esa-sceva/satcom-chunk-collection huggingface dataset:
# A Review on Design Considerations and Connection Techniques in Modular Composite Construction
## 4 Prospects and Conclusions
### Conclusions  
Modular construction has developed into a transformative approach in the construction industry, yielding significant benefits such as enhanced productivity, decreased financial outlays, and superior quality in construction outcomes. This review thoroughly examined its design principles, connection techniques, and obstacles, yielding a detailed comprehension of its present status and prospects.  
* Modular construction has proven its capacity to shorten project timelines by as much as 50% and decrease costs by around 20%, mainly due to the incorporation of off-site manufacturing and optimised processes.
* Volumetric modular construction has been shown to reduce on-site labour activities by transferring up to 80% of work off-site, greatly minimising site disruptions and improving safety and accuracy.
* Composite connections show significant improvements in load transfer mechanisms, boosting efficiency by 15-30% and reaching superior maximum loads, such as 575 kN for bolted connections as opposed to 518 kN for cast-in-place joints.
* The application of Non-Destructive Evaluation (NDE) techniques enhances the assessment of internal quality and structural integrity in composite connections, supporting durability, and effective real-time monitoring in modular construction.
* Despite its benefits, the widespread implementation of modular construction faces obstacles, including connection effectiveness, adherence to regulations, and maintaining structural integrity during transportation and assembly.
* Continued research into automated assembly technologies, frameworks that resist seismic activity, and advanced composite connection systems will foster further innovations and assist in overcoming current challenges in modular construction practices.  
**Author Contributions:** Conceptualisation, M.T.L., K.S.K.K.R., B.K. and R.A.-A.; methodology, M.T.L., K.S.K.K.R., B.K. and R.A.-A.; formal analysis, M.T.L.; writing--original draft preparation, M.T.L.; writing--review and editing, K.S.K.K.R., B.K. and R.A.-A.; visualisation, M.T.L.; supervision, K.S.K.K.R., B.K. and R.A.-A.; project administration, B.K. and R.A.-A. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
## 3 Data Processing Methods  
Based on the equivalent ULA derived from a CBS, this section introduces a data processing framework designed for monitoring millimeter-level ground deformations using a CBS. The framework comprised four components, and the overall workflow is illustrated in Figure 3 (the four colors represent four processing sections, corresponding to the four subsections in this section). Initially, echoes are acquired by observing the target area using two CBSs. Based on the preceding analysis, these echoes can be regarded as SAR echo data, which, after Back Projection Algorithm (BPA) imaging processing, yield a 2D SAR image of the target area. Ultimately, differential interferometric processing is applied to multiple SAR images to extract the deformation values of the target region.  
Figure 2: Geometric diagram of a Uniform Linear Array.
## 3 Results & Discussion
### Evaluation of Molecular Weight and Chemical Composition
#### 3.4.2 Chemical Composition  
Figure 11 shows the FT-IR spectra of the VPE and the shear-treated HDPE at 100/s. The FT-IR spectra of the 100/s HDPE was similar to that of VPE. The characteristic bands of the HDPE were detected in both the VPE and the 100/s samples for C-H stretching at 2915 and 2848 cm\({}^{-1}\), CH\({}_{2}\) bending at 1472 and 1462 cm\({}^{-1}\), and CH\({}_{2}\) rocking at 730 and 719 cm\({}^{-1}\)[24]. In order to confirm the changes of chemical composition after the shear treatment process, the carbonyl peak from oxidation at 1700 cm\({}^{-1}\)[25] was focused; however, it was not detected in the shear-treated HDPE at 100/s. Therefore, no oxidative reaction occurred in the 100/s HDPE. From the results of FT-IR spectra, it can be also suggested that shear treatment has no effect on changes of chemical composition in HDPE.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Sample** & **Mn [g/mol]** & **Mw [g/mol]** & **Mz [g/mol]** & **Mw/Mn** \\ \hline VPE & 27,644 & 156,167 & 825,827 & 5.65 \\
100/s & 26,249 & 150,914 & 786,072 & 5.75 \\ \hline \hline \end{tabular}
\end{table}
Table 4: The averaged molecular weight (Mn, Mw, Mz) and polydispersity index (Mw/Mn) of VPE and shear-treated HDPE at 100/s.  
Figure 10: Molecular weight distribution curves of VPE and shear-treated HDPE at 100/s.
## 2 Materials and Methods
### Model Description  
The mathematical model of microbial fuel cells to be developed simulated and predicted the electrochemical performance in batch or continuous mode of operation. A few assumptions were made to simplify the modeling of different MFC reactors. First, the anode-attached microbes were assumed to be the catalyst for the exoelectrogenic process; second, the exchange current density, or the catalytic effect, was proportional to the concentration of the attached biomass; third, the mass transfer of acetate to anode and oxygen gas to cathode, assumed to be fast enough, compared to the electrochemical processes, was not a limiting factor and was thus neglected; and fourth, the hydrolytic products of dead cells were assumed to not provide a carbon source or energy to the suspended or attached bacterial growth.
## 4 Verification and Discussion of the Example
### Viscoelastic Displacement of the Rod Subject to Uniaxial Tension
#### 4.2.2. Analytical Solution of Viscoelastic Displacement  
According to elastic mechanics, the analytical solution for the vertical displacement of elastic materials is as follows:  
\[w=\frac{P}{2E}\Big{[}\mu\left(x^{2}+y^{2}\right)+z^{2}-L^{2}\Big{]} \tag{28}\]  
where \(E\) and \(\mu\) are the elastic modulus and Poisson's ratio of the material, respectively. Using the same approach as in Section 4.1 and based on the principle of elasticity-viscoelasticity correspondence, the solution of Equation (28) in the phase space after Laplace transform can be obtained as follows:  
\[w(s)=\frac{P}{2}\Big{[}\frac{\mu(s)}{sE(s)}\Big{(}x^{2}+y^{2}\Big{)}+\frac{z^{ 2}-L^{2}}{sE(s)}\Big{]}=w_{1}(s)+w_{2}(s) \tag{29}\]  
and  
\[w_{1}(s)=\frac{P}{2}\Big{(}x^{2}+y^{2}\Big{)}\frac{1}{s}\cdot\frac{\mu(s)}{E(s)} \tag{30}\]  
Figure 4: Slender members with equal cross-section and viscoelastic material. \[w_{2}(s)=\frac{P}{2}\Big{(}z^{2}-L^{2}\Big{)}\frac{1}{sE(s)} \tag{31}\]  
where \(\mu(s)\) and \(E(s)\) represent the Laplace transform of [PERSON]'s ratio and elastic modulus in phase space, respectively. For this example, within the generalized Maxwell model describing the relaxation characteristics of elastic modulus, \(m=1\), and in the generalized Kelvin model used to describe the creep [PERSON]'s ratio, \(n=1\).
# Micro-Gear Point Cloud Segmentation Based on Multi-Scale Point Transformer
## 3 Methods
### Multilayer Feature Fusion Point Transformer
#### 3.3.3 Decoder  
The Decoder, divided into two similar blocks, as depicted in Figure 11 is designed for extracting both global and local features. It consists of alternating Transition Up blocks and PT blocks, with the integration of Skip Connections. These connections link the Encoder's features to the downsampled features, recapturing details lost in the downsampling process. This procedure is repeated until the point cloud returns to its original form, a notable feature of the U-Net network. The Decoder adeptly fuses the point cloud's inherent information with the encoded context, methodically reconstructing and generating a high-quality, complete point cloud. Distinct from the Encoder, the Decoder includes additional Skip Connection attention layers, which are crucial for effective point cloud reconstruction. The Transition Up unit, as shown in Figure 15, leverages the Encoder's features for upsampling operations.  
After decoding through the Decoder, global features undergo another round of Max pooling for extraction. Following the approach of PointNet, these global features are concatenated to each local feature to facilitate point cloud segmentation operations, as illustrated in Figure 11. This method ensures that global context is effectively integrated with local details, enhancing the accuracy and effectiveness of the segmentation process.
## 4 Data Fusion
### Ray-Casting Technique  
Since the complete point cloud of the object may be utilized, it is a common situation that only a subset of all the 3D points is seen by the thermal camera when each thermogram is acquired. The process of spotting the points seen by the thermal camera is normally fulfilled by a ray-casting technique, which allows us, among other things, to handle occlusions. When working with point clouds, one common approach is to first convert the original point cloud into a different data type, such as voxels or a mesh representation. Then, to perform the visibility check, one can start from each pixel of the thermal image and move with discrete steps on a specific line, stopping when the desired voxel (or mesh triangle) is reached ([14; 33]).  
The approach we propose, however, does not need this kind of type conversion and works with data in form of point cloud. Starting from all the 3D points, two types of exclusion are applied in order to obtain a subset, representing all and only the 3D points seen by the camera. In the next sections, the scheme of these two exclusions will be analyzed, but first it is to be said that there is actually another exclusion, which is trivial--that is, the exclusion of all the 3D points projected outside the image plane.
## 4 Building Blocks and Recognition
### Correctness  
**Lemma 4.2**.: _Algorithm \(7\) returns \(True\) on input \(G\) iff \(G\in\mathcal{GS}^{+}\)._  
Proof.: First assume that \(G\in\mathcal{GS}^{+}\) and let \(R=(V_{0},V_{1})\) be an arbitrary representation of \(G\). Let \(I=\texttt{indep}(G)\). By Lemma 3.2, \(|I|\geq s(G)\geq s(R,G)\). Since \(V_{0}\) is a clique and \(I\) is an independent set, we have \(|V_{0}\cap I|\leq 1\).  
Case 1: \(V_{0}\cap I=\emptyset\). Observe that Algorithm 6 returns test\((G,I^{\prime})\), where \(I^{\prime}\) is either \(I\) or \(I\setminus\{v\}\) for some \(v\in I\), hence \(|I^{\prime}|\geq|I|-1\geq s(G)-1\); \(I^{\prime}\subseteq I\subseteq V_{1}\), so test\((G,I^{\prime})=True\) from Lemma 4.1.  
Case 2: \(V_{0}\cap I=\{c\}\). Algorithm 6 starts by calculating the set \(C\), where \(C=I\) if there is no \(v\in V\) with \(|N^{+}(v)\cap I|=2\), and otherwise  
\[C=\bigcap\{N^{+}(v)\cap I:v\in V(G),|N^{+}(v)\cap I|=2\}.\]  
Assume that \(|N^{+}(v)\cap I|=2\) for some \(v\in V\). If \(v\in V_{0}\), then \(c\in N^{+}(v)\), because \(V_{0}\) is a clique. If \(v\in V_{1}\), then \(N^{+}(v)\) can intersect at most one vertex from \(I\cap V_{1}\) and at most one vertex from \(I\cap V_{0}=\{c\}\) and since \(|N^{+}(v)\cap I|=2\), we have \(c\in N^{+}(v)\). For each \(v\in V\) if \(|N^{+}(v)\cap I|=2\), then \(c\in N^{+}(v)\cap I\)so \(c\) belongs to their intersection. If no \(v\in V\) exists with \(|N^{+}(v)\cap I|=2\), then \(C=I\), but \(c\in I\), so again \(c\in C\). We deduce that if \(V_{0}\cap I=\{c\}\), then \(c\in C\) and \(|C|>0\).  
If \(|C|=1\) or \(|C|=2\) then \(\mathtt{test}(G,I\setminus\{i\})\) is tested individually for each vertex \(i\in C\), but \(c\in C\) and \(\mathtt{test}(G,I\setminus\{c\})=True\) by Lemma 4.1.  
If \(|C|>2\), then there is no \(v\in V\) with \(|N^{+}(v)\cap I|=2\). Either \(|I|=s(R,G)\) or \(|I|=s(R,G)+1\), so either all side cliques are represented by vertices of \(I\), or at most one is not represented, say \(S\). We can handle both cases simultaneously by saying that \(S=\emptyset\) in the former case. We have that \(I\) is a maximal independent set, but no vertex of \(I\setminus\{c\}\) can see a vertex of \(S\), because they belong to different side cliques, so \(c\) is connected to all vertices of \(S\) and therefore \(\{c\}\cup S\) is a clique. Let \(T=N(c)\cap(V_{1}\setminus S)\). Then \(|N^{+}(v)\cap I|=2\) for each \(v\in T\), but no such vertex exists by assumption, so \(T=\emptyset\). Now \(N(c)\cap V_{1}=S\), and \(V_{1}\) is a union of disjoint cliques, so \(V_{1}\cup\{c\}\) is also a union of disjoint cliques. Hence \(R^{\prime}=(V_{0}\setminus\{c\},V_{1}\cup\{c\})\) is a representation of \(G\), so from Lemma 4.1\(\mathtt{test}(G,I)=True\).  
On the contrary, if \(G\
otin\mathcal{GS}^{+}\), then there is no representation for \(G\), hence Algorithm 5 cannot generate a block decomposition of \(G\), and therefore Algorithm 5 will return \(False\). \(\Box\)
# Communication Technologies in Emergency Situations
## 3 Desk Research  
Following the description of ECS of Section 2, an overview of the most relevant surveys related to ECS technologies identified in the literature will be presented in this chapter. This is a preliminary study and the starting point for the later systematic review presented in Section 3, and as such, the main outputs of each of the fourteen surveys gathered from the literature are described. Furthermore, the ECS Requirements as well as the main technologies addressed by each of them are identified to motivate the need and the focus of the systematic review presented in Section 3. The conclusions and Table 2 at the end of this chapter summarize the outputs of this preliminary desk research. The research domain of ECS is not new and has been active for many years. Indeed, the interest from the research community on the technologic deployment of emergency management systems has been growing for the last ten years, as reported in [12], an interesting bibliometric survey on the research performance in ICT-based disaster management covering the period from 2009 to 2018. A similar search in Scopus has been performed here, particularizing the domain of the previous work to only ECS and extending it over the time, and it has been confirmed that, effectively, the amount of research publications in the field of Emergency Communication Systems from 2009 until 2020 has continued to grow year after year, being 893 in 2012, 1076 in 2018, and 1314 in 2020, just to mention some examples. Among the most co-occurring keywords identified in [12], it was not surprising to find wireless sensors networks, or ubiquitous computing, but it was also remarkable to find that Unmanned Aerial Vehicles (UAV) were already identified as an emerging technological topic in this domain, including the three most-cited works up to 2018, which are related to the use of UAVs as ad-hoc infrastructure for communication networking, sensing, and processing during disasters [13; 14; 15], from 2016, 2017, and 2018, respectively. As will be seen later in this section, it was identified that most of the surveys on ECS conducted in the last years still tend to pay little attention (or even no attention at all) to this topic. In the review presented in this paper, the emerging topic of Flying Networks, already identified by [12],
# Phytotoxic Substances Involved in Teak Allelopathy and Agroforestry
## 2 Ecological Impact of Teak  
The effects of teak on biodiversity, and its allelopathic effects, are discussed in this section. Teak plantations have replaced a significant proportion of natural forests in the tropical and subtropical regions in the world, and have, subsequently, affected the biodiversity of those forests [29; 30; 31; 32]. The population and diversity of the understory vegetation of the 10-year-old teak plantation were reported to be significantly less than those of native rehabilitated forests nearby, although sunlight intensity on the forest floor was not different between them [4]. Weed diversity under teak trees was also lower than that under the trees of _Albizzia procera_ ([PERSON].) [PERSON], _Aleurites fordii_ ([PERSON].) [PERSON], _Arcesa cantechu_ [PERSON], _Azadiracha indica_ [PERSON], _Gmelina arbora_ [PERSON], and _Toona ciliata_ [PERSON]. [33]. There were also more understory plant species outside of the teak canopy than under its own canopy [34].  
The shade produced by large teak leaves may partially explain this phenomenon. The allelopathic characteristics of teak may also be one of the reasons to reduce the population and diversity of undergrowth plant species of teak forests. Several phytotoxic substances were identified in teak leaves [2; 16; 21; 35]. Teak leaves drop to the forest floor through annual defoliation, and the phytotoxic substances in the leaves may be common in the forest soil due to the decomposition process of the leaves. Those substances may affect the growth of undergrowth plant species. Therefore, many researchers have focused on evaluating the allelopathic potential of the leaves, as teak is a deciduous tree species [2; 16; 21; 35]. In addition, the amount of fallen leaf litter is significant [36].
# Scaled Model Simulation and Experimental Verification of Submarine Flexible Pipeline Laying System
## 4 Experiments and Analysis of Scale Model of Paved Tower
### Experimental Principles  
When carrying out relevant experiments, traditional pool tests can not satisfy the test conditions for flexible piping laying in deep water due to the limitation of the test site. In order to carry out the experiments under the laying conditions of 2000 m water depth, when the scale experiments are carried out at the ratio of 1:20, the models need to be used. The depth of the model pond is 100 m. The current experimental pond of marine engineering cannot meet this requirement [31]. According to actual needs, this paper carries out the method of structural mixing model experiment, combining the results of computer simulation with the experiments of scaling mechanics. The pipeline-laying system is divided into the main hull structure and paving tower. The maximum tensile force of flexible pipe under different sea conditions is calculated and simulated as the load of tensioner support in the experiment. Due to the limitation of the laboratory site, the length of the pipe cannot be simulated completely so that the equivalent truncation treatment can be applied to the pipe. The treatment is to replace the tension generated by the pipe with the same size and direction at the clamping point of the tensioner to the pipe. During the process of simulating vertical laying, the simulated tension is maintained in a vertical downward state. Thus, a flexible pipe laying system is established.
## 2 Materials and Methods
### Column Experiments--Operation System
#### 2.2.3 Sampling  
To evaluate the degradation of TWWE constituents and to determine vertical concentration profiles, samples were collected once a week through five ports in each column. While simulating the precipitation events, sampling was carried out directly before the event and 24 h and/or 72 h after the event to investigate the influence of the precipitation events on the purification efficiency. However, the sampling procedure always needed a total period of 3 h starting from 9 a.m. until 12 p.m. on the specific days to get an equal amount of sample through five suction cups for successful chemical analysis.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Event**} & \multicolumn{2}{c}{**Duration**} & \multicolumn{2}{c}{**Intensity**} & \multicolumn{2}{c}{**Loading Rate Per**} & \multicolumn{2}{c}{**Total Infiltrated**} \\  & \multicolumn{2}{c}{**(min)**} & \multicolumn{2}{c}{**(L s\({}^{-1}\) ha\({}^{-1}\))**} & \multicolumn{2}{c}{**Column Surface**} & \multicolumn{2}{c}{**Volume Per**} \\  & \multicolumn{2}{c}{**(min)**} & \multicolumn{2}{c}{**(L s\({}^{-1}\) ha\({}^{-1}\))**} & \multicolumn{2}{c}{**(L s\({}^{-1}\))**} & \multicolumn{2}{c}{**(L s\({}^{-1}\))**} \\ \cline{2-9}  & **Soil** & **Soil** & **Soil** & **Soil** & **Soil** & **Soil** & **Soil** & **Soil** \\  & **1, 3, 4** & **2** & **1, 3, 4** & **2** & **1, 3, 4** & **2** & **1, 3, 4** & **2** \\ \hline
1 (5a) & 30 & 120 & 136 & 51.6 & 14.4 & 5.5 & 432 & 656 \\
2 (Intensity * 5, Duration * 10 & 300 & 600 & 680 & 258 & 72.1 & 27.4 & 21,630 & 16,413 \\
3 (24 h) & 1440 & 1440 & 136 & 51.6 & 14.4 & 5.5 & 20,765 & 7878 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Precipitation duration (min) and intensities as well as loading rate per soil surface area and total infiltrated volume for the 3 simulated events.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Duration (min)** & **5** & **10** & **15** & **20** & **30** & **45** & **60** & **90** & **120** \\ \hline Intensities (L s\({}^{-1}\) ha\({}^{-1}\)) & 322.9 & 245.1 & 201.4 & 172.5 & 136 & 105.5 & 87.4 & 64.2 & 51.6 \\ \hline
**Duration (min)** & **180** & **240** & **360** & **540** & **720** & **1080** & **1440** & **2880** & **4320** \\ \hline Intensities (L s\({}^{-1}\) ha\({}^{-1}\)) & 38 & 30.6 & 22.5 & 16.6 & 13.4 & 10.5 & 8.8 & 5.5 & 4.2 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Precipitation intensities of different event durations for an event of statistical recurrence interval of 5 years for the site Schöneck/Vogtland.