Previous Analyses Research Articles

What support do international doctoral students claim they need to improve their academic writing in English?

Novice scholars from non-native English-speaking (NNES) backgrounds tend to encounter challenges in their doctoral education related to scholarly writing in English. This study investigated the support that NNES doctoral students perceive as crucial for achieving their desired proficiency in English academic writing (EAW). A survey was conducted during the 2021–2022 academic year, involving 255 NNES international doctoral students studying in 65 English medium PhD programs across Hungary. Volunteers from 49 countries, representing 48 languages, participated in the study. An analysis of their responses to an open question revealed that the majority felt a need for support in enhancing their EAW skills. Very few believed they could already produce publishable texts or that the support of their doctoral schools was sufficient. Most participants recognized specific areas where improvement was necessary and took full responsibility for their progress. Thus, findings of this study align with previous quantitative analyses involving the same participants and the conceptual metaphors they provided, emphasizing the high demand for support in developing English academic writing skills (Authors, 2022a, 2022b, 2023).

Comparative analyses of various IgE-mediated and non-IgE-mediated inducers of mast cell degranulation for in vitro study.

In vitro investigations of mast cell (MC) degranulation are essential for studying many diseases, particularly allergy and urticaria. Many MC-degranulation inducers are currently available. However, there is no previous systematic comparative analysis of these available inducers in term of their efficacies to induce MC degranulation. Herein, we performed systematic comparisons of efficacies of five well-known and commonly used MC-degranulation inducers. RBL-2H3 cells were sensitized with 50ng/ml anti-DNP IgE or biotinylated IgE followed by stimulation with 100ng/ml DNP-BSA or streptavidin, respectively. For non-IgE-mediated inducers, the cells were treated with 5µg/ml substance P, compound 48/80, or A23187. At 15-, 30-, 45- and 60-min post-induction, several common MC-degranulation markers (including intracellular [Ca2+], β-hexosaminidase release, tryptase expression by immunofluorescence staining, cellular tryptase level by immunoblotting, secretory tryptase level by immunoblotting, CD63 expression by immunofluorescence staining, and CD63 expression by flow cytometry) were evaluated. The data showed that all these markers significantly increased after activation by all inducers. Among them, A23187 provided the greatest degrees of increases in intracellular [Ca2+] and β-hexosaminidase release at all time-points and upregulation of CD63 at one time-point. These data indicate that all these IgE-mediated (anti-DNP IgE/DNP-BSA and biotinylated IgE/streptavidin) and non-IgE-mediated (substance P, compound 48/80, and A23187) inducers effectively induce MC degranulation, while A23187 seems to be the most effective inducer for MC degranulation.

Abstract 5485: Spatial characterization of the immunosuppressive tumor microenvironment in estrogen receptor positive breast cancer at single cell level

Abstract We characterized immune cell exclusion in estrogen receptor positive (ER+) breast cancer through the study of spatial relationships among various subsets of cancer-associated fibroblasts (CAFs), tumor-associated macrophages (TAMs), and other immune cells using a novel in-situ spatial transcriptomic technology. ER+ breast cancer is the most common breast cancer subtype. While endocrine therapy and immune checkpoint inhibitors have considerably reduced relapse and mortality for breast cancer patients, tumor resistance to treatment remains a major challenge. The tumor microenvironment (TME) plays an important role in this mechanism of resistance. Our previous spatial proteomic analysis of ER+ breast FFPE samples demonstrated the intricate relationship between tumor and immunosuppressive cells such as CAFs and TAMs via the CXCR4-CXCL12 axis associated with the exclusion of CD8 T cells from the TME. However, the limited number of antibodies in the panel made it challenging to investigate the diversity of those CAF and TAM populations and better understand their contribution to T cell exclusion. For this purpose, we further characterized the TME of 4 human ER+ breast cancer FFPE cores using the Xenium in-situ transcriptomic platform with a breast cancer-focused panel of 280 genes from 10x Genomics plus 100 additional genes selected from literature and publicly available single cell datasets to delineate CAF and TAM sub-populations. Image analysis enabled the quantification and spatial mapping of the target genes within each cell boundary. Cells were manually annotated through unsupervised clustering of over 1 million cells. The cell phenotyping analysis allowed us to annotate major cell types including tumor cells, macrophages, T cells and fibroblasts. With our curated panel, we further characterized CAF and TAM sub-populations by identifying myofibroblastic CAFs (myCAFs), inflammatory CAFs (iCAFs), and antigen-presenting CAFs (apCAFs) in addition to M1 and M2-like macrophages as reported in the literature. We then performed spatial neighborhood analysis based on the similarity of the cell type composition in the vicinity of each cell. The results showed that myCAFs and M2-like macrophages are found in proximity to tumor cells and may play a role in T-cell exclusion. In addition, iCAFs mainly express CXCL12, a chemokine known to attract immunosuppressive cells such as regulatory T cells and M2-like macrophages as well as repel cytotoxic T cells from infiltrating the tumor via the CXCR4-CXCL12 axis. Overall, our work shows the potential of spatial transcriptomics to elucidate the spatial distribution of cells and their contribution to the immunosuppressive TME, which may enable researchers to improve understanding of tumor biology and drug target discovery efforts. Citation Format: Julien Tessier, Sandra Curras-Alonso, Joon Sang Lee, Fabien Delahaye, Hong Ma, Katie Malley, Dinesh Bangari, Donald Jackson, Angela Hadjipanayis. Spatial characterization of the immunosuppressive tumor microenvironment in estrogen receptor positive breast cancer at single cell level [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5485.

(Un)muzzled: Dogs in Mid-Nineteenth-Century Fiction

Abstract This article considers the relationship between dogs as fictional constructs and the shifting dynamics of the novel form in the mid-nineteenth century in order to account more fully for their particular importance to realist writing. In revisiting three canonical novels associated with the realist tradition, Charles Dickens’s Dombey and Son (1848), Charlotte Brontë’s Villette (1853), and George Eliot’s Adam Bede (1859), it demonstrates the ways in which writers regularly rely on dogs in depicting moments of deep personal and interpersonal conflict. Where most previous analyses of animals in Victorian fiction have tended to treat them as minor characters within their respective human narratives, this article is attuned to the affective functions of the domestic dog in contexts that exceed mere verisimilitude, exploring the significance of the connection between the dog’s textual body and the intense experience of grief, sexual desire, and anger respectively. I argue that the dog’s simultaneously narrative and extra-narrative position in the emergent realist novel reflects the genre’s larger formal tensions, generated by the representation of excess affects. These tensions are closely linked to the novel’s primary mode of representation: language. I conclude that it is the dog’s extralinguistic presence, predicated on its inability to encode affect in language, that marks it as the ideal, if increasingly unstable, nexus of powerful, unprocessed emotion in the mid-nineteenth-century novel.

Phylogenetically diverse wild plant species use common biochemical strategies to thrive in the Atacama Desert.

The best ideotypes are under mounting pressure due to increased aridity. Understanding the conserved molecular mechanisms that evolve in wild plants adapted to harsh environments is crucial in developing new strategies for agriculture. Yet our knowledge of such mechanisms in wild species is scant. We performed metabolic pathway reconstruction using transcriptome information from 32 Atacama and phylogenetically related species that do not live in Atacama (Sisters species). We analyzed reaction enrichment to understand the commonalities and differences of Atacama plants. To gain insights into the mechanisms that ensure survival, we compared expressed gene isoform numbers and gene expression patterns between the annotated biochemical reactions from 32 Atacama and Sister species. We found biochemical convergences characterized by reactions enriched in at least 50% of the Atacama species, pointing to potential advantages against drought and nitrogen starvation, for instance. These findings suggest that the adaptation in the Atacama Desert may result in part from shared genetic legacies governing the expression of key metabolic pathways to face harsh conditions. Enriched reactions corresponded to ubiquitous compounds common to extreme and agronomic species and were congruent with our previous metabolomic analyses. Convergent adaptive traits offer promising candidates for improving abiotic stress resilience in crop species.

Component-specific clusters for diagnosis and prediction of allergic airway diseases.

Previous studies which applied machine learning on multiplex component-resolved diagnostics arrays identified clusters of allergen components which are biologically plausible and reflect the sources of allergenic proteins and their structural homogeneity. Sensitization to different clusters is associated with different clinical outcomes. To investigate whether within different allergen component sensitization clusters, the internal within-cluster sensitization structure, including the number of c-sIgE responses and their distinct patterns, alters the risk of clinical expression of symptoms. In a previous analysis in a population-based birth cohort, by clustering component-specific (c-s)IgEs, we derived allergen component clusters from infancy to adolescence. In the current analysis, we defined each subject's within-cluster sensitization structure which captured the total number of c-sIgE responses in each cluster and intra-cluster sensitization patterns. Associations between within-cluster sensitization patterns and clinical outcomes (asthma and rhinitis) in early-school age and adolescence were examined using logistic regression and binomial generalized additive models. Intra-cluster sensitization patterns revealed specific associations with asthma and rhinitis (both contemporaneously and longitudinally) that were previously unseen using binary sensitization to clusters. A more detailed description of the subjects' within-cluster c-sIgE responses in terms of the number of positive c-sIgEs and unique sensitization patterns added new information relevant to allergic diseases, both for diagnostic and prognostic purposes. For example, the increase in the number of within-cluster positive c-sIgEs at age 5 years was correlated with the increase in prevalence of asthma at ages 5 and 16 years, with the correlations being stronger in the prediction context (e.g. for the largest 'Broad' component cluster, contemporaneous: r = .28, p = .012; r = .22, p = .043; longitudinal: r = .36, p = .004; r = .27, p = .04). Among sensitized individuals, a more detailed description of within-cluster c-sIgE responses in terms of the number of positive c-sIgE responses and distinct sensitization patterns, adds potentially important information relevant to allergic diseases.

Replica analysis of overfitting in regression models for time to event data: the impact of censoring

We use statistical mechanics techniques, viz. the replica method, to model the effect of censoring on overfitting in Cox’s proportional hazards model, the dominant regression method for time-to-event data. In the overfitting regime, Maximum Likelihood (ML) parameter estimators are known to be biased already for small values of the ratio of the number of covariates over the number of samples. The inclusion of censoring was avoided in previous overfitting analyses for mathematical convenience, but is vital to make any theory applicable to real-world medical data, where censoring is ubiquitous. Upon constructing efficient algorithms for solving the new (and more complex) Replica Symmetric (RS) equations and comparing the solutions with numerical simulation data, we find excellent agreement, even for large censoring rates. We then address the practical problem of using the theory to correct the biased ML estimators without knowledge of the data-generating distribution. This is achieved via a novel numerical algorithm that self-consistently approximates all relevant parameters of the data generating distribution while simultaneously solving the RS equations. We investigate numerically the statistics of the corrected estimators, and show that the proposed new algorithm indeed succeeds in removing the bias of the ML estimators, for both the association parameters and for the cumulative hazard.

FOXG1 variants can be associated with milder phenotypes than congenital Rett syndrome with unassisted walking and language development.

Since 2008, FOXG1 haploinsufficiency has been linked to a severe neurodevelopmental phenotype resembling Rett syndrome but with earlier onset. Most patients are unable to sit, walk, or speak. For years, FOXG1 sequencing was only prescribed in such severe cases, limiting insight into the full clinical spectrum associated with this gene. Next-generation sequencing (NGS) now enables unbiased diagnostics. Through the European Reference Network for Rare Malformation Syndromes, Intellectual and Other Neurodevelopmental Disorders, we gathered data from patients with heterozygous FOXG1 variants presenting a mild phenotype, defined as able to speak and walk independently. We also reviewed data from three previously reported patients meeting our criteria. We identified five new patients with pathogenic FOXG1 missense variants, primarily in the forkhead domain, showing varying nonspecific intellectual disability and developmental delay. These features are not typical of congenital Rett syndrome and were rarely associated with microcephaly and epilepsy. Our findings are consistent with a previous genotype-phenotype analysis by Mitter et al. suggesting the delineation of five different FOXG1 genotype groups. Milder phenotypes were associated with missense variants in the forkhead domain. This information may facilitate prognostic assessments in children carrying a FOXG1 variant and improve the interpretation of new variants identified with genomic sequencing.

A Pan-STARRS1 Search for Planet Nine

We present a search for Planet Nine using the second data release of the Pan-STARRS1 survey. We rule out the existence of a Planet Nine with the characteristics of that predicted in Brown & Batygin to a 50% completion depth of V = 21.5. This survey, along with previous analyses of the Zwicky Transient Facility and Dark Energy Survey data, rules out 78% of the Brown & Batygin parameter space. Much of the remaining parameter space is at V > 21 in regions near and in the area where the northern galactic plane crosses the ecliptic.

Nonlinear Evolution of Instabilities in a Laminar Separation Bubble at Hypersonic Speeds

The development of both convective stationary perturbation and global instabilities in the vicinity of a laminar separation bubble above an axisymmetric compression corner in hypersonic flow was investigated using numerical simulations. The flow configuration of interest corresponded to the cone–cylinder–flare model used in experimental measurements in the Boeing/U.S. Air Force Office of Scientific Research Mach-6 Quiet Tunnel (BAMQT) at Purdue University. For a flare angle of 10 deg and unit Reynolds number of 11.5×106 m−1, their surface flow visualizations identified the presence of streamwise elongated thermal streaks near the reattachment location that had a dominant azimuthal wave number m=36. Previous linear stability analyses predicted that the amplification characteristics of small-amplitude, unsteady, and convective instabilities within this flow were consistent with the surface pressure fluctuations measured in the experiment. However, their accompanying investigation of global instabilities showed that the separation bubble was weakly unstable at the 10 deg flare angle, with the most unstable global mode corresponding to a stationary disturbance with m≈5–6 (i.e., well below the measured wave number of m=36. Besides characterizing the global instability for selected flare angles, the present numerical simulations quantify the details of the stationary equilibrium state associated with supercritical bifurcation resulting from the nonlinear saturation of the unstable global mode. Although velocity perturbations associated with the saturated global mode are dominated by the fundamental spanwise wavelength associated with the linear global instability, the surface heat flux downstream of the reattachment is dominated by m=36, in agreement with the experimental measurements.

Persistent or temporary? Effects of social assistance benefit sanctions on employment quality

Abstract This article analyzes the effects of sanctions for unemployed recipients of the social assistance benefit in Germany. I conduct an analysis using administrative data from 2012 to 2018, applying a dynamic entropy balancing approach. In contrast to most previous analyses of benefit sanction effects, I analyse outcomes over a longer period and assess effects on various dimensions of employment quality, including education (mis)match. The results show, in line with previous research, that benefit sanctions increase the employment probability in the first months after treatment. In the long run, the employment probability and employment quality of sanctioned benefit recipients are lower than those for the comparison group of non-sanctioned benefit recipients, indicating long-lasting negative effects. The negative consequences of benefit sanctions for employment quality are hence not temporary, but persistent.

The origin and evolution of Cynodontia (Synapsida, Therapsida): Reassessment of the phylogeny and systematics of the earliest members of this clade using 3D-imaging technologies.

The origin of cynodonts, the group ancestral to and including mammals, is one of the major outstanding problems in therapsid evolution. One of the most troubling aspects of the cynodont fossil record is the lengthy Permian ghost lineage between the latest possible divergence from its sister group Therocephalia and the first appearance of definitive cynodonts in the late Permian. The absence of cynodonts and dominance of therocephalians in middle Permian strata has led some workers to argue that cynodonts evolved from within therocephalians, rendering the latter paraphyletic, but more recent analyses support the reciprocal monophyly of Cynodontia and Therocephalia. Furthermore, although a fundamental dichotomy in the derived subclade Eucynodontia is well-supported in cynodont phylogeny, the relationships of more stemward cynodonts from the late Permian and Early Triassic are unresolved. Here, we provide a re-evaluation of the phylogeny of Eutheriodontia (Cynodontia + Therocephalia) and an assessment of character evolution within the group. Using computed tomographic data derived from extensive sampling of the earliest known (late Permian and Early Triassic) cynodonts and selected exemplars of therocephalians and later (Middle Triassic onwards) cynodonts, we describe novel aspects of the endocranial anatomy of these animals. These data were incorporated into a new phylogenetic data set including a comprehensive sample of early cynodonts. Our phylogenetic analyses support some results previously recovered by other authors, but recover therocephalians as paraphyletic with regards to cynodonts, with cynodonts and eutherocephalians forming a clade to the exclusion of the "basal therocephalian" families Lycosuchidae and Scylacosauridae. Though both conservatism and homoplasy mark the endocranial anatomy of early non-mammalian cynodonts, we were able to identify several new endocranial synapomorphies for eutheriodont subclades and recovered generally better-supported topologies than previous analyses using primarily external craniodental characters.

Take Companion Animals as an Example to Explore the Legislative Dilemma of Animal Welfare

By comparing the current animal protection laws and regulations at home and abroad, this paper points out the existing problems and legal gaps in China's animal protection laws and regulations, and focuses on summarizing the disputes and dilemmas in China's animal welfare legislation, namely the disputes in rights and the disputes in utilization and protection. This paper analyzes the meaning and feasibility of the theory of "abolition of use" and "limited use" in academic circles and briefly analyzes the impact of animal welfare issues on China's foreign trade and international cooperation, explains the necessity and importance of animal welfare legislation, and puts forward legal solutions with high feasibility. Then, taking companion animals as an example, combined with the previous analysis of the current situation of China's domestic law, specifically explained the disputes in the rights of companion animals and the dilemma of power empowerment, and put forward the problems in the utilization and protection of companion animals through practical examples, and finally put forward a more specific and comprehensive solution.

Applications of the kinetic theory for a model of a confined quasi-two dimensional granular mixture: Stability analysis and thermal diffusion segregation

The Boltzmann kinetic theory for a model of a confined quasi-two dimensional granular mixture derived previously [Garzó et al., “Navier–Stokes transport coefficients for a model of a confined quasi-two dimensional granular binary mixture,” Phys. Fluids 33, 023310 (2021)] is considered further to analyze two different problems. First, a linear stability analysis of the hydrodynamic equations with respect to the homogeneous steady state (HSS) is carried out to identify the conditions for stability as functions of the wave vector, the coefficients of restitution, and the parameters of the mixture. The analysis, which is based on the results obtained by solving the Boltzmann equation by means of the Chapman–Enskog method to first order in spatial gradients, takes into account the (nonlinear) dependence of the transport coefficients and the cooling rate on the coefficients of restitution and applies in principle to arbitrary values of the concentration, and the mass and diameter ratios. In contrast to the results obtained in the conventional inelastic hard sphere (IHS) model, the results show that all the hydrodynamic modes are stable so that the HSS is linearly stable with respect to long enough wavelength excitations. On the other hand, this conclusion agrees with previous stability analysis performed in earlier studies for monocomponent granular gases. As a second application, segregation induced by both a thermal gradient and gravity is studied. A segregation criterion based on the dependence of the thermal diffusion factor Λ on the parameter space of the mixture is derived. In the absence of gravity, the results indicate that Λ is always positive, and hence, the larger particles tend to accumulate near the cold plate. However, when gravity is present, our results show the transition between Λ>0 (larger particles tend to move toward the cold plate) to Λ<0 (larger particles tend to move toward the hot plate) by varying the parameters of the system (masses, sizes, composition, and coefficients of restitution). Comparison with previous results derived from the IHS model is carried out.

Gravitational wave oscillations in bimetric cosmology

Unlike general relativity, in bimetric gravity linear gravitational waves do not evolve as free fields. In this theory there are two types of tensor perturbations, whose interactions are inherited from non-trivial couplings between two dynamical metric tensor fields in the Hassan-Rosen action, and are responsible for the phenomenon of bigravity oscillations. In this work, we analyze the dynamics of cosmological tensor modes in bimetric gravity on sub-horizon scales and close to the general relativity limit. In this limit, the system has a characteristic length scale L that is strictly contained within the comoving Hubble radius. Thus, depending on the magnitude of the comoving wavelength λ relative to L, we identify two regimes of interest where the system can be studied analytically: (i) deep sub-horizon modes with λ ≪ L, whose dynamics can be studied using multiple scale analysis and are characterized by small and slowly evolving super-imposed perturbations; (ii) sub-horizon modes with λ ≫ L, where the dynamics is characterized by fast super-imposed oscillations that can be studied using asymptotic techniques for highly oscillatory problems. Furthermore, our analysis represents a substantial improvement compared to previous analyses based on a generalization of the WKB method, which, as we show, is ill-suited to study the system at hand.

Computational study of the Nitrogen-16 source term in the ITER vacuum vessel cooling circuit through the coupling of system-level analysis code and CFD

In ITER, the evaluation of the activated water radiation source and its impact on the radiological levels is necessary to demonstrate compliance with the safety requirements. The use of simplified or conservative approaches often results in the application of expensive constraints on the installation that impact its economics, operations, and construction schedule. In this work, we propose a novel methodology to calculate the activated water source term with a higher degree of realism. The methodology is based on the coupling of a system-level code with a Computational Fluid Dynamics (CFD) code in an explicit, one-way approach. We apply this methodology to the evaluation of the 16N radioisotope within the ITER Vacuum Vessel Primary Heat Transfer System (VV-PHTS) cooling circuit in a steady-state and transient scenarios. We chose this system since previous analyses of the VV-PHTS were done with simple, ad-hoc calculations that yielded results that differed by up to a factor of five, underscoring a higher level of uncertainty. As a result, we generate a computational model of the source term that can be used to evaluate the radiological condition surrounding the cooling systems during the operations.

Precise estimate of charged Higgsino/Wino decay rate

Higgsinos and Winos in the supersymmetric Standard Model are prime candidates for dark matter due to their weakly interacting nature. The mass differences between their charged components (charginos) and neutral components (neutralinos) become degenerate when other superparticles are heavy, resulting in long-lived charginos. In the case of the Winos, the mass difference is approximately 160 MeV across a wide range of the parameter space. Consequently, the chargino decays into the lightest neutralino, emitting a single charged pion. For Higgsinos, however, mass differences ranging from O(0.1) GeV to O(1) GeV are possible, leading to a variety of decay channels. In this paper, we extend our previous analysis of Wino decay to the chargino with a larger mass difference. We emphasize characterizing its decay signatures through leptonic and hadronic modes. By utilizing the latest experimental data, we perform a comprehensive study of the decay rate calculations incorporating these hadronic modes to determine the impact on the predicted chargino lifetime. Additionally, we conduct next-to-leading order (NLO) calculations for the leptonic decay modes. Our NLO results can be applied to the case of more general fermionic electroweak multiplets, e.g., quintuplet dark matter.

One-third of global population at cancer risk due to elevated volatile organic compounds levels

Outdoor air pollution, particularly volatile organic compounds (VOCs), significantly contributes to the global health burden. Previous analyses of VOC exposure have typically focused on regional and national scales, thereby limiting global health burden assessments. In this study, we utilized a global chemistry-climate model to simulate VOC distributions and estimate related cancer risks from 2000 to 2019. Our findings indicated a 10.2% rise in global VOC emissions during this period, with substantial increases in Sub-Saharan Africa, the Rest of Asia, and China, but decreases in the U.S. and Europe due to reductions in the transportation and residential sectors. Carcinogenic VOCs such as benzene, formaldehyde, and acetaldehyde contributed to a lifetime cancer burden affecting 0.60 [95% confidence interval (95CI): 0.40–0.81] to 0.85 [95CI: 0.56–1.14] million individuals globally. We projected that between 36.4% and 39.7% of the global population was exposed to harmful VOC levels, with the highest exposure rates found in China (82.8–84.3%) and considerably lower exposure in Europe (1.7–5.8%). Open agricultural burning in less-developed regions amplified VOC-induced cancer burdens. Significant disparities in cancer burdens between high-income and low-to-middle-income countries were identified throughout the study period, primarily due to unequal population growth and VOC emissions. These findings underscore health disparities among different income nations and emphasize the persistent need to address the environmental injustice related to air pollution exposure.

Numerical Analysis of Narrow-gap Underfill Flow in the Flip-chip Process Using the Lattice Boltzmann Method

Flip-chip packaging is a first-level interconnect technology, and to predict its melt front of capillary driven underfill analytical models have been made. Using the Analytical models, prediction of the melt front can be efficiently done, however it is difficult to reflect the flow resistance resulting from complex solder bump arrangement. Therefore, 3D numerical analysis is required. In this study, Lattice Boltzmann method (LBM) is used for observing the micro void generation that occurs in a underfill process with a height of several tens of microns. LBM statistically expresses the motion of the molecule, to solve the mass transfer of the microscale. In particular, LBM has strengths in multiphase flow analysis of several microscales that cannot be solved by continuum assumption. In this paper, underfill process of several tens of micro scales, which was not covered in previous 3D numerical analysis studies, was simulated using LBM. The improvement of the new LBM model, which more accurately simulates the resistance due to pressure by considering collisions between air and molten mold molecules, is introduced. With the hydraulic diameter greatly reduced due to the narrow gap, it is observed how the solder bump pitch affects the micro void generation. And it is observed whether the air ventilation could change significantly according to the ambient pressure.

Validation of four optimization evolutionary algorithms combined with artificial neural network (ANN) for landslide susceptibility mapping: A case study of Gilan, Iran

Landslides, the most significant geohazards in Iran, adversely affect the region's socioeconomic conditions and the environment. Landslide susceptibility mapping is crucial for proactive risk management, sustainable development, and protecting human lives, infrastructure, and the environment. It enables decision-makers to make informed choices, implement appropriate mitigation measures, and plan for potential landslide events, leading to safer and more resilient communities. Using a recommended subdivision methodology, this research has developed a landslide susceptibility map for a significant Gilan, Iran region. The production of the map involved utilizing an artificial neural network (ANN) model. This model incorporated sixteen causal components from several characteristics, including topographic and geomorphologic features, geological factors, land use patterns, hydrological aspects, and hydrogeological properties. Three hundred seventy instances were identified using multiple verified sources and analyzing aerial photographs to create the landslide inventory map. Examining and verifying the weights assigned to the causal elements were conducted per accepted mathematical standards, incorporating sensitivity analysis, earlier research, and empirical data on landslides. The area under the receiver operating characteristic curve (AUROC) was used to compare the various models. The study's findings indicated that the best swarm size value for COA-MLP11Cuckoo Optimization Algorithm (COA). is equal to 450, and the accuracy indices for this algorithm were 0.998 and 0.995 in training and testing datasets, respectively. Similarly, the AUC22Area under the curve (AUC). for the HS-MLP,33Harmony Search Algorithm (HS). SFS-MLP,44Stochastic Fractal Search (SFS). and TLBO-MLP55Teaching- Learning-Based Optiization (TLBO). were 0.997, 0.999, and 0.999 in training and 0.995, 0.996, and 0.995 in the testing dataset, respectively. Therefore, the use of optimization algorithms leads to an increase in the performance and accuracy of the neural network, and the high accuracy of the SFS-MLP model demonstrates the existence of a dependable criterion for delineating the susceptibility zones about forthcoming landslide occurrences. The model is a cost-effective and potentially indispensable tool for urban planners in growing cities and municipalities. Its effectiveness is demonstrated by comparisons with previous susceptibility analyses conducted in the region.