Projecting Wintertime Newly Formed Arctic Sea Ice through Weighting CMIP6 Model Performance and Independence

Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice,changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project(CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models' performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario.Thereafter, it may decrease(or remain stable) if the Arctic warming crosses a threshold(or is extensively constrained).

Analysis of the Role of Problem-Based Independent Learning Model in Teaching Cerebral Ischemic Stroke First Aid in Emergency Medicine

Objective:To analyze the effect of using a problem-based(PBL)independent learning model in teaching cerebral ischemic stroke(CIS)first aid in emergency medicine.Methods:90 interns in the emergency department of our hospital from May 2022 to May 2023 were selected for the study.They were divided into Group A(45,conventional teaching method)and Group B(45 cases,PBL independent learning model)by randomized numerical table method to compare the effects of the two groups.Results:The teaching effect indicators and student satisfaction scores in Group B were higher than those in Group A(P<0.05).Conclusion:The use of the PBL independent learning model in the teaching of CIS first aid can significantly improve the teaching effect and student satisfaction.

Transformation from computation independent model to platform independent model with pattern

Model driven architecture(MDA) is an evolutionary step in software development.Model transformation forms a key part of MDA.The transformation from computation independent model(CIM) to platform independent model(PIM) is the first step of the transformation.This paper proposes an approach for this transformation with pattern.In this approach, we take advantage of"reuse"from various standpoints.Feature model is used to describe the requirement of the application.This can help us bring"reuse"into effect at requirement level.Moreover we use pattern to transform CIM to PIM.This can help us bring"reuse"into effect at development level.Meanwhile, pattern was divided into four hierarchies.Different hierarchies of pattern are used to help us utilize reuse at different phase of development.From another standpoint, feature model describes the problem of a domain while pattern describe the problem across domains.This can help us reuse the element in and across domains.Finally, the detailed process of the transformation is given.

Multi-Model Ensemble Projection of Precipitation Changes over China under Global Warming of 1.5 and 2℃ with Consideration of Model Performance and Independence

A weighting scheme jointly considering model performance and independence(PI-based weighting scheme) is employed to deal with multi-model ensemble prediction of precipitation over China from 17 global climate models. Four precipitation metrics on mean and extremes are used to evaluate the model performance and independence. The PIbased scheme is also compared with a rank-based weighting scheme and the simple arithmetic mean(AM) scheme. It is shown that the PI-based scheme achieves notable improvements in western China, with biases decreasing for all parameters. However, improvements are small and almost insignificant in eastern China. After calibration and validation, the scheme is used for future precipitation projection under the 1.5 and 2℃ global warming targets(above preindustrial level). There is a general tendency to wetness for most regions in China, especially in terms of extreme precipitation. The PI scheme shows larger inhomogeneity in spatial distribution. For the total precipitation PRCPTOT(95 th percentile extreme precipitation R95 P), the land fraction for a change larger than 10%(20%) is 22.8%(53.4%)in PI, while 13.3%(36.8%) in AM, under 2℃ global warming. Most noticeable increase exists in central and east parts of western China.

Differential cross sections of elastic electron scattering from CH4. CF4 and SF6 in the energy range l00-700eV

We investigate the differential cross sections （DCS） of elastic electron scattering from CH4, CF4 and SF6 at six impact energies in a range of 100 700eV by employing the independent atom model （IAM） together with the relativistic partial waves. The atom is present in an optical potential which is complex, spherically symmetric, and energy dependent. The optical potential of the atom is the sum of the direct static, dynamic polarization, local exchange and modified absorption potentials. The results obtained by using a modified absorption potential show significant improvements on the unmodified absorption potential results. The present results are generally in good agreement with experimental data available. In addition, the present results indicate that the structure of molecule manifests the observable effects on electron- molecule scattering.

Advancements in food authentication using soft independent modelling of class analogy(SIMCA):a review

Food authentication verifies the match between product characteristics and claims and it is crucial in a globalized and complex food sector.Currently.class-modelling approaches,such as soft independent modelling of class analogy(SiMCA),are powerful tools for assessing food authenticity.The aim of this review is to discuss the application of SiMCA for food authentication and to describe the conceptual differences between discriminant and class-modelling approaches.The discussion of research articles is organized around three elements:(i)the research objectives,(ii)the analytical methodologies,and(il)the food products investigated.Moreover,the challenges and future perspectives considering the development of innovative food products are discussed.Adulteration is the most investigated food authentication issue,followed by verification of geographical origin.Food authenticity appeared to be predominantly evaluated using non-destructive spectroscopy.Overall,the articles collectively cover a broad spectrum of food categories,representing those most prone to adulteration.However,there is a notable lack of food authentication studies on innovative food products,underscoring the urgency for further research in this field.

Decomposition of two classes of structural models

The conditional independence structure of a common probability measure is a structural model. In this paper, we solve an open problem posed by Studeny [Probabilistic Conditional Independence Structures, Theme 9, p. 206]. A new approach is proposed to decompose a directed acyclic graph and its optimal properties are studied. We interpret this approach from the perspective of the decomposition of the corresponding conditional independence model and provide an algorithm for identifying the maximal prime subgraphs in a directed acyclic graph.

Preliminary application of turn-by-turn data analysis to the SSRF storage ring

There is growing interest in utilizing the beam position monitor turn-by-turn（TBT） data to debug accelerators. TBT data can be used to determine the linear optics,coupled optics and nonlinear behaviors of the storage ring lattice. This is not only a useful complement to other methods of determining the linear optics such as LOCO,but also provides a possibility to uncover more hidden phenomena. In this paper,a preliminary application of a β function measurement to the SSRF storage ring is presented.

Shell evolution in neutron-rich nuclei:the single particle perspective

The isospin dependence of spin-orbit(SO)splitting becomes increasingly important as N/Z increases in neutron-rich nuclei.Following the initial independent-particle strategy toward explaining the occurrence of magic numbers,we systematically investigated the isospin effect on the shell evolution in neutron-rich nuclei within the Woods-Saxon mean-field potential and the SO term.It is found that new magic numbers N=14 and N=16 may emerge in neutron-rich nuclei if one changes the sign of the isospin-dependent term in the SO coupling,whereas the traditional magic number,N=20,may disappear.The magic number N=28 is expected to be destroyed despite the sign choice of the isospin part in the SO splitting,corresponding to the strength of the SO coupling term.Meanwhile,the N=50 and 82 shells may persist within the single particle scheme,although there is a decreasing trend of their gaps toward extreme proton-deficient nuclei.Besides,an appreciable energy gap appears at N=32 and 34 in neutron-rich Ca isotopes.All these results are more consistent with those of the interacting shell model when enhancing the strength of the SO potential in the independent particle model.The present study may provide a more reasonable starting point than the existing one for not only the interacting shell model but also other nuclear many-body calculations toward the neutron-dripline of the Segrèchart.

Efficient Algorithms for Maximizing Group Influence in Social Networks

In social network applications,individual opinion is often influenced by groups,and most decisions usually reflect the majority’s opinions.This imposes the group influence maximization(GIM) problem that selects k initial nodes,where each node belongs to multiple groups for a given social network and each group has a weight,to maximize the weight of the eventually activated groups.The GIM problem is apparently NP-hard,given the NP-hardness of the influence maximization(IM) problem that does not consider groups.Focusing on activating groups rather than individuals,this paper proposes the complementary maximum coverage(CMC) algorithm,which greedily and iteratively removes the node with the approximate least group influence until at most k nodes remain.Although the evaluation of the current group influence against each node is only approximate,it nevertheless ensures the success of activating an approximate maximum number of groups.Moreover,we also propose the improved reverse influence sampling(IRIS) algorithm through fine-tuning of the renowned reverse influence sampling algorithm for GIM.Finally,we carry out experiments to evaluate CMC and IRIS,demonstrating that they both outperform the baseline algorithms respective of their average number of activated groups under the independent cascade(IC)model.