Miracle-dz/UniFAR-FTUs huggingface dataset:
Stochastic electrotransport selectively enhances the transport of highly electromobile molecules

Significance Many chemical and biomedical techniques rely on slow diffusive transport because existing pressure-based methods or electrokinetic methods can incidentally damage the sample. This study introduces a novel transport concept termed stochastic electrotransport that can selectively and nondestructively expedite transport of electromobile molecules into a porous sample, such as fixed biological tissues. We use the method to rapidly transport several classes of molecules into whole mouse brains and other organs and achieve rapid clearing and staining of the entire tissue in record time without damaging the sample. Our new method may facilitate the application of various molecular techniques to large and dense tissues. Nondestructive chemical processing of porous samples such as fixed biological tissues typically relies on molecular diffusion. Diffusion into a porous structure is a slow process that significantly delays completion of chemical processing. Here, we present a novel electrokinetic method termed stochastic electrotransport for rapid nondestructive processing of porous samples. This method uses a rotational electric field to selectively disperse highly electromobile molecules throughout a porous sample without displacing the low-electromobility molecules that constitute the sample. Using computational models, we show that stochastic electrotransport can rapidly disperse electromobile molecules in a porous medium. We apply this method to completely clear mouse organs within 1–3 days and to stain them with nuclear dyes, proteins, and antibodies within 1 day. Our results demonstrate the potential of stochastic electrotransport to process large and dense tissue samples that were previously infeasible in time when relying on diffusion.
varrank: an R package for variable ranking based on mutual information with applications to observed systemic datasets

This article describes the R package varrank. It has a flexible implementation of heuristic approaches which perform variable ranking based on mutual information. The package is particularly suitable for exploring multivariate datasets requiring a holistic analysis. The core functionality is a general implementation of the minimum redundancy maximum relevance (mRMRe) model. This approach is based on information theory metrics. It is compatible with discrete and continuous data which are discretised using a large choice of possible rules. The two main problems that can be addressed by this package are the selection of the most representative variables for modeling a collection of variables of interest, i.e., dimension reduction, and variable ranking with respect to a set of variables of interest.
Fast Bayesian hyperparameter optimization on large datasets

Bayesian optimization has become a successful tool for optimizing the hyperparameters of machine learning algorithms, such as support vector machines or deep neural networks. Despite its success, for large datasets, training and validating a single configuration often takes hours, days, or even weeks, which limits the achievable performance. To accelerate hyperparameter optimization, we propose a generative model for the validation error as a function of training set size, which is learned during the optimization process and allows exploration of preliminary configurations on small subsets, by extrapolating to the full dataset. We construct a Bayesian optimization procedure, dubbed FABOLAS, which models loss and training time as a function of dataset size and automatically trades off high information gain about the global optimum against computational cost. Experiments optimizing support vector machines and deep neural networks show that FABOLAS often finds high-quality solutions 10 to 100 times faster than other state-of-the-art Bayesian optimization methods or the recently proposed bandit strategy Hyperband.
Analog beam tracking in linear antenna arrays: Convergence, optimality, and performance

The directionality of millimeter-wave (mmWave) communications creates a significant challenge in serving fast-moving mobile terminals on, e.g., high-speed vehicles, trains, and UAVs. This challenge is exacerbated in mmWave systems using analog antenna arrays, because of the inherent non-convexity in the control of the phase shifters. In this paper, we develop a recursive beam tracking algorithm which can simultaneously achieve fast tracking speed, high tracking accuracy, low complexity, and low pilot overhead. In static scenarios, this algorithm converges to the minimum Cramer-Rao lower bound (CRLB) of beam tracking with high probability. In dynamic scenarios, even at SNRs as low as 0dB, our algorithm is capable of tracking a mobile moving randomly at an absolute angular velocity of 1020 degrees per second, using only 5 pilot symbols per second. If combining with a simple TDMA pilot pattern, this algorithm can track hundreds of high-speed mobiles in 5G configurations. Our simulations show that the tracking performance of this algorithm is much better than several state-of-the-art algorithms.
Wireless Powered Communications With Finite Battery and Finite Blocklength

We analyze a wireless communication system with finite block length and finite battery energy, under quasi-static Nakagami-m fading. Wireless energy transfer is carried out in the downlink while information transfer occurs in the uplink. Transmission strategies for scenarios with/without energy accumulation between transmission rounds are characterized in terms of error probability and energy consumption. A power control protocol for the energy accumulation scenario is proposed and results show the enormous impact on improving the system performance, in terms of error probability and energy consumption. The numerical results corroborate the existence and uniqueness of an optimum target error probability, while showing that a relatively small battery could be a limiting factor for some setups, especially when using the energy accumulation strategy.
Simulating serious games: a discrete-time computational model based on cognitive flow theory

ABSTRACT This paper presents a computational model for simulating how people learn from serious games. While avoiding the combinatorial explosion of a games micro-states, the model offers a meso-level pathfinding approach, which is guided by cognitive flow theory and various concepts from learning sciences. It extends a basic, existing model by exposing discrete-time evolution, allowing for failure, drop-out, and revisiting of activities, and accounting for efforts made and time spent on tasks, all of which are indispensable elements of gaming. Three extensive simulation studies are presented involving over 10,000 iterations across a wide range of game instances and player profiles for demonstrating model stability and empirical admissibility. The model can be used for investigating quantitative dependences between relevant game variables, gain deeper understanding of how people learn from games, and develop approaches to improving serious game design.
Genomic in situ hybridization in interspecific hybrids of scallops (Bivalvia, Pectinidae) and localization of the satellite DNA Cf303, and the vertebrate telomeric sequences (TTAGGG)n on chromosomes of scallop Chlamys farreri (Jones & Preston, 1904)

Abstract Mitotic chromosome preparations of the interspecific hybrids Chlamys farreri (Jones & Preston, 1904) × Patinopecten yessoensis (Jay, 1857), C. farreri × Argopecten irradians (Lamarck, 1819) and C. farreri × Mimachlamys nobilis (Reeve, 1852) were used to compare two different scallop genomes in a single slide. Although genomic in situ hybridization (GISH) using genomic DNA from each scallop species as probe painted mitotic chromosomes of the interspecific hybrids, the painting results were not uniform; instead it showed species-specific distribution patterns of fluorescent signals among the chromosomes. The most prominent GISH-bands were mainly located at centromeric or telomeric regions of scallop chromosomes. In order to illustrate the sequence constitution of the GISH-bands, the satellite Cf303 sequences of C. farreri and the vertebrate telomeric (TTAGGG)n sequences were used to map mitotic chromosomes of C. farreri by fluorescence in situ hybridization (FISH). The results indicated that the GISH-banding pattern presented by the chromosomes of C. farreri is mainly due to the distribution of the satellite Cf303 DNA, therefore suggesting that the GISH-banding patterns found in the other three scallops could also be the result of the chromosomal distribution of other species-specific satellite DNAs.
Effect of Paste Viscosity on Direct-Current Resistance in Improving the Efficiency of Dye-Sensitized Solar Cell

The quality of photoelectrode film plays an important role in producing high performing dye-sensitized solar cell (DSC). A well-deposited film would ensure the stability of photoelectrode material and improve electron transport and recombination. This study aims to evaluate the effect of paste viscosity on the direct-current resistance of the fabricated DSC. Photoelectrode paste of different viscosity was prepared by varying the amount of terpineol as the solvent. Photoelectrode films were then deposited on fluorine-doped tin oxide glass substrate by screen printing method. Electrochemical impedance spectroscopy analysis was utilized to analyse the direct-current resistance of fabricated DSC integrated with different paste viscosity. Direct-current resistance is found to be reduced with increasing paste viscosity. This is attributed to the increase in electron density which reduces the transport as well as recombination resistance leading to an improvement in the conversion efficiency.
Shear Bond Strength of Metal brackets to Zirconia Treated with Er:YAG Laser Sandblasting and Silane

1 Assistant Professor, Dental Research Center, Dentistry Research Institute, Tehran University of Medical Sciences, Tehran, Iran AND Department of Orthodontics, School of Dentistry, Tehran University of Medical Sciences, Tehran, Iran 2 Postgraduate Student, Department of Orthodontics, School of Dentistry, Tehran University of Medical Sciences, Tehran, Iran 3 Assistant Professor, Laser Research Center of Dentistry, Dental Research Institute, Tehran University of Medical Sciences, Tehran, Iran
Three-dimensional GPU-accelerated active contours for automated localization of cells in large images

Cell segmentation in microscopy is a challenging problem, since cells are often asymmetric and densely packed. Successful cell segmentation algorithms rely identifying seed points, and are highly sensitive to variablility in cell size. In this paper, we present an efficient and highly parallel formulation for symmetric three-dimensional contour evolution that extends previous work on fast two-dimensional snakes. We provide a formulation for optimization on 3D images, as well as a strategy for accelerating computation on consumer graphics hardware. The proposed software takes advantage of Monte-Carlo sampling schemes in order to speed up convergence and reduce thread divergence. Experimental results show that this method provides superior performance for large 2D and 3D cell localization tasks when compared to existing methods on large 3D brain images.
Optimal operator deployment and replication for elastic distributed data stream processing

Processing data in a timely manner, data stream processing (DSP) applications are receiving an increasing interest for building new pervasive services. Due to the unpredictability of data sources, these applications often operate in dynamic environments; therefore, they require the ability to elastically scale in response to workload variations. In this paper, we deal with a key problem for the effective runtime management of a DSP application in geo‐distributed environments: We investigate the placement and replication decisions while considering the application and resource heterogeneity and the migration overhead, so to select the optimal adaptation strategy that can minimize migration costs while satisfying the application quality of service (QoS) requirements. We present elastic DSP replication and placement (EDRP), a unified framework for the QoS‐aware initial deployment and runtime elasticity management of DSP applications. In EDRP, the deployment and runtime decisions are driven by the solution of a suitable integer linear programming problem, whose objective function captures the relative importance between QoS goals and reconfiguration costs. We also present the implementation of EDRP and the related mechanisms on Apache Storm. We conduct a thorough experimental evaluation, both numerical and prototype‐based, that shows the benefits achieved by EDRP on the application performance.
A disease annotation study of gene signatures in a breast cancer microarray dataset

Breast cancer is a complex disease with heterogeneity between patients regarding prognosis and treatment response. Recent progress in advanced molecular biology techniques and the development of efficient methods for database mining lead to the discovery of promising novel biomarkers for prognosis and prediction of breast cancer. In this paper, we applied three computational algorithms (RFE-LNW, Lasso and FSMLP) to one microarray dataset for breast cancer and compared the obtained gene signatures with a recently described disease-agnostic tool, the Genotator. We identified a panel of 152 genes as a potential prognostic signature and the ERRFI1 gene as possible biomarker of breast cancer disease.
Isolation of RNA From Peripheral Blood Cells: A Validation Study for Molecular Diagnostics by Microarray and Kinetic RT-PCR Assays - Application in Aerospace Medicine

Gene expression studies in clinical diagnostic setting involve a large number of samples collected at different time points requiring effective methods for collection, transportation, storage, and isolation of RNA to maintain the integrity of expression profiles. Human whole blood is a vital source of RNA for analysis of environmental exposure since blood constituents maintain homeostasis, effect immunity or inflammation, participate in stress signaling, and mediate cellular communication in vascular associated tissues including those of the central nervous system. Isolation strategies using whole blood should recognize the limited quantities of useful RNA that must be protection from the hostile leukocyte ribonucleases, in addition to the abundance of preformed mRNA in reticulocytes, high protein content, and transcriptional activation of cells during sample processing in vitro. This paper presents data showing how the collection, treatment, and storage of collected blood samples can affect subsequent RNA isolation and analysis. It is further demonstrated that total RNA isolated from human whole blood, using a modified and optimized procedure of PAXgene Blood RNA reagent kits, performed well in cDNA microarray hybridization and kinetic RT-PCR. Preservation of expression patterns was observed for 96% of the mRNAs after 24 h storage at 4 degrees C by hybridization analysis of 100 mRNA targets. There were no detectable changes in expression levels of 2 housekeeping genes, beta-actin and cyclophilin, for up to 10 days storage at 4 degrees C by RT-PCR. This validated protocol was employed for isolation of RNA from blood samples collected in the study of acute ethanol effects on performance and characterization of ethanol inducible biomarkers related to performance impairment. The ultimate goal is to utilize gene expression analysis for aerospace accident investigation and prevention.
Impact of Bythotrephes Invasion on Zooplankton Communities in Acid-Damaged and Recovered Lakes on the Boreal Shield

Invasive species introductions into freshwater ecosystems have had a multitude of effects on aquatic communities. Few studies, however, have directly compared the impact of an invader on communities with contrasting structure. Historically high levels and subsequent reductions of acid deposition have produced landscapes of lakes of varying acidity and zooplankton community structure. We conducted a 30-day enclosure experiment in Killarney Provincial Park, Ontario, Canada, to test the effects of Bythotrephes longimanus, an invasive invertebrate predator, on two contrasting zooplankton communities at different stages of recovery from acidification: recovered and acid damaged. Bythotrephes significantly decreased zooplankton biomass and abundance in both communities but had a greater negative effect on the abundance of zooplankton in the recovered community. Bythotrephes reduced species diversity of the recovered zooplankton community but not of the acid-damaged community. Species richness of both community .
Hot utilitarianism and cold deontology: Insights from a response patterns approach to sacrificial and real world dilemmas

ABSTRACT Research on moral judgment with moral dilemmas suggests that “utilitarian” responses (UR) to sacrificial high-conflict dilemmas are due to decreased harm aversion, not only in individuals with clinical conditions, but also in healthy participants with high scores in antisocial personality traits. We investigated the patterns of responses to different dilemma types in healthy participants and present evidence that some URs to sacrificial dilemmas are morally motivated, as indicated by their empathic concern (EC) or primary psychopathy (PP) scores. In study 1 (N = 230) we tested students with four categories of sacrificial dilemmas featuring innocent victims. In study 2 (N = 590) we tested students with two categories of sacrificial dilemmas and two “real-world” moral dilemmas, where the agent can improve the lot of strangers by making a personal sacrifice. Results in both studies showed no decreased harm aversion in a pattern where the only UR is to the sacrificial dilemma where the number of saved people is very high, and significantly lower harm aversion only in the pattern of all-deontological respondents in Study 2. The analysis by response patterns allowed a better discrimination of the moral motivations of participants and showed that at least some of them express moral concerns in their URs.
Comparison of Online Survey Recruitment Platforms for Hard-to-Reach Pregnant Smoking Populations: Feasibility Study

Background Recruiting hard-to-reach populations for health research is challenging. Web-based platforms offer one way to recruit specific samples for research purposes, but little is known about the feasibility of online recruitment and the representativeness and comparability of samples recruited through different Web-based platforms. Objective The objectives of this study were to determine the feasibility of recruiting a hard-to-reach population (pregnant smokers) using 4 different Web-based platforms and to compare participants recruited through each platform. Methods A screener and survey were distributed online through Qualtrics Panel, Soapbox Sample, Reddit, and Amazon Mechanical Turk (mTurk). Descriptive statistics were used to summarize results of each recruitment platform, including eligibility yield, quality yield, income, race, age, and gestational age. Results Of the 3847 participants screened for eligibility across all 4 Web-based platforms, 535 were eligible and 308 completed the survey. Amazon mTurk yielded the fewest completed responses (n=9), 100% (9/9) of which passed several quality metrics verifying pregnancy and smoking status. Qualtrics Panel yielded 14 completed responses, 86% (12/14) of which passed the quality screening. Soapbox Sample produced 107 completed surveys, 67% (72/107) of which were found to be quality responses. Advertising through Reddit produced the highest completion rate (n=178), but only 29.2% (52/178) of those surveys passed the quality metrics. We found significant differences in eligibility yield, quality yield, age, number of previous pregnancies, age of smoking initiation, current smokers, race, education, and income (P<.001). Conclusions Although each platform successfully recruited pregnant smokers, results varied in quality, cost, and percentage of complete responses. Moving forward, investigators should pay careful attention to the percentage yield and cost of online recruitment platforms to maximize internal and external validity.
An Energy‐Conserving Hair Reflectance Model

We present a reflectance model for dielectric cylinders with rough surfaces such as human hair fibers. Our model is energy conserving and can evaluate arbitrarily many orders of internal reflection. Accounting for compression and contraction of specular cones produces a new longitudinal scattering function which is non‐Gaussian and includes an off‐specular peak. Accounting for roughness in the azimuthal direction leads to an integral across the hair fiber which is efficiently evaluated using a Gaussian quadrature. Solving cubic equations is avoided, caustics are included in the model in a consistent fashion, and more accurate colors are predicted by considering many internal pathways.
Total centralisation and optimisation of an oncology management suite via Citrix®

The management of patient information and treatment planning is traditionally an intra-departmental requirement of a radiation oncology service. Epworth Radiation Oncology systems must support the transient nature of Visiting Medical Officers (VMOs). This unique work practice created challenges when implementing the vision of a completely paperless solution that allows for a responsive and efficient service delivery. ARIA® and EclipseTM (Varian Medical Systems, Palo Alto, CA, USA) have been deployed across four dedicated Citrix® (Citrix Systems, Santa Clara, CA, USA) servers allowing VMOs to access these applications remotely. A range of paperless solutions were developed within ARIA® to facilitate clinical and organisational management whilst optimising efficient work practices. The IT infrastructure and paperless workflow has enabled VMOs to securely access the VarianTM (Varian Medical Systems, Palo Alto, CA, USA) oncology software and experience full functionality from any location on multiple devices. This has enhanced access to patient information and improved the responsiveness of the service. Epworth HealthCare has developed a unique solution to enable remote access to a centralised oncology management suite, while maintaining a secure and paperless working environment.