Miracle-dz/UniFAR-FTUs huggingface dataset:
ANALYSIS OF MEMORY CD 8 T CELL DIFFERENTIATION 443 done in the context of a large research effort to understand immune memory in

CD8 T cells are specialized immune cells that play an important role in the regulation of antiviral immune response and the generation of protective immunity. In this paper we investigate the differentiation of memory CD8 T cells in the immune response using a short time course microarray experiment. Structurally, this experiment is similar to many in that it involves measurements taken on independent samples, in one biological group, at a small number of irregularly spaced time points, and exhibiting patterns of temporal nonstationarity. To analyze this CD8 T-cell experiment, we develop a hierarchical state space model so that we can: (1) detect temporally differentially expressed genes, (2) identify the direction of successive changes over time, and (3) assess the magnitude of successive changes over time. We incorporate hidden Markov models into our model to utilize the information embedded in the time series and set up the proposed hierarchical state space model in an empirical Bayes framework to utilize the population information from the large-scale data. Analysis of the CD8 T-cell experiment using the proposed model results in biologically meaningful findings. Temporal patterns involved in the differentiation of memory CD8 T cells are summarized separately and performance of the proposed model is illustrated in a simulation study.
Outage Probability for Heterogeneous Cellular Networks with Biased Cell Association

In this paper we develop a tractable framework for SINR analysis in downlink heterogeneous cellular networks (HCNs) with flexible cell association. The HCN is modeled as a multi-tier cellular network where each tier's base stations (BSs) are randomly located and have a unique transmit power, path loss exponent, spatial density, and bias towards admitting users. We implicitly assume every BS has full queues. From this model, we derive the outage probability of a typical user in the network, which can be viewed as a spatial average of SINR over all users in the network. We observe that deploying more or less BSs does not change the outage probability in interference-limited HCN with unbiased cell association, and observe how biasing affects the metric.
Application of the fuzzy multi-criteria decision-making method to identify nonlinear decision model

A large number of multi-criteria methods have been developed to deal with different kinds of problems. Most of them use a linear aggregation, what is the cause of many shortcomings in solving decision problems. This paper presents how to identify nonlinear multi-criteria decision-making models with using the new fuzzy method: the Characteristic Objects Method (COMET). In this approach, models are constructed on the basis of characteristic objects and fuzzy rules. Thereby, the COMET method is free of rank reversal phenomenon, which is one of the most commonly indicated shortcoming of the multi-criteria decisionmaking methods. This study introduces the concepts of characteristic objects and way of their determination. Subsequently, the paper presents approach to construct the fuzzy rule base and the entire model. Finally, the theoretical nonlinear problem is presented to verify the developed approach and to demonstrate its effectiveness.
Ectopic Expression of a Basic Helix-Loop-Helix Gene Transactivates Parallel Pathways of Proanthocyanidin Biosynthesis. Structure, Expression Analysis, and Genetic Control of Leucoanthocyanidin 4-Reductase and Anthocyanidin Reductase Genes in Lotus corniculatus1[W]

Proanthocyanidins (PAs) are plant secondary metabolites and are composed primarily of catechin and epicatechin units in higher plant species. Due to the ability of PAs to bind reversibly with plant proteins to improve digestion and reduce bloat, engineering this pathway in leaves is a major goal for forage breeders. Here, we report the cloning and expression analysis of anthocyanidin reductase (ANR) and leucoanthocyanidin 4-reductase (LAR), two genes encoding enzymes committed to epicatechin and catechin biosynthesis, respectively, in Lotus corniculatus. We show the presence of two LAR gene families (LAR1 and LAR2) and that the steady-state levels of ANR and LAR1 genes correlate with the levels of PAs in leaves of wild-type and transgenic plants. Interestingly, ANR and LAR1, but not LAR2, genes produced active proteins following heterologous expression in Escherichia coli and are affected by the same basic helix-loop-helix transcription factor that promotes PA accumulation in cells of palisade and spongy mesophyll. This study provides direct evidence that the same subclass of transcription factors can mediate the expression of the structural genes of both branches of PA biosynthesis.
On the Use of Strong BCH Codes for Improving Multilevel NAND Flash Memory Storage Capacity

This paper investigates the potential of using strong BCH codes to improve multilevel data-storage NAND Flash memory capacity. Current multilevel Flash memories store 2 bits in each cell. Further storage capacity may be achieved by increasing the number of storage levels per cell, which nevertheless will largely degrade the raw storage reliability. Based on a Gaussian-like memory cell threshold voltage distribution model and ASIC BCH decoder design results, we demonstrate that strong BCH codes can effectively enable the use of a larger number of storage levels per cell and hence improve the overall NAND Flash memory storage capacity up to 59.1% while maintaining the same cell programming time. Furthermore, we propose a scheme to leverage strong BCH codes to improve memory defect tolerance at the cost of increased cell programming time.
Multiple Transatlantic Introductions of the Western Corn Rootworm

The invasion of Europe by the western corn rootworm, North America's most destructive corn pest, is ongoing and represents a serious threat to European agriculture. Because this pest was initially introduced in Central Europe, it was believed that subsequent outbreaks in Western Europe originated from this area. Using model-based Bayesian analyses of the genetic variability of the western corn rootworm, we demonstrate that this belief is false: There have been at least three independent introductions from North America during the past two decades. This result raises questions about changing circumstances that have enabled a sudden burst of transatlantic introductions.
Statistical Machine Translation System for IWSLT 2007 Co ş

We describe the TÜBITAK-UEKAE system that participated in the Arabic-to-English and Japanese-toEnglish translation tasks of the IWSLT 2007 evaluation campaign. Our system is built on the open-source phrasebased statistical machine translation software Moses. Among available corpora and linguistic resources, only the supplied training data and an Arabic morphological analyzer are used in the system. We present the run-time lexical approximation method to cope with out-of-vocabulary words during decoding. We tested our system under both automatic speech recognition (ASR) and clean transcript (clean) input conditions. Our system was ranked first in both Arabic-toEnglish and Japanese-to-English tasks under the “clean” condition.
On-chip concentration of bacteria using a 3D dielectrophoretic chip and subsequent laser-based DNA extraction in the same chip

We report the on-chip concentration of bacteria using a dielectrophoretic (DEP) chip with 3D electrodes and subsequent laser-based DNA extraction in the same chip. The DEP chip has a set of interdigitated Au post electrodes with 50 µm height to generate a network of non-uniform electric fields for the efficient trapping by DEP. The metal post array was fabricated by photolithography and subsequent Ni and Au electroplating. Three model bacteria samples (Escherichia coli, Staphylococcus epidermidis, Streptococcus mutans) were tested and over 80-fold concentrations were achieved within 2 min. Subsequently, on-chip DNA extraction from the concentrated bacteria in the 3D DEP chip was performed by laser irradiation using the laser-irradiated magnetic bead system (LIMBS) in the same chip. The extracted DNA was analyzed with silicon chip-based real-time polymerase chain reaction (PCR). The total process of on-chip bacteria concentration and the subsequent DNA extraction can be completed within 10 min including the manual operation time.
A Glycine-rich RNA-binding Protein Mediating Cold-inducible Suppression of Mammalian Cell Growth

In response to low ambient temperature, mammalian cells as well as microorganisms change various physiological functions, but the molecular mechanisms underlying these adaptations are just beginning to be understood. We report here the isolation of a mouse cold-inducible RNA-binding protein (cirp) cDNA and investigation of its role in cold-stress response of mammalian cells. The cirp cDNA encoded an 18-kD protein consisting of an amino-terminal RNAbinding domain and a carboxyl-terminal glycine-rich domain and exhibited structural similarity to a class of stress-induced RNA-binding proteins found in plants. Immunofluorescence microscopy showed that CIRP was localized in the nucleoplasm of BALB/3T3 mouse fibroblasts. When the culture temperature was lowered from 37 to 32°C, expression of CIRP was induced and growth of BALB/3T3 cells was impaired as compared with that at 37°C. By suppressing the induction of CIRP with antisense oligodeoxynucleotides, this impairment was alleviated, while overexpression of CIRP resulted in impaired growth at 37°C with prolongation of G1 phase of the cell cycle. These results indicate that CIRP plays an essential role in cold-induced growth suppression of mouse fibroblasts. Identification of CIRP may provide a clue to the regulatory mechanisms of cold responses in mammalian cells.
Surgically Induced Digital Distal Syndactyly for Prevention of Digital Growth Deformities Around the Joints: A New Technique

Background Correction of digit deformities at or near the Joints is performed easily ; however, maintaining the result is often difficult either due to noncompliance of the patient to wear the postoperative splints or problems related to unequal growth of bones or normal tissues compared to the scarred or operated side. Objectives The aim of this study was to overcome the above mentioned problems for which we propose the "Distal d Digit Syndactyly" technique. Materials and Method This method is based on the concept of suturing the distal phalanx of the deformed digit to the normal adjoining finger to help prevent the recurrence of the anomaly during the child’s growth period or the very important three or four postoperative months of scar maturation in the adult. After the correction of deformity of the finger or toe, "Distal Syndactyly" is created by two flaps on the adjoining digits; one base is dorsally hinged and the other one volar and after elevating the flaps they are sutured together. During the three postoperative weeks care is taken that this attachment is not disrupted and after healing a "distal syndactyly" is created which is very durable and in children it stretches with growth and does not impede the digit’s growth. Results Eleven patients with congenital and traumatic digit anomalies were treated. The recurrence of the problem was prevented in 9 patients; in 2 patients with intact Syndactyly the contracture recurred by stretching the Syndactyly skin. The period of the “Joining” ranged from 6 months to three years and cosmetic appearance was acceptable to the patient and parents. Conclusion This technique by joining a deformed digit to a normally growing adjacent digit prevents the postoperative recurrence of the contracture or growth induced deviation in the digits of noncompliant patients especially children.
Journal of Orthopaedic Surgery and Research Open Access the Occurrence of Osteoarthritis at a Minimum of Ten Years after Reconstruction of the Anterior Cruciate Ligament

Objective: The objective of this study was to evaluate the incidence of radiographic osteoarthritis in the operated knee in comparison with the contralateral knee ten years after a bone-tendon bone patellar autograft ACL-reconstruction and to evaluate to which level patients regain activity ten years after reconstruction. Methods: Fifty-three patients with ACL instability were operated arthroscopically using the central third of the patellar tendon as a bone-tendon-bone autograft. At a minimum of 10 year follow up 28/44 patients matched the inclusion criteria and could be reached for follow-up. Evaluation included a patient satisfaction evaluation using a Visual Analog Scale, physical examination (International Knee Documentation Committee score, Tegner score, Lysholm score, KT-1000 stabilometry) and a radiological evaluation (Kellgren and Fairbanks classification). Results: The patients' satisfaction, at a mean of 10,3 year follow-up, measured with a VAS score (0–10) was high with a mean of 8.5 (range 4 to 10). The KT 1000 arthrometer laxity measurements revealed in 55% of the patients an A rating (1–2 mm), in 29% a B rating (3–5 mm) and in 16% a C rating (6–10 mm). According to the Tegner score 54% of the patients were able to perform at the same activity level as pre-operatively. The mean pre-operative Tegner score was 6.8 and the mean post-operative Tegner score was 6.0 at final follow up. The Lysholm score showed satisfactory results with a mean of 91 points (range 56 to 100). According to the Kellgren and Fairbank classifications, there is a significant difference (p < 0.05) in development of OA between the ACL injured and subsequently operated knee in comparison to the contralateral knee. Conclusion: The patellar BTB ACL reconstruction does not prevent the occurrence of radiological OA after 10 years but does help the patient to regain the pre-operative level of activity.
Thermomechanical Modeling of Scanning Joule Expansion Microscopy Imaging of Single-Walled Carbon Nanotube Devices

An analytical model, validated by experiments and finite element simulations, is developed to study the thermal imaging of single-walled carbon nanotube (SWNT) devices by scanning Joule expansion microscopy (SJEM). A simple scaling law for thermal expansion at low frequencies, which only depends on two nondimensional geometric parameters, is established. Such a scaling law provides a simple way to determine the surface temperature distribution and power dissipation per unit length in an SWNT from the measured thermal expansion in experiments. The results suggest the spatial resolution of the SJEM measurement is as good as ∼50 nm.
Detecting Communities Using Information Flow in Social Networks

Many complex networks are characterized by a community structure, i.e. the presence of groups of nodes that are more densely connected with each other than with the rest of the network. The algorithms developed to detect such communities usually consider the structural properties of the network, i.e. the static links between nodes. In the case of social networks this means considering, for example, “friendship” links on Facebook or “followers” on Twitter. We argue that these kinds of static links are not indicative of the real community structure underlying these networks, since users of social media usually have hundreds of connections even with people they are only acquaintances with. Moreover, users of social media typically only communicate with a subset of these connections, and form real communities only within these subsets. In this paper, we adapt standard community detection algorithms to account for this
Computational modelling of learning and teaching

In this chapter, we consider how computer models are being used to advance our understanding of learning within education. By the notion of 'model', we mean a simplified representation and implementation of a phenomenon that captures the key theoretical principles of its operation. In the case of computer models, the implementation of the model is in the form of a computer program. In educational neuroscience, computers are employed as model systems in two different but related ways. First, computers are used to understand the cognitive mechanisms that underlie the learning process. Second, computers are used as teaching tools that model the interaction of the teacher with the learner; these tools can take the form of intelligent tutoring systems or adaptive microworlds. Cognitive models and computer-based teaching tools are related in that both require an understanding of the learner and the way in which particular sets of experiences and kinds of feedback can advance the learner's knowledge. Indeed, some computer programs have been employed both as cognitive models and as the basis of intelligent tutoring systems (see later example of ACT-R). The two uses differ in that for cognitive models, the target of the model is the learning process taking place within the child or adult, while for the teaching tools, the target of the model is the behaviour of the human teacher and his or her interactions with the learner. Both approaches are concerned with individual differences. Cognitive modelling seeks to understand the causal mechanisms – be they of genetic or environmental origin – that lead to differences in learning outcomes. For the teaching tools, intelligent tutoring systems seek to tailor the knowledge and tasks that the individual learner must revisit to acquire a specific domain, given the successes and failures he or she has exhibited on previous tasks (an instructivist pedagogic model). 3 Adaptive microworlds contain a model of how a user can interact with a domain to construct an object or event; the program then adapts the difficulty of the task goal to the individual learner's performance on the last task (a constructionist pedagogic model). In terms of the dialogue between education and neuroscience, cognitive modelling demonstrates one active interface between the disciplines. Artificial neural networks are used to build models of learning based on the computational principles observed in actual neural circuits. To the extent that these cognitive models are successful, they will uncover the nature of …
On the symmetric information rate of two-dimensional finite-state ISI channels

We derive a pair of bounds (upper and lower) on the symmetric information rate of a two-dimensional finite-state intersymbol interference (ISI) channel model. For channels with small impulse response support, they can be estimated via a modified forward recursion of the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm. The convergence of the bounds is also analyzed. To relax the constraint on the size of the impulse response, a new upper bound is proposed which allows the tradeoff of the computational complexity and the tightness of the bound. These bounds are further extended to d-dimensional (d>2) ISI channels.
Automatic steering of behavioral model inference

Many testing and analysis techniques use finite state models to validate and verify the quality of software systems. Since the specification of such models is complex and time-consuming, researchers defined several techniques to extract finite state models from code and traces. Automatically generating models requires much less effort than designing them, and thus eases the verification and validation of large software systems. However, when models are inferred automatically, the precision of the mining process is critical. Behavioral models mined with imprecise processes can include many spurious behaviors, and can thus compromise the results of testing and analysis techniques that use those models. In this paper, we increase the precision of automata inferred from execution traces, by leveraging two learning techniques. We first mine execution traces to infer statistically significant temporal properties that capture relations between non consecutive and possibly distant events. We then incrementally refine a simple initial automaton by merging likely equivalent states. We identify equivalent states by analyzing set of consecutive events, and we use the inferred temporal properties to evaluate whether two equivalent states can be merged or not. We merge equivalent states only if the merging does violate any temporal property, since a merging that violates temporal properties is likely to introduce an imprecise generalization. Our generalization process that preserves temporal properties while merging states avoids breaking non-local relations, and thus solves one of the major cause of overgeneralized models. Thus, mined properties steer the learning of behavioral models. The technique is completely automated and generates an automaton that both accepts the input traces and satisfies the mined temporal properties. We evaluated our solution by comparing models inferred with and without checking mined temporal properties. Results show that our steering process can significantly improve precision without noticeable loss of recall.
A simplified constitutive model for predicting shape memory polymers deformation behavior

Shape memory polymers (SMPs) can keep a temporary shape after pre-deformation at a higher temperature and subsequent cooling. When they are reheated, their original shapes can be recovered. Such special characteristics of SMPs make them widely used in aerospace structures, biomedical devices, functional textiles and other devices. Increasing usefulness of SMPs motivates us to further understand their thermomechanical properties and deformation behavior, of which the development of appropriate constitutive models for SMPs is imperative. There is much work in literatures that address constitutive models of the thermo-mechanical coupling in SMPs. However, due to their complex forms, it is difficult to apply these constitutive models in the real world. In this paper, a three-element model with simple form is proposed to investigate the thermo-mechanical small strain (within 10%) behavior of polyurethane under uniaxial tension. Two different cases of heated recovery are considered: (1) unconstrained free strain recovery and (2) stress recovery under full constraint at a strain level fixed during low temperature unloading. To validate the model, simulated and predicted results are compared with Tobushi's experimental results and good agreement can be observed.
On the mechanisms of imitation in multi-agent systems

Imitation is a social learning method in which an individual observes and mimics another's actions. To implement imitation on robots, a number of questions should be answered, including what information should be copied during imitation, how to choose the behaviors to be copied and how to translate the observed behaviors. In this research, we aim to answer the first two questions in an experiment scenario with simulated agents. First, based on the content of information that is copied during imitation, we compare two different imitation methods, namely, imitation of actions only and imitation of actions and perceptions. It is shown that if the observed behaviors are highly context specific, imitating perceptions along with actions is beneficial compared to imitating actions only. Second, to answer the question of which behaviors to copy, we compared different selection strategies. It is shown that the agents can choose which behaviors to copy by checking the utility of observed behaviors by a trial and error mechanism.
Candida bracarensis Bloodstream Infection in an Immunocompromised Patient

ABSTRACT Candida bracarensis is a recently described Candida species which is phenotypically similar to Candida glabrata. A case of C. bracarensis bloodstream infection in a bone marrow transplant patient is described and confirms this organism as an opportunistic human pathogen. The organism can be distinguished from C. glabrata by its white color on CHROMagar and by DNA sequence analysis using D1/D2 and internal transcribed spacer (ITS) primers.