Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient discrete firefly algorithm for Ctrie based caching of multiple sequence alignment on optimally scheduled parallel machines

This study introduces a two-level strategy for efficient execution of multiple sequence alignment (MSA) of complex heterogeneous sequences. The two levels of the proposed technique are comprised of: designing the discrete firefly algorithm (DFFA) for the formation and implementation of makespan minimisation on parallel machines, followed by performing Ctrie-based caching for pairwise alignment to reduce the load on the data servers for handling multiple queries. The proposed strategy addresses a multi-client problem that aims to acquire the full advantage of the computational power of parallel connected machines. Further, it is shown that the inclusion of Ctrie as caching mechanism successively improves the performance of the system with accretion in several sequences. Performance of proposed DFFA is also compared with discrete versions of four swarm intelligence based algorithms at the criteria of makespan minimisation and the rate of convergence on two kinds of complex and diverse datasets. The work is unique in this sense: it is the first swarm-intelligence-based implementation for the addressed problem; it is so far the first approach for Ctrie based caching of the MSA on the scheduled parallel machines; hybridisation of DFFA with Ctrie for caching the MSA results is also a novel implementation.
Domenico Solution—Is It Valid?

The Domenico solution is widely used in several analytical models for simulating ground water contaminant transport scenarios. Unfortunately, many textbook as well as journal article treatments of this approximate solution are full of empirical statements that are developed without mathematical rigor. For this reason, a rigorous analysis of this solution is warranted. In this article, we present a mathematical method to derive the Domenico solution and explore its limits. Our analysis shows that the Domenico solution is a true analytical solution when the value of longitudinal dispersivity is zero. For nonzero longitudinal dispersivity values, the Domenico solution will introduce a finite amount of error. We use an example problem to quantify the nature of this error and suggest some general guidelines for the appropriate use of this solution.
How Learner Experience and Types of Mobile Applications Influence Performance: The Case of Digital Annotation

Abstract The study investigates how learner experience with applications (apps) and how app types (native vs. non-native) influence performance in reading comprehension. Twenty-five high school students used different apps to read four texts. The students were asked to use the annotation feature of the apps to facilitate their reading. Ease of use, usefulness, and enjoyment were self-reported. Cognitive load and valence were inferred from pupil diameter and facial expressions. Results showed no significant association between the number of annotations and reading comprehension. However, comprehension was better when the apps were perceived as easier to use, more useful, and more enjoyable. Regression analyses revealed that students performed significantly better when using native apps. There were also significant interactions between cognitive load and app types on reading comprehension, and between valence and app types on reading comprehension. Based on the students’ feedback, basic requirements for an ideal annotation tool are identified.
In Vivo Imaging of Transiently Transgenized Mice with a Bovine Interleukin 8 (CXCL8) Promoter/Luciferase Reporter Construct

One of the most remarkable properties of interleukin 8 (CXCL8/IL-8), a chemokine with known additional functions also in angiogenesis and tissue remodeling, is the variation of its expression levels. In healthy tissues, IL-8 is barely detectable, but it is rapidly induced by several folds in response to proinflammatory cytokines, bacterial or viral products, and cellular stress. Although mouse cells do not bear a clear homologous IL-8 gene, the murine transcriptional apparatus may well be capable of activating or repressing a heterologous IL-8 gene promoter driving a reporter gene. In order to induce a transient transgenic expression, mice were systemically injected with a bovine IL-8 promoter–luciferase construct. Subsequently mice were monitored for luciferase expression in the lung by in vivo bioluminescent image analysis over an extended period of time (up to 60 days). We demonstrate that the bovine IL-8 promoter–luciferase construct is transiently and robustly activated 3–5 hours after LPS and TNF-α instillation into the lung, peaking at 35 days after construct delivery. Bovine IL-8 promoter–luciferase activation correlates with white blood cell and neutrophil infiltration into the lung. This study demonstrates that a small experimental rodent model can be utilized for non-invasively monitoring, through a reporter gene system, the activation of an IL-8 promoter region derived from a larger size animal (bovine). This proof of principle study has the potential to be utilized also for studying primate IL-8 promoter regions.
Retinal ganglion cell-derived sonic hedgehog signaling is required for optic disc and stalk neuroepithelial cell development

The development of optic stalk neuroepithelial cells depends on Hedgehog (Hh) signaling, yet the source(s) of Hh protein in the optic stalk is unknown. We provide genetic evidence that sonic hedgehog (Shh) from retinal ganglion cells (RGCs) promotes the development of optic disc and stalk neuroepithelial cells. We demonstrate that RGCs express Shh soon after differentiation, and cells at the optic disc in close proximity to the Shh-expressing RGCs upregulate Hh target genes, which suggests they are responding to RGC-derived Shh signaling. Conditional ablation of Shh in RGCs caused a complete loss of optic disc astrocyte precursor cells, resulting in defective axon guidance in the retina, as well as conversion of the neuroepithelial cells in the optic stalk to pigmented cells. We further show that Shh signaling modulates the size of the Pax2+ astrocyte precursor cell population at the optic disc in vitro. Together, these data provide a novel insight into the source of Hh that promotes neuroepithelial cell development in the mammalian optic disc and stalk.
5TR1 aptamer-PEGylated liposomal doxorubicin enhances cellular uptake and suppresses tumour growth by targeting MUC1 on the surface of cancer cells

Abstract Employing targeting ligands with high affinity to tumour receptors is an important strategy to increase treatment efficacy. The use of aptamers as targeting agent is increasingly prevalent in drug delivery systems. Mucin1 (MUC1) is a glycoprotein that is over-expressed on the surface of several cancer cells and plays an important role in metastasis and invasion. 5TR1-aptamer is a DNA aptamer, which targets MUC1 receptors. The present study investigated the anti-tumour activity and therapeutic effectiveness of 5TR1-aptamer-PEGylated liposomal doxorubicin (PLD) delivery system in C26 tumour-bearing mice. The in vitro experiments demonstrated enhanced cytotoxicity and cellular uptake of PLD at the presence of 5TR1 aptamer into MUC1+C26 cell line. Biodistribution study indicated that aptamer conjugation increased tumour accumulation of PLDs. Pharmacokinetic analysis showed despite higher clearance rate, selective delivery of doxorubicin to tumour tissue was increased in the 5TR1-Doxil group. In C26-bearing tumour mice, treatment with 5TR1-Doxil exhibited significant deceleration in tumour growth and enhanced survival. The results suggested that 5TR1 aptamer is promising ligand for active targeting which improves therapeutic efficiency of PLD in cancer therapy.
Evidence for simultaneous syntactic processing of multiple words during reading

A hotly debated issue in reading research concerns the extent to which readers process parafoveal words, and how parafoveal information might influence foveal word recognition. We investigated syntactic word processing both in sentence reading and in reading isolated foveal words when these were flanked by parafoveal words. In Experiment 1 we found a syntactic parafoveal preview benefit in sentence reading, meaning that fixation durations on target words were decreased when there was a syntactically congruent preview word at the target location (n) during the fixation on the pre-target (n-1). In Experiment 2 we used a flanker paradigm in which participants had to classify foveal target words as either noun or verb, when those targets were flanked by syntactically congruent or incongruent words (stimulus on-time 170 ms). Lower response times and error rates in the congruent condition suggested that higher-order (syntactic) information can be integrated across foveal and parafoveal words. Although higher-order parafoveal-on-foveal effects have been elusive in sentence reading, results from our flanker paradigm show that the reading system can extract higher-order information from multiple words in a single glance. We propose a model of reading to account for the present findings.
Design of a Dual-Band Quadrifilar Helix Antenna Using Stepped-Width Arms

This communication proposes the design of a quadrifilar helix antenna (QHA) with stepped-width arms and a meander feeding network. The stepped-width arms are applied to reduce the antenna size and adjust the frequency interval for dual-band operation. The feeding network includes a 90°-hybrid chip coupler and two meander lines that are designed to give a 180°-phase delay. The proposed QHA is optimized using a genetic algorithm (GA) and then fabricated to measure its performances in a full anechoic chamber. The results demonstrate that the proposed antenna is suitable to be used for dual-band global positioning system (GPS) applications.
Privacy-Preserving Crowd-Sourced Statistical Data Publishing with An Untrusted Server

The continuous publication of aggregate statistics over crowd-sourced data to the public has enabled many data mining applications (e.g., real-time traffic analysis). Existing systems usually rely on a trusted server to aggregate the spatio-temporal crowd-sourced data and then apply differential privacy mechanism to perturb the aggregate statistics before publishing to provide strong privacy guarantee. However, the privacy of users will be exposed once the server is hacked or cannot be trusted. In this paper, we study the problem of real-time crowd-sourced statistical data publishing with strong privacy protection under an untrusted server. We propose a novel distributed agent-based privacy-preserving framework, called DADP, that introduces a new level of multiple agents between the users and the untrusted server. Instead of directly uploading the check-in information to the untrusted server, a user can randomly select one agent and upload the check-in information to it with the anonymous connection technology. Each agent aggregates the received crowd-sourced data and perturbs the aggregated statistics locally with Laplace mechanism. The perturbed statistics from all the agents are further combined together to form the entire perturbed statistics for publication. In particular, we propose a distributed budget allocation mechanism and an agent-based dynamic grouping mechanism to realize global $w$w-event $\epsilon$ε-differential privacy in a distributed way. We prove that DADP can provide $w$w-event $\epsilon$ε-differential privacy for real-time crowd-sourced statistical data publishing under the untrusted server. Extensive experiments on real-world datasets demonstrate the effectiveness of DADP.
Joint Inference for Event Coreference Resolution

Event coreference resolution is a challenging problem since it relies on several components of the information extraction pipeline that typically yield noisy outputs. We hypothesize that exploiting the inter-dependencies between these components can significantly improve the performance of an event coreference resolver, and subsequently propose a novel joint inference based event coreference resolver using Markov Logic Networks (MLNs). However, the rich features that are important for this task are typically very hard to explicitly encode as MLN formulas since they significantly increase the size of the MLN, thereby making joint inference and learning infeasible. To address this problem, we propose a novel solution where we implicitly encode rich features into our model by augmenting the MLN distribution with low dimensional unit clauses. Our approach achieves state-of-the-art results on two standard evaluation corpora.
Nom 2.0: innovative network operations and management for business agility

Faced with growing fierce competitive pressure on all fronts and market saturation, traditional telecommunication operators are now struggling to find the breakthrough approach by which they may successfully reshape their role from network service providers to multimedia service providers. They are re-examining their voice-centric business models and deploying next-generation networks (NGN) for QoS-guaranteed delivery of multimedia quadruple play services (QPSs). To cost effectively realize these paradigm shifts, the existing ";stability-oriented"; network operations and management infrastructure and processes should be migrated into ";service-oriented"; and ";business-driven"; network operations and management within the context of today's multimedia and converged business environments. In this article, I'd like to introduce Network Operations and Management 2.0 (NOM 2.0), which is an innovative next generation operations and management paradigm for telephone company business agility and customer value creation. KT recently proposed Telco 2.0 [1], a new role and business model in the IP world to create customer value. NOM 2.0 is a key component needed to realize the Telco 2.0 goals. Telcos need to transform their operations and management framework into a human-centric and highly intelligent and automated one, and become the market leader by providing an agile operation and management framework within ever-changing operations and business environments. I will describe what NOM 2.0 is and how it is being realized in my company, KT.
Forecasting changes in amphibian biodiversity: aiming at a moving target

Amphibian population declines and sudden species' extinctions began to be noted at the beginning of the 1980s. Understanding the causes of the losses is hampered by our poor knowledge of the amphibian fauna in many parts of the world. Amphibian taxa are still being described at a high rate, especially in the tropics, which means that even quantifying species lost as a percentage of the current fauna can be a misleading statistic in some parts of the globe. The number of species that have gone missing is only one measure of the loss of biodiversity. Long-term studies of single-species populations are needed, but this approach has its limits. Amphibian populations often show great annual variation in population size making it difficult, if not impossible, to use short-term studies as a basis for deciding if a population is increasing or decreasing in the long term. Aggregating single studies into databases and searching for patterns of variation is a way of overcoming this limitation. Several databases on species and population time series are available or in development. These records show that declines are continuing worldwide with some species and populations, especially in the tropics and at higher elevations, at greater risk of extinction than others. Unfortunately, amphibian databases with population time series have much less information for the tropics compared to the temperate zone, and less for Africa and Asia compared with Europe and North America. Focusing limited resources using comprehensive statistical designs is a way to maximize the efficiency and effectiveness of monitoring efforts. It is clear that, in the first decades of the twenty-first century, the regions of the globe with the highest diversity of amphibian species will experience the greatest rates of decrease of forests and increase in human population size, fertilizer use, agricultural production, creation of new croplands and irrigation. Many of these changes are likely negatively to affect amphibian species diversity, and their influence must be understood before concluding, at least for amphibians, that the 2010 millennium assessment goal of significantly reversing the rate of loss of Earth's biodiversity can be met.
Molecular Analysis of Group B Protective Surface Protein, a New Cell Surface Protective Antigen of Group B Streptococci

ABSTRACT Group B streptococci (GBS) express various surface antigens designated c, R, and X antigens. A new R-like surface protein from Streptococcus agalactiae strain Compton R has been identified by using a polyclonal antiserum raised against the R protein fraction of this strain to screen a lambda Zap library. DNA sequence analysis of positive clones allowed the prediction of the primary structure of a 105-kDa protein designated BPS protein (group B protective surface protein) that exhibited typical features of streptococcal surface proteins such as a signal sequence and a membrane anchor region but did not show significant similarity with other known sequences. Immunogold electron microscopy using a BPS-specific antiserum confirmed the surface location of BPS protein on S. agalactiae strain Compton R. Anti-BPS antibodies did not cross-react with R1 and R4 proteins expressed by two variant type III GBS strains but reacted with the parental streptococcal strain in Western blot and immunoprecipitation analyses. Separate R3 and BPS immunoprecipitation bands were observed when a cell extract of strain Compton R was tested with an antiserum against Compton R previously cross-absorbed to remove R4 antibodies. Immunization of mice with recombinant BPS protein by the subcutaneous route produced an efficient antigen-specific response, and immunized animals survived challenge with a lethal dose of a virulent strain. Therefore, BPS protein represents a new R-like protective antigen of GBS.
Miniaturized printed wire antenna in package for 2.4GHz wireless communications

Miniaturized printed wire antennas in system in package were investigated for 2.4 GHz wireless communication systems. An inverted F antenna was proposed, and had a small area with 15mm by 15mm. The position of feed tap connected to the antenna arm greatly influenced the impedance of antenna, namely, it could adjust the position of feed tap to match the impedance to 50 ohm. The influences of chips and epoxy molding compounds on the impedance were also studied. Eventually, the inverted F antenna in package had a bandwidth and gain with almost 200MHz and 2.8dB, respectively, and could meet the demands of 2.4GHz wireless communication.
Evaluation of the genotoxicity of cellulose nanofibers

Background Agricultural products and by products provide the primary materials for a variety of technological applications in diverse industrial sectors. Agro-industrial wastes, such as cotton and curaua fibers, are used to prepare nanofibers for use in thermoplastic films, where they are combined with polymeric matrices, and in biomedical applications such as tissue engineering, amongst other applications. The development of products containing nanofibers offers a promising alternative for the use of agricultural products, adding value to the chains of production. However, the emergence of new nanotechnological products demands that their risks to human health and the environment be evaluated. This has resulted in the creation of the new area of nanotoxicology, which addresses the toxicological aspects of these materials. Purpose and methods Contributing to these developments, the present work involved a genotoxicological study of different nanofibers, employing chromosomal aberration and comet assays, as well as cytogenetic and molecular analyses, to obtain preliminary information concerning nanofiber safety. The methodology consisted of exposure of Allium cepa roots, and animal cell cultures (lymphocytes and fibroblasts), to different types of nanofibers. Negative controls, without nanofibers present in the medium, were used for comparison. Results The nanofibers induced different responses according to the cell type used. In plant cells, the most genotoxic nanofibers were those derived from green, white, and brown cotton, and curaua, while genotoxicity in animal cells was observed using nanofibers from brown cotton and curaua. An important finding was that ruby cotton nanofibers did not cause any significant DNA breaks in the cell types employed. Conclusion This work demonstrates the feasibility of determining the genotoxic potential of nanofibers derived from plant cellulose to obtain information vital both for the future usage of these materials in agribusiness and for an understanding of their environmental impacts.
Propagating Certainty in Petri Nets for Activity Recognition

This paper considers the problem of recognizing activities as they occur in surveillance video. Activities are high-level nonatomic semantic concepts which may have complex temporal structure. Activities are not easily identifiable using image features, but rather by the recognition of their composing events. Unfortunately, these composing events may only be observed up to a particular certainty. This paper describes particle filter Petri Net (PFPN), an activity recognition process that combines uncertain event observations to determine the likelihood that a particular activity is taking place in a video sequence. Our paper is based on previous study in which activities are specified as Petri Nets. The stochastic PFPN framework proposed in this paper improves over existing deterministic approaches to activity recognition by enabling the certainty reasoning required for coping with inherent ambiguity in both low-level video processing and activity definition. Furthermore, the PFPN approach reduces the dependence on a duration model and enables the creation of holistic activity models. Often when activity recognition frameworks are proposed they are strongly paired with a particular methodology for low-level video processing and event recognition. Each proposed approach is then applied to a nonstandard dataset. In our experiments, we provide an empirical comparison of our approach with leading activity recognition approaches across several datasets, using a constant event recognition as input. Our results illustrate the tradeoff between deterministic and stochastic activity recognition approaches. Furthermore, our experiments suggest that the holistic PFPN approach is more robust for activity recognition in the surveillance video domain than competing approaches.
Plain Polynomial Arithmetic on GPU

As for serial code on CPUs, parallel code on GPUs for dense polynomial arithmetic relies on a combination of asymptotically fast and plain algorithms. Those are employed for data of large and small size, respectively. Parallelizing both types of algorithms is required in order to achieve peak performances. In this paper, we show that the plain dense polynomial multiplication can be efficiently parallelized on GPUs. Remarkably, it outperforms (highly optimized) FFT-based multiplication up to degree 212 while on CPU the same threshold is usually at 26. We also report on a GPU implementation of the Euclidean Algorithm which is both work-efficient and runs in linear time for input polynomials up to degree 218 thus showing the performance of the GCD algorithm based on systolic arrays.