esa-sceva/satcom-chunk-collection huggingface dataset:
### Existing Commercial Building
operating at DC voltages of 750 V, 375 V, and 48 V. The system integrated various components and connected to the power grid via a bidirectional AC/DC converter. The topology structure of the building's PEDF system is shown in Figure 13. The building has sufficient roof space for photovoltaic installations, with additional facade space available if necessary. Its design meets aesthetic requirements and does not impact nearby structures. Given high solar radiation intensity, BIPV is employed and the photovoltaic configuration process is shown in Figure 8. For energy management, lithium-iron-phosphate batteries have been chosen to assist with peak shaving and valley filling. Critical interactive devices have been configured. The specific configuration results are presented in Appendix A. The time-of-use electricity prices used in the configuration optimization process are detailed in Table 4.  
Table 8 presents a detailed list of evaluation indicators before and after the configuration of existing commercial buildings, while Table 9 provides a comprehensive overview of the evaluation process and results before and after the configuration of these buildings. The investment return period evaluation index has been set to 9999 due to the inability to achieve investment recovery before optimizing the configuration of existing commercial buildings. The evaluation index results show that commercial buildings can achieve investment returns while reducing levelized cost of electricity to below 0.4 CNY/kW, carbon emission have dropped by over 1 million kilograms, and photovoltaic self-consumption rate has increased to over 40%, with the self-sufficiency rate at over 45%. The system smoothing coefficient is expected to exceed 45%, the probability of power supply loss will fall below 50%, with electricity flexibility increasing to over 10%. However, the photovoltaic self-sufficiency rate in the economic priority is slightly lower than the pre-optimization benchmark, and the system smoothness coefficient for the low-carbon priority has slightly decreased. The comprehensive evaluation results indicate that the system's rating has improved after the optimization, with the highest score in reliability optimization, followed by economy and low-carbon considerations. These results validate the effectiveness of the framework proposed in this research for optimizing PEDF systems in existing commercial buildings. Figure 13: Topology of the PEDF system in the specific commercial building.
## 3 Results
### The WSM from Nano-Nacre Particles Promoted MC3T3-E1 Cells Differentiation  
The WSM extracted from nano-nacre particles significantly promoted the differentiation of MC3T3-E1 pre-osteoblastic cells by upregulating both early and late osteogenic markers (Figure 4a-c). Early markers, including RUNX2 and ALP [30], exhibited increased mRNA levels following WSM treatments, with ALP showing a higher fold-change than RUNX2. The highest fold-change for RUNX2 (-1.6) was observed on day 14 at WSM concentrations of 0.05% and 0.1% \(w/v\), both significantly different from the control (\(p\) = 0.005, \(p\) = 0.0062). For ALP, the effective WSM concentration was as low as 0.025% \(w/v\), yielding a fold-change of \(\sim\)1.4 by day 14, with the maximum (-1.8) observed in the 0.05% and 0.1% \(w/v\) treatments (\(p\) < 0.01, \(p\) < 0.0121). Late osteogenic marker OCN [31] exhibited a more pronounced response, with its mRNA levels showing a maximum fold-change of \(\sim\)3.6 on day 14 at 0.1% \(w/v\) (\(p\) < 0.0001). Across all durations, OCN mRNA fold-changes consistently exceeded 1.5 at 0.05% \(w/v\) (\(p\) < 0.009), demonstrating WSM's potent osteoinductive capacity.  
Figure 4: _Cont._  
Figure 3: Effect of WSM from nano-nacre particles of \(H\). _diversicolor_ on cell viability percentage as measured by MTT assay, indicating the non-toxic nature of WSM for MC3T3-E1 cells. Each value is the mean \(\pm\) SD of three independent experiments when compared with the DMEM group. \({}^{*}\)\(p\) < 0.05 indicates significant differences compared with the control group.
## 2 Results
### Identification of PmSTPS1 and PmSTPS2 Assay Products  
A functional characterisation of the _Pm_STPS1 and _Pm_STPS2 genes was performed by an in vitro enzyme assay of the recombinant proteins. In this crude protein assay, the _E. coli_ strain harbouring empty pQE-2 vector was used as the control strain. A GC-MS analysis showed that _Pm_STPS1 and _Pm_STPS2 produced \(\beta\)-farresene, \(\alpha\)-farresene, and farnesol as the final products. Additionally, _Pm_STPS2 also produced nerolidol. For _Pm_STPS1, the products formed were \(\beta\)-farresene (14.49 min), \(\alpha\)-farresene (15.79 min), and farnesol (16.98 min). Additionally, the principle products from _Pm_STPS2 enzyme were \(\beta\)-farresene (14.49 min), \(\alpha\)-farresene (15.83 min), farnesol (16.84 min), and nerolidol (17.25 min). Based on the GC-MS analysis, both extracts from _Pm_STPS1 and _Pm_STPS2 showed multiple peaks for corresponding sesquiterpene products, compared with no peaks observed in the control sample, which did not exhibit any major products, although exogenous substrates were added (Figure 3). These findings therefore demonstrated the successful production of sesquiterpenes in the recombinant _E. coli_ strains overexpressing _Pm_STPS1 and _Pm_STPS2 enzymes, respectively.  
Figure 3: _Cont._All of the peaks were further confirmed by comparison with NIST and Wiley libraries, mass spectra, authentic sesquiterpene standards, and control (Figure S5). Interestingly, although the sizes of _Pm_STPS1 and _Pm_STPS2 were different, the two enzymes were capable of producing similar sesquiterpene products, \(\beta\)-farnesene, \(\alpha\)-farnesene, and farnesol (Figure 3), but they did so at different levels. _Pm_STPS1 successfully converted the precursor FPP to produce 9.50% \(\beta\)-farnesene as the main product, followed by 8.86% \(\alpha\)-farnesene, and 5.08% farnesol. _Pm_STPS2 showed synthesises nerolidol (48.33%) as a major product, followed by farnesol (15.30%), \(\beta\)-farnesene (5.07%), and \(\alpha\)-farnesene (2.76%). Although the (E,E)-farnesyl pyrophosphate (FPP) substrate was added to the enzymatic assay, the control pQE-2 sample did not produce any significant products, indicating that endogenous metabolites did not affect the protein expression and analysis in this study.
## 4 Results
### Multi-Temporal Detecting Geological Hazards
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**No.**} & \multicolumn{3}{c}{**Geologic Hazard Area (ha)**} & \multicolumn{3}{c}{**Geologic Hazard Variation Area (ha)**} & \multicolumn{3}{c}{**Geologic Hazard Variation Rate (per year)**} \\ \cline{2-10}  & **2008** & **2009** & **2011** & **2008–2009** & **2009–2011** & **2008–2011** & **2008–2009** & **2009–2011** & **2008–2011** \\ \hline
1 & 260.33 & 232.70 & 235.03 & \(-\)27.63 & 2.34 & \(-\)25.29 & 0.11 & \(-\)0.01 & 0.03 \\
2 & 631.63 & 626.37 & 323.61 & \(-\)5.26 & \(-\)302.76 & \(-\)308.02 & 0.01 & 0.24 & 0.16 \\
3 & 121.68 & 122.09 & 107.11 & 0.41 & \(-\)14.98 & \(-\)14.57 & \(-\)0.003 & 0.06 & 0.04 \\
4 & 113.30 & 86.60 & 53.21 & \(-\)26.70 & \(-\)33.39 & \(-\)60.09 & 0.24 & 0.19 & 0.18 \\
5 & 148.18 & 129.20 & 88.81 & \(-\)18.98 & \(-\)40.39 & \(-\)59.37 & 0.13 & 0.16 & 0.13 \\
6 & 48.49 & 45.58 & 39.74 & \(-\)2.91 & \(-\)5.84 & \(-\)8.75 & 0.06 & 0.06 & 0.06 \\
7 & 664.73 & 454.83 & 265.57 & \(-\)209.89 & \(-\)189.26 & \(-\)399.16 & 0.32 & 0.21 & 0.20 \\
8 & 616.85 & 602.69 & 463.49 & \(-\)14.16 & \(-\)139.20 & \(-\)153.36 & 0.02 & 0.12 & 0.08 \\
9 & 110.33 & 102.74 & 105.83 & \(-\)7.59 & 3.09 & \(-\)4.51 & 0.07 & \(-\)0.02 & 0.01 \\
10 & 487.14 & 516.83 & 351.75 & 29.70 & \(-\)165.08 & \(-\)135.39 & \(-\)0.06 & 0.16 & 0.09 \\
11 & 155.32 & 163.12 & 109.39 & 7.80 & \(-\)53.73 & \(-\)45.93 & \(-\)0.05 & 0.16 & 0.10 \\
12 & 191.11 & 154.99 & 111.55 & \(-\)36.12 & \(-\)43.44 & \(-\)79.56 & 0.19 & 0.14 & 0.14 \\
13 & 373.82 & 230.04 & 224.42 & \(-\)143.77 & \(-\)5.63 & \(-\)149.40 & 0.38 & 0.01 & 0.13 \\
14 & 141.90 & 153.84 (2010) & 164.60 & 11.94 & 10.76 & 22.70 & \(-\)0.04 & \(-\)0.07 & \(-\)0.05 \\
15 & 959.59 (2009) & 972.15 (2010) & 951.05 & 12.56 & \(-\)8.53 & 12.56 & \(-\)0.01 & 0.01 & \(-\)0.01 \\ \hline Total & 3922.91 & 3467.78 & 2479.51 & \(-\)455.10 & \(-\)988.27 & \(-\)1443.40 & 0.116 & 0.142 & 0.123 \\ \hline \hline \end{tabular} Note: In the column of “geologic hazards variation rate”, positive numbers represent an decrease in hazard area; negative numbers represent a increase in hazard area; with regard to the No. 14 and No. 15 sites, the columns “2008–2009,”2008–2011,” and “2009–2011” correspond to “2008–2010,”2009–2010,” and “2010–2011,” respectively, the “Total” row is the accumulation of the first thirteen hazards sites, and does not include the last two.  
\end{table} 
Table 3: Each site’s geologic hazard area and variation rate. Figure 4: _Cont._  
Figure 5: Changes in the debris flow regions of site 1, 10, 14, 15 from 2008 to 2009 and from 2009 to 2011.
# Review of Web Mapping: Eras, Trends and Directions
## 4 Trends and Directions in Web Mapping
### Trends in Web Map Usage Components
#### 4.1.2 Web Mapping User Trends
organizations and applications embed the usage of web mapping and geospatial data into their organizations and web infrastructure. What can be identified as the possibly the most significant influence of web mapping developments on users is their contribution to enhancing and promoting collaboration. Users could, via online maps and mobile mapping devices, contribute data and information using Web 2.0 technologies, but more importantly, together participate in building and utilizing geospatial information for decision-making. Participatory GIS systems, involving the empowerment of communities through active input, access to and analysis using GIS, were enhanced by online mapping and geospatial analysis. [PERSON] [117] and [PERSON] [118] outlined how web mapping applications have had a significant positive effect on public participation in mapping. Public users can work collaboratively using online web maps to share and access data as well as be content providers via crowdsourcing and VGIS environments [58]. For example, GISCorps uses a community of volunteers engaged using online GIS to support humanitarian relief, community development, local capacity building, health and education. As of early 2017, they have deployed over 1000 volunteers from 50 countries to use online mapping to collaborate in 198 missions across 66 countries [119]. OpenStreetMap is a further example of a community of geospatial content providers for world data. More than three million contributors have generated almost four billion nodes, 40 million ways and five million relations [120]. Currently, an average of 30,000 active contributors per month generates over 1.5 million new nodes and ways per day in OpenStreetMap, as it can be derived from the OpenStreetMap Statistics Report [121]. Even as early as 2010, Wikimapia had over one million registered users contributing geospatial content [122]. By 2012, there were already over 17 million contributed locations and descriptions [122] with the total number of contributed objects being around 27 million by May 2017 [123]. Although web maps will continue to be used by end users, the trend is in the growth on the number of applications and systems that directly consume geospatial information and services. Geospatial information, semantics and analytics (see Section 4.1.1) will need to be consumed by applications that automatically discover, access, and use it. The end users will benefit from the greater level of knowledge and decision-making that will be undertaken in a semi-automated or even fully automated environment.
###### Abstract  
Underwater optical wireless communication (UOWC) has great potential to provide high-speed and intensive communications over short ranges underwater. However, the mobility of the UOWC system is limited by the strict alignment requirements between the transceivers. In this paper, a multi-degree-of-freedom (MDOF) UOWC system with high flexibility and improved transmission performance is proposed and experimentally demonstrated based on the off-the-shelf light-emitting diode (LED) source. A hardware pre-equalization circuit is employed at the transmitter to extend the modulation bandwidth from 5.03 MHz to 50 MHz. At the receiving end, a Fresnel lens array is constructed to achieve efficient convergence of multiple incident optical signals from different directions. To improve the underwater signal transmission quality, we designed an additional digital signal recovery module after the trans-impedance amplifier. Finally, an experimental system is established with a 460 nm blue LED. The communication reliability of the system is verified by the measurement of the eye diagram and the bit error rate of the recovered signal at the receiving end. The experimental results show that optical signals from three different incident directions with a maximum data rate of 100 Mbps are reliably transmitted over a 1.2-m-long water tank using the non-return-to-zero on-off-keying modulation format.  
underwater optical wireless communication; multi-degree-of-freedom; light-emitting diode; pre-equalization; lens array +
Footnote †: journal: _Mar. Sci. Eng._**2023**, _11_, 48. [[https://doi.org/10.3390/jmse11010048](https://doi.org/10.3390/jmse11010048)]([https://doi.org/10.3390/jmse11010048](https://doi.org/10.3390/jmse11010048))
## 3 Results and Discussion
### Feasibility of Applying Circular Economy Strategies to Different Building Types
#### 3.3.4 End-of-Life Stage  
The end-of-life stage was ranked fourth with a total score of 16. Participants acknowledged this stage as an important opportunity to recover value from materials and components through strategies like recycling, reuse, and repurposing. However, responses varied, with higher ratings contingent on how effectively CE principles were implemented in earlier stages. For example, A2 highlighted that \"_The end of life phase is where the building's circularity potential is truly tested. If the structure was not designed for disassembly or reuse, recovering materials becomes much more challenging and expensive._\" CN1 added that successful CE implementation at this stage depends significantly on decisions made during the design and planning phases. They stated, \"_Buildings that were not designed with circularity in mind often result in more waste and fewer opportunities for material recovery_\". C1, C3, and CT2 expressed concerns about the challenges of implementing CE principles at the end-of-life stage, with three believing that most of the product value is already lost by this phase. They acknowledged that recovering significant value can be particularly difficult for certain building materials and components. C1 argued that current practices, such as downcycling, often dominate at this stage and can be hard to move away from due to technical and economic constraints, and finally commented, \"_This may not align with higher-value circular strategies, it remains a practical solution in many cases_\".
## 2 Materials and Methods
### Data Analysis
#### 2.3.3 Semi-Automated RFF Estimation
Acoustic feature trends were then examined relative to HSV-derived voicing transitions as a function of the number of pitch periods (\"pitch period\" refers to the duration of one glottal cycle and was computed per /ifi/ production using the average \(f_{o}\) determined using Auditory-SWIPE\({}^{\prime}\)) away from the \"true\" boundary cycle; specifically, the true boundary cycle was set to reference the time of voicing offset (t\({}_{\text{off}}\)) and the time of voicing onset (t\({}_{\text{on}}\)) to investigate the relationship between these acoustic features and the physiologically derived termination and initiation of vocal fold vibration, respectively. To comprehensively examine trends in feature values, the acoustic features were analyzed as a function of \(\pm\)10 pitch periods from the true boundary cycle, resulting in 21 feature values (i.e., one feature value for each pitch period) for each of the 31 acoustic features per /ifi/. The feature values were then visually inspected to determine which acoustic features failed to exhibit a substantial change in feature magnitude (empirically chosen at >0.25 normalized feature units) and/or demonstrated a large standard deviation (empirically chosen at >2 standard deviations from the mean) in feature magnitude during the transition between the voiceless consonant and vowel; such features were removed from subsequent analysis. The remaining acoustic features were then used as predictors in a stepwise binary logistic regression to determine the probability of feature values corresponding to a voiced (1) or unvoiced (0) segment. The 21 values per acoustic feature for each of the 7721 /ifi/ productions were continuous predictors. Feature values were assumed independent in the regression model to identify which features were significantly related to voicing status rather than to create a regression equation for predicting voicing status. Variable significance was set to \(p\) < 0.05. Highly correlated features (variable inflation factor >10) were removed from the model to reduce multicollinearity. Acoustic features that exhibited significant predictive effects and were sufficiently independent were retained for further algorithmic refinement.
## 2 Security Protocols
### Network-Layer Security
HIP defines also an Host Identity Tag (HIT), a 128-bit representation of the HI based on the hash of HI plus other information, which can be used for example as unique host identifier at the existing IPv6 API and by application protocols. HIP defines also an HIP exchange that can be used between IP hosts to establish a HIP security association that in turn can be used to start secure host-to-host communications based on the (IPSec) ESP protocol [14]. In addition to security, HIP provides methods for IP multihoming and host mobility that are important features for an IP-based IoT network architecture. Some works are also being carried on to let the HIP exchange run on very constrained devices, by using proper public-key cryptographic primitives, for example the ones described in Section 3.
# Neural Architecture Search for a Highly Efficient Network with Random Skip Connections
## 4 Experimental Results
### Benefits Regarding Memory and Computational Power  
The use of less computational resources is an important performance criterion for a network. We compared our auto-generated network with the standard LSTM [15] and JANET, which comprises only one forgetting gate and can save resources remarkably well. Assuming the standard LSTM has \(n_{1}\) inputs and \(n_{2}\) hidden units, as declared in Westhuizen and Lasenby [4], the total number of parameters with the LSTM and JANET were \(4(n_{1}n_{2}+n_{2}^{2}+n_{2})\) and \(2(n_{1}n_{2}+n_{2}^{2}+n_{2})\), respectively. In our network (see Equation (3)), the numbers were as follows: \(f_{t}\): \(n_{1}n_{2}+n_{2}\), \(i_{t}\): \(n_{2}^{2}+n_{2}\), and others: \(1+n_{1}n_{2}+n_{2}\); therefore, the total number was \(n_{2}^{2}+2n_{1}n_{2}+3n_{2}\). Typically, the values are dominated by the \(n_{2}^{2}\) term since the hidden units number \(n_{2}\) is usually much larger than the input size \(n_{1}\). The memory requirements lie in approximately the same range as the parameter numbers [4]. As for the computational power, [PERSON] et al. [20] demonstrated that the LSTM matrix and element-wise multiplication occupy roughly half of the computation, and JANET requires roughly \(\frac{5}{6}\) of the amount of LSTM. In our network, there are no matrix nor element-wise multiplication operations with the output gate, hence the ratio to the LSTM is about \(\left(\frac{n_{1}}{n_{1}+n_{2}}\times\frac{1}{4}+\frac{2n_{2}}{n_{1}+n_{2}} \times\frac{1}{4}\right)\times\frac{1}{2}+\frac{2}{3}\times\frac{1}{2}=\frac{ n_{1}+2n_{2}}{8(n_{1}+n_{2})}+\frac{1}{3}\); if \(n_{1}\) is small enough compared to \(n_{2}\), and hence ignorable, the ratio equals \(\frac{3.5}{6}\), and if \(n_{1}\approx n_{2}\), it roughly equals \(\frac{3.1}{6}\). In both cases, a large amount of computational power is saved.
# Multiscale YOLOv5-AFAM-Based Infrared Dim-Small-Target Detection
## 2 Methods
### Multiscale YOLOv5-AFAM
#### 2.2.2 Improved Downsampling Module  
Due to the low resolution of infrared images and the blurring of targets, it becomes difficult to extract features such as edges and textures of targets. Our proposed downsampling module (DownC) in YOLOv5 can effectively expand the receptive field, reduce the number of parameters to be learned, and prevent overfitting during training.  
To preserve more information while extracting the feature map, we design DownC to improve the downsampling method. Our design follows two principles. (1) Maxpool Layer can reduce computational burden and preserve the texture features better. (2) A learnable convolution layer with a corresponding step size can retain more information.  
As shown in Figure 4, DownC consists of two branches for downsampling operation. The first branch is an \"All-Conv\" branch, while the second branch is a \"MaxPool-Conv\" branch. To concatenate the features of two branches and keep the number of channels unchanged, the channel of each branch is halved. Specifically, the \"All-Conv\" branch contains two Conv modules. The stride of the first Conv module is set as 1 so that the number of channels is halved. The \"MaxPool-Conv\" branch first uses a MaxPool operation and then applies a \(1\times 1\) Conv module. Similar to the \"All-Conv\" branch, the Conv module set stride as 1 to halve the channel number. Compared to YOLOv5's Conv module with step size 2, DownC has less computation and retains the maximum pooled texture feature information.  
Figure 4: The structure of DownC module.
# Automatic Modulation Classification Using Hybrid Data Augmentation and Lightweight Neural Network
## 3 Our Proposed AMC Method
### Framework of the Proposed AMC Method  
The framework of the proposed AMC method is shown in Figure 2. Our proposed AMC method is composed of a training process and a testing process. In the training process, the parameters of an excellent lightweight network are trained using a hybrid DA method. In the testing process, the lightweight network is used for modulating signal classification.
# Vertical GaN MOSFET Power Devices
###### Abstract  
Gallium nitride (GaN) possesses remarkable characteristics such as a wide bandgap, high critical electric field, robust anriradiation properties, and a high saturation velocity for high-power devices. These attributes position GaN as a pivotal material for the development of power devices. Among the various GaN-based devices, vertical GaN MOSFETs stand out for their numerous advantages over their silicon MOSFET counterparts. These advantages encompass high-power device applications. This review provides a concise overview of their significance and explores their distinctive architectures. Additionally, it delves into the advantages of vertical GaN MOSFETs and highlights their recent advancements. In conclusion, the review addresses methods to enhance the breakdown voltage of vertical GaN devices. This comprehensive perspective underscores the pivotal role of vertical GaN MOSFETs in the realm of power electronics and their continual progress.  
GaN power device; MOSFET; breakdown voltage; specific on-resistance; electric field +
Footnote †: journal: Micromachines