Miracle-dz/UniFAR-FTUs huggingface dataset:
Identifying the transition to the maturation zone in three ecotypes of Arabidopsis thaliana roots

ABSTRACT The Arabidopsis thaliana (hereafter Arabidopsis) root has become a useful model for studying how organ morphogenesis emerge from the coordination and balance of cell proliferation and differentiation, as both processes may be observed and quantified in the root at different stages of development. Hence, being able to objectively identify and delimit the different stages of root development has been very important. Up to now, three different zones along the longitudinal axis of the primary root of Arabidopsis, have been identified: the root apical meristematic zone (RAM) with two domains [the proliferative (PD) and the transition domain (TD)], the elongation zone (EZ) and the maturation zone (MZ). We previously reported a method to quantify the length of the cells of the meristematic and the elongation zone, as well as the boundaries or transitions between the root domains along the growing part of the Arabidopsis root. In this study, we provide a more accurate criterion to identify the MZ. Traditionally, the transition between the EZ to the MZ has been established by the emergence of the first root-hair bulge in the epidermis, because this emergence coincides with cell maturation in this cell type. But we have found here that after the emergence of the first root-hair bulge some cells continue to elongate and we have confirmed this in three different Arabidopsis ecotypes. We established the limit between the EZ and the MZ by looking for the closest cortical cell with a longer length than the average cell length of 10 cells after the cortical cell closest to the epidermal cell with the first root-hair bulge in these three ecotypes. In Col-0 and Ws this cell is four cells above the one with the root hair bulge and, in the Ler ecotype, this cell is five cells above. To unambiguously identifying the site at which cells stop elongating and attain their final length and fate at the MZ, we propose to calculate the length of completely elongated cortical cells counting 10 cells starting from the sixth cell above the cortical cell closest to the epidermal cell with the first root-hair bulge. We validated this proposal in the three ecotypes analyzed and consider that this proposal may aid at having a more objective way to characterize root phenotypes and compare among them.
Neighborhood deprivation and depression in adult twins: genetics and gene×environment interaction

Background Depression is a significant problem and it is vital to understand its underlying causes and related policy implications. Neighborhood characteristics are implicated in depression but the nature of this association is unclear. Unobserved or unmeasured factors may confound the relationship. This study addresses confounding in a twin study investigating neighborhood-level effects on depression controlling for genetics, common environment, and gene×environment (G × E) interactions. Method Data on neighborhood deprivation and depression were gathered from 3155 monozygotic twin pairs and 1275 dizygotic pairs (65.7% female) between 2006 and 2013. The variance for both depression and neighborhood deprivation was decomposed into three components: additive genetic variance (A); shared environmental variance (C); and non-shared environmental variance (E). Depression was then regressed on neighborhood deprivation to test the direct association and whether that association was confounded. We also tested for a G × E interaction in which the heritability of depression was modified by the level of neighborhood deprivation. Results Depression and neighborhood deprivation showed evidence of significant A (21.8% and 15.9%, respectively) and C (13.9% and 32.7%, respectively) variance. Depression increased with increasing neighborhood deprivation across all twins (p = 0.009), but this regression was not significant after controlling for A and C variance common to both phenotypes (p = 0.615). The G × E model showed genetic influences on depression increasing with increasing neighborhood deprivation (p < 0.001). Conclusions Neighborhood deprivation is an important contributor to depression via increasing the genetic risk. Modifiable pathways that link neighborhoods to depression have been proposed and should serve as targets for intervention and research.
K-Best Solutions of MSO Problems on Tree-Decomposable Graphs

We show that, for any graph optimization problem in which the feasible solutions can be expressed by a formula in monadic second-order logic describing sets of vertices or edges and in which the goal is to minimize the sum of the weights in the selected sets, we can find the $k$ best solutions for $n$-vertex graphs of bounded treewidth in time $\mathcal O(n+k\log n)$. In particular, this applies to the problem of finding the $k$ shortest simple paths between given vertices in directed graphs of bounded treewidth, giving an exponential speedup in the per-path cost over previous algorithms.
Results GWAS identify two candidate genes involved in the accumulation of Pi in the shoot under zn deficiency

All living organisms require a variety of essential elements for their basic biological functions. While the homeostasis of nutrients is highly intertwined, the molecular and genetic mechanisms of these dependencies remain poorly understood. Here, we report a discovery of a molecular pathway that controls phosphate (Pi) accumulation in plants under Zn deficiency. Using genome-wide association studies, we first identified allelic variation of the LysoPhosphatidylCholine (PC) AcylTransferase 1 (LPCAT1) gene as the key determinant of shoot Pi accumulation under Zn deficiency. We then show that regulatory variation at the LPCAT1 locus contributes significantly to this natural variation and we further demonstrate that the regulation of LPCAT1 expression involves bZIP23 TF, for which we identified a new binding site sequence. Finally, we show that in Zn deficient conditions loss of function of LPCAT1 increases the phospholipid Lyso-PhosphatidylCholine/PhosphatidylCholine ratio, the expression of the Pi transporter PHT1;1, and that this leads to shoot Pi accumulation. DOI: https://doi.org/10.7554/eLife.32077. 001
Dynamic weighted voting games

We initiate the study of dynamic cooperative games --- cooperative games where the characteristic function may change over time. We introduce two types of algorithmic problems for such games: computing a given solution concept at time t, and checking that a certain function of the game (e.g., the Shapley value of a given player or the value of the least core) remains within given bounds during time interval [t_0, t_1]. We then investigate the complexity of these problems for dynamic weighted voting games, where the weight of each player and the quota are functions of time that are given by low-degree polynomials with integer coefficients. We provide pseudopolynomial algorithms for problems of both types, for a variety of solution concepts. We then use our results to investigate the changes in power distribution in the Council of the European Union over the next 50 years.
Neural-network based model predictive control for piezoelectric-actuated stick-slip micro-positioning devices

The piezoelectric-actuated stick-slip micro-positioning devices (PASSMDs) have been drawing considerable attention for micro-positioning applications due to their theoretically unlimited motion and good positioning precision. However, the inherent hysteresis of the piezoelectric actuators (PEAs) seriously deteriorates the positioning accuracy of the PASSMDs. In addition, due to the stick-slip actuated principle of PASSMDs, the control of PASSMDs is a challenging job in the literature. This paper proposes a neural network based model predictive control for PASSMDs, which includes the one step control phase and the sub-step control phase. By the proposed method, the hysteresis can be effectively dealt with, which can achieve a relatively accurate positioning performance of PASSMDs. Moreover, to verify the proposed method, a prototype of PASSMDs is developed and experiments are conducted. The experiment results show that the proposed method is an promising way to solve the positioning control of PASSMDs.
Constructing Robust Dissemination Paths in Centralized Control Network

With increasing development of forwarding network, the configuration and management of so many distributed devices has become a great challenge. This has motivated a renewed interest in centralized control of routing network. It enables the control-plane functionalities to be centralized on specific network devices in order to separate from packet forwarding. As a result of centralized control, the management information is delivered by dissemination paths between control element and forwarding engines. The construction of dissemination paths is a key component of centralized control, which must be independent of data-plane convergence. Existing approaches are not quite suitable for centralized control network, thus distinct protocols are required. In this paper, we propose an automatic approach to construct robust dissemination paths for centralized control network. We describe the basic procedure of construction with several reasonable optimizations. We also identify how this approach guarantees the robustness of the constructed path, and demonstrate why the approach is operational, flexible and light weighted. The approach can be easily incorporated into any centralized control network systems as an integrated module with minor modifications, thus leveraging their abilities.
A Learning Approach for Low-Complexity Optimization of Energy Efficiency in Multicarrier Wireless Networks

This paper proposes computationally efficient algorithms to maximize the energy efficiency in multicarrier wireless interference networks, by a suitable allocation of the system radio resources, namely, the transmit powers and subcarrier assignment. The problem is formulated as the maximization of the system global energy efficiency subject to both maximum power and minimum rate constraints. This leads to a challenging nonconvex fractional problem, which is tackled through an interplay of fractional programming, learning, and game theory. The proposed algorithmic framework is provably convergent and has a complexity linear in both the number of users and subcarriers, whereas other available solutions can only guarantee a polynomial complexity in the number of users and subcarriers. Numerical results show that the proposed method performs similarly as other, more complex, algorithms.
Simultaneous colonization of Campylobacter jejuni and Salmonella typhimurium in day-old chicks.

Day-old chicks were challenged with Campylobacter jejuni or Salmonella typhimurium or both to assess the influence of these two bacteria upon the colonization of one another. Median colonization dose (CD50), a measure indicating the number of organisms required to colonize one-half of the challenged chickens, was used to assess the influence of these organisms upon the colonization of one another. Chicks were gavaged with serial dilutions of 1) C. jejuni, 2) S. typhimurium, 3) dilutions of C. jejuni and a fixed level of S. typhimurium, or 4) dilutions of S. typhimurium and a fixed level of C. jejuni. Six days postchallenge, cecal contents were quantitatively assayed for the challenge organisms. Birds challenged with only C. jejuni or birds challenged with both C. jejuni and S. typhimurium had a CD50 of 120 C. jejuni cells. The CD50 values for S. typhimurium alone (48 cells) and S. typhimurium simultaneously colonized with C. jejuni (180 cells) were not significantly different (P less than .05). The colonization levels of either organism were generally correlated with the challenge dose and ranged up to 63 million cells per gram. It was concluded that the CD50 for both C. jejuni and S. typhimurium in 24-h-old chicks were similar, and the presence of one of these particular co-colonizers does not influence the CD50 of the other.
Software tools for pre-and post-processing of oceanic regional simulations.

ROMSTOOLS, a collection of global datasets and a series of Matlab programs collected in an integrated toolbox, generates the grid, surface forcing, initial condition, open boundary conditions, and tides for climatological and inter-annual ROMS ocean simulations. ROMSTOOLS generates also embedded models, real-time coastal modeling systems, as well as experiments including biology. Tools for visualization, animations and diagnostics are also provided
Viral RNA Degradation and Diffusion Act as a Bottleneck for the Influenza A Virus Infection Efficiency

After endocytic uptake, influenza viruses transit early endosomal compartments and eventually reach late endosomes. There, the viral glycoprotein hemagglutinin (HA) triggers fusion between endosomal and viral membrane, a critical step that leads to release of the viral segmented genome destined to reach the cell nucleus. Endosomal maturation is a complex process involving acidification of the endosomal lumen as well as endosome motility along microtubules. While the pH drop is clearly critical for the conformational change and membrane fusion activity of HA, the effect of intracellular transport dynamics on the progress of infection remains largely unclear. In this study, we developed a comprehensive mathematical model accounting for the first steps of influenza virus infection. We calibrated our model with experimental data and challenged its predictions using recombinant viruses with altered pH sensitivity of HA. We identified the time point of virus-endosome fusion and thereby the diffusion distance of the released viral genome to the nucleus as a critical bottleneck for efficient virus infection. Further, we concluded and supported experimentally that the viral RNA is subjected to cytosolic degradation strongly limiting the probability of a successful genome import into the nucleus.
Adaptive Control of a Class of Nonlinear Pure-Feedback Systems Using Fuzzy Backstepping Approach

A controller is proposed for the robust backstepping control of a class of nonlinear pure-feedback systems using fuzzy logic. The proposed control scheme utilizes fuzzy logic systems to learn the behavior of the unknown plant dynamics. Filtered signals are employed to circumvent algebraic loop problems encountered in the implementation of the usual controllers, and the approximation errors can be efficiently counteracted by employing smooth robust compensators. Most importantly, the uniform ultimate boundedness of all signals in the closed-loop system can be guaranteed, and a priori knowledge of the plant dynamics is no longer required. Furthermore, the proposed method can be used for adaptive control of a large class of single-input--single-output nonlinear systems in both strict-feedback and pure-feedback forms, and has great potential in many diverse applications. The performance of the proposed approach is demonstrated through three simulation examples, including one nonlinear pure-feedback and two nonlinear strict-feedback systems.
A Lightweight and Real-Time Worldwide Earthquake Detection and Monitoring System Based on Citizen Sensors

We propose an algorithm and system that detects earthquakes worldwide in real time based on reports of social media users, or "citizen-sensors. " Earthquake detections are based on user postings in any language and from any region. This approach is unsupervised, adapting automatically to changes in the input data stream, and only requires a general list of keywords for each language. Our method is noise tolerant and simple, providing good results both in terms of precision and recall. This complements prior work that mostly consists of supervised approaches that focus on performing detections in a specific geographical area and are difficult to generalize to a global scope. We demonstrate the effectiveness of this approach by using it within a real-time on-line system, which is publicly available and currently in use at National Seismology Center in Chile and Oceanographic and Hydrological Office of the Chilean Army. The quantitative evaluation of our system, performed during a 9-month period, shows that our solution is competitive to the best state-of-the-art methods. Overall, our findings indicate that our approach is an effective low-cost alternative for earthquake monitoring at a global scale.
Detecting Volcano Deformation in InSAR using Deep learning

Globally 800 million people live within 100 km of a volcano and currently 1500 volcanoes are considered active, but half of these have no ground-based monitoring. Alternatively, satellite radar (InSAR) can be employed to observe volcanic ground deformation, which has shown a significant statistical link to eruptions. Modern satellites provide large coverage with high resolution signals, leading to huge amounts of data. The explosion in data has brought major challenges associated with timely dissemination of information and distinguishing volcano deformation patterns from noise, which currently relies on manual inspection. Moreover, volcano observatories still lack expertise to exploit satellite datasets, particularly in developing countries. This paper presents a novel approach to detect volcanic ground deformation automatically from wrapped-phase InSAR images. Convolutional neural networks (CNN) are employed to detect unusual patterns within the radar data.
Geocomposites against reflective cracking in asphalt pavements: laboratory simulation of a field application

Asphalt pavements often suffer reflective cracking phenomena. Crack appearance at the road surface leads to several detrimental effects, including the loss of watertightness. Geocomposites, such as grid-reinforced bituminous membranes, represent an efficient method against reflective cracking since they combine improved tensile properties of grids and stress-relieving effects of membranes. Moreover, membranes allow pavement waterproofing. This paper presents laboratory and field studies carried out to investigate the reflective cracking resistance of geocomposite-reinforced asphalt systems. The study is based on a real-scale field trial constructed along an in-service motorway. Five geocomposites were taken into account and the possible use of a tack coat and application on a milled surface were also evaluated. Interface shear tests were carried out both on field cores and on laboratory-made samples. Moreover, pre-notched laboratory specimens were subjected to specifically developed simulative tests through the Wheel Tracking equipment. Experimental results clearly showed that a proper selection and application of optimised grid-reinforced bituminous membranes can significantly enhance reflective cracking resistance of asphalt pavements.
Mode Competition in Dual-Mode Quantum Dots Semiconductor Microlaser

´This paper describes the modeling of quantum dots lasers with the aim of assessing the conditions for stable cw dual-mode operation when the mode separation lies in the THz range. Several possible models suited for InAs quantum dots in InP barriers are analytically evaluated, in particular quantum dots electrically coupled through a direct exchange of excitation by the wetting layer or quantum dots optically coupled through the homogeneous broadening of their optical gain. A stable dual-mode regime is shown possible in all cases when quantum dots are used as active layer whereas a gain medium of quantum well or bulk type inevitably leads to bistable behavior. The choice of a quantum dots gain medium perfectly matched the production of dual-mode lasers devoted to THz generation by photomixing.
A study on structural and electronic properties of GaAs1-xNx and GaAs1-xBix alloys

We have performed first principles method to investigate structural and electronic properties of GaAs1-xNx and GaAs1-xBix ternary semiconductor alloy using Density Functional Theory and pseudo potential method within the Generalized Gradient Approximations and Local Density Approximation. The Zinc-Blende phase is found stable for GaAsN and GaAsBi alloys. In this study we investigate the both bowing parameters changing with Bismuth concentration in GaAsBi and Nitrogen concentration in GaAsN alloys. By using the bowing parameter of GaAsBi and GaAsN alloys we obtained the bandgap energies for all x concentrations (0 < x < 1) and lattice constant of both alloys which are important for wide range device application. For studied materials, lattice parameters and band gap energies are compared with available theoretical and experimental works.
Rear object detection method based on optical flow and vehicle information for moving vehicle

This paper proposes a method to detect rear object using vehicle information and optical flow in moving vehicles. The previous method detects objects by method using optical flow, background removal, and frame difference in the stopped vehicle state. In particular, optical flow method uses analysis of background or flow distribution to remove the background flow. In this paper, however, objects detect in moving vehicles by removing the background flow generated by vehicle movement using vehicle information. The performance of the proposed algorithm evaluated through experiments using stored images and vehicle information obtained from actual moving vehicles.
Effect of Meta Kaolin Filler on the Physico-mechanical Properties and Chemical Resistance of Chain Extended Polyurethane

A series of meta kaolin (MK, clay) filler incorporated chain extended castable polyurethane (PU) [100/0, 90/10, 80/20, and 70/30 PU/MK], based on castor oil and 2,4-toluene diisocyanate (TDI) with tartaric acid as chain extender, were synthesized. The effect of meta kaolin loading on the physico-mechanical properties and chemical resistance of filled chain extended PU have been studied. From the tensile behavior it was noticed that a drastic improvement in tensile strength and tensile modulus increased with filler content. It was observed that the PU composites showed more resistance to acid compared to alkali.