Representing dynamic textures (DTs) plays an important role in many real implementations in the computer vision community. Due to the turbulent and non-directional motions of DTs along with the negative impacts of different factors (e.g., environmental changes, noise, illumination, etc.), efficiently analyzing DTs has raised considerable challenges for the state-of-the-art approaches. For 20 years, many different techniques have been introduced to handle the above well-known issues for enhancing the performance. Those methods have shown valuable contributions, but the problems have been incompletely dealt with, particularly recognizing DTs on large-scale datasets. In this article, we present a comprehensive taxonomy of DT representation in order to purposefully give a thorough overview of the existing methods along with overall evaluations of their obtained performances. Accordingly, we arrange the methods into six canonical categories. Each of them is then taken in a brief presentation of its principal methodology stream and various related variants. The effectiveness levels of the state-of-the-art methods are then investigated and thoroughly discussed with respect to quantitative and qualitative evaluations in classifying DTs on benchmark datasets. Finally, we point out several potential applications and the remaining challenges that should be addressed in further directions. In comparison with two existing shallow DT surveys (i.e., the first one is out of date as it was made in 2005, while the newer one (published in 2016) is an inadequate overview), we believe that our proposed comprehensive taxonomy not only provides a better view of DT representation for the target readers but also stimulates future research activities.
Nowadays, broadcasting news on social media and websites has grown at a swifter pace, which has had negative impacts on both the general public and governments; hence, this has urged us to build a fake news detection system. Contextualized word embeddings have achieved great success in recent years due to their power to embed both syntactic and semantic features of textual contents. In this article, we aim to address the problem of the lack of fake news datasets in Persian by introducing a new dataset crawled from different news agencies, and propose two deep models based on the Bidirectional Encoder Representations from Transformers model (BERT), which is a deep contextualized pre-trained model for extracting valuable features. In our proposed models, we benefit from two different settings of BERT, namely pool-based representation, which provides a representation for the whole document, and sequence representation, which provides a representation for each token of the document. In the former one, we connect a Single Layer Perceptron (SLP) to the BERT to use the embedding directly for detecting fake news. The latter one uses Convolutional Neural Network (CNN) after the BERT’s embedding layer to extract extra features based on the collocation of words in a corpus. Furthermore, we present the TAJ dataset, which is a new Persian fake news dataset crawled from news agencies’ websites. We evaluate our proposed models on the newly provided TAJ dataset as well as the two different Persian rumor datasets as baselines. The results indicate the effectiveness of using deep contextualized embedding approaches for the fake news detection task. We also show that both BERT-SLP and BERT-CNN models achieve superior performance to the previous baselines and traditional machine learning models, with 15.58% and 17.1% improvement compared to the reported results by Zamani et al. [
], and 11.29% and 11.18% improvement compared to the reported results by Jahanbakhsh-Nagadeh et al. [
Invasive species are an environmental problem affecting worldwide ecosystems. In the case of Acacia dealbata Link., the negative impacts affect the productivity of the forests due to the competition established with native species while contributing to a significant increment in the available fuel load, increasing the risk of fire. In Portugal, chemical and mechanical methods are mostly used in the control of these species. However, the costs are often unsustainable in the medium term, being abandoned before completing the tasks, allowing the recovery of the invasive species. The establishment of value chains for the biomass resulting from these actions was pointed out by several authors as a solution for the sustainability of the control process, as it contributes to reducing costs. However, the problems in quantifying the biomass availability make it challenging to organize and optimize these actions. This work, which started from a dendrometrical analysis carried out in stands of A. dealbata, created a model to assess woody biomass availability. The model proved to be statistically significant for stands with trees younger than 20 years old. However, the amount of data collected and the configuration of the settlements analyzed do not allow extrapolation of the model presented to older settlements.
COVID-19 lockdowns have resulted in school closures worldwide, requiring curriculum to be delivered to children remotely (home schooling). Qualitative evidence is needed to provide important context to the positive and negative impacts of home schooling and inform strategies to support caregivers and children as the pandemic continues. This study aimed to explore the experiences of home schooling caregivers at multiple time-points during the pandemic.
Data were obtained from a longitudinal survey of a representative Australian sample conducted over 8 waves during 2020 and 2021. Participants who had home schooled at least one child during COVID-19 completed open-ended questions at Wave 4 (May 2020; n = 176), Wave 7 (June 2020; n = 145), and Wave 8 (March 2021; n = 57). Participants were asked to describe what they found positive and challenging about home schooling (Wave 4), what they would do differently if they home schooled their children again (Wave 7), and the longer-term impacts of home schooling on caregivers and children (Wave 8).
91% of participants at Wave 4 reported at least one positive and/or negative aspect of home schooling. At Wave 8, 32% and 29% of participants reported no long-term positive or negative impacts of home schooling respectively. Using a qualitative content analysis approach, six themes were developed from the data, encompassing the impacts of home schooling on parents, and the perceived impacts on children. Impacts on parents included connecting with children, managing the work-life-school balance, and the challenge of home schooling when parents are not teachers. Perceived impacts on children included: quieter and safer learning at home, and the negatives of managing schoolwork load and social isolation. At Wave 7, 56 participants (44%) identified at least one thing they would do differently.
Despite some participants reporting positive experiences associated with home schooling, it remains challenging for many parents and their children. Supports for parents and children engaged in home schooling should provide clear and flexible guidance on how to balance schoolwork with other competing demands, assist parents who lack confidence in supporting their children’s remote learning, and address risks associated with social isolation.
The last century has witnessed an increasing rate of new disease emergence across the world leading to permanent loss of biodiversity. Perkinsea is a microeukaryotic parasitic phylum composed of four main lineages of parasitic protists with broad host ranges. Some of them represent major ecological and economical threats because of their geographically invasive ability and pathogenicity (leading to mortality events). In marine environments, three lineages are currently described, the Parviluciferaceae, the Perkinsidae, and the Xcellidae, infecting, respectively, dinoflagellates, mollusks, and fish. In contrast, only one lineage is officially described in freshwater environments: the severe Perkinsea infectious agent infecting frog tadpoles. The advent of high-throughput sequencing methods, mainly based on 18S rRNA assays, showed that Perkinsea is far more diverse than the previously four described lineages especially in freshwater environments. Indeed, some lineages could be parasites of green microalgae, but a formal nature of the interaction needs to be explored. Hence, to date, most of the newly described aquatic clusters are only defined by their environmental sequences and are still not (yet) associated with any host. The unveiling of this microbial black box presents a multitude of research challenges to understand their ecological roles and ultimately to prevent their most negative impacts. This review summarizes the biological and ecological traits of Perkinsea—their diversity, life cycle, host preferences, pathogenicity, and highlights their diversity and ubiquity in association with a wide range of hosts.
Harmful algal blooms (HABs) are extreme biological events representing a major issue in marine, brackish, and freshwater systems worldwide. Their proliferation is certainly a problem from both ecological and socioeconomic contexts, as harmful algae can affect human health and activities, the marine ecosystem functioning, and the economy of coastal areas. Once HABs establish, valuable and environmentally friendly control actions are needed to reduce their negative impacts. In this study, the influence exerted by the filter-feeding activity of the two sabellid polychaetes Branchiomma luctuosum (Grube) and Sabella spallanzanii (Gmelin) on a harmful dinoflagellate was investigated. Clearance rates (C) and retention efficiencies were estimated by employing the microalga Amphidinium carterae Hulburt. The Cmax was 1.15 ± 0.204 L h−1 g−1 DW for B. luctuosum and 0.936 ± 0.151 L h−1 g−1 DW for S. spallanzanii. The retention efficiency was 72% for B. luctuosum and 68% for S. spallanzanii. Maximum retention was recorded after 30 min for both species. The obtained results contribute to the knowledge of the two polychaetes’ filtration activity and to characterize the filtration process on harmful microalgae in light of the protection of water resources and human health. Both species, indeed, were extremely efficient in removing A. carterae from seawater, thus suggesting their employment as a new tool in mitigation technologies for the control of harmful algae in marine environments, as well as in the aquaculture facilities where HABs are one of the most critical threats.
This article provides a case study of child sex tourism (CST) in Surabaya, Indonesia. CST cases are difficult to surface because the victims of CST are such vulnerable human beings. Victims of CST need a variety of forms of support for their recovery and reintegration. This article contends that social, economic, political, technological, and individual factors cause CST. It examines the negative impacts of CST, which are medical, social, psychological, and physical in nature. It also reveals that the techniques used for CST recruitment are fake promises, debt bondage, emotional abuse, counterfeit love, drug addiction, physical abuse, and gifts and favors. The elimination of CST calls for ending certain depraved cultural practices and beliefs, rehabilitation and reintegration of the victims, proactive anti-CST government policies and programs, enactment and effective enforcement of tough laws prohibiting CST, prosecution of the offenders, raising public awareness about the ills of CST, providing education for all children, the provision of national identification documents to all children, and strict border controls to prevent the trafficking of children for sex tourism.
The COVID-19 pandemic propelled many physicians and their patients into an unfamiliar world of virtual care. This presentation is based on the perceptions of a family physician/ teacher/ researcher with 43 years of interest in, and promotion of, a strong doctor-patient relationship. It will describe a protocol that governed how tele-medicine and video-conferencing took place over nearly 18 months in his practice. It will then describe observed positive and negative impacts for the patients, their family members, the physician, and members of the family medicine health care team. Interpretation will be made about what such observations mean for the doctor-patient relationship.
Microplastics (MPs) are ubiquitous in our environment. Its presence in air, water and soil makes it a serious threat to living organisms. The present study aimed to assess the availability of MPs in air and street dust of a metropolitan city Varanasi, India. Suspended dust samples and street dust samples were collected from various sampling sites. The assessment of MPs was conducted by for physical identification binocular microscopy, fluorescence microscopy and Scanning Electron Microscopy (SEM), while elemental analysis done by Energy Dispersive X-Ray Analysis (EDX). and finally, Fourier-transform infrared spectroscopy (FTIR) was used for functional group analysis. the presence of MPs in both suspended dust and street dust samples of all selected sampling sites was confirmed by results. MPs of different color with the shape of Fragments, Films, Spherules and Fibers were observed in the study. However, most of the MPs were less than 1mm in size. The MPs identified in our study were majorly polypropylene, polystyrene, polyethylene, polyethylene terephthalate, polyester, and polyvinyl chloride. EDX analysis showed presence of trace elements like aluminum, cadmium, magnesium, sodium, and silicon apart from carbon and oxygen, which indicates the presence of additives or adsorption capacity of MPs. Confirmation of MPs in the air of a locality of Varanasi explains the need of deep research in this concerned field to protect our future from negative impacts of breathing MPs.