esa-sceva/satcom-chunk-collection huggingface dataset:
# The Influence of Storage Conditions of Cold-Pressed Rapeseed Oil on Its Quality Parameters
## 2 Materials and Methods
### Measurement Methodology
#### 2.3.4 Measurement of Radical Scavenging Activity  
A solution of 2,2\({}^{\prime}\)-azinobis(3-ethylbenzothazoline-6-sulfonic acid) (ABTS) diammonium salt with a concentration of 7.00 mM and potassium persulfate with a concentration of 2.45 mM was prepared in a 10 mL volumetric flask. The solution was left in the dark for 12 h to generate the ABTS** radical. Afterward, 1 mL of the analyzed oil and 1 mL of anhydrous ethanol were added to the test tube, and the resulting solution was mixed thoroughly. A volume of 30 \(\mu\)L of the solution was then taken and transferred to a spectrophotometric cuvette. Then, a solution of the ABTS** radical was prepared in methanol so that the absorbance of electromagnetic radiation with a wavelength of \(\lambda\) = 734 nm reached 0.700.  
Every 10 s, 3 mL of the prepared ABTS** radical solution was added to the previously prepared oil-ethanol mixture. The absorbance measurement was performed 10 min after adding the ABTS** radical solution. Subsequent measurements were performed every 10 s. Finally, the H\({}_{2}\)O absorbance value was measured three times [29]. Three replicates were performed for each test sample, and the percentage change in \(RSA\) relative to the blank sample was calculated using Formula (5):  
\[RSA\ (\%)=\frac{\text{A}_{0}-\text{ A}}{\text{A}_{0}}\times 100 \tag{5}\]  
where:  
A\({}_{0}\)--absorbance of blank test (ethanol)  
A--absorbance of tested sample
# Screening of Plants and Indigenous Bacteria to Improve Arsenic Phytoextraction
## 1 Introduction
In fact, the only metals that plants can absorb are those in bioavailable form, i.e., present in soluble forms in the soil solution [34; 35], and chelating agents have the precise function of favoring the release of heavy metals bound to soil particles into the soil solution, thus increasing their phyto-availability [36]. Another possibility to help phytoextraction by maximizing its effectiveness is the use of plant growth-promoting rhizobacteria (PGPR) [37]. This strategy involves rhizobacteria that can stimulate plant growth both by facilitating the bioavailability of soil nutrients and by modulating the production and level of phytohormones in plants [38]. In addition, thanks to the microbial processes active in the rhizosphere, PGPR can also promote the mobility and bioavailability of metals in the soil, increasing their uptake by plants [39; 40]. This work aimed to investigate the single and synergistic effect of PGPR and different chelating agents, namely dipotassium phosphate (KH\({}_{2}\)PO\({}_{4}\)), potassium hydrogen oxalate (KHC\({}_{2}\)O\({}_{4}\)), and ascorbic acid (C\({}_{6}\)H\({}_{8}\)O\({}_{6}\)), on the growth and uptake of As of three tolerant species, _Cannabis sativa_ (hemp), _Brassica juncea_, and _Zea mays_ (corn), to evaluate their potential use in a site contaminated by As. The selection of bacterial strains capable of improving the efficiency of the phytoremediation is a fundamental step, made non-trivial by the specificity of the action of PGPR and by their effectiveness, which depends on numerous factors related to the complex interactions with the soil and plants [38]. In this study, the addition of a selected microbial consortium with indigenous endophytic bacteria made it possible to obtain detectable levels of phytoextraction even without the addition of chemical mobilizing agents.
## 5 Discussion
### Comparison to Published Multistage Registration Methods
A fair comparison is therefore only possible if all multistage approaches are evaluated on the same datasets, e.g., by also evaluating the published multistage methods on the datasets used in our experiments. The performance of the published networks on our datasets then also depends on the generalizability of the networks to new data. A comparative study on affine medical image registration networks [37] has shown that only a few networks are generalizable to new data and applications.
# A Comprehensive Review of In-Body Biomedical Antennas: Design, Challenges and Applications
## 4 Challenges That Influence the Design of In-Body Antennas
### Effect of Tissue Diversification
In summary, higher conductivity of biological tissues can cause significant reduction in the propagation speed of radio waves.
# Emerging Trends in Hybrid Additive and Subtractive Manufacturing
## 1 Introduction
In this paper, after addressing the origin and evolution of the concept of hybrid additive and subtractive manufacturing, and briefly presenting the most important milestones in the development of hybrid machines, the incorporation of additive manufacturing-based parts in industry, the integration of additive and subtractive subprocesses into a single hybrid flow in the same machine, and establishing the current context in which research on the subject is being developed, a systematic review based on PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) of the scientific literature on hybrid additive and subtractive manufacturing is developed. Once the starting point has been established, and the conceptual debates have been overcome, it is considered important to systematize the search and analysis of scientific works, with the intention of reducing the risk of bias and being able to answer a series of essential questions previously defined, as explained in the Section 2. After applying the method, a total of 27 papers published between 1 January 2020, and 31 December 2024 (5 years) were analyzed. The WoS (Web of Science) search platform was used to develop the work, and the SCI (Science Citation Index Expanded) and CPCI-S (Conference Proceedings Citation Index-Science) databases from the Main Collection were used for searches. The inclusion and exclusion criteria for papers are: open access; published in English; from Q1 or Q2 journals or prestigious conference proceedings (Journal Citation Reports). These decisions and criteria are justified in the methodology chapter. Several conclusions emerge from the analysis. There is a significant dispersion when classifying the articles by area and country, although less so by year of publication. Unquestionably, the aerospace sector is identified by most papers as a key field of application and development for hybrid additive and subtractive manufacturing. The manufacturing of stamping dies and injection molds with conformal cooling channels is also notable. The most used materials in the various experimental studies and simulations are titanium and nickel alloys. The extension of the studies to real-life industrial cases, the inclusion of new materials, including polymers, a deeper understanding of the technologies involved and their integration and interaction, the development of comprehensive CAD/CAE/CAM systems, and the design of optimized processes are some of the future works proposed by the researchers.
## 3 Results for the Research Questions
### RQ1: Which Domains Used the Expert Finding Systems?  
The expert finding systems have been developed in different domains such as academia, enterprise, and social networks. For example, expert finding systems have been used in academia to find supervisors, paper reviewers, and research collaborators. In this SLR, the authors noted that 68 studies developed expert finding systems. After analysing all these studies, the researchers observed that these systems were developed in six different domains for different purposes. These domains are enterprises, academia, knowledge sharing communities (KSCs), medicine, social networks, and online forums. Table 3 describes these domains and studies in further details. From the table, we noted that academia is the largest domain, comprising 44 studies (65%). A majority of the expert finding systems were used in the academic domain. Additionally, in this field, the majority of the systems were developed for specific tasks like paper reviewing, research collaborations, finding similar experts, industry and  
Figure 4: Research methodology.  
university collaborations, and finding a suitable supervisor. Enterprise is the next largest domain, consisting of 10 studies (15%). A majority of the studies in this domain applied expert finding systems for general tasks, except reference [35], wherein the researchers designed the expert finding system for offering formal help. In another study [36], an expert finding system was developed for developer recommendations. The third major domain is medicine, which consisted of two studies (3%). These studies focused on the development of expert finding systems for finding medical experts. The fourth domain is the online knowledge sharing communities (KSCs), consisting of six studies (9%). In the past few years, there has been a rapid development of the online KSCs, like question-answering (Q&A) communities, discussion boards, and blogs, which generate a massive amount of data and expertise. Online KSC users exchange ideas, share experiences, and use these communities for solving their issues. The fifth domain is online forums, consisting of two studies (3%). These studies developed expert finding systems for helping the users of such forums to find experts in a specific area. Social media is the sixth domain, with three studies (5%), which developed these systems for finding experts from various social networks like Twitter and Facebook.  
As described in the academic domain, the expertise retrieval systems could be developed for a variety of tasks, which were described in 43 studies, presented in Table 3. Fourteen (30%) of the studies did not specify the tasks. Thirteen studies (30%) used the expert finding systems for research collaborations in the academic domain, followed by paper reviewing in nine studies (21%), finding group of experts in three studies (7%), university industry collaboration in two studies (5%), finding a similar expert in two studies (5%), and finding a supervisor in one study (2%).
## 3 The Land Based Classification Standards (LBCS)
Nevertheless, LBCS is independent of classification units, enabling land use data to be integrated from a variety of scales. LBCS can be equally applied to units such as traffic zones, buildings, parcels, parcel aggregates, grids, and combinations of such units. The database implementation of LBCS can be described by adding new fields to the land use database. The total number of land use fields in the database should equal the number of dimensions. Dimensions may be added or dropped as needed, depending on the purpose of the data. Relational databases offer an easy platform for implementing a database schema that can store multiple codes required to mirror the multi-dimensional nature of land use.
## 4 Implementation of Multi-GNSS Time and Frequency Transfer using RVCE  
Details of the four-step data processing procedure for time and frequency transfer using a RVCE algorithm are shown in Figure 1. First, when combining the three CDMA GNSSs for time and frequency transfer, the observation model can be formed according to Equation (3), and the receiver clock offset is our parameter of interest. Meanwhile, the initial weights of the three GNSSs are temporarily set as equal. The parameters in Equation (6) are then estimated using LSQ adjustment. The residuals of all satellites can be derived according to Equation (7), and may be further standardized by Equation (8). Next, the three variance components are estimated according to Equation (11). It is worth noting that when the robust function is employed, the weighs matrices for the three GNSSs in Equation (11) must be determined by their equivalent weight functions and standardized residuals before the robust variance components may be acquired. Finally, whether the three weight variance components are equal or not must be judged. If equal, the previous weights from the second step are output and used to estimate receiver clock parameters based on Equation (5), thereafter, the progress of time and frequency transfer is completed using Equation (4). If the weight variance components are not equal, the posterior weights are determined based on Equation (11), and then used to begin the next loop in LSQ adjustment until the three weight variance components are equal.
## 2 Results and Discussion
### Identification of S. cerevisiae Enzymes for Unexpected IPP-Utilizing Activity  
We cultured INVSc1 yeast without LLA66 and performed DEAE ion exchange chromatography to partially purify the enzyme mixture. The activity of using [14C]IIPP alone was detected at 200 to 300 mM NaCl eluting fractions (Supplementary Figure S2a). For the next chromatographic step, the yeast enzyme mixture with the activity was bound to Ni-NTA and eluted by at least 100 mM imidazole (Supplementary Figure S2b). Then, a strong anion exchange chromatography (Supplementary Figure S2c), followed by a size exclusion chromatography (Supplementary Figure S2d) were used to reveal an active protein peak. SDS-PAGE of the fractions after three purification steps is shown in Supplementary Figure S3a. Finally, after size exclusion chromatography, bands of approximately 60, 40, and 30 kDa of the active protein peak resolved on SDS-PAGE (Supplementary Figure S3b) were subjected to LC-MASS/MASS analysis. These proteins were identified to be alkaline phosphatase, FPPS and IPP:DMAPP isomerase (Supplementary Figure S4 shows the detected fragmented peptides in red from the protein bands, and Table S1 lists the identified proteins). This could explain that adding [14C]IIPP alone generated C15 product, as shown by TLC analysis, because IPP was converted to DMAPP by the isomerase, which was condensed with two IPP molecules to generate FPP by FPPS, and finally, the phosphatase hydrolyzed FPP to C15 farnesol. This protein complex could strongly bind to NiNTA, probably due to the high content of His (26 His) in alkaline phosphatase. This is worth noticing because others could experience the same problem when expressing prenyltransferases using _S. cerevisiae_.
###### Abstract  
Human zoonotic infection with _Campylobacter_ is a major cause of gastroenteritis in the United States and worldwide. _Listeria monocytogenes_ causes a potentially fatal infection in humans and is often attributed to contaminated food. Genetic typing has demonstrated that _Campylobacter_ infection is often associated with the consumption of contaminated poultry products, with _Campylobacter_ often colonizing the poultry gastrointestinal tract, while listeriosis is commonly associated with the consumption of contaminated ready-to-eat (RTE) foods. In this study, a strain of endospore-forming bacterium (strain NH) that is bactericidal towards the human food pathogens _Campylobacter jejuni_ and _Listeria monocytogenes_ was identified and characterized. Transwell experiments demonstrated that the bactericidal effect on both _C. jejuni_ and _L. monocytogenes_ is due to secretions from the spore former. These foodborne pathogens consistently exhibited 7 log reductions in growth when exposed to the NH cell-free culture filtrate. Sequencing of the 16s rRNA gene V4 variable region and analysis of the full-length 16s rRNA gene sequence from the WGS indicated that strain NH belongs to the species _Aneurinilvicus_. A microplate bioassay demonstrated that a bactericidal substance that is sensitive to protease could be collected from cell-free filtrates by salting out with ammonium sulfate. Gel filtration chromatography indicated a native molecular weight for the bactericidal protein of ca. 50 kDa, consistent with a class III bacteriocin. The active protein bound strongly to a cation-exchange resin and with an isoelectric point of ten, suggesting a positively charged protein. Both cation-exchange chromatography and isoelectric focusing indicated the enrichment of an 11 kDa protein on SDS-PAGE. This protein was identified through mass spectroscopy as the figM protein, an anti-sigma factor. Analysis of whole genome sequencing (WGS) of the strain NH genome indicated the presence of a number of non-conservative amino acid substitutions in the _figM_-gene-derived amino acid sequence of strain NH and _A. anurinilvicus_ compared to other members of the _Aneurinilvicus_ genus. Further investigation is needed to determine whether these substitutions are correlated with the bactericidal activity. The identified strain may be useful as a feed additive for the pre-harvest control of _Campylobacter jejuni_ in poultry.  
Aneurinobacillus; bacteriocin; figM; _Campylobacter jejuni; Listeria monocytogenes_
# Synchrotron X-ray Microprobes: An Application on Ancient Ceramics
## 3 Results  
### Portable XRF  
Even with obvious limits, a fast and non-destructive scan of the surface provided some clues on compositional differences among the studied productions. In fact, Attic and Laconian vessels, and Chalcidian, south-Italian (Locrian?) and Sicilian colonial (Geloan) samples show different features.  
In Attic fragments glaze is mainly Fe-rich with low amounts of silicon and potassium. Laconian samples are characterized by a Fe-based black-gloss with Mn co-localization, along with silicon and potassium in lower amount. Sicilian colonial fragments are characterized by Fe-based gloss with potassium and manganese. On the other hand, Chalcidian and Locrian products show a co-localization of Fe and Zn, along with silica and low amount of K and Mn. Of course, this qualitative analysis provided a not-univocal classification criteria. However, a portable XRF approach seems to permit the discrimination between Attic and colonial products, and between Sicilian and South-Italian colonial products based on Zn marker (Figure S1).
# Trade-Off Analysis for Array Configurations of Chipless RFID Sensor Tag Designs
## 3 Link Budget of Chipless RFID Arrays
#### The Role of Chipless RFID Arrays in Link Budget  
Figure 4 illustrates the link budget of a chipless RFID array system. The RCS of a chipless RFID tag (\(\sigma_{\rm tag}\)) plays a crucial role in link budget analysis, particularly in understanding how efficiently the tag scatters incident power back to the reader. In the unit cell chipless tag, the RCS is relatively small compared to the array configurations, which reduces the tag scattering effect. Then, it reduces the power received by the RFID reader. Moreover, when considering the chipless RFID array configurations, it is evident that RCS increases when the number of elements in the array increases (i.e., Array 1 to Array 3). Therefore, it also increases the power received by the reader \(P_{r}\). However, the array enhanced from Array 1 to Array 3 shows no linear variation. This is because when the  
elements in the array increase, the polarisation mismatch and radiation losses also increase, leading to proportionally reduced received power to the reader as shown in Figure 4.  
In the dislocated bistatic configuration, as shown in Figure 3a, the received power to the chipless RFID reader can be theoretically estimated using the following formula [24]:  
\[P_{r}=\frac{P_{t}G_{t}G_{r}\lambda^{4}X_{f}X_{b}\sigma(\theta,\phi)}{(4\pi)^{4 }r_{f}^{2}r_{b}^{2}B_{f}B_{b}F} \tag{5}\]  
where \(\lambda\) is the wavelength of the resonance frequency, \(X_{f,b}\) is the forward and reverse-link polarisation mismatch, \(r_{a,b}\) is the tag-to-reader and reader-to-tag distances (m), \(B_{f,b}\) is the forward and reverse blockage losses, and \(F\) is the bistatic fade margin.  
In the collocated bistatic configuration, as shown in Figure 3b, \(X_{f}=X_{b}\), \(r_{f}=r_{b}\), and \(B_{f}=B_{b}\). In addition to these parameters, \(G_{t}=G_{r}\) happens in a monostatic configuration since it uses only one antenna as shown in Figure 3c.
# ZSM Framework for Autonomous Security Service Level Agreement Life-Cycle Management in B5G Networks
## 3 Security Framework Overview  
Traditional ZSM frameworks have made significant strides in specifying automation for service life-cycle management, even though they are still grappling with challenges in security. Generally, security is often considered an overarching aspect, but its definition is either omitted or left ambiguous. Our approach [10] relies on ETSI's ZSM reference architecture [8] to integrate security assets in autonomous and intelligent intent-driven E2E service management (Figure 1). We adapt the standard's closed loops to enhance the framework's autonomy through self-healing, self-repairing, self-configuring, and self-protecting capabilities. We therefore define the closed loops' interactions covering single domain security management and cross-domain coordination. To drive them, we follow an intent-driven approach, proposing three distinct security abstraction levels: SSLAs, MSPL-OP, and final configuration.  
The decisions taken within the closed loops are tailored to the requirements specified in the intent. As an innovation, we integrate DLT-based trust management to ponder decision making at its various steps; more details can be found in [41]. Trust is evaluated through continuous SSLA monitoring and analysis. Trust metrics represent the historical assets' and domains' behavior for SSLA compliance. Genuine behavior is rewarded, while vulnerabilities are punished. In ETSI's ZSM definition, single management domains are able to self-manage their own services and infrastructure, but for cross-domain actions, an E2E domain is used. As a novelty, our E2E domain vision presents a centralized data analysis that correlates security information from different domains. This view expands the security coverage across the entire infrastructure, including Federated Cyberthreat Intelligence (CTI) sharing, cross-domain threat mitigation, and the redeployment of mistrusted assets among other E2E domain functionalities.  
The remainder of this section is structured as follows: first, we present the various intent models and outline the procedures for transforming them. Next, we detail the key steps involved in both intra-domain and cross-domain closed-loop processes. Finally, we provide a precise definition of the ZSM framework interactions, focusing on the proactive and reactive components of the closed loops.
## 4 Protocol for Source Location Protection Based on Limited Flooding  
The base station initializes the network by broadcast in a similar way as described by [PERSON] in [22]. After the network initialization, every sensor knows its neighbors and its shortest distance away from the base station (denoted by \(D_{bs}\)). When the source (e.g., \(s\)) detects the panda, \(s\) starts a flooding within a limited area \(Q\), which covers the area within \(h\)-hops from \(s\). The flooding packet will be transmitted to every sensor in \(Q\). After the flooding, each sensor in \(Q\) acquires its shortest distance from the \(s\) (denotedby \(D_{s}\)). After that, the source generates and sends a packet to the base station by a \(h\)-directed routing and then the shortest path routing. In particular, in the \(h\)-directed routing, a packet will always be sent to a neighbor whose \(D_{s}\) is larger than that of the current sensor (_i.e._, the sensor that forwards this packet to the neighbor). After \(h\) directed transmissions, the packet reaches a location called the phantom location. For the \(h\)-directed routing, the phantom locations obtained for the packets are expected to be widely distributed and also far from the source. Finally, the packets will be transmitted from the phantom locations to the base station through the shortest path routing. During this process, the packet will always be forwarded to a neighbor which is nearer to the base station than the current sensor. Our proposed SLP includes four phases: network initialization, \(h\)-hops limited flooding initialized from the source, \(h\)-directed routing, and the shortest path routing. Table 1 lists the notations used in this paper.