A multimodal deep learning architecture for smoking detection with a small data approach

Introduction: Covert tobacco advertisements often raise regulatory measures. This paper presents that artificial intelligence, particularly deep learning, has great potential for detecting hidden advertising and allows unbiased, reproducible, and fair quantification of tobacco-related media content. Methods: We propose an integrated text and image processing model based on deep learning, generative methods, and human reinforcement, which can detect smoking cases in both textual and visual formats, even with little available training data. Results: Our model can achieve 74\% accuracy for images and 98\% for text. Furthermore, our system integrates the possibility of expert intervention in the form of human reinforcement. Conclusions: Using the pre-trained multimodal, image, and text processing models available through deep learning makes it possible to detect smoking in different media even with few training data

Fragment connectivity shapes bird communities through functional trait filtering in two types of grasslands

Habitat fragmentation is considered one of the most severe threatening factors for global biodiversity. Here we assessed, how local and landscape scale environmental variables, such as fragment size (small vs. large) and landscape configuration (measured as connectivity index) relates to bird community composition, species richness, abundance and functional diversity. We surveyed 60 grassland fragments in Hungary, belonging to two different threatened grassland types, namely forest-steppes and kurgans. Forest-steppes are natural mosaics of grasslands and forests at the contact zone between closed-canopy temperate forests and steppe grasslands. Kurgans are ancient burial mounds, found on the Eurasian steppe and forest steppe zone. These fragments were embedded in plantation forestry, respectively, agricultural matrix with gradients of size and connectivity. Both habitats are threatened by forestry and agricultural intensification, though these fragments may serve as important wildlife refuges. Our findings revealed that forest-steppe birds were more diverse and abundant in large and well-connected than in small isolated fragments. High connectivity affected ground nesting birds in small forest-steppe fragments positively. Birds inhabiting kurgan area showed higher trait similarity in well-connected than in isolated fragments. Bird abundance of kurgans associated with small home range size and ground feeding habit were higher in connected compared to isolated fragments. Highly isolated kurgans filtered for more specialised bird species but not for generalists. We provide conservation implications for enhancing grassland specialist bird communities, which consist of preservation of large, well-connected grassland fragments within production landscapes and through reconsideration of the currently used intensive forestryinfo:eu-repo/semantics/publishedVersio

A Cloud-based Machine Learning Pipeline for the Efficient Extraction of Insights from Customer Reviews

The efficiency of natural language processing has improved dramatically with the advent of machine learning models, particularly neural network-based solutions. However, some tasks are still challenging, especially when considering specific domains. In this paper, we present a cloud-based system that can extract insights from customer reviews using machine learning methods integrated into a pipeline. For topic modeling, our composite model uses transformer-based neural networks designed for natural language processing, vector embedding-based keyword extraction, and clustering. The elements of our model have been integrated and further developed to meet better the requirements of efficient information extraction, topic modeling of the extracted information, and user needs. Furthermore, our system can achieve better results than this task's existing topic modeling and keyword extraction solutions. Our approach is validated and compared with other state-of-the-art methods using publicly available datasets for benchmarking

Applicability of flexible photovoltaic modules onto membrane structures using grasshopper integrative model

The potentials of integrating thin-film photovoltaic technology into buildings make it the recommended renewable energy source not only for traditional architectures, but also the most innovative applications that favour envelopes characterized by free morphologies such as membrane structures. The integration of Photovoltaic technology into membrane structures offers a promising significant step in the market development. However, some challenges and questions are arising relating to the applicability of such systems and how they are significantly dependant on a list of complex aspects that have to be taken into account during the design phase. These aspects include the wide variety of membrane three-dimensional geometries that in turn govern the modules distribution, orientation and shadowing as well as the distribution of stresses and deflections for each single project and how both the structure and modules react to them. The interference between the aforementioned aspects makes it hardly investigated without using a parametric tool that's able to analyze multiple parameters in an integrative real time process. Therefore, a parametric Photovoltaic model using Grasshopper was developed as a part of the PhD dissertation of the first author, Ibrahim H., With the target to analyze the aspects that impact the payback time of the PV system such as the layout orientation, the effect of shadowing and the maximum deflection allowed for the membrane surface under different loading conditions concluding with calculating the total clear surface area available for allocating PV modules. This paper presents how Grasshopper parametric tool can be efficiently used for analysing and evaluating the feasibility of applying flexible PV systems on tensile structures geometries. The outcomes of this research work will be applied to the structures designed and manufactured by Inside2Outside Ltd within the research activities founded by Innovate UK during the 30 month Knowledge Transfer Partnership KTP9912

A miniaturized bioreactor system for the evaluation of cell interaction with designed substrates in perfusion culture

In tissue engineering, the chemical and topographical cues within three-dimensional (3D) scaffolds are normally tested using static cell cultures but applied directly to tissue cultures in perfusion bioreactors. As human cells are very sensitive to the changes of culture environment, it is essential to evaluate the performance of any chemical, and topographical cues in a perfused environment before they are applied to tissue engineering. Thus the aim of this research was to bridge the gap between static and perfusion cultures by addressing the effect of perfusion on cell cultures within 3D scaffolds. For this we developed a scale down bioreactor system, which allows to evaluate the effectiveness of various chemical and topographical cues incorporated into our previously developed tubular ε-polycaprolactone scaffold under perfused conditions. Investigation of two exemplary cell types (fibroblasts and cortical astrocytes) using the miniaturized bioreactor indicated that: (1) quick and firm cell adhesion in 3D scaffold was critical for cell survival in perfusion culture compared with static culture, thus cell seeding procedures for static cultures might not be applicable. Therefore it was necessary to re-evaluate cell attachment on different surfaces under perfused conditions before a 3D scaffold was applied for tissue cultures, (2) continuous medium perfusion adversely influenced cell spread and survival, which could be balanced by intermittent perfusion, (3) micro-grooves still maintained its influences on cell alignment under perfused conditions, while medium perfusion demonstrated additional influence on fibroblast alignment but not on astrocyte alignment on grooved substrates. This research demonstrated that the mini-bioreactor system is crucial for the development of functional scaffolds with suitable chemical and topographical cues by bridging the gap between static culture and perfusion culture

Landscape-scale connectivity and fragment size determine species composition of grassland fragments

As a consequence of agricultural intensification and habitat fragmentation since the mid-20th century, biological diversity has declined considerably throughout the world, particularly in Europe. We assessed how habitat and landscape-scale heterogeneity, such as variation in fragment size (small vs. large) and landscape configuration (measured as connectivity index), affect plant and arthropod diversity. We focused on arthropods with different feeding behaviour and mobility, spiders (predators, moderate dispersal), true bugs (mainly herbivores and omnivores with moderate dispersal), wild bees (pollinators with good dispersal abilities), and wasps (pollinators, omnivores with good dispersal abilities). We studied 60 dry grassland fragments in the same region (Hungarian Great Plain); 30 fragments were represented by the grassland component of forest-steppe stands, and 30 were situated on burial mounds (kurgans). Forest-steppes are mosaics of dry grasslands with small forests in a matrix of plantation forests. Kurgans are ancient burial mounds with moderately disturbed grasslands surrounded by agricultural fields. The size of fragments ranged between 0.16 6.88 ha (small: 0.16 0.48 ha, large: 0.93 6.88 ha) for forest-steppes and 0.01 0.44 ha (small: 0.01 0.10 ha and large: 0.20 0.44 ha) for kurgans. Fragments also represented an isolation gradient from almost cleared and homogenous landscapes, to landscapes with relatively high compositional heterogeneity. Fragment size, connectivity, and their interaction affected specialist and generalist species abundances of forest-steppes and kurgans. Large fragments had higher species richness of ground-dwelling spiders, and the effect of connectivity was more strongly positive for specialist arthropods and more strongly negative for generalists in large than in small fragments. However, we also found a strong positive impact of connectivity for generalist plants in small kurgans in contrast to larger ones. We conclude that besides the well-known effect of enhancing habitat quality, increasing connectivity between fragments by restoring natural and semi-natural habitat patches would help to maintain grassland biodiversityinfo:eu-repo/semantics/publishedVersio

Development of a novel 3D culture system for screening features of a complex implantable device for CNS repair

Tubular scaffolds which incorporate a variety of micro- and nanotopographies have a wide application potential in tissue engineering especially for the repair of spinal cord injury (SCI). We aim to produce metabolically active differentiated tissues within such tubes, as it is crucially important to evaluate the biological performance of the three-dimensional (3D) scaffold and optimize the bioprocesses for tissue culture. Because of the complex 3D configuration and the presence of various topographies, it is rarely possible to observe and analyze cells within such scaffolds in situ. Thus, we aim to develop scaled down mini-chambers as simplified in vitro simulation systems, to bridge the gap between two-dimensional (2D) cell cultures on structured substrates and three-dimensional (3D) tissue culture. The mini-chambers were manipulated to systematically simulate and evaluate the influences of gravity, topography, fluid flow, and scaffold dimension on three exemplary cell models that play a role in CNS repair (i.e., cortical astrocytes, fibroblasts, and myelinating cultures) within a tubular scaffold created by rolling up a microstructured membrane. Since we use CNS myelinating cultures, we can confirm that the scaffold does not affect neural cell differentiation. It was found that heterogeneous cell distribution within the tubular constructs was caused by a combination of gravity, fluid flow, topography, and scaffold configuration, while cell survival was influenced by scaffold length, porosity, and thickness. This research demonstrates that the mini-chambers represent a viable, novel, scale down approach for the evaluation of complex 3D scaffolds as well as providing a microbioprocessing strategy for tissue engineering and the potential repair of SCI

The loss of histone H3 lysine 9 acetylation due to dSAGA-specific dAda2b mutation influences the expression of only a small subset of genes

In Drosophila, the dADA2b-containing dSAGA complex is involved in histone H3 lysine 9 and 14 acetylation. Curiously, although the lysine 9- and 14-acetylated histone H3 levels are drastically reduced in dAda2b mutants, these animals survive until a late developmental stage. To study the molecular consequences of the loss of histone H3 lysine 9 and 14 acetylation, we compared the total messenger ribonucleic acid (mRNA) profiles of wild type and dAda2b mutant animals at two developmental stages. Global gene expression profiling indicates that the loss of dSAGA-specific H3 lysine 9 and 14 acetylation results in the expression change (up- or down-regulation) of a rather small subset of genes and does not cause a general transcription de-regulation. Among the genes up-regulated in dAda2b mutants, particularly high numbers are those which play roles in antimicrobial defense mechanisms. Results of chromatin immunoprecipitation experiments indicate that in dAda2b mutants, the lysine 9-acetylated histone H3 levels are decreased both at dSAGA up- and down-regulated genes. In contrast to that, in the promoters of dSAGA-independent ribosomal protein genes a high level of histone H3K9ac is maintained in dAda2b mutants. Our data suggest that by acetylating H3 at lysine 9, dSAGA modifies Pol II accessibility to specific promoters differently

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Auditory Cortex Tracks Both Auditory and Visual Stimulus Dynamics Using Low-Frequency Neuronal Phase Modulation

How is naturalistic multisensory information combined in the human brain? Based on MEG data we show that phase modulation of visual and auditory signals captures the dynamics of complex scenes