Adaptive, locally-linear models of complex dynamics

The dynamics of complex systems generally include high-dimensional, non-stationary and non-linear behavior, all of which pose fundamental challenges to quantitative understanding. To address these difficulties we detail a new approach based on local linear models within windows determined adaptively from the data. While the dynamics within each window are simple, consisting of exponential decay, growth and oscillations, the collection of local parameters across all windows provides a principled characterization of the full time series. To explore the resulting model space, we develop a novel likelihood-based hierarchical clustering and we examine the eigenvalues of the linear dynamics. We demonstrate our analysis with the Lorenz system undergoing stable spiral dynamics and in the standard chaotic regime. Applied to the posture dynamics of the nematode $C. elegans$ our approach identifies fine-grained behavioral states and model dynamics which fluctuate close to an instability boundary, and we detail a bifurcation in a transition from forward to backward crawling. Finally, we analyze whole-brain imaging in $C. elegans$ and show that the stability of global brain states changes with oxygen concentration.Comment: 25 pages, 16 figure

The image of an employee in Russian psychological studies: a desk study

The article covers the background of Russian psychological studies on the image of an employee. The article deals with the self-concept as a building block of the image of an employee. The author analyzes the role of professional self-determination, motivational characteristics and mental regulators in creating the image of an employee

Capturing the nonlinear dynamics of animal behavior with Applications to the Nematode C. elegans

From microorganisms to humans, animals behave by making complex changes in their shape and posture over time with remarkable flexibility. To deal with the complexity of animal behavior existing analysis methods view it as a discrete time process, which is composed of transitions between a finite number of stereotyped motifs, such as walking or reaching. This viewpoint, however, ignores the fact that most behavior is not stereotyped. There is, therefore, a need for a perspective that captures the continuous complexity of animal behavior and offers detailed insights into general principles underlying its generation and control. In my Ph.D. thesis, I propose a new approach of analyzing animal behavior, based on the idea that it is fundamentally a continuous time spatiotemporal dynamical system. I develop methods to transform behavioral recordings into a geometrical object called the "behavioral state space". As an organism moves, the corresponding behavioral state traces out a continuous trajectory in the state space, such that the geometry and topology of the trajectories encode quantitative and qualitative properties of behavior. Finally, I characterize an organism\u27s behavioral dynamics in terms of the topological invariants estimated from the local Jacobians of the state space trajectories. The invariants capture essential aspects of a dynamical system, such as the number of degrees of freedom, symmetries in the governing equations of motion, and measures of predictability and variability. I use the tools and concepts developed the above to perform a detailed characterization of continuous dynamics of freely behaving \textit{C. elegans} worms.Okinawa Institute of Science and Technology Graduate Universit

Toward Automated UML Diagram Assessment:Comparing LLM-Generated Scores with Teaching Assistants

This paper investigates the feasibility of using Large Language Models (LLMs) to automate the grading of Unified Modeling Language (UML) class diagrams in a software design course. Our method involves carefully designing case studies with constraints that guide students’ design choices, converting visual diagrams to textual descriptions, and leveraging LLMs’ natural language processing capabilities to evaluate submissions. We evaluated our approach using 92 student submissions, comparing grades assigned by three teaching assistants with those generated by three LLMs (Llama, GPT o1-mini, and Claude). Our results show that GPT o1-mini and Claude Sonnet achieved strong alignment with human graders, reaching correlation coefficients above 0.76 and Mean Absolute Errors below 4 points on a 40-point scale. The findings suggest that LLM-based grading can provide consistent, scalable assessment of UML diagrams while matching the grading quality of human assessors. This approach offers a promising solution for managing growing student numbers while ensuring fair and timely feedback.</p

Patterns and prevalence of benign breast disease in Western India

Background: Benign breast diseases constitute a heterogeneous group of disorders including developmental abnormality, epithelial and stromal proliferation, inflammatory lesions and neoplasm. Benign breast lesions deserve attention because of their high prevalence, their impact on women’s life and due to cancerous potential of some histological types. Treatment of BBDS is preservation of breast tissue as far as possible in contrast to traumatizing mutilating surgeries in breast cancers.Methods: This study of 210 cases of histologically diagnosed benign breast lesions was carried out in the Department of Pathology, at tertiary care teaching hospital with attached peripheral hospitals in a metropolitan city of western India from August 2014 to August 2016.Results: Out of 210 benign lesions, 201 (95.7%) were found in females and 9 (4.3%) were found in males. Commonest benign breast lesion was fibroadenoma (77.62%), followed by fibrocystic disease (4.3%) and gynaecomastia (4.3%).Conclusions: Fibroadenoma is the most common benign breast disease. Most of the patients presented with painless lump in the breast in upper outer quadrant of the breast. Histopathology plays an important role in the diagnosis of benign breast diseases

A Markovian dynamics for C.elegansC. elegans behavior across scales

How do we capture the breadth of behavior in animal movement, from rapid body twitches to aging? Using high-resolution videos of the nematode worm $C. elegans$, we show that a single dynamics connects posture-scale fluctuations with trajectory diffusion, and longer-lived behavioral states. We take short posture sequences as an instantaneous behavioral measure, fixing the sequence length for maximal prediction. Within the space of posture sequences we construct a fine-scale, maximum entropy partition so that transitions among microstates define a high-fidelity Markov model, which we also use as a means of principled coarse-graining. We translate these dynamics into movement using resistive force theory, capturing the statistical properties of foraging trajectories. Predictive across scales, we leverage the longest-lived eigenvectors of the inferred Markov chain to perform a top-down subdivision of the worm's foraging behavior, revealing both ``runs-and-pirouettes'' as well as previously uncharacterized finer-scale behaviors. We use our model to investigate the relevance of these fine-scale behaviors for foraging success, recovering a trade-off between local and global search strategies.Comment: 28 pages, 14 figure

Capturing the Continuous Complexity of Behavior in C. elegans

Animal behavior is often quantified through subjective, incomplete variables that may mask essential dynamics. Here, we develop a behavioral state space in which the full instantaneous state is smoothly unfolded as a combination of short-time posture dynamics. Our technique is tailored to multivariate observations and extends previous reconstructions through the use of maximal prediction. Applied to high-resolution video recordings of the roundworm \textit{C. elegans}, we discover a low-dimensional state space dominated by three sets of cyclic trajectories corresponding to the worm's basic stereotyped motifs: forward, backward, and turning locomotion. In contrast to this broad stereotypy, we find variability in the presence of locally-unstable dynamics, and this unpredictability shows signatures of deterministic chaos: a collection of unstable periodic orbits together with a positive maximal Lyapunov exponent. The full Lyapunov spectrum is symmetric with positive, chaotic exponents driving variability balanced by negative, dissipative exponents driving stereotypy. The symmetry is indicative of damped, driven Hamiltonian dynamics underlying the worm's movement control.Comment: 26 pages, 14 figure

Providing oxygen to children in hospitals: a realist review

OBJECTIVE: To identify and describe interventions to improve oxygen therapy in hospitals in low-resource settings, and to determine the factors that contribute to success and failure in different contexts. METHODS: Using realist review methods, we scanned the literature and contacted experts in the field to identify possible mechanistic theories of how interventions to improve oxygen therapy systems might work. Then we systematically searched online databases for evaluations of improved oxygen systems in hospitals in low- or middle-income countries. We extracted data on the effectiveness, processes and underlying theory of selected projects, and used these data to test the candidate theories and identify the features of successful projects. FINDINGS: We included 20 improved oxygen therapy projects (45 papers) from 15 countries. These used various approaches to improving oxygen therapy, and reported clinical, quality of care and technical outcomes. Four effectiveness studies demonstrated positive clinical outcomes for childhood pneumonia, with large variation between programmes and hospitals. We identified factors that help or hinder success, and proposed a practical framework depicting the key requirements for hospitals to effectively provide oxygen therapy to children. To improve clinical outcomes, oxygen improvement programmes must achieve good access to oxygen and good use of oxygen, which should be facilitated by a broad quality improvement capacity, by a strong managerial and policy support and multidisciplinary teamwork. CONCLUSION: Our findings can inform practitioners and policy-makers about how to improve oxygen therapy in low-resource settings, and may be relevant for other interventions involving the introduction of health technologies