Recently, there has been extensive research in the area of diagnostic expertise. The model of diagnostic reasoning and clinical expertise has been well documented (Patel et al., in press). This study ...attempts to extend this research in order to include therapeutic reasoning. Using the expert-novice paradigm, this study attempts to investigate the use of knowledge, specifically, both biomedical and clinical sciences, and the directionality of reasoning during decision making about patient management and therapeutic planning in respiratory medicine.
Subjects at four levels of expertise were given two clinical problems with the diagnosis and asked (a) to provide therapeutic plans, and (b) describe the underlying pathophysiological explanations of the diseases. Think-aloud protocols were audio-taped and analyzed using methods of protocol analysis. The results showed that the use of basic medical sciences increased as a function of expertise in the procedure-oriented decision-making tasks. The novices generated rule-based prototypical textbook descriptions based on the clinical information, and the diagnosis given in the task. In contrast, the experts' therapeutic responses showed a predominance of causal-level inferences, reflecting more backward-directed inferences than novices. Although both the novices and experts generated forward-directed inferences, the novices were unable to provide accurate and adequate explanations for their decisions. Finally, the pathophysiological explanations of the disease were generated from a different knowledge source than that used to develop therapeutic decisions.
The implications of these findings for development of theory of expertise and for education in the medical domain are discussed.
Recently, there has been extensive research in the area of diagnostic expertise. The model of diagnostic reasoning and clinical expertise has been well documented (Patel et al., in press). This study ...attempts to extend this research in order to include therapeutic reasoning. Using the expert-novice paradigm, this study attempts to investigate the use of knowledge, specifically, both biomedical and clinical sciences, and the directionality of reasoning during decision making about patient management and therapeutic planning in respiratory medicine. Subjects at four levels of expertise were given two clinical problems with the diagnosis and asked (a) to provide therapeutic plans, and (b) describe the underlying pathophysiological explanations of the diseases. Think-aloud protocols were audio-taped and analyzed using methods of protocol analysis. The results showed that the use of basic medical sciences increased as a function of expertise in the procedure-oriented decision-making tasks. The novices generated rule-based prototypical textbook descriptions based on the clinical information, and the diagnosis given in the task. In contrast, the experts' therapeutic responses showed a predominance of causal-level inferences, reflecting more backward-directed inferences than novices. Although both the novices and experts generated forward-directed inferences, the novices were unable to provide accurate and adequate explanations for their decisions. Finally, the pathophysiological explanations of the disease were generated from a different knowledge source than that used to develop therapeutic decisions. The implications of these findings for development of theory of expertise and for education in the medical domain are discussed.
An accurate prediction of bugs in software projects can help in improving software projects' quality. A simple majority voting (SMV) ensemble is an effective technique for bug prediction. SMV ...combines the results of base classifiers (BCs) based on the majority voting of class. All the stand-alone BCs do not perform equally well, yet all the BCs in SMV are given equal weights. Therefore, in order to improve the performance of SMV, BCs should be assigned different weights. Therefore, here, we propose a novel reward-based weighted majority voting (WMV) ensemble technique to build a bug prediction model. In WMV, the performance of each classifier in the ensemble is evaluated; then, a reward-based mechanism is used to calculate the weights of each classifier. When a BC predicts the correct class of an instance, then a reward is provided, but no punishment is given for wrong prediction. A BC will get higher weight in an ensemble that predicts more instances correctly. Naive Bayes, support vector machine, K-nearest neighbor, random forest, and C5.0 heterogeneous algorithms are used as BCs in the WMV ensemble. WMV outperforms aforesaid BCs, SMV, and also majority of state-of-the-art techniques published recently in terms of accuracy, <inline-formula><tex-math notation="LaTeX">F</tex-math></inline-formula>-measure, and Matthew's correlation coefficient.
Carbon emission is a prime reason for global warming. There are various industrial processes which discharge significant amount of carbon dioxide to the atmosphere. Carbon emission from industrial ...process can be controlled by the application of technologies at different stages in industries. This paper reviews the research works carried out for executing energy efficient and low carbon technologies for industries at different stages and classifies these works into inward, in and outward process stages. The review outlines few major approaches that are followed in majority of the research works. Process integration technique and improving energy and matter efficiency are key approaches of inward process stage. Retrofitting of existing industries with best available technique and utilizing energy model tools for predicting energy consumption and carbon emission are key approaches of inward process stage. Incorporating CCUS technology and targeting of CCUS via process integration technique are key approaches of outward process stage. The research works carried out for planning of carbon emission limits are also studied. Further a methodology based on pinch analysis is developed for determining restrictions on the carbon emission on tenure track basis. The emission limits can guide policy maker about the future course of action with respect to process modifications and technological innovations.
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•Presents review on carbon emission reduction technologies in industries.•The classification of technologies is based on energy and material flow.•The research works carried out for planning of carbon emission limits are studied.•A pinch based method is developed for determining carbon emission limits.
PurposeThe study is an attempt to explore much talked but less understood issue of “blockchain in logistics industry” in modern perspective. The customers' acceptance of blockchain technology in ...logistics and supply chain is tested through “Technology Acceptance Model” by using attitude, perceived usefulness (PU), perceived ease of use (PEOU), behavioral intention and use behavior.Design/methodology/approachData has been collected through online and offline medium, where active 240 responses have been collected finally using convenience sampling. Confirmatory factor analysis with structural equation modeling (SEM) was carried out for data analysis.FindingsThe customers' acceptance of blockchain technology in logistics and supply chain is tested through “Technology Acceptance Model.” The findings reveal model fit where PEOU, PU and attitude are the major constructs of the model to realize the substantial gains in logistics process efficiency.Research limitations/implicationsConvenience sampling has been considered for the study to collect the data of online users of various technology applications for tracking and shipment detail, whereas a more specified method sampling can be considered for the future research. The study has been conducted in the Indian context, which has been considered as the limitation pertaining to generalization across countries and industries.Practical implicationsThe findings of this study will be helpful for market practitioners to build transparency between customers and industry to overcome the frictions in logistics. Blockchain will help in monitoring the performance history and previous commitments of logistics professionals resulting in selecting a responsible logistics solution provider. Access to critical data by the authorized member of the supply chain will reduce unsubstantiated disputes.Social implicationsBlockchain technology will be available to everyone on the network. This will bring transparency and help logistics professionals such as carriers, shippers and brokers to detect early frauds and prevent thefts. It will increase customer trust toward any financial transaction for tracking the ownership of titles.Originality/valueBlockchain technology is envisioned to be a technology that could be a game-changer for decentralizing infrastructure, introducing transparency and building trust in the supply chain. The current study is a novel addition to the literature where blockchain technology enables the indisputable storage of verified data that was previously kept in safeguarded silos.
Today’s demand has approached the sustainable agriculture with synergistic bioinoculants for improved crop production and soil rejuvenation. Furthermore, the emergence of chemical fertilizers, for ...intensive farming practice increasing for many decades without the knowledge of health hazards and environmental problems, can be resolved. Purposely, the present study was conducted on commercially grown medicinal plant
Mentha arvensis
L. to improve productivity and yield using natural bio-sources such as bioinoculant and vermicompost. The new findings illustrated that
M. arvensis
L. showed significantly (
P
< 0.05) improved plant growth, secondary metabolites, total phytoconstituents, and total antioxidant capacity in bioinoculant-treated plants as compared to the control with carrier vermicompost. Moreover, the highly effective treatment also exceeded the most prominent aroma compounds menthol, menthone, and isomenthone. Most interestingly, with high yield increment, the essential oil also showed significant antibacterial activity. The present study concluded an unambiguous fortification of bioinoculant with carrier vermicompost, showing a promising synergistic potential that validates itself as bio-stimulants in enhancing physiological and biochemical properties of
M. arvensis
L. resulting in high yield and improved quality.
Graphic Abstract
Tomato (Solanum lycopersicum L.) is one of the most important Solanaceous and remunerative vegetable crops. However, despite its value in fresh and processing markets, many farmers are concerned ...about pest resistance. Therefore, looking to the seriousness of pest menace particularly leaf curl and fruit borer, research is needed to reduce the chemical pressure and establish an ecological equilibrium in tomato fields. A combination of bio‐intensive pest management (BIPM) and chemo‐intensive pest management (CIPM) were followed trap crop marigold (Tagetes erecta L.) and yellow sticky traps to manage these pests during 2016–2017 and 2017–2018. The percent plant infestation with leaf curl (0.6–0.9) and fruit infestation with fruit borer (5.2–6.7) were observed in BIPM and CIPM. In these fields, the application of insecticides increased yields 30–38.3%. There was 47.1–56.8% higher net return in BIPM and 59.5–68.9% higher in CIPM than farmers’ practices. Similarly, benefit cost ratio was analyzed 2.5:3.6 in BIPM and 2.5:3.7 in CIPM.
