Undecidability of QLTL with two variables and one monadic predicate letter

We study the algorithmic properties of the quantified linear-time temporal logic QLTL in languages with restrictions on the number of individual variables as well as the number and arity of predicate letters. We prove that the satisfiability problem for QLTL in languages with two individual variables and one monadic predicate letter in Σ 11 -hard. Thus, QLTL is Π 11 -hard, and so not recursively enumerable, in such languages. The resultholds both for the increasing domain and the constant domain semantics and is obtained by reduction from a Σ 11 -hard N×N recurrent tiling problem. It follows from the proof for QLTL that similar results hold for the quantified branching-time temporal logic QCTL, and hence for the quantified alternating-time temporal logic QATL. The result presented in this paper strengthens a result by I. Hodkinson, F. Wolter, and M. Zakharyaschev, who have shown that the satisfiability problem for QLTL is Σ 11 -hard in languages with two individual variablesand an unlimited supply of monadic predicate letters.

A QPTAS for ɛ-Envy-Free Profit-Maximizing Pricing on Line Graphs

We consider the problem of pricing edges of a line graph so as to maximize the profit made from selling intervals to single-minded customers. An instance is given by a set E of n edges with a limited supply for each edge, and a set of m clients, where each client specifies one interval of E she is interested in and a budget B j which is the maximum price she is willing to pay for that interval. An envy-free pricing is one in which every customer is allocated an (possibly empty) interval maximizing her utility. Grandoni and Rothvoss (SIAM J. Comput. 2016) proposed a polynomial-time approximation scheme ( PTAS ) for the unlimited supply case with running time ( nm ) O ((1/ɛ) 1/ɛ ) , which was extended to the limited supply case by Grandoni and Wiese (ESA 2019). By utilizing the known hierarchical decomposition of doubling metrics , we give a PTAS with running time ( nm ) O (1/ ɛ 2 ) for the unlimited supply case. We then consider the limited supply case, and the notion of ɛ-envy-free pricing in which a customer gets an allocation maximizing her utility within an additive error of ɛ. For this case, we develop an approximation scheme with running time ( nm ) O (log 5/2 max e H e /ɛ 3 ) , where H e = B max ( e )/ B min ( e ) is the maximum ratio of the budgets of any two customers demanding edge e . This yields a PTAS in the uniform budget case, and a quasi-PTAS for the general case. The best approximation known, in both cases, for the exact envy-free pricing version is O (log c max ), where c max is the maximum item supply. Our method is based on the known hierarchical decomposition of doubling metrics, and can be applied to other problems, such as the maximum feasible subsystem problem with interval matrices.

Learning Within an Instance for Designing High-Revenue Combinatorial Auctions

We develop a new framework for designing truthful, high-revenue (combinatorial) auctions for limited supply. Our mechanism learns within an instance. It generalizes and improves over previously-studied random-sampling mechanisms. It first samples a participatory group of bidders, then samples several learning groups of bidders from the remaining pool of bidders, learns a high-revenue auction from the learning groups, and finally runs that auction on the participatory group. Previous work on random-sampling mechanisms focused primarily on unlimited supply. Limited supply poses additional significant technical challenges, since allocations of items to bidders must be feasible. We prove guarantees on the performance of our mechanism based on a market-shrinkage term and a new complexity measure we coin partition discrepancy. Partition discrepancy simultaneously measures the intrinsic complexity of the mechanism class and the uniformity of the set of bidders. We then introduce new auction classes that can be parameterized in a way that does not depend on the number of bidders participating, and prove strong guarantees for these classes. We show how our mechanism can be implemented efficiently by leveraging practically-efficient routines for solving winner determination. Finally, we show how to use structural revenue maximization to decide what auction class to use with our framework when there is a constraint on the number of learning groups.

Adipose Derived Mesenchymal Stem Cells Restore Spermatogenesis in Male non Obstructive Azoospermia (Literature Review)

Stem cells are considered as new much promising therapeutic agents in treatment of male infertility due to their high differentiation potential and unlimited supply. In this review we summarized current views on application of mesenchymal stem cells in reproductive medicine.

Scalable generation of mesenchymal stem cells and adipocytes from human pluripotent stem cells

Human pluripotent stem cells (hPSCs) can provide unlimited supply for mesenchymal stem cells (MSCs) and adipocytes that can be used for therapeutic applications. Here we developed a simple and highly efficient All-trans-retinoic acid (RA)-based method for generating an off-the-shelf and scalable number of human pluripotent stem cell (hPSC)-derived MSCs with enhanced adipogenic potential. We showed that short exposure of multiple hPSC lines (hESCs/ hiPSCs) to a high RA concentration (10 μM) dramatically enhances embryoid body (EB) formation through regulation of genes activating signaling pathways associated with cell proliferation, survival and adhesion, among others. Disruption of cell adhesion induced the subsequent differentiation of the highly expanded RA-derived EB-forming cells into a pure population of multipotent MSCs (up to 1542-fold increase in comparison to RA-untreated counterparts). Interestingly, the RA-derived MSCs displayed enhanced differentiation potential into adipocytes. Thus, these findings present a novel RA-based approach for providing an unlimited source of MSCs and adipocytes that can be used for regenerative medicine, drug screening, and disease modeling applications.

Increased summer food supply decreases non-breeding movement in black-legged kittiwakes

Individual condition at one stage of the annual cycle is expected to influence behaviour during subsequent stages, yet experimental evidence of food-mediated carry-over effects is scarce. We used a food supplementation experiment to test the effects of food supply during the breeding season on migration phenology and non-breeding behaviour. We provided an unlimited supply of fish to black-legged kittiwakes ( Rissa tridactyla ) during their breeding season on Middleton Island, Alaska, monitored reproductive phenology and breeding success, and used light-level geolocation to observe non-breeding behaviour. Among successful breeders, fed kittiwakes departed the colony earlier than unfed controls. Fed kittiwakes travelled less than controls during the breeding season, contracting their non-breeding range. Our results demonstrate that food supply during the breeding season affects non-breeding phenology, movement and distribution, providing a potential behavioural mechanism underlying observed survival costs of reproduction.

Circular Economy and Sustainability

In the last decades, the concern over natural resources, sustainability, and the current linear economic model based on continuous growth is one of the great challenges of our time. The assumption that there is an unlimited supply of natural resources and that the environment has an unlimited capacity to absorb waste and pollution is no longer a current trend, and growing attention has been paid to it worldwide. This chapter represents a contribution to the continuous conceptual development of circular economy and sustainability, and it also reviews how these two concepts have evolved over the past decades. An extensive literature review was conducted, employing bibliometric analysis to scrutinise the state of the art, the perspectives, the agreements and disagreements among these concepts and their correlation.

A computational approach for mapping heme biology in the context of hemolytic disorders

Heme is an iron ion-containing molecule found within hemoproteins such as hemoglobin and cytochromes that participates in diverse biological processes. While its unlimited supply has been implicated in deleterious processes in several diseases including malaria, sepsis, ischemia-reperfusion, and disseminated intravascular coagulation, little is known about its regulatory and signaling functions. A majority of the computational research to elucidate these functions has been purely data-driven due to the absence of curated pathway resources, which have proven useful in the computational study in other indications. Here, we present two resources aimed to exploit this unexplored information to model heme biology. The first resource is an ontology covering heme-specific terms not yet included in standard controlled vocabularies. Using this ontology, we curated and modeled a corpus of 46 scientific articles to generate a mechanistic knowledge graph representing the heme’s interactome for that particular literature. Finally, we demonstrated the utility of these resources by investigating the role of heme in the Toll-like receptor signaling pathway. Our analysis proposed a series of crosstalk events that could explain the role of heme in activating the TLR4 signaling pathway. In summary, the presented work opens the door for the scientific community to explore in more detail the published knowledge on heme biology.