The impact of "July effect" on "failure to rescue" : do patients who undergo coronary artery bypass grafting at teaching hospitals face a selective disadvantage? [abstract]

The new academic cycle in July is associated with the commencement of postgraduate medical education. Although this is presumed to be associated with poor patient outcomes, supportive evidence is limited for Cardiac surgery patients. We sought to determine if the new academic cycle had a direct bearing on outcomes of patients undergoing Coronary Artery Bypass Grafting

Union Averaged Operators with Applications to Proximal Algorithms for Min-Convex Functions

In this paper we introduce and study a class of structured set-valued operators which we call union averaged nonexpansive. At each point in their domain, the value of such an operator can be expressed as a finite union of single-valued averaged nonexpansive operators. We investigate various structural properties of the class and show, in particular, that is closed under taking unions, convex combinations, and compositions, and that their fixed point iterations are locally convergent around strong fixed points. We then systematically apply our results to analyze proximal algorithms in situations where union averaged nonexpansive operators naturally arise. In particular, we consider the problem of minimizing the sum two functions where the first is convex and the second can be expressed as the minimum of finitely many convex functions

Constraint reduction reformulations for projection algorithms with applications to wavelet construction

We introduce a reformulation technique that converts a many-set feasibility problem into an equivalent two-set problem. This technique involves reformulating the original feasibility problem by replacing a pair of its constraint sets with their intersection, before applying Pierra’s classical product space reformulation. The step of combining the two constraint sets reduces the dimension of the product spaces. We refer to this technique as the constraint reduction reformulation and use it to obtain constraint-reduced variants of well-known projection algorithms such as the Douglas–Rachford algorithm and the method of alternating projections, among others. We prove global convergence of constraint-reduced algorithms in the presence of convexity and local convergence in a nonconvex setting. In order to analyze convergence of the constraint-reduced Douglas–Rachford method, we generalize a classical result which guarantees that the composition of two projectors onto subspaces is a projector onto their intersection. Finally, we apply the constraint-reduced versions of Douglas–Rachford and alternating projections to solve the wavelet feasibility problems and then compare their performance with their usual product variants. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature

Constraint reduction reformulations for projection algorithms with applications to wavelet construction

We introduce a reformulation technique that converts a many-set feasibility problem into an equivalent two-set problem. The reformulation can be viewed as a variant of Pierra's classical product space decomposition which reduces the dimension of the product space by replacing a pair of constraint sets with their intersection. We refer to this as the constraint reduction reformulation and use it to obtain constraint-reduced variants of well-known projection algorithms such as the Douglas--Rachford algorithm and the method of alternating projections, among others. We prove global convergence of constraint-reduced algorithms in the presence of convexity and local convergence in a nonconvex setting. In order to analyse convergence of the constraint-reduced Douglas--Rachford method, we generalize a classical result which guarantees that the composition of two projectors onto subspaces is a projector onto their intersection. Finally, we apply the constraint-reduced versions of Douglas--Rachford and alternating projections to solve the wavelet feasibility problems, and then compare their performance with their usual product variants

Efficiency of Farmer Organisations in Supplying Supermarkets with Quality Food in Vietnam

The development of supermarkets in Vietnam, as in other emerging countries, goes along with an increasing concern on the part of purchasers for food quality. The paper investigates whether farmer organisations are able to help small-scale farmers get access to supermarkets, and the role that supermarkets and public support play in their emergence and development. It is based on case studies involving a number of stakeholders marketing vegetables, flavoured rice and litchi fruit in Vietnam. The interviews investigated patterns of horizontal and vertical coordination that link farmers to supermarkets, the distribution of costs and benefits between farmers and traders along the chains in relation to the strategy of quality differentiation. Eight farmer associations that work in the form of private commercial organisations are regular supermarket suppliers for the selected products. Their ability to supply supermarkets is related to the combination of functions they make available to their members, especially as regards training to improve quality (appearance, taste, safety), quality promotion and control, for which they receive public support, as well as their participation in flexible contracts with supermarkets, shops and schools. Supermarket supply through farmer associations increases farmer incomes when compared with traditional chains, yet the situation is reported to change with the increase in supermarket competition. The paper argues that changes in farmer organisation are not only due to supplying supermarkets, but also to public and international support to food quality improvement, which have been of benefit to supermarkets.Agribusiness, Industrial Organization,

Evaluation of COVID-19 protease and HIV inhibitors interactions

The epidemic of the novel coronavirus disease (COVID-19) that started in 2019 has evoked an urgent demand for finding new potential therapeutic agents. In this study, we performed a molecular docking of anti-HIV drugs to refine HIV protease inhibitors and nucleotide analogues to target COVID-19. The evaluation was based on docking scores calculated by AutoDock Vina and top binding poses were analyzed. Our results suggested that lopinavir, darunavir, atazanavir, remdesivir, and tipranavir have the best binding affinity for the 3-chymotrypsin-like protease of COVID-19. The comparison of the binding sites of three drugs, namely, darunavir, atazanavir and remdesivir, showed an overlap region of the protein pocket. Our study showed a strong affinity between lopinavir, darunavir, atazanavir, tipranavir and COVID-19 protease. However, their efficacy should be confirmed by in vitro studies since there are concerns related to interference with their active sites