Miracle-dz/UniFAR-FTUs huggingface dataset:
Real Time Genetic Scheduling of Aircraft

| Evolutionary approaches are not usually considered for real time scheduling problems due to long computation times and uncertainty about the length of the computation time. We argue that for some kinds of problems, such as optimizing aircraft landing times, genetic algorithms have advantages over other methods as a best solution is always available when needed, and, since the computation is inherently parallel, more processors can be added to get higher quality solutions if necessary. Furthermore, the computation time can be decreased and the quality of the generated schedules increased by seeding the genetic algorithm from a previous population. We have performed a series of experiments on landing data for Sydney airport on the busiest day of the year. Our results show that high quality solutions can be computed in the time window between aircraft landings.
Real-time dense multi-scale workspace modeling on a humanoid robot

Without a precise and up-to-date model of its environment a humanoid robot cannot move safely or act usefully. Ideally, the robot should create a dense 3D environment model in real-time, all the time, and respect obstacle information from it in every move it makes as well as obtain the information it needs for fine manipulation with its fingers from the same map. We propose to use a multi-scale truncated signed distance function (TSDF) map consisting of concentric, nested cubes with exponentially decreasing resolution for this purpose. We show how to extend the KinectFusion real-time SLAM algorithm to the multi-scale case as well as how to compute a multi-scale Euclidean distance transform (EDT) thereby establishing the link to optimization-based planning. We overcome the inability of KinectFusion's localization to handle scenes without enough constraining geometry by switching to mapping-with-known-poses based on forward kinematics. The latter is always available and we know when it is precise. The resulting map has the desired properties: It is computed in real-time (7.5 ms per depth frame for a (8 m)3 multi-scale TSDF volume), covers the entire laboratory, does not depend on scene properties (geometry, texture, etc.) and is precise enough to facilitate grasp planning for fine manipulation tasks - all in a single map.
Stochastic Modeling of Polymerase Chain Reaction and Related Biotechnologies

The polymerase chain reaction (PCR) is a method that uses test tubes in biological laboratories for producing large amount of identical copies of a specific gene from small amount of complex molecules. Here we present our work on the stochastic modeling and theoretical studies of PCR, sexual PCR (DNA shuffling) and their applications to in vitro evolution: an experimental method to evolve proteins with improved functions.
Phenolic Assesment of Uncaria tomentosa L. (Cat’s Claw): Leaves, Stem, Bark and Wood Extracts

The phenolic composition of extracts from Uncaria tomentosa L. from different regions of Costa Rica was studied using advanced analytical techniques such as UPLC/TQ-ESI-MS and 13C-NMR. Samples from leaves, stems, bark and wood (n = 22) were subjected to extraction to obtain phenolic and alkaloid extracts, separately. Comparatively, higher values of total phenolic content were observed for leaves, stems and bark (225–494 gallic acid equivalents/g) than for wood extracts (40–167 gallic acid equivalents/g). A total of 32 non-flavonoid and flavonoid compounds were identified in the phenolic extracts: hydroxybenzoic acids (benzoic, salicylic, 4-hydroxybenzoic, prochatechuic, gallic, syringic and vanillic acids), hydroxycinnamic acids (p-coumaric, caffeic, ferulic and isoferulic acids), flavan-3-ols monomers [(+)-catechin and (−)-epicatechin)], procyanidin dimers (B1, B2, B3, B4, B5, B7 and two other of unknown structure) and trimers (C1, T2 and one of unknown structure), flavalignans (four unknown structures pertaining to the cinchonain family) and propelargonidin dimers (four unknown structures, reported for the first time in U. tomentosa). Additionally, alkaloid extracts obtained from the plant residue after phenolic extraction exhibited a content of tetracyclic and pentacyclic alkaloids ranging between 95 and 275 mg/100 g of dry material for bark extracts, and between 30 and 704 mg/100 g for leaves extracts. In addition, a minor alkaloid was isolated and characterized, namely 18,19-dehydrocorynoxinoic acid. Our results confirmed the feasibility of U. tomentosa as a suitable raw material for obtaining phenolic- and alkaloid-rich extracts of potential interest.
Advances in computer architecture

In the past, efforts were taken to improve the performance of a processor via frequency scaling. However, industry has reached the limits of increasing the frequency and therefore concurrent execution of instructions on multiple cores seems the only possible option. It is not enough to provide concurrent execution by the hardware, software also have to introduce concurrency in order to exploit the parallelism.
Recent Directions in Telemedicine: Review of Trends in Research and Practice

Objectives Healthcare is now routinely delivered by telecommunications-based services in all developed countries and an increasing number of developing countries. Telemedicine is used in many clinical specialities and across numerous healthcare settings, which range from mobile patient-centric applications to complex interactions amongst clinicians in tertiary referral hospital settings. This paper discusses some recent areas of significant development and progress in the field with the purpose of identifying strong trends in both research and practice activities. Methods To establish the breadth of new ideas and directions in the field, a review of literature was made by searching PubMed for recent publications including terms (telemedicine OR telehealth) AND (challenge OR direction OR innovation OR new OR novel OR trend), for all searchable categories. 3,433 publications were identified that have appeared since January 1, 2005 (2,172 of these since January 1, 2010), based on a search conducted on June 1, 2015. Results The current interest areas in these papers span both synchronous telemedicine, including intensive care, emergency medicine, and mental health, and asynchronous telemedicine, including wound and burns care, dermatology and ophthalmology. Conclusions It is concluded that two major drivers of contemporary tele medicine development are a high volume demand for a particular clinical service, and/or a high criticality of need for clinical exper tise to deliver the service. These areas offer promise for further study and enhancement of applicable telemedicine methods and have the potential for large-scale deployments internationally, which would contribute significantly to the advancement of healthcare.
Irrelevant Variability Normalization via Hierarchical Deep Neural Networks for Online Handwritten Chinese Character Recognition

This paper presents a novel irrelevant variability normalization (IVN) approach via hierarchical deep neural networks (HDNNs) and prototype-based classifier for online handwritten Chinese character recognition. The recent insight of deep neural network (DNN) is the deep architecture with large training data can bring the best performance in many research areas. The architecture design of our proposed hierarchical deep neural networks focuses on both "depth" and "width" of artificial neural network. Specifically for the multivariate regression, HDNN consists of multiple subnets, which is empirically more powerful than DNN. In this work, HDNN is adopted as a nonlinear feature transform to normalize the feature vector of handwritten samples with irrelevant variabilities to a target prototype. The effectiveness of proposed method is verified on a Chinese handwriting recognition task. Furthermore, we have an very interesting observation that DNN-based IVN can not even bring performance gain over the prototype-based classifier while HDNN-based IVN yields significant improvements of recognition accuracy.
Inhibition of heat shock protein 27 phosphorylation promotes sensitivity to 5-fluorouracil in colorectal cancer cells

The aim of the present study was to investigate whether the inhibition of HSP27 phosphorylation, which affects certain cellular functions, modulates sensitivity to 5-fluorouracil (5-FU) in colorectal cancer cells. Exposure to 5-FU in HCT116 and HCT15 cells expressing high levels of HSP27 with a low 5-FU sensitivity caused a minimal change in HSP27 expression, but induced the upregulation of HSP27 phosphorylation, particularly at Ser78. By contrast, exposure to 5-FU in HT29 cells expressing a low level of HSP27 with a high 5-FU sensitivity marginally increased HSP27 expression, with minimal phosphorylation. Treatment with a selective inhibitor, p38 mitogen-activated protein kinase (MAPK; SB203580), caused the dose-dependent suppression of HSP27 phosphorylation, which was upregulated by 5-FU, reducing the half maximal inhibitory concentration values of 5-FU in the HCT116 and HCT15 cells. However, treatment with SB203580 exhibited no significant effect on cell growth or survival. In conclusion, this study indicated that the inhibition of HSP27 phosphorylation by a selective inhibitor of p38 MAPK promotes 5-FU sensitivity without causing cytotoxicity in colorectal cancer cells.
Overloaded multiuser MISO transmission with imperfect CSIT

A required feature for the next generation of wireless communication networks will be the capability to serve simultaneously a large number of devices with heterogeneous CSIT qualities and demands. In this paper, we consider the overloaded MISO BC with two groups of CSIT qualities. We propose a transmission scheme where degraded symbols are superimposed on top of spatially-multiplexed symbols. The developed strategy allows to serve all users in a non-orthogonal manner and the analysis shows an enhanced perfomance compared to existing schemes. Moreover, optimality in a DoF sense is shown.1
Transcriptomics of the Bed Bug (Cimex lectularius)

Background Bed bugs (Cimex lectularius) are blood-feeding insects poised to become one of the major pests in households throughout the United States. Resistance of C. lectularius to insecticides/pesticides is one factor thought to be involved in its sudden resurgence. Despite its high-impact status, scant knowledge exists at the genomic level for C. lectularius. Hence, we subjected the C. lectularius transcriptome to 454 pyrosequencing in order to identify potential genes involved in pesticide resistance. Methodology and Principal Findings Using 454 pyrosequencing, we obtained a total of 216,419 reads with 79,596,412 bp, which were assembled into 35,646 expressed sequence tags (3902 contigs and 31744 singletons). Nearly 85.9% of the C. lectularius sequences showed similarity to insect sequences, but 44.8% of the deduced proteins of C. lectularius did not show similarity with sequences in the GenBank non-redundant database. KEGG analysis revealed putative members of several detoxification pathways involved in pesticide resistance. Lamprin domains, Protein Kinase domains, Protein Tyrosine Kinase domains and cytochrome P450 domains were among the top Pfam domains predicted for the C. lectularius sequences. An initial assessment of putative defense genes, including a cytochrome P450 and a glutathione-S-transferase (GST), revealed high transcript levels for the cytochrome P450 (CYP9) in pesticide-exposed versus pesticide-susceptible C. lectularius populations. A significant number of single nucleotide polymorphisms (296) and microsatellite loci (370) were predicted in the C. lectularius sequences. Furthermore, 59 putative sequences of Wolbachia were retrieved from the database. Conclusions To our knowledge this is the first study to elucidate the genetic makeup of C. lectularius. This pyrosequencing effort provides clues to the identification of potential detoxification genes involved in pesticide resistance of C. lectularius and lays the foundation for future functional genomics studies.
Robust zero-watermarking for medical image based on DCT

When designing watermarking algorithm of the medical image, one of the principal problems faced is how to determine the region of interest (ROI). This paper proposes a zero-watermarking algorithm of the medical image using DCT, which can effectively solve this problem. This algorithm can enhance medical image security, confidentiality and integrity in the application for the clinical. The algorithm combines the visual feature vector of images, encryption technology with the third party authentication, and avoids the selection of ROI to speed up watermarking embedding and extracting. The simulation results demonstrate the algorithm has desired robustness against common attacks and geometric attacks, such as JEPG, rotation, scaling and translation, etc.
Impact of cognitive styles on the frequency of use of social media amongst university students

This study was carried out to examine the impact of undergraduates’ cognitive styles on the frequency of use of social media. There are research studies/reports on impact of social media on teaching and learning but a few that look at the relationship between cognitive style and social media. A sample of 900 students were selected through convenience sampling procedure from six universities. From each selected universities, 150 students were selected through convenience sampling. The research instruments used for this study were the adopted cognitive style inventory of Group Embedded Figures Test (GEFT) and self-constructed questionnaire. Group Embedded Figure Test (GEFT) was used to determine the students Cognitive styles and the Questionnaire to determine frequency of use of the social media. Results indicate that there were more Field Independents students than the Field Dependent. It also showed that most of the social media were frequently used while other were occasionally, sparingly and rarely used. The result further showed a significant relationship between cognitive styles and the frequency of use of social media, particularly Facebook and Whatsapp. It was concluded that cognitive styles had an influence on undergraduate’s frequency of use of some social media.
Quantization Noise Reduction Techniques for Digital Pulsed RF Signal Generation Based on Quadrature Noise Shaped Encoding

The digital generation of pulsed radio frequency (RF) signals based on noise shaped encoding in complex baseband is a popular concept in digital RF transmitters. However, as the pulsed complex-baseband signals are up-converted to an RF frequency, a conjugate image overlaps with the signal band, which complicates the center frequency tuning for the transmitters in question. In this paper novel ways related to equalization techniques used for imbalanced digital complex valued systems are presented to mitigate conjugate image noise. Firstly, the distortion generation mechanism of the digital up-conversion is explained. Based on the analysis two cancelation techniques are derived. Secondly, novel quadrature encoder topologies implementing the given compensation techniques are developed. The analytical and the simulation based results show conjugate quantization noise suppression of more than 50 dB, which extends the potential center frequency tuning range considerably. Finally, a comparison with previously given encoders reveals nearly 10 dB improvement in dynamic range.
OPUS : Developing a personalised online learning environment for Continuing Professional Education

A survey of CPD students at Oxford University revealed that typically only 30% of course content is directly and immediately relevant to their professional needs. Thus the OPUS (Oxford Professional Updating System) project has been designed to produce a system that delivers a CPD course as a personalised learning programme This is a field in which existing work is much less developed than might be anticipated, and where progress has lagged behind scholarly discussion. The evidence from earlier projects provides us with far more questions than answers. However it does highlight several key issues in the areas of personalisation, knowledge diagnosis, learning objects, knowledge representation and learner models. Existing research in this area has focused primarily on the technical problems, and neglects the core area of user experience. As a result little attention has been paid to how students and tutors are affected by individualised learning. The research project has considered how professionals think about their learning requirements, and how this process might be aided to deliver the learning they need in a more focused and timely manner. As the project has progressed two contrasting approaches to development have emerged, centred on the system and the student respectively. The latter approach has emerged as the most appropriate from both a practical as well as pedagogical perspective, making it the focus for development and evaluation. In response to the issues outlined above, the project is developing a new emphasis on the discovery of sustainable extendable methodologies for individualised learning. This paper will explore these issues, discuss some of the solutions being investigated and stimulate discussion on the approach adopted in the OPUS project.
Data-Based Choice of Histogram Bin Width

Abstract The most important parameter of a histogram is the bin width because it controls the tradeoff between presenting a picture with too much detail (“undersmoothing”) or too little detail (“oversmoothing”) with respect to the true distribution. Despite this importance there has been surprisingly little research into estimation of the “optimal” bin width. Default bin widths in most common statistical packages are, at least for large samples, quite far from the optimal bin width. Rules proposed by, for example, Scott lead to better large sample performance of the histogram, but are not consistent themselves. In this paper we extend the bin width rules of Scott to those that achieve root-n rates of convergence to the L 2-optimal bin width, thereby providing firm scientific justification for their use. Moreover, the proposed rules are simple, easy and fast to compute, and perform well in simulations.
Hiding Information in Retransmissions

The paper presents a new steganographic method called RSTEG (Retransmission Steganography), which is intended for a broad class of protocols that utilises retransmission mechanisms. The main innovation of RSTEG is to not acknowledge a successfully received packet in order to intentionally invoke retransmission. The retransmitted packet carries a steganogram instead of user data in the payload field. RSTEG is presented in the broad context of network steganography, and the utilisation of RSTEG for TCP (Transport Control Protocol) retransmission mechanisms is described in detail. Simulation results are also presented with the main aim to measure and compare the steganographic bandwidth of the proposed method for different TCP retransmission mechanisms as well as to determine the influence of RSTEG on the network retransmissions level.
Attaining performance fairness in big.LITTLE systems

In the dark silicon era, achieving energy-efficient execution on highly heterogeneous platforms requires a much tighter integration of hardware and software solutions. To tackle this problem, we propose a framework for energy-aware task management in heterogeneous embedded systems with several multi-core clusters. The proposed framework integrates a set of novel application-aware management mechanisms for efficient resource utilization, frequency scaling and task migration at intra-cluster and inter-cluster levels. These mechanisms rely on a new management concept, which promotes performance fairness among running tasks as a mean for attaining energy savings, while respecting the target performance of parallel applications. With this purpose, the proposed framework integrates several components for highly accurate run-time monitoring and application self-reporting. Experimental results show that the proposed framework allows achieving energy savings of up to 38% in a state-of-the-art embedded platform, while maintaining performance fairness for a set of real-world SPEC CPU2006 and PARSEC benchmarks.
Optimal TCSC placement based on line flow equations via mixed-integer linear programming

Research effort has been given to find the optimal location and initial settings of Thyristor-Controlled Series Capacitor (TCSC) using Mixed-Integer Linear Programming (MILP). As a useful tool for combinatorial optimisation over integer and continuous variables, mixed-integer programming approach can provides robust performance as well as high computation efficiency when solving complex optimal problems. Artificial Intelligence (AI) techniques, as the mainstream resolvent of system planning, are intractable for large scale systems when dealing with mixed integer problems. Previous work with MILP on power system planning issues employed dc load flow model ignoring reactive power balance, power loss and tapped transformer ratios. In this paper, a novel approximation planning methodology is proposed for preliminary system design. The objective of this planning strategy is to improve system loadability in the network by choosing optimal locations and settings of TCSC. Simulation results are presented for IEEE 9and 14-bus systems.
Ambulatory monitoring in the diagnosis and management of obstructive sleep apnoea syndrome

Obstructive sleep apnoea (OSA) is a highly prevalent disorder associated with complications such as arterial hypertension, cardiovascular diseases and traffic accidents. The resources allocated for OSA are insufficient and OSA is a significant public health problem. Portable recording devices have been developed for the detection of OSA syndrome and have proved capable of providing an equivalent diagnosis to in-laboratory polysomnography (PSG), at least in patients with a high pre-test probability of OSA syndrome. PSG becomes important in patients who have symptoms and certain comorbidities such as chronic obstructive pulmonary disease or stroke, as well as in patients with a clinical history suggesting a different sleep disorder. Continuous positive airway pressure is the most effective treatment in OSA. Ambulatory monitoring of the therapeutic modalities has been evaluated to enhance the care process and reduce costs compared to the conventional approach, without sacrificing efficiency. This review evaluates the role of portable monitoring devices in the diagnostic process of OSA and the search for alternative strategies based on ambulatory management protocols.
Recognizing 3D objects from 2D images: an error analysis

Object recognition systems that use a small number of pairings of data and model features to compute the 3D transformation from model to sensor coordinates are considered. The effects of 2D sensor uncertainty on such computations are examined. The uncertainty in transformation parameters is bounded, and the effect of this uncertainty on false positive recognition rates is analyzed. <<ETX>>