Agriculture plays a vital role in the economic growth of any country. With the increase of population, frequent changes in climatic conditions and limited resources, it becomes a challenging task to ...fulfil the food requirement of the present population. Precision agriculture also known as smart farming have emerged as an innovative tool to address current challenges in agricultural sustainability. The mechanism that drives this cutting edge technology is machine learning (ML). It gives the machine ability to learn without being explicitly programmed. ML together with IoT (Internet of Things) enabled farm machinery are key components of the next agriculture revolution. In this article, authors present a systematic review of ML applications in the field of agriculture. The areas that are focused are prediction of soil parameters such as organic carbon and moisture content, crop yield prediction, disease and weed detection in crops and species detection. ML with computer vision are reviewed for the classification of a different set of crop images in order to monitor the crop quality and yield assessment. This approach can be integrated for enhanced livestock production by predicting fertility patterns, diagnosing eating disorders, cattle behaviour based on ML models using data collected by collar sensors, etc. Intelligent irrigation which includes drip irrigation and intelligent harvesting techniques are also reviewed that reduces human labour to a great extent. This article demonstrates how knowledge-based agriculture can improve the sustainable productivity and quality of the product.
We present a novel vertical flow-based paper immunosensor for the rapid and sensitive electrochemical and colorimetric detection of influenza H1N1 viruses using a different pore size (DP) sample pad. ...The DP sample pad consisted of two different pore size papers: larger pores (diameter: 11 µm) facing the inlet, and smaller pores (diameter: 0.45 µm) facing the conjugate pad. This sample pad offered moderate and uniform flows, and hence concentrated horseradish peroxidase tagged antibodies (HRP-Abs)-H1N1 complexes from 40 µL of sample volumes on a conjugate pad for 2 min after sample injection, thereby providing fast detection (6 min for both detection methods) with 100 µL of flushing afterwards, high sensitivity, and the simplicity of the sensor. The filtration characteristics of the DP sample pad were evaluated using fluorescent beads, indicating that only small-sized bio-particles such as viruses can pass through the sample pad. Sandwich immunoreactions of HRP-Ab-H1N1-Ab were performed on the gold paper electrode of the immunoStrip, which was determined by electrochemical impedance spectroscopy (EIS) measurements. Simultaneously, the color signal of free HRP-Ab captured on the colorimetric zone was obtained using a scanner, and the intensity was analyzed using ImageJ. This immunosensor detected H1N1 virus concentration as low as 3.3 plaque forming units (PFU)/mL (phosphate buffer saline; PBS) and 4.7 PFU/mL (saliva) by EIS, and 1.34 PFU/mL (PBS) and 2.27 PFU/mL (saliva) by the colorimetric method. Furthermore, integrating these two detection methods can reduce false results with double assurance, and this device can provide a simple and economical on-site detection platform.
•The first paper immunosensor using a double pore size (DP) sample pad.•The first vertical flow assay-based, sandwich ELISA-type paper immunosensor for the detection of influenza viruses.•Dual (electrochemical and colorimetric) detection methods to provide double assurance.•The DP sample pad offered fast detection (~6 min), high sensitivity (the limit of detection <5 PFU/mL), and the simplicity.•The DP sample pad also acted as a filter to pass only small-sized particles.
The COVID-19 pandemic has forced tourism practitioners to create efficient strategies to attract travelers. Using three theoretical frameworks, such as tourist trust (political, destination, and ...interactional trust), travel constraint (intrapersonal, interpersonal, and “social distancing” structural constraint), and extended theory of planned behavior (travel attitude, perceived behavioral control, subjective norm, perceived health risk, past travel experience), we develop a comprehensive framework to explain the impact of travel promoting, restricting, and attitudinal factors on travel decision during and after the pandemic. Data was obtained through an extensive survey conducted on 1451 Korean travelers and was analyzed using probabilistic choice models and count models. The results show the specific factors that determine travel decisions during the pandemic (whether to travel and frequency) and travel intention after the pandemic. This study provides important theoretical and practical insights into how to develop successful COVID-19 recovery strategies in the tourism industry.
The COVID-19 pandemic has hit the global at a colossal scale. With worldwide reported cases of 5.34 million it has led to severe impact on humanity. Being a highly contagious disease, it has given ...global health services their most severe challenge. Various countries are fighting to minimize the losses due to the outbreak, however a common trait is enforcing lockdown, which has become the main defence mechanism. Researchers are working around the clock to find a breakthrough in the diagnostics and treatment of the pandemic.
AI technology is useful for fast drug development and treatment. In the starting phase of COVID-19 pandemic, the medical fraternity in China diagnosed the virus using computed tomography (CT) and X-ray images due to the limitation of testing kits. Deep learning neural network model have also been used for COVID-19 diagnosis. AI assisted intelligent humanoid robots can be used to reduce the human contact and spread of COVID-19. In Italy robots have been used for measuring blood pressure, oxygen saturation and temperature of patients. Robots have also found applications in disinfecting and sterilizing of public places, COVID-19 testing, food and medicine delivery as well as entertaining patients in hospitals and quarantine centers, thereby reducing the workload of doctors and nurses.
Prediction of the spread of virus and providing the guidelines or prevention measures is another AI application in COVID-19. Kaggle and GitHub are the two websites where the real-time data of COVID-19 is aggregated. This includes confirmed cases, active cases, cured cases and deaths in each country. This data set can be used for predicting the active cases across different regions of the world so that appropriate amount of health infrastructure can be made available to these places.
Preface Acknowledgement List of Contributors List of Figures List of Tables List of Notations and Abbreviations 1 The History of Pandemics and Evolution So Far 2 Tracing the Origins of COVID-19 3 AI for COVID-19: The Journey So Far 4 Technological Opportunities to Fight COVID-19 for 5 Mobile Robots in COVID-19 6 Predictor System for Tracing COVID-19 Spread 7 Discovery of Robust Distributions of COVID-19 Spread 8 Toward Smart Hospital: An Intelligent Personnel Scheduling Using Evolutionary Algorithms 9 Role of Artificial Intelligence Based Wireless Sensor Network for Pandemic Control: A Case 10 Peculiarities of Technical Measures During the COVID-19 Pandemic 11 Climate Change and COVID-19: An Interplay 12 COVID-19 Pandemic: A New Era in Higher Education 13 Virtual Reality: Solution to Reduce the Impact of COVID-19 on Global Economy References Index About the Editors
Arpit Jain, Abhinav Sharma, Jianwu Wang, Mangey Ram
Patients with spinopelvic pathology, including lumbar spine stiffness and sagittal spinal deformity, are at increased risk for postoperative complications, including instability, dislocation, and ...revision after total hip arthroplasty (THA). Recent evidence has suggested that the Lewinnek safe zone should no longer be considered an appropriate target for all patients, especially those with spinopelvic pathology, as the safe zone is a dynamic rather than static target. There are 2 distinct issues for arthroplasty surgeons to consider: lumbar spinal stiffness and sagittal spinal deformity, each of which has its own management.
In order to manage patients with spinopelvic pathology undergoing THA, a basic understanding of spinopelvic parameters, including sagittal balance, sacral slope, and anterior pelvic plane, is essential. Techniques outlined in this manuscript describe a systematic preoperative work-up and intraoperative management of acetabular component positioning according to patient-specific spinopelvic parameters, ensuring optimal component placement and a reduced risk for impingement, instability, and poor postoperative outcomes.
Evaluation of each patient’s spinopelvic parameters informs patient classification according to the Hip-Spine Classification for THA. Patient classification is determined by the presence of spinal stiffness and spinal deformity, with corresponding scoring and classification into one of the 4 categories used to determine risk for postoperative dislocation, define patient-specific cup positioning, and create their functional safe zone.
A simple 2-step preoperative assessment with measurements of the anterior pelvic plane and the sacral slope on standing and seated lateral X-rays will identify patients at high risk for postoperative dislocation due to spinal deformity and/or stiffness. Accounting for spinopelvic pathology and adhering to the Hip-Spine Classification guidelines for acetabular component positioning can help reduce the burden of instability and revisions in this complex patient population.
Stress controls the mechanics of collagen networks Licup, Albert James; Münster, Stefan; Sharma, Abhinav ...
Proceedings of the National Academy of Sciences - PNAS,
08/2015, Volume:
112, Issue:
31
Journal Article
Peer reviewed
Open access
Collagen is the main structural and load-bearing element of various connective tissues, where it forms the extracellular matrix that supports cells. It has long been known that collagenous tissues ...exhibit a highly nonlinear stress–strain relationship, although the origins of this nonlinearity remain unknown. Here, we show that the nonlinear stiffening of reconstituted type I collagen networks is controlled by the applied stress and that the network stiffness becomes surprisingly insensitive to network concentration. We demonstrate how a simple model for networks of elastic fibers can quantitatively account for the mechanics of reconstituted collagen networks. Our model points to the important role of normal stresses in determining the nonlinear shear elastic response, which can explain the approximate exponential relationship between stress and strain reported for collagenous tissues. This further suggests principles for the design of synthetic fiber networks with collagen-like properties, as well as a mechanism for the control of the mechanics of such networks.
Display omitted
•A transparent CNT immunosensor is presented for detection of a prostate cancer biomarker osteopontin.•This immunosensor showed a highly linear and reproducible behavior from 1pgmL−1 ...to 1μgmL−1.•The limit of detection of the immunosensor was 0.3pgmL−1.•This immunosensor demonstrated high selectivity against bovine serum albumin and human serum.
Osteopontin (OPN) is involved in almost all steps of cancer development, and it is being investigated as a potential biomarker for a diagnosis and prognosis of prostate cancer. Here, we report a label-free, highly sensitive and transparent immunosensor based on single-walled carbon nanotubes (SWCNTs) for detection of OPN. A high density of COOH functionalized SWCNTs was deposited between two gold/indium tin oxide electrodes on a glass substrate by dielectrophoresis. Monoclonal antibodies specific to OPN were covalently immobilized on the SWCNTs. Relative resistance change of the immunosensors was measured as the concentration of OPN in phosphate buffer saline (PBS) and human serum was varied from 1pgmL−1 to 1μgmL−1 for different channel lengths of 2, 5, and 10μm, showing a highly linear and reproducible behavior (R2>97%). These immunosensors were also specific to OPN against another test protein, bovine serum albumin, PBS and human serum, showing that a limit of detection for OPN was 0.3pgmL−1. This highly sensitive and transparent immunosensor has a great potential as a simple point-of-care test kit for various protein biomarkers.
In this paper, a new hybrid TSA-PSO algorithm is proposed that combines tunicate swarm algorithm (TSA) with the particle swarm optimization (PSO) technique for efficient maximum power extraction from ...a photovoltaic (PV) system subjected to partial shading conditions (PSCs). The performance of the proposed algorithm was enhanced by incorporating the PSO algorithm, which improves the exploitation capability of TSA. The response of the proposed TSA-PSO-based MPPT was investigated by performing a detailed comparative study with other recently published MPPT algorithms, such as tunicate swarm algorithm (TSA), particle swarm optimization (PSO), grey wolf optimization (GWO), flower pollination algorithm (FPA), and perturb and observe (P&O). A quantitative and qualitative analysis was carried out based on three distinct partial shading conditions. It was observed that the proposed TSA-PSO technique had remarkable success in locating the maximum power point and had quick convergence at the global maximum power point. The presented TSA-PSO MPPT algorithm achieved a PV tracking efficiency of 97.64%. Furthermore, two nonparametric tests, Friedman ranking and Wilcoxon rank-sum, were also employed to validate the effectiveness of the proposed TSA-PSO MPPT method.
Recently, there have been many efforts to use mobile apps as an aid in contact tracing to control the spread of the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) (COVID-19 coronavirus ...disease 2019) pandemic. However, although many apps aim to protect individual privacy, the very nature of contact tracing must reveal some otherwise protected personal information. Digital contact tracing has endemic privacy risks that cannot be removed by technological means, and which may require legal or economic solutions. In this brief communication, we discuss a few of these inherent privacy limitations of any decentralized automatic contact tracing system.
The literature on climate change research has evolved tremendously since the 1990s. The goal of this study is to use text mining to review the climate change literature and study the evolution of the ...main trends over time. Specific keywords from articles published in the special issue “ Industrial Ecology for Climate Change Adaptation and Resilience” in the Journal of Industrial Ecology are first selected. Details of over 35,000 publications containing these keywords are downloaded from the Web of Science from 1990 to 2018. The number of publications and co‐occurrence of keywords are analyzed. Moreover, latent Dirichlet allocation (LDA)—a probabilistic approach that can retrieve topics from large and unstructured text documents—is applied on the s to uncover the main topics (consisting of new terms) that naturally emerge from them. The evolution in time of the importance of some emerging topics is then analyzed on the basis of their relative frequency. Overall, a rapid growth in climate change publications is observed. Terms such as “climate change adaptation” appear on the rise, whereas other terms are declining such as “pollution.” Moreover, several terms tend to co‐occur frequently, such as “climate change adaptation” and “resilience.” The database collected and the LiTCoF (Literature Topic Co‐occurrence and Frequency) Python‐based tool developed for this study are also made openly accessible. This article met the requirements for a gold – gold JIE data openness badge described http://jie.click/badges.
PDF
