esa-sceva/satcom-chunk-collection huggingface dataset:
# Minimally-Invasive Neural Interface for Distributed Wireless Electrocorticogram Recording Systems
## 1 Introduction
Recently, a 64-channel ECoG recording chip with an RF-based data transmission and power harvesting has been presented to overcome those limitations [5]. Although it exhibited the state-of-the-art power consumption (2.3 uW/Ch and 225 uW for total power consumption), there were drawbacks. It showed a significant channel-to-channel gain variation from their open-loop architecture which requires off-chip calibration upon start-up. Also, its front-end gain is limited due to the low supply voltage which was chosen to reduce power consumption [5]. Still, there are numerous technical challenges to be addressed in order to accomplish a reliable, fully-functional ECoG neural interface system. Low-power analog front-end circuits should be combined with wireless data telemetry in a small form factor with modular expandability for high channel counts. We present a minimally invasive neural interface for multi-channel wireless ECoG recording by using the intra-skin communication (ISCOM) [8]. The wireless data transmission through ISCOM can provide multi-channel recording in a distributed system for a behaving animal. Moreover, the interface system can be all-in-one since it equips all necessary electronic components and units inside a small implantable platform, including a microelectrode array, an energy harvesting coil, and a rechargeable battery, an analog frontend, and an ISCOM wireless transceiver. In this paper, we focus on describing the design and implementation of low-power integrated circuits (ICs) suitable for the proposed wireless ECoG recording system. The implemented IC is the core unit that enables the recording of 16-channel of ECoG signals with high power-noise efficiency while providing a wireless ISCOM in combination of the custom-microfabricated flexible ECoG electrode array. This paper is organized as follows. Section 2 describes the overall architecture of the proposed system. Section 3 presents the details of IC design and implementation including a noise-power efficient double-gated push-pull preamplifier, a low-voltage successive approximation register analog-to-digital converter (SAR ADC), an on-chip programmable voltage/current reference generator, and a wireless ISCOM module. In Section 4, the design and fabrication of the flexible microelectrode array is given. In Section 5, the results of 16-channel in vivoECoG measurements from a primate is presented, followed by the bench-top characterization of the fabricated IC. Finally, Section 6 concludes this paper.
# Intelligibility and Listening Effort of Spanish Oesophageal Speech +
## 2 Literature Review
### Listening Effort  
LE has been measured in several contexts where the listeners have to put in extra investment of their neurocognitive resources. This includes understanding of distorted speech signals. Distortion can come from the speaker (e.g., foreign accent, impaired speech), the listener (e.g., hearing impairment) or from the environment or channel (e.g., noise).  
LE has been measured in several ways: Self-reporting (questionnaires, ratings); behavioural measures (performance of single tasks, multiple tasks and deriving LE from them); and physiological measures (electroencephalography, pupillometry). A review of LE and various methods of measuring LE is presented in [22].  
While there is research on LE in the context of speech in noise [23], non-native or accepted speech [24; 25], and hearing impairment [26], LE of impaired speech is a less researched field, and physiological LE measurements, even less so.  
Amongst pathological speech, we found some LE research for dysarthric speech. [PERSON] and [PERSON] [27] conducted a listening experiment to collect LE ratings, and found segmental features and factors of voice quality to be the predictors of LE ratings. The authors of [28] found that severity of speech impairment and listener familiarity had an effect on 'ease of listening'. In [29], words spoken by children with dysarthria were presented and listeners performed a word recognition and subjective LE rating task. The response time (time taken to recognise the words) was a significant predictor of the subjective LE ratings. Words with high accuracy in recognition had shorter response times and lower LE ratings.  
We found some research that looked into some subjective processing load-based measures of OS. In [30] the authors measured the acceptability of OS, ELS, and HS. They found that HS was the most acceptable, followed by superior OS and then ELS. In [31], high-intelligibility TOS was played to listeners and they were asked to rate the effort of listening as well as acceptability for each sample and found an inverse correlation between LE and acceptability. Another observation from this study was that even highly intelligible speech can have varying listener effort. We have followed this thread in our second experiment (Section 4).  
Therefore, by measuring LE for OS, we hope to expand the literature on processing load-based measurements of impaired speech as well as gain an understanding of OS on a dimension beyond intelligibility.
## 2 Materials and Methods
### Data
#### 2.1.2 Ceres-Ebaf  
The Clouds and the Earth's Radiant Energy System--Energy Balanced and Filled (CERES-EBAF) product provides 1-degree latitude-longitude global monthly mean shortwave, longwave and net fluxes, at the Top-of-Atmosphere and at the Earth's surface, under clear and all-sky conditions. CERES instruments are onboard the Terra, Aqua, Suomi National Polar-Orbiting Partnership (SNPP) and NOAA-20 satellites. Each instrument measures filtered radiances in the shortwave (between 0.3 and 5 \(\upmu\)m), total (between 0.3 and 200 \(\upmu\)m), and window (between 8 and 12 \(\upmu\)m) regions [80]. The filtered radiances are transformed to unfiltered shortwave, longwave and window radiances following the [81] scheme, which then are converted to instantaneous TOA radiative fluxes using empirical angular distribution models [82]. These instantaneous TOA fluxes are spatially averaged on a 1\({}^{\circ}\) equal-area grid and interpolated between observed values at 1-h increments for each hour in coordinated universal time (UTC) of every month, and finally averaged over all hour boxes in a month [83]. CERES-EBAF data span the period from March 2000 to the present and produce a long-term, integrated global climate data record for detecting decadal changes in the Earth's Radiation Budget from the surface to the Top of Atmosphere together with the associated cloud and aerosol properties. Here we use the EBAF Edition 4.1 level 3b Top of The Atmosphere monthly mean shortwave flux under all-sky conditions, named \"toa_sw_all_mon\", for the period July 2000-June 2020. The data can be ordered and freely obtained at [84].
## 4 Results  
### Microscopic Mineral Identification and Alteration Zonation  
The main minerals in this sampling cross-section were magnetite, chlorite and garnet, with a small amount of quartz. The magnetite was black and massive. There were two types of magnetite, one of which was fine grained and denser with high iron content, and the other coarse grained, euhedral and with low content (Figure 6a,b). The main altered rocks closely related to the mineralization were dark green, and were mainly composed of garnet and chlorite. From the high-grade iron ore to the periphery, the garnet in the alteration wall rocks gradually decreases, while the chlorite increases. According to the hydrothermal minerals and their paragenesis, the alteration types can be classified into three categories, i.e., the proximal chlorite-garnetization, the transitional garnet-chloritization and the distal chloritization (Figure 6).  
Figure 5: Spectral curves of different rock types and standard spectrum: (**a**) quartz; (**b**) chlorite; (**c**) garnet.  
Proximal to the high-grade iron ore body, G 05 is the chlorite-garnetite, and garnet accounts for more than 75%. It is stratiform and occurred in the top and bottom of the high-grade iron body. Garnet is broken, fleshy red, subhedral-anhedral and has no zoning structure. Quartz and magnetite are mostly scattered in the garnet. Chlorite is mainly disseminated around garnet or in the cracks. Chlorite is mostly dark green or yellowish green (Figure 6c).  
In transitional zone, G 06 is the garnetic chlorite, mainly composed of garnet, chlorite and a small amount of quartz and magnetite. The chlorite is greenish to dark green and accounts for more than 60% of total content of the rock. Usually the chlorite is scattered within garnet in the form of stockwork.  
Figure 6: Photomicrographs showing the representative mineral assemblage and texture of iron ore and wall-rock from the Gongchangling number 2 mining area. (**a**) high-grade magnetite (Mag) under a reflected light microscope; (**b**) magnetite of large grain size (**c**) chlorite garnetite consisting of garnet (Grt) and chlorite (Chl), showing porphyoblastic texture (plane-polarized light); (**d**) garnetic chlorite; (**e**) and (**f**) chloritite.  
The garnet is subhedral-anhedral, relatively small and grayish brown. In most cases, the content of garnet in this alteration zone is less than 30% (Figure 6d).  
G 07 belongs to the distal chloritite zone, and mainly consists of dark or emerald green chlorite (more than 75%) with a variable amount of garnet debris (less than 20%), whose grain size is too small to be recognized by naked eyes. Occasionally there occur small amounts of magnetite and quartz. Magnetite usually scatters in chlorite. As shown in red box in Figure 6e, some garnet is probably metasomatized into chlorite, especially at the boundary (Figure 6e,f).
## 2 Rf Model: Simulation Results vs. Experimental Measurements
### Quality Factor  
The unloaded quality factor \(Q_{0}\) has been determined from the 3 dB bandwidth measurement made with a Vector Network Analyzer (VNA). As expected also from other analyses in literature [15; 16; 22; 23], the measured quality factor is less than the simulated values due to many factors: sliding contact, losses to brazed and welded joints, temperature increase, surface oxidation and cleaning, etc. A mismatch ranging from 16 to 30% is shown in Figure 9.
# GAO-FCNN-Enabled Beamforming of the RIS-Assisted Intelligent Communication System
## 5 Conclusions  
This paper focuses on the study of effectively solving the problem of BER optimization of joint beamforming in the RIS-assisted intelligent communication system. A hybrid optimization strategy of GAO-FCNN is proposed to realize the intelligent collaborative tuning of system parameters and to avoid convergence of the local optimum. Numerical results demonstrate significant SNR gains when compared to the other RIS-assisted intelligent communication systems. In future practical applications, more investigations should be performed to the optimization learning of the broadband multi-user RIS-assisted system.  
Conceptualization, K.C.; methodology, K.C.; software, K.C.; validation, T.L. and X.W.; formal analysis, T.L.; investigation, K.C. and X.W.; resources, K.C.; data curation, K.C.; writing--original draft preparation, K.C.; writing--review and editing, T.L. and X.W.; visualization, K.C.; supervision, K.C. and T.L.; project administration, K.C. and T.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by NSFC (62101274) and Jiangsu NSF (BK20210640).  
Data Availability Statement: Data are contained within the article.  
The authors would like to thank all authors of their fundings.  
The authors declare no conflicts of interest.  
Figure 7: The loss value of different training methods.
# A Web-Based BIM-AR Quality Management System for Structural Elements
## 6 Conclusions and Future Work  
In this paper, a comprehensive approach for QM has been proposed by integrating BIM and AR technology. Exploiting advantages and help from the potentials of BIM and AR and their integration, a system has been developed for acquiring inspection data, processing the results, and facilitating collaboration among the actors involved in QM, through the web. The approach has been implemented and a preliminary test has been carried out on a real building project to study the efficiency and effectiveness of the system.  
The results confirm that objectives such as delay reduction, quality improvement, and cost optimization can be pursued through the proposed quality management system. The produced web-based checklist makes the access to updated information easier, by improving the communication between the involved parties. Moreover, the quality dashboard summarizing the results, combined with the color-coded model, gives an overview of the current quality status of the project both in qualitative and quantitative terms.  
Figure 14: Examples of problematic behaviors: occlusion of the real objects by the wall model (**left and middle**) and positioning accuracy problems (**right**).  
In the frame of the experimental approach followed for the proposed methodology check, difficulties also encountered during the testing phase can be considered to be positive outcomes, and the seeds for further considerations and research work.  
Regarding possible future developments to optimize the proposed approach for integrating BIM and AR for QM purposes, a more stable and accurate positioning of the AR platform would improve the experience, offering the possibility to add tools to measure and record the as-built situation for real-time comparisons with the designed plan and make the control of geometric quality parameters more efficient. Furthermore, other improvements could be represented by a priority index for each defect, ranking its influence on the others, and by a feature allowing superimposition of the model onto the appropriate LOD (Level Of Detail), to avoid visualizing too many details, and to make the AR experience better.  
Conceptualization, M.M. and C.I.D.G.; Methodology, M.M. and C.I.D.G.; Software, M.M.; Validation, M.M. and C.I.D.G.; Formal analysis, M.M. and C.I.D.G.; Investigation, M.M.; Writing--original draft preparation, M.M., C.I.D.G. and F.M.; Writing--review and editing, C.I.D.G. and F.M.; Visualization, M.M. and C.I.D.G.; Supervision, C.I.D.G. and F.M.  
This research received no external funding.  
The authors declare no conflict of interest.  
List of quality parameters for the control of the material of a concrete structure.
## 5 Performance Analysis
### Impact of Different Hyperparameter Configurations  
We carried out further studies on the PEMS04 and PEMS08 datasets to thoroughly assess the impact of hyperparameter settings. The ADDGCN model has only one hyperparameter related to its structure, which is the number of feature channels. This is because we did not use the strategy of stacking repeated modules to capture features. Results from experiments indicate that the effectiveness of the ADDGCN model is significantly affected by the number of feature channels as illustrated in Figure 8 [46]. However, adding more feature channels does not always result in an improvement in the performance of ADDGCN. Once the quantity of feature channels reaches a particular value, the performance  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**PEMS04**} & \multicolumn{3}{c}{**PEMS08**} \\ \hline  & **MAE** & **MAPE** & **RMSE** & **MAE** & **MAPE** & **RMSE** \\ \hline without DGCN & 24.45 & 16.60 & 37.99 & 20.15 & 12.83 & 30.95 \\ \hline without Down-sampling Conv & 21.93 & 14.72 & 34.17 & 17.57 & 12.06 & 27.30 \\ \hline without Adapt adjacency (\(A_{opt}\)) & 18.92 & 12.69 & 30.56 & 14.63 & 9.51 & 23.71 \\ \hline without Graph Generator (\(A_{L}\)) & 18.82 & 12.84 & 30.44 & 14.62 & 9.62 & 23.62 \\ \hline without Feature Augmentation & 18.69 & 12.87 & 30.23 & 14.52 & 9.52 & 23.56 \\ \hline ours ADDGCN & 18.62 & 12.43 & 30.11 & 14.50 & 9.49 & 23.49 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The impact of different components on ADDGCN prediction performance on the PEMS04 and PEMS08 datasets.  
of ADDGCN stabilizes. For the PEMS04 dataset, we found that the ADDGCN model performs best when the quantity of feature channels is approximately 64. On the other hand, for the PEMS08 dataset, the optimal number of feature channels is around 32. It is crucial to remember that the training time considerably rises along with the number of feature channels. As a result, we ultimately determined the number of feature channels in ADDGCN to be 32. This choice achieved a reasonable balance between training time and model performance.
# Recent Developments in Modulation Spectroscopy for Methane Detection Based on Tunable Diode Laser
## 4 Application of Modulation Spectroscopy for Methane Detection
### Frequency Modulation Spectroscopy Applied for Methane Detection
#### 4.2.3 Optimization of Methane Detection Based on FMS  
Some researchers [115; 116; 117] have tried to improve the performance of methane sensors based on QCLs in several ways. For example, a fast optical modulation was achieved by introducing an fs NIR pulse train in a typical QCL, which was different from the traditional modulation method by temperature tuning or current injection [115]. The FM was obtained at frequencies up to 1.67 GHz, which was a benefit to get higher sensitivity of detection. [PERSON] et al. [116] found out that the FM technique with QCLs at terahertz (THz) frequencies was suitable for high-resolution molecular spectroscopy. Then DFB QCLs, as the radiation source, were used to set up THz spectrometers [116; 117]. The investigated molecular parameters such as transition frequency and pressure broadening of CH\({}_{3}\)OH were presented.
# Theory and Design of Blink Jamming
## 3 Modelling Formation Jamming
### Jammers and Target RF Models  
Both jammer sources were modelled as point targets travelling from their initial position at a constant velocity. During the course of the Electronic Attack (EA) development and optimization process this was confined to a separation that put the two jammers within a formation of several hundred meters, inside the main lobe of the monopulse antenna. The distance of less than a kilometer replicates several possible formation jamming configurations including active and towed decoys, as well as chaff illumination jamming.  
The jammers were developed to allow for several techniques to be evaluated: continuous illumination, blink jamming, and an amplitude modulated blink jamming attack, all with an adjustable jammer-to-signal ratio (this allowed for the skin return's impact to be evaluated).  
The jammer system, shown in Figure 7, is separated on the left and right into the two jammers with adjustable frequencies for the blink jamming attacks. The standard blink jamming attack's envelope is created using a square wave of adjustable duty cycle. Similarly, the sinusoidal blink jamming attack uses the standard blink waveform, multiplied by a sinusoid of the same frequency.  
The selected formation jamming technique was then combined with the skin return and White Gaussian Noise (WGN) to reflect the signal-to-noise ratio of the monopulse receiver. The transmitter RF parameters were then embedded in a vector signal with the waveform, to allow the receiver to calculate the RF power received for each signal.  
Figure 6: The monopulse tracking radar model Field Programmable Gate Array (FPGA) implementation and testbed in Simulink.
## 3 Challenges in Terahertz-Based FSO Communication
### Manufacturing Challenges in THz Communication
#### 3.6.4 Packaging and Integration of THz Systems  
THz components must be seamlessly integrated into compact, high-performance systems while ensuring thermal stability and electromagnetic shielding. Unlike traditional RF and optical systems, THz circuits require the precise alignment of photonic and electronic elements, which significantly increases their manufacturing complexity and costs. The transition toward the monolithic integration of THz photonics and electronics (e.g., THz CMOS and III-V semiconductors) could address these challenges but demands significant advancements in hybrid chip fabrication and interconnect technology [73].
## 3 Results and Discussion
### Determination of Relevant Visual Information
#### 3.2.7 Live Video or Graphical Display of Information  
A majority of participants indicated a preference for retaining important visual information in the format of live video on a hypothetical automation interface for remotely supervising an autonomous agricultural machine. For clips 1 and 2 (perceived to display the most important information), participants noted that it would be difficult to perceive the same information if they were replaced with graphical displays. However, they indicated that replacing clips 3, 5, 6, and 7 with a graphical display would not have any substantial impact on their ability to operate the sprayer. This divergent result may be due to the fact that most participants did not perceive any valuable information from the latter set of clips. Observed results from several of the other clips (i.e., clips 4, 8, 9, and 10) is more difficult to interpret. In-depth analysis revealed that the participant's response to this question was related to the information perceived from the clip. For example, in clip 8, some participants identified relevant information such as spray drift, spray pattern, and backing up; these aspects of sprayer operation might be difficult to portray on a graphical display, perhaps leading these participants to prefer live video. For the same video clip, other participants reported no substantial impact when replacing live video with a graphical display. These participants identified features such as wheel alignment or following a previous wheel track--features that could perhaps be displayed more easily using a graphical display. Overall, experienced sprayer operators reported higher preference for presenting  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Clip** & **General Description** & **\textless{} 5 Years Experience** & **5-15 Years Experience** & **\textgreater{}15 Years Experience** \\ \hline \multirow{3}{*}{8} & Back of sprayer & \multirow{3}{*}{Nozzle status, nothing.} & Nozzle status, spray & Sprayer is operating, field & \multirow{3}{*}{
\begin{tabular}{} \end{tabular} } \\  & driving up a field. & & & \\ \cline{1-1}  & & Nozzle status, nothing. & & \\ \cline{1-1}  & & Nozzle status, wrong & & \\ \  
visual information on an automation interface using live video than presenting that same information using some type of graphical display.
# Minimized Triple-Band Eight-Element Antenna Array for 5G Metal-frame Smartphone Applications
## 2 Antenna Geometry  
The detailed geometry of the proposed triple-band eight-element array for 5G metal-frame smartphone applications is shown in Figure 1. There are two kinds of PCBs in the proposed MIMO antenna, including the mainboard and two sideboards. The dimensions of the mainboard and the sideboards are 150 mm \(\times\) 75 mm \(\times\) 0.8 mm and 150 mm \(\times\) 6.2 mm \(\times\) 0.8 mm, respectively. The system ground plane is printed on the bottom of the mainboard. In addition, there is a metal frame on the edge plate of each sideboard. The eight antenna elements are printed on the two sideboards which are placed vertically to the mainboard. The sideboards and mainboard are all printed on a FR4 substrate with \(\varepsilon_{\tau}\) = 4.4, and tan\(\delta\) = 0.02, which are bonded to each other by tin. Each antenna is fed with a 50-\(\Omega\) microstrip feedline and a SMA connector via a hole from the backside of the main substrate. The proposed antenna array has advantages of small volume (the single antenna element is only 6.5 mm \(\times\) 7 mm) and triple-band operation (the \(-\)6 dB impedance bandwidth can fully cover 3.3-3.8 GHz, 4.8-5 GHz, and 5.15-5.925 GHz). Furthermore, a side view of the four antenna elements is given in Figure 1b. The values of the parameters are: L = 6.5 mm; H = 7 mm; D = 22.5 mm; d34 = d12 = 21 mm; d23 = 37 mm; D34 = D12 = 27.5 mm; and D23 = 46 mm.  
Figure 1: _Cont._