esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Implications for Design of Vibrotactile Interfaces  
Vibrotactile interfaces designed for BMIs often rely on a multi-channel setup, wherein multiple skin sites are stimulated with various frequencies of vibration, with each site encoding stimuli with different meanings [14; 37; 38; 39]. Some vibrotactile interfaces use the 2-point touch discrimination threshold (2-TDT) to determine the minimum inter-stimulus distance between two stimuli [13; 28; 40]. The 2-TDT is defined as the distance needed to confidently distinguish between two simultaneous touch stimuli applied to the skin. For dermatomal regions of the arm and forearm, mean 2-TDT values range from 3.1 cm to 4.5 cm [41]. However, the 2-TDT may not accurately represent the distance needed to distinguish between two simultaneous vibrotactile stimuli because different mechanoreceptors are involved in the perception of touch vs. vibratory stimuli (i.e., Merkel's disks for touch perception vs. MCs/PCs for vibration perception) (cf., [34]; see also [42]).  
As shown in Figure 2, we observed mechanical propagation of vibrotactile stimuli across the hairy skin of the arm at distances up to approximately 8 cm. For high-intensity source stimuli, propagated vibrations could be expected to confound perceptual discrimination within a second stimulation channel applied 4 cm from the source. With an inter-site distance of 8 cm however, the magnitude of propagated vibration is just a small fraction of the vibrotactile discrimination threshold. Thus, vibrotactile interfaces that employ low-cost ERM vibrating motors can avoid potential perceptual errors caused by the propagation of high-intensity vibration stimuli if they ensure a minimum distance of 8 cm between two stimulation sources.  
We have employed this kind of low-cost vibrotactile interface to mitigate proprioceptive deficits observed in stroke survivors. We attached a multi-channel feedback interface to the less affected arm, with inter-stimulus distances greater than 8 cm. The interface provided hand position feedback of the more affected arm to the non-moving, less-affected arm [18; 43; 44]. While the system proved to be effective in improving the accuracy of simple, single-degree-of-freedom movements [45], future work is focused on determining efficacy on multi-degree-of-freedom movements. Note that our system builds upon previous designs, which have utilized vibrotactile feedback to provide grip force feedback for upper extremity amputees [17], and to reduce visual attention needed to make movements in people with spinal cord injury [12]. These vibrotactile interfaces could also be applied to other locations of the body if the tactile sense of the arm is affected by disease or injury. Therefore, future studies should look to investigate vibration propagation on the skin of other body regions such as the chest, back, and legs.
# EngraveChain: A Blockchain-Based Tamper-Proof Distributed Log System
## 4 Security Analysis
### Security against Attacks  
We now analyze the security of our solution against the following attack scenarios:  
_Modifying the records:_ The security of the blockchain guarantees that an attacker cannot modify the records in the log. As long as more than \(\frac{2}{3}\) of the peer nodes are not compromised, the BFT consensus protocol ensures the integrity and consistency of the records of the honest nodes [11].  
_Privacy:_ The privacy of the information stored on the blockchain is achieved both by the access control mechanism of the blockchain (the separate Hyperledger channels in our implementation) and by encrypting the data before writing it to the log file. The channels in Hyperledger ensure that only authorized entities can access the data on the blockchain. Encrypting the data before writing it to the blockchain, ensures that even nodes that are authorized to read the data from the channel can only read the ciphertext. This preserves the privacy of the information between participants and nodes that wish to collaborate in order to better secure their data, but do not wish to share the data. While the privacy of the data is secured by strong encryption, the write pattern (i.e., data size and writing rate) is visible. Parties who are concerned that the writing pattern may leak some information to their competitors can modify their writing pattern. This can be done,  
Figure 5: Separate channels with distinct blockchains. Here we demonstrate a set of peer nodes (who are also participants in this figure), all of whom have access to the public channel (**bottom**), yet with only some of the peer nodes having access to the restricted channel (**top**).  
for example, by grouping logs or adding dummy records (as encrypted dummy records are indistinguishable from other encrypted records). We note that in the case where the writer uses a public key encryption scheme [34] (a.k.a. asymmetric encryption) to encrypt its data while safeguarding its private key off of the infected machine, the participant can also prevent an attacker from reading past records of the compromised system.  
_DoS:_ An attacker that controls a participant can try to clog the blockchain by sending far more log entries than expected. In order to prevent this, the peer nodes can specify a policy limiting the rate and sizes of entries from any single participant. We note that anomaly detection in writing patterns can be carried out by participants and peers and also trigger a temporary revocation of the attacking participant, e.g., by using the Hyperledger Fabric revoke method [33].
# Hand Posture Recognition Using Skeletal Data and Distance Descriptor
## 3 Proposed Method
### Classification  
Four classifiers were tested: support vector machine with linear kernel function (SVM-Lin) [47], linear discriminant (LD) [48], ensemble of multiple decision trees--tree bagger (TreeBag) [49], and weighted \(k\)-nearest neighbors classifier with \(k=10\) (10 NN-W) [50]. The parameters of the tested classifiers are listed in Table 1. We chose parameters starting from default values of our classification tool. We then tried to change each of them and observed if the changes caused improvement of results.  
Some of the recognized shapes differ only in the spatial orientation of the hand. Therefore, the following modification of the nearest neighbor classifier was proposed. When searching for the nearest neighbor, only those samples from the training set whose orientation is similar to the tested one are taken into account. The training sample is then marked as a potential nearest neighbor only if  
\[acos\left(\frac{n_{cx}\cdot n_{ct}}{|n_{cx}||n_{ct}|}\right)\leq\gamma_{t}, \tag{8}\]  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Classifier** & **Parameter** & **Value** \\ \hline SVM-Lin & kernel function & linear \\  & box constraint level & 1 \\  & multiclass method & one-vs-one \\ \hline LD & covariance structure & full \\ \hline TreeBag & number of learners & 30 \\ \hline
10 NN-W & number of neighbors & 10 \\  & distance metric & Euclidean \\  & distance weight & squared inverse \\ \hline \hline \end{tabular}
\end{table}
Table 1: The parameters of the tested classifiers.  
where \(n_{cx}\), \(n_{ct}\) are normals to the palm of the classified and training sample respectively, \(\cdot\) denotes scalar vector product, and \(\gamma_{t}\) is the threshold. We named the proposed method the nearest neighbor classifier with orientation restriction (NNOR). It should be considered as one of the novelties proposed in this paper.
# Polyimide Encapsulation of Spider-Inspired Crack-Based Sensors for Durability Improvement
## 1 Introduction  
Sensor encapsulation is a crucial issue that needs to be taken care of in order to increase its applicability to various research fields. For example, bio-implantable devices, artificial skin, and wearable sensors need to endure wet and biochemical environments, and encapsulation of the device would guarantee the device performance [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12]. Recently, a new type of mechanosensor inspired by a spider's sensory organ system has been reported, which includes nanoscale cracks on a metallic layer over a polymer substrate [13]. This spider-inspired sensor dramatically changes its electric resistance with the applied strain which widens the crack width. It also shows incredibly high sensitivity to strain with its extremely high gauge factor of over 2000 and vibration which is estimated to be measurable up to 10 nm amplitude [13]. The gauge factor (GF)--one of the most important indicators of the sensitivity of strain sensors--is defined as \(\mathrm{GF}=(\Delta\mathrm{R}/\mathrm{R}_{0})/\varepsilon\). Where \(\Delta\mathrm{R}\) is the resistance change with deformation, \(\mathrm{R}_{0}\) is the resistance before deformation, and \(\varepsilon\) is the applied deformation. Moreover, it has diverse advantages including flexibility, wearability, and multifunctional sensing abilities [13; 14; 15; 16; 17]. However, the durability of the sensor in harsh environments of liquids and/or high temperature isstill a challenging issue. Sensor systems are usually exposed to various surrounding environments including different surrounding liquid, humidity and temperature, which lead to damage of the sensory system and shortening of the sensor's life. To solve this matter, we have demonstrated the extended capability of the crack sensory system by replacing the substrate from polyethylene terephthalate (PET) with polyimide (PI) and encapsulating the sensor with PI. Because the polyimide is widely used in flexible electronics or sensor systems due to its high durability and flexibility [2; 18; 19], there are various advantages in applying our crack-based sensor system. Furthermore, [PERSON] et al. has developed a device encapsulated with polyimide, demonstrating new opportunities for the sensors to be applied in clinical fields [20; 21]. The encapsulated crack sensor can be used in diverse applications such as a wearable voice/pulse/motion sensor, strain gauge sensor at high temperature, vibration monitoring sensor for identifying internal damage to bridges, ultra-sensitive pressure/force sensor for surgical devices, and skin attachable health monitoring sensor.
# Comparison between Laser and Stamping without Die (SWD) for Micro Tapered Hole Forming
## 5 Conclusions  
This study proposes SWD, and the experimental results prove the feasibility. This method overcomes the bottleneck of a required lower die for micro stamping. The specific conclusions are described as follows:  
1. We have demonstrated the feasibility of stamping process by a micro-scale tapered punch head and the micro punch head is not apparently worn in the stamping process.
2. Micro stamping produces a better micro tapered hole wall quality with Ra value of 0.8 \(\upmu\)m than by laser processing.
3. The stamping results of Al6061 and C2680 workpieces show that, with the same stamping depth, the prominence height at the inlet of the C2680 is lower than Al6061 (\(\sim\)20%). The results show that the C2680 workpiece has better micro tapered hole wall quality than Al6061.
4. The required tapered hole morphology and size can be accurately obtained by controlling the stamping depth. The inlet and outlet diameter of microholes can be adjusted by the stamping depth or punch head angle.
5. The micro tapered hole depth is 300 \(\upmu\)m, and the maximum ratio of inlet to outlet diameter is 18:1.
6. Laser processing is used to form tapered holes. Although the energy and defocusing distance can be adjusted, the largest taper angle in the experiments was 9.7\({}^{\circ}\), which was smaller than the angle of 23.5\({}^{\circ}\) produced by the stamping process.
7. The surface roughness of micro stamping is 33% lower than laser processing.
8. SWD, as proposed in this study, can make the required taper angle by changing the punch angle.  
Figure 17: Micro punch head morphology after stamping (**a**) OM image (**b**) partially enlarged SEM image.  
While reverse EDM used in this experiment is a low throughput process, grinding punch head is an alternative method and can be used for mass production.  
The authors would like to acknowledge the financial support provided by Ministry of Science and Technology, China (Taiwan) (103-2221-E-027-135-MY2).  
[PERSON], [PERSON] and [PERSON] performed the experiment and data analysis work; [PERSON], [PERSON] and [PERSON] wrote the manuscript; [PERSON], [PERSON], [PERSON] and [PERSON] contributed revision of this paper.  
The authors declare no conflict of interest.
## 3 Results and Discussion
### Thermal Stability  
Regular onset decomposition temperature \(T_{d}\) and 5% onset decomposition temperature \(T_{d,5\%}\) for the pure components are presented in Table 2. TGA thermograms are included in the Supplementary Materials. Again, differences regarding values previously published were likely due to impurities, especially water, in the samples. In addition, the eutectic mixture was subjected to thermogravimetric analysis in order to determine its decomposition temperature. Figure 2 shows the dynamic TGA thermogram of the mixture, as well as that of the pure components.  
The \(T_{d,5\%}\) value obtained for the eutectic mixture was 473 K, while \(T_{d}\) was 575 K. Unlike the pure components, the mixture exhibited a two-step decomposition that could be related to an independent decomposition of surfactant and polymer.
# Joint Location-Allocation Model for Multi-Level Maintenance Service Network in Agriculture
## 2 Literature Review
Several experiments were conducted to demonstrate the efficiency of the developed method compared with other exact approaches. [PERSON] and [PERSON] et al. [37] developed a Benders decomposition-based exact approach to determine the location of the service facility and service region in each stage. [PERSON] et al. [38] developed an exact algorithm integrating with the convexification strategy and branch and cut method for solving larger cases in the real world. [PERSON] et al. [39] focused on the capacitated facility location problem. Lagrangean relaxation was applied for the nonlinear objective function, and the branch and bounded method was then introduced to obtain an optimal location plan with a lower bounding scheme. [PERSON] et al. [40] proposed a brand-and-brunch-based solution method, and two valid inequalities were introduced with an approximation algorithm to obtain the optimal results. Considering heuristic algorithms for FLAPs, [PERSON] et al. [41] developed a hybrid genetic algorithm integrating with a logarithmic-quadratic proximal prediction-correction method to obtain the optimal location of retailers in a decentralized supply chain system. [PERSON] et al. [42] designed an improved particle swarm optimization method to solve the multi-objective in dynamic facility location problem. [PERSON] et al. [43] proposed a MIP-based optimization model, and an improved firefly algorithm-based heuristic approach was designed to solve a larger case with more than 100 nodes and 600 candidates. [PERSON] et al. [44] concentrated on the mobile facility location problem and developed two local search neighbourhood algorithms to solve two subproblems in reality. [PERSON] et al. [45] developed a heuristic solution approach integrating the greedy search and maximum coverage approach to determine the location and allocation of drone launching centres. [PERSON] [46] considered these NP-hard problem and proposed a heuristic solution method based on maximum flow to find the optimal location. In addition, other heuristic algorithms were also applied to obtain the optimal location of a service facility in the service network, e.g., the simulated annealing algorithm [47], the kernel search heuristic algorithm [48], the tabu search method [49], and the greedy search heuristic approach [50]. In all, although several studies have been conducted on FLAPs, few studies exist on multi-level FLDPs in maintenance service networks, especially in agriculture. In addition,unlike in traditional studies, maintenance demands in connected areas are always clustered as a service unit in agriculture, and few studies consider facility location problems based on service district. Therefore, it is urgent to develop a more comprehensive solution framework considering contiguity criteria and multi-level constraints in maintenance service networks in agriculture.
Three different indicators are introduced in the evaluation process that includes fit values analysis, poles estimation, and computation time. The results from several cases indicate that the UPC algorithm provides the best performance. The paper is organized as follows: Section 2 provides the methodology of the study and theory behind the design and implementation of the subspace algorithm. In Sections 3 and 4, the numerical and experimental examples for verification of the weight matrices are presented, respectively. In Section 5, the findings of the study are presented and discussed. Finally, concluding remarks of the work are given in Section 6.
## 2 Use of Graph Theory  
### Generalities  
In reference [13], a graph theory approach was used by means of the TSP, where the solution obtained from the assembly of fragments is a series of _contigs_ rather than a Hamiltonian Path. In TSP, all possible edges of the graph are considered, but when there is no possible connection between two nodes, it is usually represented using a very large weight to prevent it from showing up in the final solution. Applying TSP to DNA fragment assembly might be considered excessive, even though the expected results are obtained, since the fraction of real connections is very small. A graph theoretical approach using other algorithms might give better results.  
The size of real life DNA fragment assembly problems is huge, with 35 base fragments and a coverage of 40, we get about 700 million fragments for human chromosome number 1, which has 245 million base pairs. It is known that the DNA fragment assembly problem is NP-hard (Non-deterministic Polynomial time hard), since it can be reduced from the shortest common superstring problem [14]; in practice, we must only use linear time algorithms, even if by doing so we sacrifice correctness and obtain only an approximate solution.
## 3 Transmission Point Selection in Multi-Band Multi-Connectivity Operation
### Sequential Transmission Point Selection Algorithm
We know that the TP \(n^{*}\) has the minimum service time among all TPs according to the sequential TPS algorithm. Thus, by Lemmas 1 and 2  
\[T_{n^{*}}^{l}(=T) =T_{n^{*}}^{l-1}+t_{k^{*}}^{n^{*}} \tag{19}\] \[\leq\frac{1}{N}\sum_{n=1}^{N}T_{n}^{l-1}+t_{k^{*}}^{n^{*}}\] (20) \[\leq\frac{1}{N}\sum_{n=1}^{N}T_{n}^{l}+t_{k^{*}}^{n^{*}}\] (21) \[\leq\frac{1}{N}(\sum_{n=1}^{N}\hat{t}_{k}-t_{k^{*}}^{n^{*}})+t_{k ^{*}}^{n^{*}}\] (22) \[=\frac{1}{N}\sum_{n=1}^{N}\hat{t}_{k}+(1-\frac{1}{N})t_{k^{*}}^{n ^{*}}\] (23) \[\leq\frac{1}{N}\sum_{n=1}^{N}\hat{t}_{k}+(1-\frac{1}{N})\hat{t}_ {k}\] (24) \[\leq\frac{1}{N}\sum_{n=1}^{N}\hat{t}_{k}+T^{*} \tag{25}\]  
**Theorem 1**. : _Sequential transmission point selection algorithm is a \(2\)-approximation of optimal solution._  
Proof. : According to Lemmas 1-3, it is true that  
\[T\leq\frac{1}{N}\sum_{n=1}^{N}\hat{t}_{k}+T^{*}. \tag{17}\]0  
where \(T^{*}\) and \(T\) denote the optimal solution and the approximation algorithm solution. Here, \(N\) denotes the number of TPs in the network and is assumed to be large. Therefore, the sequential transmission point selection algorithm is a \(2\)-approximation algorithm.
## 3 FLARoute: Fair Locality Aware Routing
### FLARoute Design
#### 3.2.1 Phase 1: Computing the Fair Forwarding Utility  
Phase 1 introduces PoiUtility, which is elaborated in [72]. \(U_{a}(d)\in[-\infty,1]\), the PoiUtility of a node \(a\) for a destination \(d\), is given by Equation (1), where \(E_{a}(d)\) and \(L_{a}(d)\) represent the encounter-based and location-based forwarding utilities, respectively, and the constants \(\mu\) and \(\omega\) are non-negative parameters of the forwarding utility, such that \(\mu\gg\omega\) and their sum equals 1. Encounter history is only maintained between nodes that have a mutual POI (i.e., either home or office location), and in absence of a transitive property, location-based information--which is obtained via GPS traces collected at fixed intervals - is used to forward messages closer to the location of their destination. Due to spatial locality, forwarding the message closer to the destination's location increases the likelihood of finding relay nodes that have encounter history with the destination.  
\[U_{a}(d)=E_{a}(d)\mu+L_{a}(d)\omega \tag{1}\]  
Unlike encounter-based forwarding utilities reinforced with a transitive property that epidemically extends the visibility of node popularity over multiple hops, the adopted location-based utility allows a more even contribution among nodes. The choice of relay nodes with the location-based utility depends on their spatial closeness to the destination--a property that relies more on routine than popularity. That way, the potential of less popular nodes can be fully utilized through their ability to deliver messages in multiple hops, thereby making routing less biased towards popular nodes.
# Exploring the Potential of Sensing for Breast Cancer Detection
## 5 Biosensors for Breast Cancer Detection
### Molecularly Imprinted Polymer  
A molecularly imprinted polymer (MIP) is a polymer that has been designed by applying the molecular imprinting technique, and MPI can generate cavities in the matrix of the polymer to attract a particular template molecule [130]. Manufacturing a nano-MIP involves controlled polymerization around a targeted choice, immobilized on solid-face support [131]. This is then packed as a column. The nano-MIP is made by first exposing the target to monomers that find their optimal binding positions on the target through self-assembly. Different solvents and cross-linking agents have been used to complete this step. In the pre-polymerization step, the distribution of the functional monomers around the template is precisely organized by the chemical properties and shape (see Figure 5).  
Figure 5: Different steps of molecularly imprinted polymer preparation [132].  
The monomers are fused together through polymerization by exposing the column to UV light, activating a catalyst that generates free radicals. The free radicals collide with the carbon-to-carbon double bonds in the monomers, initiating a polymerization chain reaction. Once sufficient polymerization has occurred to form the desired level of polymer formation around an individual template molecule, we stop polymerization. Stopping polymerization is simple. The UV lamp is turned off, and the living radical becomes an inhibitor, dropping up the free radicals. Each discrete single polymer particle or nano-MIP has one binding site. We then wash away the unreacted monomers and lower-affinity polymers. By controlling the stringency of the wash process, we regulate the affinity of the nano-MIPs, which are subsequently harvested. We can further modify the surface of the nano-MIPs retained on the column by attaching other compounds of interest, such as biotin or peg. This allows us to create the best possible MIPs for application in a new world of diagnostic solutions. In [133], the authors observed that the sensitivity of the ammonia sensor developed using the MIP-doped boric acid method was 0.243 Hz/ppm, which is three times greater than that of a sensor developed without the MIP method (i.e., 0.079 Hz/ppm).  
In [134], carbohydrate antigen 15-3 (CA 15-3) was detected by employing the MIP strategy, and the following observations were made: (a) the redox peak current decreased with an increase in the value of the CA 15-3 concentration; (b) LOD was observed 0.10 U mL\({}^{-1}\); (c) the MIP biosensor detected the CA 15-3 associated with breast cancer below the clinically recognized value. In [131], the author considered the MIP method to observe the susceptible BRCA-1 gene associated with breast cancer and reported that the suggested biosensor maintained a wide linear range from 10 fM to 100 nM and had an LOD of 2.53 fM.