Fast Time Research Articles

Impact of yoga on the cognitive function among desk‐based workers

IntroductionProlonged sitting negatively impacts cognitive functions, such as working memory and inhibitory control. As sedentary behaviour rises in workplaces, interventions like yoga breaks, which combine physical activity and mindfulness, may mitigate these effects. While specific research on yoga breaks is limited, related studies suggest potential cognitive benefits. MethodsThis prospective, single-centre crossover trial took place from September 2022 to January 2023 at the Radiology Lab, KMC Manipal. Participants experienced three sessions: uninterrupted sitting, pranayama breaks, and yoga breaks, each lasting four hours. Executive functions were assessed hourly using computer-based tests (Eriksen’s Flanker Test and N-Back Test). Statistical analyses included repeated measures ANOVA and Friedman’s test. ResultsParticipants, with a mean age of 30.24 years, showed fastest reaction times during the yoga intervention in the Flanker Test, followed by pranayama and sitting. However, accuracy did not significantly differ between groups in both tests.Reaction times decreased significantly from the 0th to the 2nd and 4th hours in the Flanker Test, but not between the 2nd and 4th hours. In the N-Back test, accuracy declined over time for all interventions, without significant group differences. ConclusionYoga and pranayama breaks potentially improve reaction times during prolonged sitting but do not significantly impact accuracy in cognitive tasks. These findings suggest that while activity breaks can enhance certain cognitive functions, further research is needed to optimize interventions for cognitive health in sedentary work environments.

Modeling Multiband SEDs and Light Curves of BL Lacertae Using a Time-dependent Shock-in-jet Model

The origin of fast flux variability in blazars is a long-standing problem, with many theoretical models proposed to explain it. In this study, we focus on BL Lacertae to model its spectral energy distribution (SED) and broadband light curves using a diffusive shock acceleration process involving multiple mildly relativistic shocks, coupled with a time-dependent radiation transfer code. BL Lacertae was the target of a comprehensive multiwavelength monitoring campaign in early 2021 July. We present a detailed investigation of the source’s broadband spectral and light-curve features using simultaneous observations at optical–UV frequencies with the Swift Ultraviolet/Optical Telescope, in X-rays with the Swift X-Ray Telescope and AstroSat-SXT/LAXPC, and in gamma rays with Fermi-LAT, covering the period from 2021 July to August (MJD 59400–59450). A fractional variability analysis shows that the source is most variable in gamma rays, followed by X-rays, UV, and optical. This allowed us to determine the fastest variability time in gamma rays to be on the order of a few hours. The AstroSat-SXT and LAXPC light curves indicate X-ray variability on the order of a few kiloseconds. Modeling simultaneously the SEDs of low- and high-flux states of the source and the multiband light curves provided insights into the particle acceleration mechanisms at play. This is the first instance of a physical model that accurately captures the multiband temporal variability of BL Lacertae, including the hour-scale fluctuations observed during the flare.

Utilization of outdoor units as freshwater freezing machines on various masses of salt solution

The effect of solution mass on freezing the freshwater using an AC outdoor unit was investigated. The AC outdoor capacity was ½ PK and the evaporator to absorb the heat from the freshwater was designed in the form of a square spiral placed in a freezing box. The outdoor used R32 as the working fluid. The solution mass variations were 10 kg, 12 kg and 14 kg. The freezing box was filed with saline solution with a concentration of 20%. The mass of fresh water that was frozen was wrapped in plastic with a mass of water per package of 500 grams. The total mass of the freshwater was 10 kg. The results show that the fastest freezing time occurs at a mass of 10 kg of salt solution with a freezing time of 3.5 hours and the longest freezing time is at a mass of 14 kg of solution with a freezing time of 6 hours. The highest total heat flow rate is 554 W found in the variation of 10 kg solution mass. The AC outdoor unit is very effective to be used as a freezing machine with an EER of 5.8.

Molecular mechanics studies of factors affecting overall rate in cascade reactions: Multi-enzyme colocalization and environment.

Millions of years of evolution have optimized many biosynthetic pathways by use of multi-step catalysis. In addition, multi-step metabolic pathways are commonly found in and on membrane-bound organelles in eukaryotic biochemistry. The fundamental mechanisms that facilitate these reaction processes provide strategies to bioengineer metabolic pathways in synthetic chemistry. Using Brownian dynamics simulations, here we modeled intermediate substrate transportation of colocalized yeast-ester biosynthesis enzymes on the membrane. The substrate acetate ion traveled from the pocket of aldehyde dehydrogenase to its target enzyme acetyl-CoA synthetase, then the substrate acetyl CoA diffused from Acs1 to the active site of the next enzyme, alcohol-O-acetyltransferase. Arranging two enzymes with the smallest inter-enzyme distance of 60 Å had the fastest average substrate association time as compared with anchoring enzymes with larger inter-enzyme distances. When the off-target side reactions were turned on, most substrates were lost, which suggests that native localization is necessary for efficient final product synthesis. We also evaluated the effects of intermolecular interactions, local substrate concentrations, and membrane environment to bring mechanistic insights into the colocalization pathways. The computation work demonstrates that creating spatially organized multi-enzymes on membranes can be an effective strategy to increase final product synthesis in bioengineering systems.

Revealing Fast Negative Capacitance in PbZr0.2Ti0.8O3 Thin Film with Acicular Ferroelastic Domains.

Negative capacitance effects with fast response times hold great potential for reducing the power consumption in high-frequency nanoelectronics. Nevertheless, the negative capacitance effect faces considerable complexity arising from the dynamic interplay among electrostatic, nucleation energies, and domain evolution. This intricate balance poses a formidable challenge to achieving fast negative capacitance. Herein, we have achieved a fast negative capacitance time of ∼16.23 ns in PbZr0.2Ti0.8O3 (PZT) thin film, and our investigation confirms the presence of acicular ferroelastic domains within the PZT thin film. Under reversal electric fields, these acicular ferroelastic domains undergo a unique flipping process, transitioning through domain expansion and contraction. This distinct domain flipping manner accelerates the nucleation and growth of ferroelectric domains, thereby facilitating the observed fast negative capacitance. The realization of fast negative capacitance holds substantial promise for reducing operational time and power consumption, offering prospects for the design of nanoelectronics with significantly lower power requirements.

Synthesis of pyrazolopyrano pyrimidines via one-pot solvent free greener approach utilizing lanthanum trifluoroacetate and trichloroacetate Lewis acids supported on mesoporous silica: An experimental and DFT studies

Herein, an economic, environment-benign and sustainable greener protocol was developed for the production of pyrazolopyrano pyrimidines utilizing water competent Lanthanum trifluoroacetate and trichloroacetate Lewis acids based over silica via one-pot reaction involving aromatic aldehydes, ethyl acetoacetate, hydrazine hydrate and barbituric acid. The capability to incorporate a broad spectrum of functional groups, fast reaction times, best product yield, gentle reaction medium, solvent-free synthesis and the easy recoverability and multiple-time reusability of catalysts are notable advantages of the present synthetic approach. Furthermore, DFT studies was employed to study the pyrazolopyrano pyrimidines (5a-l), highlighting role of computational methods in predicting and understanding reactivity. Consequently, the integration of DFT studies with synthesis has proven to be a potent strategy for creating the current synthesis method.

Experimental validation of a novel hybrid Equilibrium Slime Mould Optimization for solar photovoltaic system

Maximizing Power Point Tracking (MPPT) is an essential technique in photovoltaic (PV) systems that guarantees the highest potential conversion of sunlight energy under any irradiance changes. Efficient and reliable MPPT technique is a challenge faced by researchers due to factors such as fluctuations in irradiance and the presence of partial shading. This paper introduced a novel hybrid Equilibrium Slime Mould Optimization (ESMO) MPPT-based algorithm combining the advantages of two recent algorithms, Slime Mould Optimization (SMO) and Equilibrium Optimizer (EO). The ESMO algorithm is compared with highly efficient MPPT-based techniques such as SMO, EO, Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Whale Optimization Algorithm (WOA), both under a Simulink environment and a real-time experimental laboratory setup using a Dspace1104 controller and PV emulator. The comparison focuses on performance under several irradiance cases, including instant irradiance change, partial shading, complex partial shading, and dynamic partial shading. The key advantage of ESMO is the fact that it has a single tunable parameter, which makes implementation much easier and, at the same time, reduces the computational resources that are required by the control system. Extensive testing proves the superiority of ESMO over all other techniques, the average efficiency of which is 99.98% under all conditions. Additionally, ESMO provides fast average tracking times of 244 ms under simulation experiments and 200 ms for real-time experiments. These results show that ESMO can be very important for future implementation in large-scale solar PV systems.

An unidentified yet notable modification on I Na and I K (DR) caused by ramelteon.

Despite advancement in anti-seizure medications, 30% of patients continue to experience recurrent seizures. Previous data indicated the antiepileptic properties of melatonin and its agonists in several animal models. However, the underlying mechanisms of melatonin and its agonists on cellular excitability remain poorly understood. In this study, we demonstrated the electrophysiological changes of two main kinds of ion channels that are responsible for hyperexcitability of neurons after introduction of melatonin agonists- ramelteon (RAM). In Neuro-2a cells, the amplitude of voltage-gated Na+ (I Na) and delayed-rectifier K+ currents (I K (DR)) could be suppressed under RAM. The IC50 values of 8.7 and 2.9 μM, respectively. RAM also diminished the magnitude of window Na+ current (I Na (W)) elicited by short ascending ramp voltage, with unchanged the overall steady-state current-voltage relationship. The decaying time course of I Na during a train of depolarizing pulses arose upon the exposure to RAM. The conditioning train protocol which blocked I Na fitted the recovery time course into two exponential processes and increased the fast and slow time constant of recovery the presence of RAM. In pituitary tumor (GH3) cells, I Na amplitude was also effectively suppressed by the RAM. In addition, GH3-cells exposure to RAM decreased the firing frequency of spontaneous action potentials observed under current-clamp conditions. As a result, the RAM-mediated effect on INa was closely associated with its ability to decrease spontaneous action potentials. Collectively, we found the direct attenuation of I Na and I K (DR) caused by RAM besides the agonistic action on melatonin receptors, which could partially explain its anti-seizure activity.

INhaled Sedation versus Propofol in REspiratory failure in the Intensive Care Unit (INSPiRE-ICU1): protocol for a randomised, controlled trial

IntroductionSedation in mechanically ventilated adults in the intensive care unit (ICU) is commonly achieved with intravenous infusions of propofol, dexmedetomidine or benzodiazepines. Significant limitations associated with each can impact their...

BrainQCNet: A Deep Learning attention-based model for the automated detection of artifacts in brain structural MRI scans

Abstract Analyses of structural MRI (sMRI) data depend on robust upstream data quality control (QC). It is also crucial that researchers seek to retain maximal amounts of data to ensure reproducible, generalizable models and to avoid wasted effort, including that of participants. The time-consuming and difficult task of manual QC evaluation has prompted the development of tools for the automatic assessment of brain sMRI scans. Existing tools have proved particularly valuable in this age of Big Data; as datasets continue to grow, reducing execution time for QC evaluation will be of considerable benefit. The development of Deep Learning (DL) models for artifact detection in structural MRI scans offers a promising avenue toward fast, accurate QC evaluation. In this study, we trained an interpretable Deep Learning model, ProtoPNet, to classify minimally preprocessed 2D slices of scans that had been manually annotated with a refined quality assessment (ABIDE 1; n = 980 scans). To evaluate the best model, we applied it to 2141 ABCD T1-weighted MRI scans for which gold-standard manual QC annotations were available. We obtained excellent accuracy: 82.4% for good quality scans (Pass), 91.4% for medium to low quality scans (Fail). Further validation using 799 T1w MRI scans from ABIDE 2 and 750 T1w MRI scans from ADHD-200 confirmed the reliability of our model. Accuracy was comparable to or exceeded that of existing ML models, with fast processing and prediction time (1 minute per scan, GPU machine, CUDA-compatible). Our attention model also performs better than traditional DL (i.e., convolutional neural network models) in detecting poor quality scans. To facilitate faster and more accurate QC prediction for the neuroimaging community, we have shared the model that returned the most reliable global quality scores as a BIDS-app (https://github.com/garciaml/BrainQCNet).

A Fluorescent Probe for Hydrazine Based on 4-hydroxycoumarin with High Selectivity and Sensitivity

Background: Therefore, the development of reliable analytical techniques with high selectivity and sensitivity to detect hydrazine is required for the protection of human health and safety. Objectives: Traditional methods for detecting N2H4 are frequently time-consuming, less accurate, and unsuitable for the analysis of living systems. Numerous fluorescent probes for hydrazine have been produced and gained some valuable results recently. The creation of a simple fluorescent probe for hydrazine detection is the goal of this project Method: In this study, 300 µL of probe 3-methyl-2-oxo-2H-chromen-7-yl propionate (MOCP) was mixed with an equivalent amount of the solution of each analyte to obtain the measurement solution. Following a 10-minute room temperature incubation period, the fluorescence spectra of the resultant solution were recorded. Results: The fluorescence intensity of the probe was noticeably enhanced when N2H4 was added to the probe, but almost no fluorescence enhancement was observed when other competitive ions were added. Conclusion: A hydrazine fluorescent probe based on 4-hydroxycoumarin fluorophore was developed. The probe MOCP displayed high sensitivity and selectivity for hydrazine, with a color change from colourless to blue for detection by the naked eye. Moreover, it demonstrated a low detection limit of 20 nM and a fast reaction time of 30 s.

Extraordinarily Time- and Memory-Efficient Large-Scale Canonical Correlation Analysis in Fourier Domain: From Shallow to Deep.

Canonical correlation analysis (CCA) is a correlation analysis technique that is widely used in statistics and the machine-learning community. However, the high complexity involved in the training process lays a heavy burden on the processing units and memory system, making CCA nearly impractical in large-scale data. To overcome this issue, a novel CCA method that tries to carry out analysis on the dataset in the Fourier domain is developed in this article. Appling Fourier transform on the data, we can convert the traditional eigenvector computation of CCA into finding some predefined discriminative Fourier bases that can be learned with only element-wise dot product and sum operations, without complex time-consuming calculations. As the eigenvalues come from the sum of individual sample products, they can be estimated in parallel. Besides, thanks to the data characteristic of pattern repeatability, the eigenvalues can be well estimated with partial samples. Accordingly, a progressive estimate scheme is proposed, in which the eigenvalues are estimated through feeding data batch by batch until the eigenvalues sequence is stable in order. As a result, the proposed method shows its characteristics of extraordinarily fast and memory efficiencies. Furthermore, we extend this idea to the nonlinear kernel and deep models and obtained satisfactory accuracy and extremely fast training time consumption as expected. An extensive discussion on the fast Fourier transform (FFT)-CCA is made in terms of time and memory efficiencies. Experimental results on several large-scale correlation datasets, such as MNIST8M, X-RAY MICROBEAM SPEECH, and Twitter Users Data, demonstrate the superiority of the proposed algorithm over state-of-the-art (SOTA) large-scale CCA methods, as our proposed method achieves almost same accuracy with the training time of our proposed method being 1000 times faster. This makes our proposed models best practice models for dealing with large-scale correlation datasets. The source code is available at https://github.com/Mrxuzhao/FFTCCA.

An Improved Hyper Spectral Imaging for Accurate Disease Diagnosis in Sustainable Medical Environments

Hyper spectral imaging (HSI) has emerged as a powerful technique for accurate disease diagnosis in medical environments. It provides high-resolution images with detailed spectral information, making it possible to identify subtle differences between healthy and diseased tissues. However, current HSI systems face challenges in terms of accuracy and efficiency, limiting their widespread application in sustainable medical environments. To overcome these challenges, our team has developed an improved HSI system that utilizes state-of-the-art spectral imaging technology and machine learning algorithms. This system is capable of capturing and analyzing a wider range of spectral data, enabling more precise identification of disease-specific spectral signatures. Furthermore, our system has been optimized to operate with minimal power consumption, making it environmentally friendly and suitable for sustainable medical environments. The improved HSI system has been successfully tested in clinical settings and has shown promising results in accurately diagnosing various diseases such as cancer, dermatitis, and cardiovascular conditions. Its high accuracy and fast processing time make it a valuable tool for early disease detection and treatment planning. Moreover, the ability to operate with low energy consumption makes it a sustainable solution for medical facilities in resourcelimited areas. In addition to its accuracy and efficiency, our improved HSI system is also user-friendly and can be easily integrated into existing medical imaging systems.

ANALISIS METODE PELAKSANAAN COR BERTAHAP PRECAST PADA PENYELESAIAN PROYEK OVERPASS PT. TALENTA BUMI MARABAHAN STUDI KASUS PADA PROYEK OVERPASS – MARABAHAN

The precast method work is adjusted because the slab elevation is ± 7 meters high, so it takes a lot of scaffolding (material) and time. Determination of precast concrete is done by analyzing preliminary design calculations, precast loading calculations, evaluating the load to be lifted, in the form of precast self-load, for precast concrete lifting time, precast concrete reinforcement, scaffolding calculations against precast self-load. Based on the results of the study for the age of 1 day concrete for the lifting permit of K-35 tons crane more than the precast load, then the load can be carried by the crane. But in the cylinder validation test, the value is obtained on the first day, so the work can be done earlier. As for the top cast with insitu cast method using the coefficient on day 3 with a value of 0.4, the comparative value of Mu = 30.893 tons.m and Mr = 31.877 tons.m according to the cylinder validation test graph with fc' 12 MPa, the work was obtained on day 2 and because the concreting was carried out in the fastest time of 1 day, the casting could be done on day 3 where the quality of concrete compressive strength has met according to PBI'71 regulations.

Preoperative Fasting Time Is Not Associated with Development of AKI after Cardiac Surgery

Preoperative Fasting Time Is Not Associated with Development of AKI after Cardiac Surgery

Analysis of pre-procedure fasting times: A pilot study for implementing fasting abbreviation in a hospital unit

Analysis of pre-procedure fasting times: A pilot study for implementing fasting abbreviation in a hospital unit

Review of thermal neutron scintillators: Evaluation metrics and future prospects for demanding applications

Neutron applications are progressing rapidly, requiring detectors to meet increasingly rigorous criteria. Specifications such as high neutron counting rates, fast timing resolution and low background have a significant impact on choice of scintillator and how scintillators are evaluated. This work considers detector requirements for neutron scattering instruments that are becoming more stringent as the sources and scattering technologies continue to improve. Meanwhile, both prominent scintillators used for neutron scattering detectors, ZnS:Ag/6LiF and GS-glass, remain stagnant. While these scintillators have been suitable for many years, they are becoming a limiting factor for neutron scattering instruments. ZnS:Ag is inhibiting count rate capability and GS-glass is too gamma sensitive so alternatives need to be found. A brief explanation of neutron scattering, its detector requirements and how those relate to scintillator properties will be discussed. Furthermore, this work explains how standard characterization methods and reporting of scintillation properties are not entirely suitable for high count rate, low background applications like neutron scattering. As a result, modifications to characterization of gamma discrimination, light output, and decay kinetics are suggested. Additional steps are suggested including neutron activation and a more appropriate assessment of count rate capability. A non-exhaustive set of 6Li containing neutron sensitive scintillators including ZnS:Ag/6LiF, GS20 glass, ZnO:Zn/6LiF, Cs6LiYCl:Ce, 6LiI:Eu, 6LiI:Ce, 6LiCaAlF:Eu, LiCaAlF:Ce, transparent rubber sheet (TRUST) 6LiCaAlF:Eu, TRUST 6LiCaAlF:Eu with added fluorophore and EJ-270 (6Li containing plastic) are reviewed and studied from this different perspective. Finally, new scintillator developments relevant to high count rate, low background applications are discussed.

Assessment of fasting times and energy and protein provision in patients requiring elective tracheostomy placement to facilitate weaning from mechanical ventilation during their critical care stay

Assessment of fasting times and energy and protein provision in patients requiring elective tracheostomy placement to facilitate weaning from mechanical ventilation during their critical care stay

Evaluation of cumulative fasting times of patients requiring elective tracheostomy placement to facilitate weaning from the ventilator during their critical care stay

Evaluation of cumulative fasting times of patients requiring elective tracheostomy placement to facilitate weaning from the ventilator during their critical care stay

Fast Competitive Swimmers Demonstrate a Diminished Diving Reflex.

Competitive swimmers complete 50-m front crawl swimming without breathing or with a limited number of breaths. Breath holding during exercise can trigger diving reflex including bradycardia and diminished active muscle blood flow, whereas oxygen supply to vital organ such as brain is maintained. We hypothesized that swimmers achieving faster time in 50-m front crawl with limited number of breaths demonstrate a blunted diving reflex of cardiac and active muscle blood flow responses with elevated cerebral perfusion to counteract peripheral and central fatigues. Twenty-eight competitive swimmers (12 females) underwent a 50-m front crawl swimming time trial with minimum respiratory interruptions, following which they were categorized into two groups: Fast (n = 13) and Slow (n = 15). Additionally, they performed knee extension exercises with maximal voluntary breath- holding, wherein leg blood flow (Doppler ultrasound), cardiac output (Modelflow), heart rate (electrocardiogram), and middle cerebral artery mean blood velocity (transcranial Doppler ultrasound) were evaluated. The pattern of leg blood flow response differed between the two groups (p = 0.031) with the Fast group experiencing a delayed onset of reductions in leg blood flow (p = 0.035). The onset of bradycardia was also delayed in the Fast group (p = 0.014), with this group demonstrating a higher value of the lowest heart rate (between-trial difference in average: 15.9 [3.73, 28.2] beats/min) and cardiac output (between-trial difference in median: 2.84 L/min) (both, p ≤ 0.013). Middle cerebral artery mean blood velocity was similar between the groups (all p ≥ 0.112). We show that swimmers with superior performance in 50-m front crawl swim with limited breaths display a diminished diving reflex.