Code generation and comprehension by Large Language Models (LLMs) have emerged as core drivers of industrial intelligence and decision optimization, finding widespread application in fields such as finance, automation, and aerospace. Although recent advancements have demonstrated the remarkable potential of LLMs in general code generation, existing benchmarks are mainly confined to single domains and languages. Consequently, they fail to effectively evaluate the generalization capabilities required for real-world industrial applications or to reflect the coding proficiency demanded by complex industrial scenarios. To bridge this gap, we introduce IndustryCode, the first comprehensive benchmark designed to span multiple industrial domains and programming languages. IndustryCode comprises 579 sub-problems derived from 125 primary industrial challenges, accompanied by rigorous problem descriptions and test cases. It covers a wide range of fields, including finance, automation, aerospace, and remote sensing-and incorporates diverse programming languages such as MATLAB, Python, C++, and Stata. In our evaluation, the top-performing model, Claude 4.5 Opus, achieved an overall accuracy of 68.1% on sub-problems and 42.5% main problems. The benchmark dataset and automated evaluation code will be made publicly available upon acceptance.
Accretion in black hole X-ray binaries is commonly believed to be supplied by the Roche lobe overflow or the stellar wind. The former is thought to form a geometrically thin disc while the diffuse wind could form a geometrically thick hot accretion flow. In this paper, we instead consider a more generalised case, i.e., accretion with both cold and hot gas supplies, which feed a disc and a corona respectively. We investigate the interaction of disc and corona by analysing the energy coupling and matter exchange, i.e. corona condensation/disc evaporation, with a semi-analytical method. It is found that the accretion geometry in the radial direction and the resultant emission spectrum depend strongly on both the total gas supply rate and the ratio of cold and hot gases. For gas supply rates of a few percent of the Eddington value, diverse geometries and spectral shapes are possible, depending on the fraction of cold gas supply. This provides an interpretation for the various spectra observed in intermediate states. However, at higher accretion rates, regardless of the form of the feeding gas, the inner accretion flow is always disc-dominated, implying an inevitable transition to the soft state, while at very low gas supply rates, hard state spectrum dominated by the hot flow is expected. We also present the predicted hardness-intensity correlation of Cygnus X-1, and constrain the value of the viscosity parameter of the accretion flow to the range of 0.25--0.35 by comparing our results with MAXI observations.
Gauthier Roussilhe, Thibault Pirson, David Bol
et al.
Growing attention is given to the environmental impacts of the digital sector, exacerbated by the increase of digital products and services in our globalized societies. The materiality of the digital sector is often presented through the environmental impacts of mining activities to point out that digitization does not mean dematerialization. Despite its importance, such a narrative is often restricted to a few minerals (e.g., cobalt, lithium) that have become the symbols of extractive industries. In this paper, we further explore the materiality of the digital sector with an approach based on the diversity of elements and their purity requirements in the semiconductor industry. Semiconductors are responsible for manufacturing the key building blocks of the digital sector, i.e., microchips. Given that the need for ultra-high purity materials is very specific to the semiconductor industry, a few companies around the world have been studied, revealing new critical actors in complex supply chains. This highlights strong dependencies towards other industrial sectors with mass production and the need for a deeper investigation of interactions with the chemical industry, complementary to the mining industry.
Climate change is one of the most critical challenges of the twenty-first century. Public understanding of climate issues and of the goals regarding the climate transition is essential to translate awareness into concrete actions. In this context, social media platforms play a crucial role in disseminating information about climate change and climate policy. To better understand the dynamics of information circulation and the emergence of information voids we propose a model that takes into account the supply and demand of information related to the Italian climate-transition discourse. We conceptualise information supply as the production of content on Facebook, Instagram and GDELT (an online news database) while leveraging Google searches to capture information demand. Our findings highlight responsiveness and temporal coupling between supply and demand, particularly during moments of heightened public attention triggered by significant external events. These responsive interactions reveal an overall adaptive information ecosystem. However, we also observe persistent information voids which may limit public understanding and delay meaningful engagement.
This paper proposes a Trans-XFed architecture that combines federated learning with explainable AI techniques for supply chain credit assessment. The proposed model aims to address several key challenges, including privacy, information silos, class imbalance, non-identically and independently distributed (Non-IID) data, and model interpretability in supply chain credit assessment. We introduce a performance-based client selection strategy (PBCS) to tackle class imbalance and Non-IID problems. This strategy achieves faster convergence by selecting clients with higher local F1 scores. The FedProx architecture, enhanced with homomorphic encryption, is used as the core model, and further incorporates a transformer encoder. The transformer encoder block provides insights into the learned features. Additionally, we employ the integrated gradient explainable AI technique to offer insights into decision-making. We demonstrate the effectiveness of Trans-XFed through experimental evaluations on real-world supply chain datasets. The obtained results show its ability to deliver accurate credit assessments compared to several baselines, while maintaining transparency and privacy.
ABSTRACT The objectives of the study are to analyse the perception of consumers on piped water supply, the consumers’ willingness to pay for improved water supply, and the factors that affect it. The sample unit is the consumer household of the public health divisions. The sample size is 181. A multistage random sampling procedure was adopted to choose the sample household. Descriptive statistics and structural equation models are used to analyse the data. This study found that consumer satisfaction is influenced by water supply quantity, pressure, timing, and visual aspects. The main factors causing interruptions include pipeline breakage, cyclone impact, summer water depletion, construction work, motor damage, and reservoir cleaning. Households are not well-informed about advance payment, its benefits, and the proper procedure for obtaining a receipt. Household income, education, satisfaction with water quality, the period of the service association, supply water price, and sufficiency of water during summer directly affect consumers’ willingness to pay. Discontent with appearance and taste affects quality dissatisfaction and indirectly willingness to pay.
Fouad Oubari, Raphael Meunier, Rodrigue Décatoire
et al.
Generative design is an increasingly important tool in the industrial world. It allows the designers and engineers to easily explore vast ranges of design options, providing a cheaper and faster alternative to the trial and failure approaches. Thanks to the flexibility they offer, Deep Generative Models are gaining popularity amongst Generative Design technologies. However, developing and evaluating these models can be challenging. The field lacks accessible benchmarks, in order to evaluate and compare objectively different Deep Generative Models architectures. Moreover, vanilla Deep Generative Models appear to be unable to accurately generate multi-components industrial systems that are controlled by latent design constraints. To address these challenges, we propose an industry-inspired use case that incorporates actual industrial system characteristics. This use case can be quickly generated and used as a benchmark. We propose a Meta-VAE capable of producing multi-component industrial systems and showcase its application on the proposed use case.
Ayman A. El-Zoka, Leigh T. Stephenson, Se-Ho Kim
et al.
Gas-solid reactions are cornerstones of many catalytic and redox processes that will underpin the energy and sustainability transition. The specific case of hydrogen-based iron oxide reduction is the foundation to render the global steel industry fossil-free, an essential target as iron production is the largest single industrial emitter of carbon dioxide. Our perception of gas-solid reactions has not only been limited by the availability of state-of-the-art techniques which can delve into the reacted solids in great structural and chemical detail, but we continue to miss an important reaction partner that defines the thermodynamics and kinetics of gas phase reactions: the gas molecules. In this investigation, we use the latest development in cryogenic atom probe tomography to study the quasi in-situ evolution of gas phase heavy water at iron-iron oxide interfaces resulting from the direct reduction of iron oxide by deuterium gas at 700°C. The findings provide new insights into the formation kinetics and location of water formed during hydrogen-based reduction of FeO, an its interaction with the ongoing redox reaction.
Sean J. Weinberg, Fabio Sanches, Takanori Ide
et al.
Noisy intermediate-scale quantum (NISQ) hardware is almost universally incompatible with full-scale optimization problems of practical importance which can have many variables and unwieldy objective functions. As a consequence, there is a growing body of literature that tests quantum algorithms on miniaturized versions of problems that arise in an operations research setting. Rather than taking this approach, we investigate a problem of substantial commercial value, multi-truck vehicle routing for supply chain logistics, at the scale used by a corporation in their operations. Such a problem is too complex to be fully embedded on any near-term quantum hardware or simulator; we avoid confronting this challenge by taking a hybrid workflow approach: we iteratively assign routes for trucks by generating a new binary optimization problem instance one truck at a time. Each instance has $\sim 2500$ quadratic binary variables, putting it in a range that is feasible for NISQ quantum computing, especially quantum annealing hardware. We test our methods using simulated annealing and the D-Wave Hybrid solver as a place-holder in wait of quantum hardware developments. After feeding the vehicle routes suggested by these runs into a highly realistic classical supply chain simulation, we find excellent performance for the full supply chain. Our work gives a set of techniques that can be adopted in contexts beyond vehicle routing to apply NISQ devices in a hybrid fashion to large-scale problems of commercial interest.
We consider belief propagation (BP) as an efficient and scalable tool for state estimation and optimization problems in supply networks such as power grids. BP algorithms make use of factor graph representations, whose assignment to the problem of interest is not unique. It depends on the state variables and their mutual interdependencies. Many short loops in factor graphs may impede the accuracy of BP. We propose a systematic way to cluster loops of naively assigned factor graphs such that the resulting transformed factor graphs have no additional loops as compared to the original network. They guarantee an accurate performance of BP with only slightly increased computational effort, as we demonstrate by a concrete and realistic implementation for power grids. The method outperforms existing alternatives to handle the loops. We point to other applications to supply networks such as gas-pipeline or other flow networks that share the structure of constraints in the form of analogues to Kirchhoff's laws. Whenever small and abundant loops in factor graphs are systematically generated by constraints between variables in the original network, our factor-graph assignment in BP complements other approaches. It provides a fast and reliable algorithm to perform marginalization in tasks like state determination, estimation, or optimization issues in supply networks.
The plasma-liquid interaction is an important issue in plasma technology. The simulation of discharge in spherical bubbles in the water that produced plasma-activated water (PAW) is investigated using finite element methods (FEM) for a simulated 2D dielectric barrier discharge in three different geometries. The electron density changes with voltage, frequency, dielectric thickness, and bubble radius are investigated in different time duration. The results show that electron density increases linearly by increasing voltage, frequency and bubble radius, while it is vice versa for dielectric thickness. High plasma density indicates sufficient plasma-water interaction.
Takahiro Murono, Kenta Hongo, Kousuke Nakano
et al.
Controlling the water contact angle on a surface is important for regulating its wettability in industrial applications, which involves developing ab initio prediction scheme of accurately predicting the angle. The scheme requires structural models for the adsorption of liquid molecules on a surface, but their reliability depend on whether the surfaces comprise insulating or metallic materials. Previous ab initio studies have focused on the estimation of the water contact angle on insulators, where the periodic-honeycomb array of water molecules was adopted as the adsorption model for the water on the insulating surface and succeeded in the insulating cases. This study, however, focus on the water contact angle on a metallic surface, and propose a simple ab initio based estimation scheme. We not only adopt the previously proposed structural modeling based on the periodic-honyecomb array, but also consider an ensemble of isolated water oligomers that have different molecular coverage (ML) values. We established a statistic model to predict a contact angle of the water wetting on a Cu(111) surface: The coverage-dependent contact angles obtained from each of the isolated clusters was fit to a quadratic regression, and the contact angle was interpolated by referring to a ML value of water layer in literature. This interpolated value lay within the deviation of experimental angles. In addition, the Boltzmann-average over the isolated clusters was found to agree well with the interpolated one. This indicates that the Boltzmann-average is useful for estimating the contact angle of other metallic surfaces without knowing a ML value a priori.
Heterogeneous nucleation and subsequent growth of surface water occur on the natural substrate when the water vapor concentration reached the point of super-saturation. This study focuses on the parameterization of super-saturation on the canopy-air interface by field observations monitoring surface water formation (SWF) such as dew and frost in the evergreen shrub at an urban cite during autumn and winter in 2015-2017. Here we show that both the interfacial and vertical temperature differences ranged from 1 to 3 K and were necessary but not sufficient for super-saturated condensation on the natural surface. Excessive supplies of moisture must exist, continuously contribute to the growth of the condensed water embryos, originate from both the local and the external sources such as evapotranspiration and atmospheric advection driven by the reduced air pressure, cause SWF not only on the ground soil but also on the vegetation canopy at 1-2 m height. The super-saturation ratio is mainly determined by the coefficient of thermophoresis deposition, which approaches to 1. SWF on the natural surface is not only an indicator but also a weak cleaner of air pollution. The downward thermophoresis deposition of fine particle and droplets favors SWF and the scavenging of air pollutants. The removal efficiency of the deposition flux during SWF event for [SO42-+NO3-] is estimated by ~0.3 mmol (per [Ca2+] meq)/m2(per leaf area).
Water is the most important liquid in the Universe. At the same time it is the most anomalous liquid. It demonstrates several dozens of anomalies, among which are density anomaly, diffusion anomaly etc. Anomalous behavior of water is a topic numerous publications. However, most of the publications investigate the anomalous behavior of water in the vicinity of critical points: the liquid-gas critical point and the second hypothetical critical point in supercooled region. Here we analyze experimental data on such properties of water as heat capacity, speed of sound, dynamic viscosity and thermal conductivity. We show that these properties demonstrate anomalous maxima and minima in a region which is far from both critical points. Therefore, we find a novel region of anomalous properties of water (anomalous triangle) which cannot be related to critical fluctuations. We also perform a molecular dynamics simulations of this region with two common water models - SPC/E and TIP4P - and show that these models fail to describe the novel anomalous region.
Visible light, ultraviolet and x-ray radiation have been found to increase chemical reactivity of water. The irradiated solution of water in acetonitrile reacts with triethyl phosphite considerably faster than the non-irradiated control solution. This phenomenon is accounted for by the decomposition of water clusters under the influence of light with the formation of chemically more active free water molecules.
Topological concepts have been introduced into electronic, photonic, and phononic systems, but have not been studied in surface-water-wave systems. Here we study a one-dimensional periodic resonant surface-water-wave system and demonstrate its topological transition. By selecting three different water depths, we can construct different types of water waves - shallow, intermediate and deep water waves. The periodic surface-water-wave system consists of an array of cylindrical water tanks connected with narrow water channels. As the width of connecting channel varies, the band diagram undergoes a topological transition which can be further characterized by Zak phase. This topological transition holds true for shallow, intermediate and deep water waves. However, the interface state at the boundary separating two topologically distinct arrays of water tanks can exhibit different bands for shallow, intermediate and deep water waves. Our work studies for the first time topological properties of water wave systems, and paves the way to potential management of water waves.
Water dissociation is a rate limiting step in many industrially important chemical reactions. In this investigation, climbing image nudged elastic band (CINEB) method, within the framework of density functional theory, is used to report the activation energies (E a ) of water dissociation on Cu(111) surface with a vacancy. Introduction of vacancy results in a reduced coordination of the dissociated products, which facilitates their availability for reactions that involve water dissociation as an intermediate step. Activation energy for dissociation of water reduces by nearly 0.2 eV on Cu(111) surface with vacancy, in comparison with that of pristine Cu(111) surface. We also find that surface modification of the Cu upper surface is one of the possible pathways to dissociate water when the vacancy is introduced. Activation energy, and the minimum energy path (MEP) leading to the transition state remain same for various product configurations. CINEB corresponding to hydrogen gas evolution is also performed which shows that it is a two step process involving water dissociation. We conclude that the introduction of vacancy facilitates the water dissociation reaction, by reducing the activation energy by about 20%.
We use near infrared spectroscopy to obtain concentration dependent glucose absorption spectra in their aqueous solutions in the near-infrared range (3800 - 7500 cm^{-1}). We introduce a new method to obtain reliable glucose absorption bands from aqueous glucose solutions without measuring the water displacement coefficients of glucose separately. Additionally, we are able to extract the water displacement coefficients of glucose, and this may give a new general method using spectroscopy techniques applicable to other water soluble materials. We also observe red shifts in the absorption bands of water in the hydration shell around solute molecules, which comes from contribution of the interacting water molecules around the glucose molecules in solutions. The intensity of the red shift get larger as the concentration increases, which indicates that as the concentration increases more water molecules are involved in the interaction. However, the red shift in frequency does not seem to depend significantly on the concentration up to our highest concentration. We also performed the same measurements and analysis with sucrose instead of glucose as solute and compare.
We investigate water and deuterated water chemistry in turbulent protoplanetary disks. Chemical rate equations are solved with the diffusion term, mimicking turbulent mixing in vertical direction. Water near the midplane is transported to the disk atmosphere by turbulence and destroyed by photoreactions to produce atomic oxygen, while the atomic oxygen is transported to the midplane and reforms water and/or other molecules. We find that this cycle significantly decreases column densities of water ice at r < 30 AU, where dust temperatures are too high to reform water ice effectively. The radial extent of such region depends on the desorption energy of atomic hydrogen. Our model indicates that water ice could be deficient even outside the sublimation radius. Outside this radius, the cycle decreases the D/H ratio of water ice from 2x10^-2, which is set by the collapsing core model, to 10^-4-10^-2 in 10^6 yr, without significantly decreasing the water ice column density. The resultant D/H ratios depend on the strength of mixing and the radial distance from the central star. Our finding suggests that the D/H ratio of cometary water (10^-3-10^-4) could be established (i.e. cometary water could be formed) in the solar nebula, even if the D/H ratio of water ice delivered to the disk was very high (10^-2).