esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### The Influence of SBF Immersion Time on the Surface Energy Spectrum of an HA/WS Skeleton  
Energy dispersive spectroscopy (EDS) is a crucial technique for micro component analysis, enabling the simultaneous characterization of sample surface morphology and composition when combined with the SEM method. As depicted in Figure 15, calcium (Ca) elements are highlighted in red and phosphorus (P) elements in green during energy spectrum analysis. A substantial deposition of calcium and phosphorus elements from simulated body fluids onto the three-dimensional porous HA/WS skeleton surface was observed, without any noticeable accumulation. The distribution of elements provides an enhanced visualization of the morphology of laminar sediments, and an increase in immersion time in simulated body fluids leads to the formation of intensified biomineralization deposits. Based on EDS results, the sediments primarily consist of calcium and phosphorus minerals, with the released calcium and phosphorus from mechanical degradation being fully utilized during the mineralization process. Furthermore, the sediments were subjected to elemental quantitative analysis using the EDS electron probe. The results revealed the presence of Ca, P, and O elements in addition to C elements on the sediment surface. The results detailing the HA/WS surface element content after EDS analysis are shown. As illustrated in Figure 16, the EDS analysis of the prepared three-dimensional porous HA/WS skeleton revealed that the calcium content in the calcium-rich region was 32.6 atomic percent (At%) while the phosphorus content was 17.9 At%, resulting in a Ca/P ratio of 1.82. In contrast, the calcium content, phosphorus content, and Ca/P ratio were found to be 16.9 At%, 13.2 At%, and 1.28, respectively in the calcium-poor region. These experimental findings provide strong evidence supporting the crystal theory of calcium-rich and calcium-poor apatite discussed in this manuscript.  
Figure 15: Surface morphology and elemental analysis of three-dimensional porous HA/WS skeleton immersed in simulated body fluids for 21 days.
# An Updated Review of Smac Mimetics, LCL161, Birinapant, and GDC-0152 in Cancer Treatment
###### Abstract  
Inhibitor of apoptosis proteins (IAPs) are suggested as therapeutic targets for cancer treatment. Smac/DIABLO is a natural IAP antagonist in cells; therefore, Smac mimetics have been developed for cancer treatment in the past decade. In this article, we review the anti-cancer potency and novel molecular targets of LCL161, birinapant, and GDC-0152. Preclinical studies demonstrated that Smac mimetics not only induce apoptosis but also arrest cell cycle, induce necroposis, and induce immune storm in vitro and in vivo. The safety and tolerance of Smac mimetics are evaluated in phase 1 and phase 2 clinical trials. In addition, the combination of Smac mimetics and chemotherapeutic compounds was reported to improve anti-cancer effects. Interestingly, the novel anti-cancer molecular mechanism of action of Smac mimetics was reported in recent studies, suggesting that many unknown functions of Smac mimetics still need to be revealed. Exploring these currently unknown signaling pathways is important to provide hints for the modification and combination therapy of further compounds.  
inhibitor of apoptosis proteins (IAPs); Smac/DIABLO; LCL161; birinapant; GDC-0152
## 3 Results
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & & **Group** & **N** & **Mean (mm)** & **Std. Deviation (mm)** & _p-Value_ \\ \hline \multirow{4}{*}{MBL loss} & \multirow{2}{*}{preoperatively} & control & 11 & 3.57 & 1.34 & \multirow{2}{*}{0.063 \({}^{\#}\)} \\ \cline{3-5}  & & graft & 11 & 4.66 & 2.3 & \\ \cline{2-5}  & 1 year & control & 11 & 2.85 & 1.27 & \multirow{2}{*}{0.000 \({}^{\#}\)} \\ \cline{2-5}  & postoperatively & graft & 11 & 1.24 & 0.55 & \\ \hline \multirow{4}{*}{MBL gain after 1 year} & \multirow{2}{*}{preoperative MBL} & control & 3 & \(-\)0.01 & 0.32 & \multirow{2}{*}{0.027 \({}^{\#}\)} \\ \cline{2-5}  & loss \textless{ }3 mm & graft & 3 & 0.58 & 0.34 & \\ \cline{1-1} \cline{2-5}  & \multirow{2}{*}{preoperative MBL} & control & 8 & 0.99 & 0.89 & \multirow{2}{*}{0.000 \({}^{\#}\)} \\ \cline{1-1} \cline{3-5}  & loss \textgreater{} 3 mm & graft & 8 & 4.49 & 1.45 & \\ \hline \multirow{4}{*}{MBL gain after 1 year} & \multirow{2}{*}{bone ridge between teeth} & control & 2 & \(-\)0.15 & 0.29 & \multirow{2}{*}{0.029 \({}^{\#}\)} \\ \cline{1-1} \cline{3-5}  & regarding proximity & & graft & 4 & 0.99 & 0.87 & \\ \cline{1-1} \cline{3-5}  & \multirow{2}{*}{no bone ridge} & control & 9 & 0.91 & 0.86 & \multirow{2}{*}{0.000 \({}^{\#}\)} \\ \cline{1-1} \cline{3-5}  & & graft & 7 & 4.81 & 1.21 & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Changes of the marginal bone level (MBL) at the distal site of second molar. For statistical analysis One-way ANOVA test (\({}^{\#}\)) was used. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Group** & **N** & **Mean (mm)** & **Std. Deviation (mm)** & _p-Value_ \\ \hline \multirow{2}{*}{vertical buccal bone reduction} & control & 11 & \(-\)2.54 & 2.01 & \multirow{2}{*}{0.004 \({}^{\#}\)} \\ \cline{2-5}  & graft & 11 & \(-\)1.37 & 1.04 & & \\ \hline horizontal buccal bone reduction at 3 mm depth & control & 11 & \(-\)1.04 & 0.84 & \multirow{2}{*}{0.313 \({}^{\#}\)} \\ \cline{2-5}  & graft & 11 & 0.07 & 1.58 & \\ \hline horizontal buccal bone reduction at 5 mm depth & control & 11 & \(-\)0.55 & 0.54 & \multirow{2}{*}{0.410 \({}^{\#}\)} \\ \cline{2-5}  & graft & 11 & 1.05 & 1.67 & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Alveolar ridge dimension changes at 1-year follow-up. Abbreviations: One-way ANOVA test (\({}^{\#}\)), independent-samples Mann-Whitney-U test (\({}^{\#}\)). The reliability of interobserver data was verified with a 0.968 intraclass correlation coefficient (ICC) in the case of vertical buccal bone loss and MBL loss. Raw data of all analysis can be find as Supplementary Material Files online.
## 4 L-MMCF Manufacturing Process
### Preparation of Feedback
Retting is a process that breaks down the pectin (an extractive) in hemp stalks, which reduces cooking chemical requirements during the Kraft pulping process. 3. Ash content (inorganics): \"The ash content of the sample may consist of: (1) various residues from chemicals used in its manufacture, (2) metallic matter from piping and machinery, (3) mineral matter in the pulp from which the paper was made, and (4) filling, coating, pigmenting and/or other added materials\" (p. 1) [39]. The measurement of the ash content helps determine inorganic contaminants, with a focus on heavy metal content. As discussed in Section 4.3, heavy metal content needs to be measured methodically throughout the pulping, dope preparation, and spinning process to reduce the risk of exothermic reactions. 4. Metallic ion content, including heavy metals, alkaline, and earth alkaline, needs to be determined separately from ash content via inductively-coupled plasma optical emission spectroscopy (ICP-OES) [60; 65; 78; 79]. Concentration of metal ions, particularly transition metals with multiple oxidation states, above certain limits can result in runaway exothermic reactions or degradation of cellulose pulp yield. 5. Sulphur content: High sulphur content in feedstock, as well as content introduced to Kraft pulps via sodium sulphide (Na\({}_{2}\)S) in the cooking liquor, can lead to yellowing, reduced strength, and evolution of toxic gases during the pulping and regenerated cellulose spinning process [80]. Sulphur must be rinsed out after PHK pulping. 6. Moisture content during all stages of L-MMCF manufacturing needs to be carefully monitored as this directly affects the proper processing of the dissolved pulp and dissolution of the pulp. Evaporation of moisture is needed to obtain the required ratio of NMMO:water:cellulose in the final L-MMCF dope prior to spinning. 7. Lignin content is measured and reported via the kappa number [81]. A lower kappa number indicates a high alpha cellulose content. A low lignin content is desired to improve brightness and increase solubility/accessibility of cellulose during the Kraft pulping process [58; 60]. It is imperative to analyse the pulp to ensure proper removal of contaminants, as well as monitor for potential pickup of contaminants (e.g., metals). Such characterisation for carbohydrate content, extractives, ash content, metal ion content, sulphur content, and moisture content must to be performed during all stages of processing (i.e., feedstock, pulping, dissolution, dope preparation).
# Experimental Study of Composite Hollow RC Column under Uniaxial Compressive Load
## 1 Introduction  
Recently, the use of high-strength concrete (HSC) in composite structures has greatly improved. The HSC has higher compressive strength, greater elastic modulus, and smaller size compared to normal-strength concrete ([PERSON] and Paultre [1]). [PERSON] et al. [2] undertook a comparison of the fracture resistance of normal- and high-strength concrete, which was evaluated in an experimental study. [PERSON] et al. [3] studied the fire resistance of recycled aggregate concrete columns with different concrete compressive strengths.  
The steel-composite hollow reinforced concrete (RC) column was proposed by [PERSON] et al. [4]. That study aimed to prevent the occurrence of brittle failure in a hollow RC column. It featured an inner tube that reinforced the inner face of the hollow RC column, which is shown in Figure 1. This offered strong and durable confinement, because of the reinforcement provided by the inner tube. The column's strength and ductility were enhanced, because of the continuous confinement stress provided by the inner tube. This column had cover concrete on its outside but the hollow section don't has cover concrete by the inner tube. The strength and ductility of the columns were enhanced by the continuous confining stress provided by the inner tube. The confinement of normal-strength concrete (NSC) for steel-composite hollow RC columns has been studied in the last few years [4; 5; 6; 7]. Stress-strain models for confined concrete have been proposed based on the material model created by [PERSON] [8] ([PERSON] et al. [4]). A nonlinear concrete model and a compressive strength model with normal-strength concrete were studied in experiments evaluating its column [6; 7]. [PERSON] et al. [5] studied the optimal confining stress on the core concrete through finite element analysis. Based on [PERSON]'s materialmodel [8], these studies proposed a material model and applied it in evaluating composite hollow RC columns. However, if the strength of the concrete is increased, the proposed material model and analysis method may not be suitable, because [PERSON]'s material model [8] was proposed for a column with normal-strength concrete.  
The main objective of this paper was to investigate the compressive behavior of a steel-composite hollow RC column with an HSC of 50 MPa. This paper presents an experimental study of the compressive behavior of steel-composite hollow RC columns with HSC confined by circular reinforcement, which was tested under axial loading. There were 22 columns used as samples for this test. Test variables included inner tube thickness, hollow ratio, diameter of column, transverse reinforcement space, and normal-strength concrete (20 MPa).
# Potential of Homomorphic Encryption for Cloud Computing Use Cases in Manufacturing
## 4 Use Cases for Homomorphic Encryption for Cloud Computing in Manufacturing
### Predictive Maintenance for SME
The result of the model execution is a report with specific information about the machine's maintenance time, according to the model assumptions and the SME's input data. This report is encrypted in the cloud due to the use of homomorphic encryption and is transmitted to the SME. At the SME, the report is decrypted on premise, and the report is made available to maintenance in manufacturing. For the use case, an FHE process is envisaged, as this offers the most comprehensive functionality and is, therefore, best suited for the use of a complex predictive maintenance model. In contrast to the other homomorphic encryption methods, the FHE method allows an unlimited number of additions and multiplications, with which all mathematical operations can be mapped. These functionalities form the basis for the development of a homomorphically encrypted predictive maintenance model. The use of homomorphic encryption has different advantages in the considered use cases. For the SME, the focus is on the security of the data, as this is a process that is crucial for competition. Homomorphic encryption ensures the security of the data as it uses encrypted data over the entire data life cycle. As part of this, the use of homomorphic encryption also allows the complete outsourcing of model computation to the cloud, as the encrypted in-use data can be used in combination with the model. In summary, the use case illustrates that costs can be saved by strategically selecting a public cloud and service offerings. Combined with the use of homomorphic encryption,  
Figure 7: Classification and cloud architecture for predictive maintenance of an extrusion process. resource-intensive processes can be delegated to the cloud, while ensuring the security of the data throughout its lifecycle. There is no need for a tradeoff between using cloud resources and ensuring data security, as homomorphic encryption enables both.
# Improved Anti-Collision Algorithm for the Application on Intelligent Warehouse
## 3 Group Mapping Query Tree Algorithm
### Protocol Instructions  
1. Query (PRE) represents the query instruction, PRE is the query prefix, and the tag whose ID matches the prefix PRE receives the instruction and responds to the reader query, and sends the new group number information and the remaining ID except PRE.
2. Query(PRE, G) represents the query instruction, PRE is the query prefix, and \(G\) is the group number, \(G\in\{00,01,10,11\}\). In addition, the tag whose ID matches the prefix PRE and group number is \(G\) is activated and participates in this query process.
3. PUSH(S, P) indicates read and write instructions, pushing P onto the bottom of the stack S.
4. P = POP(S) indicates a read and write instruction, and P pops up from the top of stack S.
5. ACK indicates a confirmation instruction, and the reader notifies the tag that it has been successfully identified and that the tag is placed in a dormant state.
6. '\(\mid\mid\)' denotes a connector, which combines two sets of data into a group, such as '00 \(\mid\mid\) 01' means '0001'.
# Analysis of Application Parameters of Hydraulic Slotting Technology in Jointed Coal Reservoirs
## 3 Optimization of Slotting Parameters
### Effect of Slotting Parameters on Crack Development  
To observe the development of cracks in the coal after slotting, the coal was scanned before and after slotting using CT. Because the specimen was artificial and consisted of pulverized coal and clay, there were no natural cracks and only a few pores existed in the specimen. There are two types of CT scanning for specimens, namely, plane scanning, and vertical scanning. In Figure 10, plane scanning is denoted as type I, and was carried out perpendicularly to the direction of the water jet slotting; the vertical scanning is denoted as type II, and was carried perpendicular to the transverse direction of the water jet.  
In Figure 10, it can be clearly seen that various coal fragments peeled off from the edge. When the water jet pressure was low, the shape of the slot was relatively complete. As the pressure increased, the fragment peel-off also increased and the shape of the slot became more uneven. The specimens slotted by 15 MPa (0.09 m/s) and 20 MPa (0.12 m/s) were not split into two parts, but cracks existed at the ends of the slot inside the specimen, and formed a splitting trend.  
To observe the crack morphology, CT (type II) scanning was carried out at the end of the slot at 6-mm intervals as shown in Figure 11. The crack was essentially a vertical crack, and the propagation direction was the water jet transverse direction. Additionally, certain distortion existed in the crack propagation process, which increased the coal's permeability. This indicates that, as the hydraulic slotted pressure increased, the slotted time became longer, and new cracks were more likely to form. Therefore, the water pressure could appropriately increase, provided that the peeled-off coal did not block the hole. The results revealed that the slotting time and pump pressure were the main factors affecting crack development.  
Figure 10: CT scanning image of slots.
# Variational Mode Decomposition Based Time-Varying Force Identification of Stay Cables
## 3 Stay Cable Experiments
### Scale-Model Experiment
#### 3.1.1 Recognition Results for Conditions 1 and 2  
The operating conditions 1 and 2 were under constant tensile force of 5 kN and 6 kN, respectively. In each condition, the original signal of the cable vibration was obtained and smoothed to remove the interference signal during the acquisition process according to Equation (9). The ordinary and smoothed signal of condition 1 were shown in Figure 3 for an example. Then, a fast Fourier transform was performed on the smoothed signal to obtain the fundamental frequency by the frequency difference method, as shown in Figure 4. It was found that the fundamental frequency belonged to [4.33 Hz] and [4.05 Hz] for conditions 1 and 2 respectively.Therefore, a bandpass filter with a cut-off threshold of 4 Hz and a cut-off threshold of 6 Hz, namely, [4 Hz, 6 Hz], was constructed to filter the smoothed signal in two conditions. Then the VMD algorithm was performed on the filtered signal and the processed signals are shown in Figure 4. Obviously, the first component (IMF1) was fuller than the other two components (IMF2 and IMF3), and the value also showed a progressively decreasing form on the order of magnitude, indicating that IMF1 was a relatively major component. Taking the 1 st component (IMF1) as the input, the Hilbert-Huang transform was used to obtain the instantaneous frequency curve. At last, the time-varying cable force value can be calculated from the instantaneous frequency value according to Equation (16). Comparing the calculated instantaneous cable force with the real cable force obtained by the tension sensor, the cable force of conditions 1 and 2 fluctuated around the real value of 5.0 kN and 6.0 kN respectively.  
Figure 3: Condition 1 of scale model experiment: original and smoothed cable vibration signal processed by Equation (9).
## 2 Experimental Program, Materials, Mix Designs, Mix Preparation, and Test Methods
### Mix Proportions  
The experimental study consisted of a total of 32 AAEC mixes with two types of multi-component activators (Type 1 and Type 2) and three different fillers/additive materials (MgO, MWCNT, and rGO). All AAEC mixes were prepared following either the \"one part\" or \"dry mix\" technique. The mix proportions for all 32 one-part AAEC mixes are presented in Table 2, along with their mix designations. Four control mixes (B1, B2, T1, T2) without additions of MgO, MWCNT, or rGO were produced based on previous studies [1; 65; 66; 67; 68], in addition to the other 24 AAEC mixes that contained MgO, MWCNT, and rGO. The binary (B) mixes contained the combinations of FA-C and GGBFS, whereas the ternary (T) mixes were prepared with FA-C, FA-F, and GGBFS. The FA and GGBFS contents were varied from 52% to 60% and from 38% to 45%, respectively, and the silica sand content was kept constant at 30% by mass of the total binder content. The water-to-binder ratio was varied from 0.35 to 0.4 to achieve a minimum slump flow diameter of 500 mm. The dosage of HRWRA was kept constant (0.02 wt% of binder) due to its acidic nature and to prevent the effect of its alkalinity on the varying mix proportions. The PVA fiber was used at 2% by volume for all mixes to induce strain hardening and multiple-micro  
Figure 2: Source, sand, activator, additive, fiber, and admixture materials.  
The AAEC mixes incorporating MgO were prepared using 5% MgO, while those with MWCNT and rGO were prepared by incorporating 0.3% and 0.6% MWCNT and rGO by wt  
of binder contents. The activator/reagent components and the initial chemical ratios in the mix compositions of all AAECs are also presented in Table 2. Activator type 1 has a reagent component ratio (calcium hydroxide to sodium metasilicate) of 1:2.5, while activator type 2 has a reagent component ratio (calcium hydroxide to sodium sulfate) of 2.5:1. These ratios were chosen based on previous research studies on AABs [60; 61; 65]. The fundamental chemical ratios in terms of silicon oxide/aluminum oxide, sodium oxide/silicon oxide, calcium oxide/silicon oxide, and sodium oxide/aluminum oxide were evaluated based on their chemical compositions of reagents and source materials. These chemical ratios were all found to be within the acceptable range as per research studies on fly ash- and slag-based mortars [60; 61; 65].
# Mueller Matrix Decomposition and Image for Non-Destructive Testing of UAVs Skin
###### Abstract  
Recently, Mueller matrix polarimetry (MMP) has been widely applied in many aspects, such as radar target decomposition, monitoring the glucose level, tissue diagnostics, biological samples, etc., but it is still challenging for the complex light-matter interactions of rough surfaces and non-uniform structures such as 3D composite materials. In this work, a unitary matrix-based Mueller matrix decomposition (UMMMD) is proposed for non-destructive testing (NDT) of unmanned aerial vehicles (UAVs) skin. The decomposition model is constructed by the unitary matrix transformation of coherency matrices. In the model, the non-uniform depolarization caused by multiple scattering is quantified with the depolarization matrix and the entropy. From this model, the Mueller matrix of multiple scattering media can be completely decomposed. The proposed method can provide more polarization information than some traditional methods for multiple scattering under different polarization states. The contrast of the obtained polarization image can be improved by about 13 times compared to that of the original image. In addition, the key features of UAV skin such as deformation, shear angles, and density are obtained. The shear angles vary from 17\({}^{\circ}\) to 90\({}^{\circ}\), and the average density is about 20/cm\({}^{2}\). The provided experimental results show that this method is effective for the NDT of UAVs skin. The method also shows great potential for applications in target decomposition, NDT of 3D composite materials, 3D polarization imaging, light-matter interactions of non-uniform complex structures, etc.  
M +
Footnote †: journal: Applied Sciences  
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