Split Times Research Articles

Running Variability in Marathon-Evaluation of the Pacing Variables.

Background and Objectives: Pacing analyses for increasingly popular long-distance running disciplines have been in researchers' spotlight for several years. In particular, assessing pacing variability in long-distance running was hardly achievable since runners must repeat long-running trials for several days. Potential solutions for these problems could be multi-stage long-distance running disciplines. Therefore, this study aimed to assess the long-distance running variability as well as the reliability, validity, and sensitivity of the variables often used for pacing analyses. Materials and Methods: This study collected the split times and finish times for 20 participants (17 men and three women; mean age 55.5 years ± 9.5 years) who completed the multiday marathon running race (five marathons in 5 days), held as part of the Bretzel Ultra Tri in Colmar, France, in 2021. Seven commonly used pacing variables were subsequently calculated: Coefficient of variation (CV), Change in mean speed (CS), Change in first lap speed (CSF), Absolute change in mean speed (ACS), Pace range (PR), Mid-race split (MRS), and First 32 km-10 km split (32-10). Results: Multi-stage marathon running showed low variability between days (Intraclass correlation coefficient (ICC) > 0.920), while only the CV, ACS, and PR variables proved to have moderate to good reliability (0.732 < ICC < 0.785). The same variables were also valid (r > 0.908), and sensitive enough to discern between runners of different performance levels (p < 0.05). Conclusions: Researchers and practitioners who aim to explore pacing in long-distance running should routinely utilize ACS, CV, and PR variables in their analyses. Other examined variables, CS, CSF, MRS, and 32-10, should be used cautiously. Future studies might try to confirm these results using different multi-stage event's data as well as by expanding sensitivity analysis to age and gender differences.

Droplet pair breakup in microfluidic expansion channel

Previous studies on droplet splitting mainly focus on monodisperse droplets, and the understanding of the breakup of polydisperse droplet systems is still lacking. In this work, we experimentally study the breakup of droplet pairs in the expansion region of microfluidic channel. The results show that with the increase in the size ratio of the droplets in the droplet pair, the breakup mode of droplet pairs changes from rear droplet breakup to front droplet breakup, and then to front droplet alternate breakup. The expansion angle can affect the critical size ratio of the splitting mode transition, but it cannot change the transition trend. The expansion angle plays a major role in the splitting time and distance of the droplet pair. When the expansion angle is increased, the splitting time of the droplet pair is reduced and the splitting distance is shorter. Our study extends the understanding of the breakup of non-monodisperse droplet systems and provides a feasible approach for the selective and controllable splitting of droplets, which is important for laboratory-on-a-chip droplet volume manipulation and has potential applications.

Knowledge-based modeling of simulation behavior for Bayesian optimization

Numerical simulations consist of many components that affect the simulation accuracy and the required computational resources. However, finding an optimal combination of components and their parameters under constraints can be a difficult, time-consuming and often manual process. Classical adaptivity does not fully solve the problem, as it comes with significant implementation cost and is difficult to expand to multi-dimensional parameter spaces. Also, many existing data-based optimization approaches treat the optimization problem as a black-box, thus requiring a large amount of data. We present a constrained, model-based Bayesian optimization approach that avoids black-box models by leveraging existing knowledge about the simulation components and properties of the simulation behavior. The main focus of this paper is on the stochastic modeling ansatz for simulation error and run time as optimization objective and constraint, respectively. To account for data covering multiple orders of magnitude, our approach operates on a logarithmic scale. The models use a priori knowledge of the simulation components such as convergence orders and run time estimates. Together with suitable priors for the model parameters, the model is able to make accurate predictions of the simulation behavior. Reliably modeling the simulation behavior yields a fast optimization procedure because it enables the optimizer to quickly indicate promising parameter values. We test our approach experimentally using the multi-scale muscle simulation framework OpenDiHu and show that we successfully optimize the time step widths in a time splitting approach in terms of minimizing the overall error under run time constraints.

"Falling Behind," "Letting Go," and Being "Outsprinted" as Distinct Features of Pacing in Distance Running.

In distance running, pacing is characterized by changes in speed, leading to runners dropping off the leader's pace until a few remain to contest victory with a final sprint. Pacing behavior has been well studied over the last 30years, but much remains unknown. It might be related to finishing position, finishing time, and dependent on critical speed (CS), a surrogate of physiologic capacity. We hypothesized a relationship between CS and the distance at which runners "fell behind" and "let go" from the leader or were "outsprinted" as contributors to performance. 100-m split times were obtained for athletes in the men's 10,000-m at the 2008 Olympics (N = 35). Split times were individually compared with the winner at the point of "falling behind" (successive split times progressively slower than the winner), "letting go" (large increase in time for distance compared with winner), or "outsprinted" (falling behind despite active acceleration) despite being with the leader with 400m remaining. Race times ranged between 26:55 and 29:23 (world record = 26:17). There were 3 groups who fell behind at ∼1000 (n = 11), ∼6000 (n = 16), and ∼9000m (n = 2); let go at ∼4000 (n = 10), ∼7000 (n = 14), and ∼9500m (n = 5); or were outkicked (n = 6). There was a moderate correlation between CS and finishing position (r = .82), individual mean pace (r = .79), "fell behind" distance (r = .77), and "let go" distance (r = .79). D' balance was correlated with performance in the last 400 m (r = .87). Athletes displayed distinct patterns of falling behind and letting go. CS serves as a moderate predictor of performance and final placing. Final placing during the sprint is related to preservation of D' balance.

Variable success in linking micro- and macroevolution

Abstract Attempts to predict macroevolution from microevolution, and microevolution from macroevolution, when natural selection is the main cause have met with varying success. Explanations for failure are numerous, but the reasons are uncertain even when a link is found. Here, I discuss possible explanations for outcomes of three efforts and ways to test them. First, quantitative genetic variation within populations often predicts directions of species divergence with surprising accuracy. Natural selection probably contributes to this pattern, but the evidence suggests that even long-term phenotypic evolution is influenced by enduring genetic biases. Second, the rate of evolution of reproductive isolation repeatedly fails to predict species diversification rates for unknown reasons. Suspicion falls on the influence of ecological and population demographic processes that might play a dominant role in the net rate of accumulation of species, an idea as yet little tested. Third, macroevolutionary patterns in the distribution of phenotypes of species in clades can in principle predict selection coefficients in diverging populations. I use the concept of adaptive landscape to suggest why the macroevolutionary signal of divergent selection is strongest at the time of splitting and why little information about selection coefficients from phylogenetic methods remains in the long run. Estimating adaptive landscapes from first principles would facilitate further efforts to link microevolution and macroevolution.

The Effects of Neuromuscular Training on Sand Versus Hard Surfaces on Physical Fitness in Young Male Tennis Players.

To examine the effects of a neuromuscular training program combining plyometric exercises with acceleration, deceleration, and change-of-direction drillsconducted on sand or hard surfaces on the fitness qualities of young male tennis players. Thirty-one young male players were allocated to a training group performing 12 training sessions on sand or hard surfaces, during a 6-week period. Tests included linear sprint (10-m acceleration with 5-m split times), change of direction (modified 5-0-5 test), vertical jumps (countermovement jump and the 10/5 repeated-jump test), isometric hip abduction and adduction strength, and dynamic balance (Y-balance test). Perceived training loads and muscle soreness were assessed during the intervention. Both training strategies were similarly effective in improving the analyzed fitness components. Group × time interaction effects were noticed, with countermovement jump (P = .032), repeated-jump test (P = .029), and reactive strength index (P = .008) favoring hardsurfaces and 5-m sprint (P = .009), dynamic balance (P < .05), adduction strength (P < .05), and abduction strength (P < .001) indices favoring sand. Furthermore, the sand group promoted greater perceived training loads and muscle soreness (P < .05) than the hard group across the intervention period. Neuromuscular training strategies characterized by a relatively low volume (∼35min), conducted on sand or hard surfaces, promoted similar improvements in the fitness qualities of young tennis players, with selected surface-interaction effects. Training on sand can cause transiently higher training loads and persistently higher muscle soreness, suggesting the need for an adequate familiarization period.

The validity and reliability of a hydraulic resistance device for assessing resisted sprint time.

The aim of this study was to assess the validity and reliability of a hydraulic resistance device (HRD) for monitoring sprint split times under different loads within and between sessions. Three 20-m sprints with low (15 N), medium-low (40 N), medium-high (50 N), and high (130 N) HRD resistance levels (loads) were performed on two separate occasions 14 days apart. Twenty-four student athletes (24.8 ± 3.8 years) participated in the first session and 13 (24.1 ± 3.2 years) of them in the second session. Resisted sprints split times over a distance of 0-20 m (t0-5, t0-10, t0-20, t5-10, t10-15, t15-20) were measured simultaneously with magnetic incremental encoder embedded in the HRD and a system of single-beam timing gates. The results showed acceptable to high within session (ICC3,1 = 0.91-0.99; CV = 0.92%-3.38%) and between session (ICC3,1 = 0.82-0.99; CV = 1.62%-4.84%) reliability of HRD for measuring all split times at all loads. The minimal detectable change between sessions ranged from 3.3% at high load to 9.9% at low load. The HRD systematically underestimated timing gates times at all loads (bias = 2.01-11.08%), yet good to excellent consistency was observed between the HRD and timing gates, specifically for t0-10 and t0-20 (ICC3,k lower 95% CI = 0.84-0.99). Due to high reliability and good validity in monitoring resisted sprint times, the HRD holds potential for practical and research applications.

TRAM: A new non‐hydrostatic fully compressible numerical model suited for all kinds of regional atmospheric predictions

AbstractA new limited‐area numerical model (TRAM, for Triangle‐based Regional Atmospheric Model) has been built using a non‐hydrostatic and fully compressible version of the Navier–Stokes equations. Advection terms are solved using a Reconstruct–Evolve–Average (REA) strategy over the computational cells. These cells consist of equilateral triangles in the horizontal. The classical z‐coordinate is used in the vertical, allowing arbitrary stretching (e.g., higher resolution in the Planetary Boundary Layer, PBL). Proper treatment of terrain slopes in the bottom boundary conditions allows for accurately representing the orographic forcing. To gain computational efficiency, time splitting is used to integrate fast and slow terms separately and acoustic modes in the vertical are solved implicitly. For real cases on the globe, the Lambert map projection is applied, and all Coriolis and curvature terms are retained. No explicit filters are needed. The first part of the manuscript describes the dynamical core of the model and provides its thorough validation using a variety of benchmark tests (mostly in two dimensions) in the context of a dry‐adiabatic atmosphere. In the second part, TRAM is reformulated for a moist atmosphere and is completed with a proper set of physical parametrizations of cloud microphysics, cumulus convection, short and long‐wave radiation, PBL processes and surface fluxes. Various examples of the great versatility offered by this full version will be presented, with special emphasis on Mediterranean case studies. In summary, TRAM performs as well as state‐of‐the‐art numerical models and is suitable for simulating circulations ranging from small‐scale thermal bubbles (≈100 m scale) to synoptic‐scale baroclinic cyclones (&gt;1000 km size), including orographic circulations, thermally driven flows, squall lines, supercells, all kinds of precipitation systems and medicanes. Besides opening a myriad of academic and research applications, TRAM regional forecasts at different resolutions are being disseminated in the web (see https://meteo.uib.es/tram).

Vehicle routing problem simultaneous deliveries and pickups with split loads and time windows with genetic algorithm (case study in shipping company)

Vehicle routing problem simultaneous deliveries and pickups with split loads and time windows with genetic algorithm (case study in shipping company)

The pacing differences in performance levels of marathon and half-marathon runners.

Many studies indicate a considerable impact of optimal pacing on long-distance running performance. Given that the amount of carbohydrates in metabolic processes increases supralinearly with the running intensity, we may observe differences between the pacing strategies of two long-distance races and different performance levels of runners. Accordingly, the present study aimed to examine the differences in pacing strategies between marathon and half-marathon races regarding the performance levels of runners. The official results and split times from a total of 208,760 (marathon, N = 75,492; half-marathon, N = 133,268) finishers in the "Vienna City Marathon" between 2006 and 2018 were analyzed. The percentage of the average change of speed for each of the five segments (CS 1-5), as well as the absolute change of speed (ACS) were calculated. The CS 1-5 for the marathon are as follows: up to the 10th km, 10th - 20th km, 20th - 30th km, 30th - 40th km, and from the 40th km to the 42.195 km. For the half-marathon, the CS 1-5 are half of the marathon values. Four performance groups were created as quartiles of placement separately for sexes and races: high-level (HL), moderate to high-level (MHL), moderate to low-level (MLL), and low-level (LL). Positive pacing strategies (i.e., decrease of speed) were observed in all performance groups of both sex and race. Across CS 1-5, significant main effects (p < 0.001) were observed for the segment, performance level, and their interaction in both sex and race groups. All LL groups demonstrated higher ACS (men 7.9 and 6.05%, as well as women 5.83 and 5.49%, in marathon and half-marathon, respectively), while the HL performance group showed significantly lower ACS (men 4.14 and 2.97%, as well as women 3.16 and 2.77%, in marathon and half-marathon, respectively). Significant main effects (p < 0.001) for the race were observed but with a low effect size in women (ŋ2 = 0.001). Better runners showed more even pacing than slower runners. The half-marathoners showed more even pacing than the marathoners across all performance groups but with a trivial practical significance in women.

Effect of Different Levels and Times of Nitrogen Application on Grain and Forage Quality of Sweet Corn (Zea mays L. saccharata)

This field experiment conducted during the rabi season of 2017-18 at N. M. College of Agriculture, Navsari Agricultural University, Gujarat, aimed to investigate the response of sweet corn (Zea mays L. saccharata) to different levels and times of nitrogen application under the south Gujarat conditions. The factorial randomized block design (FRBD) with three replications was employed, considering four nitrogen levels (90 kg/ha, 120 kg/ha, 150 kg/ha, and 180 kg/ha) and four split application treatments (½ basal + ½ at knee height, ½ basal + ¼ knee height + ¼ tasseling, 1/3 basal + 1/3 knee height + 1/3 tasseling, and ¼ basal + ½ at knee height + ¼ tasseling). The results of the study demonstrated that the application of 180 kg/ha nitrogen significantly increased the protein content in grain and fodder (10.51% and 3.88% respectively) and total sugar content (14.96). Additionally, higher NPK uptake and available nitrogen (197.25 kg/ha) and phosphorus (47.53 kg/ha) levels were observed with a 180 kg/ha nitrogen application rate. When nitrogen was applied in three splits, specifically at ¼ basal + ½ at knee height + ¼ tasseling, it resulted in significantly higher protein content in grain and fodder (9.89% and 3.54% respectively), total sugar content (13.65), as well as NPK uptake in grain and fodder and available nitrogen and phosphorus (189.95 kg/ha and 45.84 kg/ha). These findings highlight the importance of nitrogen management in sweet corn cultivation to enhance the nutritional quality and productivity of both grain and fodder. Implementing the optimal nitrogen levels (180 kg/ha) and split application timings (¼ basal + ½ at knee height + ¼ tasseling) can contribute to achieving desirable protein and sugar content, as well as improving NPK uptake and availability of nitrogen and phosphorus.

Modeling the Early and Late Acceleration Phases of the Sprint Start in Elite Long Track Speed Skaters.

Zukowski, MH, Jordan, MJ, and Herzog, W. Modeling the early and late cceleration phases of the sprint start in elite long track speed skaters. J Strength Cond Res 38(2): 236-244, 2024-This study established the reliability of an exponential function to model the change in velocity during the speed skating sprint start and the validity of associated model parameters in a group of subelite and elite long track speed skaters. Long track speed skaters ( n = 38) performed maximal effort 50-m on-ice accelerations from a standing start while tethered to a horizontal robotic resistance device that sampled position and time data continuously. An exponential function was applied to the raw data to model the change in velocity throughout the acceleration phase and compute the maximal skating speed (MSS), maximal acceleration capacity (MAC), maximum relative net horizontal power ( PMax ), and an acceleration-time constant ( τ ). All constructed models provided a sufficient fit of the raw data ( R -squared > 0.95, mean bias <2%). Intraday reliability of all model parameters ranged from good to excellent (intraclass correlation coefficient >0.8 and coefficient of variation <5%). Strong negative correlations ( r : -0.72 to -0.96) were observed between MSS and PMax and the 10 and 20 m split times measured with the robotic resistance and with 100 split times obtained from 500 m races. Moderate-to-large between-group differences were observed in MSS, MAC, and PMax between the elite vs. subelite speed skaters (Cohen d effect sizes: 1.18-3.53). Our results indicate that monoexponential modeling is a valid and reliable method of monitoring initial acceleration performance in elite level long track speed skaters.

Droplet splitting on chemically heterogeneous surface: A 3D lattice Boltzmann study

The uniform splitting of droplets on heterogeneous surfaces without external stimuli has gained increasing attention due to its wide and flexible applications. To precisely control and predict the droplet splitting, the 3D multiphase lattice Boltzmann model (LBM) is used to study the mechanism of the impact splitting on a hydrophilic surface with a superhydrophobic strip. A parallel implementation of the 3D multiphase LBM is presented to improve the performance by using an effective kernel fusion to reduce the off-chip memory data traffic. Two splitting modes with single or double liquid bridge are contrasted and analyzed. The results show that the size of the air bubble trapped during the impacting process leads to various splitting modes. By calculating the unbalanced Young's force in the three-phase contact lines, unbalanced surface tension at the superhydrophobic/hydrophilic surface is observed. In addition, we find that the increase in the initial velocity of the drop can not only shorten the splitting time but also lead to a change in splitting mode. The increase in the wettability contrast of the surface can stably shorten the splitting time. However the splitting time did not linearly shorten with the increase in strip width. Our findings would advance the understanding of drop impact splitting and possibly inspire new guidance for the design of functional interfaces. The present study also provides an efficient parallel implementation to simulate the 3D droplet motion on heterogeneous surfaces.

Urea Split Application to Maize (Zea mays L.) Growth Stages of Medium Maturities, Influenced on Grain Yield and Parameter for Yield at Bako, East Wollega, Ethiopia

Appropriate timing of application can improve crop nutrient consumption efficiency. Maize production is still significantly below than its potential output, even though it is comparatively better than other main cereal crops. One of the main abiotic variables affecting crop growth is the timing of urea split application. Due to these gaps, an experiment was carried out at the Bako Agricultural Research Center during the 2019 and 2020 cropping seasons in order to ascertain the best time to apply urea split in order to maximize the yield and yield attributes of the maize varieties BH-546 and BH-547 in a study area and in countries with comparable agroecologies. Six levels of urea split application time (T1, T2, T3, T4, T5, and T6) were arranged in factorial combinations with two levels of maize varieties. In addition, a randomized complete block design with three replications was used for the previously advised urea split application. The harvest index of maize, grain yield, number of kernels per ear, ear dimension, and number of ears per plant all significantly differed depending on when nitrogen split administration occurred. Mean dry biomass, cob diameter, cob length, cob weight, and thousands seed weight of maize were all highly impacted by the interaction varietals and split time of nitrogen treatment. Compared to the previously recommended (1/2 dose at planting and 1/2 dose at knee height stage of maize), the time of N split application resulted in a significantly higher grain yield (9003.88 kg·ha−1): 1/4 dose at planting + 1/2 dose of N at knee height + 1/4 dose at tasseling of maize. However, three urea application regimes 1/4 dosage at planting time, 1/2 dose at knee height, and 1/4 dose of split application should be utilized in the event of irregular and intensely rainy seasons in order to maximize grain output and yield attributable.

Population genomic analysis unravels the evolutionary roadmap of pericarp color in rice

Pigmented rice stands out for its nutritional value and is gaining more and more attention. Wild rice, domesticated red rice, and weedy rice all have a red pericarp and a comprehensive genetic background in terms of the red-pericarp phenotype. We performed population genetic analyses using 5104 worldwide rice accessions, including 2794 accessions with red or black pericarps, 85 of which were newly sequenced in this study. The results suggested an evolutionary trajectory of red landraces originating from wild rice, and the split times of cultivated red and white rice populations were estimated to be within the past 3500 years. Cultivated red rice was found to feralize to weedy rice, and weedy rice could be further re-domesticated to cultivated red rice. A genome-wide association study based on the 2794 accessions with pigmented pericarps revealed several new candidate genes associated with the red-pericarp trait for further functional characterization. Our results provide genomic evidence for the origin of pigmented rice and a valuable genomic resource for genetic investigation and breeding of pigmented rice.

Anisotropic Velocity Structure Beneath Shikoku, Japan: Insights From Receiver Function and Shear Wave Splitting Analyses

AbstractA combination of receiver function (RF) analysis and shear wave splitting can reveal the anisotropic properties of the Earth's velocity structure. The RF profile exhibits harmonic patterns partially generated from the discontinuities of anisotropic media near the receiver. The anisotropic properties are determined using splitting parameters, which include the fast polarization direction (FPD) and split time. We utilized the seismograms recorded by stations on Shikoku Island, Japan. Also, we applied the Bayesian information criterion to control the spike count of each RF, which consists of a series of spikes generated by time‐domain iterative deconvolution. Anisotropic differences arose between northern and southern regions along the 30‐km iso‐depth line of the top surface of the Philippine Sea Plate. In the southern part of Shikoku Island, the FPDs are sub‐perpendicular to the plunge of the subducting slab, while in the northern part, they are sub‐parallel to the plunge of the slab. Our results indicate that anisotropic strengths are weaker in the tectonic‐tremor band in northwestern Shikoku and stronger in the northern part of central and eastern Shikoku around the no tectonic‐tremor area. These anisotropic variations may characterize Shikoku Island’s geological structure.

Effect of trade unions on the mental health of UK workers before and during the COVID-19 pandemic: a longitudinal analysis using Understanding Society data

BackgroundAlthough trade union membership rates have continuously decreased over the past 30 years, about 50% of UK employees are still represented by a union. Yet, studies on the association between collective bargaining and workers' mental health are sparse, especially in the pandemic context. This study examines differences on UK workers' mental health due to trade union presence and membership between pre-pandemic and pandemic periods. MethodsIn this longitudinal study, we analysed Understanding Society panel data in which the same participants are followed over time. The data concerned individuals aged 16 years and older and were collected biannually before COVID-19 pandemic (Waves 8–10: 2017–2020) and on a more frequent basis during pandemic (all COVID-19 surveys from 2020 [April, May, June, July, September, November] to 2021 [January, March, September] periods). The primary outcome was General Health Questionnaire-12 (GHQ-12) caseness (GHQ-12 score ≥4: probability of caseness). Two exposures were used separately: trade union presence and trade union membership, interacting with a binary variable splitting time periods between before and during the pandemic. Our analytical sample included 49 915 observations from 5988 individuals. 3341 (56%) individuals worked in unionised workplaces. We fitted mixed–effects logistic regression models adjusting for age, gender, ethnicity, UK residence, educational level, financial situation, workplace size, and survey interview date. We then replicated the analyses including a 3-way interaction with industry. All Understanding Society participants gave written informed consent. Ethics approval was not required. FindingsIn our sample, approximately 41% were male and 59% were female, and the mean age was 47·2 years (SD 11·4). Comparing pre-pandemic and pandemic periods, we found that the odds of GHQ-12 caseness for those in non-unionised workplaces increased by 45% (odds ratio 1·45, 95% CI 1·17–1·80), whereas in unionised workplaces odds increased by 28% (1·28, 1·05–1·57). When analysis was confined to unionised workplaces, the odds of GHQ-12 caseness for non-union members increased more (1·40, 1·07–1·83) compared with members (1·18, 0·91–1·53); however, with wide CIs. Overall, industry had no modification effect in both exposures. Sensitivity analysis using GHQ-36 as a continuous outcome demonstrated no real change in the patterns of the results. InterpretationThe mental health of workers in unionised workplaces appears to have worsened less than the mental health of those in non-unionised workplaces; however, there is insufficient evidence of effect differential by type of industrial sector. Designing policies that encourage and facilitate trade union presence in workplaces should be promoted, as they are likely to mitigate adverse mental health effects in times of extreme uncertainty. FundingMedical Research Council, Chief Scientist Office, Belgian National Scientific Fund.

COVID-19 lockdowns and working women's mental health: Does motherhood and size of workplace matter? A comparative analysis using understanding society

The COVID-19 pandemic had detrimental and unequal repercussions on mental health. To date there is little evidence exploring how motherhood and workplace size moderates this relationship for working women. This study aimed to estimate changes in working women's mental health at the start of each UK lockdown and estimate the effect of motherhood and workplace size on mental health. We used Understanding Society data from women in paid employment, who participated in at least: one pre-COVID-19 Wave (9 or 10/11) and one COVID-19 lockdown wave (Lockdown 1: April 2020, Lockdown 2: November 2020, Lockdown 3: January 2021). Primary outcome was probable psychological distress (i.e., score≥4 in the General Health Questionnaire-12 (GHQ-12)). In Model 1, exposure was motherhood (binary), interacting with a variable that split time in the pre-pandemic and lockdown periods. In Model 2, workplace size (Micro:1–24, Medium: 25–199, Large: More than 200 employees) was added as an exposure (3-way interaction) to investigate moderation effects. We fitted mixed–effects logistic regression models, adjusting for age, ethnicity, UK country of residence, cohabitation, educational qualifications, working hours, furlough, subjective financial difficulty and previous health condition. In the adjusted Model 1, pre-pandemic, odds of GHQ-12 caseness were lower for mothers compared to non-mothers (OR:0.89 95%CI:0.77,1.03). However post-pandemic compared to pre-pandemic, odds for mothers were higher than non-mothers, especially during lockdown 3 (Non-mothers: OR:1.93 95%CI:1.69,2.20; Mothers: OR:2.87 95%CI:2.36,3.49). In Model 2, workplace size did not modify the relationship. Pre-pandemic, there was no difference in the odds of GHQ-12 caseness by workplace size; however, the differences observed in Lockdown 3 between non-mothers and mothers, are mainly attributed to differences in medium-sized enterprises (Non-mothers: OR:1.95 95%CI:1.53,2.48; Mothers: OR:3.56 95%CI:2.54,4.99). Future policies should be designed to facilitate the working lives of mothers, but especially for medium-sized enterprises as extreme uncertainty appears to affect these employees more.

Mitochondrial genome characteristics of six Phylloscopus species and their phylogenetic implication.

The mitochondrial genomes of six Phylloscopus species-small insectivores belonging to the Phylloscopidae family-were obtained using the Illumina sequencing platform. The mitogenomes were closed circular molecules 16,922-17,007 bp in size, containing 13 protein-coding genes, 22 tRNA genes, two rRNA genes, and two control regions (CR1 and remnant CR2). The gene orders were conserved in 35 sampled Phylloscopus mitogenomes in the GenBank database, with a gene rearrangement of cytb-trnT-CR1-trnP-nad6-trnE-remnant CR2-trnF-rrnS. The average base compositions of the six Phylloscopus mitogenomes were 29.43% A, 32.75% C, 14.68% G, and 23.10% T, with the A+T content slightly higher than that of G+C. ATG and TAA were the most frequent initiating and terminating codons, respectively. Several conserved boxes were identified in CR1, including C-string in domain I; F, E, D, and C boxes, as well as bird similarity and B boxes, in domain II; and CSB1 in domain III. Tandem repeats were observed in remnant CR2 of the Phylloscopus fuscatus and Phylloscopus proregulus mitogenomes. A phylogenetic analysis with maximum likelihood (ML) and Bayesian inference (BI) methods, based on 13 protein-coding genes and two rRNA genes, indicated that the Phylloscopus species was divided into two larger clades, with a splitting time approximately 11.06 million years ago (mya). The taxa of Phylloscopus coronatus/Phylloscopus burkii and Phylloscopus inornatus/P. proregulus were located at the basal position of the different clades. The phylogenetic result of the cox1 gene showed that Seicercus was nested within Phylloscopus. The complete set of mitogenomes of the Phylloscopus species provides potentially useful resources for the further exploration of the taxonomic status and phylogenetic history of Phylloscopidae.

A Time Splitting Method for the Three-Dimensional Linear Pauli Equation

Abstract We analyze a numerical method to solve the time-dependent linear Pauli equation in three space dimensions. The Pauli equation is a semi-relativistic generalization of the Schrödinger equation for 2-spinors which accounts both for magnetic fields and for spin, with the latter missing in preceding numerical work on the linear magnetic Schrödinger equation. We use a four term operator splitting in time, prove stability and convergence of the method and derive error estimates as well as meshing strategies for the case of given time-independent electromagnetic potentials, thus providing a generalization of previous results for the magnetic Schrödinger equation.