Equal Sample Sizes Research Articles

Analysis of genotyping data reveals the unique genetic diversity represented by the breeds of sheep native to the United Kingdom

BackgroundSheep breeds native to the United Kingdom exhibit a striking diversity of different traits. Some of these traits are highly sustainable, such as seasonal wool shedding in the Wiltshire Horn, and are likely to become more important as pressures on sheep production increase in coming decades. Despite their clear importance to the future of sheep farming, the genetic diversity of native UK sheep breeds is poorly characterised. This increases the risk of losing the ability to select for breed-specific traits from native breeds that might be important to the UK sheep sector in the future. Here, we use 50 K genotyping to perform preliminary analysis of breed relationships and genetic diversity within native UK sheep breeds, as a first step towards a comprehensive characterisation. This study generates novel data for thirteen native UK breeds, including six on the UK Breeds at Risk (BAR) list, and utilises existing data from the publicly available Sheep HapMap dataset to investigate population structure, heterozygosity and admixture.ResultsIn this study the commercial breeds exhibited high levels of admixture, weaker population structure and had higher heterozygosity compared to the other native breeds, which generally tend to be more distinct, less admixed, and have lower genetic diversity and higher kinship coefficients. Some breeds including the Wiltshire Horn, Lincoln Longwool and Ryeland showed very little admixture at all, indicating a high level of breed integrity but potentially low genetic diversity. Population structure and admixture were strongly influenced by sample size and sample provenance – highlighting the need for equal sample sizes, sufficient numbers of individuals per breed, and sampling across multiple flocks. The genetic profiles both within and between breeds were highly complex for UK sheep, reflecting the complexity in the demographic history of these breeds.ConclusionOur results highlight the utility of genotyping data for investigating breed diversity and genetic structure. They also suggest that routine generation of genotyping data would be very useful in informing conservation strategies for rare and declining breeds with small population sizes. We conclude that generating genetic resources for the sheep breeds that are native to the UK will help preserve the considerable genetic diversity represented by these breeds, and safe-guard this diversity as a valuable resource for the UK sheep sector to utilise in the face of future challenges.

P-561 Clinical outcomes following PGT-M and PGT-SR cycles

Abstract Study question Are the clinical outcomes following PGT-M Superior to PGT-SR and do female carriers of SR have more favourable outcomes than male carriers? Summary answer PGT-SR group was associated with improved clinical outcomes compared to PGT-M group. A higher PR and LBR observed amongst PGT-SR female carriers compared to males. What is known already Pre-implantation genetic testing for monogenic disorders (PGT-M) involves the genetic screening of embryos prior to transfer, where two individuals are carriers or affected by a specific genetic condition. Pre-implantation genetic testing for structural rearrangement (PGT-SR), however, tests for embryos in individuals who are carriers of Robertsonian or reciprocal translocations. The aim of both screening tests is to avoid passing on a known genetic condition to an offspring, resulting in fatal outcomes including physical or mental disabilities. Some studies have demonstrated improved clinical outcomes following PGT-M compared to PGT-SR. However, there is limited understanding of why this may be the case. Study design, size, duration Retrospective study of 916 patients who underwent PGD (M/SR) cycles carried out between 2015 to 2022 at a single fertility centre. There were (n = 759) who underwent PGT-M and (n = 157) PGT-SR. Clinical outcomes: pregnancy (PR), clinical pregnancy (CPR) and live birth (LBR) were determined following transfer of either an unaffected/euploid, or carrier/euploid embryo after PGT-M and transfer of a balanced/euploid embryo following PGT-SR. Subgroup analysis compared cycles including PGT-SR female carriers (n = 55) with male carriers (n = 102). Participants/materials, setting, methods Data was collected from the medical database (IDEAS). The overall mean age at oocyte retrieval was 32.9 (SD 3.7) years. SPSS software was used to determine whether PR, CPR and LBR were statistically significant when the two groups were compared. student t-test where (p < 0.05) is statistically significant was applied. Main results and the role of chance Clinical outcomes for PGT-M vs PGT-SR were comparable and not statistically significant: PR (66% vs 69%; p = 0.310) CPR (60% vs 61%; p = 0.930), LBR (55% vs 59%; p = 0.359) respectively. PR (80% vs 63%; p = 0.02), CPR (69% vs 56%; p = 0.10) and LBR (69% vs 54%; p = 0.06) were superior following PGT-SR amongst female carriers (n = 44/55), compared to male carriers (n = 64/102) respectively. However, only the pregnancy rate was statistically significant when the female was the carrier. Quality of the blastocyst(s) transferred was also higher amongst PGT-SR cycles where the female was the carrier. Limitations, reasons for caution The sample size of the PGT-SR group for both male and female carriers were significantly lower compared to the PGT-M group. A larger and equal sample size is required in order to generalise findings. Wider implications of the findings The quality of the blastocyst transferred has a significant effect on clinical outcomes, despite the euploid status. Such findings can be used to counsel patients or couples who consider undergoing IVF for the purpose of PGT-M/SR genetic screening prior to embryo transfer. Trial registration number IRB-0001CRGH-CITY-FL-2024

Attributions of Sexual Assault: Effects of Victim and Perpetrator Stereotypes, Presentation Order, and Participant Characteristics.

Research on sexual assault has shown that victim, perpetrator, and participant characteristics can influence evaluations of an assault. However, the studies have not examined a possible main effect or interactions from respectively introducing the victim or perpetrator first in an assault description, and previous studies have used participant samples with little diversity. We conducted two studies with factorial between-groups designs that varied presentation order in addition to victim and perpetrator stereotypicality and then assessed the impacts on participants' judgments of sexual assault scenarios. We used the online marketplace Prolific to collect large, diverse samples of participants, and in the second study, we collected roughly equal sample sizes of individuals who identified as Black females/males and White females/males. Our results indicate that multiple factors-including victim and perpetrator stereotypicality, presentation order, and participants' gender identities-significantly influenced judgments of the sexual assault, and there were numerous interactions. The results provide strongest support for a spreading activation model in which each factor can influence a participant's judgment of the other factors and the overall scenario. As such, the findings may bear on the legal handling of sexual assault cases as well as suggesting how different presentation formats and emphases in media coverage may sway the court of public opinion.

Optimal sample size allocation for two-arm superiority and non-inferiority trials with binary endpoints.

The sample size of a clinical trial has to be large enough to ensure sufficient power for achieving the aim the study. On the other side, for ethical and economical reasons it should not be larger than necessary. The sample size allocation is one of the parameters that influences the required total sample size. For two-arm superiority and non-inferiority trials with binary endpoints, we performed extensive computations over a wide range of scenarios to determine the optimal allocation ratio that minimizes the total sample size if all other parameters are fixed. The results demonstrate, that for both superiority and non-inferiority trials the optimal allocation may deviate considerably from the case of equal sample size in both groups. However, the saving in sample size when allocating the total sample size optimally as compared to balanced allocation is typically small.

Comparing Causal Bayesian Networks Estimated from Data.

The knowledge of the causal mechanisms underlying one single system may not be sufficient to answer certain questions. One can gain additional insights from comparing and contrasting the causal mechanisms underlying multiple systems and uncovering consistent and distinct causal relationships. For example, discovering common molecular mechanisms among different diseases can lead to drug repurposing. The problem of comparing causal mechanisms among multiple systems is non-trivial, since the causal mechanisms are usually unknown and need to be estimated from data. If we estimate the causal mechanisms from data generated from different systems and directly compare them (the naive method), the result can be sub-optimal. This is especially true if the data generated by the different systems differ substantially with respect to their sample sizes. In this case, the quality of the estimated causal mechanisms for the different systems will differ, which can in turn affect the accuracy of the estimated similarities and differences among the systems via the naive method. To mitigate this problem, we introduced the bootstrap estimation and the equal sample size resampling estimation method for estimating the difference between causal networks. Both of these methods use resampling to assess the confidence of the estimation. We compared these methods with the naive method in a set of systematically simulated experimental conditions with a variety of network structures and sample sizes, and using different performance metrics. We also evaluated these methods on various real-world biomedical datasets covering a wide range of data designs.

Maintenance of different life stages of old-growth forest trees in deforested tropical landscapes.

Tropical tree species are increasingly being pushed to inhabit deforested landscapes. The habitat amount hypothesis posits that, in remaining forest patches, species diversity in equal-sized samples decreases with decreasing forest cover in the surrounding landscape. We tested this prediction by taking into account three important factors that can affect species responses to forest loss. First, forest loss effects can be linear (proportional) or nonlinear, as there can be threshold values of forest loss beyond which species extirpation may be accelerated. Second, such effects are usually scale dependent and may go unnoticed if assessed at suboptimal scales. Finally, species extirpation may take decades to become evident, so the effects of forest loss can be undetected when assessing long-lived organisms, like adult old-growth forest trees. Here, we evaluated the linear and nonlinear effects of landscape forest loss across different spatial scales on site-scale abundance and diversity of old-growth forest trees, separately for four plant-life stages (seeds, saplings, juveniles, and adults) in two rainforest regions with different levels of deforestation. We expected stronger (and negative) forest loss effects on early plant-life stages, especially in the region with the highest deforestation. Surprisingly, in 13 of 16 study cases (2 responses × 4 life stages × 2 regions), null models showed higher empirical support than linear and nonlinear models at any scale. Therefore, the species richness and abundance of local tree assemblages seem to be weakly affected by landscape-scale forest loss independently of the spatial scale, life stage, and region. Yet, as expected, the predictive power of forest cover was relatively lower in the least deforested region. Our findings suggest that landscape-scale forest loss is poorly related to site-scale processes, such as seed dispersal and seedling recruitment, or, at least, such effects are too small to shape the abundance and diversity of tree assemblages within forest patches. Therefore, our findings do not support the most important prediction of the habitat amount hypothesis but imply that, on a per-area basis, a unit of habitat (forest) in a highly deforested landscape has a conservation value similar to that of a more forested one, particularly in moderately deforested rainforests.

Effects of length-to-diameter ratio and strain rate on strain energy accumulation and dissipation in sandstone

To investigate the influence of the length-to-diameter (L/D) ratio and strain rate on the evolution of strain energy of sandstone under uniaxial compression, experimental tests were conducted using the RMT-150B rock mechanics test system. Specifically, uniaxial compression experiments (UCE), uniaxial loading-unloading experiment(ULUE) and uniaxial cyclic loading-unloading experiments (UCLUE) were performed. The results show that: 1) Based on an investigation of the Kaiser effect in UCLUE, it is postulated that a small degree of loading-unloading has negligible impact on the storage of strain energy in rock masses. The hypothesis regarding the limited influence of loading-unloading on the elastic strain energy storage of rocks is confirmed through a comparative analysis between the elastic strain energy storage in UCLUE and ULUE. 2) By analyzing the ESED and ISED of sandstone under different L/D ratios and strain rates, it is found that it follows the linear energy storage law. The evolution of elastic strain energy is not affected by strain rate. Therefore, the UCLUE at any strain rate can analyze the elastic strain energy of uniaxial compression experiment with the same size at any strain rate, and provide a new method for strain energy analysis at different length-diameter ratios and strain rates. 3) When the stress of sandstone samples of equal size is equal, the smaller the strain rate, the longer the loading experiment of sandstone, the more time the friction development and interconnection of cracks in sandstone are, and the more dissipated strain energy and input strain energy are generated. 4) Smaller L/D ratios are associated with larger ESED and DSED values in sandstone. As the stress intensifies, the ESED and DSED of certain sandstones with larger L/D ratios experience a sharp increase when approaching the failure stress. Under equal stress levels, it is possible for sandstones with larger L/D ratios to exhibit higher ESED and DSED values compared to those with smaller L/D ratios.

Usability of fractometer for the purpose of a practical preliminary assessment tool for wood density of Pinus brutia

The fractometer is a device that breaks increment cores to measure fracture strength. The advantages of the device are that it is relatively fast, easy to use in the field, and it can perform direct strength measurements on increment cores. The main purpose of the study was to evaluate the usability of the fractometer as a preliminary evaluation tool for wood density traits of standing Turkish Pinus brutia (red pine) trees. Fracture strength was measured on 5 mm diameter increment cores, and X-ray densitometry was used for density measurements. Due to the high correlation between the two traits (fracture and density), a model was built using linear regression. Fifty trees were sampled to build the statistical model (r2: 0,74), and an equal sample size was used to test the model. The density value obtained from the model was 0,546 gcm-3, while the density value averaged by the X-ray method for the same group was 0,543 gcm-3. When considering mean values, it can be said that the model provides a good prediction. Based on personal experience and research results, some trees exhibited better growth and wood quality traits than others. Breeding from these trees could offer improvement in timber production and performance for Pinus brutia (red pine). As a general consequence, the fractometer and increment core sampling can be used for pine tree breeding programs for the preliminary assessment of wood density.

Comparing the variances of several treatments with that of a control treatment: Theory and applications.

A common and important problem in medicine, economics and environmental studies is the comparison of the variances of several treatments with that of a control treatment. Among the existing methods, Spurrier's optimal test based on multivariate F distribution has exact type I error rates. However, it requires equal sample sizes among the treatment groups. To extend the application scope, in this paper, we propose a new efficient test for comparing several variances with a control using the marginal inferential model (MIM). Simulation studies show that the MIM test guarantees the exact type I error rate whether the sample size is equal or unequal. Moreover, the power of the MIM test is competitive with that of Spurrier's optimal test. Finally, two real examples are used to demonstrate the application of the proposed method.

Comparison of Test Statistics for Mean Difference Testing Between Two Independent Populations

The purpose of the article is to evaluate the efficiency of seven test statistics for mean difference testing between two independent populations. The evaluation was based on the probability of type I error and power of the test at 0.05 significance level under population distributions assumed to be normal, exponential, log-normal, gamma, and Laplace with equal sample sizes, and both equal and unequal variances. The results showed that for equal variance, the test statistics with the highest testing power controlled the probability of type I error were Z-test for normal and exponential distributions, Welch based on rank test (WBR) for log-normal and gamma distributions, and Mann-Whitney U test (MWU) for Laplace distribution. For unequal variance, Z-test was more efficient under normal, exponential, log-normal, and gamma distributions, while WBR was appropriate for Laplace distribution.

Financing policy of large listed family businesses: Evidence from the Arab world

This paper aims to contribute to the literature on the capital structure and financing behavior of large listed family businesses by examining the differences and/or similarities in the determinants influencing the financing policy in the Arab world. The study focuses on two samples of equal size, consisting of 103 large listed family firms and 103 large listed non-family firms, covering the period from 2013 to 2019. Through a quantitative analysis of panel data, the research investigates the level of indebtedness and its determinants in these two categories of firms. The findings of this study reveal significant differences in the financing patterns between large listed family and non-family firms. These findings contribute to our understanding of the unique characteristics and preferences of large listed family firms in the Arab world, a region that has received limited attention in previous studies (Basly, 2017). By exploring this developing and relatively unexplored region, the study fills a gap in the literature and expands our knowledge of the capital structure dynamics within large listed family businesses

Elevated secretion of pro-collagen I-alpha and vascular endothelial growth factor as biomarkers of acetabular labrum degeneration and calcification in hip osteoarthritis: An explant study

BackgroundHip osteoarthritis (OA) involves structural degeneration of different joint compartments, including femoral head cartilage, periarticular ligaments and the acetabular labrum. However, the molecular mechanisms underlying labrum degeneration in hip OA remain poorly understood. AimTo assess secretion of putative biomarkers for OA from explanted human labrum tissues under basal and inflammatory conditions and to determine whether these could differentiate between OA and calcification status compared to fracture controls. MethodsIntact labrum specimens were collected from patients undergoing joint arthroplasty for primary hip OA (n ​= ​15, mean age 70) or non-OA femoral neck fracture (n ​= ​5, mean age 64). Tissues were dissected in equal-sized samples and explanted for one week. To mimic activation of inflammatory signaling by endogenous damage-associated molecular patterns (DAMP) tissue were stimulated with a toll-like receptor 4 (TLR4) agonist (1 ​μg/mL LPS). The involvement of transforming growth factor-beta (TGF-beta) signaling was evaluated by treatment with a TGF-beta type 1 receptor inhibitor (10 ​μM SB-505124). Secretion of aggrecan (ACAN), pro-collagen-I alpha (Pro-Col-Iα), cartilage oligomeric matrix protein (COMP), interleukin-6 (IL-6) and vascular endothelial growth factor (VEGF) was assessed by enzyme-linked immunosorbent assay (ELISA). Labrum calcification was evaluated by 3D whole mount fluorescent microscopy of ethyl cinnamate-based optically cleared tissues stained with Alcian blue/Alizarin red. ResultsWhole mount microscopy revealed non-OA fracture controls were non-calcified, whereas six OA labra (40%) were partially calcified or ossified. Basal secretion of Pro-Col-Iα and VEGF was increased four-fold in OA versus non-OA labra. Pro-Col-Iα levels were correlated with those of VEGF (r ​= ​0.65) and COMP (r ​= ​0.54). Stimulation of DAMP signaling through TLR4 affected secretion of IL-6, VEGF, COMP and Pro-Col-Iα, with distinct responses between non-OA and OA tissues. Inhibition of TGF-beta signaling specifically reduced elevated secretion of Pro-Col- Iα and VEGF in calcified OA labrum. ConclusionsSecretion of the putative OA biomarkers Pro-Col-Iα and VEGF is elevated in degenerated human acetabular labrum and may serve as indicators of OA and calcification status. Secretion of both factors was partially regulated by TGF-beta signaling in calcified OA labrum tissues.The Translational potential of this article:Our findings suggest that a biomarker panel consisting of Pro-Col-Iα/VEGF/COMP may be valuable for assessing subradiographic labrum degeneration and calcification in hip OA. Targeting TGF-beta signaling may offer a means to reduce vascular invasion and fibrosis in acetabular labrum tissue.

Knowledge and Attitude about Radiation Hazards on Pregnant Women Among Non-Healthcare Students in Universiti Sultan Zainal Abidin (UniSZA)

Lack of awareness on radiation exposure during pregnancy in Malaysia can lead to a higher possibility of rejection from pregnant women to undergo an examination using ionizing radiation. This study aims to assess the general knowledge and attitude regarding radiation hazards on pregnant women among students at Universiti Sultan Zainal Abidin (UniSZA). A cross-sectional study was conducted among non-healthcare students in UniSZA. A questionnaire was distributed online using Google Form to assess knowledge and attitude of radiation hazards on pregnant women. Descriptive statistics and Independent T-test were used to determine the knowledge and attitude of the respondents. A total of 120 students have participated in this study. Equal sample sizes are obtained with 60 male students and 60 female students. The total mean knowledge and attitude score for all students is 1.31 and 4.13 respectively. The mean knowledge of female students (M=24.27) (P < .05) was higher compared to male students (M=20.20) (P < .05). Mean attitude of female students (M=17.40) (P < .05) was higher compared to male students (M=15.65) (P < .05). Female students have higher knowledge and attitude towards radiation hazards on pregnancy compared to male students. Lack of knowledge and attitude on radiation hazards on pregnancy can give serious effects in the future. Continuous awareness campaigns on the benefits and risks of radiation must be held through various platforms to educate people regarding the radiation hazards on pregnant women.

Quality Control Using Convolutional Neural Networks Applied to Samples of Very Small Size

Abstract Artificial neural networks (NNs) have been extensively studied for their application to quality control (QC) to monitor the conformity of processes to quality specifications. However, the requirement of at least five QC measurements increases the associated costs. This study explores the potential of using NNs on samples of QC measurements of very small size. To achieve this, three one-dimensional (1-D) convolutional NNs (CNNs) were designed, trained, and tested on datasets of n-tuples of simulated, standardized, normally distributed QC measurements, where 2 ≤ n ≤ 4 {2\leq n\leq 4} . The performance of the designed CNNs was compared to that of statistical QC functions applied to samples of equal sizes, maintaining equal probabilities for false rejection. The results demonstrated that for n-tuples of QC measurements distributed as 𝒩 ⁢ ( 0 , s 2 ) \mathscr{N}(0,s^{2}) , where 1.2 < s ≤ 9.0 1.2<s\leq 9.0 , the designed CNNs outperformed their statistical QC functions counterparts. Therefore, the use of 1-D CNNs applied to samples of two to four QC measurements can effectively enhance the detection of nonconformity of a process to quality specifications. This approach has the potential to significantly reduce the costs of QC measurements and improve the overall efficiency of the QC process.

A higher dysregulation burden of brain DNA methylation in female patients implicated in the sex bias of Schizophrenia.

Sex differences are pervasive in schizophrenia (SCZ), but the extent and magnitude of DNA methylation (DNAm) changes underlying these differences remain uncharacterized. In this study, sex-stratified differential DNAm analysis was performed in postmortem brain samples from 117 SCZ and 137 controls, partitioned into discovery and replication datasets. Three differentially methylated positions (DMPs) were identified (adj.p < 0.05) in females and 29 DMPs in males without overlap between them. Over 81% of these sex-stratified DMPs were directionally consistent between sexes but with different effect sizes. Females experienced larger magnitude of DNAm changes and more DMPs (based on data of equal sample size) than males, contributing to a higher dysregulation burden of DNAm in females SCZ. Additionally, despite similar proportions of female-related DMPs (fDMPs, 8%) being under genetic control compared with males (10%), significant enrichment of DMP-related single nucleotide polymorphisms (SNPs) in signals of genome-wide association studies was identified only in fDMPs. One DMP in each sex connected the SNPs and gene expression of CALHM1 in females and CCDC149 in males. PPI subnetworks revealed that both female- and male-related differential DNAm interacted with synapse-related dysregulation. Immune-related pathways were unique for females and neuron-related pathways were associated with males. This study reveals remarkable quantitative differences in DNAm-related sexual dimorphism in SCZ and that females have a higher dysregulation burden of SCZ-associated DNAm than males.

Mixed Bootstrap-Marascuilo test for testing equality of means under unequal variances in a completely randomized design

This study introduces a pioneering statistical methodology, the Mixed Bootstrap-Marascuilo test, which emerges from the fusion of the Bootstrap method and the Marascuilo test. The test examines the means of three or more populations with unequal variances in a completely randomized design. The research compares the Mixed Bootstrap-Marascuilo test's ability to control the probability of type I error using Cochran's criteria and its test power using penalized power with those of One-Way ANOVA and the Marascuilo test. The research design thoughtfully encompasses three populations: small, medium, and large, each exhibiting variations in size and equality. It systematically manipulates variances, encompassing a range from equal to slightly different, moderately different, and significantly different. Furthermore, the error distribution is specified to be normal with a designated mean. The research methodology embraces the utilization of R ver.4.2.2 and the Monte Carlo technique, leveraging 5,000 simulations per case to ensure the robustness and reliability of the study's findings. The outcomes of the comprehensive analysis yield intriguing insights. The results indicate that the Mixed Bootstrap-Marascuilo test exhibits superior testing ability in scenarios involving equal small sample sizes with equal and moderate variances, as well as medium sample sizes with equal and small variances. Furthermore, it demonstrates effectiveness even when dealing with large, unequal sample sizes with equal and large variances. In essence, this research advances the realm of statistical hypothesis testing through the introduction and meticulous evaluation of the Mixed Bootstrap-Marascuilo test. Its demonstrated ability to navigate complexities in mean examination across diverse populations, coupled with its versatile applicability to scenarios of unequal variances and varying sample sizes, underscores its potential as a valuable tool for researchers across disciplines.

Sample coverage estimation, rarefaction, and extrapolation based on sample-based abundance data.

Sample coverage, the proportion of individuals that belong to observed species in a sample, is a metric used to measure the completeness of a sample. Rather than using equal sample sizes, equal sample coverage has become a widely accepted standard for comparing diversity across multiple assemblages, resulting in a more accurate representation of the true relationship between the richness of the assemblages. In practice, sample-based abundance data are the most frequently used data type for evaluating species diversity. In sample-based abundance data, the sampling unit (e.g., a plot, net, trap, or transect) is randomly selected from the target area, and the number of individuals for each species observed in the sampled unit is recorded. In this case, the individuals in the sample are no longer randomly and independently sampled, and the Good-Turing estimators of abundance-based sample coverage in reference, rarefied, and extrapolated samples may be severely biased when individuals present a highly spatially aggregated pattern. Here, I derive a novel estimator of abundance-based sample coverage based on the Good-Turing frequency formula. Additionally, a new analytical approach is introduced for enabling smooth coverage-based rarefaction and extrapolation to compare richness among assemblages. The near unbiasedness of the proposed estimator and a less biased richness ratio achieved using the newly developed coverage-based standardizing approach are demonstrated by analyzing three ForestGEO permanent forest plot data sets.

Waste Recycling: Waste to Energy System

The current economic growth trend of increased urbanization has resulted in huge amounts of municipal waste and energy consumption. Many emerging countries, such as Iraq, suffer from the worsening of such a problem. Thus, an adequate municipal waste management system and the innovation of renewable energy alternatives are the fundamental issues that need to be addressed. Two test rigs were used in this study: the first separates waste based on the principle of gravity and the difference in density between the constituent elements of the waste, The test rig consists of a conveyor belt (0.5 meter) width and (1.5 meter) length with variable height and speed that throws the waste into special containers to separate the waste. The study suggested taking samples of equal size (1 cm3) for all elements and showing the effect of the sampling process on the separation methods approved by the test rig. The second is a laboratory test rig that analyzes waste and produces combustible gas, thus producing thermal energy. The main components of the rig are a digester (0.4 meter diameter - 0.64 meter height), a calorimeter, and several other components. The data analysis method developed by Japanese scientist Takeuchi was used to analyze the results of the first test rig's experimental work. The main results of this analysis showed that the height is (0.67 meter), the speed is (1.9 meter/second), and the distance of the samples falling ranges from about (0.53 meter) to (0.58 meter). The significant findings of the current study for the second test rig are obtained for the amount of thermal energy and measured using a calorimeter, and it was found that the highest value of energy was obtained on the 23 day of the start of the fermentation process; the amount was (10752.88 Jules) in the second experimental test.

Ensemble average method for runtime saving in Large Eddy Simulation of free and Ducted Fuel Injection (DFI) sprays

Computational Fluid Dynamics (CFD) with Large Eddy Simulation (LES) turbulence model is a valuable tool to investigate complex problems. However, for high Reynolds number problems, the associated huge computational cost often leads researchers to the use of more simplified and less accurate approaches, especially if statistics is needed for the generalization of the results and comparison against experimental data. Therefore, the introduction of innovative methodologies to reduce the computational cost maintaining results reliability would be of paramount importance for LES-based investigation.In this context, the aim of this work is to assess a runtime saving methodology to ensemble average several axial symmetric spray simulations obtained with LES. In particular, the number of independent samples for the average procedure has been increased by exploiting the axial symmetry characteristics of a diesel spray case study, extracting more realizations from a single simulation. This ensemble average approach was compared with the standard one, based on one realization per simulation, at equal statistical sample size. Main spray physical quantities and turbulence characteristics were examined, both globally and locally. The same procedure was also applied to a different diesel-relevant spray configuration, known as ducted fuel injection.The reliability of this ensemble average methodology has been herein proven for both spray configurations, highlighting a dramatic runtime saving without any worsening of the accuracy level. In particular, this approach, as applied in this work, guaranteed a computational cost reduction of 50–75%. Thereby, the present methodological assessment could motivate researchers involved in the investigation of spray processes to undertake the path of statistically significant LES analysis.

Quantifying annual spatial consistency in chick-rearing seabirds to inform important site identification

Animal tracking has afforded insights into patterns of space use in numerous species and thereby informed area-based conservation planning. A crucial consideration when estimating spatial distributions from tracking data is whether the sample of tracked animals is representative of the wider population. However, it may also be important to track animals in multiple years to capture changes in distribution in response to varying environmental conditions. Using GPS-tracking data from 23 seabird species, we assessed the importance of multi-year sampling for identifying important sites for conservation during the chick-rearing period, when seabirds are most spatially constrained. We found a high degree of spatial overlap among distributions from different years in most species. Multi-year sampling often captured a significantly higher portion of reference distributions (based on all data for a population) than sampling in a single year. However, we estimated that data from a single year would on average miss only 5 % less of the full distribution of a population compared to equal-sized samples collected across three years (min: −0.3 %, max: 17.7 %, n = 23). Our results suggest a key consideration for identifying important sites from tracking data is whether enough individuals were tracked to provide a representative estimate of the population distribution during the sampling period, rather than that tracking necessarily take place in multiple years. By providing an unprecedented multi-species perspective on annual spatial consistency, this work has relevance for the application of tracking data to informing the conservation of seabirds.