esa-sceva/satcom-chunk-collection huggingface dataset:
# Large Field-Size Elliptic Curve Processor for Area-Constrained Applications
## 5 Conclusions  
This article has presented a novel elliptic curve cryptographic processor over \(GF(2^{409})\) and \(GF(2^{571})\) using Lopez-Dahab projective point arithmetic operations. The critical feature of this work is a hybrid Karatsuba multiplier of 4-split polynomials to multiply two polynomial multiplications. A hybrid multiplier is implemented using a general Karatsuba and traditional schoolbook multiplication approaches. For low hardware resource utilizations, the proposed multiplier design is employed to implement the modular squares and addition chains of the Itoh-Tsujii algorithm for inverse computations. On Xilinx Virtex 7 FPGA device, the number of the required slices is 4439 and 5683 over \((2^{409})\) and \(GF(2^{571})\), respectively. Similarly, on ASIC 65 nm process technology, the core size is 30,561 \(\upmu\)m\({}^{2}\) and 36,857 \(\upmu\)m\({}^{2}\) for \(GF(2^{409})\) and \(GF(2^{571})\), respectively. The comparison to existing designs in the literature shows that the proposed architecture utilizes less area and provides competent performance for PM computation. Therefore, the proposed design is an alternate for area-constrained cryptosystems.  
Conceptualization, M.R. and M.A.; methodology, M.R. and M.Y.I.Z.; software, N.K. and M.A.; validation, M.R. and M.A.; formal analysis, M.R. and N.K.; investigation, M.A. and M.R.; resources, M.R. and N.K.; data curation, O.S.S.; writing--original draft preparation, M.R. and M.H.S.; writing--review and editing, M.R. and M.Y.I.Z.; visualization, O.S.S.; supervision, M.R. and M.Y.I.Z. All authors have read and agreed to the published version of the manuscript. The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code: (22 UQU4320020 DSR01).  
Not applicable.  
The authors declare that they have no conflict of interest.
## 4 Application to WWTP
### Operating Conditions  
The BSM1 defines the operational requirements of the plant as well as some performance criteria to characterize the effluent quality and the energy consumption [32]:  
* Influent load and disturbances: In order to test the performance of control strategy in different situations, the BSM1 provides standardized influent data considering different weather situations. In this work, data for 336 h, corresponding to 2 weeks starting at time 168 h are considered, with a sampling period of 0.25 h (=15 min) in this work. Figures 3-5 present the profiles for stormy weather.
* ammonium \((S_{NH})\) concentration, total nitrogen \((N_{tot})\) concentration, suspended solid \((S_{S,e})\) concentration, biological oxygen demand over a 5-day period \((BOD_{5})\) and \((COD)\) are given Table 4.
* Inputs: The two manipulated variables are the internal recycle flow rate \(Q_{a}\) and the mass transfer coefficients \(K_{la}\). The bounds for the input variables are \(Q_{a}<3850\,\mathrm{m}^{3}/\mathrm{d}\) and \(Kla<200\,\mathrm{d}^{-1}\). The mass transfer coefficient corresponds to the efficiency of the aeration in the aerated tank.
* the ammonium concentration, the concentration of suspended solids, the \(BOD_{5}\), the \(COD\) and the total nitrogen
- are used to demonstrate the performance of the control system.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Effluent Qualities** & **Upper Bound** & **Unit** \\ \hline \(S_{NH}\) & 4 & mg/L \\ \(S_{NO}\) & 10 & mg/L \\ \(N_{tot}\) & 18 & mg/L \\ \(TSS\) & 30 & mg/L \\ \(COD\) & 100 & mg/L \\ \(K_{La}\) & 200 & \(\mathrm{d}^{-1}\) \\ \(Q_{a}\) & 3850 & \(\mathrm{m}^{3}/\mathrm{d}\) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Bounds of the effluent concentrations.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Notation** & **Definition** \\ \hline \(\mathrm{S_{O,sat}}\) & Oxygen saturation concentration \\ \(\mu_{\mathrm{H}}\) & Heterotrophic max. specific growth rate \\ \(\mathrm{K_{S}}\) & Half saturation coefficient for heterotrophs \\ \(\mathrm{K_{O,H}}\) & Oxygen saturation coefficient for heterotrophs \\ \(\mathrm{K_{NH}}\) & Ammonia saturation coefficient for heterotrophs \\ \(\mathrm{K_{O,A}}\) & Oxygen saturation coefficient for autotrophs \\ \(\mathrm{Y_{H}}\) & Heterotrophic yield \\ \(\mathrm{Y_{A}}\) & Autotrophic yield \\ \(\mathrm{i_{ab}}\) & Nitrogen fraction in biomass \\ \hline \hline \end{tabular}
\end{table}
Table 3: Kinetic parameters and stoichiometric coefficient characteristics.  
Figure 4: Concentration of organic matter in the influent \(S_{N_{in}}\) for stormy weather.  
Figure 5: Concentration of ammonium compounds in the influent \(S_{N\!H_{in}}\) for stormy weather.  
Figure 3: Influent flow \(Q_{in}\) for stormy weather.
# Optimizing the Scheduling of Teaching Activities in a Faculty
## 1 Introduction
### Motivation  
Organizing educational activities is a complex problem with broader applications across various sectors such as healthcare, transportation, and entertainment, where resource allocation and scheduling limitations present significant challenges [2; 3]. These issues fallinto the NP-complete category, meaning optimal solutions are difficult to find efficiently [4], and heuristic approaches are often employed to generate practical results. This research aims to improve scheduling at universities by automating the process, addressing the limitations of manual methods, and optimizing resource allocation, conflict minimization, and satisfaction among stakeholders.  
Traditional approaches demand considerable time and effort from administrators and faculty, often resulting in schedules that fail to optimally allocate resources, avoid conflicts, or meet the preferences of all involved. By automating the process, the system will create timetables that better allocate resources, reduce scheduling conflicts, and improve satisfaction for both students and faculty.
# Progress in Ski Jumping Technology Based on Biomechanical Sport Research Methods
## 2 Progress of Different Research Methods
### Wearable Inertial Measurement and Sensor Equipment  
Dynamic changes in athletes' bodies are the fundamental reason for changes in kinematics. Observing the dynamic changes throughout the ski jumping process is very important for studying the factors affecting the distance of movement. Wearable inertial measurement units (IMUs), including gyroscopes and accelerometers, are a powerful option for measuring human motion in natural environments, and a measurement system consisting of an IMU attached to the sacrum can be used to determine a variety of forces and work in the form of motion. With the development of inertial sensor technology, IMUs can also be used to calculate the joint angle and speculate the position of the centroid during motion. In ski jumping, [PERSON], [PERSON], [PERSON], and [PERSON] [20] used seven IMU units affixed to the sacrum, thigh, calf, and snowboard and set up a camera to estimate the aerodynamics of the contestants during flight. [PERSON] et al. used a system based on wearable inertial sensors to calculate the kinematics and dynamic parameters of all stages of ski jumping, such as the force on the centroid during the take-off stage, the angular velocity of the roll, and the air force during the flight stage [44; 45]. [PERSON] used 10 IMU units, combined with force plates and morphometric methods, to analyze the forces and moments of the ankle, knee, and hip joints during the slide and take-off phases [46]. In recent years, wearable inertial measurement units have achieved promising results when measuring the kinematics and dynamics of ski jumping [44; 45; 46; 47]. However, some studies have shown the possibilities GNSSs provide for collecting data efficiently from the start of the invn to the landing [48; 49]. Using this measurement, a trajectory with \(\pm\)0.05 m of global position accuracy can be achieved [50].  
These measurement methods can achieve data monitoring in the moving process, which is very suitable for data recording in actual field training. The primary disadvantage of wearable equipment is that it cannot be used in competitions. The background technology for this measurement technology is the use of extrapolation methods, so the reliability of the data needs to be verified. The consistency of data generated by different measurement units and systems must be considered.
## 3 Results and Discussion
### Molecular Docking Study  
A molecular docking study was used to check the interaction between the NQO1 enzyme and compounds **1-3**, **6-7**, and streptonigrin (ST). The structure of the enzyme as a complex with the flavin adenine dinucleotide (FAD) cofactor was downloaded from the PDB (PDB ID:2F1O). The scoring values (\(\Delta\)G) of all molecules are presented in Table 5. The lowest value of \(\Delta\)G corresponds to a strong binding affinity and the most probable ligand-protein complexes in vitro.  
The scores of protein-ligand complexes range from \(-8.0\) to \(-8.3\) kcal/mol. All dichloro-5,8-quinolinedones (**1-3** and **5-6**) have lower scores than streptonigrin (ST), indicating their strong binding affinity.  
Complete models of interaction between the NQO1 enzyme and ligands **1-3** and **6-7** are presented in Figure 6. Details on the type and length of the bonds are summarized in Table S1.  
Figure 5: Enzymatic conversion rate of NQO1 of compounds **1–3**, **6–7**, and streptonigrin (ST).  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Molecules** & \(\Delta\)**G (kcal/mol)** \\ \hline
**1** & \(-8.1\) \\
**2** & \(-8.0\) \\
**3** & \(-8.3\) \\
**6** & \(-8.3\) \\
**7** & \(-8.2\) \\
**ST** & \(-7.1\) \\ \hline \hline \end{tabular}
\end{table}
Table 5: Scoring values (\(\Delta\)G) of molecules **1–3**, **6–7**, and **ST**.  
6,7-Dichloro-5,8-quinolinedione **1** creates the hydrogen bond between the formyl group at the C8 position and tyrosine (TYR126) as well as hydrophobic interactions with phenylalanine (PHE178), tyrosine (TYR128), and the FAD cofactor. Molecules with a substituent at the C2 position (**2-3** and **6-7**) create also the hydrogen bond between nitrogen  
Figure 6: Visualization of interactions between the NQO1 enzyme and derivatives: (**a**) **1**, (**b**) **2**, (**c**) **3**, (**d**) **6**, (**e**) **7**.  
atom and tyrosine (TYR126). Additionally, in the complex of 6,7-dichloro-2-hydroxy-5,8-quinolinedione **6** with NQO1, a hydrogen bond is observed between the formyl group at the C8 position and tyrosine (TYR126).
# A Novel Variable Step Size Incremental Conductance Method with an Adaptive Scaling Factor
## 5 Discussions and Limitations
### Tracking Time  
The simulation and experimental results showed that the novel VSS INC MPPT technology with adaptive scaling factor proposed in this paper has a faster tracking speed than the conventional VSS INC MPPT method. According to the experimental results, the proposed method can improve the  
Figure 10: Experimental results of different \(M\) values (**a**) \(M\) = 0.65, (**b**) \(M\) = 1.8, (**c**) \(M\) = 0.65/1.8.  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline  & **tt of ii** & **tt of di** & **ta of ii** & **ta of di** & **Total Energy** & **Total Energy** \\  & **Case** & **Case** & **Case** & **Case** & **Loss of ii** & **Loss of di** \\  & **Case** & **Case** & **Case** & **Case** & **Case** \\ \hline VSS INC (\(M\) = 0.65) & 2.2 s & 1.5 s & 99.8\% & 99.1\% & 401.5 W & 402.5 W \\ VSS INC (\(M\) = 1.08) & 1.5 s & X & 97.7\% & X & 275.6 W & X \\ VSS INC (\(M\) = 1.8) & X & N.A. & X & 96.3\% & X & 358.6 W \\ Proposed method & 1.5 s & 1.5 s & 99.8\% & 99.8\% & 225.5 W & 282.3 W \\ \hline \hline \end{tabular} Note: tt: tracking time, ta: tracking accuracy, ii: increasing irradiance, di: decreasing irradiance.  
\end{table}
Table 5: Summarized experimental results of different \(M\) values.  
tracking time by 31.8% under the tested increasing irradiance level conditions. It should be noted that the voltage waveform oscillates and never reach the steady state; hence, the tracking time value is not available in decreasing irradiance level conditions.
## 3 A Short Introduction to the PPP Method
### Precise Point Positioning Correction Models  
Developers of GNSS software are generally aware of the corrections they must apply to code (pseudorange) or carrier (phase) observations to eliminate effects such as special and general relativity, Sagnac delay, satellite clock offsets, and atmospheric delays. All of these effects are quite significant and can exceed several metres. They must be considered for pseudorange positioning at the metre precision level. Therefore, when attempting to combine satellite positions and clocks with a precision of a few centimetres with ionospheric-free carrier phase observations (with millimetre resolution), it is very important to account for some of these effects which may be neglected in code or precise differential Carrar processing.  
The corrections that need to be made are ([21]):  
* Satellite antenna: To account for the distance between the satellite centre of mass, to which the satellite coordinates are referred, and the phase centre of the antenna, from which observations are measured. The magnitude of potential error is at the level of metres.
* Phase Wind-Up: To account for a change in phase measurement due to the satellite rotating around its vertical axis during noon-turn and eclipse. The magnitude of potential error is at the level of decimetres.
* Solid Earth Tides: To account for the periodic displacement of the Earth's crust due to the sun and moon. The magnitude of potential error is at the level of decimetres.
* Ocean Loading: To account for the deformation of the Earth's crust caused by the increased load of water along coasts resulting from tidal action. The magnitude of potential error is at the level of centimetres.
* Relativity correction: To account for the effect of relativity on the GNSS onboard atomic clocks. The magnitude of potential error is at the level of metres.
* Pseudo-Range: This depends on pseudo-range observations with respect to the clock. The magnitude of potential error is about 2 ns of the user's clock.
* Receiver antenna: To account for receiver antenna phase centre variations. The magnitude of potential error is at the level of centimetres.  
In addition to applying correction models, atmospheric delays must be modelled, eliminated, or estimated. First-order ionospheric delay is eliminated using ionosphere free linear combinations of dual-frequency observations. The troposphere effect (tropospheric zenith delay) is modelled using default surface temperatures, and pressures adjusted to reflect antenna height and mapped along the signal path using the Niell Mapping Function [23].
# Impact of Disruption on Ship Emissions in Port: Case of Pandemic in Long Beach
###### Abstract  
To achieve environmental sustainability on ships, stakeholders should make efforts to reduce emissions. Port authorities are crucial to attain this goal by introducing new policies. This study takes the Port of Long Beach as an example to assess port-wide ship emissions and explain the significance of shore power policy. Additionally, the study considers the impact of disruptions, such as the COVID pandemic, on ship emissions. The analysis compares data from three years before and after the pandemic to examine the relationship between ship waiting times, quantities, and emissions. The findings indicate that the majority of port-wide ship emissions are generated by berthing or anchoring vessels, from ship auxiliary engines and boilers. Furthermore, ship congestion due to reduced port productivity during the pandemic significantly increased emissions from berthing and anchoring vessels, with the emission proportion increasing from 68% to 86%. Adopting the shore power policy has effectively reduced ship emissions in port areas, and increasing the number of ships utilising shore power will be instrumental in tackling excessive ship emissions.  
shore power policy; COVID pandemic; ship emission; Automatic Identification System (AIS); bottom-up +
Footnote †: journal: _Sustainability_
# Graphene-Based Functional Hybrid Membranes for Antimicrobial Applications: A Review
## 5 Antimicrobial Applications
### Antibacterial Applications
Compared with the unmodified PVDF membrane, the hydrophilicity, antibacterial property and mechanical properties of the modified membrane were significantly enhanced. [PERSON] et al. proposed a novel PES membrane prepared by the phase inversion method with different loadings of GO and 1 wt% gum arabic (AG) as nanofillers and pore formers [112]. The prepared membranes were tested for contamination with bovine serum albumin (BSA) solution, model bacterial suspensions of Gram-positive bacteria (_Bacillus subtilis_) and Gram-negative bacteria (_Escherichia coli_), and actual treated sewage (TSE) conduct a biofouling test. The results show that the novel PES/GO membrane has strong hydrophilicity and a negative surface charge, and increases the porosity, pore size, and water flux. The PES/GO membrane showed a superior antibacterial effect against both Gram-positive and Gram-negative bacteria, which means that the PES membrane with GO and AG as the novel membrane has high-throughput and high antibacterial properties. [PERSON] et al. prepared a novel synergistic antibacterial guanidine-functionalized graphene/polysulfone (GFG/PSF) mixed-matrix ultrafiltration membrane by a non-solvent-induced phase separation method (Figure 6b) [113]. The guanidized graphene nanosheets were prepared by a two-step grafting method of amination and guanidine. The graphene nanosheets showed high dispersibility in the casting solution and good compatibility with the polymer matrix. The bis-diester binding between guanidine and phosphate groups on the cell wall that it induces allows for high bactericidal rates, even at low concentrations. Compared with pure PSF membrane, GFG/PSF mixed matrix membrane not only exhibits excellent permeability and remarkable antifouling performance against BSA, but also exhibits good antibacterial activity against _Escherichia coli_ and _Staphylococcus aureus_ and long-term duration. GOQDs with hydrophilic groups and single-atom-thick structures have attracted extensive interest in the field of membrane preparation. By providing additional water channels in the membrane, GOQDs can increase the permeability of the membrane without compromising the selectivity. As an effective bactericidal material, silver nanoparticles were uniformly deposited on GOQDs by a facile method. [PERSON] et al. used interfacial polymerization to embed GOQD/Ag into a PA selective layer to obtain a nanocomposite thin film (TFN-GOQD/Ag) film [114]. Due to the synergistic effect of GOQD and Ag, the TFN-GOQD/Ag200 membrane exhibited significant bactericidal ability against both Gram-negative _Escherichia coli_ (98.6%) and Gram-positive _Staphylococcus aureus_ (96.5%).
## 2 Pulse Selective Approach  
This analytical approach is one of the simplest methods to evaluate the power quality concerns of current or voltage waveforms that apparently seem to be non-sinusoidal or complex. The non-sinusoidal nature of waveforms is due to the switching mechanism involved in the switching converters. That may invert, non-invert, or chop the input voltage waveform at the output in a single-phase supply system. This may also be due to the summation or subtraction of the input voltage sources at the output in a three-phase supply system. Thus, it results in harmonic contents. So, a resultant non-sinusoidal voltage or current waveform is a series of various harmonic frequencies.  
In the pulse selective approach (PSA), such non-sinusoidal current or voltage waveforms are decomposed into their parent sinusoidal components. Then each component is analyzed for its period that is required to compute its harmonic coefficients. The harmonic coefficients of each sinusoidal component present in the considered (current or voltage) waveform are computed. The harmonic coefficients of all sinusoidal components are added by the superposition principle to have the harmonic coefficients of a complete waveform. This way, well-distinct numerical expressions of non-sinusoidal currents and voltages are obtained to compute the harmonics. The steps involved in the PSA are presented in the form of a flow chart shown in Figure 1.  
It should be remembered that the selection of a period is quite crucial. For example, in the case of direct AC-AC and AC-DC converters, the period of the input voltage waveform is always '2\(\pi\)', but the periods of the output voltage or current waveforms may or may not be '2\(\pi\)'. To add more insight, the outputs of the frequency controllers for double and half frequency become periodic after '\(\pi\)' and '4\(\pi\)' intervals respectively. For these outputs, the period of the required components is equal to the period of the instantaneous waveform but this is not always true. For example, the voltage waveform where the required output frequency is three times the input voltage frequency, the period of the required component (voltage component having frequency three times the input frequency) and instantaneous output voltage waveform is one third and is equal to the period of the input voltage waveform respectively. The periods of these sinusoidal components are chosen by analyzing them for zero average value during selected periods.  
As can be seen, the PSA needs not to involve look-up tables, Bessel functions, and numerical techniques for the computation of harmonic magnitude and angle. Realizing this fact, the application of PSA to compute the harmonic contents of non-sinusoidal current and voltage waveforms of AC-AC voltage controllers is presented in the coming sections.  
The harmonic coefficients for other types of switching converters can also be computed by PSA. Switching mechanism, converter type (single-phase or three-phase), input and output waveform frequencies, and so on result in different current and voltage waveforms.
# A Surrogate Model Based Multi-Objective Optimization Method for Optical Imaging System
## 2 Methodology  
Compared with the above-mentioned methods/models, the surrogate model-based multi-objective optimization method presented in this paper is a data-driven method. It trains the surrogate model using a relatively small set of sample data before optimizing the design. Sample points are chosen using the DOE algorithms, and the data set can then be obtained by simulation at sample points using optical tracking methods, such as ray tracing. Benefiting from the surrogate model, this method has a low calculation cost. This is especially useful when the amount of calculation is very high, such as for the optimization of multiple objectives in a design space with high dimensionality.