Radiative transfer (RT) modelling is a necessary tool in the interpretation of observations of the thermal emission of interstellar dust. It is also often part of multi-physics modelling. In this context, the efficiency of radiative transfer calculations is important, even for one-dimensional models. We investigate the use of the so-called immediate re-emission (IRE) method for fast calculation of one-dimensional spherical cloud models. We wish to determine whether weighting methods similar to those used in traditional Monte Carlo simulations can speed up the estimation of dust temperature. We present the program DIES, a parallel implementation of the IRE method, which makes it possible to do the calculations also on graphics processing units (GPUs). We tested the program with externally and internally heated cloud models, and examined the potential improvements from the use of different weighted sampling schemes. The execution times of the program compare favourably with previous programs, especially when run on GPUs. On the other hand, weighting schemes produce only limited improvements. In the case of an internal radiation source, the basic IRE method samples the re-emission wel
A mathematical approach to solve the porthole die design problem is achieved by statistical analysis of a large amount of geometric data of successful porthole die designs. Linear and logarithmic regression are used to analyse geometrical data of 596 different ports from 88 first trial dies. Non-significant variables or high correlated variables are discarded according to knowledge of the extrusion process and statistical criteria. This paper focuses on a validation model for a typical case of porthole dies: four cavities and four ports per cavity dies. This mathematical formulation is a way of summarizing in a single expression the experience accumulated in a large number of designs over time. A broad way of research is open to generalise this model or extend it to other types of porthole dies.
Bezuidenhout and Grimmett proved that the critical contact process dies out. Here, we generalize the result to the so called contact process in a random evolving environment (CPREE), introduced by Erik Broman. This process is a generalization of the contact process where the recovery rate can vary between two values. The rate which it chooses is determined by a background process, which evolves independently at different sites. As for the contact process, we can similarly define a critical value in terms of survival for this process. In this paper we prove that this definition is independent of how we start the background process, that finite and infinite survival (meaning nontriviality of the upper invariant measure) are equivalent and finally that the process dies out at criticality.
A simple computer-based algorithm has been developed to identify pre-modern coins minted from the same dies, intending mainly coins minted by hand-made dies designed to be applicable to images taken from auction websites or catalogs. Though the method is not intended to perform a complete automatic classification, which would require more complex and intensive algorithms accessible to experts of computer vision its simplicity of use and lack of specific requirement about the quality of pictures can provide help and complementary information to the visual inspection, adding quantitative measurements of the "distance" between pairs of different coins. The distance metric is based on a number of pre-defined reference points that mark key features of the coin to identify the set of coins they have been minted from.
The recent return of the US to the Paris Climate Accord, massive increase in solar panel production and energy storage solutions has resulted in pressure on supply for solar cell materials and recycling of panels installed in the 90's and beginning of the 2000's which have reached their end of life. In this work we focus on recycling silicon wafers and dies by stripping previous structures from the die using potent acids after which its base material is characterized and binned. We demonstrate the process for silicon p-type substrates where n-type doping is attained by using a simple solution of phosphoric acid, which is diffused into the substrate using a furnace thus creating a PN junction. In case the substrate is n-type it could be replaced by boric acid. This is followed by deposition of a conductive antireflective coating, bus bars and rear wafer metal coating. The initial demonstrated laboratory results indicate the feasibility of recycling wafers using simple low cost standard industrial methods.
The Born rule may be stated mathematically as the rule that probabilities in quantum theory are expectation values of a complete orthogonal set of projection operators. This rule works for single laboratory settings in which the observer can distinguish all the different possible outcomes corresponding to the projection operators. However, theories of inflation suggest that the universe may be so large that any laboratory, no matter how precisely it is defined by its internal state, may exist in a large number of very distantly separated copies throughout the vast universe. In this case, no observer within the universe can distinguish all possible outcomes for all copies of the laboratory. Then normalized probabilities for the local outcomes that can be locally distinguished cannot be given by the expectation values of any projection operators. Thus the Born rule dies and must be replaced by another rule for observational probabilities in cosmology. The freedom of what this new rule is to be is the measure problem in cosmology. A particular volume-averaged form is proposed.
This paper will provide a method to decompose forging dies for machining planning in the case of high speed machining finishing operations. This method lies on a machining feature approach model presented in the following paper. The two main decomposition phases, called Basic Machining Features Extraction and Process Planning Generation, are presented. These two decomposition phases integrates machining resources models and expert machining knowledge to provide an outstanding process planning.
This paper describes the isothermal die swell using our recent quasi-1D model for fast (high Deborah number) contraction flows of polymers melts. Because the model analyzes the flow in several flow regions as one continuous process, it makes possible to evaluate the die swell as a qusi-1D extrudate flow in dies of various lengths. Using the asymptotic matching condition for the change in flow type at the die exit allowed us to find the swelling profile for extrudate along the flow direction. The calculations in paper performed using a multi-mode viscoelastic constitutive equation of differential type, are compared with the experimental/direct numerical data including basic rheological tests. The presented swelling model involves no fitting parameter and is applicable for calculations using any viscoelastic constitutive equation.
Faculty hiring shapes the flow of ideas, resources, and opportunities in academia, influencing not only individual career trajectories but also broader patterns of institutional prestige and scientific progress. While traditional studies have found strong correlations between faculty hiring and attributes such as doctoral department prestige and publication record, they rarely assess whether these associations generalize to individual hiring outcomes, particularly for future candidates outside the original sample. Here, we consider faculty placement as an individual-level prediction task. Our data consist of temporal co-authorship networks with conventional attributes such as doctoral department prestige and bibliometric features. We observe that using the co-authorship network significantly improves predictive accuracy by up to 10% over traditional indicators alone, with the largest gains observed for placements at the most elite (top-10) departments. Our results underscore the role that social networks, professional endorsements, and implicit advocacy play in faculty hiring beyond traditional measures of scholarly productivity and institutional prestige. By introducing a predicti
Large language models (LLMs) are increasingly used as information sources, yet small changes in semantic framing can destabilize their truth judgments. We propose P-StaT (Perturbation Stability of Truth), an evaluation framework for testing belief stability under controlled semantic perturbations in representational and behavioral settings via probing and zero-shot prompting. Across sixteen open-source LLMs and three domains, we compare perturbations involving epistemically familiar Neither statements drawn from well-known fictional contexts (Fictional) to those involving unfamiliar Neither statements not seen in training data (Synthetic). We find a consistent stability hierarchy: Synthetic content aligns closely with factual representations and induces the largest retractions of previously held beliefs, producing up to $32.7\%$ retractions in representational evaluations and up to $36.3\%$ in behavioral evaluations. By contrast, Fictional content is more representationally distinct and comparatively stable. Together, these results suggest that epistemic familiarity is a robust signal across instantiations of belief stability under semantic reframing, complementing accuracy-based f
The spread of information through socio-technical systems determines which individuals are the first to gain access to opportunities and insights. Yet, the pathways through which information flows can be skewed, leading to systematic differences in access across social groups. These inequalities remain poorly characterized in settings involving nonlinear social contagion and higher-order interactions that exhibit homophily. We introduce a enerative model for hypergraphs with hyperedge homophily, a hyperedge size-dependent property, and tunable degree distribution, called the $\texttt{H3}$ model, along with a model for nonlinear social contagion that incorporates asymmetric transmission between in-group and out-group nodes. Using stochastic simulations of a social contagion process on hypergraphs from the $\texttt{H3}$ model and diverse empirical datasets, we show that the interaction between social contagion dynamics and hyperedge homophily -- an effect unique to higher-order networks due to its dependence on hyperedge size -- can critically shape group-level differences in information access. By emphasizing how hyperedge homophily shapes interaction patterns, our findings undersco
A spectral approach based on the Fourier diffraction theorem is combined with a pair of U-NETs to perform quantitative microwave imaging of an anthropomorphic breast phantom. The U-NET pair is trained on a spectral database constructed from combinations of different realistic parts of the breast. Some preliminary numerical results are presented to show the major improvement brought by the U-NET.
Complexity science, despite its broad scope and potential impact, has not kept pace with fields like artificial intelligence, biotechnology and social sciences in addressing ethical concerns. The field lacks a comprehensive ethical framework, leaving us, as a community, vulnerable to ethical challenges and dilemmas. Other areas have gone through similar experiences and created, with discussions and working groups, their guides, policies and recommendations. Therefore, here we highlight the critical absence of formal guidelines, dedicated ethical committees, and widespread discussions on ethics within the complexity science community. Drawing on insights from the disciplines mentioned earlier, we propose a roadmap to enhance ethical awareness and action. Our recommendations include (i) initiating supportive mechanisms to develop ethical guidelines specific to complex systems research, (ii) creating open-access resources, and (iii) fostering inclusive dialogues to ensure that complexity science can responsibly tackle societal challenges and achieve a more inclusive environment. By initiating this dialogue, we aim to encourage a necessary shift in how ethics is integrated into complex
Deep inelastic scattering data on $F_2$ structure function from various fixed-target experiments were analyzed in a nonsinglet approximation in the MSbar and DIS scheme. The study of high statistics deep inelastic scattering data provided by BCDMS, SLAC and NMC collaborations, was carried out using a combined analysis. The application of the DIS scheme leads to the resummation of contributions that are important for large x values. It is found that using the DIS scheme does not significantly change the strong coupling constant itself but does strongly change the values of the twist-four corrections.
Assuming the Unique Games Conjecture (UGC), the best approximation ratio that can be obtained in polynomial time for the MAX CUT problem is $α_{\text{CUT}}\simeq 0.87856$, obtained by the celebrated SDP-based approximation algorithm of Goemans and Williamson. The currently best approximation algorithm for MAX DI-CUT, i.e., the MAX CUT problem in directed graphs, achieves a ratio of about $0.87401$, leaving open the question whether MAX DI-CUT can be approximated as well as MAX CUT. We obtain a slightly improved algorithm for MAX DI-CUT and a new UGC-hardness result for it, showing that $0.87446\le α_{\text{DI-CUT}}\le 0.87461$, where $α_{\text{DI-CUT}}$ is the best approximation ratio that can be obtained in polynomial time for MAX DI-CUT under UGC. The new upper bound separates MAX DI-CUT from MAX CUT, resolving a question raised by Feige and Goemans. A natural generalization of MAX DI-CUT is the MAX 2-AND problem in which each constraint is of the form $z_1\land z_2$, where $z_1$ and $z_2$ are literals, i.e., variables or their negations (In MAX DI-CUT each constraint is of the form $\bar{x}_1\land x_2$, where $x_1$ and $x_2$ are variables.) Austrin separated MAX 2-AND from MAX C
A new experimental treatment may have found a way to outsmart glioblastoma’s toughest defense: the blood-brain barrier。 Researchers used sugar-coated nanoparticles to ferry genetic instructions that restore a key tumor-suppressing protein directly into brain cancer cells。 In mouse studies, the therapy increased median survival by 50% while shrinkin
A powerful new AI tool has uncovered what could be one of the biggest integrity problems in modern science。 After analyzing 2。6 million cancer research papers published between 1999 and 2024, researchers identified more than 250,000 studies with writing patterns resembling papers suspected of being produced by fraudulent "paper mills
ATLAS observed a limit for {the cross section of di-jets resonances, which is weaker than expected for a} mass slightly below $\approx$1\TeV. In addition, CMS reported hints for the (non-resonant) pair production of di-jet resonances $X$ via a particle $Y$ at a very similar mass range with a local (global) significance of 3.6\,$σ$ (2.5\,$σ$) at $m_X\approx950\,$GeV. In this article we show that using the preferred range for $m_X$ from the ATLAS analysis, one can reinterpret the CMS analysis of di-di-jets in terms of a resonant search with $Y\to XX$, with a significantly reduced look-elsewhere effect, finding an excess for $m_Y\!\approx\!3.6$\TeV with a significance of $4.0\,σ$ ($3.2\,σ$) locally (globally). We present two possible UV completions capable of explaining the (di-)di-jet excesses, one containing two scalar di-quarks, the other one involving heavy gluons based on an $SU(3)_1\!\times\! SU(3)_2\!\times\! SU(3)_3$ gauge symmetry, spontaneously broken to $SU(3)$ color. In the latter case, non-perturbative couplings are required, pointing towards a composite or extra-dimensional framework. In fact, using 5D-AdS space-time, one obtains the correct mass ratio for $m_X/m_Y$, ass