Miracle-dz/UniFAR-FTUs huggingface dataset:
A dosimetric comparison of copper and Cerrobend electron inserts

The purpose of this work was to evaluate differences in dose resulting from the use of copper aperture inserts compared to lead‐alloy (Cerrobend) aperture inserts for electron beam therapy. Specifically, this study examines if copper aperture inserts can be used clinically with the same commissioning data measured using lead‐alloy aperture inserts. The copper inserts were acquired from . decimal, LLC and matching lead‐alloy, Cerrobend inserts were constructed in‐house for 32 combinations of nine square insert field sizes (2×2 to 20×20 cm2) and five applicator sizes (6×6 to 25×25 cm2). Percent depth‐dose and off‐axis relative dose profiles were measured using an electron diode in water for select copper and Cerrobend inserts for a subset of applicators (6×6,10×10,25×25 cm2) and energies (6, 12, 20 MeV) at 100 and 110 cm source‐to‐surface distances (SSD) on a Varian Clinac 21EX accelerator. Dose outputs were measured for all field size‐insert combinations and five available energies (6−20 MeV) at 100 cm SSD and for a smaller subset at 110 cm SSD. Using these data, 2D planar absolute dose distributions were generated and compared. Criteria for agreement were ±2% of maximum dose or 1 mm distance‐to‐agreement for 99% of points. A gamma analysis of the beam dosimetry showed 94 of 96 combinations of insert size, applicator, energy, and SSD were within the 2%/1 mm criteria for >99% of points. Outside the field, copper inserts showed less bremsstrahlung dose under the insert compared to Cerrobend (greatest difference was 2.5% at 20 MeV and 100 cm SSD). This effect was most prominent at the highest energies for combinations of large applicators with small field sizes, causing some gamma analysis failures. Inside the field, more electrons scattered from the collimator edge of copper compared to Cerrobend, resulting in an increased dose at the field edge for copper at shallow depths (greatest increase was 1% at 20 MeV and 100 cm SSD). Dose differences decreased as the SSD increased, with no gamma failures at 110 cm SSD. Inserts for field sizes ≥6×6cm2 at any energy, or for small fields (≤4×4cm2) at energies <20 MeV, showed dosimetric differences less than 2%/1 mm for more than 99% of points. All areas of comparison criteria failures were from lower out‐of‐field dose under copper inserts due to a reduction in bremsstrahlung production, which is clinically beneficial in reducing dose to healthy tissue outside of the planned treatment volume. All field size‐applicator size‐energy combinations passed 3%/1 mm criteria for 100% of points. Therefore, it should be clinically acceptable to utilize copper insets with dose distributions measured with Cerrobend inserts for treatment planning dose calculations and monitor unit calculations. PACS number(s): 87.56. jk
Virtual learning environment for children with disabilities: A proposal based on MOODLE and content management with Over The Top (OTT) technology

Nowadays the Learning Management Systems (LMS) are widely used in all educational levels (schools, colleges and universities). MOODLE, one of the most used platforms, had been registered in more than 76000 sites over 230 countries. However, the World Health Organization (WHO) claims that 5.1 percent of children worldwide have a disability. In the same line, one third of all children not in primary school are those that present disabilities. This situation becomes more complicated in developing countries due the lack of educational services and tools adapted to needs of children with disabilities as well as the poor connectivity of centers of special education to online resources. For these reasons, in this paper we present an approach to address three important aspects Virtual Learning Environments (VLE) as support tools for special education in Ecuador: the connectivity problems of centers of special education, the lack of online resources for children with disabilities, and the lack of tools to analyze the children and teachers perception about educational contents stored in VLE. Our proposal uses the Over The Top (OTT) technology and performs statistical and data mining analysis to provide support for decision making. The approach has been put to test with 26 children with different types of disabilities and has reached encouraging results.
Data sampling imbalance with steerable wavelets for abnormality detection in brain images

A long standing goal within artificial intelligence application for medical imaging has been the ability for appropriate detecting abnormalities in MRI image of brains to support early diagnostics of cancer. This paper presents a solution relying on analysis of class imbalance in data sampling from brain image database instead of error statistics to improve accuracy of the abnormality detection. Here we use modification of training data set both for minority class and majority class to overcome under-segmentation and over-segmentation in detection of abnormality where abnormality is seen as minority class but its distribution is assumed unknown. In this approach, steerable wavelet based features are encoded with machine learning methods to allow the study of data sampling imbalance. In order to increase the detection sensitivity a set of wavelet features is selected from a number of feature sets in the learning task. The results with a benchmark medical image database show the effectiveness of the proposed method for abnormality detection in brain images.
Analytics over large-scale multidimensional data: the big data revolution!

In this paper, we provide an overview of state-of-the-art research issues and achievements in the field of analytics over big data, and we extend the discussion to analytics over big multidimensional data as well, by highlighting open problems and actual research trends. Our analytical contribution is finally completed by several novel research directions arising in this field, which plays a leading role in next-generation Data Warehousing and OLAP research.
hc-OTU: A Fast and Accurate Method for Clustering Operational Taxonomic Units Based on Homopolymer Compaction

To assess the genetic diversity of an environmental sample in metagenomics studies, the amplicon sequences of 16s rRNA genes need to be clustered into operational taxonomic units (OTUs). Many existing tools for OTU clustering trade off between accuracy and computational efficiency. We propose a novel OTU clustering algorithm, hc-OTU, which achieves high accuracy and fast runtime by exploiting homopolymer compaction and k-mer profiling to significantly reduce the computing time for pairwise distances of amplicon sequences. We compare the proposed method with other widely used methods, including UCLUST, CD-HIT, MOTHUR, ESPRIT, ESPRIT-TREE, and CLUSTOM, comprehensively, using nine different experimental datasets and many evaluation metrics, such as normalized mutual information, adjusted Rand index, measure of concordance, and F-score. Our evaluation reveals that the proposed method achieves a level of accuracy comparable to the respective accuracy levels of MOTHUR and ESPRIT-TREE, two widely used OTU clustering methods, while delivering orders-of-magnitude speedups.
A Comprehensive Study of Implemented International Standards, Technical Challenges, Impacts and Prospects for Electric Vehicles

The impending environmental issues and growing concerns for global energy crises are driving the need for new opportunities and technologies that can meet significantly higher demand for cleaner and sustainable energy systems. This necessitates the development of transportation and power generation systems. The electrification of the transportation system is a promising approach to green the transportation systems and to reduce the issues of climate change. This paper inspects the present status, latest deployment, and challenging issues in the implementation of Electric vehicles (EVs) infrastructural and charging systems in conjunction with several international standards and charging codes. It further analyzes EVs impacts and prospects in society. A complete assessment of charging systems for EVs with battery charging techniques is explained. Moreover, the beneficial and harmful impacts of EVs are categorized and thoroughly reviewed. Remedial measures for harmful impacts are presented and benefits obtained therefrom are highlighted. Bidirectional charging offers the fundamental feature of vehicle to grid technology. In this paper, the current challenging issues due to the massive deployment of EVs, and upcoming research trends are also presented. It is envisioned that the researchers interested in such areas can find this paper valuable and an informative one-stop source.
The function of Notch1 intracellular domain in the differentiation of gastric cancer

Due to the complex function of the Notch signal pathway in gastric cancer (GC), the association between Notch homolog 1 (Notch1) intracellular domain (NICD) and differentiation of GC remains unknown. The present study aimed to investigate the potential association between NICD and GC differentiation, and demonstrated that poorly differentiated GC expressed increased NICD levels compared with well differentiated GC. A γ-secretase inhibitor inhibited the growth of AGS cells through downregulating NICD level. Additional data suggested that a COX-2 inhibitor caused a marked reduction of NICD level in comparison with a control group treated with dimethyl sulfoxide. Combined administration of γ-secretase and COX-2 inhibitor produced a marked inhibition of growth in AGS cells, which suggests that patients with poorly differentiated GC may benefit from the blockage of NICD, which potentially serves a role in GC differentiation.
Runtime Performance Management for Cloud Applications with Adaptive Controllers

Adaptability is an expected property of modern software systems in order to cope with changes in the environment by self-adjusting their structure and behaviour. Robustness is a crucial component of adaptability and it refers to the ability of the systems to deal with uncertainty, i.e. perturbations or unmodelled system dynamics that can affect the quality of the adaptation. Cost is another important property to ensure that resources are used prudently and frugally, whenever possible. Engineering robust and cost-effective adaptive systems can be accomplished using a control theory approach. In this paper, we show how to implement a model identification adaptive controller (MIAC) using a combination of performance and control models and how such a system satisfies the goals for robustness and cost-effectiveness. The controller we employ is multi-input, meaning that it can issue a variety of commands to adapt the system and multi-output, meaning it can regulate multiple performance indicators simultaneously. We show that such a solution can account for uncertainty and modelling errors and efficiently adapt a web application with multiple tiers of functionality spanning multiple layers of deployment, software and virtual machines, on Amazon EC2, an actual cloud environment.
The importance of sponges and mangroves in supporting fish communities on degraded coral reefs in Caribbean Panama

Fish communities associated with coral reefs worldwide are threatened by habitat degradation and overexploitation. We assessed coral reefs, mangrove fringes, and seagrass meadows on the Caribbean coast of Panama to explore the influences of their proximity to one another, habitat cover, and environmental characteristics in sustaining biomass, species richness and trophic structure of fish communities in a degraded tropical ecosystem. We found 94% of all fish across all habitat types were of small body size (≤10 cm), with communities dominated by fishes that usually live in habitats of low complexity, such as Pomacentridae (damselfishes) and Gobiidae (gobies). Total fish biomass was very low, with the trend of small fishes from low trophic levels over-represented, and top predators under-represented, relative to coral reefs elsewhere in the Caribbean. For example, herbivorous fishes comprised 27% of total fish biomass in Panama relative to 10% in the wider Caribbean, and the small parrotfish Scarus iseri comprised 72% of the parrotfish biomass. We found evidence that non-coral biogenic habitats support reef-associated fish communities. In particular, the abundance of sponges on a given reef and proximity of mangroves were found to be important positive correlates of reef fish species richness, biomass, abundance and trophic structure. Our study indicates that a diverse fish community can persist on degraded coral reefs, and that the availability and arrangement within the seascape of other habitat-forming organisms, including sponges and mangroves, is critical to the maintenance of functional processes in such ecosystems.
A Descriptive Framework for Temporal Data Visualizations Based on Generalized Space‐Time Cubes

We present the generalized space‐time cube, a descriptive model for visualizations of temporal data. Visualizations are described as operations on the cube, which transform the cube's 3D shape into readable 2D visualizations. Operations include extracting subparts of the cube, flattening it across space or time or transforming the cubes geometry and content. We introduce a taxonomy of elementary space‐time cube operations and explain how these operations can be combined and parameterized. The generalized space‐time cube has two properties: (1) it is purely conceptual without the need to be implemented, and (2) it applies to all datasets that can be represented in two dimensions plus time (e.g. geo‐spatial, videos, networks, multivariate data). The proper choice of space‐time cube operations depends on many factors, for example, density or sparsity of a cube. Hence, we propose a characterization of structures within space‐time cubes, which allows us to discuss strengths and limitations of operations. We finally review interactive systems that support multiple operations, allowing a user to customize his view on the data. With this framework, we hope to facilitate the description, criticism and comparison of temporal data visualizations, as well as encourage the exploration of new techniques and systems. This paper is an extension of Bach et al.'s (2014) work.
Metamaterial Inspired Patch Antenna for ISM Band by Adding Single-Layer Complementary Split Ring Resonators

In this work, we propose the design of metamaterial inspired compact circular patch antennas loaded with complementary split-ring resonators (CSRRs) for ISM band operation. CSRRs have been incorporated horizontally inside the dielectric. The various models of CSRR loaded antennas with different patch radius are produced and are evaluated numerically with Ansoft HFSS software. The results of the suggested antenna designs are presented that reveal a comparable impedance match and radiation characteristics with those of a normal patch antenna without CSRR. The proposed antennas yield high levels of miniaturization and similar performance to the conventional patch antenna at the 2.45GHz.
Fabrication and in vivo demonstration of microchip-embedded smart electrode device for neural stimulation in retinal prosthesis

A smart electrode device for use as a retinal prosthesis was fabricated and demonstrated. As a dedicated CMOS microchip is embedded in the smart electrode, each electrode on the electrode array works as an active component individually. Operation of the smart electrode, such as selecting target electrodes and adjusting the stimulus intensity, can be controlled by external control signals from bus wirings. A smart electrode array for an animal experiment was specially designed to proof the stimulus function of the smart electrode. An in vivo demonstration using the fabricated electrode was successfully performed. Brain activation was observed as a response to retinal stimulation.
Computational Prediction of Pathogenic Network Modules in Fusarium verticillioides

Fusarium verticillioides is a fungal pathogen that triggers stalk rots and ear rots in maize. In this study, we performed a comparative analysis of wild type and loss-of-virulence mutant F. verticillioides co-expression networks to identify subnetwork modules that are associated with its pathogenicity. We constructed the F. verticillioides co-expression networks from RNA-Seq data and searched through these networks to identify subnetwork modules that are differentially activated between the wild type and mutant F. verticillioides, which considerably differ in terms of pathogenic potentials. A greedy seed-and-extend approach was utilized in our search, where we also used an efficient branch-out technique for reliable prediction of functional subnetwork modules in the fungus. Through our analysis, we identified four potential pathogenicity-associated subnetwork modules, each of which consists of interacting genes with coordinated expression patterns, but whose activation level is significantly different in the wild type and the mutant. The predicted modules were comprised of functionally coherent genes and topologically cohesive. Furthermore, they contained several orthologs of known pathogenic genes in other fungi, which may play important roles in the fungal pathogenesis.
Experimental Technologies for Imposing Mechanical Force on Cells

Most of the experimental technologies for imposing force on cells mimic only one in vivo or in vitro mechanical environment. According to the different source of forces, the loading methods can be divided into two types: modeling the force in vivo mainly to simulate fluid shear stress, liquid hydrostatic pressure, circumferential strain and substrate stretch stress; and modeling mechanics in vitro mainly including microgravity culture system, centrifugal field culture system, air hydrostatic pressurization, ultrasound stimulus and microbeam irradiation. In addition, the main experimental technologies for single cell exposed to force are listed as Micropipette aspiration technique, atomic force microscope cantilevers deflection stimulus, magnetic twisting method, and force generated by a laser tweezers trap. These main experimental technologies are discussed in this paper.
Tabata protocol: a review of its application, variations and outcomes

The great popularity of the Tabata Protocol is accompanied by an uncomfortable lack of consistency and criteria in its use, which results in many controversies in the results obtained from its utilization. The purpose of this study was to analyse the studies that based their interventions on the Tabata Protocol and to provide a critical analysis of its use.
Nanoecotoxicity assessment of graphene oxide and its relationship with humic acid

The risk assessment of nanomaterials is essential for regulatory purposes and for sustainable nanotechnological development. Although the application of graphene oxide has been widely exploited, its environmental risk is not well understood because several environmental conditions can affect its behavior and toxicity. In the present study, the graphene oxide effect from aquatic ecosystems was assessed considering the interaction with humic acid on 9 organisms: Raphidocelis subcapitata (green algae), Lemna minor (aquatic plant), Lactuca sativa (lettuce), Daphnia magna (planktonic microcrustacean), Artemia salina (brine shrimp), Chironomus sancticaroli (Chironomidae), Hydra attenuata (freshwater polyp), and Caenorhabditis elegans and Panagrolaimus sp. (nematodes). The no‐observed‐effect concentration (NOEC) was calculated for each organism. The different criteria used to calculate NOEC values were transformed and plotted as a log‐logistic function. The hypothetical 5 to 50% hazardous concentration values were, respectively, 0.023 (0.005–0.056) and 0.10 (0.031–0.31) mg L−1 for graphene oxide with and without humic acid, respectively. The safest scenario associated with the predicted no‐effect concentration values for graphene oxide in the aquatic compartment were estimated as 20 to 100 μg L−1 (in the absence of humic acid) and 5 to 23 μg L−1 (in the presence of humic acid). Finally, the present approach contributed to the risk assessment of graphene oxide–based nanomaterials and the establishment of nano‐regulations. Environ Toxicol Chem 2018;37:1998–2012. © 2018 SETAC
Snap Angle Prediction for 360$^{\circ}$ Panoramas

360$^{\circ}$ panoramas are a rich medium, yet notoriously difficult to visualize in the 2D image plane. We explore how intelligent rotations of a spherical image may enable content-aware projection with fewer perceptible distortions. Whereas existing approaches assume the viewpoint is fixed, intuitively some viewing angles within the sphere preserve high-level objects better than others. To discover the relationship between these optimal snap angles and the spherical panorama's content, we develop a reinforcement learning approach for the cubemap projection model. Implemented as a deep recurrent neural network, our method selects a sequence of rotation actions and receives reward for avoiding cube boundaries that overlap with important foreground objects. We show our approach creates more visually pleasing panoramas while using 5x less computation than the baseline.
Neuron Segmentation With High-Level Biological Priors

We present a novel approach to the problem of neuron segmentation in image volumes acquired by an electron microscopy. Existing methods, such as agglomerative or correlation clustering, rely solely on boundary evidence and have problems where such an evidence is lacking (e.g., incomplete staining) or ambiguous (e.g., co-located cell and mitochondria membranes). We investigate if these difficulties can be overcome by means of sparse region appearance cues that differentiate between pre- and postsynaptic neuron segments in mammalian neural tissue. We combine these cues with the traditional boundary evidence in the asymmetric multiway cut (AMWC) model, which simultaneously solves the partitioning and the semantic region labeling problems. We show that AMWC problems over superpixel graphs can be solved to global optimality with a cutting plane approach, and that the introduction of semantic class priors leads to significantly better segmentations.
Systematic Review, Meta-analysis, and Network Meta-analysis of the Cardiovascular Safety of Macrolides

ABSTRACT Studies reporting an increased risk for cardiac toxicities with macrolide antibiotics have raised concern regarding their cardiovascular safety. We sought to assess the cardiac safety of macrolide antibiotics as a class and of the individual agents by conducting a systematic review and network meta-analysis. Medline, Embase, and the Cochrane Library were searched up to February 2018 for studies reporting on cardiovascular outcomes with macrolides. We followed the PRISMA 2009 guidelines for data selection and extraction. Outcomes were pooled using random-effects models and odds ratios (OR), and 95% confidence intervals (CI) were calculated for arrhythmia, cardiovascular death, and myocardial infarction (MI). A total of 33 studies and data on 22,601,032 subjects were retrieved and included in the current meta-analyses. Macrolide use was not associated with the risk of arrhythmia or cardiovascular mortality. In the primary analysis, macrolide use was associated with a small but statistically significant 15% increase in risk for MI (OR = 1.15 [95% CI, 1.01 to 1.30]). In indirect network meta-analysis, erythromycin and clarithromycin were ranked considerably more likely to be associated with a higher risk for MI and significantly associated with increased risk of MI compared to azithromycin (OR = 1.58 [95% CI, 1.18 to 2.11] and OR = 1.41 [95% CI, 1.11 to 1.81], respectively). Our findings indicate that macrolide antibiotics as a group are associated with a significant risk for MI but not for arrhythmia and cardiovascular mortality. Among the macrolides, erythromycin and clarithromycin were associated with a greater risk of MI. However, it is possible that the association between macrolide use and risk of MI is the result of residual confounding.