esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results  
### Technological Parameters  
The milk-clotting activity could only be assessed visually, as the r value could not be detected (higher than 30 min) either for BM-K or SM-K (Table 1).  
The first appearance of solid material after adding the kiwifruit extract was observed after 20-22 min and 15-17 min in buffalo and sheep milk, respectively. These times were significantly higher than the milk with rennet calf (Table 1).  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Buffalo**} & \multicolumn{4}{c}{**Sheep**} \\ \cline{2-9}  & **BM\({}_{\mathrm{C}}\)** & **BM\({}_{\mathrm{K}}\)** & **SEM** & **S** & **SM\({}_{\mathrm{C}}\)** & **SM\({}_{\mathrm{K}}\)** & **SEM** & **S** \\ \hline Yield (\%) & 51.25 & 33.18 & 2.82 & ** & 24.90 & 21.27 & 1.10 & * \\ Whey volume (mL) & 84.67 & 120.67 & 7.12 & ** & 130.83 & 143.83 & 1.77 & *** \\ Yield after 24 h (\%) & 38.95 & 27.85 & 1.71 & ** & 23.15 & 20.52 & 0.87 & * \\ Weight reduction (\%) & 23.78 & 15.18 & 1.83 & ** & 6.73 & 3.52 & 0.87 & * \\ pH whey 24 h & 5.23 & 5.16 & 0.14 & ns & 4.62 & 4.92 & 0.02 & ns \\ Clotting time (min) & 13.50 & 21.00 & 0.23 & *** & 11.50 & 16.50 & 0.22 & *** \\ r (min) & 10.96 & n.r. & 3.7 & ne & 7.38 & n.r. & 6.03 & ne \\ k20 (min) & 1.95 & n.r. & 0.41 & ne & 1.33 & n.r. & 1.66 & ne \\ a30 (mm) & 42.47 & n.r. & 6.20 & ne & 41.67 & n.r. & 2.86 & ne \\ \hline \hline \end{tabular} BMC, buffalo– calf rennet cheese; BMK, buffalo–kiwifruit cheese; SMC, sheep–calf rennet cheese; SMK, sheep–kiwifruit cheese; SEM, standard error medium; S, significance. *, 0.01 \(<\)\(P\)\(<\) 0.05; **, 0.01 \(<\)\(P\)\(<\) 0.001; ***, \(P\)\(<\) 0.001; ns: not significant; n.r., not reactive; ne: not estimable.  
\end{table}
Table 1: Technological parameters of the cheeses made with kiwi extract or calf rennet.  
The kind of coagulant was a significant variation factor with respect to whey volume, and to initial cheese yield (Table 1). These differences became smaller after 24 h (rennet cheese weight decreased more than the kiwi extract) but the cheese yield was still significant.
# Potentiality of Rod-Type Chitosan Adsorbent Derived from Sewage Sludge  
[PERSON]  
Department of Environmental and Energy Engineering, Yonsei University, 1 Yonseidae-gil, Wonju 26493, Republic of Korea Correspondence: [EMAIL_ADDRESS]; Tel.: +82-33-760-2435; Fax: +82-33-760-2571  
[PERSON]  
Department of Environmental and Energy Engineering, Yonsei University, 1 Yonseidae-gil, Wonju 26493, Republic of Korea Correspondence: [EMAIL_ADDRESS]; Tel.: +82-33-760-2435; Fax: +82-33-760-2571  
Munsik Park  
Department of Environmental and Energy Engineering, Yonsei University, 1 Yonseidae-gil, Wonju 26493, Republic of Korea Correspondence: [EMAIL_ADDRESS]; Tel.: +82-33-760-2435; Fax: +82-33-760-2571  
[PERSON]  
The potential use of wastewater sludge as a biosorbent for the removal of various metals and metalloids from aqueous solutions was investigated. The sludge was immobilized in a rod shape with chitosan to improve sorption capacity and solid-liquid separation ability. An optimal condition for the production of rod-shaped chitosan-immobilized sludge (RCS) was determined by considering the biosorbent production potential and As(V) removal efficiency. The optimal sludge and chitosan contents and RCS thickness were 6.0%, 4.0%, and 0.2-0.3 mm, respectively. The anion removal performance of RCS was investigated for As(V), Cr(VI), and Mn(VII), and the cation removal performance was investigated for Cd(II). Pseudo-first-order and pseudo-second-order models adequately explained the kinetic data for the RCS, while the Langmuir and Freundlich models explained the equilibrium data for the RCS. These results showed that RCS has a higher adsorption capacity for anions than for cations. The results also indicated that electrostatic attraction or ion exchange is the main mechanism for metal/metalloid removal by RCS, except for the case of Mn(VII) where an adsorption-coupled reduction mechanism may be suggested.  
sewage sludge; biosorption; chitosan; arsenic; mechanism
## Structure Design of the Wearable Upper Limb Rehabilitation Robot
### Elbow Joint Design  
The elbow joint is the most important joint connecting the upper arm and forearm. It is a main trochlear joint. The joint movement is realized by the relative movement of cartilage. The flexion and extension of the upper limb depend on the joint, including flexion/extension and internal rotation/external rotation of the forearm [29]. These two degrees of freedom in the human body when the upper limb completes the daily activities of the movement angle: elbow joint flexion/extension of the maximum angle range is \(135^{\circ}\), forearm internal rotation/external rotation is \(90^{\circ}\), the largest range of motion should be considered, the elbow joint mainly completes such as eating, holding things, touching the head and so on in people's daily life. If the elbow joint movement is restricted, it will be greatly restricted, and other joints, which will also have a greater impact for the patient's daily life. Therefore, the elbow joint plays an important role in the upper limb joint. However, when the current arm is fixed internal/external rotation, there is almost no internal/external rotation of shoulder joint [30]. Meanwhile, based on the redundancy of the freedom of the motion mechanism, the above analysis of the shoulder joint has already considered the internal/external rotation movement. To facilitate the control and the stability of the structure, it can be considered that the internal/external rotation of the forearm is fixed to move together, so that the internal/external rotation of the shoulder is designed to the maximum angle range of \(110^{\circ}\). As a result, the flexion/extension of elbow joint is equivalent to a single joint motion pair. The degree of freedom of elbow joint movement is shown in Figure 3a.  
Figure 2: The structure diagram of shoulder joint. (**a**) Three-dimensional (3D) model of shoulder joint; (**b**) 3D model of shoulder joint rotation degree of freedom.  
As illustrated in Figure 3, the elbow motion mechanism is constructed by two-way winding coil structure. It avoids the synchronization of double motor winding mechanism by two-way precise drive of the motor. The driven part of the elbow joint movement mechanism is mounted on the base, and the two-way driven plate of the motor transmits the power to the two-way wire plate of the elbow through the rope, thus, it completes the elbow flexion/extension motion. Since the elbow needs to bear a large torque and has excellent rotational accuracy, two crossed roller bearings are applied to the elbow joint. As a consequence, it increases the bearing capacity of the elbow mechanism, and reduces the radial error of the rotating shaft. The use of the silicone pad increases the wearing comfort and aesthetics of the device, which satisfies the requirements of the elbow movement when the human arm moves and also makes it more comfortable to wear.
# Network Slicing for Beyond 5G Systems: An Overview of the Smart Port Use Case
## 3 Enabling Technologies
### Software Defined Networking (SDN)  
The purpose of SDN is to replace the existing networking system with programmable services by separating the data plane and control plane (CP) [14]. It offers the flexibility, security, and less operating cost as compared to a traditional network. Due to the centralized architecture, it is easy to manage and run the operations across the larger network. The control plane is easy to configure, as it provides useful management functions. Controllers help to forward the packets in an SDN via APIs. A comparison of the existing network and SDN is shown in Figure 2. SDN is lean to undertake the traditional network issues by offering the centralized programmable services, which are well suited for the heterogeneous environment. The controller in SDN organizes the slicing of the network instance by using the protocols. It helps to create the client and server environment along with the installation of their concerned protocols as defined in the Open Network Foundation (ONF) SDN architecture [15]. SDN also offers the ability to promptly answer to the changing network environments and enterprise community.
# A Survey on Massive MIMO Systems in Presence of Channel and Hardware Impairments
## 4 Waveform Selection
### Studies on Multi-Carrier Waveforms  
In this subsection we will briefly study some of the works done on massive MIMO systems with multi-carrier waveform.  
In [22], uplink of OFDM massive MIMO systems has been considered. In this paper achievable rates of the system with MF, ZF, and MMSE detectors under perfect and imperfect channel state information have been derived. The results show that with perfect channel knowledge the users can reduce their transmit power by the number of BS antennas to have a rate similar to the SISO case.  
Figure 5: Block diagram of SC-FDP Massive MIMO system.  
Figure 6: Block diagram of single-carrier frequency domain processing (SC-FDMA) massive MIMO system.  
For imperfect channel knowledge case this reduction in power is by the square root of number of BS antennas. In [31], the power efficiency of OFDM massive MIMO system with power allocation and random distributed users has been computed in the uplink and downlink. In this paper a relation between optimum number of users and number of BS antennas and other system parameters was investigated. Also, to reduce the intercell and intracell interference a new detector and precoder called the full pilot zero forcing (P-ZF) was designed. In [32], the performance of OFDM massive MIMO system with MF and ZF precoder in the downlink was studied and lower bounds for the capacity were derived. The results indicate that at high SNRs, ZF precoder has better performance than MF precoder and at low SNRs it is the opposite. It is also concluded that ZF precoder is more suitable for high spectral efficiency and low power efficiency cases while MF precoder is more suitable for high power efficiency and low spectral efficiency cases. The authors of [33] studied the pilot contamination effect in OFDM massive MIMO downlink and proposed a precoder based on MMSE to reduce this interference. Also, some works addressed the problem of resource allocation in OFDM massive MIMO systems. For example, in [34] the authors have studied optimum power allocation and pilot assignment of users in uplink of OFDM massive MIMO system with MF precoder. Also, in [35] the optimum power allocation in the downlink to maximize the sum-rate was investigated. The results showed that as the number of BS antennas increases with respect to number of users, the gain achieved from power allocation strategies is decreased and equal power allocation will be the optimum.
## 4 Application of Fe-MOF in Advanced Oxidation Processes
### Catalytic AOP
However, for Fe(PIP) the ratio was similar, suggesting that the one-electron reduction of \(\equiv\)Fe\({}^{3+}\) regeneration to persulfate anion took places (Equation (8)). Their studies also confirmed the coexistence of other radicals generated by several of the reactions showed in Equations (9)-(16) that contributed in the SMX degradation. Based on the characterization and degradation studies, it was determined that the different behavior of the synthesized Fe-MOFs was due to the organic ligands used that were capable of regulating the amount of \(\equiv\)Fe\({}^{2+}\) active sites. \[\equiv Fe^{2+}+S_{2}O_{8}^{2-}\rightarrow\equiv Fe^{3+}+SO_{4}^{2-}+SO_{4}^{-\bullet} \tag{7}\]  
\[\equiv Fe^{3+}+S_{2}O_{8}^{2-}\rightarrow\equiv Fe^{2+}+S_{2}O_{8}^{-\bullet} \tag{8}\]  
\[\equiv Fe^{2+}+O_{2}\ \leftrightarrow\equiv Fe^{3+}+O_{2}^{-\bullet} \tag{9}\]  
\[O_{2}^{-\bullet}+H^{+}\leftrightarrow\ HO_{2}^{\bullet} \tag{10}\]  
Figure 7:0  
Figure 7:1  
Figure 7:2  
Figure 7:3  
Figure 7:4  
Figure 7:5  
During the reuse experiments, it was observed that ferric oxide layers were formed on the surface blocking the active sites that reduced the reactivity of these catalysts in successive cycles. Thus, for real applications of these catalysts in wastewater treatment, it is essential to solve the sustainability and self-decomposition problems associated with Fe-MOFs that allow them to operate in a flow system with high activation capacities. PBAs are a type of metal-containing coordination polymer that are considered a subset of the MOF and able to act as a catalyst in the PMS decomposition. [PERSON] et al. [164], combined Co\({}_{3}\)[Fe(CN)\({}_{6}\)]\({}_{2}\), and graphene oxide (GO) by a two-step hydrothermal procedure and obtained a Co-Fe PBAs@rGO nanocomposite. In contrast to the previous study with Fe-MOFs, in this case, in addition to the catalytic effect of anchored Fe, the capacity of Co was added, being responsible for the activation of PMS. It was demonstrated that GO reduced the aggregation of the nanoparticles GO doped with nitrogen increasing the stability of the catalyst. However, Co and Fe were released to the bulk solution (lower than 1 mg/L) to reduce the metallic content on the catalyst in successive cycles. In addition, the reduction in catalytic activity of this bimetallic MOF could be also due to the adsorption of reaction intermediates that were attached to the catalyst surface.
## 3 Results and Discussion
### Selection of Optimal Materials and Conditions for Sorbent Synthesis
#### 3.1.3 Assessment of Synthesis Temperature Influence  
The effect of synthesis temperature was assessed at the first and second stages of sorbent production--modification with potassium ferrocyanide and modification with a transition metal salt. The synthesis was carried out at room temperature (22-25 \({}^{\circ}\)C), as well as at 50 and 80 \({}^{\circ}\)C using an IR-1M3 rotary evaporator (LOIP, St. Petersburg, Russia).  
The effect of reaction mixture temperature on the sorption-active properties of the materials produced was assessed in different variations, in particular under the influence of temperature only at the first stage, only at the second stage, and also at both stages.  
It was found that synthesis temperature does not affect the sorption properties of the materials produced; the obtained cesium distribution coefficients differ within the error. The results obtained are shown in Supplementary Materials in Table S1.  
Further studies were carried out on sorbents that showed the best sorption characteristics--CoFeFC-PAN, CoMnFC-PAN, and FeMnFC-PAN.
## 1 Introduction
[28] introduced a miniaturized particle separation and detection system based on 3D printed virtual impactor (VI) and quartz crystal microsphere (QCM) sensor, but its measurement range was relatively small. [PERSON] et al. [29] studied the separation behavior of the original silicon in the high-silicon aluminum-silicon melt during directional solidification under alternating electromagnetic fields, at different frequencies and pulling speeds. [PERSON] et al. [30] used an electromagnetic cooperative oil-water separation experiment system to study the spatial distribution, electric field, and the sequence of magnetic field action on oil-water separation. There was little research on particle separation using electric or magnetic fields. In this paper, a particle separation detection method based on the composite electric field is proposed. After corona discharge, particles with different diameters are charged with different charges. Then, the atmospheric particles can be separated by using the idea that the particles with different charges have different trajectories under multiple field forces. Compared with the manual weighing method, \(\beta\)-ray attenuation method, and oscillation balance method, the operation is simple, less time-consuming, and does not need high environmental requirements. The composite electric field refers to the entire electric field in the separation room, which is distributed in three areas. Each area is composed of a different electric field. Under the action of multiple fields, the separation of atmospheric particles can be achieved. In this paper, the diameter of the particles, the electric field, and drag force are studied to discuss the effect on the separation of particles. It has been found that it is feasible to separate particles of different diameters by reducing the drag force and increasing the electric field intensity. This paper first establishes the dynamic model of particulate matter in the compound electric field, then numerically solves and analyzes the separation effect of particulate matter, and finally gives the conclusion that the proposed method, by reducing drag and increasing electric field intensity, is a viable separation method.
# Comparative Study on Vibration Characteristics of Biaxial Carbon/Glass Hybrid Wind Turbine Blades
## 4 Numerical Simulation
### Grid Independence Verification  
To ensure accurate structural field calculations of the wind turbine model, we adopted a multiregion grid partitioning method. By dividing the wind turbine model into multiple regions, details in the structural field can be better captured. At the same time, in order to improve the accuracy of the calculation, we have encrypted the grid to make it more dense. This can better simulate the structural characteristics of the wind turbine and ensure the accuracy of the calculation results. Figure 14 shows the division of the wind turbine structural field model.  
To verify the grid independence in the structural field, we conducted calculations under rated wind speed of 10 m/s and rated speed of 160 r/min. We used different numbers of structural field grids to calculate the equivalent stress and deformation of the blades. The validation results are shown in Table 6:  
Figure 14: Grid division of structural field.  
Figure 13: Blade simulation process.  
From Table 6, it can be seen that as the number of structural field grids increases, the values of equivalent stress and deformation gradually tends to stabilize. When the number of grids reaches 79,886, the values of equivalent stress and deformation basically do not change significantly. Therefore, we can conclude that for this specific working condition, using 79,886 structural field grids can obtain more accurate results, and further mesh refinement has little impact on the calculation results.
# Micro-Satellite Systems Design, Integration, and Flight
## 3 ChipSat RTOS and RF Development
### Ground Station
#### 3.5.2 Verifying Transmitting Using SDR Sharp  
To confirm that the RTL-SDR worked, it was tested to see if it could detect the transmissions sent by the TI launchpad. SDRSharp, which is SDR software v1.0.0.1784 developed by AIRSPY, was used for the test. AIRSPY connects to the RTL-SDR through the COM port and records signals within a specified range. SDRSharp can be downloaded from the AIRSPY website and configured with the RTL-SDR [38; 39]. After setting up SDRSharp with the RTL-SDR, the TI launchpad can be plugged in. The RTL should be able to receive the packages if they are transmitting. The packages can be seen as a visual representation at the top of the screen. Figure 24 shows how the AIRSPY dashboard looks when it receives the ChipSat transmissions at 915 MHz.  
Figure 24: AIRSPY dashboard identifies ChipSat transmissions at 915 MHz.
## 3 Results and Discussion
### Changes in Microbial Diversity during Fermentation
#### 3.1.2 Fungal Diversity
At the genus level, _Saccharomyces_ was highly abundant in both CK and CK-JASF, playing a crucial role in fermentation due to its capabilities in ethanol production and flavor enhancement. In contrast, genera such as _Tetradadium_ and _Pseudogymnascus_ were more prominent in CK but became less abundant in JASF, implying their involvement in the early stages of fermentation but reduced activity later. _Pichia_ and _Penicillium_ showed increased abundance in JASF, suggesting their importance in the later stages of fermentation. _Pichia_ is recognized for its ability to ferment a wide range of sugars and produce aromatic compounds, while _Penicillium_ can break down complex organic materials and potentially produce antimicrobial compounds that inhibit spoilage organisms. Other genera, such as _Cephalotrichum_, _Pleospora_, _Neecallimastix_, _Alternaria_, and _Tausonia_, contributed to the overall fungal diversity. _Cephalotrichum_ and _Pleospora_ may assist in plant material degradation, while _Neocallimastix_ is typically found in the r- or herbivores and specializes in degrading fibrous plant material; its detection in our samples may suggest contamination or a transient presence, and its role in the fermentation of Jerusalem aritchoke juice requires further investigation. _Alternaria_ and _Tausonia_ can produce various metabolites that may influence the flavor profile of the fermented juice [53; 54]. These results highlight the dynamic changes in fungal community composition during fermentation, influenced by pH and substrate availability. The CK-JASF overlap suggests shared metabolic activities, while the differences in CK and JASF reflect distinct microbial processes at different fermentation stages.
## 4 Experiments
### Experimental Setup and Evaluation Metrics  
We applied the proposed method (CAS-DA + filtering) in two different domain-shift scenarios: (1) adaptations between images collected by satellites and UAVs, including dataset B \(\rightarrow\) dataset C (B \(\rightarrow\) C), dataset C \(\rightarrow\) dataset B (C \(\rightarrow\) B), dataset A \(\rightarrow\) dataset C (A \(\rightarrow\) C), and dataset C \(\rightarrow\) dataset A (C \(\rightarrow\) A); (2) adaptations between images collected by different satellites, including dataset A \(\rightarrow\) dataset B (A \(\rightarrow\) B) and dataset B \(\rightarrow\) dataset A (B \(\rightarrow\) A). Note that s \(\rightarrow\) t above means adaptation from source domain to target domain.  
We implemented our method based on PyTorch [58] on Ubuntu 18.04 using a GeForce RTX 1080 Ti. Our backbone network was ResNet-101 pretrained with Image-Net [59]. The network was trained with the backpropagation algorithm. The initial learning rate was 0.001, and it was divided by 10 every 50k iterations. Each batch included one image from the source domain and one image from the target domain. Conventionally, all images were resized to 600 \(\times\) 600 after preprocessing. With this design, the feature maps from the three stages were resized to 38 \(\times\) 38 \(\times\) 1024 by the convolutional layer and pooling layer introduced in Section 3.2. For cascade RPNs, the threshold for an easy sample was set to 0.99 and \(\mu_{R}=\mu_{3}=1\). According to the size of tree crowns in our image, we defined the anchors to have a width of [64; 80] pixels and only assign a {1:1} aspect ratio considering that the shape of the tree crown was close to a square, which caused the number of anchor locations in an image (i.e., the length of a) to be fixed to 2888. For the loss function, we set the trade-off parameter \(\lambda=0.1\). Readers can refer to [40] for further details of the implementation of Strong Weak Faster R-CNN.  
In validation, only the images from the target domain were used. We set the maximum number of tree crowns in an image to 100 and used NMS as the postprocessing method before the proposed filtering strategy.  
We used true positive (TP), false positive (FP), false negative (FN), precision, recall, and F1-score as evaluation indicators. TP represents true positives, which is the number of crowns correctly detected. FP represents false negatives, referring to other objects mistaken for the crown. FN represents false negatives and denotes the number of crowns undetected. In our validation, the detecting results with a probability score over 0.5 and an IoU with the ground truth that was higher than 0.5 were considered to be TP. Precision indicates the proportion of correctly detected tree crowns in the detected tree crowns. Recall describes the proportion of correctly detected tree crowns in all ground-truth data. F1-score was introduced to balance these two indicators by computing their harmonic mean value.