esa-sceva/satcom-chunk-collection huggingface dataset:
# Temperature-Insensitive Imaging Properties of a Broadband Terahertz Nonlinear Quantum Cascade Laser
## 2 Methods  
A broadband THz NL-QCL with a distributed feedback (DFB)/Fabry Perot (FP) configuration operating in pulsed mode was used for the THz imaging experiment; details of the device structure are described in ref. 23. Figure 1a shows the THz spectra of a 14 \(\upmu\)m-wide, 3 mm-long device, collected at different temperatures. As shown in the figure, the device exhibited a small temperature dependence, and the THz emission bandwidth remained constant over the whole temperature range. The broadband emission spectra extended from 1.2 THz to 3.0 THz, covering more than one octave at room temperature, which is a consequence of the nonlinear mixing between distributed-feedback single-mode lasing and multi-mode emission, due to the use of an FP cavity.  
Figure 1b depicts the temperature dependence of the THz current-output (I-L) characteristics in the temperature range of 160-297 K, and the inset shows plots of the output power at a current of 1.7 A as a function of temperature. The device showed a THz peak output power of approximately 275 \(\upmu\)W at 160 K, and approximately 80 \(\upmu\)W at 297 K. The higher THz output power at low temperatures is attributed to the increased mid-IR pump power. On the other hand, the measured THz output powers were smaller than those in our previous report; this is mainly due to the shift of the center frequency of the broadband THz spectrum of the device. In general, the THz output power due to DFG is proportional to the square of the THz frequency and the optical nonlinearity.  
We obtained THz imaging with a transmission imaging system [26]. Figure 2 depicts the experimental setup of our imaging system. The THz beam from our device was collimated with an off-axis parabolic (OAP) mirror (\(f=50\) mm) and was focused onto a test object by using an aspheric plastic lens (\(f=40\) mm; Tsurupica(r), Pax Co., Sendai, Japan). Then, the THz beam transmitted through the object was collimated using another aspheric lens (Tsurupica(r), \(f=40\) mm) and was collected on the Golay cell detector using another off-axis parabolic mirror (\(f=100\) mm). Terahertz images were acquired by the raster-scanning method. The object was mounted on a computer-controlled two-axis translation stage. To obtain spectroscopic images at a specific frequency, we placed the bandpass filter of that frequency in front of the detector. At the focal point, the THz beam diameter was about 0.5-0.6 mm.  
Figure 1: (**a**) Spectra of the THz NL-QCL (terahertz nonlinear quantum cascade laser): at 297 K, 240 K, 200 K and 160 K. (**b**) Current-voltage-THz-light-output characteristic of the THz NL-QCL at different temperatures, measured in pulsed mode. Inset shows normalized output intensity of THz NL-QCL as a function of temperature.
## 2 Principle and Signal Processing Method  
### Digital LFM Signal and Direct Detection  
In this section, we introduce a method for generating a digital LFM signal. To clarify the method for generating a digital LFM signal, we need to generate a section of LFM signal \(S(t)\) first, expressed as \[S(t)=rect(\frac{t}{T})\cos(2\pi f_{0}t+\pi Kt^{2}), \tag{1}\]  
where \(T\) is the pulse width, \(f_{0}\) is the start frequency of the LFM signal, \(K\) is the frequency modulation (FM) slope of the LFM signal, and \(rect(\cdot)\) denotes the rectangular function.  
We propose a digital LFM signal generation method by performing a symbolic operation on \(S(t)\). Hence, we can obtain a digital LFM signal \(DS(t)\), as follows:  
\[DS(t)=rect(\frac{t}{T})sign[\cos(2\pi f_{0}t+\pi Kt^{2})], \tag{2}\]  
where \(sign(\cdot)\) denotes the symbolic operation.  
The digital LFM signal represented in Equation (2) is bipolar. However, as shown in Figure 1, we use a direct modulation laser as the optical source at the transmitting end, and the generated signal controls whether the laser is on or off, that is, the optical source can actually produce only a unipolar digital signal representing 0 and 1. With reference to the encoding OTDR, the effect of transmitting bipolar digital signals can be obtained by transmitting two strings of complementary unipolar digital signals. Therefore, the signal generator can emit two series of periodic complementary unipolar digital LFM signals, \(DSA(t)\) and \(DSB(t)\), expressed as  
\[DSA(t)=\frac{1+DS(t)}{2},\;DSB(t)=\frac{1-DS(t)}{2}. \tag{3}\]  
The intensity-modulated optical pulses having \(DSA(t)\) and \(DSB(t)\) as modulation signals are then sequentially injected into FUT as probe pulses, whose power expressions can be written as  
\[P_{\text{DSA}}(t)=P_{0}\cdot DSA(t),\;P_{\text{DSB}}(t)=P_{0}\cdot DSB(t), \tag{4}\]  
where \(P_{0}\) is the output optical power of the laser.  
As shown in Figure 1, the backscattered light becomes a current signal after the direct detection and photoelectric conversion, and can be expressed as  
\[i_{DSA}(t)=R_{d}\cdot P_{\text{DSA}}(t)\otimes G(t),\;i_{DSB}(t)=R_{d}\cdot P _{\text{DSB}}(t)\otimes G(t), \tag{5}\]  
where \(\otimes\) represent a convolution sign, \(R_{d}\) is a constant representing the photodetector responsivity and \(G(t)\) is the impulse response of the backscattered light to the probe signal when this is a delta function signal. Finally, the detected signals \(i_{DSA}(t)\) and \(i_{DSB}(t)\) are differentially operated to recover the bipolar digital LFM signal, as follows:  
\[i_{s}(t)=i_{DSA}(t)-i_{DSA}(t)=R_{d}\cdot P_{0}\cdot DS(t)\otimes G(t), \tag{6}\]  
where the signal \(i_{s}(t)\) is equivalent to the value measured when the probe signal is bipolar.  
Figure 1: Schematic block diagram of the digital LFM-based optical time-domain reflectometry method. LD: laser diode; APD: avalanche photodiode; FUT: fiber under test; DSP: digital signal processing.
## 4 Materials and Methods
### Methods for Measuring the Properties of Powder Materials  
The flow and packing properties of the powdered raw materials were evaluated using a dedicated powder characterization device that complies with current pharmacopoeial standards. All measurements were performed with the Powder Tester PT-S (Hosokawa Micron B.V., Doetinchem, The Netherlands). The evaluated parameters included angle of reproge, angle of fall, angle of difference, aerated bulk density, and packed bulk density. The angle of repose indicates the flowability of the powder based on the natural slope formed when the material is poured. The angle of fall is measured after the powder collapses from its initial repose state, while the angle of difference, calculated as the difference between the angles of repose and fall, serves as an indicator of powder cohesiveness. Aerated bulk density refers to the density of the loosely poured powder including interparticle voids, whereas packed bulk density is measured after the powder has been tapped or mechanically compacted in a fixed volume. The bulk density was determined by measuring the mass of a known volume of powder, taking into account the space between particles. Based on the obtained values of aerated and packed bulk densities, two derived parameters were calculated. The compressibility was calculated using the formula: Compressibility Index(%) = ((\(\rho\_\)packed \(-\)\(\rho\_\)erated)/\(\rho\_\)packed) \(\times\) 100. The Hausner ratio was calculated using the formula: Hausner Ratio = \(\rho\_\)packed/\(\rho\_\)erated, where \(\rho\_\)erated is the aerated bulk density and \(\rho\_\)packed is the packed bulk density. These indices are commonly used in pharmaceutical preformulation to assess powder flowability and cohesiveness. The results provided critical insight into the handling behavior of the raw materials during both direct compression and wet granulation processes.  
Particle size distribution of the raw materials was determined using laser diffraction with a wet dispersion technique. Measurements were conducted employing a Mastersizer 2000 Hydro MU (Malvern Instruments, Malvern, Worcestershire, UK), which allows for particle size analysis within the range of 0.01 to 2000 \(\upmu\)m by means of dynamic light scattering. All measurements were performed in compliance with the ISO 13320-1:1999 standard [33]. The instrument generates output data as particle size distributions (PSDs), which are mass-normalized for each analyzed sample.
## 5 Three-Phase Pyrotechnic Explosions
### Scaling of Pyrotechnic Explosions  
The scaling laws for the gas phase were discussed in Section 2. For pyrotechnic explosions, we must deal with all three phases. One can say that the conservation laws for phases 2 and 3 describe inertial flow, since there are no pressure gradient forces. However, there are source/sink terms on the right-hand side of the equations, expressing mass transfer, drag, and heat transfer with the gas phase.  
They are functions of the Reynolds and Prandtl numbers. How these scale with change in problem scale is discussed below.  
The initial conditions for a pyrotechnic charge are illustrated in Figure 2. It shows the detonation wave structure for the gas phase (as before) and the linear velocity profile for the droplet phase. This corresponds to similarity solution of inertial flow expansion into a vacuum, as published by [PERSON] [15] in 1960. The ball radius of the droplet phase extends to 10% of the charge radius (i.e., \(R_{B}=0.1\cdot R_{c}\)). These initial conditions scale with the explosion scale, \(r_{0}\), in other words \(x_{B}=R_{B}/r_{0}=0.1\cdot R_{c}/r_{0}\). Thus, we consider two pyrotechnic explosion scales:  
* A full-scale charge (the dynamics of this pyrotechnic charge system was published in the _16 th Detonation Symposium_[21]) where \(R_{c}\equiv 100\) cm with a mass of 7175 kg;
* 1/3 scale charge where \(R_{c}\equiv 100/3\) cm with a mass of 265.7 kg.  
As mentioned above [21], the pyrotechnic charge contains a liquid ball of radius \(R_{B}=0.1\cdot R_{c}\), and thus a full-scale charge would have a ball radius of \(R_{B}=10\) cm, while a 1/3-scale charge would have a ball radius of \(R_{B}=10/3\) cm. The ball is made up of droplets; we estimated the droplet diameter as \(d_{i}=3\) mm, which will be the same for both scales. (We assumed the liquid sphere was put under strong radial strain, creating droplets. According to [PERSON] (1949) [29], the droplet size is controlled by surface tension, which is a material property. Thus, the droplet size will be the same for full scale and subscale.) The number of droplets scaled as \(n_{i}=\left(2R_{B}/d_{i}\right)^{3}\), which was equal to 296,296 droplets at full scale and 10,974 at 1/3 scale. The droplet wake diameter scaled as \(d_{w}=d_{i}/100\), and thus was \(d_{w}=3\) um in both cases. The wake equilibration length scaled as \(l_{w}/d_{w}=10,000\), and thus the wake equilibration length was 30 cm in both cases. The droplet Reynolds number scaled as \(Re_{i}=u\cdot d_{i}/v\). Assuming a characteristic velocity of 1 km/s, one finds the droplet Reynolds number of \(Re_{i}=2\times 10^{5}\), and the wake Reynolds number of \(Re_{W}=2\times 10^{3}\). These have drag coefficients of \(C_{D}=0.48\) and Nusselt numbers of \(Nu\sim~{}40\) (see Appendix C for more Nusselt number correlations versus data). These results are summarized in Table 1. We note that here the particle sizes introduced an additional length scale, and thus we did not expect to maintain self-similarity.
###### Abstract  
This article presents the results of a study on the influence of a three-level dispersed composition of the cluster component of a binder, which includes coarse, medium, and fine fractions, on the physical and mechanical properties of self-compacting concrete (SCC). One of the current challenges in SCC technology is enhancing its durability and resistance to aggressive environments while maintaining self-consolidating properties. Addressing this challenge holds significant engineering importance, especially for infrastructure under freeze-thaw cycles and chemical exposure. The work aimed to determine the optimal polyfractional composition that ensures the maximum packing density of cement binder particles and to assess the changes in the operational characteristics of SCC. A software and calculation complex featuring a three-dimensional modeling algorithm, Drop and Roll, was used to select the optimal composition. Experimental studies were conducted for mixtures with varying fraction contents, differing in average particle sizes of 12 \(\upmu\)m, 6.6 \(\upmu\)m, and 4.9 \(\upmu\)m. It was found that the optimum composition, consisting of 15% of the 1500 cm\({}^{2}\)/g fraction, 75% of the 3000 cm\({}^{2}\)/g fraction, and 10% of the 4500 cm\({}^{2}\)/g fraction, contributes to an increase in compressive strength of 26%, bending strength of 10%, a times two increase in freeze-thaw resistance, a decrease in water absorption, and an improvement in chemical resistance to aggressive environments. The results confirm the effectiveness of optimizing the grain composition of the binder to enhance the durability and performance characteristics of SCC used in aggressive conditions.  
self-compacting concrete (SCC); polyfractional binder; packing density; chemical resistance of concrete; freeze-thaw chemical resistance of concrete +
Footnote †: journal: Applied sciences  
Article
# Spatiotemporal Feature Enhancement for Lip-Reading: A Survey
## 3 Spatiotemporal Feature Enhancement Methods
### Spatiotemporal Feature Enhancement Based on Attention
#### 3.3.2 Spatiotemporal Feature Enhancement Based on Hybrid Attention  
The attention mechanism mixed Channel-spatial features, like CBAM, artfully integrates the strengths of channel and spatial attention, demonstrating remarkable capability in lip-reading by adeptly capturing a wide range of features.  
Based on CBAM attention, [PERSON] et al. [99] and [PERSON] et al. [80] made efforts to fortify the representation of spatiotemporal features respectively. The former embedded CBAM in ResNet50, offering a refinement that profoundly heightened the network's sensitivity to the nuanced distinctions between acoustically similar words in the Mandarin database. The latter seamlessly integrated CBAM into ShuffleNet, empowering the front-end network to concentrate on both the channel and spatial characteristics of lip movements, adeptly navigating the complexities of spatiotemporal features within video sequences.  
Differently from the above two methods, [PERSON] et al. [1] introduced a fused attention mechanism that intricately weaves together temporal, spatial, and channel dimensions, assigning weights to input data through convolution to filter out vital information before merging these insights. Furthermore, they designed the TCSAM module, which was embedded in ResNet-18 to adeptly extract lip features from images, thereby enhancing the model's capacity to emphasize both channel and spatial characteristics of lip shape and significantly improving the representational power of these two features.
# Image Super-Resolution Based on CNN Using Multilabel Gene Expression Programming
## 4 Experiments  
### Experimental Environment and Parameter Settings  
The experimental software environment used was Ubuntu 14.04, Python 2.7, TensorFlow 1.4; the hardware environment was an Intel Core i7-6700K, RAM 16 GB, and the GPU was an NVIDIA GTX1080.  
As the training set, we used ImageNet-91 [5], and as the test set, we used Set5 [21], Set14 [22], BSD100 [23], and Urban100 [24]. We tested on three commonly used scale factors, 2, 3, and 4, and compared the results with those of the Bicubic, SCN [9], SRCNN [5], VDSR [8], and DRCN [10] algorithms. Two evaluation indexes, PSNR and Structural Similarity (SSIM), were selected as an objective reference basis for the superiority of algorithm reconstruction to measure the effect of image restoration.
###### Abstract
Similarly, [PERSON] and [PERSON] (2023), in Slovakia, validated an HPLC-FLD method with pretreatment in an immunoaffinity column that met the analytical performance criteria established by European standards [19]. In Hungary, routine monitoring of AFM1 in both raw and processed milk was conducted using commercial test kits, highlighting the need for continuous monitoring along the entire dairy production chain [20]. In the Latin American context, [PERSON] et al. (2018) investigated AFM1 levels in liquid milk sold in Monterrey, Mexico, reporting concentrations that exceeded European regulatory limits [21]. Additionally, other studies have documented the presence of AFM1 in raw, pasteurized, and UHT milk samples throughout Mexico [22; 23; 24; 25; 26; 27]. In particular, [PERSON] et al. (2022) reported concentrations of AFM1 exceeding the national regulatory threshold of 0.5 \(\upmu\)g/L in commercially available dairy products [22; 28]. These results underscore the significance of region-specific risk assessments and the necessity of continuous monitoring in various dairy markets. While this study emphasizes the issue of AFM1 contamination in commercial milk in Mexico, it is essential to note that AFM1 contamination in dairy products has been extensively documented globally, underscoring its international significance. Researchers have reported elevated detection rates of AFM1, frequently surpassing established regulatory limits. This evidence affirms that AFM1 contamination is not restricted to particular regions but represents a pervasive issue associated with feed contamination, unsatisfactory storage conditions, and climatic influences [29; 30; 31; 32; 33]. Consequently, local evaluations like the one presented in this study are crucial for delineating exposure risks within specific national contexts. These studies provide essential data regarding prevalence; a paucity of research assesses the carcinogenic risk of AFM1 based on age-specific consumption patterns, which is vital for informing regulatory and public health strategies [34; 35]. Therefore, accurate quantification necessitates using highly sensitive and reliable analytical techniques, such as HPLC-FLD, which is esteemed for its precision and reproducibility in detecting AFM1 [36,37]. In addition to quantification, the carcinogenic risk index (CRI) estimation provides a more comprehensive perspective by incorporating AFM1 concentrations alongside actual consumption patterns and body weight across diverse population groups [10,38]. This methodology aids in prioritizing regulatory actions and meaningfully assessing public health risks. Consequently, this study aimed to quantify the levels of AFM1 present in various brands of CM sold in Mexico and evaluate the cancer risks associated with its consumption among different age groups.
# Visible Light Communication System Technology Review: Devices, Architectures, and Applications
## 4 Modulation Technology in VLC System
### M-Ary Quadrature Amplitude Modulation (QAM) Technique  
QAM combines both PSK and amplitude-shift keying by changing the two parameters of the carrier. For that reason, this method is also known as amplitude phase keying [120]. With the same average signal strength, the number of symbols can be raised to represent more bits by a single symbol, resulting in improved bandwidth efficiency compared to MPSK. The constellation diagrams of 8-QAM and 16-QAM are shown in Figure 11. The BER and SNR relation of M-QAM can be determined by Equation (16) [121]:  
\[BER_{M-QAM}\cong\frac{\sqrt{M}-1}{\sqrt{M}}\frac{4}{\log_{2}M}Q\Bigg{(}\sqrt{ \frac{3}{M-1}\ SNR}\Bigg{)} \tag{16}\]
# Influence of Deep Foundation Pit Excavation on Adjacent Pipelines: A Case Study in Nanjing, China
## 2 Case Study  
### Site Investigation and Data Collection  
This study was conducted in Jiangsu province, China. As shown in Figure 1, the project consists of two fifty-story office buildings plus a four-story basement. The foundation pit's excavation depth is roughly 25.00 m, and the excavation area is around 117,000 m\({}^{2}\). There are two buildings on the south and west sides of the foundation pit. The two buildings on the south side are 10-story frame structures with raft-pile foundations, where the pile diameter is 700 mm, and the pile length is 30 m. The two buildings on the west side are 15-story frame-shear wall structures with raft-pile foundations, where the pile diameter is 800 mm, and the pile length is 35 m. The minimum clear distance between the foundation pit and the buildings on the south and west sides is 41.6 m and 24.9 m, respectively. On the north side of the excavation, 140 m away from the edge of the excavation, is the YangtzeRiver. On the south side of the foundation pit, 8.7 m to 11 m away, there are gas pipelines and water pipelines, buried at depths of 5-6 m.
# State of the Art and Trends Review of _Smart Metering_ in Electricity Grids
## 4 Development of _Smart Metering_ Worldwide
### Asia-Pacific
#### 4.3.3 Australia  
Australian \(SG\) and _Smart Metering_ initiatives are focused on demand management, energy security, and energy efficiency and have been mainly propelled by governmental programs. Additionally, severe energy problems caused by energy shortages suffered in 2006 and 2007 have contributed to the attempt to improve the energy supply system [70]. In fact, in response to those energy shortages, there was a government committed to a national \(SM\) rollout as part of the National _Smart Metering_ Program. The rollout areas were chosen from a cost-benefit analysis and the State of Victoria was the first to commence a mandatory rollout of _Smart Metering_ infrastructure, which started in 2009 and finished in 2013 with 2.8 million installed \(SM\)s equipped with \(RF\) mesh technology and _WiMAX_. As happened with the Ontario deployment, a _ZigBee HAN_ network was also implemented. The government determined minimum functionality and services to be conformed to by the distributors, specified in terms of four key services: (i) recording of energy imported or exported from a metering point by half-hour trading interval; (ii) remote reading of the \(SM\)s; (iii) remote power supply disconnection; and (iv) remote power supply connection [38]. All costs associated with this deployment were passed along to consumers, including the cost of the \(SM\) itself, which generated cost concerns from customers. This, together with customer implications and engagement, were identified as the two main problems of the deployment [75]. The Ausgrid utility has also performed several _Smart Metering_ pilots. In 2010 a consortium led by Ausgrid won the tender for the Australian Government's \"Smart Grid Smart City\" project, consisting of the rollout of up to 50,000 \(SM\)s to homes across the trial sites. Residentsare able to see a real-time analysis of electricity usage for their households, as well as for individual appliances. The deployment also improves the grid performance by controlling the efficiency and network operations for energy transmission. The project employs \(LTE\) for its 4\(G\) communications network [39]. Additionally, the \"Essential Energy\" project, from 2004, consisting of the deployment of _SM_s for predominately residential customers, started with a size of approximately 2500 _SM_s equipped with mesh radio and 3\(G\). The pilot assesses demand management trial including in-home displays and critical peak pricing tariffs. The trial confirmed the importance of real-time consumption data in driving energy efficiency since customers involved in the trial achieved an overall reduction in energy consumption and up to 30% reduction in their peak demand [38]. Additional _Smart Metering_ pilots and trials performed in Australia are discussed in [39; 81].