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Recently, firms like Toyota and social planners like the Government of India have invested in various initiatives leading to the firm's cost reduction. Further, such cost reduction collaborations also benefit the social planner because of higher industry output, and therefore, higher employment opportunities. In this paper, we investigate different scenarios in which the firm, or the social planner, or both exert efforts to reduce the firm's manufacturing cost. Interestingly, we find that under certain conditions, the firm may exert lower effort than the social planner. Our analysis reveals that when both players' cost reduction effectiveness is low, then collaboration results in higher payoffs for both the players. However, when the effectiveness of any player is high, then both players are better off if only one of them exerts effort. Our study further reveals that collaboration between the social planner and the firm always leads to a win–win situation. [ABSTRACT FROM AUTHOR]

This study uses digital image processing and machine learning to quantify the infection patterns on tomato leaves due to blight diseases. Quantification, also known as severity measurement, is a technique to determine how much a leaf is diseased by calculating a numeric value. This value could be a fraction representing how much the diseased region is present on the leaf compared to the entire leaf region, or it can be a percentage value too. There are two main approaches to measuring disease severity; the first technique involves visual estimation using references like standard area diagrams. The second approach involves taking a digital image of the leaf, separating the diseased regions from the healthy regions, and then calculating the area of those two regions. The approach we took is similar. We first took the digital image and segmented the diseased and healthy regions. For quantification, we calculated the ratio of total pixels representing the diseased region to the total number of pixels representing the leaf. While finding ways to improve the accuracy of the segmentation algorithm, we also discovered our segmentation technique which automatically segments the diseased regions of the leaves from the healthy areas using k‐means clustering. The clustering‐segmentation algorithm did give good results for the sample images to which it was applied. The main thing about the clustering‐segmentation algorithm is that it tends to be automatic compared to some of the semi‐automatic segmentation approaches that have been discovered till now. We could reproduce the validated quantification results as other authors achieved in the recent work, which also validated our methodology. [ABSTRACT FROM AUTHOR]

In this work, we investigate the impact of social brokerage on the innovation productivity of users in online innovation networks. Innovation in online networks is leveraged by coordinated interactions between the participating users. We leverage the data of users contributing on posts between 2017 and 2019 in two community question answering (CQA) forums: Stack Overflow and Math Stack Exchange. The innovation productivity of users in such online innovation networks, as valued by other participating users is quantified by the total score they received on their contributing posts. Users occupying brokerage positions are exposed to better ideas that boost the value of their contributing posts, thus improving their total score. Again, existing users with low social brokerage are also likely to gain from resource sharing owing to their denser networks. Our econometric analysis reveals that users in online innovation networks with very low or very high values of social brokerage receive higher scores as valued by other community users. Overall, we access the data of 537,938 users in Stack Overflow contributing on 6,002,996 questions, and 7,903,416 answers, and 20,393 users in the Math Stack Exchange contributing on 488,389 questions, and 638,110 answers. We observe a U‐shaped effect of the user's social brokerage on the user's innovation productivity. Our empirical findings have various implications for firms hosting online CQA forums. [ABSTRACT FROM AUTHOR]

In this article, we investigate the pricing and quality decisions of mobile applications (apps) by the platform owner and third‐party app developer. The third‐party app developer shares some fraction of revenue with the platform owner. We investigate the impact of revenue sharing fraction on quality enhancement and pricing decisions. One would expect that, as the revenue sharing fraction earned by the platform increases, the platform's effort toward enhancing the quality of her app should increase. However, our analysis reveals that when the third‐party app developer's cost structure is high (/low), and the difference between initial app quality valuation of the platform's app and developer's app is high (/low), then the platform decreases the quality improvement efforts. Similarly, we also find that if the developer's revenue‐sharing fraction increases, he may also decrease the quality efforts. Later, we also analyze the scenario where a platform can influence the competing developer's app quality. We find that if the platform's effort only influences the competing third‐party developer's app quality, then the platform reduces the rival's app quality. Finally, in our analysis, we find that if the platform's effort toward the rival's app also enhances her app's quality, she may increase the rival's app quality. [ABSTRACT FROM AUTHOR]

We examine the association between studying science in higher secondary school and labor market earnings in India. Studying science in high school is associated with 22% greater earnings than studying business or humanities. Earnings for science students are further enhanced with some fluency in English. Science education is also associated with more years of education, completing a professional degree, returns to entrepreneurship and working in public sector positions. Primary survey of high school students shows no discernible differences in behavioral characteristics of science students compared to others. [ABSTRACT FROM AUTHOR]

Introduction: To evaluate the performance of the Vesical Imaging–Reporting and Data System (VIRADS) in differentiating muscle‐invasive and non‐muscle‐invasive bladder cancer and whether this reporting system improves inter‐reader agreement. Methods: Sixty‐four cases of multiparametric 3 tesla bladder MRI from January 2014 to May 2020 were reviewed retrospectively. T2‐weighted, diffusion and post‐contrast images were reviewed. All magnetic resonance images were reported by a radiologist with 15 years' experience (Reader 1) and a final year radiology trainee with a special interest in urogenital imaging with 3 years of experience (Reader 2). Both readers were blinded to clinical history and histopathology results when scoring each lesion. Results: The sensitivity and specificity for differentiating MIBC and NMIBC were 91% and 68%, respectively, for Reader 1 and 91% and 63%, respectively, for Reader 2. The inter‐reader agreement for assigning VIRADS scores was 0.79. The area under the receiver operator curve for Reader 1 and 2 were not significantly different (Reader 1 = 0.79, Reader 2 = 0.77, P = 0.83). Conclusions: Staging of bladder cancer prior to treatment can be accurately and reliably diagnosed using VIRADS, a novel, standardised reporting system for bladder MRI. [ABSTRACT FROM AUTHOR]

In this article, we study the scenario under which two information technology (IT) vendor firms compete for the outsourcing requirements of a client firm. The vendors' cost structures are private information. In addition, the vendors can improve their unit costs through learning‐by‐doing and by making investments in process improvement, that is, induced learning. We study the impacts of vendor‐based learning and process improvement in the asymmetric cost setting on the client firm's outsourcing strategy and the vendor firms' process improvement investments. Our analysis reveals that the client firm may adopt the single‐sourcing strategy or a combination of dual and single‐sourcing strategies depending on the learning efficiency of the vendor base. We also find that high heterogeneity in the vendor cost structure increases the first‐period outsourcing requirements of the client firm. Our findings provide interesting managerial implications for the IT outsourcing industry. [ABSTRACT FROM AUTHOR]

The use of tertiary health care by socially proximate peers helps individuals learn about program and treatment procedures, signals that using such care is socially appropriate, and could support the use of formal health care, all of which could increase program utilization. Using complete administrative claims data from a publicly financed tertiary care program in India, we estimate that the elasticity of first-time claims with respect to claims by members of caste groups within the village is 0.046, with smaller effects of more socially distant individuals. The point elasticity of inpatient care expenditure with respect to claims filed by the same group in village peers in the previous quarter is - 0.035. We find support for an information channel as peers increase awareness of the program and its features. Our findings have implications for the development of network-based models to determine health-care demand, as well as in use of network-based targeting to boost tertiary health-care utilization. [ABSTRACT FROM AUTHOR]

Supply chains are often characterized by the presence of a dominant buyer purchasing from a supplier with limited capacity. We study such a situation where a single supplier sells capacity to an established and more powerful buyer and also to a relatively less powerful buyer. The more powerful buyer enjoys the first right to book her capacity requirements at supplier's end, and then the common supplier fulfills the requirement of the less powerful buyer. We find that when the supplier's capacity is either too low (below the lower threshold) or too high (above the higher threshold), there is no excess procurement as compared to the case when supplier has infinite capacity. When the supplier's capacity is between these two thresholds, the more powerful buyer purchases an excess amount in comparison to the infinite capacity case. [ABSTRACT FROM AUTHOR]

This paper examines how students' network size, distance, prestige, and connections to influential individuals impact academic performance. Larger and closer networks facilitate information exchange, but may also increase distractions that decrease productivity. We resolve this ambiguity using administrative data from a business school that features random assignment of students to multiple overlapping sets of peers, allowing us to calculate degree, closeness, eigenvector, and Katz‐Bonacich centrality for each node. We find that increasing closeness centrality within the network negatively affects student performance measured by grade point average, suggesting that synergy reduction and information processing costs outweigh benefits from greater information access. [ABSTRACT FROM AUTHOR]

Zinc is one of the most important metal ions found in proteins performing specific functions associated with life processes. Coordination geometry of the zinc ion in the active site of the metalloprotein-ligand complexes poses a challenge in determining ligand binding affinities accurately in structure-based drug design. We report here an all atom force field based computational protocol for estimating rapidly the binding affinities of zinc containing metalloprotein-ligand complexes, considering electrostatics, van der Waals, hydrophobicity, and loss in conformational entropy of protein side chains upon ligand binding along with a nonbonded approach to model the interactions of the zinc ion with all the other atoms of the complex. We examined the sensitivity of the binding affinity predictions to the choice of Lennard-Jones parameters, partial atomic charges, and dielectric treatments adopted for system preparation and scoring. The highest correlation obtained was R2 = 0.77 ( r = 0.88) for the predicted binding affinity against the experiment on a heterogenous dataset of 90 zinc containing metalloprotein-ligand complexes consisting of five unique protein targets. Model validation and parameter analysis studies underscore the robustness and predictive ability of the scoring function. The high correlation obtained suggests the potential applicability of the methodology in designing novel ligands for zinc-metalloproteins. The scoring function has been web enabled for free access at as BAPPL-Z server (Binding Affinity Prediction of Protein-Ligand complexes containing Zinc metal ions). Proteins 2007. © 2007 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Calcific tendinosis is characterized by macroscopic deposits of hydroxyapatite within the tendon. Commonest location is rotator cuff of shoulder. Cortical erosion with intraosseous migration of calcium deposits is rare complication of this condition. It may be confused with neoplasm or infection, resulting in unnecessary biopsies or interventions. The knowledge of this uncommon complication and its appearance should enable its detection by imaging and lead to specific treatment. [ABSTRACT FROM AUTHOR]

Abstract: We report here a computationally fast protocol for predicting binding affinities of non-metallo protein–ligand complexes. The protocol builds in an all atom energy based empirical scoring function comprising electrostatics, van der Waals, hydrophobicity and loss of conformational entropy of protein side chains upon ligand binding. The method is designed to ensure transferability across diverse systems and has been validated on a heterogenous dataset of 161 complexes consisting of 55 unique protein targets. The scoring function trained on a dataset of 61 complexes yielded a correlation of r =0.92 for the predicted binding free energies against the experimental binding affinities. Model validation and parameter analysis studies ensure the predictive ability of the scoring function. When tested on the remaining 100 protein–ligand complexes a correlation of r =0.92 was recovered. The high correlation obtained underscores the potential applicability of the methodology in drug design endeavors. The scoring function has been web enabled at www.scfbio-iitd.res.in/software/drugdesign/bappl.jsp as binding affinity prediction of protein–ligand (BAPPL) server. [Copyright &y& Elsevier]