Miracle-dz/UniFAR-FTUs huggingface dataset:
Induction of Glycerol Synthesis and Release in Cultured Symbiodinium

Background Symbiotic dinoflagellates transfer a substantial amount of their photosynthetic products to their animal hosts. This amount has been estimated to represent up to 90% of the photosynthetically fixed carbon and can satisfy in some instances the full respiratory requirements of the host. Although in several cnidarian-dinoflagellate symbioses glycerol is the primary photosynthetic product translocated to the host, the mechanism for its production and release has not been demonstrated conclusively. Principal Findings Using Symbiodinium cells in culture we were able to reproduce the synthesis and release of glycerol in vitro by employing an inductor for glycerol synthesis, osmotic up-shocks. Photosynthetic parameters and fluorescence analysis of photosystem II showed that the inductive conditions did not have a negative effect on photosynthetic performance, suggesting that the capacity for carbon fixation by the cells was not compromised. The demand for glycerol production required to attain osmotic balance increased the expression of ribulose 1,5-bisphosphate and of glycerol 3-phosphate dehydrogenase, possibly competing with the flux of fixed carbon necessary for protein synthesis. In longer exposures of cultured Symbiodinium cells to high osmolarity, the response was analogous to photoacclimation, reducing the excitation pressure over photosystem II, suggesting that Symbiodinium cells perceived the stress as an increase in light. The induced synthesis of glycerol resulted in a reduction of growth rates. Conclusions Our results favor a hypothetical mechanism of a signaling event involving a pressure sensor that may induce the flux of carbon (glycerol) from the symbiotic algae to the animal host, and strongly suggest that carbon limitation may be a key factor modulating the population of symbionts within the host.
A biologically inspired model based on a multi-scale spatial representation for goal-directed navigation

Inspired by the multi-scale nature of hippocampal place cells, a biologically inspired model based on a multi-scale spatial representation for goal-directed navigation is proposed in order to achieve robotic spatial cognition and autonomous navigation. First, a map of the place cells is constructed in different scales, which is used for encoding the spatial environment. Then, the firing rate of the place cells in each layer is calculated by the Gaussian function as the input of the Q-learning process. The robot decides on its next direction for movement through several candidate actions according to the rules of action selection. After several training trials, the robot can accumulate experiential knowledge and thus learn an appropriate navigation policy to find its goal. The results in simulation show that, in contrast to the other two methods(G-Q, S-Q), the multi-scale model presented in this paper is not only in line with the multi-scale nature of place cells, but also has a faster learning potential to find the optimized path to the goal. Additionally, this method also has a good ability to complete the goal-directed navigation task in large space and in the environments with obstacles.
A cross-sectional analysis of long-term immunosuppressive regimens after liver transplantation at Asan Medical Center: Increased preference for mycophenolate mofetil

Backgrounds/Aims Long-term immunosuppression regimens after liver transplantation (LT) are rarely reported in detail. We aimed to provide information on actual long-term immunosuppression regimens through this cross-sectional study. Methods Our institutional LT database was searched for adult patients who underwent primary LT operation from 2000 to 2016. We identified 3620 live recipients with actual information on immunosuppressive agent use for 1–17 years. Results The study cohort was divided into 7 groups according to posttransplantation period. The immunosuppressive agents used at the cross-sectional review period were tacrolimus in 2884 (79.7%), cyclosporine in 445 (12.3%), mycophenolate mofetil in 2007 (55.4%), and everolimus in 138 (3.8%) recipients. There was no marked difference in immunosuppressive agent use according to pretransplantation liver malignancy or type of LT operation. Tacrolimus, cyclosporine, mycophenolate mofetil, and everolimus were used in 97.4%, 1.8%, 60.9%, and 9.2%, respectively, in the year 2 group; 94.1%, 3.9%, 51.6%, and 8.3%, respectively, in the year 3 group; 87.3%, 8.4%, 68.9%, and 4.8%, respectively, in the year 4–5 group; 78.2%, 12.9%, 64.6%, and 3.0%, respectively, in the year 6–7 group; 76.9%, 10.8%, 58.8%, and 2.4%, respectively, in the year 8–10 group; 66.7%, 22.4%, 43.4%, and 1.5%, respectively, in the year 11–15 group; and 73.8%, 15.4%, 32.9%, and 1.7%, respectively, in the year ≥15 group. Conclusions Tacrolimus and mycophenolate mofetil are the primary immunosuppressive agents after LT, and the indications for everolimus have started to increase at our institution. We believe our results will help establish tailored long-term immunosuppression regimens.
Capsules from Pathogenic and Non-Pathogenic Cryptococcus spp. Manifest Significant Differences in Structure and Ability to Protect against Phagocytic Cells

Capsule production is common among bacterial species, but relatively rare in eukaryotic microorganisms. Members of the fungal Cryptococcus genus are known to produce capsules, which are major determinants of virulence in the highly pathogenic species Cryptococcus neoformans and Cryptococcus gattii. Although the lack of virulence of many species of the Cryptococcus genus can be explained solely by the lack of mammalian thermotolerance, it is uncertain whether the capsules from these organisms are comparable to those of the pathogenic cryptococci. In this study, we compared the characteristic of the capsule from the non-pathogenic environmental yeast Cryptococcus liquefaciens with that of C. neoformans. Microscopic observations revealed that C. liquefaciens has a capsule visible in India ink preparations that was also efficiently labeled by three antibodies generated to specific C. neoformans capsular antigens. Capsular polysaccharides of C. liquefaciens were incorporated onto the cell surface of acapsular C. neoformans mutant cells. Polysaccharide composition determinations in combination with confocal microscopy revealed that C. liquefaciens capsule consisted of mannose, xylose, glucose, glucuronic acid, galactose and N-acetylglucosamine. Physical chemical analysis of the C. liquefaciens polysaccharides in comparison with C. neoformans samples revealed significant differences in viscosity, elastic properties and macromolecular structure parameters of polysaccharide solutions such as rigidity, effective diameter, zeta potential and molecular mass, which nevertheless appeared to be characteristics of linear polysaccharides that also comprise capsular polysaccharide of C. neoformans. The environmental yeast, however, showed enhanced susceptibility to the antimicrobial activity of the environmental phagocytes, suggesting that the C. liquefaciens capsular components are insufficient in protecting yeast cells against killing by amoeba. These results suggest that capsular structures in pathogenic Cryptococcus species and environmental species share similar features, but also manifest significant difference that could influence their potential to virulence.
Coupling Niche Browsers and Affect Analysis for an Opinion Mining Application

Newspapers generally attempt to present the news objectively. But textual affect analysis shows that many words carry positive or negative emotional charge. In this article, we show that coupling niche browsing technology and affect analysis technology allows us to create a new application that measures the slant in opinion given to public figures in the popular press.
A Protein Aggregation Based Test for Screening of the Agents Affecting Thermostability of Proteins

To search for agents affecting thermal stability of proteins, a test based on the registration of protein aggregation in the regime of heating with a constant rate was used. The initial parts of the dependences of the light scattering intensity (I) on temperature (T) were analyzed using the following empiric equation: I = K agg(T−T 0)2, where K agg is the parameter characterizing the initial rate of aggregation and T 0 is a temperature at which the initial increase in the light scattering intensity is registered. The aggregation data are interpreted in the frame of the model assuming the formation of the start aggregates at the initial stages of the aggregation process. Parameter T 0 corresponds to the moment of the origination of the start aggregates. The applicability of the proposed approach was demonstrated on the examples of thermal aggregation of glycogen phosphorylase b from rabbit skeletal muscles and bovine liver glutamate dehydrogenase studied in the presence of agents of different chemical nature. The elaborated approach to the study of protein aggregation may be used for rapid identification of small molecules that interact with protein targets.
Multi-Agent Submodular Optimization

Recent years have seen many algorithmic advances in the area of submodular optimization: (SO) $\min/\max~f(S): S \in \mathcal{F}$, where $\mathcal{F}$ is a given family of feasible sets over a ground set $V$ and $f:2^V \rightarrow \mathbb{R}$ is submodular. This progress has been coupled with a wealth of new applications for these models. Our focus is on a more general class of \emph{multi-agent submodular optimization} (MASO) which was introduced by Goel et al. in the minimization setting: $\min \sum_i f_i(S_i): S_1 \uplus S_2 \uplus \cdots \uplus S_k \in \mathcal{F}$. Here we use $\uplus$ to denote disjoint union and hence this model is attractive where resources are being allocated across $k$ agents, each with its own submodular cost function $f_i()$. In this paper we explore the extent to which the approximability of the multi-agent problems are linked to their single-agent {\em primitives}, referred to informally as the {\em multi-agent gap}. We present different reductions that transform a multi-agent problem into a single-agent one. For maximization we show that (MASO) admits an $O(\alpha)$-approximation whenever (SO) admits an $\alpha$-approximation over the multilinear formulation, and thus substantially expanding the family of tractable models. We also discuss several family classes (such as spanning trees, matroids, and $p$-systems) that have a provable multi-agent gap of 1. In the minimization setting we show that (MASO) has an $O(\alpha \cdot \min \{k, \log^2 (n)\})$-approximation whenever (SO) admits an $\alpha$-approximation over the convex formulation. In addition, we discuss the class of "bounded blocker" families where there is a provably tight O$(\log n)$ gap between (MASO) and (SO).
Universal kinetics for engagement of mechanosensing pathways in cell adhesion

When plated onto substrates, cell morphology and even stem cell differentiation are influenced by the stiffness of their environment. Stiffer substrates give strongly spread (eventually polarized) cells with strong focal adhesions, and stress fibers; very soft substrates give a less developed cytoskeleton, and much lower cell spreading. The kinetics of this process of cell spreading is studied extensively, and important universal relationships are established on how the cell area grows with time. Here we study the population dynamics of spreading cells, investigating the characteristic processes involved in cell response to the substrate. We show that unlike the individual cell morphology, this population dynamics does not depend on the substrate stiffness. Instead, a strong activation temperature dependence is observed. Different cell lines on different substrates all have long-time statistics controlled by the thermal activation over a single energy barrier ∆G ≈ 19 kcal/mol, while the early-time kinetics follows a power law ~ t5. This implies that the rate of spreading depends on an internal process of adhesion-mechanosensing complex assembly and activation: the operational complex must have 5 component proteins, and the last process in the sequence (which we believe is the activation of focal adhesion kinase) is controlled by the binding energy ∆G.
Salience and Attention in Surprisal-Based Accounts of Language Processing

The notion of salience has been singled out as the explanatory factor for a diverse range of linguistic phenomena. In particular, perceptual salience (e.g., visual salience of objects in the world, acoustic prominence of linguistic sounds) and semantic-pragmatic salience (e.g., prominence of recently mentioned or topical referents) have been shown to influence language comprehension and production. A different line of research has sought to account for behavioral correlates of cognitive load during comprehension as well as for certain patterns in language usage using information-theoretic notions, such as surprisal. Surprisal and salience both affect language processing at different levels, but the relationship between the two has not been adequately elucidated, and the question of whether salience can be reduced to surprisal / predictability is still open. Our review identifies two main challenges in addressing this question: terminological inconsistency and lack of integration between high and low levels of representations in salience-based accounts and surprisal-based accounts. We capitalize upon work in visual cognition in order to orient ourselves in surveying the different facets of the notion of salience in linguistics and their relation with models of surprisal. We find that work on salience highlights aspects of linguistic communication that models of surprisal tend to overlook, namely the role of attention and relevance to current goals, and we argue that the Predictive Coding framework provides a unified view which can account for the role played by attention and predictability at different levels of processing and which can clarify the interplay between low and high levels of processes and between predictability-driven expectation and attention-driven focus.
A Branch-Price-and-Cut Algorithm for Optimal Decoding of LDPC Codes

Channel coding aims to minimize errors that occur during the transmission of digital information from one place to another. Low-density parity-check (LDPC) codes can detect and correct transmission errors if one encodes the original information by adding redundant bits. In practice, heuristic iterative decoding algorithms are used to decode the received vector. However, these algorithms may fail to decode if the received vector contains multiple errors. We consider decoding the received vector with minimum error as an integer programming problem and propose a branch-and-price method for its solution. We improve the performance of our method by introducing heuristic feasible solutions and adding valid cuts to the mathematical formulation. Computational results reveal that our branch-price-and-cut algorithm significantly improves solvability of the problem compared to a commercial solver in high channel error rates. Our proposed algorithm can find higher quality solutions than commonly used iterative decoding heuristics.
On the path toward organic spintronics

Organic materials provide a unique platform for exploiting the spin of the electron—a field dubbed organic spintronics. Originally, this was mostly motivated by the notion that because of weak spin-orbit coupling, due to the small mass elements in organics and small hyperfine field coupling, organic matter typically displays a very long electron spin coherence time. More recently, however, it was found that organics provide a special class of spintronic materials for many other reasons—several of which are discussed throughout this issue. Over the past decade, there has been a growing interest in utilizing the molecular spin state as a quantum of information, aiming to develop multifunctional molecular spintronics for memory, sensing, and logic applications. The aim of this issue is to stimulate the interest of researchers by bringing to their attention the vast possibilities not only for unexpected science but also for the enormous potential for developing new functionalities and applications. The six articles in this issue deal with some of the breakthrough work that has been ongoing in this field in recent years.
Characterization of Hot-Electron-Stressed MOSFET's by Low-Temperature Measurements of the Drain Tunnel Current

We show that measurements of the forward and reverse current in the gated drain-substrate diode of a MOSFET in accumu- lation, before and after stress, provide a novel and sensitive means to characterize hot-electron-induced degradation. Measurements on this diode under forward and reverse bias at tem- peratures between 300 and 77 K reveal an important anomalous cur- rent that is weakly temperature-dependent. Computer simulations sug- gest that under reverse bias this excess current is due to band-to-band tunneling, while under forward bias it is due to tunneling through in- terface states. Both currents are modified after hot-electron (HE) in,jection in the gate-drain overlap region. Under reverse bias, the current is mostly sensitive to oxide trapped charges, while under forward bias, it is also sensitive to the generated interface states. Our measurements confirm the high concentration of trapped elec- trons and acceptor interface states above the drain in NMOSFET's, after an HE stress. Characteristic peaks in the I-V curves are related to the energetic and spatial distribution of these interface states. In PMOSFET's, no degradation is detected above the drain after a HE stress.
Optimization of robot path planning parameters based on genetic algorithm

The paper introduces a method which is based o n genetic algorithm to select more properly parameters for local path planning of mobile robot. In our experiments, according to experience, we choose properly parameter domain as chromosomes in Genetic algorithm(GA). Then we will extract several different individual cost function from DWA algorithm, adopted by Local path planning, and merge them into a fitness function. Experiments show that the automatic tuning method, proposed in this paper, can generate smoother and faster trajectories than manual tuning method and perform better in avoiding obstacle. This method can also be used for other platforms.
Integrated prevention of obesity and eating disorders: barriers, developments and opportunities

Abstract Objective The serious consequences of obesity and eating disorders (ED), difficulties encountered in treatment and the high prevalence of these conditions are important reasons to develop efforts aimed at their prevention. The implementation of integrated interventions aimed at preventing risk factors for both obesity and ED constitutes a very exciting development. In the present paper we discuss and review the main reasons for an integrated approach to the spectrum of eating- and weight-related problems, which include anorexia nervosa, bulimia nervosa, anorexic and bulimic behaviours, unhealthy dieting practices, body dissatisfaction, binge-eating disorder, overweight and obesity. Given differences between the fields with regard to current perspectives and objectives, key barriers to an integrated approach to prevention are discussed. In order to show the possibilities of development of this approach, we review the main contributions made to date in the fields of both obesity and ED prevention. In particular, environmental approaches in the prevention of obesity and ED are reviewed, given their potential for preventing a broad spectrum of eating- and weight-related problems. Furthermore, several examples of initiatives that have utilized an integrated approach to prevention are discussed. Design Narrative review. Conclusions We recommend a scenario in which the two fields share knowledge to enhance the difficult work of preventing and treating both ED and obesity.
Automatic seed selection for segmentation of liver cirrhosis in laparoscopic sequences

For computer aided diagnosis based on laparoscopic sequences, image segmentation is one of the basic steps which define the success of all further processing. However, many image segmentation algorithms require prior knowledge which is given by interaction with the clinician. We propose an automatic seed selection algorithm for segmentation of liver cirrhosis in laparoscopic sequences which assigns each pixel a probability of being cirrhotic liver tissue or background tissue. Our approach is based on a trained classifier using SIFT and RGB features with PCA. Due to the unique illumination conditions in laparoscopic sequences of the liver, a very low dimensional feature space can be used for classification via logistic regression. The methodology is evaluated on 718 cirrhotic liver and background patches that are taken from laparoscopic sequences of 7 patients. Using a linear classifier we achieve a precision of 91% in a leave-one-patient-out cross-validation. Furthermore, we demonstrate that with logistic probability estimates, seeds with high certainty of being cirrhotic liver tissue can be obtained. For example, our precision of liver seeds increases to 98.5% if only seeds with more than 95% probability of being liver are used. Finally, these automatically selected seeds can be used as priors in Graph Cuts which is demonstrated in this paper.
DA-FTL: Dynamic associative flash translation layer

Considering the increasing growth of technology, various components of a system are becoming more advanced day by day, and according to statistics and reports, the most advancement has been made in the field of processors. In spite of all these advancements, we can still observe that computer systems suffer a lot of delays and slowness and the only section which attracts the attention is the memory, especially the data storage section. In recent years, we have witnessed many nonvolatile memories, each of which has their own capabilities and drawbacks. However, the memory that dominated ultimately the competition in the market was the nonvolatile flash memory. Later, this kind of memory was used in storage systems, and the technology of solid-state drives emerged to replace the conventional hard disk drives. The emergence of this new technology has been associated with a lot of challenges. In some applications, such as laptops, the increased lifetime is not a major challenge, but in many applications which are based on MLC (Multi Level Cell) technology, the increased lifetime is a very important parameter. A lot of control algorithms have been provided in the flash translation layer (FTL) section of this storage system to avoid additional (write/erase) operations that cause the erosion and reduction of the lifetime of memory and to increase the efficiency and lifetime of memory blocks. In this paper, we present a new FTL that dynamically controls the associativity of update blocks with data blocks and reduces the cost of write and erase operations in the Full Merge operation. This solution ultimately increases the lifetime of the memory blocks.