esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Results and Analysis  
This section presents both quantitative and qualitative performance results for the three proposed models. A comparative analysis highlights the superior performance of the difference-based model while also providing a deep dive into its inherent limitations to establish a valuable benchmark for future research. Furthermore, this study discusses the applicability of the proposed models in real-world disaster response scenarios.
## 3 Results and Discussions
### Transmission Path Characteristics
This enabled an assessment of the influence of each trajectory cluster on air pollution dynamics in Chenzhou City across the four seasons, as depicted in Table 2.  
Figure 7: Seasonal variations in backward trajectory cluster analysis for Chenzhou City (**(a)** Backward Trajectory Cluster Analysis (Spring) (**b**) Backward Trajectory Cluster Analysis (Summer) (**c**) Backward Trajectory Cluster Analysis (Autumn) (**d**) Backward Trajectory Cluster Analysis (Winter)) (note: the illustration was crafted utilizing ArcGIS software, specifically version 10.2. For further reference, please visit the following URL: [[https://www.arcgis.com/index.html](https://www.arcgis.com/index.html)]([https://www.arcgis.com/index.html](https://www.arcgis.com/index.html)) (accessed on 16 October 2023)). Drawing insights from both Figure 7 and Table 2, distinct disparities emerge in the likelihood of occurrence, spatial extent, velocity of movement, pollutant concentration, and seasonal distribution of trajectory clusters across the various seasons in Chenzhou City. During the spring season, Trajectory 6 emanates from Xinji, traversing Ganzhou and Xinyu in Jiangxi Province. This trajectory boasts the highest occurrence probability and pollution trajectory proportion among the six trajectories, standing at 24.95% and 20.69%, respectively. Owing to its limited distance and relatively swift transmission speed, the constrained trajectory and abbreviated air mass transit distance hinder the dispersion of pollutants. This constraint primarily accounts for its elevated pollution trajectory proportion and intensified pollution concentration, reaching 112.46 \(\upmu\)g\(\cdot\)m\({}^{-3}\). In contrast, Trajectory 3, stemming from western Mongolia and crossing the Loess Plateau, navigates the Qinling Mountains before extending to Hunan and traversing urban centers such as Xi'an, Linfen, Shaoyang, and Yongzhou. Despite its recorded pollutant concentration of 113.91 \(\upmu\)g\(\cdot\)m\({}^{-3}\), its likelihood and contribution to pollution trajectories during spring are notably limited, accounting for just 10.46% and 9.52%, respectively. During the summer season, the predominant focus lies on short-distance transmissions. Notably, Trajectory 2, originating from the northern and western regions of Guangdong and passing through locales such as Shaoguan, Qingyuan, and Heyuan, boasts the highest occurrence probability at 35.60%. However, its pollution trajectory proportion and concentration stand at a mere 1.02% and 77.13 \(\upmu\)g\(\cdot\)m\({}^{-3}\), respectively. When juxtaposed with the national standard secondary concentration daily average limit for PM\({}_{2.5}\) (75 \(\upmu\)g\(\cdot\)m\({}^{-3}\)), the analysis indicates that the majority of air masses reaching Chenzhou during summer convey relatively diminished concentrations of pollutants. During the autumnal season, atmospheric trajectories emanating from Hubei, Jiangxi, and Hunan prevail. Particularly noteworthy is Trajectory 1, originating from Jiangxi
## 4 Numerical Results and Comparisons  
In making use of the key rate formulae of Equations (19) and (22) above, we need to first assume a value for the security parameter \(\epsilon_{S}\), for which we set as \(10^{-10}\). Then, for a given value for errors in the CM (errors in EM is then immediately defined), setting the number for \(M(n,k)\), we determine the value \(k\) which achieves the maximal value for secure key length. As \(M(n,k)\) approaches infinite for \(n\rightarrow\infty\), following [9] we could let \(k<\mathcal{K}\sqrt{n}\) for some fixed \(\mathcal{K}\), so that  
\[\lim_{n\rightarrow\infty}\mu(n,k)=0, \tag{23}\]  
and consider secure keys within the infinite key regime. In the infinite key regime, the efficiency for the protocols SDC becomes  
\[\lim_{n\rightarrow\infty}L_{SDC}/2M(n,k)=1-h_{2}\left(\frac{q}{2}\right)- \frac{h_{4}(\mathcal{Q}_{E})}{2}, \tag{24}\]  
and for LM05 we have  
\[\lim_{n\rightarrow\infty}L_{LM05}/M(n,k)=1-h_{2}\left(\frac{q}{2}\right)-h_{ 2}(Q_{f}). \tag{25}\]  
It is worth noting that the 'additional' term \(\sqrt{nk}\) for amount of bits that can be derived from EM in LM05 becomes negligible in the infinite key regime and \(\lim_{n\rightarrow\infty}\sqrt{nk}/M(n,k)=0\). Furthermore, for this condition, it would be only the final term (related to error correction) that would determine how one protocol outperforms another.
# A Digital Currency Architecture for Privacy and Owner-Custodianship
## 4 Analysis
### Impact on the Financial Industry  
Our proposal frames CBDC as a distinct financial instrument but one that nonetheless shares many features with cash, including being fully collateralized and not providing for the ability to lend or rehypothecare. In essence, it would strictly remain M0 money. Moreover, we are not proposing a subordinate role for banknotes, nor for bank deposits. On the contrary, we understand all three instruments to have merit and value to households and firms within an economy and can be used to complement one another and increase the overall welfare of individuals and firms through the adoption of CBDC [26]. An example of the inherent difficulties within proposals that argue for the abolition of cash is that the increase in its use is predominantly situated within lower socioeconomic segments of a community, and using CBDC to drive out cash would adversely impact those households and firms. One question to ask is whether the cost of maintaining cash infrastructure outweighs the cost of providing universal access to technology infrastructure that would replace it.  
The most direct impact of our approach to digital currency on the financial industry involves risk management, on several levels. By improving the speed of settlement, digital currency can be used to facilitate liquidity risk management among financial institutions. Digital currency can also be used to address systemic risk, both explicitly, by offering regulators a view into substantially every transaction, as well as implicitly, by offering governments a tool to implement stimulus while controlling the aggregate leverage in the system.  
Considering that, in general, DLT offers a promising risk-mitigation tool [59], our design relies on a DLT network operated by MSBs and other private-sector institutions rather than a centralized ledger run by a single public (or private, like in all the stablecoin solutions) organization. As such, our approach addresses a variety of risks associated with relying upon a central arbiter: (1) technical risks associated with availability, reliability, and maintenance; (2) risks associated with trust and operational transparency; and (3) financial and legal risks. Our approach also allows the private sector to operate the infrastructure for retail payments, clearing, and settlement, while allowing government regulators to oversee the system at an organizational level. Because we imagine that digital currency will complement rather than substitute for bank deposits, our approach leverages the role of commercial banks without forcibly decreasing their balance sheets. In particular, because we believe that the main purpose of CBDC tokens will be to facilitate electronic payments rather than to serve as a long-term store of value, we do not anticipate that the balance sheets of central banks will increase significantly as a result of its introduction.
## 4 Experiment Results  
In this part, a series of experiments are designed to estimate the accuracy of the developed DMDD, location sources accuracy indicators, and final proposed H-IPS. Two experimental sites contain the office and corridor scenes and NLOS effects are selected for evaluation purposes. In this case, the Google Pixel 3, 4, and 6 are applied as the test terminals, and the sampling rate of the Wi-Fi, acoustic signals, and sensors are 0.3 Hz, 1 Hz, and 50 Hz, respectively.
## 3 Analysis of Resources for the Hybrid System
### Demand and Recorded Weather Conditions  
To ensure the suitability of the equipment considered in this study, it is important to consider parameters such as energy demand and weather conditions, which are key when placing the complete equipment into operation. The optimal physical location within the building must then be identified, especially the location of the solar panels, avoiding shadows, ensuring they are not exposed to destruction or deterioration, and ensuring access to allow for periodic maintenance. All of these factors are essential, and the most precise configuration will be achieved based on demand conditions. Parameters such as solar radiation, temperature, and system load, which must always be considered, are essential to avoid absorbing a large amount of energy from the grid. Ideally, the system should aim to be autonomous despite having a grid connection. The electrical demand profile is presented in Figure 3a, while the heating and cooling energy used are presented in Figure 3b. The solar radiation and temperature profiles for the location are also presented in Figures 3c and 3d, respectively. As you can see, the system is not very large, but it could serve as a reference for new developments of this type in neighboring areas or in sites with similar characteristics where medical care is needed in rural areas. Ecological infrastructures, like those developed, complement each other very well, not only due to their architectural design but also due to their internal operating conditions. Energy efficiency is vital to ensuring service. The heating and cooling loads in the building's compartments can be seen in Figure 3b. The consumption levels do not exceed 2950 W for heating or 1940 W for cooling.  
Figure 3: Main input data: (**a**) seasonal load profile; (**b**) heating and cooling profile; (**c**) solar radiation; (**d**) temperature.  
Heat pumps will be used to source heat from the natural environment and transport it into the buildings, heating them. It also works in reverse, transporting heat from the interior of the rooms to the exterior and cooling them. This equipment is presented as an excellent option for providing greater thermal comfort to the various spaces within the building, and especially in a medical center, it is essential that these requirements be met. Furthermore, this technology is mature and ready to be utilized to meet the diverse needs of buildings.
## 3 Application Domains
### Asset Utilization  
Thanks to ubiquitous Internet access and M2M communication, it will be possible to know anytime and anywhere the state of industrial assets. This is related not only to their current condition but also to their location. Some embedded sensors, such as RFID tags, will be used to locate assets that can be moved from one place to another, thus improving _asset tracking_ and reducing _inventory management_ costs and mistakes [27]. Furthermore, data gathered from sensors embedded into assets or workers' personal devices will be used for _environmental monitoring_, to ensure that working conditions are good [28]. Smart meters will be used to collect information on _energy consumption_, which can be later analysed to find optimal energy utilization patterns [10]. Analysis of data coming from asset monitoring will be used for _fault detection_ and _predictive maintenance_ purposes [29]. Based on  
Figure 1: Enabling technologies and application domains in Industry 4.0.  
Figure 2: Application domains and related applications in Industry 4.0.  
the acquired information and also taking advantage of M2M communication, assets will be _remotely controlled_ to improve industrial processes [30].
## 3 Related Work  
SCAs represent a significant threat to the security of IoT devices, leveraging physical leakages such as power consumption, electromagnetic emissions, and timing information to extract sensitive cryptographic keys. Addressing these vulnerabilities has been a major focus in both academic and industrial research, leading to the development of hardware- and software-based countermeasures.
## 3 Results  
### The Construction and Validation of the CT26 EMMPRIN-KD Cells  
To learn about the involvement of EMMPRIN in the metastatic outbreak, we knockdown its expression in the CT26 parental cell line (CT26-WT), using the lentivirusv vector. After 3 weeks of continuous exposure to puromycin, we isolated cells that expressed reduced EMMPRIN levels. Since the cells did not carry the GFP marker, which is immunogenic injected to mice and drives tumor rejection [37], we could not follow the cells or select them according to the intensity of the GFP expression. Therefore, we used a strategy of limiting dilutions, and seeded the cells at a concentration of one per well, so that the resulting clones originated from the same cells and were homogenous in their EMMPRIN expression. We then selected a clone that showed a maximal reduction in EMMPRIN expression (CT26-KD), and used it for the following experiments.  
We examined the expression of EMMPRIN at both the protein and RNA levels. We observed no change in the EMMPRIN mRNA levels compared to the CT26-WT cells (Figure 1A), whereas the protein levels within the cells (Figure 1C,D) and the secreted levels of EMMPRIN (Figure 1B) were significantly reduced. This strongly suggests that the lentivirus vector regulation on EMMPRIN expression is post-transcriptional, in agreement with our previous experiments that implicated miR-146a-5p in its regulation [38]. It is noteworthy that the levels of EMMPRIN in the CT26-KD cells are reduced by 70-86%, as assessed by the immunofluorescence and by the WB analysis, so that sufficient amounts of the protein are still present in the CT26-KD cells to allow for their viability. In the supernatants, we observed a reduction of only 40%, which could be explained by the accumulation of EMMPRIN over time.
## 2 Materials and Methods
### Calculation of Energy Requirement  
Operating costs are directly dependent on the efficiency of the treatment processes used in advanced oxidation processes. To facilitate comparison of reaction performance, an indicator called \(EE\)/O (electrical energy required to reduce the pollutant concentration by one order of magnitude in one cubic meter of water or wastewater) was applied. The \(EE\)/O metric provides a direct link to the energy efficiency of the AOP process, independent of system characteristics, allowing for the comparison of different AOP technologies. This evaluation parameter is essential not only to compare AOP technologies but also to provide the data needed for scaling and economic analysis compared to conventional treatment methods [7]. The \(EE\)/O values were calculated based on Equation (8):  
\[\frac{EE}{O}=\frac{P\cdot t\cdot 1000}{V\cdot 60\log\left(\frac{C_{0}}{C_{t}} \right)}\left[\frac{\text{kWh}}{\text{m}^{3}}\right] \tag{8}\]  
\(P\) is the power input of the UV lamp, the ozone generator, the ultrasound generator [kW]; \(t\) is the oxidation time [min]; \(V\) is the volume of the effluent [liters]; \(C_{t}\) is the final concentration of the contaminant; and \(C_{0}\) is the initial concentration of the contaminant.
# A Proposal of Printed Table Digitization Algorithm with Image Processing
###### Abstract  
Nowadays, _digital transformation (DX)_ is the key concept to change and improve the operations in governments, companies, and schools. Therefore, any data should be digitized for processing by computers. Unfortunately, a lot of data and information are printed and handled on paper, although they may originally come from digital sources. Data on paper can be digitized using an _optical character recognition (OCR)_ software. However, if the paper contains a table, it becomes difficult because of the separated characters by rows and columns there. It is necessary to solve the research question of \"how to convert a printed table on paper into an _Excel_ table while keeping the relationships between the cells?\" In this paper, we propose a _printed table digitization algorithm_ using image processing techniques and OCR software for it. First, the target paper is scanned into an image file. Second, each table is divided into a collection of _cells_ where the topology information is obtained. Third, the characters in each cell are digitized by OCR software. Finally, the digitalized data are arranged in an _Excel_ file using the topology information. We implement the algorithm on _Python_ using _OpenCV_ for the image processing library and _Tessenct_ for the OCR software. For evaluations, we applied the proposal to 19 scanned and 17 screenshotted table images. The results show that for any image, the _Excel_ file is generated with the correct structure, and some characters are misrecognized by OCR software. The improvement will be in future works.  
digitization; printed table; OCR; Python; OpenCV; Tesseract +
Footnote †: journal:
## 4 Discussion
### Limitations of the QPAML Classification Model  
The QPAML is fed with FBA simulations, and therefore, it is predominantly driven by stoichiometric forces, omitting thermodynamic and regulatory factors.  
The model may misclassify specific reversible reactions because fluxes could not represent truly physiological conditions. For instance, the tryptophanase reaction degrades tryptophan under normal conditions. Still, the reverse reaction is a shorter pathway to produce tryptophan, which is only possible in exceptional conditions with low concentrations of tryptophan and high concentrations of pyruvate and ammonia [44]. A potential solution to this limitation could be the implementation of thermodynamic Flux Balance Analysis (tFBA) [99], albeit with the drawback of requiring reaction thermodynamic values. Alternatively, manual correction can be applied by ensuring that pFBA optima reactions align with the most frequently described pathways.  
The QPAML model demonstrates robustness in classifying most reactions that enhance tryptophan production, such as the overexpression of _pntBA_ genes that reinforce the supply of NAD and NADPH cofactors when depleted by the Crabtree effect [9; 10]. However, the overexpression of _sthA_, catalyzing the reverse reaction, may be explained as a compensatory mechanism to _pntBA_ overexpression [9].  
Since this model relies on QPA, its classification is purely qualitative, lacking scores for reaction modulation. This algorithm restriction is attributed to limited experimental information; however, the model can adapt to the availability of more data by applying Extended Qualitative Perturbation Analysis, which provides quantitative results [34].  
In this study, we used QPAML built with qualitative attributes of the reactions that constitute a metabolic network. Once the candidate reactions for disruption were classified, they were prioritized, considering their position in the metabolic network. Currently, algorithms such as Fuzzy-Based Deep Attributed Graph Clustering use the graph's structure and the attributes of its nodes and vertices to perform seamless clustering tasks [100]. These algorithms could be used for reaction classification when a larger dataset of genetic modifications is available.
# Photodegradation Assessment of Calicotriol in the Presence of UV Absorbers by UHPLC/MSE
## 4 Conclusions  
The newly developed UHPLC/MS\({}^{\mathrm{E}}\) method, validated in accordance with ICH Q2(R2) guidelines, demonstrated high specificity, linearity over the range of 50-150 \(\mathrm{\SIUnitSymbolMicro m}\mathrm{L}^{-1}\), satisfactory precision, and accuracy. Photostability studies indicated that calcipotriol undergoes significant degradation in the presence of the UV filter sulisobenzone, which led to the formation of four main degradation products (CP-2 to CP-5). Exposure to sulisobenzone, a commonly used UV filter, induced degradation of calcipotriol both in methanolic solution and commercial formulation. The identification of the degradation products was achieved using UHPLC/MS\({}^{\mathrm{E}}\), and their structures and fragmentation patterns were proposed for the first time. In silico toxicity assessment using the OSIRIS Property Explorer indicated that neither calcipotriol nor its photodegradation products exhibited mutagenic, tumorigenic, reproductive, or irritant properties. Two out of the five degradation products interacted with the VDR in a manner similar to calcipotriol; however, their predicted binding free energies were higher, indicating a potentially weaker pharmacological effect. These findings expand our understanding of calcipotriol stability, emphasizing the significance of assessing interactions not only with excipients but also with commonly used UV filters. The study demonstrates that real-world conditions--such as the simultaneous use of pharmaceutical and cosmetic products--can markedly affect drug stability, which is crucial for maintaining therapeutic efficacy.  
Conceptualization, A.K.-P.; Methodology, A.K.-P. and P.Z.; Software, P.Z.; Validation, M.K.; Formal analysis, P.Z.; Investigation, M.K. and A.B.; Writing--original draft, M.K., A.B. and A.K.-P.; Writing--review & editing, A.K.-P.; Supervision, A.K.-P. All authors have read and agreed to the published version of the manuscript.  
The research was supported by the Polish Ministry of Education and Science, N42/DBS/000356.  
Not applicable.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
A part of this research was carried out with the use of research infrastructure co-financed by the Smart Growth Operational Programme, POIR 4.2 project no. POIR. 04.02.00-00-D023/20.  
The authors declare that they have no conflicts of interest.