esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
The purpose of this research was to enhance the ballistic performances of the 3D warp interlock fabric considering appropriate internal warp yarn structural compositions for seamless female soft body armor development. Four different 3D warps interlock architecture which comprises 8:0, 8:6, 8:8, and 4:8 of binding: stuffer warp yarn ratio inside the structure was designed and manufactured. 2D plain weave fabrics (CT-709) made of the same types of material and yarn densities are also considered for comparison. One target panel from 2D plain weave fabric and another four target panels from each 3D warp interlock fabrics were molded with a bust-shaped punch to mimic the frontal seamless female upper torso shape before testing. The ballistic test based on NJJ Level-IIIA standard shows that samples with no stuffer warp yarn (3D-40-8B:0S) and maximum stuffer warp yarn ratios (3D-40-4B:8S) shows perforation at two-shot points and six (all) shots points respectively. On the contrary, samples with balanced binding and stuffer warp yarn ratios (3D-40-8B:8S and 3D-40-8B:4S) performs very well against perforation in all shot points. Besides, samples made of two-dimensional fabrics (2D-35) were penetrated in shot point 6. Besides, sample 3D-40-8B:4S revealed better BFS depth and diameter measurement (lower BFS values) as compared to sample 2D-35 and other 3D warp interlock variants. On the contrary, sample 3D-40-8B:0S recorded the highest BFS diameter as compared to all 3D warp interlock fabric samples, except 3D-40-4B:8S where its entire target points were penetrated. A significant difference in energy-absorbing capability (%) was also observed among 3D warp interlock fabrics and 2D plain fabric panels at different shot points. The energy-absorbing percentage value was found higher for sample 3D-40-8B:4S than 3D-40-8B:8S and 2D-35 panels for majority shot points. This generally shows that a 3D warp interlock fabric should involve an optimized and balanced warp yarn ratios inside its structure for better ballistic performances and lower BFS effects.  
Figure 13: Energy-absorbing capability (%) for 3D and 2D fabric samples at different shot locations. (* All shots penetrated sample 3D-40-4B:8S, * shot six penetrated sample 2D-35 and * shot 1 & 4 penetrated sample 3D-40-8B:0S).
## 3 Results and Discussion
### Gastric Stability and Zinc Dialyzability  
The structural properties, such as the molecular weight and amino acid composition, of peptides can influence the behavior of their metal complexes. Zinc release is attributed to the disintegration of the complex at the acidic gastric pH and the proteolytic action of pepsin, which causes further hydrolysis of peptide and dissociation of their zinc complexes [10]. Unsurprisingly, zinc was released from the three peptide fractions-zinc complexes during simulated gastrointestinal digestion. However, zinc release was notably lower from the P1-zinc complex than from the other complexes (Table 4), which indicated that a peptide fraction-zinc complex with low molecular weight was more stable in the gastric phase, possibly because of its high net negative surface charge [37]. Zinc release from the three peptide-zinc complexes significantly increased after further digestion by pancreatin but remained highest for P1-zinc than for the others (Table 3). A similar study found that two whey protein-derived peptide-zinc complexes with different chelation capacities released low amounts of zinc during simulated gastric digestion but released large quantities of zinc after hydrolysis by pancreatic enzymes [10]. Peptide fractions with a net charge are expected to maintain their zinc chelation capacity at pancreatic pH. Therefore, the release of zinc at this pH can be attributed to further cleavage by pancreatic enzymes, which is desirable for intestinal absorption. The C-terminal end of both Cys and Ser can be hydrolyzed by pancreatic enzymes, while the contents of Cys and Ser in the P1-Zn complex was higher than that in the other complexes and could lead to higher hydrolysis [38]. As a result, zinc dialyzability is higher for low molecular weight peptide fraction-zinc complex, with higher solubility, than for high molecular weight peptide fraction, indicating that the zinc delivered via the former is more bioaccessible (available for absorption). However, more than half of the zinc was retained in the three peptide-zinc complexes after simulated gastric intestinal digestion. The molecular weight of peptide fraction can influence the formation and stability of the zinc complexes, which indicated that peptide structure can affect the zinc release from peptide-zinc complexes for intestinal absorption. This  
Figure 3: Zinc solubility of three peptide-zinc complexes at various pH values.  
suggest the low molecular weight peptide fraction-zinc complex may have the potential to improve zinc bioavailability and to be used as an ingredient in foods.
## 3 Results and Discussion
### Experimental Results of Mechanical Properties  
#### 3.3.1 Compressive Strength  
The compressive strength variations with RWG at 28 and 90 days of curing are presented in Figure 12. At 28 days the compressive strength increased slightly by 1.49% and 1.63% with the incorporation of 10% and 20% of RWG respectively, compared to RC. This slight increase may be attributed to the geometry and size of the RWG compared to the rounded natural sand which improves adhesion between cement paste and glass particles [14; 15]. However, it decreased by 12.43% and 29.45% respectively for CRWG30 and CRWG50. This drop is due to the RGW amount increase in concrete which leads to a low fineness modulus [18], and to the slow pozzolanic reaction that occurs at a later stage and leads to low adherence between cement paste and glass particles for the highest volume content of RWG in the mixture [29].  
At 90 days of curing, the compressive strength increased by 21.11%, 28.89%, and 9.58% respectively with addition of 10%, 20%, and 30% of RWG in concrete; the maximum value was observed for RWG20, whereas it decreased slightly for RWG50 by 3.22% compared to RC. As an overall observation, compressive strength evaluated better with cure age, mainly the one of CRWG50 which reached 30.51% between 28 and 90 days of curing compared to 4.68% of RC. It means that at 28 days of curing, RC achieved 95.32% of its final strength; however, the compressive strength of RWG50 reached only 77% of its strength at 90 days. This finding is due to the pozzolanic effect of glass in concrete, leading to slow growth in compressive strength [55].  
From the microscopic view at 90 days of curing (Figure 10), it can be noticed that the RWG particles are well bound to the ones of cement. These bounds were produced by C-S-H from the slow pozzolanic reaction between silica in glass and alkali ions in cement [28; 35].  
Figure 12: Compressive strength influence of concrete reinforced with different volume percentages of RWG.
## 7 Discussion  
This study offers a comprehensive investigation of the convergence of Artificial Intelligence (AI) and sixth-generation (6G) wireless networks, emphasizing the revolutionary possibilities and related obstacles of this cooperative effort. To support the wide range of anticipated applications, such as virtual reality, online gaming, smart cities, autonomous vehicles, UAV communication, smart robotics, and smart agriculture, the planned 6G networks seek to utilize frequencies between 100 GHz and 1 THz. This will greatly increase the amount of spectrum that is available. In order to optimize these applications and improve network speed, efficiency, and user experience, key artificial intelligence technologies like machine learning, predictive analytics, and real-time data processing are essential. However, there are significant obstacles to the rollout of 6G networks with AI capabilities. The exponential growth in connected devices and data quantities has made scalability a serious problem. Robust solutions are necessary to address security problems, namely those related to intelligent routing, botnet detection, and network traffic prediction. Careful control and oversight are required, due to ethical concerns such algorithmic bias and data privacy. The necessity for a complete infrastructure that promotes mutual enhancement is highlighted by the dynamic interplay between AI and 6G technologies. In order to overcome these obstacles and fully utilize AI-enabled 6G networks, future research will need to focus on computing efficiency enhancement, real-time video analytics, big data analytics, hardware development, and energy management. In order to manage the complexities and guarantee responsible and creative breakthroughs in this field, cooperation between researchers, industry players, and policymakers will be crucial.  
Table 3 shows the summary of challenges in AI for 6G and IoT networks. The integration of AI with 6G technologies in the Internet of Things (IoT) ecosystem presents several challenges that must be addressed to unlock its full potential. Key issues include data privacy and security, scalability, interoperability, energy efficiency, and regulatory and ethical concerns. Advanced encryption and blockchain technology can enhance data protection, while edge computing and hierarchical architectures improve scalability by processing data closer to the source. Standardization and open protocols are essential for interoperability, ensuring seamless communication between diverse IoT devices. Energy-efficient hardware designs and AI-driven power management can extend the battery life of IoT devices. Clear regulations and ethical guidelines are crucial to address the legal and ethical implications of AI and IoT, fostering public trust and ensuring compliance. By addressing these challenges through technological innovation, regulatory oversight, and industry collaboration, the AI-enabled 6G IoT ecosystem can achieve its full potential.
## 4 Resource Management in Heterogeneous Network (RM HetNet)
### User Association (UA)
#### 4.2.1 Signal to Interference Noise Ratio (SINR)  
To evaluate these access schemes' ability to accommodate users, sum rate, EE, and SE, the following summarizes the current research on UA optimization schemes based on SINR in HetNets. In [100], the authors proposed a deep learning scheme based on ultra-dense networks to intelligently associate user devices with competing MBS and SBS. They considered user cell association in the downlink and assumed that each BS always transmits data to its associated UEs based on SINR. The problem of UA is formulated as a constrained optimization problem. A cross-entropy algorithm is employed to attain the optimal labeling solution in supervised learning. Through a combination of the mean squared errors (MSE) criterion and load balancing and fairness constraints, they define a differentiable loss function for the supervised deep learning framework. According to the results, the proposed schemes are comparable to the asymptotically optimal genetic algorithm scheme in terms of maximum data rate and sum rate. Moreover, the proposed schemes outperform the latter in terms of reduced computation time and robustness of the network. Nonetheless, it is important to control the power and allocate resources that need to be considered to improve the performance of the HetNet. The authors tackled the issue of user association and spectrum allocation in 5G HetNets, which use both mmWave and sub-6 GHz technology to deploy macro cells and small cells [101]. UA evaluation is based on the peak rate and SINR in BS for each user in the network. They unveiled a framework for associating users and allocating spectrum in a way that considers the number of users in the network. Specifically, they came up with an innovative approach to cell load estimation. This method was used to assign the spectrum to account for the users' distribution and strike a balance between spectral efficiency and frequency reuse. The UA discussed using two methods: a centralized approach that solved utilizing convex optimization techniques and a distributed method presented as an NC game. A fast-converging best response algorithm achieves the game's unique Nash equilibrium. The UA algorithms and spectrum allocation that were based on centralized, distributed, or relatively basic state-of-the-art approaches were all implemented in their coordinated framework. In simulation results, they evaluated the algorithms' performance based on BS density, traffic distribution, user density, global objective, and cluster size. In addition, they provided useful insights into the development of 5G HetNets. Nevertheless, the network energy efficiency is not taken into consideration. In [102],
# Fault Tolerant Spectral/Spatial Optical Code Division Multiple Access Passive Optical Network
## 6 Comparative Analysis  
Table 6 compares the proposed 2D DW-ZCC ring-based OCDMA system with spectral-spatial and temporal encoding with existing systems based on system cardinality, data rate, received power, reliability, and encoding-decoding techniques. It can be observed that the proposed system supports a cardinality of 128, similar to its conventional 2D DW-ZCC counterpart but optimized for higher reliability and performance.  
In terms of data rate, the proposed 2D DW-ZCC ring-based OCDMA system significantly outperforms conventional 3D implementations, like 3D diagonal eigenvalue unity and multi-diagonal (DEU-DEU-MD), 3D multi-diagonal (MD), 3D single weight zero cross-correlation (SW-ZCC), and 3D perfect difference/multi-diagonal (PD-MD), which operate in the range of 1 to 5 Gbps, while the proposed system reaches 10 Gbps. It is worth  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Code Name** & **System Cardinality** & **Data Rate** &
\begin{tabular}{c} **Received Power** \\ **(dBm)** \\ \end{tabular} & **Reliability** & **Encoding–Decoding** \\ \hline
2D DW-ZCC [5] & 128 & 10 Gbps & \(-\)21 & None & Optimized \\ \hline
3D-DEU-DEU-MD [31] & 136 & 1 Gbps & \(-\)13.9 & None & Conventional \\ \hline
3D-MD [21] & 100 & 1 Gbps & \(-\)12.8 & None & Conventional \\ \hline
3D SW-ZCC [23] & 200 & 4.8 Gbps & \(-\)10 & None & Conventional \\ \hline
3D PD-MD [32] & 150 & 1 Gbps & Not given & None & Conventional \\ \hline Proposed & 128 & 10 Gbps & \(-\)19 & High & Optimized \\ \hline \hline \end{tabular}
\end{table}
Table 6: Comparison of the proposed architecture with existing systems.  
menting that most of the existing work provides analytical analysis of 3D OCDMA systems. Additionally, it can be observed that the proposed system operates efficiently at a received power of approximately \(-19\) dBm, close to the 2D DW-ZCC system's \(-21\) dBm and considerably better than conventional 3D systems that require higher power levels, such as \(-10\) dBm for a 3D SW-ZCC code-based system.  
Furthermore, it can be observed that the proposed system is optimized to ensure high reliability and low-cost implementation unlike conventional 3D systems that are implemented with multiple parallel long-span optical fiber links for spatial encoding and decoding. Consequently, these systems require a high cost of implementation and offer no reliability against system failure at the feeder level. In summary, the proposed system offers superior data rates, better power tolerance, and greater reliability, making it a highly efficient solution for optical network communications.
# Optical Code Construction of 2D Spectral/Spatial BIBD Codes for SAC-OCDMA Systems
## 2 2D-BIBD Code for SAC-OCDMA Systems
### Construction of BIBD Code Families
#### 2.1.1 1D-BIBD Code Construction  
As mentioned above, the code sequences of the BIBD code family are represented as \((L,\ w,\ \lambda_{a},\ \lambda_{c})\). This construction gives the optimal code cardinality i.e.,  
\[|c|=(L-1)/w(w-1) \tag{5}\]  
For example, when \(L=13\) and \(w=3\), \(c=2\). This means that the number of users is limited to 2 (i.e., \(N_{max}=2\)), and a total of 26 codewords can be generated.  
The primitive element \(\alpha\) for \(GF(13)\) is 2. Therefore, the initial blocks for the codes are given as \((2^{0},\ 2^{4},2^{8})(2^{1},2^{5},2^{9})\), which corresponds to coded sequences (1, 3, 9) and (2, 6, 5). Using these two codes sets, different users can be assigned, such as the first user (C1 = 1010000010000) and the second user (C2 = 010011000000). Further, a total of 26 BIBD codewords can be designed by rotating C1 and C2 either left or right.  
Table 1 illustrates an example of the code sequence based on two different 1D-BIBD code families. First, 1D-BIBD code is represented by \(X\) (\(N_{max}=3\) and \(w=3\)), and the second 1D-BIBD code is represented by \(Y\) (\(N^{\prime}_{max}=2\) and \(w=3\)), each having a code length 19 and 13, respectively. Further, a total of 57 and 26 code sequences (i.e., number of users are 57 and 26) can be generated by a cyclic shifting approach.
## 4 Corrosion Protection Measures
### Internal Anti-Corrosion Technique
#### 4.3.3 Composite Pipe Technology  
With the popularity of trenchless repair technology, composite pipe-lining technology for pipeline corrosion repair has attracted more people's attention. For instance, Fiber-glass lining has creep resistance and good performance at high temperatures. Bimetal composite pipes not only improve the corrosion resistance of pipelines but also retain the mechanical strength of steel pipes. The ceramic lining has good wear resistance, high strength, and high-temperature resistance. Moreover, a new composite pipe technology named multilayer lining anticorrosive technology is gaining popularity. The outer layer is a fabric-reinforced flexible plastic pipe, which is usually made of wear-resistant, temperature-resistant, puncture-resistant, and hydrolysis-resistant materials, such as wear-resistant PE/PU/PUX, while the middle layer is made of fiber composite materials, usually made of fiber materials such as polyester or aramid. Different materials are selected for the inner layer according to different application scenarios, but the performance satisfied is nothing more than hydrolysis resistance, swelling resistance, chemical resistance, temperature resistance, and wear resistance. Most of them are made of PE/PU/PUX, PVDF, or other materials. For example, oil-resistant TPU was selected for the inner layer of a fuel transmission pipeline, and polyester fiber was selected for the intermediate fiber layer.  
Although the above three technologies can reduce the corrosion of pipelines to a certain extent, a corrosion prediction and protection system with feedback is the most accurate and reflects the future of the development of anti-corrosion technology. Establishing a high-precision corrosion prediction and protection model has been a hot topic in the research of corrosion protection in recent years. The specific application of corrosion technology needs to take into account the actual working conditions, including the external environment (e.g., soil zone, temperature, water quality), construction conditions, and factors such as cost, on-site installation, and supply of engineering materials. In recent years, researchers have carried out predictive research on the application of coatings, the cathodic protection effect, and the use of corrosion inhibitors in different situations. The main purpose of such research is to optimize the performance of anti-corrosion technology, save costs, and avoid wasting resources. In addition, it will pave the way for the establishment of a real-time model of a corrosion monitoring system in the future.
### Research Contributions  
We mainly focus on enhancement of the coverage and optimization of energy consumption in the network to achieve better QoSensing. The following are the major contributions of this work:  
* A robust network topology is built by implementing the unequal Sierpinski cluster-tree topology (USCT) in order to improve the energy efficiency in the transmission of data.
* The optimal cluster head selection is performed by multi-objective black widow optimization (MoBWo) to increase the efficiency of data transmission.
* The dynamic sleep scheduling is carried out to further reduce the energy consumption by the node which is carried out by the Tsallis entropy enabled Bayesian probability (TE2 BP) algorithm.
* The coverage hole is detected both inside the cluster and between the clusters by implementing the virtual sector-based hole detection (ViSHD) protocol.
* A novel multi-agent SARSA (MA-SARSA) algorithm is presented to learn the environment and repair the holes to achieve better QoSensing.
## 2 Statistics and Methods
### Data Sources and Processing  
Due to technical limitations and other difficulties associated with data acquisition, compiling the inter-regional input-output tables is demanding in terms of time and resources. These challenges can contribute to delays and irregularities in input-output table publication schedules. In China, for example, the initial data acquisition process for the regional virtual water input-output assessment was initiated in 1987 and has since been repeated at 5-year intervals. Within this process, input-output tables are launched every 3-years, however, these are usually presented 2-6 years after data acquisition for the cycle. The current study utilizes the input-output tables for 2007, 2010 and 2012.  
Water consumption data for all industries in Gansu province were derived from the Gansu Water Resources Bulletin in 2007, 2010, and 2012 [37; 38; 39]. Forty-two industry sectors were classified into primary, secondary and tertiary industries according to the Industry Classification Regulations [40]. Primary industries include agriculture, forestry, animal husbandry and fishery; secondary industries consist of those in the manufacturing and construction category, while the remaining industries were classified as tertiary (Table 2 presents industry specific classifications). The complete and direct water use coefficients, with the former referring to the water demand of the entire economic system from the perspective of product life cycles, and the latter referring to water used in the production of intermediate products [41; 42], were calculated and the volume of virtual water exported from Gansu to other provinces was inferred.