esa-sceva/satcom-chunk-collection huggingface dataset:
# Fatty Acid Composition and Volatile Profile of _M. longissimus thoracic_ from Commercial Lambs
## 4 Discussion
### Non-Lipid Volatiles  
Some identified volatiles were not generated from lipid oxidation directly and were influenced by the production systems via fatty acid profile differences. Terpenes could be transferred from grass to animal tissue, so these compounds are also considered as green forage indicators [41; 42]. For the 6- to 8-month-old lambs, no differences were found in the abundances of beta-pinene and isododecane in meat between lambs grazed on red clover, chicory, perennial ryegrass or mixed pasture. [PERSON] et al. [43] suggested that beta-pinene in beef could be used to determine the region that an animal came from. Our results indicate that meat hydrocarbons from the forage diets did not differ geographically among the farms investigated in New Zealand.  
Sulphur compounds originate from the degradation of cysteine and methionine, two sulphurcontaining amino acids [44]. Dimethyl sulfone, which has an unfavourable \"milky\" flavour in meat from pasture-fed sheep [45], was more abundant in lambs that grazed on red clover compared to lambs that grazed perennial ryegrass, chicory or mixed pasture. This may be a result of different volatiles' degradation pathways influenced by post-slaughter conditions; under more acidic pH (<6) and oxidised conditions, amino acids and glucose tend to produce more pyrazines and furans instead of sulphur compounds [33]. Dimethyl sulphide, which has a sulphurous, onion, and green odour in raw meat [46], was least abundant in Merino lambs. Unlike straight-chain aldehydes, 2-methylbutanal is a Strecker reaction product from amino acids [47], which had the greatest abundance in MIX-W-6-8 lambs. [PERSON] et al. [48] reported that the abundance of acetone in raw beef increased during aging when the post-mortem proteolysis increased the pool of non-volatile compounds, such as free amino acids and nucleotides. 2-Ethylfuran is formed when amino acids and ribose interact in the lipid oxidation pathway [32] and has a high odour threshold of 8.0 mg/L in water [49]. The ewe lambs that grazed on perennial ryegrass had greater abundance of 2-ethylfuran than wether lambs, but this sex effect was not observed between contrast groups with the other diets.
## 4 Process of Remediation for Oil-Contaminated Soil
### Techniques for Chemistry Remediation
#### 4.3.1 Oxidation  
Chemical oxidation is another way to eliminate hazardous chemicals from soil. Oxidation of organic pollutants is performed by using reactive oxidants such as hydrogen peroxide (H\({}_{2}\)O\({}_{2}\)), ozone (O\({}_{3}\)), permanganate (MnO\({}_{4}\)\({}^{-}\)), and persulphate (S\({}_{2}\)O\({}_{8}\)\({}^{2-}\)). The approach depends on the soil medium for efficiency [38]. The Fenton reagent, a mixture of Fe\({}^{+3}\) and H\({}_{2}\)O\({}_{2}\), is also employed in chemical oxidation. In contrast, in the reaction of Fenton, the Fe\({}^{+3}\) inducts processes while H\({}_{2}\)O\({}_{2}\), an oxidising agent, creates O.H. ions. The efficiency of the Fenton reagent on oil removal from sand at a low pH has been proven. Under the right circumstances, this technology removes forty-eight percent of total petroleum hydrocarbons in polluted soils in two hours, indicating it might be utilised to eradicate T.P.H.s from contaminated soils quickly [40]. Other studies have used O\({}_{3}\) as an oxidative approach for eliminating oil from the soil since it is readily created, stored, and managed notably under in situ remediation. Soils treated with this technology may be reused since O\({}_{3}\) returns to O\({}_{2}\) rapidly. Some studies have combined bioremediation with ozonation to boost the effectiveness of the decomposition process. Despite the numerous advantages of ozone, it kills soil microbes. Therefore, supplementation is essential for soil repair. The oxidation process is typically utilised in heavily polluted soil since its implementation is in toxins and at short-range may be oxidised for weeks. The approach may not work well in low-permeability soils [41].
## 1 Introduction
### Brain-Computer Interface Fundamentals  
A brain-computer interface (BCI) is a direct communication pathway between the brain and an external device that allows the user to control or interact with the device using their neural activity. BCI is a device that allows humans to communicate with a computer using only EEG signals taken from the surface of the head. After proper calibration, the user, using the device and dedicated software, is able to control a computer in a way similar to using a mouse or keyboard. The operation of a brain-computer interface begins with the user initiating a specific task or action. This can involve imagining movement, reaching a certain focus threshold, or engaging in meditation, depending on the characteristics the equipment is designed to detect. This is followed by the acquisition and preprocessing of brain signals, which include removing artifacts from the data. Characteristic features are then extracted from the processed signals. Brain-computer interfaces operate by detecting specific patterns of brain activity and translating them into commands that can be used to control a computer application or external device. Slow Cortical Potentials, Sensorimotor Rhythms, and Event-Related Potentials are among the primary neural correlates that have been used to operate BCIs [6]. These neural signals reflect different aspects of brain activity and can be used to control various functions of a brain-computer interface. Slow Cortical Potentials, for example, are low-frequency shifts in the brain's electrical activity, which can be modulated by the user's mental state and utilized for BCI control. Sensorimotor rhythms, which are oscillations in the mu and beta frequency bands over the sensorimotor cortex, can be used to detect motor imagery and intentions. Event-Related Potentials, on the other hand, are time-locked responses to specific sensory, cognitive, or motor events, which can be leveraged for BCI applications like P300-based spellers. The selection and integration of these neural features depend on the specific requirements and design of the BCI system to optimize its performance and usability for the end-user. SSVEP is yet another important and widely employed brain signal in BCIs, which represents the brain's response to a visual stimulus flickering at a specific frequency [7]. This steady-state visual evoked potential has been extensively studied and utilized in various BCI applications due to its high signal-to-noise ratio, ease of detection, and ability to elicit robust responses in the brain. The SSVEP-based BCI approach allows users to control external devices or computer interfaces by focusing their visual attention on flickering visual stimuli, which induces corresponding frequency-specific responses in the brain's electrical activity, which, in turn, can be detected and translated into control commands [7; 8; 9; 10].
assessed various RANS based turbulence models for a slot jet impinging flow at the two values of nozzle to plate spacing ([PERSON] et al., 2012). [PERSON] et al. (2012) focused on jet-axis switching, for which a non-circular free jet is faced with a major change of shape as the downstream distance from the plane of jet origination increases. A comparative study of different Reynolds averaged Navier-Stokes (RANS) based turbulence models has been carried out by [PERSON] and [PERSON] (2018) by numerically simulating a two-dimensional turbulent slot jet impinging air normally on a flat plate, to obtain information about the performance which can be obtained with such an approach. Slot impingement heat transfer has been investigated numerically in the cases of moving plate or moving nozzle separately by [PERSON] and [PERSON] (2018). [PERSON] and [PERSON] (2018) present experimental and numerical investigations of slot air jet impingement cooling of a circular heated cylinder, taking into account a semi-circular confinement to improve the heat transfer rate behind the cylinder. The confined jet impingement heat transfer with different nozzle-plate spacing is also considered by [PERSON] et al. (2018) focusing on the intermittency transition model and crossflow transition model in applying a RANS method. Therefore, there is a relative abundance of numerical analyses on slot jet configurations, mainly focused on reference geometries and turbulence investigations. The application of slot jets to industrial processes is still under development. Indeed, the extensive use of CFD can provide significant support in the development of industrial components, based on fluid dynamics and heat transfer phenomena, as its support to glass production and galvanizing of metal bands testifies [27; 28; 29; 30]. A CFD model, able to simulate the slot jet in different configurations, has been developed. Initially, a single slot has been considered with a 2D model, then a multi-slot jet with two or three slots has been simulated with 3D models. Several distances of the jet from the target surface have been investigated. Moreover, different turbulence models have been considered and discussed, in order to identify the most appropriate model. The numerical results have been compared with the measurements from Gardon and Akfirat [12]. In addition, the slot jet configuration has also been compared with the round jet configuration, developed in a previous work [30] which describes the advantages and merits of one or the other geometry. The CFD model developed for the slot jet impingement technique has been applied on an existing vertical galvanizing industrial line designed with round jets clusters [30] in order to test the present technique on a practical configuration.
# Screening Mechanism and Properties of a Cantilevered Vibrating Sieve for Particles Processing
## 1 Introduction  
Screening is the most fundamental technological process in coal preparation and metallurgy. In industrial practice, vibration screens are used for particle classification, dehydration, medium draining, and other operations [1]. Screening of fine wet particles by traditional screen devices is often not quite effective because of the existence of thin water film on the surface of fine wet particles. Under the combined action of the liquid bridge force and water film surface tension, adjacent particles cluster together and adhere to the sieve. With the extension of screening time, more and more particles adhere to the sieve, thus eventually forming a cover film that plugs the screen sieve [2, 3]. Moreover, near-aperture particles are close to screen holes in size, so they can very quickly get stuck in screen holes, resulting in sieve plugging [4]. One way of solving this problem is to increase sieve acceleration; however, due to the direct rigid coupling between sieve and screen body, an excessive sieve acceleration inevitably increases the acceleration of screen body, influences its structural strength and fatigue life, and even causes structural damage [5].  
At present, elastic sieves [6] and flip-flow sieves [7] can solve the problem of plugging encountered in the screening of fine wet particles to some extent. Relying on their elastic vibration, elastic sieves may experience a geometric deformation, thus further loosening fine wet particles and cracking the cover film [8, 9]. By contrast, the flip-flow sieve made of elastic polyurethane would engage in reciprocating bending-tensioning motion and has a higher amplitude and acceleration relative to traditional rigidsieves. These two kinds of screen sieves help to overcome the adhesive force of the cover film, and promote the dispersion of adhered clustered particles [10; 11; 12].  
According to the studies on the screening property of vibrating screens, discrete element method (DEM)-based numerical simulation can effectively save physical experiment time and increase analysis efficiency. So far, DEM has been extensively applied on vibrating screens, such as the circular vibrating screen [13; 14], the linear vibrating screen [15; 16; 17], the elliptical vibrating screen [18], and the banana screen [19; 20]. Studies in this field mainly focus on rigid rectangular or circular mesh sieves, which do not deform during screening. When they are utilized to process near-aperture particles or fine wet particles, the plugging may reduce the screening efficiency of vibrating screens [21].  
Based on studies about elastic sieves, and as the cantilevered vibration under foundation displacement excitation is more significant than fixed end vibration, this paper will propose a cantilevered vibrating sieve (CVS), analyze its anti-plugging mechanism and screen-penetrating probability, establish a vibration characteristic calculation model for the anti-plugging mechanism, and investigate its screening performances through the discrete element method.
# An Experimental Analysis of Gas Reduction in Multiphase Flow with a KMS Helical Static Mixer
###### Abstract  
The separation dynamics of a multiphase fluid mixture is studied with the aim to validate the gas reduction from the mixture by means of a KMS helical static mixer device through a laboratory prototype based on the jet-pump artificial lift system for oil extraction. The study is focused on the cyclone phenomenon, produced by the KMS, to experimentally verify the reduction of foaming in a reservoir behaving as a horizontal gravity separator of an oil-gas-water mixture under specific dynamics conditions of velocity and pressure of an incoming streamline, as well as some physical mounting configurations of the device. The results were numerical and experimentally validated, projecting the real performance in three-phase separators in an oil extraction field to improve efficiency in pumping machines regarding the negative effects of the gas. Concerning the gas reduction, a KMS of two elements located at 100 mm from the entrance of the horizontal reservoir and 20 mm from a gas casing tube successfully improves the gas isolation from the mixture, from 29.2% to practically 0% over 200 min in the reservoir, to let oil and water become separated by sedimentation. This gas reduction is indirectly assessed by the emulsion that is generated, which affects the time of oil separation in the counterbalance.  
Keywords:KMS; gas separation; sedimentation; oil extraction Article
# Optimization of Signal Detection Using Deep CNN in Ultra-Massive MIMO
## 4 Conclusions  
Ultra-massive MIMO systems, representing a significant future advancement, incorporate additional communication antennas and new techniques or procedures that can enhance system efficiency and problem-solving capabilities. This paper focused on finding methods that lead to more effective communication and reduce issues. One such approach was the introduction of a CNN-SD deep learning signal detection technique within an ultra-massive MIMO system. The authors employed various techniques for comparison with the LS, MMSE, and ELMx-based machine learning groups. Three algorithms of ELM, RELM, and ORELM, along with the proposed CNN-SD, were examined to assess their performance for signal detection. The analysis of MSE, BER, capacity, and outage probability demonstrated that CNN-SD outperformed the other algorithms. Therefore, for future systems utilizing ultra-massive MIMO, CNN-SD emerges as the optimal choice for signal detection. In our future work, we aim to enhance the efficacy of our proposed method by employing a strategy that integrates score combination techniques and multi-scale neural networks, as well as exploring additional neural network architectures for performance optimization.  
Conceptualization, P.U. and A.I.; methodology, C.K, P.U., and A.I.; software, C.K.; supervision, P.U. and A.I.; validation, P.U.and A.I.; formal analysis, P.U. and A.I.; funding acquisition, P.U.; investigation, C.K.; project administration, P.U. and A.I.; resources, C.K., P.U., and A.I.; data curation, C.K.; writing--original draft preparation, C.K.; writing--review and editing, C.K. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Figure 10: The outage probability performance of ELMx and CNN-SD in ultra-massive MIMO systems.
## 2 Materials and Methods
### Statistical Analysis and Mapping  
Statistical analyses were performed using the SPSS software, version 17. All individual variables were estimated in terms of minimum, maximum, standard deviation (SD), skewness and kurtosis. The correlation analysis was based on Pearson's coefficients and the spatial distribution maps for the natural radionuclides and radiological hazard indexes were built using the inverse-distance weighting (IDW) interpolation method, generated in ArcGIS software, version 10.2.
## 5 Conclusions  
It was necessary to develop new, proper strategies for controlling insect pests in agricultural facilities due to a dramatic increase in insecticide resistance in major insect pests, toxicological issues to workers, and residual properties of pesticides in crops. With this regard, we studied a new application of ethyl formate, a safe fumigant, to control _B. tabaci_, which has severely damaged yellow melon (YM) in vinyl houses. The LCT\({}_{90}\) values of 2, 4, and 12 h EF fumigation against _B. tabaci_ were 1.67, 2.08, and 7.65 g h m\({}^{-3}\), respectively. As for the LCT\({}_{90}\) values of _B. tabaci_ by fumigation times on YM, 2 and 4 h EF fumigation treatments had no phytotoxic effects on YM. Based on these results, high efficacy of ethyl formate was found to control _B. tabaci_ adults and had no phytotoxic effects on YM in a vinyl house. Therefore, EF fumigation for 2 h with a 2 g m\({}^{-3}\) concentration level could control against over 90% _B. tabaci_ with no phytotoxic effects on YM. It would be a new alternative tool for the currently used pesticides.  
Conceptualization, T.H.K., B.-H.L. and S.-E.L.; methodology, T.H.K., B.-H.L. and I.-H.J.; software, T.H.K.; validation, B.-H.L., I.-H.J. and S.-E.L.; formal analysis, T.H.K. and B.-H.L.; investigation, C.G.P., B.-H.L. and S.-E.L.; resources, T.H.K. and C.G.P.; data curation, T.H.K., B.-H.L., I.-H.J. and S.-E.L.; writing--original draft preparation, T.H.K., B.-H.L. and S.-E.L.; writing--review and editing, T.H.K., C.G.P., B.-H.L., I.-H.J. and S.-E.L.; visualization, T.H.K. and S.-E.L.; supervision, B.-H.L. and S.-E.L.; project administration, S.-E.L.; funding acquisition, B.-H.L. and S.-E.L. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through the Crop Viruses and Pests Response Industry Technology Development Program, funded by the Ministry of Agriculture, Food and Rural Affairs (MAFRA) (321098-3).  
Not applicable.  
The authors declare no conflict of interest.
## 4 Conclusions  
To improve FSP parameters for AMMC joint fabrication, a Taguchi L9 factorial design was employed. The process of optimizing the parameters involved fabricating AMMCs with two distinct reinforcements, namely silicon and coal. The fabricated composites were AA5083/Silicon carbide composite and AA5083/Coal composite. Mechanical properties such as hardness, tensile strength, and percent elongation were evaluated after the composites were fabricated.  
The Taguchi approach based on the S/N ratio demonstrated that:  
* The highest UTS and the percentage elongation for the AA5083/Silicon carbide composites fabrication process can be achieved if the rotation speed has been set to level 2 on the control panel, the traverse speed at level 1, and the tilt angle was at level 3. The best parameters for optimum microhardness are tilt angle at level 3, traversal speed at level 2, and rotational speed at level 2.
* At the second level of rotational speed, the third level of traversal speed, and the third level of tilt angle, for the the AA5083/Coal composite joints had the best FSP parameters to enhance the ultimate tensile strength, percentage elongation, and micro hardness.  
The Taguchi approach based on the ANOVA demonstrated that:  
* According to an ANOVA study, rotating speed has a larger impact on percentage elongation and microhardness for AA5083/Silicon carbide and AA5083/Coal composite joints. The ultimate tensile strength of AA5083/Silicon carbide is more affected by rotating speed, whereas the ultimate tensile strength of AA5083/Coal is more affected by tilt angle. The results indicate that the two different reinforcements have varying effects on the process parameters, suggesting that customized optimization strategies may be required based on the type of reinforcement used. These differences in ranking order are significant because they highlight the distinct material behaviors of the reinforcements during FSP. Harder reinforcements like SiC rely more on heat generation and plastic deformation for effective distribution and bonding, which iswhy rotational speed is dominant. In contrast, softer reinforcements like coal benefit more from controlled material flow and uniform particle dispersion, making tilt angle a critical factor. Based on the results the conclusion was drawn that:
* The best processing parameters for fabricating AA5083/Coal composite were a tilt angle of 2 degrees, a traverse speed of 60 mm/min, and a rotation speed of 900 rpm.
* The best processing parameters used when fabricating AA5083/Silicon carbide composite that yielded maximum microhardness were at a rotational speed of 900 rpm, traversal speed of 45 mm/min, and tilt angle of 2 degrees; the best combination of parameters to attain the maximum ultimate tensile strength and percentage elongation of the composite was achieved at a rotational speed of 900 rpm, traverse speed of 30 mm/min, and tilt angle of 2 degrees.
# Vehicular Edge-Computing Framework for Making Use of Parking and Charging Electric Vehicles
## 3 System Model and Definitions
### Utility Function for Requesting Vehicle  
Generally speaking, with the payment for the computation offloading service, the requesting vehicle expects to obtain high service satisfaction. Consequently, the utility function of the requesting vehicle can be defined as the service satisfaction minus the payment and its data transmission energy consumption. We assume that \(p_{iv}\) and \(p_{ie}\) denote the service prices given by the edge server and the ECP, respectively. Then, the utility function of the requesting vehicle can be defined as \(U_{R_{i}}\):  
\[U_{R_{i}}=D_{R_{i}}-p_{iv}q_{iv}-p_{ie}q_{ie}-\left(E_{iv}^{t}+E_{ie}^{t}\right), \tag{8}\]  
where \(D_{\text{req}}\) is the satisfaction function of the requesting vehicle, which is determined by the allocated computation resources and the task processing delay obtained by the requesting vehicle, denoted as:  
\[\begin{split} D_{R_{i}}=\omega\Big{[}(1-\mu T_{\text{iv}}^{c})q_ {iv}+\Big{(}1-\mu T_{ij}^{c}\Big{)}q_{ie}\Big{]}\\ =\omega\Bigg{[}\Big{(}1-\frac{\mu\alpha q_{iv}}{C_{o}}\Big{)}q_{ iv}+\Big{(}1-\frac{\mu\alpha(Q_{i}-q_{iv})}{C_{je}}\Big{)}(Q_{i}-q_{iv}) \Bigg{]}\\ =\omega\Bigg{[}Q_{i}-\frac{\mu\alpha Q_{i}^{2}}{C_{je}}+\frac{2 \mu\alpha Q_{i}q_{iv}}{C_{je}}-\Bigg{(}\