esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Sensitivity Analysis  
The relative importance of parameters in modeling of pressure drop \(\Delta P\) was determined through a sensitivity analysis, which was performed by generating a randomized combination of input parameters (\(v_{a}\), \(H_{b}\), \(\varepsilon\), \(d_{e}\), \(\rho_{a}\), \(\mu_{a}\)) of Equation (9) within their range of operating conditions and evaluating their impact on pressure drop \(\Delta P\). Figure 7 presents the standardized regression coefficients of sensitivity analysis, with parameters ranked by influence. Results of the analysis indicated that air velocity \(v_{a}\) is the most influential parameter, which significantly influences the pressure drop \(\Delta P\) due to its contribution to energy dissipation of air pathways due to friction and turbulence. A value of 0.85 was obtained, indicating how decisive \(v_{a}\) is for the airflow resistance and aeration process of wheat bulk. Therefore, bulk depth \(H_{b}\) makes a considerable contribution in \(\Delta P\), where a value of 0.47 was observed, demonstrating a relatively weaker influence (\(-44.71\%\)) compared to  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Storage Time \(t\), h** & **Mathematical Model** & \(\mathbf{R^{2}}\)**, -** \\ \hline
1 & \(\varepsilon=\varepsilon_{0}-(\varepsilon_{min})\cdot(1+0.292H_{b}-1.026)\) & 0.987 \\
65 & \(\varepsilon=\varepsilon_{0}-(\varepsilon_{0}-\varepsilon_{min})\cdot(1+0.238 H_{b}-0.851)\) & 0.977 \\
164 & \(\varepsilon=\varepsilon_{0}-(\varepsilon_{0}-\varepsilon_{min})\cdot(1+0.205H _{b}-0.733)\) & 0.963 \\
236 & \(\varepsilon=\varepsilon_{0}-(\varepsilon_{0}-\varepsilon_{min})\cdot(1+0.156H _{b}-0.557)\) & 0.980 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Mathematical models for describing pore volume \(\varepsilon\) as function of bulk height \(H_{b}\) at different storage times \(t\).  
airflow velocity \(v_{a}\). Noticeably, \(v_{a}\) and \(H_{b}\) are positively correlated with \(\Delta P\), therefore higher values of velocity or bulk depth result in the increase of pressure drop with the magnitude determined by the analysis. Pore volume \(\varepsilon\) and particle diameter \(d_{e}\) were identified as less decisive, which negatively affect \(\Delta P\) with values of \(-0.18\) and \(-0.15\), respectively. They are responsible for the bulk configuration, therefore, their reduction increases the resistance to airflow and consequently increases the pressure drop \(\Delta P\). The parameters that had the least influence were air density \(\rho_{a}\) (0.05) and dynamic viscosity of air \(\mu_{a}\) (0.01) which were affected by the minor variations of temperature \(T_{a}\) and relative humidity \(\varphi_{a}\) of the air passing through the grain bulk.
# A Deep Learning Approach to Predict Autism Spectrum Disorder Using Multisite Resting-State fMRI
## 4 Conclusions  
In this paper, a deep learning approach using multisite resting-state fMRI was introduced to predict ASD. ASD detection is a challenging task since no standard modeling choice has yet been recognized, and the current practice is very much diverse. In this paper, preprocessed fMRI data were obtained from the CPAC pipeline. To extract mean BOLD signals from preprocessed data, brain atlases were used. A single brain atlas that can serve as a biomarker for the detection of ASD has not yet been discovered. Thus, four different standard and predefined atlases were used to extract ROIs. Connectivity matrices were prepared using tangent embedding and flattened to form a feature vector removing redundant information. This feature vector was provided as input to our proposed model. Hidden layer configuration of the model was also varied, and its impact on detection observed. After performing a wide array of experiments, it has been confirmed that the BASC atlas using 122 ROIs yields higher predictive power than AAL, CC200, or Power atlases and can be considered to be more reliable in ASD diagnosis. It achieved 88% accuracy, 90% sensitivity, 87% F1-score, and 96% area under receiver operating characeristic curve. This result transcends most of the performances of existing works indicating that it is a promising method for ASD diagnosis. The successful implementation of this method may be used for a wide range of applications, such as identifying neural activation patterns responsible for autism and performing visual evaluation of the functional characteristics of the autistic brain. By examining the contrast between the autistic and control brain, the underlying neural or biological basis of ASD can also be unveiled and established.  
Conceptualization, K.D.; Data curation, F.Z.S.; Formal analysis, F.Z.S.; Funding acquisition, P.K.D. and T.K.; Investigation, F.Z.S.; Methodology, F.Z.S.; Software, F.Z.S.; Supervision, K.D.; Validation, F.Z.S.; Visualization, F.Z.S.; Writing--original draft, F.Z.S.; Writing--review & editing, K.D., P.K.D., and T.K. All authors have read and agreed to the published version of the manuscript.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Methods** & **Year Published** & **Accuracy (\%)** \\ \hline [PERSON] et al. [53] & 2017 & 66.80 \\ [PERSON] et al. [37] & 2018 & 70.00 \\ [PERSON] et al. [38] & 2019 & 70.30 \\ [PERSON] et al. [54] & 2020 & 74.52 \\ [PERSON] et al. [55] & 2020 & 75.27 \\ [PERSON] et al. [39] & 2020 & 74.00 \\ Our Proposed Model & – & 87.87 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Performance comparison with existing literature.
# Drone Deployment Algorithms for Effective Communication Establishment in Disaster Affected Areas
## 3 Proposed Methods
### Proof That Our Method Uses the Minimum Number of Drones
#### 3.6.6. The Region Filling-Algorithm Minimizes the Number of Drones Required  
After filling the first layer, the starting circle of the next layer is filled using _ThreeNeighbours_, followed by filling along the inner \(x\)-direction and \(y\)-direction. This process continues until the stopping condition is met. As it is proven that the procedures used by the region-filling algorithm distribute wastage of coverage equally and minimize the required number of drones, the combination of these procedures results in the minimum number of drones.
## 1 Introduction  
Lithium is the lightest metal element in nature, which is widely used in daily life, aviation, medicine, the chemical industry, high-energy batteries and thermonuclear reactions, and is known as an \"energy metal to promote world progress\" [1; 2]. With the popularity of electric vehicles, the global demand for lithium is increasing [3; 4; 5; 6], and traditional lithium resources [7; 8; 9] are far from meeting market demand [10]; therefore, it is urgent to find new unconventional lithium resource supply channels.  
Coal fly ash (CFA) is considered as a substitute for lithium resources [11; 12; 13]. As one of the solid wastes produced by coal-fired power plants, CFA has the characteristics of flammability, corrosiveness, reactivity and toxicity, which are difficult to treat and pose a threat to the environment and public health [14; 15]. Although CFA is currently used in soil improvement, the construction industry, the ceramic industry and zeolite synthesis [16; 17; 18], its overall high-added utilization rate is low, so recovering lithium from CFA can not only alleviate the shortage of lithium resources and improve the utilization value of CFA but also reduce the environmental pollution caused by CFA.  
At present, the processes for leaching lithium from CFA mainly include acid leaching [19; 20; 21], water leaching [22] and alkali leaching [23; 24]. The resin adsorption method [25; 26] and solvent extraction [27; 28] are mainly used to extract lithium from low lithium concentration solutions. Compared with the solvent extraction method, the resin adsorption method has a simpler technological process and less environmental pollution. However, the adsorption effect of resin on high-valence ions in solution is better than that of low-valence ions. In solutions where several ions coexist, the resin gives priority to high-valence ions and then lithium ions, which significantly affects the efficiency of lithium extraction.  
In the present study, desiliconized CFA (DCFA) is considered as a potential supply channel for lithium resources. DCFA has lower silicon content, and its chemical characteristics are more suitable for lithium adsorption and recovery than CFA [20]. Through orthogonal experiment and single factor experiment, the influencing factors of the preparation of a manganese dioxide lithium ion sieve were investigated, including the mass ratio of manganese dioxide to lithium hydroxide, roasting temperature, roasting time, HCl concentration, soaking time and stirring time. At the same time, the effects of adsorption time, pH of NaOH solution and scrubbing time on lithium adsorption efficiency, and the effects of HCl concentration and elution time on lithium elution efficiency were investigated. By preparing a manganese dioxide lithium ion sieve and optimizing the adsorption and elution process conditions, the interference problem of multiple ions coexisting can be effectively solved, and the efficient adsorption and recovery of lithium can be realized.
# Mitigation of Electro Magnetic Interference by Using C-Shaped Composite Cylindrical Device
###### Abstract
The most practical way to increase the shielding effectiveness (SE) is the improvement of absorption loss [25]. It is well-known that high-permeability materials such as permalloy materials have an excellent shielding capability [26]. On the other hand, current-carrying electric coils certainly establish an electromagnetic field around itself [27]. If the electromagnetic field from the source can be minimized, the maximum SE for the productivity of high-performance tools could be achieved. Therefore, in this study, the passive shielding method was combined with the active shielding methodology to mitigate the electromagnetic fields on the target space with a higher efficiency by wrapping passive shielding materials with a C-shaped cylindrical device around the coils of the active shielding system. In this study, the tubular structure was suggested to collect all electromagnetic fields around power cable lines. Presumably, the C-shaped cylindrical structure with high-permeability materials emits an electromagnetic field to the opening space for a better shielding design [28; 29]. A similar shape effect can be observed in U-type barium hexaferrite-epoxy composites [30] and hollow conducting tubes [31].
## 5 Comparative Analysis
### Limited Use of Machine Learning in the Maritime Industry  
While Machine Learning (ML) has significantly permeated various industries, its adoption in the maritime industry remains relatively limited. This discrepancy largely stems from industry-specific complexities and challenges that impede the widespread use of ML.  
The maritime sector is a traditionally entrenched industry with well-established processes and systems, many of which are manual and involve high degrees of human intervention. Consequently, the integration of ML, which requires the digitization and automation of processes, faces inherent resistance. Furthermore, ML thrives on large datasets for training, which are often scarce in the maritime industry due to data privacy concerns and the lack of consistent data collection and management protocols.
## 2 Methodology and Experiments
### Fabrication of the Hierarchical Micro/Nanostructure  
To create a hierarchical micro/nanostructure, a gold thin film with a thickness of 100 nm was first deposited on micro-pyramids using a dc magnetron sputtering system (Cressington 108 Sputter Coater). The wafer with the gold film deposited was diced into \(15\times 15\) mm chips before the electrochemical treatment. The chip was then attached to a glass slide and wire connected as shown in Figure 1c. The conductive wire was covered with silicone to prevent reaction with electrolyte. The chip (working electrode) was then immersed in the KCL solution along with a counter electrode (platinum) and a reference electrode (Ag/AgCl). The sample was then electrochemically treated by applied oxidation and reduction cycles to form the nanostructure on the surface of the gold thin film. The electrochemical treatment was performed by using a VidaBio VS1 electrochemical potentiostat with a voltage sweep range of \(-800\) mV to \(800\) mV, voltage sweep rate: \(50\) mV/s, oxidation and Reduction cycles from \(1\) to \(15\) cycles in a KCL solution with a concentration of \(0.2\) mol/L. The micro-pyramids combined with the nanostructured gold thin film formed the hierarchical micro/nanostructure. The fabrication process of the described micro/nano hierarchical structure is illustrated in Figure 1.
# Key Technologies in the Context of Future Networks: Operational and Management Requirements
###### Abstract  
The concept of Future Networks is based on the premise that current infrastructures require enhanced control, service customization, self-organization and self-management capabilities to meet the new needs in a connected society, especially of mobile users. In order to provide a high-performance mobile system, three main fields must be improved: radio, network, and operation and management. In particular, operation and management capabilities are intended to enable business agility and operational sustainability, where the addition of new services does not imply an excessive increase in capital or operational expenditures. In this context, a set of key-enabled technologies have emerged in order to aid in this field. Concepts such as Software Defined Network (SDN), Network Function Virtualization (NFV) and Self-Organized Networks (SON) are pushing traditional systems towards the next 5G network generation.This paper presents an overview of the current status of these promising technologies and ongoing works to fulfill the operational and management requirements of mobile infrastructures. This work also details the use cases and the challenges, taking into account not only SDN, NFV, cloud computing and SON but also other paradigms.  
5G; future network; NFV; SDN +
Footnote †: journal:  
_Future Internet_
## 1 Introduction  
Cycling is becoming an increasingly popular activity with subsequent increase in overuse injury occurrence [1]. This has resulted in a higher number of physiotherapy and sport science specialists working in the field to prevent and treat the injured cyclists using advanced diagnostic approaches in a process of adjusting body position (i.e., bike fitting), off-the-bike assessment, and equipment optimization [2]. Cycling is also frequently used during rehabilitation in a clinical setting [3].  
Most overuse injuries in cycling occur due to repetitive high loads applied to the joints. These loads normally excel when riding in low gear, long uphill riding, or with incorrect body position [4, 5]. Along the entire kinetic chain, the knee is the most affected joint [6], with varus/valgus and internal/external torques as the primary mechanisms for the overuse injury occurrence [7]. To reduce the loads on the lower extremity and test the efficacy of specific constraints, a comprehensive three-dimensional (3D) model of the lower extremity loading needs to be used.  
The driving power during cycling comes from the hip and knee extension in the downstroke [8]. For that reason, the knee is also the most common site of an overuse injury [9]. Even though pedaling is constraint to a constant path in a sagittal plane defined by the crank trajectory, a recent study [10] showed that varus/valgus moments can reach values of up to 16 Nm at relatively low workloads (~150 W at 60 rpm).  
To understand the interaction between the injury occurrence and knee loading during cycling, a valid diagnostical approach needs to be developed. To the best of our knowledge, only two studies have attempted to develop such a model. The first one, presented by [PERSON], [PERSON], and [PERSON] (1992) used two two-dimensional (2D) models with one defined in the sagittal and the other in the frontal plane. The model calculated all six loads relative to the three axes at the knee joint. They assumed that both the knee and pedal local medial-lateralaxis is perpendicular to the sagittal plane, which can cause an error in the calculations [11]. The second model presented by [PERSON] and [PERSON] (2003) was calculated using a 3D inverse dynamic approach, but only non-driving (varus/valgus and internal/external) torques at the knee joint were presented. The virtual point on the pedal was used as a foot marker, which can be done only when zero-float clipless pedals are used. Their main purpose was to compare a complete spherical joint model with a simplified spherical and revolution joint model [12].  
Therefore, the main objective of this study was to develop a complete 3D model of the lower extremity to evaluate joint loading during seated cycling with a specific emphasis given to the knee joint by calculating the net joint forces and torques [13]. Moreover, the secondary aim was to test the measured and calculated variables for intra-session reliability. We hypothesized that all variables would exhibit high reliability without statistically significant differences between two trials.
## 4 III-V-on-Silicon Devices for Optical Communication Applications  
Silicon photonic integrated circuits are currently finding applications mostly in the realm of optical communication. Both transceivers for optical interconnects in datacenters as well as transceivers for long-haul coherent communication are being commercialized. These transceivers use external III-V laser sources that are interfaced with the PIC. The scaling of the required aggregate bandwidth of these transceivers, especially in the context of optical interconnect applications, will require wavelength division multiplexed transceivers, therefore requiring the integration of multiple lasers on a single transceiver chip. This requires a scalable approach to laser integration, for which we use adhesive die-to-wafer bonding. Besides lasers, other opto-electronic devices such as EAMs can also be integrated  
Figure 4: **(a)** Schematic view of grating coupler interface between Si waveguide circuit and III-V photodetector **(b)** Simulation example of grating based coupling to a III-V photodetector. Design B has antireflection coating while Design A does not (reproduced from [13]).  
this way. In the subsequent sections, we will elaborate on the realization of III-V-on-silicon laser sources and EAMs for optical communication applications.
# Clinical Brain Monitoring with Time Domain NIRS: A Review and Future Perspectives
###### Abstract  
Near-infrared spectroscopy (NIRS) is an optical technique that can measure brain tissue oxygenation and haemodynamics in real-time and at the patient bedside allowing medical doctors to access important physiological information. However, despite this, the use of NIRS in a clinical environment is hindered due to limitations, such as poor reproducibility, lack of depth sensitivity and poor brain-specificity. Time domain NIRS (or TD-NIRS) can resolve these issues and offer detailed information of the optical properties of the tissue, allowing better physiological information to be retrieved. This is achieved at the cost of increased instrument complexity, operation complexity and price. In this review, we focus on brain monitoring clinical applications of TD-NIRS. A total of 52 publications were identified, spanning the fields of neonatal imaging, stroke assessment, traumatic brain injury (TBI) assessment, brain death assessment, psychiatry, perioperative care, neuronal disorders assessment and communication with patient with locked-in syndrome. In all the publications, the advantages of the TD-NIRS measurement to (1) extract absolute values of haemoglobin concentration and tissue oxygen saturation, (2) assess the reduced scattering coefficient, and (3) separate between extra-cerebral and cerebral tissues, are highlighted; and emphasize the utility of TD-NIRS in a clinical context. In the last sections of this review, we explore the recent developments of TD-NIRS, in terms of instrumentation and methodologies that might impact and broaden its use in the hospital.  
NIRS; diffuse optics; time-domain; time-resolved; brain oxygenation; tissue saturation; scattering; absorption +
Footnote †: journal: Medical Imaging
# Dynamic Stability Analysis of Isolated Power System
## 8 Conclusions  
Stability-related questions regarding the electric power system (EPS) operating in an islanded mode were addressed in this research. The considered issues include: the reaction of the islanded system to a load change with and without the HVDC BtB con  
Figure 27: Frequency change in the isolated power system caused by disconnection of the HVDC BtB converter.  
Figure 26: (**a**) Frequency change in the isolated power system caused by disconnection of the unit operating in pump mode. (**b**) Response of the HVDC BtB converter to a disconnection of the unit operating in pump mode.  
verter's frequency control capabilities; switching on/off the units working in synchronous condenser mode; the optimization of the HVDC BtB converter's settings and the reaction of the system to major disturbances, such as the disconnection of the pumped-storage power station's unit working in pump mode and the disconnection of the HVDC BtB converter. The summarized results of the research are:  
In the isolated EPS, a 200 mHz frequency deviation is reached in the case of a 25 MW disturbance after disabling the HVDC BtB converter frequency control function.  
It is recommended to use two switched-on harmonic filters of the HVDC BtB converter during the operation of the isolated EPS.  
The optimal HVDC BtB converter frequency control parameters during simulation are as follows: gain factor \(K=250\) MW/Hz, corresponding to 4% droop; ramp = 100 MW/s; dead-band \(db=10\) mHz; control range \(\pm 50\) MW.  
When two synchronous condenser units are operating and one of them disconnects, a faster dynamic process is observed after the disturbance, i.e., the isolated EPS stabilizes in a shorter period of time. If possible, it is recommended to use two units operating in synchronous condenser mode.  
Connecting a synchronous condenser unit to the isolated EPS results in a system frequency reduction of up to 200 mHz when the frequency control function of the HVDC BtB converter is switched off, and 100 mHz when the frequency control function of the HVDC BtB converter is switched on.  
In the isolated EPS, short-term overvoltage up to 363 kV is possible when the HVDC BtB converter operates in frequency control mode. In response to the frequency increase, it is recommended that the voltage of the isolated EPS not exceed 357 kV before switching on the frequency control function of the HVDC BtB converter.  
Conceptualization, R.D.; methodology, R.L.; software, K.O.; validation, R.L.; formal analysis, R.D.; investigation, K.O. and R.L.; resources, R.L.; data curation, R.D.; writing--original draft preparation, K.O., R.D. and R.L.; writing--review and editing, K.O., R.D. and R.L.; visualization, R.L.; supervision, R.D. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.