esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Results and Discussion
### TGF-\(\beta\) Inhibition Assessments of the Isolated Compounds  
Liver fibrosis is the result of a chronic wound-repairing response after injury [37]. While injured by viruses, toxins, or cholestasis, the quiescent hepatic stellate cells (HSCs) are targeted by profibrogenic cytokines TGF-\(\beta\) and activated as myofibblasts to produce fibrotic-related marker collagen type I, fibronectin (FN), N-cadherin (N-cad), and \(\alpha\)-smooth muscle actin [38]. The hepatoprotective activity against the hepatic fibrosis of the isolated compounds was evaluated in TGF-\(\beta\)-induced LX-2 HSCs by Western blot. The results showed that compounds **1**, **5**, **9**, and **11** inhibited the TGF-\(\beta\)-induced Smad3 phosphorylation at 25 \(\upmu\)M in LX-2 cells (Figure S89). Compounds **1** and **5** were then chosen for the further analysis of their effects on the TGF signaling pathway at different concentrations, using SB-431542 (a TGF-\(\beta\) inhibitor) as a positive control. Compound **5** showed significant inhibitory effects on the TGF-\(\beta\)-induced Smad3 phosphorylation at 12.5, 25, and 50 \(\upmu\)M, while a weaker inhibitory effect of **1** on the TGF-\(\beta\)-induced Smad3 phosphorylation was observed in LX-2 cells (Figure 7). The TGF-\(\beta\)-induced upregulation of N-cad and FN was suppressed by **1** and **5** in a dose-dependent manner (Figure 6). These data indicated that **1** and **5** could inhibit the LX-2 cell epithelial-mesenchymal transition by inhibiting the TGF/Smad signaling pathway and should be potential anti-fibrosis agents.
# Unsupervised SAR Imagery Feature Learning with Median Filter-Based Loss Value
## 2 Neural Networks Training for SAR Imagery
### Self-Supervised Learning Techniques  
For some applications, when scans are taken from off-nadir angles (look-down-angle \(\
eq\) 90\({}^{\circ}\)), a good pretext task could be for a neural network to predict the scan angle or the azimuth angle of the satellite position during the scanning process. The information about it is contained in the metadata of the scan files. The main problem with such an approach is the fact that such a pretext task could lead to focusing only on buildings and other high, man-made (usual steel) objects and their shadows. The task itself requires imagery containing high objects and it is difficult even for human operators to deduce from the imagery. An example is shown in Figure 4.  
It is worth mentioning that the illustrations in Figure 4 skip the phenomenon related to the creation of the shadow area on the side of the radar. In addition, the image presents a single, high building, which is a perfect object for angle determination.  
An alternative approach could be the resolution prediction task. The SAR imagery rescaling heavily alters the contained information. Due to this effect, scaling can only be performed by a total number. Thus, the image can only be presented in basic image resolutions and multiples. Due to the limited number of potential output values and the complexity of the task, it is not an effective pretext task.  
Therefore, the first suggestion, i.e., azimuth angle determination, is better suited as the angle can be a floating point value <0\({}^{\circ},360^{\circ}\)). The neural network would be able to focus on shadows and high objects for such a task. This can be advantageous, as shown in [26].  
For such pretext tasks, a Self-supervised learning (SSL) algorithm such as SESEMI [27] can be used. In this research, no SSL technique was used for the reasons mentioned above.  
It is worth mentioning the novel approach to \"Unsupervised self-learning\" presented by [PERSON] and [PERSON]. [28]. It is able to achieve very good results but requires the training of a second model and works on correlated scan images, which makes the approach difficult to perform in a real environment. Especially when considering airplane carriers rather than satellites.
# The Impact of Additive Manufacturing on the Flexibility of a Manufacturing Supply Chain
## 3 Case Study
### Manufacturing Cost Parameters  
As pointed out by [PERSON] [40], firms must flexibly respond to sudden market changes with little or no penalty in cost or performance. In this case study, one important cost factor is the scale of production size or quantity. It is anticipated, based on the economies of scale phenomenon, that higher production volumes lead to lower unit costs (i.e., cost per part) [2]. In IM in particular, economies of scale exist as the cost of tooling (i.e., cost of producing the mould) is spread over production quantity. This phenomenon, however, does not relatively manifest itself in parts fabricated by AM due to the lack of tooling [41]. Unit cost models, therefore, are developed for both manufacturing technologies based on the general model structure for inter-process comparisons proposed by [PERSON], [PERSON], [PERSON] and [PERSON] [33], described in Appendix A.  
The material used to produce the part using IM is PVC procured as a feedstock at \(\copyright\)16/kg. Since PVC cannot be processed with the investigated variant of AM technology, laser sintering, the corresponding material employed in the AM supply chain is a Nylon 12 type material (PA2200) procured at the cost of \(\copyright\)54/kg. Due to the characteristics of proposed AM technology, sacrificial support structures are not needed in the AM route and the degraded raw material is the only form of waste. Labour costs entered the AM pathway in the form of the direct cost of \(\copyright\)0.23/part. The purchase price for each AM system (EOS P770) is estimated at \(\copyright\)668,475, based on Hasan [42], with assumed useful life of five years. A depreciation cost of \(\copyright\)133,695 per year therefore has been estimated in this study following a straight-line depreciation technique. These cost parameters have resulted in a constant unit cost for AM with a value of \(\copyright\)2.72. We note that the observed AM cost level is broadly in line with the cost performance reported by [PERSON], et al. [42].  
For the IM route, the most significant cost element is the tooling expense, estimated by the company at \(\copyright\)30,000; this cost was amortised over the manufactured quantity. This cost is incurred only once since the tooling can be re-used to produce the same part repeatedly, but cannot be exchanged with other toolings in the production line as it is part-specific. The tooling features four mould cavities, allowing the concurrent processing of four units in the moulding cycle, with each moulding cycle taking 74 s to complete. The operator cost  
Figure 6: Flowchart of the supply chain configuration with AM only.  
per part for IM, arising as a direct cost, is \(\ell 0.009/\)part. The IM machine (Haitian MA 5300) price is estimated at \(\ell 110,000\) with an assumed service life of five years. This results in a depreciation cost of \(\ell 22,000\) per year.
# Hybrid Quantum Dot as Promising Tools for Theranostic Application in Cancer
## 3 Hybrid Quantum Dot as Cancer Theranostics: Contemporary Research
### Therapeutic Application  
[PERSON] et al. formulated doxorubicin (DOX) loaded-fluorescent hyper-cross-linked-cyclodextrin-carbon quantum dot (CD-COD) hybrid nanospones (DOX-\(\beta\)-CD-COD) with a size of around 300 nm with a DOX loading capacity of 39.5% through host\(-\)guest complexation [82]. This is because of the supramolecular complexation of DOX with the CD units in the CD-CQD nanosponges. The developed DOX-CD-CQD nanosponges demonstrated pH-responsive controlled release in the simulated tumor microenvironment. The loaded DOX molecules in the surface layer of the DOX-CD-COD were released in the first 30 h, similar to the pH 7.4 medium. Due to the higher solubility of DOX in acidic media attributed to its protonation, the supramolecular complexation of DOX with \(\beta\)-CD units had a lower inclusion constant and a greater release ratio than in pH 7.4 conditions. Due to the high formation constant, they took longer to get out of the loaded DOX inner layer. Protonated DOX diffusion was prevented by hydrophobic DOX-complexed CD. After 12 h of DOX release, with an accumulative release of approximately 50%, hydrophilic outer shells formed, facilitating protonated DOX diffusion out of the theranostic system. After 24 h of incubation, the DOX concentration gradient climbed to 1.7 ug/mL with the DOX-\(\beta\)-CD-CQD theranostic system concentration of 20 ug/mL. Cell viability (29%) was comparable to free DOX at 10 ug/mL. In terms of antitumor efficacy, the DOX-CD-CQD outperformed free DOX. The DOX-\(\beta\)-CD-CQD had an IC\({}_{50}\) of 5.00 ug/mL (equivalent to 0.425 ug/mL), compared to 2.26 ug/mL for free DOX. DOX-CD-CQD was internalized
# Damage Imaging in Lamb Wave-Based Inspection of Adhesive Joints
## 3 Results and Discussion
### SLDV Maps  
Figure 7 shows snapshots of the guided wave propagation signals that were obtained in the experimental scanning of the analyzed specimens. The SLDV maps are presented at the time instance of 27.7 us. Disturbances of the wavefront shape on the disbond area were visible for each specimen from #2-#9 when compared with the intact specimen #1. The differences were more or less considerable, depending on the geometry of the defect. The most significant disturbances were observed for the specimens with stripped defects skewed and parallel to the primary direction of propagation (#4-#6). For specimens that had the disbond area in the shape of a strip perpendicular to the direction of propagation (#2, #7), the changes were not clearly visible. The exception was specimen #3, which had no adhesive near the edge of the overlap and resulted in the limited appearance of the wavefront on the overlap surface. Internal defects (#8, #9) were moderately detectable. In summary, the presence of the defects in the damaged specimens was visible in the maps, but their geometry was not determinable.  
Figure 6: Experimental and theoretical dispersion curves obtained for different excitation frequencies of 50 kHz, 100 kHz, and 200 kHz: (**a**) steel 3 mm plate (\(E\) = 195.2 GPa, \(v\) = 0.3, \(\rho\) = 7741.7 kg/m\({}^{3}\)); and (**b**) two adhesively jointed steel 3 mm plates (\(E\) = 195.2 GPa, \(v\) = 0.3, \(\rho\) = 7741.7 kg/m\({}^{3}\)) adhesively bonded with the adhesive layer of a thickness of 0.2 mm (\(E\) = 5 GPa, \(v\) = 0.35, \(\rho\) = 1130 kg/m\({}^{3}\)).  
Figure 7: Scanning laser Doppler vibrometry (SLDV) maps of considered joints at the time instance 27.7 us (dimensions of the joint are given in meters; the adhesive was 0.06–0.12 m).
# Advances in Mechanical Systems Dynamics 2020
## 3 Fields of Application
### Noise and Vibration Control  
Vibrations and noise are a potential problem for any application that includes moving components. For many years, the increase in working speed has been a typical trend of machines, but often the increased speed leads to high levels of vibrations and noise, which have to be controlled. The Internet of things and the fourth industrial revolution are characterized by networks of sensors that monitor industrial plants, machines, and vehicles. On the one hand, the sensors' performance and durability can be affected by high amplitude vibrations; on the other hand, environment vibrations can be exploited to feed the distributed sensors adopting vibration energy harvesting technologies based on piezoelectric, electromagnetic, and capacitive phenomena. In the Special Issue, there are four papers that focus on noise and vibration control. Paper [6] deals with machinery vibrations and presents a simplified approach for the analysis of varying compliance vibrations of rolling bearings. New viscoelastic materials are frequently adopted to control and dampen vibrations, in [9], two generalized formulations of viscoelastic materials are deeply analyzed and a comparison with experimental results is made. In [4], the problem of noise vibrations and harshness (NVH) in engines is considered. A coupled model, including an FE model of the structural parts and a multi-body model of valve train dynamics, is developed. An interesting comparison between results obtained with un-coupled and coupled models is made. Finally, in [5], a novel vibration absorbing mechanism for cables is presented. It exploits multi-physical components (magnetic springs and hydraulic cylinders). The mechanical design and the mathematical model ofthe mechanism are developed, and numerical results are presented; future applications will include stayed bridges.
# Hub-and-Spoke Network Design Considering Congestion and Flow-Based Cost Function
## 6 Experiments and Numerical Results
### Heuristic Algorithm Results  
To find an optimal or near-optimal solution in a reasonable amount of time, we developed a heuristic algorithm. In this section, we analyze the efficiency and performance of the algorithm. We run the heuristic algorithm for small instances, for which we have the optimal solution. Thus, we are able to compare the quality of the results of the heuristic algorithm with the ones of exact method.  
The results in Table 6 show that the heuristic algorithm is able to find high-quality solutions (and find the optimal solution for small instances). The runtime of the heuristic method is also reported. For instances with six nodes, the exact algorithm reaches optimality in a relatively shorter run time, but as the number of nodes increase, the heuristic algorithm lags with the exact solution; for exhaustive networks of only nine nodes, the heuristic method outperforms the exact method by far, compared the runtime of other the two. The quality of the obtained solutions from the heuristic algorithm is confirmed by the experiments, as shown in Table 6, and while the runtime is significantly improved, we run larger instances using the heuristic algorithm to find good enough solutions. To achieve a robust solution and comparison with the heuristic algorithm, we ran the algorithm 25 times on the base model and we report the average values of run time and cost function in Table 6.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & & & \multicolumn{4}{c}{\(\alpha\) = 0.2} & & & \multicolumn{4}{c}{\(\alpha\) = 0.5} \\ \hline  & & \multicolumn{3}{c}{**Total Cost**} & \multicolumn{3}{c}{**Run time**} & \multicolumn{3}{c}{**Total Cost**} & \multicolumn{3}{c}{**Run time**} \\ \cline{2-11}
**\multirow{-2}{*}{**
\begin{tabular}{c}
## 1 Introduction
The implementation of a soft sensor generating a biochemical oxygen demand (BOD) signal for water in an open system based on measurements of many signals and the use of a self-organizing neural network with random weights was presented in [15]. An additional requirement of this application is the preprocessing of data. Soft sensors can also be implemented using Kalman filter algorithms [16]. This approach used measurements from two different sources to obtain the estimated signal sought, and in the Kalman algorithm, the stages of prediction and updating of the signal estimation were separated. The final results of the soft sensor were based on measurements of online signals and signals developed in laboratory tests, which imposed an additional load on the proposed method. An extended Kalman filter was used in [17] to obtain better results. The methods used there, in the form of Monte Carlo or polynomial chaos theory, give hope for improvement of the computational efficiency of methods for estimating current parameters but at the cost of greater computational complexity. The studies discussed above present different approaches for achieving appropriate improvements in the quality of final results, however, they are burdened with significant computational inputs. This article proposes an adaptive approach to the implementation of the soft sensor, enabling generation of desired signals describing the object, obtained on the basis of possible online measurements and signals generated from a mathematical model. This approach is characterized by lower computational complexity and greater accuracy of the solution compared with algorithms using Kalman filters mechanisms. The essence of the proposed adaptation mechanism consists of changing the gain coefficient in time in the soft sensor's filtration equation used for online monitoring of river water quality.
# Atmospheric GNSS RO 1D-Var in Use at UCAR: Description and Validation
## 3 Results
### Validation Using NWP Model Data
#### 3.3.3 Dependence on the Background
In the standard deviation from the ECMWF analysis, COSMIC2 (right panels) is notably smaller than the background (left) in both specific humidity (upper) and precipitable water (lower). Besides validating that 1D-Var can produce value-added retrievals, this presents the potential of COSMIC-2 data for improving atmospheric humidity in weather analysis and forecasting. Figure 12: Root-mean-square differences of 2.5 km specific humidity (g kg\({}^{-1}\)) among the operational NCEP analysis (denoted GFS), the ECMWF Interim reanalysis (denoted ERA), and two 1D-Var retrievals (denoted COSMIC\({}_{\text{GFS}}\) and COSMIC\({}_{\text{ERA}}\)) for each of which GFS and ERA are used as a priori data, for the period from January 2008 to August 2014. The dashed lines in upper panels, denoted A and B, coincide with the times that NCEP GFS underwent major system upgrades. See text for details. Figure 13: COSMIC-2 humidity retrievals (marked COSMIC2) versus short-term GFS forecasts (used as the background; marked GFS\({}_{\text{FCTST}}\)), with reference to ECMWF analysis (ECMWF\({}_{\text{ANAL}}\)) for the period from 16 July 2019 to 1 February 2020. Left panels are standard deviations of GFS\({}_{\text{FCTST}}\)-ECMWF\({}_{\text{ANAL}}\) and right panels are those of COSMIC2-ECMWF\({}_{\text{ANAL}}\). Upper panels are for the specific humidity (g kg\({}^{-1}\)) and lower panels are for the precipitable water (mm).
# Secure Delivery Method for Preserving Data Integrity of a Video Frame with Sensitive Objects
###### Abstract  
Data integrity and authenticity verification are essential requirements to provide reliability for applications running in a video delivery system. We design a prototype system for handling data integrity as well as encoding sensitive objects in a video frame. This system is composed of two components, a logger and a verifier. The logger operates a cryptography hash function of a feature vector of a video data frame and an XOR encoding scheme used for hiding the privacy information of sensitive objects in the video data frame. The XOR encoding scheme is operated at the encoder as part of the logger. The hash value outputted from the hash function is signed by a private key owned by the logger. It is listed as one of the attributes in the metadata of the video frame. In the key distribution phase for the authenticity verification process, the logger maintains the private key, and the public key is stored on the verifier by handshaking. In order to reduce the processing load for data integrity verification, a hash tree configured for each stream of sensor data is used to minimize the verification time. This paper is mainly focused on the design of a logger for data integrity verification and encoding of sensitive objects. To evaluate performance of the proposed method, we build a prototype in a client-server manner. The designed method is operated on the logger, used to mitigate the risk of video data frame tampering and to significantly help in preserving sensitive objects securely.  
video data frame; data integrity; authenticity; logger; XOR encoding; sensitive object 26 February 2025  
14 March 20  
GDPR, protecting personal data against unauthorized access, alteration, or disclosure is crucial. In terms of integrity and confidentiality, data must be processed in a manner that ensures appropriate security, including protection against unauthorized or unlawful processing and accidental loss, destruction, or damage.
## 4 Data Analysis and Results
### Wind Analysis  
Natural ventilation as an effective energy saving measure uses various construction techniques, such as temperature control and expelling moisture, to guide and optimize airflow to improve the indoor air quality. Natural ventilation considerations covered construction materials, natural lighting, underground cold and heat storage, and automatic control. The building layout had a great effect on natural ventilation. Figures 21 and 22 present the wind frequency, wind direction, and wind speed distribution throughout the year, indicating that the main wind direction is southeast in summer and northeast in winter. Smart use of natural ventilation for cooling could be aided by the wind frequency chart. For example, the main roads in the scheme area were aligned with the prevailing wind direction to allow smooth passage. For the building itself, the main wind direction in summer is southeast; thus, the height of the north window was raised to make the air outlet higher than the air inlet. Meanwhile, movable vertical shutters were set up on the south facade so that adjusting the vertical shutter according to the wind direction and sun height angle could increase the air intake and effectively reduce the indoor temperature.
## 7 Issues and Challenges
### DSM with Hydro Energy Sources  
Generation sources pertaining to hydro-based sources are a major part of the power supply to grids. Complex hydropower-generating units installed in dams and tidal-based generation can be leveraged to a high extent, owing to their pollution-free generation and the replenishable source of waterbodies, which are naturally replenished via the water cycle. The major issues that are present in the existing power generation scenario that can affect DSM operation, to a certain extent, are highlighted as follows:  
* The availability of water sources for potential generation is not feasible in every possible geographical location. Large-scale generation is only possible if the geographical arrangement allows for dams to be constructed or the waves to be harnessed suitably without causing ecological imbalance to nearby flora and fauna.
* The ratios of cost-to-establishment and revenue generation-to-cost are generally low, owing to high recurring and installation expenditures. However, these can be leveraged by using an environmental outlook to justify the cost.
* Maintaining the frequency of the power generated is complex due to the intermittent nature of water flow at the available head level. This prevents the energy generated from the wind turbines to be directly integrated into the transmission system, as pre-conditioning the power supplied is necessary for reliable grid operation. This adds significantly to the power generation costs as additional power conditioning units are required to bring the frequency and other parameters up to an acceptable generation level.