esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Discussion and Conclusions  
In this paper, as far as we know, it is the first time a SNPCO method is proposed for mitigating the impacts of random mask absorber errors on lithography performance. First, the freeform source is represented by the linear superposition of Zernike polynomials to balance the source flexibility and computation burden. Then, a weighted cost functions consisting of PAE and PW which incorporates the impacts of random absorber errors is created. In view of the distribution laws of random absorber errors, a gradient-based statistical optimization algorithm is used to optimize the lithographic system parameters. The optimization procedures are carried out alternately. Simulations of 1D mask pattern at 14 nm technology node demonstrate that for the system with extreme absorber errors, the CDEs of the proposed method are reduced by 62.1% and 58.9%, respectively. In addition, the corresponding DOFs at EL = 5% are increased by 40.3% and 36.4%, respectively. The results manifest that the proposed method is effective in mitigating the CDEs induced by absorber errors and improving the PW.  
Conceptualization, N.S. and Y.L.; methodology, N.S. and E.L.; software, Y.S. and P.W.; validation, N.S. and T.L.; formal analysis, N.S. and Y.L.; investigation, Y.L. and L.L.; resources, L.L.; data curation, N.S. and Y.S.; writing--original draft preparation, N.S. and Y.L.; writing--review and editing, N.S. and Y.L.; visualization, E.L. and T.L.; supervision, Y.L.; project administration, Y.L. and L.L.; funding acquisition, Y.L.  
This research was funded by the General Program of National Natural Science Foundation of China (Grant No.61675026) and National Science and Technology Major Project (Grant No. 2017 ZX02101006-001).  
We gratefully acknowledge KLA-Tencor Corporation for providing academic use of PROLITH. We thank Mentor Graphics Corporation for providing academic use of Calibre.  
The authors declare no conflict interest.
###### Abstract  
Coal mine waste rocks, mainly broken gangue, can be used as filling materials to backfill into goafs. Under the overburden load, the backfill body is vulnerable to compressive deformation and particle breakage. With the increase in mining depth, the overlying strata will impose different loads on waste rock filling materials at different loading velocities, which further affect the material compressive deformation and particle breakage. In this paper, an experimental scheme and a loading device are designed to study the influence of loading stress and velocity on the compressive deformation and particle size distributions of the backfill materials before and after compression. The results show that the axial strain of the gangue filling materials increases rapidly with the axial stress and then gradually stabilizes, showing a logarithmic functional relationship. Increasing the loading velocity will destroy the contact structures among the gangue particles and cause a larger deformation to the filling materials. When the loading stress is relatively low (5 MPa), the gangue particles with a size larger than 20 mm have a stronger bearing capacity compared with particles of 16-20 mm, which are the first particles to be crushed under these conditions. Further increasing the loading velocity will increase the breakage degree of the filling materials. The breakage ratio (\(B_{\text{M}}\)) has a logarithmic functional relationship with the loading stress and the loading velocity. When the ground stress is lower than 5 MPa, the content of coarse particles should be increased to enhance the bearing capacity of the gangue materials; when the ground stress is higher than 10 MPa, the content of fine particles should be increased to reduce the porosity ratio and the particle breakage ratio.  
backfill materials; backfill mining; compression behaviour; particle breakage; loading stress; loading velocity +
Footnote †: journal: Applied Sciences
## 4 Numerical Results
We notice that both the selected modulation scheme and the phase noise process are irrelevant. Although the use of DF relays doubles the propagation distance, this leads to a severe increase of the MOD per hour values. It is also shown that the reliability increases for lower sensitivity thresholds and a weaker non-zero boresight pointing errors effect. Thus, according to the specific requirements in terms of the duration of the outage, we can make a decision--by means of an analysis based on the MOD metric--whether it is feasible to extend the FSO link length by using DF relay(s) or not.
## 1 Introduction
Many experimental [21] results showed that the chemotaxis of bacteria to petroleum hydrocarbon pollutants [22] can indeed strengthen the bioremediation of petroleum contaminated areas [23]. Therefore, in order to achieve a better remediation effect for petroleum-contaminated soil, it is very important to conduct theoretical research on the chemotaxis and migration of bacteria to petroleum hydrocarbon pollutants. In previous studies, the oil-water two-phase flow is often simplified as a single-phase water flow, and then the chemotaxis enrichment effect of bacteria in single-phase convection diffusion field is studied. The numerical model is quite different from the actual oil-water two-phase flow; the numerical simulation of two-phase flow ignores the concentration gradient of oil phase components dissolved in water at the oil-water interface, which hinders the study of bacterial chemotaxis under the condition of oil-water two-phase flow. In this paper, the experimental phenomena (chemotaxis of bacteria to oil-water interface of high concentration petroleum hydrocarbon pollutants) observed and summarized by previous people are taken as the research background. Combined with the relevant mathematical models, the numerical simulation of chemotaxis bacteria migration in the oil-water two-phase diffusion flow field is carried out. The innovation of this study is to couple the three processes of oil-water two-phase flow, the diffusion and convection of pollutants in oil to water and the migration of chemotaxis bacteria, and to study the phenomenon of convection, dissolution and diffusion of oil-phase pollutants in water and the migration of chemotaxis bacteria in water during water flooding. This study provides a novel and improved numerical simulation method for the migration of chemotactic bacteria in the oil-water two-phase transfer field, provides simulation verification and support for the experimental phenomena of migration and aggregation of chemotactic bacteria in oil-contaminated areas, and provides a theoretical basis for the development of the bioremediation of oil-contaminated soil, based on bacterial chemotaxis.
###### Abstract  
Ceramic membranes and ion exchangers are effective at removing turbidity and ionic contaminants from water, respectively. In this study, we demonstrate the performance of a hybrid ion-exchange fabric/ceramic membrane system to treat metal ions and turbidity at the same time in synthetic wastewater. The removal rate of As(V) and Zn(II) by the ceramic membrane increased with solution pH, while turbidity was completely removed regardless of the solution pH. The main reaction of As(V) removal was adsorption at solution pH 6 and precipitation at solution pH 8, whereas phase-change was the predominant reaction for Zn(II) removal at both solution pH values. The removal efficiency of the ion-exchange fabric was affected by the solution pH, with the maximum removal capacity of As(V) occurring at solution pH 4. The As(V) adsorption capacity of the ion-exchange fabric reached equilibrium within 120 min. The ion-exchange capacity of the ion-exchange fabric was compared with commercial ion-exchange fibers. The regeneration efficiency of the ion-exchange fabric using 0.1 M NaCl solution was around 95% on average and decreased slightly as the number of regeneration cycles was increased. Over 80% of As(V) and Zn(II) were steadily removed at solution pH 6 by the hybrid ion-exchange fabric/ceramic membrane system. Reduced flow rate and removal capacity were recovered through a backwashing process during continuous treatment with the hybrid ion-exchange fabric/ceramic membrane system.  
Keywords:ion-exchange fabric; ceramic membrane; Zn(II) removal; As(V) removal; turbidity removal +
Footnote †: journal: Applied Sciences
## 2 Region, Data, Method
### Seismic Noise Parameters
#### 2.4.2 Visualization of the Seismic Noise Parameters Distribution  
For all four statistical parameters, daily GRD files were created, representing tables of their values at the nodes of a regular grid of 50 \(\times\) 50 nodes in size, covering the area in the latitude range of 50-64\({}^{\circ}\) N and in the longitude range of 155-168\({}^{\circ}\) E for the entire observation period. The distribution of each noise statistic over the territory, obtained by interpolating the median values of the parameters from the three stations closest to each node of the grid, was reflected on digital maps created using a geographic information system [44].  
When averaging daily maps over all days within a given time interval, averaged maps were obtained that characterize the features of noise parameters' changes over space for the corresponding time intervals. An analysis of the set of such maps for the same time interval and their variability in time in comparison with maps over a long-term period makes it possible to trace the features of the seismic noise parameters' distribution for the territory under consideration as a whole and in the areas of earthquake sources.  
When interpreting maps, we analyzed areas located at distances not exceeding the average minimum distance between network stations (120 km). The shaded area of the maps is limited by a line corresponding to the envelope of circles with centers in the regions of outlying stations and a radius of 120 km (Figure 3a). Such a limitation allowed us to uniformly adjust the coloring area on the maps (Figure 3b). On digital maps, only this selected area was colored and analyzed (Figure 4).  
Figure 3: Determination of the coloring area on maps showing the distribution of noise parameters. (**a**) circular areas with a radius of 120 km around seismic stations; (**b**) corresponding colored area (see text for explanation).  
Figure 4: Maps of seismic noise parameters’ distribution for 2011–2018 (left) and for 2019–2021 (right). (**a**) Generalized Hurst exponent \(\alpha\)**; (**b**) singularity spectrum support width \(\Delta\alpha\); (**c**) wavelet-based spectral exponent \(\beta\); and (**d**) normalized entropy of the squared orthogonal wavelet coefficients \(En\). The white circles show the earthquake epicenters (Table 3) that occurred over the corresponding time periods. Rectangles with a coordinate grid show the area of noise parameters’ calculation. The coloring corresponding to the color scales was carried out for the area at a distance of no more than 120 km from the edge stations of the network (Figure 3).
# Recent Advances in Plasmonic Sensor-Based Fiber Optic Probes for Biological Applications
## 4 Theoretical Framework
### SPR in Grating Configuration  
The in-plane wave vector of the incident electromagnetic field on the metal-dielectric interface is increased to match the associated surface plasmons by a diffraction grating, \(G\) as shown in Figure 5. The x-component of wave vector of the incident light, \(k_{x}\), is increased by \(G\) through the order of the diffraction order, \(m=+1\) to match that of the surface plasmons [45].  
Figure 4: (**a**) Otto configuration and (**b**) Kretschmann configuration for the excitation of surface plasmon at the metal-dielectric interface [23].  
The propagation constant of the electromagnetic field on the surface of the grating is given as  
\[k_{SPR}=\ k_{x}+mG\ \ \ \ k_{SPR}=\frac{2\pi}{\lambda}n_{1}\sin(\theta)+m\ \frac{2\pi}{\Lambda}, \tag{4}\]  
where \(k_{SPR}\) is the propagation constant of the diffracted light of the grating, \(k_{x}\) is the propagation constant of the electromagnetic field, \(m\) is the diffraction order (\(m=0\), \(\pm 1\), \(\pm 2\), \(\pm 3\),... ), \(G\) is the wave number of the grating, \(\Lambda\) is the grating period, and \(n_{1}\) is the refractive index of medium 1.
# Addressing Sustainability within Public Procurement of Food: A Systematic Literature Review
## 3 Results
### Content Analysis
#### 3.1.1 Objectives of the Articles  
Upon reviewing the articles, a number of themes emerged related to the objectives of the studies, see Figure 3. The most common objective among the reviewed articles, identified in 30 of the articles, was the 'evaluation of an implemented policy' aiming to improve food procurement. Examples of such policies include the _Farm to School_ program [34; 35], the _Balanced Menu Challenge_ in Maryland [36], and the _Food for Life Partnership_ program in the UK [37].  
'Exploring different policy options' was the second most frequently occurring objective, which was identified in 26 of the articles. Examples of these included policies to support local food in public catering [38], increasing the shares of organic foods [39], and examining opportunities to promote small and medium-sized enterprises (SME) through public procurement [28; 40]. 'Exploring good practice', i.e., reviewing previously successful or perceived beneficial examples of sustainable procurement, was the objective of five articles. These include using public procurement for human well-being and meeting environmental objectives [41], in addition to more specific practices for improving nutritional standards [42]. Other types of objectives included, e.g., 'practical examples' of how municipalities procure food [43; 44], 'how to write public procurement documents' [43; 45], and the 'development of procurement criteria' [44].  
Figure 2: Depiction of the methodology and found focus areas employed for the content and relational analyses.
## 2 State of the Art
### Examples of Framework Implementations with Dynamic Configurations
#### 2.4.1 ESP8266 IoT Framework
The web interface plays a vital role in the configuration manager's functionality, as it is dynamically generated based on the JSON file [23]. This allows users to view and modify configuration parameters in real time. When changes are submitted, the configuration manager processes them anew, enabling seamless interaction that simplifies the process of customizing device settings. This component thus enhances the flexibility and user experience of the ESP8266 IoT Framework, making it easier for developers to create adaptable IoT applications. Figure 4: ESP8266 IoT Framework architecture (adapted from [22]).
# Dual PID Adaptive Variable Impedance Constant Force Control for Grinding Robot
## 6 Experimental Study
### Slope Surface Constant Force Control  
The end contact force was controlled on the slope surface shown in Figure 12b. The desired force was set as \(f_{d}=-5\) N and the running time was 10 s. The control parameters of the CIC, AVIC, and DPAVIC methods were set as follows:  
* CIC: \(m=1,b=8,k=0\).
* AVIC: \(m=1,b=5,k=0,\sigma=0.003\).
* DPAVIC: \(m=1,b=5,k=0,\sigma=0.005\), \(k_{p}=0.4\), \(k_{d}=0.05\), \(k_{i}=0.001\), \(r=100\), \(h=0.01\).  
Figure 14 shows the control response curves of the end compensation displacement and the end contact force. It can be found that when CIC and AVIC are used, the overshoot of the system is 29.46% and 12.45%, respectively, and the force control error is 0.331 N and 0.247 N. When the DPAVIC force control strategy is adopted, the overshoot is less than 1.02%, and the error is within \(\pm 0.2\) N.
## 3 Results and Discussion
### Plant Growth-Promoting Essays  
The plant growth promotion test results are summarized in Table 3. Biofilm formation was the main parameter to consider, followed by plant growth-promotion features. Thirteen isolates showed a high capacity for biofilm formation using the crystal violet (CV) method (letter a). Positive PGP characteristics were analyzed to discriminate between these isolates, discarding ARI_A2-2, ARI_A4-11, and ARI_A20-13 isolates and selecting those with outstanding features. Subsequently, ten of the remaining isolates were tested for biofilm formation on the perlite mineral carrier, resulting in the selection of ARI_A20-3, ARI_A20-5, and ARI_A30-32 isolates for the pot essay, which showed excellent biofilm formation. These three isolates presented all the tested PGP characteristics except for the ARI_A20-3 isolate, which was reported to be a low IAA producer. This strain was selected to determine differences in growth compared to the other chosen isolates, as this feature is important for stimulating root elongation [66]. [PERSON] et al. reported an improvement in plant nutrient uptake, soil microbial properties, and enzymatic activities in the pomergnate rhizosphere against a pathogen using planktonic _Streptomyces_ consortia [67]. [PERSON] et al. highlighted the use of planktonic _Streptomyces_ griseorubens_ and _Nocardiopsis_ as PGP's in wheat, describing higher activity in root growth and IAA and siderophore producers [68]. The previously reported actinobacteria were similar to those used in this study; however, our strains were isolated from the avocado rhizosphere. In this study, the advantages of biofilm formation on a carrier were assessed.
# Effect of Phase Noise on the Optical Millimeter-Wave Signal in the DWDM-RoF System
## 2 Phase Noise and Phase Imbalance Effects
Theoretically, the phase imbalance affects the insertion losses and the amplitude of the mm-wave signal, as proved in this equation [18]:  
\[|\mathrm{A}|=1+2\ \gamma^{2}-2\gamma+2\gamma(1-\gamma)\cos\varphi \tag{6}\]  
where A is the amplitude of the signal and \(\gamma\) is the splitting ratio of the MZM scheme. In addition, phase imbalance causes a high phase noise in the mm-wave signal [20]. Low phase noise is the key requirement in modern mm-wave and microwave communication systems to ensure the adequate recovery of the transmitted signals. Thus, low phase noise is essential to enable an efficient system. In general, phase noise can be defined as the frequency-domain representation of random fluctuations in the phase of a waveform. In a simulation system, the phase noise can be calculated using the signal analyzer in the frequency domain. In addition, other parameters such as signal-to-noise ratio (SNR) and error vector magnitude (EVM) have been used to estimate the phase noise [20; 28; 29; 30], while another study used optical signal to noise ratio (OSNR) to describe the noise in the signal [31]. Hence, the effect of phase noise on the optical mm wave can be calculated by identifying the equations of the EVM and SNR values, as expressed in the following equations [20; 30]:  
\[\Delta\varphi=2\pi n\Delta\mathrm{L}/\lambda \tag{1}\]0  
\[\Delta\varphi=2\pi n\Delta\mathrm{L}/\lambda \tag{1}\]1  
where \(\varphi\) is the phase imbalance and \(\delta\) is the phase noise of the mm-wave signal and both affect the EVM. From Equations (7) and (8), the EVM can be expressed by:  
\[\Delta\varphi=2\pi n\Delta\mathrm{L}/\lambda \tag{1}\]2Furthermore, the equations of SNR, EVM and OSNR can be expressed by [29; 32]:  
\[\Delta\varphi=2\pi n\Delta\mathrm{L}/\lambda \tag{1}\]3  
\[\Delta\varphi=2\pi n\Delta\mathrm{L}/\lambda \tag{1}\]4  
and  
\[\Delta\varphi=2\pi n\Delta\mathrm{L}/\lambda \tag{1}\]5  
According to the theoretical expressions, the phase imbalance affects the insertion losses of the mm-wave signal and the amplitude of the signal, as shown in Equations (5) and (6). Equation (7) proves that phase imbalance affects the EVM, where phase imbalance is an important parameter to estimate phase noise. In addition, Equations (8) and (9) show that the phase noise is influenced by the SNR and the phase imbalance of the mm-wave signal. In conclusion, the theoretical expressions shown prove that phase imbalance results in phase noise. The phase noise of the mm-wave signal can be analyzed using SNR and EVM parameters to enhance the results of phase noise from the signal analyzer in the simulated system. The following section discusses the system setup and the implementation of the mm wave in the DWDM-RoF system.
## 4 Discussion
### Clinical Relevance  
From a clinical perspective, the primary focus of rehabilitation should be on improving PC and enhancing the motor system's adaptability to dynamic demands [44]. Deficits in stability and adaptability, commonly observed in stroke survivors, highlight the need for targeted interventions addressing lateral stability during transitions such as GI and intersegmental coordination during complex tasks [17]. The inability to effectively adjust to dynamic postural demands often results in compensatory motor strategies that, while stabilizing in the short term, limit flexibility and increase the risk of falls and functional limitations [20].  
Rehabilitation based on linear approaches, traditionally aimed to reduce instability or variability, play a key role in addressing immediate biomechanical impairments. These methods, which focus on minimizing CoP displacement, improving joint ROM, or increasing muscle strength, are effective for stabilizing the postural system [4; 18; 177; 178]. However, their limitations become apparent when dealing with dynamic, real-world demands, as they may inadvertently reinforce rigid motor patterns [6; 104; 179].  
In contrast, the intervention based on a non-linear approach emphasizes adaptability and flexibility, which are essential for functional recovery [13]. These methods capture the dynamic organization of PC by promoting variability within functional limits, addressing the constrained dynamic range and impaired neuromuscular coordination commonly observed in stroke survivors. Rooted in dynamic systems theory, this approach considers movement and PC as emergent properties arising from interactions between the individual, task, and environment [6,44]. By targeting the interdependence of sensory, motor, and cognitive subsystems, these interventions focus on system-wide complexity and adaptability rather than isolated deficits [44]. It fosters long-term resilience, enabling the motor system to effectively respond to dynamic and unpredictable environments, instead of merely optimizing performance under static or controlled conditions [6,180].  
By integrating linear and non-linear approaches, clinicians can create a comprehensive framework for intervention. Linear strategies are essential for addressing immediate biomechanical impairments, while non-linear methods target the adaptability and flexibility required for functional recovery. Together, these complementary approaches provide a robust foundation for improving both stability and adaptability in stroke survivors, supporting long-term functional outcomes [44].