esa-sceva/satcom-chunk-collection huggingface dataset:
# TSKT-ORAM: A Two-Server \(k\)-ary Tree Oblivious RAM without Homomorphic Encryption +
## 4 Preliminary Construction: TSBT-ORAM
### Data Query Process
#### 4.2.2 Servers' Response to Query  
Upon receiving query vectors \(\{\overrightarrow{Q}_{i}^{l}|l\,=\,0,\,\ldots,\,L-1\}\) for \(i\in\{0,1\}\), server \(\mathcal{S}_{i}\) needs to conduct bit-wise XOR operations on some data blocks and return the resulting block. Before elaborating the operations, let us introduce the bit-wise XOR operator on blocks as follows.  
**Definition 2**.: _Let \(\bigoplus\) denote a bit-wise XOR operator on blocks. More specifically, assume:_  
\[b_{D,0}\,b_{D,1}\,\ldots\,b_{D,|D|-1}, \tag{2}\]  
_where each \(b_{D,\ldots}\in\{0,1\}\), is a bit-stream representation of block \(D\). The bit-wise XOR of a set of blocks denoted as \(\mathcal{D}\), i.e.,_  
\[\hat{D}=\bigoplus\mathcal{D}, \tag{3}\]  
_is a block whose bit-stream representation is:_  
\[b^{\prime}_{D,0}b^{\prime}_{D,1}\ldots b^{\prime}_{D,|D|-1}, \tag{4}\]  
_where each \(b^{\prime}_{\hat{D},i}=\oplus\{b_{D,i}|D\in\mathcal{D}\}\), i.e., the XOR of the bits with offset \(i\) in every block of set \(\mathcal{D}\)._  
Responding to the query, server \(\mathcal{S}_{i}\) first conducts the following computations for each layer \(l\in\{0,\ldots,L-1\  
denote the subset of blocks that are selected by query vector \(\overrightarrow{Q}_{i}^{l}\). The server computes:  
\[\hat{D}_{i}^{l}=\bigoplus\mathcal{D}_{i}^{l}. \tag{7}\]  
Once \(\hat{D}_{i}^{l}\) has been computed for each layer \(l\in\{0,\ldots,L-1\}\), the server further computes:  
\[\hat{D}_{i}=\bigoplus\{\hat{D}_{i}^{l}|l=0,\ldots,L-1\}, \tag{8}\]  
and then sends \(\hat{D}_{i}\) back to the client.
## 4 Design of MIM-QSMS Decoder for RC-QC-LDPC Codes
### Proposed SMIM-DE  
In [14], the joint edge-degree distributions were considered by the DE in the LUT design process to support rate compatibility. Inspired by this, we propose a SMIM-DE to construct the LUTs of the RC-MIM-QSMS decoder, which is modified from the DE in [14] and considers both the joint edge-degree distributions and the shuffled decoding schedule. Let \(\mathcal{D}_{c}\) and \(\mathcal{D}_{v}\) be the sets of CN and VN degrees for \(K\) target LDPC codes, respectively.  
Then,  
\[\mathcal{D}_{c}=\bigcup_{k=1}^{K}\mathcal{D}_{c,k}=\{d_{c,1},\,d_{c,2},\, \ldots,\,d_{c,\max}\}, \tag{7}\]  
Figure 1: The decoding architecture of the layer-specific MIM-QSMS decoder [15].  
where \(\mathcal{D}_{c,k}\) and \(\mathcal{D}_{v,k}\) represent the sets of the CN and VN degrees of the \(k\)th target LDPC code, respectively. The joint edge-degree distributions can be given by [14]  
\[\rho(\xi)=\sum_{d\in\mathcal{D}_{c}}\rho_{d}\xi^{d-1},\,\theta(\xi)=\sum_{d\in \mathcal{D}_{v}}\theta_{d}\xi^{d-1}, \tag{8}\]  
where \(\rho_{d}\) and \(\theta_{d}\) are the fractions of edges connected to the CNs of degree \(d\) and the VNs of degree \(d\), respectively, in the Tanner graphs of all \(K\) target LDPC codes. Similar to the MIM-QSMS decoder described in Section 3, we consider the LUT design to be processed on the base matrices of the target LDPC codes. For the \(k\)th target LDPC code, we assume its base matrix has \(N_{b,k}\) columns, which correspond to \(N_{b,k}\) layers for the shuffled schedule. Define \(N_{b,\max}=\max\{N_{b,k}:\,k=1,2,\ldots,K\}\) as the maximum number of layers for \(K\) target LDPC codes. Let \(X\in\mathcal{X}=\{0,1\}\) be the random variable for the coded bit. For a random variable \(A\) taking values from \(\mathcal{A}\), we denote \(P_{A|X}(a|x)\) as the pmf of \(A=a\in\mathcal{A}\) conditioned on \(X=x\in\mathcal{X}\). We also define the random variable for the channel output by \(L\in\mathcal{L}\), and the random variable for the V2C (respectively, C2V) message by \(R\in\mathcal{R}\) (respectively, \(S\in\mathcal{S}\)). For convenience, we use the superscript \((t,\,j)\) to represent a pmf computed at the \(j\)th layer and \(t\)th iteration, where \(j=1,2,\ldots,N_{b,\max}\) and \(t=1,2,\ldots,T_{\max}\). The SMIM-DE is illustrated as follows.
# A Blockchain-Based Protocol for Fair Delivery for Receips
## 8 Security Analysis  
Next, we evaluate compliance with the security requirements of our proposal.  
_Effectiveness._ There is no TTP involved in the execution of the protocol. Therefore, the protocol meets the effectiveness requirement.  
_Timeliness._ The protocol ends when or before the deadline \(t_{d}\) expires. Therefore, the protocol meets the timeliness requirement.  
_Nonrepudiation._ The sender provides a signature on the encrypted document (\(f(C)\)) and a signature on the data required to recover the decryption key (\(k\) recorded on the transaction log), which prohibits her from denying having sent this information. The recipient provides a signature indicating a willingness to accept the document (recorded on the blockchain using the _accept_ function), which prohibits him from denying having agreed to receive the document. Therefore, the protocol meets the nonrepudiation requirement.  
_Confidentiality._ The sender sends the document encrypted with a secret key \(K\) (\(C=E_{K}(M)\)) and publishes the data for recovering the secret key on the blockchain so that only the recipient can recover it via his private key. Therefore, the protocol meets the confidentiality requirement.  
_Fairness._ Next, we analyze the different situations that can occur.  
1. _Situation 1._ Only Step 1 is executed. The sender does not have an acknowledgment of receipt, and the recipient does not have the document.
2. _Situation 2._ Steps 1 and 2 are executed. The recipient does not have the content of the document, and the sender does not have an acknowledgment of receipt (they have evidence of the sender's willingness to accept but do not have evidence of key publication).
3. _Situation 3._ All steps of the protocol are executed. In this situation, we distinguish two possible cases: the sender has published correct data for recovering the decryption key (Situation 3.1) and the sender has published incorrect data for recovering the decryption key (Situation 3.2).  
Figure 6: _Publish_ function input data.  
Figure 7: Event logs for the _Publish_ transaction receipt.  
* _Situation 3.1_.: The recipient has the document since they have the encrypted document (Step 1) and the decryption key (Step 3). The sender has the acknowledgement of receipt since they have the recipient's acceptance (Step 2) and proof that they published the data for recovering the key (Step 3).
* _Situation 3.2_.: The recipient has a key that does not allow them to access the content of the document, but they have the evidence to prove that this is the case and that therefore they have not received the document. The sender has the recipient's acceptance (Step 2), but the evidence posted in Step 3 shows that they were dishonest and therefore do not have evidence that they delivered the document.  
The conclusion of the analysis is that the protocol meets the fairness requirement (the recipient receives the document and the sender obtains the receipt, or neither party receives either).
# Path Planning Based on NURBS for Hyper-Redundant Manipulator Used in Narrow Space
## 3 Kinematics Modeling of the Manipulator
### Kinematics Modeling of the Manipulator  
The manipulator consists of eight UCR parallel mechanisms (also regarded as four identical double-UCR parallel mechanism units). Each mechanism rotates 60\({}^{\circ}\) alternately. Four double-UCR mechanism units work together to finish the task of path planning in free space.  
As shown in Figure 6, the \(Z\)-axis of the coordinate is along the normal direction of the platform. The rotation matrix of UCR parallel mechanism between fixed platform and moving platform is expressed as follows:  
\[\begin{array}{c}{}_{n}^{n-1}T=Trans(X_{c},Y_{c},Z_{c})R_{Y}(\beta)R_{X}( \alpha)=\left[\begin{array}{ccc}\cos(\beta)&\sin(\alpha)\sin(\beta)&\sin( \beta)\cos(\alpha)&X_{c}\\ 0&\cos(\alpha)&-\sin(\alpha)&Y_{c}\\ -\sin(\beta)&\cos(\beta)\sin(\alpha)&\cos(\alpha)\cos(\beta)&Z_{c}\\ 0&0&0&1\end{array}\right]\end{array} \tag{14}\]  
where \(\alpha,\beta\in(-90^{\circ},90^{\circ}),\alpha,\beta\) and \(X_{c},Y_{c},Z_{c}\) are mutually coupled variables. The transformation matrix of \(i\)-th platform with respect of the base can be obtained by following equation:  
\[\begin{array}{c}{}_{i}^{0}T=\frac{0}{1}T_{2}^{1}T_{3}^{2}T\cdots\overset{i-2 }{i-1}T_{i}^{i-1}T(i=1,2,\cdots,8)\end{array} \tag{15}\]
# A Novel Method for 3D Lung Tumor Reconstruction Using Generative Models
## 3 The Proposed Model  
Figure 1 illustrates the overall structure of the proposed model, which encompasses three key steps: lung segmentation, tumor detection, and 3D tumor reconstruction. In the subsequent sections, we will discuss each step, elaborating on their functionalities and processes.  
Figure 1: Overview of the proposed model: In step \(1\), two lungs are segmented in CT images using the GAN-based model. In step 2, the tumor is detected using the second GAN-based model. After the features are extracted by VGG16, a 3D model of the tumor is reconstructed using the third GAN in step 3.
# Waves in a Hyperbolic Predator-Prey System
## 2 The Governing Equations and Scaling  
The governing equations read as:  
\[p_{t}+q_{x} = F(p,s) \tag{1}\] \[\tau q_{t}+\
u q = \chi(p,s)ps_{x}-\mu(p,s)p_{x},\] (2) \[s_{t} = G(p,s)+D_{s}s_{xx}. \tag{3}\]  
In this system, the dependent variables, \(x\) and \(t\), stand for the spatial and temporal coordinates, correspondingly, \(x\in\mathbb{R}\), \(t>0\). The dependent variables are \(p=p(x,t)\), \(q=q(x,t)\) and \(s=s(x,t)\). The first and the last one play the parts of the densities of the species, say, the predators and the prey, correspondingly. The first two equations constitute the Cattaneo model for the prey-sensitive movement of the predators, so that the remaining dependent variable, \(q\), stands for the predators' flux. The prey spreads itself purely by diffusion, and the notation of \(D_{s}\) stands for its diffusivity. In what follows, \(D_{s}\equiv\mathrm{const}\) by assumption. We also assume that the predators' diffusivity, \(\mu(p,s)\), and the sensitivity, \(\chi(p,s)\), are specified, and  
\[p\chi(p,s)\to 0,\ p\to+0,\quad\forall\,s\geq 0. \tag{4}\]  
We assume that the reaction terms, \(G\) and \(F\), are prescribed, but postpone further detailing them to Section 5. The mechanical analogy suggests treating the second term on the left hand side of the second equation as a contribution of the resistance of the environment to the predator's motion. So, we will be calling the correspondent coefficient, \(\
u\), as the resistivity.  
Let the notations \(T\), \(X\), \(P\), \(S\), \(Q\), \(D_{p}\), \(C\), \(J_{p}\), \(J_{s}\) stand for characteristic scales for the time, length, predator's density, prey's density, diffusivity, sensitivity, predator's and prey's sources densities correspondingly. The resistivity coefficient, \(\
u\), is naturally dimensionless. Since the values of \(D_{p}\), \(D_{s}\) and \(C\) depend on the concrete species, it is natural to consider them as anyhow given. In contrast, the values of \(X\), \(T\), \(S\), \(P\), \(J_{p}\) and \(J_{s}\) are free to choose. Given this, let us set  
\[T=\tau,\ X=\sqrt{\tau D_{p}},\ Q=P\sqrt{\frac{D_{p}}{\tau}},\ J_{p}=J_{s}=\tau^ {-1}, \tag{5}\]  
and postpone defining the values of \(P\) and \(S\). We also set  
\[\tilde{\mu}(\tilde{p},\tilde{s})=D_{p}^{-1}\mu(P\tilde{p},S\tilde{s}),\quad \tilde{\chi}(\tilde{p},\tilde{s})=C^{-1}\chi(P\tilde{p},S\tilde{s}). \tag{6}\]  
In what follows, every variable employed is dimensionless by default.  
Upon the above scaling, the dimensionless form of the governing equations reads:  
\[p_{t}+q_{x} = F(p,s), \tag{7}\] \[q_{t}+\
u q = \kappa\chi(p,s)ps_{x}-\mu(p,s)p_{x},\] (8) \[s_{t} = G(p,s)+\delta s_{xx},\] (9) \[\kappa=CS/D_{p}, \delta=D_{s}/D_{p}. \tag{10}\]  
For the forthcoming analysis, it is important to distinguish the case when the right-hand side in the flux equation is integrable in the sense that:  
\[\kappa\chi(p,s)ps_{x}-\mu(p,s)p_{x}=(\varphi(p,s))_{x}. \tag{11}\]  
For such an integrability, it is necessary and sufficient to link the diffusivity to the sensitivity as follows:  
\[\mu_{s}(p,s)=-\kappa(p\chi)_{p}. \tag{12}\]
# Study of Surface Defect Detection Techniques in Grinding of SiCp/Al Composites
## 4 Influence of Machining Parameters on Surface Quality
### Analysis of the Effect of Tool Parameters  
Figure 12 shows the effect of tool parameters on the total area and number of defects in the machining region. Figure 12a shows that for the same machining area, the number of surface defects and the total area of defects increase with the increasing tool diameter. This is due to the fact that as the tool diameter increases, the contact area between the end face of the tool and the machined surface increases, leading to an increase in the cutting force, which reduces the surface quality. The values of \(A_{\mathrm{t}}\) and \(N_{\mathrm{d}}\) decrease again when the tool diameter exceeds 6 mm. This is because an increase in diameter leads to an increase in the linear velocity of the abrasive grains on the tool, which has the same effect as a high spindle speed, leading to better surface quality. An increase in the size of the abrasive grain results in an increase in the abrasive spacing on the tool. For a single abrasive, this will cause an increase in the thickness of the undeformed chip. This allows a large number of silicon carbide particles to be removed in the form of brittle cracks, resulting in more defects on the machined surface, as shown in Figure 12b.
## 1 Introduction
In the authors' opinion, the problem of hand tool pose estimation can be solved with a direct or indirect approach. In a direct approach, the tool is detected and then tracked using some robust features that are visible even if it is occluded. In an indirect approach, body joints of the operator and their hands are detected and tracked; the tool pose is derived assuming a unique handling pose of the tool. In order to investigate both paradigms, four artificial vision-based systems have been design, implemented and compared. Each developed system has been evaluated with a set of experiments replicating real industrial scenarios, and their performances have been compared to analyze the pros and cons according to the task properties. Even though, in this work, the authors proposed general methodologies, the developed systems have been tested with a specific use case considering the estimation of the 3D position of a cordless power drill. This study has the ambition to identify the best method(s) to integrate in the next cutting-edge workstations for training and assessment in Industry 4.0. Such systems will be designed with the following objectives:  
* Training an operator on assembly and maintenance procedures with a recorded sequence of actions;  
Figure 1: Vir.GIL virtual guidance system: (**Left**) hardware setup of the system; (**Right**) application UI workflow for starting a new procedure. * Tracking an operator activity to validate each manual operation and certify the quality of the job;
* Detecting risky actions and behaviors in time and alerting the operator;
* Ergonomics monitoring during the procedure for always proposing to the operator the less stressful posture to perform the operations. The main constraints of these solutions should be:
* Real-time execution;
* High accuracy. The real-time execution is a key factor of a virtual guidance system because it has to be ready to warn the operator as soon as possible when their safety is compromised, when ergonomics guidelines are not respected [3; 20] or when the process is going to be completed in the wrong way. On the other hand, a high level of accuracy is required to control the operator's movement in the assembling process to avoid errors. The paper is organized as follows: in Section 2, the authors explain the technical characteristics of the selected methods, how they have been implemented, the experiments designed to evaluate the relative performance, the metrics computed and the statistical analysis conducted for the quantitative comparisons; Section 3 reports the results of the metrics computed on the data acquired during the experiment and the statistical analysis; in Section 4, the results are extensively discussed; Section 5 reports the conclusions of this paper and the future scope.
# Innovation and Application of the Type III Secretion System Inhibitors in Plant Pathogenic Bacteria
###### Abstract  
Many Gram-negative pathogenic bacteria rely on a functional type III secretion system (T3 SS), which injects multiple effector proteins into eukaryotic host cells, for their pathogenicity. Genetic studies conducted in different host-microbe pathosystems often revealed a sophisticated regulatory mechanism of their T3 SSs, suggesting that the expression of T3 SS is tightly controlled and constantly monitored by bacteria in response to the ever-changing host environment. Therefore, it is critical to understand the regulation of T3 SS in pathogenic bacteria for successful disease management. This review focuses on a model plant pathogen, _Dickeya dadantii_, and summarizes the current knowledge of its T3 SS regulation. We highlight the roles of several T3 SS regulators that were recently discovered, including the transcriptional regulators: FlhDC, RpoS, and SlyA; the post-transcriptional regulators: PNPage, Hfq with its dependent sRNA ArcZ, and the RsmA/B system; and the bacterial second messenger cyclic-di-GMP (c-di-GMP). Homologs of these regulatory components have also been characterized in almost all major bacterial plant pathogens like _Erwinia amylova_, _Pseudomonas syringae_, _Pectobacterium_ spp., _Xanthomonas_ spp., and _Ralstonia_ spp. The second half of this review shifts focus to an in-depth discussion of the innovation and development of T3 SS inhibitors, small molecules that inhibit T3 SSs, in the field of plant pathology. This includes T3 SS inhibitors that are derived from plant phenolic compounds, plant coumarins, and salicidene acylhydrazides. We also discuss their modes of action in bacteria and application for controlling plant diseases.  
T3 SS; plant bacterial diseases; _Dickeya dadantii_; fire blight; T3 SS inhibitors; c-di-GMP
## 5 The Simulation Validation and Results Analysis
### The Effect of Different Communication Topology Optimization Strategies
#### 5.2.3 Monte-Carlo Simulations for Scenario 2  
Again, we ran ten Monte Carlo simulations for Scenario 2. The statistical results are shown in Table 5.  
It can be seen from Table 5 that, compared with the fixed communication topology strategy, the global estimate results are more accurate and more effective by using the topology optimization strategy. The simulation results verify the rationality and validity of the topology optimization strategy based on the minimum spanning tree.
## 4 Problem Formulation and Algorithm Proposed
### Algorithm Proposed
Lemma 3: _Given a disk with 6 sectors, if each sector covers at least 1 node with beamwidth \(\pi/3\), called HexNodes, and another 3 homogeneous nodes, which are called TriNodes that are located in 3 interlaced sectors of them, the nodes interconnect if the maximal interior angle of the TriNodes is no more than \(2\pi/3\)._  
Proof: For the reason that further constraint of orientations emerge, here, we need to prove that the connections are assured between _HexNodes_ and _TriNodes_ as well as the connections of the inner _TriNodes_. First of all, it is known that two _HexNodes_ in opposite sectors are connected, so if we want to connect the 6 _HexNodes_ through _TriNodes_, there must be one _TriNode_ in each opposite sector. This can be described as a permutation and combination problem, i.e., how we can select from sector sets of [0, 3], [1, 4] and [2, 5] that every set is chosen as the only element? Taking [0, 1, 2] and [0, 1, 5] as examples, both sets construct a semicircle, implying that the three _TriNodes_ lay on one side of the diameter; in this situation, they cannot communicate with all the _HexNodes_. Thus, there are only two possible scenarios left: [0, 2, 4] and [1, 3, 5]. Figure 9: Any 3 nodes with directional transducer of \(\pi/3\) beamwidth are interconnected. As depicted in Figure 10, 9 nodes construct a _target group_ satisfying the above conditions, where the dashed lines denote symmetric connections of the inner \(HexNodes\) that are colored in orange. The solid lines will be analyzed next. Without loss of generality, let \(x,y,z\) be the outer nodes in the sectors, which cover no less than 2 nodes, and the corresponding \(x^{\prime},y^{\prime},z^{\prime}\) lay in the opposite sectors. From Lemma 2, we know there must be an acute angle formed by \(TriNodes:x,y,z\), assuming \(\angle xyz\), so node \(y\) can cover \(x,z\) with a \(\pi/3\) beam as well as node \(y^{\prime}\), covered by \(\angle xyz\). On the other hand, \(y\) lays in the sector covered by \(y^{\prime}\); thus, a symmetric connection \(y\leftrightarrow y^{\prime}\) and two directed connections, \(y\to x\) and \(y\to z\), are set up. Meanwhile, assuming that \(\angle yzx\) is the maximal interior angle, which is less than \(2\pi/3\) and larger than \(\pi/3\), then \(\angle xzz^{\prime}+\angle z^{\prime}zy<2\pi/3\); this implies that either \(\angle xzz^{\prime}\) or \(\angle z^{\prime}zy\) must be less than \(\pi/3\), so a symmetric connection \(z\leftrightarrow z^{\prime}\) and an only directed connection of either \(z\to y\) or \(z\to x\) can be established. The same applies for \(x\). Thus, the Lemma 3 is proved. Based on the analyses above, an ingenious way to construct a connected group that radiates the entire plane is thus formed, as is detailed in the following algorithm.
## 3 Results
### lgE Level Analysis in Serum (ELISA)  
Serum IgE levels were quantified using ELISA after inducing a hyperimmune reaction through repeated DNCB exposure. This analysis revealed distinct differences in IgE levels between the experimental groups. The control group had an average IgE level of 66.63 ng/mL, whereas the AOO group had a level of 136.65 ng/mL. PEMF stimulation at 15 Hz and 75 Hz resulted in average IgE levels of 307.09 ng/mL and 553.69 ng/mL, respectively, illustrating a frequency-dependent increase in IgE secretion. The most pronounced elevation was observed in the sham group, with an average level of 1942.32 ng/mL, signifying a substantial increase in IgE secretion, approximately 29.2 times that of the control group (** \(p<0.01\)).  
Upon detailed comparison, although the 15 Hz and 75 Hz PEMF groups showed elevated IgE levels, indicating a 1.8-fold increase with frequency, this difference was not statistically significant (\(p>0.05\)). When comparing the PEMF and sham groups, which exhibited severe skin abnormalities caused by DNCB, a significant reduction in IgE levels was observed. The PEMF 75 Hz group showed a 3.51-fold decrease, whereas the PEMF 15 Hz group displayed a more substantial reduction, with a 6.32-fold difference in IgE concentration, both achieving significant decreases (** \(p<0.01\)) (Figure 5).  
These findings underscore the role of PEMF frequency in modulating serum IgE levels after DNCB exposure, suggesting the frequency-dependent efficacy of PEMF stimulation in altering immune responses.  
Figure 4: Comparative analysis of the total splenocyte numbers in the spleen in each group. All groups were statistically based on the control group. Each bar represents the average number of splenocytes \(\pm\) standard deviation, emphasizing the observable reduction in splenocyte counts in the PEMF groups compared with the sham group (*** \(p<0.001\)).