The Political Essence of the State in the Teachings of V.I. Lenin and P.I. Kropotkin: comparative Legal Analysis

In connection with the search in the modern world for a more perfect model of the structure of society, the article discusses the ideas of Lenin and Kropotkin of its construction. The author analyzes the models of both politicians on reforming the state and transition to a new society. Highlights the similarities and differences of their views.

A Robust Method for Detecting Item Misfit in Large Scale Assessments

Viable methods for the identification of item misfit or Differential Item Functioning (DIF) are central to scale construction and sound measurement. Many approaches rely on the derivation of a limiting distribution under the assumption that a certain model fits the data perfectly. Typical assumptions such as the monotonicity and population independence of item functions are present even in classical test theory but are more explicitly stated when using item response theory or other latent variable models for the assessment of item fit. The work presented here provides an alternative approach that does not assume perfect model data fit, but rather uses Tukey’s concept of contaminated distributions and proposes an application of robust outlier detection in order to flag items for which adequate model data fit cannot be established.

A Robust Method for Detecting Item Misfit in Large Scale Assessments

Viable methods for the identification of item misfit or Differential Item Functioning (DIF) are central to scale construction and sound measurement. Many approaches rely on the derivation of a limiting distribution under the assumption that a certain model fits the data perfectly. Typical assumptions such as the monotonicity and population independence of item functions are present even in classical test theory but are more explicitly stated when using item response theory or other latent variable models for the assessment of item fit. The work presented here provides an alternative approach that does not assume perfect model data fit, but rather uses Tukey’s concept of contaminated distributions and proposes an application of robust outlier detection in order to flag items for which adequate model data fit cannot be established.

Towards Reliable Probabilistic Time-Series Projections of Global Mean Surface Temperature

Quantifying the risk of global warming exceeding critical targets such as 2.0 ◦ C requires reliable projections of uncertainty as well as best estimates of Global Mean Surface Temperature (GMST). However, uncertainty bands on GMST projections are often calculated heuristically and have several potential shortcomings. In particular, the uncertainty bands shown in IPCC plume projections of GMST are based on the distribution of GMST anomalies from climate model runs and so are strongly determined by model characteristics with little influence from observations of the real-world. Physically motivated time-series approaches are proposed based on fitting energy balance models (EBMs) to climate model outputs and observations in order to constrain future projections. It is shown that EBMs fitted to one forcing scenario will not produce reliable projections when different forcing scenarios are applied. The errors in the EBM projections can be interpreted as arising due to a discrepancy in the effective forcing felt by the model. A simple time-series approach to correcting the projections is proposed based on learning the evolution of the forcing discrepancy so that it can be projected into the future. This approach gives reliable projections of GMST when tested in a perfect model setting. When applied to observations this leads to projected warming of 2.2 ◦ C (1.7 ◦ C to 2.9 ◦ C) in 2100 compared to pre-industrial conditions, 0.4 ◦ C lower than a comparable IPCC anomaly estimate. The probability of staying below the critical 2.0 ◦ C warming target in 2100 more than doubles to 0.28 compared to only 0.11 from a comparably IPCC estimate.

At the Root of Nodule Organogenesis: Conserved Regulatory Pathways Recruited by Rhizobia

The interaction between legume plants and soil bacteria rhizobia results in the formation of new organs on the plant roots, symbiotic nodules, where rhizobia fix atmospheric nitrogen. Symbiotic nodules represent a perfect model to trace how the pre-existing regulatory pathways have been recruited and modified to control the development of evolutionary “new” organs. In particular, genes involved in the early stages of lateral root development have been co-opted to regulate nodule development. Other regulatory pathways, including the players of the KNOX-cytokinin module, the homologues of the miR172-AP2 module, and the players of the systemic response to nutrient availability, have also been recruited to a unique regulatory program effectively governing symbiotic nodule development. The role of the NIN transcription factor in the recruitment of such regulatory modules to nodulation is discussed in more details.

Trivial improvements in predictive skill due to direct reconstruction of the global carbon cycle

State-of-the art climate prediction systems have recently included a carbon component. While physical-state variables are assimilated in reconstruction simulations, land and ocean biogeochemical state variables adjust to the state acquired through this assimilation indirectly instead of being assimilated themselves. In the absence of comprehensive biogeochemical reanalysis products, such an approach is pragmatic. Here we evaluate a potential advantage of having perfect carbon cycle observational products to be used for direct carbon cycle reconstruction. Within an idealized perfect-model framework, we reconstruct a 50-year target period from a control simulation. We nudge variables from this target onto arbitrary initial conditions, mimicking an assimilation simulation generating initial conditions for hindcast experiments of prediction systems. Interested in the ability to reconstruct global atmospheric CO2, we focus on the global carbon cycle reconstruction performance and predictive skill. We find that indirect carbon cycle reconstruction through physical fields reproduces the target variations. While reproducing the large-scale variations, nudging introduces systematic regional biases in the physical-state variables to which biogeochemical cycles react very sensitively. Initial conditions in the oceanic carbon cycle are sufficiently well reconstructed indirectly. Direct reconstruction slightly improves initial conditions. Indirect reconstruction of global terrestrial carbon cycle initial conditions are also sufficiently well reconstructed by the physics reconstruction alone. Direct reconstruction negligibly improves air–land CO2 flux. Atmospheric CO2 is indirectly very well reconstructed. Direct reconstruction of the marine and terrestrial carbon cycles slightly improves reconstruction while establishing persistent biases. We find improvements in global carbon cycle predictive skill from direct reconstruction compared to indirect reconstruction. After correcting for mean bias, indirect and direct reconstruction both predict the target similarly well and only moderately worse than perfect initialization after the first lead year. Our perfect-model study shows that indirect carbon cycle reconstruction yields satisfying initial conditions for global CO2 flux and atmospheric CO2. Direct carbon cycle reconstruction adds little improvement to the global carbon cycle because imperfect reconstruction of the physical climate state impedes better biogeochemical reconstruction. These minor improvements in initial conditions yield little improvement in initialized perfect-model predictive skill. We label these minor improvements due to direct carbon cycle reconstruction “trivial”, as mean bias reduction yields similar improvements. As reconstruction biases in real-world prediction systems are likely stronger, our results add confidence to the current practice of indirect reconstruction in carbon cycle prediction systems.

Lexical Indices of Variation in „Amintiri din copilărie” by Ion Creangă

Ion Creangă’s literary work is an inexhaustible source of expressiveness, which lends itself to versatile interpretations, from various perspectives, never finished. In this study, we analyze the lexical variation indices of „Amintiri din copilărie” through the prism of the variational dimensions: diachrony, diatopia, diastratia and diaphasia. Their inventory demonstrates that Ion Creangă's work abounds in contextual expressive-aesthetic meanings and is a perfect model for rendering the simultaneous harmonious functioning of these indices, which actually builds the oral and popular character of his writing. Obsolete lexical units, archaic forms, as well as words of Slavic origin are indices of diachronic and diatopic variation. The terms of popular occupations or the lexemes related to the village life and its activities become diastratic indices, their intentional insertion involving various moods, emotions or attitudes.

An evidence theory-based validation method for models with multivariate outputs and uncertainty

Researchers usually rely on simulations to predict the response of complex systems, we recognize that the models that underlie these simulations are never perfect. Model validation is a crucial ingredient in simulation credibility assessment. Multivariate responses under uncertainty often exist in complex simulation model, and the corresponding validation problem is not be solved effectively based on the existing validation methods. Hence, this paper presents a new validation method based on evidence theory for simulation model under uncertainty. For analyzing the extent of agreement between simulation outputs and experimental observations under uncertainty, the data features of system responses under uncertainty are extracted primarily. Next, the validation data such as large sample, small sample, data features, and expert opinions are represented as evidence theory. Then the traditional evidence distance method is improved to measure the agreement extent of simulation outputs and experimental observations. The proposed method is verified through an application example on validation of a simulation model about the terminal guidance stage of flight vehicle to illustrate their validity and potential benefits.

Transposable element activity in the transcriptomic analysis of mouse pancreatic tumors

Transposable elements (TEs) are middle-repeated DNA sequences that can move along chromosomes using internal coding and regulatory regions. By their ability to move and because they are repeated, TEs can promote mutations. Especially they can alter the expression pattern of neighboring genes and have been shown to be involved in the mammalian regulatory network evolution. Human and mouse share more than 95% of their genomes and are affected by comparable diseases, which makes the mouse a perfect model in cancer research. However not much investigation concerning the mouse TE content has been made on this topics. In human cancer condition, a global activation of TEs can been observed which may ask the question of their impact on neighboring gene functioning. In this work, we used RNA sequences of highly aggressive pancreatic tumors from mouse to analyze the gene and TE deregulation happening in this condition compared to pancreas from healthy animals. Our results show that several TE families are deregulated and that the presence of TEs is associated with the expression divergence of genes in the tumor condition. These results illustrate the potential role of TEs in the global deregulation at work in the cancer cells.

What is a Library Website, Anyway? Reconsidering Dominant Conceptual Models

In late 2019, Thompson Rivers University embarked on a multi-phase website usability project beginning with a website user survey, to be followed shortly afterward by usability testing and interviews. While the survey was completed as planned, the COVID-19 pandemic closed the library and interrupted the usability testing phase. This interruption and the frantic website changes that followed led me to consider survey findings within the context of differing conceptual models of the library website as a whole. This study explores a number of conceptual models of the library website in further depth, considering evidence from both the existing literature and the user survey in addition to the researcher’s own experience making post-COVID website updates. Particular models that are examined include Website as Research Portal, Website as Extension or Representation of the physical library, and Website as Library Branch. Each of these conceptual models has different implications on priorities, structure, purpose, and resource allocation. Rather than considering the models of library employees superior or more advanced than those of students, I contend that an awareness of myriad ways to understand the website can best bridge the gap between library employees and other users. The study concludes that while there is no perfect model of the library website, considering and communicating our models may sharpen collegial decision-making structures and create greater unity of purpose within the library.