Channel Configuration Research Articles

Automated planning of curved needle channels in 3D printed patient-tailored applicators for cervical cancer brachytherapy.

Purpose&#xD;Patient-tailored intracavitary/interstitial (IC/IS) brachytherapy (BT) applicators may increase dose conformity in cervical cancer patients. Current configuration planning methods in these custom applicators rely on manual specification or a small set of (straight) needles. This work introduces and validates a two-stage approach for establishing channel configurations in the 3D printed patient-tailored ARCHITECT applicator. &#xD;&#xD;Methods&#xD;For each patient, the patient-tailored applicator shape was based on the first BT application with a commercial applicator and integrated connectors to a commercial (Geneva) intrauterine tube and two lunar ring channels. First, a large candidate set was generated of channels that steer the needle to desired poses in the target region and are contained in the applicator. The channels' centrelines were represented by Bézier curves. Channels running between straight target segments and entry points were optimised and refined to ensure (dynamic) feasibility. Second, channel configurations were selected using geometric coverage optimisation. This workflow was applied to establish patient-tailored geometries for twenty-two patients previously treated using the Venezia applicator. Treatment plans were automatically generated using the in-house developed algorithm BiCycle. Plans for the clinically used configuration, TPclin, and patient-tailored configuration, TParch, were compared.&#xD;&#xD;Results&#xD;Channel configurations could be generated in clinically feasible time (median: 2651s, range 1826-3812s). All TParchand TPclinplans were acceptable, but planning aims were more frequently attained with patient-tailored configurations (115/132 versus 100/132 instances). Median CTVIRD98and bladderD2cm3doses significantly improved (p< 0.001 andp< 0.01 respectively) in TParchplans in comparison with TPclinplans, and in approximately half of the patients dosimetric indices improved. &#xD;&#xD;Conclusion&#xD;Automated patient-tailored BT channel configuration planning for 3D printed applicators is clinically feasible. A treatment planning study showed that all plans met planning limits for the patient-tailored configurations, and in selected cases improved the plan quality in comparison with commercial applicator configurations.&#xD.

A Task-driven Adversarial Channel Selection Method for Binary Classification Based on Magnetocardiography.

As the number of sensors in magnetocardiography (MCG) arrays increases to capture detailed cardiac activity, some channels contribute minimally to task performance, resulting in data redundancy and resource consumption. Although existing methods can reduce the number of channels required to meet task demands, they often struggle to balance computational time and the accuracy of the selected channels and overlook the scalability of the selected channels. This limitation means that when environmental conditions change, or when sensors malfunction, redesigning channel configurations becomes necessary, which increases experimental uncertainties. This study introduces a task-driven adversarial channel selection method tailored for binary classification of MCG signals. The optimal channel combination is determined through a group-wise search using a heuristic algorithm, whose objective function is designed to maximize the difference between the classification accuracy and cosine similarity of the selected channel. In evaluations using an MCG dataset from Qilu Hospital of Shandong University, the proposed method successfully reduced the number of channels from 36 to 5 without compromising classification performance. Furthermore, it outperforms existing hybrid sequential forward search method by achieving comparable accuracy with fewer channels, while also demonstrating superior scalability compared to both hybrid sequential forward search and pearson-rank methods. This approach strikes a balance between computational consumption and accuracy, while improving the scalability of the selected channel combinations, enhancing the efficiency and practicality of the MCG system.

A Novel A105Y Mutant of CYP17A1 Exhibits Almost Perfect Regioselectivity in the Production of 17α-Hydroxyprogesterone.

17α-Hydroxyprogesterone (17α-OHP) is a steroid hormone with significant biological activity that can be obtained by catalyzing progesterone (PROG), the main product of sitosterol, through CYP17A1. However, increasing the catalytic specificity of HCYP17A1 for C17 hydroxylation of progesterone (PROG) poses a formidable challenge due to the close proximity of the C16 and C17 positions. In this study, a rational design was utilized to alter the spatial configuration of the substrate channel, leading to the complete abolition of its 16-hydroxylation activity. Subsequent molecular dynamics simulations revealed that the A105Y mutation heightened the rigidity of the G95-I112 region of CYP17A1, consequently regulating the direction of the entry of PROG into the catalytic pocket. Moreover, the establishment of hydrogen bonding between Y105 and R239, coupled with Pi-stacking of A105Y with F114, effectively immobilizes the substrate PROG in a fixed position, explaining the practically perfect regioselectivity observed in A105Y. Finally, a multifaceted enzymatic cascade system, incorporating A105Y, cytochrome P450 reductase (CPR), and glucose-6-phosphate dehydrogenase (ZWF) for NADPH cofactor regeneration, was constructed in Pichia pastoris GS115. The resulting biocatalyst produced 106 ± 3.2 mg L-1 17α-OHP, a 4.6-fold increase compared with A105Y alone. Thus, this study provides valuable insights for improving the regioselectivity and activity of P450 enzymes.

Cooling of highly concentrated photovoltaic cells with confined jet impingement by introducing channel configurations

Appropriate cooling techniques are required to be integrated into highly concentrated photovoltaic cells to maintain the surface of the photovoltaic cell at a uniform temperature. This study focuses on cooling photovoltaic cells with confined jet impingement to reduce non-uniform temperature distribution and thermal and bending stresses to avoid hotspots and current mismatching problems, thereby improving the cell electrical efficiency. Channels are formed in an aluminium heat sink on the backside of solar cell layers such that the coolant strikes the heat sink surface at the centre and exits at the four corners of the module. Different designs of confined jet channel configurations are studied. The effect of the coolant mass flow rate on the hydrothermal performance of the concentrated photovoltaic thermal (CPV-T) system is examined for all channel configurations. The electrothermal performance of the CPV-T system is at its maximum with a quadrant mini-channel with a single inlet. The net electrical power generated by the PV cell is at its maximum of 30.5 W for a mass flow rate of 50 g/min with this channel configuration. Further, the pressure loss is minimal at 163 Pa at 25 g/min, and the temperature uniformity is also maximum, with a temperature difference over the cell surface of 6.3 °C at 50 g/min. The present study will be useful in the thermal management of highly concentrated photovoltaic thermal systems and high-temperature applications.

Real-time, specific, and label-free transistor-based sensing of organophosphates in liquid

Organophosphates (OP), commonly used in agriculture and as chemical warfare agents, pose significant environmental risks, necessitating real-time, low-cost OP detection methods. In particular, liquid-phase OP sensing with minimal sample volumes is crucial. While several methods allow rapid detection of low concentrations of OP vapors, they are effective only in the short term, while vapors are still being produced. Many OP compounds are semi-volatile, leading to the contamination of water, soil, and surfaces, posing a risk of secondary, long-term exposure. Detecting this contamination requires methods that can be directly applied to droplets of the affected medium. Currently, no method provides the desired combination of ultra-sensitivity, quantitative detection, rapid response, and low-cost for detecting OPs in liquid samples. This study aims to demonstrate quantitative, low-cost, real-time, specific, and label-free OP sensing in ultra-small samples using a transistor-based approach. The current work employs the 2-(4-Aminophenyl)-1,1,1,3,3,3-hexafluoro-2-propanol (aminophenyl-HFIP) functionalized meta-nano-channel field-effect chemical sensor (MNChem sensor) to monitor the organophosphate, diethyl cyanophosphonate (DCNP), in liquid samples. The silicon component of the MNChem is fabricated using a complementary metal-oxide semiconductor (CMOS) process, and the amine-based chemical functionalization of the sensing area is performed post-fabrication. The MNChem sensor provides electrostatic control over the source-drain current (IDS), allowing an optimized channel configuration that efficiently transduces localized OP recognition events into significant IDS variations. Sensing is performed using 0.5 μL buffer solution to simulate a miniature field-deployable sensor for on-site liquid analysis. We report the sensing of DCNP with a limit-of-detection of 100 fg/mL, a dynamic range of 9 orders of magnitude, and excellent linearity (≥0.97) and sensitivity. Control measurements confirm the specificity and reliability of the sensor's response, validating its applicability. This study introduces a novel method for OP detection in contaminated droplets using a low-cost disposable transistor technology.

Experimental study on the thermal management performance of immersion cooling for 18650 lithium-ion battery module

Direct liquid cooling technology stabilizes the battery module at the ideal operating temperature by leveraging the coolant's high heat capacity and its heat dissipation ability through circulation. This study introduced a forced-flow immersion cooling method employing transformer oil as the cooling medium for 18650 lithium-ion battery modules. The performance of this cooling system design was assessed under various discharge rates, coolant flow rates, and channel positions. Experimental data reveals that the average temperature of the oil-immersion-cooled battery module was around 26.3% lower than that of the naturally air-cooled battery module under a 2C discharge condition with zero flow rate. The cooling capacity of the oil-immersion system was limited, with theoretical analyses indicating an optimal flow rate of 200mL/min. Four unique cooling channel configurations was designed: side center inlet to center outlet, side upper inlet to lower outlet, front upper inlet to lower outlet, and front center inlet to center outlet. The peak temperatures of the battery module for these setups were 31.7 ℃, 31.0 ℃, 31.0 ℃, 31.0 ℃, and 31.6 ℃, respectively, with a temperature difference of about 2 ℃. Notably, the side upper inlet to lower outlet channel configuration displays superior cooling performance. These findings contribute to advancing more efficient cooling systems and offer valuable insights for optimizing direct liquid-cooled thermal management systems for lithium-ion batteries in the future.

Enhancement of heat dissipation efficiency in the CSNS target through the innovative design of a serial cooling water channel

This paper presents a coupling of the Monte Carlo method with computational fluid dynamics (CFD) to analyze the flow channel design of an irradiated target through numerical simulations. A novel series flow channel configuration is proposed, which effectively facilitates the removal of heat generated by high-power irradiation from the target without necessitating an increase in the cooling water flow rate. The research assesses the performance of both parallel and serial cooling channels within the target, revealing that, when subjected to equivalent cooling water flow rates, the maximum temperature observed in the target employing the serial channel configuration is lower. This reduction in temperature is ascribed to the accelerated flow of cooling water within the serial channel, which subsequently elevates both the Reynolds number and the Nusselt number, leading to enhanced heat transfer efficiency. Furthermore, the maximum temperature is observed to occur further downstream, thereby circumventing areas of peak heat generation. This phenomenon arises because the cooling water traverses the target plates with the highest internal heat generation at a lower temperature when the flow channels are arranged in series, optimizing the cooling effect on these targets. However, it is crucial to note that the pressure loss associated with the serial structure is two orders of magnitude greater than that of the parallel structure, necessitating increased pump power and imposing stricter requirements on the target container and cooling water pipeline. These findings can serve as a reference for the design of the cooling channels in the target station system, particularly in light of the anticipated increase in beam power during the second phase of the China Spallation Neutron Source (CSNS Ⅱ).

Computational Fluid Dynamics Analysis on Proton Exchange Membrane (PEM) Fuel Cell Performance using Honeycomb Flow Channel

Proton exchange membrane fuel cell (PEMFC) systems have the ability to meet our energy demands in the near future since they are green, economical, and clean. They can also use hydrogen as a direct fuel. One of the key design factors influencing the PEMFC's performance is flow field configuration. The configuration of the flow channel in a PEMFC has a profound effect on reactant distribution and water management within the fuel cell. Current study aims to ameliorate fuel cell (FC) performance, water management, and pressure drop (PD) across channels. ANSYS Fluent 18.2 software, including its PEMFC add-on module, is utilized to execute a computational fluid dynamics (CFD) simulation of a 3D model of a PEMFC with a flow channel shaped like a honeycomb structure. A polarization curve, as well as factors such as PD, hydrogen and oxygen concentrations, membrane water content, and current density distribution along flow channels, have been included in the simulation results. The findings suggest that when the FC is operated at 0.45V, homogeneous reactant consumption and greater power and current densities are achieved, and, water generation is high across the Membrane Electrode Assembly (MEA).

Multi-layer topology optimization of dual-fluid convective heat transfer in printed circuit heat exchangers

Optimizing channel configurations in printed circuit heat exchangers is essential for enhancing heat transfer and minimizing pumping power. The present study aims to optimize channel configurations by developing a multi-layer topology optimization (TO) model that simultaneously optimizes the fin structures in both the cold and hot fluid layers. The TO model directly integrates the heat transfer rate as the target function while using the pressure drop from an airfoil structure as the constraint. Counterintuitive channel configurations are generated by the TO model under various Reynolds numbers (Re). The evaluation under both laminar and turbulent conditions demonstrates that the TO-designed channel configuration outperforms conventional channel configurations including empty, airfoil, heatric, louver, modified louver, sine curve, and S-shaped designs. Compared with the airfoil structure, at Re = 300, the optimized structure can reduce pumping power by 17.0 % while increasing heat transfer by 10.8 %, and at Re = 20000 it reduces pumping power by 52.0 % and enhances heat transfer by 1.2 %. The present study introduces a promising method for designing novel printed circuit heat exchangers.

A parametric investigation of Dual-throat nozzle bypass channel configurations for advanced Aviation applications

The Bypass Dual-Throat Nozzle (BDTN) has garnered growing attention due to its remarkable thrust vectoring capabilities. This type of nozzle boasts broad application prospects as it achieves deflection control of the jet stream merely through regulating the opening and closing of bypass channels. Our comprehensive study delves deeply into the intricate parameterization of the bypass channel within the BDTN. Research has demonstrated that utilizing Fluent software in conjunction with the Realizable k-epsilon turbulence model, standard wall functions, and the Sutherland formula for viscosity coefficient approximation can yield a relatively accurate representation of the vector flow field structure within the BDTN. Following the validation of the numerical computation methodology employed in this study, we have investigated the influence of factors such as bypass channel radius, precise valve positioning, and actuation direction on the nozzle's vectoring performance. Key findings indicate that, due to the relatively small proportion of secondary flow, the radius of the bypass channel has minimal impact on the thrust vector angle. The positioning of the valve and its opening direction are critical in determining the thrust vector angle, requiring careful consideration during the design and optimization process. Fully opening the bypass channel does not necessarily yield the maximum thrust vector angle. Moreover, the total pressure, velocity, position, and direction of the secondary flow within the bypass channel exert a more profound influence on the nozzle's vector performance compared to the mere presence of the secondary flow itself. Notably, the forward opening method of the valve emerges as the preferred choice, as it facilitates more precise later vector control.

Energy Efficient Electrolytic-Gated Synapse Transistors Using InGaZnO/HfO2 Gate Stacks With Vertical Channel Configurations

Energy Efficient Electrolytic-Gated Synapse Transistors Using InGaZnO/HfO₂ Gate Stacks With Vertical Channel Configurations

УТОЧНЕНА МОДЕЛЬ ДВОКАНАЛЬНОГО ЕЛЕКТРОПРИВОДА ПОДАЧІ З ПІДСУМОВУВАННЯМ РУХІВ НА ХОДОВІЙ ГАЙЦІ ДЛЯ ВИСОКОТОЧНИХ МЕТАЛОРІЗАЛЬНИХ ВЕРСТАТІВ

The iterative two-channel feed electric drive (ED) with the summation of movements on the rotating sliding nut (RSN) is designed to increase the speed and accuracy of traditional single-channel ED feed mechanisms (FM) of metal-cutting machines with an inertial working tool (WT). A refined generalized mathematical model of movement of the two-channel ED with RSN was obtained, which was built for WT FM of the high-precision coordinate metal-cutting ma-chine of the 24К60АФ4 model. The model takes into account the main static moments of resistance during metalwork-ing, as well as the nonlinear nature of the sliding friction forces in the machine WT FM. Convenient recurrence rela-tions are obtained for the calculation and modeling of sections of the linearized friction characteristic. The structural-algorithmic diagram of the compensated iterative two-channel feed ED with subordinate configuration of control chan-nels is proposed, which makes it possible to compensate in steady-state conditions the negative impact on the accuracy of WT feed of the main static moments of resistance and nonlinearities of sliding friction forces in the drive load. Ref. 9, fig. 3, table.

The influence of water turbulence on surface deformations and the gas transfer rate across an air–water interface

We present experimental results of a study on oxygen transfer rates in a water channel facility with varying turbulence inflow conditions set by an active grid. We compare the change in gas transfer rate with different turbulence characteristics of the flow set by four different water channel and grid configurations. It was found that the change in gas transfer rate correlates best with the turbulence intensity in the vertical direction. The most turbulent cases increased the gas transfer rate by 30% compared to the low turbulence reference case. Between the two most turbulent cases studied here, the streamwise turbulence and largest length scales in the flow change, while the gas transfer rate is relatively unchanged. In contrast, for the two less turbulent cases where the magnitude of the fluctuations normal to the free surface are also smaller, the gas transfer rate is significantly reduced. Since the air–water interface plays an important role in the gas transfer process, special attention is given to the free-surface deformations. Despite taking measures to minimise it, the active grid also leaves a direct imprint on the free surface, and the majority of the waves on the surface originate from the grid itself. Surface deformations were, however, ruled out as a main driver for the increase in gas transfer because the increase in surface area is < 0.25%, which is two orders of magnitude smaller than the measured change in the gas transfer rate.

Parametric study of PEM water electrolyzer performance

AbstractGreen hydrogen can contribute significantly to combating climate change by helping to establish an energy economy that is both sustainable and carbon-free. One pathway to obtaining green hydrogen is by water electrolysis powered by renewable energy. Proton exchange membrane water electrolysis (PEMWE) is a promising option owing to its high current density at high efficiency. Here, we report on experimental results from a parametric investigation of PEMWE. We have examined the effect of water flow rate at 80 °C using a 5 cm2 PEM electrolyzer cell hardware and lab-fabricated membrane electrode assemblies. The results showed that a water flow rate of 0.08 ml cm−2 min−1 was sufficient to meet the water consumption by electrochemical reactions at the anode as well as water depletion by diffusion and electroosmotic drag. We then employed this optimal flow rate to examine the effect of various operating parameters on PEMWE performance and efficiency such as operating temperature, membrane thickness, flow field channel configuration, and porous transport layers as a function of the applied voltage. The results provide useful insights into the operating conditions for optimal PEMWE performance. Graphical abstract

Textile-Based Membraneless Microfluidic Double-Inlet Hybrid Microbial-Enzymatic Biofuel Cell.

This study reports the development of a textile-based colaminar flow hybrid microbial-enzymatic biofuel cell. Shewanella MR-1 was used as a biocatalyst on the anode, and bienzymatic system catalysts based on glucose oxidase and horseradish peroxidase were applied on an air-breathing cathode to address the overpotential loss in a body-friendly way. A single-layer Y-shaped channel configuration with a double-inlet was adopted. Microchannels of biofuel cells were patterned by silk screen printing with Ecoflex to maintain the flexibility of textile substrates without harm to the human body. The electrodes were fabricated with poly(3,4-ethylenedioxythiophene):polystyrene sulfonate and a mixture of multiwalled carbon nanotubes and single-walled carbon nanotubes by screen printing. The effects of electrode materials, catalyst type, catalyst concentration, and glucose concentration in the catholyte were investigated to optimize the fuel cell performance. The peak power density (44.9 μW cm-2) and maximum current density (388.9 μA cm-2) of the optimized hybrid biofuel cell were better than those of previously reported textile- or paper-substrate microscale single microbial fuel cells. The developed biofuel cell will be a useful platform as a microscale power source that is harmless to the environment and living organisms.

Heterostructure-anchored 3D CNT-bridged graphene architecture via layer-by-layer structural engineering for thick electrodes of supercapacitors

The emerging thick electrode concept is dedicated to maximize active material areal loading at the device-scale through straightforward structural designs to meet the high energy density demand. Nevertheless, overcoming the sluggish charge kinetics and complex manufacturing route in thick composite electrodes is still challenging. Herein, a novel all-laser structural engineering protocol is developed to construct MnO-Mn3O4/MnS heterostructure-anchored 3D porous graphene architecture with reinforced carbon nanotube (CNT) interface (MHGC) by layer-by-layer laser induction of polyethersulfone film containing manganese acetate precursors without introducing any templates or catalysts. Creatively, along with the synchronous generation of porous graphene and multivalent manganese compounds heterostructures, a uniform distribution process of nanoparticles is integrated into a one-step in-situ laser irradiation, which is unique and straightforward for preparing thick composite electrodes. Besides, the interlayer bridging of CNT network between MnO-Mn3O4/MnS/graphene layers accelerates electron transport, accompanied by the ameliorative deep diffusion of ions by open graphene macropores derived from laser-assisted vaporization. Thanks to the configuration of efficient electronic bridge and ion channel, combined with multi-heterointerface and fast surface reaction kinetics endowed by heterostructure nanoparticles, MHGC electrode with a thickness of 442 μm delivers a high specific capacitance of 954.5 mF cm−2 (at 0.5 mA cm−2). The assembled symmetrical supercapacitor with LiCl aqueous electrolyte exhibits a broadened potential window of 1.3 V, obtaining a prominent energy density (39.99 μWh cm−2) and power density (1625 μW cm−2). This advanced laser engineering and enabled thick electrodes open a brand-new avenue in burgeoning energy chemistries, not limited to supercapacitors and rechargeable batteries.

Development of a toroidally resolved broadband ECE imaging system for measurement of turbulent fluctuations on the KSTAR.

The two electron cyclotron emission imaging (ECEI) systems installed at adjacent ports (G and H) on the KSTAR tokamak incorporate large-aperture mm-wave optics, broadband electronics, and high speed digitization (up to 1 MSa/s) for 2D and quasi-3D visualization of MHD-scale fluid dynamics. Recently, the ECEI systems have been proved to be capable of visualization of smaller scale fluctuations albeit with a limited spatiotemporal resolution and even capable of measurement of ion cyclotron harmonic waves by direct high-speed sampling of the ECE IF signals. A four-channel prototype subsystem with a higher sampling rate up to 16 GS/s has been integrated into the G-port ECEI system, enabling the measurement of plasma waves in the GHz range in the form of modulated ECE signals and characterization of high-frequency turbulence during the evolution of pedestal. To achieve higher toroidal resolution in the turbulence measurement, the H-port ECEI system is now being upgraded to have a toroidally dual detector array of 2(toroidal) × 12(vertical) × 8(radial) channel configuration and a high-speed subsystem of 2(toroidal) × 4 channel configuration. The new mm-wave optics has been designed via beam propagation simulation, and the measured performance of the fabricated lens indicates a toroidal resolution of 8-10cm depending on the focus position and zoom factor, allowing for the measurement of parallel wavenumber up to k‖ ∼ 0.8cm-1.

Design and Fabrication of 3D‐Printed Lab‐On‐A‐Chip Devices for Fiber‐Based Optical Chromatography and Sorting

Microfluidic lab‐on‐a‐chip (LOC) devices have become essential tools for multitudes of applications in various research fields. 3D printing of microfluidic LOC devices offers many advantages over more traditional manufacturing processes, including rapid prototyping and single‐step fabrication of complex 3D structures. In this work, 3D‐printed microfluidic devices are designed and fabricated for optical chromatography and sorting. Optical chromatography is performed by inserting a single‐mode optical fiber into the device creating a counter‐propagating laser beam to the fluid flow. Particles are separated depending on refractive index and size. To demonstrate optical sorting, a cross‐type sorter 3D‐printed microfluidic device is fabricated that directs the laser beam perpendicular to the flow direction. Design features such as a sloping channel and a channel configuration for 3D hydrodynamic focusing (to aid in controlled sample flow and particle position) help to optimize sorting performance. Stable optofluidic trapping and sorting are successfully achieved using the fabricated microfluidic devices. These results highlight the tremendous potential of 3D printing of microfluidic LOC devices for applications aimed at the optofluidic manipulation of micron‐sized particles.

Pore engineering in highly stable hydrogen-bonded organic frameworks for efficient CH4 purification

The unsatisfactory stability of hydrogen-bonded organic frameworks (HOFs) arising from the weakness and flexibility of hydrogen-bonding (H-bonding) has generally hindered their practical applications. By synergistically employing three key strategies: (Ⅰ) introducing charge-assisted H-bonding to increase the polarity of the framework, (Ⅱ) optimizing the length of the building unit by extending the core structure of the linker molecule, and (III) incorporating functional sites containing methoxy and trifluoromethyl, to increase the stability of HOFs and the adsorption affinity for gas molecules, we successfully synthesized three charge-assisted hydrogen-bonded HOFs (NKM-HOF-3, NKM-HOF-4, and NKM-HOF-5; NKM = Nankai Materials). These HOFs exhibit distinct space configurations of nonporous packing, discrete cavities or continuous one-dimensional channels. Notably, NKM-HOF-5 exhibits commendable thermal and chemical stability and can be readily regenerated by re-solvothermal reaction. The activated NKM-HOF-5a exhibits a low affinity for CH4 but captures C2H6 and C3H8 with a relatively high affinity. According to theoretical calculations, the suitable pore size, together with functionalized and polarized surface environments in NKM-HOF-5a contribute to the excellent selective gas adsorption performance of NKM-HOF-5a. Furthermore, the dynamic breakthrough experiments demonstrate the highly efficient separation performance of NKM-HOF-5a for C2H6/CH4, C3H8/CH4, and C3H8/C2H6/CH4.

EEG-based Sleep Deprivation Classification: A Performance Analysis of Channel Selection on Classifier Accuracy

This study analyses the effect of electroencephalogram (EEG) channel selection on the classification accuracy of sleep deprivation using four distinct classifiers: Random Forest (RF), k-Nearest Neighbours (k-NN), Support Vector Machine (SVM), and Artificial Neural Network (ANN). In this study, the EEG data from ten male individuals in good health were collected. Two distinct sets of EEG channels—a limited frontal channel set (Fp1, Fp2) and a thorough 19-channel set—were used to compare the performance of the classifiers. According to our findings, the k-NN classifier produced the greatest classification accuracy of 99.7% when applied to the 19-channel EEG signals. In contrast, both SVM and ANN classifiers were able to obtain the greatest accuracy of 94% with the frontal channels. Though there are not many gaps, these results imply that employing a larger range of EEG channels greatly improves the classification accuracy of sleep deprivation. The present study emphasizes the significance of channel selection in EEG-based sleep deprivation investigations by showcasing the significant advantages of full EEG signal capture over minimum channel configurations.