Step Pulse Research Articles

Correlation between body fat percentage and aerobic capacity in various athletes

Introduction: The Body Fat Percentage is an indicator of the Body's fitness level and its effects on VO2max and thus the cardiovascular status of the athletes. Physical exercise can help to improve a healthy life interestingly. Aims: This study aims to understand the relationship between Body Fat Percentage and Aerobic Capacity of different athletes. Methods: A total of 150 athletes were randomly selected as the subjects for the present study. In the present study VO2max was measured by Step test in millimeters of oxygen per kilogram of body weight per minute (ml.kg-1.min-1) and Fat percentage was measured by Skinfold Calliper in Millimeters (mm). The collected data were inferential statistics and an independent t-test was applied to check the level of significance. The significance level was set at p < .05. Descriptive and for the relationship appropriate multiple relation statistical tools will be used for the analysis of gathering data. Results: In between fat percentage and Step Test Pulse rate (b/min) coefficient of correlation (r = .441) and level of significance (p = .00) indicated statistical significance with a small positive correlation. At the time relationship between fat percentage and VO2max (ml/kg/min) (r = -.450) and level of significance (p = .00) indicated a statistically significant and medium negative correlation. Conclusion: The relationship between body fat percentage variables and VO2max was statistically significant and indicated a negative correlation but step pulse rate and fat percentage were statistically significant with a small positive correlation.

Insights into lithium plating characteristics enable plating-free heating strategy for bidirectional pulse utilizing a refined physics-based model

Bidirectional pulse heating, known for its fast heating rate and good consistency, is a promising preheating solution for addressing the dilemma of poor performance of lithium-ion batteries (LIBs) at low temperatures. But applying this method to batteries, particularly at high state-of-charges (SOCs), can increase the risk of lithium plating, which in turn raises the potential for thermal runaway. Here, we introduce a refined physics-based model to explore, for the first time, the lithium plating behavior during the bidirectional pulse heating process. Further, we propose a stepped rate pulse strategy based on the lithium precipitation temperature boundary, designed to rapidly warm batteries without inducing lithium plating. Our findings reveal that both capacity loss and the onset temperature for lithium plating increase with higher SOCs and pulse rates. Moreover, due to the uneven temperature distribution, the lithium plating current at the cell periphery is larger compared to that inside the cell, and the outmost cell experiences a more severe capacity loss than the internal cell in a module. The plating-free heating rate varies at different SOC levels and exhibits a 1.5 times improvement as the SOC decreases from 0.5 to 0.2. This study contributes to an enhanced comprehension of lithium plating characteristics and offers invaluable insights into the design of efficient and safe pulse heating strategies.

Electrically smoothing gain-switched optical pulses from a semiconductor laser diode.

The typical optical pulse from a gain-switched semiconductor laser diode (LD) usually consists of a first-spike (FS) component and a quasi-steady-state (QSS) lasing component. For the stability and accuracy in some specific applications of sensing and detection, it is necessary to achieve a smooth QSS component without the FS component (regarded as spike noise). This Letter reports a technique to smooth the optical pulse shape from gain-switched LDs via stepped electric pulse, which can eliminate or suppress the FS component effectively, without any postprocessing. Rate-equation calculations well reproduced the major features of the experimental results and revealed that the pre-pump of the stepped electrical pulse plays a crucial role by adjusting the accumulated carrier density to be close to threshold before lasing in the LD, which suppresses the FS generation during the main pump injects and allows LD transit more rapidly into the QSS mode. The stepped electrical pulse pump provides a feasible and convenient method to smooth the optical pulse shape of gain-switched semiconductor LDs for various applications.

Aptamer-Triggered Nucleic Acid Amplification Strategy for the Electrochemiluminescence Detection of Perfluorooctanoic Acid.

Per- and polyfluoroalkyl substances (PFASs) are a class of persistent micropollutants. Due to their chemical stability and bioaccumulation, concentrations of PFASs in environmental media, even at ultratrace levels, pose significant environmental and health risks. However, currently reported detection methods lack an effective signal amplification strategy, and the detection sensitivity is limited, which can not meet the requirements of ultratrace detection. Herein, a groundbreaking aptamer-recognition-driven nucleic acid strategy was developed to significantly amplify the detection signal of perfluorooctanoic acid (PFOA). Furthermore, step pulse (SP) was used instead of cyclic voltammetry (CV) as an electrochemical excitation method to modulate the low electrochemiluminescence (ECL) triggering potential of poly [9,9-bis (3'-(N, N-dimethylamino) propyl) -2,7-fluorene]-alt-2,7-(9,9-dioctylfluorene)] (PFN) nanoparticles (NPs) so that a strong signal of +0.80 V was emitted without any exogenous coreactants. PFN NPs coupled rolling circle amplification-assisted PAM-free CRISPR/Cas12a system to construct an ultrasensitive ECL aptasensor for PFOA detection and the limit of detection was as low as 1.97 × 10-15 M. This ECL system integrated the advantages of no exogenous coreactants, low trigger potential, and nucleic acid amplification strategy and provided an ultrasensitive method for monitoring trace PFOA in the real water sample.

Step Pulse-Mediated Low-Triggering Potential Electrochemiluminescence of Polyfluorene Nanoparticles for Bioassay.

When the electrochemiluminescence (ECL) reaction occurs at a triggering potential beyond ±1.0 V, the interference from the adverse oxidation-reduction reaction cannot be ignored. However, currently reported anode ECL usually occurs above +1.0 V. This study innovatively developed a convenient and simple step pulse (SP) method to modulate the low ECL triggering potential of poly [(9,9-dioctyl-fluorenyl-2,7-diacyl)-alt-co-(9-hexyl-3,6-carbazole)] (PFA) nanoparticles (NPs). Compared to cyclic voltammetry with a triggering potential exceeding +1.25 V for PFA NPs, SP scanning enabled PFA NPs to exhibit a strong and stable ECL emission with a triggering potential as low as +0.75 V and tripropylamine (TPrA) as a coreactant. PFA NPs coupled an efficient aptameric recognition-driven cascade nucleic acid amplification strategy to construct a sensitive biosensing platform for measuring phosphorylated Tau (p-Tau) protein as an Alzheimer's disease biomarker. p-Tau could release the secondary target (ST) chain through the aptameric recognition reaction with the aptamer, and the released ST could further trigger cascade catalytic hairpin assembly (CHA) and rolling circle amplification (RCA) at the PFA NP-modified electrode, producing a large number of long chains. The large amount of G-quadruplex/hemin formed by long chains and hemin will consume the ECL quencher H2O2 added in detection solution, thereby restoring the ECL signal and enabling the low potential quantitative analysis of p-Tau with a limit of detection of 4.15 fg/mL. SP technique provides a new way to reduce ECL triggering potential, and PFA NPs create a promising low-triggering potential ECL-sensing platform for bioanalysis.

Coevolution of the holocene coastal barrier and lagoon terraces and their implications on the record of relative sea-level change in southernmost Brazil

This paper presents the coeval history of a sandy coastal barrier and four lagoon margins located in the Rio Grande do Sul State, southernmost Brazil. To achieve this objective we compared the Holocene relative sea-level changes recorded along a regressive coastal barrier with the register of base-level fluctuations preserved in the lagoon terraces. We used geomorphology, geochronology, geophysics (GPR), and high-resolution sequence stratigraphy to evaluate changes on the relative sea- and base-level recorded in the barrier and lagoon terraces, respectively. The record of the relative sea-level fall (forced regression) began at ∼4 ka in the coastal barrier and around 3.4 ka in the lagoon system. Maximum altitudes of the eolian/beach deposits boundary are similar on both barrier and lagoon settings, hence pointing out that relative sea-level controlled lagoon base-level. The forced regression stage is more accurately preserved in the margin of the lagoons than in the coastal barrier. Along the former, four progradational sets related to stepped terraces record pulses of relative sea-level fall at 3.4, 1.4, 0.35, and 0.27 ka. The pulses that took place from 1.4 ka onwards are recorded as low terraces in the lagoon but appear in the coastal barrier as an acceleration in the rate of the relative sea-level fall. Each relative sea-level fall is supposed to have liberated beach sands for eolian reworking during the subsequent stillstand phase and allowed the development of transgressive dunes. Therefore, we conclude that lagoonal terraces vertical displacements are adequate proxies for high-resolution analysis of relative sea-level changes.

Random subspace ensemble-based detection of false data injection attacks in automatic generation control systems

Automatic Generation Control (AGC) systems in smart grids are increasingly vulnerable to cyber-attacks, particularly False Data Injection (FDI) attacks, due to their reliance on information and communication technologies. These vulnerabilities pose significant threats to the reliable operation of power systems. To address this challenge, this research paper introduces the machine learning (ML) based cyberattack detection technique designed to identify FDI attacks with the highest accuracy proficiently. The study involves a comprehensive analysis of three features: the original discrete signal feature, the cycle-to-cycle-based feature, and the sample-to-sample-based feature. These features are utilized for detecting FDI attacks and distinguishing them from normal load variations. The research meticulously collects data by simulating diverse FDI attacks, including step attacks, pulse attacks, random attacks, and normal load variation cases on an AGC power system. Four ML classifiers are selected and compared for the classification task. The simulation results reveal that the sample-to-sample-based feature proves highly effective in distinguishing FDI attacks compared to the original signal and cycle-to-cycle-based features. Notably, the results indicate that the random subspace ensemble (RaSE) classifier, utilizing sample-to-sample-based features, effectively identifies and classifies all normal and FDI attacks. This research provides valuable insights into the potential of ML techniques for enhancing FDI attack detection in the AGC of power systems. It provides a potential pathway for overcoming the limitations associated with traditional model-based FDI detection methods.

First demonstration of 2T0C-FeDRAM: a-ITZO FET and double gate a-ITZO/a-IGZO FeFET with a record-long multibit retention time of >4-bit and >2000 s.

Conventional DRAM, consisting of one transistor and one capacitor (1T1C), requires periodic data refresh processes due to its limited retention time and data-destructive read operation. Here, we propose and demonstrate a novel 3D-DRAM memory scheme available with a single transistor and a single ferroelectric field-effect transistor (FeFET) DRAM (2T0C-FeDRAM), which offers extended retention time and non-destructive read operation. This architecture uses a back-end-of-line (BEOL)-compatible amorphous oxide semiconductor (AOS) that is suitable for increasing DRAM cell density. Notably, the device structures of a double gate a-ITZO/a-IGZO FeFET, used for data storage and reading, are engineered to achieve an enlarged memory window (MW) of 1.5 V and a prolonged retention time of 104 s. This is accomplished by a double gate and an a-ITZO/a-IGZO heterostructure channel to enable efficient polarization control in hafnium-zirconium oxide (HZO) layers. We present successful program/erase operations of the double gate a-ITZO/a-IGZO FeFET through incremental step pulse programming (ISPP), demonstrating multi-level states with remarkable retention characteristics. Most importantly, we perform 2T0C-FeDRAM operations by electrically connecting the double gate a-ITZO/a-IGZO FeFET and the a-ITZO FET. Leveraging the impressive performance of the double gate a-ITZO/a-IGZO FeFET technology, we have effectively showcased an exceptionally record-long retention time exceeding 2000 s and 4-bit multi-level states, positioning it as a robust contender among emerging memory solutions in the era of artificial intelligence.

Machine Learning for Accurate Energy Analysis of Double Beta Decay Events

Point-contact germanium detectors are used to detect and analyze particles and their decay processes. This research focuses on the search for a phenomenon known as neutrinoless double beta decay, where two neutrons within a nucleus transform into two protons, emitting electrons in the process. Unlike standard double beta decay, no neutrinos are emitted, suggesting that the neutrino may act as its own antiparticle, effectively canceling itself out. Detecting this process would provide crucial insights into the nature of neutrino mass. During such an event, the detector registers a spike in energy due to the emitted electrons, producing a step-like pulse in the output channels. The energy of the event is determined by the difference in charge between the ‘top’ and ‘bottom’ steps of the pulse. However, accurately determining the energy is complicated by the presence of a resistor in the detector, which causes the top step to decay exponentially back to a baseline in preparation for the next event. This decay makes it challenging to determine the true energy of the pulse. My work this summer focused on developing machine learning models to reconstruct the step-like nature of pulses from their decayed versions recorded by the detector. This involved constructing deep neural networks trained on inputs (decayed pulses) and corresponding targets (the original step pulses) to learn to accurately reconstruct the target from the input. Initially, the networks were trained on simulated detector data. Once proficient in reconstruction, electronic noise was added to the input pulses to simulate real-world conditions, under which the models were trained to remove both electronic noise and decay. The models were trained to handle pulses with varying decay constants to improve their generalization ability. These neural networks can now be applied to real detector data for accurate energy analysis of double beta decay events.

Formation of high areal density core using an efficient and robust implosion method for fast ignition

Abstract A new fuel compression method for a fast ignition scheme is discussed. To form a high areal density fuel plasma for the ignition condition, homogenous isentropic compression (HIC) with solid spherical target is effective. We improve a multi-step pulse shape method that uses progressive shockwaves and reflected shockwaves for the compression, where a precisely controlled step-pulse laser drives the shockwaves to compress the fuel and suppress entropy increase. Another advantage of this approach is the relatively smooth high dense fuel is distributed at maximum compression time, compared to our previous design based on Kidder’s HIC method. In addition, we insert a power dip as a preconditioning before the last pulse step to reduce the electron and ion temperature near critical density. As a result, an optimum implosion is designed using 245 kJ of implosion laser energy to meet the ignition condition.

Electro-assisted photothermal synergy for removal of volatile organic compounds over Au single atoms anchored TiO2 nanotubes

Gas-phase photoelectrocatalysis (GPEC) systems for treating gas pollution may lead to a Joule-heat effect and form photothermal synergy under an external bias voltage. However, such a synergistic effect and mechanism remain unclear. Herein, a electro-assisted photothermal synergistic removal of VOCs by defective TiO2 nanotube array decorated with atomically dispersed Au species was chosen as a prototypical illustration. By introducing single Au atoms, the carrier concentration and mobility of the catalytically active layer, i.e., TiO2 nanotube arrays anchored with Au single atoms, were substantially increased to the semi-metal level through an electrochemical reduction step and square-wave pulse method for anchoring single atoms. This not only contributes to the photogenerated carrier separation at low external bias but also significantly enhances the Joule heating effect on the catalyst surface. As a result, the catalyst used exhibited an excellent electro-assisted photothermal synergistic effect and outstanding efficiency in toluene removal in the designed tubular reactor. SynopsisA novel electro-assisted photothermal synergy system was constructed, which combines the advantages of gas-phase photoelectrocatalysis and electrothermal catalysis to remove VOCs with high efficiency and low energy consumption.

Instrumental and theoretical advancements in pulsed elution-LC × LC: Investigation of pulse parameters and application to wastewater effluent

Due to the decoupling of the first (1D) and second (2D) dimension in pulsed elution-LC × LC (PE-LC × LC), method development is more flexible and straightforward compared to fast comprehensive LC × LC where the dependencies of key parameters between the two dimensions limits its flexibility. In this study we present a method for pulse generation, which is based on a switching valve alternating between one pump that delivers the gradient and a second pump that delivers low eluotrophic strength for the pause state. Consequently, the dwell volume of the system was circumvented and 7.5, and 3.75 times shorter pulse widths could be generated at flow rates of 0.2, and 0.4 mL/min with satisfactory accuracies between programmed and observed mobile phase composition (relative deviation of 6.0 %). We investigated how key parameters including pulse width and step height, 2D gradient time and flow rate affected the peak capacity in PE-LC × LC. The conditions yielding the highest peak capacity for the PE-LC × LC- high-resolution mass spectrometry (HRMS) system were applied to a wastewater effluent sample. The results were compared to a one dimensional (1D)-LC-HRMS chromatogram. The peak capacity increased with a factor 34 from 112 for the 1D-LC run to 3770 for PE-LC × LC-HRMS after correction for undersampling. The analysis time for PE-LC × LC-HRMS was 12.1 h compared to 67.5 min for the 1D-LC-HRMS run. The purity of the mass spectra improved for PE-LC × LC-HRMS by a factor 2.6 (p-value 3.3 × 10−6) and 2.0 (p-value 2.5 × 10−3) for the low and high collision energy trace compared to the 1D-LC-HRMS analysis. Furthermore, the signal-to-noise ratio (S/N) was 4.2 times higher (range: 0.06–56.7, p-value 3.8 × 10−2) compared to the 1D-LC-HRMS separation based on 42 identified compounds. The improvements in S/N were explained by the lower peak volume obtained in the PE-LC × LC-HRMS.

Unique electrophysiological property of a novel Nav1.7, Nav1.8, and Nav1.9 sodium channel blocker, ANP-230

Voltage-gated sodium channel subtypes, Nav1.7, Nav1.8, and Nav1.9 are predominantly expressed in peripheral sensory neurons. Recent genetic studies have revealed that they are involved in pathological pain processing and that the blockade of Nav1.7, Nav1.8, or Nav1.9 will become a promising pharmacotherapy especially for neuropathic pain. A growing number of drug discovery programs have targeted either of the subtypes to obtain a selective inhibitor which can provide pain relief without affecting the cardiovascular and central nervous systems, though none of them has been approved yet. Here we describe the in vitro characteristics of ANP-230, a novel sodium channel blocker under clinical development. Surprisingly, ANP-230 was shown to block three pain-related subtypes, human Nav1.7, Nav1.8, and Nav1.9 with similar potency, but had only low inhibitory activity to human cardiac Nav1.5 channel and rat central Nav channels. The voltage clamp experiments using different step pulse protocols revealed that ANP-230 had a “tonic block” mode of action without state- and use-dependency. In addition, ANP-230 caused a depolarizing shift of the activation curve and decelerated gating kinetics in human Nav1.7-stably expressing cells. The depolarizing shift of activation curve was commonly observed in human Nav1.8-stably expressing cells as well as rat dorsal root ganglion neurons. These data suggested a quite unique mechanism of Nav channel inhibition by ANP-230. Finally, ANP-230 reduced excitability of rat dorsal root ganglion neurons in a concentration dependent manner. Collectively, these promising results indicate that ANP-230 could be a potent drug for neuropathic pain.

Study of Hydrodynamics and Residence Time Distribution in a Trickle Bed Reactor

This study focuses on investigating the hydrodynamics using computational fluid dynamics (CFD) simulation and residence time distribution (RTD) within a trickle bed reactor (TBR). CFD simulation was performed on a packed column filled with structured packing of glass beads, while the experiments for RTD studies were conducted in a TBR filled with random packing of Raschig rings. The geometry of TBR and size of packing during CFD simulation was kept close to that of the experimental setup. CFD simulation results were obtained which predicted the flow of fluid through the TBR at different vertical planes along the column. The fluctuations of liquid velocity at various positions inside the reactor were predicted by the CFD model. RTD studies were performed for both pulse input and step input using a non-reactive tracer such as sodium hydroxide. The flowrate of water was varied from 0.6 LPH to 6 LPH for pulse input, while for step input the ratio of water to tracer flowrates was kept at 1:1, 1:2 and 2:1. This study allows us to understand how hydrodynamics and residence time distribution may have an effect on the performance of TBR.

Reliability Improvement in Vertical NAND Flash Cells Using Adaptive Incremental Step Pulse Programming (A-ISPP) and Incremental Step Pulse Erasing (ISPE)

Reliability Improvement in Vertical NAND Flash Cells Using Adaptive Incremental Step Pulse Programming (A-ISPP) and Incremental Step Pulse Erasing (ISPE)

An Inductive Method for Comprehensive Estimation of Temperature-Dependent Electrical and Thermal Properties of Conductive Ferromagnetic Materials

Reliable information about the properties of the processed materials has a significant impact on the effects of their processing. In induction heating processes, this also applies to information about the influence of temperature T on these properties. These are both thermal and electro-magnetic properties. Based on previous studies, a comprehensive experimental method is presented for estimating the temperature characteristics of thermal diffusivity, volumetric heat capacity and resistivity on one measurement station, with particular attention to ferromagnetic materials. The estimation process is carried out on an induction heating stand using forcing signals from an inverter generator. In a computer-controlled cycle that changes the base temperature level, basic measurements of thermal and electrical properties are carried out on a material sample in the form of a cylindrical disk. They are the results of the analysis of the temperature and electromagnetic responses of a material sample to short- and long-term step pulses of a sinusoidal excitation signal with a frequency of approximately 40 kHz. The presented estimation method can be treated as a final method or a preliminary procedure for radically narrowing the variability in decision variables inthe optimization process of simultaneous determination of the sought material characteristics.

Proportional-retarded control of a quasi-zero-stiffness vibration isolator

This paper explores the control design and performance analysis of an active quasi-zero-stiffness vibration isolator utilizing the proportional-retarded (PR) control architecture. The PR architecture replaces the conventional “derivative” term in the proportional-derivative (or displacement-velocity) controller with the novel “retarded (time-delayed)” term, which is a new and effective way of active vibration suppression. Comprehensive gain-delay conjoint regulation strategies are developed for the strengthened isolation performance. For impact excitations, a complete stability analysis is conducted near the equilibrium position. Furthermore, a parameterized dominant pole placement algorithm is proposed to optimize the transient response of the PR-actuated isolator. Focusing on the rectangular pulse and long-duration step impacts, the algorithm adjusts the dominant poles to optimize the transient performance metrics, including the maximum displacement overshoot, steady-state displacement overshoot, and settling time. Regarding harmonic excitations, the delay-coupled effect is scrutinized for better low-frequency isolation performance, including the resonance frequency, nonlinear steady-state amplitude, multiple steady-state bands and nonlinearity elimination, equivalent active damping and stiffness, and absolute displacement transmissibility. In the case of random excitations, we demonstrate the superiority of the PR structure over the passive system.

Transient analysis of laminated plates in thermal environment

Transient displacement of laminated plates under combined load based on Mantari' s displacement field are investigated. The solution is implemented under transient mechanical load (sinusoidal, step and triangular sinusoidal distributed pressures pulse) and thermal buckling for plates with different layer orientation and thickness ratio. Equations of motion based on higher-order theory are derived through Hamilton' s principle, and solved using Naviertype solution for simply supported laminated plates. The results are presented for many effective parameters such as the number of laminate and orientation on the dynamic response of plates. Results show the validity of this displacement field in studying response of laminated thick and thin plates under varied transient loading and design parameters.

Diverse thermal desorption combined with self-aspirating corona discharge ionization for direct mass spectrometry analysis of complex samples.

The thermal desorption (TD) technique is widely employed in modern mass spectrometry to facilitate the detection of non-volatile analytes. In this study, we developed a compact TD device based on a small resistance wire and coupled it with a self-aspirating corona discharge ionization (CDI) source to conduct direct MS analysis of various liquid and solid samples. Due to its small size and low heat capacity, the temperature of the TD module can be flexibly and rapidly modulated by controlling the power sequence. Multiple heating modes, including pulse heating (PH), isothermal heating, and step heating (SH), are realized and characterized, and then applied for the detection of different real samples. In particular, the PH mode is suitable for the simultaneous detection of multiple components in samples with relatively simple matrices, while the SH mode is capable of component separation. In addition, the sensitivity and quantitative capability of the TD-CDI system for DEP solutions were tested, showing acceptable stability with a relative standard deviation of about 6.7% and a detection limit of 0.088 ng. Overall, the developed TD-CDI system provides a simple, convenient, and versatile tool for direct mass spectrometry analysis of real samples.

Precise weight tuning in quantum dot-based resistive-switching memory for neuromorphic systems.

In this study, nonvolatile bipolar resistive switching and synaptic emulation behaviors are performed in an InGaP quantum dots (QDs)/HfO2-based memristor device. First, the physical and chemical properties of InGaP QDs are investigated by high-resolution transmission electron microscopy and spectrophotometric analysis. Through comparative experiments, it is proven that the HfO2 layer improves the variations in resistive switching characteristics. Additionally, the Al/QDs/HfO2/ITO device exhibits reversible switching performances with excellent data retention. Fast switching speeds in the order of nanoseconds were confirmed, which could be explained by trapping/detrapping and quantum tunneling effects by the trap provided by nanoscale InGaP QDs. In addition, the operating voltage is decreased when the device is exposed to ultraviolet light for low-power switching. Biological synapse features such as spike-timing-dependent plasticity are emulated for neuromorphic systems. Finally, the incremental step pulse using proven algorithm method enabled the implementation of four-bit states (16 states), markedly enhancing the inference precision of neuromorphic systems.