esa-sceva/satcom-chunk-collection huggingface dataset:
# Utility-Centric Service Provisioning in Multi-Access Edge Computing
## 3 System Model and Problem Formulation
### Service Latency Estimation
#### 3.3.1 Communication Latency  
The communication latency of user \(u\) at node \(n\) consists of two parts: (i) the network latency between user \(u\) and its connected MEC \(n_{u}\), denoted as \(\tau_{u,n_{u}}^{comm}\), and (ii) the network latency between the connected MEC \(n_{u}\) (i.e., source node) and the selected node \(n\) for executing the user request (i.e., target node), denoted as \(\tau_{u_{u},n}^{comm}\). Each network latency is composed of transmission delay and propagation delay. It is noteworthy that a user's connected MEC can host the service and process its request (i.e., \(n=n_{u}\)), and in this case \(\tau_{u_{u},n}^{comm}=0\). Hence, let \(\tau_{u,n}^{comm}\) denote the communication latency of user \(u\) at node \(n\). Then it is estimated as  
\[\tau_{u,n}^{comm}=\tau_{u,n_{u}}^{comm}+\tau_{u_{u},n}^{comm}=\left\{\begin{array} []{ll}\frac{d_{u_{u}}}{\tau_{u,n_{u}}}+D_{u,n_{u}},&\text{if }n=n_{u}\\ \frac{d_{u_{u}}}{\tau_{u,n_{u}}}+D_{u,n_{u}}+\frac{d_{u_{u}}}{\tau_{u_{u},n} }+D_{n_{u},n},&\text{otherwise}\end{array}\right. \tag{1}\]  
where \(r_{u,n_{u}}\) and \(D_{n_{u},n}\) are the transmission rate and round-trip propagation delay between the user \(u\) and its connected MEC \(n_{u}\), respectively; \(r_{u_{u},n}\) and \(D_{n_{u},n}\) are the transmission rate and the round-trip propagation delay of the network links between node \(n_{u}\) and \(n\), respectively. Here, we omit the time cost for transferring the computation result back to the user since the size of the computation outcome is much smaller than that of the input data [41; 42].
# An In-Depth Review on Blockchain Simulators for IoT Environments
## 5 Potential Simulators
### Cardano Simulator  
Cardano is a new blockchain that investors are paying attention to. The network is being used as a simulator in a similar way to Ethereum and Bitcoin [56]. Cardano intends to address issues such as scalability, interoperability, and sustainability in cryptocurrency. The issues in cryptocurrency are similar to the issues found in IoT devices.  
With problems relating to scalability, networks have become sluggish and costs have gone up due to increased transaction volumes. Ouroboros, a Cardano algorithm, is the proposed solution for its scalability issues. To save energy and enable rapid transaction processing, Ouroboros uses a proof of stake (PoS) technique. Cardano's blockchain reduces the number of nodes in a network by choosing leaders who are responsible for checking and approving transactions from a set of nodes rather than having a copy of separate blockchains on each node; the leader node then sends transactions to the primary network. Like IoT devices, a large number of devices would be connected to one IoT network. This causes the other devices on the same network to become slow, resulting in the network shutting down. If the creators of Ouroboros were to modify its algorithm to fit IoT devices, then it may solve that problem.  
In interoperability, it is the mobility of a cryptocurrency both inside its native environment and in its interaction with the current global financial ecosystem. As of right now, there is no mechanism to execute cross-chain cryptocurrency transactions or a smooth transaction between cryptocurrencies and the world's financial ecosystem. The only mid-dlemen are exchanges that collapse or demand high fees. Cardano wants to facilitate cross-chain transfers using side chains, which let two parties perform transactions off-chain. Applying this to IoT will help the communication between IoT devices happen much more effortlessly. It also prevents attacks or viruses that may hinder a successful connection between the devices.  
Finally, there are problems relating to sustainability. This refers to governance mechanisms that give rewards to miners and other stakeholders, as well as the development of a cryptocurrency's self-sustaining economic model. Cardano's dedication to creating a sustainable cryptocurrency environment can transfer to IoT devices. Cardano can help IoT reduce our carbon footprint by enabling different applications related to energy management and resource efficiency such as water management or waste management.
# Smart Contract-Enabled Secure Sharing of Health Data for a Mobile Cloud-Based E-Health System
## 4 Proposed System
### Process of the Proposed Work  
In this section, we implement secure data-upload and data sharing mechanisms by utilizing smart contracts and blockchains. The use of smart contracts enables high productivity and transparency in the automated management of blockchain transactions. We built decentralized user modules for smartphones; the decentralized modules provide basic functionalities to users to interact with the blockchain network throughout the cloud. This layer is responsible for encoding transactions and data demands, generating digital signatures for transactions, and connecting to the blockchain to monitor transaction activities. In  
Figure 4: The Structure of a Block.  
Figure 5: The Sequence Diagram of Activities of the Proposed Method.  
addition, the user interface module is intended to communicate with the user and request a controller unit to manage the user request information. The workflow of the operations for uploading and exchanging EHRs is shown in Figure 6. The description of every sequence of iterations is as follows:  
1. A mobile adapter instantiates a query to migrate the data to a cloud server as a new block.
2. The blockchain client, the user, evaluates and provides the query for authentication to an administrator of the EHRs, as well as the consensus mechanism.
3. The administrator of the EHRs authenticates the application through a consensus mechanism with a tight security rule. If a request is approved, a notification of the uploaded data is forwarded to the firewall.
4. The firewall can now pick the EHR, a health data file gathered via smart technologies, and encrypt the data using the EHR owner's key pair. The firewall automatically releases encrypted messages to cloud services using the IPFS.
5. IPFS management stores the file system in a user device by employing uploaded details, and dynamically generates a hash code stored in the DHT database.
6. Copying accounts are organized into data items and incorporated into transaction repositories to validate the ledger by mining.
7. The uploaded operation is modified for monitoring by a wireless terminal.
8. The mobile user executes a query containing the ID and signature of the secret key of the server.
9. The blockchain application node provides an authenticated user grant of access to upload the data.
10. The EHR manager can check the user's legal entitlement through the hashing algorithm access management plan. If the query for permission is authenticated, the administrator of the EHRs should review the IDs and then forward the requests to the IPFS repositories for data retrieval.
11. EHR management requires an asymmetric encryption algorithm to decrypt the required information and return it to a recipient.
12. The recipient's smartphone is updated with the uploaded transactions for monitoring through the blockchain application.
# Fast Sound Source Localization Based on SRP-PHAT Using Density Peaks Clustering
###### Abstract  
Sound source localization has been increasingly used recently. Among the existing techniques of sound source localization, the steered response power-phase transform (SRP-PHAT) exhibits considerable advantages regarding anti-noise and anti-reverberation. When applied in real-time situations, however, the heavy computational load makes it impossible to localize the sound source in a reasonable time since SRP-PHAT employs a grid search scheme. To solve the problem, an improved procedure called ODB-SRP-PHAT, i.e., steered response power and phase transformation with an offline database (ODB), was proposed by the authors. The basic idea of ODB-SRP-PHAT is to determine the possible sound source positions using SRP-PHAT and density peak clustering before real-time localization and store the identified positions in an ODB. Then, at the online positioning stage, only the power values of the positions in the ODB will be calculated. When used in real-time monitoring, e.g., locating the speaker in a video conference, the computational load of ODB-SRP-PHAT is significantly smaller than that of SRP-PHAT. Simulations and experiments under a real environment verified the high localization accuracy with a small computational load of ODB-SRP-PHAT. In addition, the advantages of anti-noise and anti-reverberation remained. The suggested procedure displayed good applicability in a real environment.  
sound source localization; SRP-PHAT; density peak clustering; offline database +
Footnote †: journal: Applied Sciences
## 3 Results
### Effects of RT on Auditory Sustained Attention  
The OE, CE, total errors (E), and MRT of the subjects under different RT conditions were obtained statistically. The data were tested for reliability and validity and met the requirements. The ANOVA test was performed on the data under different RT scenarios, and it was found that reverberation time significantly affected the perception of OE (\(p\) = 0.000), CE (\(p\) = 0.000), E (\(p\) = 0.000), and MRT (\(p\) = 0.000). The impact of different RT on ACPT is shown in Figure 7.  
The OE at 0 s and 1 s of RT (mean = 5.0 and 6.9) are significantly lower than the OE at RT = 3 s (mean = 10.0). There is a significant difference in CE between RT = 0 s, 1 s, and 2 s (mean = 3.1, 3.0, and 3.3). The MRT at RT = 0 s (mean = 780.1) is significantly lower than that at RT = 3 s and (mean = 836.0 and 850.5).  
Figure 8 shows the perceptual characteristic curves of OE, CE, E, and MRT under different RT. As can be seen from Figure 8, OE, CE, E, and MRT all increase with the increase in RT. Within the range of 0 s to 3 s of RT, OE increases significantly, and OE still holds an increasing trend within 3 s to 7 s, but the increase becomes significantly smaller. CE has a very small range of slow growth within 0 s to 2 s, and CE corresponding to 1 s of RT is the smallest, and it starts to grow rapidly from 2 s to 7 s. The MRT of the subjects fluctuated greatly in the range of RT from 0 s to 1 s and from 2 s to 3 s, increased slowly from 3 s to 7 s, and then stabilized. It was analyzed that for every 1 s decrease in RT, the reaction time of auditory sustained attention could decrease by about 2%. The above results indicate that the masking effect of reverberation can affect human perception of speech and reduce perceptual performance. As shown in Figure 8d, the scatter points of error perception values are all distributed near the center line, indicating that the perception has high precision on OE, CE, and E in the reverberant environment.  
The fitting formulas are shown in Equations (4)-(7):  
\[\text{OE}=6.382+2.429\text{ln (RT}+0.5),\,\text{R}^{2}=0.97, \tag{4}\]  
\[\text{CE}=2.917\text{e}^{\,\,0.107\text{RT}},\,\text{R}^{2}=0.92, \tag{5}\]  
\[\text{E}=9.546+3.502\text{ln (RT}+0.5),\,\text{R}^{2}=0.91, \tag{6}\]  
\[\text{MRT}=917.817+31.399\text{ln (RT}+0.5),\,\text{R}^{2}=0.90, \tag{7}\]  
where E is the total error, and R\({}^{2}\) is the coefficient of determination. For the case where only reverberant interference is present, the auditory sustained attention-perceptual values can be predicted directly from the above-fitted curves based on the actual measured values.
## 3 Hypothesis Development and Research Model
### Technology Acceptance Factors and Psychological Experience Factor for Users  
#### 3.2.1 Perceived Ease of Use  
The Technology Acceptance Model (TAM) has identified the role of the PU and ease of use constructs in the technology adoption process, that is, intentions towards behavior (willingness to accept) are jointly determined by people's attitudes and PU [15]. [PERSON] [10] also assumed that PEU is an a priori variable and not just parallel to PU. Therefore, the proposed relationship between PU and PEU is reasonable. TAM effectively expresses the user's intention to participate in the technology.  
Consumers sometimes have a large knowledge background barrier when purchasing cultural heritage products, and AR helps to remove this barrier. Consumers of cultural heritage products tend to derive pleasure from accessing detailed information tailored to their needs, increasing their attentiveness to opportunities for acquiring product information [41]. [PERSON] [42] highlights that the perception of 'complete product information' constitutes the most significant advantage of AR shopping tools, explaining why AR technology is highly effective at capturing customer attention. Owing to AR technology's capacity to furnish detailed information about product attributes, consumers are more thoroughly engaged in these intriguing and enjoyable experiences within a specific context [43].  
AR can supply trustworthy information that assists consumers in making informed and rational purchasing decisions, enhancing their experiential value, and culminating in an optimal shopping experience. Based on this understanding, the following hypothesis is proposed:  
**Hypothesis 4**.: _Consumers perceived ease of use positively affects their perceived usefulness in cultural heritage product purchases._Hypothesis 5: _Consumer perceived ease of use positively affects consumers' flow experience in cultural heritage product purchases._
# Electromagnetic Field-Aware Radio Resource Management for 5G and Beyond: A Survey
## 5 Challenges and Open Research Topics
### Challenges
#### 5.1.2 Resource Allocation in Dense 5G Networks  
Balancing network performance with EMF exposure constraints in dense 5G deployments poses numerous challenges. Increased base station deployment to improve coverage and capacity can lead to higher EMF levels, particularly with advanced technologies such as cooperative MIMO, beamforming, and multi-tier heterogeneous networks. Practical issues, including dual main beam effects and other beamforming abnormalities, exacerbate these difficulties by causing an uneven EMF distribution. Effective strategies for EMF-aware resource allocation must consider these factors while maintaining optimal service quality.
# Inter-Annual Variability of Peatland Vegetation Captured Using Phenocam- and UAV Imagery
## 3 Results
### Monitoring Vegetation Phenology
#### 3.2.3. Capturing Spatial and Temporal Variability Within the Growing Season  
Phenocam-derived \(G_{cc}\) was calculated as an average for the entire ROI, hence smoothing out the spatial variability observed in the imagery (Figure 2). In contrast, the spatially referenced UAV-derived VIs revealed a strong heterogeneity in greening across the survey area. This heterogeneity can be seen in Figure 6, which maps the pixel-wise change in greenness between surveys conducted in the early (14 May 2021) and peak growing season (3 August 2021). Although, greening was observed across the scene, the area to the northeast exhibited a more pronounced greening than the rest of the survey area. These pixels correspond to areas with a dominant vegetation cover of the deciduous grass species, _M. caerulea_.  
We extracted VIs for each species by overlaying the UAV survey data and species-level classification map (see Figure 1). Overall, we found that the shrubs _C. vulgaris_ and _Vaccinium_ spp. and the grass, _M. caerulea_, displayed the largest seasonal amplitude (i.e., growing season peak to trough, see Figure 7) in greenness for the calculated VIs. In contrast, mosses (_P. schreberi_, _Sphagnum_ spp.) and the rush, _J. effusus_, exhibited the smallest seasonal amplitude and lowest peak greenness values of all species examined. Towards the start and end of the growing season, we observed that variability in the VIs at the species-level was relatively small (Figure 7). However, heterogeneity in greenness across the individual species increased substantially over the summer months once the canopy had developed.  
Figure 6: UAV-derived reNDVI1 difference map. Shown is the percentage difference in reNDVI1 from 14 May to 3 August 2021. Negative values indicate a reduction in greenness from May to August, whereas positive values indicate an increase in greenness.
# tRNA and tsRNA: From Heterogeneity to Multifaceted Regulators
## 4 Revisit the Regulatory Mechanisms of tRNA and tsRNA
### tsRNA Regulation: Structure Dictates Function  
Given the heterogeneous nature of tsRNAs, which exhibit variations in origin, sequence, length, and modifications, their regulatory mechanisms are diverse and encompass a wide range of functions. These regulatory functions of tsRNAs have been elucidated and classified according to the various stages of cellular activity, including transcription, post-transcriptional regulation, and translation control. It is noteworthy that tsRNAs can form higher-order structures stabilized by intra or intermolecular interactions that are influenced by intrinsic sequence pairing propensity or specific RNA modifications. This structural versatility contributes to a more complex and diverse regulatory landscape of tsRNAs, exerting regulatory effects distinct from those mediated by sequence complementarity.
# Effect of PAS-LuxR Family Regulators on the Secondary Metabolism of _Streptomyces_
## 3 Regulation of Related Product Biosynthesis by PAS-LuxR Family Regulators
### Regulatory Mechanisms of PAS-LuxR Family Regulators
On the basis of the comparison of the amino acid sequences of TtmRIV with other PAS-LuxR family regulators, amino acids at 25-43 aa at the N-terminus of the PAS region of TtmRIV had 19 additional amino acid residues compared with the corresponding positions of other regulators (Figure 8), the same observation was made in the LuxR at the C-terminus. On the basis of the comparison of the secondary structures, the PAS regions of AmphRIV, FscRI, NysRIV, and PimM all contain three \(\alpha\)-helices and two \(\beta\)-folded structures in the PAS region, while the PAS region of TtmRIV contains three \(\alpha\)-helices and one \(\beta\)-folded structure. Structurally, TtmRIV do not form another \(\beta\)-fold structure because of the 19 additional amino acid residues, indicating that the PAS structure in TtmRIV differs from the normal PAS structure that has been reported. As shown in Figure 9, on the basis of the comparison of the conserved sequence 5\({}^{\prime}\)-YVSGGAWWTCCSBR-3\({}^{\prime}\) of the TtmRIV binding sites sequence with the conserved sequence 5\({}^{\prime}\)-CTVGGGAWWTCCCBAG-3\({}^{\prime}\) of the PAS-LuxR family regulator binding site sequence reported (Y for C or T; V for A, C or G; S for C or G; W for A or T; B for C, G or T; R for A or G), difference was observed at the \(-\)5/4 and \(-\)7/6 bases. In _S. avermitilis_, PteF formed vertical regulatory system with SARP-LAL family regulator in the filipin pathway. In addition, PteF affected the transcriptions of genes related to various metabolic processes, including genetic information processing; DNA, energy, carbohydrate, and lipid metabolism; morphological differentiation; and transcriptional regulation, among others, but were particularly related to 10 potential secondary metabolites [53]. Therefore, the study on the regulatory mechanism of PAS-LuxR family regulators is still incomplete, thus requiring further studies on the presence of two PAS-LuxR family regulators in the same strain without functional crossover for the understanding of the precise regulation of such family regulators. Figure 7: Prediction of binding sites of the PAS-LuxR family regulators. Figure 8: Comparison of amino acid sequences in the PAS region. **(a)**, TtmRIV; **(b)**, FscRI; **(c)**, AmphRIV; **(d)**, NysRV; **(e)**, PimM. Figure 9: Sequence logo comparison of TtmRIV and PAS-LuxR family regulon binding sites. **(a)** Sequence logo of TtmRIV binding sites. **(b)** Sequence logo of PAS-LuxR family regulator binding sites reported in the literature.
# Effect of Primary Spruce Lamella Aging on the Bending Characteristics of Glulam Beams
## 1 Introduction
Wood exposed to high temperatures above 160 \({}^{\circ}\)C loses its strength quickly and its stiffness slowly [43], it is less hygroscopic-more hydrophobic, and its surfaces are less wettable by polar liquid glues [43; 44; 45]. [PERSON] et al. [46] found that the processing time needed for the glue to be absorbed into thermally modified wood is longer due to the slower penetration rate. Changes in the pH value of the thermally modified wood surface might retard or accelerate the curing of glues, depending on their type [47]. Finally, the mechanical properties of glulam from thermally modified wood lamellas are usually lowered [48]. In many cases, chemical preservatives--many of which are aggressive chemical substances or such substances can be formed over time in a wet environment--negatively affect the wettability of wood lamellas with polar glues [12] and deteriorate the lignin-saccharide matrix of wood cells in lamellas [39]. So, such chemicals can worsen the adhesion of glues to wood lamellas and/or decrease the strength of wood lamellas and finally degrade the mechanical properties of glulam beams [49]. For example, in the study by [PERSON] et al. [50], who dealt with the use of wood material from old pine telecommunication poles in the production of glulam beams, the strength of glulam prepared from aged wood was reduced due to the presence of the biocidal preservative CCA (chromated copper arsenate). However, today, in several European countries, old wood containing CCA, creosote, Cu-azole, pentachlorophenol or other more toxic contaminants of the fourth healthy-environmental class cannot be used for new panels including glulam [51]. The basic aim of this work was to examine the influence of the primary aging of spruce lamellas--natural aging under the action of wood-destroying insects, as well as artificial aging due to high temperatures or inorganic wood preservatives commonly used in the past--on the bending characteristics of glulam beams. Simultaneously, the relationship between the bending characteristics of glulam beams prepared from aged and sound spruce lamellas and the shear strength of glued joints between these lamellas was evaluated.