Miracle-dz/UniFAR-FTUs huggingface dataset:
Biocultural, Productive, and Ecocentric Restoration in La Mintzita Spring-fed Wetland, Michoacán, México

ABSTRACT The increasing loss of wetlands at the global scale demands immediate response by improving management practices and ecological restoration. When people degrade wetlands, environmental restoration must overcome biotic and economic barriers that can be considerable. We assessed the floristic composition of a wetland subjected to anthropic disturbances and expansion of invasive species, then compared our results with historical data from 2005 to 2015. The result revealed that changes in floristic composition and dominant native and invasive dominant species occurred during this 16-year period. In the dry season, we found significant differences in species richness between the years 2005 and 2021, with a significant reduction in species richness in the latter year. This loss of species richness represents an unfavorable change in the floristic composition trajectory, which we explain as an effect of sustained anthropic disturbance. Floristic data from the rainy season was not conclusive. Typha domingensis, and the invasives Phragmites australis and Festuca arundinacea have been favored by disturbances and increased their cover at the expense of other wetland species, reducing the wetland’s floristic diversity. Our objective was to redirect the floristic composition trajectory in the La Mintzita wetland by proposing management strategies for controlling the above-mentioned species based on three ecological restoration strategies: biocultural (targeting simultaneously the loss of biodiversity and of traditional use of Typha), productive (to control expansion of P. australis which has no traditional use in the region, we propose a new use), and ecocentric (to control F. arundinacea and recover native species cover).
The Perfect Schoolyard for Future Children: Primary School Children's Participation in Envisioning Workshops

Abstract:This Swedish study investigates how primary school children's perspectives on a "good schoolyard" can be illuminated through envisioning workshops using model-making. In addition to advocating for the qualities and affordances of the standard schoolyard equipment, children also suggested and constructed new features affording playing with domestic animals, being in peace and quiet in tree houses, picking fruit, and using digital playgrounds. For the children to go beyond reproducing the features, environmental qualities, and affordances of their current schoolyards, they needed plenty of time for communication and hands-on activities, opportunities to relax, imagine, and receive input and inspiration from others' experiences.
Smartphone Addiction and Phubbing in International Students in Turkey: The Moderating Role of Mindfulness

Abstract:With the advent of smartphone technologies, connections to other people, information, and services have transcended everyday norms. However, together with the evolving technologies, unprecedented changes in the behaviors of individuals are emerging. Among these changes is phubbing, the practice of ignoring those in the immediate surroundings during real conversations in favor of smartphones. In light of this, the aim of the present study was to determine if there is a relationship between smartphone addiction and phubbing in international students and if mindfulness is a moderator of this relationship. A cross-sectional survey with snowball sampling was adopted, and a total of 294 international students volunteered to complete self-report measures. In this study, while there was a significant positive relationship between smartphone addiction and phubbing, no such significant association was determined for mindfulness in its relationship with smartphone addiction and phubbing. The moderation analysis revealed that mindfulness significantly moderated the relationship between smartphone addiction and phubbing; however, high mindfulness did not serve as a protective factor against the effects of smartphone addiction on phubbing.
Co-Generating Urban Knowledge with Children in Istanbul: Children as Urban Investigators and Problem Solvers

Abstract:Children's participation has been recognized as essential in participatory urban planning towards creating child-focused urban environments. However, it remains a challenge for researchers to address children's role in urban planning, particularly in contexts where a culture of participation is missing from everyday practice. The COVID-19 pandemic posed additional challenges in executing participatory research. In this article, we applied a methodology of online artwork elicitations with ten children from Istanbul. From our co-generated research findings, we argue that children are valuable social agents not only in urban planning but also in the fight against urgent and dramatic challenges facing our planet. Children's participation better informs solutions when children guide knowledge generation.
Seasonal Shifts in Diversity and Composition of a Tallgrass Prairie Restoration Have Implications for Sampling Time

ABSTRACT Restorations change across the growing season. Because of this, the point in the season that a restoration is sampled may affect the conclusions reached based on the sample. In this study, we explore seasonal changes in a prairie restoration experiment in eastern Kansas and investigate how these changes affect observed composition, biodiversity, and the effects of seeding density treatment on the plant community based on when, and how completely, vegetation is sampled. Free State Prairie was established in 2014 to test the effects of forb seeding density on forb establishment, diversity, and restoration success. We compared absolute cover data collected in early June and early September 2019 to each other and to combined data. We found changes in both composition and biodiversity from early-to-late in the season. Sown forbs decreased in cover and richness, while sown grasses increased in cover and richness. Nonsown species did not change in cover but decreased in richness. Neither individual sample fully represented the overall composition or biodiversity of the community. We detected a significant negative effect of forb seeding density on diversity in June, and with combined data, but not in September. As sampling time can affect both broad patterns of composition and diversity and observed results of establishment and management techniques, sampling multiple times in a year will provide the fullest and most accurate picture of the community. When multiple samples are impractical, sampling time should be selected carefully based on the phenology of the restoration and the variables of interest.
scMinerva: an Unsupervised Graph Learning Framework with Label-efficient Fine-tuning for Single-cell Multi-omics Integrated Analysis

Single-cell multi-omics is a rapidly growing field in biomedicine, where multiple biological contents, such as the epigenome, genome, and transcriptome, can be measured simultaneously. Despite its potential, the integrated analysis and prediction of cellular states based on this complex multi-omics data pose significant challenges due to data sparsity, high noise, and computational overhead. To address these challenges, we developed scMinerva, an unsupervised framework for single-cell multi-omics integrated analysis. The learned embeddings from the multi-omics data enable accurate integrated classification of cell types and stages. Specifically, we construct a heterogeneous graph from multiple omics and propose a novel biased random walk algorithm omics2vec, which can learn the heterogeneous biological graph in a way that balances both local and global network structures. scMinerva successfully outperforms existing unsupervised methods on various simulated and real-world datasets when fine-tuned by very few labels. Additionally, scMinerva demonstrates strong label efficiency, is robust to fluctuation in data quality, allows one omics to compensate for weakness in others and could effectively classify cells with different annotation granularities. Furthermore, we showcase scMinerva’s ability to accurately provide prospective biomarkers and predict cell differentiation trends for COVID-19-infected cells, through the joint analysis of multi-omics data.
Running modulates primate and rodent visual cortex differently

When mice run, activity in their primary visual cortex (V1) is strongly modulated. This observation has altered conception of a brain region assumed to be a passive image processor. Extensive work has followed to dissect the circuits and functions of running-correlated modulation. However, it remains unclear whether visual processing in primates might similarly change during locomotion. We measured V1 activity in marmosets while they viewed stimuli on a treadmill. In contrast to mouse V1, marmoset V1 was slightly but reliably suppressed during running. Population-level analyses revealed trial-to-trial fluctuations of shared gain across V1 in both species, but these gain modulations were smaller and more often negatively correlated with running in marmosets. Thus, population-scale gain fluctuations of V1 reflect a common feature of mammalian visual cortical function, but important quantitative differences yield distinct consequences for the relation between vision and action in primates versus rodents.
Elastin-like polypeptide delivery of anti-inflammatory peptides to the brain following ischemic stroke

Inflammatory processes are activated following ischemic strokes and lead to increased tissue damage for weeks following the ischemic insult, but there are no approved therapies that target this inflammation-induced secondary injury. Here, we report that SynB1-ELP-p50i, a novel protein inhibitor of the nuclear factor kappa B (NF-κB) inflammatory cascade bound to drug carrier elastin-like polypeptide (ELP), is able to enter both neurons and microglia, cross the blood-brain barrier, localize exclusively in the ischemic core and penumbra in Wistar-Kyoto and spontaneously hypertensive rats (SHRs), and reduce infarct volume in male SHRs. Additionally, in male SHRs, SynB1-ELP-p50i treatment improves survival for 14 days following stroke with no effects of toxicity or peripheral organ dysfunction. These results show high potential for ELP-delivered biologics for therapy of ischemic stroke and other central nervous system disorders and further support targeting inflammation in ischemic stroke.
Growth-dependent Gene Expression Variation Influences the Strength of Codon Usage Biases

The most highly expressed genes in microbial genomes tend to use a limited set of synonymous codons, often referred to as “preferred codons. ” The existence of preferred codons is commonly attributed to selection pressures on various aspects of protein translation including accuracy and/or speed. However, gene expression is condition-dependent and even within single-celled organisms transcript and protein abundances can vary depending on a variety of environmental and other factors. Here, we show that growth rate-dependent expression variation is an important constraint that significantly influences the evolution of gene sequences. Using large-scale transcriptomic and proteomic data sets in Escherichia coli and Saccharomyces cerevisiae, we confirm that codon usage biases are strongly associated with gene expression but highlight that this relationship is most pronounced when gene expression measurements are taken during rapid growth conditions. Specifically, genes whose relative expression increases during periods of rapid growth have stronger codon usage biases than comparably expressed genes whose expression decreases during rapid growth conditions. These findings highlight that gene expression measured in any particular condition tells only part of the story regarding the forces shaping the evolution of microbial gene sequences. More generally, our results imply that microbial physiology during rapid growth is critical for explaining long-term translational constraints.
Leveraging gene correlations in single cell transcriptomic data

BACKGROUND Many approaches have been developed to overcome technical noise in single cell RNA-sequencing (scRNAseq). As researchers dig deeper into data—looking for rare cell types, subtleties of cell states, and details of gene regulatory networks—there is a growing need for algorithms with controllable accuracy and fewer ad hoc parameters and thresholds. Impeding this goal is the fact that an appropriate null distribution for scRNAseq cannot simply be extracted from data when ground truth about biological variation is unknown (i.e., usually). RESULTS We approach this problem analytically, assuming that scRNAseq data reflect only cell heterogeneity (what we seek to characterize), transcriptional noise (temporal fluctuations randomly distributed across cells), and sampling error (i.e., Poisson noise). We analyze scRNAseq data without normalization—a step that skews distributions, particularly for sparse data—and calculate p-values associated with key statistics. We develop an improved method for selecting features for cell clustering and identifying gene-gene correlations, both positive and negative. Using simulated data, we show that this method, which we call BigSur (Basic Informatics and Gene Statistics from Unnormalized Reads), captures even weak yet significant correlation structures in scRNAseq data. Applying BigSur to data from a clonal human melanoma cell line, we identify thousands of correlations that, when clustered without supervision into gene communities, align with known cellular components and biological processes, and highlight potentially novel cell biological relationships. CONCLUSIONS New insights into functionally relevant gene regulatory networks can be obtained using a statistically grounded approach to the identification of gene-gene correlations.
Loss Of function of Male-Specific Lethal 3 (Msl3) Does Not Affect Spermatogenesis in Rodents

Msl3 is a member of the chromatin-associated male-specific lethal MSL complex which is responsible for the transcriptional upregulation of genes on the X chromosome in males Drosophila. Although the dosage complex operates differently in mammals, the Msl3 gene is conserved from flies to humans. Msl3 is required for meiotic entry during Drosophila oogenesis. Recent reports indicate that also in primates, Msl3 is expressed in undifferentiated germline cells before meiotic entry. However, if Msl3 plays a role in the meiotic entry of mammals has yet to be explored. To study this, we used mouse spermatogenesis as a study model. Analyses of single cells RNA-seq data revealed that, in mice, Msl3 is mostly expressed in meiotic cells. To test the role of Msl3 in meiosis, we used a male germline-specific Stra8-iCre driver and a newly generated Msl3flox conditional knock-out mouse line. Msl3 conditional loss-of-function in spermatogonia did not cause spermatogenesis defects or changes in the expression of genes related to meiosis. Our data suggest that, in mice, Msl3 exhibits delayed expression compared to Drosophila and primates, and loss-of-function mutations disrupting the chromodomain of Msl3 alone do not impede meiotic entry in rodents.
Topography of inputs into the hippocampal formation of a food-caching bird

The mammalian hippocampal formation (HF) is organized into domains associated with different functions. These differences are driven in part by the pattern of input along the hippocampal long axis, such as visual input to the septal hippocampus and amygdalar input to temporal hippocampus. HF is also organized along the transverse axis, with different patterns of neural activity in the hippocampus and the entorhinal cortex. In some birds, a similar organization has been observed along both of these axes. However, it is not known what role inputs play in this organization. We used retrograde tracing to map inputs into HF of a food-caching bird, the black-capped chickadee. We first compared two locations along the transverse axis: the hippocampus and the dorsolateral hippocampal area (DL), which is analogous to the entorhinal cortex. We found that pallial regions predominantly targeted DL, while some subcortical regions like the lateral hypothalamus (LHy) preferentially targeted the hippocampus. We then examined the hippocampal long axis and found that almost all inputs were topographic along this direction. For example, the anterior hippocampus was preferentially innervated by thalamic regions, while posterior hippocampus received more amygdalar input. Some of the topographies we found bear resemblance to those described in the mammalian brain, revealing a remarkable anatomical similarity of phylogenetically distant animals. More generally, our work establishes the pattern of inputs to HF in chickadees. Some of these patterns may be unique to chickadees, laying the groundwork for studying the anatomical basis of these birds’ exceptional hippocampal memory.
Identifying drug effects in a cardiac model of electrophysiology using kernel-based parameter estimation methods

Computational models of cardiac electrophysiology hold great potential in the drug discovery process to bridge the gap between in vitro and in vivo preclinical trials. Current methods for solving inverse problems in cardiac electrophysiology are limited by their accuracy, scalability, practicality, or a combination of these. We investigate the feasibility of using kernel methods to solve the inverse problem of estimating the parameters of ionic membrane currents from observations of corresponding action potential (AP) traces. In particular, we consider AP traces generated by a cardiac cell action potential model, which mimics those obtained experimentally in measurable in vitro cardiac systems. This proof-of-concept study aims to improve existing pipelines for identifying drug effects in ”heart-on-a-chip” systems by introducing a new approach to solving the inverse problem. Using synthetic training data from the 1977 Beeler-Reuter AP model of mammalian ventricular cardiomyocytes, we demonstrate our recently proposed boosted KRR solver ( StreaMRAK ), which is particularly robust and well-adapted for high-complexity functions. We show that this method is less memory demanding, estimates the model parameters with higher accuracy, and is less sensitive to parameter identifiability problems than existing methods, such as standard KRR solvers and loss-minimization schemes based on nearest neighbor heuristics.
Method of rough set and AHP theory in IT project risk group decision making

Aiming at the imprecision and uncertainty of risk factors,this paper analyzes the basic characters of IT project,and points out the problems existing in the group decision making.Meanwhile,the basic steps of RSGDS is put forward.With the rough set theory,the main processes of knowledge reasoning such as attributes reduction and rules mining are discussed,especially introducing the concept of dynamic weight,then the algorithm of rules reduction and mining is optimized and ameliorated.
QSAR Investigation on Quinolizidinyl Derivatives in Alzheimer’s Disease

Sets of quinolizidinyl derivatives of bi- and tri-cyclic (hetero) aromatic systems were studied as selective inhibitors. On the pattern, quantitative structure-activity relationship (QSAR) study has been done on quinolizidinyl derivatives as potent inhibitors of acetylcholinesterase in alzheimer’s disease (AD). Multiple linear regression (MLR), partial least squares (PLSs), principal component regression (PCR), and least absolute shrinkage and selection operator (LASSO) were used to create QSAR models. Geometry optimization of compounds was carried out by B3LYP method employing 6–31 G basis set. HyperChem, Gaussian 98 W, and Dragon software programs were used for geometry optimization of the molecules and calculation of the quantum chemical descriptors. Finally, Unscrambler program was used for the analysis of data. In the present study, the root mean square error of the calibration and R2 using MLR method were obtained as 0.1434 and 0.95, respectively. Also, the R and R2 values were obtained as 0.79, 0.62 from stepwise MLR model. The R2 and mean square values using LASSO method were obtained as 0.766 and 3.226, respectively. The root mean square error of the calibration and R2 using PLS method were obtained as 0.3726 and 0.62, respectively. According to the obtained results, it was found that MLR model is the most favorable method in comparison with other statistical methods and is suitable for use in QSAR models.
Approximate truth of perfectness: An experimental test

Approximate truth refers to the principle that border cases should be analyzed by solving generic cases and solving border cases as limits of generic ones (Brennan et al., 2008). Our study experimentally explores whether this conceptual principle is also behaviorally appealing. To do so, we focus on perfectness (Selten, 1975) and use his example game with (no) multiplicity of (perfect) equilibria. Distinguishing three uniform perturbation levels, we check for monotonicity (all players react monotonically to the perturbation level) and then explore the behavioral relevance of approximate truth.
Evaluation of a dual PEM Stokes polarimeter using different signal processing methods

In our laboratory we built a Stokes polarimeter using two photoelastic modulators (PEMs). We applied two different signal processing methods to this dual PEM Stokes polarimeter. In one method, we used lock-in amplifiers to measure the PEM modulated signals. In the other method, we used Fourier analysis of a digitized waveform that contains the modulated signals. The dual PEM Stokes polarimeter can measure all normalized Stokes parameters. In this paper we present and compare results obtained using both signal processing methods. We discuss how each method benefits selected applications of the dual PEM Stokes polarimeter.
Blindness removal in arrays of rectangular waveguides using dielectrically loaded hard walls

We analyze an infinite planar array of open-ended rectangular waveguides in which the E-plane walls are loaded with dielectric slabs in order to create a hard boundary condition. The analysis is done by using the mode-matching method with Floquet modes in the exterior region. The results show that the hard walls remove the blind spots otherwise present in the element patterns of wide-angle scanning arrays. This occurs both for rectangular and for triangular lattices. In addition, the array becomes better matched to free-space in a rectangular lattice. In limited-scan arrays of large square waveguides, the use of the hard walls increases the array gain by 0.9 dB, it reduces the grating lobe level in the H plane by 11 dB and considerably decreases the difference between the array characteristics in the E and H planes.
Simulation of Rotational Vibration of Spur Gears

This paper introduces a developed simulator on a rotational vibration and a strain at a root of a tooth, on a power transmission spur gear. The simulator solves a differential equation with one degree of freedom in consideration of the behaviour of the stiffness around tooth tip meshing. The stiffness function is discussed and determined with static and dynamic meshing tests under load. The developed simulator has one more distinctive feature that the errors of the gears are put into the simulator with a newly developed automatic gear accuracy measuring instrument. The simulated outputs depict precisely the experimental behaviours. Through the development of this simulator, the the discussion becomes easier on the effectiveness of a spur gear for the decrease of vibration.