Unimodal Distribution Research Articles

Quantitative Microstructure Prediction of Powder High-Temperature Alloy during Solution Heat Treatment and Its Validation

Heat treatment, particularly solution heat treatment, is a critical process in the preparation of powder metallurgy superalloys, where the cooling process significantly impacts the microstructure. This study, based on thermodynamic and kinetic databases as well as the precipitation mechanism of strengthening phases, delves into the influence of cooling process, especially the cooling path, on the material’s microstructure. The results indicate that under slow cooling rates, the precipitated phases are more likely to exhibit a multimodal size distribution, while under rapid cooling rates, a unimodal distribution may form. The average cooling rate does not consistently accurately reflect the growth of the precipitated phases; even with the same average cooling rate, different cooling paths can lead to significant differences in the size of the precipitates. To accurately predict the size of the precipitates, it is necessary to consider the specific cooling process. Constant cooling rate experiments designed for the study and the dissection testing of full-size turbine discs produced in manufacturing validated the calculated results of the precipitates. Therefore, optimizing cooling through simulation calculations can effectively and accurately control the precipitates, thereby obtaining a microstructure that can meet performance requirements.

Oligomer Formation by Physiologically Relevant C-Terminal Isoforms of Amyloid β-Protein.

Alzheimer's disease (AD) is a neurological disorder associated with amyloid β-protein (Aβ) assembly into toxic oligomers. In addition to the two predominant alloforms, Aβ1-40 and Aβ1-42, other C-terminally truncated Aβ peptides, including Aβ1-38 and Aβ1-43, are produced in the brain. Here, we use discrete molecular dynamics (DMD) and a four-bead protein model with amino acid-specific hydropathic interactions, DMD4B-HYDRA, to examine oligomer formation of Aβ1-38, Aβ1-40, Aβ1-42, and Aβ1-43. Self-assembly of 32 unstructured monomer peptides into oligomers is examined using 32 replica DMD trajectories for each of the four peptides. In a quasi-steady state, Aβ1-38 and Aβ1-40 adopt similar unimodal oligomer size distributions with a maximum at trimers, whereas Aβ1-42 and Aβ1-43 oligomer size distributions are multimodal with the dominant maximum at trimers or tetramers, and additional maxima at hexamers and unidecamers (for Aβ1-42) or octamers and pentadecamers (for Aβ1-43). The free energy landscapes reveal isoform- and oligomer-order specific structural and morphological features of oligomer ensembles. Our results show that oligomers of each of the four isoforms have unique features, with Aβ1-42 alone resulting in oligomers with disordered and solvent-exposed N-termini. Our findings help unravel the structure-function paradigm governing oligomers formed by various Aβ isoforms.

Hydrogen bond symmetrisation in D2O ice observed by neutron diffraction

Hydrogen bond symmetrisation is the phenomenon where a hydrogen atom is located at the centre of a hydrogen bond. Theoretical studies predict that hydrogen bonds in ice VII eventually undergo symmetrisation upon increasing pressure, involving nuclear quantum effect with significant isotope effect and drastic changes in the elastic properties through several intermediate states with varying hydrogen distribution. Despite numerous experimental studies conducted, the location of hydrogen and hence the transition pressures reported up to date remain inconsistent. Here we report the atomic distribution of deuterium in D2O ice using neutron diffraction above 100 GPa and observe the transition from a bimodal to a unimodal distribution of deuterium at around 80 GPa. At the transition pressure, a significant narrowing of the peak widths of 110 is also observed, attributed to the structural relaxation by the change of elastic properties.

Bayesian modal regression based on mixture distributions

Compared to mean regression and quantile regression, the literature on modal regression is very sparse. A unifying framework for Bayesian modal regression is proposed, based on a family of unimodal distributions indexed by the mode, along with other parameters that allow for flexible shapes and tail behaviors. Sufficient conditions for posterior propriety under an improper prior on the mode parameter are derived. Following prior elicitation, regression analysis of simulated data and datasets from several real-life applications are conducted. Besides drawing inference for covariate effects that are easy to interpret, prediction and model selection under the proposed Bayesian modal regression framework are also considered. Evidence from these analyses suggest that the proposed inference procedures are very robust to outliers, enabling one to discover interesting covariate effects missed by mean or median regression, and to construct much tighter prediction intervals than those from mean or median regression. Computer programs for implementing the proposed Bayesian modal regression are available at https://github.com/rh8liuqy/Bayesian_modal_regression.

Pore Structure Characterization and Fractal Characteristics of Tight Limestone Based on Low-Temperature Nitrogen Adsorption and Nuclear Magnetic Resonance

Pore structure characterization and fractal analysis have great significance for understanding and evaluating tight limestone reservoirs. In this work, the pore structure of tight limestone, low-temperature nitrogen adsorption (LTNA), and low-field nuclear magnetic resonance (NMR) are characterized, and the fractal dimension of the pore structure of tight limestone is discussed based on LTNA and NMR data. The results indicate that the pores of tight limestone have H3 and H4 types, the pore size distribution (PSD) of the H3 type is a wave distribution ranging from 2 to 10 nm, and the PSD of the H4 type is a unimodal distribution ranging from 2 to 10 nm. The transverse relaxation time (T2) spectrum of tight limestone shows a single peak (DF), double peak (SF), and triple peak (TF), and the ranges for the T2 spectra for micropores, mesopores, and macropores are 0.1 to 10 ms, 10 to 100 ms, and greater than 100 ms, respectively. The LTNA fractal dimension of tight limestone (DL) ranges between 2.4446 and 2.7688, with an average of 2.5729, and the NMR fractal dimensions of micropores (DNMR1), mesopores (DNMR2), and macropores (DNMR3) are distributed between 0.3744 and 1.1293, 2.4263 and 2.9395, and 2.6582 and 2.9989, respectively. Moreover, there is a negative correlation between DL and average pore radius, a positive correlation between DL and specific surface area, and a positive correlation between DNMR2 and DNMR3 and micropore content, while DNMR2 and DNMR3 are negatively correlated with the content of mesopores and macropores.

Porous ZrO2–ZrO2 ceramics with excellent mechanical strength and permeability for transpiration cooling

AbstractThe great development of transpiration cooling technology challenges the coolant medium seriously. In this paper, porous ZrO2–ZrO2 ceramics have been satisfactorily prepared to meet the requirements of the coolant medium in transpiration cooling. The results illustrate that porous ZrO2–ZrO2 ceramics have excellent compressive strengths; meanwhile, percentages of compressive strength difference (parallel and perpendicular to the mold‐pressing direction) have an upward trend due to the increasing fiber contents. Besides, the failure mode has a huge distinction between parallelity (45° oblique section) and perpendicularity (wedge shape). These ceramics have unimodal pore size distribution (2–10 µm), and their wettability has a substantial improvement reflected by contact angle from 118° to 0°. Permeability behavior across these ceramics has been accurately described using the Darcy–Forchheimer equation, while obtaining viscous and inertial resistance coefficients, respectively. This work can provide an essential reference for coolant medium in transpiration cooling.

Regional disparities in the European Union. A machine learning approach

We investigate the hypothesis of regional convergence in the per-capita GDP in 242 European regions (NUTS2) during the 2000–2021 period. The literature shows mixed results, from absolute convergence towards a joint long-run distribution to multiple regimes (convergence club). Our results show a broad convergence to an unimodal distribution. Although the GDP distribution was characterized by a twin-peak property in 2000, it tends to disappear over time, bringing, in 2021, to an unimodal distribution. Physical and human capital is the most responsible for the convergence process and the EU cohesion funds. To empirically investigate the question, we first apply alternative techniques of cluster identification. Later, we assess whether clusters and covariates affect the per-capita GDP. We use a novel machine learning algorithm (GPBoost) instead of the more traditional techniques used in the current literature. The results show that a convergence process is at work; physical and human capital are mainly responsible for the gdp explanation. but eu funds play a relevant role as well. moreover, complementarities do exist among these variables.

Sports and Recreation-Related Wrist Fractures: An Epidemiological Study.

Background Wrist fractures have increased over the past several decades. The objective of this study was to identify all-cause and sports-related incidence rates of wrist fractures presenting to emergency departments (EDs) in the United States (U.S.) from 2013 to 2022. A secondary aim of the study was to identify if wrist fractures significantly decreased during 2020. Methodology The National Electronic Injury Surveillance System database was queried to identify the number of wrist fractures presenting to U.S. EDs from 2013 to 2022. Incidence rates in 100,000 person-years were calculated by sport, age, sex, and year. Results From 2013 to 2022, there were 2,027,131 wrist fractures evaluated at U.S. EDs. Injuries peaked in the 10-14-year-old age group, followed by the 5-9 and 85+-year-old age groups. In total, 1,096,598 were sustained during sports and recreation. Cycling, playgrounds, and skateboarding were the leading sports and recreation-related activities. Sports-related wrist fractures followed a unimodal distribution peaking in the 10-14-year-old age group. Females sustained 52% of wrist fractures overall but only 39% of sports-related wrist fractures. All-terrain vehicle and skateboarding-related wrist fractures significantly increased over the study period. Playground and soccer-related wrist fractures significantly decreased in 2020. Conclusions All-cause wrist fractures presenting to U.S. EDs significantly increased from 2013 to 2022 though sports-related wrist fractures did not. Pediatric males and elderly females are most at risk for wrist fractures overall while sports-related wrist fractures predominate in the pediatric population. Youth sports and recreation officials should be aware of the risks to mitigate the incidence of sports-related wrist fractures.

Distributional Learning and Overnight Consolidation of Nonnative Tonal Contrasts by Tonal Language Speakers.

Previous studies have reported the success of distributional learning for adult speakers across segmental and suprasegmental categories immediately after training. On the other hand, second language (L2) perception models posit that the ease with which learners perceive a nonnative speech contrast depends on the perceptual mapping between the contrast and learners' first language (L1) categories. This study examined whether a difference in perceptual mapping patterns for different L2-Mandarin tonal contrasts might result in a difference in distributional learning effectiveness for tonal speakers and whether an interval of sleep enhanced the knowledge through consolidation. Following a pretest-training-posttest design, 66 L1-Cantonese participants with fewer than 9 years of Mandarin training were assigned to either the bimodal or unimodal distribution conditions. The participants of each group were asked to discriminate Mandarin level-falling (T1-T4) and level-rising (T1-T2) tone pairs on novel syllables in a within-subject design. All participants were trained in the evening, tested after training, and returned after 12 hr for overnight consolidation assessment. A significant distributional learning effect was observed for Mandarin T1-T4, but only after sleep. No significant distributional learning effect was observed for Mandarin T1-T2, either after training or after sleep. The findings may imply that distributional learning is contingent on perceptual mapping patterns of the target contrasts and that sleep may play a role in the consolidation of knowledge in an implicit statistical learning paradigm. https://doi.org/10.23641/asha.25970008.

Genotype and epidemiological characteristics of human metapneumovirus among hospitalized cases of acute respiratory infection in children in Changchun City, Jilin Province from 2019 to 2023

Objective: To investigate the genotype and epidemiological characteristics of human metapneumovirus (HMPV) among hospitalized cases with acute respiratory infections (ARI) in children in Changchun City, Jilin Province, China. Methods: From June 2019 to June 2023, throat swabs of ARI inpatients in Changchun Children's Hospital were collected, and their epidemiological and clinical information were also collected. Quantitative reverse transcription-PCR was used to identify HMPV-positive cases, followed by the amplification of the G gene and genetic analysis in the HMPV-positive cases. Results: A total of 3 311 children hospitalized with ARI were included in this study. Their age ranged from 0 to 17 years old, and the M (Q1, Q3) of age was 2 (1, 3) years. About 1 811 (54.70%) cases were males. A total of 167 HMPV-positive cases were detected with a positive rate of 5.04%, of which 92.81% (155/167) were children under 5 years old. The positive rate of HMPV in 2019 was 6.37% (30/471), which dropped to the lowest in 2020 (2.31%, 10/432). The HMPV-positive rate was then rebounded in 2021 (4.70%, 60/1 277) and 2022 (4.56%, 21/461), which increased to 6.87% (46/670) in 2023. The difference in HMPV-positive rate among each year was statistically significant (P<0.05). The prevalence peak of HMPV varied in different years, showing either a unimodal or bimodal distribution in one year. A total of 79 HMPV G gene sequences were obtained, of which subtype A and subtype B accounted for 48.10% and 51.90%, respectively. All of the subtype A sequences were clarified as A2c duplicated variants, and subtype B was mainly B2 genotype. Besides, subtypes A and B were prevalent alone or co-circulated in different years, and there was a subtype replacement pattern in HMPV. Conclusion: The positive rate of HMPV in hospitalized ARI cases in children is significantly different from 2019 to 2023 in Changchun City. Notably, there are certain switch patterns of HMPV subtypes A and B in different years.

Mitochondrial DNA evidence reflects high genetic divergence of Amynthas aspergillum (Oligochaeta: Megascolecidae) in southern China.

Amynthas aspergillum (Perrier, 1872), a natural resource used in traditional Chinese medicine (Guang-dilong) with high economic value, is widely distributed in forests and farmland habitats in the hilly areas of southern China. To investigate the extent of genetic differentiation and diversity in A. aspergillum, a population genetic structure study was performed on 157 samples from 75 locations in southern China using the mitochondrial genes COI, COII, 12S rRNA, 16S rRNA, and NDI. The results indicated that A. aspergillum had a high level of genetic diversity, and variation within populations was the main source of the total variation. Six deeply divergent mitochondrial clades (I-VI) were detected using both phylogenetic tree and haplotype network analyses. This finding was supported by the high Kimura two-parameter genetic distance and the pairwise fixation index value obtained based on the COI gene. No significant phylogeographic structures were observed. The widespread geographic distribution of clades II, IV, and VI suggested a recent demographic expansion based on multiple analysis results. These results include a high level of Hd and low π, star-shaped haplotype network structures with a high number of less frequent haplotypes, significantly negative neutrality test values, and a unimodal mismatch distribution pattern. The divergence time estimates and reconstruction of the ancestral area revealed that A. aspergillum originated in Guangxi Province and underwent initial intraspecific diversification in the early Pliocene to generate clade I. Then, it gradually dispersed eastward and rapidly differentiated into clades II-V during the Pleistocene. The Yunnan-Guizhou Plateau and Nanling and Wuyi Mountains might act as geographical barriers for the spread of A. aspergillum to the west and north.

Mode mixture of unimodal distributions for insurance loss data

Mode mixture of unimodal distributions for insurance loss data

Particle filter performance of soot-loaded diesel particulate filter and the effect of its regeneration on the particle number and size distribution

The DPF regeneration is crucial for reducing backpressure, minimizing negative impacts on engine power and fuel economy, but the changes in particulate emission characteristics it brings are worth studying. In this study, the influence of DPFs with different soot loadings on exhaust back pressure and particle emission characteristics, as well as the particle number emission, particle size distribution, and thermal field distribution characteristics during regeneration was investigated based on engine bench test. Results reveal that the exhaust back pressure increases linearly with the engine speed, as well as the soot loading. The increase of DPF soot loading leads to a considerable increase in the reduction efficiency of particle number (PN) and particulate matter emissions, especially for the accumulation mode particles. Moreover, the performance in reducing nucleation mode particles is markedly better than that of accumulation mode ones, and this effect is greatly influenced by the engine operating conditions. At the beginning of DPF regeneration, the PN concentration increases sharply, especially the nucleation mode particles. After regeneration, the PN emissions decrease by two orders of magnitude. During regeneration, the particle size distribution exhibits a unimodal distribution, with the peak value increasing considerably and shifting toward smaller particle sizes. After regeneration, the particle size of the PN peak value slightly decreases and markedly shifts toward larger sizes, the accumulation mode particle concentration increases by 7.2 times, and the nucleation mode particle concentration increases by 2.6 times. Before the DPF regeneration, the axial temperature gradually decreases along the direction of the airflow, and the radial temperature gradually decreases from the center to the edge. During regeneration, the highest temperature occurs in the center of the DPF cross-section, whereas the temperature peak at the outlet interface occurs at the middle position of the DPF. The findings of this paper can provide scientific references to formulation and optimization of DPF regeneration strategies.

Pollution characteristics, source apportionment and absorption spectra of size-resolved PAHs in atmospheric particles in a cold megacity of China

Polycyclic aromatic hydrocarbons (PAHs) have the capability for solar radiation absorption related to climate forcing. Herein, pollution characteristics and absorption spectra of size-resolved PAHs in atmospheric particles in a cold megacity were comprehensively investigated. The mean concentrations of Σ18PAHs in all the 11 particle size ranges were 3.95 ± 4.77 × 104 pg/m3 and 2.17 ± 1.54 × 103 pg/m3 in heating period (HP) and non-heating period (NHP), respectively. Except for most PAHs with 2 and 3 benzene rings in NHP, most other PAHs showed a unimodal distribution pattern with the peak at 0.56–1.0 µm in both periods, which was caused by PAH emission sources. The PAH-related climate forcing was mainly caused by the solar radiation absorptions at ∼325 (∼330) nm and ∼365 nm. In general, the absorption intensities were higher in HP than NHP. The absorption intensity in the particle size range of 0.56–1.0 µm was the highest, and benzo[e]pyrene was the dominant contributor. In colder periods in HP, higher PAH concentrations caused more intensive PAH-related climate forcing. This study provided new insights for pollution characteristics and absorption spectra of size-resolved PAHs in atmospheric particles, which will be useful for better understanding PAH-related climate forcing.

Balanced Adversarial Tight Matching for Cross-Project Defect Prediction

Cross-project defect prediction (CPDP) is an attractive research area in software testing. It identifies defects in projects with limited labeled data (target projects) by utilizing predictive models from data-rich projects (source projects). Existing CPDP methods based on transfer learning mainly rely on the assumption of a unimodal distribution and consider the case where the feature distribution has one obvious peak. However, in actual situations, the feature distribution of project samples often exhibits multiple peaks that cannot be ignored. It manifests as a multimodal distribution, making it challenging to align distributions between different projects. To address this issue, we propose a balanced adversarial tight-matching model for CPDP. Specifically, this method employs multilinear conditioning to obtain the cross-covariance of both features and classifier predictions, capturing the multimodal distribution of the feature. When reducing the captured multimodal distribution differences, pseudo-labels are needed, but pseudo-labels have uncertainty. Therefore, we additionally add an auxiliary classifier and attempt to generate pseudo-labels using a pseudo-label strategy with less uncertainty. Finally, the feature generator and two classifiers undergo adversarial training to align the multimodal distributions of different projects. This method outperforms the state-of-the-art CPDP model used on the benchmark dataset.

Biomass Burning Greatly Enhances the Concentration of Fine Carbonaceous Aerosols at an Urban Area in Upper Northern Thailand: Evidence From the Radiocarbon‐Based Source Apportionment on Size‐Resolved Aerosols

AbstractTo study the role of biomass burning (BB) in air pollution at upper‐northern Thailand, the source apportionment of size‐resolved carbonaceous aerosols from Chiang Mai was carried out based on the radiocarbon (14C) analysis. The fraction of modern carbon (F14C) was generally decreased with particle size increasing and with the highest and lowest values of 0.90 ± 0.04 and 0.61 ± 0.04, respectively. Elemental carbon, regardless of emission sources, and BB‐derived organic carbon (OCbb) showed unimodal size distribution patterns with peaks at 0.43–0.65 μm. Fossil‐fuel derived‐OC (OCf) displayed a bimodal mode with the major peak at 2.1–10 μm, and the minor one at 0.43–0.65 μm. The biogenic secondary organic aerosols (BSOA) showed a typical fine‐mode unimodal size distribution pattern during the high BB (HBB) season, and a bimodal mode during the low BB season. The BSOA concentration increased by 189% ± 80% due to the interaction with open BB plums during HBB season, which was quantified by a 14C‐involved random forest model. Besides, the concentration of biogenic primary organic aerosols also showed a significant increment during the HBB season, especially in sub‐microns. Our results highlight the critical importance of controlling open fires to reduce air pollutants and the potential exposure risk.

Calculating premium principles from the mode of a unimodal weighted distribution

Abstract The theory of utility is a well-known method of constructing insurance premiums (see e.g., Newton et al. (1986) Actuarial Mathematics. Itasca, Illinois: The Society of Actuaries.). Furman and Zitikis ((2008) Insurance: Mathematics and Economics, 42, 459–465.) proposed an alternative method using the mean value of a weighted random variable. According to this approach, for various choices of weighting, popular premiums such as net premium, modified variance premium, Esscher premium, and Kamps premium are obtained. On the other hand, some premiums cannot be obtained with this method, such as the premium of the exponential principle. In this paper, we provide a complementary theory by introducing a family of unimodal weighted distributions for which the mode is a premium principle.

Soil Requirements, Genetic Diversity and Population History of the Juniperus sabina L. Varieties in Europe and Asia

Trees and shrubs belonging to the genus Juniperus L. are pivotal species in arid and semiarid ecosystems in the Northern Hemisphere. However, unfavourable phenomena are observed in their populations due to global warming. We aimed to investigate the soil requirements, genetic diversity and population history of Juniperus sabina L. from Europe, Georgia, and Kyrgyzstan. Genetic resources were evaluated in 16 populations using nuclear microsatellites, while past demographic events were described based on the chloroplast DNA haplotypes. Seven chemical parameters in 36 soil samples from the European range of J. sabina were compared. In the studied area, three distinct phylogenetic lineages corresponding to different varieties of J. sabina, namely var. sabina, var. balkanensis, and the Asian variety, were revealed. Unimodal mismatch distributions and significantly negative Tajima’s D and Fu’s Fs parameters indicated that the sabina and balkanensis varieties underwent a population expansion. Microsatellite variation was moderate, potentially influenced by inbreeding, clonal propagation, and limited gene flow between populations. Bayesian clustering revealed five genetic groups. Compared to var. sabina, the balkanensis variety occupies areas with significantly higher potassium content in the soil, which probably mitigates the adverse effects of drought in its localities.

Come rain or come shine, the species richness will decline in the Moroccan mountains

Plant species richness in mountainous regions generally follows a unimodal distribution with lower values at both low and high altitudes in relation to precipitation. In the Atlas mountains, Morocco, plant species richness is currently highest at 800–1200 m elevation, but the extent and altitudinal limits of this species-rich belt have shifted in the past with climate change.Here, we trace the evolution of pollen taxonomic richness (PTR) as a proxy for plant species richness, with the aim of understanding the relationship with climatic changes over the past 19,000 years, and make some assumptions about future changes in species richness. Past PTR was inferred through an analogy with an extensive modern pollen dataset, and past climatic variables were reconstructed from a fossil record collected in the Middle Atlas, Morocco.We found that the current PTR distribution in Morocco is more closely associated with precipitation than with temperature. During the last glacial period, both PTR and annual precipitation were low, and the analogs were located at lower altitudes than the altitude of the fossil record. During the early Holocene, the PTR increased by approximately 15%, and the modern analogs were found approximately 600–800 m higher than the analogs of the last glacial period. After 6000 years BP, we observe a steady decline in annual precipitation of approximately 30%, resulting in a species richness loss of approximately 18% and a retreat of the upper boundary of the species-rich belt.Climate projections suggest that annual precipitation in Northwest Africa will decrease by 20–30% over the next 50 years, an annual amount comparable to that of the last glacial period, but under much warmer conditions and in a significantly shorter time. Such a decline in precipitation could result in an unprecedented loss of plant species richness of approximately 15% in just a few decades and put 35% of the protected areas at risk. The forested mountains above 1600 m could then resemble the treeless and less diverse steppes found at higher altitudes above today's tree line.

Error analysis of wave intercomparison based on sampling variability

Quantitative analysis of error sources in wave measurement intercomparison under real-world conditions remains challenging due to various factors such as spatial and temporal offsets in the field, diverse configurations of wave sensors and platforms, and distinct measurement algorithms. This study introduces a modified error analysis method based on sampling variability. Measurements from two co-deployed Datawell Waverider buoys at the National Marine Test Site (Weihai) in China offer an opportunity to assess the spatial variability error. The results reveal that for non-directional wave parameters, like significant wave height and mean zero-crossing period, the wave conditions in the field can be considered stationary, with random errors primarily arising from inherent sampling variability. Spatial offsets significantly impact directional wave parameters at peak frequencies, with large deviations (greater than 20°) in peak wave direction primarily attributed to bimodal distribution. For data with significant wave heights exceeding 0.5 m, random errors in the mean wave direction at the same frequency can be mainly attributed to sampling variability. The bulk directional wave parameters weighted by the energy spectrum demonstrate lower sensitivity to spatial offsets, and there is excellent agreement between the bulk mean directions when considering only the unimodal distribution data.