esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
The treatment of textile wastewater (TWW) loaded with recalcitrant azo dyes in biogeochemical systems (BES) rather than in physicochemical processes is a low-cost and environmentally friendly process. The main objective of this study is to investigate the potential of different saline sediments collected from extreme Tunisian environments for the formation of bioanodes capable of simultaneous azo dyes degradation and electric current generation in synthetic (STWW) and real textile wastewaters (RTWW) characterized by a varied composition of azo dyes and a high salinity. The obtained bioanodes and analytes were studied comparatively by electrochemical, microscopic, analytical, and molecular tools.Based on the UV-visible spectra analysis, the breakdown of the azo bond was confirmed. With RTWW, the BES achieved a chemical oxygen demand (COD) abatement rate of 85%with a current density of 2.5 A/m\({}^{2}\). Microbial community analysis indicated that a diverse community of bacteria was active for effluent treatment coupled with energy production. At the phylum level, the electrodes were primarily colonized by proteobacteria and firmicules, which are the two phyla most involved in bioremediation. The analysis of the microbial community also showed the abundance of _Marinibacter_ hydrocarbonsticus and _Marinibacter_ sp. species characterized by their high metabolic capacity, tolerance to extremophilic conditions, and role in hydrocarbon degradation.  
microbial electrochemical systems; halophilic inoculums; textile wastewater; energy recovery; azo dyes degradation
# An Attention-Based Convolutional Neural Network for Acute Lymphoblastic Leukemia Classification
## 3 Materials and Methods  
### Dataset Description  
We have used the publicly available dataset C-NMC 2019. The dataset is released by the cancer imaging archive (TCIA) for the ALL challenge competition. The objective of this competition is to create a computer-aided design (CAD) system to differentiate the normal cells from the leukemic blast (malignant cells) in microscopic images of blood clotting. Both training and test images have been processed to 24-bit RGB format with a consistent resolution of 450 \(\times\) 450 pixels. Errors in lighting, uneven staining, and image noise have been resolved using the methods given by [11; 12]. The images in this dataset were labeled as normal or malignant by an experienced oncologist. The dataset consists of 10,661 single cell images collected from 76 individual subjects, whereas 7272 images were taken from 47 patients having ALL, and the rest 3389 were taken from 26 healthy subjects. The C-NMC dataset includes a considerably large number of images that can help in designing a robust diagnostic ALL classifier. In our experiment, the dataset is divided into 7 folds based on subject-level variability as shown in Table 1. To avoid overfitting and to make the dataset balanced, we applied different data augmentation techniques.
# Privacy-Preserving Federated Learning Using Homomorphic Encryption
## 6 Performance Analysis
### Overhead Comparison  
Compared with the PPDL system in [2] that used the HE scheme, the proposed technique requires additional overhead to allow clients to use different private keys. In the proposed system, a certain degree of computational overhead for cooperative decryption and encryption processes is added, and the communication overhead is also added for the data exchanges between the CS and the CPs. The computational and communication overhead analysis was performed in Sections 6.1.2 and 6.2.2, respectively. The computational overhead comparison between the PPDL system and the proposed system is shown in Section 7.1, and the communication overhead between the CS and the CP is shown in Table 1.
# Framework for Developing Bio-Inspired Morphologies for Walking Robots
## 6 Phase: Analysis
### Movement Versatility  
To investigate the models' _Movement versatility_, it was tested how far forward and backward the end-effector of the legs can reach on a flat surface before any of the motors reach the maximum torque output of 4.8 Nm and are overloaded (Figure 10-max line). This highlighted the step ranges that can be used in future gait controllers. Therefore, the legs were set to step in a line 0.08 m below and 0.20 m lateral to their origin point (Figure 9), which creates a path where the legs do not collide with the rest of the robot. Figure 9 represents static stances, and therefore do not include additional torques from when the leg was moving the body forwards or backwards.  
Figure 9: The CoppeliaSim simulation setup used throughout the analysis (Section 6) for measuring and comparing the motor torques of legs with a (**a**) template morphology and (**b**) anchor morphology. Each leg was loaded with 2.0 kg, and their origin point was positioned 0.08 m above ground. The stepping intervals of the first tests (Section 6.1) are also depicted, where the stepping line is 0.20 m lateral to the origin point. The white arrows indicate forward movement direction.  
The template morphology can perform steps of 0.18 m before being overloaded, while the anchor morphology can perform steps of 0.27 m (Figure 9-pink line and Figure 10-filled area). Hence, the anchor morphology is capable of performing 50.0% longer steps. Meanwhile, this causes a higher total torque output for the anchor morphology (Figure 11) and, thereby, a higher power consumption.
## 6 Results and Discussions
On the fully overcast day, both EOTP and PVP were equal at 42.99%, indicating a directly proportional relationship between system operation and energy availability. Table 5 presents the total number of pump start/stop events--both theoretical and measured--per hour across four representative days. Theoretical data indicate that, except on a clear-sky day, the numbers of start/stop cycles exceed the manufacturer's recommended limit of eight starts per hour, as specified in the pump data sheet. In contrast, measured data show that this threshold was never exceeded, with a maximum of five starts per hour. This discrepancy highlights the conservative nature of the real-time control strategy, which incorporates a protective mechanism to limit start attempts. Specifically, after two failed start attempts, the system initiates a 10 min delay before retrying. If a subsequent attempt fails, a 20 min delay follows and the counter resets. This strategy effectively caps the maximum number of starts to six per hour (e.g., attempts at 0 [twice], 10, 30 [twice], 40 and 60 [twice] minutes). These protective constraints, designed to extend the operational life of the hydraulic system, inherently reduce the responsiveness of the system under variable irradiance conditions. As a result, the theoretical values for operating time and pumped volume are only closely matched under clear-sky conditions. On cloudy days, both metrics drop significantly, with PVP and EOTP dropping from 88% under a single dense, slow-moving cloud to 77% under frequent fast-moving clouds and to 43% on fully overcast days. The IEC 62253 standard provides a framework for evaluating the performance of photovoltaic pumping systems (PVPSs), but it is limited to steady-state conditions and largely omits transient behaviors. Although it includes a test for starting power, this is confined to identifying the minimum power required to initiate operation, without addressing the broader dynamics of system start-up or rapid power fluctuations. In contrast, the methodology proposed in this study introduces a non-intrusive, high-resolution monitoring approach capable of capturing both steady-state and transient operational regimes. By acquiring electrical, hydraulic and environmental data at one-second intervals through integrated data acquisition systems and sensors, this method allows for continuous and automated performance evaluation over extended periods, independent of environmental conditions. It further enables detection of electrical and hydraulic shocks and provides a robust platform for dynamic analysis, system optimization and real-time supervision. The enhanced temporal resolution and operational insight offered by this approach substantially exceed the capabilities of the current IEC 62253 standard. Table 6 presents a point-by-point comparison between the IEC 62253 standard and the proposed non-intrusive, high-resolution methodology for evaluating the performance of photovoltaic pumping systems (PVPSs).
###### Abstract  
This paper presents the design and validation of a novel specialized fixture device for machining inclined planes with barrel cutters on 3-axis CNC machine tools. Barrel milling, also known as Parabolic Performance Cutting (PPC), is extensively used on 5-axis machines to enhance the efficiency of machining complex surfaces. While significant research has focused on optimizing barrel milling for aspects such as surface roughness and cutting forces, implementing this technique on 3-axis machines poses a challenge due to limitations in tool orientation. To overcome this, an innovative adaptable device was designed, enabling precise workpiece orientation relative to the barrel cutter. To overcome this limitation, an adaptable device was designed that enables precise workpiece orientation relative to the barrel cutter. The device utilizes interchangeable locating elements for different cutter programming angles (such as 18\({}^{\circ}\), 20\({}^{\circ}\), and 42.5\({}^{\circ}\)), thereby ensuring correct workpiece positioning. Rigid workpiece clamping is provided by the device's mechanism to maintain precise workpiece positioning during machining, and probing surfaces are integrated into the device to facilitate the definition of the coordinate system necessary for CNC machine programming. Device control was performed using a Hexagon RA-7312 3D measuring arm. Inspection results indicated minimal dimensional deviations (e.g., surface flatness between 0.002 mm and 0.012 mm) and high angular accuracy (e.g., angular non-closure of 0.006\({}^{\circ}\)). The designed device enables the effective and precise use of barrel cutters on 3-axis CNC machines, offering a previously unavailable practical and economical solution for cutting tool tests and cutting regime studies.  
barrel milling; 3-axis CNC machining; fixture design; workpiece orientation; dimensional validation 2020
# A Critical Review of Flood Risk Management and the Selection of Suitable Measures
## 3 Risk-Based Flood Management
### Assorting Suitable Measures  
Detailed risk assessment of all possible flood management measures is not economically feasible. A competent professional with knowledge of the domain of flood management while using available data can discard certain flood management options without going into a deep analysis [58]. Similarly, certain measures are preferable under certain prevailing conditions. For example, floodproofing of individual areas within the floodplain has been proven to be more economically feasible compared with flood protection by constructing dykes under conditions where the floodplain is not densely populated. Some measures are highly counterproductive in certain situations. One example is constructing a dyke in a mountainous area, where flood levels fluctuate more rapidly and chances of dyke failure are high. In this case, the dyke prevents the floodwaters from receding once the flood peak has passed. The selection of a suitable measure is done by considering the appraisal needs and the contribution of the measures in achieving appraisal objectives.  
Different flood management options should be evaluated one by one by approximation. Developing options correctly can save time and resources. The following steps are recommended in order to develop the most suitable combination suited to appraisal needs:  
1. Identification of a wide range of options considering the topographical, environmental, social, and cost-effective constraints
2. Screening out impractical and infeasible options
3. Shortlisting options that most probably can achieve the best use of resources
4. Development of a wide range of options by combining different combinations of measures  
Figure 4 provides a rule-of-thumb guideline example in order to shortlist the measures under the predominant conditions of the floodplain. The data are compiled based on extensive literature review [2; 5; 16; 19; 29; 33; 59; 60; 61; 62; 63; 64] and field experts' opinions. Plenty of case studies were observed and their preferred approaches were noted. Figure 4 is developed after detailed brainstorming sessions with field experts. This guidance is tentative and is based on a range of typical benefits, including reduced costs and additional socio-environmental benefits.  
Figure 4: A practical example of flood management option priorities about different characteristics of the floodplain.
## 2 Materials and Methods
### Experimental Validation  
The DEFORM-3D simulation results were validated for low and high strain rate conditions. For the low strain rates (0.1 to 10/s), the peak stress from published flow stress data for three titanium (\(\alpha\) + \(\beta\)) alloys--Ti-4.5 Al-1V-3 Fe, Ti-6 Al-1V-3 Fe, and Ti-6 Al-4V--were used [16; 17; 18; 19]. The data were generated from uniaxial compression testing on the Gleeble 3500 thermomechanical simulator at deformation temperatures of 800 to 950 \({}^{\circ}\)C. For the high strain rate test, uniaxial compression testing was conducted on commercial-grade Ti-6 Al-4V alloy with a complex initial microstructure. The complex microstructure consisted of nearly equiaxed alpha grains (diameter = 5 \(\pm\) 2 \(\upmu\)m), elongated alpha grains (length between 12 and 49 \(\upmu\)m), and a network of intergranular beta phase. The test samples were 8 mm in diameter and 12 mm in length. Uniaxial compression testing conducted on the same machine was carried out at a deformation temperature of 900 \({}^{\circ}\)C, total strain of 0.6,  
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**Ti Alloy** & \(\alpha\) & \(\beta\) & \(n^{\prime}\) & \(n\) & \(Q\) (kJ/mol) & \(A\) \\ \hline Ti-4.5 Al-1V-3 Fe & 0.008 & 0.04 & 4.958 & 3.335 & 465 & \(1.20\times 10^{20}\) \\ \hline Ti-6 Al-1V-3 Fe & 0.006 & 0.03 & 5.595 & 3.808 & 487 & \(1.50\times 10^{21}\) \\ \hline Ti-6 Al-4V & 0.005 & 0.04 & 7.569 & 5.057 & 620 & \(1.44\times 10^{28}\) \\ \hline \end{tabular}
\end{table}
Table 1: Constitutive parameters for titanium alloys investigated [20].  
and strain rates of 20 and 50/s. The 900 \({}^{\circ}\)C deformation temperature was chosen since it was previously reported as a safe deformation temperature for the three titanium alloys [20]. The samples were heated directly to the deformation temperature and then held for 180 s prior to deformation for homogenization, and thereafter deformed at specified strain rates. A chromel-alumel (type K) thermocouple was spot-welded to the midspan of the samples to measure the temperature. Graphite foil and nickel paste were placed between the anvils and the samples to minimize frictional effects on flow stress. After deformation, the flow stress of the deformed samples was corrected for frictional effects following Obiko [10].  
The experimentally determined peak flow stress was compared with the DEFORM-3D simulation peak stress. Optical microscopy was performed on the deformed samples following standard metallographic procedures described by [PERSON] et al. [21].
# A Review of Physical Layer Security Techniques for Internet of Things: Challenges and Solutions
## 4 Promising PLS Solutions for IoT  
As described in the previous section, IoT has four unique features compared to traditional wireless networks: low cost, wide-range coverage, massive connection, and diversified services. In what follows, we would like to highlight three emerging PLS techniques that match these features well and have great potential in future applications.
## 3 Numerical Simulation and Its Verification  
### Numerical Simulation Settings  
The ejector geometric parameters and experimental data were based on [PERSON] et al. [1]. The structure parameters are summarized in Table 1. The model was established using ICEM and solved using FLUENT 15.0. The implicit density-based solver was selected to compute flow-governing equations. A 2D axisymmetric geometry was used to save time and computing costs. The pressure-inlet boundary condition was applied to the primary and secondary inlets. Turbulence intensity I was 5% for the primary fluid and 2% for the secondary fluid [32]. The pressure-outlet boundary condition was applied to the outlet of the ejector. The inner wall was set as adiabatic and no-slip. The near-wall treatment did not need to be set because it was already implemented in the mathematical structure of the \(k\)-\(\omega\) SST turbulence model [37]. All the initial boundary conditions are listed in Table 2. The second-order upwind scheme was used for all e convection terms, and central difference discretization was applied for diffusion terms. Discrete systems were solved using the Gauss-Seidel method. All the calculated residuals were less than 10e-6 for the continuity equation, energy equation, momentum equation, and turbulent kinetic energy. Moreover, the flow mass difference between the inlet and outlet boundaries must be less than \(10\times 10^{-7}\).  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Geometrical Parameters** & **Value (mm)** \\ \hline Diameter of nozzle inlet section & 7.75 \\ Diameter of nozzle outlet section & 8 \\ Diameter of nozzle throat & 2 \\ Nozzle exit position & 35 \\ Diameter of mixing chamber inlet section & 24 \\ Diameter of throat & 19 \\ Length of mixing chamber & 130 \\ Length of throat & 95 \\ Length of diffuser & 180 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Geometrical parameters of the steam ejector.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Steam** & **Temperature (\({}^{\circ}\)C)** & **Pressure (kPa)** & **Air Mass Fraction** \\ \hline Primary & 120/130 & 198/270 & 0/0.1/0.3/0.5 \\ Secondary & 5/10 & 1.2 & 0/0.1/0.3/0.5 \\ Discharge & - & 2.0/6.5 & - \\ \hline \hline \end{tabular}
\end{table}
Table 2: Initial values of steam pressure and temperature.
## 5 Changing Land Cover and Transition Zones
The evaluation of a global forest cover map based on Landsat showed that forests closely matched canopies of at least 2 m in height in the tundra-taiga transition zone [98]. Apart from distinguishing forest from non-forested areas, shrubs were studied in the transition zone. [PERSON] et al. [99] applied a random forest approach to map small and tall shrubs (>1 m) as their distribution reflects climatic conditions. Very high resolution datasets reveal shrub encroachment on disturbance sites [87]. The tundra-taiga transition area is also of interest to reindeer herding. Pastures, especially the abundance of lichens, have therefore been investigated with satellite data. For herding purposes, winter and summer pastures (different vegetation communities as a proxy for certain lichen types, on trees or within tundra heath) have been distinguished by [PERSON] et al. [100] applying supervised (maximum-likelihood) classification. Hybrid classification has been used by [PERSON] et al. [101] and [PERSON] et al. [102] for grazing impact assessment. Grazing impact has also been addressed by the analysis of the fractional coverage of fruitcose lichens with supervised (maximum-likelihood) classification [103].
## 1 Introduction
* Our implementation provides statistical metrics, such as goal rate, for detailed comparison and analysis, with the flexibility to extend output to additional data such as trajectory paths and robot LiDAR readings. Moreover, our implementation can be extended to output additional metrics such as trajectory data, robot LiDAR data, etc. The insights gleaned from this study are invaluable to practitioners and researchers for their specific robotic navigation tasks. * We conducted extensive physical experiments to evaluate the real-world navigation performance under varied environment configurations. Our results show that the agent trained in simulation can achieve a success rate of over 88% in our physical environments. Simulated training is not restricted by physical constraints such as the robot's battery power, and is more efficient in training data collection. This finding demonstrates the value of simulated training with RL for real world mobile navigation. The organization of the paper is provided as follows. The algorithm background of PPO is presented in Section 2. The automated framework development and the integration of it with the PPO algorithm for robot navigation is presented in Section 3. The experimental set-up along with the set parameters for each environment is presented in Section 4. The results with relevant figures are provided in Section 5. Finally, Section 6 concludes the work.
# Target Recognition and Navigation Path Optimization Based on NAO Robot
## 2 NAO Robot's Monocular Vision Spatial Target Localization
### Target Recognition  
In the image preprocessing stage, the red image areas have been marked, but these areas contain some interference, which needs to be further extracted through geometric features. Hough circle detection [29; 30] is used in this paper to further extract the target and obtain its central coordinates. In the process of using the Hough circle transformation to detect the shape, each boundary pixel \((x,y)\) of the image is extracted with the Canny detection algorithm, and then judged according to Equation (1). If the three parameters of the detection circle, namely C \((x_{0},y_{0},r)\), meet Equation (1), the value of the accumulator will be increased by 1, and finally, a group of peaks will be selected, which is the required center coordinates and radius.  
\[(x-x_{0})^{2}+(y-y_{0})^{2}-r^{2}\leq\delta \tag{1}\]  
During the experiment, many small balls may be detected using the Hough circle transform, which may also contain some noise, so the results need to be further processed. For each red ball detected, a green circumscribed square, with the center of the red ball and 4 times the radius of the red ball as the side length, is drawn. Then, we calculate the ratio of red and green pixels in the square area. In the ideal case, the proportion of red pixels is 0.196, as shown in Equation (2), and the proportion of green pixels is 0.804. In the actual detection, there are many uncertain factors (such as circle detection error, a color change caused by uneven light, interferences, etc.), which are difficult to achieve in the ideal situation. During the experiment, we set the condition that the percentage of red and green pixels is 0.12 and 0.1, respectively.  
\[(\pi r^{2})/(16r^{2})=0.196 \tag{2}\]
# Privacy-Preserving Electricity Trading for Connected Microgrids
## 5 System Description
### Actors  
The microgrid is composed of the following actors:  
* Substation: This party is managed by the electricity provider (the DSO). It coordinates the trading system. It is in charge of matching electricity offers and demands. When required, it asks the global grid to pour additional electricity into the microgrid. In case of surplus, the excess of energy may be fed into the global grid. A microgrid includes just one substation.
* Smart meters: A dwelling is equipped with a smart meter which can both take or pour energy. It can also send and receive messages through the communication channel. When the individual production exceeds the individual demand, smart meters sell their surplus. Otherwise, they request and pay for additional energy.