Miracle-dz/UniFAR-FTUs huggingface dataset:
H∞-type control for discrete-time stochastic systems

In this paper we consider discrete-time, linear stochastic systems with random state and input matrices which are subjected to stochastic disturbances and controlled by dynamic output feedback. The aim is to develop an H∞-type theory for such systems. For this class of systems a stochastic bounded real lemma is derived which provides the basis for a linear matrix inequality (LMI) approach similar to, but more general than the one presented in Reference 1 for stochastic differential systems. Necessary and sufficient conditions are derived for the existence of a stabilizing controller which reduces the norm of the closed-loop perturbation operator to a level below a given threshold γ. These conditions take the form of coupled nonlinear matrix inequalities. In the absence of the stochastic terms they get reduced to the linear matrix inequalities of deterministic H∞-theory for discrete time systems. Copyright © 1999 John Wiley & Sons, Ltd.
Is environmental enrichment beneficial for laboratory animals? A systematic review of studies in zebrafish

Environmental enrichment (EE) consists of a series of interventions that are carried out in the home environment to provide greater exposure to sensory stimuli with the objective of mimicking the natural habitat for the animals housed in the laboratory, offering a more complex environment like those found in nature. Some studies have shown the positive effects of EE on zebrafish housed in a laboratory environment. However, this evidence is still very recent and accompanied by contradictory results. Furthermore, there is great variability in the protocols applied, and in the conditions of the tests, tanks, and materials used for creating an EE environment. This substantial variability can bring many uncertainties to the development of future studies and hinder the reproducibility and replicability of research. In this context, the main objective of this study was to carry out a systematic review of the literature aiming to provide an overview of the EE protocols used in zebrafish. We conducted a systematic review following PRISMA recommendations. The literature search was performed in PubMed, Scopus, and Web of Science databases and the studies were selected based on inclusion/exclusion criteria. We performed data extraction and risk of bias analysis of the studies included. A total of 901 articles were identified in the databases and 27 of these studies were included in this review. Among these studies, the effect of EE was evaluated as two different proposals. (1) to improve animal welfare and (2) as an intervention for the prevention of some disorders. Although the zebrafish EE protocols presented a series of experimental differences, the results showed that the benefits of the EE for zebrafish were robust. According to the results described here, the use of EE in the zebrafish home tank provides better welfare and may reduce sources of bias in scientific experiments, such as high-stress levels and fighting events.
Benchmarking algorithms for joint integration of unpaired and paired single-cell RNA-seq and ATAC-seq data

Single-cell RNA-sequencing (scRNA-seq) measures gene expression in single cells, while single-nucleus ATAC-sequencing (snATAC-seq) enables the quantification of chromatin accessibility in single nuclei. These two data types provide complementary information for deciphering cell types/states. However, when analyzed individually, scRNA-seq and snATAC-seq data often produce conflicting results regarding cell type/state assignment. In addition, there is a loss of power as the two modalities reflect the same underlying cell types/states. Recently, it has become possible to measure both gene expression and chromatin accessibility from the same nucleus. Such paired data make it possible to directly model the relationships between the two modalities. However, given the availability of the vast amount of single-modality data, it is desirable to integrate the paired and unpaired single-modality data to gain a comprehensive view of the cellular complexity. Here, we benchmarked the performance of seven existing single-cell multi-omic data integration methods. Specifically, we evaluated whether these methods are able to uncover peak-gene associations from single-modality data, and to what extent the multiome data can provide additional guidance for the analysis of the existing single-modality data. Our results indicate that multiome data are helpful for annotating single-modality data, but the number of cells in the multiome data is critical to ensure a good cell type annotation. Additionally, when generating a multiome dataset, the number of cells is more important than sequencing depth for cell type annotation. Lastly, Seurat v4 is the best at integrating scRNA-seq, snATAC-seq, and multiome data even in the presence of complex batch effects.
Serial Capture Affinity Purification and Integrated Structural Modeling of the H3K4me3 Binding and DNA Damage Related WDR76:SPIN1 Complex

WDR76 is a multifunctional protein involved in many cellular functions. With a diverse and complicated protein interaction network, dissecting the structure and function of specific WDR76 complexes is needed. We previously demonstrated the ability of the Serial Capture Affinity Purification (SCAP) method to isolate specific complexes by introducing two proteins of interest as baits at the same time. Here, we applied SCAP to dissect a subpopulation of WDR76 in complex with SPIN1, a histone marker reader that specifically recognizes trimethylated histone H3 lysine4 (H3K4me3). In contrast to the SCAP analysis of the SPIN1:SPINDOC complex, H3K4me3 was copurified with the WDR76:SPIN1 complex. In combination with crosslinking mass spectrometry, we built an integrated structural model of the complex which revealed that SPIN1 recognized the H3K4me3 epigenetic mark while interacting with WDR76. Lastly, interaction network analysis of copurifying proteins revealed the potential role of the WDR76:SPIN1 complex in the DNA damage response. Teaser In contrast to the SPINDOC/SPIN1 complex, analyses reveal that the WDR76/SPIN1 complex interacts with core histones and is involved in DNA damage.
Influence of root cortical aerenchyma on the rhizosphere microbiome of field-grown maize

The root anatomical phenotype root cortical aerenchyma (RCA) decreases the metabolic cost of soil exploration and improves plant growth under drought and low soil fertility. RCA may also change the microenvironment of rhizosphere microorganisms by increasing oxygen availability or by reducing carbon rhizodeposition. We tested the hypothesis that plants with contrasting expression of RCA have different rhizosphere prokaryotic communities. Maize inbreds were grown in two field sites, Limpopo Province, South Africa and Pennsylvania, USA, and their rhizosphere soil sampled at flowering. High- and low-nitrogen fertilization was imposed as separate treatments in the experiment in South Africa. The rhizosphere microbial composition of plants with contrasting RCA was characterized by metabarcoding of the 16S rRNA genes. Geographic location was the most important factor related to the composition of rhizosphere microbial communities. In the site in South Africa, RCA explained greater percent of variance (9%) in the composition of microbial communities than genotype (7%). Although other root anatomical and architectural phenotypes were studied as possible cofactors affecting the microbial composition, RCA was among the best significant explanatory variables for the South African site although it was neutral in the Pennsylvania site. High-RCA rhizospheres significantly enriched OTUs of the families Burkholderiaceae (in South Africa) and Bacillaceae (in USA), compared to low-RCA plants, and OTUs of the families Beijerinckiaceae and Sphingomonadaceae were enriched at the two nitrogen levels in high RCA plants in South Africa. Our results are consistent with the hypothesis that RCA is an important factor for rhizosphere microbial communities, especially under suboptimal nitrogen conditions.
Statistic Inference under Two Structurally Different Approaches to Interval Data

Two broadly different approaches have been proposed for handling data that contain non-negligible interval uncertainty from censoring, plus-minus digital readouts, and other sources of measurement imprecision or incertitude. Modeling interval data with uniform distributions over their ranges allows relatively straightforward calculation of sample statistics, but does not guarantee these estimates will approach the parameters of the actual distribution, even for asymptotically many random samples. In contrast, modeling interval data as bounds on possible values yields corresponding bounds on sample statistics that are easier to interpret although often more difficult to calculate. We illustrate the approaches in estimating descriptive statistics, empirical distribution functions, and best-fit distributions. Statistical inference under the bounding approach generally yields a class of decisions under the theory of imprecise probabilities. In contrast, the uniforms approach will yield a unique decision (up to indifference), although this decision cannot be said to be implied by the data alone because it depends on ancillary assumptions that may not
The dynamics of collapsing Bose-Einstein condensates.

This project aims to study the behavior of a cloud of Rubidium-85 atoms under an attractive interaction potential when used to create a Bose-Einstein condensate. Efforts to describe the dynamics of an attractive condensate using only the Gross-Pitaevskii equation have been unable to describe all of the features of such a system, and so the mathematical approach used is a perturbative method of corrections to the Gross-Pitaevskii equation. A system of analytical equations to describe a condensate is derived herein, which is then arranged into a form suitable for numerical solution. The actual calculation is not performed, but details of the computational procedure are provided, as well as an analysis of the difficulties inherent in the calculation.
Is machine translation a dim technology for its users? An eye tracking study

State-of-the-art research shows that the impact of language technologies on public awareness and attitudes toward using machine translation has been changing. As machine translation acceptability is considered to be a multilayered concept, this paper employs criteria of usability, satisfaction and quality as components of acceptability measurement. The study seeks to determine whether there are any differences in the machine-translation acceptability between professional users, i.e., translators and language editors, and non-professional users, i.e., ordinary users of machine translation who use it for non-professional everyday purposes. The main research questions whether non-professional users process raw machine translation output in the same way as professional users and whether there is a difference in the processing of raw machine-translated output between users with different levels of machine-translated text acceptability are analyzed. The results of an eye tracking experiment, measuring fixation time, dwell time and glance count, indicate a difference between professional and non-professional users' cognitive processing and acceptability of machine translation output: translators and language editors spend more time overall reading the machine-translated texts, possibly because of their deeper critical awareness as well as professional attitude toward the text. In terms of acceptability overall, professional translators critically assess machine translation on all components of which confirms the findings of previous similar research. However, the study draws attention to non-professional users' lower awareness regarding machine translation quality. The study was conducted within a research project that received funding from the Research Council of Lithuania (LMTLT, agreement No S-MOD-21-2), seeking to explore and evaluate the impact on society of machine translation technological solutions.
Human movement in simulated hypogravity—Bridging the gap between space research and terrestrial rehabilitation

Human movement is optimized to Earth's gravity and based on highly complex interactions between sensory and neuro-muscular systems. Yet, humans are able to adapt—at least partially—to extreme environments upon and beyond Earth's surface. With upcoming Lunar Gateway and Artemis missions, it is crucial to increase our understanding of the impact of hypogravity—i.e., reduced vertical loading—on physiological and sensory-motor performances to improve countermeasure programs, and define crewmember's readiness to perform mission critical tasks. Several methodologies designed to reduce vertical loading are used to simulate hypogravity on Earth, including body weight support (BWS) devices. Countering gravity and offloading the human body is also used in various rehabilitation scenarios to improve motor recovery in neurological and orthopedic impairments. Thus, BWS-devices have the potential of advancing theory and practice of both space exploration and terrestrial rehabilitation by improving our understanding of physiological and sensory-motor adaptations to reduced vertical loading and sensory input. However, lack of standardization of BWS-related research protocols and reporting hinders the exchange of key findings and new advancements in both areas. The aim of this introduction paper is to review the role of BWS in understanding human movement in simulated hypogravity and the use of BWS in terrestrial rehabilitation, and to identify relevant research areas contributing to the optimization of human spaceflight and terrestrial rehabilitation. One of the main aims of this research topic is to facilitate standardization of hypogravity-related research protocols and outcome reporting, aimed at optimizing knowledge transfer between space research and BWS-related rehabilitation sciences.
Characterization of early myocardial inflammation in ischemia-reperfusion injury

Background Myocardial injury may be caused by myocardial ischemia-reperfusion (IR), and salvaging such an injury is still a great challenge in clinical practice. This study comprehensively characterized the physiopathologic changes of myocardial injury after IR to explore the underlying mechanism in the early reperfusion phase with particular emphasis on early myocardial inflammation. Methods and Results The experimental IR model was obtained by the left anterior descending artery’s transient ligation of C57BL/6 mice. T2W signals of all mice showed increased signal at different IR stages. It was positively correlated with inflammatory cytokines and cells. T2W imaging by 7.0 T MRI surprisingly detected signal enhancement, but histopathology and flow cytometry did not reveal any inflammatory cells infiltration within 3 h after IR. Cardiomyocyte swelling and increased vascular permeability were observed by WGA staining and ultrastructural analysis, respectively. The 3 h IR group showed that the cardiomyocytes were severely affected with disintegrating myofilaments and mitochondria. Both VEGF and phosphorylated Src protein were markedly expressed in the 3 h IR group in comparison with the sham group, and TUNEL staining displayed little positive cells. Cleaved caspase-3 apoptin also has similar expression levels with that of the sham group. Resident macrophages had notably become M1 phenotype. The T2W signal was still elevated, and we observed that collagen deposition occurred from 1 to 7 days. Conclusions The inflammation response during the first week after reperfusion injury gradually increase 3 h later, but the main manifestation before that was edema. This study indicated that the first 3 h may be crucial to the early rescue process for reperfusion-induced myocardial injury due to inflammatory cell infiltration absence and apoptosis. Graphical Abstract
The transcriptional regulatory network of hormones and genes under salt stress in tomato plants (Solanum lycopersicum L.)

Salt stress has become one of the main limiting factors affecting the normal growth and development of tomatoes as well as fruit quality and yields. To further reveal the regulatory relationships between tomato hormones under salt stress, the interaction between hormones and TF and the genome-wide gene interaction network were analyzed and constructed. After salt treatment, the levels of ABA, SA, and JA were significantly increased, the levels of GA were decreased, and IAA and tZ showed a trend of first increasing and then decreasing. The expression patterns of hormone biosynthesis and signal transduction related genes were analyzed based on RNA-seq analysis, the co-expression network of hormones and genome-wide co-expression networks were constructed using weighted gene co-expression network analysis (WGCNA). The expression patterns of specific transcription factors under salt stress were also systematically analyzed and identified 20 hormone-related candidate genes associated with salt stress. In conclusion, we first revealed the relationship between hormones and genes in tomatoes under salt stress based on hormone and transcriptome expression profiles and constructed a gene regulatory network. A transcriptional regulation model of tomato consisted of six types of hormones was also proposed. Our study provided valuable insights into the molecular mechanisms regulating salt tolerance in tomatoes.
In vitro responses of human dermal fibroblasts to mechanical strain: A systematic review and meta-analysis

In vitro research in the field of mechanotransducive regulation of dermal fibroblasts is characterized by highly variable methodology and contradictory results. The primary objective of this systematic review was to establish how in vitro mechanical stretch affects human dermal fibroblast function, by means of a quantitative synthesis of all available evidence. The secondary objectives were to examine the effects of covariates related to donor age, fibroblast origin, experimental treatments, and mechanical stimulation parameters on dermal fibroblast responsiveness to mechanical strain. Summary outcomes for fibroblast proliferation and collagen production were combined using a fixed-effects meta-analytical model. Subgroup analysis and meta-regression were used to investigate the effects of different conditions on the summary outcomes. Mechanical strain was found to not affect fibroblast proliferation in neonatal fibroblasts, while adult fibroblasts proliferation was significantly increased. Collagen production was significantly increased in response to mechanical stimulation, with Vitamin C stimulation as the most important covariate. Stretching frequency emerged as positively associated with fibroblast proliferation and negatively associated with collagen production. We conclude from this study that distinct differences exist in the effects of mechanical stretching between dermal fibroblasts from neonatal and adult donors, which will help to further elucidate the pathophysiological mechanism behind tension-induced scarring.
Transcription factor-based biosensors for screening and dynamic regulation

Advances in synthetic biology and genetic engineering are bringing into the spotlight a wide range of bio-based applications that demand better sensing and control of biological behaviours. Transcription factor (TF)-based biosensors are promising tools that can be used to detect several types of chemical compounds and elicit a response according to the desired application. However, the wider use of this type of device is still hindered by several challenges, which can be addressed by increasing the current metabolite-activated transcription factor knowledge base, developing better methods to identify new transcription factors, and improving the overall workflow for the design of novel biosensor circuits. These improvements are particularly important in the bioproduction field, where researchers need better biosensor-based approaches for screening production-strains and precise dynamic regulation strategies. In this work, we summarize what is currently known about transcription factor-based biosensors, discuss recent experimental and computational approaches targeted at their modification and improvement, and suggest possible future research directions based on two applications: bioproduction screening and dynamic regulation of genetic circuits.
Cerebrovascular reactivity measurements using 3T BOLD MRI and a fixed inhaled CO2 gas challenge: Repeatability and impact of processing strategy

Introduction: Cerebrovascular reactivity (CVR) measurements using blood oxygen level dependent (BOLD) magnetic resonance imaging (MRI) are commonly used to assess the health of cerebral blood vessels, including in patients with cerebrovascular diseases; however, evidence and consensus regarding reliability and optimal processing are lacking. We aimed to assess the repeatability, accuracy and precision of voxel- and region-based CVR measurements at 3 T using a fixed inhaled (FI) CO2 stimulus in a healthy cohort. Methods: We simulated the effect of noise, delay constraints and voxel- versus region-based analysis on CVR parameters. Results were verified in 15 healthy volunteers (28.1±5.5 years, female: 53%) with a test-retest MRI experiment consisting of two CVR scans. CVR magnitude and delay in grey matter (GM) and white matter were computed for both analyses assuming a linear relationship between the BOLD signal and time-shifted end-tidal CO2 (EtCO2) profile. Results: Test-retest repeatability was high [mean (95% CI) inter-scan difference: −0.01 (−0.03, −0.00) %/mmHg for GM CVR magnitude; −0.3 (−1.2,0.6) s for GM CVR delay], but we detected a small systematic reduction in CVR magnitude at scan 2 versus scan 1, accompanied by a greater EtCO2 change [±1.0 (0.4,1.5) mmHg] and lower heart rate [−5.5 (−8.6,−2.4] bpm]. CVR magnitude estimates were higher for voxel- versus region-based analysis [difference in GM: ±0.02 (0.01,0.03) %/mmHg]. Findings were supported by simulation results, predicting a positive bias for voxel-based CVR estimates dependent on temporal contrast-to-noise ratio and delay fitting constraints and an underestimation for region-based CVR estimates. Discussion: BOLD CVR measurements using FI stimulus have good within-day repeatability in healthy volunteers. However, measurements may be influenced by physiological effects and the analysis protocol. Voxel-based analyses should be undertaken with care due to potential for systematic bias; region-based analyses are more reliable in such cases.
Learning from humans to build social cognition among robots

Self-organized groups of robots have generally coordinated their behaviors using quite simple social interactions. Although simple interactions are sufficient for some group behaviors, future research needs to investigate more elaborate forms of coordination, such as social cognition, to progress towards real deployments. In this perspective, we define social cognition among robots as the combination of social inference, social learning, social influence, and knowledge transfer, and propose that these abilities can be established in robots by building underlying mechanisms based on behaviors observed in humans. We review key social processes observed in humans that could inspire valuable capabilities in robots and propose that relevant insights from human social cognition can be obtained by studying human-controlled avatars in virtual environments that have the correct balance of embodiment and constraints. Such environments need to allow participants to engage in embodied social behaviors, for instance through situatedness and bodily involvement, but, at the same time, need to artificially constrain humans to the operational conditions of robots, for instance in terms of perception and communication. We illustrate our proposed experimental method with example setups in a multi-user virtual environment.