(Self-)evaluation of computer competence: how gender matters

Is the negative stereotype of women with regard to computer competence still exerting power in our society? In this study, 206 participants observed a target person (either a woman or a man) on a video who was about to solve a complex computer task. Participants had to estimate whether the target person was successful on this task in a limited amount of time. After they had received the information that the target person had solved the task successfully in the required time period, and that the person’s performance was above average, they were asked to provide a reason for the success (luck vs. skill attribution) and to evaluate the general computer competence of the target. Then, participants had to evaluate their own (hypothetical) computer competence in comparison to the target. Results suggest that for the direct evaluation of the target persons and for the causal attribution of success, no systematic gender-related biases occurred. In the self-ratings of participants; however, findings showed that (a) women judged their computer competence to be lower than did men, and (b) both women and men judged their own hypothetical performance in the computer-related task to be relatively higher when comparing it to the identically scripted performance of a woman vs. a man

Application of Petri net based analysis techniques to signal transduction pathways

BACKGROUND: Signal transduction pathways are usually modelled using classical quantitative methods, which are based on ordinary differential equations (ODEs). However, some difficulties are inherent in this approach. On the one hand, the kinetic parameters involved are often unknown and have to be estimated. With increasing size and complexity of signal transduction pathways, the estimation of missing kinetic data is not possible. On the other hand, ODEs based models do not support any explicit insights into possible (signal-) flows within the network. Moreover, a huge amount of qualitative data is available due to high-throughput techniques. In order to get information on the systems behaviour, qualitative analysis techniques have been developed. Applications of the known qualitative analysis methods concern mainly metabolic networks. Petri net theory provides a variety of established analysis techniques, which are also applicable to signal transduction models. In this context special properties have to be considered and new dedicated techniques have to be designed. METHODS: We apply Petri net theory to model and analyse signal transduction pathways first qualitatively before continuing with quantitative analyses. This paper demonstrates how to build systematically a discrete model, which reflects provably the qualitative biological behaviour without any knowledge of kinetic parameters. The mating pheromone response pathway in Saccharomyces cerevisiae serves as case study. RESULTS: We propose an approach for model validation of signal transduction pathways based on the network structure only. For this purpose, we introduce the new notion of feasible t-invariants, which represent minimal self-contained subnets being active under a given input situation. Each of these subnets stands for a signal flow in the system. We define maximal common transition sets (MCT-sets), which can be used for t-invariant examination and net decomposition into smallest biologically meaningful functional units. CONCLUSION: The paper demonstrates how Petri net analysis techniques can promote a deeper understanding of signal transduction pathways. The new concepts of feasible t-invariants and MCT-sets have been proven to be useful for model validation and the interpretation of the biological system behaviour. Whereas MCT-sets provide a decomposition of the net into disjunctive subnets, feasible t-invariants describe subnets, which generally overlap. This work contributes to qualitative modelling and to the analysis of large biological networks by their fully automatic decomposition into biologically meaningful modules

Graph test of controllability in qubit arrays: A systematic way to determine the minimum number of external controls

The ability to implement any desired quantum logic gate on a quantum processing unit is equivalent to evolution-operator controllability of the qubits. Conversely, controllability analysis can be used to minimize the resources, i.e., the number of external controls and qubit-qubit couplings, required for universal quantum computing. Standard controllability analysis, consisting in the construction of the dynamical Lie algebra, is, however, impractical already for a comparatively small number of qubits. Here, we show how to leverage an alternative approach, based on a graph representation of the Hamiltonian, to determine controllability of arrays of coupled qubits. We provide a complete computational framework and exemplify it for arrays of five qubits, inspired by the ibmq_quito architecture. We find that the number of controls can be reduced from five to one for complex qubit-qubit couplings and to two for standard qubit-qubit couplings.Comment: 18 pages, 7 figures, 3 tables, 3 algorithm

Measuring Snow Liquid Water Content with Low-Cost GPS Receivers

The amount of liquid water in snow characterizes the wetness of a snowpack. Its temporal evolution plays an important role for wet-snow avalanche prediction, as well as the onset of meltwater release and water availability estimations within a river basin. However, it is still a challenge and a not yet satisfyingly solved issue to measure the liquid water content (LWC) in snow with conventional in situ and remote sensing techniques. We propose a new approach based on the attenuation of microwave radiation in the L-band emitted by the satellites of the Global Positioning System (GPS). For this purpose, we performed a continuous low-cost GPS measurement experiment at the Weissfluhjoch test site in Switzerland, during the snow melt period in 2013. As a measure of signal strength, we analyzed the carrier-to-noise power density ratio (C/N-0) and developed a procedure to normalize these data. The bulk volumetric LWC was determined based on assumptions for attenuation, reflection and refraction of radiation in wet snow. The onset of melt, as well as daily melt-freeze cycles were clearly detected. The temporal evolution of the LWC was closely related to the meteorological and snow-hydrological data. Due to its non-destructive setup, its cost-efficiency and global availability, this approach has the potential to be implemented in distributed sensor networks for avalanche prediction or basin-wide melt onset measurements

How Will Hydroelectric Power Generation Develop under Climate Change Scenarios?

Climate change has a large impact on water resources and thus on hydropower. Hydroelectric power generation is closely linked to the regional hydrological situation of a watershed and reacts sensitively to changes in water quantity and seasonality. The development of hydroelectric power generation in the Upper Danube basin was modelled for two future decades, namely 2021-2030 and 2051-2060, using a special hydropower module coupled with the physically-based hydrological model PROMET. To cover a possible range of uncertainties, 16 climate scenarios were taken as meteorological drivers which were defined from different ensemble outputs of a stochastic climate generator, based on the IPCC-SRES-A1B emission scenario and four regional climate trends. Depending on the trends, the results show a slight to severe decline in hydroelectric power generation. Whilst the mean summer values indicate a decrease, the mean winter values display an increase. To show past and future regional differences within the Upper Danube basin, three hydropower plants at individual locations were selected. Inter-annual differences originate predominately from unequal contributions of the runoff compartments rain, snow-and ice-melt

Quantum control of ro-vibrational dynamics and application to light-induced molecular chirality

Achiral molecules can be made temporarily chiral by excitation with electric fields, in the sense that an average over molecular orientations displays a net chiral signal [Tikhonov et al., Sci. Adv. 8, eade0311 (2022)]. Here, we go beyond the assumption of molecular orientations to remain fixed during the excitation process. Treating both rotations and vibrations quantum mechanically, we identify conditions for the creation of chiral vibrational wavepackets -- with net chiral signals -- in ensembles of achiral molecules which are initially randomly oriented. Based on the analysis of symmetry and controllability, we derive excitation schemes for the creation of chiral wavepackets using a combination of (a) microwave and IR pulses and (b) a static field and a sequence of IR pulses. These protocols leverage quantum rotational dynamics for pump-probe spectroscopy of chiral vibrational dynamics, extending the latter to regions of the electromagnetic spectrum other than the UV.Comment: 16 pages, 8 figure