esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Expression of the Mutants and Characterisation of Their Hydrolysis Profiles
Similar to the L302 mutants, a decrease in the overall hydrolytic activities was observed in the esterase/lipase assays, with L305N showing the lowest activity. The I529A mutant showed little to no activity, while the I529D, I529G, and I529W mutants showed a comparable (I529G) or even increased (I529D/W) overall activity compared to the WT. The I529D and I529G mutants both showed a favorable increase in the pNPO/pNPP ratio of 2.4 for I529D and of 1.8 for I529G. Furthermore, these mutants showed increased selectivity for pNPH. Figure 1: Relative specific activity [%] of PCI_Lip mutants (expression: \(n=1\), mutants marked with \({}^{\star}\)\(n=3\)) against selected model substrates. The relative specific activities were based on the specific activity [U mg\({}^{-1}\)] of the PCI_Lip WT against pNPO (set to 100%, red line). The photometric esterase/lipase assays were performed in triplicates. The error bars represent the standard deviation of these measurements. In conclusion, the mutations in the substrate channel of PCI_Lip led to mutants with the desired chain length specificity. Especially L302G had a major impact on the hydrolysis profile by shifting the maximal activity from pNPO towards pNPH. L305A showed a less drastic shift in its hydrolysis profile but drastically reduced activity towards pNPP. F91L, L302G, and L305A were selected for further biochemical characterization and application experiments.
# Narrowband-Internet of Things Device-to-Device Simulation: An Open-Sourced Framework
## 5 Conclusions and Future Work
(2018) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] Path loss model for outdoor parking environments at 28 GHz and 38 GHz for 5G wireless networks. _Symmetry_**2018**, _10_, 672. [CrossRef]
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* [PERSON] (2017) [PERSON] Evaluating the Suitability of Narrowband-Internet of Things (NB-IoT) for Smart Grids. Master's Thesis, TU Delft, Delft, The Netherlands, 2017. Available online: [[http://resolver.tudelft.nl/uuid:29b59](http://resolver.tudelft.nl/uuid:29b59) edf-122b-4 adf-b26e-35504a2454 fc]([http://resolver.tudelft.nl/uuid:29b59](http://resolver.tudelft.nl/uuid:29b59) edf-122b-4 adf-b26e-35504a2454 fc) (accessed on 1 March 2018). * [PERSON] et al. (2018) [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] Radio resource management scheme in NB-IoT systems. _IEEE Access_**2018**, \(6\), 15051-15064. [CrossRef]
* [PERSON] et al. (2016) [PERSON]; [PERSON]; [PERSON]; [PERSON] Radio Frequency global positioning system for real-time vehicle parking. In Proceedings of the IEEE 2016 International Conference on Signal Processing and Communication (ICSC), Noida, India, 26-28 December 2016; pp. 479-483. * [PERSON] (2010) [PERSON] _Wireless Communications: Principles and Practice_, 2 nd ed. ; Pearson Education: London, UK, 2010. * [PERSON] et al. (2017) [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON] Narrowband IoT data transmission procedures for massive machine-type communications. _IEEE Netw._**2017**, _31_, 8-15. [CrossRef]
* [PERSON] and [PERSON] (2019) [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON] On the evaluation of the nb-iot random access procedure in monitoring infrastructures. _Sensors_**2019**, _19_, 3237. [CrossRef] [PubMed]
* [PERSON] et al. (2018) [PERSON]; [PERSON]; [PERSON]; [PERSON] Latency-energy tradeoff based on channel scheduling and repetitions in NB-IoT systems. In Proceedings of the 2018 IEEE Global Communications Conference (GLOBECOM), Abu Dhabi, United Arab Emirates, 9-13 December 2018; pp. 1-7.
## 6 Data Preprocessing and Standardization
### Text Tokenization  
Text tokenization is the process of splitting a piece of text into smaller manageable units known as tokens. The tokenization process, applied on tweet t, results in a sequence of tokens tx = (t1, t2,...tk), where x denotes the number of a tweet, and k represents the number of tokens. The sample output on Roman Urdu micro text after tokenization is shown in Figure 3.
## 3 Experimental Results
### In-Plane Shear Resistance  
The skeleton curves the walls are illustrated in Figure 8. The in-plane shear resistance of W1 was low because the historical bricks and mortar were weak. Moreover, irregular shapes of the historical bricks resulted in complicated interactions between the bricks and the surrounding mortar. Failure was more prompt to happen under the combined effect of shear stress, compressive stress, and extra stress introduced by the strain difference between the bricks and the mortar. The wall cracked and crushed severely and lost integrity when it failed. Although it was crushed and split into several parts, the UHPC layer effectively rehabilitated it. The in-plane shear resistance of W1S, which was constructed by strengthening the crushed W1, was 147% higher than that of W1.  
The W2 was strengthened by the UHPC layer before loading, and it had the highest in-plane shear resistance within all the walls. Its resistance was 193% higher than that of W1. It shows that the applied UHPC layer also improved the resistance of the masonry wall that has visible but not severe damages.  
The W3 was strengthened by the reinforced polymer mortar layer before loading. Its in-plane shear resistance increased less than that of W2 and W1S.  
Figure 7: Failure modes of the walls: (**a**) Shear-compressive failure of the unstrengthened W1; (**b**) bed-joint slide of the strengthened walls.
# High-Frequency Artifacts-Resistant Image Watermarking Applicable to Image Processing Models
## 3 Experimental Results and Analysis
### Qualitative and Quantitative Results  
The main objective of this paper is to mitigate the impact of high-frequency artifacts on generative model watermarking, focusing on enhancing imperceptibility and security. It is important to note that strong imperceptibility inherently enhances system security. To achieve this goal, we propose an innovative image watermarking framework that addresses imperceptibility in generative model watermarking within both the spatial and frequency domains. In this section, we will demonstrate the excellent imperceptibility of our proposed framework in both the spatial and frequency domains.
# _Applied_
## 3 Results
### SB Extracts Decrease \(H_{2}\)O\({}_{2}\)-Induced ROS Production in PC12 Neuronal Cells  
As shown in Figure 1, SB extracts (SBW and SBE) at up to 200 \(\mathrm{\SIUnitSymbolMicro g}\)/mL did not affect cell viability compared to H\({}_{2}\)O\({}_{2}\)-treated PC12 cells. At 200 \(\mathrm{\SIUnitSymbolMicro g}\)/mL SBW and SBE, cell viability remained \(>\)100%. Therefore, further experiments were carried out using SB extracts at \(\leq\)200 \(\mathrm{\SIUnitSymbolMicro g}\)/mL.  
To verify the effect of the SB extracts on H\({}_{2}\)O\({}_{2}\)-induced oxidative stress, the intracellular ROS generation was measured based on DCF-DA staining [29]. The intensity of the fluorescent signal from the liberated DCF in the H\({}_{2}\)O\({}_{2}\)-treated cells was significantly increased by 1.9-fold relative to the untreated control (Figure 2a). Treatment with SBW and SBE (12.5 to 200 \(\mathrm{\SIUnitSymbolMicro g}\)/mL) decreased the H\({}_{2}\)O\({}_{2}\)-induced cellular ROS generation in a concentration-dependent manner. The inhibitory activity of SBE on ROS production was higher than that of SBW. SBE at 12.5, 25, 50, 100, and 200 \(\mathrm{\SIUnitSymbolMicro g}\)/mL reduced the ROS level approximately 0.61-, 0.47-, 0.41-, 0.28-, and 0.18-fold, respectively; SBW decreased the ROS level by 0.69-, 0.61-, 0.56-, 0.51-, and 0.53-fold, respectively (Figure 2a). Additionally, SBE reduced the ROS generation in non-treated cells in a concentration-dependent manner. (Figure 2b). Next, we visually investigated the fluorescence changes in the PC12 cells treated with H\({}_{2}\)O\({}_{2}\) (50 \(\mathrm{\SIUnitSymbolMicro m}\)) and SBE (50, 100 and 200 \(\mathrm{\SIUnitSymbolMicro g}\)/mL). As shown in Figure 2c, SBE (50 to 200 \(\mathrm{\SIUnitSymbolMicro g}\)/mL) decreased H\({}_{2}\)O\({}_{2}\)-induced cellular ROS generation in a concentration-dependent manner.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Extract**} & **DPPH 1 ** & **ABTS+2 ** \\  & **(mg AAE 5/g. d.b.)** & **(mg AAE 5/g. d.b.)** \\ \hline SBW 3 ** & 60.91 \(\pm\) 0.13  & 165.14 \(\pm\) 5.08  \\  & 49.63 \(\pm\) 1.02  & 144.84 \(\pm\) 2.82  \\ \hline \hline \end{tabular}
\end{table}
Table 1: Antioxidant activity based on DPPH and ABTS+ assays of _S. borealis_ extracts.  
Figure 1: (a) SB extracts (12.5 to 200 \(\mathrm{\SIUnitSymbolMicro g}\)/mL) and H\({}_{2}\)O\({}_{2}\) (50 \(\mathrm{\SIUnitSymbolMicro m}\)) did not show toxicity in PC12 cells. (b) SB extracts (25 to 200 \(\mathrm{\SIUnitSymbolMicro g}\)/mL) did not show toxicity in PC12 cells. SBW, _Sasa borealis_ water extract; SBE, _Sasa borealis_ ethanolic extract. Data are means \(\pm\) SDs (n = 3).
# An Intelligent Approach to Resource Allocation on Heterogeneous Cloud Infrastructures
## 3 Allocating Resources in Heterogeneous Cloud Infrastructures
### Tier 1: Node Allocation in the Cloud Using Genetic Programming
#### 3.1.1 Allocating Nodes to Virtual Machines  
The CPU allocation problem in a multiprocessor system has a highly complex computational solution. This is an NP-hard problem [18], and several approximate solutions have been proposed based on heuristics [19; 20]. This section focuses on mapping the cores of a set of virtual machines to the cores of NUMA nodes in a CC system. Figure 2 shows an example of a possible mapping scenario. In this case, four virtual machines, each with eight virtual cores, are mapped to a node with eight cores distributed in two NUMA domains. For efficient mapping, the degree to which virtual cores share memory should be considered in order to reduce the contention between them. Likewise, an ideal algorithm would consolidate the virtual cores in the least number of cores in the physical node to apply low energy consumption mechanisms to the idle physical cores.  
Additionally, this system should take advantage of the NUMA domains present in physical machines by mapping virtual cores with a high degree of shared memory to the same NUMA domain to reduce communication costs. Likewise, virtual cores that do not share memory to a high degree should be mapped to different NUMA domains, with the aim of reducing interference problems. Simultaneously, the algorithm should seek to maximize the use of physical cores and reduce power consumption by consolidating virtual cores into the fewest possible number of physical cores.
# Patient-Specific Dosimetry Evaluations in Theranostics Software for Internal Radiotherapy
###### Abstract  
In Internal Radiotherapy, radiopharmaceutical dosimetry provides an accurate estimation of absorbed radiation doses to organs at risk and tumours. In this paper Velocity Theranostics (Varian Medical Systems), is investigated. Its performances are compared to OLINDA 2.0 in both an anthropomorphic phantom and a group of patients. Velocity Theranostics was evaluated with a cohort of patients (15) treated with \({}^{177}\)Lu radiolabelled peptides. The absorbed doses were calculated for the liver, spleen and kidneys, separately with OLINDA 2.0 and Velocity Theranostics using the same set of images. To reduce the contribution of Time-integrated activities (TIAs) on the results and to merely compare the dose calculation algorithms, the OLINDA 2.0 absorbed doses were calculated using the TIA values calculated in Velocity Theranostics. The absorbed doses from Velocity Theranostics were found to be correlated with the doses from OLINDA 2.0 with the TIAs from Theranostics (Lin's coefficient = 0.894 and R\({}^{2}\) = 0.9531). Absorbed doses from Velocity Theranostics are reliable at least as reliable as those for OLINDA 2.0, with many advantages regarding accuracy of calculations and robustness. In conclusion, the personalisation of dosimetry may be totally fulfilled by computational systems for absorbed dose in internal radiotherapy, equipped with a complete workflow and borrowed from external radiotherapy.  
internal radiotherapy; dosimetry; \({}^{177}\)Lu; theranostics; software Article
## 3 Underwater Channel Characterization
### EM Propagation in Freshwater
#### 3.3.2 Absorption Losses in Freshwater  
The amount of absorption loss is calculated using Equation (6) [7]:  
\[\alpha\approx\frac{\sigma}{2}\sqrt{\frac{\mu}{\epsilon}} \tag{6}\]  
where \(\sigma\) is electrical conductivity, \(\epsilon\) is electrical permittivity and \(\mu\) is the permeability of the medium. It is clearly evident from Equations (5) and (6) that the velocity of propagation and the absorption coefficient both are independent of the operating frequency.
# Research Progress in Methods for the Analysis of the Internal Stability of Landslide Dam Soils
## 2 Qualitative Identification of Internal Stability Based on Physical Properties of Soils
### Identification Methods Based on Fine Content and Porosity
#### 2.2.1 Theoretical Formula  
[PERSON] et al. [44] followed the Loebotsjkov theory, assessing the maximum particle size of the filling soil based on the pore size formed by the skeletal particles. A method for evaluating the internal stability of soils has been proposed. When the condition \(4P_{f}(1-n)\geq 1\) is met, the soil is considered internally stable. Here, \(P_{f}\) is the mass percentage of fine particles filling the coarse particle pores, and \(n\) is the porosity of the soil. The theoretical calculation results of [PERSON]'s method have been experimentally validated [42].
# Ethical Issues in AI-Enabled Disease Surveillance: Perspectives from Global Health
## 1 Introduction  
Infectious diseases such as COVID-19 pose a global health threat in an interconnected world. In the last 20 years, resistant infectious diseases such as severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), H1N1 influenza (swine flu), Ebola virus, Zika virus, and now COVID-19 are impacting global health defences, and aggressively flourishing due to the rise of global travel, urbanization, climate change, and ecological degradation.  
In parallel, this episode in global human health highlights the potential for artificial intelligence (AI)-enabled disease surveillance to collect and analyse vast amounts of unstructured and real-time data to inform epidemiological responses. The exploration of the requirements of a global data-driven and epidemic intelligence surveillance system finds precedence in the literature [1], but the implementation has still a long way to go. A 2020 Lancet commentary provides insights into what might be possible in a collective approach to address the unpredictable and evolving COVID-19 transmission rates using AI [2]. However, this promise is also hampered by the challenges of AI, including the opaqueness of the outputs derived from informal sources, and the commensurate need for transparency at multi-stakeholder levels [3, 4].  
AI as a component of global health surveillance systems is relatively new and largely bounded by both specific applications and geographies [5, 6]. Global health itself is builton national public health actions and institutions, primarily concerning population-wide interventions. However, global health is ideally concerned with all strategies for health improvement, whether population-wide or individual-based health care actions. In other words, it goes across geographical administrative boundaries. There is no formalized definition for _global health_, but [PERSON] et al. [7] is widely cited for defining it as: \"an area for study, research, and practice that places a priority on improving health and achieving health equity for all people worldwide\". Taking on board the parameters of this approach, we are faced with both opportunities and ethical stumbling blocks of an AI-enabled disease surveillance for global health. For example, how might we take into account the interconnected levels of individual and population disease contexts and stakeholders, multiple data sources, and geographical boundaries, and the implementation of equitably applied interventions?
## 4 Experimental Verification of Control Algorithm
### Sinusoidal Guidance Experiments  
For the sinusoidal guidance experiments, the input signal was set to sinusoidal 0.1 mrad/s-sin(2 _TK_), for a sampling time \(T=0.001\). The velocity sinusoidal guidance contrast curve and sinusoidal guidance error curve are shown as follows.  
According to the data presented in Figure 10, the pitch axis motor exhibits smooth sinusoidal operation driven by three controllers, but there are large torque ripples because of nonlinear factors such as friction and nonuniform torque. The data presented in Figure 11 show the absolute value of error. When the servo turntable stably tracks the sinusoidal guidance signal, the absolute error RMS of the PID algorithm is 13.7 \(\upmu\)rad/s, the average absolute error is 9.9 \(\upmu\)rad/s, and the maximum absolute  
Figure 9: Contrast curve of rated speed 0.1 mrad/s experiment.  
error is 46 \(\upmu\)rad/s. The absolute error RMS of the chatter-reduced algorithm described in Ref. [22] is 2.8 \(\upmu\)rad/s, the average absolute error is 2.4 \(\upmu\)rad/s, and the maximum absolute error is 15.6 \(\upmu\)rad/s. The absolute error RMS of the proposed chatter-free algorithm is 2.3 \(\upmu\)rad/s, the average absolute error is 2.1 \(\upmu\)rad/s, and the maximum absolute error is 8.1 \(\upmu\)rad/s. There is obvious high frequency noise caused by chattering using the algorithm from [22], but this noise is not present when using the proposed chatter-free algorithm. Therefore, to more clearly analyze the frequency distribution of noise, the sinusoidal guidance absolute error was next analyzed by single-sided Fourier transform in the frequency domain, as shown in Figure 12.  
Figure 11: Absolute value of sinusoidal guidance error curve.  
Figure 10: Velocity sinusoidal guidance contrast curve.  
According to the results presented in Figure 12, nonlinear disturbance can be effectively suppressed by both the proposed and the algorithm described in [22]. The PID linear controller exhibits limited ability to suppress medium and low frequency noise. There is obvious high frequency noise in the error curve caused by the sliding mode chattering of the Ref. [22] chatter-reduced algorithm, reducing the accuracy and the stability of the system. The high frequency noise is significantly reduced by the proposed chatter-free algorithm.  
Meanwhile, it is noted that the biased error generated by the proposed algorithm means that the switching gain is not the optimal, but it is sufficient to prove the advancement of the proposed algorithm. If the switching gain is set to be larger, \(\kappa T=0.7\), the biased error can be eliminated as shown in Figure 13.
## 1 Development Status and Research Content of Fuel Cell  
### Prospect of Fuel Cell  
In the process of collecting, refining, and burning traditional fossil energy, a large number of greenhouse gases and harmful substances are generated, which have harmful effects on the environment, and endanger people's health. As such, it is urgent for people to find alternative energy sources. Hydrogen fuel cells, as a new energy technology, has a wide range of application prospects. In the aspect of urban transportation, hydrogen fuel cell buses have a long driving distance, and are clean, and are environmentally friendly, which can effectively reduce urban pollution. Many cities around the world have dedicated passenger lines [1]. In terms of electricity, renewable energy such as wind energy, solar energy, and other power generation methods are greatly affected by environmental factors. During off-peak periods, fuel cells can store an excess capacity in the form of hydrogen energy. During peak periods, the stored energy can be used to generate electricity, ensuring the stability of the power supply [2, 3]. Research on fuel cell technology is carried out in different countries. Academic achievements in many fields of hydrogen energy technology, such as production, storage, transportation, and power generation, have emerged in large numbers in recent years. Among them, the United States has published the most important papers [4]. Other countries have followed suit and put forward their own new energy development regulations.  
The proper operation of the fuel cell reactor requires the coordination of different systems. The air supply system is used to provide oxygen for the reaction while maintainingpressure inside the reactor. The hydrogen supply system is used to supply hydrogen for the reaction and recycle it. The water management system is used to keep the reaction gas moist and remove excess water. The thermal management system is used to keep the fuel cell temperature within a certain range. Fuel cell cooling methods include air cooling, liquid cooling, phase change cooling, and so on. For higher power fuel cells, liquid cooling is the most common cooling method. Compared with air cooling, liquid cooling has the advantages of a high heat transfer ability, and low flow rate. Fuel cell thermal management control methods include PI (proportional integral) control, fuzzy control, predictive control, and so on. The fuzzy PID control has a fast response speed and a strong anti-interference ability, especially suitable for the control of a hysteresis system. The thermal management system adopted in this paper is a water cooled fuzzy PID control. The membership function is optimized using a double body genetic algorithm to achieve the optimal temperature control.