Peak Time Research Articles

A review of skin cancer primary prevention activities in primary care settings.

Skin cancer is highly preventable through primary prevention activities such as avoiding ultraviolet radiation exposure during peak times and regular use of sun protection. General practitioners (GPs) and primary care nurses have key responsibilities in promoting sustained primary prevention behaviour. We aimed to review the evidence on skin cancer primary prevention activities in primary care settings, including evidence on feasibility, effectiveness, barriers and enablers. Rapid review and narrative synthesis. We searched published literature from January 2011 to October 2022 in Embase, Medline, PsychInfo, Scopus, Cochrane Central and CINAHL. The search was limited to skin cancer primary prevention activities within primary care settings, for studies or programs conducted in Australia or countries with comparable health systems. Analysis of barriers and enablers was informed by an implementation science framework. A total of 31 peer-reviewed journal articles were included in the review. We identified four main primary prevention activities: education and training programs for GPs; behavioural counselling on prevention; the use of novel risk assessment tools and provision of risk-tailored prevention strategies; and new technologies to support early detection that have accompanying primary prevention advice. Enablers to delivering skin cancer primary prevention in primary care included pairing preventive activities with early detection activities, and access to patient resources and programs that fit with existing workflows and systems. Barriers included unclear requirements for skin cancer prevention counselling, competing demands within the consultation and limited access to primary care services, especially in regional and remote areas. These findings highlight potential opportunities for improving skin cancer prevention activities in primary care. Ensuring ease of program delivery, integration with early detection and availability of resources such as risk assessment tools are enablers to encourage and increase uptake of primary prevention behaviours in primary care, for both practitioners and patients.

Changes in attitudes, beliefs, and experiences related to pregnancy during graduate medical education training from 2005 to 2021.

Today, 50% of medical students are women, and residency and fellowship training years overlap with peak times for starting families. The authors describe attitudes toward pregnancy during residency and fellowship and report pregnancy rates and complications for female residents and resident partners across several decades. A web-based survey was emailed to 1,057 residents in 2005 (period 1) and 1,860 residents in 2021 (period 2). Anonymous surveys were sent to all trainees including pregnant trainees, affected co-trainees and trainee partners. Resident attitudes and pregnancy characteristics were compared between groups using the chi-square (χ2) test for categorical variables and the Kruskal-Wallis test for ordinal variables. A total of 442 residents (41.8%) responded to the 2005 survey, and 525 (28.2%) responded to the 2021 survey. Most residents who covered for a pregnant resident had positive feelings about covering for their colleagues during both time periods, although more positive attitudes were present during the period 2. Only about 10% of residents received compensation for their coverage during both time periods. Among residents with a pregnancy during training (i.e., themselves or partners), most characterized having a baby in training as "somewhat difficult" or "very difficult" at both time periods. Pregnancy complication rates were 33% and 44% for training years 2005 and 2021. As medical education evolves, training programs should be proactive in creating structured support systems for pregnant residents and resident partners to minimize adverse maternal and fetal outcomes and to improve training programs. Future studies are needed to elucidate the causality of higher-than-expected pregnancy complication rates.

Injection rate, scanning position, and values of parameters on pulmonary computed tomography perfusion in normal Beagles.

This study evaluated the effects of scanning position and contrast medium injection rate on pulmonary CT perfusion (CTP) images in healthy dogs. 7 healthy Beagles. Experiments involved 4 conditions: dorsal and sternal recumbency at 2.5 mL/s (first) and sternal recumbency with additional rates of 1.5 and 3.5 mL/s (second). Various parameters, including the initial time of venous enhancement (Tv), peak time of arterial enhancement (PTa), and peak enhancement values of the artery, were measured. The PTa to Tv interval was calculated. Perfusion mapping parameters (pulmonary blood flow, pulmonary blood volume, mean transit time, time to maximum, and time to peak) were determined in different lung regions (left and right dorsal, middle, and ventral). There are significant variations in most perfusion mapping parameters based on the pulmonary parenchymal location. Dorsal recumbency had a lower peak value of arterial enhancement than sternal recumbency. Pulmonary blood flow in the dorsal region and mean transit time and time to maximum in all regions showed no significant differences based on position. Pulmonary blood volume and time to peak varied with scanning position. The PTa to Tv interval did not differ based on the injection rate, but the injection time at 1.5 mL/s was longer than at other rates. All perfusion mapping parameters of the ventral region increased with higher injection rates. The recommended CTP imaging approach in dogs is a low injection rate of 1.5 mL/s in the sternal recumbency. This study provides reference ranges for perfusion parameters based on the pulmonary parenchymal location, contributing to the acquisition and application of pulmonary CTP images for differential diagnosis in small-breed dogs.

Influence of biophysical attributes and locations on the consumer acceptability of backslopped fermented gari

The backslopped fermentation method was used to produce gari to reduce the variability in the sensory attributes and their composition. The relationship between the quality attributes of backslopped fermented gari (BFG) and the sensory and instrumental texture profile of the cooked dough (eba) has been reported. There is presently no information on the drivers of the consumer acceptability of the BFG based on locations. Hence, this study aimed to evaluate the influence of biophysical attributes and locations on the consumer acceptability of BFG. The BFG was produced using an established method with the traditional spontaneous fermentation used as a control in each location. The consumer acceptability of the gari samples was carried out using a well-structured questionnaire in each location, and the biophysical attributes were analyzed in the laboratory using standard methods. The principal component analysis results showed that the consumers prefer the BFG in the Tse-Hom community because of their starch and sugar contents, bulk density, and peak time. The consumer acceptability of the 24 hrs and 48 hrs BFG in the Amatta community and the 24 hrs BFG in the Ubomiri community was associated with the trough and final viscosities and sugar content of the product. Also, the gari consumers in the Obaagun community accepted the 48 hrs BFG due to the water absorption capacity, pasting temperature, and the peak time of the product. Therefore, the consumer acceptability of the BFG is attributed to its biophysical traits but differs between locations.

Differences in kinetic factors affecting gait speed between lesion sides in patients with stroke.

The differences in kinetic mechanisms of decreased gait speed across brain lesion sides have not been elucidated, including the arrangement of motor modules reflected by kinetic interjoint coordination. The purpose of this study was to elucidate the differences in the kinetic factors of slow gait speed in patients with stroke on the lesion sides. A three-dimensional motion analysis system was employed to assess joint moment in the lower limb and representative gait parameters in 32 patients with right hemisphere brain damage (RHD) and 38 patients with left hemisphere brain damage (LHD) following stroke as well as 20 healthy controls. Motor module composition and timing were determined using principal component analysis based on the three joint moments in the lower limb in the stance phase, which were the variances accounted for principal components (PCs) and the peak timing in the time series of PCs. A stepwise multiple linear regression analysis was performed to identify the most significant joint moment and PC-associated parameter in explaining gait speed. A negligible difference was observed in age, weight, height, and gait speed among patients with RHD and LHD and controls. The following factors contributed to gait speed: in patients with RHD, larger ankle plantarflexion moment on the paretic (p = 0.001) and nonparetic (p = 0.002) sides and ankle dorsiflexion moment on the nonparetic side (p = 0.004); in patients with LHD, larger ankle plantarflexion moment (p < 0.001) and delayed peak timing of the first PC (p = 0.012) on the paretic side as well as ankle dorsiflexion moment on the nonparetic side (p < 0.001); in the controls, delayed peak timing of the first PC (p = 0.002) on the right side and larger ankle dorsiflexion moment (p = 0.001) as well as larger hip flexion moment on the left side (p = 0.023). The findings suggest that the kinetic mechanisms of gait speed may differ among patients with RHD following patients with stroke with LHD, and controls.

Beyond optimal disturbances: a statistical framework for transient growth

The theory of transient growth describes how linear mechanisms can cause temporary amplification of disturbances even when the linearized system is asymptotically stable as defined by its eigenvalues. This growth is traditionally quantified by finding the initial disturbance that generates the maximum response at the peak time of its evolution. However, this can vastly overstate the growth of a real disturbance. In this paper, we introduce a statistical perspective on transient growth that models statistics of the energy amplification of the disturbances. We derive a formula for the mean energy amplification and spatial correlation of the growing disturbance in terms of the spatial correlation of the initial disturbance. The eigendecomposition of the correlation provides the most prevalent structures, which are the statistical analogue of the standard left singular vectors of the evolution operator. We also derive accurate confidence bounds on the growth by approximating the probability density function of the energy. Applying our analysis to Poiseuille flow yields a number of observations. First, the mean energy amplification is often drastically smaller than the maximum. In these cases, it is exceedingly unlikely to achieve near-optimal growth due to the exponential behaviour observed in the probability density function. Second, the characteristic length scale of the initial disturbances has a significant impact on the expected growth, with large-scale initial disturbances growing orders of magnitude more than small-scale ones. Finally, while the optimal growth scales quadratically with Reynolds number, the mean energy amplification scales only linearly for certain reasonable choices of the initial correlation.

Enhancing stability and odor control of water-based foam for pesticide site restoration using xanthan gum

Foam stability plays an important role in the effect of blocking the odorous substances. Based on the characteristic of xanthan gum of enhancing foam stability and preventing foam from water drainage and coarsening, this paper investigated the half-life, foaming volume, viscosity, drainage curve, and bubble microstructure of foam filled with 0.1%, 0.2%, and 0.3% xanthan gum respectively, and further analyzed the correlation between xanthan gum dosage, viscosity of foam solution and foam stability. The effect of different stability foams on para-xylene was tested. The results showed that compared with no xanthan gum, the half-life of foam with 3% xanthan gum was extended from 1 to 61 h, the drainage time increased from 4.5 to 85 h, and the foaming coarsening rate slowed down 3 times. The addition of 0.3% xanthan gum reduced the peak value of the p-xylene dispersion by 83.7% and postponed the peak time by 6 times.

Characterization of differences in immune responses during bolus and continuous infusion endotoxin challenges using mathematical modelling.

Endotoxin administration is commonly used to study the inflammatory response, and though traditionally given as a bolus injection, it can be administered as a continuous infusion over multiple hours. Several studies hypothesize that the latter better represents the prolonged and pronounced inflammation observed in conditions like sepsis. Yet very few experimental studies have administered endotoxin using both strategies, leaving significant gaps in determining the underlying mechanisms responsible for their differing immune responses. We used mathematical modelling to analyse cytokine data from two studies administering a 2ngkg-1 dose of endotoxin, one as a bolus and the other as a continuous infusion over 4 h. Using our model, we simulated the dynamics of mean and subject-specific cytokine responses as well as the response to long-term endotoxin administration. Cytokine measurements revealed that the bolus injection led to significantly higher peaks for interleukin (IL)-8, while IL-10 reaches higher peaks during continuous administration. Moreover, the peak timing of all measured cytokines occurred later with continuous infusion. We identified three model parameters that significantly differed between the two administration methods. Monocyte activation of IL-10 was greater during the continuous infusion, while tumour necrosis factor and IL-8 recovery rates were faster for the bolus injection. This suggests that a continuous infusion elicits a stronger, longer-lasting systemic reaction through increased stimulation of monocyte anti-inflammatory mediator production and decreased recovery of pro-inflammatory catalysts. Furthermore, the continuous infusion model exhibited prolonged inflammation with recurrent peaks resolving within 2days during long-term (20-32h) endotoxin administration.

The double-peaked type I X-ray bursts with different mass accretion rate and fuel composition

ABSTRACT Using the mesa (Modules for Experiments in Stellar Astrophysics) code, we have carried out a detailed survey of the available parameter space for the double-peaked type I X-ray bursts. We find that the double-peaked structure appears at mass accretion rate $\dot{M}$ in the range of $\sim (4-8)\times 10^{-10}\, {\rm M}_{\odot }\,{\rm yr}^{-1}$ when metallicity Z = 0.01, while in the range of $\sim (4-8)\times 10^{-9}\, {\rm M}_{\odot }\,\rm {yr}^{-1}$ when Z = 0.05. Calculations of the metallicity impact suggest that the double peaks will disappear when Z ≲ 0.005 for $\dot{M}=5\times 10^{-10}\, {\rm M}_{\odot }\,\rm {yr}^{-1}$ and Z ≲ 0.04 for $\dot{M}=5\times 10^{-9}\, {\rm M}_{\odot }\,\rm {yr}^{-1}$. Besides, the impacts of base heating Qb, as well as nuclear reaction waiting points: $^{22}\rm {Mg}$, $^{26}\rm {Si}$, $^{30}\rm {S}$, $^{34}\rm {Ar}$, 56Ni, $^{60}\rm Zn$, $^{64}\rm {Ge}$, $^{68}\rm {Se}$, and $^{72}\rm {Kr}$ have been explored. The luminosity of the two peaks decreases as Qb increases. 68Se(p, γ)69Br is the most sensitive reaction, the double peaks disappear assuming that 56Ni(p, γ)57Cu, and 64Ge(p, γ)65As reaction rates have been underestimated by a factor of 100 and the 22Mg(α, p)25Al reaction rate has been overestimated by a factor of 100, which indicates that 22Mg, 56Ni, 64Ge, and 68Se are possibly the most important nuclear waiting points impedance in the thermonuclear reaction flow to explain the double-peaked bursts. Comparisons to the double-peaked bursts from 4U 1636−53 and 4U 1730−22 suggest that the nuclear origins of double-peaked type I X-ray bursts are difficult to explain the observed larger peak times ($t_{\rm p,1}\gtrsim 4\, {\rm s}$, $t_{\rm p,2}\gtrsim 8\, {\rm s}$) and smaller peak ratio (r1, 2 ≲ 0.5). The composition of ashes from double-peaked bursts is very different from the single-peaked bursts especially for the heavier p-nuclei.

Characterization workflow for fragments detected in capillary electrophoresis sodium dodecyl sulfate analysis of therapeutic monoclonal antibodies.

Product-related fragments in monoclonal antibodies (mAbs) can have a significant impact on the efficacy and safety of the product. Capillary electrophoresis sodium dodecyl sulfate (CE-SDS) is a commonly used method for fragment quantification, but it has challenges in peak identification due to the inability to enrich components and the incompatibility of SDS with mass spectrometry (MS). This article presents a workflow for identifying peaks in CE-SDS analysis. The workflow involves comparing the migration time of peaks with that of standards and utilizing MS analysis to identify fragments. By employing this innovative systematic workflow, we successfully identified the CE-SDS impurity peaks of seven antibody products. Among them, four products exhibited characteristic fragments associated with disulfide bonds (light chain [LC], heavy-light [HL] chain, heavy-heavy [HH] chain, and HH-LC) and a glycosylation-related fragment non-glycosylated heavy chain. Additionally, one product showed a fragment formed by the connection of HC_C130 and HC_C130, which is associated with a thioether bond. Furthermore, two other products displayed amino acid backbone breakage, with one product showing clipping at the HC region of A233-G285 and the other product showing clipping at the HC regions of A97-S158 and N342-T366. This workflow can be applied in early drug research, process development, or during the biologics license application stage to characterize fragments in therapeutic mAbs analyzed by CE-SDS.

Searching for ringdown higher modes with a numerical relativity-informed post-merger model

Robust measurements of multiple black hole vibrational modes provide a unique opportunity to characterise gravity in extreme curvature and dynamical regimes, to better investigate the nature of compact objects and search for signs of new physics. We use a numerically-tuned quasicircular non-precessing ringdown model, TEOBPM, and the pyRing analysis infrastructure to perform a time-domain spectroscopic analysis of the third catalog of transient gravitational-wave signals, GWTC-3, searching for higher angular modes. The TEOBPM model effectively includes non-linearities in the early post-merger signal portion, and carries information about the progenitors parameters through time-dependent excitation amplitudes of the black hole quasinormal modes. Such a strategy allows us to accurately model the full post-merger emission, recovering higher signal-to-noise ratios compared to templates based on more agnostic superpositions of damped-sinusoids. We find weak evidence for the presence of (l,m)=(3,3)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(l,m)=(3,3)$$\\end{document} [(l,m)=(2,1)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(l,m)=(2,1)$$\\end{document}] mode in several events, with the largest Bayes factor in favour of this mode being B≃2.6\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {B}} \\simeq 2.6$$\\end{document} [B≃1.2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {B}} \\simeq 1.2$$\\end{document}] within the support of the peak time distribution. For GW190521, we observe B≃5.1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {\\mathcal {B}} \\simeq 5.1$$\\end{document}, but only for times outside the peak time support reconstructed using the highly accurate NRSur7dq4 model, indicating significant systematics affecting such putative detection. Allowing for deviations from general relativity under the assumption of the presence of two modes, we find tentative support for the Kerr “final state conjecture”. Our work showcases a systematic methodology to robustly identify and characterise higher angular modes in ringdown-only signals, highlighting the significant impact of modelling assumptions and peak time uncertainty on spectroscopic measurements, at current signal-to-noise ratios.

Natural history and biomarkers of KCNV2-associated retinopathy.

KCNV2-associated retinopathy is an autosomal recessive inherited retinal disease classically named cone dystrophy with supernormal rod response (CDSRR). This study aims to identify the best biomarker for evaluating the condition. A retrospective review of eight patients from seven families with genetically confirmed KCNV2-associated retinopathy was performed. The best corrected visual acuity (BCVA), full-field electroretinogram (ffERG), pattern ERG (pERG), fundus imaging: retinal photograph and fundus autofluorescence (FAF), and optical coherence tomography (OCT) were analysed. There was a disproportionate increase in b-wave amplitude with a relatively small light intensity increase, especially between the two dimmest stimuli of DA 0.002 and 0.01 (-2.7 and -2.0 log cd.s/m2). The a-wave amplitude was normal. The a-wave peak time was delayed in all stimuli. The b-wave peak time was delayed compared to normal, but the gap tightened as intensity increased. The b:a wave ratio was above or at the upper limit for the reference values. FAF bull's eye maculopathy pattern was prominent and variable foveal disruption on OCT was apparent in all patients. Legal blindness was reached before the age of 25. We identified three potential electrophysiology biomarkers to assist in evaluating future therapies: the disproportionate b-wave amplitude jump, delayed a-wave and b-wave peak time, and the higher than normal b:a wave ratio. Any of these biomarkers found with photoreceptor ellipsoid zone foveal-perifoveal disruption should prompt consideration for KCNV2 retinopathy. The BCVA natural history data suggests the probable optimum therapeutic window in the first three decades of life.

Global dynamics of heterogeneous epidemic models with exponential and nonexponential latent period distributions

AbstractMany epidemic models assume an exponential distribution for the latent stage, but this may not accurately represent reality and could impact disease transmission predictions. Previous studies for short time scale models have shown that the choice of latency distribution affects estimates of the epidemic peak, time to peak, and infection eradication time, but has little effect on the final infection size. However, it is unclear if these conclusions hold for long time scale models. To address this, we investigate the impact of different latency distributions on disease dynamics in long‐term models, comparing them with short‐term models. We propose two susceptible‐exposed‐infected‐hospitalized‐recovered () models with multiple groups, using exponential and gamma distributions for latency. We derive the basic reproduction number () for both models and prove the global stability of the equilibrium points. We conduct numerical simulations and find that the gamma distribution may lead to larger epidemic peak sizes and longer peak times compared to the exponential distribution. However, the impact of latency distribution on estimating the peak and time to peak is smaller in long‐term models than in short‐term models. Additionally, the effect on the final total infected size is negligible regardless of the time scale. Therefore, when analyzing long‐term epidemic dynamics using heterogeneity models, the choice of latency distribution does not significantly affect the results. Assuming an exponential distribution for the latency is sufficient for simplifying the model and facilitating analysis. Our study provides valuable insights for selecting appropriate mathematical models in epidemiology.

Ab initio morphology prediction of Pd, Ag, Au, and Pt nanoparticles on (0001) sapphire substrates

We energetically predict the morphology of Pd, Ag, Au, and Pt nanoparticles on (0001) sapphire substrates, using density functional theory (DFT) simulations and the well-known Young–Dupre equation. In all cases, the contact angles exceed 90°, indicating that the nanoparticles are spherical. Notably, Au nanoparticles exhibit a higher contact angle than those of their counterparts. The validity of the proposed abinitio nanoparticle morphology prediction approach based on DFT simulations was assessed in comparison with our previous experimental findings pertaining to the time variation of the full width at half maximum (FWHM) of the resonant peak. Furthermore, the diffusivities of single Pd, Ag, Au, and Pt atoms on the substrate were evaluated by calculating the activation energy, offering insights into the underlying physics governing the timing of FWHM peaks. The analysis confirms a higher diffusivity of Au and Ag compared with Pd and Pt. According to the comparison between DFT and experiment results, although no clear relation is observed between the contact angles and timing of FWHM peaks, the diffusivity of sputtered atoms may influence the timing of FWHM peaks. Thus, timing can help to clarify the nanoparticle size, rather than shape.

Light Bridges and Solar Active Region Evolution Processes

The formation mechanism of light bridges (LBs) is strongly related to the dynamic evolution of solar active regions (ARs). To study the relationship between LB formation and AR evolution phases, we employ 109 LB samples from 69 ARs in 2014 using observational data from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. LBs are well matched with the weak field lanes (WFLs), except those aligned on the polarity inversion line of δ sunspots. For penumbral intrusion (type-A) and umbral-dot emergence (type-C) LBs, the WFLs represent the splitting of magnetic flux systems. The sunspots tend to decay and split into several parts after type-A and type-C LBs are formed. For sunspot/umbra-merging (type-B) LBs, the declining WFLs are caused by collisions of flux systems. The sunspots merged and remained stable after type-B LBs formed. We conclude that type-B LBs are formed by collisions of flux systems, while type-A and type-C LBs are generated by splits. The time differences (δ T) between LBs appearing and ARs peaking have an average value of 1.06, −1.60, and 1.82 days for type-A, B, and C LBs, with the standard deviations of 3.27, 2.17, and 1.89, respectively. A positive value of δ T means that the LB appears after the AR peaks, whereas a negative δ T means it appears before the peak. Type-A LBs tend to form in the decaying phase or around the peak time. Type-B LBs are more likely to be formed in the developing phase. Type-C LBs mostly take shape in the decaying phase of ARs.

Energy optimization of stand-alone electrical grid considering the optimal performance of the hydrogen storage system and consumers

The surge in energy storage systems and the increasing involvement of demand-side participation can be attributed to their favorable characteristics, including their seamless integration into electrical networks and their capacity to offer operational flexibility during critical periods. This scholarly article focuses on enhancing energy utilization in an autonomous electrical grid by incorporating hydrogen storage and demand-side participation. The optimization of the stand-alone electrical grid is based on maximizing efficiency and minimizing energy consumption costs as the main objective functions are modeled. The modeling efficiency is formulated considering the ratio of the energy not supplied (ENS) to energy generation by resources. And costs of energy consumption are modeled as consumption of fuel costs by resources. The consumers’ participation is proposed based on an incentive approach to consumers for demand shaving in peak times. Also, the hydrogen storage system is installed in the stand-alone electrical grid to improve the main objectives. The particle swarm optimization (PSO) algorithm for energy optimization and solving objective functions is applied. In the end, numerical simulation is carried out in some case studies to confirm and supremacy of energy optimization with the participation of the hydrogen storage system and consumers. The case studies based on non-participation and participation of the storage system and consumers in energy management are implemented. The implementation of case studies examines the impact of both non-participation and participation of the storage system and consumers in energy management. The findings reveal that when the storage system and consumers actively participate, there is a significant improvement in efficiency and a substantial reduction in energy costs. Specifically, the efficiency is enhanced by 3% and the energy costs are reduced by 29.5% compared to the scenario where they do not participate.

Implementation of ARM STM32F4 microcontroller for speed control of BLDC motor based on bat algorithm

Brushless direct current (BLDC) motor speed performance is an essential component that must be considered in the electric vehicle drive system. This research aims to obtain the transfer function from the mathematical modeling of the BLDC motor and optimization of the BLDC motor so that a high transient response is received. The method used in this study is to identify system parameters and then model them using the structure of the autoregressive exogenous (ARX) polynomial model. Meanwhile, to get a high transient response performance, optimization is done with a hybrid intelligent controller. The experimental findings indicate that the optimization process utilizing the bat method yielded the most favorable transient response. The resulting values for the proportional gain (Kp), integral gain (Ki), and derivative gain (Kd) were determined to be 31.2685, 7.7375, and -1.1934, respectively. In the current investigation, the minimum frequency value is 6381934.619. Also determined are the transient response characteristics, which include a rise time of 0.289 seconds, a settling time of 10.9 seconds, an overshoot of 3.4%, and a peak time of 1.04 seconds. Furthermore, the closed-loop system demonstrates stable behavior in terms of stability.

A Practical Guide to Whole Genome Sequencing in the NICU.

The neonatal period is a peak time for the presentation of genetic disorders that can be diagnosed using whole genome sequencing (WGS). While any one genetic disorder is individually rare, they collectively contribute to significant morbidity, mortality, and health-care costs. As the cost of WGS continues to decline and becomes increasingly available, the ordering of rapid WGS for NICU patients with signs or symptoms of an underlying genetic condition is now feasible. However, many neonatal clinicians are not comfortable with the testing, and unfortunately, there is a dearth of geneticists to facilitate testing for every patient that needs it. Here, we will review the science behind WGS, diagnostic capabilities, limitations of testing, time to consider testing, test initiation, interpretation of results, developing a plan of care that incorporates genomic information, and returning WGS results to families.

Optimal resilient operation and sustainable power management within an autonomous residential microgrid using African vultures optimization algorithm

This paper introduces an adaptive artificial intelligence (AI)-based home energy management system (HEMS) to mitigate the discomfort of customers and reduce operational costs. A techno-economic smart HEMS is proposed for home microgrid management, employing two control approaches. The initial approach involves employing an FPGA as a central control unit due to its high-speed processing capabilities and efficient handling of rapid changes within desired limits. The other approach aims to optimize the performance of the microgrid and obtain an optimal operating plan for home microgrids by integrating power limitations using a developed coordinated strategy. A multi-objective optimization problem is formulated that involves the coordinated operation of backup sources. The study utilizes the African Vultures Optimization Algorithm (AVOA) and compares it with newly introduced algorithms, with a specific emphasis on three techno-economic objectives. The simulation and experimental results indicate that the AI-embedded FPGA-based HEMS not only enhances performance and extends Battery Energy Storage Systems (BESSs) life but also reduces peak times resulting from random electric vehicle charging. Through comparative analysis, the superiority of the AVOA is evident, attaining the lowest operating cost of 1308.85$ by the end of the day, reflecting a 3.77% reduction in operating costs compared to the previous study.

Implementation of FOPID controller with modified harmony search optimization for precise modelling and auto-tuning of nonlinear systems

This research aims to optimize the fractional order proportional integral derivative (FOPID) controller for nonlinear process tests. Instead of relying on the traditional trial-and error method for dynamic parameter selection, this proposes a modified harmony search optimization method to compute the optimal dynamic parameters. Based on the physical parameters, using mathematical modelling techniques system transfer function is determined. Additionally, the delay of the control scheme is determined using the Open Loop Transfer Function (OLTF) response. The dynamic parameters of the FOPID controller are evaluated using the Harmonic Search Algorithm – Fractional Order Proportional Integral Derivative (HAS_FOPID) optimization technique, which aims to minimize the system's Integral Square Error (ISE). Time responses, including rise time, peak time, and peak overshoot, are obtained and optimized through the HAS_FOPID algorithm. To verify systems stability, the output response is analysed using various techniques such as bode plots, pole placement, and Nyquist plots. Furthermore, the HAS_FOPID optimization technique is compared with other natural optimization techniques to assess its effectiveness. The research also evaluates the system's robustness by supply/ load disturbances. The objective is to demonstrate that, the optimized HAS_FOPID technique, has significantly enhanced control performance, stability, and robustness of nonlinear systems compared to natural and alternative optimization approaches.