3714 research outputs found
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The worldwide impact of telemedicine during COVID-19: current evidence and recommendations for the future
No full textDuring the COVID-19 pandemic, telemedicine has emerged worldwide as an indispensable resource to improve the surveillance of patients, curb the spread of disease, facilitate timely identification and management of ill people, but, most importantly, guarantee the continuity of care of frail patients with multiple chronic diseases. Although during COVID-19 telemedicine has thrived, and its adoption has moved forward in many countries, important gaps still remain. Major issues to be addressed to enable large scale implementation of telemedicine include: (1) establishing adequate policies to legislate telemedicine, license healthcare operators, protect patients’ privacy, and implement reimbursement plans; (2) creating and disseminating practical guidelines for the routine clinical use of telemedicine in different contexts; (3) increasing in the level of integration of telemedicine with traditional healthcare services; (4) improving healthcare professionals’ and patients’ awareness of and willingness to use telemedicine; and (5) overcoming inequalities among countries and population subgroups due to technological, infrastructural, and economic barriers. If all these requirements are met in the near future, remote management of patients will become an indispensable resource for the healthcare systems worldwide and will ultimately improve the management of patients and the quality of care
Accelerated development of hard high-entropy alloys with data-driven high-throughput experiments
No full textThe development of multicomponent alloys with target properties poses a significant challenge, owing to the enormous number of potential component combinations, high costs and the inefficiency of conventional empirical trial-and-error experimental approaches. To tackle this challenge, we develop a machine learning (ML)-guided high-throughput experimental (HTE) approach to accelerate the development of non-equimolar hard CoxCryTizMouWv high-entropy alloys (HEAs). We first develop a set of all-process HTE facilities ranging from multi-tube ingredient assignment to multi-station electrical arc smelting and specimen preparation for bulk alloy samples with discrete compositions. Instead of random or combinatorial composition searching, HEAs with only ~1/28 of all the potential compositions are synthesized in two stages guided by the ML prediction. The final ML models, trained using 138 experimental data, predict the alloy hardness with mean relative errors of 5.3%, 6.3% and 15.4% at high (HV > 800), medium (HV = 600-800) and low (HV < 600) hardness ranges, respectively. In total, 14 superhard HEAs with HV > 900 are discovered by our ML-guided HTE approach. Moreover, the multiple ML models predict the hardness of 3876 hypothetical alloys covering the whole composition range, thereby revealing the systematic component effects based on the complete composition-hardness and descriptor-hardness correlations. The hardening mechanisms are elaborated by analyzing the microstructures of CoCrTiMoW. Furthermore, physical insights can be gained by transitioning from “machine learning” to “learning from machine”. This work demonstrates that our ML-guided HTE approach provides an effective strategy for multicomponent alloy development with a potential hundred-fold overall increase in efficiency at a fraction of the cost compared to conventional methods
An open-closed-loop iterative learning control for trajectory tracking of a high-speed 4-dof parallel robot
No full textPrecise control is of importance for robots, whereas, due to the presence of modeling errors and uncertainties under the complex working environment, it is difficult to obtain an accurate dynamic model of the robot, leading to decreased control performances. This work presents an open-closed-loop iterative learning control applied to a four-limb parallel Schönflies-motion robot, aiming to improve the tracking accuracy with high movement, in which the controller can learn from the iterative errors to make the robot end-effector approximate to the expected trajectory. The control algorithm is compared with classical D-ILC, which is illustrated along with an industrial trajectory of pick-and-place operation. External repetitive and non-repetitive disturbances are added to verify the robustness of the proposed approach. To verify the overall performance of the proposed control law, multiple trajectories within the workspace, different working frequencies for a prescribed trajectory, and different design methods are selected, which show the effectiveness and the generalization ability of the designed controller
Deep learning for LiDAR-only and LiDAR-fusion 3D perception: a survey
No full textThe perception system for robotics and autonomous cars relies on the collaboration among multiple types of sensors to understand the surrounding environment. LiDAR has shown great potential to provide accurate environmental information, and thus deep learning on LiDAR point cloud draws increasing attention. However, LiDAR is unable to handle severe weather. The sensor fusion between LiDAR and other sensors is an emerging topic due to its supplementary property compared to a single LiDAR. Challenges exist in deep learning methods that take LiDAR point cloud fusion data as input, which need to seek a balance between accuracy and algorithm complexity due to data redundancy. This work focuses on a comprehensive survey of deep learning on LiDAR-only and LiDAR-fusion 3D perception tasks. Starting with the representation of LiDAR point cloud, this paper then introduces its unique characteristics and the evaluation dataset as well as metrics. This paper gives a review according to four key tasks in the field of LiDAR-based perception: object classification, object detection, object tracking, and segmentation (including semantic segmentation and instance segmentation). Finally, we present the overlooked aspects of the current algorithms and possible solutions, hoping this paper can serve as a reference for the related research
Bacteriophage-host interactions as a platform to establish the role of phages in modulating the microbial composition of fermented foods
No full textFood fermentation relies on the activity of robust starter cultures, which are commonly comprised of lactic acid bacteria such as Lactococcus and Streptococcus thermophilus. While bacteriophage infection represents a persistent threat that may cause slowed or failed fermentations, their beneficial role in fermentations is also being appreciated. In order to develop robust starter cultures, it is important to understand how phages interact with and modulate the compositional landscape of these complex microbial communities. Both culture-dependent and -independent methods have been instrumental in defining individual phage-host interactions of many lactic acid bacteria (LAB). This knowledge needs to be integrated and expanded to obtain a full understanding of the overall complexity of such interactions pertinent to fermented foods through a combination of culturomics, metagenomics, and phageomics. With such knowledge, it is believed that factory-specific detection and monitoring systems may be developed to ensure robust and reliable fermentation practices. In this review, we explore/discuss phage-host interactions of LAB, the role of both virulent and temperate phages on the microbial composition, and the current knowledge of phageomes of fermented foods
Cross-talk between the infant/maternal gut microbiota and the endocrine system: a promising topic of research
No full textThe infant gut microbiota is the set of microorganisms colonizing the baby’s intestine. This complex ecosystem appears to be related to various physiological conditions of the host and it has also been shown to act as one of the most crucial determinants of infant’s health. Furthermore, the mother’s endocrine system, through its hormones, can have an effect on the composition of the newborn’s gut microbiota. In this perspective, we summarize the recent state of the art on the intricate relationships involving the intestinal microbiota and the endocrine system of mother/baby to underline the need to study the molecular mechanisms that appear to be involved
Reducing carbon footprints of agriculture and food systems
No full textIncrease in global populations of humans and domesticated livestock are impacting the resource use and have a large ecological footprint (EFP). The ever-increasing EFP of humanity is accelerating climate change, increasing water scarcity and contamination, aggravating soil degradation, and dwindling above and below-ground biodiversity. Several sub-components of EFP include resource footprint (RFP) which comprises land (LFP), water (WFP), nitrogen (NFP), biodiversity (BFP) power (PFP), carbon (CFP), etc. Agricultural practices (e.g., tillage, fertilizer and pesticide use, farm operations such as irrigation, harvesting, baling, etc.) also cause the emission of greenhouse gases (GHGs) such as CO2, CH4, and N2O, and these gasses equivalent in their global warming potential (GWP). In general, CFP is reported as CO2eq by converting CH4 and N2O into CO2. The Human diet, consisting of plant and/or animal-based products and grown diversely with or without chemicals, irrigation, and modern innovations, has a wide range of EFP. The latter, is the widely used measure of resource consumption and humanity’s impact on the planet. EFP encompasses the cumulative GHG emissions by an individual, community, organization, institution, nation for a specific service or product. It can vary widely because of using different reference systems of the studies and differences in system boundaries. Therefore, standardization of the methodologies may require a better understanding of the various ways related CFP concepts are relevant for decisions at individual to global levels. There is no one size that fits all. It is also widely recognized that the global average per capita CFP of humanity, estimated at 4.47 Mg CO2eq in 2020 is not sustainable, and must be reduced to < 2 Mg CO2eqif the global warming is to be limited to 2 0C. Therefore, understanding the magnitude of CFP of agriculture and food systems (FSs), and factors affecting it, can lead to identification of technological options which can enhance the use efficiency of inputs, reduce wastage, and decrease the CFP. Different FSs affect CFP through diverse components of production and supply chains, and in the manner in which food is stored and cooked and the waste is disposed or recycled. There is need to adopt international standard (ISO) protocol. Therefore, this review identifies and deliberates technological options which may be needed for reducing CFP of humanity in general but that of agriculture and FSs in particular, while also advancing Sustainable Development Goals of the Agenda 2030 of the United Nations. CFP of diverse agro-ecosystems, land use and management systems are also discussed. Specific examples of CFP include type of farming systems (organic vs.. conventional, dietary preferences, and food waste). There are several options for the humanity to change lifestyle and make it more sustainable. Food waste, about one-third of all, is an important factor impacting CFP while also accelerating global warming. The impact of avoidable food waste on gaseous emissions, estimated at 2.0 to 3.6 Mg CO2eq per Mg of food waste on dry weight basis, must be minimized
Combined grafts and flaps in urethral stricture repair
No full textAlthough urethral strictures have been known since antiquity, the surgical management of urethral strictures has undergone a great (re)evolution over the last six decades, both in the perception of the disease and in the surgical repair techniques, always presenting itself as a challenge for the surgeon and patient. Reconstruction of urethral stricture disease involving a combination of grafts and flaps consists of a group of complex procedures with specific clinical indications. The knowledge of these procedures by reconstructive urologists is both necessary and relevant. A thorough understanding of the anatomy, including blood supply, is a crucial proviso for the correct evaluation and successful management of urethral stricture disease. We discuss the main techniques and indications in combined graft and flap urethroplasties
Soft tissue coverage of lower extremity defects: pearls and pitfalls in the chronic wound population
No full textThe incidence of chronic lower extremity (LE) wounds continues to increase. Lower limb amputations are associated with increased cardiovascular exertion, further decline in functional ability, and higher mortality rates. As such, there has been a shift towards limb salvage modalities. These include local debridement with advanced wound care, revascularization, bony reconstruction, and soft tissue reconstruction. Perioperative planning for soft tissue reconstruction requires careful consideration of several factors, including patient comorbidities, wound size and location, exposed underlying structures, and in the case of possible free flap, patency of donor and recipient vessels. This article reviews the perioperative factors that should be considered in preparation for successful soft tissue reconstruction of the LE
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