esa-sceva/satcom-chunk-collection huggingface dataset:
## Appendix A  
This appendix details the costs used for the analysis.  
The total operation cost will be calculated using Equation (11), where \(C_{x}\) is the cost of the energy supplied by \(x\) as detailed below:  
* \(C_{G}\) is the cost of the energy bought from the grid (shown in Figure 4), including the fixed term of the power capacity (approximately EUR 14.4 per day). If \(P_{G}=0\), then \(C_{G}(P_{G})\) will be only that fixed term.
* \(C_{P}\) is the cost of the energy produced by the PV installation. For this study, for a whole year, a constant value \(C_{P}(P_{P})_{[year]}=F\) is assumed, with \(F=\frac{I_{P}}{N}+C_{MP}\), where \(I_{P}\) is the investment needed to build the PV plant, \(N\) is the plant lifetime in years (a linear amortisation of the plant is used with \(N=20\) years), and \(C_{MP}\) is the annual maintenance cost. A value of \(I_{P}=1.5\) EUR/W has been used, considering the cost of panels, electronic inverters, wiring, support structures, and plot renting [68]. \(C_{MP}\) has been calculated considering two 8 h workdays per month (2 \(\times\) 8 h of manpower/month), at a cost of EUR 100 per day. Once F is obtained, for every hour of the year, a cost \(C_{P}(P_{P})=\frac{F}{8/600}\) EUR/h is applied whether the installation is producing energy or is at rest.
* \(C_{B}(P_{B})\) is the cost of the energy produced by the BG reactor. This cost has a fixed term and a variable term. The fixed term corresponds to the linear amortisation of the initial investment \(B=\frac{I_{B}}{N}+C_{MB}\), similar to the case of the PV plant. The cost of this plant in EUR has been estimated as \(I_{B}=200,000+1500\cdot P_{m}+750\cdot V_{b}\), where \(P_{m}\) is the rated power of the motor-generator to be installed (in kW) and \(V_{b}\) is the volume of the BG reactor (in m\({}^{3}\)). These values are based on recently designed facilities data and equipment prices. \(N\) has also been assumed as 20 years. \(C_{MB}\) has been calculatedwith two 8 h workdays per day (2 \(\times\) 8 h of manpower/day), at a cost of EUR 100 per manpower day. The variable cost is estimated as \(C_{Bv}=C_{v}\cdot P_{B}\), where \(P_{B}\) is the energy produced during the considered time interval, and \(C_{v}\) is a term that can have null or negative values, due to the expected income of this plant for receiving and processing animal slurry.
* Finally, in those moments in which \(P_{B}+P_{P}>P_{D}\), the surplus \(P_{E}=P_{D}-P_{P}-P_{B}\) will be sold to the grid at a price \(C_{E}\), which is shown in Figure 4, according to the average prices published by the Spanish system's operators on their website (Red Electrica de Espana) [67].
# Phishing Attacks Survey: Types, Vectors, and Technical Approaches
## 5 Current Anti-Phishing Methodologies and Techniques
### Technical Anti-Phishing Techniques
#### 5.2.1 Black and White Listing  
The primary method by which the threat of phishing websites are mitigated is the use of black and white listing. Blacklisting is an approach whereby an extensive list of domain names or URLs of suspicious or harmful sites is maintained and users can check to see if the site they are being directed to is likely a phishing site. Blacklisting can cause severe financial harm to a phishing site by reducing the amount of traffic by up to 95% [72]. There are many publicly available blacklists available, although some are more effective than others. The primary characteristics that define the effectiveness of a public blacklist can be defined as how long it takes to update the blacklist and the accuracy of the phishing detection used by the blacklist. The use of blacklisting is now often included in browser-based security tools (browser plug-ins and anti-phishing toolbars) for automated detection of suspicious sites to help prevent users from being tricked into entering their credentials into illegitimate sites. There are also other anti-phishing tools that have been developed that scour the internet for clones of official websites to aid in the detection of phishing sites.  
Whitelisting is a database of legitimate sites rather than suspicious ones. However, this method of phishing detection is impractical as it is near impossible to predict the sites the user will go to, and any new site would be classified as suspicious even if it was a legitimate site.
# Photocatalytic Lithography
## 3 Photocatalytic Lithography
### Direct and Remote Photocatalytic Lithography  
[PERSON] et al. first reported that the oxidation of organic molecules and other phenomena associated with photocatalysis does not necessarily occur only on the irradiated photoactive surface, but can also manifest at a relatively considerable distance (up to 500 \(\upmu\)m). The mechanism of this phenomenon--which was called \"remote photocatalysis\" or \"remote photooxidation\" [5; 12]--had been highly controversial until [PERSON] and [PERSON] demonstrated that H\({}_{2}\)O\({}_{2}\) molecules, generated at the photoactive surface mainly from adsorbed atmospheric water (and in a smaller percentage, from oxygen) [9], can migrate in the surrounding air and are cleaved into \({}^{\bullet}\)OH in the exposed areas of the target surface [13; 14] (Figure 2).  
Recently, [PERSON] et al. [16] compared the effect of the remote (\({}^{\bullet}\)OH-mediated) oxidation pathway with the direct (h\({}^{+}\)-mediated) oxidation pathway for the degradation of dyes. They described  
Figure 2: Schematic representation of direct (**a**) and remote (**b**) photocatalytic lithography for the patterning of a self-assembled monolayer (SAM). The photocatalytically-generated reactive oxygen species responsible for the patterning are represented as red stars. Adapted with permission from [15], Beilstein-Institut for the Advancement of Chemical Sciences, 2011.  
the \({}^{\bullet}\)OH-mediated oxidation to be somewhat limited to certain molecular structures and much slower than the direct one. [PERSON] et al. [17] analyzed the effect of different parameters (i.e., humidity and gas flow rate) on the remote oxidation of plasmonic silver nanoparticles by platinum-modified TiO\({}_{2}\), while [PERSON]. [PERSON] et al. [18] analyzed the formation of \({}^{\bullet}\)OH and H\({}_{2}\)O\({}_{2}\) in an aqueous environment. [PERSON] and [PERSON] analyzed the remote photooxidation of different photoactive inorganic materials (i.e., TiO\({}_{2}\), ZnO, and WO\({}_{3}\)) and their metal (Au, Pt, and Ag)-loaded counterparts, demonstrating the superiority of the latter, which apparently was due to processes involving plasmon resonance and hot electrons [19].
## 3 Results and Discussion
### Enhanced Stability of Silica Microcapsules for Harsh Environments  
To prevent or delay fragrance leakage from the microcapsules, we examined coating additional silica on the surfaces of previously synthesized silica microcapsules at room temperature. Hydrolyzed TEOS has stronger affinity with preformed silica surfaces compared with other hydrolyzed TEOS, resulting in seeded growth [40]. A thin silica layer grew on the surfaces of the silica microcapsules after post-silica coating (Figure 2A). The silica shells measured 102.3, 70.0, and 57.7 nm thick, on average, when additional TEOS concentrations of 5% (T5), 3% (T3), and 1% (T1), respectively, were added (Figure 2B). The untreated capsules (T0) had an average thickness of 42.3 nm. The thickness of the silica shell increased as the concentration of TEOS applied increased. However, although the thickness of T5 increased, SEM images revealed that this increase in thickness was less uniform than in the other samples. (Figure 2). Beyond a specific TEOS concentration, additional reactions occurred along with seeded growth on the surfaces of the microcapsules. The addition of more than 6% TEOS resulted in the formation of a gel throughout the phase (data not shown), which suggests that the maximum concentration of 5% TEOS can be added to the microcapsules.  
Stirring speed also had an effect on the reaction during the introduction of TEOS. Hydrophobic TEOS emulsifies into small particles that disperse throughout the phase. However, stirring the mixture at less than 200 rpm for less than 10 min led to phase  
Figure 2: (**A**) Scanning microscopy images of silica microcapsules synthesized following the addition of various concentrations of TEOS, (bar: left, 1 \(\upmu\)m; right, 400 nm) and (**B**) silica shell thicknesses determined using the ImageJ software.  
separation with a large emulsified TEOS phase and non-uniform coating or gelation in the partial phase. In addition, when hydrolyzed sodium silicate was added directly to the phase in place of TEOS, the sol-gel reaction occurred throughout the phase rather than selectively on the silica microcapsule surface (data not shown).  
TEOS presumably hydrolyzed and slowly dissolved in the aqueous phase at pH 4.2, then bound to the silanol groups of the silica microcapsules, which have a stronger affinity for TEOS than other hydrolyzed TEOS, resulting in a seeded growth reaction [41]. However, as the TEOS concentration increases, whether by the higher rate of dissolution of hydrolyzed TEOS in the aqueous phase or, if TEOS is oversupplied, by adding additional TEOS, increasing the reaction temperature, changing the pH to acidic or basic, or adding sodium silicate, as examples, the silica reaction occurs not only on the surface of the microcapsules but the sol-gel reaction also take place in the aqueous phase; thus, the amount of TEOS added, temperature, and pH needs to be adjusted.
# From Genomics to AI: Revolutionizing Precision Medicine in Oncology
## 4 Genomics in Cancer Treatment
### Contributions and Limitations of Genomics in Cancer Treatment  
In summary, genomics has profoundly transformed cancer treatment by enabling highly personalized and effective strategies through targeted therapies and immunotherapy. Key contributions include the identification of specific oncogenic drivers, the development of drugs precisely inhibiting these targets (e.g., EGFR and PARP inhibitors), and the use of genomic biomarkers (MSI-H, TMB, neoantigens) to predict responses to immunotherapies [56]. Furthermore, genomic monitoring is crucial for understanding and overcoming drug resistance by tracking tumor evolution and adapting treatment dynamically [57]. However, the integration of genomics into cancer treatment faces several limitations. Despite advancements, drug resistance remains a significant challenge, often driven by new genomic alterations that necessitate continuous monitoring and the development of novel therapies. Not all genomic alterations have actionable targeted therapies, leaving a subset of patients without highly specific options. The high cost of comprehensive genomic profiling and targeted drugs can limit equitable access, particularly in resource-constrained settings [44]. Furthermore, interpreting complex genomic landscapes and predicting treatment responses accurately for every patient remains challenging, requiring further research into predictive biomarkers beyond single gene alterations. The clinical utility of certain genomic findings may also vary, and the optimal timing and sequence of genomic testing throughout a patient's treatment journey are still evolving.
# FLINT: Flows for the Internet of Things
## 2 Case Study--Port of the Future
### Data Transformation  
In the past, ports, port services and general services already have developed systems to improve their day-to-day operations. By interconnecting (existing) infrastructure, the efficiency of the entire port can improve even more. Connecting non-interoperable platforms is often addressed as _platform interoperability_ and requires data transformation. In order to do so, traffic must be transformed and interconnected between several platforms.  
A common way of interconnecting data is by means of the Linked (Open) Data schema ([[https://Sstardata.info/en/](https://Sstardata.info/en/)]([https://Sstardata.info/en/](https://Sstardata.info/en/))) (accessed on 14 July 2021). Linked Data (LD) can be the result of applying the collection of Semantic Web technologies, such as (Resource Description Framework (RDF), Web Ontology Language (OWL), etc.) on non-interoperable data. These tools are standardized by the World Wide Web Consortium (W3C) to provide an environment where applications can query (using SPARQL) and interconnect data from several domains [18]. Converting real world data to interlinked data can be challenging, due to their heterogeneity. This can be optimized using the RDF Mapping Language (RML) [19]. RML uses a Turtle mapfile that defines customized mapping rules, that can be applied to heterogeneous data sources. However, managing multiple data sources requires a specific mapfile on a per device basis.  
Another common problem exists in the management of wireless equipment and IoT devices. In order to limit coding and integration effort it can be useful to have a unified mechanism to manage such wireless tools. For this, several management protocols are available today [20]. However, integration of already deployed infrastructure and sensors with standardized solutions can be hard. In this paper, we focus on the Open Mobile Alliance (OMA) Light Weight Machine to Machine (LwM2M) protocol [21]. FLINT tries to minimize the required effort so that their proprietary format can be transformed into LwM2M compliant equipment.  
An abstract overview of the required components is given in Figure 1.  
Figure 1: An abstract representation of the system. Wireless sensor networks on the left are integrated using Application Programming Interfaces (APIs). Their data are collected in a central point that provides an abstraction for devices with multiple network interfaces. From this central point, data are distributed to processing nodes and other platforms.
# Monthly Precipitation over Northern Middle Atlas, Eastern Morocco: Homogenization and Trends
## 2 Materials and Methods  
### Study Area Description  
The northern Middle Atlas is bounded by the Prerifan hills to the north of the Fezz-Taza corridor, the Guercif basin to the northeast, Oued Moulouya river to the east and the central Middle Atlas to the west and southwest (Figure 1). It is located between 33\({}^{\circ}\)10\({}^{\prime}\) and 34\({}^{\circ}\)20\({}^{\prime}\) north and between 4\({}^{\circ}\)50\({}^{\prime}\) and 5\({}^{\circ}\)30\({}^{\prime}\) west. This mountain area is classified among the best-watered mountain ranges in Morocco and is of great hydrogeological interest. The annual precipitation varies between 200 and 500 mm in most of the territory, and average annual temperatures are generally higher, reaching 22 \({}^{\circ}\)C. The significant elevations and the relatively complex structure of the limestone and dolomitic terrains have allowed the formation of several natural lakes. The particularly favorable climatic factors (precipitation) and the predominance of karst also make it one of the greatest underground water reservoirs, supplying and regulating the upper tributaries of the most important rivers in the country (Sebou and Moulouya) [37].  
In the Middle Atlas, agricultural land covers only 20% of the area. This low rate is explained by the fact that the local economy was once linked to pastoralism [38]. Currently, it is based on unsophisticated agriculture associated with extensive livestock farming and the exploitation of the forest (State domain), which occupies 24% of the space (while 56% is occupied by non-forest rangelands).  
This territory is very seldom studied from a climatic point of view, despite its importance in terms of the supply of water for both drinking and agriculture.
_Applied_  
_sciences_  
_Article_  
**The Effect of Irradiation on the Quality Properties**  
**of Tarhana**  
**[PERSON] and [PERSON] *\({}^{\copyright}\)**  
Department of Food Engineering, University of Pamukkale, 20017 Denizli, Turkey;  
[EMAIL_ADDRESS]  
* Correspondence: [EMAIL_ADDRESS]; Tel.: +90-258-296-3015  
Received: 27 May 2020; Accepted: 3 July 2020; Published: 10 July 2020  
**Featured Application: Irradiation is a useful application to preserve tarhana by preventing microbiological risks and pest formation. An irradiation dose of 5 kGy and below can be applied for the preservation of the tarhana without quality loss.**  
**Abstract:** Tarhana is a traditional food produced by the fermentation, drying and grinding of dough prepared with wheat flour, yoghurt, various vegetables and spices. Microbiological risks and pest formation are the major problems encountered during the storage of tarhana. In this study, the effect of irradiation was determined in order to eliminate microbiological risks and pest formation while preserving the quality features during the storage of tarhana. Depending on the irradiation dose, microbial inhibition occurred in tarhana samples, and the maximum protection was achieved with 10 kGy. Nevertheless, doses of 2.5 and 5 kGy inhibited the growth of _Bacillus cereus_. Additionally, all irradiation doses prevented pest formation. The consistency coefficient of soups prepared with irradiated tarhana samples decreased depending on the irradiation doses. There was no difference in 2,2-diphenyl-1-picrylhydrazyl radical scavenging activity and total phenol content in the control with irradiated tarhana samples. However, the 10 kGy irradiated tarhana sample included higher thiobarbituric acid reactive substances. In conclusion, irradiation was applied for the first time to preserve tarhana by reducing the microbiological risk and preventing pest formation. Accordingly, a 5 kGy irradiation dose was recommended, with which the tarhana rheology was affected slightly.  
**Keywords:** tarhana; food irradiation; microbiological safety; pest control; food safety
## 4 AI-Enabled Intelligent 6G Network Applications
### Smart Agriculture  
The advent of 6G will revolutionize automation and precision agriculture, ushering in a new era of connectivity, data collection, and automation. According to predictions, 6G will be up to 100 times faster than 5G, opening up new possibilities for data collection and real-time analysis. By using this knowledge, farmers will be able to make better decisions and boost agricultural production. The data gathered may include information on the amount of soil moisture present, water utilization, and other environmental factors. With 6G, farmers can quickly obtain information and take action, leading to better decisions and greater yields.  
This automation may save expenses, boost productivity, and lessen the chance of human mistakes. Farmers will have access to real-time connection and speedier data transfer thanks to 6G, which will allow them to manage their business from anywhere. Farmers will thus have better access to business data and control over their businesses [26].
## 4 Discussion
### Comparing to Previous Studies of Sensitive Parameters  
In the flux-based ecological model, the sensitive parameters were \(V_{m}^{25}\), \(\alpha_{q}\), and \(f_{Ci}\) for GPP, and \(ER_{0}\), \(Q_{10}\), and \(f_{Ci}\) for NEE. The variation of \(V_{m}^{25}\) and SIs of \(V_{m}^{25}\) were the main factor causing the uncertainty of GPP simulation. The results of related studies showed that varying with species, seasonal, nitrogen (N),  
Figure 5: Results of GPP optimization of the two experiments comparing parameter optimization schemes. (**a**) Results of GPP optimization based on all parameters; (**b**) Results of GPP optimization based on four sensitive parameters.  
and light intensity [58; 59]. [PERSON] found that global GPP varied between 108.1\(\sim\)128.2 PgC yr\({}^{-1}\) with nine implementations of the global distribution of \(V_{m}^{25}\)[59], and greater effort was needed to pay close attention to the sensitivity of the variation in \(V_{m}^{25}\) in the growing season and Fluxnet-stations. So, future research of the comparison of the SIs of parameters, especially \(V_{m}^{25}\), would be in demand. \(f_{Ci}\) was also important, and the most sensitive parameter overall for the GPP and NEE output, and a recent study indicates that \(f_{Ci}\) was not a constant and varies along with environmental gradients [61], which was coincided with the parameter SA experiment. According to the above, the SA and other studies need to discover some parameters vary with the environment, the initial setting of the parameters as a constant was thus a crucial source of uncertainty [1; 62].
## 4 Conclusions  
The HABR for treating dyeing wastewater was systematically investigated in this pilot scale study. The HABR system was able to treat the wastewater efficiently after FeSO\({}_{4}\) pretreatment, as indicated by removal efficiencies of 33.7% for COD and 39.9% for SS, as well as 22.5% for SO\({}_{4}\)[2]-during operational period of 73-107 days. HABR may maintain a relatively high COD removal efficiency at high concentrations of sulfates (approximately 800-1200 mg/L) and SS (maximumly between 500-700 mg/L) and large fluctuation of SS concentrations (around 100-700 mg/L) in the influent. Results of GC-MS analysis indicated a satisfactory biodegradability improvement of the wastewater: the concentrations of alkanes, amides, organic acids, ketones, phenols, and esters were much lower in the effluent than those in the influent; many high-molecular-weight compounds such as cyclanes, quinolines, and phenols were successfully converted to low-molecular-weight ones. COD removal efficiency was closely associated with flow rate, OLR, water temperature, and influent SS.  
Based on the overall treating effectiveness and the GGRA study, the optimized operation strategy of HABR to process the dyeing wastewater was obtained as the HRT of 12 h for steady-state operation, up-flow velocity of 1.7 m/h, water temperature of 30-35 \({}^{\circ}\)C, and OLR of 1.5-2.0 kg COD/(m\({}^{3}\)-d).  
For the next stage, water indexes and dominant microbes in each compartment will be investigated to prove the separation of microbial populations by the ABR technique. Meanwhile, the biodegradability of the effluent to the subsequent aerobic treatment unit will be further validated. In addition, the results obtained from this work will be confirmed by testing the performance of full-scale plants [39; 40].  
Conceptualization, Methodology, Formal analysis, Funding acquisition, Writing--original draft, Z.Q.; Investigation, Software, G.X.; Writing--review and editing, D.X. This research was funded by National Natural Science Foundation of China (41807466), the Fundamental Research Funds for the Central Universities (3132019148), and the Natural Science Foundation of Liaoning Province, China (20170540099).  
**Acknowledgments:** [PERSON], [PERSON] and [PERSON] are thanked for their comments on this work.  
**Conflicts of Interest:** The authors declare no conflict of interest.