Miracle-dz/UniFAR-FTUs huggingface dataset:
Mitotic inhibition of corneal endothelium in neonatal rats.

PURPOSE Corneal endothelium in humans does not divide to any significant extent after birth; therefore, with age there is a gradual loss of cells. When cell density is reduced to a critical level, the endothelium cannot function to maintain corneal clarity, and the cornea becomes permanently cloudy. Currently, the blindness that results can be treated only by corneal transplantation. The long-term goal is to find methods to stimulate corneal endothelial proliferation in a clinically relevant manner. The first step toward achieving this goal is to identify mechanisms responsible for the induction and maintenance of mitotic inhibition of the corneal endothelium in vivo. During corneal development, the endothelium is formed by migration and proliferation of mesenchymal cells from the ocular periphery. Soon after the monolayer is formed, proliferation ceases. In tissue culture, many cell types cease proliferating upon formation of stable cell-cell and cell-substrate attachments. The goal of the present studies was to determine whether establishment of stable contacts correlates with cessation of endothelial proliferation during corneal development in vivo. METHODS Corneas from neonatal (days 1, 3, 7, 10, 13, 14, 17, 21, 28, and 42) and adult rats were used for immunolocalization of the following: bromodeoxyuridine (BrdU), an S-phase marker; p27kip1 and p21cip1, G1-phase inhibitors; connexin-43 and ZO-1, proteins associated with gap and tight junctions, respectively; Na+/K+-ATPase and beta3-integrin, markers of plasma membrane polarity; and fibronectin and collagen type IV, constituents of Descemet's membrane. Nuclei staining positively for BrdU were counted to determine the relative number of S-phase cells at various times after birth. Marker protein expression and localization were determined by conventional fluorescence microscopy and by confocal microscopy. RESULTS The number of endothelial cells staining positively for BrdU gradually decreased between postnatal days 1 and 13. After postnatal day 13, positive BrdU staining was no longer detectable. During the first postnatal week, cells stained positively for the G1-phase inhibitor p27kip1 but not for p21cip1. Connexin-43 achieved its mature location by postnatal day 1. ZO-1, Na+/K+-ATPase, beta3-integrin, fibronectin, and collagen type IV achieved their mature localization patterns between postnatal days 14 and 21. CONCLUSIONS In neonatal rat, corneal endothelial cells are still entering the cell cycle at birth, but cell cycle entry gradually decreases, so that by postnatal day 13 cells are no longer entering the S-phase. The G1-phase inhibitor p27kip1, but not p21cip1, may help mediate this inhibition. Stable cell-cell and cell-substrate contacts gradually form, and monolayer maturation is complete between postnatal days 14 and 21. The results lead to the hypothesis that, in developing rat cornea in vivo, the establishment of stable cell-cell and cell-substrate contacts initiates a cascade of events, mediated by p27kip1, which induces mitotic inhibition in the endothelial monolayer.
Speciation through Exaptation

In this paper we present a simple genetic algorithm, possessing a notion of viability, in which a population of individuals in one niche spreads to populate a second niche with a different fitness function. The two niche populations then diverge genetically to such a degree that offspring produced by the crossover operator are inviable in both niches. We argue that this simple adaptive evolutionary behavior in the genetic algorithm can be likened to the concept of speciation in biology
Long-Acting Depot Formulation of Luprolide Acetate as a Method of Hypothalamic Down Regulation for Controlled Ovarian Hyperstimulation and Oocyte Production in Macaca fascicularis1

Abstract Reproductive function in some nonhuman primate species parallels that of the human. As a result, studies addressing aspects of reproductive function primarily involve the use of nonhuman primate models. The objective of the present study was to assess the efficiency of two hypothalamic down-regulation techniques combined with a single controlled ovarian hyperstimulation protocol for mature oocyte production in the cynomolgus macaque (Macaca fascicularis). Hypothalamic GnRH down regulation was first induced using the clinical long protocol of the short-acting GnRH-agonist luprolide acetate combined with controlled ovarian hyperstimulation and oocyte retrieval. Resulting oocyte yield and maturity with this regimen was insufficient for further evaluation of oocyte competency. Hypothalamic down regulation was induced in the second experiment using the long-acting depot formulation of luprolide acetate in conjunction with controlled ovarian hyperstimulation. This regimen allowed for the consistently efficient production of oocytes (15.5 oocytes per oocyte retrieval) and an oocyte maturity rate of 56%. Oocyte competence, as determined by the ability to undergo fertilization or parthenogenic activation and to reach specific cleavage stages at appropriate time intervals, was evaluated. Intracytoplasmic sperm injection resulted in a 59% fertilization rate and a 91% cleavage rate. Parthenogenic activation resulted in a 70% activation rate and an 86% cleavage rate. These data suggest that use of the long-acting form of luprolide acetate in conjunction with controlled ovarian hyperstimulation results in the production of competent, mature oocytes and allows the efficient use of nonhuman primate resources in studies of reproductive function in cynomolgus macaques.
Nearest neighbor discriminant analysis for robust speaker recognition

With the advent of i-vectors, linear discriminant analysis (LDA) has become an integral part of many state-of-the-art speaker recognition systems. Here, LDA is primarily employed to anni-hilate the non-speaker related (e.g., channel) directions, thereby maximizing the inter-speaker separation. The traditional approach for computing the LDA transform uses parametric representations for both intra-and inter-speaker scatter matrices that are based on the Gaussian distribution assumption. However, it is known that the actual distribution of i-vectors may not necessarily be Gaussian, and in particular, in the presence of noise and channel distortions. Motivated by this observation, we present an alternative non-parametric discriminant analysis (NDA) technique that measures both the within-and between-speaker variation on a local basis using the nearest neighbor rule. The effectiveness of the NDA method is evaluated in the context of noisy speaker recognition tasks using speech material from the DARPA Robust Automatic Transcription of Speech (RATS) program. Experimental results indicate that the NDA is more effective than the traditional parametric LDA for speaker recognition under noisy and channel degraded conditions.
Low Illumination Image Enhancement Algorithm Using Iterative Recursive Filter and Visual Gamma Transformation Function

In this paper, a Retinex based enhancement algorithm is proposed for enhancing low illumination images. The novelty of algorithm lies in the use of Iterative Recursive filter for image decomposition and Visual Gamma transformation function for pixel mapping. The edge preserving Iterative Recursive Filter estimates the base layer efficiently and 2D Visual Gamma transformation function map the pixels based on Human Vision System (HVS). The proposed Visual gamma function mimics the local and global adoption capability of HVS. The experimental results show that algorithm produce naturally looking and artifact free enhanced images with improved visibility in local regions. The subjective and objective assessment on publicly available dataset illustrates the effectiveness of the proposed method comparing with other enhancement algorithms.
Ambiguity in language networks

Abstract Human language defines the most complex outcomes of evolution. The emergence of such an elaborated form of communication allowed humans to create extremely structured societies and manage symbols at different levels including, among others, semantics. All linguistic levels have to deal with an astronomic combinatorial potential that stems from the recursive nature of languages. This recursiveness is indeed a key defining trait. However, not all words are equally combined nor frequent. In breaking the symmetry between less and more often used and between less and more meaning-bearing units, universal scaling laws arise. Such laws, common to all human languages, appear on different stages from word inventories to networks of interacting words. Among these seemingly universal traits exhibited by language networks, ambiguity appears to be a specially relevant component. Ambiguity is avoided in most computational approaches to language processing, and yet it seems to be a crucial element of language architecture. Here we review the evidence both from language network architecture and from theoretical reasonings based on a least effort argument. Ambiguity is shown to play an essential role in providing a source of language efficiency, and is likely to be an inevitable byproduct of network growth.
Cryptic Rac-binding and p21 Cdc42HS/Rac -activated Kinase Phosphorylation Sites of NADPH Oxidase Component p67 phox *

Rac1 is a member of the Rho family of small molecular mass GTPases that act as molecular switches to control actin-based cell morphology as well as cell growth and differentiation. Rac1 and Rac2 are specifically required for superoxide formation by components of the NADPH oxidase. In binding assays, Rac1 interacts directly with p67 phox , but not with the other oxidase components: cytochrome b, p40 phox , or p47 phox (Prigmore, E., Ahmed, S., Best, A., Kozma, R., Manser, E., Segal, A. W., and Lim, L. (1995) J. Biol. Chem. 270, 10717–10722). Here, the Rac1/2 interaction with p67 phox has been characterized further. Rac1 and Rac2 can bind to p67 phox amino acid residues 170–199, and the N terminus (amino acids 1–192) of p67 phox can be used as a specific inhibitor of Rac signaling. Deletion of p67 phox C-terminal sequences (amino acids 193–526), the C-terminal SH3 domain (amino acids 470–526), or the polyproline-rich motif (amino acids 226–236) stimulates Rac1 binding by ∼8-fold. p21 Cdc42Hs/Rac -activated kinase (PAK) phosphorylates p67 phox amino acid residues adjacent to the Rac1/2-binding site, and this phosphorylation is stimulated by deletion of the C-terminal SH3 domain or the polyproline-rich motif. These data suggest a role for cryptic Rac-binding and PAK phosphorylation sites of p67 phox in control of the NADPH oxidase.
Adaptive critic based adaptation of a fuzzy policy manager for a logistic system

We show that a reinforcement learning method, adaptive critic based approximate dynamic programming, can be used to create fuzzy policy managers for adaptive control of a logistic system. Two different architectures are used for the policy manager, a feed forward neural network, and a fuzzy rule base. For both architectures, policy managers are trained that outperform LP and GA derived fixed policies in stochastic and non-stationary demand environments. In all cases the fuzzy system initialized with expert information outperforms the neural network.
Plasma–Liquid Interactions at Atmospheric Pressure for Nanomaterials Synthesis and Surface Engineering

Plasma-induced non-equilibrium liquid chemistry (PiLC) offers enhanced opportunities over solution chemistry for developing new nanomaterials and tailoring their functional properties. Recent advances in the design and scientific understanding of microplasma devices operating at atmospheric pressure offer simple and effective routes to non-equilibrium chemistry for both scientific study and future nanomanufacturing. This paper presents a short review of our recent work on atmospheric pressure plasmaâliquid interactions used in the fabrication and functionalization of nanoparticles. A brief discussion of possible electron-liquid reactions highlights outstanding scientific and engineering questions.
Internet traffic classification demystified: on the sources of the discriminative power

Recent research on Internet traffic classification has yield a number of data mining techniques for distinguishing types of traffic, but no systematic analysis on "Why" some algorithms achieve high accuracies. In pursuit of empirically grounded answers to the "Why" question, which is critical in understanding and establishing a scientific ground for traffic classification research, this paper reveals the three sources of the discriminative power in classifying the Internet application traffic: (i) ports, (ii) the sizes of the first one-two (for UDP flows) or four-five (for TCP flows) packets, and (iii) discretization of those features. We find that C4.5 performs the best under any circumstances, as well as the reason why; because the algorithm discretizes input features during classification operations. We also find that the entropy-based Minimum Description Length discretization on ports and packet size features substantially improve the classification accuracy of every machine learning algorithm tested (by as much as 59.8%! ) and make all of them achieve >93% accuracy on average without any algorithm-specific tuning processes. Our results indicate that dealing with the ports and packet size features as discrete nominal intervals, not as continuous numbers, is the essential basis for accurate traffic classification (i.e., the features should be discretized first), regardless of classification algorithms to use.
Laypeople and Experts risk perception of Cloud Computing Services

Cloud computing is revolutionising the way software services are procured and used by Government organizations and SMEs. Quantitative risk assessment of Cloud services is complex and undermined by specific security concerns regarding data confidentiality, integrity and availability. This study explores how the gap between the quantitative risk assessment and the perception of the risk can produce a bias in the decision-making process about Cloud computing adoption. The risk perception of experts in Cloud computing (N=37) and laypeople (N=81) about ten Cloud computing services was investigated using the psychometric paradigm. Results suggest that the risk perception of Cloud services can be represented by two components, called dread risk and unknown risk, which may explain up to 46% of the variance. Other factors influencing the risk perception were perceived benefits, trust in regulatory authorities and technology attitude. This study suggests some implications that could support Government and non-Government organizations in their strategies for Cloud computing adoption.
Come-and-Go Patterns of Group Evolution: A Dynamic Model

How do social groups, such as Facebook groups and Wechat groups, dynamically evolve over time? How do people join the social groups, uniformly or with burst? What is the pattern of people quitting from groups? Is there a simple universal model to depict the come-and-go patterns of various groups? In this paper, we examine temporal evolution patterns of more than 100 thousands social groups with more than 10 million users. We surprisingly find that the evolution patterns of real social groups goes far beyond the classic dynamic models like SI and SIR. For example, we observe both diffusion and non-diffusion mechanism in the group joining process, and power-law decay in group quitting process, rather than exponential decay as expected in SIR model. Therefore we propose a new model comeNgo, a concise yet flexible dynamic model for group evolution. Our model has the following advantages: (a) unification power: it generalizes earlier theoretical models and different joining and quitting mechanisms we find from observation. (b) succinctness and interpretability: it contains only six parameters with clear physical meanings. (c) accuracy: it can capture various kinds of group evolution patterns preciously and the goodness of fit increase by 58% over baseline. (d) usefulness: it can be used in multiple application scenarios such as forecasting and pattern discovery.
Learned Watershed: End-to-End Learning of Seeded Segmentation

Learned boundary maps are known to outperform handcrafted ones as a basis for the watershed algorithm. We show, for the first time, how to train watershed computation jointly with boundary map prediction. The estimator for the merging priorities is cast as a neural network that is convolutional (over space) and recurrent (over iterations). The latter allows learning of complex shape priors. The method gives the best known seeded segmentation results on the CREMI segmentation challenge.
Bioinspired approaches for optimizing the strength and toughness of graphene-based polymer nanocomposites

The exceptional mechanical properties of graphene have revealed appealing potential in developing lightweight, mechanically robust polymer materials. However, how to effectively balance their strength and toughness remains a challenge so far. Although only weak or brittle constituents can be utilized, nature exhibits a miraculous capacity for creating biological composites that can meet a variety of functional needs, which has stimulated one's strong interest in the design and manufacture of novel polymer nanocomposites. This highlight article briefly describes the advances of bioinspired approaches in improving the mechanical properties of graphene-based nanocomposites, involving three selected aspects, i.e., structure and mechanical properties of graphene oxide papers, construction of novel graphene–polymer interphases and synergistic mechanical improvements in graphene-based nanocomposites. It is emphasized that the hierarchical structure and interplay between different toughening mechanisms play crucial roles in the development of strong, tough graphene–polymer nanocomposites.
Genetic variation and pharmacogenomics: concepts, facts, and challenges

The analysis of genetic variation in candidate genes is an issue of central importance in pharmacogenomics. The specific approaches taken will have a critical impact on the successful identification of disease genes, the molecular correlates of drug response, and the establishment of meaningful relationships between genetic variants and phenotypes of biomedical and pharmaceutical importance in general. Against a historical background, this article distinguishes different approaches to candidate gene analysis, reflecting different stages in human genome research. Only recently has it become feasible to analyze genetic variation systematically at the ultimate level of resolution, ie, the DNA sequence. In this context, the importance of haplotype-based approaches to candidate gene analysis has at last been recognized; the determination of the specific combinations of variants for each of the two sequences of a gene defined as a haplotype is essential. An up-to-date summary of such maximum resolution data on the amount, nature, and structure of genetic variation in candidate genes will be given. These data demonstrate abundant gene sequence and haplotype diversity. Numerous individually different forms of a gene may exist. This presents major challenges to the analysis of relationships between genetic variation, gene function, and phenotype. First solutions seem within reach. The implications of naturally occurring variation for pharmacogenomics and “personalized” medicine are now evident. Future approaches to the identification, evaluation, and prioritization of drug targets, the optimization of clinical trials, and the development of efficient therapies must be based on in-depth knowledge of candidate gene variation as an essential prerequisite.
Measurement of treatment response to sertraline in depressed multiple sclerosis patients using the Carroll scale.

We studied 11 patients with stable multiple sclerosis (MS) with major depression in terms of response to Sertraline at 100 mg q.d. in an open label trial. Patients were evaluated with self assessment measurements (Carroll scale) prior to and during treatment. Only one patient discontinued the drug during the three month treatment trial, and this was due to perceived lack of efficacy by the patient. The remainder of the patients completed at least three months of treatment and had significant improvement in depressive symptoms by self assessment measurements. No patients experienced side effects. Sertraline appears to be well tolerated and effective in treatment of major depression in MS. The Carroll scale is an easily administered means of assessing treatment response, and correlated highly with our clinical impressions.
On the Stackelberg fuel pricing problem

We consider the Stackelberg fuel pricing problem in which a company has to decide the fuel selling price at each of its gas stations in order to maximize its revenue, assuming that the selling prices of the competitors and the customers’ preferences are known in advance. We show that, even in the basic case in which the road network is modeled by an undirected planar graph and the competitors discriminate on two different selling prices only, the problem is APX-hard. On the positive side, we design a polynomial time algorithm for instances in which the number of gas stations owned by the company is constant, while, in the general case, we show that the single-price algorithm (which provides the best-known solutions for essentially all the Stackelberg pricing problems studied in the literature up to date) achieves an approximation ratio which is logarithmic in some parameters of the input instance. This result, in particular, is tight and holds for a much more general class of Stackelberg network pricing problems.
Extracting Comparative Sentences from Korean Text Documents Using Comparative Lexical Patterns and Machine Learning Techniques

This paper proposes how to automatically identify Korean comparative sentences from text documents. This paper first investigates many comparative sentences referring to previous studies and then defines a set of comparative keywords from them. A sentence which contains one or more elements of the keyword set is called a comparative-sentence candidate. Finally, we use machine learning techniques to eliminate non-comparative sentences from the candidates. As a result, we achieved significant performance, an F1-score of 88.54%, in our experiments using various web documents.
Gaussian approximation for sum-product decoding of low-density parity-check codes

We use a Gaussian approximation (GA) for analyzing the sum-product algorithm for low-density parity-check (LDPC) codes and memoryless binary-input continuous-output additive white Gaussian noise (AWGN) channels. This simplification allows us to calculate the threshold quickly and to understand the behavior of the decoder better. We have also designed high rate LDPC codes using the Gaussian approximation that have thresholds less than 0.05 dB from the Shannon limit.