esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 SCODE_plus_: Enhanced Secure Routing and Key Management Scheme
### Secure Data Dissemination Scheme to Mobile Sinks  
In this section, we present SCODE_plus_, a significantly enhanced version of the SCODE [12]. Different from the previous version, the routing algorithm in SCODE_plus_ does not require locations of sensor nodes. Each node knows their own group ID (cell ID) prior to the deployment. SCODE_plus_ also has three phases: _data announcement, query transfer_, and _data dissemination_. Those phases are similar to that of the SCODE except the routing algorithm in _query transfer_ phase. The previous routing algorithm is based on square-grid structure. In this version, the routing algorithm is based on the hexagonal network topology which provides more straight routing path between a source and a sink. On the other hand, thank to our enhanced deployment model, the new routing algorithm can eliminate the void cell problem of the previous scheme.  
Based on our improvement in this version, we lessen the assumptions 1, 2, and 3 mentioned in Section 4.1 as follows:  
* There may be hundreds or thousands of homogeneous nodes distributed into a sensor field. The distribution of nodes within a cell conforms to _Gaussian_. This is more realistic.
* All sensor nodes are stationary and NOT aware of their locations.
* Each node/sink has a unique ID and maintains three key types based on our key management scheme: a unique individual key \(K_{A}\) that each node \(A\) shares with a sink; a cluster key \(K_{CH}\) shared among all nodes in the same cell; and a pair-wise shared key \(K_{AB}\) shared between a node/sink \(A\) and its neighbor \(B\) (Node B is defined as a neighbor of node A if and only if B coexists in the same or adjacent cell of A). Those keys can establish through _direct key establish_ phase or the _indirect key establish_ phase.  
\begin{table}
\begin{tabular}{l l} \hline
**Notation** & **Description** \\ \hline \(ID_{A}\) & Identification of node A \\ \(CID_{A}(X,Y)\) & Cell identification of node A, indicating X and Y axes of the cell \\ \(PID\) & Packet Sequence Number (packet ID) \\ \(R\) & Radio range of a sensor node \\ \(r\) & Cell size \\ \(K_{A}\) & A secret key held by node A \\ \(K_{AB}\) & A shared key between A and B. \\ MAC (\(K\), \(M\)) & Message authentication code of message M using a symmetric \\  & key \(K\) \\ \(\{M\}\)K & Message M is encrypted with a key \(K\) \\ \(N_{0}\), \(N_{I}\) & _Nonces_, one-time random number generated by nodes \\ \(A\)\(\xrightarrow{}\) broadcast: \(M\) & Node \(A\) broadcasts a message \(M\) \\ \(A\)\(\xrightarrow{}\)\(B\): \(M\) & Node \(A\) sends a message \(M\) to node \(B\) \\ \hline \end{tabular}
\end{table}
Table 1: Notations.  
Table 1 provides the notation description which will be used in the paper.
# Effects of Physical Exercise on Substance Use Disorder: A Comprehensive Review
## 2 Methods
### Selection and Review Process  
The selection process adhered to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [24]. Two reviewers independently evaluated the titles and abstracts of all the retrieved records to establish their eligibility. For studies that met the inclusion criteria or where eligibility was unclear, the full-text articles were obtained for further review. Then, the reviewers independently assessed these articles for consistency with the criteria. Any disagreements were resolved through discussion between the reviewers. If consensus could not be reached, a third reviewer was consultedto mediate and finalize the decision. Then, the two reviewers assessed the full-text articles, with doubts being resolved through consultation between each other, a third reviewer was consulted in case of any disagreement. The flow chart of this process can be found in Figure 1. The articles reviewed were published between 2007 and 2024, highlighting a growing trend in scientific production regarding the impact of physical exercise on individuals with substance use disorders. This time frame reflects the increasing recognition of exercise as a complementary intervention for SUD.
# Smart Viniculture: Applying Artificial Intelligence for Improved Winemaking and Risk Management
## 4 Artificial Intelligence in Production, the Fermentation Process, and Bottling Quality Control
### Machine Vision Systems for Bottling Quality Inspection
#### 4.3.2 Ensuring Label Accuracy  
Accurate labeling is crucial for compliance with industry regulations and for providing consumers with essential information. AI-powered vision systems can verify the accuracy and placement of labels, ensuring that each bottle displays the correct information regarding its contents, origin, and other mandatory details. This automated verification process significantly reduces the likelihood of human error and enhances operational efficiency.  
Advanced machine vision systems use high-resolution cameras and sophisticated algorithms to inspect labels in real-time. These systems can identify defects such as smudges, misprints, and improper adhesion. For instance, [PERSON] et al. (2020) developed a machine vision system for automatic online inspection of transparent label defects on curved glass bottles. This system employs an area-array camera and a custom-made blue dome illumination device to capture high-quality images, effectively eliminating reflection and refraction issues. By integrating advanced image processing techniques, the system can accurately detect even small defects, ensuring that all labels are applied correctly and legibly, which is essential for maintaining brand integrity and consumer trust [98].  
Additionally, AI-driven vision systems can be trained using large datasets to improve their accuracy over time. The work by [PERSON] demonstrated the effectiveness of using convolutional neural networks (CNNs) for wine label image recognition. By applying data augmentation techniques, the system achieved high accuracy in identifying wine labels, showcasing the potential of AI in enhancing label verification processes [99]  
Another study by [PERSON] and [PERSON] focused on distributed search and fusion strategies for wine label image retrieval. This approach addresses the challenge of imbalanced sample images among different wine brands, significantly improving the training of retrieval systems based on deep learning. Such advancements ensure that AI systems remain robust and reliable, even when dealing with a vast array of label designs and quality standards [100].
## 4 Experimental Evaluation  
### Dataset Description and System Configuration  
We used various datasets for the evaluation of LPaMI as displayed in the Table 2. The 8-Scene and INRIA Holidays datasets are used to evaluate the performance of our utilised classifiers to recognise OOIs from the photograph collection. The 8-Scene dataset has various images containing eight class labels i.e., coasts, inside city, forests, highways, open country, mountains, streets, and tall buildings. Similarly, the INRIA holidays dataset also has eight categories, e.g., mountains, waterfalls, sunsets, beaches, historical buildings, restaurants, marine habitats, and rivers. For the INRIA dataset we have used 700 images for training and 200 images for testing. For the 8-Scene dataset we have used 1880 images for training and 808 images for testing. Since both of these datasets are much smaller in size, they cannot be used to evaluate the scalability of LPaMI in terms of its performance in data migration from the HDFS to a structured format in a persistent storage space. Hence, we simulate the MT, BK, and T7 datasets for the aforementioned purposes. For the data migration phase, we set up the distributed Hortonworks Data Platform (HDP 2.6.1.0) cluster consisting of one server (Intel machine Core i7-6950X CPU @ 3.00 GHz) and four agents while using the Ubuntu 14.04 LTS operating system. Each machine consists of 4 processors, 8 GB of RAM and 100 GB of hard disk.  
All the aforementioned datasets are used for the performance evaluation of its OOI extraction plus data migration phases. For the lifestyle pattern mining phase, we opt to perform effectiveness analysis of LPaMI using the INRIA dataset only since it is a real-world dataset of photographs. The INRIA Holidays dataset contains outdoor scene images. This dataset is helpful for us to simulate the photograph collection created in a smartphone of a user because the outdoor scene images can be referred to as photographs taken during different trips. The results discovered in the INRIA datasets are of travelling patterns and we present the visualisations obtained using LPaMI.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Input** & **Algorithm** & **Output** \\ \hline Set of sequence graphs & gSpan & Frequent patterns \\ Set of sequence graphs & Gaston & Maximal frequent patterns \\ Set of sequence graphs & kFISH & Top-k frequent induced patterns \\ Cumulated graph & GRAMI & Frequent patterns \\ \hline \hline \end{tabular}
\end{table}
Table 1: List of algorithms along with their features.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Name** & **Instances** & **Class Labels** & **Type of Evaluation** \\ \hline
8-Scenes (8S) [1] & 2688 & 8 & accuracy of processing OOIs \\ INRIA Holidays [2] & 900 & 8 & accuracy of processing OOIs, pattern mining \\ Memetracker (MT) & 13 M & & execution time of data migration phase \\ Brightkite (BK) & 4.4 M & & execution time of data migration phase \\ Twitter7 (T7) & 15 M & & execution time of data migration phase \\ \hline \hline \end{tabular}
\end{table}
Table 2: List of datasets used.
# Chiral Metasurfaces: A Review of the Fundamentals and Research Advances
## 3 Types of Chiral Metasurfaces
### Single-Layered Chiral Metasurfaces
Similarly, a chiral metasurface with C2 symmetry, which supports BICs, exhibits chiroptical responses with almost perfect circular dichroism (CD = 0.99) [11]. To create the BIC state, the author used a scythe-shaped double-sided-Si inclusion that has C2 inversion symmetry and without mirror symmetry (Figure 2h). Intrinsic chirality was achieved with a CD peak of \(>\) 0.99 at W1 = 191 nm, W2 = 231 nm, and \(\delta\) = 40 nm and a wavelength of 1392 nm by proposing an in-plane simple geometric asymmetry variable of \(\delta=\) W\({}_{2}-\)W\({}_{1}\)[11]. Extrinsic chirality with C2 symmetry of L\({}_{1}\) = L\({}_{2}\), W\({}_{1}\) = W\({}_{2}\), and L\({}_{1}\
eq\) W\({}_{1}\), at an oblique illumination of \(\theta\) = 8\({}^{\circ}\) and \(\varphi\) = 90\({}^{\circ}\) resulted in a strong CD with a peak of over 0.95 (Figure 2i) [11]. These metasurfaces are easily fabricated and have a broad spectrum of applications, such as nonlinear filters, chiral lasers, and tunable chiroptical devices. To solve the low Q-factor resonance of plasmonic chiral metasurfaces, and to overcome the trade-off between the CD and Q-factor in the BIC chiral metasurfaces, plasmonic chiral BIC metasurfaces were proposed [114, 127]. Ref. [114] suggested a plasmonic BIC metasurface with a honeycomb-shaped gold hole metasurface to generate strong CD (Figure 2n). The study proved that with the increment of the period of the structure (hole spacing) the CD decreases gradually (Figure 2o). Spin-selective absorption is facilitated by the structure through the excitation of chiral quasi-BIC resonances, as shown in Figure 2o [114]. However, the CD and Q-factor are strongly correlated due to the configuration, which limits the independent manipulation of the CD and Q-factor. To overcome the trade-off, [113] proposed a novel plasmonic chiral BIC metasurface, as shown in Figure 2l. The metasurface is composed of an integrated-resonance unit that has a twisted vertical split-ring resonator (SRR) as well as a wall. This plasmonic chiral BIC metasurface exhibits a strong CD of around 0.67 and high-Q BIC resonance (Figure 2m). The result shows a new CD manipulation degree of freedom in high-Q plasmonic resonances, which makes it applicable for the detection of chiral molecules and quantum information processing [113]. Fabricating high-Q plasmonic chiral metasurfaces poses challenges related to maintaining structural integrity and lowering losses. These challenges have been addressed through advanced nanofabrication methods, materials with lower optical losses, and precise control over the geometry to obtain both strong CD and high-Q resonance [113, 114].
## 7 Conclusions  
In this work, the demands for modeling the radio channel in inhomogeneous vegetation environments are presented. The obtained results show the complexity of vegetation scenarios. It can be concluded that the morphology as well as the topology of the scenario plays a key role in the estimation of radio signal propagation, due to the strong impact of multipath components in the overall loss mechanism of the propagating radiowave. The agreement between simulation and measurement results validates the 3D ray launching algorithm, making it adequate for radioplanning analysis with the aim of deploying WSN within this type of environments. Moreover, a detailed characterization and analysis of the radio wave propagation for ISM 2.4 GHz wireless sensor networks in heterogeneous vegetation scenarios allow to design environment monitoring tools based on ZigBee and WiFi technologies where WSN and smartphones cooperate providing rich and customized monitoring information to users in a friendly manner, enabling context aware scenario implementation.
## 3 Results and Discussion  
### Comparison of the Primary Channels  
Figure 3 shows the comparison of mass distributions for the six models in Figure 1. In Figure 3a,b, it can be observed that there was a large area of dead flow in the cavity of the cooling plates, which led to a large mass maldistribution, flow resistance to coolant, and increased pump power required for the coolant flowing through the plate. Therefore, for an empty plate, its pressure drop would be augmented due to no flowing channel. It could also validate the importance of designing a suitable flowing channel in a cooling plate. The good flowing channel should be designed to avoid dead flow and flow eddy in order to decrease pressure drop.  
Note that although the dead flow zones were greatly reduced by the parallel and serpentine channels, there were still some dead flow zones existing especially at the corners of flowing channels. For parallel channels, regardless of channel number, most of the coolant flowed into one main channel and about 10-20 percentage flowed through the other channels; thus is can be derived that a parallel channel can lead to a large mass maldistribution and is bad for temperature uniformity.  
Serpentine flow-field designs have been proposed to solve the maldistribution problem inherent to parallel flow-fields as it is only one flowing channel and there is no mass uniformity problem. However, the accompanying problem is that its flow speed and pressure drop are both very high. In order to increase heat transfer effect, the dissipation surface should be enlarged. One of the methods is to widen the channel but that will increase flow dead zones. Another method is to lengthen the tube path in the same plate. However, that will consequently increase the number of corners, resulting in a large local head loss and frictional pressure loss. Therefore, it needs further optimization to balance the mass uniformity and pressure loss.
## 6 Current Therapy for Diabetic Foot Complications  
In order to treat and manage the diabetic foot, it is essential to properly diagnose its stage and severity. Alongside the maintenance of blood sugar levels, current therapeutic strategies involve targeting wound healing, controlling the spread of infection, relieving pressure, and improving blood flow [29]. Analgesic medications such as tapentadol, pre-gabalin, tramadol, duloxetine, acetaminophen, and some opioids (e.g., oxycodone) are employed to alleviate diabetic peripheral neuropathy (DPN)-associated pain. Although these drugs are effective in reducing mild to moderate pain, their frequent use causes nausea, constipation, drowsiness, and confusion [29]. Many antibiotics including nfacillin, flucloxacinillin, dicloxacillin, ceftazidime, cefazolin, ceftiaxone, dalbavancin, oritavancin, telavancin, doxycycline, sulfamethoxazole, or trimethoprim have been effectively used to treat diabetic foot infections, even though no prospective comparative trials have been conducted [60]. It should be noted that several factors such as wound age, the host's immunological state, polymicrobial infection, sanitary conditions, and former antimicrobial therapy may contribute to the development of antimicrobial resistance [61]. Furthermore, the cost of antimicrobial agents recommended for the treatment of infected diabetic foot burdens a large number of diabetic patients, particularly in underdeveloped nations. This results in advanced grades of diabetic foot ulcers that are untreatable in a resource-constrained healthcare system [60; 61]. The initial and most crucial step to heal wounds and lower the likelihood of amputations in patients with DFU is debridement. This involves the removal of necrotic and senescent tissues along with foreign and infectious materials from the wound. Debridement tends to lower the bacterial count while increasing the generation of local growth factors, as well as relieving pressure and facilitating wound drainage [36]. The primary purpose of surgical debridement is to transform a chronic ulcer into an acute ulcer. This has been demonstrated to be more successful in treating DFU than mechanical, biological, enzymatic, or autolytic debridement methods [36]. The use of appropriate wound dressing, revascularization for ischemia, pressure relief, laser therapy, and surgery also play an important role in the treatment and control of diabetic foot [29; 36; 60]. More research is needed, however, to assess the patient demographics for whom these treatments are promising, as well as their cost-to-benefit ratios. [29]. Table 1 summarizes some of the available conventional therapies and their advantages and disadvantages in the management of diabetic foot.  
Figure 5: A schematic diagram representing the pathophysiology of diabetic foot ulcers via different mechanistic pathways. Endothelial dysfunction, ischemia, neuroarthropathy, and impaired immunology contribute to the pathophysiology of DFU.
## 2 Results and Discussion
### Application in Biological Samples
#### 2.4.2 Concentration of Piperacillin and Imipenem in Plasma  
The first group considered consists of patients receiving 4 g of piperacillin as an intravenous infusion over 20 min in 6-h intervals. According to the Summary of Product Characteristics (SmPC) for Piperacillin/Tazobactam (4 g/0.5 g), the maximum concentration of piperacillin after infusion in healthy volunteers was 298 \(\mathrm{\SIUnitSymbolMicro g}\)/mL [35]. The results obtained demonstrate that, for some of the critically ill patients enrolled in this study, the post-infusion concentration of piperacillin in plasma was higher than the declared literature value for healthy subjects. Moreover, for a few subjects, an elevated plasma level was also found before drug infusion (Table 8). It should, however, be noted that VAP patients enrolled in this study were receiving antibiotics over different periods, usually several days before the collection of blood/BAL specimen, which may lead to the accumulation of a drug in the body, thus affecting the intra- and inter-patient variations in antibiotic \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Compounds** & **Peak Area for Blank** & **Peak Area for LLOQ** & **\% of LLOQ** \\ \hline \multirow{4}{*}{Imipenem} & 4.40 \(\times\) 10\({}^{3}\) & & 2.10\% \\  & 7.73 \(\times\) 10\({}^{2}\) & & 0.37\% \\  & 3.24 \(\times\) 10\({}^{3}\) & & 1.55\% \\  & 4.05 \(\times\) 10\({}^{3}\) & & 1.94\% \\ \hline \multirow{4}{*}{ Piperacillin} & 2.82 \(\times\) 10\({}^{4}\) & & 4.13\% \\  & 8.61 \(\times\) 10\({}^{3}\) & & 1.26\% \\ \cline{1-1}  & 1.56 \(\times\) 10\({}^{4}\) & & 2.28\% \\ \cline{1-1}  & 2.77 \(\times\) 10\({}^{4}\) & & 4.05\% \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Carryover presented as the ratio of Peak Area for blank and Peak Area for LLOQ. concentrations measured with TFME-LC-MS/MS. This is in line with other studies, where high piperacillin variabilities were reported in the critically ill [11].
## 9 Simulation Results
Under high dropping probabilities, the recall (resp., false negative rate) is 100% (resp., 0%) for all of the training periods. Under low dropping probabilities, the detection rate decreases as the malicious behavior becomes very close to the normal one. We can notice that the false positive rate becomes 0 when the training period \(T\) reaches 30 in certain cases and 40 in others. At these values of the training period, \(N_{Low}^{*}\) is observed and the IDS can accurately distinguish between normal traffic and selective routing attack. For instance, when the dropping probability is 0.5, the false positive rate becomes 0 at \(T=30\). Before \(N_{Low}^{*}\) is observed (i.e., \(T<30\) or \(T<40\)), the false positive rate curves are random, as they depend on the number of times the monitored profile is observed inside the interval \([N_{Low}^{*},N_{Low}]\), which itself depends on the probability of packet loss.
# Experiment Investigation of Bistable Vibration Energy Harvesting with Random Wave Environment
## 5 Conclusions  
In this study, in order to develop renewable energy, a vibration power generation system using a bistable vibration model for an inverted cantilever beam is designed, and the following conclusions were obtained.  
1. The stochastic resonance phenomenon by the bistable oscillation model in the random wave environment can be reproduced in the laboratory, and theoretical analysis shows that the vibration system has bistable vibration characteristics in the wide range of displacement. In addition, by using Kramer rate, the prediction equation of the excitation frequency of the proposed bistable vibration model is obtained.
2. Using the experimental apparatus developed in this experiment, we can confirm the stochastic resonance which changes the response from mass stability to bistable vibration, the amplification effect was evaluated quantitatively by the measurement results. As a result of the actual measurement, the frequency range in which the probability resonance is most likely to be generated is 0.4 Hz to 0.5 Hz, and this measurement result coincides with the theoretical prediction value of 0.42 Hz in this research.
3. We have developed a bistable vibratory power generation system using piezoelectric elements, a case in which stochastic resonance does not occur; average electric workability was measured by vibration generated, and the measurement results confirmed the effectiveness of the stochastic resonance.
4. Our practical application of a vibratory power generation system to a random wave environment using bistable vibration model was performed; the study on bistable vibration model of an inverted cantilever beam with a mass block at its tip, providing design coverage for detailed configuration parameters, the basic technology which is useful for the research and development of the vibration power generation system for future renewable energy development was prepared.  
[PERSON] contributed to study concepts, study design and manuscript preparation; [PERSON], [PERSON] and [PERSON] contributed to data acquisition and manuscript editing; [PERSON] and [PERSON] contributed to guarantor of integrity of entire study. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Data available in a publicly accessible repository.  
The authors declare no conflict of interest.