Miracle-dz/UniFAR-FTUs huggingface dataset:
Expansion Mechanisms and Functional Annotations of Hypothetical Genes in the Rice Genome[W]

In each completely sequenced genome, 30% to 50% of genes are annotated as uncharacterized hypothetical genes. In the rice (Oryza sativa) genome, 10,918 hypothetical genes were annotated in the latest version (release 6) of the Michigan State University rice genome annotation. We have implemented an integrative approach to analyze their duplication/expansion and function. The analyses show that tandem/segmental duplication and transposition/retrotransposition have significantly contributed to the expansion of hypothetical genes despite their different contribution rates. A total of 3,769 hypothetical genes have been detected from retrogene, tandem, segmental, Pack-MULE, or long terminated direct repeat-related duplication/expansion. The nonsynonymous substitutions per site and synonymous substitutions per site analyses showed that 21.65% of them were still functional, accounting for 7.47% of total hypothetical genes. Global expression analyses have identified 1,672 expressed hypothetical genes. Among them, 415 genes might function in a developmental stage-specific manner. Antisense strand expression and small RNA analyses have demonstrated that a high percentage of these hypothetical genes might play important roles in negatively regulating gene expression. Homologous searches against Arabidopsis (Arabidopsis thaliana), maize (Zea mays), sorghum (Sorghum bicolor), and indica rice genomes suggest that most of the hypothetical genes could be annotated from recently evolved genomic sequences. These data advance the understanding of rice hypothetical genes as being involved in lineage-specific expansion and that they function in a specific developmental stage. Our analyses also provide a valuable means to facilitate the characterization and functional annotation of hypothetical genes in other organisms.
PART OF A SPECIAL ISSUE ON FUNCTIONAL -STRUCTURAL PLANT MODELLING An approach to multiscale modelling with graph grammars

†Background and Aims Functional–structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. †Methods A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. †KeyResults Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. †Conclusions The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with singlescale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.
Adaptive filtering using filter banks and sparse subfilters

Some convergence properties of an adaptive filter structure which employs an analysis filter bank and sparse adaptive subfilters are investigated in this paper. By properly choosing the filter bank and the number of adaptive coefficients, such a structure is capable of modeling any linear system with finite impulse response (FIR). Using the analysis results derived in this paper, an optimization procedure is described to select the prototype filter of a cosine modulated filter bank that results in the best convergence rate for a given input signal statistics. The convergence behavior of the proposed subband adaptation algorithm is verified by computer simulations and compared to the behavior of previously proposed algorithms. It is shown that significant improvement in the convergence rate can be obtained with the sparse subband structure using very simple filter banks, when compared to the conventional direct-form LMS algorithm, for colored input signals.
Progenitor cells in vascular disease

Stem cell research has the potential to provide solutions to many chronic diseases via the field of regeneration therapy. In vascular biology, endothelial progenitor cells (EPCs) have been identified as contributing to angiogenesis and hence have therapeutic potential to revascularise ischaemic tissues. EPCs have also been shown to endothelialise vascular grafts and therefore may contribute to endothelial maintenance. EPC number has been shown to be reduced in patients with cardiovascular disease, leading to speculation that atherosclerosis may be caused by a consumptive loss of endothelial repair capacity. Animal experiments have shown that EPCs reendothelialise injured vessels and that this reduces neointimal formation, confirming that EPCs have an atheroprotective effect. Smooth muscle cell accumulation in the neointimal space is characteristic of many forms of atherosclerosis, however the source of these cells is now thought to be from smooth muscle progenitor cells (SMPCs) rather than the adjacent media. There is evidence for the presence of SMPCs in the adventitia of animals and that SMPCs circulate in human blood. There is also data to support SMPCs contributing to neointimal formation but their origin remains unknown. This article will review the roles of EPCs and SMPCs in the development of vascular disease by examining experimental data from in vitro studies, animal models of atherosclerosis and clinical studies.
Competition, Market Structure, and Bid‐Ask Spreads in Stock Option Markets

This paper examines the effects of competition and market structure on equity option bid-ask spreads from 1986 to 1997. Options listed on multiple exchanges have narrower spreads than those listed on a single exchange, but the difference diminishes as option volume increases. Option spreads become wider when a competing exchange delists the option. Options traded under a "Designated Primary Marketmaker" (DPM) have narrower quoted spreads than those traded in a traditional open outcry crowd. Effective spreads are found to be slightly narrower under the DPM than in the crowd, but only since 1992, and only on low-volume options. Copyright The American Finance Association 2002.
Color coding for visualization of the directional information of DTI

A new color coding scheme which can fully retrieve the directional information of diffusion tensor image (DTI) with maximum use of the color space is proposed and implemented. This new scheme overcomes the loss of directional information in conventional schemes and easy to implement. Comparison between the new scheme and the conventional color coding method are presented using the DTI data of human brain.
Performance Management of Optical Transport Networks through Time Series Forecasting

As the importance of the Internet increases, developing technologies for data transmission at higher bit rates became as important as challenging. Optical Transport Networks (OTN), based on Wavelength Division Multiplexing (WDM), emerged to meet this need. ITU has standardized OTN, including its management functions. Network elements in OTN store performance monitoring information as time series of performance events, which could be explored to enable more efficient preventive maintenance and better resource provisioning. With the use of time series forecasting models, faults could even be avoided, along with Service Level Agreement breaches. In this work, we propose the use of time series forecasting in performance monitoring of OTN, investigating how three forecasting methods behave in scenarios of stability and degradation in network performance and how the number of monitoring intervals affects their accuracy. In accordance with results we state recommendations for application of tested time series forecasting methods in managing OTN.
Classification of Satellite Images based on Scale-Invariant Feature Transform

From the immense amount of images being sent to Earth by satellites, it takes too much time for a human to go through each image and classify what the image represents. Therefore, we are able to use classifiers to classify these images. In this paper, we used two different classification methods to classify satellite images. Between the two classifiers we used, both K-Nearest-Neighbor and Support Vector Machines showed promising results for image classification in satellite images. In the future, we hope to find certain characteristics of satellite images in order to enhance the performance of classifiers.
Interactive control of holographic optical traps with fast hologram generation

Holographic optical tweezers (HOTs) make use of computer generated holograms to manipulate multiple optical traps. Uptill now, various algorithms have been proposed to calculate the hologram patterns. However the update rate of such holograms for a spatial light modulator (SLM) is often restricted to around 10Hz due to the slow computation in computer, limiting fast manipulation of optical traps in real-time. In this paper, we present the method and control software for interactive control of holographic optical traps with fast hologram generation by increasing the update rate of holograms. The developed software is written in Visual C++ platform and is capable of computing complex holograms with an update rate of 55 Hz, regardless of the number of traps. For experimental demonstrations, we show three dimensional, real-time manipulations of 5 µm polystyrene beads.
Feature selection using genetic algorithm to improve classification in network intrusion detection system

In this paper, we present Genetic Algorithm based optimized feature selections for intrusion detection systems. We used one-point crossover for the Genetic Algorithm parameters instead of two-point crossover used by the previous research as it one-point crossover is faster. For evaluations, we used the NSL-KDD Cup 99 data set and we modified the data set by looking into to the recent attacks, hence making the data set more relevant to the current situations. Several classifiers were used on these data sets and we found that Random Forest gave the best results in terms of the classification rate and the training time. The results also showed that our parameters performed better in these two metrics and the classifications using our optimized features on the modified data sets gave mixed results compared to ones with the original features.
Molecular-dynamics study of a supercooled two-component Lennard-Jones system.

Molecular-dynamics (MD) simulations have been carried out on a two-component Lennard-Jones system, quenched into supercooled and amorphous states. Two different regimes of viscous behavior are found in the time window accessible in MD simulation studies (of the order of nanoseconds if units appropriate for argon are used). The results for the time dependence of the self-intermediate scattering function ${\mathit{F}}^{\mathit{s}}$(q,t) show two different slow relaxation processes, where the slowest (\ensuremath{\alpha} relaxation) can be represented by a stretched exponential, exp[-(t/${\mathrm{\ensuremath{\tau}}}_{\mathrm{rel}}$${)}^{\mathrm{\ensuremath{\beta}}}$]. In the frequency domain this gives rise to a quasielastic peak, and it is found that its area, the nonergodicity parameter ${\mathit{f}}^{\mathit{s}}$(q)==a, shows an anomalous decrease when increasing the temperature towards a critical value ${\mathit{T}}_{\mathit{c}}$. This happens in the supercooled-liquid regime, and it is one of the basic predictions of the recent mode-coupling theory for the liquid-glass transition problem. In the strongly supercooled-liquid regime the diffusion is of the hopping type, and it is found to be strongly cooperative in nature.
Implementation of a Computerized Algorithmic Support Tool for Identifying Depression and Anxiety at the Pediatric Well-Child Visit

The high prevalence of unaddressed mental health problems among children and adolescents has received a considerable amount of public attention in recent years with a growing demand for a greater role for pediatric primary care in detecting and managing mental health problems. Indeed, the pediatric primary care setting possesses a number of assets that make it well poised to take on an expanded role. More than 90% of children across all economic and ethnic populations use pediatric primary care services providing a unique opportunity to universally detect mental health problems early and connect children to mental health services. Also, the long-term nature of pediatricians’ relationships with families is conducive to continued mental health surveillance and monitoring across the course of child development. Despite these strengths, evidence indicates that pediatricians are not systematically screening for mental health problems, and when they do, tend to rely on suboptimal procedures that fail to utilize best-practice, evidence-based screening, and assessment strategies. These shortcomings stem from a number of systemic and practice-level barriers including insufficient training, practical resources, time required to administer and score standardized instruments, guidance interpreting results, and options for referring children identified as needing mental health services. The current study examines implementation of a computerized algorithmic support tool that facilitates screening and assessment of depression and anxiety in pediatric primary care and provides referral and treatment guidance. The algorithm incorporates standardized, psychometrically sound screening and next level assessment instruments for detecting clinically significant pediatric depression and anxiety. Pediatricians are prompted to enter demographic data and information indicating the existence of significant risk factors including family history of mental health problems and current family stress or loss. Next, caregivers complete the Pediatric Symptom Checklist (PSC-17). Patients with total scores greater or equal to 15 or who score positive on the depression subscale (sum ≥5 on items 1-5) complete a follow-up assessment—the Patient Health Questionnaire (PHQ-9; ≥5 is clinical threshold) for children older than 12 years and the Center for Epidemiological Studies Depression Scale (CESD; ≥15 is clinical threshold) for children 12 years old or younger. Patients with total scores greater or equal to 15 or who are positive on the anxiety subscale (≥2 on item 4) complete the Self-Report for Childhood Anxiety Related Disorders (SCARED; ≥25 is clinical threshold). The algorithm then summarizes the data from these reports and prompts pediatricians to choose 1 of 11 clinical dispositions, each with clinical recommendations (see Figure 1). The computerized algorithmic support tool was implemented in 4 pediatric primary care practices over a 6-month period for administration at all wellchild visits.
BRAVO: A black-hole resilient ad-hoc on demand distance Vector rOuting for tactical communications

Mobile Ad Hoc Networks (MANET) are widely used in tactical scenarios because they can be deployed rapidly in hostile areas and the distributed nature of their operations makes them robust to nodes failures. However, distributed control involves new vulnerabilities that might be critical in electronic warfare scenarios. In this paper we focus on black hole attacks which introduce in the network fake routing information. On the consequence of the above information, the malicious node enters in the end-to-end path of most communication sessions and discards all received packets. In this paper a solution, named BRAVO is proposed, that exploits a mechanism based on credits allowing nodes to estimate the trustworthiness of neighboring nodes. Simulation results demonstrate that in most scenarios BRAVO is robust to black hole attacks.
Power Distribution Network Reliability Modeling Based on theStatistical Data and Multi-agent Simulation

The paper describes an innovative approach to the exploration of the power distribution network reliability problem. The approach is based on dynamic modeling of the power distribution network features, its failures and their consequences. The actual modeling processes are conducted by a network of independent and autonomous software agents whose behavior is defined by a declarative language. A particular network model can be machine-generated on the basis of a real-life failure database data. The hypothesis is that we can bring new findings to the research field by joining the real-life statistical data with the highly flexible multi-agent simulation.
High Hematocrit Resulting from Administration of Erythropoiesis-stimulating Agents Is Not Fully Predictive of Mortality or Toxicities in Preclinical Species

We conducted a retrospective analysis of publicly available preclinical toxicology studies with erythropoiesis-stimulating agents (ESAs) to examine common adverse events in rats, Beagle dogs, and cynomolgus monkeys. Mortality and/or thrombotic events were reported sporadically in a subset of studies and attributed to the high hematocrit (HCT) achieved in the animals. However, similarly high HCT was achieved in both high-dose and low-dose groups, but there were no reported adverse events in the low-dose group suggesting HCT was not the sole contributing factor leading to toxicity. Our analysis indicated that increased dose, dose frequency, and dosing duration in addition to high HCT contributed to mortality and thrombosis. To further evaluate this relationship, the incidence of toxicities was compared in rats administered an experimental hyperglycosylated analog of recombinant human erythropoietin (AMG 114) at varying dosing schedules in 1-month toxicity studies. The incidence of mortality and thrombotic events increased in higher dose groups and when dosed more frequently, despite a similarly high HCT in all animals. The results from the investigative study and retrospective analysis demonstrate that ESA-related toxicities in preclinical species are associated with dose level, dose frequency, and dosing duration, and not solely dependent upon a high HCT.
Local volatility in the Heston model: a Malliavin calculus approach

We implement the Heston stochastic volatility model by using multidimensional Ornstein-Uhlenbeck processes and a special Girsanov transformation, and consider the Malliavin calculus of this model. We derive explicit formulas for the Malliavin derivatives of the Heston volatility and the log-price, and give a formula for the local volatility which is approachable by Monte-Carlo methods.
Multimodal rule transfer into automatic knowledge based topic models

Topic models are used in text analysis to extract domain features and to explore unknown domains. The topic models and its extensions follow traditional machine learning approach as single-shot learning. Automatic knowledge based topic models (AKBTM) filled this gap by learning from each task and carrying it to future tasks as knowledge rules. Most of the research in AKBTM focuses on rule extraction techniques. The transfer of rules is ignored for the most part of it, using single transfer mode. In this research paper, a multimodal rule transfer mechanism is proposed that operate in three modes to transfer the impact of rules into the inference technique. The rules are divided into two bins, based on their quality, as correlation strength. The mode of transferring rules bias is governed by the strength of rule and time phase the inference technique is in. It resulted in 24 points of improvement in topic coherence of the proposed model as compared to state of the art. The efficient and appropriate transfer of rule bias into the model, helped improve performance by 38%.
Long-Term Retention of a Spatial Mental Model for Younger and Older Adults

Mental models are knowledge structures that are used to describe, predict, and explain the system that they represent. Mental models can be useful for both younger and older adults. Past research (Gilbert & Rogers, 1999, Journal of Gerontology: Psychological Sciences, 54B, P246–P255) indicated that both younger and older adults were able to acquire and utilize a new spatial mental model. Younger and older adult participants from that research returned after a 2-week interval and a group of younger adult participants returned after 4 weeks to determine if their mental model was retained over time. Retention was best for the younger adult 2-week group; performance did not differ for the older adult 2-week and younger adult 4-week groups. Participants who were able to reconstruct the map initially were able to utilize the information very well, regardless of age or retention interval. In addition, both younger and older adults who showed lower initial retention benefited from a brief study time. Implications for refresher training are discussed.
Protease‐activated receptors in hemostasis, thrombosis and vascular biology

Summary. The coagulation cascade and protease‐activated receptors (PARs) together provide an elegant mechanism that links mechanical information in the form of tissue injury to cellular responses. These receptors appear to largely account for the cellular effects of thrombin and can mediate signaling to other trypsin‐like proteases. An important role for PARs in hemostasis and thrombosis is established in animal models, and studies in knockout mice and nonhuman primates raise the question of whether PAR inhibition might offer an appealing new approach to the prevention and treatment of thrombosis. PARs may also trigger inflammatory responses to tissue injury. For example, PAR activation on endothelial cells and perhaps sensory afferents can trigger local accumulation of leukocytes and platelets and transudation of plasma. However, panoply of signaling systems and cell types orchestrates inflammatory responses, and efforts to define the relative importance and roles of PARs in various inflammatory processes are just beginning. Lastly, roles for PARs in blood vessel formation and other processes during embryonic development are emerging, and whether these reflect new roles for the coagulation cascade and/or PAR signaling to other proteases remains to be explored.