Miracle-dz/UniFAR-FTUs huggingface dataset:
Area-preserving curve-shortening flows: from phase separation to image processing

Some known models in phase separation theory (Hele–Shaw, nonlocal mean curvature motion) and their approximations by means of Cahn–Hilliard and nonlocal Allen–Cahn equations are proposed as a tool to generate planar curve-shortening flows without shrinking. This procedure can be seen as a level set approach to area-preserving geometric flows in the spirit of Sapiro and Tannenbaum [38], with application to shape recovery. We discuss the theoretical validation of this method and its implementation to problems of shape recovery in Computer Vision. The results of some numerical experiments on image processing are presented.
Decoupling of sexual signals and their underlying morphology facilitates rapid phenotypic diversification

How novel phenotypes evolve is challenging to imagine because traits are often underlain by numerous integrated phenotypic components, and changes to any one form can disrupt the function of the entire module. Yet novel phenotypes do emerge, and research on adaptive phenotypic evolution suggests that complex traits can diverge while either maintaining existing form–function relationships or through innovations that alter form–function relationships. How these alternate routes contribute to sexual signal evolution is poorly understood, despite the role of sexual signals in generating biodiversity. In Hawaiian populations of the Pacific field cricket, male song attracts both female crickets and a deadly acoustically orienting parasitoid fly. In response to this conflict between natural and sexual selection, male crickets have evolved altered wing morphologies multiple times, resulting in loss and dramatic alteration of sexual signals. More recently, we and others have observed a radical increase in sexual signal variation and the underlying morphological structures that produce song. We conducted the first combined analysis of form (wing morphology), function (emergent signal), and receiver responses to characterize novel variation, test alternative hypotheses about form–function relationships (Form–Function Continuity vs. Form–Function Decoupling), and investigate underlying mechanistic changes and fitness consequences of novel signals. We identified three sound‐producing male morphs (one previously undescribed, named “rattling”) and found that relationships between morphology and signals have been rewired (Form–Function Decoupling), rapidly and repeatedly, through the gain, loss, and alteration of morphological structures, facilitating the production of signals that exist in novel phenotypic space. By integrating across a hierarchy of phenotypes, we uncovered divergent morphs with unique solutions to the challenge of attracting mates while evading fatal parasitism.
T‐cell immunoglobulin‐ and mucin‐domain‐containing molecule‐4 maintains adipose tissue homeostasis by orchestrating M2 macrophage polarization via nuclear factor kappa B pathway

Obesity is generally associated with low‐grade inflammation. Adipose tissue macrophages (ATMs) orchestrate metabolic inflammation. The classical (M1‐like) or alternative (M2‐like) activation of ATMs is functionally coupled with the metabolic status of fat tissues. It has been found that T‐cell immunoglobulin‐ and mucin‐domain‐containing molecule‐4 (Tim‐4) inhibits inflammation by regulating macrophages. However, the exact role of Tim‐4 in macrophage polarization and obesity remains unknown. Here, we identified Tim‐4 as a critical switch governing macrophage M1/M2 polarization and energy homeostasis. Tim‐4 deletion led to spontaneous obesity in elder mice and promoted obesity severity of db/db mice. Obesity microenvironment enhanced the expression of Tim‐4 in white adipose tissue and ATMs. In vitro, we detected an increase in M1‐like cells and decrease in M2‐like cells in both peritoneal macrophages and bone marrow‐derived macrophages from Tim‐4 knockout mice. Mechanistically, we demonstrated that Tim‐4 promoted M2‐like macrophages polarization via suppressing nuclear factor kappa B (NF‐κB) signaling pathway. In addition, we found that Tim‐4 promoted TLR4 internalization, which might contribute to regulation of NF‐κB signaling. Collectively, these results indicated that Tim‐4 maintained adipose tissue homeostasis by regulating macrophage polarization via NF‐κB pathway, which would provide a new target for obesity intervention.
Exponential stabilisation of delayed Lur'e systems with multi-rate sampled-data control

In this paper, we focus on the multi-rate sampled-data based exponential stabilisation problem of delayed Lur'e systems. First, a merging time sequence is constructed from the sampling instants of multiple sensors to form the so-called analysis interval and the closed-loop system is represented by a system with multiple time-varying delays over the constructed analysis interval. Then, a useful estimation about the norm of the system state is established. On this basis, a stabilisation criterion is proposed by constructing a two-sided looped-functional. The proposed functional drops positive definite restrictions over the whole analysis interval . Therefore, it can reduce the conservatism of the derived criterion. And, the feasible solution of the multi-rate sampled-data controller gain can be provided by solving a set of LMIs. Finally, the given example shows the advantage of the main results.
Analysis of structural network topology alterations in autism and its relationship with autism severity

Autism Spectrum Disorder (ASD) is a public health concern ranging along a continuum of severity. The neurobiological motives behind ASD have been widely explored with reports about aberrant brain anatomy and functional connectivity. However, research on the underlying structural connectivity alterations is limited. We propose the application of a novel connectomic measure called Network Normality Score (NNS) to identify brain abnormalities and quantity topological dissimilarities in individuals with ASD. We show that the network topology of structural connectivity is altered in ASD brains relative to healthy controls at the global and system levels. We demonstrate that structural connectivity differences are more pronounced in certain subnetworks. Finally, we quantify the association between network similarity and behavioral autism severity to show the efficacy of NNS as a neuroimaging measure.
Network-Guided Sparse Subspace Clustering on Single-Cell Data

With the rapid development of single-cell RNA sequencing (scRNA-seq) technology, people are able to investigate gene expression at the individual cell level. Identification of cell types via unsupervised clustering is one of the fundamental issues in analyzing single-cell data. However, due to the high dimensionality of expression profiles, traditional clustering methods are difficult to generate satisfactory results. To address this problem, we designed NetworkSSC, a network-guided sparse subspace clustering (SSC) approach. NetworkSSC is based on a similar assumption in SSC that the expression of cells within the same type lies in the same subspace. Moreover, it integrates an additional regularization term to include the gene network’s Laplacian matrix, so as to utilize the network information. The comparison results of 5 scRNA-seq data sets show that NetworkSSC outperforms ordinary SSC and other clustering methods in most cases.
motifNet: A Neural Network Approach for Learning Functional Sequence Patterns in mRNA

We present a new approach for predicting functional sequence patterns in mRNA, known as motifs. These motifs play an important role in understanding the mechanisms of the cell life cycle in clinical research and drug discovery. However, many existing neural network models for mRNA event prediction only take the sequence as input, and do not consider the positional information of the sequence. In contrast, motifNet is a lightweight neural network that uses both the sequence and its positional information as input. This allows for the implicit neural representation of the various motif interaction patterns in human mRNA sequences. The model can then be used to interactively generate motif patterns and the positional effect score in mRNA activities. Additionally, motifNet can identify violations of motif patterns in real human mRNA variants that are associated with disease-related cell dysfunction.
How Often Likelihood Ratios are Misleading in Sequential Trials

How often would investigators be misled if they took advantage of the likelihood principle and used likelihood ratios—which need not be adjusted for multiple looks at the data—to frequently examine accumulating data? The answer, perhaps surprisingly, is not often. As expected, the probability of observing misleading evidence does increase with each additional examination. However, the amount by which this probability increases converges to zero as the sample size grows. As a result, the probability of observing misleading evidence remains bounded—and therefore controllable—even with an infinite number of looks at the data. Here we use boundary crossing results to detail how often misleading likelihood ratios arise in sequential designs. We find that the probability of observing a misleading likelihood ratio is often much less than its universal bound. Additionally, we find that in the presence of fixed-dimensional nuisance parameters, profile likelihoods are to be preferred over estimated likelihoods which result from replacing the nuisance parameters by their global maximum likelihood estimates.
Spatiotemporal variation in the competitive environment, with implications for how climate change may affect a species with parental care

Burying beetles of the genus Nicrophorus have become a model for studying the evolution of complex parental care in a laboratory. Nicrophorus species depend on small vertebrate carcasses to breed, which they process and provision to their begging offspring. However, vertebrate carcasses are highly sought after by a wide variety of species and so competition is expected to be critical to the evolution of parental care. Despite this, the competitive environment for Nicrophorus is rarely characterized in the wild and remains a missing factor in laboratory studies. Here, we performed a systematic sampling of Nicrophorus orbicollis living near the southern extent of their range at Whitehall Forest in Clarke County, Georgia, USA. We determined the density of N. orbicollis and other necrophilous species that may affect the availability of this breeding resource through interference or exploitation competition. In addition, we characterize body size, a key trait involved in competitive ability, for all Nicrophorus species at Whitehall Forest throughout the season. Finally, we compare our findings to other published natural history data for Nicrophorines. We document a significantly longer active season than was observed twenty years previously at Whitehall Forest for both N. orbicollis and Nicrophorus tomentosus, potentially due to climate change. As expected, the adult body size of N. orbicollis was larger than N. tomentosus, the only other Nicrophorus species that was captured in 2022 at Whitehall Forest. The other most prevalent interspecific insects captured included species in the families Staphylinidae, Histeridae, Scarabaeidae, and Elateridae, which may act as competitors or predators of Nicrophorus eggs and larvae. Together, our results indicate significant variation in intra- and interspecific competition relative to populations within the N. orbicollis range. These findings suggest that the competitive environment varies extensively over space and time, which help to inform the role of ecology in the evolution of parental care in this species.
The response of a turbulent boundary layer to a short length of surface roughness

Extensive measurements were made of the response of a high-Reynolds-number turbulent boundary layer to a short length (about three boundary-layer thicknesses) of surface roughness. The measurements include the mean velocity, all the Reynolds streses as well as all the triple products occurring in the Reynolds-stress transport equations. At the last measurement station, 55 boundary-layer thicknesses from the roughness, the boundary layer still had not relaxed to the universal smooth-wall structure. Comparison of the measurements with a calculation of the flow suggests the major requirement for improving the agreement is a more sophisticated treatment of the turbulent-diffusion process.
Turbulent Couette flow between concentric cylinders at large Taylor numbers

Measurements have been made of the Couette flow in the annular space between concentric cylinders with a radius ratio of 1.5, the outer cylinder being held stationary and the inner one rotated at speeds to give Taylor numbers in the range 1.0 × 104−2.3 × l06 times the critical value for first instability of the steady viscous flow. Mean velocities have been measured both with Pitot tubes and with linearized hot-wire anemometers, and turbulent intensities and stresses, frequency spectra and space-time correlations have been obtained using single hot-wire anemometers of X-form and linear arrays of eight single-wire anemometers. For Taylor-number ratios to the critical number less than 3 × l05, the most prominent feature of the flow is a system of toroidal eddies, encircling the inner cylinder and uniformly spaced in the axial direction with nearly the separation of the Taylor vortices of the viscous instability. They are superimposed on a background of irregular motion and, except within the thin wall layers, the toroidal eddies contribute more to the total intensity. With increase of rotation speed, the toroidal eddies lose their regularity, and they cannot be clearly distinguished at Taylor-number ratios beyond 5 × l05. The change of flow type from quasi-regular toroidal to fully irregular turbulent takes place over an extensive range of Taylor-number ratio centred near 3 × l05, and it may be linked with changes in the thin wall layers that separate the flow boundaries from the central region of nearly constant circulation. For ratios over 5 × l05, an appreciable part of the wall layers is comparatively unaffected by flow curvature and has a logarithmic distribution of mean velocity similar to that found in channel flows. It is suggested that the motion in the wall layers changes from a set of Gortler vortices characteristic of curved-wall flow to the more irregular motion found on plane walls, causing the toroidal eddies to break into sections of length ranging from a considerable fraction of the flow perimeter to nearly the separation of the cylinders. Changes in the frequency spectra of the radial and azimuthal velocit'y fluctuations are consistent with such a change.
Comparing the speed of action initiation and action inhibition

Much work has examined the process of canceling or inhibiting an impending action. However, the converse process of initiating a movement has, comparatively, been much less studied. Action initiation and action inhibition are generally considered to be independent and qualitatively distinct processes, while the exact relationship between these processes remains unclear. One respect in which action initiation and action inhibition are often thought to differ is in their speed; action inhibition is typically considered to be faster than action initiation, which allows for impending actions to be inhibited before they are initiated. This apparent contrast is, however, largely observed in tasks in which there is much greater urgency to inhibit an action that there is to initiate an action. This asymmetry in the urgency between action initiation and action inhibition, as well as other asymmetries in how action initiation and inhibition are cued, make it impossible to compare their relative time courses. Here, we demonstrate that, when action initiation and action inhibition are measured under conditions that are matched as closely as possible, their speed is the same. In light of this, we suggest that action initiation and action inhibition may not necessarily be qualitatively distinct processes, but may instead reflect two opposing states of a single process supporting a decision about whether to act or not. This perspective carries significant implications for computational models and presumed neural mechanisms of action control.
Totally laparoscopic total gastrectomy with Uncut Roux-en-Y for gastric cancer may improve prognosis: A propensity score matching comparative study

Background Laparoscopic total gastrectomy (LTG) with Roux-en-Y (RY) is often accompanied by a series of complications. Uncut RY (URY) can effectively reduce Roux stasis syndrome (RSS) in laparoscopic distal gastrectomy. To determine whether totally LTG (TLTG) with URY for gastric cancer (GC) can replace RY in short-term and long-term prognosis. Methods This comparative retrospective study selected GC patients from 2016 to 2022. The patients were divided into URY group and RY group. Cox multivariate proportional hazard regression analysis was used to explore the independent prognostic factors. Propensity score matching (PSM) was used to reduce bias. Results A total of 100 GC patients met the inclusion criteria. Compared to RY group, URY group showed significant advantages in operation time and length of hospital stay. In addition, URY group can significantly reduce short-term and long-term complications, especially RSS. The 1-, 3- and 5-year progression free survival (PFS) of URY group and RY group were 90.4% vs. 67.8% (P=0.005), 76.6% vs. 52.6% (P=0.009) and 76.6% vs. 32.8% (P<0.001), respectively. After PSM, the advantage of URY in PFS was verified again, while there was no significant difference in overall survival (OS) between the two groups. Cox multivariate analysis suggested that lower RSS was associated with better PFS. Conclusions TLTG with URY for GC helps control disease progression, speed up recovery and reduce short and long-term complications, especially RSS.
On the joint use of scattering and damping models to predict X-band co-polarized backscattering from a slick-covered sea surface

In this study, sea surface scattering with and without surfactants is predicted using the two-scale boundary perturbation model (BPM) and the advanced integral equation model (AIEM) augmented with two different damping models, i.e., the Marangoni one and the model of local balance (MLB). Numerical predictions are showcased for both mineral oil and biogenic slicks. They are contrasted with actual satellite Synthetic Aperture Radar (SAR) measurements collected at X-band by the German TerraSAR-X sensor over mineral oil and plant oil slicks of known origin. Experimental results show that the two-scale BPM augmented with the Marangoni damping model is more suitable for predicting the normalized radar cross section and the damping ratio of plant oil (biogenic) slicks. In contrast, the AIEM combined with the damping MLB results in a better agreement with SAR measurements collected over mineral oil slicks.
Learners’ satisfaction of courses on Coursera as a massive open online course platform: A case study

Online education has become more prevalent in the 21st century, especially after the COVID-19 pandemic. One of the major trends is the learning via Massive Open Online Courses (MOOCs), which is increasingly present at many universities around the world these days. In these courses, learners interact with the pre-designed materials and study everything mostly by themselves. Therefore, gaining insights into their satisfaction of such courses is vitally important to improve their learning experiences and performances. However, previous studies primarily focused on factors that affected learners’ satisfaction, not on how and what the satisfaction was. Moreover, past research mainly employed the narrative reviews posted on MOOC platforms; very few utilized survey and interview data obtained directly from MOOC users. The present study aims to fill in such gaps by employing a mixed-methods approach including a survey design and semi-structured interviews with the participation of 120 students, who were taking academic writing courses on Coursera (one of the world-leading MOOC platforms), at a private university in Vietnam. Results from both quantitative and qualitative data showed that the overall satisfaction of courses on Coursera was relatively low. Furthermore, most learners were not satisfied with their learning experience on the platform, primarily due to inappropriate assessment, lack of support, and interaction with teachers as well as improper plagiarism check. In addition, there were moderate correlations between students’ satisfaction and their perceived usefulness of Coursera courses. Pedagogically, teachers’ feedback and grading, faster support from course designers as well as easier-to-use plagiarism checking tools are needed to secure learners’ satisfaction of MOOCs.
The contribution of gut-brain axis to development of neurological symptoms in COVID-19 recovered patients: A hypothesis and review of literature

The gut microbiota undergoes significant alterations in response to viral infections, particularly the novel SARS-CoV-2. As impaired gut microbiota can trigger numerous neurological disorders, we suggest that the long-term neurological symptoms of COVID-19 may be related to intestinal microbiota disorders in these patients. Thus, we have gathered available information on how the virus can affect the microbiota of gastrointestinal systems, both in the acute and the recovery phase of the disease, and described several mechanisms through which this gut dysbiosis can lead to long-term neurological disorders, such as Guillain-Barre syndrome, chronic fatigue, psychiatric disorders such as depression and anxiety, and even neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease. These mechanisms may be mediated by inflammatory cytokines, as well as certain chemicals such as gastrointestinal hormones (e.g., CCK), neurotransmitters (e.g., 5-HT), etc. (e.g., short-chain fatty acids), and the autonomic nervous system. In addition to the direct influences of the virus, repurposed medications used for COVID-19 patients can also play a role in gut dysbiosis. In conclusion, although there are many dark spots in our current knowledge of the mechanism of COVID-19-related gut-brain axis disturbance, based on available evidence, we can hypothesize that these two phenomena are more than just a coincidence and highly recommend large-scale epidemiologic studies in the future.
Alternative neural systems: What is a neuron? (Ctenophores, sponges and placozoans)

How to make a neuron, a synapse, and a neural circuit? Is there only one ‘design’ for a neural architecture with a universally shared genomic blueprint across species? The brief answer is “No.” Four early divergent lineages from the nerveless common ancestor of all animals independently evolved distinct neuroid-type integrative systems. One of these is a subset of neural nets in comb jellies with unique synapses; the second lineage is the well-known Cnidaria + Bilateria; the two others are non-synaptic neuroid systems in sponges and placozoans. By integrating scRNA-seq and microscopy data, we revise the definition of neurons as synaptically-coupled polarized and highly heterogenous secretory cells at the top of behavioral hierarchies with learning capabilities. This physiological (not phylogenetic) definition separates ‘true’ neurons from non-synaptically and gap junction-coupled integrative systems executing more stereotyped behaviors. Growing evidence supports the hypothesis of multiple origins of neurons and synapses. Thus, many non-bilaterian and bilaterian neuronal classes, circuits or systems are considered functional rather than genetic categories, composed of non-homologous cell types. In summary, little-explored examples of convergent neuronal evolution in representatives of early branching metazoans provide conceptually novel microanatomical and physiological architectures of behavioral controls in animals with prospects of neuro-engineering and synthetic biology.