esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Life Cycle Assessment Results
#### 3.3.2 Carbon Footprint Results  
The estimation of the carbon footprint considers the fabrication and use phases of the vehicle. Regarding the use periods, the results are given in different localities according to the electricity mix and solar irradiance: both cities studied and average Europe, which has the same irradiance as Paris and average European electricity mix. The considered global warming scenario is set at +2.7 \({}^{\circ}\)C.  
Figures 11-13 present life cycle assessment results.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Component** & **Via 12 V Battery** & **Via 48 V Battery** & **In Main Battery** \\ \hline Total & 76 & 139 & 76 \\ PV module & 62 & 62 & 62 \\ Electronic/cable & 13 & 27 & 13 \\ Additional battery & NA & 50 & NA \\ \hline \hline \end{tabular}
\end{table}
Table 2: LCA results (fabrication phase) (kg CO\({}_{2}\)-eq).  
Figure 10: Yearly distance covered by VIPV in Malaga and Paris, passenger car, 30% shading, 157 Wh/km electrical consumption, with different peak power and threshold values.  
These figures show that in the case of the passenger car, VIPV may have a positive balance but not in all cities. The CO\({}_{2}\) balance depends mainly on the locality. With a very high correlation between the PV and the PV, the PV is more likely to be affected by the PV.  
Figure 11: Avoided emissions in Malaga, 0.312 Wp VIPV, global warming scenario +2.7 \({}^{\circ}\)C. (**a**) Graph with the three electrical architectures, (**b**) Graph for the impact of the frequency of recharge with the grid, architecture with direct transmission of PV electricity to the HV battery.  
Figure 12: Avoided emissions in Average Europe, 0.312 Wp VIPV, global warming scenario +2.7 \({}^{\circ}\)C. (**a**) Graph with the three electrical architectures, (**b**) Graph for the impact of the frequency of recharge with the grid, architecture with direct transmission of PV electricity to the HV battery.  
Figure 13: Avoided emissions in Paris, 0.312 Wp VIPV, global warming scenario +2.7 \({}^{\circ}\)C. (**a**) Graph with the three electrical architectures, (**b**) Graph for the impact of the frequency of recharge with the grid, architecture with direct transmission of PV electricity to the HV battery.  
low-carbon electricity mix in France, VIPV on a passenger car is not convincing. It has a negative CO\({}_{2}\) balance in Paris with 30% and 49% shading losses between \(-2\) and \(-102\) kg CO\({}_{2}\)-eq. The best case in Europe avoids up to 489 kg CO\({}_{2}\)-eq (Malaga, 30% shading and charge through 12 V battery). For average Europe, in terms of electricity mix and solar irradiance, VIPV may be not interesting because avoided emissions are 122 kg CO\({}_{2}\)-eq in the best conditions (30% shading, charge through 12 V battery) and \(-39\) kg CO\({}_{2}\)-eq in the worst conditions.
# Nanometric Plasmonic Rulers Based on Orthogonal Plasmonic Gap Modes in Metal Nanoblocks
## 1 Introduction  
Localized surface plasmon resonances of noble metal nanoparticles (e.g., gold and silver) depend on the shape and size of the particles at the visible and infrared wavelength regions [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13]. Specifically, because of strong plasmonic coupling at the small air gap between the metal particles, a resonant wavelength of the gap plasmon increases when metal particles are placed close together [1; 2; 3; 4; 5].  
Plasmonic rulers that have ultrafine sensitivity to the position of the target particle are useful for investigating molecular dynamic processes, such as DNA hybridization, enzyme cleavage, and protein-protein interaction in the real-time monitoring of spectral shifts [6; 7; 8; 9]. Because of the strong gap dependences, most available plasmonic rulers are used to measure a change in distance in one dimension along the gap direction. However, plasmonic rulers have recently been able to achieve three-dimensional (3D) nanometer-scale position monitoring using five gold nanorods and their dipole-quadrupole interactions [10; 11]. This advancement provides the opportunity to study 3D molecular dynamics. To take advantage of 3D rulers for biosensors, plasmonic rulers which have a simpler geometry are needed.  
In this paper, we propose a 3D plasmonic ruler that achieves a 2.5 nm resolution, which is limited by the numerical precision of the calculation. The resolution can be improved by using a smaller spatial grid in the simulations. The proposed structure consists of three rectangular silver nanoblocks, separated by 10 nm air gaps. In the air gaps, two orthogonal higher-order dipole modes with different wavelengths can be excited by injecting lights with vertical, linear polarization. The proposed 3D plasmonic ruler enables accurate measurements of a nanometer distance change by a single measurement of an absorption spectrum.
###### Abstract  
The 1-10 terahertz (THz) spectral window is emerging as a key region for plenty of applications, requiring not yet available continuous-wave room-temperature THz spectrometers with high spectral purity and ultra-broad tunability. In this regard, the spectral features of stabilized telecom sources can actually be transferred to the THz range by difference frequency generation, considering that the width of the accessible THz spectrum generally scales with the area involved in the nonlinear interaction. For this reason, in this paper we extensively discuss the role of Lithium Niobate (LN) channel-waveguides in the experimental accomplishment of a room-temperature continuous wave (CW) spectrometer, with \(\mu\)W-range power levels and a spectral coverage of up to 7.5 THz. To this purpose, and looking for further improvements, a thought characterization of specially-designed LN waveguides is presented, whilst discussing its nonlinear efficiency and its unprecedented capability to handle high optical power (\(10^{7}\) W/cm\({}^{2}\)), on the basis of a three-wave-mixing theoretical model.  
waveguide; nonlinear optics; terahertz sources +
Footnote †: journal: Applied Physics Letters
## 3 Results and Discussion  
### Influence of Approach and Crop Type on WUE Estimates  
Growing season water use efficiency (WUE) for maize and alfalfa are summarized in Table 2. Seasonal values reported in this study are within range of those reported elsewhere for both maize HWUEET [18; 55; 56] and EWUES [57; 58] and alfalfa HWUEET [59; 60]. Alfalfa EWUES was greater than values recorded elsewhere [61], which is attributed to greater GPP found here.  
Differences in WUE were observed at the maize and alfalfa sites during the 2018 growing season (Table 2); however, these differences were inconsistent when different methods of calculating WUE were used. For example, when growing season harvested WUE (HWUEP and HWUEET) was employed, the WUE of maize was greater than that of alfalfa. In contrast, when growing season EWUES was employed, the WUE of alfalfa exceeded that of maize. This is notable given that literature suggests that C4 pathway (maize) of photosynthesis typically exhibits greater ecosystem WUE than the C3 pathway (alfalfa) [62; 63; 64; 65; 66; 67] due to physical separation of an additional metabolic cycle, which reduces photorespiration [67], and physiological differences in the hydraulic pathway [65; 68]. The inconsistency between HWUE and EWUE of maize and alfalfa is likely related to differences in plant physiology where alfalfa inveses more carbon into below ground biomass. Comparatively, alfalfa has a substantially greater root component, with shoot: root ratios estimated at 1.33-1.37 in year one [69; 70], 0.80-0.87 in year two [69; 70], 0.58 in year three [70], and 0.34 in the fourth growing season after seeding [71]. In contrast, maize has higher above ground biomass accumulation with other studies suggesting maize only stores 24-29% of carbon below ground [72; 73] and lower photorespiration due to its C4 pathway of photosynthesis [67] resulting in smaller differences between EWUE and HWUE.  
Not only are there inherent differences between HWUE and EWUE methods, there are also inconsistencies observed within EWUE and HWUE methods themselves. These differences can be attributed to their input variable selection, which can be impacted differently by the physiological components of different crops. In this study, climatic differences or soil factors did not differ significantly between the two sites which suggests that inconsistencies between species were driven by crop physiology. To confirm this, linear regressions of half-hour intervals of air temperature (R\({}^{2}\) = 0.98, \(p\) < 0.001, n = 6336) and relative humidity (R\({}^{2}\) = 0.96, \(p\) < 0.001, n = 4264) measured at the two fields demonstrate 1:1 relationships, indicating that conditions were comparable at the sites (data not shown). In addition, another study using these study fields found that water availability in the soil was not limiting at rooting depths [74], and soil textures were similar at the two sites. These inconsistencies are investigated in the following sections.
## 1 Introduction
In this new scenario, it is common to see PV plants constituted by the aggregation of micro-plants with the participation of several owners. Based on this, the distributed metering system would be deployed in an existing PV plant, located in the town of Pozoblanco (Cordoba, Spain) [20]. It is a plant with a total generation of 4 MW, with four transformation centres (CT) connected to the distribution network. Each sector has a nominal power capacity of 1 MW, which are each further partly divided into 50 or 100 kW sectors. The objective is to measure the entire production with a multi-bus metering system. Simultaneous capture of three-phase voltages and currents at the four CTs located at distances of 15 m from CT1 to CT2, 15 m from CT3 to CT4, and 150 m from CT1 to CT3 are required. Figure 1 shows the distribution of the four cDAQ acquisition systems that carry out the irradiance measurements, with a mesh distribution to cover the whole plant. In short, the architecture of the system under evaluation is divided into three operation areas: the area dedicated to irradiance measurements located in strategic positions along the surface of the plant, with connections (4-20 mA) to minimize losses associated with the length of the conductors; the area associated with power quality (PQ) measurements located in each of the CT distribution centres; and the area where the \(\upmu\)PMUs that carry out the system synchronisation would be located. TSN synchronism would be essential to guarantee the simultaneous capture of all samples deriving from the four cDAQs. Each cDAQ would capture the samples from the eight pyranometers in its sector and would act as a PQ in each CT sector. The distributed measurements in each 1 MW sector with TSN technology would allow for the aligning of samples, with the quality analysed in the following sections of this work. In addition to the three areas described above, there would be an area dedicated to data collection in a local database. It is an important task to decide which resolution is the most appropriate to store the time series based on the needs of the research. This storage would be done locally at a higher resolution and then would be transmitted to a global database in the cloud. The rest of the article is organised as follows. Section 2 presents the methodology used for the analysis of the improved \(\upmu\)PMU architecture and the experimental procedure for the estimation of the synchronism level achieved with the TSN standard in an in-line topology with two and four distributed capture systems. Section 3 shows and discusses the statistical results obtained, while Section 4 presents the conclusions.
## 4 Discussion
Geometrically based optical metrology usually has a comparatively simple and cheap setup as compared to interferometric systems, is rugged, and use of incoherent light sources such as projectors or monitors lends itself to easy use in a fabrication environment. However, it requires substantial effort to turn geometrical metrology techniques into a precise and easy to use measurement tool. Here, our recent work on improved and faster calibration techniques for Deflectometry and Fringe Projection has shown significant progress in precision and speed of system calibration [41; 63; 64].
## 1 Introduction  
Based on customers needs, the warehousing and the order picking processes are principal components of any supply chain. Since 1984, the Storage Education and Research Council (WERC) [1], has identified the order picking process as the main area of opportunity for the warehousing industry. Studies carried out by [2, 3], show that the order picking is one of the most critical processes at an operational level within a warehouse, because it represents 55-60% of costs; therefore, companies are forced to perform this activity in the best possible way. [PERSON] [4] mentions that in warehouses, especially for distribution centers (DC); the order picking process for distribution centers (DC), has become more important and complex, because of its flexibility, which provides many advantages, such as the ability to handle products of different sizes, forms, weights and volumes with the same resources to react to market fluctuations. However, it also increases the number of decision variables and the complexity of the system, which complications decision-making activities.  
On the other hand, in the research of [1; 5; 6] it is established that several factors like average, the variation of order delivery time, integrity and accuracy, are components of the service level. Moreover, a crucial link between order picking and service level is that a product becomes available for shipping as quickly as it is retrieved. Otherwise, a delay in the delivery may be incurred, causing a bad performance of the service or nonconformity by the client. Nonetheless, the company could incur additional work to deliver on time, raising the costs of operation.  
The order picking process involves a series of activities, such as the selection or scheduling of orders (batches); the assignment of stock keeping units (SKU) to a storage location; and the shifting of different items from their storage locations to the shipping area in response to requests made by customers. Nevertheless, for [5; 7] the main target of order picking is the minimization of either the travel distance or the picking time; these activities are accomplished by routing policy, which determines the picker sequence for retrieval of the items from their storage locations. Therefore, this specifies both the order in which they have to be picked and the order in which the aisles must be visited.  
However, according to [8; 9], the correct storage assignment facilitates the process precision and the most efficient placement of stocks, achieving faster order cycles and better customer service, which makes storage assignment and routing one of the main problems in practice. Therefore, in this research, we focus on solving both problems together in a company where there is no appropriate location of the products, increasing direct labor to avoid non-compliance with deliveries to customers. The description of the case study is presented in Section 3.
# Learning Form Closure Grasping with a Four-Pin Parallel Gripper
## 3 Method
### Agent and Environment of the Learning Framework  
To adapt to the reinforcement learning policy, we regarded the four-pin gripper as the agent and the interaction between the gripper and the object as the environment.  
The gripper used in this work is depicted in Figure 3. Let \(\{G\}\) be a fixed frame attached to the gripper, \(\{W\}\) be the world frame fixed in the workspace and \(\{B\}\) be a fixed frame attached to the center of mass (CoM) of the object.  
The positions of the four pins on the gripper are represented by the coordinates of the end points of the pins as \(f_{i}=[x_{i},y_{i},z_{i}]^{\top},i=1,2,3,4\). We then define \(p_{1}\) as the distance between \(f_{1}\) and \(f_{2}\), \(p_{2}\) as the distance between \(f_{3}\) and \(f_{4}\), \(q\) as the distance between \(\overline{f_{1}f_{2}}\) and \(\overline{f_{3}f_{4}}\) and \(r\) as the distance between the middle lines of \(\overline{f_{1}f_{2}}\) and \(\overline{f_{3}f_{4}}\). In this way, we obtained a bidirectional mapping between the Cartesian space of the pins and the parameter space of the gripper:  
\[\Pi:\{f_{1},f_{2},f_{3},f_{4}\}\leftrightarrow\{p_{1},p_{2},q,r\}. \tag{1}\]  
Meanwhile, the configuration \(c_{\text{obj}}\) of a 3D rigid body can be described by the element in \(\text{SE}(3)=\mathbb{R}^{3}\times\text{SO}\). Such an element can be parameterized by six numbers \((x,y,z,\theta,\phi,\gamma)\), where \((x,y,z)\in\mathbb{R}^{3}\) quantifies the position of the CoM of \(\{B\}\) relative to \(\{W\}\) and \((\theta,\phi,\gamma)\) represents the Euler angles of the object pose by defining a mapping \(g:(\theta,\phi,\gamma)\in\mathbb{R}^{3}\rightarrow\mathbb{R}^{3\times 3}\).  
Without loss of generality, we assumed that most of the objects had finite stable states \(S_{i},i=1,2,\cdots,Q\) at which they could stay still even after applying a disturbance wrench, where \(Q\) is the number of stable states that is dependent on the geometry and mass distribution of the object. We may express the configuration of an object as follows:  
\[c_{\text{obj}}(S_{i}) =c_{\text{obj}}\Big{(}x,y,z^{S_{i}},\theta^{S_{i}},\phi^{S_{i}},\gamma \Big{)}\] \[=c_{\text{obj}}(x,y,\gamma|S_{i}),i=1,2,\cdots,Q \tag{2}\]  
where \(z^{S_{i}}\), \(\theta^{S_{i}}\) and \(\phi^{S_{i}}\) are invariable values determined by \(S_{i}\). Using Equation (2), we may confine the number of parameters to describe the pose of a 3D object from 6 to 3, when the stable state is given. Following this approach, we may construct the environmental constraints for the four-pin grasping problem, which will be discussed in detail in Section 3.3.1.  
Figure 3: Illustration of the four-pin gripper and the grasping model. (**a**) The gripper pins and the object to grasp. (**b**) The 2D view of the gripper parameters \(p_{1}\), \(p_{2}\), \(q\) and \(r\).
# Signal-to-Noise Ratio Analysis of Bandpass Sampling Time-Modulated Fourier Transform Spectroscopy
## 2 Modeling Analysis of SNR
### Modeling of Monochromatic Light Interferogram Based on Energy Transfer
At this time, since there is no correlation between all the noises of a single pixel and no correlation between the noises of different pixels, the noise energy can usually be obtained by calculating the square root of the number of electrons output by the detector, as shown in Equation (7):  
\[ \begin{array}{l}n=\sqrt{\overline{e_{s}(x,\
u)}}\\ =\sqrt{\frac{1}{\hbar c\
u}\cdot\frac{A_{d}\pi(1-\epsilon)}{4F^{2}}\cdot\tau \cdot\eta\cdot\frac{1}{2s}}.\\ \left[2 RTB(\
u)\cdot 2s\Delta t+2s\Delta t\cdot 2 RTB(\
u)\cdot\cos(2\pi\
u x) \text{sinc}(2\pi\
u s\Delta t)\right]\end{array}  \tag{7}\]  
Therefore, the SNR equation of the FTS interferogram can be written as follows:  
\[ \begin{array}{l}SNR=e_{s}(x,\
u)/\sqrt{\overline{e_{s}(x,\
u)}}\\ =\sqrt{\frac{1}{\hbar c\
u}\cdot\frac{A_{d}\pi(1-\epsilon)}{4F^{2}}\cdot\tau \cdot\eta\cdot\frac{1}{2s}}.\\ \left[2 RTB(\
u)\cdot 2s\Delta t+2s\Delta t\cdot 2 RTB(\
u)\cdot\cos(2\pi\
u x )\text{sinc}(2\pi\
u s\Delta t)\right]\end{array}  \tag{8}\]
# The Size Effect on Flexural Fracture of Polyolefin Fibre-Reinforced Concrete
###### Abstract  
The reinforcement of concrete by using polyolefin fibres may be considered in structural design to meet the requirements of the applicable code rules. To achieve a reliable use of such a composite material, use of full-scale real structures is needed. The conversion of lab testing data into real practice properties is challenging and significantly influenced by various aspects, among which the size effect is a key one. Given that the available literature does not report coinciding conclusions about such an effect on quasi-brittle materials reinforced with fibres, further research is justified. Therefore, this work studies the behaviour of notched beams with three proportional sizes by using self-compacting polyolefin reinforced concrete with a fibre volume fraction of 1.1%. Flexural testing was carried out according to the standard EN-14651, with the results revealing the existence of the size effect. In addition, a reduction of the residual strength identified in the larger specimens was observed in fracture surfaces with equal fibre content.  
Keywords:polyolefin fibre-reinforced concrete; fracture behaviour; size effect; bending tests +
Footnote †: journal: Applied Sciences
# Infection Control with Antimicrobial Solid-State ZnO Nanoparticles on Silk Fiborin Gauze
## 4 Conclusions  
A novel electrospun silk fibroin gauze was coated with antimicrobial zinc oxide nanoparticles using an efficient and scalable electroless deposition method. This innovative material shows significant potential for reducing hospital-acquired infections. ZnO was chosen for its antimicrobial properties, low toxicity, and biodegradability, making it a superior choice among metal oxides. The gauze's antimicrobial efficacy was tested, showing a 29.9% \(\pm\) 1.1% reduction in _S. aureus_ bacteria and a 38.2% \(\pm\) 1.5% reduction in _P. aeruginosa_ bacteria after 72 h. Cytotoxicity was evaluated using a viability assay with CHO cells, revealing over 70% cell viability across all conditions and exposure times. This study highlights the promise of ZnO-coated silk fibroin gauze as an antimicrobial agent in medical textiles and suggests further optimization of Zn\({}^{2+}\) loading to enhance its effectiveness in preventing healthcare-associated infections. Future studies should focus on these optimizations and include biofilm assessment to address the more challenging aspects of biofilm-related infections. This comprehensive approach will better inform the development of advanced wound care solutions.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app1467103/s1](https://www.mdpi.com/article/10.3390/app1467103/s1)]([https://www.mdpi.com/article/10.3390/app1467103/s1](https://www.mdpi.com/article/10.3390/app1467103/s1)). Figure S1. EDS spectrum of ZnO-SF silk fibroin gauze. Figure S2. (A) XRD patterns, (B) FTIR spectra, (C) Thermal behaviour of ZnO nanoparticles. Figure S3. Standard curve for zinc ions release measurement.  
Conceptualization, D.V. and G.M.; methodology, D.V., R.M. and S.A.; validation, D.V., R.M. and S.A.; formal analysis, D.V., R.M. and S.A.; resources, G.M.; data curation, D.V., R.M. and S.A.; writing--original draft preparation, D.V., C.-T.D. and A.M.; writing--review and editing, E.H., U.G. and G.M.; supervision, G.M.; funding acquisition, G.M. and U.G. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by Merle, NSERC: RGPIN-2020-05884; FRQS chercheur boursier: 266388.  
**Data Availability Statement:** Data is contained within the article or Supplementary Materials. The data presented in this study are available on request from the corresponding author.  
**Conflicts of Interest:** There are no conflicts to declare.