Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel CpG island methylation panel predicts survival in lung adenocarcinomas

The lack of clinically useful biomarkers compromise the personalized management of lung adenocarcinomas (ADCs); epigenetic events and DNA methylation in particular have exhibited potential value as biomarkers. By comparing genome-wide DNA methylation data of paired lung ADCs and normal tissues from 6 public datasets, cancer-specific CpG island (CGI) methylation changes were identified with a pre-specified criterion. Correlations between DNA methylation and expression data for each gene were assessed by Pearson correlation analysis. A prognostically relevant CGI methylation signature was constructed by risk-score analysis, and was validated using a training-validation approach. Survival data were analyzed by log-rank test and Cox regression model. In total, 134 lung ADC-specific CGI CpGs were identified, among which, a panel of 9 CGI loci were selected as prognostic candidates, and were used to construct a risk-score signature. The novel CGI methylation signature was identified to classify distinct prognostic subgroups across different datasets, and was demonstrated to be a potent independent prognostic factor for overall survival time of patients with lung ADCs. In addition, it was identified that cancer-specific CGI hypomethylation of RPL39L, along with the corresponding gene expression, provided optimized prognostication of lung ADCs. In summary, cancer-specific CGI methylation aberrations are optimal candidates for novel biomarkers of lung ADCs; the 9-CpG methylation panel and hypomethylation of RPL39L exhibited particularly promising significance.
Workflow Scheduling Algorithms in the Grid

The development of wide-area networks and the availability of powerful computers as low-cost commodity components are changing the face of computation. These progresses in technology make it possible to utilize geographically distributed resources in multiple owner domains to solve large-scale problems in science, engineering and commerce. Research on this topic has led to the emergence of Grid computing. To achieve the promising potentials of tremendous distributed resources in the Grid, effective and efficient scheduling algorithms are fundamentally important. However, scheduling problems are well known for their intractability, and many of instances are in fact NP-Complete. The situation becomes even more challenging in the Grid circumstances due to some unique characteristics of the Grid. Scheduling algorithms in traditional parallel and distributed systems, which usually run on homogeneous and dedicated resources, cannot work well in the new environments. This work focuses on workflow scheduling algorithms in the Grid scenario. New challenges are discussed, previous research in this realm is surveyed, and novel heuristic algorithms addressing the challenges are proposed and tested. The proposed algorithms contribute to the literature by taking the following factors into account when a schedule for a DAG-based workflow is produced: predictable performance fluctuation and non-deterministic performance model of Grid resources, the computation and data staging co-scheduling, the clustering characteristic of Grid resource distribution, and the ability to reschedule according to performance change after the initial schedule is made. The performance of proposed algorithms are tested and analyzed by simulation under different workflow and resource configurations.
A new group detection strategy for DS/CDMA systems

We present a new group detection strategy for asynchronous DS/CDMA systems. The new detector is a two-stage one: the first stage is a linear filter, aimed at suppressing the effect of the unwanted users signals, while the second stage is a non-linear block, implementing a maximum likelihood (ML) detection rule on the set of desired users signals. Simulation results confirm that the new structure, which encompasses Varanasi's (1995) group detector as a special case, achieves very satisfactory performance.
Extraction of contextual knowledge and ambiguity handling for ontology in virtual environment

This dissertation investigates the extraction of knowledge from a known environment. Virtual ontology – the extracted knowledge – is defined as a structure of a virtual environment with semantics. While many existing 3D reconstruction approaches can generate virtual environments without structure and related knowledge, the use of Metaearth architecture is proposed as a more descriptive data structure for virtual ontology. Its architecture consists of four layers: interactions and relationships between virtual components can be represented in the virtual space layer; and the library layers contribute to the design of large-scale virtual environments with less redundancy; and the mapping layer links the library layer to the virtual space layer; and the ontology layer functions as a context for the extracted knowledge. The dissertation suggests two construction methodologies. The first method generates a scene structure from a 2D image. Unlike other scene understanding techniques, the suggested method generates scene ontology without prior knowledge and human intervention. As an intermediate process, a new and effective fuzzy color-basedover-segmentation method is suggested. The second method generates virtual ontology with 3D information using multi-view scenes. The many ambiguities in extracting 3D information are resolved by employing a new fuzzy dynamic programming method (FDP). The hybrid approach of FDP and 3D reconstruction method generates more accurate virtual ontology with 3D information. A virtual model is equipped with virtual ontology whereby contextual knowledge can be mapped into the Metaearth architecture via the proposed isomorphic matching method. The suggested procedure guarantees the automatic and autonomous processing demanded in virtual interaction analysis with far less effort and computational time.
Revising the scanning plan for continued visual exploration: the neurophysiology of refixation-related behavior

Abstract Regarding the continued exploration of a visual scene, little is known about how far ahead we plan our eye-movements. We propose that when the eyes return to a previously visited location, this refixation may have already been planned at the initial visit, i.e., at the precursor fixation. Precursor fixations are effective markers of strategic locations for later scrutiny. This implies visual processing is enhanced at precursor fixations. Moreover, since marking involves updating the scanning plan, activation of oculomotor control routines may also be expected. The opposite is expected when refixations are only made to recover information lost or missed during scanning. However, the eye-movement literature so far has ignored precursor fixations. Using EEG-eye movement co-registration in a natural viewing task, we analyzed fixation-related EEG in precursor fixations, ordinary fixations, and refixations. The analysis crucially involved matching potentially confounding eye movement characteristics between fixation types. In precursor fixations, amplitude of fixation-related potentials over posterior areas was increased and EEG alpha power over frontal areas was decreased, compared to ordinary fixations. These findings, respectively, indicate enhanced rather than deficient visual processing at precursor fixations and enhanced oculomotor control activity. Our results question the major role of refixations as compensating for lost information and support the proposal of periodic updating of saccade planning at precursor fixations in the course of visual exploration.
Plants of Nepeta cataria var. citriodora Beck. and essential oils from them for food industry

Nepeta cataria var. citriodora Beck. (catmints) is a source industrial production of citral and attractive raw material for food industry and cooking. Aerial part of Nepeta are characterized by high antimicrobial activity and fungicidal action against mold fungi, used in folk medicine, as ingredient in recipes for sausages, liqueurs and soft drinks, vegetable and fruit canned food, in the manufacture of vermouth. Ukrainian variety 'Melody' was created specifically for growing in the Forest-Steppe zone, and variety 'Peremozhets' – in the Steppe zone. Data on the yield aerial part and essential oil Nepeta was determined. The dry aerial part of plants N. cataria we used to create a dry spicy mixture for sweet dessert dishes. Quantitative content and qualitative composition of essential oil of plants by organs and phases of vegetation are presented in the article. In our research we used essential oils obtained by hydro distillation procedure for 2 h using Clevendger-type apparatus from the flowering parts of plants N. cataria 'Peremozhets' and 'Melody'. Investigate of components was carried out by high effective gas chromatography with HP 6890 chromatograph coupled with HP 5972 mass selective detector. The most abundant components of Nepeta essential oil was citral, geraniol, as well as nerol, citronellol, citronellal, carvacrol, camphor, eugenol. We proposed fractional distillation of essential oils to obtain a line of flavors with stable sensory and physicochemical indicators for food industry. The separation of essential oils into fractions was carried out on a pilot installation of fractional distillation DFD (Device of Fractional Distillation). Calculations of parameters controlled dispersal of essential oils (residual pressure, temperature regimes, number of theoretical plates, reflux number) were carried out. During fractionation of essential oil of N. cataria four fractions were obtained with a content of 96 ±0.5% to the total mass of samples. Sensory and physicochemical analysis of aromatic fractions announced them as promising flavours for food industry.
Targeting destabilized DNA G-quadruplexes and aberrant splicing in drug-resistant glioblastoma

Temozolomide (TMZ) is a chemotherapy agent that adds mutagenic adducts to guanine, and is first-line standard of care for the aggressive brain cancer glioblastoma (GBM). Methyl guanine methyl transferase (MGMT) is a DNA repair enzyme that can remove O6-methyl guanine adducts prior to the development of catastrophic mutations, and is associated with TMZ resistance. However, inhibition of MGMT fails to reverse TMZ resistance. Guanines are essential nucleotides in many DNA and RNA secondary structures. In several neurodegenerative diseases (NDs), disruption of these secondary structures is pathogenic. We therefore took a structural view of TMZ resistance, seeking to establish the role of guanine mutations in disrupting critical nucleotide secondary structures. To test whether these have functional impacts on TMZ-resistant GBM, we focused on two specific guanine-rich regions: G-quadruplexes (G4s) and splice sites. Here we report broad sequence- and conformation-based changes in G4s in acquired or intrinsic TMZ resistant vs. sensitive GBM cells, accompanied by nucleolar stress and enrichment of nucleolar RNA:DNA hybrids (r-loops). We further show widespread splice-altering mutations, exon skipping, and deregulation of splicing-regulatory serine/arginine rich (SR) protein phosphorylation in TMZ-resistant GBM cells. The G4-stabilizing ligand TMPyP4 and a novel inhibitor of cdc2-like kinases (CLKs) partially normalize G4 structure and SR protein phosphorylation, respectively, and are preferentially growth-inhibitory in TMZ-resistant cells. Lastly, we report that the G4- and RNA-binding protein EWSR1 forms aberrant cytoplasmic aggregates in response to acute TMZ treatment, and these aggregates are abundant in TMZ resistant cells. Preliminary evidence suggests these cytoplasmic EWSR1 aggregates are also present in GBM clinical samples. This work supports altered nucleotide secondary structure and splicing deregulation as pathogenic features of TMZ-resistant GBM. It further positions cytoplasmic aggregation of EWSR1 as a potential indicator for TMZ resistance, establishes the possibility of successful intervention with splicing modulatory or G4-targeting agents, and provides a new context in which to study aggregating RNA binding proteins.
A systems chemoproteomic analysis of acyl-CoA/protein interaction networks

Acyl-CoA/protein interactions are required for many functions essential to life including membrane synthesis, oxidative metabolism, and macromolecular acetylation. However, despite their importance, the global scope and selectivity of these protein-metabolite interactions remains undefined. Here we describe the development of CATNIP (CoA/AcetylTraNsferase Interaction Profiling), a chemoproteomic platform for the high-throughput analysis of acyl-CoA/protein interactions in endogenous proteomes. First, we apply CATNIP to identify acetyl-CoA-binding proteins through unbiased clustering of competitive dose-response data. Next, we use this method to profile diverse protein-CoA metabolite interactions, identifying biological processes susceptible to altered acetyl-CoA levels. Finally, we apply systems-level analyses to assess the features of novel protein networks that may interact with acyl-CoAs, and demonstrate a strategy for high-confidence proteomic annotation of acetyl-CoA binding proteins. Overall our studies illustrate the power of integrating chemoproteomics and systems biology, and provide a resource for understanding the roles of acyl-CoA metabolites in biology and disease.
Noisy optimal control strategies for modelling saccades

Eye movements have for a while provided us a closer view into how the brain commands the body. Particularly interesting are saccades: fast and accurate eye movements that allow us to scan our visual surroundings. One observation is that motor commands issued by the brain are corrupted by a signal-dependent noise. Moreover, the variance of the signal scales linearly with the control signal squared. It is assumed that such uncertainty in the dynamics introduces a probability distribution of the eye that the brain accounts for during motion planning. We propose a framework for computing the optimal control law for arbitrary dynamical systems, subject to noise, and where the cost function depends on a statistical distribution of the eye’s position. A key contribution of this framework is estimating the endpoint distribution of the plant using Monte Carlo sampling, which is done efficiently using commodity graphics hardware in parallel. We then describe a modified form of gradient descent for computing the optimal control law for an objective function prone to stochastic effects. We compare our approach to other methods, such as downhill simplex and Covariance-Matrix-Adaptation, which are considered “gradient-free” approaches to optimization. We finally conclude with several examples that show the framework successfully controlling saccades for different plant models of the oculomotor system: this includes a 3D torque-based model of the eye, and a a nonlinear model of the muscle actuator that drives the eye.
Remnant forest in Costa Rican working landscapes fosters bird communities that are indistinguishable from protected areas

The outcome of the ongoing biodiversity crisis depends on the capacity of the Earth’s wildlife to persist in working landscapes. Yet, the species that occupy working landscapes are often distinct from those in protected areas, with a large group of “sensitive species” thought to rarely venture into human‐dominated landscapes. As governments have committed to restoring degraded lands world‐wide, determining whether and how working landscapes can be restored to benefit sensitive species remains a major challenge. We surveyed Neotropical birds across Northwestern Costa Rica in protected areas, farms and forests embedded within working landscapes. We analysed community composition to understand how gradients of forest cover, fragmentation and regional precipitation determine how conserving (or restoring) tropical forests in working landscapes could safeguard entire communities, especially sensitive species with limited ranges. We found agricultural sites maintained relatively high bird diversity but hosted very distinct communities from those found in protected areas. The average range size of species found in agricultural communities was double the size of species in protected areas. However, high forest cover sites in working landscapes housed bird communities with small range sizes that were equivalent to those in nearby protected areas, despite being twice as fragmented and significantly more disturbed. The effect of local forest cover on bird composition was contingent on both landscape context and regional climate. When local forest cover increased in wetter regions and more forested landscapes, bird communities in working landscapes exhibited a stronger shift towards the assemblages found in protected areas. Specifically, we found that reforesting the wettest sites would increase similarity to protected areas fourfold compared to only a twofold increase in the driest sites. Synthesis and applications. Despite experiencing much more fragmentation and degradation than protected areas, forests in Costa Rican working landscapes can maintain bird communities that strongly resemble those found in protected areas. This suggests that conserving or restoring forests in working landscapes, particularly within wetter regions and already forested landscapes, may safeguard bird communities when creating protected areas is infeasible.
How do changes in environmental conditions affect stress-tolerant and competitive species in wet grasslands.

As a result of changing temperature, water availability and nutrient availability plant diversity is declining. In particular wet grassland species suffer from fluctuating precipitation and competition with other plant species that are better adapted to environmental changes. Recent studies are suggesting that survival of species under such circumstances is dependent on the survival strategy that a species utilizes. In this study I test this hypothesis by using a diverse group of wet, mesotrophic and oligotrophic, grassland species. These species are subjected to a period of 2/3 weeks of drought and shade to simulate the environmental changes. Changes in photochemical efficiency, dryweight/freshweight ratio, rootweight/shootweight ratio, leafweight/stemweight ratio, Specific Leaf Area and stomatal density were measured after the treatment. Plants from different survival strategies were compared under each treatment. This study found that none of the plants adjusted physiological characteristics to the imposed environmental changes. Furthermore no expressed plasticity was found in plants despite differences in survival strategy and treatment. Overall it is concluded that plants barely apply plasticity when they reach an optimal state. This implicates that mesotrophic and oligotrophic grassland communities are more vulnerable for environmental changes rather than competition. The absence of plasticity effects in this study increases the importance of genetic diversity of the plant community. Habitat fragmentation is therefore thought to be a primary cause for the loss of biodiversity. Grasslands are indeed highly fragmented in the Lowlands. Creating sustainable oligotrophic grasslands is thus dependent on restoration efforts. Which in turn are dependent to changes in agricultural land use of the surrounding areas.
SIGNS OF INFLAMATION IN THE AIRWAYS IN CHILDREN WITH EXERCISE-INDUCED BRONCHIAL ASTHMA

The study basing on examination of 102 children with bronchial asthma defines indices of inflammatory activity in the airways and sets the diagnostic value of these indices as tests for verification exercise-induced bronchial asthma. The children with no signs of exercise-induced asthma compared to patients having them, were shown to experience some changes in the exhaled breath condensate, indicating a higher activity of inflammation in the airways. The content of nitrogen monoxide metabolites less than 50 mcmol/L or markers of proteolytic activity by azocol lysis less than 0.2 ml/hour in pulmonary expiration products increase the chances of having exercise-induced bronchial asthma phenotype with these tests sensitivity within 66.7-75.7%.
Opinion Mining Framework in the Education Domain

— The internet is growing larger and becoming the most popular platform for the people to share their opinion in different interests. We choose the education domain specifically comparing some Malaysian universities against each other. This comparison produces benchmark based on different criteria shared by the online users in various online resources including Twitter, Facebook and web pages. The comparison is accomplished using opinion mining framework to extract, process the unstructured text and classify the result to positive, negative or neutral (polarity). Hence, we divide our framework to three main stages; opinion collection (extraction), unstructured text processing and polarity classification. The extraction stage includes web crawling, HTML parsing, Sentence segmentation for punctuation classification, Part of Speech (POS) tagging, the second stage processes the unstructured text with stemming and stop words removal and finally prepare the raw text for classification using Named Entity Recognition (NER). Last phase is to classify the polarity and present overall result for the comparison among the Malaysian universities. The final result is useful for those who are interested to study in Malaysia, in which our final output declares clear winners based on the public opinions all over the web.
Functional divergence and natural selection underlying genome wide introgressive hybridization of protein coding genes between the Algerian mouse (Mus spretus) and the house mouse (Mus musculus domesticus)

Functional divergence and natural selection underlying genome wide introgressive hybridization of protein coding genes between the Algerian mouse (Mus spretus) and the house mouse (Mus musculus domesticus) by Eslam Mohamed Mohamed Elshahat Genome-wide introgression has been reported between two mouse species in Europe, Mus musculus domesticus (the western European house mouse) and Mus spretus (the Algerian mouse). Introgression was observed outside the area of sympatry between the two species. My dissertation is an attempt to understand introgression in ideal biological species and to determine how introgression affects genome evolution using the house mouse as a model for study. I used genome-wide diversity array data from 45 M. m. domesticus and 6 M. spretus mice, as well as 67 whole genome sequences from Mus genus species. I calculated the molecular evolutionary rates of protein-encoding genes in the two mouse species and studied the functionality of the introgressed genes. I sought to determine if introgression in mice is a rare or frequent phenomenon. Introgression between the two species affected large portions (almost 135 Mb) of the M. m. domesticus genome. I also studied the directionality of introgression and concluded that it is a bidirectional process; the flow of genetic material favored the M. spretus-to-M. m. domesticus direction. I investigated the geographical distribution and the genic content of introgressed tracts. Most introgressions occur in genomic regions that contain genes, and most introgressed genes contain nonsynonymous mutations. Introgressed genes have a wide variety of biological functions. Genes encoding olfactory receptors and proteins involved in immune responses were among the most frequently introgressed. The largest introgressed fragments were found in chromosome 7 and contained the Vkorc1 gene, which is a gene responsible for resistance to anticoagulant rodenticides. I explored the Mus genetic polymorphisms in introgressed fragments using M. spretus, M. m. domesticus, M. m. musculus, and M. m. castaneus. I concluded that the history of the Mus likely is complex and may affect studies with aim to detect introgressive hybridization. Introgressive hybridization plays an important role in introducing adaptive genetic mutations. An improved understanding of how species hybridize and exchange genes in nature will help us to better understand adaptation and evolution.