Experimental Setup Research Articles

Hybrid Version of the Kedem-Katchalsky-Peusner Equations for Diffusive and Electrical Transport Processes in Membrane.

One of the most important formalisms used to describe membrane transport is Onsager-Peusner thermodynamics (TOP). Within the TOP framework, a procedure has been developed for the transformation of the Kedem-Katchalsky (K-K) equations for the transport of binary electrolytic solutions across a membrane into the Kedem-Katchalsky-Peusner (K-K-P) equations. The membrane system with an Ultra Flo 145 Dialyser membrane used for hemodialysis and aqueous NaCl solutions was used as experimental setup. The H version of K-K-P formalism for binary electrolyte solutions was used to evaluate theoretical coefficients characterizing fluxes of energies and efficiencies for membrane transport processes. The coupling coefficients of membrane processes and the dissipative energy flux were calculated on the basis of the Peusner coefficients obtained from transformation of K-K coefficients. The knowledge of dissipative energy flux, which is a function of thermodynamic forces, allows for the determination of the energy conversions during transport processes in a membrane system. In addition, a frictional interpretation of the obtained coefficients is presented.

Phantom-based gradient waveform measurements with compensated variable-prephasing: Description and application to EPI at 7 T.

Introducing compensated variable-prephasing (CVP), a phantom-based method for gradient waveform measurements. The technique is based on the variable-prephasing (VP) method, but takes into account the effects of all gradients involved in the measurement. We conducted measurements of a trapezoidal test gradient and of an EPI readout gradient train with three approaches: VP, CVP, and fully compensated variable-prephasing (FCVP). We compared them to one another and to predictions based on the gradient system transfer function. Furthermore, we used the measured and predicted EPI gradients for trajectory corrections in phantom images on a 7 T scanner. The VP gradient measurements are confounded by lingering oscillations of the prephasing gradients, which are compensated in the CVP and FCVP measurements. FCVP is vulnerable to a sign asymmetry in the gradient chain. However, the trajectories determined by all three methods resulted in comparably high EPI image quality. We present a new approach allowing for phantom-based gradient waveform measurements with high precision, which can be useful for trajectory corrections in non-Cartesian or single-shot imaging techniques. In our experimental setup, the proposed "compensated variable-prephasing" method provided the most reliable gradient measurements of the different techniques we compared.

Effect of Clamped Member Material and Thickness on Bolt Self-Loosening Under Transverse Loads.

Bolted joints, prevalent in industrial applications for component fastening, are susceptible to self-loosening-a critical issue resulting in a gradual reduction in clamping force. Gaining insight into the underlying mechanisms of self-loosening is crucial. While prior research has largely focused on evaluating component stiffness, limited attention has been given to its impact on the self-loosening behavior of bolted joints under transverse cyclic loading. This study investigates how component stiffness influences self-loosening in bolted joints by varying the material and thickness of clamped members. An experimental setup replicating real-world conditions is devised to simulate loosening caused by cyclic lateral displacement. Tests are conducted using steel and high-density polyethylene (HDPE) clamped members of different grip lengths to explore the relationship between stiffness and self-loosening. Key parameters measured include bolt axial load, transverse force on clamped members, relative displacement, and rotation between the bolt and nut. The findings provide valuable insights into the effects of stiffness across various clamped member materials and grip length combinations, which can enhance the understanding of conditions that promote loosening resistance. Moreover, by highlighting stage-II or rotational loosening, with each test resulting in complete preload loss, the study provides a comparative analysis of the influencing factors. This enables the identification of distinct loosening patterns and supports the development of improved bolted joint designs to reduce loosening.

Examination of the cooling performance of the lithium-ion battery module created using phase change material at different discharge rates and different ambient temperatures

Batteries are one of the most important systems in electric vehicles. The performance of batteries varies depending on temperature, and high battery temperatures reduce battery efficiency and life. In recent years, intensive studies have been carried out on passive systems to prevent the battery module from heating, and many studies have been conducted especially on the use of phase change material (PCM). In this study, a novel battery module design created using PCM is tested by setting up experimental setups at both different discharge rates and different ambient temperatures, and the cooling performance of PCM is examined. As a result, it was found that the temperature increase in the PCM decreases during the melting process and the increase in the battery surface temperature varies according to the current value of the total heat generated in the battery. If the total heat generated in the battery increases, both the battery surface temperature and the temperature rise rate increase; if the total heat generated in the battery is constant or decreasing, the battery surface temperature increases but the temperature rise rate decreases.

Experimental Setup and Machine Learning-Based Prediction Model for Electro-Cyclone Filter Efficiency: Filtering of Ship Particulate Matter Emission

Experimental Setup and Machine Learning-Based Prediction Model for Electro-Cyclone Filter Efficiency: Filtering of Ship Particulate Matter Emission

Microbead Encapsulation for Protection of Electronic Components

Abstract This study investigates the application of microbeads as an innovative encapsulation technique to protect electronic components from harsh mechanical strain. Traditional encapsulation methods using hard epoxy provide substantial mechanical support but create thermal expansion mismatch issues, potentially leading to electronic component failure. We explore the use of finely powdered microbeads to achieve protective structures combining stiffness and energy absorption. The research focuses on key variables, including microbead size, microbead roughness, compaction of microbeads, and circuit board mounting in the encapsulation, all of which influence the encapsulation's effectiveness. Experimental setups and testing protocols were developed to assess the performance of various microbead materials under different impact conditions. Results demonstrate that microbead encapsulation significantly reduces strain on circuit boards, minimizing the risk of damage during mechanical shocks. However, challenges remain, such as optimizing microbead characteristics and modeling their behavior within large-scale circuit board assemblies. Despite these challenges, the findings suggest that microbead encapsulation offers a promising alternative to conventional methods, enhancing the durability and reliability of electronic components in high-stress environments.

The SPICE Modeling of a Radiation Sensor Based on a MOSFET with a Dielectric HfO2/SiO2 Double-Layer.

We report on a procedure for extracting the SPICE model parameters of a RADFET sensor with a dielectric HfO2/SiO2 double-layer. RADFETs, traditionally fabricated as PMOS transistors with SiO2, are enhanced by incorporating high-k dielectric materials such as HfO2 to reduce oxide thickness in modern radiation sensors. The fabrication steps of the sensor are outlined, and model parameters, including the threshold voltage and transconductance, are extracted based on experimental data. Experimental setups for measuring electrical characteristics and irradiation are described, and a method for determining model parameters dependent on the accumulated dose is provided. A SPICE model card is proposed, including parameters for two dielectric thicknesses: (30/10) nm and (40/5) nm. The sensitivities of the sensors are 1.685 mV/Gy and 0.78 mV/Gy, respectively. The model is calibrated for doses up to 20 Gy, and good agreement between experimental and simulation results validates the proposed model.

A wireless optogenetic setup in freely moving mice for evaluation of cortical spreading depolarization in a chronic disease model.

Spreading depolarization (SD) is an electrophysiological phenomenon of massive neuronal depolarization that occurs in a multitude of brain injuries. Clinical studies and experimental data have linked the occurrence of SDs with secondary brain damage. However, there is a translational gap because of methodological limitations between clinical and experimental approaches focusing on short-term effects. Moreover, usage of highly invasive SD triggers has put into question to what extent SDs themselves or the induction method had caused emergence of tissue damage. To overcome this gap, we here show the successful realization of an experimental approach for long-term SD induction in a wireless setup of minimal invasive optogenetic stimulation in freely behaving mice. The proposed method allows for reliable SD induction over the course of three weeks. SD characteristics induced with the wireless setup were comparable to SDs elicited by KCl or cable-bound optogenetic systems. Immunohistological analysis of c-Fos expression revealed neuronal depolarization across the stimulated hemisphere, whereas TUNEL staining revealed no stimulation related apoptosis. Optogenetic SD induction so far relied on cable- or fiber-bound systems which restrict experimental possibilities. The proposed model relies on wireless stimulation that allows SD induction in the home cage. In contrast to existing systems, the wireless setup also allows cage enrichment and group housing, therefore allowing behavioral analyses. This experimental setup has excellent potential to investigate the question of possible long-term SD effects in mouse models of different acute pathologies like traumatic brain injury or migraine.

Text mining technologies applied to free-text answers of students in e-assessment

Educational Text Mining is a rapidly growing field, thanks to the adoption of modern probabilistic and machine learning algorithms. The current study focuses on student e-assessment by means of open-ended questions that require free-text answers (i.e., student essays), whose analysis and evaluation are resource-demanding tasks for the instructor, even when supported by modern e-learning platforms. Topic modeling through the Latent Dirichlet Allocation algorithm is employed in an experimental setup, aiming to (a) extract meaningful topics from the body of pooled student answers (interpretable in the educational context of the course), (b) align the extracted topics with the ‘native’ internal structure of the body of texts, and (c) offer recommendations for the teacher in the form of alternative (meaningful) restructurings of the e-assessment units and consequently of the course content units. Quantitative and qualitative evaluation of the extracted topic models have yielded positive results regarding the first two aims, and as far as the third aim is concerned, the extracted topic models expilicitly suggest that the teacher should proceed with relevant restructurings of the course content. These recommendations are of practical use for the teacher, especially when the teacher seeks to restructure the content of the course towards either fewer or more internal units. In conclusion, topic modeling provides a spectrum of possibilities to the teacher who is interested in exploring ways to improve the structure and organization of a course.

Biosynthesis of Zinc Oxide Nanoparticles Using Dried Leaves of Camellia sinensis: Methods to Characterize and Assess Their Effects on Mesenchymal Stem Cell Viability.

Stem cell nanotechnology (SCN) is an important scientific field to guide stem cell-based research of nanoparticles. Currently, nanoparticles (NPs) have a rich spectrum regarding the sources from which they are obtained (metallic, polymeric, etc.), the methods of obtaining them (physical, chemical, biological), and their shape, size, electrical charge, etc. properties. It is also essential to expand green synthesis applications for the use of NPs in the field of biomedical sciences. For this purpose, there is a need to produce NPs using biological sources (plant, microorganism, algae, yeast etc.…), characterization and investigation of their effects on biological activities of stem cells. This process involves long and laborious procedures, and there may be differences in methods between individual laboratories.In this protocol, biofabrication and characterization of ZnO NPs using dried leaves of Camellia sinensis is described. This experimental setup includes conventional and novel methods that can be applied to biofabricate and characterize the NPs and to examine the viability, apoptotic, and necrotic effects on human adipose tissue-derived mesenchymal stem cells (ADMSCs) in vitro.

Programmed neurite degeneration in human central nervous system neurons driven by changes in NAD+ metabolism

Neurite degeneration (ND) precedes cell death in many neurodegenerative diseases. However, it remains unclear how this compartmentalized cell death process is orchestrated in the central nervous system (CNS). The establishment of a CNS axotomy model (using modified 3D LUHMES cultures) allowed us to study metabolic control of ND in human midbrain-derived neurons without the use of toxicants or other direct disturbance of cellular metabolism. Axotomy lead to a loss of the NAD+ synthesis enzyme NMNAT2 within 2 h and a depletion of NAD+ within 4-6 h. This process appeared specific, as isolated neurites maintained ATP levels and a coupled mitochondrial respiration for at least 6 h. In the peripheral nervous system (PNS) many studies observed that NAD+ metabolism, in particular by the NADase SARM1, plays a major role in the ND occurring after axotomy. Since neither ferroptosis nor necroptosis, nor caspase-dependent apoptosis seemed to be involved in neurite loss, we investigated SARM1 as potential executioner (or controller). Knock-down or expression of a dominant-negative isoform of SARM1 indeed drastically delayed ND. Various modifications of NAD+ metabolism known to modulate SARM1 activity showed the corresponding effects on ND. Moreover, supplementation with NAD+ attenuated ND. As a third approach to investigate the role of altered NAD+ metabolism, we made use of the WLD(s) protein, which has been found in a mutant mouse to inhibit Wallerian degeneration of axons. This protein, which has a stable NMNAT activity, and thus can buffer the loss of NMNAT2, protected the neurites by stabilizing neurite NAD+ levels. Thus CNS-type ND was tightly linked to neurite metabolism in multiple experimental setups. Based on this knowledge, several new strategies for treating neurodegenerative diseases can be envisaged.

Experimental Study of Novel Linear Compressor in Refrigeration System

This study investigates the performance of linear compressor used in vapour compressor refrigeration systems (VCRS). Conventionally, crank-drive reciprocating compressors or rotary compressors are used in VCRS, but the study deals with the innovative Linear compressor, which has been found to pose many merits in comparison to conventional ones. The objective of this research is to provide a comprehensive understanding of the system's performance characteristics from various perspectives, ultimately contributing to the enhancement of future VCRS designs. The experimental test rig has been meticulously designed and developed, utilizing a simple VCRS that incorporates both a crank drive reciprocating compressor and a spring-based linear compressor. A solenoid valve facilitates the operation of one compressor at a time. The performance of this experimental setup was assessed by varying the air flow speed of the fan mounted on the evaporator, ranging from 1 m/s to 2.5 m/s in increments of 0.5 m/s. Also, the observations were made at different ambient conditions. Performance evaluation was conducted based on key parameters, including power consumption, cooling capacity and the Coefficient of Performance (COP). The refrigerant considered for analysis in this study is R600a, which is used in both crank drive and linear compressors. The experimental results indicate the relative advantages and disadvantages of the spring-based linear compressor over the crank-drive compressor. With a redesigned configuration, it is expected that the linear compressor's overall performance could be further improved.

A Robotic Flutist Framework for Exploring Acoustics, Human—Instrument Interaction, and Musical Creation

Abstract This article introduces an experimental robotic setup designed to investigate the performance and sound production of flutes. The flute, renowned for its intricate mechanism enabling musicians to dynamically adjust various parameters, yields a diverse range of rich sounds. A key feature of the flute involves the embouchure—the shaping of the air channel by the musician's lips—providing control over airflow, velocity, distance to the labium, inclination, and position. The robotic testbed manipulates critical parameters of the sound-producing system, incorporating an artificial mouth and a motorized mechanism for adjusting jet length, incident angle, and offset. Specialized software aids in route planning, visualization, and description of the controllable parameter trajectories, also generating automatic positions based on a predefined dictionary. Experimental findings showcase the robot's proficiency in playing simple melodies and producing harmonically rich sounds within the specified range. Spectrogram analysis reveals successful reproduction of intended pitches and timbres. This robotic testbed emerges as a valuable tool for delving into the acoustics of the flute and the interaction between performers and flutes. It provides a robust platform for composers to create music that surpasses normal human capabilities and contributes to the comprehension and design of these intricate instruments.

Conditioning a collective avoidance response in rummy-nose tetra.

Escape waves in animal groups, such as bird flocks and fish schools, have attracted a lot of attention, as they provide the opportunity to better understand how information can efficiently propagate in moving groups, and how individuals can coordinate their actions under the threat of predators. There is a lack of appropriate experimental protocols to study escape waves in highly social fish, in which the number of individuals initiating the escape and the identity of the initiators are controlled. Indeed, highly social fish or obligate schoolers have a tendency to not respond well or to freeze when tested in experimental setups designed for single individuals. In this manuscript, we report the results of a pilot experiment with limited sample size using an aversive conditioning protocol to trigger a collective escape response to a green light in a group of rummy-nose tetra (Hemigrammus rhodostomus). Our experimental results suggest that aversive conditioning can (i) be successfully used in this schooling species, (ii) trigger collective escape responses, and (iii) be transferred from the training setup to a new environment. We also introduce metrics to characterize learning and forgetting at group level. These results nurture promising future empirical research on the cognitive and behavioral mechanisms of escape responses in schools of fish, both at the individual and collective scales.

Heat Enhancement of Ethylene Glycol/Water Mixture in the Presence of Gyroid TPMS Structure: Experimental and Numerical Comparison

Cooling small components is becoming an attractive topic for researchers. In this paper, an attempt is made to use an ethylene glycol/water mixture as a cooling liquid. This liquid is a helpful application for when the fluid is in a harsh environment and should not freeze. The experiment uses an ethylene glycol/water mixture circulating through a triply periodic minimal surface structure (TPMS) made of aluminum and silver. A constant heat flux equal to 38,000 W/m2 is applied, and three different flow rates, 11.8 cm3/s, 15.5 cm3/s, and 19.6 cm3/s, are studied. The experimental setup is complemented with numerical modelling by solving the Navier–Stokes equation and the energy equation using the finite element technique. The flow is Newtonian, and a laminar regime is implemented. Results reveal that the performance of the ethylene glycol/water mixture did not enhance heat removal when compared to water. The average Nusselt number is similar regardless of the concentration of ethylene glycol in the mixture. This average Nusselt number, Nuaverage, in the presence of aluminum TPMS ranges between 60 and 80 (60 < Nuaverage < 80) and between 65 and 85 (65 < Nuaverage < 85) using silver TPMS. The increase in the mixture’s viscosity due to ethylene glycol increased the pressure drop. The performance evaluation criteria reach the maximum value of 90 when the mixture is composed of 5%vol ethylene glycol in water with aluminum TPMS. In the presence of silver TPMS, the maximum performance evaluation criterion is around 95 with a 5% ethylene glycol/water mixture. Finally, it is proven experimentally and confirmed numerically that the TPMS structure secures uniform heat extraction from the hot surface.

The Stability of Trend Management Strategies in Chaotic Market Conditions

This study investigates the stability of trend management strategies under stochastic chaos conditions, with a focus on speculative trading in the Forex market. The primary aim is to evaluate the feasibility and robustness of these strategies for asset management. The experimental setup involves sequential optimization and testing of trend strategies across three EURUSD observation intervals, where each subsequent interval alternates between training and testing roles. Methods include numerical data analysis, parametric optimization, and the use of both conventional and bidirectional exponential filters to isolate system components and improve trend detection. Observations reveal that while trend strategies optimized for specific intervals yield positive results, their effectiveness diminishes on unseen intervals due to inherent market instability. The results show significant limitations in using linear trend-based strategies in chaotic environments, with optimized strategies often leading to losses in subsequent periods. The discussion highlights the potential of integrating trend statistics into multi-expert decision systems, leveraging fuzzy solutions based on fundamental analysis to enhance decision-making reliability. In conclusion, while standalone trend strategies are unsuitable for stable asset management in chaotic markets, their integration into hybrid systems may provide a pathway for improved performance and resilience.

Syntalos: a software for precise synchronization of simultaneous multi-modal data acquisition and closed-loop interventions

Complex experimental protocols often require multi-modal data acquisition with precisely aligned timing, as well as state- and behavior-dependent interventions. Tailored solutions are mostly restricted to individual experimental setups and lack flexibility and interoperability. We present an open-source, Linux-based integrated software solution, called ‘Syntalos’, for simultaneous acquisition and synchronization of data from an arbitrary number of sources, including multi-channel electrophysiological recordings and different live imaging devices, as well as closed-loop, real-time interventions with different actuators. Precisely matching timestamps for all inputs are ensured by continuous statistical analysis and correction of individual devices’ timestamps. New data sources can be integrated with minimal programming skills. Data is stored in a comprehensively structured format to facilitate pooling or sharing data between different laboratories. Syntalos enables precisely synchronized multi-modal recordings as well as closed-loop interventions for multiple experimental approaches. Preliminary neuroscientific experiments on mice with different research questions show the successful performance and easy-to-learn structure of the software suite.

Electromagnetic Railguns and Coil Guns: Comprehensive Analysis of Physical Principles and Applications and Experimental Improvements

This research is mainly to provides a report and summary of the production and experimental principle of our last electromagnetic gun Electromagnetic guns use the basic principle in physics that moving charges or current-carrying conductors are subjected to the electromagnetic force (i.e., the Lorentz force) in a magnetic field to accelerate projectiles. According to the acceleration method, electromagnetic guns can be divided into rail guns and coil guns . An electromagnetic railgun accelerates projectiles using the fundamental principles of physics involving moving charges and current-carrying conductors interacting with a magnetic field, known as the Lorentz force. Electromagnetic Railguns accelerate projectiles to very high speeds using Lorentz force generated by strong electric pulses through parallel conductive rails . A coilgun is a device that uses electromagnetic fields to accelerate metallic projectiles. Its working principle is based on Faraday's law of electromagnetic induction. By passing current through a coil, a strong magnetic field is generated, which propels the projectile along the guide rail. Coilguns offer several advantages over traditional gunpowder-based propulsion methods, including higher initial velocities, extended ranges, reduced recoil, and lower launch noise. However, despite these potential benefits, our experimental setup revealed several limitations.This report summarizes the challenges encountered and Outlines suggested strategies for improving the design and addressing the identified deficiencies, analyzing the problem through a qualitative perspective. To provide readers with effective information

Visualization Experiment on the Influence of the Lost Circulation Material Injection Method on Fracture Plugging

The drilling fluid loss or lost circulation via near-wellbore fractures is one of the most critical problems in the drilling of deep oil and gas resources, which causes other problems such as difficulty in achieving wellbore pressure control and reservoir damage. The conventional treatment is to introduce granular lost circulation material (LCM) into the drilling fluid to plug the fractures. As the migration mechanism of the LCM in irregular fractures has not been completely figured out as of yet, the low success rate of fracture plugging and repeated drilling fluid loss still obstruct the exploitation of deep oil and gas resources. In this paper, the spatial data of actual rock fracture surfaces were obtained through structured light scanning, and an irregular surface identical to the rock was machined on a transparent polymethyl methacrylate plate. On this basis, a visualization experimental apparatus for fracture plugging was established, and the fracture flow space of this device was consistent with that of the actual rock fracture. Employing cylindrical nylon particles as LCM, a visualization experiment study was carried out to investigate the process of LCM bridging and fracture plugging and the influence of LCM injection methods. The experimental results show that the process of fracture plugging includes the sporadic bridging, plugging zone extension and merging, thickening of the plugging zone and complete plugging of the fracture. It was observed in the visualization experiment that a large number of small particles flow deep into the fracture in the traditional fracture plugging method, where all types and sizes of LCM are injected at one time. After changing the injection sequence, which injects the large particles first and the small particles subsequently, it is found that the large particles will form single-particle bridging at a specific depth of the fracture, intercepting subsequently injected particles and thickening the plugging zone, which finally increases the area of the plugging zone by 19%. The visualization experiment results demonstrate that modifying the LCM injection method significantly enhances both the LCM utilization rate and the fracture plugging effect, thereby reducing reservoir damage. This is conducive to reducing the drilling cost of fractured formation. Additionally, the visualized experimental approach introduced in this study can also benefit other research areas, including proppant placement and solute transport in rock fractures.

Factors affecting iron and manganese dissolution in groundwater: treatments with simultaneous oxidation and precipitation methods

ABSTRACT This study explores variations in groundwater (GW) pH, conductivity, ammonium, iron, and manganese parameters to reveal prospective interactions having an impact on the dissolved metal concentrations. To this end, bivariate and partial correlation procedures were applied to the data to obtain incisive evaluation. Besides characterisation efforts, photocatalytic iron and manganese removal experiments were also carried out with Ni-doped TiO2 nano-composite thin films (TFs) on real GW samples. UV-A (365 nm) An LED array was used as the illumination source. The experimental setup was based on three treatment routes including photocatalytic oxidation (PCO), NaOH-aided precipitation and PCO with simultaneous precipitation (SPCO-P). The main statistical analysis and treatment efforts have been performed on data and samples of a single well, respectively (N = 15). However, extended statistical analysis has also been performed on larger data groups (N = 1366) obtained from different GW sources as well. Analytical results have revealed that about 90% of iron and manganese were in oxidised forms which do not precipitate by simple pH regulation. Statistical analysis has also revealed significant interactions between metal concentrations and observed parameters depending on the level of pH and conductivity. Furthermore, the SPCO-P strategy has provided a four-fold increase in reaction rate (pseudo-first-order, kobs: 0.04 min−1). Removal efficiencies of iron and manganese also increased from 10% to 96% – 85%, respectively.