esa-sceva/satcom-chunk-collection huggingface dataset:
# Laser Synthesized Graphene and Its Applications
## 3 Applications of Laser Synthesized Graphene
### Biosensing  
Biosensing typically refers to the detection of molecules or biomolecules using a device employing a biological component. LIG has been identified as a suitable component for biosensing due to the porous structure allowing a high surface area, similar to other sensing applications. One of the first reports that appeared demonstrated the detection of Bisphenol-A [66], a molecule used in many industrial applications that is often found in the environment. The detection, down to femto- or attonolar concentrations, involved the functionalization of the LIG surface by aptamers, i.e., oligonucleotides or peptides that bind specifically to the target molecule. Here, the LIG was patterned as interdigitated electrodes to provide a capacitive sensing through an AC electroosmotic effect [66]. LIG decorated by Pt nanoparticles was used for the detection of ascorbic acid (AA), dopamine (DA), and uric acid (UA) [67]. This was achieved by electrochemical sensing using cyclic voltammetry and the limit of detection was of the order of the micromolar. Later, the same group used LIG to demonstrate the detection of thrombin [68], an enzyme that induces coagulation and may cause thrombosis. Here, LIG surface was functionalized by 1-pyrenebutyric acid that subsequently attached an aptamer for thrombin. The system uses a redox marker such  
Figure 11: (**a**) LIG-based system to detect motion of a finger. Reproduced with permission from Ref. [60]. Copyright 2015, American Chemical Society. (**b**) ECG from an LIG-based system. Reproduced with permission from Ref. [64]. Copyright 2018, Wiley. (**c**) Heart beat detection from an LIG system. Reproduced with permission from ref. [63]. Copyright 2018, Wiley.  
as hexacyanoferrate(III) ([Fe(CN)6]3-) that upon binding of thrombin to the aptamer is inhibited to reach the electrodes and causes a current drop [68], as schematized in Figure 12.  
A DA sensor has recently been demonstrated by [PERSON] et al., where LIG is used without further functionalization [69]. LIG decorated with Cu nanocubes, deposited by electroplating, was used for the detection of biogenic amines [70], which are known as indicators of food degradation. Still related to food quality, [PERSON] et al. proposed an LIG-based detection method for salmonella [71]. This is achieved through binding salmonella antibodies to the LIG surface and using electrochemical impedance spectroscopy for device characterization. [PERSON] et al. proposed a dual LIG-based detector for AA and amoxicillin (AMOX) sensing, two ingredients found in fish farms that can leak into the outer environment [72]. Table 1 summarizes the findings from this section with the relevant sensor information.
## 3 Experimental Procedures
### Prediction of Depth of Cut  
A Mitutoyo stylus profilometer with a stylus tip radius of 5 \(\upmu\)m was used to measure the depth of cut across the grinded path. Mitutoyo profilometer primarily consists of a traverse unit and a processor control module. The grinded workpieces are so adjusted that the area of interest of measurement is across the grinded path. The length is profiled across locations A, B, and C along the tool path, as shown in Figure 6. 3D and 2D profiles were extracted from the workpiece surface across the machined length, using the profilometer to measure the depth of cut, as illustrated in Figure 7.  
The depth of cut is measured as the distance between the deepest point in the grinded path and the surface of the word coupon. Each experimental trial was repeated three times to have consistency, and depth of cut was measured across three locations for each trial, resulting in a total of nine reading per test. Figure 8 shows the standard deviation of the depth of cut measure taken from Taguchi's L27 orthogonal array based experimental trials for all 27 test conditions. Table 2 shows the experimental results for the mean depth of cut and corresponding \(S/N\) ratios. The depth of cut, i.e., material removal, was identified as the process output as well as the quality characteristic with the concept 'the larger-the-better'. The \(S/N\) ratio for the larger-the-better is: \(S/N=-10\times\log\) (mean square deviation):  
\[\frac{S}{N}=-10 log_{10}\bigg{(}\frac{1}{n}\sum\frac{1}{y^{2}}\bigg{)} \tag{8}\]  
Figure 7: (**a**) 3D profile extracted from the workpiece surface across the machined surface using Taly-scan; (**b**) 2D profile obtained from the workpiece surface across the grinded path to measure the depth of cut.  
where \(n\) is the number of measurements in a trial/row, in this case, \(n=1\), and y is the measured value in a run/row. A higher \(S/N\) value agrees with a higher depth of cut. Consequently, the ideal level of the grinding parameters is the level with the most significant \(S/N\) value.
## 6 Results and Discussion
### Case 2. Partial Shading Condition  
In case 2 partial shading is discussed and their irradiance pattern is presented in Table 2. Partial shading occurs because of not receiving equal irradiance values by PV arrays. Bypass diodes are used for less-performing diodes due to PS. There are multiple peaks that appear on the I-V and the P-V characteristics curve that can result in complications for searching the peaks. Furthermore, multiple peaks are characterized as a number of LM and single GM. Conventional techniques cannot differentiate between LM and GM that may result in the reduction of power loss. The I-V and P-V characteristic curves of PS cases 2 and 3 are described in Figure 10. There are three LM and single GM observed on the I-V and P-V characteristics curve. The value of GM for PS1 is 512 W.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Case** & \multicolumn{3}{c}{**Irradiance \(S_{i}\) (\(\frac{\text{KW}}{m^{2}}\))**} & \multicolumn{1}{c}{\(Pover_{max}\)} \\ \hline \multirow{2}{*}{Case 1 UI} & PV-1:0.70 & PV-2:0.70 & PV-3:0.70 & \multirow{2}{*}{864 W} \\  & PV-4:0.70 & & & \\ \hline \multirow{2}{*}{Case 2 PS1} & PV-1:1.00 & PV-2:0.80 & PV-3:0.10 & \multirow{2}{*}{512 W} \\  & PV-4:0.20 & & & \\ \hline \multirow{2}{*}{Case 3 PS2} & PV-1:0.90 & PV-2:1.00 & PV-3:0.80 & \multirow{2}{*}{781 W} \\  & PV-4:0.50 & & & \\ \hline \multirow{3}{*}{Case 4 CPS} & PV-1:1.10 & PV-2:0.25 & PV-3:0.84 & \multirow{3}{*}{1250 W} \\  & PV-4:0.40 & PV-5:1.00 & PV-6:0.50 & \\ \cline{1-1} \cline{3-5}  & PV-7:0.90 & PV-8:0.40 & PV-9:0.80 & \\ \cline{1-1} \cline{3-5}  & PV-10:0.20 & & & \\ \hline \hline \end{tabular}
\end{table}
Table 2: P-V and I-V characteristic curves at different irradiance values.  
Figure 10: P-V and I-V Characteristics Curves for Partial Shading Cases 2 and 3.  
The proposed InC-DFO technique successfully obtained the GM value for the PS condition. Power tracked by proposed hybrid and all other DFO, CS, PSO, FA, InC, and ACO techniques are 511.4 W, 509 W, 506 W. 498 W, 325 W, and 507 W, respectively. ACO techniques are stuck on LM1 and cannot find GM. PSO techniques have the highest oscillations and settling time of 1.80 s which results in loss of power and therefore their efficiency also decreases. Conventional InC techniques tracked the lowest power. The settling time of PSO, DFO, InC, Hybrid, CS, FA, and ACO techniques are 1.80 s, 0.75 s, 0.52 s, 0.62 s, 1.78 s, 1.30 s, and 0.93 s, respectively. Power, Current and Voltage comparison of all techniques for Case 1 and Case 2 are shown in Figure 11.
## 3 Results
### Technical Analysis
#### 3.2.2 Fuzzy Logic Controller Features
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Reference** & **Control System** & **Description** & **Efficacy** & **Efficacy** \\ \hline \multirow{2}{*}{[72]} & \multirow{2}{*}{_Self-tuned fuzzy-PI_} & Mitigation of voltage sags, voltage, and THD by using a dynamic voltage restorer and two FLCs & Efficacy assessment using simulations & Comparison between the system with and without dynamic voltage restorer \\ \hline \multirow{2}{*}{[73]} & \multirow{2}{*}{_Fuzzy fractional-order PI_} & Single-phase active power filter controlled to increase power factor and limit harmonics & Simulations and experimental testing of the efficacy & Proposed methodology with the controller without fuzzy usage \\ \hline \multirow{2}{*}{[74]} & \multirow{2}{*}{_EV-fuzzy-PID_} & Voltage and frequency control with automatic voltage regulator and particle swarm optimization & Software implementation for efficacy evaluation & Results show the comparison of the proposed method with another hybrid method from the literature \\ \hline \multirow{2}{*}{[75]} & \multirow{2}{*}{_Tuned fuzzy-PID_} & Frequency regulation employing static synchronous series compensator (SSSC) and teaching learning optimization technique & Efficacy assessment through software implementation & The proposed method compared with the control without SSSC and with the genetic algorithm \\ \hline \hline \end{tabular}
\end{table} 
Table 4: _Cont._Figure 4: Article distribution regarding the type of membership function. Tr—triangle; Ta—trapeze; Ga—Gauss; Trô&Ta—triangle and trapeze; Be—bell; Si—sigmoid; Sin—singleton. Figure 3: Article distribution regarding the number of linguistic variables of the fuzzy controllers. Figure 2: Article distribution regarding the number of inputs and number of outputs of the fuzzy controllers. Table 5 presents 10 articles that contain whole data about all features of the proposed FLC. The table's header is divided into the four FLC features, the reference number, and the fuzzy-based control systems' efficacy testing and efficiency demonstrations.
## 5 Modes of Operation
### STARDUST (Subpayload 2) Camera Real-Time Operation
#### 5.2.2 Real-Time RSO Detection  
RSO detection was performed on three images at a time, in a rolling window fashion. This meant that RSO detection was performed starting on the third iteration (once the third image was read in). After this iteration, image reading and preprocessing was only performed on one image at a time. The algorithm was based on the idea that RSOs will travel roughly linearly in the camera's FOV, and so a simple two-step algorithm was created. The first step involved extracting the x and y pixel locations of the centroids for every detected object in the image. This step made use of image processing techniques such as thresholding and performing Connected Components Analysis (CCA) to uniquely segment objects. The next step involved associating three unique, equally spaced points together, that all lie on a straight line, within a tolerance. These conditions classified these points as RSOs, while additional constraints such as distance thresholds removed points that were too far apart (and likely noise), or too close together (and likely stars, moving slightly due to the gondola sway).  
Figure 6 shows the entire STARDUST software block diagram. All functions were run in series with error handling to ensure that faults in some functions do not impact the execution of other functions.
###### Abstract  
Hybrid energy systems combine multiple energy sources and storage technologies to enhance performance and meet diverse energy needs. Hybrid heat pump systems are particularly suitable for heating and cooling buildings in rural areas. Air-source heat pumps have two well-known disadvantages during the coldest period of the year, when the building's heating load is at its peak: the heat pump's capacity is reduced and it needs to perform defrost cycles. A potential solution is to size the heat pump to cover only a portion of the peak load and to use a second heat generator in a hybrid heat pump system. There is a gap in the literature regarding the configurational analysis of hybrid heat pump (HHP) systems, particularly in terms of combining heat pumps and biomass boilers, and evaluating their efficiency, economic aspects, and environmental impact. Thus, in this research, a dynamic model of a HHP system, consisting of an air-to-water heat pump paired with a biomass boiler as a backup, is presented. Various configurations of the HHP system have been developed to evaluate key performance indicators, such as efficiency, emissions, operational costs, and other relevant factors. The findings of this paper indicate that the energy performance of HHP systems is significantly affected by the system layout, heat pump size, cut-off temperature, and the control algorithm used to activate the heat generators. Moreover, series operation of HHP systems is not only more efficient than parallel operation but also results in lower emissions and reduced operation costs. As expected, the energy loss associated with defrost cycles significantly impacts the overall performance of a hybrid system based on an air-source heat pump. Finally, the impact of the cut-off temperature on the key parameters in the configuration analysis was examined, and the optimal performance of the HHP system, in terms of minimizing operational costs and emissions, was depicted using a heat map diagram.  
hybrid heat pump system; configurational analysis; biomass boiler; control strategy; dynamic modeling +
Footnote †: journal: Applied sciences
## 4 Simulation and Experimental Results
### Experimental Results  
In order to verify the feasibility of the three-phase energy mutual-aid control strategy, we performed an experiment on the grid-connected experimental platform, shown in Figure 13.  
In this experiment, only the lower-level method is used to realize the three-phase energy mutual aid, and the mutual power is manually set. Unlike the simulation in Section 4.3, not only the lower-level method is used, but also the upper-level method is used to calculate the appropriate mutual power to achieve three-phase voltage balance.  
In the experimental platform, a 750 V DC regulated power supply is connected to the three-phase 380 V AC power grid, via a self-made inverter, as shown in Figure 13. The grid line impedance is negligible, and the control target parameters are shown in Table 4.  
The measured voltage and current are shown in Figure 14. In Figure 14, the upper half screen shows the measured waveform of the three-phase voltage \(V_{\text{PCC\_A/B/C}}\) of the PCC, and the lower half screen shows the measured waveform of the three-phase grid current \(I_{\text{A/B/C}}\) of the inverter. It can be seen that:  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Physical Quantities** & **Symbol** & **Set Value** \\ \hline Positive sequence D-axis target current & \(I_{\text{dref}}\) & 10 A \\ \hline Positive sequence Q-axis target current & \(I_{\text{dref}}\) & 0 A \\ \hline Negative sequence Phase A target current & \(X_{\text{A}}\) & 0 A \\ \hline Negative sequence Phase B target current & \(X_{\text{B}}\) & 0 A \\ \hline Negative sequence Phase C target current & \(X_{\text{C}}\) & 5 A \\ \hline \hline \end{tabular}
\end{table}
Table 4: Target current given in the experiment.  
Figure 13: Experimental platform of the grid-connected inverter.  
1. The three-phase voltage of the PCC is balanced, and the waveform is approximately sinusoidal without obvious distortion. The RMS is about 220 V, which can be regarded as an ideal power grid.
2. In the three-phase grid current, \(I_{\rm A}\) and \(I_{\rm B}\) are approximately equal, and the RMS is about 10 A; \(I_{\rm C}\) is significantly larger than \(I_{\rm A}\) and \(I_{\rm B}\), and the RMS of \(I_{\rm C}\) is about 15 A, which is the same as the given target. By this means, three-phase current decoupling control is realized, in other words, three-phase energy mutual aid is achieved.
3. Although the magnitude of the grid current \(I_{\rm A/B/C}\) is not equal, the current of each phase has no obvious distortion, the waveform is approximately sinusoidal, and the power quality meets the requirements of the grid-connected system.
# Performance of API Design for Interoperability of Medical Information Systems
###### Abstract  
After the experience of the COVID-19 pandemic, it has become evident that efficient and secure interoperability of medical information is crucial for effective diagnoses and medical treatments. However, a significant challenge arises concerning the heterogeneity of the systems storing patient information in medical centers or hospitals. Memory management becomes a pivotal element for the effective operation of the proposed API, as it must seamlessly execute across various devices, ranging from healthcare units, such as mobile phones, to servers in cloud computing. This proposal addresses these issues through techniques designed to enhance the performance of the software architecture in creating a medical interoperability API. This API has the capacity to be cloned and distributed to facilitate the exchange of data related to a patient's medical history. To tackle heterogeneity, efficient memory management was implemented by utilizing an object-oriented approach and leveraging design patterns like abstract factory and wrapper. Regarding the evaluation of the proposal, this study showed an estimated performance of 94.5 percent, which was indirectly demonstrated through the assessment of operation sequences. This result suggests a satisfactory level based on complexity and coupling.  
API; application programming interface; information medical interoperability; performance design; design patterns; HL7 +
Footnote †: journal: Medical Information Systems  
2.x and 3.x. FHIR boasts a simplified implementation, offering the advantage of using the HTTP protocol and RESTful principles for the development of efficient services. It utilizes HTML and cascading style sheets to generate graphical interfaces, providing the flexibility to integrate the user interface into a broader environment. Additionally, FHIR allows for the selection between JSON, XML, or RDF to represent detailed information in the resulting data.  
Despite its strengths, FHIR has faced technical criticism, particularly in the development of API interoperability applications, where its implementation can become complex. In another critique, RIM version 3 is characterized as a standard with challenges in implementation, usability, scope, documentation, and marketing [18].  
The proposed approach sought to address the following research questions, which are considered primary contributions:  
1. Is an object-oriented-design-based API following the HL7 CDA standard a viable solution for addressing the heterogeneity of legacy medical systems?
2. How can design patterns enhance the architectural design performance of the API to provide interoperability on medical information systems?
3. Can valid measures of complexity and coupling be employed to assess the efficiency of the API's architectural design?
# Dynamic Graph Convolutional Crowd Flow Prediction Model Based on Residual Network Structure
## 4 Experiments and Analysis
### Ablation Experiments  
This section performs ablation experiments to assess each component's impact on the model's accuracy in order to show the effectiveness of the components designed in this paper. The component units used in the experiments include SA, sCondConv, and Huber. By combining these units in different ways, six variants of Res-DGCN are designed to understand the roles and contributions of each component in the model, providing guidance for further optimization of the model.  
As shown in Table 3 (\(\Delta\) indicates percentage of performance improvement), the three components proposed in this paper have significantly enhanced the model's prediction accuracy. Removing any of these components would increase the prediction error. In the TaxiNYC dataset, considering the spatial dependency between the target node and multi-order neighboring nodes appears to be more important, indicating the crucial role of the SA module. On the other hand, in the BikeNYC dataset, considering the temporal trend of nearby time steps seems to be more important, highlighting the significance of the sCondConv module. Since the proposed model needs to simultaneously consider both spatial and temporal information along with input features, the SA module and sCondConv are used in combination.  
However, in this ablation experiment, the SA+sCondConv variant showed a 2.2% decrease in prediction accuracy compared to the SA variant in the Taxi dataset. Similarly, in the Bike dataset, the SA+sCondConv variant showed a 0.7% decrease in prediction  
Figure 6: Predicted inflow for a region in a day compared to ground truth data.  
Figure 7: Comparison of model training loss variation in the BikeNYC dataset.  
accuracy compared to the sCondConv variant. However, in the complete Res-DGCN model, the prediction accuracy improved by 1.8% to 6.2% compared to the single-module variants. The experiment demonstrates that the Huber loss function can reduce the model's sensitivity to outliers, leading to improved prediction accuracy. Whether used alone or in combination, the Huber loss function contributes to varying degrees of enhancement in the model's accuracy.
## 3 Results and Discussion
In the interaction of XUV laser radiation with solid targets, the damage could be classified into 'desorption' and 'ablation' [18]. If the local fluence of the laser is around the damage threshold, desorption is dynamically possible. Generally, a characteristic microscopic time scale for desorption varies from 200 fs to 3 ps [19]. However, in the case of the metallic surface, the dissipation of initial electronic or vibrational excitations from absorbed photons occurs on a time scale of a few femtoseconds. That means desorption cannot take place on a pure metallic surface. In addition, from the detection results, the surface behavior of copper-induced by the 46.9 nm laser irradiation was quite drastic, which fitted the 'ablation' expression better. Therefore, in the interaction of a 46.9 nm laser with copper, the damage on the target surface could be characterized as 'ablation'. Copper contained plenty of free electrons under room temperature. That meant, in the interaction, the laser energy could be absorbed directly by free electrons, resulting in the temperature rise in the irradiated area. Then the lattices were distorted and the damage took place. In this process, the thermal effect was dominant. We could expect that most of the laser energy contributed to the temperature rise of the irradiated area. According to the simulation result, with the absorption of one pulse energy, the highest temperature of the irradiated area was above the evaporating point of copper. Therefore, the surface of copper was melted and evaporated by the irradiation of the 46.9 nm laser. According to the results, the surface behavior induced by a 46.9 nm laser on copper differed from that on other types of materials, such as large bandgap dielectrics (PMMA [20], BaF\({}_{2}\)[12]) and multiple layers [9]. In the case of dielectrics, regardless of the type of organic or inorganic, the damage always induced by a non-thermal effect, leaving clear patterns with a certain depth and a clean edge. The bound electrons absorb photon energy and are ionized. Or the molecular bond is directly broken by the photon. In the case of multiple layers, discoloration was detected resulting from heat-triggered interdiffusion in upper layers. Cracks covered damaged area indicated tensile stress induced by thermal expansion and the following cooling down process. The similar cracks were not observed in the damage of copper in this work because the material characteristic of copper is different from the multiple layers and also the fluence of the laser was lower which was not able to generate such a temperature difference. According to Reference [20], in the interaction of a 46.9 nm laser with solid targets, attenuation length was a crucial factor in determinate the damage mechanism, which was classified involving the traveling ionization wave of ablation and ablation threshold. Based on that statement, the damage that occurred on copper fits the former mechanism.