Timing Control Research Articles

Trigger transceiver and timing control system for ADITYA-U tokamak

The trigger transceiver and timing control system described in this study is developed to generate multiple triggers with varying delays to synchronize various subsystems with plasma discharges in the ADITYA Upgrade (ADITYA-U) tokamak (Ghosh et al., 2016) [1]. The Toroidal Field Power Supply (TFPS) is a fundamental component for each plasma discharge in the ADITYA-U, which generates a master trigger pulse for the particular discharge. The rise time of Toroidal Field Power Supply is 2 s and the loop voltage which is required to initiate the plasma discharge begins at 2.4 s after the master trigger. So the loop voltage is time-stamped at t = 0 and the master trigger from TFPS is time-stamped at t = −2.4 s and considered as a pre-trigger. Apart from this master trigger at t = −2.4 s, two more pre-trigger pulses, one at ∼ −40 ms and another at ∼ −4 ms, prior to the initiation of loop voltage trigger are generated by the power supply. These pre-trigger pulses generated by TFPS constitute the backbone of the entire discharge timing sequence, and they operate/control/initiate numerous ADITYA-U subsystems such as the gas puffing system, data acquisition system, radio frequency pre-ionization and heating system, plasma position control, and so on. So a suitable trigger generator system was needed to be developed in which three pre-trigger pulses (time stamped @ −2.4 s, −40 ms, and −4 ms prior to the loop voltage trigger) arriving from the TFPS may be selected and altered based on the experimental needs. To cater these requirements in ADITYA-U, a trigger transceiver and timing control system has been developed. The system has been successfully operated over ∼6000 discharges of ADITYA-U and functioned satisfactorily in all discharges in daily experiments with no failures. This study will discuss the detailed design elements and implementation of the Trigger Transceiver and Timing Control System for ADITYA-U plasma operations.

Distributed Localization for UAV–UGV Cooperative Systems Using Information Consensus Filter

In the evolving landscape of autonomous systems, the integration of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) has emerged as a promising solution for improving the localization accuracy and operational efficiency for diverse applications. This study introduces an Information Consensus Filter (ICF)-based decentralized control system for UAVs, incorporating the Control Barrier Function–Control Lyapunov Function (CBF–CLF) strategy aimed at enhancing operational safety and efficiency. At the core of our approach lies an ICF-based decentralized control algorithm that allows UAVs to autonomously adjust their flight controls in real time based on inter-UAV communication. This facilitates cohesive movement operation, significantly improving the system resilience and adaptability. Meanwhile, the UAV is equipped with a visual recognition system designed for tracking and locating the UGV. According to the experiments proposed in the paper, the precision of this visual recognition system correlates significantly with the operational distance. The proposed CBF–CLF strategy dynamically adjusts the control inputs to maintain safe distances between the UAV and UGV, thereby enhancing the accuracy of the visual system. The effectiveness and robustness of the proposed system are demonstrated through extensive simulations and experiments, highlighting its potential for widespread application in UAV operational domains.

Role of the Cerebellum in the Construction of Functional and Geometrical Spaces.

The perceptual and motor systems appear to have a set of movement primitives that exhibit certain geometric and kinematic invariances. Complex patterns and mental representations can be produced by (re)combining some simple motor elements in various ways using basic operations, transformations, and respecting a set of laws referred to as kinematic laws of motion. For example, point-to-point hand movements are characterized by straight hand paths with single-peaked-bell-shaped velocity profiles, whereas hand speed profiles for curved trajectories are often irregular and more variable, with speed valleys and inflections extrema occurring at the peak curvature. Curvature and speed are generically related by the 2/3 power law. Mathematically, such laws can be deduced from a combination of Euclidean, affine, and equi-affine geometries, whose neural correlates have been partially detected in various brain areas including the cerebellum and the basal ganglia. The cerebellum has been found to play an important role in the control of coordination, balance, posture, and timing over the past years. It is also assumed that the cerebellum computes forward internal models in relationship with specific cortical and subcortical brain regions but its motor relationship with the perceptual space is unclear. A renewed interest in the geometrical and spatial role of the cerebellum may enable a better understanding of its specific contribution to the action-perception loop and behavior's adaptation. In this sense, we complete this overview with an innovative theoretical framework that describes a possible implementation and selection by the cerebellum of geometries adhering to different mathematical laws.

Expression of immune-related genes and breast cancer recurrence in women with ductal carcinoma in situ

Background and aimDuctal carcinoma in situ (DCIS) is a non-obligate precursor of invasive breast cancer with highly variable clinical behavior, but risk stratification is still challenging. We sought to identify immune-related gene expression signatures of pure DCIS associated with different risks of breast cancer recurrence. MethodsA retrospective nested case-control study of 143 pure DCIS was performed including 70 women with subsequent ipsilateral breast event (IBE, in situ or invasive; cases) and 73 DCIS women with no IBE and matched for age, tumor size, treatment, hormone receptors/HER2 status, and follow-up time (controls). RNA was extracted from DCIS samples and subjected to next-generation sequencing gene expression analysis of 395 immune-related genes. Correlations between DCIS immune-related gene expression and IBE were analyzed using weighted Cox regression for nested case-control data. ResultsEight immune-related genes were differentially expressed between cases and controls. MAGEA10 expression (present vs. absent) and high expression levels of IFNA17 and CBLB (Q4 vs. Q1) were observed more frequently in DCIS of women with subsequent IBE, mainly invasive (p-valueFDR < 0.05). Conversely, expression of IL3RA1, TAGAP, TNFAIP8, and high expression levels of CCL2 and LRP1 were associated with a lower risk of IBE (p-valueFDR < 0.05). ConclusionThis exploratory analysis of pure DCIS showed significant differences in immune-related gene expression profiles between women with and with no subsequent IBE, particularly as invasive IBE. These results, after additional validation, could improve risk stratification and management of DCIS patients.

An Intelligent Controller of LED Street Light Based on Discrete Devices

To combat global environmental deterioration and energy scarcities, it is crucial to implement energy-saving upgrades for urban road lighting. Comparatively, LEDs have emerged as an advanced and eco-friendly lighting option due to their low energy consumption, excellent performance, high color rendering index, and prolonged lifespan. By incorporating solar cell technology, a smart LED street light controller based on small-scale integrated circuits was developed to enable intelligent control for various lighting needs such as dimming, timing, automatic detection, and sound and light control. Through circuit simulations and experimental outcomes, it has been validated that the controller’s structure and performance parameters align with the design specifications. This design encompasses knowledge from diverse fields, including fundamentals of circuit and electronic technology, photovoltaic cell technology, power electronics, and sensor technology, showcasing robust engineering and practicality. Its utilization in the experimental course for second-year college students majoring in electrical engineering contributes to the grooming of professionals and expands the perspectives of future talents, enriching their application of knowledge and practical innovation capabilities.

Pressure–temperature–time controls on shock vein formation within the Steen River impact structure

ABSTRACTThermodynamic modeling has been applied to determine pressure–temperature–time conditions leading to shock vein formation during the passage of a natural shock wave generated by hypervelocity impact. The approach is novel in considering both shock front and rarefaction pressures, as well as simultaneously forming and cooling the shock veins via two‐dimensional steady‐state conduction. Model results are tested using shock veins developed in granitic rocks that constitute the central uplift of the Steen River impact structure in Canada. Here, two variants of majoritic garnet were generated in different settings: (1) along the margins of shock veins due to pargasite and biotite breakdown (accompanied by maskelynite formation), and (2) within the originally molten shock vein matrix as newly grown crystals. We determine that during shock vein formation, the shock front pressure and wave width at the reconstructed sample location were 18 GPa and 830 m, respectively, with a dwell time of 160 ms. Intra‐vein melting at 2150°C was attained within 1 μs. Melt cooled to the solidus in 150 ms following shock front passage. Majoritic garnet formation was facilitated by the high temperatures realized within the veins as a result of frictional melting that accompanied shock loading. The calculated pressure–temperature–time (P–T–t) path provides constraints on the formation conditions of majoritic garnet at Steen River. The model results independently support previously determined P–T conditions based on mineral stability fields. The vein margin garnets (35–39 mole% majorite) and maskelynite formed first under higher P–T conditions for a longer duration (36 ms). The matrix garnets (11–22 mole% majorite) crystallized from melt under lower P–T conditions and for a shorter duration (22 ms). Our results indicate that shock pressure alone should not be used as a basis for shock classification. Instead, the interplay between pressure and temperature with time and the duration of shock immersion (dwell) must be considered.

Rapid and sensitive visual detection of avian leukosis virus by reverse transcription loop-mediated isothermal amplification combined with a lateral flow immunochromatographic strip assay.

Considering that avian leukosis virus (ALV) infection has inflicted massive economic losses on the poultry breeding industry in most countries, its early diagnosis remains an important measure for timely treatment and control of the disease, for which a rapid and sensitive point-of-care test is required. We established a user-friendly, economical, and rapid visualization method for ALV amplification products based on reverse transcription loop-mediated isothermal amplification (RT-LAMP) combined with an immunochromatographic strip in a lateral flow device (LFD). Using the ALVp27 gene as the target, five RT-LAMP primers and one fluorescein-isothiocyanate-labeled probe were designed. After 60 min of RT-LAMP amplification at 64 °C, the products could be visualized directly using the LFD. The detection limit of this assay for ALV detection was 102 RNA copies/μL, and the sensitivity was 100 times that of reverse transcription polymerase chain reaction (RT-PCR), showing high specificity and sensitivity. To verify the clinical practicality of this assay for detecting ALV, the gold standard RT-PCR method was used for comparison, and consistent results were obtained with both assays. Thus, the assay described here can be used for rapid detection of ALV in resource-limited environments.

Tailoring the Microstructure using Quenching and Partitioning Processing in a Commercial Mn-Si-Cr Spring Steel to Improve Tensile Properties

This study explores a novel approach to quenching and partitioning (Q&P) heat treatment applied to AISI 9260 spring steel, comprising Fe-0.65C-1.58Mn-1.05Si-0.41Cr (wt.%). Our research focuses on balancing strength and ductility through optimized Q&P pathways, leading to a diverse microstructure that includes martensite, bainite, carbide, and retained austenite. Advanced X-ray diffraction and scanning electron microscopy techniques were employed to analyze the complexities of this microstructure. A key aspect of this study is the precise control of partitioning temperature and time, crucial for modulating lattice distortion and dislocation density within martensitic and bainitic structures. Optimal partitioning temperature promotes carbon distribution into austenite, tempering lattice distortions, and dislocation densities. Concurrently, carbide precipitation and segregation contribute to the refinement of the bainite phase. The sample quenched at 125 °C and partitioned at 350 °C (Q&P-125/350) demonstrates notable mechanical properties: a yield strength of 950 ± 15 MPa, an ultimate tensile strength of 1710 ± 15 MPa, and an elongation of approximately 9.7%. These results are partly attributed to the effect of silicon in preventing cementite coarsening and the effective distribution of carbide. Our findings highlight the potential of Q&P heat treatment in developing tailored microstructures with enhanced mechanical properties in steel, without relying on costly alloying elements. This approach presents new avenues for the design and application of high-performance materials.

Axial behavior of slugging flow in a gas–solid CFB riser using distributed ECVT with 64 electrodes

Understanding particle flow characteristics within circulating fluidized bed (CFB) reactors is crucial for enhancing reaction efficiency. To study the flow characteristics of Geldart D particles with a mean diameter of 3.0 mm and a bulk density of 1640 kg/m3 in a CFB riser with a height of 1090 mm, a 64-electrode electrical capacitance volume tomography (ECVT) sensor with a height-to-diameter ratio (HDR) of 12 is arranged on the CFB riser with an inner diameter of 59 mm. A distributed ECVT architecture under the control of a timing controller is formed to synchronously acquire capacitance data of two 32-electrode ECVT data acquisition systems. So, the three-dimensional axial flow imaging of a CFB riser with a branch pipe is realized with a 14-plane ECVT sensor. The flow rules of slugging flow in the CFB riser under gas velocities of 3.5 m/s, 2.86 m/s, and 2.5 m/s are analyzed from the continuous ECVT images, especially the process of rupture, decomposition, and collapse of particle slugs. The flow parameter characteristics, such as the solid fraction in the riser, the slug rising tail velocity, the slug length, and the spectral characteristics, are investigated. The experimental results demonstrate that the proposed distributed ECVT can effectively realize the collaborative operation of multiple ECVT data acquisition systems and then splice sub-ECT images to achieve complex space imaging.

On the regional-scale variability in flow duration curves in Peninsular India

Abstract. Peninsular India is a unique region with major mountain ranges that govern regional atmospheric circulation and precipitation variability, the monsoons, and regional geology at range of timescales and process scales. However, the landscape and climatic feature controls on streamflow variability at a regional scale using flow duration curves (FDCs) – compact descriptions of streamflow variability that offer a window into the multiple, interacting processes that contribute to streamflow variability – have received little attention. This study examines the suitability of the partitioning of (1) an annual streamflow FDC into seasonal FDCs and (2) a total streamflow FDC into fast- and slow-flow FDCs to unravel the process controls on FDCs at a regional scale, with application to low-gradient rivers flowing east from the Western Ghats in Peninsular India. The results indicate that bimodal rainfall seasonality and subsurface gradients explain the higher contribution of slow flow to total flow across the north–south gradient of the region. Shapes of fast and slow FDCs are controlled by recession parameters, revealing the role of climate seasonality and geological profiles, respectively. Systematic spatial variation across the north–south gradient is observed, highlighting the importance of the coherent functioning of landscape–hydroclimate settings in imparting a distinct signature of streamflow variability. The framework is useful to discover the role of time and process controls on streamflow variability in a region with seasonal hydro-climatology and hydro-geological gradients.

Miniaturized MXene-based electrochemical biosensors for virus detection

The timely control of infectious diseases can prevent the spread of infections and mitigate the significant socio-economic damage witnessed during recent pandemics. Diagnostic methods play a significant role in detecting highly contagious agents, such as viruses, to prevent further transmission. The emergence of advanced point-of-care techniques offers several advantages over conventional approaches for detecting infectious agents. These techniques are highly sensitive, rapid, can be miniaturized, and are cost-effective. Recently, MXene-based 2D nanocomposites have proven beneficial for fabricating electrochemical biosensors due to their suitable electrical, optical, and mechanical properties. This article covers electrochemical biosensors based on MXene nanocomposite for the detection of viruses, along with the associated challenges and future possibilities. Additionally, we highlight various conventional techniques for the detection of infectious agents, discussing their pros and cons. We delve into the challenges faced during the fabrication of MXene-based biosensors and explore future endeavors. It is anticipated that the information presented in this work will pave the way for the development of Point-of-Care (POC) devices capable of sensitive and selective virus detection, enhancing preparedness for ongoing and future pandemics.

Advancements in homogeneous charge compression ignition technology: Efficiency, emissions, and applications in the modern automotive industry

Homogeneous charge compression ignition (HCCI) technology is a novel approach in internal combustion engines that combines the efficiency of gasoline engines with the spontaneous ignition characteristics of diesel engines. HCCI engines offer cleaner emissions, reduced noise, and wider fuel adaptability, overcoming many drawbacks of traditional engines. The paper explores the HCCI combustion process, highlighting its unique features and advantages over spark ignition (SI) and compression ignition (CI) engines. It also discusses innovations in HCCI technology, including its combination with other strategies like spark-controlled compression ignition (SCCI) and low-temperature combustion (LTC) to expand its load range. The challenges of HCCI technology, especially in combustion timing control, are addressed, along with suggestions for future research directions. The application of HCCI technology for energy savings and emission reduction and its impact on the automotive industry are also discussed, citing examples from manufacturers like Volvo, Nissan, and General Motors. The paper concludes by emphasizing the importance of ongoing research, integration with other technologies, and financial support to further advance HCCI technology and its market potential.

Design and process of force-electric fusion for electromagnetic driven Si based MEMS S&A

In order to meet the technical requirements for precise control of the arming time in high-dynamic environments and ammunition safety, this article proposes a silicon-based MEMS safety system force-electric fusion design scheme for small-caliber ammunition platforms. Modeling and computational analysis are conducted on the sensitive units in S&A. A mechanical equilibrium model is established to study the centrifugal overload and electromagnetic forces, followed by verification through dynamic simulation. The design aimed to achieve the safety and arming control of the MEMS security system using a plate-type electromagnetic driving scheme. A low driving energy electromagnetic coil model is designed, and the driving capability of the electromagnetic coil is analyzed. It is found that under the condition of a distance of 0.1mm and 8V, a driving force of 270mN could be achieved. Considering the complex operating conditions during the arming process, a low damping model is developed for the arming degree of the MEMS arming device. After the design is completed, the S&A and electromagnetic coils are processed and prepared using deep silicon etching and microcasting techniques. Finally, threshold verification is conducted for the recoil and centrifugal arming mechanisms of the S&A. The designed S&A ultimately achieved a size of less than or equal to ∅20mm.

A Review of Recent Developments in Nanomaterial Agents for Water Shutoff in Hydrocarbon Wells.

Reducing water production from hydrocarbon wells is one of the major requirements to prolong the life span of production wells. Gel treatment is commonly regarded as one of the traditional cost-effective methods for water shut-off applications. Different gel systems have been developed to overcome the challenges of performing a successful water shut-off treatment. Each gel system has its advantages and disadvantages. A new proposed technology is to enhance the gel performance by utilizing nanomaterials in its composition. Nanomaterials such as nanosilica, nanoclay, and graphene can significantly modify gel properties to improve plugging efficiency. This paper provides a brief review of the added value of using nanomaterials in the structure of polymer in situ gel, preformed particle-gel, and nanosilica-based fluid. Nanomaterials such as nanoclay, nanosilica, and nanographene are capable of adjusting the properties of in situ gel, such as control of gelation time (9-10) hours and enhancing gel strength up to 4.5 times. Nanomaterials also improved the swelling ratio of the preformed particle-gel by up to 400%, accompanied by increased gel strength. Notably, nanosilica-based gels exhibit an exceptional plugging efficiency (100%). Additionally, the paper discusses how modeling can be used to overcome operational challenges in terms of placement and plugging performance.

Studies on Impact and Opinion of Organic Food Products of Human Life during Covid-19

Organic food has become useful nowadays and every person know the benefits and effect of the organic products. Organic food products Opinion of consumer price and quality of organic food products during Covid-19 49.2% respondents give the opening organic food is good and health effective other conventional food products standard deviations 1.9. The COVID-19 pandemic has had a profound impact on various aspects of human life, including dietary choices and health concerns. As people have become increasingly conscious of their health and well-being, the demand for organic food products has surged.Organic food products have gained popularity for several reasons. Firstly, they are perceived as being healthier and more nutritious than conventionally produced foods, as they are cultivated without synthetic pesticides, herbicides, and genetically modified organisms. During the pandemic, individuals have shown a heightened awareness of the need to bolster their immune systems, leading to a greater interest in organic foods believed to contain fewer chemical residues and potentially higher levels of essential nutrients. Secondly, the pandemic has accentuated the importance of food safety and security. With disruptions in the global food supply chain, people have turned to locally-sourced and organic foods as a means of ensuring a steady supply of high-quality, uncontaminated products. Many have come to value transparency and traceability associated with organic food production, as it offers a sense of control and security in uncertain times. Furthermore, the COVID-19 pandemic has exposed the vulnerabilities of industrial agriculture and the associated environmental concerns. Consumers have become more conscious of the environmental impact of their food choices and have turned to organic products, which often have lower carbon footprints, support sustainable farming practices, and promote biodiversity. This abstract highlights the opinion people about organic food products in human life during the COVID-19 pandemic. The pandemic has led to an increased focus on health, food safety, and sustainability, organic foods have emerged as a preferred choice for many consumers, reflecting a broader shift towards more conscious and conscientious eating habits.

Research on the electronic control system for multispectral infrared detectors

In order to acquire and fully exploit multispectral information of scenes, and to establish a foundation for the research of multispectral image algorithms, a laboratory has developed a multispectral infrared detector capable of detecting short-wave infrared, mid-wave infrared, and long-wave infrared in three bands. Additionally, a preliminary electronic control system has been designed. The system employs a field-programmable gate array (FPGA) to accomplish the timing control, data acquisition, preprocessing of individual channel images, and multispectral image fusion of the detector. The preprocessing involves black level correction, blind element correction, non-uniformity correction, and histogram equalization of the raw images. For trispectral fusion, color enhancement is applied to linearly combined images in the YUV color space using a color transfer method. The system utilizes a pipeline design to ensure algorithm efficiency. In simulation, the electronic control system for the multispectral infrared detector obtains trispectral information of the scenes, and through image preprocessing and fusion, enhances the understanding of scene information.

Macroeconomic effects of a declining wage share: A meta‐analysis of the functional income distribution and aggregate demand

AbstractThis paper reviews the theoretical and empirical literature on the relationship between the functional distribution of income and aggregate demand, which investigates whether declining wage shares increase (“profit‐led”) or decrease (“wage‐led”) demand. It conducts a meta‐regression analysis of 33 studies with 578 estimates for total and domestic demand, covering up to 163 years and 59 countries and regions. Our results suggest that, on average and across all countries, total demand is predominantly profit‐led and domestic demand mainly wage‐led. The effects in the literature range between 0.8 and −0.3 within one standard deviation for domestic demand and between 0.4 and −0.7 for total demand, which are economically significant at the outer bounds. We find mixed evidence for publication selectivity, which may affect the size but not the direction of the results in the literature. If one was to nonetheless correct for this, then total demand would be less profit‐led or statistically insignificant. A set of moderator variables, including publication characteristics, estimation strategies, the covariates included in the studies’ estimation functions, and, in particular, controls for time and space, help explain the variation in the empirical estimates.

Performance Prediction and Optimization of Single-Piston Free Piston Expander-Linear Generator Based on Machine Learning and Genetic Algorithm

This paper proposed a single-piston free piston expander-linear generator (SFPE-LG) prototype applied to organic Rankine cycle systems. Two valve timing control strategies, namely, time control strategy (TCS) and position control strategy (PCS), were developed. Based on the experimental data, a back propagation neural network (BPNN) prediction model was established. The effects of structural parameters such as neural network layers, transfer function, training function, hidden layer nodes, and learning rate on the prediction accuracy of this BPNN model were discussed. The training and prediction accuracy of the BPNN model was verified using 5-fold cross-validation and Wilcoxon signed-rank test. Moreover, the BPNN model was integrated with a genetic algorithm to predict and optimize the maximum output power of the SFPE-LG. The results showed that the BPNN model used to predict the motion characteristics and output performance of the SFPE-LG exhibits strong learning ability and high prediction accuracy. Notably, the prediction accuracy of the BPNN model is significantly higher under the PCS compared to TCS. The effect of hidden layer nodes on mean square error (MSE) and correlation coefficient (R) is greater than that of the learning rate. When the number of hidden layer nodes exceeds 30, the BPNN model consistently achieves low MSE and high R. The optimization results showed that the SFPE-LG can obtain a maximum output power of 141.69 W under the TCS, when the working parameters are inlet pressure of 0.7 MPa, intake duration of 35 ms, load resistance of 67 Ω, and expansion duration of 104 ms, respectively.

Reactivity of dihydropyridines as reducing agents in redox initiating systems

For mild and ecofriendly polymerization conditions, Redox Initiating Systems (RISs) are more and more attractive. Indeed, the redox polymerization can be carried out at room temperature without any external energetic stimulus. Moreover, these latter processes can be very efficient under air and without purification of the monomers/resins. In this work, new redox initiating systems based on dihydropyridines are reported. An excellent reactivity is found in presence of copper complexes as catalyst, acid and peroxide. A full control of the gel time is possible by the selection of the appropriated reactant concentrations. These systems were characterized by optical pyrometry experiments as well as FTIR spectroscopy. Tack-free surfaces as well as potential photoactivation for on-demand polymerization can be obtained.

Field-effect transistor biosensor with signal amplification by ternary initiation complexes for detection of wide-range RNA concentration

Electrical detection of RNAs using transistor-based biosensors has attracted attention as a strategy for medical diagnosis and environmental monitoring. Herein, we demonstrated a proof-of-concept for specific, sensitive, and label-free RNA detection using a field-effect transistor (FET) biosensor with signal amplification by ternary initiation complexes (SATIC), which is an isothermal one-step nucleic acid amplification initiated by the combination of target RNA, circular DNA template and DNA primer. The SATIC system-applied FET biosensor specifically and quantitatively detected the target RNA with a single-nucleotide difference via the negative charges derived from the amplification products formed by a nucleic acid amplification reaction with φ29 DNA polymerase on the gate surface. In particular, the control of the amplification time allowed the detection of target RNA molecules over a wide concentration range, resulting in a detection limit of up to 6 copies/μL. Therefore, a transistor-based bioassay using the SATIC system could be useful for simple and sensitive nucleic acid analysis.