Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid Simulations of the Effects of Energetic Particles on Low-Frequency MHD Waves

A hybrid MHD-gyrokinetic simulation model is presented which is suitable for self-consistent study of the interaction of energetic particles with low-frequency MHD waves. Fully electromagnetic gyrokinetic equations are used to describe the energetic particles, while the cold background plasma is treated as a fluid, using nonlinear one-fluid MHD equations. Based on this model a hybrid MHD-gyrokinetic particle code has been developed. A ? falgorithm has been implemented in the code for s ~ 1 electromagnetic perturbations. The gyrokinetic description enables us to remove the restriction on the particle time step dictated by the gyromotion, while the ? falgorithm strongly reduces the simulation numerical noise level. Therefore, considerably larger time steps and a smaller number of particles can be used in the simulations as compared to conventional methods. The conservation properties of the model and corresponding ? fscheme have been investigated. Representative two-dimensional simulations of the mirror instability and the temperature gradient driven instability of the compressional mode were performed, and the simulation results are in very good agreement with linear theory.
Case study on demand side management‐based cost optimized battery integrated hybrid renewable energy system for remote rural electrification

Power demand of isolated villages where on‐grid power supply is not economical can be met by standalone renewable energy system. Hybrid renewable energy system (HRES) considered in the current study involves photo‐voltaic, wind turbine, diesel generator, and battery. In the present study, the demand side energy management methods are used for energy management. The load shifting and strategic conservation methods are used. The energy management schemes are applied in the stage of load estimation. It is observed in the analysis that, the net present cost (NPC) of $55 263 is reduced to $34 009 with the application of demand side energy management strategies. The two control strategies, load‐following and predictive‐dispatch strategy are incorporated. The three types of batteries like lead‐acid, lithium‐ion, and zinc‐bromide are integrated, one at a time, for analysis. The analysis results in the optimal HRES configuration solution with the combination of both load shifting and strategic conservation techniques of demand side energy management. The NPC is reduced by 37% in comparison with the HRES without the application of energy management methods. The zinc‐bromide battery integrated HRES configuration through predictive dispatch control strategy with the application of demand side energy management schemes results in optimal solution for electrification of cluster of villages located in Uralagallu panchayat, Sagar Taluk, Shivamogga District, Karnataka, India. To the similar kind of geographical condition areas, the same HRES configuration with similar approach can be extended for electrification.
polynomial time approximation scheme for the minimum maximal matching problem in planar graphs (New Developments of Theory of Computation and Algorithms)

: Given an undirected graph $G$ , the minimum maximal matching problem asks to ﬁnd aminimum matching that is inclusionwise maximal. The problem is known to be NP-hard even if the graph is planar. We consider the problem for planar graphs, and show that apolynomial time approximation scheme (PTAS) can be obtained by adivide-and-conquer method based on the planar separator theorem. For agiven $ \epsilon>0$ , our scheme delivers in $O(n \log nf\alpha e\epsilon^{-1}n)\star$ time asolution with size at most $(1+ \epsilon)$ times the optimal value, where $n$ is the number of vertices in $G$ and $ \alpha$ is aconstant number.
Complex pulsing schemes for high frame rate imaging

High frame rate ultrasound imaging can be achieved by simultaneous transmission of multiple focused beams along different directions. However, image quality degrades by the interference among beams. An alternative approach is to transmit spherical waves of a basic short pulse with frequency coding and a constant transmit delay from channel to channel. In this way, transmit diversity is provided on a time and channel basis rather than on a beam direction basis. The non-focused transmitted acoustic waves carry spatial information from the entire imaging region. At a given imaging point, all pulses will add up to a pulse train. The acoustically generated high time-bandwidth (TB) product waveforms can be compressed by using a filter bank of matched filters one for every beam direction. Matched filtering compresses the pulse train to a single pulse at the scatterer position plus a number of spike axial sidelobes. Frequency and phase modulation of the transmitting pulses allows control and elimination of the ambiguous spikes. QLFM pulse trains are found to give the best performance. Simulation results and images are presented showing the feasibility of the method. The excitation consists of 32 pulses with linear frequency modulation along the transducer elements, that cover the 70% fractional bandwidth of the 7 MHz transducer. The resulted images (after beamforming and matched filtering) show an axial resolution at the same order as in conventional pulse excitation and axial sidelobes down to -45 dB. With the proposed imaging strategy of pulse train excitation, a whole image can be formed with only two emissions, making it possible to obtain high quality images at a frame rate of 20 to 25 times higher than that of conventional phased array imaging.
An intermembrane space protein facilitates completion of mitochondrial division in yeast

Mitochondria are highly dynamic double membrane-bound organelles that maintain their shape in part through fission and fusion. Mitochondrial fission is performed by the dynamin-related protein Dnm1 (Drp1 in humans), a large GTPase that constricts and divides the mitochondria in a GTP hydrolysis-dependent manner. However, it is unclear whether factors inside mitochondria help coordinate the process and if Dnm1/Drp1 activity alone is sufficient to complete fission of both mitochondrial membranes. Here, we identify an intermembrane space protein required for mitochondrial fission in yeast, which we propose to name Mdi1. Loss of Mdi1 leads to hyper-fused mitochondria networks due to defects in mitochondrial fission, but not lack of Dnm1 recruitment to mitochondria. Mdi1 plays a conserved role in fungal species and its homologs contain a putative amphipathic α-helix, mutations in which disrupt mitochondrial morphology. One model to explain these findings is that Mdi1 associates with and distorts the mitochondrial inner membrane to enable Dnm1 to robustly complete fission. Our work reveals that Dnm1 cannot efficiently divide mitochondria without the coordinated function of a protein that resides inside mitochondria.
A rapid and robust leaf ablation method to visualize bundle sheath cell chloroplasts in C3 species

Background It has been proposed that engineering the C4 photosynthetic pathway into C3 crops could significantly increase yield. This goal requires an increase in the chloroplast compartment of bundle sheath cells in C3 species. To facilitate large-scale testing of candidate regulators of chloroplast development in the rice bundle sheath, a simple and robust method to phenotype this tissue in C3 species is required. Results We established a leaf ablation method to accelerate phenotyping of rice bundle sheath cells. The approach allowed bundle sheath cell dimensions, chloroplast area and chloroplast number per cell to be measured. Using this method, bundle sheath cell dimensions of maize were also measured and compared with rice. Our data show that bundle sheath width but not length significantly differed between C3 rice and C4 maize. Comparison of paradermal versus transverse bundle sheath cell width indicated that bundle sheath cells were intact after leaf ablation. Moreover, comparisons of planar chloroplast areas and chloroplast numbers per bundle sheath cell between wild-type and transgenic rice lines expressing the maize GOLDEN-2 (ZmG2) showed that the leaf ablation method allowed differences in chloroplast parameters to be detected. Conclusions Leaf ablation is a simple approach to accessing bundle sheath cell files in C3 species. We show that this method is suitable for obtaining parameters associated with bundle sheath cell size, chloroplast area and chloroplast number per cell.
TECHBREAK: a technology foresight activity for the European Space Agency points the way to future space telescopes

We report on a joint European Science Foundation-ESA “Forward Look” project called TECHBREAK aimed at identifying technological breakthroughs for space originating in the non-space sector. We show how some of the technologies highlighted may impact future space programmes, in particular novel ideas to enable future long-life large telescopes to be deployed. The study’s final report was presented to ESA’s High level Science Policy Advisory Committee (HISPAC) in late 2014. The goals of the study were to forecast the development of breakthrough technologies to enable novel space missions in the 2030-2050 timeframe, and to identify related partnerships through synergies with non-space specialists. It was not prepared to serve as a definitive guide for very specific technologies to be developed for future space missions, but to inform on and flag up the main developments in various technological and scientific areas outside space that may hold promise for use in the space domain. The report does this by identifying the current status of research for each domain, asserting the development horizon for each technology and providing some entry points, in the form of key European experts and institutions with knowledge of the domain. The identification of problems and solutions specific to the space area led us to focus the discussion around the concept of “Overwhelming Drivers” for space research and exploration, i.e. long-term goals that can be transposed into technological development goals. Two of these overwhelming drivers are directly relevant to ambitious future telescope projects, and we will show how some of the technologies we identified such as biomimetic structures, nanophotonics, novel materials and additive manufacturing could be combined to enable revolutionary new concepts for space telescopes.
Selective inhibition of OSBP blocks retrograde trafficking by inducing partial Golgi degradation

Sterol-binding proteins are important regulators of lipid homeostasis and membrane integrity; however, the discovery of selective small molecule modulators can be challenging due to structural similarities in the sterol binding domains. We report the discovery of highly potent and selective inhibitors of oxysterol binding protein (OSBP), which we term oxybipins. Sterol-containing chemical chimeras aimed at identifying new sterol binding proteins by targeted degradation, led to a significant reduction in Golgi-associated proteins. The degradation was found to occur at lysosomes, concomitant with changes in general protein glycosylation, indicating that the degradation of Golgi proteins was a downstream effect. By establishing a sterol transport protein biophysical assay panel, we discovered that the oxybipins potently inhibited OSBP, resulting in blockage of retrograde trafficking and attenuating Shiga toxin toxicity. As the oxybipins do not target any other sterol transporters tested, we advocate their use as chemical tools to study OSBP function and therapeutic relevance.
Adaptation of the binding domain of Lactobacillus acidophilus S-layer protein as a molecular tag for affinity chromatography development

The SLAPTAG is a novel molecular TAG derived from a protein domain present in the sequence of Lactobacillus acidophilus SlpA (SlpA284–444). Proteins from different biological sources, with different molecular weights or biochemical functions, can be fused in frame to the SLAPTAG and efficiently purified by the specific binding to a bacterial-derived chromatographic matrix named here Bio-Matrix (BM). Different binding and elution conditions were evaluated to set an optimized protocol for the SLAPTAG-based affinity chromatography (SAC). The binding equilibrium between SLAPTAG and BM was reached after a few minutes at 4°C, being the apparent dissociation constant (KD) of 4.3 µM, a value which is similar to different Kd determined for other S-layer proteins and their respective bacterial cell walls. A reporter protein was generated (H6-GFP-SLAPTAG) to compare the efficiency of the SAC against a commercial system based on a Ni2+-charged agarose matrix, observing no differences in the H6-GFP-SLAPTAG purification performance. The stability and reusability of the BM were evaluated, and it was determined that the matrix was stable for more than a year, being possible to reuse it five times without a significant loss in the efficiency for protein purification. Alternatively, we explored the recovery of bound SLAP-tagged proteins by proteolysis using the SLAPASE (a SLAP-tagged version of the HRV-3c protease) that released a tag-less GFP (SLAPTAG-less). Additionally, iron nanoparticles were linked to the BM and the resulting BMmag was successfully adapted for a magnetic SAC, a technique that can be potentially applied for high-throughput-out protein production and purification.
FIBONACCI COLLOCATION METHOD FOR SOLVING LINEAR DIFFERENTIAL - DIFFERENCE EQUATIONS

This study presents a new method for the solution of mth-order linear differential-difference equations with variable coefficients under the mixed conditions. We introduce a Fibonacci collocation method based on the Fibonacci polynomials for the approximate solution. Numerical examples are included to demonstrate the applicability of the technique. The obtained results are compared by the known results.
A Comprehensive Transcriptional Signature in Pancreatic Ductal Adenocarcinoma Reveals New Insights into the Immune and Desmoplastic Microenvironments

Pancreatic ductal adenocarcinoma (PDAC) prognosis and treatment response remains devastatingly poor due partly to the highly heterogeneous, aggressive, and immunosuppressive nature of this tumor type. The intricate relationship between stroma, inflammation, and immunity remains vaguely understood in the PDAC microenvironment. Here, we performed a meta-analysis of stroma-, and immune-related gene expression in the PDAC microenvironment to improve disease prognosis and therapeutic development. We selected twenty-one PDAC studies from the Gene Expression Omnibus and ArrayExpress databases, including 922 samples (320 controls and 602 cases). Differential gene enrichment analysis identified 1153 significant dysregulated genes in PDAC patients that contribute to a desmoplastic stroma and an immunosuppressive environment (the hallmarks of PDAC tumors). The results highlighted two gene signatures related to the immune and stromal environments that cluster PDAC patients in high- and low-risk groups, impacting patient stratification and therapeutic decision-making. Moreover, HCP5, SLFN13, IRF9, IFIT2, and IFI35 immune genes were related to prognosis value in PDAC patients, for the first time. Simple Summary Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease with few curative options. Desmoplastic stroma and immune system evasion in PDAC represent challenges to the success of therapeutic strategies that function well in other tumor types. Characterizing the PDAC microenvironment (including the immune environment) remains critical to developing safe and efficient therapies. Here, we present a comprehensive meta-analysis identifying 1153 significantly dysregulated genes, which mainly impact extracellular matrix remodeling and the immune system. We identify two signatures of twenty-eight immune-related genes and eleven stroma-related genes influencing PDAC patient survival. Additionally, five immune genes are associated with PDAC prognosis for the first time.
Chromosome-level genome assembly provides insights into adaptive evolution of chromosome and important traits in the gecko Gekko japonicus

Gekko japonicus possess excellent flexible climbing and detoxification ability under insectivorous habits, and its chromosomes and the genetic evolutionary mechanisms behind these traits are still unclarified. Here, we assembled a chromosome-level genome of G. japonicus with a total size of 2.53 Gb contained in 19 pairs of chromosomes. The evolutionary breakpoint regions (EBRs) are significantly enriched for some repetitive elements compared to the rest of genome and the genes located in the EBRs are enriched in defense response pathway. G. japonicus specific gene families, expanded gene families and positively selected genes are mainly enriched in some pathways related to the immune, sensory and nervous systems. These results from comprehensive comparative genomics and evolutionary genomics analyses indicated that bitter taste receptor type 2 (T2Rs) expanded in different lineages by tandem gene duplication. The expansion and independent duplication events of T2Rs and positively selected branches were predominantly present in insectivorous species, suggests that T2Rs are associate with clearance of bitter toxins in gekkotans. Detoxification genes in detox and biosynthetic cytochrome P450 of G. japonicas have frequent duplication and loss events, suggests that they undergo more birth and death processes compared to biosynthesis type genes. Pro, Cys, Gly and Ser are the most abundant amino acids in 66 epidermis formation corneous beta proteins (CBPs) of G. japonicas, the abundance of Gly and Cys in CBPs implying significant effects on the flexibility and setae adhesiveness of gekkotans. Some thermosensitive thermoregulatory transient receptor potential channels under relaxed purifying selection or positive selection in G. japonicus, implying that one of the important factors improve the ability to adapt to climate change.
Seizure dynamotype classification using non-invasive recordings

Objective Recently, a seizure classification approach derived from complex systems and nonlinear dynamics has been suggested, termed the “taxonomy of seizure dynamotypes. ” This framework is based on modeling the dynamical process of the transition in and out of a seizure. It has been examined in computational and animal models in-vitro and recently in human intracranial data. However, its applicability and value in surface EEG remain unclear. This study examined the applicability of dynamotype classification to seizure information extracted from surface EEG and tested how it relates to clinical factors. Methods Surface EEG recordings from 1,215 seizures were analyzed. We used an automated pre-processing pipeline, resulting in independent components (ICs) for each seizure. Subsequently, we visually identified ICs with clear seizure information and classified them based on the suggested taxonomy. To examine the possibility of automatic classification, we applied a random forest classifier combined with EEG features and evaluated its performance in identifying seizure-related ICs and classifying dynamical types. Lastly, we used a Bayesian estimator to examine the likelihood of the different dynamical types under various clinical conditions. Results We found an apparent onset and offset bifurcation in 49.5% and 40.3% of seizures, respectively. Bifurcation prevalence aligns with that previously reported using intracranial data and computational modeling. The automated classifiers, evaluated with a leave-one-patient-out paradigm, provided good performance. In addition, bifurcation prevalence differed between vigilance states and seizure classes. Significance We demonstrated a method to extract seizure information and classify dynamotypes in non-invasive recordings with a visual as well as an automated framework. Extending this classification to a larger scale and a broader population may provide further insights into seizure dynamics. Key Points Box We characterized the dynamical types of transitions at seizure onset and offset based on seizure information extracted from surface EEG. We classified the dynamical types (dynamotypes) in 49.5% and 40.3% of seizure onsets and offsets, respectively. The dynamotype distribution in surface EEG data aligns with previous findings from intracranial EEG and theoretical expectations. The likelihood of the dynamical type of a seizure exhibits differences across clinical seizure classes and vigilance states. Automated detection and classification of seizure bifurcations are possible using relevant features and pre-existing tools.
Stochastic modeling of a gene regulatory network driving B cell development in germinal centers

Germinal centers (GCs) are the key histological structures of the adaptive immune system, responsible for the development and selection of B cells producing high-affinity antibodies against antigens. Due to their level of complexity, unexpected malfunctioning may lead to a range of pathologies, including various malignant formations. One promising way to improve the understanding of malignant transformation is to study the underlying gene regulatory networks (GRNs) associated with cell development and differentiation. Evaluation and inference of the GRN structure from gene expression data is a challenging task in systems biology: recent achievements in single-cell (SC) transcriptomics allow the generation of SC gene expression data, which can be used to sharpen the knowledge on GRN structure. In order to understand whether a particular network of three key gene regulators (BCL6, IRF4, BLIMP1), influenced by two external stimuli signals (surface receptors BCR and CD40), is able to describe GC B cell differentiation, we used a stochastic model to fit SC transcriptomic data from a human lymphoid organ dataset. The model is defined mathematically as a piecewise-deterministic Markov process. We showed that after parameter tuning, the model qualitatively recapitulates mRNA distributions corresponding to GC and plasmablast stages of B cell differentiation. Thus, the model can assist in validating the GRN structure and, in the future, could lead to better understanding of the different types of dysfunction of the regulatory mechanisms.
When cheating turns into a stabilizing mechanism of mutualistic networks

Mutualistic interactions, such as plant-mycorrhizal or plant-pollinator interactions, are widespread in ecological communities and frequently exploited by cheaters, species that profit from interactions without providing benefits in return. Cheating usually negatively affects the fitness of the individuals that are cheated on, but the effects of cheating at the community level remains poorly understood. Here we describe two different kinds of cheating in mutualistic networks and use a generalized Lotka-Volterra model to show that they have very different consequences for the persistence of the community. Conservative cheating, where a species cheats on its mutualistic partners to escape the cost of mutualistic interactions, negatively affects community persistence. In contrast, innovative cheating occurs with species with whom legitimate interactions are not possible, because of a physiological or morphological barrier. Innovative cheating can enhance community persistence under some conditions: when cheaters have few mutualistic partners, cheat at low or intermediate frequency and the cost associated with mutualism is not too high. In this case, the negative effects of cheating on partner persistence are over-compensated at the community level by the positive feedback loops that arise in mutualistic networks. Using an empirical dataset of plant-bird interactions, we found that observed cheating patterns are highly consistent with theoretical cheating patterns found to increase community persistence. This result suggests that the cheating patterns observed in nature could contribute to promote species coexistence in mutualistic communities, instead of necessarily destabilizing them.