esa-sceva/satcom-chunk-collection huggingface dataset:
# An Empirical Study on Customer Churn Behaviours Prediction Using Arabic Twitter Mining Approach
## 5 Conclusions  
With the rising growth of the telecommunication industry, the customer churn problem has grown in significance as well. One of the most critical challenges in the data and voice telecommunication service industry is retaining customers, thus reducing customer churn, by increasing customer satisfaction. The use of social media mining to predict customer churn in the telecommunication sector is unexplored. Therefore, new methods to extract real-time customer satisfaction feedback must be proposed and used to predict customer churn. The current customer churn models used in the telecom companies depend on the historical customer data which become less valuable over time for making predictions, due to the lack of Arabic resources for natural language processing (NLP) and because of the difficulty of the Arabic language. Our proposed SentiChurn model proved its efficiency firstly based on various standard metrics; average precision for our model was 0.93, the average recall was 0.97, the average F1-score was 0.95 and the model accuracy was 95.8%, and secondly based on a comparison with the ground-truth real and recent outcomes provided by a telecom company as 27% of customer churn rate.  
In future work, we will try to obtain more historical data variables from the telecom company. In addition, we will apply more data mining techniques.  
Conceptualization, L.A.; Formal analysis, L.A.; Methodology, L.A.; Project administration, F.S.A.; Supervision, A.I.C.; Writing--original draft, L.A.; Review & editing, F.S.A. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University through the Fast-track Research Funding Program.  
Not applicable.  
The authors declare no conflict of interest.
# Development of Antibiofilm Therapeutics Strategies to Overcome Antimicrobial Drug Resistance
## 6 Investigative Strategies to Eradicate Biofilms
### Antibodies and Macrophages  
Antibodies targeted towards bacterial surface attachment, if used prophylactically, can prevent biofilm biogenesis [209; 210]. A human monoclonal antibody mAb 3H3, was assessed by [PERSON] et al. for its pan-amyloid binding ability. The antibody disrupted biofilms formed by _S. typhimurium_ and eventually enhanced the efficacy of antibiotic treatment _in vivo_. In mice, a 3H3 injection showed antibiotic conciliated clearance of _S. typhimurium_ biofilms in catheters [211; 212; 213; 214]. [PERSON] et al. used a mixture of two MAbs, 12C6/12A1 and 3C1/12A1, which synergistically reduced the attachment and accumulation of _S. epidermidis_ up to 87% [215]. A cocktail of macrophages has the ability to avert _Proteus mirabilis_ biofilms formed on catheters [216]. Additionally, macrophages could eliminate _P. aeruginosa_ biofilms in murine model lungs and eradicate biofilms formed in wounds associated to _S. aureus_[217]. A phage lysin has proven to be efficacious in eradicating biofilms by fundamentally cleaving the bacterial cell and also effective towards  
Figure 13: Investigative strategies to eradicate biofilms.  
persister cells. Recombinant exebacase (Lysin CF-301) for treatment of MRSA endocarditis and bacteria in synergism with some antibiotics is now in clinical trials [218; 219; 220]. The stumbling block with macrophage treatment is the resistance formed and their swift clearance by the host immune response. The spatially architectural community of the biofilm allows the dwelling of phage-sensitive bacteria.
# Cm-Level Photonic-Crystal-Like Subwavelength Waveguide Platform with High Integration Density
## 1 Introduction
As the number of air-hole columns continues to increase, the hybrid waveguide tends to be a PhC-like line-defect waveguide. The transmittance (normalized power) is defined to be \(T=P_{out}/P_{in}\), where \(P_{in}\) and \(P_{out}\) are, respectively, the input and output powers of the waveguide. The corresponding transmission spectra are recorded by power monitors.
# Robotized Mobile Platform for Non-Destructive Inspection of Aircraft Structures
## 2 Structural Design and Control System
### Hardware
The voltage at the input of the MP, under full load (maximum power of the propeller drive), drops to 14.4 V. The voltage drop of 2.6 V results, among other factors, from the resistance of the power cable, which, for a cable with a cross-section of 4 mm\({}^{2}\) and the sum of the lengths of both wires of 8 m, considered in this study, is 0.035 \(\Omega\) with a voltage drop of 1.6 V. The remaining 1 V drop results from the internal resistance of the power supply and the resistance on the connectors used. The maximum recommended supply voltage of the main propeller drive engine, according to the manufacturer's data, is 14.8 V. Therefore, the 14.4 V voltage that powers the engine during its maximum load should be considered correct. The operation of the MP is controlled using a wireless remote control. Similarly to the main system, the remote control is also divided into several functional blocks. Figure 3: The electrical scheme of the MP: M1–M4—wheel drive motors, SM—probe lifting servo, MW—propeller drive motor, R—engine speed controller, ZI—switching power supply. Figure 2: The design (**a**) and hardware implementation (**b**) of the printed circuit of the main system for the MP. The first one is the power supply block. It includes the MCP73831 battery charging system from Microchip. It is an integrated charging system for a single lithium-ion cell. A 18650 battery with a capacity of 2900 mAh from Samsung was used to power the remote control. The last element of the Microchip power supply system is the TC1015-3.3V stabilizer, which is a low-dropout stabilizer. This means that it can operate with a small voltage difference between the input and the output. This is important when the system is powered by a battery, the output voltage of which ranges from 2.8 to 4.2 V, depending on the degree of charge. The next block, similarly to the main system, is the RFM75 radio data transmission system. The third block is the ATMEGA328 microprocessor, which manages the operation of the entire remote control. The fourth block is the layout of the 12-key matrix keyboard. A total of 12 buttons are connected in a 4 \(\times\) 3 matrix arrangement. This allows the microprocessor to read the status of 12 buttons using only seven input/output ports. The next system is the LCD-AG-C128064 CF display. It is a monochrome display with a resolution of 128 \(\times\) 64 pixels with a chip-on-glass design, which is only 2.8 mm thick. It has a built-in ST7565R controller, which allows for simple (programmatic) graphics display. The remote control, like the main control system, is equipped with the MAX3232 serial data transmission system. The system was assembled on a double-sided printed circuit board (see Figure 4a) using mostly surface-mount components. The whole system was mounted in the universal PL2943 WH housing made of ABS plastic (Figure 4b) and covered with a front panel with holes for a display and buttons (Figure 4c).
# Visuospatial Working Memory for Autonomous UAVs: A Bio-Inspired Computational Model
## 3 Materials and Methods  
The bio-inspired VSWM computational model proposed in this paper was implemented on a Bebop 2. This is a low-cost commercial drone equipped with a 14 mega-pixel camera with a fish-eye lens, dual-core processor with quad-core GPU, GPS, and 8-GB flash storage system. Nevertheless, the bio-inspired VSWM computational model was not embedded in the drone. Instead, a laptop (with an Intel core i7 processor, an external NVIDIA GeForce GTX 1060 video card, and 16 GB of RAM) was used to host the bio-inspired VSWM computational model. Therefore, the drone and the bio-inspired VSWM computational model communicate through a Wi-Fi connection. Currently, the bio-inspired VSWM computational model can identify people and vehicles (cars and trucks) in the real world. The following research questions were studied in order to identify the performance and accuracy of the bio-inspired VSWM computational model proposed in this paper:  
1. What is the visuospatial ability of the bio-inspired VSWM computational model when the drone flies between 9.84 and 16.40 feet?
2. Can the bio-inspired VSWM computational model offer a coherent and continuous representation of visual and spatial relationships among interest objects present in the environment?  
To answer these questions, a total of 30 test cases were designed and executed. These test cases were grouped into three scenarios (i) environments with static and dynamic vehicles, (ii) environments with people, and (iii) environments with people and vehicles. Detailed information on these test cases is available at CogniDron/VSWM/test_report. In all the test cases, the drone did not have a specifically defined target in the visual task. Therefore, visual attention was driven by bottom-up processes for generating visuospatial maps of the environment.
## 9 Conclusions  
In this study, we performed scheduling of PTGs in HDCS using three characteristics: critical path, layering, and graph density. The scheduling was performed using two separate algorithms--UMDA and genetic algorithm--to evaluate two parameters: makespan and waiting time. The tests showed that the UMDA had faster response times than the genetic algorithm in the tests proposed for this work. Both algorithms produced similar results with loads lower than 500 PTGs; with loads equal or higher than 500, the genetic algorithm had slower task allocation times in the target system. We found that the genetic algorithm looks for potentially more specific allocations in the clusters, aiming to keep the tasks closer to the allocated resources.  
In addition to the tests proposed, we experimented with the quality of allocation parameter, which allowed us to count the resources that were allocated and to obtain the percentages of resources used in each allocation. This parameter allowed us to observe that the genetic algorithm improves the quality of resource allocation because it produces more combinations during the search and allocation process. Comparatively, the UMDA speeds up the allocations, but leaves resources unallocated into clusters, whereas the genetic algorithm is slow in the allocations, but optimizes the allocations of the resources available in clusters. The acceleration in the generation of allocations produced by the lack of translations make the UMDA faster in generating results, whereas the genetic algorithm is able to improve the results it provides.  
Stricter testing of the allocation quality parameter will be conducted in subsequent studies.
## 1 Introduction  
Secondary infections and organ failure are the gravel consequences observed worldwide during COVID-19, causing a high mortality rate [1]. Secondary infections specifically associated with SARS-CoV-2 are still poorly known; however, many studies have shown that co-infection factors include _Salmonella_, _Shigella_, and _E. coli_[2, 3, 4]. On the other hand, human extra-intestinal diseases, including urinary tract infection (UTI), bacteremia, and meningitis can be caused by a group of pathogens such as _Escherichia coli_[5]. _E. coli_, a producer of ESBLs, is recorded among the six highest multi-resistant grom that are particularly curable with only a few effective drugs [6]. It is frequently correlated with high healthcare costs, morbidities, and mortalities [7, 8]. In 2017, the estimated number of critical cases of infection with pathogens producing ESBLs was about 200,000 with 9100 deaths; however, the total healthcare cost was estimated to be USD 1.2B [9]. Furthermore, numerous investigations have confirmed that the ESBL, exhibited among _E. coli_, is the major mechanism reported for the \(\beta\)-lactam resistance [10, 11]. Over the last two decades, the fast diffusion of ESBLs has emerged globally, with the development of a worldwide outbreak being a powerful menace to human health, while continuous surveys and molecular characterizations of these strains have been conducted in healthcare units.  
The discovery of pharmaceutical compounds with new antibacterial properties used to fight these bacterial infections seems to have been dropped, due to the vicious circle of new resistance for each new antibiotic discovered [12]. On the other hand, the high number of intra-travelers and extra-travelers in KSA has contributed to the wide dissemination of antibiotic resistance, making antibiotic prescriptions a complicated process, especially when it is due to bacterial co-infections or complications in healthcare units for critical clinical cases, particularly throughout the COVID-19 pandemic [13].  
The spread of ESBLs is related to the diversity of enzymes and transferable genetic elements, and the capacity for a large spread of clones [14]. Indeed, a significantly large amount of published data in different countries [15] has indicated that the ST131 clone producing CTX-15 was associated with noticeable epidemiological changes in hospitals and communities for infectious diseases [16]. In KSA, a few epidemiological data on pathogens producing ESBLs were given, and seemed to be mainly focused on Riyadh and Dammam.  
In this observational study, we determined the implication of ESBL genetic factors and plasmids. We assessed the clonal relatedness and virulence factors among a collection of _E. coli_ samples collected between November 2016 and March 2017 in King Fahad Hospital (KFH), Al-Ahsa in KSA.
# From Patient to Musician: A Multi-Sensory Virtual Reality Rehabilitation Tool for Spatial Neglect
## 1 Introduction  
Approximately 25 to 30% of all stroke individuals suffer from Unilateral Spatial Neglect (USN) [1]. Moreover, USN is a syndrome that is systematically under-diagnosed due to a lack of sensitivity in the used assessment methods [2]. Stroke is the leading cause of disability according to the World Health Organisation (WHO), and neglect predicts poor outcomes in functional recovery, leading to longer hospitalisations, functional dependency or long-term disability in everyday activities. Therefore, USN is an important syndrome that requires careful diagnosis and treatment [1, 3].  
USN is a syndrome that is commonly caused by unilateral brain injury, most often a stroke [4]. It is defined as the failure to report, respond or orient to meaningful or novel stimuli that occur on the side contralateral to the hemispheric lesion, where this failure cannot be attributed to either an elemental sensory or motor deficit [5]. The different modalities in which this lack of awareness manifests itself are manifold, and its presence severely hinders functional recovery after brain injury [6].  
Moreover, USN is considered to be a heterogeneous syndrome, which means that the disorder can affect various modalities [7]. The most prevalent ones are the visual, auditoryand motor modality [8]. Although it is crucial for a rehabilitation method to include all the affected modalities, more often than not, solely the visual modality receives attention in current treatments [9]. Visual Scanning Training (VST), for example, is a technique that enjoys a high adoption rate in clinical practice but fails to incorporate other sensory modalities [10]. However, Music Neglect Therapy (MNT) is a therapy method based on active music-making that shows potential for the multi-sensory rehabilitation of USN [11].  
The aim of this paper is to research the feasibility of translating MNT to a Virtual Reality (VR) environment for the rehabilitation of patients with USN, exploiting the immersive power and versatility of VR to provide a multi-sensory experience. For the design of this VR therapy tool, an interdisciplinary approach is taken in close cooperation with experts from the Ghent University Hospital. The resulting proof of concept is evaluated in a pilot study with four individuals suffering from USN and four non-neglect individuals.  
The remainder of this paper is structured as follows. First, relevant related research is discussed in Section 2, followed by the vision of the therapy tool for USN in Section 3. Hereafter, the materials and methods will be discussed, subdivided into Section 4, which elaborates on the design of the proposed therapy tool, and Section 5, which discusses the implementation of the system. Next, Section 6 presents the setup of the performed pilot study. We follow with Sections 7 and 8, which present and discuss the findings of the pilot study. Finally, a concise conclusion will be given in Section 9.
## 2 Guiding the Light
### Single-Mode Coupling  
Single-mode operation is critical for certain precision measurements, such as exoplanet radial velocity [15; 16; 17]. With the advent of adaptive optics (AO) to correct for atmospheric aberrations, the spot size is reduced (i.e., higher Strehl ratio) to allow few-mode fibers to capture the focused light [18; 19]. Moreover, coupling the AO-corrected light on a SMF has recently been demonstrated using a lenslet array of off-axis parabolic mirrors with a coupling efficiency of \(\sim\)25% in the Y-band (970-1070 nm) [20] and in the R-band (570-720 nm) [21].  
With recent developments in extreme AO in concert with phase-induced apodized aperture (PIAA) lenses, a coupling efficiency as high as \(\sim\)74% has been demonstrated in the H-band (1500-1600 nm) for coupling the focused light into a single-mode fiber [22; 23; 24]. This is close to the maximum achievable coupling efficiency in such a system with apodization in the diffraction limit (\(\sim\)90%). Despite these developments, it is more convenient and economical to capture the light in a bundle of few-mode fibers and use the concept of photonic lanterns [25; 26] to transition the few-mode fibers to SMFs [18], since at present extreme AO is effective for only bright astronomical sources in the NIR bands (e.g., i-band magnitude of \(<\)9).
# An Improved Winkler Foundation Modulus for a Beam in a Full Space
## 3 Verification
### Comparison with Previous Research  
An analytical solution for the tunnel's response under fault creep was proposed by [PERSON] et al. [24], wherein a model with a [PERSON] beam resting on the Winkler foundation was used to obtain the analytical solution. The foundation modulus by [PERSON] et al. [20] was used in [PERSON]'s research. In this subsection, the tunnel's responses under fault creep are obtained based on the analytical solution obtained by [PERSON] using the proposed Winkler foundation modulus and [PERSON]'s Winkler foundation modulus. Meanwhile, the corresponding numerical solutions obtained using the solid finite element model in ABAQUS are also given to calculate the errors.  
The elastic modulus of the fixed and moving block is set to 2 GPa, 3 GPa, and 4 GPa, respectively. The corresponding Poisson's ratio is set as 0.32. Meanwhile, the fault zone has an elastic modulus of 1 GPa and a Poisson's ratio of 0.35. The tunnel has an outer radius of 3.1 m and a thickness of 0.35 m. The other parameters are the same as those in the work by [PERSON] et al. [24]. By comparing with the numerical solution, the errors of internal force from the analytical solutions are given below.  
Figure 8: Beam displacement along the axis obtained via different methods [20].  
Figure 9: Beam internal forces along the axis obtained using different methods (a) bending moment; (b) shear force [20].  
Figure 10 gives the errors of the peak internal force response of the tunnel along the tunnel's axis under fault creep. Regardless of bending moment and shear force, the errors of the analytical solutions by the proposed Winkler foundation modulus are smaller than those of [PERSON]'s Winkler foundation modulus. In detail, the error for the bending moment in [PERSON]'s Winkler modulus exceeds 10% for elastic moduli of 3 GPa and 4 GPa. The errors for the bending moment using the proposed Winkler modulus are all less than 10% for different cases. In terms of shear force, the errors of the analytical solution obtained using the proposed Winkler foundation modulus slightly decrease.  
Figures 8-10 show that the accuracy of the Winkler foundation modulus determined by the fitting solutions of the Euler beam on the Winkler foundation and the beam on the three-dimensional elastic foundation, disregarding tangential interactions, is notably higher than that obtained using [PERSON]'s method, in which the tangential interaction is ignored in the elastic foundation model but considered in the model with a beam on the three-dimensional elastic continuum foundation.
## 5 Discussion
### Cost of PRS Prototype  
The cost of each component used in developing the PRS prototype is depicted in Table 2, providing insights into the financial implications of implementing this innovative recycling solution. The amount of EUR 186.1 encompasses elements such as the Asus Tinker Board, sensors, a stepper motor, two cameras, the load cell with amplifier, battery holder, materials for building the prototype, cables, wires, and additional materials that ensure the prototype's functionality. Although the initial financial outlay may seem significant, it is essential to consider the long-term benefits of improved waste management and improved environmental sustainability.  
As technology matures and production scales, costs may decrease, further improving the cost-effectiveness of implementing innovative solutions in regard to recycling efforts.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Component** & **Function** & **Price (EUR)** \\ \hline Asus Tinker Board R2 & \begin{tabular}{c} Serves as the primary processing unit \\ for the system \\ \end{tabular} & 131.71 \\ PIR sensor & \begin{tabular}{c} Motion detection to initiate the \\ recycling process \\ \end{tabular} & 0.52 \\ Stepper motor with driver & \begin{tabular}{c} Controls the movement of the \\ recycling mechanism \\ \end{tabular} & 13.23 \\ Camera (two pieces) & \begin{tabular}{c} Captures images for QR code \\ scanning and object recognition \\ \end{tabular} & 6.04 \\ Load cell with amplifier & \begin{tabular}{c} Measures the weight of the recycled \\ PET bottles \\ \end{tabular} & 0.92 \\ Battery holder (for four batteries) & \begin{tabular}{c} External charging \\ Structural components necessary for \\ the assembly of the prototype \\ \end{tabular} & 3.68 \\ \begin{tabular}{c} Cables, wires, and additional \\ materials \\ \end{tabular} & \begin{tabular}{c} Structural components necessary for \\ the assembly of the prototype \\ \end{tabular} & 20 \\ \begin{tabular}{c} Cables, wires, and additional \\ materials \\ \end{tabular} & \
\begin{tabular}{c} Connect sensors and modules \\ \end{tabular} & 10 \\
\begin{tabular}{c} TOTAL \\ \end{tabular} & - & 186.1 \\ \hline \hline \end{tabular}
\end{table}
Table 2: PRS prototype component costs.