Miracle-dz/UniFAR-FTUs huggingface dataset:
Heterogeneity and spatial correlations in stochastic many-particle systems

Life can only exist due to an intriguingly high degree of organization and differentiation. To establish this order, biological systems rely on a constant flux of energy from their environment and they therefore operate far from thermal equilibrium. The ensuing phenomenology often is highly complex such that a deep going understanding poses significant challenges to theoretical science. In this thesis, we investigate how biological systems maintain functional differentiation and why this specialization is sometimes disfavored by evolution. We are interested in the fundamental physical mechanisms behind these processes and develop paradigmatic models that are simple enough to be accessible by mathematical and physical reasoning, but which at the same time capture the principal characteristics of the biological system under consideration. On the largest time scales, differentiation is subject to evolutionary forces. How species differentiation can be maintained is still an open question. Indeed, according to Darwinian evolution, only a single species the fittest should survive. Recent studies have shown that spatial correlations and nonhierarchical competition promote species coexistence. We study the processes that lead to the maintenance and loss of biodiversity in a paradigmatic model of three cyclically interacting species. By calculating the full distribution of extinction times we show that these processes are surprisingly rich, comprising several dynamical states on different time scales. We furthermore argue that the dynamic processes leading to the transient maintenance of biodiversity are closely linked to minima of a coarse-grained potential. These minima give information about the scaling of extinction times with the system size and thereby the stability of biodiversity. Similar as in statistical physics, this effective free energy landscape changes qualitatively at certain threshold values of the species’ mobility and the relative strength of different types of competition. We provide the complete phase diagrams for the population dynamics and give a comprehensive analysis of the spatio-temporal dynamics and routes to extinction in the respective phases. We then take a broader perspective on biodiversity and ask, under which conditions specialization arises and when it is circumvented by phenotypic heterogeneity. Genetic diversity and phenotypic heterogeneity are commonly found in bacterial populations and viruses. As an example, some bacteria stochastically switch between phenotypic states to minimize the risk of population extinction due to an attack with antibiotics. Inspired by these phenomena, we investigate heterogeneous, stochastic many-particle systems. The basic idea is that each particle is endowed with distinct
Isomorphisms of some quantum spaces

We consider a series of questions that grew out of determining when two quantum planes are isomorphic. In particular, we consider a similar question for quantum matrix algebras and certain ambiskew polynomial rings. Additionally, we modify a result by Alev and Dumas to show that two quantum Weyl algebras are isomorphic if and only if their parameters are equal or inverses of each other.
Evaluations of Antibacterial Properties of Zingiber purpureum Essential Oil Against 13 Different Gram-positive and Gram-negative Bacteria

BACKGROUND: Indonesia's tropical forest is home to around 80% of the world's medicinal plants. One of these is Zingiber purpureum, which have traditionally been used to treat joint discomfort, the common cold, and jaundice. The rhizomes of this plant have been suggested to possess antibacterial action in the treatment of infections. In this study, Z. purpureum was screened for antibacterial activity against 13 bacteria (Gram-positive and Gram-negative). METHODS: Z. purpureum rhizomes were obtained and the distillated extracts were made to generate essential oil. The minimum inhibitory concentration (MIC) and Kirby Bauer disk diffusion methods were used to determine the antibacterial activity.RESULTS: All bacteria activity were inhibited by the essential oil of Z. purpureum at concentrations ranging from 2.5 vol% to 10 vol%. However, several bacterias (Escherichia coli, Pseudomonas aeruginosa, and Enterobacter cloacae) were inhibited at the lowest concentration (0.63 vol %), with the inhibition zones ranging from 6.7 mm to 8.0 mm. Meanwhile, the widest inhibition zone (13.3 mm) was reported on E. cloacae at 10 vol% concentration.CONCLUSION: A 10 vol% Z. purpureum rhizome extract inhibits Gram-positive and Gram-negative bacteria, particularly those that are resistant to a variety of antibiotics.KEYWORDS: Zingiber purpureum, antibacterial agents, susceptibility test, infection
TOWARDS A FREQUENCY-DEPENDENT DISCRETE MAXIMUM PRINCIPLE FOR THE IMPLICIT MONTE CARLO EQUATIONS

It has long been known that temperature solutions of the Implicit Monte Carlo (IMC) equations can exceed the external boundary temperatures, a so-called violation of the 'maximum principle. ' Previous attempts at prescribing a maximum value of the time-step size {Delta}{sub t} that is sufficient to eliminate these violations have recommended a {Delta}{sub t} that is typically too small to be used in practice and that appeared to be much too conservative when compared to numerical solutions of the IMC equations for practical problems. In this paper, we derive a new estimator for the maximum time-step size that includes the spatial-grid size {Delta}{sub x}. This explicitly demonstrates that the effect of coarsening {Delta}{sub x} is to reduce the limitation on {Delta}{sub t}, which helps explain the overly conservative nature of the earlier, grid-independent results. We demonstrate that our new time-step restriction is a much more accurate means of predicting violations of the maximum principle. We discuss how the implications of the new, grid-dependent timestep restriction can impact IMC solution algorithms.
Tremor in Parkinson’s Disease: From Pathophysiology to Advanced Therapies

Background: Tremor is one of the most prevalent symptoms in Parkinson’s Disease (PD). The progression and management of tremor in PD can be challenging, as response to dopaminergic agents might be relatively poor, particularly in patients with tremor-dominant PD compared to the akinetic/rigid subtype. In this review, we aim to highlight recent advances in the underlying pathogenesis and treatment modalities for tremor in PD. Methods: A structured literature search through Embase was conducted using the terms “Parkinson’s Disease” AND “tremor” OR “etiology” OR “management” OR “drug resistance” OR “therapy” OR “rehabilitation” OR “surgery. ” After initial screening, eligible articles were selected with a focus on published literature in the last 10 years. Discussion: The underlying pathophysiology of tremor in PD remains complex and incompletely understood. Neurodegeneration of dopaminergic neurons in the retrorubral area, in addition to high-power neural oscillations in the cerebello-thalamo-cortical circuit and the basal ganglia, play a major role. Levodopa is the first-line therapeutic option for all motor symptoms, including tremor. The addition of dopamine agonists or anticholinergics can lead to further tremor reduction. Botulinum toxin injection is an effective alternative for patients with pharmacological-resistant tremor who are not seeking advanced therapies. Deep brain stimulation is the most well-established advanced therapy owing to its long-term efficacy, reversibility, and effectiveness in other motor symptoms and fluctuations. Magnetic resonance-guided focused ultrasound is a promising modality, which has the advantage of being incisionless. Cortical and peripheral electrical stimulation are non-invasive innovatory techniques that have demonstrated good efficacy in suppressing intractable tremor.
Comparison of Treatment Methods for Syndesmotic Injuries With Posterior Tibiofibular Ligament Ruptures: A Cadaveric Biomechanical Study

Background: Studies on ankle syndesmosis have focused on anterior inferior tibiofibular ligament (AITFL) and interosseous membrane injuries; however, the characteristics of posterior inferior tibiofibular ligament (PITFL) ruptures remain unclear. Purpose/Hypothesis: This study evaluated the biomechanical characteristics of syndesmotic instability caused by PITFL injury and compared various treatment methods. We hypothesized that PITFL injury would lead to syndesmotic internal rotational instability and that the stability would be restored with suture tape (ST) PITFL augmentation. Study Design: Controlled laboratory study. Methods: Ten uninjured fresh-frozen cadaveric leg specimens were tested via forces applied to the external and internal rotation of the ankle joint. The fibular rotational angle (FRA) related to the tibia, anterior tibiofibular diastasis (aTFD), and posterior tibiofibular diastasis (pTFD) were measured using a magnetic tracking system. Six models were created: (1) intact, (2) AITFL injury; (3) AITFL + PITFL injury; (4) suture button (SB) fixation; (5) SB + anterior ST (aST) fixation; and (6) SB + aST + posterior ST fixation. The FRA, aTFD, and pTFD were statistically compared between the intact ankle and each injury or fixation model. Results: In the intact state, the changes in FRA and aTFD were 1.09° and 0.33 mm when external rotation force was applied and were 0.57° and 0.41 mm when internal rotation force was applied. In the AITFL injury model, the changes in FRA and aTFD were 2.38° and 1.51 mm when external rotation force was applied, which were significantly greater versus intact (P = .032 and .008, respectively). In the AITFL + PITFL injury model, the changes in FRA and pTFD were 2.12° and 1.02 mm when internal rotation force was applied, which were significantly greater versus intact (P = .007 and .003, respectively). In the SB fixation model, the change in FRA was 2.98° when external rotation force was applied, which was significantly higher compared with intact (P < .001). There were no significant differences between the SB + aST fixation model and the intact state on any measurement. Conclusion: PITFL injury significantly increased syndesmotic instability when internal rotation force was applied. SB + aST fixation was effective in restoring syndesmotic stability. Clinical Relevance: These results suggest that SB + aST fixation is sufficient for treating severe syndesmotic injury with PITFL rupture.
Climate change, moose, and subsistence harvest: social-ecological assessment of Nuiqsut, Alaska

Assessing the impact of a rapidly warming climate on subsistence-based livelihoods in the Arctic is critical for building resilience for rural communities. We used a social-ecological system (SES) framework to evaluate the possible range of changes in moose abundance, distribution, and harvesting for Nuiqsut, a small native community in northern Alaska. Our results indicate that within the area used for hunting by the village, moose ( Alces alces ) abundance has been highly variable despite recent increases in tall shrubs, which provide forage and cover for moose. Projections for moose abundance also indicate continued fluctuation in the future. Our analysis shows that future increases in moose distribution under a warming climate will not be in river systems accessible to hunters by boat. Hunter access (i.e., river navigability) also may not increase under warming. The community of Nuiqsut thus offers a case study of high exposure to an expansion of moose habitat and distribution under warming, but low sensitivity to this change because of constraints on harvesting. These outcomes are not evident when evaluating social and ecological components separately, illustrating the value of an SES approach. They also provide an example in which a rapid change in an arctic landscape and subsistence resource under climate warming may not translate into altered harvest opportunities.
A critical examination of models of annual‐plant population dynamics and density‐dependent fecundity

Mathematical models serve many purposes in biology. Each and every model is a necessary simplification of reality, and, as simplifications, these models are also wrong by definition. And yet there are many ways to be wrong, and some of these are a much greater concern than others. For example, a paradoxical model‐based prediction may simply be puzzling whereas unphysical variables (e.g. negative amounts of time or temperatures below absolute zero) and nonbiological variables (e.g. negative abundances or negative feeding rates) should be avoided altogether. Here I analyse a discrete‐time model of annual‐plant population dynamics and three phenomenological models for density‐dependent fecundity. These phenomenological models are generally interchanged solely on the basis of their statistical fit to data. On the other hand, I highlight ways in which their phenomenological basis hampers our ability to capture known aspects of annual‐plant biology. I then demonstrate how to specify a more flexible, biologically appropriate model and illustrate this model's behaviour and interpretation in single‐species and multi‐species contexts. By constructing this generative model for annual‐plant population dynamics, I can also demonstrate how and why emergent phenomena, such as negative density dependence, emerge. Although my focus is on a model applied to annual plants, the biological implications extend to modelling any species with a discrete life cycle and nonoverlapping generations. More broadly, my exploration here showcases that there are many more criteria with which we could, and arguably should, ground‐truth mathematical models across biology.
Transformation of dissolved organic matter by two Indo‐Pacific sponges

Dissolved organic matter (DOM) is the largest organic carbon reservoir in the ocean and an integral component of biogeochemical cycles. The role of free‐living microbes in DOM transformation has been studied thoroughly, whereas little attention has been directed towards the influence of benthic organisms. Sponges are efficient filter feeders and common inhabitants of many benthic communities circumglobally. Here, we investigated how two tropical coral reef sponges shape marine DOM. We compared bacterial abundance, inorganic and organic nutrients in off reef, sponge inhalant, and sponge exhalant water of Melophlus sarasinorum and Rhabdastrella globostellata. DOM and bacterial cells were taken up, and dissolved inorganic nitrogen was released by the two Indo‐Pacific sponges. Both sponge species utilized a common set of 142 of a total of 3040 compounds detected in DOM on a molecular formula level via ultrahigh‐resolution mass spectrometry. In addition, species‐specific uptake was observed, likely due to differences in their associated microbial communities. Overall, the sponges removed presumably semi‐labile and semi‐refractory compounds from the water column, thereby competing with pelagic bacteria. Within minutes, sponge holobionts altered the molecular composition of surface water DOM (inhalant) into a composition similar to deep‐sea DOM (exhalent). The apparent radiocarbon age of DOM increased consistently from off reef and inhalant to exhalant by about 900 14C years for M. sarasinorum. In the pelagic, similar transformations require decades to centuries. Our results stress the dependence of DOM lability definition on the respective environment and illustrate that sponges are hotspots of DOM transformation in the ocean.
Analytic NLFM Waveform Design With Harmonic Decomposition for Synthetic Aperture Radar

The nonlinear frequency modulation (NLFM) waveform is a promising candidate for the linear frequency modulation (LFM) signal because its autocorrelation output exhibits low sidelobes without loss of signal-to-noise ratio (SNR), also avoiding the transmitting power loss for spaceborne synthetic aperture radar (SAR). However, the acquisition of the analytical expression of the NLFM waveform is often closely related to the indirect instantaneous frequency function generated by the principle of stationary phase (POSP), thus it is not inconvenient for the real-time generation of the efficient and precise NLFM signal on board. In this letter, based on the harmonic decomposition, closed-form expressions of the NLFM waveform, which are directly calculated by the predefined window, are derived in both time and frequency domains. Therefore, it is very beneficial to the real-time generation and process of the NLFM waveform for the SAR system. All the simulation results and analyses validate the promising potential of the closed-form expressions of the NLFM waveform for SAR application.
MDFlow: Unsupervised Optical Flow Learning by Reliable Mutual Knowledge Distillation

Recent works have shown that optical flow can be learned by deep networks from unlabelled image pairs based on brightness constancy assumption and smoothness prior. Current approaches additionally impose an augmentation regularization term for continual self-supervision, which has been proved to be effective on difficult matching regions. However, this method also amplify the inevitable mismatch in unsupervised setting, blocking the learning process towards optimal solution. To break the dilemma, we propose a novel mutual distillation framework to transfer reliable knowledge back and forth between the teacher and student networks for alternate improvement. Concretely, taking estimation of off-the-shelf unsupervised approach as pseudo labels, our insight locates at defining a confidence selection mechanism to extract relative good matches, and then add diverse data augmentation for distilling adequate and reliable knowledge from teacher to student. Thanks to the decouple nature of our method, we can choose a stronger student architecture for sufficient learning. Finally, better student prediction is adopted to transfer knowledge back to the efficient teacher without additional costs in real deployment. Rather than formulating it as a supervised task, we find that introducing an extra unsupervised term for multi-target learning achieves best final results. Extensive experiments show that our approach, termed MDFlow, achieves state-of-the-art real-time accuracy and generalization ability on challenging benchmarks. Code is available at https://github.com/ltkong218/MDFlow.
Optimization of Artistic Image Segmentation Algorithm Based on Feed Forward Neural Network under Complex Background Environment

Based on the theory and application, this paper discusses the optimization of art image segmentation algorithm based on FFNN (Feed Forward Neural Network). In this paper, residual units are used in the corresponding stages of encoder and decoder, and feature information of several convolution layers in each convolution stage of encoder is extracted at the same time. And the feature pyramid module is used to extract multiscale features from the feature map of the last convolution stage in the encoder. Finally, pixel by pixel additions combine the previously mentioned feature information into the corresponding layer of the decoder. Additionally, an improved weight adaptive algorithm based on feature preservation is suggested in this paper, which addresses the issue that the conventional image segmentation algorithm is noise-sensitive. The adaptive connection weight mechanism is also introduced. The accuracy and recall rates of this optimization algorithm can both reach 96.574%, according to the results of 50% cross-validation. All the segmentation performance evaluation indexes of this algorithm are higher than the existing main algorithms. Moreover, the algorithm takes a short time, does not need too much manual intervention, and can effectively segment artistic images. The optimization algorithm in this paper has certain reference significance for the related research of artistic image segmentation.
Hierarchical Variation in Phenotypic Flexibility across Timescales and Associated Survival Selection Shape the Dynamics of Partial Seasonal Migration

Population responses to environmental variation ultimately depend on within-individual and among-individual variation in labile phenotypic traits that affect fitness and resulting episodes of selection. Yet complex patterns of individual phenotypic variation arising within and between time periods, as well as associated variation in selection, have not been fully conceptualized or quantified. We highlight how structured patterns of phenotypic variation in dichotomous threshold traits can theoretically arise and experience varying forms of selection, shaping overall phenotypic dynamics. We then fit novel multistate models to 10 years of band-resighting data from European shags to quantify phenotypic variation and selection in a key threshold trait underlying spatioseasonal population dynamics: seasonal migration versus residence. First, we demonstrate substantial among-individual variation alongside substantial between-year individual repeatability in within-year phenotypic variation (“flexibility”), with weak sexual dimorphism. Second, we demonstrate that between-year individual variation in within-year phenotypes (“supraflexibility”) is structured and directional, consistent with the threshold trait model. Third, we demonstrate strong survival selection on within-year phenotypes—and hence on flexibility—that varies across years and sexes, including episodes of disruptive selection representing costs of flexibility. By quantitatively combining these results, we show how supraflexibility and survival selection on migratory flexibility jointly shape population-wide phenotypic dynamics of seasonal movement.
Quality of Life in Schoolchildren, Their Parents and Teachers during the COVID-19 Pandemic: Psychosomatic Health, Teachers’ and Parents’ Burnout Along with the Prevalence of Depressive and Anxiety Symptoms

The COVID-19 pandemic and the related changes in the implementation of educational activities affected three groups of the school community: schoolchildren, their parents and teachers. The purpose of this study is to assess psychological functioning in these groups in the period before returning to full-time face-to-face education. The study involved 88 schoolchildren, 99 parents and 36 teachers from Poland. Life satisfaction, subjective physical and mental health complaints as well as the quality of life were assessed in students. Anxiety and depressive symptoms, teachers’ and parental burnout were also studied. Additionally, the usage of such maladaptive coping strategies as rumination was assessed in teachers. The analysis revealed that lower levels of psychological well-being were shown by girls (compared to boys) and schoolchildren from grades 7 to 8 (compared to younger pupils). Teachers scored relatively high on the anxiety/depressive symptoms and work burnout scales. In contrast, parents had lower levels of anxiety/depressive symptoms and the level of parental burnout was average.Among the participants of the educational process, pupils in the higher grades (7–8), especially girls, as well as teachers had poorer well-being. We suggest that measures should be taken to provide psychological support to these risk groups.
Improved thermal stability of Al2O3/HfO2/Al2O3 high-k gate dielectric stack on GaAs

Thermal stability of HfO2 high-k gate dielectric on GaAs is investigated. Compared to HfO2 gate dielectric, significant improvements in interfacial properties as well as electrical characteristics were found by constructing a Al2O3/HfO2/Al2O3 dielectric stack. At elevated temperatures, the amorphous Al2O3 layers were effective in inhibiting crystallization of HfO2. Since the passivating Al2O3 layers prevent interfacial oxide and trap charge formation, it aids in reducing the increasing rate of equivalent oxide thickness as well as capacitance-voltage hysteresis. Transmission electron microscopy and x-ray photoelectron spectroscopy data supported the improved electrical characteristic of GaAs metal-oxide-semiconductor capacitors with Al2O3/HfO2/Al2O3 gate dielectric stack.