Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward a Cell Culture Model of Portal Axis Lipid Handling

The health risks posed by excessive visceral white adipose tissue (WAT) may arise from exposure to deleterious intestinal factors in transit through the portal system. These may include an altered bile acid (BA) pool – particularly with respect to 12α-hydroxylated BA (12-HBA), which we have previously demonstrated are closely associated with insulin resistance. However, given the complexity of the enterohepatic milieu, we have worked to develop a co-culture system that allows for controlled study of the interactions between human induced pluripotent stem cell (hiPSC) derived adipocytes and primary human intestinal organoids (hIO). We present preliminary data on the characterization of both cellular compartments and their interactions, particularly in the context of BA treatment. We have recapitulated the basic functionality of each tissue type and have found reciprocal, potentially important changes in gene expression in each. However, we also have encountered numerous technical challenges in the development of this co-culture system and provide methodological observations to assist others seeking to work with a co-culture system of this type.
High-efficiency transfection of Acanthamoeba castellanii using a cationic polymer

The free-living amoeba Acanthamoeba castellanii is an ecologically, clinically, and evolutionarily important microorganism. A. castellanii amoebae are directly pathogenic to humans and serve as reservoirs for bacterial pathogens (e.g., Legionella pneumophila) but also regulate the proliferation of other microorganisms in the soil. Despite their importance, no reliable genetic system has been developed, hampering the use of A. castellanii and related species as model organisms. Transfecting A. castellanii with plasmids is possible with commercial kits, but it is expensive, inefficient, and vulnerable to product discontinuation. In this contribution, we present a method for efficient transfection of A. castellanii with readily available and inexpensive polyethylenimines. We systematically explore the method’s parameters, obtaining up to 100-fold higher efficiency than currently used protocols. The method presented here provides a robust step towards a complete genetic toolbox for A. castellanii, hence expanding its use as a model organism.
Interfacial atomic structures, energetics and band offsets of Ge:ZrO2 interfaces

Future field effect transistors may use germanium as a high mobility channel material instead of silicon, and high dielectric constant (κ) oxides such as ZrO2 and HfO2 instead of SiO2 as the gate dielectric. First principles calculations of the polar (100) and nonpolar (110) Ge:ZrO2 interfaces are presented. A number of interface configurations that satisfy the valence bonding requirements are constructed and their relaxed structures, total energies, interface electronic states, and band offsets are calculated. For the polar (100) interfaces, the results are quite similar to those of (100) Si:ZrO2. There are numerous semiconducting O-terminated interfaces. The most stable O-terminated interface for a 1×1 surface unit cell has three coordinated oxygen sites. The interface with a tenfold coordinated Zr is the most stable metal-terminated interface, but it is metallic which makes this interface not useful for devices. The band offsets of the O-terminated interfaces have a relatively narrow range, whereas the.
Narrativizing Knowledge Graphs

Any natural language expression of a set of facts – that can be represented as a knowledge graph – will more or less overtly assume a specific perspective on these facts. In this paper we see the conversion of a given knowledge graph into natural language as the construction of a narrative about the assertions made by the knowledge graph. We, therefore, propose a specific pipeline that can be applied to produce linguistic narratives from knowledge graphs using an ontological layer and corresponding rules that turn a knowledge graph into a semantic specification for natural language generation. Critically, narratives are seen as necessarily committing to specific perspectives taken on the facts presented. We show how this most commonly neglected facet of producing summaries of facts can be brought under control.
Reducing Causal Illusions through Deliberate Undersampling

Domain scientists interested in the causal mechanisms are usually limited by the frequency at which they can collect the measurements of social, physical, or biological systems. It is a reasonable assumption that higher frequency is more informative of the causal structure. This assumption is a strong driver for designing new, faster instruments. This task is expensive and often impossible at the current state of technology. In this work, we show that counter to the intuition it is possible for causal systems to improve the estimation of causal graphs from undersampled time-series by augmenting the measurements with those collected at a rate slower than currently available. We present an algorithm able to take advantage of measurement time-scale graphs estimated from data at various sampling rates and lower the underdeterminacy of the system by reducing the equivalence size. We investigate the probability of cases in which deliberate undersampling yields a gain and the size of this gain.
Supplemental Material for the Paper: ShipShape: A Drawing Beautiﬁcation Assistant

The rules are evaluated using a piecewise-linear ramp functions, both continuous and discontinuous. These functions transform the input values, such as angular differences or view-space distances, to likelihood values from the interval [0,1] used to direct the tree expansion and final suggestion sorting described in the paper. For each rule listed in section 3.1 in the main paper, we show the exact scoring function we used in out implementation.
Reduced Expression of PRX2/ATPRX1, PRX8, PRX35, and PRX73 Affects Cell Elongation, Vegetative Growth, and Vasculature Structures in Arabidopsis thaliana

Class III peroxidases (PRXs) are involved in a broad spectrum of physiological and developmental processes throughout the life cycle of plants. However, the specific function of each PRX member in the family remains largely unknown. In this study, we selected four class III peroxidase genes (PRX2/ATPRX1, PRX8, PRX35, and PRX73) from a previous genome-wide transcriptome analysis, and performed phenotypic and morphological analyses, including histochemical staining, in PRX2RNAi, PRX8RNAi, PRX35RNAi, and PRX73RNAi plants. The reduced mRNA levels of corresponding PRX genes in PRX2RNAi, PRX8RNAi, PRX35RNAi, and PRX73RNAi seedlings resulted in elongated hypocotyls and roots, and slightly faster vegetative growth. To investigate internal structural changes in the vasculature, we performed histochemical staining, which revealed alterations in cell wall structures in the main vasculature of hypocotyls, stems, and roots of each PRXRNAi plant compared to wild-type (Col-0) plants. Furthermore, we found that PRX35RNAi plants displayed the decrease in the cell wall in vascular regions, which are involved in downregulation of lignin biosynthesis and biosynthesis-regulated genes’ expression. Taken together, these results indicated that the reduced expression levels of PRX2/ATPRX1, PRX8, PRX35, and PRX73 affected hypocotyl and root elongation, vegetative growth, and the vasculature structures in hypocotyl, stem, and root tissues, suggesting that the four class III PRX genes play roles in plant developmental processes.
Using Relative Projection Density for Classification of Terrestrial Laser Scanning Data with Unknown Angular Resolution

Point cloud classification is a key step for three-dimensional (3D) scene analysis in terrestrial laser scanning but is commonly affected by density variation. Many density-adaptive methods are used to weaken the impact of density variation and angular resolution, which denotes the angle between two horizontally or vertically adjacent laser beams and are commonly used as known parameters in those methods. However, it is difficult to avoid the case of unknown angular resolution, which limits the generality of such methods. Focusing on these problems, we propose a density-adaptive feature extraction method, considering the case when the angular resolution is unknown. Firstly, we present a method for angular resolution estimation called neighborhood analysis of randomly picked points (NARP). In NARP, n points are randomly picked from the original data and the k nearest points of each point are searched to form the neighborhood. The angles between the beams of each picked point and its corresponding neighboring points are used to construct a histogram, and the angular resolution is calculated by finding the adjacent beams of each picked point under this histogram. Then, a grid feature called relative projection density is proposed to weaken the effect of density variation based on the estimated angular resolution. Finally, a 12-dimensional feature vector is constructed by combining relative projection density and other commonly used geometric features, and the semantic label is generated utilizing a Random Forest classifier. Five datasets with a known angular resolution are used to validate the NARP method and an urban scene with a scanning distance of up to 1 km is used to compare the relative projection density with traditional projection density. The results demonstrate that our method achieves an estimation error of less than 0.001° in most cases and is stable with respect to different types of targets and parameter settings. Compared with traditional projection density, the proposed relative projection density can improve the performance of classification, particularly for small-size objects, such as cars, poles, and scanning artifacts.
Building and Analyzing the Brazilian Legal Knowledge Graph

Artificial Intelligence has proven to be effective in streamlining processes in several domains. The Brazilian judiciary, specifically, has a very large number of cases, above the work capacity of the courts, generating urgency in the creation of methods that mainly support the access and manipulation of unstructured data. This paper presents the construction of a Knowledge Graph of the Brazilian Legislation using Semantic Web standards that allows an understanding of how Brazilian laws interact with each other. The Knowledge Graph was quantitatively evaluated using complex network analysis and it was found to be useful to support experts in understanding the Brazilian legislation by detecting special nodes, namely the “bridge-like nodes”, that play an important role in the structure of the graph.
An endogenous growth model with quality ladders and consumers’ heterogeneity

This paper develops an endogenous growth model with quality ladders where consumers heterogeneity is assumed and is modelled through non homothetic preferences. We show that in such a model, unlike mainstream quality ladders models, the steady state equilibrium is characterised by a duopoly were the state of the art technology and the one immediately below it are both able to survive and thrive, under given conditions for the income distribution. In the words of Schumpeter, this model delivers only partial creative destruction. Furthermore, we show that under duopoly, an increase in the degree of income inequality, raises the intensity of research activities and the growth rate of the economy.
Effects of Lewis Number on Conditional Fluid Velocity Statistics in Low Damköhler Number Turbulent Premixed Combustion: A Direct Numerical Simulation Analysis

The effects of global Lewis number Le on the statistics of fluid velocity components conditional in unburned reactants and fully burned products in the context of Reynolds Averaged Navier Stokes simulations have been analysed using a Direct Numerical Simulations (DNS) database of statistically planar turbulent premixed flames with a low Damkohler number and Lewis number ranging from 0.34 to 1.2. The conditional velocity statistics extracted from DNS data have been analysed with respect to the well-known Bray-Moss-Libby (BML) expressions which were derived based on bi-modal probability density function of reaction progress variable for high Damkohler number flames. It has been shown that the Lewis number substantially affects the mean velocity and the velocity fluctuation correlation conditional in products, with the effect being particularly pronounced for low Le. As far as the mean velocity and the velocity fluctuation correlation conditional in reactants are concerned, the BML expressions agree reasonably well with the DNS data reported in the present work. Based on a priori analysis of present and previously reported DNS data, the BML expressions have been empirically modified here in order to account for Lewis number effects, and the non-bimodal distribution of reaction progress variable. Moreover, it has been demonstrated for the first time that surface averaged velocity components and Reynolds stresses conditional in unburned reactants can be modelled without invoking expressions involving the Lewis number, as these surface averaged conditional quantities remain approximately equal to their conditionally averaged counterparts in the unburned mixture.
Magnetic properties and microstructure of Fe-O and Co-O thin films

Iron oxide and cobalt oxide thin films were prepared by reactive DC magnetron sputtering in a mixture of Ar and O/sub 2/ gases. The stoichiometry of the oxide films was studied as a function of the amount of O/sub 2/ during deposition. Sputtering conditions, including dc power and oxygen-to-argon ratio, were found which allowed pure FeO, Fe/sub 3/O/sub 4/, /spl alpha/-Fe/sub 2/O/sub 3/, CoO, and Co/sub 3/O/sub 4/ films to be fabricated. The microstructure of the films, and especially the grain shape and size distribution, were quite different for oxide films with different stoichiometry. The crystallographic axes of Fe-O films were randomly oriented in contrast to Co-O films in which a strong texture was found. A strong ferromagnetic-like behavior was observed in FeO and /spl alpha/-Fe/sub 2/O/sub 3/ films, in contrast to the well-established antiferromagnetic behavior in bulk. The reason for this anomalous behavior is attributed to clusters of defects in FeO films and uncompensated surface spins in /spl alpha/-Fe/sub 2/O/sub 3/ films. A large shift (3800 Oe) was observed in the low temperature hysteresis loop of a field cooled sample consisting of 50% Co and 50% CoO. A similar but less pronounced effect was observed in FeO and /spl alpha/-Fe/sub 2/O/sub 3/ films. This result is believed to be caused by a strong exchange coupling between the ferromagnetic and antiferromagnetic constituents in these composite films.
The Effects of Soccer Specific Exercise on Countermovement Jump Performance in Elite Youth Soccer Players

The aims of the study were to examine the test–retest reliability of force-time (F-T) characteristics and F-T curve waveform of bilateral and unilateral countermovement jumps (CMJ) in elite youth soccer players and to evaluate the effects of competitive match-play on CMJ performance. 16 male youth soccer players completed CMJs on two separate occasions to determine reliability, and immediately pre, post and 48 h following a competitive match. Coefficient of variation (CV%), Intra-class correlation coefficient (ICC) and limits of agreement were used to assess reliability of discreate CMJ variables. Single factor repeated measures ANOVA were used to determine the effects of match play. Statistical parametric mapping was used to evaluate the repeatability of the CMJ force-time waveform and the effects of match play. Jump height had limited reliability in all three jumps and only a select few jump specific F-T variables were found to be reliable (CV < 10%, ICC > 0.5). Select variables were reduced immediately post game but recovered 48 h post game. The F-T curve waveform was found to be repeatable but did not differ following match-play. This study suggest that select F-T variables change following match-play and may be suitable tools to allow practitioners to detect decrements in performance. These data may help inform practitioners to use the most appropriate F-T variables to assess fatigue and recovery, with implications for performance and injury risk.
Current Challenges and Perspectives for the Catalytic Pyrolysis of Lignocellulosic Biomass to High-Value Products

Lignocellulosic biomass is an excellent alternative of fossil source because it is low-cost, plentiful and environmentally friendly, and it can be transformed into biogas, bio-oil and biochar through pyrolysis; thereby, the three types of pyrolytic products can be upgraded or improved to satisfy the standard of biofuel, chemicals and energy materials for industries. The bio-oil derived from direct pyrolysis shows some disadvantages: high contents of oxygenates, water and acids, easy-aging and so forth, which restrict the large-scale application and commercialization of bio-oil. Catalytic pyrolysis favors the refinement of bio-oil through deoxygenation, cracking, decarboxylation, decarbonylation reactions and so on, which could occur on the specified reaction sites. Therefore, the catalytic pyrolysis of lignocellulosic biomass is a promising approach for the production of high quality and renewable biofuels. This review gives information about the factors which might determine the catalytic pyrolysis output, including the properties of biomass, operational parameters of catalytic pyrolysis and different types of pyrolysis equipment. Catalysts used in recent research studies aiming to explore the catalytic pyrolysis conversion of biomass to high quality bio-oil or chemicals are discussed, and the current challenges and future perspectives for biomass catalytic pyrolysis are highlighted for further comprehension.
Gastric Cancer and the Immune System: The Key to Improving Outcomes?

Simple Summary Gastric cancer (GC) is a lethal form of cancer usually arising from the inner mucosa layer of the stomach. The treatment options for gastric cancer often includes surgery and chemotherapy, but recurrent or advanced disease remains difficult to cure. In aiming to improve outcomes, newer immune-based therapies using antibodies and strategically altered immune cells are being studied. This review summarizes the immune system’s role in the GC tumor microenvironment as well as the current research on immunologic therapies specific to GC. Abstract Gastric adenocarcinoma is by far the most common form of gastric cancer (GC) and is a highly lethal form of cancer arising from the gastric epithelium. GC is an important area of focus of the medical community, given its often late-stage of diagnosis and associated high mortality rate. While surgery and chemotherapy remain the primary treatments, attention has been drawn to the use of immunologic therapies, which have shown promise in the treatment of other malignancies. The role for immune-based therapies has become clearer as we obtain a greater understanding of the role of the immune system in gastric cancer formation and growth. A variety treatment to augment the immune system are under evaluation in clinical trials, and these include immune checkpoint inhibitors, antibody-drug conjugates, and immune cell-based therapies. Here, we review the immune landscape and immune-based therapies for GC.
Continual Learning for Time-to-Event Modeling

Temporal point process serves as an essential tool for modeling time-to-event data in continuous time space. Despite having massive amounts of event sequence data from various domains like social media, healthcare etc., real world application of temporal point process are not capable of thriving in continually evolving environment with minimal supervision while retaining previously learnt knowledge. To tackle this, we propose HyperHawkes , a hypernetwork based continually learning temporal point process for continuous modeling of time-to-event sequences with minimal forgetting. We demonstrate the application of the proposed framework through our experiments on two real-world datasets.
Astragaloside IV Alleviates Brain Injury Induced by Hypoxia via the Calpain-1 Signaling Pathway

Long-term hypoxia can induce oxidative stress and apoptosis in hippocampal neurons that can lead to brain injury diseases. Astragaloside IV (AS-IV) is widely used in the antiapoptotic therapy of brain injury diseases. However, its mechanism of action is still not fully understood. In this study, we investigated the effect of AS-IV on hypoxia-induced oxidative stress and apoptosis in hippocampal neurons and explored its possible mechanism. In vivo, mice were placed in a hypoxic circulatory device containing 10% O2 and gavaged with AS-IV (60 and 120 mg/kg/d) for 4 weeks. In vitro, mouse hippocampal neuronal cells (HT22) were treated with hypoxia (1% O2) for 24 hours in the presence or absence of AS-IV, MDL-28170 (calpain-1 inhibitor), or YC-1 (HIF-1α inhibitor). The protective effect of AS-IV on brain injury was further explored by examining calpain-1 knockout mice. The results showed that hypoxia induced damage to hippocampal neurons, impaired spatial learning and memory abilities, and increased oxidative stress and apoptosis. Treatment with AS-IV or calpain-1 knockout improved the damage to hippocampal neurons and spatial learning and memory, attenuated oxidative stress and inhibited cell apoptosis. These changes were verified in HT22 cells. Overexpression of calpain-1 abolished the improvement of AS-IV on apoptosis and oxidative stress. In addition, the effects of AS-IV were accompanied by decreased calpain-1 and HIF-1α expression, and YC-1 showed a similar effect as AS-IV on calpain-1 and caspase-3 expression. In conclusion, this study demonstrates that AS-IV can downregulate the calpain-1/HIF-1α/caspase-3 pathway and inhibit oxidative stress and apoptosis of hippocampal neurons induced by hypoxia, which provides new ideas for studying the antiapoptotic activity of AS-IV.
MILNOR FIBRATIONS AND d-REGULARITY FOR REAL ANALYTIC SINGULARITIES

We study Milnor fibrations of real analytic maps , n ≥ p, with an isolated critical value. We do so by looking at a pencil associated canonically to every such map, with axis V = f-1(0). The elements of this pencil are all analytic varieties with singular set contained in V. We introduce the concept of d-regularity, which means that away from the axis each element of the pencil is transverse to all sufficiently small spheres. We show that if V has dimension 0, or if f has the Thom af-property, then f is d-regular if and only if it has a Milnor fibration on every sufficiently small sphere, with projection map f/‖f‖. Our results include the case when f has an isolated critical point. Furthermore, we show that if f is d-regular, then its Milnor fibration on the sphere is equivalent to its fibration on a Milnor tube. To prove these fibration theorems we introduce the spherefication map, which is rather useful to study Milnor fibrations. It is defined away from V; one of its main properties is that it is a submersion if and only if f is d-regular. Here restricted to each sphere in ℝn the spherefication gives a fiber bundle equivalent to the Milnor fibration.
Advances in asynchronous and decentralized estimation

Two key challenges associated with fusion of information in large-scale systems are the asynchronous nature of information flow and the consistency requirements associated with decentralized processing. This paper provides contributions in both these areas. First, we build on an existing minimum variance estimation algorithm for out-of-sequence processing of sensor measurements, extending the algorithm to handle multiple lags and multiple dynamic models. We study the performance of the algorithms with numerical examples. Second, we establish a connection between the maximum entropy of a partially known multivariable Gaussian distribution and a particular Bayesian network, whose structure is based on the available information. The connection leads to a useful methodology for identifying missing information in systems described by Bayesian networks, a key tool in developing algorithms for information flow in decentralized systems.