esa-sceva/satcom-chunk-collection huggingface dataset:
# Exploring Virtual Environments to Assess the Quality of Public Spaces
## 3 Materials and Methods
### Measures: Indicators of Public Spaces Quality
#### 3.3.1 Pedestrian Level of Service PLOS--Trip Quality Method
Thirdly, buffer areas were also used to obtain the pedestrian level of service indicator. Buffer areas are spaces in which people can stop to rest or converse with others while being at a sufficient distance from vehicular traffic without interrupting the pedestrian flow on sidewalks or public spaces. The presence of this buffer zone between a pedestrian and the flow of moving vehicles enhances pedestrian safety and comfort. If the distance is accompanied by solid objects between pedestrians and traffic, this physically improves safety as it reduces the likelihood of a pedestrian-involving accident occurrence. Additionally, perceived safety, which goes hand-in-hand with perceived comfort, is proportional to the size of buffer areas, as pedestrians feel safer when they feel further away from traffic. Objects that increase the feeling of safety in buffer zones include large trees, on-street parking spots, and other large street furniture elements. To assess this, the question used was \"Rate the availability of buffer areas* for pedestrians to wait or converse in the space\". The last factors used to compute the PLOS-TQM indicator were shade and trees. The presence of shade within the walkway creates an atmosphere of comfort for pedestrians on summer days. In addition to protecting pedestrians from excess heat, it also adds a green aesthetic to the walkways and contributes to the concept of solid objects in the buffer space. This is found in the questionnaire through the questionaite the sufficiency of shade and shelter provided along the area\". The questions were asked for each of the three POVs for both their real videos and their immersive virtual environment through our mandated questionnaire. To summarize, the questions compiled in this indicator were the following. * How simple is it to understand the pedestrian path network in the area? * How simple is it to understand the function* of the surrounding public spaces in the area? * Rate the availability of buffer areas* for pedestrians to wait or conversate in the space. * Rate the sufficiency of shade and shelter provided along the area. A description of what is meant by \"function\" and \"buffer area\" was given as follows. Examples of functions are: commercial, residential, educational, leisure, and touristic. Buffer areas: Spaces in which people can stop to rest or conversate while being at a sufficient distance from vehicular traffic without interrupting pedestrian flow.
# Numerical Investigations of Micro-Scale Diffusion Combustion: A Brief Review
## 4 Conclusions  
The increasing attentions to the combustion-based micro power generation systems, mainly due to the high energy density of hydrocarbon fuels, has persuaded researchers to expand their efforts to investigate the combustion characteristics at micro scales and seek ways to achieve stabilized combustion and optimize the power generation process in such devices. This work summarized the pertinent investigations revolved around non-premixed (diffusion) combustion regime, which is most commonly employed in practical systems. With the complexities and expenses associated to the experimental analyses, the application of numerical simulations to model combustion at micro scales, especially diffusion flames which are the focus of this work, has been widely considered and shown to provide promising insights. The review in this paper confirmed the strength of the numerical simulations, to both qualitatively and quantitatively predict the flame behavior if used properly. Using different numerical approaches over the past couple of decades, diffusion combustion at micro scale has been extensively studied and characterized. Such case are found to be very sensitive to the operating conditions, i.e., the flame characteristics, stability conditions, and flammability limits can be altered by varying different parameters or the system configuration. For example, conjugate heat transfer or heat recirculation were found to have strong impacts on the flammability limit. Various studies showed that changing the fuel type, fuel/air composition, inlet velocity, burner geometry or material, etc. can change the flame characteristics such flame location, flame height, flame temperature and flame stability considerably. This review of the studies on the numerical investigations and approaches in diffusion combustion characteristics at micro scales presents a pathway for researchers in this field to more efficiently move forward with their research.  
Conceptualization, P.R.R., M.A. and A.M.A.; methodology, P.R.R., M.A. and A.M.A.; investigation, P.R.R., M.A. and A.M.A.; writing--original draft preparation, P.R.R.; writing--review and editing. P.R.R., M.A. and A.M.A.; funding acquisition, P.R.R., M.A. and A.M.A.  
This research received external funding by FAPESP through Project No. 2015/26842-3. [PERSON] acknowledges the funding by FCT under Project No. PTDC/EMS-ENE/3362/2014.  
**Acknowledgments:** [PERSON] acknowledges the funding by FAPESP through Project No. 2015/26842-3. [PERSON] acknowledges the funding by FCT under Project No. PTDC/EMS-ENE/3362/2014. [PERSON] acknowledges the support from Wayne State University for this publication.  
Figure 17: Numerical investigation on the thermo-chemical structures of methane-oxygen diffusion flame-streets in a microchannel by [PERSON] et al. [29]. (**Left**): Contours of OH mass fractions and heat release rate (HRR) on the sliced XY- and XZ-plane along the channel centerline; (**Right**): Effects of wall thermal conditions on flame behaviors.
# Evaluation of Garlic Landraces from Foggia Province (Puglia Region; Italy)
## 2 Materials and Methods  
### Description of Collecting Sites, Plant Materials, and Sampling  
Six landraces of garlic (_Allium sativum_ L.) were directly collected from local growers which had very small farms in marginal areas, in the province of Foggia, in the North of Puglia region (Italy), which lies geographically between 41\({}^{\circ}\)54\({}^{\prime}\)44\({}^{\prime\prime}\)N and 41\({}^{\circ}\)02\({}^{\prime}\)27\({}^{\prime\prime}\)N in latitude and 14\({}^{\circ}\)55\({}^{\prime}\)58\({}^{\prime\prime}\)E and 14\({}^{\circ}\)02\({}^{\prime}\)27\({}^{\prime\prime}\)E in longitude. All the interested growers had very small farms in marginal areas and all of them adopted low input agronomic practices such as minimum soil tillage, hand weed control and scarce or no use of irrigation, pesticides or fertilizers.  
Details of the collected landraces and the collecting sites are presented in Table 1. Bulbs of 'Spanish white garlic' ('Palmieri Import', Afragola (Na); Origin: Spain), widely available on the European and national market, was used as a reference standard. Pictures of the examined genotypes are shown in Figure S1.  
Samples of bulbs (3 \(\pm\) 0.5 kg per each genotype) were well mixed to obtain three independent replicates, each consisting of 15-40 bulbs. Morphological and biometrical measurements on cloves and bulbs were carried out on fresh material, dealing with 7-15 bulbs for each replicate. Chemical analyses of peeled cloves were performed in triplicate for each replicate, after being freeze-dried (CoolSafe SCANVAC, Labo0 Gene, Allerod, Denmark), powdered, packed in hermetic jars and then stored in the dark at \(-18\pm 1\)\({}^{\circ}\)C until the analyses were carried out.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
## 2 Materials and Methods
### Test Designs
#### 2.3.1 Test 1  
The first of the three tests, \"Test 1\", was based on the recognition, memorization, and comparison of letters (Figure 3A). The test started with a 1.5 s fixation cross. Next, 9 letters of the same size appeared for 3.5 s in 9 different positions, allowing participants to freely move their eyes. After this time, all of the letters disappeared except for the central reference letter. The objective of the test was to determine how many peripheral letters  
\begin{table}
\begin{tabular}{c c c c c c c} \hline  & **White TV** & **White LED** & **Blue TV** & **Blue LED** & **Red TV** & **Red LED** \\ \hline Irradiance (W/m\({}^{2}\)) & 1.20 & 1.00 & 0.33 & 0.39 & 0.28 & 0.80 \\ \hline Illuminance (lx) & 62.00 & & 76.00 & & 83.00 \\ \hline Luminance (cd/m\({}^{2}\)) & 350.37 & & 33.47 & & 71.00 \\ \hline \end{tabular}
\end{table}
Table 1: Results of irradiance, luminance, and illuminance in the corneal plane. The measurements of the luminaire were recorded at the corneal plane, whereas those of the television were taken on the screen.  
Figure 2: Normalized emission spectra of light sources for different lighting conditions.  
matched the central letter, with possible correct responses: press \"1\" if it was repeated once, \"2\" if it was repeated twice, and \"0\" if the central letter did not repeat among the peripherals. There was no time limit to respond, and participants had the option to respond from the moment the nine letters appeared.  
The test began with four practice attempts, allowing participants to adapt to the test and become familiar with pressing the different keys. Throughout the test, four attempts were made for each letter size, starting from VA 0.22 logMAR and increasing in steps of 0.05 logMAR up to VA 0.0 logMAR. To ensure standardization and efficiency, we used a fixed step size protocol in Test 1, avoiding the need for additional programming and aligning with typical VA testing methods.  
Owing to the screen resolution of the television where the tests were projected, easily recognizable letters were chosen starting from a VA of 0.10 logMAR to avoid distortion due to the small size or confusion caused by illuminated pixels. The selected letters were L, I, H, T, X, and F. This restriction did not apply to other VA levels. Additionally, a vertical bar was placed on both sides of each letter to make recognition more challenging due to the crowding phenomenon.  
The background color varied depending on the type of ambient lighting. Thus, for white lighting conditions, the background of the screen used for Test 1 was white; for red lighting conditions, it was red; and for blue ambient conditions, it was blue. Moreover, the letters were white for red and blue lighting conditions, whereas they were black for white ambient lighting. Therefore, to maintain consistent conditions across different illuminations, for the case of white ambient lighting in Test 1, two variations were used: white letters on a black background and black letters on a white background. The participants performed either one format or the other pseudorandomly, never both.
## 3 Fuzzy Set Theory-Based Risk Assessment System for Navigational Obstacles  
### Development of Framework for Risk Assessment System  
Figure 2 illustrates the development framework of a fuzzy set theory-based navigational obstacle risk assessment system that considers both the collision and pollution risks. The system comprises two models: a collision risk assessment model and pollution risk assessment model. First, the evaluation factors for the collision and pollution risks were extracted and defined using relevant laws and regulations, expert interviews, and ship transit data. Second, the respective assessment models were developed as follows. For the collision risk assessment model, the probability of a collision between a ship and a navigational obstacle was calculated using Monte Carlo simulation, and a regression model was built to establish the risk management criteria. The pollution risk assessment model identifies an evaluation index that focuses on the hazards presented by sunken ships and assesses the risk in stages. Finally, the risk indices derived from these two models were integrated to create a system that infers the comprehensive risk using the fuzzy set theory.
## 3 The Proposed Approach
### Using Linear Estimation with the Kalman filter  
The Kalman filter [29] is an approach used to minimize output variation by predicting the output based on previous values. Then, the output is updated based on the error between the measured output and the predicted output. The Kalman filter model is expressed in Equations (11) and (12):  
\[y_{1}^{\mathrm{t}}=D^{\mathrm{t}}y_{1}^{\mathrm{t-1}}+E^{\mathrm{t}}s^{\mathrm{ t}}+w_{1}^{\mathrm{t}} \tag{11}\]  
\[z_{1}^{\mathrm{t}}=C_{1}^{\mathrm{t}}y_{1}^{\mathrm{t}}+m_{1}^{\mathrm{t}} \tag{12}\]  
where \(y_{1}^{\mathrm{t}}\) is the state vector containing the abrasive nozzle position at time t; \(D^{\mathrm{t}}\) is the state transition matrix that applies the effect of the system state parameter(s) at time t \(-\) 1 on the system state at time t; \(E^{\mathrm{t}}\) is the control input matrix that applies the effect of the control input parameter(s) in the vector \(\mathbf{s}_{t}\) on the state vector; \(w_{1}^{\mathrm{t}}\) is the vector containing the process disturbance or noise terms for the parameter(s) in the state vector; \(z_{1}^{\mathrm{t}}\) is the measurement vector; \(C_{1}^{\mathrm{t}}\) is a matrix that transforms the state vector \(\mathbf{y}_{t}\) into the measurement unit; and \(m_{1}^{\mathrm{t}}\) is the vector containing the measurement noise terms for observation(s) in the measurement vector.  
In practical terms, the Kalman filter works by predicting the current state first. The prediction equation is given in Equation (13):  
\[\hat{y}_{1}^{-\mathrm{t}}=D^{\mathrm{t}}y_{1}^{\mathrm{t-1}}+E^{\mathrm{t}}s^ {\mathrm{t}} \tag{13}\]  
where \(\hat{y}_{1}^{-\mathrm{t}}\) is the predicted current state. Then, the confidence of the prediction, \(P^{-\mathrm{t}}\), is estimated by (14):  
\[P^{-\mathrm{t}}=D^{\mathrm{t}}P^{\mathrm{t-1}}D^{\mathrm{t}T}+W^{\mathrm{t}} \tag{14}\]  
Figure 4: An example of a guideline (dash) with a human-made line (solid).  
where \(\rm W^{t}\) is the covariance of the process noise, which is assumed to normally distribute with a zero mean. After the current state has been predicted by Equations (13) and (14), we can determine how good the prediction is by using the updating Equations (15)-(17) as follows:  
\[\rm K^{t}\rm=P^{-t}C^{t\rm T}\left(C^{t}P^{-t}C^{t\rm T}\rm+M^{t}\right)^{-1} \tag{15}\]  
\[\rm\hat{y}_{1}^{t}=\rm\hat{y}_{1}^{-t}\rm+K^{t}(z_{1}^{t}\rm-C^{t}\rm\hat{y}_{1 }^{-t}\rm) \tag{16}\]  
\[\rm P^{t}\rm=(I-K^{t}C^{t})P^{-t} \tag{17}\]  
where \(\rm K^{t}\) is the Kalman gain used in the updating process. The measurement noise is assumed to be normally distributed with a zero mean and covariance \(\rm M^{t}\).  
To apply the Kalman filter to the system, the quality measurement from stage 1, \(z_{1}^{t}\) (see Equations (1) and (2)), is taken as an input to the Kalman filter. Then, the output from the Kalman filter, \(\rm\hat{y}_{1}^{t}\), is set to be the stage output.
# Broken versus Non-Broken Time Reversal Symmetry: Irreversibility and Response
## 3 Time Reversible Dissipative Dynamics
This does not apply to systems made of a small number of elementary constituents, or for observations lasting only a short time. As a matter of fact, fluctuations of the dissipation have been observed in macroscopic systems Reference [17], and other kinds of microscopic fluctuations are commonly observed in macroscopic objects (see e.g., Reference [18] and references therein). It is interesting to note that the symmetry defined by Equation (10) leaves invariant the Hamiltonian of a system subject to a constant magnetic field [19], so that results directly related to TRI continue to hold if a magnetic field is switched on. This makes the Casimir modification of the Onsager reciprocal relations unnecessary (albeit obviously correct), unlike standard wisdom tells [20]: as long as one is interested in the Onsager reciprocal relations, Ref. [19] shows that such a symmetry can be experimentally verified on a single system, not combining the results of two experiments with opposite magnetic fields [this work complements that of Reference [21] in which the TP parity was found to be sufficient for the validity of the Onsager reciprocal relations]. Analogously, dissipation in the presence of a constant magnetic field will result in the validity of the FR for a single system, making unnecessary the comparison of the statistics concerning two experiments with opposite magnetic fields [22]. This does not exclude the fact that different kinds of applications may still require the Casimir approach. The point here is that the time reversal symmetry of the microscopic dynamics persists even in situations in which it was usually thought to fail. Indeed, we are now going to show that TRI holds in rotating reference frames. Consider a free particle with position \(\vec{r}=(x,y,z)\) in a reference frame rotating with constant angular velocity \(\vec{\omega}=(0,0,\omega)\). The Lagrangian takes the form:  
\[L=\frac{1}{2}m\dot{\vec{r}}^{2}=\frac{1}{2}m[(\dot{x}-\omega y)^{2}+(\dot{y}- \omega x)^{2}+\dot{z}^{2}], \tag{12}\]  
from which the following dynamical equations are derived:  
\[ \begin{cases}p^{x}=m(\dot{x}-\omega y),\\ p^{y}=m(\dot{y}+\omega x),\\ p^{z}=m\dot{z},\\ p^{x}=m(\dot{y}+\omega x)\omega,\\ p^{y}=m(\dot{x}-\omega y)(-\omega),\\ \dot{p}^{z}=0.\end{cases}  \tag{13}\]  
One notices that such equations have the same structure of those concerning a magnetic field, hence they are likewise time reversal invariant with TRI symmetry operator \(i\) given by Equation (10). In the next section, we will consider the case of time dependent perturbations.
## 5 Discussion  
### Geoelectric Strike Direction Dependent of the Periods  
#### 5.1.1 Comparison of Geoelectric Strike with Strike Determined from Other Studies  
Magnetotelluric data analysis allowed us to infer the subsurface conductivity structure with evidence of defined geoelectric strike and anisotropy direction beneath Asal rift. The strike orientation estimated from the phase tensor for short period is north-east close to N40\({}^{\circ}\)E, whereas for the long periods it is north-north-east (Figure 3). While the geoelectric strike derived from both the invariant impedance and decomposition model showed the same results, a mean strike direction around N120\({}^{\circ}\)E can be deduced for the long periods (Figure 4). The majority of the induction vectors are parallel to the geoelectric strike derived from phase tensor with low skew angle (Figure 5). The latter is generally described as a consequence of a dominant 2D regional conductivity structure in the area [22,25]. Structural, geological and bathymetry studies conducted in the Asal-Ghoubbet indicated average strike of fissures and normal faults of N125\({}^{\circ}\)E [13,15,19]. Seismicity was recorded from 6 November to 10 November 1978, with epicenters trending along a N120\({}^{\circ}\)E alignment in the Ghoubbet Bay [13,19], which is believed to correspond to the direction of the dyke injection. The seismicity continued for 60 days after the 10 November 1978 event, in the eastern part of the Asal-Ghoubbet rift, particularly in the Ghoubbet Pass and the transfer zone between Asal-Ghoubbet and Tadjourah submerged rift segment [13]. In addition, telluric field polarized in the direction of N100\({}^{\circ}\)E was determined by [5] with the Telluric-Telluric (TT) method. This strike is close to the average strike determined from the decomposition model and the impedance invariant for the long periods and can be considered an approximate strike with the strike calculated from the phase tensor for the long period. Furthermore, it is surprising to note that some MT stations have an average strike of N120\({}^{\circ}\)E for the short periods (approximately at the depth of upper and lower crust) and those MT stations are close to the Major and Minor faults(Figures 1 and 4). This indicates that a causal relationship between diking, striking, fracturing and dipping may exist. Moreover, in both Asal and Ghoubbet, normal faults are dipping to the north-east direction [15; 19] and the mean strike calculated from all dimensionality analysis for the short-intermediate periods is approximately north-east and north-north-east (Figures 3-5 and 7). Seismological studies have proposed a dipping angle of N50\({}^{\circ}\)E for normal faults far from the rift axis and also suggested sub-vertical dipping normal faults close to the rift axis [4]. Kinematics and 3D dimensional deformation of Feiale volcano (Figure 1) over the past 300 kyr indicated a spreading rate range of 17-30 mm yr\({}^{-1}\) in the N40\({}^{\circ}\)E direction that mainly accommodates the separation between Arabia and Somali plates [16].
## 4 Software System
### Coordinate Transformation from Scanning Frame to External Work Coordinate System
#### 4.3.1 Transformation from Scanning Frame to Tool Coordinate System  
The spraying path data derived for the lasted upper are initially defined in the coordinate system established by the three-sided laser scanning system described in Section 4.1.1. However, for practical robotic execution, this coordinate system must be transformed into the tool coordinate system of the robotic arm.  
In this study, the 3D scanning system and the robotic arm are located in physically separate environments, making it infeasible to directly acquire common reference points in both coordinate systems for conventional calibration. To overcome this limitation, a  
Figure 20: The 3D point cloud of the lasted upper with computed surface normal vectors. Yellow lines represent the surface normals along the generated adhesive spraying path. (color coding: blue-bottom; green-left side; red-right side).  
portable calibration fixture with known geometric features is employed as an intermediate reference object. The fixture is first placed within the scanning system's field of view, and its pose is recorded relative to the scanning coordinate system. It is then transferred to the robotic workspace, where its spatial orientation is identified using the robot's vision system. By capturing the pose of the same fixture in both environments, a transformation matrix--comprising rotation and translation components--is computed to convert the spraying path data from the scanning coordinate system into the robotic tool coordinate system. This coordinate transformation enables the robotic arm to accurately follow the adhesive spraying path generated from the pre-scanned 3D model of the lasted upper.  
In this system, the bottom of the shoe last--gripped by the robotic arm's end-effector--is defined as the tool coordinate system. The origin of this frame, also referred to as the tool center point (TCP), is set at a small circular hole located at the heel of the shoe last. The axes of the tool coordinate system are defined as follows: the \(Z\)-axis points outward and normal to the bottom surface of the shoe last; the \(X\)-axis points from the heel to the toe along the longitudinal direction of the shoe last; and the \(Y\)-axis is determined by the right-hand rule to complete the orthonormal basis.