esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Intervention
#### 2.5.1 Physical Therapy Group  
Each session for the control group lasted 30 min, and the treatment consisted of education, manual therapy, and therapeutic exercises.  
_Education:_ At the beginning of each session, a series of recommendations were provided to correct inappropriate behaviors such as parafunctions. This included explaining the correct resting position of the tongue and jaw, and proper breathing type to facilitate diaphragmatic function. Additionally, strategies to prevent the onset of symptoms such as avoiding hard foods, chewing gum, nail-biting, tongue or cheek biting, and teeth clenching were shared with the study participants [37].  
Manual Therapy: Divided into four sections:  
* Distraction of the TMJ [38]: The technique was applied bilaterally at Grade II intensity (Kaltenborn-Evjenth Concept) for 90 s, divided into three 30 s intervals with 15 s of rest between them.
* Mobilization of the Occipital-Atlas segment [39]: Dorsal sliding was performed at Grade III intensity (Kaltenborn-Evjenth Concept). The therapist stabilized the atlas with one hand and pushed the forehead with the shoulder. Four sustained mobilizations of 30 s each were performed with 15 s of rest between them.
* Mobilization of the Atlas-Axis segment [39]: The traction of the atlas over the axis was performed at Grade III intensity (Kaltenborn-Evjenth Concept). The therapist stabilized the axis with one hand and performed the traction of the atlas with the other hand. Four sustained mobilizations of 30 s each were performed with 15 s of rest between them.
* Manual Pressure [37; 38]: Bilateral pressure was applied to the masseter, temporalis, sternocleidomastoid, and upper trapezius muscles. As a pressure guide, when participants experienced a pain level of 7/10 on the VAS, this pressure was maintained. When the pain decreased to 3/10, the pressure increased until the pain returned to 7/10. This process was repeated for each muscle for a maximum of 60 s or less if relaxation was previously observed.  
Therapeutic Exercise: A total of 3 exercises were performed.  
* Opening and closing of the TMJ [37]: The controlled opening and closing exercises of the TMJ with the tongue in the resting position and in front of a mirror. Three sets of six repetitions were performed with 30 s of rest between each set.
* Isometrics [37]: Isometric exercises were performed in the opening, protrusion, and lateral excursion of the TMJ from a position close to the jaw's resting position. The subject maintained an isometric contraction for 10 s for each movement, and the process was repeated 3 times.
* Deep Cervical Muscle Training [40]: The deep cervical muscles were trained using StabilizerTM biofeedback, without contracting the superficial muscles (manual control of the sternocleidomastoid). The baseline pressure was 20 mmHg, and the patient had to perform craniocervical flexion to increase the pressure to 22 mmHg and maintain this position for 10 s. Five different pressure levels were applied: 22, 24, 26, 28, and 30 mmHg, and in each position, two repetitions of 10s were performed.
# Efficacy Improvement of Anomaly Detection by Using Intelligence Sharing Scheme
## 4 Proposed Architecture
### Proposed Algorithm
#### 4.2.5 Pairwise Optimization of Normalization Error
To alleviate this issue, we introduced a weighting parameter \(wh=\mid\{n\mid h\in H_{n}\}\mid\) (the number of networks that \(h\) is observed in) and used it to weight the error function:  
\[E=\sum_{h}\ \sum_{n}\ \sum_{m}\ \frac{1}{w_{h}}\cdot(q_{n,h}-q_{m,h})^{2} \tag{10}\]  
The resulting error function \(E=E\ (g\theta_{1},g\theta_{2},\ldots,g\theta_{\mid N\mid})\) contains only sums and multiplications of \(g\theta_{n}\), so it is differentiable with respect to \(g\theta_{n}\), and with respect to \(\theta_{n}\) whenever \(g\theta_{n}\) is differentiable, so it can in principle be optimized by a first-order iterative optimization algorithm. It should be noted that this error function may not be useful depending on the scale of the error function on parameters \(\theta_{n}\). For example, if we choose mean and scale parameters \(g_{un,un}(x)=\frac{x-un}{\sigma n}\), the optimal solution \(E=0\) would be for the degenerate case of \(\sigma n=0,\ n\in N\). In cases like this, a more involved error function or a limited domain of parameters would be necessary to get useful solutions. For simplicity, a shift normalization function \(g_{un}\ (x)=x-\ {un}\) was used that does not suffer from these problems. This simple normalization function should eliminate the biggest calibration errors and improve the ensemble classification. After substituting for \(q_{n,h}\) and using the shift normalization, the final normalization error function was obtained:  
\[E\ (u)=\sum_{h}\ \sum_{n}\sum_{m}\frac{1}{w_{h}}\left(f_{n\ (h)}-f_{m\ (h)}+u_{m}-u_{n}\ \right)^{2} \tag{11}\]  
After differentiating with respect to \(u_{n}\), the following equation was achieved:  
\[\frac{\partial E}{\partial u_{n}}=\sum_{h}\ \sum_{m}\frac{4}{w_{h}}\ \left(f_{m\ (h)}-f_{n\ (h)}+u_{n}-u_{m}\ \right) \tag{12}\]  
This gradient function can be used to minimize \(E\) by any first-order optimization method, such as gradient descend. Time Complexity  
In the worst-case scenario where all the hostnames \(H\) are present in all the networks \(N\), the gradient function \(\
abla E\) has \(\mid\!N\!\mid\) dimensions and \(\mid\!H\!\mid\cdot\!\mid\!N\!\mid\) summands. Combined with the number of iterations \(I\) required to get to the minimum, the time complexity \(t\) of our algorithm is:  
\[t\in O\ (|N|^{2}\cdot|H|\cdot I) \tag{13}\]  
The \(O\) notation reflects the fact that the complexity is linear to the number of hostnames and the number of iterations and quadratic to the number of networks in the ensemble. In practice, this complexity did not pose problems; for approx. 300 networks, 6.5 million unique hostnames and 50 iterations, optimization using gradient descent took approximately 2 min. In our case, the computation was not parallelized, so this solution is very scalable.
# Orbit Decomposition Method for Rotordynamic Coefficients Identification of Annular Seals
## 7 Limitations and Future Research Directions  
The proposed method is valid when the whirl amplitude is less than 20% of seal clearance. When the whirl amplitude is larger than 20% of seal clearance, the accuracy of the proposed method decreases. The whirl amplitude should be carefully decided.  
Additionally, only the widely used labyrinth seal is used as the research object in this article. In practice, many kinds of annular seals are applied, including the hole-pattern seal, honeycomb seal, and pocket damper seal. To further demonstrate the reliability and accuracy, the orbit decomposition method could be used to calculate the rotordynamic  
Figure 18: Comparison of rotordynamic coefficients with the measured data.  
coefficients of all kinds of annular seals. The prediction results could be compared with the experimental data.
## 4 Genome Editing for Autosomal Dominant Retinitis Pigmentosa
### Rho
Lastly, [PERSON] and colleagues conducted a proof-of-concept study delivering shRNA and wild type _RHO_ with nanoparticles to a knock-in _Rho_*/- mouse model and reported partial improvement of visual function [66]. Taken together, these studies showed moderate results. This may be explained by the fact that rhodopsin is an intensely active gene and it is challenging to reduce protein levels sufficiently by interfering at the mRNA level. Recently, [PERSON] and colleagues used an alternative approach, which consisted of mutation-independent _Rho_ ablation with the CRISPR/Cas9 system followed by gene supplementation. The authors tested this approach on two mouse models, one for the P23H mutation and one for the p.Asp190 Asn mutation, using a dual AAV2/8 vector system to vehicle the CRISPR/Cas system and the exogenous_RHO_ gene. Following ablation and replacement, ONL thickness was reported to be increased by up to 35% and accompanied by significantly improved ERG responses in both models, in contrast to gene supplementation alone [67]. Due to the partial success of these dual allele-independent gene therapy approaches, it is not surprising that many teams have taken advantage of the advent of CRISPR/Cas9 technology to explore allele-specific invalidation of _RHO_. [PERSON] and colleagues were the first to target an allele-specific PAM sequence present only in the _Rho5334_ mutant allele of an RP mouse model. Following subretinal administration and electroporation of the CRISPR/Cas components, the photoreceptor phenotype was rescued and visual acuity was increased by 53% [29]. Similarly, [PERSON] et al. targeted a _RHOP23H_ minigene expressed in a transgenic mouse model. They reduced expression of this mutant allele by subretinal electroporation of Cas9 and two gRNAs that targeted the 5' and the 3' regions of exon 1 [30]. More recently, [PERSON] et al., used a variant of SpCas9 called VQR, which recognizes a different PAM sequence than wild type SpCas9, to selectively target the mutant allele in a _Rho+P23H_ mouse model. Following delivery of the CRISPR/Cas system by AAV2/9 vectors, the degeneration of photoreceptors was slowed and visual function was improved [68]. Lastly, [PERSON] et al., reported discrimination between the human wild type and mutant allele in the Rho-P23H mice using an improved version of SpCas9-VQR, called VRQR, and truncated gRNAs. They report that 45% of the mutant protein was edited at the DNA level and that photoreceptor degeneration was significantly delayed [69]. Although all these studies are at initial stages, they provide promise for the gene therapy of _RHO_-associated adRP. As CRISPR/Cas9 technology continues to advance it is certain that more studies will take place with interesting results. The particularly high prevalence of the P23H mutation, notably in the US population, renders these studies highly pertinent clinically.
## 2 Materials and Methods
### Data Acquisition
The experimental system has multiple sensors with the ability to collect a total of \(11\) parameters, as follows:  
* The once value in the (1) \(X\) and (2) \(Y\)-axes (Kistler 9601A sensor; Impexron GmbH, Pfullingen, Germany);
* (3) acoustic emission (Kistler 8152B sensor; Kistler Group, Winterthur, Switzerland);
* (4) noise level (Bruel & Kjaer 4189 sensor; Bruel and Kjaer, Narum, Denmark);
* (5) vibration level (Kistler 5127B sensor; Kistler Group, Winterthur, Switzerland);
* (6) device-rated current (Finest HR 30 sensor; Micon Elektronika, Zagreb, Croatia);
* (7) device-rated voltage (Testec TT-Si9001 sensor; Testec, Dreieich, Germany);
* (8) head-rated current (Finest HR 30 sensor; Micon Elektronika, Zagreb, Croatia);
* (9) head-rated voltage (Testec TT-Si9001 sensor; Testec, Dreieich, Germany);
* (10) servo-rated current (Finest HR 30 sensor; Micon Elektronika, Zagreb, Croatia);
* (11) servo-rated voltage (Testec TT-Si9001 sensor; Testec, Dreieich, Germany). For the data acquisition part, two measurement cards were used. National Instruments PCI-6111 was used for acoustic emission, while the National Instruments PCI-6034E was utilized for other parameters. This setup ensures comprehensive and consistent analysis, and its efficiency was also confirmed during previous experiments [5]. For the data collection part, a PC with Lab ViewTM software was used. The software version from the National Instruments Corporation (Austin, TX, USA) was 2015 SP1. The composition of the dataset assembled during this phase is detailed in Table 1. A total of 75 samples were collected for the experiments, 25 for each of the represented classes. The number of samples was set at this level to make sure that each class would contain highly representative examples, outlining the signal characteristics for this specific label. Figure 3 illustrates sample raw signal plots for acoustic emission, \(X\)-axis force, \(Y\)-axis force, and noise levels. Figure 3: Illustrative examples of raw signal data for (**a**) acoustic emission, (**b**) \(X\)-axis force, (**c**) \(Y\)-axis force, and (**d**) noise levels.
## 1 Introduction
However, there is limited research on the effects of the processing conditions of this method on the synthesis of millimeter-sized spherical porous ceramic supports [11]. Therefore, it is important to explore applications of comparable examples of this route in the synthesis of alternative spherical porous ceramic supports and study their resultant properties. Porous ceramic supports with hierarchical pore systems (macro-, meso-, and/or micro-pores) within their solid networks have garnered increasing interest due to the combined structural stability and functionality offered by these features [2; 5]. Diatomite, also known as diatomaceous earth, is a lightweight fine-grained biogenic sediment with a unique set of properties that has gained attention in both the industrial and academic fields as a suitable raw material for certain applications, including filters, absorbers, catalytic supports, and fillers [36; 37]. Diatomite is derived from the frustules of diatoms, which are fossilized unicellular algae or microscopic plants. These frustules primarily consist of amorphous hydrated silica (SiO\({}_{2}\).nH\({}_{2}\)O), which is categorized as a non-crystalline opal-A [36; 38]. With dimensions in the range of 1-100 \(\upmu\)m (usually \(>\)10 \(\upmu\)m, depending on the species), diatomite frrustules display distinctive bimodal meso/macproposivity [38; 39], which influences the specific surface area and facilitates efficient mass-transport and diffusion processes [38]. Additionally, diatomite exhibits strong acid resistance, thermal stability, low-thermal conductivity, and high-mechanical strength, making it highly desirable for the aforementioned applications [36; 38]. Moreover, diatomite is an inexpensive, easily available, and abundant form of silica [36; 37]. To the best of the authors' knowledge, no previous report has focused on the preparation and optimization of millimeter-sized spherical porous diatomite supports (hereafter referred as porous diatomic granules) based on the \"integrated gelling\" approach [29]. Additionally, there is a lack of research on the effects of heat-treatment conditions on the pore and mechanical characteristics of these granules. Therefore, this study aims to propose the preparation of an alternative porous ceramic carrier, with potential applicability as a catalytic support using a low-cost and abundant raw material along with a processing route that involves non-toxic reactants. Specifically, the suggested method entails the use of diatomite/sodium alginate dispersions and the gelling of sodium alginate by cross-linking with Ca\({}^{2+}\) cations as the gelling agent (physical cross-linking) [30].
# Sensor Fusion Architecture for Fault Diagnosis with a Predefined-Time Observer
## 3 Case Study
### Prototype  
Our prototype, depicted in Figure 3, is a three-wheeled omnidirectional mobile robot. It has three omnidirectional wheels driven by EC 22 brushless Maxon motors connected to gearbox reducers with a ratio of 109:1. Each motor shaft speed and rotational direction is controlled by the Maxon DECS 50/5 driver. As a computational unit, the 32-bit Experimenter Kit Delfino F28335 Texas Instruments microcontroller is used.  
The position and orientation of the mobile robot are measured by a Marvelmind Starter set HW 4.9 indoor GPS system, while every motor shaft velocity is obtained by Maxon encoders with a resolution of 512 counts per turn. The sensors have a frequency of 100 Hz and the sensors' data are collected with a sampling time of 0.025 s.
###### Abstract  
The unpredictable increase in electrical demand affects the quality of the energy throughout the network. A solution to the problem is the increase of distributed generation units, which burn fossil fuels. While this is an immediate solution to the problem, the ecosystem is affected by the emission of CO\({}_{2}\). A promising solution is the integration of Distributed Renewable Energy Sources (DRES) with the conventional electrical system, thus introducing the concept of Smart Microgrids (SMG). These SMGs require a safe, reliable and technically planned two-way communication system. This paper presents a heuristic based on planning capable of providing a bidirectional communication that is near optimal. The model follows the structure of a hybrid Fiber-Wireless (FiWi) network with the purpose of obtaining information of electrical parameters that help us to manage the use of energy by integrating conventional electrical system with SMG. The optimization model is based on clustering techniques, through the construction of balanced conglomerates. The method is used for the development of the clusters along with the Nearest-Neighbor Spanning Tree algorithm (N-NST). Additionally, the Optimal Delay Balancing (ODB) model will be used to minimize the end to end delay of each grouping. In addition, the heuristic observes real design parameters such as: capacity and coverage. Using the Dijkstra algorithm, the routes are built following the shortest path. Therefore, this paper presents a heuristic able to plan the deployment of Smart Meters (SMs) through a tree-like hierarchical topology for the integration of SMG at the lowest cost.  
optimization; smart metering; IoT; microgrid; heuristic; sensor networks +
Footnote †: journal: Sensors
# Brain-Like Navigation Scheme based on MEMS-INS and Place Recognition
###### Abstract  
Animals have certain cognitive competence about the environment so they can correct their navigation errors. Inspired by the excellent navigational behavior of animals, this paper proposes a brain-like navigation scheme to improve the accuracy and intelligence of Micro-Electro-Mechanical System based Inertial Navigation Systems (MEMS-INS). The proposed scheme employs vision to acquire external perception information as an absolute reference to correct the position errors of INS, which is established by analyzing the navigation and error correction mechanism of rat brains. In addition, to improve the place matching speed and precision of the system for visual scene recognition, this paper presents a novel place recognition algorithm that combines image scanline intensity (SI) and grid-based motion statistics (GMS) together which is named the SI-GMS algorithm. The proposed SI-GMS algorithm can effectively reduce the influence of uncertain environment factors on the recognition results, such as pedestrians and vehicles. It solves the problem that the matching result will occasionally go wrong when simply using the scanline intensity (SI) algorithm, or the slow matching speed when simply using grid-based motion statistics (GMS) algorithm. Finally, an outdoor Unmanned Aerial Vehicle (UAV) flight test is carried out. Based on the reference information from the high-precision GPS device, the results illustrate the effectiveness of the scheme in error correction of INS and the algorithm in place recognition.  
Keywords:inertial navigation system; visual navigation; place recognition; image matching +
Footnote †: journal: Applied
# Rapid Planning of an Assembly Path by Reusing the Prior Path
## 2 Establishment of Prior Path Space  
### Segmentation of the Assembly Path  
The assembly paths of different parts in a complex product are varied; thus, it is difficult to reuse an assembly path completely. A feasible method is to segment the assembly path and then reuse it [52]. Based on a method of segmenting the assembly path into two phases, the assembly path of a part is divided into three phases in turn by four key positions of the part from the shelf to assembly in this paper, as shown in Figure 1. The four positions are the initial point, the start point, the end point, and the target point, and the three phases are the handling phase, the logistics phase, and the assembly phase.  
In the handling phase, the part is transferred from the initial point (the position where the part is stored on the shelf) to the start point (the position where the part is waiting to be transported near the shelf). In the logistics phase, the part is transported from the start point to the end point (the position where the part is waiting to be assembled near the assembly), bypassing various obstacles. In the assembly phase, the part is transferred from the end point to the target point (the final position where the part is assembled) after position-posture transformation.  
Since the initial point, the start point, and the target point of each part are typically different, it is difficult to plan the handling phase and the assembly phase of a new assembly path by reusing the corresponding phases of other planned paths.  
However, in the logistics phase, all the parts can be moved to the same position before assembly, which means that their end points are the same. Two assembly paths with the same end point may coincide within a certain range even if their start points are different, which makes the reuse of the logistics phase of planned paths possible. Therefore, the path reuse in this paper focuses on the logistics phase.
## 3 Results
### Growth Inhibitory Effect of VPA on HDFs  
The cellular toxicity of VPA was measured by observing the morphological changes in the HDFs (Figure 2a). HDFs have a large, flat, and elongated shape and are characterized by processes extending out from the ends of the cell body giving bipolar or multipolar morphology. No apparent morphological differences were observed when VPA was treated in the 0-2 mM range. However, when the concentration of VPA was increased to 4 mM, a longer cellular body and thinner sprouting were observed. Nevertheless, no observable cell death was seen at high concentration, which indicates that VPA is not cytotoxic but it may be a growth inhibitor.  
In addition, the cellular toxicity of VPA was measured on HDFs using MTT assay (Figure 2b). No significant decrease in the cell viability was observed after 24 h exposure with VPA in the 0-4 mM range (Figure 2b, left panel). A slight decrease in the MTT reduction was observed after 48 h exposure with VPA at 4 mM (Figure 2b, middle panel). Similarly, as the exposure time period was increased to 72 h, a decrease in the cell viability was observed in all concentrations (1, 2, and 4 mM VPA), indicating the time-dependent growth inhibitory property of VPA (Figure 2b, right panel). As 4 mM VPA resulted in high growth inhibition, we then continued the experiments with less than 2 mM VPA. It was noticeable that with prolonged exposure to VPA, the growth inhibition of the fibroblasts went from 80% on day 3 down to 40% on day 16 (Figure 2b,c).