Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptation of a Luciferase Gene Reporter and lac Expression System to Borrelia burgdorferi

ABSTRACT The development of new genetic systems for studying the complex regulatory events that occur within Borrelia burgdorferi is an important goal of contemporary Lyme disease research. Although recent advancements have been made in the genetic manipulation of B. burgdorferi, there still remains a paucity of basic molecular systems for assessing differential gene expression in this pathogen. Herein, we describe the adaptation of two powerful genetic tools for use in B. burgdorferi. The first is a Photinus pyralis firefly luciferase gene reporter that was codon optimized to enhance translation in B. burgdorferi. Using this modified reporter, we demonstrated an increase in luciferase expression when B. burgdorferi transformed with a shuttle vector encoding the outer surface protein C (OspC) promoter fused to the luciferase reporter was cultivated in the presence of fresh rabbit blood. The second is a lac operator/repressor system that was optimized to achieve the tightest degree of regulation. Using the aforementioned luciferase reporter, we assessed the kinetics and maximal level of isopropyl-β-d-thiogalactopyranoside (IPTG)-dependent gene expression. This lac-inducible expression system also was used to express the gene carried on lp25 required for borrelial persistence in ticks (bptA). These advancements should be generally applicable for assessing further the regulation of other genes potentially involved in virulence expression by B. burgdorferi.
Visual Speech Analysis, Application to Arabic Phonemes

The aim of this work is to introduce a primary research on Arabic audiovisual analysis. Each language has multiple phonemes and visemes and each viseme can have multiple phonemes. The first part focuses on how to classify Arabic visemes from still images, whereas the second part shows the variation of Pitch for each viseme. We haven’t taken coarticulation of visemes in context. To evaluate the performance of the proposed method, we collected a large number of speech visual signal of ten Algerian speakers male and female at different moments pronouncing 28 Arabic syllabuses. In our work, we demonstrate 11 final visemes representing the 28 consonantal Arabic phonemes.
Genetic algorithm and forward method for feature selection in EEG feature space

There are a lot of problems that arise in the process of building a brain-computer interface based on electroencephalographic signals (EEG). A huge imbalance between a number of experiments possible to conduct and the size of feature space, containing features extracted from recorded signals, is one of them. To reduce this imbalance, it is necessary to apply methods for feature selection. One of the approaches for feature selection, often taken in brain-computer interface researches, is a classic genetic algorithm that codes all features within each individual. In this study, there will be shown, that although this approach al- lows obtaining a set of features of high classification precision, it also leads to a feature set highly redundant comparing to a set of features selected using a forward selection method or a genetic algorithm equipped with individuals of a given (very small) number of genes.
Belief Revision by Multi-Agent Genetic Search

The revision of beliefs is an important general purpose functionality that an agent must exhibit. The agent usually needs to perform this task in cooperation with other agents, because access to knowledge and the knowledge itself are distributed in nature. In this work, we propose a new approach for performing belief revision in a society of logic-based agents, by means of a (distributed) genetic algorithm, where the revisable assumptions of each agent are coded into chromosomes as bit-strings. Each agent by itself locally performs a genetic search in the space of possible revisions of its knowledge, and exchanges genetic information by crossing its revisable chromosomes with those of other agents. We have performed experiments comparing the evolution in beliefs of a single agent informed of the whole of knowledge, to that of a society of agents, each agent accessing only part of the knowledge. In spite that the distribution of knowledge increases the diiculty of the problem, experimental results show that the solutions found in the multi-agent case are comparable in terms of accuracy to those obtained in the single agent case. The genetic algorithm we propose, besides encompassing the Darwinian operators of selection, mutation and crossover, also comprises a Lamarckian operator that mutates the genes in a chromosome as a consequence of the chromosome phenotype's individual experience obtained while solving a belief revision problem. These chro-2 Lamma, Pereira, Riguzzi / Belief Revision by Multi-Agent Genetic Search mosomic mutations are directed by a (logic-based) belief revision procedure that relies on tracing the logical derivations leading to inconsistency of belief, so as to remove these derivations' support on the gene coded assumptions, eeectively by mutating the latter. Because of the use a Lamarckian operator, and following the literature, the genes in these chromosomes that are modiied by the Lamarckian operator are best dubbed \memes", since they code the memory of the experiences of an individual along its lifetime, besides being transmitted to its progeny. Due to the speciic nature of memes, we further gain in accuracy by modifying the Dar-winian crossover operator so that memes of an another agent can be acquired only if they have been checked for consistency, and possibly mutated, as a result of its own observational experience. We believe our method to be important for situations where classical belief revision methods hardly apply: those where environments are non-uniform and time changing. These can be explored by distributed …
Effects of valproic acid, a histone deacetylase inhibitor, on improvement of locomotor function in rat spinal cord injury based on epigenetic science.

BACKGROUND The primary phase of traumatic spinal cord injury (SCI) starts by a complex local inflammatory reaction such as secretion of pro-inflammatory cytokines from microglia and injured cells that substantially contribute to exacerbating pathogenic events in secondary phase. Valproic acid (VPA) is a histone deacetylase inhibitor. Acetylation of histones is critical to cellular inflammatory and repair processes. METHODS In this study, rats were randomly assigned to five experimental groups (laminectomy, untreated, and three VPA-treated groups). For SCI, severe contusion was used. In treated groups, VPA was administered intraperitoneally at doses of 100, 200 and 400 mg/kg daily three hours after injury for 7 days. To compare locomotor improvement among experimental groups, behavioral assessments were performed by the Basso, Beattie and Bresnahan (BBB) rating scale. The expression of neurotrophins was evaluated by RT-PCR and real-time PCR. RESULTS VPA administration increased regional brain-derived neurotrophic factor and glial cell-derived neurotrophic factor mRNA levels. Local inflammation and the expression of the lysosomal marker ED1 by activated macrophages/microglial cells were reduced by VPA and immunoreactivity of acetylated histone and microtubule-associated protein were increased. CONCLUSION The results showed a reduction in the development of secondary damage in rat spinal cord trauma with an improvement in the open field test (BBB scale) with rapid recovery.
Feature Selection and Classifier Parameters Estimation for EEG Signals Peak Detection Using Particle Swarm Optimization

Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. Two versions of PSO are used in the study: (1) standard PSO and (2) random asynchronous particle swarm optimization (RA-PSO). The proposed framework tries to find the best combination of all the available features that offers good peak detection and a high classification rate from the results in the conducted experiments. The evaluation results indicate that the accuracy of the peak detection can be improved up to 99.90% and 98.59% for training and testing, respectively, as compared to the framework without feature selection adaptation. Additionally, the proposed framework based on RA-PSO offers a better and reliable classification rate as compared to standard PSO as it produces low variance model.
Automatic Music Transcription using row weighted decompositions

Automatic Music Transcription (AMT) seeks to understand a musical piece in terms of note activities. Matrix decomposition methods are often used for AMT, seeking to decompose a spectrogram over a dictionary matrix of note-specific template vectors. The performance of these methods can suffer due to the large harmonic overlap found in tonal musical spectra. We propose a row weighting scheme that transforms each spectrogram frame and the dictionary, with the weighting determined by the effective correlations in the decomposition. Experiments show improved AMT performance.
Structural analysis of testicular appendices in patients with cryptorchidism.

OBJECTIVES Report the incidence and structure of testicular appendices (TAs) in patients with cryptorchidism, comparing their incidence with epididymal anomalies (EA) and patency of the vaginal process (PVP) and analyzes the structure of TAs. MATERIAL AND METHODS We studied 72 testes of patients with cryptorchidism (average of 6 years), and 8 testes from patients with hydroceles (average of 9 years). We analyzed the relations among the testis, epididymis and PVP and prevalence and histology of the TAs. The appendices of 10 patients with cryptorchidism and 8 with hydrocele were dissected and embedded in paraffin and stained with Masson trichrome; Weigert and Picro-Sirius Red with polarization and immunohistochemistry analysis of the collagen type III fibers to observe collagen. The stereological analysis was done with the software Image Pro and Image J, using a grid to determine volumetric densities (Vv). Means were statistically compared using the ANOVA and unpaired T test (p < 0.05). RESULTS Of the 72 testes with cryptorchidism, 20 (27.77%) presented EA, 41 (56.9%) had PVP and 44 (61.1%) had TAs. Of the 44 testes with cryptorchidism and appendices, 30 (68.18%) presented PVP and 11 (25%) presented EA. There was no alteration of the epithelium in the appendices of patients in both groups. Stereological analysis documented the prevalence of ESFs (mean of 1.48%), prevalence of veins (mean of 10.11%) and decrease (p = 0.14) of SMCs in the TAs of patients with cryptorchidism (mean = 4.93%). Collagen III prevailed in the TAs of patients with cryptorchidism. CONCLUSION The testicular appendices presented significant structural alteration in the patients with cryptorchidism, indicating that TAs present a structural remodeling.
Perception-guided global illumination solution for animation rendering

We present a method for efficient global illumination computation in dynamic environments by taking advantage of temporal coherence of lighting distribution. The method is embedded in the framework of stochastic photon tracing and density estimation techniques. A locally operating energy-based error metric is used to prevent photon processing in the temporal domain for the scene regions in which lighting distribution changes rapidly. A perception-based error metric suitable for animation is used to keep noise inherent in stochastic methods below the sensitivity level of the human observer. As a result a perceptually-consistent quality across all animation frames is obtained. Furthermore, the computation cost is reduced compared to the traditional approaches operating solely in the spatial domain.
Critical Success Factors of Location-Based Services

The objective of this study is to gain a comprehensive and holistic understanding of the critical success factors of location-based services. Electronic brainstorming technique was used to gather the opinions of an expert group of practitioners, researchers, and users on the critical success factors of location-based services. By grouping similar factors together based on past literature, 15 categories of critical success factors were identified. Information quality, personalizable or preference setting, and privacy are the three most mentioned critical success factors. For the next stage of this research, students will be recruited to rank and rate these critical success factors. The results of this research will highlight potential areas for research and development, and provide guidelines for practitioners to formulate strategies to increase consumer adoption.
Novel Formaldehyde-Activating Enzyme inMethylobacterium extorquens AM1 Required for Growth on Methanol

ABSTRACT Formaldehyde is toxic for all organisms from bacteria to humans due to its reactivity with biological macromolecules. Organisms that grow aerobically on single-carbon compounds such as methanol and methane face a special challenge in this regard because formaldehyde is a central metabolic intermediate during methylotrophic growth. In the α-proteobacterium Methylobacterium extorquens AM1, we found a previously unknown enzyme that efficiently catalyzes the removal of formaldehyde: it catalyzes the condensation of formaldehyde and tetrahydromethanopterin to methylene tetrahydromethanopterin, a reaction which also proceeds spontaneously, but at a lower rate than that of the enzyme-catalyzed reaction. Formaldehyde-activating enzyme (Fae) was purified from M. extorquens AM1 and found to be one of the major proteins in the cytoplasm. The encoding gene is located within a cluster of genes for enzymes involved in the further oxidation of methylene tetrahydromethanopterin to CO2. Mutants of M. extorquens AM1 defective in Fae were able to grow on succinate but not on methanol and were much more sensitive toward methanol and formaldehyde. Uncharacterized orthologs to this enzyme are predicted to be encoded by uncharacterized genes from archaea, indicating that this type of enzyme occurs outside the methylotrophic bacteria.
Regression Model Fitting under Differential Privacy and Model Inversion Attack

Differential privacy preserving regression models guarantee protection against attempts to infer whether a subject was included in the training set used to derive a model. It is not designed to protect attribute privacy of a target individual when model inversion attacks are launched. In model inversion attacks, an adversary uses the released model to make predictions of sensitive attributes (used as input to the model) of a target individual when some background information about the target individual is available. Previous research showed that existing differential privacy mechanisms cannot effectively prevent model inversion attacks while retaining model efficacy. In this paper, we develop a novel approach which leverages the functional mechanism to perturb coefficients of the polynomial representation of the objective function but effectively balances the privacy budget for sensitive and non-sensitive attributes in learning the differential privacy preserving regression model. Theoretical analysis and empirical evaluations demonstrate our approach can effectively prevent model inversion attacks and retain model utility.
A Survey on Failure Prediction of Large-Scale Server Clusters

As the size and complexity of cluster systems grows, failure rates accelerate dramatically. To reduce the disaster caused by failures, it is desirable to identify the potential failures ahead of their occurrence. In this paper, we survey the state of the art in failure prediction of cluster systems. The characteristic of failures in cluster systems are addressed, and some statistic results are shown. We explore the ways of the collection and preprocessing of data for failure prediction, and suggest a procedure for preprocessing the records in automatically generated log files. Focused on the main idea of five prediction methods, including statistic based threshold, time series analysis, rule-based classification, Bayesian network models and semi-Markov process models, are analyzed respectively. In addition, concerning the accuracy and practicality, we present five metrics for evaluating the failure prediction techniques and compare the five techniques with the five metrics.
Factors Affecting Long-term Myopic Regression after Laser In Situ Keratomileusis and Laser-assisted Subepithelial Keratectomy for Moderate Myopia

Purpose High myopia is known to be a risk factor for long-term regression after laser refractive surgery. There have been few studies about the correction of moderate myopias that did not need retreatment after long-term follow-up. We evaluated 10 years of change in visual acuity and refractive power in eyes with moderate myopia after laser refractive surgery. Methods We included patients that had undergone laser in situ keratomileusis (LASIK) or laser-assisted subepithelial keratectomy (LASEK) to correct their myopia and that had at least 10 years of follow-up. We evaluated the stability of visual acuity in terms of safety, efficacy, and refractive changes at examinations 6 months and 1, 2, 5, 7, and 10 years after surgery. Results The study evaluated 62 eyes (36 eyes in LASIK patients and 26 eyes in LASEK patients). In both groups, the efficacy index tended to decrease, and it was consistently higher in the LASEK group compared to the LASIK group over the 10 years of follow-up. The safety index improved over 10 years and was always higher than 0.9 in both groups. The difference between the spherical equivalent at 6 months postoperatively and later periods was statistically significant after 5, 7, and 10 years in both groups (LASIK, p = 0.036, p = 0.003, and p < 0.001, respectively; LASEK, p = 0.006, p = 0.002, and p = 0.001, respectively). Ten years after surgery,26 eyes (66.7%) in the LASIK group and 19 eyes (73.1%) in the LASEK group had myopia greater than 1 diopter. In comparison with the thickness at 6 months postoperatively, central corneal thickness was significantly increased after 5, 7, and 10 years in both LASIK and LASEK groups (LASIK, p < 0.001, p < 0.001, and p < 0.001, respectively; LASEK, p = 0.01, p < 0.001, and p < 0.001, respectively). Conclusions Moderately myopic eyes showed progressive myopic shifting and corneal thickening after LASIK and LASEK during 10 years of follow-up. We also found that early refractive regression may indicate the long-term refractive outcome.
Modeling Percentage Change of fMRI BOLD Signal and Reaction Time of a Dual Task with a Queuing Network Modeling Approach

To model the percentage change of blood oxygenation leveldependent (BOLD) signal and reaction time in a dual task, we propose a new mathematical modeling approach—a queuing network approach based on queuing network theory of human performance (Liu, 1996, 1997) and current discoveries in neuroimage studies. This approach includes a queuing network architecture representing the information processing in the brain and mathematical equations to quantify the reaction time, BOLD signal and its percentage signal change (PSC). Both reaction time and the percentage change of BOLD signal in an fMRI study of the dual task are successfully modeled with analytical solutions of the mathematical equations, which demonstrates its usefulness and parsimony in modeling the brain activation pattern and human performance simultaneously. Furthermore, the current modeling approach uniquely quantifies the queuing mechanism discovered by the fMRI study and also provides a coherent and quantitative linkage between the neural signals and behavioral data. Further extension and development of the current modeling approach are discussed.
Analysis of QoS in next generation wireless networks

IP technology will play a key role in next generation wireless networks, which face the great challenge of integration in order to provide seamless service to users anywhere and anytime. On the basis of the architecture for Qos in next generation wireless network, a coordinated call admission control mechanism was presented, providing an end-to-end RSVP context transfer for real-time applications to overcome the weakness of the context transfer protocol which cannot meet the need of end-to-end QoS mechanisms because the contexts were only transferred between the previous and new access routers. This mechanism decreased the delay caused by re-initiate QoS signaling from scratch to reestablish QoS forwarding process, and minimized the handover service disruption.
Synthetic biology - putting engineering into biology

Synthetic biology is interpreted as the engineering-driven building of increasingly complex biological entities for novel applications. Encouraged by progress in the design of artificial gene networks, de novo DNA synthesis and protein engineering, we review the case for this emerging discipline. Key aspects of an engineering approach are purpose-orientation, deep insight into the underlying scientific principles, a hierarchy of abstraction including suitable interfaces between and within the levels of the hierarchy, standardization and the separation of design and fabrication. Synthetic biology investigates possibilities to implement these requirements into the process of engineering biological systems. This is illustrated on the DNA level by the implementation of engineering-inspired artificial operations such as toggle switching, oscillating or production of spatial patterns. On the protein level, the functionally self-contained domain structure of a number of proteins suggests possibilities for essentially Lego-like recombination which can be exploited for reprogramming DNA binding domain specificities or signaling pathways. Alternatively, computational design emerges to rationally reprogram enzyme function. Finally, the increasing facility of de novo DNA synthesis-synthetic biology's system fabrication process-supplies the possibility to implement novel designs for ever more complex systems. Some of these elements have merged to realize the first tangible synthetic biology applications in the area of manufacturing of pharmaceutical compounds.
ICN-RE: redundancy elimination for information-centric networking

This paper bridges Information-Centric Networking (ICN), a novel form of networking centered around information or content, and Redundancy Elimination (RE), a popular technique widely used to identify content with similar bytestream. The result is ICN-RE, the first ICN design that supports redundancy elimination. We show by means of numerical evaluations that ICN-RE improves bandwidth efficiency by 15-40% compared to vanilla ICN, and that the state of the art hardware can support ICN-RE at line speeds up to 100Gbps. Also, we discuss several benefits of adopting ICN-RE as a networkwide RE solution when compared to state of the art redundancy elimination designs.