esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results  
The results of the measurements performed with the use of the three light sources, 635, 532 and 447 nm for each phantom, are presented in Table 1.  
The obtained results are consistent with those of [30]. The order of magnitude of the reduced scattering coefficient is about 1.60-1.65 for a wavelength of 635 nm and 1.70-1.75 for a wavelength of 532 nm (reference sample). Reference data presented in [30] do not include the scattering coefficient for a wavelength of 447 nm. The values obtained from the measurements, using the system described in this paper, are 1.67 and 1.75 for wavelengths of 635 and 532 nm, respectively. The absorption coefficient results are also consistent with reference [30] and within the range of 0.05-0.06.  
The measurement results for samples B and C show a significant change in the absorption coefficient with the addition of small amounts of ink. However, further studies are planned to accurately determine the quantitative ink concentration.  
While maintaining due diligence, the uncertainty of measurement for the reference sample (A) was estimated to be \(\pm\)0.02 for \(\mu_{\rm a}\) and \(\pm\)0.05 for \(\mu_{\rm s}\)'. The estimated uncertainty of measurement for samples B and C are greater, mainly due to the noticeable non-uniformity of the thickness of these samples.  
Based on the gathered data, a few relevant observations can be made. Firstly, the ability to obtain a high-scattering medium with a minimum absorption was verified. Secondly, it was found that wavelength does not influence the absorption coefficient. Furthermore, the correlation between the reduced scattering coefficient and wavelength was demonstrated. Based on the measurements of the three wavelengths, this parameter could be approximated in the spectral range.
## 7 Research Gaps and Future Opportunities
### Protection against Computational Attacks
#### 7.2.1 Lack of Self-Awareness  
The blockchain-based supply chain systems typically have no information about the actual process-the process could be cyber or physical component/interface in Industry 4.0-through which the data has been generated or exchanged. These systems do not understand what they are trying to do with a certain input data. Therefore, we can say that they are not self-aware. Hence, due to the lack of business process information of the involved stakeholders, such systems could not detect advanced and complex attacks, arising due to either insiders or external adversaries with the knowledge of parts orprocesses or sub-processes. Furthermore, without self-awareness, the main purpose of supply chain automation cannot be achieved, because of its requirement of high-degree of trust among stakeholders.
# Diurnal Cycle of Passive Microwave Brightness Temperatures over Land at a Global Scale
## 4 Results and Discussion  
### Assessment of the Global Land Diurnal Cycle of PMW TBs  
In order to assess the accuracy of the proposed method qualitatively, TB diurnal cycles at four PMW bands have been compared for different seasons and for two distinct land covers in Figure 7. It is preliminarily observed that the vertical polarization shows higher values in comparison to horizontal polarization. Additionally, as the channel frequency increases, the difference between vertical and horizontal TB values decreases. However, the differences between both vertical and horizontal polarizations at any frequency channel is larger for boreal and xeromorphic shrulband land cover than that for wooded and non-wooded grassland land cover. The magnitude of diurnal cycle of TB at 23 GHz (V) is the largest as compared to other frequency channels for boreal and xeromorphic shrulband land cover, while it is comparable to 19 GHz (V) for wooded and non-wooded grassland land cover. Moreover, the peak in the diurnal cycle is about two hours earlier over wooded and non-wooded grassland land cover than that over boreal and xeromorphic shrulband land cover. However, the magnitude of peak diurnal TBs is always higher for wooded and non-wooded grassland land cover than boreal and xeromorphic shrulband land cover. It is worthwhile to note that these results are in good agreement with previous studies by [PERSON] et al. [6,7] and [PERSON] et al. [32]. Furthermore, the shape and peak of the obtained TB diurnal cycle is almost similar to the LST diurnal cycle as proposed by [PERSON] et al. [28].
## 2 Status and Literature Review
### Domestic and Overseas Design-for-Safety Review
#### 2.3.1 U.S.--Prevention through Design  
The U.S. design-for-safety review was introduced under the term PtD and was introduced to reduce the risks in construction projects from the design stage. This concept was introduced by organizing partnerships in each field under the supervision of government agencies such as the Center for Disease Control and Prevention (CDC) and OSHA (Occupational Safety & Health Administration). In addition, pilot credits were distributed by adding PtD-related evaluation items to LEED credit items [11; 25]. Items for PtD review were provided so that there was no great difficulty in acquiring information on PtD considerations for each situation. In addition, efforts are being made to introduce this concept, such as distributing separate educational software to recognize hazards in the workplace.  
Among them, construction hazard prevention through design (CHPtD) is used to identify hazards in the construction site in advance, and risks are managed through qualitative evaluation. In addition, CHPtD implements integrated safety management of construction sites in the U.S. through quantitative risk assessment such as the SCSH rating system and the MIL-STD-882E model. In addition, they are focusing on BIM as an objective safety management tool, and several studies have been conducted on BIM [26; 27]. For example, a study was conducted on how to recognize the hazards of a fall disaster using a BIM model [28], and another study focused on the analogy of a disaster that could occur in scaffolding work using schedule data [29; 30]. The result is a simulation-level study of control measures. However, there are insufficient research cases on how to directly use it for risk assessment or PtD review.
## 3 Results
### Cellulose Production by Cellulophag sp. J9-3 in Liquid Culture  
Cellulophag sp. J9-3 decomposed the substrate in AZCL-cellulose-containing MA medium to give a blue color (Figure 1A). In addition, cellulose-degradation activity was detected, using the DNS method, in the supernatant of MB medium cultures (Figure 3). From these results, J9-3 was expected to secrete cellulose-degrading enzymes extracellularly.  
When J9-3 was incubated in MB medium, the addition of 0.2% CMC did not affect its growth. Cell growth (A\({}_{600}\)) peaked at 36 h of cultivation, and then gradually decreased due to depletion of limiting nutrients (probably carbon sources) in both media. Although enzyme activity was weakly detected (A\({}_{540}\) = 0.064) in MB medium, the addition of CMC to the medium resulted in a rapid increase in enzyme activity, reaching 4.3 times higher than the activity in MB medium alone (A\({}_{540}\) = 0.274) in 48 h (Figure 3). This result suggested that enzyme production can be actively induced by the addition of the substrate, CMC.  
Figure 1: Characteristic features of the bacterial isolate, J9-3. (**A**) Detection of cellulase activity on Marine Agar plate containing AZCL-cellulose; (**B**) scattering electron microscopy of J9-3 cells after staining with 1% phosphotungstic acid.  
Figure 2: Neighbor-joining phylogenic tree based on 16S rRNA gene sequences between strain J9-3 and other species. Nucleotide sequence accession numbers are given in parentheses. Scale bar, 0.01 substitutions per 100 nucleotides.
## 2 Materials and Methods
### Experiments
#### 2.1.4 Phantom Preparation and Measurement Protocol  
Two primary parameters were varied in the flow phantoms as shown in Figure 1b--the volume flow rate \(F\) through the flow channel and the depth \(D\) of the flow channel from the fluid surface. The flow rate \(F\) was cycled through for four rates (\(F_{0}\)-\(F_{3}\)), for four cycles. The depth of the flow-channel from the liquid surface was held fixed (from \(D_{0}\) to \(D_{3}\)) for each flow speed cycle.  
The plastic flow chamber had equal length and breadth (\(L=5.5\) cm), thus addition of a given volume \(v\) of liquid to the chamber would raise the height of the fluid surface by \(\Delta h=v/L^{2}\). For the first phantom to be measured, the chamber was filled with prepared liquid media such that liquid surface was visually assessed to have just submerged the flow channel. The depth of the flow channel for this first phantom was assumed to be \(D_{0}\). DCS measurements were acquired in this phantom by cycling through the four different flow rates (\(F_{0}\)-\(F_{3}\)), giving four measurements (labeled \(D_{0}F_{0}\)-\(D_{0}F_{3}\)).  
Next, 1.0 mL of phantom was added to the container, which was estimated to increase the depth of the channel from the surface by approximately \(\Delta h=0.03\) cm, as done previously [49]. The depth of the flow channel from fluid surface was \(D_{1}=D_{0}+\Delta h\). DCS measurements were acquired for a full cycle of pump volume flow rates (\(F_{0}\)-\(F_{3}\)) and gave phantoms \(D_{1}F_{0}\)-\(D_{1}F_{3}\). The process was repeated twice--each time, 1 mL of liquid was added to the chamber (increasing depth of channel by \(2\Delta h\) and \(3\Delta h\)). Thus, DCS measurements were obtained for 16 phantoms, corresponding to each depth and flow-rate used and were sequentially measured in sets of 4, starting from \(D_{0}F_{0}\)-\(D_{0}F_{3}\) and ending in \(D_{3}F_{0}\)-\(D_{3}F_{3}\). It is worth noting that this experimental protocol implied that in all but the first set of four measurements, the pump had been active for at least one cycle of operation before additional media was added to the chamber (i.e., \(D_{1}F_{0}\) was measured chronologically after \(D_{0}F_{3}\)).  
Figure 1: Photograph of the phantom flow chamber (**a**) and schematic of the flow chamber’s construction and measurement system (**b**). The gray arrows in (**b**) show the direction of the fluid flow. The flow rate \(F\) was controlled using a motorized syringe pump (see text). \(h\) is the distance from of the liquid surface to the top of the flow channel, which was controlled by addition of specific volumes of the liquid phantom to the chamber. The chamber (edges shown as thick black lines in (**b**) was placed atop a homogeneous tissue phantom block with optical properties matched to the liquid phantom at the laser wavelength. The DCS probe was positioned directly above the flow channel and at center of the flow chamber.
## 2 Modeling and Experimental Studies of the Geometry of Injector Nozzles
### Influence of Geometrical Features on the Functioning of the Injector  
The nozzle-hole geometry is one of the important parameters considered in the engine to alter engine's performance, combustion and emission courses. To improve the entire air-fuel mixture in self-ignition engines, swirl and turbulence characteristics need modification in the combustion chamber shape and injector nozzle geometry.  
The flow characteristics at the orifice outlet for the four investigated nozzles were analyzed in terms of their stationary mass flow, effective outlet velocity and area coefficient [14]. The results showed that divergent nozzles exhibit high cavitation intensity. The geometry of injector nozzles significantly affected the characteristic spray behavior and emissions formation of diesel engines. In paper [14], a nozzle concept consisting of orifices with convergent -divergent shapes was investigated. Three nozzles, characterized by different degrees of conicity, were compared to a nozzle with cylindrical orifices, which acts as a baseline.  
In the article [24], a method of calculation of the hydraulic working process of a diesel fuel feed system having an injector nozzle with different positions of its spray holes was tested. Research in self-ignition engine injector nozzle design for two groups of holes was carried out. Inlet edges of the first group of flow were in the sack volume and inlet edges of the second group were on the locking taper surface of the nozzle body. The coefficients of flow in both groups differ considerably and depend on the nozzle needle position. This makes it possible to distribute the injection quantity rationally by spray holes considering the operating conditions of the self-ignition engine and the combustion chamber zones.  
[PERSON] and [PERSON] 2010 [11] observed the 10-hole nozzle geometry hole nozzle had the best performance in the engine at full-load conditions. The number and cone of hole variations in the nozzle injector lead to better engine performance and reduced emissions in work by [PERSON] and [PERSON] 2014 [12]. The combined effect of cylindrical shape with the 5-hole nozzle geometry reduced NOx emissions up to 45% and slightly reduced CO emissions of the engine as compared to that of a standard shape by [PERSON] et al. 2018 [7].
## 4 Discussion
### Limitations and Strengths  
The study's limitations include: (i) lack of control over diet and sleep, which could affect body composition and physical fitness; (ii) short intervention duration; (iii) absence of blood tests; (iv) not assessing muscle strength through objective measures such as maximal isometric handgrip strength, which could enhance result consistency; and (v) lack of sample randomization. Key strengths were: (i) a well-planned intervention with load progression tailored to participant characteristics and baseline assessments; (ii) professional supervision during training; and (iii) high adherence, with no dropouts or injuries.
# Improved Performance in the Detection of ACO-OFDM Modulated Signals Using Deep Learning Modules
## 5 Conclusions  
In this article, we present methods that improve the performance of an ACO-OFDM decoder system by using different DL algorithms. We build two different DL decoders, using fully convolutional neural networks and fully connected neural networks. We compare the performances of the different models that we built with one another, and with the performance of the regular ACO-OFDM decoder using the MMSE estimator system. The use of DL algorithms helps to recover the corrupted modulated transmitted data and succeeds in reducing the BER of the system. Our DL systems improve the performance of the system and decrease the SNR by more than 8 dB when the channel is non-deterministic in both weak and strong turbulent channels. When the channel is stationary, we achieve performance slightly better than that of the ACO-OFDM decoder using the MMSE estimator. Moreover, our decoders are better than the regular decoder in terms of speed and energy consumption. In real environments, we train the system just one time. After the training, the weights are saved,  
Figure 9: Normalized prediction times for the different models.  
and we only need to predict each input according to the saved weights. The prediction process does not take time and does not consume energy. By using our models, we can implement ACO-OFDM in both stationary and non-stationary channels without needing previous knowledge of the CSI, unlike in the case of regular ACO-OFDM decoders such as MMSE. It is known that high-order Quadrature Amplitude Modulation (QAM) allow many bits per symbol, thus increasing spectral efficiency. Since DL can decrease BER and thus improve reliability, our DL models should also increase spectral efficiency.  
Conceptualization, L.D.; methodology, L.D.; software, L.D.; validation, L.D. and N.K.; formal analysis, L.D. and N.K.; investigation, L.D.; resources, L.D.; data curation, L.D.; writing--original draft preparation, L.D.; writing--review and editing, L.D. and N.K.; visualization, L.D.; supervision, N.K.; All authors have read and agreed to the published version of the manuscript.  
Outstanding doctoral fellowship for the Arab society and minorities in Israel from Council for Higher Education in Israel.  
We thank [PERSON] for his very helpful comments and suggestions.  
The authors declare no conflict of interest.
## 1 Introduction
The evaluation model of tunnel roof falls based on the analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was established. A comprehensive evaluation index system for roof collapses of roadways is proposed. The weight of each index is calculated by the combination of the analytic hierarchy process (AHP) and expert validity matter elements. Therefore, the influence of human factors on the evaluation results is reduced. [PERSON] et al. [13] took two underground coal mines in the western United States as engineering cases. The main parameters affecting roof falls of roadways are analyzed. The prediction index of tunnel roof falls was put forward. [PERSON] et al. [14] aimed to understand the relationship between the influencing factors of roadway roof fall accidents and the importance of accidents according to the characteristics of the expert evaluation language and the semantic network connection between the factors. It is proposed to embed the cloud model into the ANP (analytic network process) to solve the above problems. The construction process and analysis steps of the cloud ANP are given. The underground geomechanical environment of coal mines is complex and changeable, so the risk assessment of roadway roof falls should involve many factors [15; 16; 17]. However, the above evaluation method is too simple to correctly judge the actual situation of roof falls in coal mine roadways. It is necessary to study it further. Through the comprehensive analysis of various factors, the risk evaluation method of roadway roof falls in line with objective reality is obtained. Therefore, in view of the evaluation of the risk of roof falls in coal mine roadways, this paper uses the combination weight of the analytic hierarchy process (AHP), entropy weight method (EW) and the matter element extension theory to establish the risk evaluation model of roadway roof falls. According to the principle of the maximum membership degree, the risk degree of roadway roof falls is determined. Based on Java Web, a roadway roof fall risk assessment system was developed. We name the system Multiple Weight-Material Element Web (MW-MEW). The system cannot only avoid the subjectivity of an individual evaluation but can also effectively solve the problem of single factors affecting the risk evaluation of roadway roof falls. It provides a new avenue for the study of the cost of risks of roof falls in coal mine roadways.
# Disentangling Long Trajectory Contributions in Two-Colour High Harmonic Generation
## 1 Introduction
Depending on the focus position relative to the gas jet for HHG, the contribution of the long trajectories in the HHG signal can be changed [14] and, with the right balance, quantum path interference between the short and long trajectory was observed for the first time in HHG [23] in excellent agreement with theory [24], and then extended to many other gas targets [25]. During the derivation of this quantum model by [PERSON] et al. [22], several assumptions of the classical trajectory three-step-model are confirmed. The contributing trajectories must return to their parent ion again, which also imparts conditions on the initial momentum of the trajectory right after tunnel ionisation. Furthermore, in a recent experimental study, it was found that the spatial excursions of HHG trajectories are also well explained by the semiclassical model [26]. Therefore, it is valid and helpful to investigate the HHG process in greater detail using Classical Trajectory Monte Carlo (CTMC) simulations. Figure 1: Photoelectron trajectories contributing to High Harmonic Generation (HHG). The colour code represents the kinetic energy of the trajectory at the return, where red is low and dark blue is high energy. Long trajectories are greyed out because typically the short trajectories dominate the spectrum. The black solid line represents the driving laser field \(-F_{x}(t)\). Since the strong field tunnel ionisation rate declines exponentially with decreasing field strength [19], long trajectories are preferentially created. However, due to the spreading of the wave packet during the propagation, the probability of recombination decreases with increasing excursion time. In addition, long trajectories show more efficient phase matching in the converging beam, when the gas interaction region is placed before the focus of the driving laser beam [27]. For short trajectories, on the other hand, the phase matching is more efficient in the diverging beam after the laser focus, and it is easier to achieve than for short trajectories. Optimizing the gas jet parameters after the beam focus, combined with the quantum spreading of the wave packet, one can work against the preference towards long trajectories from the ionisation rate. In practice, therefore, the optimised HHG spectrum consists almost exclusively of short trajectory contributions [18; 27].
## 2 Metals Used in WDED and Types of Microstructure and Mechanical Properties
### Copper-Based Alloys  
Due to its great thermal conductivity, electrical conductivity, formability, machinability, and ductility, copper (Cu) is one of the most utilized materials in various industries such as electronics, defense, aerospace, automotive, etc. Unique mechanical properties of Cu and its alloys, such as high thermal conductivity, have encouraged industries to use it in power units, electronic connectors, and heat exchange. Recently, the need for complex geometries has increased, which obliges industries to use additive manufacturing, particularly DED. The most challenging issues to work with Cu alloys are oxide production, which creates agglomeration, and reduced fluidity of molten Cu, which decreases the wettability. So, even in the best circumstances, welding pure copper is still challenging. Therefore, utilizing standard manufacturing methods like welding and similar approaches presents a variety of challenges. The mechanical properties of the different copper-based alloys and the processing parameters and methods are given in Table 5.  
Figure 10: EBSD image of AA4043 alloy fabricated by the FDED method: (**a**) position of the samples, (**b**,**e**) top region, (**c**,**f**) middle region, (**d**,**g**) bottom region [85].  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**Technique** & **Material** & **Process Parameters** & **Microstructure** & **Condition** & **YS (MPa)** & **UTS (MPa)** & **El (\%)** & **Hardness (GPa)** & **Reported by** \\ \hline \multirow{5}{*}{**EDEDED**} & **Aluminum** & **Vacuum chamber, Beam current 4.4-72 mA, Beam acceleration voltage 30.8 kV, Wine feeding rate 400 m/min & - & & & 564.5 to 674 (90\({}^{\circ}\)) & 9 to 42.5 (90\({}^{\circ}\)) & \multirow{5}{*}{1.7 to 2.6} & [90  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline
**Technique** & **Material** & **Process Parameters** & **Microstructure** & **Condition** & **YS (MPa)** & **UTS (MPa)** & **El (\%)** & **Hardness (GPa)** & **Reported by** \\ \hline \multirow{8}{*}{**EBDEDED**} & \multirow{8}{*}{**CaAl\({}_{3}\)Mn\({}_{2}\)/Vr.**} & \multirow{8}{*}{**CaAl\({}_{3}\)Mn\({}_{2}\)/Vr.**} & \multirow{8}{*}{**CaAl\({}_{3}\)/Vr.**} & \multirow{8}{*}{**CaAl\({}_{3}\)/Vr.**} & \multirow{8}{*}{**CaAl\({}_{3}\)/Vr.**} \\  & & & & & & & & \\  & & & & & & & & & \\  &  
[PERSON] et al. [90] fabricated aluminum bronze/Udimet 500 composites by the EBDED method, The microstructures of composites with different volume percentages of Udimet 500 are shown in Figure 11. The composites with 5 Ud have dark \(\beta\)-Cu\({}_{3}\)Al in intra-grain particles and grain boundaries with coarse \(\alpha\)-Cu matrix grains. Moreover, with the Udimet 500 increased to 10 vol. %, the content of the \(\beta\)-Cu\({}_{3}\)Al is reduced. In addition, as Udimet 500 in the aluminum bronze matrix increases, the grain size of the composites decreases significantly.