DFVS: Deep Flow Guided Scene Agnostic Image Based Visual Servoing

Existing deep learning based visual servoing approaches regress the relative camera pose between a pair of images. Therefore, they require a huge amount of training data and sometimes fine-tuning for adaptation to a novel scene. Furthermore, current approaches do not consider underlying geometry of the scene and rely on direct estimation of camera pose. Thus, inaccuracies in prediction of the camera pose, especially for distant goals, lead to a degradation in the servoing performance. In this paper, we propose a two-fold solution: (i) We consider optical flow as our visual features, which are predicted using a deep neural network. (ii) These flow features are then systematically integrated with depth estimates provided by another neural network using interaction matrix. We further present an extensive benchmark in a photo-realistic 3D simulation across diverse scenes to study the convergence and generalisation of visual servoing approaches. We show convergence for over 3m and 40 degrees while maintaining precise positioning of under 2cm and 1 degree on our challenging benchmark where the existing approaches that are unable to converge for majority of scenarios for over 1.5m and 20 degrees. Furthermore, we also evaluate our approach for a real scenario on an aerial robot. Our approach generalizes to novel scenarios producing precise and robust servoing performance for 6 degrees of freedom positioning tasks with even large camera transformations without any retraining or fine-tuning.Comment: Accepted in International Conference on Robotics and Automation (ICRA) 2020, IEE

Targeting the retinoic acid signaling pathway as a modern precision therapy against cancers

Retinoic acid (RA) is a vital metabolite derived from vitamin A. RA plays a prominent role during development, which helps in embryological advancement and cellular differentiation. Mechanistically, RA binds to its definite nuclear receptors including the retinoic acid receptor and retinoid X receptor, thus triggering gene transcription and further consequences in gene regulation. This functional heterodimer activation later results in gene activation/inactivation. Several reports have been published related to the detailed embryonic and developmental role of retinoic acids and as an anti-cancer drug for specific cancers, including acute promyelocytic leukemia, breast cancer, and prostate cancer. Nonetheless, the other side of all-trans retinoic acid (ATRA) has not been explored widely yet. In this review, we focused on the role of the RA pathway and its downstream gene activation in relation to cancer progression. Furthermore, we explored the ways of targeting the retinoic acid pathway by focusing on the dual role of aldehyde dehydrogenase (ALDH) family enzymes. Combination strategies by combining RA targets with ALDH-specific targets make the tumor cells sensitive to the treatment and improve the progression-free survival of the patients. In addition to the genomic effects of ATRA, we also highlighted the role of ATRA in non-canonical mechanisms as an immune checkpoint inhibitor, thus targeting the immune oncological perspective of cancer treatments in the current era. The role of ATRA in activating independent mechanisms is also explained in this review. This review also highlights the current clinical trials of ATRA in combination with other chemotherapeutic drugs and explains the future directional insights related to ATRA usage

Prospective nutritional, therapeutic, and dietary benefits of camel milk making it a viable option for human consumption: Current state of scientific knowledge

For over five thousand years, people in Asia and Africa have known about the health benefits of camel milk. Thus, it is used not only as a food source but also as a medicine. The similarities between camel milk and human milk have been scientifically proven. Camel milk is unique among ruminant milk because it is high in vitamins C and E and low in sugar and cholesterol. Still, it contains a wide variety of beneficial minerals (including sodium, potassium, iron, copper, zinc, and magnesium), besides being rich in several nutrients, including monounsaturated and polyunsaturated fatty acids, serum albumin, lactoferrin, immunoglobulins, lysozyme and the hormone insulin. Because of these components, many medical professionals now recommend camel milk as a treatment for various human ailments. It has been demonstrated to be effective in treating gastrointestinal issues, Type 1 diabetes, and food allergies. As a bonus, camel milk has been utilized to cure autism, lower cholesterol, prevent psoriasis, heal inflammation, aid tuberculosis patients, boost the body's natural defences, and impede the spread of cancer cells. Those who have problems digesting lactose may still be able to tolerate it. Conversely, camel milk can also help reduce an excessively high bilirubin, globulin, and granulocyte count. Drinking camel milk does not affect the erythrocyte sedimentation rate, hemoglobin concentration, and leukocyte count. The proteins in camel milk have an adequate ratio of critical amino acids. Immunoglobulins, which fight disease, are contained inside, and their small size allows antigens to penetrate and boosts the immune system's efficacy. This article highlights the health benefits and medicinal uses of camel milk

Beneficial impacts of biochar as a potential feed additive in animal husbandry

In the last decade, biochar production and use have grown in popularity. Biochar is comparable to charcoal and activated charcoal because it is a pyrogenic carbonaceous matter made by pyrolyzing organic carbon-rich materials. There is a lack of research into the effects of adding biochar to animal feed. Based on the reviewed literature, including its impact on the adsorption of toxins, blood biochemistry, feed conversion rate, digestion, meat quality, and greenhouse gas emissions, adding biochar to the diet of farm animals is a good idea. This study compiles the most important research on biochar's potential as a supplement to the diets of ruminants (including cows and goats), swine, poultry, and aquatic organisms like fish. Biochar supplementation improves animal growth, haematological profiles, meat, milk and egg yield, resistance to illnesses (especially gut pathogenic bacteria), and reduced ruminant methane emission. Biochar's strong sorption capacity also helps efficiently remove contaminants and poisons from the animals' bodies and the farm surroundings where they are raised. Animal farmers are predicted to make greater use of biochar in the future. Biochar could potentially be of value in the healthcare and human health fields; hence research into this area is encouraged. The present review highlights the potential benefits of biochar as an additive to animal feed and demonstrates how, when combined with other environmentally friendly practices, biochar feeding can extend the longevity of animal husbandry

A multi-pronged approach targeting SARS-CoV-2 proteins using ultra-large virtual screening.

The unparalleled global effort to combat the continuing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic over the last year has resulted in promising prophylactic measures. However, a need still exists for cheap, effective therapeutics, and targeting multiple points in the viral life cycle could help tackle the current, as well as future, coronaviruses. Here, we leverage our recently developed, ultra-large-scale in silico screening platform, VirtualFlow, to search for inhibitors that target SARS-CoV-2. In this unprecedented structure-based virtual campaign, we screened roughly 1 billion molecules against each of 40 different target sites on 17 different potential viral and host targets. In addition to targeting the active sites of viral enzymes, we also targeted critical auxiliary sites such as functionally important protein-protein interactions

Neuromatch Academy: a 3-week, online summer school in computational neuroscience

Neuromatch Academy (https://academy.neuromatch.io; (van Viegen et al., 2021)) was designed as an online summer school to cover the basics of computational neuroscience in three weeks. The materials cover dominant and emerging computational neuroscience tools, how they complement one another, and specifically focus on how they can help us to better understand how the brain functions. An original component of the materials is its focus on modeling choices, i.e. how do we choose the right approach, how do we build models, and how can we evaluate models to determine if they provide real (meaningful) insight. This meta-modeling component of the instructional materials asks what questions can be answered by different techniques, and how to apply them meaningfully to get insight about brain function

Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016

The UN’s Sustainable Development Goals (SDGs) are grounded in the global ambition of “leaving no one behind”. Understanding today’s gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990–2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030