Miracle-dz/UniFAR-FTUs huggingface dataset:
Integration of Biochemical, Biophysical and Transcriptomics Data for Investigating the Structural and Nanomechanical Properties of the Yeast Cell Wall

The yeast cell is surrounded by a cell wall conferring protection and resistance to environmental conditions that can be harmful. Identify the molecular cues (genes) which shape the biochemical composition and the nanomechanical properties of the cell wall and the links between these two parameters represent a major issue in the understanding of the biogenesis and the molecular assembly of this essential cellular structure, which may have consequences in diverse biotechnological applications. We addressed this question in two ways. Firstly, we compared the biochemical and biophysical properties using atomic force microscopy (AFM) methods of 4 industrial strains with the laboratory sequenced strain BY4743 and used transcriptome data of these strains to infer biological hypothesis about differences of these properties between strains. This comparative approach showed a 4–6-fold higher hydrophobicity of industrial strains that was correlated to higher expression of genes encoding adhesin and adhesin-like proteins and not to their higher mannans content. The second approach was to employ a multivariate statistical analysis to identify highly correlated variables among biochemical, biophysical and genes expression data. Accordingly, we found a tight association between hydrophobicity and adhesion events that positively correlated with a set of 22 genes in which the main enriched GO function was the sterol metabolic process. We also identified a strong association of β-1,3-glucans with contour length that corresponds to the extension of mannans chains upon pulling the mannosyl units with the lectin-coated AFM tips. This association was positively correlated with a group of 27 genes in which the seripauperin multigene family was highly documented and negatively connected with a set of 23 genes whose main GO biological process was sulfur assimilation/cysteine biosynthetic process. On the other hand, the elasticity modulus was found weakly associated with levels of β-1,6-glucans, and this biophysical variable was positively correlated with a set of genes implicated in microtubules polymerization, tubulin folding and mitotic organization.
Swept Source Lasers for OCT — Light Source Technology Enhancing Imaging Speed

In the last 25 years, optical coherence tomography (OCT) has advanced to be one of the most innovative and most successful translational optical imaging techniques, achieving substantial economic impact as well as clinical acceptance. This is largely owing to the resolution improvements by a factor of 10 to the submicron regime and to the imaging speed increase by more than half a million times to more than 5 million A-scans per second, with the latter one accomplished by the state-of-the-art swept source laser technologies that are reviewed in this article. In addition, parallelization of OCT detection, such as line-field and full-field OCT, has shortened the acquisition time even further by establishing quasi-akinetic scanning. Besides the technical improvements, several functional and contrast-enhancing OCT applications have been investigated, among which the label-free angiography shows great potential for future studies. Finally, various multimodal imaging modalities with OCT incorporated are reviewed, in that these multimodal implementations can synergistically compensate for the fundamental limitations of OCT when it is used alone. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. [DOI: 10.1117/1.JBO. 19.7. 071412]
Bone-Seeking Matrix Metalloproteinase-2 Inhibitors Prevent Bone Metastatic Breast Cancer Growth

Bone metastasis is common during breast cancer progression. Matrix metalloproteinase-2 (MMP-2) is significantly associated with aggressive breast cancer and poorer overall survival. In bone, tumor- or host-derived MMP-2 contributes to breast cancer growth and does so by processing substrates, including type I collagen and TGFβ latency proteins. These data provide strong rationale for the application of MMP-2 inhibitors to treat the disease. However, in vivo, MMP-2 is systemically expressed. Therefore, to overcome potential toxicities noted with previous broad-spectrum MMP inhibitors (MMPIs), we used highly selective bisphosphonic-based MMP-2 inhibitors (BMMPIs) that allowed for specific bone targeting. In vitro, BMMPIs affected the viability of breast cancer cell lines and osteoclast precursors, but not osteoblasts. In vivo, we demonstrated using two bone metastatic models (PyMT-R221A and 4T1) that BMMPI treatment significantly reduced tumor growth and tumor-associated bone destruction. In addition, BMMPIs are superior in promoting tumor apoptosis compared with the standard-of-care bisphosphonate, zoledronate. We demonstrated MMP-2–selective inhibition in the bone microenvironment using specific and broad-spectrum MMP probes. Furthermore, compared with zoledronate, BMMPI-treated mice had significantly lower levels of TGFβ signaling and MMP-generated type I collagen carboxy-terminal fragments. Taken together, our data show the feasibility of selective inhibition of MMPs in the bone metastatic breast cancer microenvironment. We posit that BMMPIs could be easily translated to the clinical setting for the treatment of bone metastases given the well-tolerated nature of bisphosphonates. Mol Cancer Ther; 16(3); 494–505. ©2017 AACR.
Indoor localization using magnetic field anomalies and inertial measurement units based on Monte Carlo localization

Localization in indoor environments has become increasingly important for various applications which require precise indoor tracking and navigation. In this paper, a system employing magnetic field anomalies and inertial navigation systems is proposed to address the problem of indoor localization. The proposed system consists of a network of magnetometers, inertial measurement units (accelerometer and gyroscope) and motion detection as well as nearest neighbors algorithms incorporated inside Monte Carlo localization (MCL). From the experiments performed, it is found that every location in a given indoor environment has its own almost unique magnetic field value. And by integrating this local variation of magnetic field with MCL algorithm, infrastructure independent indoor localization system is presented. Furthermore, the simulation results show effective indoor localization is possible using the proposed techniques.
Analytical multi‐parametric stability boundaries of DC‐DC buck converters under V1 control concept

Two main methods for controlling switching converters exist in the literature. The direct one is the voltage mode control, which suffers from some disadvantages such as slow response to load variations and an input voltage‐dependent total loop gain. The current mode control can overcome these problems but at the expense of extra cost and more complex control design. V1 concept is a new promising control technique for designing voltage mode control of buck‐type converters with an optimal response similar to current mode control. In this paper, the dynamics and the stability of buck converters under V1 control are studied. In particular, subharmonic oscillation limits in the parameter space are addressed. First, a closed‐loop state‐space model is derived and then used to formulate an analytical matrix‐form expression for predicting the stability limit of the system. Using this expression, multi‐parametric stability boundaries are obtained. It is shown that the equivalent series inductance of the output capacitor can narrow the stability region. It is also demonstrated that the integral action in the feedback loop of a V1‐controlled buck converter has a negligible effect on the subharmonic oscillation boundary. The theoretical analysis is validated through numerical simulation of the circuit‐level switched model of the system. Copyright © 2017 John Wiley & Sons, Ltd.
Critical Lines in Gravitational Lenses and the Determination of Cosmological Parameters

We investigate the cosmological test recently done by Fort, Mellier, & Dantel-Fort (FMD), in which the observed location of the critical line in gravitational lensing is used to determine the cosmological parameters Ω and λ. Applying this method to the cluster of galaxies Cl 0024+1654, FMD obtained a bound on the cosmological constant, λ > 0.6, assuming the spatially flat universe. The fact that the angular diameter distance-redshift relation depends on the cosmological models through the cosmological parameters plays a crucial role in this method. Using the angular diameter distance in the Friedmann-Lemaître-Robertson-Walker universe for a wide range of cosmological parameters, we show that it is difficult to determine Ω by this method without the assumption of the spatially flat universe. Moreover, the uncertainty of the lens model is also mentioned, which is regarded as one of the most serious problems in this test. As a result, this method cannot be taken as a clear cosmological test to determine λ, although one may put a bound on λ by the use of many clusters of galaxies.
Challenges to Practicing HIV Sex-Risk Prevention Among People in Continuing Care for Cocaine Addiction

ABSTRACT Background: Intimate partnerships are discouraged during early recovery, despite research that highlights their capacity to be resources for change. Objective: This study seeks to provide descriptions of intimate partnerships and how such partnerships challenge and/or support minimizing HIV sex-risk among participants in continuing care for cocaine addiction in order to inform substance use programming. Methods: Forty-two recorded continuing care counseling sessions of 33 people who discussed HIV sex-risk behavior were transcribed and analyzed using thematic analysis. This sample was derived from a larger randomized controlled trial that looked at the impact of a continuing care intervention for people with cocaine use problems. Results: Although participants expressed the desire for a primary intimate partnership, casual intimate partnerships that often involved HIV sex-risk behavior were more prevalent. Challenges to having a primary intimate partner included the belief that intimate partnerships do not support recovery, difficulty in developing friendships with women among heterosexual men, and the ubiquity of drug use and sex work in home environments with limited economic opportunity. Despite these challenges, some participants reported having primary intimate partners that supported their recovery through open communication. Conclusion: Clinicians providing substance use interventions can consider encouraging components of intimate partnerships that support recovery. In addition, the strong environmental influence on individual HIV sex-risk behavior should be considered in delivering any substance use intervention.
Body Mass Index and Sex Affect Diverse Microbial Niches within the Gut

Gut microbiota is considered a separate organ with endocrine capabilities, actively contributing to tissue homeostasis. It consists of at least two separate microbial populations, the lumen-associated (LAM) and the mucosa-associated microbiota (MAM). In the present study, we compared LAM and MAM, by collecting stools and sigmoid brush samples of forty adults without large-bowel symptoms, and through a 16S rRNA gene next-generation sequencing (NGS) approach. MAM sample analysis revealed enrichment in aerotolerant Proteobacteria, probably selected by a gradient of oxygen that decreases from tissue to lumen, and in Streptococcus and Clostridium spp. , highly fermenting bacteria. On the other hand, LAM microbiota showed an increased abundance in Bacteroides, Prevotella, and Oscillospira, genera able to digest and to degrade biopolymers in the large intestine. Predicted metagenomic analysis showed LAM to be enriched in genes encoding enzymes mostly involved in energy extraction from carbohydrates and lipids, whereas MAM in amino acid and vitamin metabolism. Moreover, LAM and MAM communities seemed to be influenced by different host factors, such as diet and sex. LAM is affected by body mass index (BMI) status. Indeed, BMI negatively correlates with Faecalibacterium prausnitzii and Flavonifractor plautii abundance, putative biomarkers of healthy status. In contrast, MAM microbial population showed a significant grouping according to sex. Female MAM was enriched in Actinobacteria (with an increased trend of the genus Bifidobacterium), and a significant depletion in Veillonellaceae. Interestingly, we found the species Gemmiger formicilis to be associated with male and Bifidobacterium adolescentis, with female MAM samples. In conclusion, our results suggest that gut harbors microbial niches that differ in both composition and host factor susceptibility, and their richness and diversity may be overlooked evaluating only fecal samples.
Distribution and Causes of Global Forest Fragmentation

Because human land uses tend to expand over time, forests that share a high proportion of their borders with anthropogenic uses are at higher risk of further degradation than forests that share a high proportion of their borders with non-forest, natural land cover (e.g., wetland). Using 1-km advanced very high resolution radiometer (AVHRR) satellite-based land cover, we present a method to separate forest fragmentation into natural and anthropogenic components, and report results for all inhabited continents summarized by World Wildlife Fund biomes. Globally, over half of the temperate broadleaf and mixed forest biome and nearly one quarter of the tropical rainforest biome have been fragmented or removed by humans, as opposed to only 4% of the boreal forest. Overall, Europe had the most human-caused fragmentation and South America the least. This method may allow for improved risk assessments and better targeting for protection and remediation by identifying areas with high amounts of human-caused fragmentation.
A Theory of Sequence Indexing and Working Memory in Recurrent Neural Networks

To accommodate structured approaches of neural computation, we propose a class of recurrent neural networks for indexing and storing sequences of symbols or analog data vectors. These networks with randomized input weights and orthogonal recurrent weights implement coding principles previously described in vector symbolic architectures (VSA) and leverage properties of reservoir computing. In general, the storage in reservoir computing is lossy, and crosstalk noise limits the retrieval accuracy and information capacity. A novel theory to optimize memory performance in such networks is presented and compared with simulation experiments. The theory describes linear readout of analog data and readout with winner-take-all error correction of symbolic data as proposed in VSA models. We find that diverse VSA models from the literature have universal performance properties, which are superior to what previous analyses predicted. Further, we propose novel VSA models with the statistically optimal Wiener filter in the readout that exhibit much higher information capacity, in particular for storing analog data. The theory we present also applies to memory buffers, networks with gradual forgetting, which can operate on infinite data streams without memory overflow. Interestingly, we find that different forgetting mechanisms, such as attenuating recurrent weights or neural nonlinearities, produce very similar behavior if the forgetting time constants are matched. Such models exhibit extensive capacity when their forgetting time constant is optimized for given noise conditions and network size. These results enable the design of new types of VSA models for the online processing of data streams.
Multicompartment magnetic resonance fingerprinting

Magnetic resonance fingerprinting (MRF) is a technique for quantitative estimation of spin-relaxation parameters from magnetic-resonance data. Most current MRF approaches assume that only one tissue is present in each voxel, which neglects intravoxel structure, and may lead to artifacts in the recovered parameter maps at boundaries between tissues. In this work, we propose a multicompartment MRF model that accounts for the presence of multiple tissues per voxel. The model is fit to the data by iteratively solving a sparse linear inverse problem at each voxel, in order to express the measured magnetization signal as a linear combination of a few elements in a precomputed fingerprint dictionary. Thresholding-based methods commonly used for sparse recovery and compressed sensing do not perform well in this setting due to the high local coherence of the dictionary. Instead, we solve this challenging sparse-recovery problem by applying reweighted--norm regularization, implemented using an efficient interior-point method. The proposed approach is validated with simulated data at different noise levels and undersampling factors, as well as with a controlled phantom-imaging experiment on a clinical magnetic-resonance system.
Evidence for Ancient Origins of Bowman-Birk Inhibitors from Selaginella moellendorffii

A sequence from spikemoss uncovers the true extent of the Bowman-Birk Inhibitor family to be wider than cereals and legumes, solving a long-standing mystery about their origins. Bowman-Birk Inhibitors (BBIs) are a well-known family of plant protease inhibitors first described 70 years ago. BBIs are known only in the legume (Fabaceae) and cereal (Poaceae) families, but peptides that mimic their trypsin-inhibitory loops exist in sunflowers (Helianthus annuus) and frogs. The disparate biosynthetic origins and distant phylogenetic distribution implies these loops evolved independently, but their structural similarity suggests a common ancestor. Targeted bioinformatic searches for the BBI inhibitory loop discovered highly divergent BBI-like sequences in the seedless, vascular spikemoss Selaginella moellendorffii. Using de novo transcriptomics, we confirmed expression of five transcripts in S. moellendorffii whose encoded proteins share homology with BBI inhibitory loops. The most highly expressed, BBI3, encodes a protein that inhibits trypsin. We needed to mutate two lysine residues to abolish trypsin inhibition, suggesting BBI3’s mechanism of double-headed inhibition is shared with BBIs from angiosperms. As Selaginella belongs to the lycopod plant lineage, which diverged ∼200 to 230 million years before the common ancestor of angiosperms, its BBI-like proteins imply there was a common ancestor for legume and cereal BBIs. Indeed, we discovered BBI sequences in six angiosperm families outside the Fabaceae and Poaceae. These findings provide the evolutionary missing links between the well-known legume and cereal BBI gene families.
Calculating Groundwater Response Times for Flow in Heterogeneous Porous Media

Predicting the amount of time required for a transient groundwater response to take place is a practical question that is of interest in many situations. This time scale is often called the response time. In the groundwater hydrology literature, there are two main methods used to calculate the response time: (1) both the transient and steady‐state groundwater flow equations are solved, and the response time is taken to be amount of time required for the transient solution to approach the steady solution within some tolerance; and (2) simple scaling arguments are adopted. Certain limitations restrict both of these approaches. In this study, we outline a third method, based on the theory of mean action time. We derive the governing boundary value problem for both the mean and variance of action time for confined flow in two‐dimensional heterogeneous porous media. Importantly, we show that these boundary value problems can be solved using widely available software. Applying these methods to a test case reveals the advantages of the theory of mean action time relative to standard methods.
Grid-Free Surface Tracking on the GPU

We present the ﬁrst mesh-based surface tracker that runs entirely on the GPU. The surface tracker is both completely grid-free and fast which makes it suitable for the use in a large, unbounded domain. The key idea for handling topological changes is to detect and delete overlapping triangles as well as triangles that lie inside the volume. The holes are then joined or closed in a robust and efﬁcient manner. Good mesh quality is maintained by a mesh improvement algorithm. In this paper we describe how all these steps can be parallelized to run efﬁ-ciently on a GPU. The surface tracker is guaranteed to produce a manifold mesh without boundary. Our results show the quality and efﬁciency of the method in both Eulerian and Lagrangian liquid simulations. Our parallel implementation runs more than an order of magnitude faster than the CPU version.
A study of bus location system using LoRa: Bus location system for community bus “Notty”

The information terminal bus stop has been studied widely. It is reported that the information terminal bus stop for citizen support is effective for the purpose of improving citizens' convenience. In particular, the bus location system is considered important for the purpose of eliminating users' concern about what time will it arrive? , Will it arrive at all? ; thus, there is a great deal of research. Because conventional systems need the communication charges, there are problems including introduction and maintenance costs are high. Therefore, a method using Wi-SUN has been proposed. However, Wi-SUN has a short transmission distance characteristic and requires many repeaters. The problem of introduction cost has not been solved. In order to solve this problem, we propose a bus location system using LoRa. The proposed system was able to reduce the number of the repeaters and bus stops to 1/4 or less compared with the system using Wi-SUN. The proposed system is superior to the system using Wi-SUN in terms of installation cost.
A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models

The pattern theory of Grenander is a mathematical framework where patterns are represented by probability models on random variables of algebraic structures. In this paper, we review three families of probability models, namely, the discriminative models, the descriptive models, and the generative models. A discriminative model is in the form of a classifier. It specifies the conditional probability of the class label given the input signal. A descriptive model specifies the probability distribution of the signal, based on an energy function defined on the signal. A generative model assumes that the signal is generated by some latent variables via a transformation. We shall review these models within a common framework and explore their connections. We shall also review the recent developments that take advantage of the high approximation capacities of deep neural networks.
Strain based dynamics

We propose a new set of constraints within the Position Based Dynamics (PBD) framework that allow the control of strain in directions that are independent of the edge directions of the simulation mesh. Instead of constraining distances between points, we constrain the entries of the Green - St Venant strain tensor. Varying the stiffness values corresponding to the individual strain coefficients lets us simulate anisotropic behavior. By working with Green's rotation-independent, non-linear strain tensor directly we do not have to perform a polar decomposition of the deformation gradient as in most strain limiting approaches. In addition, we propose a modification of the constraints corresponding to the diagonal entries of the strain tensor such that they can be solved in a single step and a modification of the constraints corresponding to the off-diagonal entries to decouple stretch from shear resistance. By formulating the constraints within the PBD framework, they can be used not only for strain limiting but to perform the actual simulation of the deformable object whereas traditional strain limiting methods have to be paired with a separate simulation method.