Miracle-dz/UniFAR-FTUs huggingface dataset:
A contour-based approach to the multimode network representation of waveguide transitions

A flexible and efficient numerical method is presented by which the multimode network representation (MMNR) of the abrupt transition between a standard waveguide and a waveguide of arbitrary cross section can be established without reference to the cross-sectional fields. The approach combines the boundary integral-equation method (BIEM) with contour integral expressions for the coupling coefficients, and a novel highly efficient scheme to express modal normalization constants in terms of coupling coefficients and eigenvalues. Application is demonstrated for a variety of multiridge circular waveguide (MRCW) configurations and transitions between MRCW and circular waveguide (CW). Comparison is made against most published results for this problem.
Title: Evaluation of the disease-modifying effects of Aureobasidium pullulans AFO-202 strain produced Beta-Glucan in Parkinson’s disease – Results of a pilot clinical study Running title: AFO-202 beta glucan for Parkinson’s disease Authors: Chockanathan Vetrievel1 (drvetri@bewellhospitals.com)

Authors: Chockanathan Vetrievel1 (drvetri@bewellhospitals.com) Allimuthu Nithyanandam2 (vellorenithya@gmail.com) Subramaniam Srinivasan3 (masala76@gmail.com) Sudhakar S Bharatidasan4 (drsudhakar77@gmail.com) Vidyasagar Devaprasad Dedeepiya3 (drddp@nichimail.jp) Nobunao Ikewaki5,6 (nikewaki@phoenix.ac.jp) Masaru Iwasaki7 (miwasaki@yamanashi.ac.jp) Rajappa Senthilkumar8,9 (rsk@nichimail.jp) Senthilkumar Preethy8 (drspp@nichimail.jp) Samuel JK Abraham3,7,9,10 (drsam@nichimail.jp)
Lateral mammillary body neurons in mouse brain are disproportionately vulnerable in Alzheimer’s disease

The neural circuits governing the induction and progression of neurodegeneration and memory impairment in Alzheimer’s disease (AD) are incompletely understood. The mammillary body (MB), a subcortical node of the medial limbic circuit, is one of the first brain regions to exhibit amyloid deposition in the 5xFAD mouse model of AD. Amyloid burden in the MB correlates with pathological diagnosis of AD in human postmortem brain tissue. Whether and how MB neuronal circuitry contributes to neurodegeneration and memory deficits in AD are unknown. Using 5xFAD mice and postmortem MB samples from individuals with varying degrees of AD pathology, we identified two neuronal cell types in the MB harboring distinct electrophysiological properties and long-range projections: lateral neurons and medial neurons. lateral MB neurons harbored aberrant hyperactivity and exhibited early neurodegeneration in 5xFAD mice compared with lateral MB neurons in wild-type littermates. Inducing hyperactivity in lateral MB neurons in wild-type mice impaired performance on memory tasks, whereas attenuating aberrant hyperactivity in lateral MB neurons ameliorated memory deficits in 5xFAD mice. Our findings suggest that neurodegeneration may be a result of genetically distinct, projection-specific cellular dysfunction and that dysregulated lateral MB neurons may be causally linked to memory deficits in AD. Description Mouse lateral mammillary body neurons exhibit hyperactivity in Alzheimer’s disease and may be involved in memory loss. A vulnerable neuronal subtype in Alzheimer’s disease How brain neural circuit dysfunction, pathological insults, and the demise of neurons drive memory deficits in Alzheimer’s disease (AD) remains poorly understood. The mammillary body, a subregion of the hypothalamus, exhibits early amyloid deposition in the 5xFAD mouse model of AD. In a new study, Huang et al. used single-cell RNA sequencing of postmortem brain sections of mouse mammillary body and brain slice electrophysiology to show that lateral mammillary body neurons of 5xFAD mice harbored aberrant hyperactivity that correlated with impaired memory in two behavioral tests compared with wild-type littermate control animals. These findings implicate this neuronal subtype in the pathogenesis of AD. —OS
Statistical investigation of errors in particle image velocimetry

The accuracy of the particle image velocimetry technique was investigated using synthetic images having known characteristics. Algorithms were developed to extract two-dimensional velocity information by tracking particles between successive frames of a movie automatically without operator assistance. This allowed to parametrically investigate the influence of the various parameters (image contrast, image noise, particle density, distribution of sizes of particles and particle displacement between frames) on the accuracy of the technique. It was found that as long as the images have a good contrast, particle locations can be determined with sub-pixel accuracy and particle velocities can be determined within a few percent.
Vers une algèbre des relations de discours pour la comparaison de structures discursives

Nous proposons une méthodologie pour la construction de règles de déduction de relations de discours, destinées à être intégrées dans une algèbre de ces relations. La construction de ces règles a comme principal objectif de pouvoir calculer la fermeture discursive d’une structure de discours, c’est-à-dire de déduire toutes les relations que la structure contient implicitement. Calculer la fermeture des structures discursives peut permettre d’améliorer leur comparaison, notamment dans le cadre de l’évaluation de systèmes d’analyse automatique du discours. Nous présentons la méthodologie adoptée, que nous illustrons par l’étude d’une règle de déduction.
The Prairie Peninsula and Climate Change

ABSTRACT Transition and recovery from prolonged effects of climate change on an ecosystem will be affected by geography, topography, and plant physiology. Fire, grazing, flooding, succession, biodiversity, invasive species, and stewardship all affect the “resilience” (the capacity to recover) of an ecosystem to the effects of long-term changes in weather patterns. These significant “controls” should be part of climate change discussions. Research from various disciplines suggests that the actions of humans on the landscape minimized and/or ameliorated some of the impacts of past changes in climate. Today, stewardship and restoration efforts may mitigate some of the effects of climate change, especially in fire-dependent natural communities.
Should Ipsdienol and Ipsenol Lures be Retained in a Generic Trap Lure Blend for Pine Bark and Woodboring Beetles (Coleoptera) in the Southeastern United States?

Abstract Trap lure blends that maximize the diversity of captured insect species help to reduce the costs of detection programs that target native and nonnative invasive species of bark and woodboring beetles. In 2007, the effects of the bark beetle pheromones ipsdienol and ipsenol on catches of beetles (Coleoptera) in multiple-funnel traps baited with ethanol + α-pinene were evaluated in a trapping study in one stand of mature loblolly pine, Pinus taeda L. , in northcentral Georgia. Ipsenol and/or ipsdienol increased catches of Acanthocinus obsoletus (LeConte) and Monochamus titillator (F.) (Cerambycidae), Ips avulsus (Eichhoff), Ips calligraphus (Germar), Ips grandicollis (Eichhoff) (Curculionidae), Temnoscheila virescens (F.), and Aulonium tuberculatum (LeConte) (Zopheridae) in traps baited with ethanol and α-pinene. However, catches of most species in traps baited with ipsenol + ipsdienol were the same as those baited with either ipsenol or ipsdienol alone. Only catches of I. avulsus were greatest in traps baited with both ipsdienol and ipsenol. Catches of Thanasimus dubius (F.) (Cleridae), Platysoma spp. (Histeridae), and Lasconotus spp. (Zopheridae) increased with the addition of ipsenol but decreased with the addition of ipsdienol. In contrast, catches of Orthotomicus caelatus (Eichhoff) (Curculionidae) increased with the addition of ipsdienol; attraction was interrupted by the addition of ipsenol. A number of trade-offs exist in retaining ipsdienol and/or ipsenol in the multicomponent pine lure blend for detection programs in Georgia.
New Families of Embedded Triply Periodic Minimal Surfaces of Genus Three in Euclidean Space

Until 1970, all known examples of embedded triply periodic minimal surfaces (ETPMS) contained either straight lines or curves of planar symmetry. In 1970, Alan Schoen discovered the gyroid, an ETPMS that contains neither straight lines nor planar symmetry curves. Meeks discovered in 1975 a 5-parameter family of genus 3 ETPMS that contained all known examples of genus 3 ETPMS except the gyroid. A second example lying outside the Meeks family was proposed by Lidin in 1990. Große-Brauckmann and Wohlgemuth showed in 1996 the existence and embeddedness of the gyroid and “Lidinoid”. In a series of investigations the scientists, Lidin, et. al., numerically indicate the existence of two 1-parameter families of ETPMS that contain the gyroid and one family that contains the Lidinoid. In this thesis, we prove the existence of these families. To prove the existence of these families, we describe the Riemann surface structure using branched covers of non-rectangular tori. The holomorphic 1-forms Gdh, 1 Gdh, and dh each place a cone metric on the torus; we develop the torus with this metric into the plane and describe the periods in terms of these flat structures. Using this description of the periods, we define moduli spaces for the horizontal and vertical period problems so that Weierstraß data (X, G, dh) solves the period problem if the flat structures of X induced by these 1-forms are in the moduli spaces. To show that there is a curve of suitable data, we use an intermediate value type argument.
High‐resolution simulated water balance and streamflow data set for 1951–2020 for the territory of Poland

Long‐term simulated water balance and streamflow data for the territory of Poland with high spatio‐temporal resolution were reconstructed for the period 1951–2020 with a daily time step, using the Soil and Water Assessment Tool (SWAT) hydrological model. The spatial structure includes 4,381 sub‐basins and 47,725 hydrological response units. The SWAT model was extensively calibrated and validated following a two‐stage, multi‐site calibration method for 88 gauging stations across Poland. The simulations show satisfactory performance with a median Kling–Gupta efficiency of 0.73 and 0.7 in the calibration and validation period respectively. The model performance exceeded that of its predecessor, the SWAT model of the Vistula and Odra basins. The simulated hydrological data set covers daily water balance components at the sub‐basin level, including precipitation total, snowfall, snowmelt, evapotranspiration (actual and potential), surface runoff, soil water, percolation, groundwater recharge, groundwater flow, tile flow and water yield (all components in mm), and daily streamflow (m3/s) at the reach level. The data set is stored in an online, publicly available research data archive 4TU.Research Data (Marcinkowski, P., Kardel, I., Płaczkowska, E., Giełczewski, M., Osuch, P., Okruszko, T., Venegas‐Cordero, N., Ignar, S. & Piniewski, M (2021). PL‐SWAT‐51_20: a high‐resolution simulated water balance and streamflow data set for 1951‐2020 for the territory of Poland, 4TU.ResearchData. dataset, https://doi.org/10.4121/16843183).
Multidimensional responses of ecological stability to eutrophication in grasslands

Eutrophication usually impacts biodiversity, species composition, and functioning of grassland communities. Whether such effects propagate to influence the stability of these community aspects is unknown. Using standardized experiments across 55 global grasslands, we quantified the effects of nutrient addition on five stability facets (i.e., temporal invariability and resistance during and recovery after dry and wet growing seasons) for three community aspects (i.e., aboveground biomass, community composition, and species richness). Nutrient addition reduced the temporal invariability and resistance of species richness and community composition, but not biomass, during dry and wet growing seasons. Temporal invariability and resistance during, but not recovery after, dry and wet growing seasons were strongly positively correlated in both ambient and eutrophic conditions. This indicates that maintaining and restoring the stability of plant communities requires increasing resistance rather than recovery. Harnessing the complexity of ecological stability provides new insights for grassland ecosystem sustainability in a changing world.
Ecological genomics in the Northern krill uncovers loci for local adaptation across ocean basins

Krill is a vital food source for many marine animals but also strongly impacted by climate change. Genetic adaptation could support populations, but remains uncharacterized. We assembled the 19 Gb Northern krill genome and compared genome-scale variation among 74 specimens from the colder Atlantic Ocean and warmer Mediterranean Sea. The genome is dominated by methylated transposable elements and contains many duplicated genes implied in molting and vision. Analysis of 760 million SNPs indicates extensive homogenizing gene-flow among populations. Nevertheless, we detect extreme divergence across hundreds of genes, governing ecophysiological functions like photoreception, circadian regulation, reproduction and thermal tolerance. Such standing variation may be essential for resilience in zooplankton, necessitating insight into adaptive variation to forecast their roles in future marine ecosystems and support ocean conservation. One-Sentence Summary Genome-scans of Northern krill link genes for photoreception, reproduction and thermal tolerance to ecological adaptation.
Reproducibility of biophysical in silico neuron states and spikes from event-based partial histories

Biophysically detailed simulations attempting to reproduce neuronal activity often rely on solving large systems of differential equations; in some models, these systems have tens of thousands of states per cell. Numerically solving these equations is computationally intensive and requires making assumptions about the initial cell states. Additional realism from incorporating more biological detail is achieved at the cost of increasingly more states, more computational resources, and more modeling assumptions. We show that for both point and morphologically-detailed cell models, the presence and timing of future action potentials is probabilistically well-characterized by the relative timings of a small number of recent synaptic events alone. Knowledge of initial conditions or full synaptic input history is not a requirement. While model time constants, etc. impact the specifics, we demonstrate that for both individual spikes and sustained cellular activity, the uncertainty in spike response decreases to the point of approximate determinism. Further, we show cellular model states are reconstructable from ongoing synaptic events, despite unknown initial conditions. We propose that a strictly event-based modeling framework is capable of representing the full complexity of cellular dynamics of the differential-equations models with significantly less per-cell state variables, thus offering a pathway toward utilizing modern data-driven modeling to scale up to larger network models while preserving individual cellular biophysics.
The enemy of my enemy is my friend: a plausible defense mechanism against antagonism in bacterial communities

In a recent work we studied an artificial bacterial community where resistant bacteria assisted sensitive bacteria in surviving in the presence of antagonistic bacteria. Typically, this behavior is attributed to lateral gene exchange. However, we identified evidence of a distinct mechanism, which operates on the principle of “the enemy of my enemy is my friend”. Here, we explore the viability of this mechanism by means of a reaction-diffusion mathematical model. Our findings suggest that this mechanism is feasible under specific circumstances, particularly when bacteria undergo significant metabolic changes at high population densities. Author summary The importance of studying the formation of bacterial communities cannot be overstated. Initially, it was believed that the environment alone determined the assembly of these communities, but recent research has demonstrated that interactions among members of the community also have a crucial impact. For instance, it has been observed in some cases that, even when susceptible bacteria are confronted with antagonism, they can survive with the aid of resistant bacteria. Lateral gene exchange is typically considered the underlying mechanism responsible for this phenomenon. However, we identified in a recent work an alternative mechanism that does not involve gene exchange but operates on the principle of “the enemy of my enemy is my friend”. Using a mathematical model, we examine the plausibility of this mechanism in a small artificial bacterial community. Our results indicate that this mechanism alone cannot account for all the experimental observations, but including the assumption that bacteria undergo significant metabolic changes at high concentrations may suffice.
Structural and mechanistic insights into the MCM8/9 helicase complex

MCM8 and MCM9 form a functional helicase complex (MCM8/9) that plays an essential role in DNA homologous recombination repair for DNA double-strand break. However, the structural characterization of MCM8/9 for DNA binding/unwinding remains unclear. Here, we report structures of the MCM8/9 complex using cryo-electron microscopy single particle analysis. The structures reveal that MCM8/9 is arranged into a heterohexamer through a three-fold symmetry axis, creating a central channel that accommodates DNA. Multiple characteristic hairpins from the N-terminal oligosaccharide/oligonucleotide (OB) domains of MCM8/9 protrude into the central channel and serve to unwind the duplex DNA. When activated by HROB, the structure of MCM8/9’s N-tier ring converts its symmetry from C3 to C1 with a conformational change that expands the MCM8/9’s trimer interface. Moreover, our structural dynamic analyses revealed that the flexible C-tier ring exhibited rotary motions relative to the N-tier ring, which is required for the unwinding ability of MCM8/9. In summary, our structural and biochemistry study provide a basis for understanding the DNA unwinding mechanism of MCM8/9 helicase in homologous recombination.
Formation and Analysis of Gene Expression Data Based on the Joint Use of Data Mining and Machine Learning Techniques

Creating a system of complex disease diagnosis based on gene expression data using modern data mining and machine learning techniques is one of the topical areas of recent bioinformatics. The main problem in this subject area consists of a large volume of experimental data; each investigated object contains approximately 20000 genes. In this paper, we propose the technique of both formation and analysis of gene expression data based on the joint use of various computational and intelligent methods of complex data processing. As the experimental data, we use the gene expression data of patients who were investigated for various types of cancer diseases. Initially, the data was formed and analyzed using the functions and modules of TCGAbiolinks and Bioconductor packages. Then, the non-informative genes in terms of both the statistical and entropy criteria were removed from the initial database. To identify the level of significance of gene expression profiles, we have applied the general Harrington desirability index, which contains, as the components, transformed statistical and entropies criteria. Finally, we applied the random forest classifier and convolutional neural network with the calculation of various types of classification quality criteria for the binary and multi-classification of the investigated objects in the first and the second cases, respectively. Analyzing the simulation results has shown that the identification accuracy of the examined samples is high in all cases. To our mind, the proposed technique creates the basis for improving complex disease diagnosis systems based on gene expression data.
Transcriptomic analysis during fruit development of the oil palm revealed specific isozymes related to starch metabolism that control oil yield

The oil palm (Elaeis guineensis Jacq.) produces a large amount of oil from the fruit. A recent study has shown that starch metabolism is essential for oil synthesis in fruit-producing species. Therefore, we detected gene expression changes related to starch metabolism genes throughout the maturity stages of oil palm fruit with different oil yields. Gene expression profiles were examined with three different oil yields (low, medium, and high) at six fruit development phases (4, 8, 12, 16, 20, and 22 weeks after pollination). Using RNA-seq analysis, we successfully identified and analyzed differentially expressed genes in oil palm mesocarps during development. The results showed that the transcriptome profile for each developmental phase was unique. Additionally, we found that starch synthesis and degradation occurred during fruit development and influenced oil production. Sucrose flux to the mesocarp tissue, rapid starch turnover, and high glycolytic activity have been identified as critical factors for oil production in oil palms. For starch metabolism and the glycolytic pathway, we identified specific enzyme isoforms (isozymes) that may control the oil production. This study provides valuable information for creating new high-oil-yielding palm varieties via breeding programs or genome editing approaches.
SPADE: Spatial Deconvolution for Domain Specific Cell-type Estimation

The advent of spatial transcriptomics technology has allowed for the acquisition of gene expression profiles with multi-cellular resolution in a spatially resolved manner, presenting a new milestone in the field of genomics. However, the aggregate gene expression from heterogeneous cell types obtained by these technologies poses a significant challenge for a comprehensive delineation of cell type-specific spatial patterns. Here, we propose SPADE (SPAtial DEconvolution), an in-silico method designed to address this challenge by incorporating spatial patterns during cell type decomposition. SPADE utilizes a combination of single-cell RNA sequencing data, spatial location information, and histological information to computationally estimate the proportion of cell types present at each spatial location. In our study, we showcased the effectiveness of SPADE by conducting analyses on synthetic data. Our results indicated that SPADE was able to successfully identify cell type-specific spatial patterns that were not previously identified by existing deconvolution methods. Furthermore, we applied SPADE to a real-world dataset analyzing the developmental chicken heart, where we observed that SPADE was able to accurately capture the intricate processes of cellular differentiation and morphogenesis within the heart. Specifically, we were able to reliably estimate changes in cell type compositions over time, which is a critical aspect of understanding the underlying mechanisms of complex biological systems. These findings underscore the potential of SPADE as a valuable tool for analyzing complex biological systems and shedding light on their underlying mechanisms. Taken together, our results suggest that SPADE represents a significant advancement in the field of spatial transcriptomics, providing a powerful tool for characterizing complex spatial gene expression patterns in heterogeneous tissues.