esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experimentation and Results
### YOLOv5 Object Detection Performance  
YOLOv5 Parameters  
* Confidence Threshold:  
This parameter controls the minimum confidence required for a detection to be considered valid. We found that lowering the confidence threshold from 0.5 to 0.3 improved recall but decreased accuracy, resulting in more false positives. On the other hand, raising the threshold increased accuracy but decreased recall due to missed detections. After testing, we determined that a confidence level of 0.45 provided the optimal trade-off between recall and accuracy.
* IoU (Intersection over Union) Threshold:  
The IoU threshold determines the overlap between the predicted and actual bounding boxes needed for a detection to be accurate. While a higher IoU threshold (e.g., 0.7) improved localization accuracy, it also increased the likelihood of false negatives in scenarios with overlapping items. A lower threshold (0.5) resulted in more detections and inaccurate localizations. To balance these trade-offs, we selected an IoU threshold of 0.55.  
Table 14 summarizes the performance metrics for the YOLOv5 object detection model. The key metrics include precision, recall, F1-score, and average detection time per frame. The model demonstrates high precision and recall, indicating its accuracy and reliability in detecting objects. The F1-score of 87.79% reflects a balanced performance between precision and recall. The average detection time per frame of 0.050 s displays the model's efficiency in processing frames quickly, making it suitable for real-time applications.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Metric** & **YOLOv5 + DeepSORT** & **Traditional Methods** & **Faster R-CNN** & **SSD** \\ \hline Average Detection Time & 0.050 s & 0.090 s & 0.120 s & 0.110 s \\ Tracking Time per Frame & 0.040 s & 0.080 s & N/A & N/A \\ Real-Time Processing & 25 fps & 15 fps & 10 fps & 12 fps \\ \hline \hline \end{tabular}
\end{table}
Table 13: Summary of the computation times.  
In Figure 16, we show the YOLOv5 model's graphic performance over various criteria, accentuating how well it contains our object identification task, which gives primacy to accuracy, recall, and handling pace.
###### Abstract  
(1) Background: Intrinsic characteristics of the implant surface and the possible presence of endotoxins may affect the bone-implant interface and cause an inflammatory response. This study aims to evaluate the possible inflammatory response induced in vitro in macrophages in contact with five different commercially available dental implants. (2) Methods: one zirconia implant NobelPeart(r) (Nobel Biccare) and four titanium implants, Syra(r) (Sweden & Martina), Frama(r) (Sweden & Martina), 3 iT3(r) (Biomet 3i) and Shard(r) (Mech & Human), were evaluated. After 4 h of contact of murine macrophage cells J774a.1 with the implants, the total RNA was extracted, transcribed to cDNA and the gene expression of the macrophages was evaluated by quantitative PCR (qPCR) in relation to the following genes: GAPDH, YVHAZ, IL1, IL6, TNF\(\alpha\), NOS2, MMP-9, MMP-8 and TIMP3. The results were statistically analyzed and compared with negative controls. (3) Results: No implant triggered a significant inflammatory response in macrophages, although 3 iT3 exhibited a slight inflammatory effect compared to other samples. (4) Conclusions: All the samples showed optimal outcomes without any inflammatory stimulus on the examined macrophage cells.  
dental implants; biomaterials; implant surface; endotoxins; osteoimmunology; inflammatory response +
Footnote †: journal: Applied Sciences
# Relay-Enabled Task Offloading Management for Wireless Body Area Networks
## 1 Introduction
The offloading decision model is given along with the numerous QoS constraints. To balance the energy consumption of all relays, a resource management scheme is investigated considering the computation task, computation capacity, and the energy status of the relays. The results show that the offloading strategy-based solution outperforms the non-offloading enhanced scheme regarding energy consumption, path loss (PL), and the total number of locally executed packets. Also, the tradeoff between different computation capacities and the related QoS metrics regarding the task offload technique are presented in detail. The rest of the paper is organized as follows. Section 2 summarizes the recent work in this research area. Section 3 illustrates the proposed system regarding the structure of the C-MEC, channel models, and task offloading model. The proposed communication for the offloading-based transmission scheme is given in Section 4, and Section 5 demonstrates the system performance and comparison with our previous work. Finally, Section 6 concludes the paper and lists a collection of on-going research and future work within wireless body area network (WBAN) techniques, which are presented as motivation towards progress in medical monitoring services.
## 1 Introduction
Surface acoustic wave (SAW), bulk acoustic wave (BAW), and FPW (flexural plate wave) acoustic modes can be generated and detected by piezoelectric actuators driven at suitable frequencies to obtain wavelengths in the order of up to 100 \(\upmu\)m [13,14]. The forces generated by the interaction between acoustic waves and fluids can be used to actuate fluids and suspended particles, such as cells, at a small scale with micrometric resolution. Additionally, piezoelectric devices have the inherent advantage of allowing contactless operation between the transducer and the electronics [15]. Custom-built microfluidic perfusion bioreactors with integrated ultrasound standing wave traps have been proposed for cartilage tissue engineering [16]. In such devices, acoustic waves and continuous perfusion of the culture medium at a low-shear flow rate promote scaffold-free generation of 3D agglomerates of human articular chondrocytes and enhance cartilage formation by cells of the agglomerates via improved mechanical stimulation and mass transfer rates. A versatile SAW technique has been proposed to control the distance between two isolated cells, to drive the clustering of single cells in defined geometries, by maintaining them in suspension, and transferring them to their adherent state [17]. The typical configuration of the microfluidic devices used for fluid and particle manipulations exploiting SAWs or FPWs requires piezoelectric substrates with interdigital transducers (IDTs) to realize the actuators [18, 19, 20, 21, 22]. In this study, the use of screen-printed piezoelectric films for the generation of the FPWs on alumina substrate was explored to assemble 1D cellular structures. The aim was to demonstrate that arrangements of living human cells can be advantageously obtained by acoustic waves with actuators on generic non-piezoelectric substrates, thereby including transparent substrates typically adopted for the fabrication of microfluidic devices. This is advantageous compared to similar devices, both those based on FPWs and those based on SAWs, because non-piezoelectric substrates ease the patterning of IDTs in different positions without the need to consider the crystallographic orientations. Thus, by adding one or more pairs of IDTs, in principle it could be possible to obtain 2D-cellular structures. From a biological point of view, the use of the proposed device enables the formation of ordered cellular structures that can be merged into an engineered tissue.
###### Abstract  
The dynamics of semiconductor lasers with optical feedback and current modulation has been extensively studied, and it is, by now, well known that the interplay of modulation and feedback can produce a rich variety of nonlinear phenomena. Near threshold, in the so-called low frequency fluctuations regime, the intensity emitted by the laser, without modulation, exhibits feedback-induced spikes, which occur at irregular times. When the laser current is sinusoidally modulated, under appropriate conditions, the spikes lock to the modulation and become periodic. In previous works, we studied experimentally the locked behavior and found sub-harmonic locking (regular spike timing such that a spike is emitted every two or three modulation cycles), but we did not find spikes with regular timing, emitted every modulation cycle. To understand why 1:1 regular locking was not observed, here, we perform simulations of the well-known Lang-Kobayashi model. We find a good qualitative agreement with the experiments: with small modulation amplitudes, we find wide parameter regions in which the spikes are sub-harmonically locked to the modulation, while 1:1 locking occurs at much higher modulation amplitudes.  
semiconductor lasers; diode lasers; optical feedback; modulation; locking; laser dynamics; nonlinear dynamics Article]Locking Phenomena in Semiconductor Lasers Near Threshold with Optical Feedback and Sinusoidal Current Modulation  
1  
T.-A.-L.J.-.M.C.L.  
regular subharmonically locked spikes: rigid in the sense that the locked behavior persists in a parameter region, and regular in the sense that the spike timing is regular over very long time intervals [21]. However, we did not find rigid and regular harmonic locking. In this paper, we aim to shed light into the elusiveness of the regular 1:1 locked spikes.  
This paper is organized as follows. In Section 2, we present the model used to simulate the dynamics of the laser. In Section 3, we present the results of the simulations, and in Section 4, we present the discussion and the conclusions.
## 3 Viscoelastic Parameter Prediction of the Multi-Layered CGS  
### Measuring Viscoelastic Parameters of the Sand-Clay Matrix  
According to the Code for Design on Subgrade of Railway in China, TB10001-2005 [39], three different mass ratios of sand to clay (Table 1) were selected and uniformly mixed for preparation of the cylindric specimens (\(\Phi\) 300 mm \(\times\) 600 mm) by layered compacting method (Figure 5). Triaxial creep tests were conducted by TAJ-2000 triaxial testing system (Figure 6), where the axial stress \(\sigma_{1}\) was 300 kPa and confining pressure \(\sigma_{3}\) was 200 kPa (\(\sigma_{3}<\sigma_{1}\)).  
Figure 7 shows the tested creep curves of different sand-clay matrices. They are all composed of three stages: instantaneous deformation (\(t=0\)) stage, attenuation deformation stage (slope is decreased) and stable creep deformation stage (slope is constant). The higher the clay content, the larger the instantaneous deformation and the longer the duration time of the attenuation deformation stage. The clay content has a smaller effect on the stable creep deformation rate, since the elastic properties of the sand-clay matrices are mainly decided by the sand content and the viscous properties by clay content, that is, the viscous properties will play a dominant role as time continues, especially after the attenuation deformation stage, so the creep curves have an almost identical slope on stable creep deformation for viscosity of clay.  
Burgers rheological model is usually adopted to describe the creep curve as Equation (18):  
\[J_{m}=\frac{1}{E_{1}}+\frac{t}{\eta_{1}}-\frac{1-e^{-\frac{tE_{2}}{\eta_{2}}}}{ E_{2}} \tag{18}\]  
where \(J_{m}\) is the parameter of [PERSON] model, \(E_{1}\) and \(E_{2}\) are elastic parameters, \(\eta_{1}\) and \(\eta_{2}\) are the viscosity parameters, \(t\) is time.  
Table 2 lists the fitting viscoelastic parameters of different sand-clay matrices by the [PERSON] rheological model with high precision (\(R^{2}>0.98\)). They are all decreased as the clay content increases, indicating that the viscoelastic properties of the sand-clay matrices mainly depend on the clay contents.  
Figure 6: TAJ-2000 triaxial testing system.  
Figure 7: Fitted curves and test values of different sand–clay matrices.
# Fuzzy Preference Programming Framework for Functional Assessment of Subway Networks
## 3 Methodology and Implementation
### Failure Impacts Module
#### 3.1.2 Model Testing  
The local and global weights presented in Table 2 and illustrated graphically in Figure 3 were tested using expert judgment. Accordingly, the model was presented and approved by the Transportation agency personnel in charge of the network's risk assessment. They verified the model output was legitimate and adequately conveys the network studied.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Main Criteria** & **Global Weight** & **Attributes** & **Global Weight** & **Local Weight** \\ \hline \multirow{2}{*}{Financial Impacts} & \multirow{2}{*}{27.65\%} & F1:Revenue Loss & 14.96\% & 54.12\% \\ \cline{3-5}  & & F2: Replacement/repair cost & 12.68\% & 45.87\% \\ \hline \multirow{3}{*}{Social Impacts} & \multirow{3}{*}{38.21\%} & S1: Service continuation & 12.95\% & 33.90\% \\ \cline{3-5}  & & S2: Interruption rate & 10.22\% & 26.73\% \\ \cline{3-5}  & & S3: User traffic frequency & 15.04\% & 39.36\% \\ \hline \multirow{2}{*}{Operational Impacts} & \multirow{2}{*}{34.14\%} & O1: Ease of Providing Alt. & 15.69\% & 45.96\% \\ \cline{3-5}  & & O2: Time to repair & 18.45\% & 54.04\% \\ \hline \hline \end{tabular}
\end{table}
Table 2: Local and Global Weights of Failure impacts Module.  
Figure 3: Failure impacts attributes Global Weights.  
Figure 2: Failure impacts Calculation Sheet.  
The social impacts of failure had the highest importance, with a value of 38%, followed by operational impacts at 34%, and lastly, financial impacts at 27.65%. These values conform to the current approach followed by the transportation agency for the network under study, where stations with higher effect on customers acquire a higher priority for rehabilitation to ensure customer satisfaction. Moreover, the membership functions implications provided by experts stated that financial impacts are usually covered by operational costs for moderate and low consequence of failure.  
Attributes and criteria weights are shown graphically in Figures 3 and 4, time to repair had the highest global weight of 18.45%. This is understandable since time to repair has direct impact on revenue loss, interruption rate, and the user traffic frequency. Ease of providing alternative and user traffic frequency came next with close global weight values of 15.69% and 15.04%, respectively. Both sub-attributes are seen as interrelated, since a decent alternative ensures customers are minimally affected by the service interruption. Revenue loss has a global weight of 14.96%, based on experts' feedback; operational costs are usually used to cover moderate to low financial impacts of failure, and this explains the somehow moderate global weight of the revenue loss. Replacement/repair cost and service continuation are next, with close global weights, followed by interruption rate having the least weight of 10.22%.
# Shunt Damping Vibration Control Technology: A Review
## 3 Passive Shunt
### Multimodal Vibration Control
In this way, the circuit is decoupled so that each damping network \(L_{i}-R_{i}\) can be tuned individually to a target resonance frequency. \(L_{i}\) can be calculated according to (22), and \(\hat{L}_{i}\) (23). The series-parallel shunt offers no great advantage over comparable techniques. Benefits arise from a suitable choice in the arbitrary capacitances \(C_{i}\). The recommended capacitance value is 10-20 times that of the piezoelectric capacitance. In this case, the current blocking inductors become significantly smaller than the damping inductors. When the circuit is simplified by combining current-blocking inductors in each series network, the resulting single inductor is a fraction of that required in other single- or multi-mode circuits. It should be noted that there is another piezoelectric transducer with shaped electrodes that has attracted attention. Modal control and spatial filtering technologies can filter out undesirable and uncontrollable modes over the bandwidth to increase the robustness and stability of the controlled structural system. The idea provides a novel approach to design a resonant shunt. [PERSON] [93] employed shaped electrodes to develop a two-layered RL shunted piezo smart Euler-Bernoulli beam. The results demonstrated that the capacitance for the modal case is mode dependent and is always lower than that for uniform electrodes. As a consequence, the optimal resistor and inductance values are higher than those needed for the uniform electrode cases, which is a shortcoming of the modal approach. In summary, the passive shunts mainly utilized a resonant circuit to construct an electrical absorber to reduce the structural vibration. Either PSD or EMSD used fixed points theory to optimize the parameters of the shunt, such as the inductance, the capacitance, and the resistance. All of them are efficient and capable of suppressing the target mode vibration of a flexible structure. However, problems arise when the lower resonant frequencies of a flexible structure are too small. In this case the optimal inductance [90] or capacitance will have a bigger value and make it impossible to implement. On the other hand, there is a common drawback for a resonant type shunt circuit: the structural natural frequencies shifts as there is a stiffness variation, which will evitable make the shunt circuit detune either the single mode or a multimode. Therefore, active shunts are essential to compensate for these uncertainties.
## 2 System Model and Problem Formulation
### Channel Model  
Due to the special maritime propagation, we adopted the model of the air-to-ground channel and the two-ray path loss model [27]. More specifically, the probability of the LoS link is expressed as \(P_{u,j,k}^{\text{LoS}}=\frac{1}{1+a\exp(-b\left(\psi_{u,k}-a\right))}\), where \(a\) and \(b\) are two constant values depending on the environment. \(\psi_{u,j,k}\) denotes the elevation angle of the buoy-UAV and UAV-OBS, which is given by \(\psi_{u,i,k}=\frac{180^{\circ}}{\pi}\times\arcsin\left(\frac{H}{\sqrt{\left(x _{u,k}-x_{i}\right)^{2}+\left(y_{u,k}-y_{i}\right)^{2}}}\right)\).  
The average path loss of the buoy-UAV and UAV-OBS links is figured out according to the probability of establishing the LoS, which can be expressed as  
\[L_{u,i,k}=P_{u,j,k}^{\text{LoS}}L_{u,j,k}^{\text{LoS}}+\left(1-P_{u,j,k}^{ \text{LoS}}\right)L_{u,j,k}^{\text{NLoS}},\forall u\in\mathcal{U},i\in \mathcal{I},k\in\mathcal{K} \tag{4}\]  
where \(L_{u,j,k}^{\text{LoS}}\) and \(L_{u,j,k}^{\text{NLoS}}\) are the average path loss of the LoS and NLoS, respectively, which can be given by  
\[L_{u,j,k}^{\text{LoS}}=\left(\frac{4\pi d_{u,j,k}}{\lambda}\right)^{v^{\text {LoS}}}\mu_{u,j,k}\xi_{\text{LoS}}, \tag{5}\]  
\[L_{u,j,k}^{\text{NLoS}}=\left(\frac{4\pi d_{u,j,k}}{\lambda}\right)^{v^{\text {NLoS}}}\mu_{u,j,k}\xi_{\text{NLoS}}, \tag{6}\]  
where \(\mu_{i,k}=1\), \(\lambda\) is the wavelength, \(\xi_{\text{LoS}}\) and \(\xi_{\text{NLoS}}\) are the excessive path loss for the LoS and NLoS paths, respectively, and \(v^{\text{LoS}}\) and \(v^{\text{NLoS}}\) are the LoS and NLoS link factors, respectively.  
According to the above discussions, the channel gain of the buoy-UAV and UAV-OBS links can be expressed as  
\[h_{u,j,k}=1/L_{u,j,k}.\forall u\in\mathcal{U},i\in\mathcal{I},k\in\mathcal{K} \tag{7}\]  
The signal-to-noise-ratio (SNR) of the buoy-UAV and UAV-OBS at time slot \(k\) is given by  
\[g_{u,j,k}=\frac{P_{u,j,k}h_{u,j,k}}{\sigma^{2}},\forall u\in\mathcal{U},i\in \mathcal{I},k\in\mathcal{K} \tag{8}\]  
where \(\sigma^{2}\) is the Gaussian noise power and \(P_{u,m,k},\forall m\in\mathcal{M}\) and \(P_{u,0,k}\) are the transmit power of buoy \(m\) and UAV \(u\) at time slot \(k\), respectively. Moreover, \(0\leq P_{u,m,k}\leq P_{\max}\), and \(P_{u,0,k}\) is a constant.
###### Abstract  
Heavy atom nanoparticles, such as gold nanoparticles, are proven effective radiosensitizers in radiotherapy to enhance the dose delivery for cancer treatment. This study investigated the effectiveness of cancer cell killing, involving gold nanoparticle in proton radiation, by changing the nanoparticle size, proton beam energy, and distance between the nanoparticle and DNA. Monte Carlo (MC) simulation (Geant4-DNA code) was used to determine the dose enhancement in terms of dose enhancement ratio (DER), when a gold nanoparticle is present with the DNA. With varying nanoparticle size (radius = 15-50 nm), distance between the gold nanoparticle and DNA (30-130 nm), as well as proton beam energy (0.5-25 MeV) based on the simulation model, our results showed that the DER value increases with a decrease of distance between the gold nanoparticle and DNA and a decrease of proton beam energy. The maximum DER (1.83) is achieved with a 25 nm-radius gold nanoparticle, irradiated by a 0.5 MeV proton beam and 30 nm away from the DNA.  
radiosensitizer; DNA dosimetry; gold nanoparticles; cancer therapy; dose enhancement; Monte Carlo simulation; nanoparticle-enhanced radiotherapy
## 2 Dataset Description
### Satellite Data and in situ Measurements
#### 2.2.3 Experimental Measurements  
In general, the _in situ_ measurements were collected simultaneously with the SAR acquisitions to characterize the soil and vegetation variability (Table 1). Seven to ten training plots were sampled (see the locations in Figure 1). The dimension of sampled plot ranges between 2.13 ha and 7.23 ha.
## 4 Conclusions  
In conclusion, we have demonstrated a continuous-wave single-frequency mid-infrared MgO:PPLN OPO pumped by a continuous-wave single-frequency Nd:YVO\({}_{4}\) laser at 1064 nm. The symmetrical design of the system can easily achieve mode-matching. We used an uncoated 0.5-mm-thick YAG etalon to enhance the single-frequency operation of the MgO:PPLN OPO. With the etalon in the cavity, the OPO produced a single-frequency output of 1.1 W at 3.68 \(\upmu\)m. By using different grating periods and adjusting the nonlinear crystal temperature between 20 \({}^{\circ}\)C and 200 \({}^{\circ}\)C, the idler wavelength of the OPO can be continuously tuned in the range of 2.9-4.1 \(\upmu\)m.  
[PERSON], [PERSON], and [PERSON] conceived and designed the experiment; [PERSON] and [PERSON] performed the experiment; [PERSON] and [PERSON] supervised the entire work; [PERSON] and [PERSON] wrote the paper.  
This work was supported by the Fundamental Research Funds for the Central Universities (2016B02014, 2016B12114, and 2016B01914), National Natural Science Foundation of China (NSFC) (61378027, 61301199), and A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.  
The authors thank [PERSON] for providing technical support.  
The authors declare no conflict of interest.  
Figure 5: Output power of the 3.68 \(\upmu\)m idler versus incident pump power.  
Figure 6: Theoretical tuning curves for eight periods of the MgO:PPLN crystal.