Production of biofuels and biochemicals: in need of an ORACLE

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Using (27.12 +/- 0.14) x 10(8) psi(2S) events collected by the BESIII detector operating at BEPCII, we search for the decay eta(c) (2S) -> p (p) over bar via the process psi(2S) -> gamma eta(c)(2S) and only find a signal with a significance of 1.7 sigma. T ...

The estimation of uncertainties in cosmological parameters is an important challenge in Large-Scale-Structure (LSS) analyses. For standard analyses such as Baryon Acoustic Oscillations (BAO) and Full-Shape two approaches are usually considered. First: anal ...

Machine learning and artificial intelligence methods have achieved remarkable success, matching and even surpassing human capabilities in various complex tasks. However, many demonstrations have generally neglected a critical part of the intelligence that ...

Despite the growing interest in emotions in engineering education, empirical research on incorporating them into engineering ethics education is limited. Therefore, we designed this experimental study to assess how different methods for integrating compass ...

Being able to work effectively in a team is a vital professional skill but how do students in different disciplines, engineering and hospitality, display their emotions when working together? We investigated their self-reported use of emotional labour stra ...

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

Zoning reform is a crucial tool for cities to adapt to contemporary challenges. However, its implementation remains challenging. Property owners, with a vested interest in the value of their neighborhoods, are sensitive to local developments and the potent ...

Devising genetic interventions for desired cellular phenotypes remains challenging regarding time and resources. Kinetic models can accelerate this task by simulating metabolic responses to genetic perturbations. However, exhaustive design evaluations with ...

vanishing viscosity, networks. This work has received funding from the Alexander von Humboldt-Professorship program, the Transregio 154 Project "Mathematical Modelling, Simulation and Optimization Using the Example of Gas Networks" of the DFG, the grant PI ...

The transfer function is an important characteristic quantity of a nuclear reactor, since it contains the kinetic parameters. It expresses the response of a nuclear reactor to a disturbance of a certain frequency. If it is determined experimentally, it can ...

Uncertainty of spillover effects – including property devaluation - from proposed land-use change elicits opposition to local development. This hinders cities’ ability to implement land-use policy aimed at housing affordability and environmental sustainabi ...

We report the detailed background for the discovery and development of the synthesis of homopropargylic azides by the azidoalkynylation of alkenes. Initially, a strategy involving SOMOphilic alkynes was adopted, but only resulted in a 29% yield of the desi ...

In this paper, we present a new parameterization and optimization procedure for minimizing the weight of ribbed plates. The primary goal is to reduce embodied CO2 in concrete floors as part of the effort to diminish the carbon footprint of the construction ...

Electronic devices play an irreplaceable role in our lives. With the tightening time to market, exploding demand for computing power, and continuous desire for smaller, faster, less energy-consuming, and lower-cost chips, computer-aided design for electron ...

A method for optimizing at least one of a geometry, an implantation procedure, and/or stimulation protocol of one or more electrodes for an electrical stimulation of a target structure in a nervous system of a living being by a computer device, the method ...

Cutting plane methods are a fundamental approach for solving integer linear programs (ILPs). In each iteration of such methods, additional linear constraints (cuts) are introduced to the constraint set with the aim of excluding the previous fractional opti ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

In various robotics applications, the selection of function approximation methods greatly influences the feasibility and computational efficiency of algorithms. Tensor Networks (TNs), also referred to as tensor decomposition techniques, present a versatile ...

Randomized measurement protocols such as classical shadows represent powerful resources for quantum technologies, with applications ranging from quantum state characterization and process tomography to machine learning and error mitigation. Recently, the n ...

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

Production of biofuels and biochemicals: in need of an ORACLE

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Search for ηc (2S) → p(p)over-bar and branching fraction measurements of χcJ → p(p)over-bar via ψ(2S) radiative decays

Analytical and EZmock covariance validation for the DESI 2024 results

Sequential Reasoning with Socially Caused Beliefs

The impact of different methods of increasing the intensity of compassion in engineering ethics cases

“But of course i’m going to look happy” or “He needed to know I was angry”? Comparing use of emotional labour in teamwork in engineering and hospitality students

Scalable constrained optimization

Spatial Modeling for Building Design Evaluation: from Visual Landscape Quality Assessment to Devaluation Risk Estimation

Rational strain design with minimal phenotype perturbation

CONTROL OF HYPERBOLIC AND PARABOLIC EQUATIONS ON NETWORKS AND SINGULAR LIMITS

CORTEX experiments, Part III: Experimental determination of the zero power transfer function of AKR-2 with reliable uncertainties

Using automated design appraisal to model building-specific devaluation risk due to land-use change

SOMOphilic alkyne vs radical-polar crossover approaches: The full story of the azido-alkynylation of alkenes

Mesh-based topology, shape and sizing optimization of ribbed plates

Contemporary Logic Synthesis: with an Application to AQFP Circuit Optimization

A method and system for optimizing design, implantation, and stimulation protocols of electrodes stimulating the nervous system

Learning to Remove Cuts in Integer Linear Programming

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Robot Learning using Tensor Networks

Dual-frame optimization for informationally complete quantum measurements

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning