esa-sceva/satcom-chunk-collection huggingface dataset:
# Spectral Shaping of a Superluminescent Diode for Terahertz Cross-Correlation Spectroscopy
## 1 Introduction
In THz-QTDS systems, this light source creates a continuous spectrum in the terahertz frequency-domain, while the rest of the setup is comparable to a conventional THz-TDS system. It was demonstrated that the bandwidth of such a THz-QTDS system scales linearly with the optical bandwidth of the light source until it saturates around 1.8 THz. This was demonstrated by using different optical bandpass filters and analyzing the resulting terahertz spectrum [12]. However, none of these techniques can overcome all the disadvantages of semiconductor-based light sources-driven terahertz systems. Although theories exist for THz-CCS with an incoherent light source, they are not complete. For MMLDs, the phase relation and linewidth of the modes are neglected [4]. This leads to improper simulation results. As an example, the envelope of quasi pulse train is not reproduced, which is an effect of the finite linewidth. A better understanding of the principles is mandatory for the further development of these systems. To get a better understanding of the behavior of terahertz generation with photomixers driven by an incoherent light source, we present in this work an experimental setup for indirect terahertz pulse shaping. This is done by manipulating the optical spectrum of a SLD with special interest in system performance improvement. Dynamic range, peak-to-peak amplitude, terahertz power and bandwidth are investigated depending on the shape and optical power of the incident optical signal. We show that we can further improve these parameters with optical shaping and amplification of the optical spectrum. The shaping is realized by a programmable optical filter (POF). In the following section, the experimental setup and the different experiments are explained in detail. We created 65 different filter shapes differing in the distance between the features and the width of the features. As a next step, the corresponding terahertz spectrum was analyzed, and important parameters were extracted and are presented in Section 3. At the end of Section 3, the results are compared to a numerical simulation.
# A Unified Theory for 3D Gear and Thread Metrology
## 2 State of the Art in Gear and Thread Metrology  
Traditional gear and thread metrology refers to single-point and line measurements in selected cross-sections. While some modern applications also apply 3D inspection methods, e.g., for rapid prototyping [23], calibration laboratories still stick to the traditional approach. Involute cylindrical gears are best described in a transverse section, i.e., in a plane perpendicular to the gear axis. This is due to the kinematic principle of two gears with parallel axes where the line of contact lies in a common transverse plane. By contrast, screw threads of all types are invariably characterized in an axial section, i.e., in a plane that contains the thread axis. This has proven convenient since most geometric thread parameters can easily be described in axial sections.  
Gears and threads can both be treated as special types of a more general class of helical machine elements. The geometrical similarities of the two types of parts are depicted in Table 1 in terms of their determinants.  
Despite the obvious similarities, gears and threads are currently treated in _two different worlds_ encompassing aspects of standardization, design, manufacturing, metrology, and more. The work of the International Organization for Standardization (ISO) is spread across more than 250 technical committees (TCs). Among them, at the very top of the list, is _ISO/TC1 Screw threads_, which is responsible for thread standardization, while _ISO/TC60 Gears_ develops standards for all the different types of gears. All TCs list their official liaisons to other TCs within ISO. Apparently, there is no cross-talk between TC1 and TC60, even though these committees list liaisons to 23 and 8 other ISO/TCs, respectively [25]. A similar separation of activities can be observed in the national standardization bodies in Germany, the U.S., and other countries.  
Gears are typically measured on 3D coordinate measuring machines (CMMs) either with or without a rotary table or on dedicated gear measuring instruments which can be viewed as special CMMs that correspond to a cylindrical coordinate system rather than a Cartesian. By contrast, screw thread measurements are for the most part performed on 1D length comparators or 2D contour measuring devices. The main reason for employing these different techniques lies in the fundamental contrast in the concepts of the reference diameter of a gear on the one hand and the pitch diameter of a thread on the other. The reference diameter in gear metrology is merely a theoretical quantity that is used to determine nominal measurement points and to compute certain evaluation results. In thread metrology, the pitch diameter is agreed to be the most important measurand, the actual value of which implicitly contains information on the other determinants, including the lead and the thread angle.  
As the differences described here may be the result of historical developments rather than the inevitable consequence of technical barriers, the following subsections will briefly review the origins of the gear/thread divide.
# Finite Element Analysis of the Distribution Parameters of a Metal Dot Array in a SAW Gyroscope
###### Abstract  
A surface acoustic wave (SAW) gyroscope has many unique advantages, but a low detection sensitivity limits its development. Previous studies have shown that adding a metal dot array to the acoustic wave propagation path of the SAW delay line can enhance the Coriolis force and further improve sensitivity. Therefore, in order to optimize the detection sensitivity performance of the sensor, 128\({}^{\circ}\)YX-LiNbO3, ST-X Quartz and X112\({}^{\circ}\)Y-LiTaO3 piezoelectric substrates were selected by finite element method to analyze the influence of the metal dot array size on the SAW gyroscopic effect in this paper. The most suitable metal dot size for 128\({}^{\circ}\)YX-LiNbO3 and X112\({}^{\circ}\)Y-LiTaO3 obtained by simulation are \(5/16\lambda\) and \(1/16\lambda\), respectively; for example, when the normalized angular velocity is \(1\times 10^{-3}\), the SAW gyroscopic effect factor \(g\) of the two piezoelectric substrates distributing the optimum size metal dots can reach 22.4 kHz and 5.2 kHz. For ST-X quartz, there is a threshold between the rotation speed of the substrate and the optimum size of the metal dot. When the rotating speed is lower than the threshold, the SAW gyroscopic effect is strongest when the metal dot size is \(3/16\lambda\); otherwise, the SAW gyroscopic effect is strongest when the size is \(11/16\lambda\). These research results provide new ideas for improvement of the SAW gyroscope.  
Coriolis force; finite element simulation; SAW gyroscopic effect; piezoelectric substrate; metal dot array +
Footnote †: journal: Applied Sciences  
Article  
Finite Element Analysis of the Distribution Parameters of a Metal Dot Array in a SAW Gyroscope
## 3 Comparative Analysis of Numerical Forward Simulation and Soil Trench Modeling Experiments
### Numerical forward Simulation of the Dual-Frequency Excitation Method
#### 3.2.1 Introduction of the Cole-Cole Model in Dual Frequency IP Method  
The Cole-Cole model has been widely used in geological exploration [27]. [PERSON] et al. have verified the feasibility of the Cole-Cole model for characterizing the complex resistivity of soils through experiments on Cr-contaminated soils [28]. The Cole-Cole model is one of the models commonly used by researchers to describe the excitation effect. In this study, the Cole-Cole complex resistivity model is introduced in the numerical simulation, which fully considers the effects of contaminants concentration, soil particle homogeneity, porosity, and denseness of the contaminants on the excitation effect of the contaminated site. Cole-Cole can be expressed in the frequency domain as [14]:  
\[\rho(i\omega)=\rho_{0}\bigg{\{}1-m\bigg{[}1-\frac{1}{1+(i\omega\tau)^{c}} \bigg{]}\bigg{\}} \tag{6}\]  
Figure 5: Physical experimental modeling of earth tanks.  
where \(\omega\) is the angular frequency, rad/s; \(\rho_{0}\) is the zero-frequency resistivity, \(\Omega\cdot\mathrm{m}\), which corresponds to the DC resistivity in the time domain; \(m\) is the polarization rate; \(\tau\) is the time constant; \(c\) (\(0.1\leq c\leq 0.6\)) is the frequency correlation coefficient. Where \(\rho_{0}\) characterizes the electrical conductivity; \(m\) characterizes the strength of the excitation effect; \(\tau\) is a parameter characterizing the position of the frequency band where the IP spectrum changes; and \(c\) characterizes the degree of dithering of the IP spectrum.  
The electrical conductivity and relative dielectric constant were set in the material details column of the contaminated site. The conductivity value is equal to the reciprocal of the Cole-Cole model's zero frequency resistivity, the simulation's settings are shown in Figure 6. \(i\) is an imaginary unit; rho stands for \(\rho_{0}\); too stands for \(\tau\); pi stands for \(\pi\); 2 \(\times\) pi \(\times\) freq stands for \(\omega\). The relative permittivity \(\epsilon_{\mathrm{r}}\) is related to the polarization rate \(m\) in the Cole-Cole model as [16]:  
\[\epsilon_{\mathrm{r}}=1+m. \tag{7}\]  
The simulation schematic in COMSOL is shown in Figure 7. The background resistivity value is set to 537 \(\Omega\cdot\mathrm{m}\). The chromium contaminant 0-5 cm layer is set to 537 \(\Omega\cdot\mathrm{m}\). The middle layer 5-15 cm is set to 93 \(\Omega\cdot\mathrm{m}\). The bottom layer 15-20 cm is set to 759 \(\Omega\cdot\mathrm{m}\). The model specification was set to 1:1 for the experiment.
## 5 Conclusions  
In this study, four analytical approaches, Morris, Sobol, FAST, and EFAST, available in SWAT-SA, were used to screen the critical parameters of the SWAT model for monthly runoff simulation for the study of the UHRB in China. The following are the main findings of this study.  
1. Combined with the results calculated with the four parameter sensitivity analysis methods, 10 sensitive SWAT model parameters were defined: SMTMP, SOL_AWC, SFTMP, RCHRG_DP, SOL_K, SOL_Z, GWQMN, SOL_BD, ALPHA_BNK, and HRU_SLP.  
2. The parameter sensitivity calculated with each analytical method was different, resulting in an apparent difference between the statistical indicators of the flow simulation value obtained by optimizing these sensitive parameters. The different sampling processes, sensitivity indices, and calculation principles of each method may be the main reasons.
3. By optimizing the most sensitive parameters combined with the results of the four methods, the NSE, MSE, PBIAS, and KGE of the flow simulation value and the measured value were 0.89, 200, 8.60, and 0.90, respectively, which were better than optimizing the sensitive parameters defined by a single method and all selected parameters. The differences in performance indicate the rationality and importance of parameter sensitivity analysis for hydrological models, and the synthesis of multiple approaches to define sensitive parameters.  
Conceptualization, X.X., T.A. and Q.X.; formal analysis, X.X.; funding acquisition, T.A. and X.L.; methodology, X.X., Q.X., L.Z., Y.C., Y.B. and J.G.; software, X.X. and Q.X.; supervision, X.X. and X.L.; visualization, X.X.; writing--original draft, X.X.; writing--review and editing, X.X., T.A., Q.X. and X.L. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Key R&D projects of the Science and Technology department in Sichuan province, grant 2021 YFS028, and the science program of China Railway Eryuan Engineering Group Co., Ltd., grant KYY2018099(18-20).  
Not applicable.  
The study did not report any data.  
The authors thank the anonymous referees for their valuable comments and suggestions.  
The authors declare no conflict of interest.
# Revolution or Evolution? Technical Requirements and Considerations towards 6G Mobile Communications
###### Abstract  
Ever since the introduction of fifth generation (5G) mobile communications, the mobile telecommunications industry has been debating whether 5G is an \"evolution\" or \"revolution\" from the previous legacy mobile networks, but now that 5G has been commercially available for the past few years, the research direction has recently shifted towards the upcoming generation of mobile communication system, known as the sixth generation (6G), which is expected to drastically provide significant and evolutionary, if not revolutionary, improvements in mobile networks. The promise of extremely high data rates (in terabits), artificial intelligence (AI), ultra-low latency, near-zero/low energy, and immense connected devices is expected to enhance the connectivity, sustainability, and trustworthiness and provide some new services, such as truly immersive \"extended reality\" (XR), high-fidelity mobile hologram, and a new generation of entertainment. Sixth generation and its vision are still under research and open for developers and researchers to establish and develop their directions to realize future 6G technology, which is expected to be ready as early as 2028. This paper reviews 6G mobile technology, including its vision, requirements, enabling technologies, and challenges. Meanwhile, a total of 11 communication technologies, including terahertz (THz) communication, visible light communication (VLC), multiple access, coding, cell-free massive multiple-input multiple-output (CF-mMIMO) zero-energy interface, intelligent reflecting surface (IRS), and infusion of AI/machine learning (ML) in wireless transmission techniques, are presented. Moreover, this paper compares 5G and 6G in terms of services, key technologies, and enabling communications techniques. Finally, it discusses the crucial future directions and technology developments in 6G.  
6G; beyond 5G; future networks; next-generation mobile; terahertz; VLC; wireless transmissions +
Footnote †: journal: Sensors
###### Abstract  
Treated wastewater (TWW) is recognised as an alternative irrigation source to mitigate global water scarcity for irrigation purposes. However, one of the challenges of using TWW as an irrigation source is the accumulation of non-essential toxic elements in soil post-irrigation. Thus, this study determined whether indigenous microbes that are tolerant to toxic elements would remediate non-essential toxic elements in contaminated soil following irrigation with TWW. Soil from a fallowed field at the University of Limpopo Experimental Farm was irrigated with TWW in pots for 12 weeks. After that, an incubation study was established to assess the abilities of _Escherichia coli_, _Staphylococcus aureus_, _Aspergillus flavus_, and _Pseudomonas aeruginosa_ to remediate the contaminated soil over 12 weeks. Both water and soil samples (non-contaminated, contaminated, and remediated) were analysed for toxic elements: Aluminium (Al), Arsenic (As), Chromium (Cr), Cadmium (Cd), and Lead (Pb). Data were analysed using GenStat 20 th edition. The results revealed that irrigation with TWW increased the concentration of non-essential toxic elements in soil by 110%, 31%, 31%, 31%, and 54% for Al, As, Cr, Cd, and Pb, respectively. The inoculation of soil with indigenous microbes led to the decline in the concentration of non-essential toxic elements in soil. Furthermore, soils inoculated with _S. aureus_ led to a reduction in Cr to levels below those observed prior to irrigation with TWW. Overall, the findings of the study effectively convey that these indigenous microbes can be used for bioremediation.  
water re-use; soil pollution; bioremediation 2025
# Synchronizing Many Filesystems in Near Linear Time
## 3 Filesystem Synchronization
### Update Detector  
Depending on the data communicated by the replicas, synchronizers are categorized as either _state-based_ or _operation-based_[9; 12]. In state-based synchronization, replicas send the current state of their filesystems, or merely the differences between their current state and the last known synchronized state [21]. Frequently, the local copy does not have access to the original synchronized state because of its limited resources, and transmitting the whole current state is prohibitively expensive. It is an active research area to devise efficient transmission algorithms which transmit the differences only [18; 22; 23; 24]. Operation-based synchronizers transmit the complete log (or trace) of all operations performed by the user [25]. It has been observed that in practice these logs are poorly maintained and are not always reliable [26; 27].  
Theorem 1 suggests that the updated information that the replicas send to the central server (or, rather, the data on which the synchronizer algorithm works) can be a canonical command set which transforms the original synchronized filesystem to the current replica. By Theorem 2 below, this set is not only a succinct representation of the differences but can also be generated in time proportional to the size of the filesystems (by traversing the original \(\Phi\) and the modified filesystem \(\Phi_{i}\) simultaneously).  
**Theorem 2** ((Theorem 19 in [14])).: _Let \(\Phi\) and \(\Psi\) be two filesystems. The command set_  
\[A_{\Phi\rightarrow\Psi}=\left\{\left\langle n,\Phi(n),\Psi(n)\right\rangle:n \in\mathbb{N}\text{ and }\Phi(n)\
eq\Psi(n)\right\}\]  
_is canonical, and \(A_{\Phi\rightarrow\Psi}\Phi=\Psi\)._  
If the replica has a complete log of the commands executed by the user (as in an operation-based update detector), that is, if the updates are collected in a command sequence \(\alpha_{i}\) which transforms \(\Phi\) to \(\Phi_{i}\), then \(\alpha_{i}\) can be transformed into the requested canonical set as claimed by Theorem 1 (_c_). As detailed in Algorithm 4 in Section 4, this transformation can be performed in near linear time in the size of \(\alpha_{i}\), which can be much faster than traversing the whole filesystem.
# Aggregation Dispatch and Control Strategies for Multi-Type Loads in Industrial Parks
## 3 Aggregated Control Strategy for Multi-Type Loads in Industrial Parks
### Real-Time Predictive Control of Multiple Types Loads in Industrial Parks  
Controllable loads in industrial parks generally have a d-step response delay, and the control action \(u(k)\) at the current time \(k\) must be delayed by \(d\) cycles to affect the output of controllable loads. Therefore, in order to minimize the variance between the actual and ideal values of output power, it is necessary to predict the actual value of output power d steps ahead, and then calculate the appropriate control action \(u(k)\) based on the predicted value to compensate for the effect of random interference on the output at time \(t+d\). Through real-time iterative prediction and control, the actual value of output power can always be kept with the minimum steady-state variance from the ideal value.
## 2 Materials and Methods  
### Oilfield Water and Deposit Sampling  
Samples of produced water (PW, oil-water mixture) were collected from oil reservoirs in the Republic of Tatarstan, near the two cities of Nurlat (54\({}^{\circ}\)26' N 50\({}^{\circ}\)48' E) (Nurlat oilfield) and Leningorsk (54\({}^{\circ}\)36' N 52\({}^{\circ}\)30' E) (Romashkino oilfield). The distance between Nurlat and Leningorsk is about 109 km. Oilfields have been in production for many years and waterflooding is used to increase reservoir pressure and stimulate crude oil production. Water samples were collected directly from production wells in May and June 2023 and included samples from biocide-treated locations. All oil wells are currently being developed by the Oil and Gas Production Departments \"Nurlatneft\" and \"Leningorskneft\" (Republic of Tatarstan, Russia).  
Sampling was carried out at ambient temperatures above 18 \({}^{\circ}\)C in clear, sunny weather. Each water sample was collected in duplicate in sterile 1-L plastic bottles, after one minute of line flushing. The bottles were immediately sealed with screw caps to avoid contamination and oxygen intrusion and then transported in an ice box to the laboratory within a maximum of 3 h and processed immediately. Five produced water samples from wells near Nurlat were designated as PW_N1, PW_N2, PW_N3, PW_N4, and PW_N5. Two samples of produced water from wells near Leningorsk were labeled as PW_L1 and PW_L2. The produced water samples were subjected to three processes: (1) chemical characterization; (2) obtaining enriched bacterial cultures; and (3) assessing the ability of microbial communities (from PW_L1 and PW_L2 samples) to initiate biocorrosion of the metal coupons.  
Additionally, pipe-sized fragments (20 steel; outer diameter 20 mm, length 30 mm) were placed in oil pipelines (near Leningorsorsk) for 2 months to monitor corrosion under in-line conditions. Using sterile instruments, deposits on the surfaces of the pipe fragments were obtained after they were brought to the surface. In total, nine deposit samples were collected from different oil pipelines. Deposit samples were placed in sterile, DNase/RNase-free plastic containers. However, only four samples gave substantial bacterial growth, and, therefore, only they were analyzed further. These samples were designated as D_1, D_2, D_3, and D_4.
## 2 Materials and Methods
### Batch Adsorption Experiments  
The adsorption capacity and removal efficiency of GAC, GO, and NaY for removal of MB and RhB was determined with batch experiments. For each batch experiment, 0.01 g/L of adsorbent was added to 125 mL Erlenmeyer flasks containing an initial concentration of 4 mg/L of dye solution (MB or RhB) at room temperature (25 \({}^{\circ}\)C) with no pH adjustment, (pH\({}_{\text{MB}}\) = 6.7 and pH\({}_{\text{RhB}}\) = 5.9). To avoid exposure to light and dissociation, all samples were covered with aluminum foil. Samples were stirred on a shaker at 50 rpm to create the slow regime mixing condition; this slow mixing regime was specifically selected to better predict the efficiency of the adsorbents in large-scale applications. The concentration of the solution was measured until no change was observed in adsorption capacity over time, indicating that equilibrium was achieved. The concentrations were measured with a UV-vis spectrophotometer (Jenway 7415) at \(\lambda_{max\text{MB}}\) = 663 nm and \(\lambda_{max\text{RhB}}\) = 553 nm.  
Removal percentage (R%) of dyes' and adsorbents' adsorption capacity at equilibrium (q\({}_{\text{e}}\)) were calculated based on Equations (1) and (2), respectively [21]:  
\[\text{R}\%=\left(\frac{\text{C}_{0}-\text{C}_{\text{e}}}{\text{C}_{0}}\right) \times 100 \tag{1}\]  
\[\text{q}_{\text{e}}=\frac{\left(\text{C}_{0}-\text{C}_{\text{e}}\right)\,V}{W} \tag{2}\]  
where \(C_{\text{o}}\) is the initial concentration of MB or RhB (mg/L), \(C_{\text{e}}\) is the final concentration of MB or RhB at equilibrium time (mg/L), \(W\) represents the weight of the adsorbent (g), and \(V\) is the volume of the solution (L).