College admissions with stable score-limits

A common feature of the Hungarian, Irish, Spanish and Turkish higher education admission systems is that the students apply for programmes and are ranked according to their scores. Students who apply for a programme with the same score are tied. Ties are broken by lottery in Ireland, by objective factors in Turkey (such as date of birth) and other precisely defined rules in Spain. In Hungary, however, an equal treatment policy is used, students applying for a programme with the same score are all accepted or rejected together. In such a situation there is only one decision to make, whether or not to admit the last group of applicants with the same score who are at the boundary of the quota. Both concepts can be described in terms of stable score-limits . The strict rejection of the last group with whom a quota would be violated corresponds to the concept of H-stable (i.e. higher-stable) score-limits that is currently used in Hungary. We call the other solutions based on the less strict admission policy as L-stable (i.e. lower-stable) score-limits. We show that the natural extensions of the Gale-Shapley algorithms produce stable score-limits, moreover, the applicant-oriented versions result in the lowest score-limits (thus optimal for students) and the college-oriented versions result in the highest score-limits with regard to each concept. When comparing the applicant-optimal H-stable and L-stable score-limits we prove that the former limits are always higher for every college. Furthermore, these two solutions provide upper and lower boundaries for any solution arising from a tie-breaking strategy. Finally we show that both the H-stable and the L-stable applicant-proposing score-limit algorithms are manipulable

A 2a adenosine receptor: Structures, modeling, and medicinal chemistry

Many selective agonists and antagonists of the A 2A adenosine receptor (AR) have been reported, while allosteric modulators specific for this receptor are still needed. Many heterocyclic chemotypes have been discovered as A 2A AR antagonists, while most of the known AR agonists are nucleosides or 3,5-dicyanopyridine derivatives. A few A 2A AR ligands have been in clinical trials as antihypertensives, anti-inflammatory or diagnostic compounds (agonists), and as drugs for treating Parkinson’s disease and cancer (antagonists). The A 2A AR has become one of the most widely investigated G protein-coupled receptor (GPCR) structures using X-ray crystallography and also biophysical techniques such as NMR. Thus, the design of agonists, antagonists, and allosteric modulators has become structure-based, with numerous examples of in silico approaches, including virtual ligand screening (VLS), leading to the discovery of both novel agonists and antagonists