esa-sceva/satcom-chunk-collection huggingface dataset:
_applied sciences_  
_Article_  
Heat Transfer Investigation in Plus-Shaped Enclosure Using Power Law Fluid: A Finite Element Approach  
**[PERSON] 1, [PERSON] 1,*(c)**, [PERSON] 1, [PERSON] 2 and [PERSON] 2  
1 Interdisciplinary Research Institute, Faculty of Science, Beijing University of Technology, Beijing 100124, China; [EMAIL_ADDRESS] (I.S.C.); [EMAIL_ADDRESS] (Z.G.)  
2 Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China; [EMAIL_ADDRESS] (M.Y.); [EMAIL_ADDRESS] (M.A.M.)  
*Correspondence: [EMAIL_ADDRESS]  
**Abstract:** The main purpose of this study is to investigate the thermal behavior of power law fluid within a plus-shaped cavity under the influence of natural convection, also taking into account the Darcy number and magnetohydrodynamics (MHD). The problem is formulated as a system of partial differential equations considering the power law fluid's rheological behavior. The left-side walls are maintained at a specific low temperature while the lower and the right-side walls have uniform maximum temperatures. The boundary condition is designed to enhance heat transfer efficiency within the cavity, utilizing advanced thermal insulation methodologies. Finite element method (FEM) simulations are conducted, and a grid independence test is performed to validate the results. The impact of relevant parameters on the variation in momentum and thermal distributions is investigated using streamline and isothermal contour plots. The results indicate that as the Rayleigh number increases, the kinetic energy also increases, whereas the viscosity and circulation zones expand with an increase in the power law index. The Nusselt number exhibits a higher value in the shear-thinning case (n = 0.7) compared to the Newtonian (n = 1) and shear-thickening (n = 1.2) cases. This empirical observation underscores the vital role that fluid rheology plays in molding the overall heat transfer performance within the cavity. The study concludes that there is a distinct correlation between the heat transfer rate and the Rayleigh number (Ra). As Ra increases, there is a significant improvement in the heat transfer rate within the flow domain. Furthermore, the fluid behavior and heat transfer performance within the cavity are significantly influenced by the presence of magnetohydrodynamics (MHD) and the Darcy effect.  
**Keywords:** natural convection; power law; finite element method; plus-shape enclosure; heat transfer; MHD
# Performance Analysis of Rate Splitting in Massive MIMO Systems with Low Resolution ADCs/DACs
## 3 Performance Analysis
### Power Allocation  
Here, we analyze the power allocation for the private and common messages, respectively. We obtain the power allocation factor, \(t\), based on the metric developed in [12]. We obtain a closed-form closed-form solution based on the asymptotic results and show how the RS scheme outperforms the conventional non-RS scheme in massive MIMO. The main idea of this heuristic technique is to allocate power to the private messages to achieve approximately the same SE as the non-RS scheme. Then, the remaining power is allocated to the common message to enhance the SE. For the massive MIMO system with low-resolution ADCs/DACs, the solution takes into account not only the multiuser interference but also the QN. The SE gain of the RS scheme over the conventional scheme with RZF precoding is quantified as [12]  
\[\Delta R=R_{c}+\sum_{k=1}^{K}(R_{k,p}-R_{k,RZF}), \tag{25}\]  
where \(R_{k,RZF}\) is the rate for the non-RS scheme where the BS uses RZF precoder and zero power is allocated to the common message in (9). The power allocation factor for the private messages, \(t\), is derived as  
\[t=\min\{\Psi,1\}, \tag{26}\]where  
\[\Psi=\frac{K+(1-\alpha_{D})KP\beta_{k}}{\alpha_{D}Pe_{k}+(1-\alpha_{D})P \beta_{k}+(1-\alpha_{D})KP\beta_{k}}. \tag{27}\]  
**Remark 2**.: _From (27), when the QN is high, more power is allocated to the private messages. Hence, the rate gain of the RS scheme which depends on the common message cannot be improved. Consequently, the rate gain of the RS scheme over the non-RS scheme is degraded for an increasing number of users and for low-resolution ADCs/DACs. Also, the QN due to low-resolution DACs has a more dominant effect on the SE performance than that of the low-resolution ADCs._
## 2 PPM Reception
### PER Results  
The PER is plotted in Figure 2 against \(E_{b}/N_{0}\) for several degrees of freedom \(k\) and modulation orders \(Q\). Exact PER results are obtained via the numerical integration of (3), while approximate results are obtained from (10). As it is expected, the binary PPM results coincide, which validates the soundness of the PER derivation. A deviation between exact and approximate results is also observed at increasing modulation orders. The deviation becomes less important as the OSNR gets better, and the approximation is highly accurate for PERs lower than \(10^{-3}\). Given the accuracy of the approximation in \(\chi^{2}\) statistics, we further explore its applicability in assessing the impact of turbulence on OWC systems in the following Section.
# Detecting Malware C&C Communication Traffic Using Artificial Intelligence Techniques
## 1 Introduction  
Cybercrime poses a serious danger to cybersecurity [1], and according to [2], the cost of cybercrime reached USD 8 trillion in 2023, with malware such as banking malware accounting for a large proportion of this total cost. In recent years, banking malware has emerged as a major concern, because malicious actors can make huge profits from these types of malware variants [3], and the cost to businesses is high. For instance, Emotet banking malware infections can cost up to USD 1 million per incident to remediate [4]. Banking malware attacks are continuing to rise [5], and the discovery of new banking malware variants is also continuing to increase. For example, over a thousand variants of the banking malware Godfather were discovered in 2023 alone [6].  
The Zeus banking malware has emerged as one of the most notorious banking malware variants ever developed [7], and since the release of the Zeus source code, many additional variants of Zeus have been developed and have emerged, including Ramnit, Zeus Panda, and Ramnit [8].
## 4 Performance-Based Design Process of Reinforced Concrete Column Members  
### Performance-Based Design Process  
Based on the corresponding relationship between the energy-based damage index and the seismic parameters (\(A_{\text{PG}}\), \(V_{\text{PG}}\), and \(t_{\text{d}}\)) and the construction member parameters (\(H\), \(\rho_{\text{sv}}\), \(F_{y}\), \(u\), \(\mu\), \(m\), \(n\), \(T\)), the performance-based design process is proposed.  
As shown in Figure 4, the seismic design method can be divided into the following five steps.  
1. Elastic design stage The section of the reinforced concrete member was preliminarily selected. The modeling tool midas Gen was used to establish the single degree-of-freedom structure model, and the longitudinal reinforcement ratio of the target member under minor earthquakes was calculated by midas Gen. The structural fundamental period \(T\) was determined according to the stiffness and the mass of the structure.  
Figure 3: The influence of the ductility coefficient \(\mu\), the period \(T(m)\), the seismic intensity (\(A_{\text{PG}}\) and \(V_{\text{PG}}\)) and the earthquake duration \(t_{\text{d}}\) on the total energy dissipation \(E_{\text{C}}\): (**a**) 6 degrees (0.05 \(g\)); (**b**) 7 degrees (0.1 \(g\)); (**c**) 8 degrees (0.2 \(g\)).  
(2) Calculation of the yield load  
The yield displacement \(u_{y}\) of the target member can be obtained according to the pushover analysis. According to the yield displacement \(u_{y}\), the material elastic modulus \(E\) and the dimensions, the yield load \(F_{y}\) can be obtained by Formula (16).  
\[F_{y}=\frac{3 EIu_{y}}{H^{3}} \tag{16}\]  
Here, \(E\) is the material elastic modulus and \(I\) is the inertia moment of the section.
3. Calculation of the ductility coefficient  
The maximum displacement value \(u_{\rm m1}\) under moderate earthquakes and the maximum displacement value \(u_{\rm m2}\) under major earthquakes can be obtained according to the pushover analysis. Based on the maximum displacement value \(u_{\rm m1}\) and yield displacement \(u_{y}\), the ductility coefficient \(\mu_{1}\) under moderate earthquakes can be obtained by Formula (17). Similarly, the ductility coefficient \(\mu_{2}\) under major earthquakes can be obtained.  
\[\mu=\frac{u_{\rm m}}{u_{y}} \tag{17}\]  
(4) Calculation of the stirrup ratio  
By selecting the expected performance target (damage index \(D_{b}\)), the earthquake duration \(t_{\rm d}\) and the seismic intensity (\(A_{\rm PG}\) and \(V_{\rm PG}\)), the stirrup ratio \(\rho_{\rm sv1}\) under moderate earthquakes can be obtained according to Formula (15). When the calculated stirrup ratio cannot meet the expected performance target, the sectional dimensions and the longitudinal reinforcement need to be readjusted. Similarly, the stirrup ratio \(\rho_{\rm sv2}\) under major earthquakes can be obtained.  
(5) Determination of the stirrup ratio  
By comparing the stirrup ratio \(\rho_{\rm sv1}\) under moderate earthquakes and the stirrup ratio \(\rho_{\rm sv2}\) under major earthquakes, the larger one is set as the final stirrup ratio \(\rho_{\rm sv}\).
## 6 RNA-Binding Phage-Encoded Proteins that Affect Transcription Elongation
### HK022 Nun-Mediated Transcription Arrest  
HK022 blocks the growth of phage \(\lambda\) by arresting transcription at pause sites distal to the \(\lambda\)_nut_ elements. The arrested TEC is released by the host Mfd factor, thus prematurely terminating transcription on the \(\lambda\) chromosome [75]. Nun binds NUT RNA with its ARM motif, whereas the C-terminal region of Nun interacts with TEC. Other than the effect of Nun on \(\lambda\) growth, no other biological function has been described for the protein. Lytic growth of HK022 is unaffected by _mun_ mutations, and HK022 _mun_ mutants lysogenize with normal frequency. The specificity of Nun exclusion is unique; other phage exclusion systems are active against a broad range of superflecting phage [60].  
It has been suggested that the function of the \(\lambda\) NUT RNA is to tether Nun or \(\lambda\) N, increasing the local concentration of the protein near TEC. Indeed, _nut_ is dispensable for function of both proteins _in vitro_ (see below; [74, 76]). Furthermore, Nun overproduction is toxic to _E. coli_, although \(\lambda\) NUT sites are not encoded in the bacterial chromosome [77]. Toxicity is related to transcription termination, since host RNAP and Nun mutations that block Nun termination also suppress cell killing [77, 78]. _In vivo_, Nun arrest requires the four _E. coli_ auxiliary transcription elongation factors, NusA, NusB, NusE and NusG.  
Though these factors are not essential for Nun arrest _in vitro_, they enhance Nun specific activity, reducing the concentration of Nun required to block elongation [78].  
TEC paused by nucleotide deprivation _in vitro_ is a substrate for subsequent Nun arrest, although the site of arrest differs depending on the location of the pause [79,80]. Mutational analysis of the Nun C-terminus indicates that a penultimate aromatic residue (W108) is required for Nun arrest (Figure 3, top). The Nun C-terminus crosslinks to template DNA about 9 bp promoter-distal to the RNAP active center. This is compatible with the idea that Nun arrests transcription by anchoring TEC to the DNA template, perhaps via intercalation of the W108 residue. Two neighboring basic Nun C-terminal residues, K106 and K107 (Figure 3, top) are required for efficient arrest. They are thought to aid Nun binding to the negatively-charged DNA template. The Nun mechanism of action was tested on defined TEC scaffolds consisting of DNA template and non-template strands and RNA complementary to the template strand. These TECs differed in the length and the sequences of the RNA primer. Importantly, the scaffolds included no \(\lambda\) DNA or RNA sequences. Nun arrested all TECs tested that carried an RNA:DNA hybrid 9 bp or longer. For each TEC, Nun-mediated arrest occurred at a specific site, corresponding to an intrinsic pause site [77,81,82]. Nun-arrested TEC were found in either the pretranslocated or the posttranslocated state. Nun arrests transcription elongation by preventing movement of TEC from one register to the other [79,80].
## 3 Technology Overview
### Semantic Web Services (SWS)
#### hRESTs  
RESTful Web service descriptions are generally described in plain, unstructured HTML [10, 11]. hRESTS (HTML for RESTful Services) is a microformat aimed at making these HTML based Web APIs machine readable by annotating the key information on the HTML page. hRESTS uses the existing class and rel attributes of XHTML to identify the key information of the service description \"_effectively creating an analogue of WSDL_\" [11]. hRESTS defines (XHTML) classes such as:  
Figure 6: Semantic Layers [11]. SOAP-based WS are on the left and RESTful WS are on the right.  
* _method_ (the HTTP method used e.g., GET)
* _address_ (the URI used; may be a URI template)
# Quantum Computing for Healthcare: A Review
## 5 Quantum Computing Architectures for Healthcare
### Quantum Algorithm Design for Healthcare Applications  
The rapid advancement in quantum computers would be of little use to chemists in developing lifesaving drugs if there exist limited algorithms for healthcare applications that are optimized for these systems. Modern quantum algorithms are mostly hybrid, in that they leverage both classical as well as quantum computers. The need for the design of hybrid algorithms for healthcare applications is of utmost importance. Firstly, they allow these applications to utilize computationally superior quantum hardware. Secondly, even if they do not fully utilize quantum hardware capability, they still promote innovation in quantum-inspired classical algorithms that surpass the originals. Together, both hybrid and quantum-inspired methods will eventually evolve into pure quantum algorithms as the field matures. Both hybrid and quantum-inspired methods are organic evolutionary stages toward realizing pure quantum methods.  
[PERSON] et al. [109] developed a quantum algorithm for quicker clinical prognostic analysis of COVID-19 patients. They leveraged the growing class of quantum machine learning (QML) algorithms, which essentially grew from quantum computing theory. The idea is to employ quantum computing for machine learning tasks for solution parallelism for optimal constraint solving using Moore's law. The researchers report good performance for large-scale biased CT-scanned image classification due to efficient quantum simulation and fast convergence.  
[PERSON] et al. [110] design a multiobjective quantum-inspired genetic algorithm (MQGA) to solve the problem of healthcare deadline scheduling. The motivation is that missing the deadline for healthcare applications may have dire consequences, such as patient injury or fatality. The proposed algorithm models healthcare applications as workflows, represented as directed cyclic graphs (DAGs). Individual tasks within the workflow constitute a deadline to guarantee the quality of service (QoS).  
There are several large initiatives that aim to help translate quantum algorithmic research into practical healthcare-related software. The UK has allocated GBP 8.4 billion for the development of a quantum-enhanced computing platform [111] for pharmaceutical R&D, and many pharmaceuticals are collaborating with organizations experimenting with quantum computing to utilize quantum algorithms for drug discovery. For instance, the biotech company Biogen [112] is using the technology to develop novel neurological disease candidates, such as for fighting Alzheimer's.
# A Seamless Image-Stitching Method Based on Human Visual Discrimination and Attention
## 2 Preliminary Work  
### Non-Ideal Factors in the Mosaicking Process  
Obtaining perfect stitching results is usually not easy because of the limitations of existing mosaicking algorithms, such as false corner detection, poor matching accuracy and low efficiency rectification. More specifically, some corner detection algorithms are sensitive to the noise in the image, while some other corner detection algorithms based on contours cannot accurately locate the feature points because of the contour deformation resulting from a filter before processing [17; 18; 19]. Meanwhile, many false matches exist in feature matching process. A number of advanced corner detectors and descriptors are created to solve this problem, but error matches still cannot be eliminatedcompletely [20; 21]. Moreover, the rectification techniques such as least median-squares (LMedS) proposed by [PERSON] and random sample consensus (RANSAC) proposed by [PERSON] have poorer performance with the mismatches increasing [22; 23]. In these cases, the transformation matrix for mosaicking is not accurate and images cannot be stitched perfectly, which leads to some discontinuities especially at the edges of the graphs [1].  
In addition, external interference always exists when taking pictures, for example lens distortion [24], photorefractive effect, different exposure and illuminations. None of the images can be mosaicked to be ideal in the presence of lens distortion [25]. Similarly, the edges of objects may deform when the pictures are taken under water or in an inhomogeneous atmosphere [26; 27]. All the distortions may cause losses of pixel level alignment, these discontinuities can severely degrade the human visual perception and decrease the quality of the mosaic image. Thus, how to reduce the negative effect of discontinuities on visual perception is the key to improving image-stitching qualities.
## 4 Dynamics of NLC Functions
For the case \(p=1\), the NLCs have small oscillations with weak amplitudes, while for the case \(p=0.7\), they have notable changes, see Figure 7c,d. The correlations of the LQU and the Bell's inequality are more affected than the others quantifiers. Figure 6: The \(L(t)\) (dashed plots), \(U(t)\) (dashed dotted plots), \(B(t)\) (upper solid plots), and \(N(t)\) (solid plots) for \(\chi_{z}=0.5\), \(\Delta=1.5\), \(p=1\), \(J_{x}=J_{z}=2\) and \(\gamma=0.0\) for: \(p=1\) in panel (**a**) and \(p=0.7\) in panel (**b**). While in panels (**c,d**) \(\gamma=0.4\). Figure 7: As Figure 6a,b but for \(\chi_{z}=3\) in panels (**a,b**) and \(\Delta=0.5\) in panels (**c,d**). The two-qubit Heisenberg XYZ system can be realized from spin-1/2 pyrochlores R2V2O7 [30]. Our results present several potential applications in quantum processing as generation of quantum correlations [27; 28] and quantum simulations [44]. Quantum simulations are required to solve various complex problems in diverse areas of science such as exploring complex molecular structure in chemistry [45], studying disorder systems in many-body physics [46], and conceiving high-temperature superconductor materials [47; 48]. The two-qubit entangled system can be used to transfer unknown quantum state by employing quantum teleportation [49], or classical information through quantum dense coding [50], as the degree of entanglement plays a vital role to transfer the unknown quantum state in a perfect or probabilistic way. Furthermore, it could manage the transmission capability of the classical information, which is a crucial parameter to estimate the quality of performing dense coding. Finally, the approach used here can be applied to other physical systems. The results could be important for quantum optics, quantum computation, and quantum machine learning.
# Rapid and Precise Zoom Lens Design Based on Voice Coil Motors with Tunnel Magnetoresistance Sensors
## 3 Rapid and Precise Zoom System Design Example
### VCM Structural Design
#### 3.3.2 Coil Design  
The dimensions of the energized coil should closely match the dimensions of the magnets and the yoke in order to minimize the coil weight and reduce the driving load weight. Therefore, the structural dimensions of the coil are essentially determined in the magnetic circuit design. The coil height (\(H_{c}\)) is 12 mm, the coil thickness (\(T_{c}\)) is 2 mm, and the long side of the inner coil (\(W_{c}\)) is 21 mm, which is consistent with the width of the magnets and the yoke. The short side width (\(L_{c}\)) of the inner coil is 3.5 mm, which includes a 0.5 mm gap between the coil and the yoke both above and below. The dimensional parameters are shown in Figure 8.  
In this case study, we used low-resistivity copper wire for the energized coil. Given the core diameter \(d\) of the energized wire, the total length of the energized coil (\(L_{total}\)) was determined as shown in Equation (6).  
\[L_{total}=\frac{H_{c}}{d}\times\frac{T_{c}}{d}\times 2(W_{c}+L_{c}) \tag{6}\]  
The cross-sectional area \(S_{c}\) of a single wire is shown in Equation (7).  
\[S_{c}=\pi\bigg{(}\frac{d}{2}\bigg{)}^{2} \tag{7}\]  
The resistance of the coil is given in Equation (8), where \(\eta\) represents the electrical conductivity of the wire. In this study, we selected copper wire with resistivity of \(1.68\times 10^{-8}\)\(\Omega\cdot\)m.  
\[R_{c}=\eta\frac{L_{total}}{S_{c}} \tag{8}\]  
Thus, the current in the coil is given in Equation (9), where \(U\) represents the operating voltage.  
\[I=\frac{U}{R_{c}} \tag{9}\]  
Figure 8: Dimensional parameters of the coil.  
By substituting the parameters from Equations (6)-(9) into Equation (5), the driving force \(F_{drive}\) that the VCM can provide is as given in Equation (10).  
\[F_{drive}=\frac{BUW_{c}\tau a^{2}}{8\text{n}(W_{c}+L_{c})} \tag{10}\]  
According to Equation (10), given fixed parameters for the magnetic field strength, wire resistivity, and coil dimensions, the motor driving force is proportional to \(U\) and \(d^{2}\). Due to the system's peak power limitation (less than 18 W) and the use of a standard 12 V power supply, the wire diameter \(d\) can be calculated as 0.24 mm using Equations (6)-(9).  
According to Equation (10), the driving force \(F_{drive}\) is independent of the coil thickness \(T_{c}\) and height \(H_{c}\). In fact, the weight of the coil increases with increasing \(T_{c}\) and \(H_{c}\), which in turn increases the required driving force and makes zooming more difficult. However, in order to ensure the sufficient structural strength of the coil, \(T_{c}\) and \(H_{c}\) should not be below a certain value.
## The EnMAP Spaceborne Imaging Spectroscopy Mission for Earth Observation
The core payload of EnMAP consists of a dual-spectrometer instrument measuring in the optical spectral range between 420 and 2450 nm with a spectral sampling distance varying between 5 and 12 nm and a reference signal-to-noise ratio of 400:1 in the visible and near-infrared and 180:1 in the shortwave-infrared parts of the spectrum. EnMAP images will cover a 30 km-wide area in the across-track direction with a ground sampling distance of 30 m. An across-track tilted observation capability will enable a target revisit time of up to four days at the Equator and better at high latitudes. EnMAP will contribute to the development and exploitation of spaceborne imaging spectroscopy applications by making high-quality data freely available to scientific users worldwide. **Keywords:** EnMAP; imaging spectroscopy; hyperspectral remote sensing; environmental applications; Earth observation