Landslide Detection in Real-Time Social Media Image Streams

Lack of global data inventories obstructs scientific modeling of and response to landslide hazards which are oftentimes deadly and costly. To remedy this limitation, new approaches suggest solutions based on citizen science that requires active participation. However, as a non-traditional data source, social media has been increasingly used in many disaster response and management studies in recent years. Inspired by this trend, we propose to capitalize on social media data to mine landslide-related information automatically with the help of artificial intelligence (AI) techniques. Specifically, we develop a state-of-the-art computer vision model to detect landslides in social media image streams in real time. To that end, we create a large landslide image dataset labeled by experts and conduct extensive model training experiments. The experimental results indicate that the proposed model can be deployed in an online fashion to support global landslide susceptibility maps and emergency response

Cinética da adsorção de Cd, Co, Cr, Cu, K, Ni e Zn em soluções aquosas usando zeólita natural integrada à tecnologia LTCC.

Materiais naturais, disponíveis em grandes quantidades e que possam ser empregados como adsorventes de baixo custo para o tratamento de efluentes, vem sendo o alvo de inúmeras pesquisas. Quitosana, zeólitas, esponjas naturais e carvão ativado são empregados com sucesso para este propósito1. Dentro deste contexto, o objetivo do trabalho foi investigar a capacidade de remoção de Cd, Co, Cr, Cu, K, Ni e Zn através de uma amostra de zeólita natural integrada a dispositivos cerâmicos mediante a tecnologia LTCC

A national strategy to promote Open Educational Practices in higher education in Australia

Currently in Australia, there are no policies and regulations at national levels to promote and encourage the adoption of Open Educational Practices (OEP) across the higher education sector. As an attempt to bridge this policy gap, a project proposal was developed by a group of OEP advocates and researchers and then successfully funded by the Australian Government Department of Education and Training (AGDET). This paper explores and discusses the approaches, deliverables and recommendations of this project titled Students, Universities and Open Education (OpenEdOz) Project. One of its main deliverables was a National Policy Roadmap, which aimed to assist the government to realise the potential of OEP for the Australian higher education sector and open up opportunities for further national policy development and support in which OEP can flourish. The policy roadmap was informed by a range of national and international evidenced-based case studies related to OEP projects and initiatives

Kinetics of adsorption of Cd, Co, Cr, Cu, K, Ni and Zn in aqueous solutions using natural zeolite integrated to LTCC technology.

The LTCC technology (Low Temperature Co-fired Ceramics) has become much more versatile than any technique applied so far in the field of miniaturization, since allowing the construction of threedimensional devices quickly and easily. Due to the ease of handling, the green ceramic provide the multilayer arrangement of modules with different applications, such as, among others, in the field of microelectronics and manufacturing microvalves and microfluidic systems applied in flow injection systems. Natural materials, available in large quantities and that can be used as low cost adsorbents for wastewater treatment have been the target of numerous studies. As an example, chitosan, zeolites, natural sponges and activated carbon are used successfully for this purpose. Zeolites are natural or synthetic minerals, with a wide variety of technological applications. Its structure has channels and cavities in which it is possible to settle ions, water molecules or other adsorbates and salts. This study aimed to investigate the removal capacity of Cd, Cr, Cu, K, Ni and Zn by a sample of natural zeolite ceramic integrated devices through the LTCC technology. Ceramic systems with 2.6 cm long and 1.7 cm wide were constructed with natural zeolite integrated inside. The experimental parameters were optimized employing 10 mL of a 5 mg L-1 containing Cd, Co, Cr, Cu, K, Ni and Zn. The influence of pH and time on adsorption of metals by natural zeolite was evaluated. After the adsorption step solutions were analyzed by optical emission spectroscopy with inductively coupled plasma (ICP OES) for the analytes determination. The results showed that the determining factor in the adsorption capacity of natural zeolite is the pH of the solution. In the pH range of 6 up to 7 the competition adsorption of analytes was not observed. Values above 88% of adsorption were obtained for all metal ions studied. The kinetic study indicated that equilibrium was reached in approximately 2 hours of contact between the solution and natural zeolite. The results demonstrated the viability in the adsorption of Cd, Co, Cr, Cu, K, Ni and Zn in natural zeolite integrated ceramic systems, and the pH factor in optimizing the adsorption capacity of zeolite

Removal of visual disruption caused by rain using cycle-consistent generative adversarial networks

This paper addresses the problem of removing rain disruption from images without blurring scene content, thereby retaining the visual quality of the image. This is particularly important in maintaining the performance of outdoor vision systems, which deteriorates with increasing rain disruption or degradation on the visual quality of the image. In this paper, the Cycle-Consistent Generative Adversarial Network (CycleGAN) is proposed as a more promising rain removal algorithm, as compared to the state-of-the-art Image De-raining Conditional Generative Adversarial Network (ID-CGAN). One of the main advantages of the CycleGAN is its ability to learn the underlying relationship between the rain and rain-free domain without the need of paired domain examples, which is essential for rain removal as it is not possible to obtain the rain-free image under dynamic outdoor conditions. Based on the physical properties and the various types of rain phenomena [10], five broad categories of real rain distortions are proposed, which can be applied to the majority of outdoor rain conditions. For a fair comparison, both the ID-CGAN and CycleGAN were trained on the same set of 700 synthesized rain-and-ground-truth image-pairs. Subsequently, both networks were tested on real rain images, which fall broadly under these five categories. A comparison of the performance between the CycleGAN and the ID-CGAN demonstrated that the CycleGAN is superior in removing real rain distortions

An Augmented Negative Force-Frequency Relationship and Slowed Mechanical Restitution Are Associated With Increased Susceptibility to Drug-Induced Torsade de Pointes Arrhythmias in the Chronic Atrioventricular Block Dog

Introduction: In the chronic AV-block (CAVB) dog model, structural, contractile, and electrical remodeling occur, which predispose the heart to dofetilide-induced Torsade de Pointes (TdP) arrhythmias. Previous studies found a relation between electrical remodeling and inducibility of TdP, while structural remodeling is not a prerequisite for arrhythmogenesis. In this study, we prospectively assessed the relation between in vivo markers of contractile remodeling and TdP inducibility.Methods: In 18 anesthetized dogs, the maximal first derivative of left ventricular pressure (LV dP/dtmax) was assessed at acute AV-block (AAVB) and after 2 weeks of chronic AV-block (CAVB2). Using pacing protocols, three markers of contractile remodeling, i.e., force-frequency relationship (FFR), mechanical restitution (MR), and post-extrasystolic potentiation (PESP) were determined. Infusion of dofetilide (0.025 mg/kg in 5 min) was used to test for TdP inducibility.Results: After infusion of dofetilide, 1/18 dogs and 12/18 were susceptible to TdP-arrhythmias at AAVB and CAVB2, respectively (p = 0.001). The inducible dogs at CAVB2 showed augmented contractility at a CL of 1200 ms (2354 ± 168 mmHg/s in inducible dogs versus 1091 ± 59 mmHg/s in non-inducible dogs, p < 0.001) with a negative FFR, while the non-inducible dogs retained their positive FFR. The time constant (TC) of the MR curve was significantly higher in the inducible dogs (158 ± 7 ms versus 97 ± 8 ms, p < 0.0001). Furthermore, a linear correlation was found between a weighted score of the number and severity of arrhythmias and contractile parameters, i.e., contractility at CL of 1200 ms (r = 0.73, p = 0.002), the slope of the FFR (r = -0.58, p = 0.01) and the TC of MR (r = 0.66, p = 0.003). Thus, more severe arrhythmias were seen in dogs with the most pronounced contractile remodeling.Conclusion: Contractile remodeling is concomitantly observed with susceptibility to dofetilide-induced TdP-arrhythmias. The inducible dogs show augmented contractile remodeling compared to non-inducible dogs, as seen by a negative FFR, higher maximal response of MR and PESP and slowed MR kinetics. These altered contractility parameters could reflect disrupted Ca2+ handling and Ca2+-overload, which predispose the heart to delayed- and early afterdepolarizations that could trigger TdP-arrhythmias

A near-real-time global landslide incident reporting tool demonstrator using social media and artificial intelligence

The development of a system that monitors social media continuously for general landslide-related content using a landslide classification model to identify and retain the most relevant information is described and validated. The system harvests photographs in real-time from these data and tags each image as landslide or not-landslide. A training model was developed with input from computer scientists, geologists (landslide specialists) and social media specialists to establish a large image dataset that has then been applied to the live Twitter data stream. The preliminary model was developed by training a convolutional neural network on the dataset. Quantitative verification of the system's performance during a real-world deployment shows that the system can detect landslide reports with Precision = 76%. The demonstrator model is currently running live https://landslide-aidr.qcri.org/service.php; the next stage of development will incorporate stakeholder and user feedback

Search for lepton-flavour-violating decays of Higgs-like bosons.

A search is presented for a Higgs-like boson with mass in the range 45 to 195 GeV/c2 decaying into a muon and a tau lepton. The dataset consists of proton-proton interactions at a centre-of-mass energy of 8 TeV , collected by the LHCb experiment, corresponding to an integrated luminosity of 2 fb-1 . The tau leptons are reconstructed in both leptonic and hadronic decay channels. An upper limit on the production cross-section multiplied by the branching fraction at 95% confidence level is set and ranges from 22 pb for a boson mass of 45 GeV/c2 to 4 pb for a mass of 195 GeV/c2