Modeling Toolkit Research Articles

Response Mitigation of Floating Platform by Porous-Media-Tuned Liquid Dampers

AbstractA porous-media-tuned liquid damper (PMTLD) can serve as an effective and economical dynamic vibration absorber. Placing porous media within a water tank can improve the capacity for energy dissipation and optimize the performance by varying its material properties. Two numerical models are adopted to simulate the sloshing problem in PMTLD and the dynamics of a floating platform in waves. Besides, the effectiveness of response mitigation can be verified numerically. The first potential-based approach employs a mixed-type boundary value problem (BVP) solver and a free-surface particle tracker. This approach not only simulates the inviscid water wave but also includes the nonlinear damping of the PMTLD via a quadratic Forchheimer term. Another equivalent mechanical model is used to reduce the degree-of-freedom of the PMTLD system. The Newmark method is incorporated to solve the rigid-body dynamics. The second viscous approach uses the finite element method (FEM) to spatially discretize the Navier–Stokes (NS) equations and handles the free surface via the volume of fluid (VOF) and the level set (LS) equations. The multiphase simulation is implemented by computational modeling toolkits, Proteus and Chrono, for the fluid and solid phases, respectively. The correlations between potential flow and two-phase NS models are presented. The PMTLD is designed by analogy with the tuned mass damper (TMD). Numerical results show that the PMTLD can effectively reduce the structure's dynamic response in terms of vibration amplitude around resonance. Such damping devices have great potential for offshore platforms and wind turbine design.

An automatic speech recognition system in Indian and foreign languages: A state-of-the-art review analysis

Speech Recognition is one of the prominent research topics in the field of Natural Language Processing (NLP). The Speech Recognition technique removes the barriers and makes the system ease for inter-communication between human beings and devices. The aim of this study is to analyze the Automatic Speech Recognition System (ASRS) proposed by different researchers using Machine learning and Deep Learning techniques. In this work, Indian and foreign languages speech recognition systems like Hindi, Marathi, Malayalam, Urdu, Sanskrit, Nepali, Kannada, Chinese, Japanese, Arabic, Italian, Turkish, French, and German are considered. An integrated framework is presented and elaborated with recent advancement. The various platform like Hidden Markov Model Toolkit (HMM Toolkit), CMU Sphinx, Kaldi toolkit are explained which is used for building the speech recognition model. Further, some applications are elaborated which depict the uses of ASRS.

The Modeling Toolkit: how recruitment strategies for modeling positions influence model progress

Hydrological models play a key role in contemporary hydrological scientific research, but the social practices surrounding the use of these models receive little attention. This study focuses on the recruitment process for scientific positions in which models are used, to understand the implications for model development. Over 400 scientific hydrological vacancies were analyzed, to evaluate whether the job description already prescribed which model must be used, and whether experience with a specific model was an asset. Of the analyzed job positions, 76% involved at least some modeling. Of the PhD positions that involved any modeling, the model is already prescribed in the vacancy text in 17% of the cases, for postdoc positions this was 30%. A small questionnaire revealed that also beyond the vacancies where the model is already prescribed, in many Early-Career Scientist (ECSs) projects the model to be used is pre-determined and, actually, also often used without further discussion. There are valid reasons to pre-determine the model in these projects, but at the same time, this can have long-term consequences for the ECS. An ECS develops a “Modeling Toolkit”, a toolkit that contains all the models where the ECS has experience with. This toolkit influences the research identity the ECS develops, and influences future opportunities of the ECS—it might be strategic to gain experience with popular, broadly used models, or to become part of an efficient modeling team. This serves an instrumental vision on modeling and maintains the status quo. Seeing models as hypotheses calls for a more critical evaluation. ECSs learn the current rules of the game, but should at the same time actively be stimulated to critically question these rules.

Dumbbell-shaped brains of Polish crested chickens as a model system for the evolution of novel brain morphologies.

The evolutionary history of vertebrates is replete with emergence of novel brain morphologies, including the origin of the human brain. Existing model organisms and toolkits for investigating drivers of neuroanatomical innovations have largely proceeded on mammals. As such, a compelling non-mammalian model system would facilitate our understanding of how unique brain morphologies evolve across vertebrates. Here, we present the domestic chicken breed, white crested Polish chickens, as an avian model for investigating how novel brain morphologies originate. Most notably, these crested chickens exhibit cerebral herniation from anterodorsal displacement of the telencephalon, which results in a prominent protuberance on the dorsal aspect of the skull. We use a high-density geometric morphometric approach on cephalic endocasts to characterize their brain morphology. Compared with standard white Leghorn chickens (WLCs) and modern avian diversity, the results demonstrate that crested chickens possess a highly variable and unique overall brain configuration. Proportional sizes of neuroanatomical regions are within the observed range of extant birds sampled in this study, but Polish chickens differ from WLCs in possessing a relatively larger cerebrum and smaller cerebellum and medulla. Given their accessibility, phylogenetic proximity, and unique neuroanatomy, we propose that crested breeds, combined with standard chickens, form a promising comparative system for investigating the emergence of novel brain morphologies.

A scenario-specific nexus modelling toolkit to identify trade-offs in the promotion of sustainable irrigated agriculture in Ecuador, a Belt and Road country

Increased demand for food due to development and population growth has prompted irrigated agriculture expansion, posing enhanced global challenges to water, energy, and food security. To confront these challenges, an approach that considers the water-energy-food-environment nexus can address multidimensional trade-offs that complicate the efficient use of resources and the achievement of Sustainable Development Goals. In order to provide insights into solutions to these challenges for a specific case, this study develops a modelling toolkit that integrates biophysical and socioeconomic aspects of nexus components in the context of agro-export and irrigation expansion in Ecuador, a Belt and Road Country. The nexus toolkit is applied to agricultural-development scenarios defined in participatory workshops and incorporates a water resources model, a lifecycle environmental assessment, and a socioeconomic analysis. The modelling exercise is constructed around specific scenario-determined land use patterns in the Santa Elena peninsula of Ecuador. Agriculture in the peninsula is water-limited, relying on delivery infrastructure and transfers from a neighbouring catchment. Impacts on nexus components are analysed for ten crops under two potential land-use scenarios: a substantial increase in irrigated area due to investment in irrigation infrastructure; and a substantial shift in land use towards export crops. The two have distinct impact on water and energy use, global warming potential, freshwater eutrophication, terrestrial acidification, and fine particulate matter formation. The results provide insights into future water and energy resource challenges and environmental and socioeconomic trade-offs associated with likely changes in irrigation expansion. The results for scenarios show that, for example, banana production has the greatest environmental impacts (e.g. a 519% increase in global warming potential and 452% increase in fine particulate matter form for scenario 2), primarily due to water and energy requirements, despite the crop being mainly produced organically. In addition, total net income and labour demand increase (net income increases by 43% and 217% under scenarios 1 and 2, respectively) due to a larger crop area and crop intensification. Scale effects on labour demand are mainly due to labour intensity of maize in Ecuador, which is disadvantaged in the crop export scenario (an unexpected result). However, expanding irrigated areas would also increase total water and energy demand for irrigation, global warming potential, and freshwater eutrophication. This type of information enables stakeholders and decision-makers to design policies that achieve equitable and sustainable agricultural production, water use, and economic growth.

Development and Application of Particle Transport Monte Carlo Simulation Modeling Toolkit

In particle transport Monte Carlo simulation, the manual modeling method is not suitable for complex geometric models. A Monte Carlo Simulation Modeling Toolkit (pyMCMT) is developed based on Python language. The toolkit can generate input card in several classical format such as MCNP and GDML format automatically. In this paper, two typical applications are presented based on the pyMCMT toolkit: 1, constructing a multilayer circular geometric model in complex density distribution by pyMCMT toolkit in order to satisfy the requirement of building large-space fine model with the influence of blast wave. A two-dimensional adaptive model is built for non-uniform atmospheric induced by blast wave. The number of the cells in this model is reduced vastly with the same model resolution; 2, producing the optimized weight window parameter using the mesh-based weight window variance reduction combined with density iteration method which is realized to solve the high statistical fluctuation and low counting efficiency problem in deep penetration process. The successful application of pyMCMT shows that pyMCMT is a modularized, parameterized, customizable and easy-to-debug toolkit for particle transport Monte Carlo simulation modeling, which can improve the modeling efficiency tremendously.

Synthesis and characterization of lipopolysaccharide (LPS) anchored polystyrene microparticles as a synthetic model system for attachment studies

Outer membrane lipopolysaccharides (LPS) play a crucial role in determining attachment behavior and pathogenicity of bacteria. The aim of this study was to develop a simple procedure for anchoring bacterial lipopolysaccharides to polystyrene (PS) microparticles as a model system for in situ attachment studies. By using a swell-capture methodology, commercially available LPS of Pseudomonas aeruginosa (strain ATCC 27316 serotype 10.22) was anchored onto PS microparticles in a proof-of-concept study. A detailed chemical and morphological characterization has proven the success of LPS incorporation. It was shown that the coverage and structure of the LPS film was concentration dependent. The procedure can easily be adapted to LPS of other bacterial strains to generate a synthetic model toolkit for attachment studies.

On Transient Semi‐Arid Ecosystem Dynamics Using Landlab: Vegetation Shifts, Topographic Refugia, and Response to Climate

AbstractProjecting how arid and semi‐arid ecosystems respond to global change requires the integration of a wide array of analytical and numerical models to address different aspects of complex ecosystems. We used the Landlab earth surface modeling toolkit (Hobley et al., 2017, https://doi.org/10.5194/esurf-5-21-2017) to couple several ecohydrologic and vegetation dynamics processes to investigate the controls of exogenous drivers (climate, topography, fires, and grazing) and endogenous grass‐fire feedback mechanisms. Aspect‐controlled ecosystems and historical woody plant encroachment (WPE) narratives in central New Mexico, USA are used to construct simulations. Modeled ecosystem response to climatic wetness (i.e., higher precipitation, lower potential evapotranspiration) on topography follows the Boyko's “geo‐ecological law of distribution.” Shrubs occupy cooler pole‐facing slopes in the dry end of their ecoclimatic range (Mean Annual Precipitation, MAP ≤ 200 mm), and shift toward warmer equator‐facing slopes as regional moisture increases (MAP > 250 mm). Trees begin to occupy pole‐facing slopes when MAP > 200 mm, and gradually move to valleys. Pole‐facing slopes increase species diversity at the landscape scale by hosting relict populations during dry periods. WPE observed in the region since the middle 1800s is predicted as a three‐phase phenomenon. Phase II, rapid expansion, requires the removal of the positive grass‐fire feedback by livestock grazing or fire suppression. Regime shifts from grassland to shrubland are marked by critical thresholds that involve grass cover remaining below 40%, shrub cover increasing to 10%–20% range, and the grass connectivity, Cg, remaining below 0.15. A critical transition to shrubland is predicted when grazing pressure is not removed before shrub cover attains 60%.

Computational Design of Peptides for Biomaterials Applications.

Computer-aided molecular design and protein engineering emerge as promising and active subjects in bioengineering and biotechnological applications. On one hand, due to the advancing computing power in the past decade, modeling toolkits and force fields have been put to use for accurate multiscale modeling of biomolecules including lipid, protein, carbohydrate, and nucleic acids. On the other hand, machine learning emerges as a revolutionary data analysis tool that promises to leverage physicochemical properties and structural information obtained from modeling in order to build quantitative protein structure-function relationships. We review recent computational works that utilize state-of-the-art computational methods to engineer peptides and proteins for various emerging biomedical, antimicrobial, and antifreeze applications. We also discuss challenges and possible future directions toward developing a roadmap for efficient biomolecular design and engineering.

A Modeling Toolkit for Comparing AC and DC Electrical Distribution Efficiency in Buildings

Recently, there has been considerable research interest in the potential for DC distribution systems in buildings instead of the traditional AC distribution systems. Due to the need for performing power conversions between DC and AC electricity, DC distribution may provide electrical efficiency advantages in some systems. To support comparative evaluations of AC-only, DC-only, and hybrid AC/DC distribution systems in buildings, a new modeling toolkit called the Building Electrical Efficiency Analysis Model (BEEAM) was developed and is described in this paper. To account for harmonics in currents or voltages arising from nonlinear devices, the toolkit implements harmonic power flow, along with nonlinear device behavioral descriptions derived from empirical measurements. This paper describes the framework, network equations, device representations, and an implementation of the toolkit in an open source software package, including a component library and graphical interface for creating circuits. Simulations of electrical behavior and device and system efficiencies using the toolkit are compared with experimental measurements of a small office environment in a variety of operating and load configurations. A detailed analysis of uncertainty estimation is also provided. Key findings were that a comparison of predicted versus measured efficiencies and power losses in the validation testbed using the initial toolkit implementation predicted device- and system-level efficiencies with reasonably good accuracy under both balanced and unbalanced AC scenarios. An uncertainty analysis also revealed that the maximum estimated error for system efficiency across all scenarios was 3%, and measured and modeled system efficiency agreed within the experimental uncertainty in approximately half of the scenarios. Based on the correspondence between simulation and measurement, the toolkit is proposed by the authors as a potentially useful tool for comparing efficiency in AC, DC, and hybrid AC/DC distribution systems in buildings.

Research for forecasting the effect of various meteorological-dynamic conditions on the possible spreading of Cs-137 radioactive substances in case a level 7 incident occurs from Fengcheng nuclear power plant (China)

Because its location is quite close to the Vietnamese border, the future operation of the Fengcheng (Phong Thanh) nuclear power plant (NPP) can raise many concerns about the impact on the marine environment in case a serious incident occurs. Based on the Delft3D modeling toolkit, calculation scenarios to simulate the spreading of Cs-137 radioactive emission when a level 7 incident occurs at Phong Thanh NPP have been set up according to different dynamic/meteorological conditions presented at the time of incidents (during the northeast monsoon, transitional monsoon, or southwest monsoon) to assess/predict the possibility of radioactive emission and to spread, and their affecting the waters of Vietnam. The simulation results show that when a level 7 incident occurs from Phong Thanh NPP, the area of influence might be the entire East Sea after 3–6 months. The Gulf of Tonkin area would be contaminated with high radiation levels (300–350 Bq/m3) after about one month. The radiation would then gradually decrease to less than 150Bq/m3 after one year and below 30Bq/m3 after two years. The impacts of various dynamical and meteorological conditions on the ability to spread and disperse radioactive substances when an incident occurs are only evident in the early stages (up to 3 months after the incident). After this time, the contaminated area would cover almost the entire coastal strip of Vietnam due to a large amount of radiation, and the effects of different dynamic/meteorological conditions would be irregular.

Pragmatic Model and Faculty Toolkit for PharmD Student Engagement in Social and Administrative Pharmacy Research

ObjectiveWe aim to describe the development of a pharmacy student workgroup as an experiential education model to provide social and administrative pharmacy research opportunities and provide a toolkit for faculty seeking to increase student research engagement via this model. MethodsThree pharmacy faculty with diverse training backgrounds but a common interest in opioid medications established a workgroup named the Opioid Research Workgroup. The workgroup consisted of first-year pharmacy students, research interns, and advanced graduate trainees. A hierarchical leadership model of supervision was implemented, whereby students reported progress on research tasks directly to an advanced graduate trainee leading a project team. To understand students’ perspectives on the research experience and educational outcomes, students were asked to complete an anonymous voluntary survey after a year of participation. ResultsSince its establishment, the workgroup has published multiple conference abstracts, manuscripts, and grants. Students’ overall satisfaction with the Workgroup on a scale of 1–5, 5 being very high, was 4.69. The successful scalability and longevity of this model are dependent on administrative support that protects faculty resources. The toolkit provided offers resources for those interested in adapting this model. ConclusionOur experience with the pragmatic model of pharmacy student engagement in research proved successful in terms of research output and student training experience. Although the model can be applied across a variety of health science clinical and research topics, and faculty can leverage this approach to increase productivity in research output, faculty must ensure that resources are available to support this effort.

MODELING OF TACTICAL INNOVATIVE TOOLS OF ECONOMIC DEVELOPMENT OF ENTERPRISES IN THE CONDITIONS OF EUROPEAN INTEGRATION

Purpose. Tactical innovative tools of the economic development of the enterprise in the conditions of European integration are considered in the article as short-term adaptive and relative means, intended for the practical implementation of irreversible, controlled and purposeful changes of a quantitative, qualitative and essential nature in the economic system of the enterprise, which occur under the influence of changes in the operating environment and condition the development means of production and socio-economic relations, increasing flexibility, achieving a state of optimal and efficient functioning of the enterprise and other strategic goals. For the purpose of their modeling, the article provides a conceptual formulation of the problem, defines a function that ensures their formation on alternative bases, forms compliance criteria and a set of modeling tasks: formation of modeling input data; substantiation of the criteria by which the tools of economic development of enterprises are optimized in the conditions of the course of European integration processes; ensuring the modeling of tactical innovative tools for the economic development of enterprises in the conditions of European integration by establishing the compliance of the group of tools for the economic development of enterprises with optimization criteria for the purpose of performing the function; identification of a set of tactical innovative tools for the economic development of enterprises in the conditions of European integration; making managerial decisions regarding the tactical management of the development of the enterprise in the conditions of European integration. Design/methodology/approach. Methods of analysis, synthesis, theoretical generalization, expert evaluations, coefficient analysis, method of pattern analysis. Findings. As a modeling toolkit, the article recommends the method of pattern analysis, which provides for the formation of homogeneous groups of objects as a result of cluster analysis in the following order: setting the problem; display of objects in the parallel coordinate system; direct connection of parameter values marked on the axes; analyzing the similarity of patterns; interpretation of the results, identification of tactical innovative tools for the economic development of enterprises in the conditions of European integration, which meet the criteria of optimality and restrictive criteria. Originality/value. The recommended procedure should be applied for the purpose of modeling tactical innovative tools of economic development, which will ensure their optimization in the conditions of European integration. Practical implications. The practical approbation of the method made it possible to identify 3 priority groups of tactical innovative tools of economic development of ShK Svitanok+ LLC: starting the activities of ShK Svitanok+ LLC in free economic zones, which involves its administrative support and providing employees with a social package; ensuring the participation of ShK Svitanok+ LLC in conferences, forums and round tables, promotion of the enterprise's exports, lending and expansion of analysis tools by spreading the practice of functional-cost and factor analysis in the mentioned conditions; implementation of targeting and ensuring the participation of ShK Svitanok+ LLC in grant projects.

Acceleration with GPUs and other RooFit news

RooFit is a toolkit for statistical modeling and fitting, and together with RooStats it is used for measurements and statistical tests by most experiments in particle physics, particularly the LHC experiments. As the LHC program progresses, physics analysis becomes more computationally demanding. Therefore, RooFit development in recent years is focused on modernizing RooFit, improving its ease of use, and on performance optimization. This paper presents the new RooFit vectorized computation mode, which supports calculations on the GPU. Additionally, we discuss new features in the upcoming ROOT 6.26 release, highlighting the new pythonizations in particular.

Establishment and quality assessment of X-ray narrow spectrum series according to ISO 4037:2019 at SSDL of center for nuclear technologies

Narrow spectrum series from N-40 to N-120 were established according to ISO 4037:2019. This study was made through experimental measurements and the software modeling toolkit SpekPy v2.0. Experiments were performed to determine Inherent filtration (0.332 & 0.492 mm Al at 100 cm & 250 cm, respectively). The maximum deviation compared to ISO 4037:2019 of the measured HVLs values are not more then 0.10 mm Al and for modeling not exceed 0.09 mm Al; h range 0.91 to 0.97 for experimently and 0.89 to 0.96 for modeling (0.88 - 1, ISO 4037-1:2019). The maximum contribution of scattering is value 4.0% (< 5%, ISO 4037-1:2019). Radiation field uniformity of N-40 to N-120 should list all categories in detail 12.5, 11.0, 10.0, 9.0, 8.5 cm at 100 cm distance; and 35.5, 31.5, 29.0, 26.5, 24.5 cm at 250 cm beam center axis distance. On the basis of ISO 4037:2019, air kerma values at 100 cm and 250 cm have also been determined with uncertainties 3.85% to 5.18% for experimently and 3.41% to 4.19% for modeling (not exceed 10%, ISO 4037:2019). Therefore, the X-ray radiation field has been well established in compliance with the ISO 4037:2019, it can be used for calibrating survey meters and personal dosimeters.

Огляд сучасних підходів до формування системи управління бюджетами підприємства

The article is devoted to a review of modern approaches to the formation of the enterprise budget management system. The article examines the essence of the concept of "budgeting", establishes the main stages and aspects of enterprise budget management. In the article, it is proposed to consider a complex resource management system of the enterprise under budgeting, which is aimed at achieving planned indicators and effective control over the receipt and expenditure of funds. It was determined that the main goal of such a system is to ensure management efficiency and help make effective management decisions to achieve the planned strategic goals of the enterprise. To increase the visibility and efficiency of this system, a visualization of the budgeting system formation procedure is presented in the form of a model built on the Ramus platform in the IDF0 notation (modeling language). It was determined that an effective budgeting system (as an important component of successful management of enterprises) is a dynamic system that is constantly developing and therefore it is advisable to review, adjust and improve it, taking into account the opportunities, priorities, needs and specifics of each company. The need to look for new ways of increasing the efficiency of cost management and to implement digitalization, forecasting and modeling tools in the budgeting system is substantiated. The purpose of the article is to analyze the possibilities of forming an effective enterprise budgeting system based on the analysis of modern approaches to its formation and to determine the possibilities of its successful implementation for Ukrainian companies. The author considers the main trends and challenges that influenced the formation of an effective budgeting system. In particular, the role of IT development, business analytics automation technologies and their impact on the formation of an effective budgeting system are considered. The article draws attention to the fact that for the successful implementation of the budgeting system, it is worth using a modeling toolkit, which allows enterprises to get a better visualization of existing processes and opportunities for their improvement, to establish cooperation and communication, and to improve the data collection and analysis system. The scientific novelty of this article lies in the fact that the recommendations and conclusions provided by the author can be useful for companies wishing to improve their own budgeting systems. In general, this article is useful for those who want to learn more about the budgeting system in business.

Practical Verification of Railway Signalling Programs

SafeCap is a modern toolkit for modelling, simulation and formal verification of railway networks. This paper discusses the use of SafeCap for formal analysis and automated scalable safety verification of solid state interlocking (SSI) programs – a technology at the heart of many railway signalling solutions around the world. The main driving force behind SafeCap development was to make it easy for signalling engineers to use the technology and thus to ensure its smooth industrial deployment. The unique qualities and the novelty of SafeCap are in making the use of formal notations and proofs fully transparent for the engineers. In this paper we explain the formal foundations of the proposed method, its tool support, and its successful application by railway companies in developing industrial signalling projects.

Assessment of the potential for sustainable development of electric power enterprises: approaches, models, technologies

This article poses and solves the problem of building a model toolkit for assessing the level of sustainable development of electric power enterprises. The indicators characterizing the state of the enterprise in terms of economic, environmental and social characteristics are proposed. In the economic aspect, it is proposed to focus on such a threat to sustainable economic development as economic insolvency. In the process of modeling economic insolvency, Altman's five-factor model scenarios are used. To resolve the contradictions between economic development, the rational use of resources and the negative impact on the environment, the article proposes a logical-linguistic model that allows to resolve this conflict. Keywords: sustainable development; electric power enterprises; mathematical modeling; logical-linguistic approach.

Empowering ecological modellers with a PERFICT workflow: Seamlessly linking data, parameterisation, prediction, validation and visualisation

Abstract Modelling is widely used in ecology and its utility continues to increase as scientists, managers and policy‐makers face pressure to effectively manage ecosystems and meet conservation goals with limited resources. As the urgency to forecast ecosystem responses to global change grows, so do the number and complexity of predictive ecological models and the value of iterative prediction, both of which demand validation and cross‐model comparisons. This challenges ecologists to provide predictive models that are reusable, interoperable, transparent and able to accommodate updates to both data and algorithms. We propose a practical solution to this challenge based on the PERFICT principles (frequent Predictions and Evaluations of Reusable, Freely accessible, Interoperable models, built within Continuous workflows that are routinely Tested), using a modular and integrated framework. We present its general implementation across seven common components of ecological model applications—(i) the modelling toolkit; (ii) data acquisition and treatment; (iii) model parameterisation and calibration; (iv) obtaining predictions; (v) model validation; (vi) analysing and presenting model outputs; and (vii) testing model code—and apply it to two approaches used to predict species distributions: (1) a static statistical model, and (2) a complex spatiotemporally dynamic model. Adopting a continuous workflow enabled us to reuse our models in new study areas, update predictions with new data, and re‐parameterise with different interoperable modules using freely accessible data sources, all with minimal user input. This allowed repeating predictions and automatically evaluating their quality, while centralised inputs, parameters and outputs, facilitated ensemble forecasting and tracking uncertainty. Importantly, the integrated model validation promotes a continuous evaluation of the quality of more‐ or less‐parsimonious models, which is valuable in predictive ecological modelling. By linking all stages of an ecological modelling exercise, it is possible to overcome common challenges faced by ecological modellers, such as changing study areas, choosing between different modelling approaches, and evaluating the appropriateness of the model. This ultimately creates a more equitable and robust playing field for both modellers and end users (e.g. managers), and contributes to position predictive ecology as a central contributor to global change forecasting.

A New Mixture Differential Cryptanalysis on Round-Reduced AES

AES is the most widely used secret-key cryptosystem in industry, and determining the security of AES is a central problem in cryptanalysis. The mixture differential property proposed in Eurocrypt 2017 is an essential property to setup state-of-the-art key recovery attacks on some round-reduced versions of AES. In this paper, we exploit mixture differential properties that are automatically deduced from a mixed integer linear programming (MILP)-based model to extend key recovery attacks on AES. Specifically, we modify the MILP model toolkit to produce all mixture trails explicitly and test a 5-round secret-key mixture differential distinguisher on small-scale AES experimentally. Moreover, we utilize this distinguisher to do a key recovery attack on 6-round AES-128 that outperforms previous work in the same fashion. We also for the first time utilize a 6-round AES secret-key distinguisher to set up a key recovery attack on 7-round AES-192. This work is a new yet simple cryptanalysis on AES by exploiting mixture differential properties.