73 research outputs found
Public Goods in Networks with Constraints on Sharing
This paper considers incentives to provide goods that are partially
excludable along social links. We introduce a model in which each individual in
a networked society makes a two-pronged decision: (i) decide how much of the
good to provide, and (ii) decide which subset of neighbours to nominate as
co-beneficiaries. An outcome specifies an endogenous subnetwork generated by
nominations and a public goods game occurring over the realised subnetwork. We
show the existence of specialised pure strategy Nash equilibria: those in which
some individuals (the Drivers) contribute while the remaining individuals (the
Passengers) free ride. We then consider how the set of efficient specialised
equilibria vary as the constraints on sharing are relaxed and we show a
monotonicity result. Finally, we introduce dynamics and show that only
specialised equilibria can be stable against individuals unilaterally changing
their provision level
The Effect of Social Distancing on the Reach of an Epidemic in Social Networks
How does social distancing affect the reach of an epidemic in social
networks? We present Monte Carlo simulation results of a capacity constrained
Susceptible-Infected-Removed (SIR) model. The key modelling feature is that
individuals are limited in the number of acquaintances that they can interact
with, thereby constraining disease transmission to an infectious subnetwork of
the original social network. While increased social distancing always reduces
the spread of an infectious disease, the magnitude varies greatly depending on
the topology of the network. Our results also reveal the importance of
coordinating social distancing policies at the global level. In particular, the
public health benefits from social distancing to a group (e.g., a country) may
be completely undone if that group maintains connections with outside groups
that are not following suit
Finding all stable matchings with assignment constraints
In this paper we consider stable matchings that are subject to assignment
constraints. These are matchings that require certain assigned pairs to be
included, insist that some other assigned pairs are not, and, importantly, are
stable. Our main contribution is an algorithm that determines when assignment
constraints are compatible with stability. Whenever a stable matching
consistent with the assignment constraints exists, our algorithm will output
all of them (each in polynomial time per solution). This provides market
designers with (i) a tool to test the feasibility of stable matchings with
assignment constraints, and (ii) a separate tool to implement them
Unique Stable Matchings
We provide necessary and sufficient conditions on the preferences of market
participants for a unique stable matching in models of two-sided matching with
non-transferable utility. We use the process of iterated deletion of
unattractive alternatives (IDUA), a formalisation of the reduction procedure in
Balinski and Ratier (1997), and we show that an instance of the matching
problem possesses a unique stable matching if and only if IDUA collapses each
participant preference list to a singleton. (This is in a sense the matching
problem analog of a strategic game being dominance solvable.
Some coordination problems are harder than others
In order to coordinate players in a game must first identify a target pattern
of behaviour. In this paper we investigate the difficulty of identifying
prominent outcomes in two kinds of binary action coordination problems in
social networks: pure coordination games and anti-coordination games. For both
environments, we determine the computational complexity of finding a strategy
profile that (i) maximises welfare, (ii) maximises welfare subject to being an
equilibrium, and (iii) maximises potential. We show that the complexity of
these objectives can vary with the type of coordination problem. Objectives (i)
and (iii) are tractable problems in pure coordination games, but for
anti-coordination games are NP-hard. Objective (ii), finding the best Nash
equilibrium, is NP-hard for both. Our results support the idea that
environments in which actions are strategic complements (e.g., technology
adoption) facilitate successful coordination more readily than those in which
actions are strategic substitutes (e.g., public good provision).Comment: arXiv admin note: text overlap with arXiv:2305.0712
Preference Swaps for the Stable Matching Problem
An instance of the Stable Matching Problem (SMP) is given by a bipartite
graph with a preference list of neighbors for every vertex. A swap in is
the exchange of two consecutive vertices in a preference list. A swap can be
viewed as a smallest perturbation of . Boehmer et al. (2021) designed a
polynomial-time algorithm to find the minimum number of swaps required to turn
a given maximal matching into a stable matching. To generalize this result to
the many-to-many version of SMP, we introduce a new representation of SMP as an
extended bipartite graph and reduce the problem to submodular minimization. It
is a natural problem to establish computational complexity of deciding whether
at most swaps are enough to turn into an instance where one of the
maximum matchings is stable. Using a hardness result of Gupta et al. (2020), we
prove that it is NP-hard to decide whether at most swaps are enough to turn
into an instance with a stable perfect matching. Moreover, this problem
parameterized by is W[1]-hard. We also obtain a lower bound on the running
time for solving the problem using the Exponential Time Hypothesis
Ibrutinib Unmasks Critical Role of Bruton Tyrosine Kinase in Primary CNS Lymphoma.
Bruton tyrosine kinase (BTK) links the B-cell antigen receptor (BCR) and Toll-like receptors with NF-κB. The role of BTK in primary central nervous system (CNS) lymphoma (PCNSL) is unknown. We performed a phase I clinical trial with ibrutinib, the first-in-class BTK inhibitor, for patients with relapsed or refractory CNS lymphoma. Clinical responses to ibrutinib occurred in 10 of 13 (77%) patients with PCNSL, including five complete responses. The only PCNSL with complete ibrutinib resistance harbored a mutation within the coiled-coil domain of CARD11, a known ibrutinib resistance mechanism. Incomplete tumor responses were associated with mutations in the B-cell antigen receptor-associated protein CD79B
Long-Term Impact of Radiation on the Stem Cell and Oligodendrocyte Precursors in the Brain
Background. The cellular basis of long term radiation damage in the brain is not fully understood. Methods and Findings. We administered a dose of 25Gy to adult rat brains while shielding the olfactory bulbs. Quantitative analyses were serially performed on different brain regions over 15 months. Our data reveal an immediate and permanent suppression of SVZ proliferation and neurogenesis. The olfactory bulb demonstrates a transient but remarkable SVZ-independent ability for compensation and maintenance of the calretinin interneuron population. The oligodendrocyte compartment exhibits a complex pattern of limited proliferation of NG2 progenitors but steady loss of the oligodendroglial antigen O4. As of nine months post radiation, diffuse demyelination starts in all irradiated brains. Counts of capillary segments and length demonstrate significant loss one day post radiation but swift and persistent recovery of the vasculature up to 15 months post XRT. MRI imaging confirms loss of volume of the corpus callosum and early signs of demyelination at 12 months. Ultrastructural analysis demonstrates progressive degradation of myelin sheaths with axonal preservation. Areas of focal necrosis appear beyond 15 months and are preceded by widespread demyelination. Human white matter specimens obtained post-radiation confirm early loss of oligodendrocyte progenitors and delayed onset of myelin sheath fragmentation with preserved capillaries. Conclusions. This study demonstrates that long term radiation injury is associated with irreversible damage to the neural stem cell compartment in the rodent SVZ and loss of oligodendrocyte precursor cells in both rodent and human brain. Delayed onset demyelination precedes focal necrosis and is likely due to the loss of oligodendrocyte precursor
Antiangiogenic agents in the treatment of recurrent or newly diagnosed glioblastoma: Analysis of single-agent and combined modality approaches
Surgical resection followed by radiotherapy and temozolomide in newly diagnosed glioblastoma can prolong survival, but it is not curative. For patients with disease progression after frontline therapy, there is no standard of care, although further surgery, chemotherapy, and radiotherapy may be used. Antiangiogenic therapies may be appropriate for treating glioblastomas because angiogenesis is critical to tumor growth. In a large, noncomparative phase II trial, bevacizumab was evaluated alone and with irinotecan in patients with recurrent glioblastoma; combination treatment was associated with an estimated 6-month progression-free survival (PFS) rate of 50.3%, a median overall survival of 8.9 months, and a response rate of 37.8%. Single-agent bevacizumab also exceeded the predetermined threshold of activity for salvage chemotherapy (6-month PFS rate, 15%), achieving a 6-month PFS rate of 42.6% (p < 0.0001). On the basis of these results and those from another phase II trial, the US Food and Drug Administration granted accelerated approval of single-agent bevacizumab for the treatment of glioblastoma that has progressed following prior therapy. Potential antiangiogenic agents-such as cilengitide and XL184-also show evidence of single-agent activity in recurrent glioblastoma. Moreover, the use of antiangiogenic agents with radiation at disease progression may improve the therapeutic ratio of single-modality approaches. Overall, these agents appear to be well tolerated, with adverse event profiles similar to those reported in studies of other solid tumors. Further research is needed to determine the role of antiangiogenic therapy in frontline treatment and to identify the optimal schedule and partnering agents for use in combination therapy
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