Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthetic Notch Activation Patterns in a Proliferating Tissue

Cell-cell communication through direct contact is essential during fundamental biological processes such as tissue repair and morphogenesis. Synthetic forms of contact-mediated cell-cell communication can generate custom gene expression outputs, making them valuable for tissue engineering and regenerative medicine. To precisely control the location and timing of synthetic signal outputs in growing tissues, it is necessary to understand the mechanisms underlying its spatiotemporal patterns. Towards this goal, we combine theory and experiments to study patterns of synthetic Notch (synNotch) activation - a custom synthetic gene circuit that we implement within Drosophila wing imaginal discs. We show that output synthesis and degradation rates together with cell division are the key minimal parameters that predict the heterogeneous spatiotemporal patterns of synNotch activation. Notably, synNotch output forms a graded exponential spatial profile that extends several cell diameters from the signal source, establishing evidence for signal propagation without diffusion or long range cell-cell communication. Furthermore, we discover that the shape of the interface between ligand and receptor cells is important in determining the syn-Notch output. Overall, we elucidate key biophysical principles that underlie complex emergent spatiotemporal patterns of synNotch output in a growing tissue.
Geographic population structure and distinct population dynamics of globally abundant freshwater bacteria

Geographic separation is a principal factor for structuring populations of macroorganisms, with important consequences for evolution, by means of processes such as allopatric speciation. For free-living prokaryotes, implications of geographic separation on their evolution are more unclear. The limited phylogenetic resolution of commonly used markers such as 16S rRNA gene sequences have since long impeded prokaryotic population genetics. However, the vast amount of metagenome sequencing data generated during the last decades from various habitats around the world, now provides an excellent opportunity for such investigations. Here we exploited publicly available and new freshwater metagenomes in combination with genomes of abundant freshwater bacteria to study the impact of geographic separation on population structure. We focused on species that were detected across broad geographic ranges at high enough sequence coverage for meaningful population genomic analyses, i.e. members of the predominant freshwater taxa acI, LD12, Polynucleobacter and Ca. Methylopumilus. Population differentiation increased significantly with spatial distance in all species, but notable dispersal barriers (e.g. oceanic) were not apparent. Yet, the different species showed contrasting rates of geographic divergence and strikingly different population dynamics in time series within individual lakes. While certain populations hardly diverged over several years, others displayed high divergence after merely a few months, similar in scale to populations separated by thousands of kilometers. We speculate that populations with higher strain diversity evolve more monotonously, while low strain diversity enables more drastic clonal expansion of genotypes which will be reflected in strong but transient differentiation between temporally or spatially adjacent populations.
EnrichMiner: a biologist-oriented web server for mining biological insights from functional enrichment analysis results

Functional enrichment analysis has been widely used to help researchers obtain biological insights from -omics data. However, the results are often redundant and difficult to digest. The key is developing tools to help users explore the relationships between the enriched terms, remove the redundant terms, and finally select representative terms. However, existing tools hardly make a good integration between enrichment analysis and representative terms selection in a biological-friendly manner. Here, we developed a biologist-oriented web server named EnrichMiner to provide a one-stop solution. It is a complete analysis pipeline from a gene list or a ranked gene table to published-style figures. More importantly, it provides user-friendly interfaces and rich interactive operations to help users explore the term relationships and remove redundancy. EnrichMiner has been integrated into the ExpressVis platform, and is freely accessible at https://omicsmining.ncpsb. org.cn/ExpressVis/EnrichMiner and does not require login.
Femtosecond laser-induced transformations in ultra-low expansion glass: Microstructure and local density variations by vibrational spectroscopy

We report X-ray diffraction, resonance Raman, and infrared (IR) results on pristine ultra-low expansion (ULE) glass, a binary titanosilicate glass with 5.67 mol. % TiO2. ULE processing by femtosecond (fs) laser radiation leads to nanograting writing and photo-darkening for imaging and data storage. We investigate here the vibrational/structural changes induced by fs laser irradiation of ULE at 515 nm. Optical imaging revealed the formation of micro-cavities, and Raman mapping showed molecular oxygen trapped in such cavities of laser-irradiated ULE glass. While titanium in the pristine glass was found predominantly in tetrahedral Ti4+ sites highly dispersed in the silicate matrix, Raman and IR reflectance spectroscopy on laser-irradiated ULE indicated the formation of Ti3+ sites; Ti3+ octahedral sites are formed in the shells of cavities and aggregate in amorphous Ti2O3-type clusters, while the glass around and below cavities contains Ti3+ tetrahedral sites dispersed in the silicate network. Laser-processed ULE glass was found to also exhibit local restructuring of the silicate matrix. Shifts of the strong IR band at about 1080–1100 cm−1 were translated into changes of the average Si-O-Si bond angle in the laser-transformed areas and found to reflect local density variations; the average local density increases relative to silica glass up to about 8% in the shells of micro-cavities and decreases by about 0.5% in the surrounding material. Chemical processes were proposed to account for photo-darkening and the local structural transformation effect in the probed areas of the fs laser-processed ULE glasses.We report X-ray diffraction, resonance Raman, and infrared (IR) results on pristine ultra-low expansion (ULE) glass, a binary titanosilicate glass with 5.67 mol. % TiO2. ULE processing by femtosecond (fs) laser radiation leads to nanograting writing and photo-darkening for imaging and data storage. We investigate here the vibrational/structural changes induced by fs laser irradiation of ULE at 515 nm. Optical imaging revealed the formation of micro-cavities, and Raman mapping showed molecular oxygen trapped in such cavities of laser-irradiated ULE glass. While titanium in the pristine glass was found predominantly in tetrahedral Ti4+ sites highly dispersed in the silicate matrix, Raman and IR reflectance spectroscopy on laser-irradiated ULE indicated the formation of Ti3+ sites; Ti3+ octahedral sites are formed in the shells of cavities and aggregate in amorphous Ti2O3-type clusters, while the glass around and below cavities contains Ti3+ tetrahedral sites dispersed in the silicate network. Laser-processe.
Topological data analysis reveals a core heteroblastic program embedded in leaves of grapevine and maracuyá

Leaves have a single shape. However, embedded in that shape are a multitude of latent shapes arising from evolutionary, developmental, environmental, and other effects. These confounded effects manifest at distinct developmental time points and evolve at different tempos. Here, revisiting datasets comprised of thousands of leaves of vining grapevine (Vitaceae) and maracuyá (Passifloraceae) species, we apply a technique from the mathematical field of topological data analysis to comparatively visualize the structure of heteroblastic effects on leaf shape in each group. Consistent with a morphologically closer relationship, members of the grapevine dataset possess a strong core heteroblasty program with little deviation between species. Remarkably, we found that most members of the maracuyá family also share a core heteroblasty program despite dramatic species-to-species leaf shape differences. This conservation was not detected using traditional analyses. We also identify two morphotypes of maracuyá that deviate from the core structure, suggesting the evolution of new heteroblastic properties in this phylogenetically related sub-group. Our findings illustrate how topological data analysis can be used to disentangle previously confounded developmental and evolutionary effects to visualize latent shapes and hidden relationships, even ones embedded in complex, high-dimensional datasets.
ROBUST NONLINEAR H∞ AND MPC CONTROL FOR PATH TRACKING OF A QUADROTOR THROUGH ESTIMATION OF SYSTEM PARAMETERS

ARTICLE INFORMATION ABSTRACT Original Research Paper Received 26 April 2016 Accepted 31 May 2016 Available Online 13 July 2016 In this paper, a trajectory tracking control strategy for a quadrotor flying robot is developed. At first, dynamic model is obtained by Lagrange-Euler approach. Then, control structure, consisting of a modelbased predictive controller, has been used based on state space error to track transitional movements for reference trajectory and also robust nonlinear H control is applied for stabilizing the rotational movements and rejecting the external disturbance. In both controllers the integral of the position error is considered, allowing the achievement of a null steady-state error when sustained disturbances are acting on the system. The external disturbances are considered as aerodynamic torques. If uncertainties increase, the designed control system unable to path tracking properly. So finally, in order to eliminate the effects of parameter uncertainties the recursive least squares is used for estimating mass and moment inertia parameters which are linear and it is applied to the control system. Simulation results show that by using estimation of system parameters, the proposed control system has a promising performance in terms of stabilization and position tracking even in the presence of external disturbance and parametric uncertainties.
Ebola Virus VP35 Interacts Non-Covalently with Ubiquitin Chains to Promote Viral Replication Creating New Therapeutic Opportunities

Ebolavirus (EBOV) belongs to a family of highly pathogenic viruses that cause severe hemorrhagic fever in humans. EBOV replication requires the activity of the viral polymerase complex, which includes the co-factor and Interferon antagonist VP35. We previously showed that the covalent ubiquitination of VP35 promotes virus replication by regulating interactions with the polymerase complex. In addition, VP35 can also interact non-covalently with ubiquitin (Ub); however, the function of this interaction is unknown. Here, we report that VP35 interacts with free (unanchored) K63-linked polyUb chains. Ectopic expression of Isopeptidase T (USP5), which is known to degrade unanchored polyUb chains, reduced VP35 association with Ub and correlated with diminished polymerase activity in a minigenome assay. Using computational methods, we modeled the VP35-Ub non-covalent interacting complex, identified the VP35-Ub interacting surface and tested mutations to validate the interface. Docking simulations identified chemical compounds that can block VP35-Ub interactions leading to reduced viral polymerase activity that correlated with reduced replication of infectious EBOV. In conclusion, we identified a novel role of unanchored polyUb in regulating Ebola virus polymerase function and discovered compounds that have promising anti-Ebola virus activity. Significance Statement Ebola virus infection can result in high mortality rates with extreme risk of person-to-person transmission. Sporadic outbreaks in Africa have resulted in thousands of fatal cases, highlighting that there is still insufficient knowledge to develop effective antiviral therapies. Like other viruses, Ebola utilizes the host machinery to replicate. Understanding how viral and host proteins interact can help identifying targets for the rational design of antiviral drugs. Here, we identified interactions between the cellular ubiquitin machinery and the Ebola virus polymerase cofactor protein VP35, which are important for efficient virus replication. We developed an approach to identify and block these virus-host interactions using small chemical compounds, which provides a useful tool to study functional molecular mechanisms and at the same time a potential approach to antiviral therapies.
Singularity Avoidance as Manipulability Maximization Using Continuous Time Gaussian Processes

A significant challenge in motion planning is to avoid being in or near \emph{singular configurations}, that is, configurations in joint space that result in the loss of the ability to move in certain directions in task space. A robotic system's manipulability is reduced even in regions that are in close proximity to (i.e., neighbouring) a singularity. In this work we examine singularity avoidance in a motion planning context, that is, finding a trajectory which minimizes proximity to singular regions, subject to constraints. Representing the trajectory as a sample taken from a continuous time Gaussian process, we define a likelihood associated with singularity avoidance. We leverage recent work on motion planning using exactly sparse Gaussian processes and a factor graph representation to maximize the singularity avoidance likelihood using a \textit{maximum a posteriori} (MAP) estimator. Viewing the MAP problem as inference on a factor graph, we use gradient information from interpolated states to maximize the trajectory's overall manipulability. Both qualitative and quantitative analysis of experimental data show increases in manipulability which results in smooth trajectories with visibly more dexterous configurations.
Caracterización higroscópica del aerosol atmosférico mediante la técnica lidar Raman

La investigacion descrita en esta memoria tiene su origen en el ano 2010, dentro de las actividades planteadas en el marco del proyecto nacional “PHAESIAN” (Propiedades Higroscopicas de los Aerosoles y Efecto Sobre la Interaccion Aerosol-Nube, CGL2010-17777), que tenia por objeto caracterizar las propiedades higroscopicas de los aerosoles y la interaccion aerosol-nube, y posteriormente continuada en el proyecto nacional “PROACLIM” (PROpiedades del Aerosol atmosferico en diferentes escenarios espacio-temporales y su influencia en el CLIMa, CGL2014-52877-R) de semejantes caracteristicas. La importancia de esta investigacion reside en el hecho de que una de las mayores fuentes de incertidumbre, halladas en las diferentes estimaciones del forzamiento radiativo11 de los elementos que rigen el balance radiativo terrestre, y por ende el clima, corresponde al papel que ejercen los aerosoles en la formacion, distribucion y modificacion de las caracteristicas de las masas nubosas, de acuerdo a los resultados recogidos en el V informe del IPCC (Panel Intergubernamental de Cambio Climatico, en ingles, Intergovernmental Panel of Climate Change) (2013). En este sentido, el conocimiento de las propiedades opticas y microfisicas de los aerosoles, observados en la atmosfera a diferentes niveles de humedad, es determinante para inferir dicho forzamiento radiativo y entender mejor el mecanismo de interaccion de estos con las nubes. Esta tesis recoge la investigacion efectuada en la tematica anteriormente citada mediante el empleo de la tecnica LIDAR (LIght Detection And Ranging, de ahora en adelante “lidar”), pues esta tecnologia permite observar las propiedades opticas de los aerosoles en la atmosfera, y el contenido de vapor de agua, con resolucion en altura, de forma simultanea, y sin perturbar el medio muestreado. La tecnica lidar tal y como se utilizara en esta tesis se basa en la emision de radiacion laser pulsada a la atmosfera en direccion vertical desde la superficie terrestre y en el posterior analisis de la fraccion de radiacion devuelta por los constituyentes atmosfericos, gases y aerosoles.
Bounds on the size of the convex hull of planar Brownian motion and related inverse processes

We establish bounds on expected values of various geometric quantities that describe the size of the convex hull spanned by a path of the standard planar Brownian motion. Expected values of the perimeter and the area of the Brownian convex hull are known explicitly, and satisfactory bounds on the expected value of its diameter can be found in the literature as well. In this work we investigate circumradius and inradius of the Brownian convex hull and obtain lower and upper bounds on their expected values. Our other goal is to find bounds on the related inverse processes (that correspond to the perimeter, area, diameter, circumradius and inradius of the convex hull) which provide us with some information on the speed of growth of the size of the Brownian convex hull.
A discontinuity and cusp capturing PINN for Stokes interface problems with discontinuous viscosity and singular forces

In this paper, we present a discontinuity and cusp capturing physics-informed neural network (PINN) to solve Stokes equations with a piecewise-constant viscosity and singular force along an interface. We first reformulate the governing equations in each fluid domain separately and replace the singular force effect with the traction balance equation between solutions in two sides along the interface. Since the pressure is discontinuous and the velocity has discontinuous derivatives across the interface, we hereby use a network consisting of two fully-connected sub-networks that approximate the pressure and velocity, respectively. The two sub-networks share the same primary coordinate input arguments but with different augmented feature inputs. These two augmented inputs provide the interface information, so we assume that a level set function is given and its zero level set indicates the position of the interface. The pressure sub-network uses an indicator function as an augmented input to capture the function discontinuity, while the velocity sub-network uses a cusp-enforced level set function to capture the derivative discontinuities via the traction balance equation. We perform a series of numerical experiments to solve two- and three-dimensional Stokes interface problems and perform an accuracy comparison with the augmented immersed interface methods in literature. Our results indicate that even a shallow network with a moderate number of neurons and sufficient training data points can achieve prediction accuracy comparable to that of immersed interface methods.
The tree-child network problem for line trees and the shortest common supersequences for permutations

One strategy for reconstruction of phylogenetic networks is to solve the phylogenetic network problem, which involves inferring phylogenetic trees first and subsequently computing the smallest phylogenetic network that displays all the trees. This approach capitalizes on exceptional tools available for inferring phylogenetic trees from biomolecular sequences. Since the vast space of phylogenetic networks poses difficulties in obtaining comprehensive sampling, the researchers switch their attention to inferring tree-child networks from multiple phylogenetic trees, where in a tree-child network each non-leaf node must have at least one child that is an indegree-one node. Two results are obtained: (1) The tree-child network inference problem for multiple line trees remains NP-hard by a reduction from the shortest common supersequence problem for permutations and proving that the latter is NP-hard. (2) The tree-child networks with the least reticulate nodes that display all the line trees are the same as that display all the binary trees, whose hybridization number is $\Theta(n^3)$ for $n (>7)$ taxa.
The Effects of Mixed Sample Data Augmentation are Class Dependent

Mixed Sample Data Augmentation (MSDA) techniques, such as Mixup, CutMix, and PuzzleMix, have been widely acknowledged for enhancing performance in a variety of tasks. A previous study reported the class dependency of traditional data augmentation (DA), where certain classes benefit disproportionately compared to others. This paper reveals a class dependent effect of MSDA, where some classes experience improved performance while others experience degraded performance. This research addresses the issue of class dependency in MSDA and proposes an algorithm to mitigate it. The approach involves training on a mixture of MSDA and non-MSDA data, which not only mitigates the negative impact on the affected classes, but also improves overall accuracy. Furthermore, we provide in-depth analysis and discussion of why MSDA introduced class dependencies and which classes are most likely to have them.
Enforcing Topological Interaction between Implicit Surfaces via Uniform Sampling

Objects interact with each other in various ways, including containment, contact, or maintaining fixed distances. Ensuring these topological interactions is crucial for accurate modeling in many scenarios. In this paper, we propose a novel method to refine 3D object representations, ensuring that their surfaces adhere to a topological prior. Our key observation is that the object interaction can be observed via a stochastic approximation method: the statistic of signed distances between a large number of random points to the object surfaces reflect the interaction between them. Thus, the object interaction can be indirectly manipulated by using choosing a set of points as anchors to refine the object surfaces. In particular, we show that our method can be used to enforce two objects to have a specific contact ratio while having no surface intersection. The conducted experiments show that our proposed method enables accurate 3D reconstruction of human hearts, ensuring proper topological connectivity between components. Further, we show that our proposed method can be used to simulate various ways a hand can interact with an arbitrary object.
Need-driven decision-making and prototyping for DLT: Framework and web-based tool

In its 14 years, distributed ledger technology has attracted increasing attention, investments, enthusiasm, and user base. However, ongoing doubts about its usefulness and recent losses of trust in prominent cryptocurrencies have fueled deeply skeptical assessments. Multiple groups attempted to disentangle the technology from the associated hype and controversy by building workflows for rapid prototyping and informed decision-making, but their mostly isolated work leaves users only with fewer unclarities. To bridge the gaps between these contributions, we develop a holistic analytical framework and open-source web tool for making evidence-based decisions. Consisting of three stages - evaluation, elicitation, and design - the framework relies on input from the users' domain knowledge, maps their choices, and provides an output of needed technology bundles. We apply it to an example clinical use case to clarify the directions of our contribution charts for prototyping, hopefully driving the conversation towards ways to enhance further tools and approaches.