Psychological scale refinement traditionally relies on response-based methods such as factor analysis, item response theory, and network psychometrics to optimize item composition. Although rigorous, these approaches require large samples and may be constrained by data availability and cross-cultural comparability. Recent advances in natural language processing suggest that the semantic structure of questionnaire items may encode latent construct organization, offering a complementary response-free perspective. We introduce a topic-modeling framework that operationalizes semantic latent structure for scale simplification. Items are encoded using contextual sentence embeddings and grouped via density-based clustering to discover latent semantic factors without predefining their number. Class-based term weighting derives interpretable topic representations that approximate constructs and enable merging of semantically adjacent clusters. Representative items are selected using membership criteria within an integrated reduction pipeline. We benchmarked the framework across DASS, IPIP, and EPOCH, evaluating structural recovery, internal consistency, factor congruence, correlation preservation, and reduction efficiency. The proposed method recovered coherent factor-like groupings aligned with established constructs. Selected items reduced scale length by 60.5% on average while maintaining psychometric adequacy. Simplified scales showed high concordance with original factor structures and preserved inter-factor correlations, indicating that semantic latent organization provides a response-free approximation of measurement structure. Our framework formalizes semantic structure as an inspectable front-end for scale construction and reduction. To facilitate adoption, we provide a visualization-supported tool enabling one-click semantic analysis and structured simplification.
Street intersection counts and densities are ubiquitous measures in transport geography and planning. However, typical street network data and typical street network analysis tools can substantially overcount them. This article explains the three main reasons why this happens and presents solutions to each. It contributes algorithms to automatically simplify spatial graphs of urban street networks---via edge simplification and node consolidation---resulting in faster parsimonious models and more accurate network measures like intersection counts and densities, street segment lengths, and node degrees. These algorithms' information compression improves downstream graph analytics' memory and runtime efficiency, boosting analytical tractability without loss of model fidelity. Finally, this article validates these algorithms and empirically assesses intersection count biases worldwide to demonstrate the problem's widespread prevalence. Without consolidation, traditional methods would overestimate the median urban area intersection count by 14%. However, this bias varies drastically across regions, underscoring these algorithms' importance for consistent comparative empirical analyses.
Daniil Averkov, Gregory Emdin, Viktoriia Krivogornitsyna
et al.
The Boolean circuit simplification problem involves finding a smaller circuit that computes the same function as a given Boolean circuit. This problem is closely related to several key areas with both theoretical and practical applications, such as logic synthesis, satisfiability, and verification. In this paper, we present Simplifier, a new open source tool for simplifying Boolean circuits. The tool optimizes subcircuits with three inputs and at most three outputs, seeking to improve each one. It is designed as a low-effort method that runs in just a few seconds for circuits of reasonable size. This efficiency is achieved by combining two key strategies. First, the tool utilizes a precomputed database of optimized circuits, generated with SAT solvers after carefully clustering Boolean functions with three inputs and up to three outputs. Second, we demonstrate that it is sufficient to check a linear number of subcircuits, relative to the size of the original circuit. This allows a single iteration of the tool to be executed in linear time. We evaluated the tool on a wide range of Boolean circuits, including both industrial and hand-crafted examples, in two popular formats: AIG and BENCH. For AIG circuits, after applying the state-of-the-art ABC framework, our tool achieved an additional 4% average reduction in size. For BENCH circuits, the tool reduced their size by an average of 30%.
Le Trong Thanh Bui, Thi Kim Loan Huynh, Bao Quoc Tang
et al.
Singular limits for the following indirect signalling chemotaxis system \begin{align*} \left\{ \begin{array}{lllllll} \partial_t n = Δn - \nabla \cdot (n \nabla c ) & \text{in } Ω\times(0,\infty) , \varepsilon \partial_t c = Δc - c + w & \text{in } Ω\times(0,\infty), \varepsilon \partial_t w = τΔw - w + n & \text{in } Ω\times (0,\infty), \partial_νn = \partial_νc = \partial_νw = 0, &\text{on } \partialΩ\times (0,\infty) %(n,c,w)_{t=0} = (n_0,c_0,w_0) & \text{on } Ω, \end{array} \right. \end{align*} are investigated. More precisely, we study parabolic-elliptic simplification, or PES, $\varepsilon\to 0^+$ with fixed $τ>0$ up to the critical dimension $N=4$, and indirect-direct simplification, or IDS, $(\varepsilon,τ)\to (0^+,0^+)$ up to the critical dimension $N=2$. These are relevant in biological situations where the signalling process is on a much faster time scale compared to the species diffusion and all interactions. Showing singular limits in critical dimensions is challenging. To deal with the PES, we carefully combine the entropy function, an Adam-type inequality, the regularisation of slow evolution, and an energy equation method to obtain strong convergence in representative spaces. For the IDS, a bootstrap argument concerning the $L^p$-energy function is devised, which allows us to obtain suitable uniform bounds for the singular limits. Moreover, in both scenarios, we also present the convergence rates, where the effect of the initial layer and the convergence to the critical manifold are also revealed.
More than 10 billion tons of construction and demolition waste (CW) are generated globally each year, exerting a significant impact on the environment. In the CW recycling process, the government and the carrier are the two primary stakeholders. The carrier is responsible for transporting CW from production sites to backfill sites or processing facilities, with a primary focus on transport efficiency and revenue. Meanwhile, the government aims to minimize pollution from the recycling system, which is influenced by transport modes, shipment distances, and the processing methods used for CW. This paper develops a bi-objective, bi-level optimization model to address these challenges. The upper-level model is a linear programming model that optimizes the government's subsidy scheme, while the lower-level model is a minimum-cost flow model that optimizes the carrier's recycling plan. A hybrid heuristic solution method is proposed to tackle the problem's complexity. A case study in Chengdu, China, demonstrates the computational efficiency of the model and its small solution gap. With an optimized subsidy scheme and recycling plan, pollution can be reduced by over 29.29% through a relatively small investment in subsidies.
We proposed an equation of motion as a constraint condition on the gauge degree of freedom in general relativity theory based on a co-moving framework. This constraint equation transformed the gauge degree freedom of general relativity theory into an natural equation of motion, and provide an explicit theoretical understanding on the Mach's principle and rotating bucket experiment. The galaxy rotation curves is derived directly from general relativity theory under this constraints equation. This work may inspires different understanding on dark matter, dark energy, and the quantization of gravity.
Muhammad Mohsin, Stefano Rovetta, Francesco Masulli
et al.
Critical Raw Materials (CRMs) such as copper, manganese, gallium, and various rare earths have great importance for the electronic industry. To increase the concentration of individual CRMs and thus make their extraction from Waste Printed Circuit Boards (WPCBs) convenient, we have proposed a practical approach that involves selective disassembling of the different types of electronic components from WPCBs using mechatronic systems guided by artificial vision techniques. In this paper we evaluate the real-time accuracy of electronic component detection and localization of the Real-Time DEtection TRansformer model architecture. Transformers have recently become very popular for the extraordinary results obtained in natural language processing and machine translation. Also in this case, the transformer model achieves very good performances, often superior to those of the latest state of the art object detection and localization models YOLOv8 and YOLOv9.
The compactness of routes in distribution plans is a criterion that has not been sufficiently explored in the literature related to logistics distribution but has shown to have a significant impact on the practical implementation of routing plans, for example in solid waste collection problems. In this regard, this article presents a bi-objective model to optimize the vehicle routing problem with time constraints, considering the minimization of travel times and the compactness of routes. Experimental tests were conducted on small-scale instances using two exact solution methods for multi-objective problems: weighted sum and augmented ε-constraint methods. The results obtained allowed us to explore the trade-off relationship between both objectives while evaluating the computational efficiency of both multi-objective solution methods.
Thorben Schomacker, Michael Gille, Jörg von der Hülls
et al.
This paper examines the current state-of-the-art of German text simplification, focusing on parallel and monolingual German corpora. It reviews neural language models for simplifying German texts and assesses their suitability for legal texts and accessibility requirements. Our findings highlight the need for additional training data and more appropriate approaches that consider the specific linguistic characteristics of German, as well as the importance of the needs and preferences of target groups with cognitive or language impairments. The authors launched the interdisciplinary OPEN-LS project in April 2023 to address these research gaps. The project aims to develop a framework for text formats tailored to individuals with low literacy levels, integrate legal texts, and enhance comprehensibility for those with linguistic or cognitive impairments. It will also explore cost-effective ways to enhance the data with audience-specific illustrations using image-generating AI. For more and up-to-date information, please visit our project homepage https://open-ls.entavis.com
A computational graph in a deep neural network (DNN) denotes a specific data flow diagram (DFD) composed of many tensors and operators. Existing toolkits for visualizing computational graphs are not applicable when the structure is highly complicated and large-scale (e.g., BERT [1]). To address this problem, we propose leveraging a suite of visual simplification techniques, including a cycle-removing method, a module-based edge-pruning algorithm, and an isomorphic subgraph stacking strategy. We design and implement an interactive visualization system that is suitable for computational graphs with up to 10 thousand elements. Experimental results and usage scenarios demonstrate that our tool reduces 60% elements on average and hence enhances the performance for recognizing and diagnosing DNN models. Our contributions are integrated into an open-source DNN visualization toolkit, namely, MindInsight [2].
Bridget K. Mutuma, Ndeye F. Sylla, Amanda Bubu
et al.
This study aims at demonstrating that wastes from anaerobic biodigester plants can be effectively valorized as functional materials to be implemented in technologies that enable efficient energy management and water treatment, therefore simultaneously addressing the Water-Energy-Waste Nexus challenges. Lignin, the main solid residue of the biodigester plant, has been valorized into activated biochar with a mild activation agent, like KHCO3, to produce electrode of supercapacitors and microbial fuel cells. In addition, the same sludge that is the liquid effluent of the biodigester plant has been exploited as inoculum and electrolyte for the MFC. The lignin derived carbons obtained at lignin/KHCO3 mass ratios of 1:0.5 (LAC-0.5) and 1:2 (LAC-2) comprised of mesopores and micropores displaying BETs of 1558 m2/g and 1879 m2/g, respectively. LAC-2 carbon exhibited a superior specific capacitance of 114 F/g in 2.5 M KNO3 with respect to LAC-0.5. A supercapacitor with LAC-2 electrodes was built displaying specific energy specific power up to 10 Wh/kg and 6.9 kW/kg, respectively. Durability tests showed that the device was able to maintain a capacitance retention of 84.5% after 15,000 charge-discharge cycles. The lignin-derived carbons were also studied as electrocatalysts for ORR in a neutral medium. The LAC-2 showed higher ORR electrocatalytic activity than LAC-0.5. The interconnected porous network and the high surface area made the lignin-derived porous carbons suitable electrode materials for dual applications. The feasibility of the use of LAC 2 carbon incorporated in an air breathing cathode for MFC applications is also reported.
Jon Hasselgren, Jacob Munkberg, Jaakko Lehtinen
et al.
We present a suite of techniques for jointly optimizing triangle meshes and shading models to match the appearance of reference scenes. This capability has a number of uses, including appearance-preserving simplification of extremely complex assets, conversion between rendering systems, and even conversion between geometric scene representations. We follow and extend the classic analysis-by-synthesis family of techniques: enabled by a highly efficient differentiable renderer and modern nonlinear optimization algorithms, our results are driven to minimize the image-space difference to the target scene when rendered in similar viewing and lighting conditions. As the only signals driving the optimization are differences in rendered images, the approach is highly general and versatile: it easily supports many different forward rendering models such as normal mapping, spatially-varying BRDFs, displacement mapping, etc. Supervision through images only is also key to the ability to easily convert between rendering systems and scene representations. We output triangle meshes with textured materials to ensure that the models render efficiently on modern graphics hardware and benefit from, e.g., hardware-accelerated rasterization, ray tracing, and filtered texture lookups. Our system is integrated in a small Python code base, and can be applied at high resolutions and on large models. We describe several use cases, including mesh decimation, level of detail generation, seamless mesh filtering and approximations of aggregate geometry.
The availability of parallel sentence simplification (SS) is scarce for neural SS modelings. We propose an unsupervised method to build SS corpora from large-scale bilingual translation corpora, alleviating the need for SS supervised corpora. Our method is motivated by the following two findings: neural machine translation model usually tends to generate more high-frequency tokens and the difference of text complexity levels exists between the source and target language of a translation corpus. By taking the pair of the source sentences of translation corpus and the translations of their references in a bridge language, we can construct large-scale pseudo parallel SS data. Then, we keep these sentence pairs with a higher complexity difference as SS sentence pairs. The building SS corpora with an unsupervised approach can satisfy the expectations that the aligned sentences preserve the same meanings and have difference in text complexity levels. Experimental results show that SS methods trained by our corpora achieve the state-of-the-art results and significantly outperform the results on English benchmark WikiLarge.
Yannic Vaupel, Wolfgang R. Huster, Adel Mhamdi
et al.
Waste heat recovery for trucks via organic Rankine cycle is a promising technology to reduce fuel consumption and emissions. As the vehicles are operated in street traffic, the heat source is subject to strong fluctuations. Consequently, such disturbances have to be considered to enable safe and efficient operation. Herein, we find optimal operating policies for several representative scenarios by means of dynamic optimization and discuss the implications on control strategy design. First, we optimize operation of a typical driving cycle with data from a test rig. Results indicate that operating the cycle at minimal superheat is an appropriate operating policy. Second, we consider a scenario where the permissible expander power is temporarily limited, which is realistic in street traffic. In this case, an operating policy with flexible superheat can reduce the losses associated with operation at minimal superheat by up to 53 % in the considered scenario. As the duration of power limitation increases, other constraints might become active which results in part of the exhaust gas being bypassed, hence reduced savings.
Abstract. The testing of low-permeable materials is challenging. Yet, for the disposal of radioactive waste, it is essential, too. This workshop is aimed at gathering ambitious scientists to discuss and to collaborate on their experiences in the laboratory testing of low-permeable materials. The focus here is on the methods: What method is best for what kind of low-permeable host rock (salt/clay) and for what kind of technical barrier material (bentonite/crushed salt)? How can measurement errors be correctly determined? What are the crucial “bottlenecks” in the device setups? How can high porous but low permeable samples best be pre-saturated? How can coupled flow and cumbersome gas traps in the tests be dealt with? What is the best-practice analysis of permeability from pressure decay recordings? Is there a hope of defining a standardized procedure for low-permeability testing? These points will be reflected in the light of radioactive waste disposal and in the need to find a best-practice solution when it comes to eventual evaluation and comparison of potential underground disposal sites.
Abstract. This contributed poster shows the current state of development of a finite element implementation as part of an open source software library (OSSL) for the simulation of thermo-hydro-mechanical (THM) coupled processes. The reliable handling of numerical methods is fundamental for the understanding of scientific interrelationships and thus, a crucial prerequisite for modeling THM scenarios, as well as for the understanding and evaluation of preliminary safety investigations during the site selection process for the storage of high-level radioactive waste. There are several motivations for developing an in-house OSSL, which will allow us to: Build capacity and maintenance within BASE (Federal Office for the Safety of Nuclear Waste Management) regarding issues of the numerical modeling of safety-relevant aspects on the long-term safety analyses specified by the German legislator in the site selection process. Develop a collection of known benchmarks and evaluation examples for the comparison of different software tools, applying a uniform interface to simplify the use of the available highly specialized open source codes. Diversify the testing possibilities regarding the preliminary safety investigations by means of our own, independent modeling software. Document basic THM scenarios for internal or, if necessary, public technical training, e.g., density-driven fluid flow (Fig. 1), convergence in salt, temperature propagation in the repository area, crack development, diffusive or advective mass transport. Ensure transparency and, in principle, might allow for appropriately proven-quality (validated) and documented simulation tools for the public regarding questions about the preliminary safety investigations during the site selection process. The development of the OSSL is mainly based on the scripting language Python, which allows the necessary flexibility for the diverse fields of application and at the same time enables maximum transparency for all aspects of the source code. To ensure the high quality of the software, state of the art development tools are used (e.g., version control, automated tests, and documentation generation). Figure 1 shows our preliminary simulation results of the so-called Elder problem (Elder, 1967), a popular standard benchmark for thermo-hydrogeological coupling in which fluid motion in a porous medium is driven by buoyancy forces.
Abstract. In Germany it is planned to directly dispose spent nuclear fuel (SNF) from nuclear power plants together with other high-level radioactive wastes (HLW) from former SNF reprocessing (e.g., vitrified waste), in a deep geological repository for heat-generating wastes – the siting process for this repository was started in 2017 and is ongoing. Based on several decades of research, development, and demonstration (RD&D) it is generally accepted at the technical and scientific level that direct disposal of HLW and SNF in deep mined geological repositories is the safest and most sustainable option (CEC, 2011; IAEA, 2004). The current efforts to improve the performance and accident tolerance of fuels in nuclear power generation resulted in an increased utilization of a variety of new types of light-water reactor (LWR) fuels such as fuels doped with Cr, Al, and Si. This doping leads to a significant change of the microstructure of the fuel matrix. The corrosion behavior of these types of fuels under conditions relevant to deep geological disposal has hardly been studied so far; however, this is of crucial importance as the development of a robust safety case for deep geological disposal of SNF requires a solid understanding of its dissolution behavior over very long time scales (up to 1 million years). To fill this knowledge gap, additional systematic studies on modern doped UO2 fuels were needed. Corrosion experiments with SNF cannot entirely unravel all of the various concurring effects of the dissolution mechanism due to the chemical and structural complexity of SNF and its high beta and gamma radiation field during the first 1000 years; moreover, technical restrictions only allow a very limited number of experiments. Therefore, within the EU-DisCo project (https://www.disco-h2020.eu, last access: 11 October 2021), a very ambitious programme of corrosion studies on irradiated Cr and Al/Cr doped fuels was carried out, which was complemented by systematic single-effect dissolution studies (e.g., with respect to doping level, grain size and thermodynamic aspects) performed on carefully prepared and characterized, simplified UO2-based model materials. Here, we present recent results on the dissolution behavior of tailor-made UO2 model materials in accelerated static batch experiments using H2O2 as simulant for radiolytic oxidants, present in long-term disposal scenarios for SNF in failed container conditions due to the alpha irradiation of water. In these dissolution experiments pure UO2 reference pellets exhibiting different densities and grain sizes, as well as Cr-doped UO2 pellets with various Cr-doping levels, produced using different doping methods having different grain sizes, were used. In addition, Nd-doped and industrially produced Cr- and Cr/Nd-doped UO2 pellets were used to determine the influence of these parameters on the dissolution rates. The dissolution experiments were performed under strictly controlled conditions with respect to exclusion of oxygen, temperature control, and exclusion of light. This bottom-up approach was followed to understand how the addition of Cr-oxide into the fuel matrix affects SNF dissolution behavior under repository relevant conditions. The results of the dissolution experiments performed with real SNF and the model materials obtained by the DisCo partners build the basis for numerical simulations on the dissolution behavior of modern SNF. First results of the data evaluation indicate that the addition of dopants and the consequential modification of the fuel matrix does not lead to a significant change of the dissolution behavior of these fuels under repository relevant conditions compared to standard SNF (i.e. dissolution rates agree within an order of magnitude).
Abstract. The amendment to the atomic act in 2011 results to phase out nuclear energy in Germany until the end of 2022. Subsequently, the licensee of the nuclear power plant is responsible for decommissioning and dismantling. During operation, activation of structures near the core of the reactor occur which govern the amount of radioactive waste, the dose rate distribution and dismantling strategies. Thus, a detailed radiological characterization of in-core and out-core structures is required to optimize decommissioning processes regarding the quantification and minimization of radioactive waste, radiation protection and reducing radiation exposure. These objectives are achieved using an innovative and efficient method developed and applied at the Chair of Repository Safety (Lehrstuhl für Endlagersicherheit, ELS) RWTH Aachen University. Within the framework of the joint project „Development of a methodology for activity analysis and dose rate estimation“, funded by the Federal ministry of Education and Research, approaches the objective to develop a standardized and highly resolved method to calculate time-dependent activity of components and structures near the reactor core based on operating history of the nuclear power plant and neutron fluence distribution. The approach requires the development of a detailed model for Monte-Carlo simulations which provides the basis to neutron fluence, neutron spectra and radiation transport simulations. To calculate the nuclide specific 3-Dimensional (3D) activity distribution of the entire facility, a facility-dependent activation cross section library is produced which focuses on recent nuclear databases (ENDF/B-VIII.0). A highly resolved and space-dependent 3D activity distribution of the entire facility is obtained using a modular program package, developed at ELS, including the activation code ORIGEN2. The results are produced in the form of detailed 3D activity maps. The source terms are generated on the basis of the space-dependent 3D activity distribution using an additional module of the program package. The combination of recent nuclear databases focusing on ENDF/B-VII.1 and complemented by JEFF-3.3 ensures a comprehensive characterisation of source terms. Subsequently, source terms are prepared for 3D radiation transport simulation using the Monte-Carlo method and the computer code MCNP. The simulations are conducted separately for each individual component obtaining the partial contribution of all in-core and out-core structures as well as the dose rate distribution of the entire facility. Similar to the activity calculation, the simulation results are used to generate 3D gamma flux and dose rate maps using the graphic module of the whole program system. On the basis of the radiological characterisation and in view of a high-level radiation protection these maps allow the optimum planning and realisation of the decommissioning and dismantling process of the nuclear power plant.
E. Vlassopoulos, S. Pudollek, Olympios Alifieris
et al.
Abstract. Radioactive waste in Switzerland will be disposed of in a deep geological repository (DGR). Responsible for the planning and preparation of realization of this task is National Cooperative for the Disposal of Radioactive Waste (Nagra). Spent fuel assemblies (SFA) constitute the main high-level waste (HLW) stream that will be disposed in the DGR. Prior to final disposal they will be transferred or transported to an encapsulation plant, where they will be loaded into final disposal canisters. To ensure that the structural integrity of SFAs is not compromised during handling and transportation, it is desirable to characterize the expected mechanical parameters of SFAs after long-term interim storage. Experimental research activities performed at the JRC Karlsruhe include safety aspects of radioactive waste management, encompassing also spent fuel storage and spent fuel/HLW disposal activities. Nagra and JRC have established a collaboration to jointly study relevant properties and behaviours of spent fuel rods, with the support of the Gösgen nuclear power plant and of Framatome, and in collaboration with other partners in Europe and internationally. As part of this collaboration, 3-point bending and impact tests were performed at the hot-cell facilities of JRC Karlsruhe, to determine the mechanical response of spent fuel rodlets under quasi-static and dynamic loads. The structural integrity of fuel rods was also evaluated under different handling scenarios using finite element (FE) analysis. Starting with the construction of a static 3D FE model of a Pressurized Water Reactor (PWR) nuclear fuel rodlet in ANSYS Mechanical, Nagra has developed a series of FE models over the years. Mechanical properties of the original rodlet model were derived through an extensive validation process, using experimental data from the 3-point bending tests. To evaluate the mechanical response of an SFA in different loading scenarios, this model was expanded using 1D beam modeling approach. The development of the simplified 1D models is shown in this presentation. In particular, the effect of the contact formulation between the spacer grid and the rods is discussed. Finally, preliminary results of the bending response of a 15×15 PWR SFA sub-model are presented.
Ross Duncan, Aleks Kissinger, Simon Perdrix
et al.
We present a completely new approach to quantum circuit optimisation, based on the ZX-calculus. We first interpret quantum circuits as ZX-diagrams, which provide a flexible, lower-level language for describing quantum computations graphically. Then, using the rules of the ZX-calculus, we give a simplification strategy for ZX-diagrams based on the two graph transformations of local complementation and pivoting and show that the resulting reduced diagram can be transformed back into a quantum circuit. While little is known about extracting circuits from arbitrary ZX-diagrams, we show that the underlying graph of our simplified ZX-diagram always has a graph-theoretic property called generalised flow, which in turn yields a deterministic circuit extraction procedure. For Clifford circuits, this extraction procedure yields a new normal form that is both asymptotically optimal in size and gives a new, smaller upper bound on gate depth for nearest-neighbour architectures. For Clifford+T and more general circuits, our technique enables us to to `see around' gates that obstruct the Clifford structure and produce smaller circuits than naive 'cut-and-resynthesise' methods.