bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transcranial ultrasound neuromodulation induces neuronal correlation change in the rat somatosensory cortex
Authors: Ramachandran Sandhya , Niu Xiaodan , Yu Kai , He Bin 
Published: August 2022

Abstract

Objective. Transcranial focused ultrasound (tFUS) is a neuromodulation technique which has been the focus of increasing interest for noninvasive brain stimulation with high spatial specificity. Its ability to excite and inhibit neural circuits as well as to modulate perception and behavior has been demonstrated, however, we currently lack understanding of how tFUS modulates the ways neurons interact with each other. This understanding would help elucidate tFUS’s mechanism of systemic neuromodulation and allow future development of therapies for treating neurological disorders. Approach. In this study, we investigate how tFUS modulates neural interaction and response to peripheral electrical limb stimulation through intracranial multi-electrode recordings in the rat somatosensory cortex. We deliver ultrasound in a pulsed pattern to induce frequency dependent plasticity in a manner similar to what is found following electrical stimulation. Main Results. We show that neural firing in response to peripheral electrical stimulation is increased after ultrasound stimulation at all frequencies, showing tFUS induced changes in excitability of individual neurons in vivo. We demonstrate tFUS sonication repetition frequency dependent pairwise correlation changes between neurons, with both increases and decreases observed at different frequencies. Significance. These results extend previous research showing tFUS to be capable of inducing synaptic depression and demonstrate its ability to modulate network dynamics as a whole.
Coupling rare event algorithms with data-based learned committor functions using the analogue Markov chain
Authors: Lucente Dario , Rolland Joran , Herbert Corentin , Bouchet Freddy 
Published: August 2022

Abstract
Rare events play a crucial role in many physics, chemistry, and biology phenomena, when they change the structure of the system, for instance in the case of multistability, or when they have a huge impact. Rare event algorithms have been devised to simulate them efficiently, avoiding the computation of long periods of typical fluctuations. We consider here the family of splitting or cloning algorithms, which are versatile and specifically suited for far-from-equilibrium dynamics. To be efficient, these algorithms need to use a smart score function during the selection stage. Committor functions are the optimal score functions. In this work we propose a new approach, based on the analogue Markov chain, for a data-based learning of approximate committor functions. We demonstrate that such learned committor functions are extremely efficient score functions when used with the adaptive multilevel splitting algorithm. We illustrate our approach for a gradient dynamics in a three-well potential, and for the Charney–DeVore model, which is a paradigmatic toy model of multistability for atmospheric dynamics. For these two dynamics, we show that having observed a few transitions is enough to have a very efficient data-based score function for the rare event algorithm. This new approach is promising for use for complex dynamics: the rare events can be simulated with a minimal prior knowledge and the results are much more precise than those obtained with a user-designed score function.
Unveiling the connection between the global roughness exponent and interface fractal dimension in EW and KPZ lattice models
Authors: Mozo Luis Edwin E , de Assis Thiago A , Oliveira Fernando A 
Published: August 2022

Abstract
A connection between the global roughness exponent and the fractal dimension of a rough interface, whose dynamics are expected to be described by stochastic continuum models, still needs more support from simulations in lattice models, which are key to provide completeness for the characterization of a given universality class. In this work, we investigate the asymptotic fractal dimension of interfaces that evolve according to some specific lattice models in d + 1 dimensions (d = 1, 2), which are expected to belong to the Edwards–Wilkinson or Kardar–Parisi–Zhang universality classes. Our results, based on the Higuchi method and on the extrapolation of the effective fractal dimension, allow one to achieve dependence between the asymptotic fractal dimension and global roughness exponent, in which the latter is expected to be hardly accessible for experimentalists. Conversely, we also use a two-points correlation function, which gives the time evolution of the local roughness exponent. As a byproduct, our results suggest that, for d = 1, the fractal dimension converges faster than the global roughness exponents to the asymptotic ones. Therefore, the analysis of the fractal dimension, for d = 1, is suggested to be more accessible than the global roughness exponents to determine the universality class. Corrections for the fractal dimensions in d = 2 were found to be stronger than for d = 1.
Pedestrian counterflow in a floor field cellular automaton model coupled with an evolutionary game
Authors: Chen Ze-Hao , Wu Zhi-Xi , Guan Jian-Yue 
Published: August 2022

Abstract
We study the bidirectional pedestrian flow in a straight corridor using a floor field cellular automaton model, where a game-theoretical framework is exclusively introduced to deal with conflicts that multiple pedestrians are trying to move to the same target position. The pedestrians can behave as either cooperators or defectors, depending on whether they show gentle or aggressive in face of conflicts, respectively. When competing with cooperators, a defector always obtains a relatively greater payoff, characterizing the advantage of occupying the preferred vacant cell, while a reduced payoff factor δ is introduced for mutual defection due to the possible injuries by aggressiveness. We study how the pedestrian counterflow dynamics depends on δ, the corridor width W and the anticipation floor field parameter k
A. It is found that the average separation time of the pedestrians displays a resonance-like behavior as a function of δ, irrespective of the width of the corridor as long as jam does not happen. The way of dealing with conflicts has no qualitative effect on the lane formation, where the jam probability mainly depends on the parameters W and k
A as well as the pedestrian density. A large value of k
A means a strong tendency to avoid potential future collisions and suppress the overtaking motivation, but, at a cost, increases the average separation time of the two groups of pedestrians when the width of the corridor is not so narrow. Our results provide a meaningful perspective on the understanding of the process of lane formation and jam dissolution in the bidirectional pedestrian flow, and may shed light on designing policies to improve the efficiency of passing through.
Half-cell and noise voltages at a metal-electrode and dilute solution interface
Authors: Barbero G , Evangelista L R , Merletti R 
Published: August 2022

Abstract
The detection of bioelectric signals is usually based on an electrode-skin contact that is often mediated by a layer of conductive gel. This interface produces a DC voltage (half-cell potential) and a random noise voltage whose relationship is not well known. The first may cause amplifier saturation and the second posits a limit to the detection of small signals. This work investigates the mechanisms of generation of these two voltages in the simpler case of a metal-electrolyte junction and finds a theoretical expression for both, under a few simplifying hypotheses. An expression is found that relates the two voltages to the ionic concentration and to the parameters defining the dynamics of the adsorption–desorption phenomena taking place at the interface. A relationship is found between the two voltages that is in qualitative agreement with experimental findings reported in the literature. This theoretical background provides a basis for further investigation of the metal-gel and of the gel-skin interfaces not addressed in this work.
Transformer Health Index by Prediction Artificial Neural Networks Diagnostic Techniques
Authors: Abdullah A.M. , Ali R. , Yaacob S.B. , Ananda-Rao K. , Uloom N.A. 
Published: August 2022

Abstract
This paper presents the artificial neural network diagnostic techniques for predicting the health index in transformer. Collection data is measured and tested from insulation resistance in between phase-ground, phase to phase and also the winding resistance transformer. The data was collected from 10 units of transformers from Company Transformer Manufacturing and Servicing (CTMS) in Malaysia. The data was used to calculate condition transformer index or health index transformer. Condition transformer index can identify whether transformer in good condition or not good condition. The purpose of knowing transformer health index or condition transformer index is to prevent failures functional transformer and ensure transformer in stable condition. Prediction health index or condition transformer index can be determined by artificial neural network. Therefore, it can monitor and observe very closely conditions of the transformer. Data health index transformer is very important because it know the condition transformer and can solve the major problem in transformer or do the maintenance in early stage before the transformer is totally malfunction.
The prospect of green energy and technology in Bangladesh
Authors: Askary Md A H A , Hai T B , Showmik S S K , Kader Md A. , Rahman Md Tauhidur 
Published: August 2022

Abstract
Green Energy comes from environmental natural resources which are renewable. Green technology alludes that is earth unneighbourly, created, and utilized in a way with the goal that it does not irritate our condition and conserves natural resources. Its uses are getting a solution for widespread global warming fears and the increasing scarcity of many natural resources. Green energy and technology are interrelated to achieve a stable environment and sustainable development. This paper reviews the studies which are related to green energy and technology and shows the existing scenario, potentialities of using it in Bangladesh. Data identifying strategies are gathered from research papers, government documents, relevant green energy and technology policies, interviews with experts. There are some problems with the growing green energy and technology in the country. Therefore, based on problems, some strategic ideas are recommended in this paper.
Air Plasma Sterilizer Using a Parallel Dielectric Barrier Discharge
Authors: Santjojo Dionysius J D H , Masruroh  , Sakti Setyawan P 
Published: August 2022

Abstract
Air sterilizer is one of the essential components in combating the Covid-19. A wind tunnel model of the air sterilizer using a dielectric barrier discharge plasma is proposed to destroy the virus by direct contact with the plasma. Dangerous ozone production in the plasma reactor should be controlled to a safe level. Two parameters affecting the ozone concentration, i.e., electrical power and airflow, were investigated. The DBD reactor was a cell constructed from an array of alternate electrodes. The plasma was generated by an AC high voltage generator with a range of 2kV -3kV. The power and the high voltage were varied by controlling the DC input voltage of the generator. The airflow was varied by controlling the speed of an exhaust fan from 0.5 m/s to 3.0 m/s. The state was characterized using optical emission spectroscopy in the range of 200 nm – 1000 nm. The results showed that both parameters played a significant role in ozone concentration. The trend of the ozone is strongly correlated with the OH species, which reacts with oxygen. The highest ozone concentration of 4.51 ppm was observed at the DC voltage around 19 volts or the power of 34.2 watts. However, a decrease of the ozone concentration at a voltage higher than 19 volts related to 2.9 kV was observed. In general, the data showed that faster airflow decreases ozone concentration. A drastic decrease of the nitrogen species sustaining the plasma occurred at the airflow higher than 2 m/s.
Effect of Build Parameters on Process Energy Consumption and Material Usage in Fused Deposition Modelling Method
Authors: Omar N W Y , Shuaib N A , Azmi A I , Hadi M H J A 
Published: August 2022

Abstract
Fused deposition modelling (FDM) process is one of popular 3D printing technologies, especially on printing polymer materials for a rapid prototyping. The process is well known for its resource saving, with no tooling cost required and minimum energy demand. However, the challenge is that the process performances are highly influenced by selection of parameters. From literature, consideration on material usage and process energy demand in FDM processes is still limited. This study used an L9 Taguchi orthogonal array design in investigating effect of build orientation, printing speed and layer thickness on process energy consumption and total material usage in FDM processes. The p-values from ANOVA analysis revealed that only layer thickness and build orientation had significant effect on the outputs. In minimising material usage, the strategy is to select the correct build orientation to avoid need of support structure. For reducing energy demand, optimum layer thickness needs to be determined by considering other factors such as mechanical properties and surface roughness. This study provides preliminary findings which will benefit FDM users in using resources efficiently. Further studies are required to complement the findings from the aspects of mechanical and physical properties of the printed products.
Characteristics of Fast Electric Field Generated by Negative Lightning in Northern Peninsular Malaysia.
Authors: Hwang Yong-Jia , Wooi Chin-Leong , Ahmad Mohd Riduan Bin , Nabipour-Afrouzi Hadi 
Published: August 2022

Abstract
The development and advancement of lightning locating system (LLS) reaches until 2021 and the characteristics of lightning can be studied by observing the electric field produced by lightning. There are several studies proven that preliminary breakdown pulses (PBPs) are always preceded the return stroke, the duration of the PBPs and the time for the PBPs preceded the return stroke tend to be different depends on the types of lightning, regions, and location. This paper observed and recorded the fast electric field changes of negative cloud to ground lightning (CG). Total of ten sample data was captured on 13 May 2021 and selected to be analyzed in detail. Information such as rise time to peak, duration of preliminary breakdown pulses has been recorded. The captured result is compared with the results from other papers. The results show that the PBPs duration are very similar when compared with local results which shows an average of 2.347 ms. While the average time for PBPs to precede the first return stroke is around 9.44 ms and the rise time from 10% to 90% peak of first return stroke shows an average time of 4.86 μs
White Blood Cells Detection Using Saturation Level
Authors: Fairuz Nur Liyana Ezaty Mohd , Marzuki Nurhanis Izzati Che 
Published: August 2022

Abstract
Blood is made up of three main components; erythrocytes, leukocytes and thrombocytes. Each of these blood components all have their own roles in the human body. Leukocytes, which can be divided into five types; Basophil, Neutrophil, Eosinophil, Lymphocytes and Monocytes are all part of the body’s defence mechanism to fight against pathogens that could harm the body. Identifying the presence of these blood cells is one of the fundamental ways to diagnose a disease. Hence, blood tests are always being run by physicians in clinical practice. Manually identifying leukocytes is a tedious and time-consuming process, and does not guarantee standardised results as it depends fully on the operator’s skills. Therefore, many works have been done to develop an automated method of leukocyte identification, which aims to reduce the processing time, cost-effective and is efficient in producing standardised results. The proposed method uses the technique of segmenting the nucleus and cytoplasm of leukocytes by extracting it from the Saturation level of the image.
Performance Enhancement of Speed Control for Induction Motor Using Dolphin Algorithm
Authors: Ahmed Firas Saaduldeen , Allu Ahmed A. , Jirjees Maan A. 
Published: August 2022

Abstract
The induction motor is renowned as one of the most motors commonly used in an industry where rapid response and high control precision are needed for a wide range of speeds. In this paper, a field oriented control method (FOCM) has been used to obtain a higher control efficiency by dividing the stator current into torque and field control components, including the space vector pulse width modulation (SV-PWM) technology. FOCM also reduces the harmonics of the inverter output signal and allows the best use of DC voltage. This paper aims to enhance the speed response during a sudden change in load torque or reference speed. The Dolphin Algorithm (DA) is used to find the best parameters of the control circuit in both the current and voltage controllers of the FOCM to improve the motor speed response using two objective functions which are Mean Average Error (MAE) and Mean Error (ME). Simulation results for dolphin-PI controllers show the trial superiority by noting PI controllers error and decrease the delay time during the state change.
Eyeball segmentation and measurement in MRI images of myopic children
Authors: Rayan J E , Mokri S S , Low Y C , Mohd-Ali B , Huddin A B , Mohamad-Shahimin M , Arif N , Abdul-Hamid H , Mohidin N 
Published: August 2022

Abstract
Myopia occurs when the light beam stops before entering the retinal layer, resulting in blurred long-distance vision. Myopia in children is very common nowadays, requiring prompt intervention and effective treatment. Thus, research on myopia among children is aggressively conducted to propose better treatment technology. One of the aspects of myopia research is to analyse the shape of the eyeball and its association with this abnormality. Eyeball imaging is commonly conducted via magnetic resonance imaging (MRI). Thus, this paper presents eyeball segmentation in MRI images of myopic children based on the Chan-Vese Level Set method. MRI eye images of 35 myopic children were used. The measurement of pertinent lines was also done. The accuracy of the lines’ measurement was compared with the manual measurement. An average difference of 0.2825 mm (std 0.2386mm) for the left eye and 0.2677 mm (std 0.2526 mm) for the right eye were obtained. Also, statistical t-test evaluation showed that both measurements were statistically similar, confirming the agreement between the two. In conclusion, the process of segmentation and measurement of the eyeball is important to furnish the need for myopia treatment research and study on any treatment efficacy.
FPGA implementation of programmable Hybrid PUF using Butterfly and Arbiter PUF concepts
Authors: Devika K N , Bhakthavatchalu Ramesh 
Published: August 2022

Abstract
Physical Unclonable Functions (PUF) are physical entities that generates output as a function of process variation for a given input. It is an emerging hardware security solution to safeguard Intellectual Property, authentication of devices and to ensure data integrity through fingerprint generation. Delay based PUFs forms one of the popular category among different kinds of PUFs wherein the interconnect and gates delays due to uncontrollable manufacturing deviations are exploited to generate secret keys. However some of the designs such as arbiter and butterfly PUFs are seldom implemented in FPGA due to higher component of routing delay in comparison to random delay. This research work focus on the design of Hybrid PUF using the concepts of Butterfly and Arbiter PUF to reduce the skew delay factor in these PUFs. The proposed structure combines the benefits of both PUFs to increase the randomness and accuracy of the arbiter PUF. The architecture is designed to be programmable to work for any N-bit challenge as input. The PUF structures was simulated using Modelsim and Xilinx Vivado software version 19.2 were the tool used for implementing the design in spartan-7 FPGA.
Development of Detachable Rogowski Coil Current Sensor using PCB for High Voltage Cable Partial Discharge Measurement
Authors: Akhmal S , Isa Muzamir , Abdullah A Z , Nanyan A N , Bohari Z H 
Published: August 2022

Abstract
Insulation failure in High Voltage (HV) cables is evaluated using a variety of monitoring techniques. Previous silicon technologies were outperformed by wide-bandgap semiconductor power devices with faster switching speeds. Their precise current management or current protection measures must be upgraded. As a result, their precise current control or protection measures have become more sophisticated. The traditional Rogowski Coil (RC) with the magnetic core, on the other hand, has low measurement accuracy, a short measuring range, and is difficult to fabricate. This paper presents and discusses the development of a Rogowski Coil using a detachable Printed Circuit Board (PCB) as a current sensor for Partial Discharge (PD) measurement. Furthermore, the development of this innovative current sensor concentrated on the detachable PCB Rogowski Coil’s capability to measure as a high-voltage (HV) current sensor and its sensitivity in fault diagnosis, over-voltage current sensing, and high-impulse current sensing on HV cables. The experimental design, techniques, and measurement parameters used in models were discussed. Finally, a brief analysis of the detachable PCB RC current sensor such as sensitivity, maximum voltage and current detection is presented. This paper can also be used as a guideline for other researchers to develop an advanced RC current sensor using PCB as a HV current sensor in the future. The measurement results of the detachable PCB RC current sensor such as the sensitivity and current detection signal can also be used as a guideline by another researcher. As a result, the goal of this project is to measure PD on HV cables using an RC current sensor by utilising PCB technology.
A built-in self-test module for 16-bit parallel photon counting circuit using 180 nm CMOS process
Authors: Isaak S. , Yeo H.C. , Chang C.K. , Yusuf Y. 
Published: August 2022

Abstract
This study investigated the use of a built-in-self-test (BIST) module detecting catastrophic errors in photon-counter accumulator for liquid contamination level measurement. Efficient algorithms are exceptionally demanded for a high-count rate and low voltage system photon counting circuit on-chip. The photon counter sensors are also required high sensitivity digital counter that encodes the arrival of photon in precise timing to prevent any count erroring the absence of light. The proposed BIST is integrated on the data acquisition system, where the accumulator is located. The design circuit, functionality and topology tests of BIST and circuit under test are realized with 180 nm Silterra CMOS Process. The same Verilog codes are verified using field programmable gate array (FPGA) to predict the hardware functionality prior fabrication. The measurement was able to detect at least 90 % fault coverage within 16-bit data acquisition system at minimum operating frequency of 166.7 MHz.