13, 14, 15]. A charge-coupled device camera captured and recorded the fluorescent signal [15]. As ICG works in the optical window of tissue, it is currently the most popular contrast used for in vivo fluorescence imaging [13]. There is a growing interest in using NIRF-ICG in oncology for identification and tumor assessment in human and veterinary medicine [13,16]. Coupling ECT with NIRF-ICG is a novel approach that can influence the outcome of the ECT treatment. The authors report that this is the first examination of the use of NIRF imaging during ECT treatment.  
This study aimed to investigate the effect of electroporation of the normal and tumor cells with indocyanine green and a mixture of ICG with BLM on cell viability, accompanied by the clinical application of NIRF imaging for the ECT treatment in a feline in vivo case study.