Low Power Research Articles

Novel a-IGZO TFT Pixel Driving Circuit Using Hybrid PWM and PAM Method With Lower Power Consumption for Micro-LED Display

Novel a-IGZO TFT Pixel Driving Circuit Using Hybrid PWM and PAM Method With Lower Power Consumption for Micro-LED Display

Effects of transformational leadership on psychological empowerment and employee engagement: a comparative study of Bangladesh and Thailand

Purpose Grounded in the transformational leadership theory, conservation of resource theory and job demands-resources model, this paper aims to examine the effect of transformational leadership on psychological empowerment and employee engagement of faculty members in Bangladesh and Thailand. This study also integrates Hofstede’s cultural dimensions theory to justify whether transformational leadership could affect psychological empowerment of faculty members in these two countries differently. Design/methodology/approach Survey data were collected from a total of 457 faculty members from two universities in Bangladesh (n = 243) and two universities in Thailand (n = 241). This study used partial least squares structural equation modeling for analyzing the proposed model. Findings The evidence shows that faculty members who worked for department heads and who exhibited transformational leadership demonstrated high level of psychological empowerment and employee engagement. Psychological empowerment also mediates the effect of transformational leadership on employee engagement. Moreover, the degree to which transformational leadership positively affects psychological empowerment is stronger for faculty members in a higher power distance culture (Thailand) than for those faculty members in a lower power distance culture (Bangladesh). Practical implications Because human capital plays a crucial role in determining the potential of universities to achieve superior performance, universities should provide leadership training to help department heads understand the key elements of transformational leadership and apply them in their management practices to promote empowerment and engagement of their faculty members. Originality/value The finding provides new evidence that broadens the knowledge from existing research about the cross-cultural effectiveness of transformational leadership, which has not been explored in the area of psychological empowerment.

High-Efficiency Vertical-Chip Micro-Light-Emitting Diodes via p-GaN Optimization and Surface Passivation

Micro-LEDs have found widespread applications in modular large-screen TVs, automotive displays, and high-resolution-density augmented reality glasses. However, these micron-sized LEDs experience a significant efficiency reduction due to the defects originating from the dry etching process. By controlling the current distribution via engineering the electrode size, electrons will be less concentrated in the defect region. In this work, we propose a blue InGaN/GaN compound parabolic concentrator micro-LED with a metallic sidewall to boost efficiency by combining both an optical dipole cloud model and electrical TCAD (Technology Computer-Aided Design) model. By merely modifying the p-GaN contact size, the external quantum efficiency (EQE) can be improved by 15.6%. By further optimizing the passivation layer thickness, the EQE can be boosted by 52.1%, which helps enhance the display brightness or lower power consumption.

Modeling and simulation of earth coverage of a low earth orbit (LEO) satellite

Efficient management of operations in near space, just beyond the Earth’s atmosphere, relies on the precise control of satellites positioned relatively close to our planet. Satellite systems, serving critical functions in telecommunications, observation, exploration, and more, have demonstrated their prowess as a transformative technology, consistently delivering high-precision data over numerous years. Among satellite systems, Low Earth Orbit (LEO) technology is gaining prominence due to its advantages, including lower power requirements for transmission, reduced propagation delays, and heightened coverage for polar regions. Achieving optimal efficiency from LEO satellites necessitates a thorough understanding of their fundamental orbital parameters and precise control over them. This study explores the orbital analysis and Earth coverage considerations of LEO satellites, scrutinizing orbital parameters in detail to compute coverage areas across various scenarios. Through this investigation, the potential benefits of data exchange with ground stations facilitated by LEO satellites are explored. In addition, the implications are discussed regarding the adjustment of data exchange topologies according to geographical locations and country borders.

Transfontanellar shear wave elastography of the neonatal brain for quantitative evaluation of white matter damage

Cerebral white matter damage (WMD) is the most frequent brain lesion observed in infants surviving premature birth. Qualitative B-mode cranial ultrasound (cUS) is widely used to assess brain integrity at bedside. Its limitations include lower discriminatory power to predict long-term outcomes compared to magnetic resonance imaging (MRI). Shear wave elastography (SWE), a promising ultrasound imaging modality, might improve this limitation by detecting quantitative differences in tissue stiffness. The study enrolled 90 neonates (52% female, mean gestational age = 30.1 ±\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pm \\hspace{0.17em}$$\\end{document}4.5 weeks), including 78 preterm and 12 term controls. Preterm neonates underwent B-mode and SWE assessments in frontal white matter (WM), parietal WM, and thalami on day of life (DOL) 3, DOL8, DOL21, 40 weeks, and MRI at term equivalent age (TEA). Term infants were assessed on DOL3 only. Our data revealed that brain stiffness increased with gestational age in preterm infants but remained lower at TEA compared to the control group. In the frontal WM, elasticity values were lower in preterm infants with WMD detected on B-mode or MRI at TEA and show a good predictive value at DOL3. Thus, brain stiffness measurement using SWE could be a useful screening method for early identification of preterm infants at high WMD risk.Registration numbers: EudraCT number ID-RCB: 2012-A01530-43, ClinicalTrial.gov number NCT02042716.

Volatile threshold switching devices for hardware security primitives: Exploiting intrinsic variability as an entropy source

In the age of the Internet of Things, the proliferation of edge devices has resulted in a significant increase in personal information that is susceptible to theft and counterfeiting at various stages of data communication. As a result, substantial attention has been focused on hardware (HW) security elements, such as the true random number generator and physical unclonable function. With the recent surge in research and development of emerging memristors, which exploit the inherent variability of these devices, there has been a notable increase in studies on HW security. Particularly, volatile threshold switch (TS) devices, which exhibit insulator/metal characteristics below/above a certain threshold voltage, show great promise as security devices due to their lower power consumption and higher cycling endurance compared to nonvolatile memory devices. Despite the promising attributes and increasing demand for TS devices for HW security, there remains a lack of a comprehensive overview covering various TS devices and their potential contributions to HW privacy. To address this gap, this review provides an encompassing analysis of different types of TS devices and their performance in HW security literature, providing insight into current limitations and the future prospects of HW security primitives based on TS devices.

Acute cardiovascular and muscular response to rowing ergometer exercise in artificial gravity – a pilot trial

Prolonged immobilization and spaceflight cause cardiovascular and musculoskeletal deconditioning. Combining artificial gravity through short-arm centrifugation with rowing exercise may serve as a countermeasure. We aimed to compare the tolerability, muscle force production, cardiovascular response, and power output of rowing on a short-arm centrifuge and under terrestrial gravity. Twelve rowing athletes (4 women, aged 27.2 ± 7.4 years, height 179 ± 0.1 cm, mass 73.7 ± 9.4 kg) participated in two rowing sessions, spaced at least six weeks apart. One session used a short-arm centrifuge with +0.5 Gz, while the other inclined the rowing ergometer by 26.6° to mimic centrifugal loading. Participants started self-paced rowing at 30 W, increasing by 15 W every three minutes until exhaustion. We measured rowing performance, heart rate, blood pressure, ground reaction forces, leg muscle activation, and blood lactate concentration. Rowing on the centrifuge was well-tolerated without adverse events. No significant differences in heart rate, blood pressure, or blood lactate concentration were observed between conditions. Inclined rowing under artificial gravity resulted in lower power output (−33%, p < 0.001) compared to natural gravity, but produced higher mean and peak ground reaction forces (p < 0.0001) and increased leg muscle activation. Muscle activation and ground reaction forces varied with rotational direction. Rowing in artificial gravity shows promise as a strategy against cardiovascular and muscular deconditioning during long-term spaceflight, but further investigation is required to understand its long-term effects.

Association between time of assessment within a school year and physical fitness of primary school children

The dissociation of effects of age, time of assessment and cohort is a well-known challenge in developmental science. We examined effects of time of assessment in the school year on children’s physical fitness using data from 75,362 German third-graders from seven cohorts. Children were tested once either in the first or second school term of third grade. Tests examined cardiorespiratory endurance (6-min run), coordination (star-run), speed (20-m sprint), lower (standing long jump) and upper (ball-push test) limbs muscle power, and flexibility (stand-and-reach test). We estimated the effect of time of assessment using a regression discontinuity design specified in a linear mixed model with random factors child and school and adjusted for age, sex, and cohort effects. Coordination, speed, and upper limbs muscle power were better in second compared to first school term, with boys exhibiting a larger increase of upper limbs muscle power than girls. There was no evidence for changes in cardiorespiratory endurance, lower limbs muscle power, and flexibility between assessments. Previously reported age and sex effects as well as secular fitness trends were replicated. There is thus evidence for improvement of some physical fitness components beyond age and cohort effects that presumably reflects the benefit of physical activity in physical education and other settings. Effects of assessment time should be taken into consideration in performance-based grading or norm-based selection of children.

Optimization research of handwritten digit recognition algorithm based on hardware neural networks

In the modern era of digitization, the widespread application of handwritten numerical data has led to an exponential increase in data volume, necessitating efficient real-time recognition and processing systems. This project is grounded in the foundational structure of neural networks, with a specific focus on integrating these networks into hardware through Very-Large-Scale Integration (VLSI). The primary objective is to achieve faster processing speeds, lower power consumption, and real-time operations. The central emphasis of this study is the design and implementation of a hardware neural network system tailored specifically for handwritten digit recognition. Drawing from neural network theory, we explore the construction of a hardware-based handwritten digit classifier. The fundamental model employed is the single-layer perceptron neuron model. Upon receiving 28x28 pixel grayscale images, the image classifier utilizes pre-trained weights, activation functions, and a maximum selector to compare and output recognition results for numerical digits. The concrete implementation is realized using the Verilog hardware description language, coupled with algorithm optimization strategies to enhance performance and efficiency. This research endeavor aims to provide an effective hardware solution for real-time handwritten digit recognition in the digital age.

226 nm Far‐Ultraviolet‐C Light Emitting Diodes with an Emission Power over 2 mW

Far‐ultraviolet‐C (far‐UVC) light emitting diodes (LED) emitting at an emission wavelength of 226 nm with different n‐AlGaN contact layers, quantum well barriers, and quantum well numbers are compared regarding their emission power, operation voltage, and lifetime. Electroluminescence measurements show higher emission power but also an increased operation voltage with increasing Al mole fraction in the n‐AlGaN contact layer. Furthermore, it is found that both the mean emission power and the device lifetime decrease with increasing Al mole fraction (82–89%) of the quantum well barriers and therefore with increasing barrier height. Finally, 226 nm LEDs with 6 and 9 quantum wells are compared. It is observed that the sample with 9 quantum wells shows an around 30% lower mean emission power but, in contrast, the L70 lifetime of these LEDs is higher by a factor of around five. Based on these optimizations, 226 nm LEDs with a maximum external quantum efficiency of 0.28% (wall plug efficiency of 0.18%) as well as an emission power of 2.1 mW and an operation voltage of 9.6 V at 200 mA are realized.

Improvement of synaptic property of GeSe based CBRAM by engineering the deposition condition of switching matrix

A study of effect of deposition condition of germanium selenide (GeSe) switching layer to Conductive bridging random access memory (CBRAM) device property was conducted to enhance memory property and synaptic property. The devices deposited under the varied deposition conditions were analyzed by current distribution of each state (Low-resistance state [LRS], High-resistance state [HRS]), conduction mechanism analysis, chemical analysis, and synaptic analysis according to pulse conditions. When we deposited switching layer at lowest power (40 W), more Ag ions move to the switching matrix and make lower operation voltage. But there were some disadvantages, which were worst distribution and higher HRS current, less memory window, nonlinear and rapid increase of potentiation process. Conversely, although the device deposited at high voltage increased the operating voltage, but there are improvements, such as the highest memory window and improved linearity of potentiation. The best sample was conducted the synaptic property measurement, and the device successfully mimicked the biological synaptic property with the good linearity of potentiation and depression, spike-rate dependent plasticity (SRDP) and spike-timing dependent plasticity (STDP) properties.

Performance improvement of set of worm gears used in soot blower through profile modification

The present design of a set of worm gears used in a soot blower produced by a certain manufacturer has an efficiency of 68.8%. A soot blower is one of the most critical components in industrial applications for removing the large amounts of soot generated by boilers and is required to be operational 24×7. The energy consumption of the soot blower depends on its working efficiency and ultimately the design of its set of worm gears. This paper focuses mainly on the design and analysis of available industrial worm-gear sets used in soot blowers. The theoretical, experimental, and finite-element analysis approaches are validated for the stability of the worm gear set under typical input conditions. This paper also describes an analytical design of experiments (DOE) approach to identify the most significant factor for performance (efficiency) improvement and suggests some design improvements for the worm gear set using the profile modification approach. These ensure the efficiency improvement of the current industrial design of the set of worm gears used in a soot blower. The analytical DOE approach helped identify that the number of worm wheel teeth (Z2) and gear module (m) are the two most significant factors affecting performance. Accordingly, based on the improved design, the final efficiency increased from 68.8% to 74.6% (∼8.5% increment), resulting in lower power consumption during industrial application.

Correlations between the optical phase modulation and the optical frequency and phase shifts in ultrasound-modulated optical tomography

In ultrasound-modulated optical tomography, ultrasound causes the phase of incident light to vary periodically with ultrasound. The periodic variation in phase is known as phase modulation. The phase modulation causes the modulated light intensity to vary periodically with the ultrasound, which is called ultrasonic modulation of light. As is well known, incident light is shifted in frequency and phase by ultrasound in acousto-optic effect, and the tomography is based on the effect. However, the correlations between the phase modulation and the frequency and phase shifts in the ultrasonic modulation of light have been ignored. In this paper, the correlations are investigated theoretically and experimentally in detail. Studies reveal that the modulated light is phase-modulated by the frequency and phase shifts, and the frequency shift is the fundamental cause for the ultrasonic modulation of light. Studies show that the frequency shift, rather than the phase shift, causes the modulated light intensity to vary periodically with the ultrasound. Additionally, the modulated light intensity signal is composed of cosine signals with frequencies Ω, 2Ω, 3Ω, etc, and the amplitude of the cosine signals depends on the amplitude of the phase modulation. Then, the modulated light intensity signal contains relatively more cosine signals with high frequency as the amplitude of the phase modulation increases. At last, for the ultrasound with lower power, the amplitude ratio of cosine signals with frequencies of 2Ω and Ω increases as the scattering coefficient of turbid media increases. Studies find that both the frequency-shifted light and the amplitude ratio can be used to image turbid media.

Comparison between platelets to lymphocytes ratio, procalcitonin serum level, and SOFA score for outcome prediction in patients with sepsis

ABSTRACT Background Sepsis is a fatal condition with high treatment costs, early identification of sepsis is mandatory to avoid lethal complications. The objective of this study was to compare the predictive capabilities of platelets to lymphocytes ratio (PLR) and procalcitonin (PCT) in determining the outcome of sepsis. Methods This study was a prospective cross-sectional study and fifty-four individuals diagnosed with sepsis were involved. The participants were between the ages of twenty-one and sixty-five and had been admitted to ICU for more than twenty-four hours. The measurement of whole blood count and PCT serum levels was conducted at time of diagnosis, as well as on days three, seven, and fourteen following the onset of sepsis while SOFA score was conducted at time of admission. Results There was important elevation in platelet to lymphocytes ratio value and PCT in non survivors group compared to survivors group at day one, three, and seven of diagnosis of sepsis (p value ≤ 0.05), and day fourteen there were no data in non survivors group. The Sequential Organ Failure Assessment (SOFA) score was found to be the most effective in mortality prediction [area under the curve (AUC) = 0.982] second effective was PCT (AUC = 0.977) and PLR was third (AUC = 0.945). Conclusions In adult patients diagnosed with sepsis PLR with cutoff value > 228.89 demonstrates efficacy as a reliable prognostic indicator for predicting outcomes in sepsis. Although PLR may have a lower predictive power compared to PCT and SOFA score, it possesses the advantage of being a readily available and cost-effective technology.

Comparative Analysis of Hybrid Maximum Power Point Tracking Algorithms Using Voltage Scanning and Perturb and Observe Methods for Photovoltaic Systems under Partial Shading Conditions

Partial shading significantly affects the performance of photovoltaic (PV) power systems, rendering traditional maximum power point tracking (MPPT) methods ineffective. This study proposes a novel hybrid MPPT algorithm integrating voltage scanning and modified Perturb and Observe (P&amp;O) techniques to overcome the limitations posed by partial shading. This algorithm has a simple structure and does not require panel information such as the number of panels or voltage due to its voltage scanning feature. To test the proposed algorithm, a grid-connected PV power system with a power of 252.6 kW was created in the MATLAB/Simulink environment. In this power system, six different PS conditions, containing quite challenging situations, were listed in three different scenarios and simulated. The proposed algorithm was compared with the voltage scanning and P&amp;O and voltage scanning and variable-step P&amp;O methods. It was observed that the proposed algorithm has lower power fluctuations compared to the other two traditional methods. Additionally, this algorithm managed to achieve higher efficiency than the other methods in some cases.

High-Speed Electro-Optic Modulators Based on Thin-Film Lithium Niobate.

Electro-optic modulators (EOMs) are pivotal in bridging electrical and optical domains, essential for diverse applications including optical communication, microwave signal processing, sensing, and quantum technologies. However, achieving the trifecta of high-density integration, cost-effectiveness, and superior performance remains challenging within established integrated photonics platforms. Enter thin-film lithium niobate (LN), a recent standout with its inherent electro-optic (EO) efficiency, proven industrial performance, durability, and rapid fabrication advancements. This platform inherits material advantages from traditional bulk LN devices while offering a reduced footprint, wider bandwidths, and lower power requirements. Despite its recent introduction, commercial thin-film LN wafers already rival or surpass established alternatives like silicon and indium phosphide, benefitting from decades of research. In this review, we delve into the foundational principles and technical innovations driving state-of-the-art LN modulator demonstrations, exploring various methodologies, their strengths, and challenges. Furthermore, we outline pathways for further enhancing LN modulators and anticipate exciting prospects for larger-scale LN EO circuits beyond singular components. By elucidating the current landscape and future directions, we highlight the transformative potential of thin-film LN technology in advancing electro-optic modulation and integrated photonics.

Efficient operation of atomic frequency comb optical memory using an optical frequency comb in 167Er3+:Y2SiO5

We demonstrated a highly efficient optical memory operation using an atomic frequency comb (AFC) created from a spectrally flattened optical frequency comb with an isotopically pure 167Er3+:Y2SiO5 crystal under zero magnetic field. Compared with standard AFC creation methods such as pulse train method, our method, called comb transfer method, can create a broadband and high-efficiency AFC at lower power and with less effort. This technique can make a significant improvement in the quality of AFCs in crystals doped with low concentrations of rare-earth ions.

Influence of the Parameters of an Agricultural Biogas Plant on the Amount of Power Generated

Energy from biogas is widely available, inexpensive, and often contributes to waste management, making it one of the most promising renewable energy sources. The main factors influencing this process’ efficiency include the substrates’ chemical composition, temperature, and digester load. This paper presents the possibilities offered by a biogas plant built at a farm specialising in dairy cows. The dependence of the power generated in the micro biogas plant on its technical parameters was analysed in detail. Studies carried out by the authors in an agricultural microgas plant (with an electrical output of 40 kW) have shown that they are designed to maintain continuous energy production, despite changing process parameters such as digester mass level, biogas height, temperature or slurry flow into the digester. However, from the point of view of the amount of electricity generated, changes would have to be made to the design of the biogas plant. Firstly, a more powerful generator would have to be installed to cover the electricity requirements of the equipment installed in the biogas plant so that power close to the rated capacity of the biogas plant is still sent to the grid. Secondly, replacing the two existing agitators of the digestion mass (9 kW each) with more agitators of lower power (e.g., four agitators of 4.5 kW each) would be necessary. These should be programmed so that one of the agitators operates at any given time (the operating time of a given agitator should depend on the composition of the digestate).

КАРУСЕЛЬНАЯ УСТАНОВКА ДЛЯ РЕСУРСНЫХ ИСПЫТАНИЙ НА АБРАЗИВНЫЙ ИЗНОС

When developing new methods to make hardening coatings on the cutting tool surfaces of tilling machines, the main characteristic parameter determining the ability to serve for a long time, resisting external environmental influences and mechanical wear, is wear resistance. At the same time, this parameter should be determined before life tests in the field. Various stands and installations are available for this purpose. Each of them is characterized by their own advantages and disadvantages. Therefore, based on the specific production conditions, new devices are being developed. In this paper, a rotary-table installation of a specific design is developed for life tests of abrasive wear of various parts. A patent is obtained for it. The differences of this installation from existing analogues are the following: 1 – the pressure of the abrasive material layer on the test sample is regulated by deepening the sample into the abrasive medium; 2 - the test sample is under constant influence of the abrasive material by filling it with the required amount of abrasive materials; 3 – higher efficiency of the installation. This is achieved due to lower power consumption in the absence of friction forces between the sample bracket and the abrasive material. Comparative life tests were carried out for two harrow teeth, the original tooth and the hardened one. The harrow teeth were tested on a simplified model of a developed installation. An experimental inverter vibration control unit of Kazan Federal University was used for treatment. Hardening was performed with a multi-rod electrode at an arc current of 60A. The frequency of the electrode vibration is 100 Hz. Tests show that the service life of hardened harrow teeth when treated by a vibrating arc with a multi-rod electrode is about 5-6 times higher than the service life of factory harrow teeth.

Constrained Tiny Machine Learning for Predicting Gas Concentration with I4.0 Low-cost Sensors

Low-cost gas sensors (LCS) often produce inaccurate measurements due to varying environmental conditions that are not consistent with laboratory settings, leading to inadequate productivity levels compared to high-quality sensors. To address this issue, we propose the use of Machine Learning (ML) to predict accurate concentrations of pollutant gases acquired by LCS integrated into an embedded Internet of Things platform. However, a key challenge is to optimize an accurate ML design under low memory and computation power constraints of microcontrollers (MCUs) while maintaining accurate ML scores. After data analysis and pre-processing, we assess and analyze the performance of five ML algorithms to predict the concentration of pollutants gases from multiple specifications (weather, presence of other gases, etc.). To support the experiments, datasets from three sources are used: (1) VOCSens, (2) Belgian Interregional Environment Agency cell, and (3) Visual-Crossing. Once the best model was optimized and validated, multiple hard constraints were added to the selected ML structure to satisfy material and expert requirements. Trained models were ported to be implemented locally in a MCU after comparing several porting libraries. The assembled code obtained is evaluated based on two metrics: storage memory consumption and inference time, relative to the highest attainable capacities. The improved random forest is the best ML model for the used dataset with an R2 score meeting of 0.72 and Root Means Square Error of 0.0028 ppm. The best generated Tiny-ML model needs 3% of RAM and 98% of Flash storage. The empirical results prove that the developed ML algorithm applied to LCS provides high accuracy to predict pollutant gases. This algorithm can also be used to adjust the LCS systems to provide calibrated data in real time, even if the platform being used is not particularly advanced or powerful.