The socially responsible choice in a duopolistic market: a dynamic problem of “ethical product” differentiation

The increasing attention of profit maximizing corporations to corporate social responsibility (CSR) is a new stylized fact of the contemporary economic environment. In our theoretical analysis we model CSR adoption as the optimal response of a profit maximizing firm to the competition of a not for profit corporate pioneer in the presence of a continuum of consumers with heterogeneous preferences towards the social and environmental features of the final good. CSR adoption implies a trade-off since, on the one side, it raises production costs but, on the other side, it leads to accumulation of “ethical capital”.We investigate conditions under which the profit maximizing firm switches from price to price and CSR competition by comparing monopoly and duopoly equilibria and their consequences on aggregate social responsibility and consumer welfare. Our findings provide a theoretical background for competition between profit maximizing incumbents and not for profit entrants in markets such as fair trade, organic food, ethical banking and ethical finance

Spectral Relaxations and Fair Densest Subgraphs

Reducing hidden bias in the data and ensuring fairness in algorithmic data analysis has recently received significant attention. In this paper, we address the problem of identifying a densest subgraph, while ensuring that none of one binary protected attribute is disparately impacted. Unfortunately, the underlying algorithmic problem is NP-hard, even in its approximation version: approximating the densest fair subgraph with a polynomial-time algorithm is at least as hard as the densest subgraph problem of at most k vertices, for which no constant approximation algorithms are known. Despite such negative premises, we are able to provide approximation results in two important cases. In particular, we are able to prove that a suitable spectral embedding allows recovery of an almost optimal, fair, dense subgraph hidden in the input data, whenever one is present, a result that is further supported by experimental evidence. We also show a polynomial-time, $2$-approximation algorithm, whenever the underlying graph is itself fair. We finally prove that, under the small set expansion hypothesis, this result is tight for fair graphs. The above theoretical findings drive the design of heuristics, which we experimentally evaluate on a scenario based on real data, in which our aim is to strike a good balance between diversity and highly correlated items from Amazon co-purchasing graphs

Utility of Visual Counts for Determining Efficacy of Management Tools for California Ground Squirrels

Visual counts are frequently used to assess efficacy of management tools for ground squirrels (Marmotini), but the effectiveness of this approach has not been assessed for many ground squirrel species including California ground squirrels (Otospermophilus spp.). As such, we used visual counts of California ground squirrels to determine the efficacy of diphacinone-treated oat groat applications in rangelands in central California, USA, and compared those results to efficacy values derived from the use of radio-collared ground squirrels in the same plots. We also used location data of radio-collared ground squirrels to explore the size of buffer zone needed around census plots to provide an accurate assessment of efficacy when using visual counts. We did not observe a difference in efficacy associated with the 2 monitoring strategies, indicating that visual counts are an effective monitoring tool for ground squirrels. We observed low efficacy in 2 treatment plots, likely due to low usage of those plots by ground squirrels. Increasing the size of buffer zones would increase the usage of treatment areas by the target population and would help to minimize reinvasion by adjacent ground squirrel populations, which could bias efficacy values low. We suggest a minimum of a 61-m buffer surrounding census plots. Increasing to 66 m or more would further benefit efficacy assessments, but increased size of the buffer zone must be balanced with greater costs and regulatory constraints

Two-loop master integrals for pseudo-scalar quarkonium and leptonium production and decay

We compute the master integrals relevant for the two-loop corrections to pseudo-scalar quarkonium and leptonium production and decay. We present both analytic and high-precision numerical results. The analytic expressions are given in terms of multiple polylogarithms (MPLs), elliptic multiple polylogarithms (eMPLs) and iterated integrals of Eisenstein series. As an application of our results, we obtain for the first time an analytic expression for the two-loop amplitude for para-positronium decay to two photons at two loops

Two-loop master integrals for pseudo-scalar quarkonium and leptonium production and decay

We compute the master integrals relevant for the two-loop corrections to pseudo-scalar quarkonium and leptonium production and decay. We present both analytic and high-precision numerical results. The analytic expressions are given in terms of multiple polylogarithms (MPLs), elliptic multiple polylogarithms (eMPLs) and iterated integrals of Eisenstein series. As an application of our results, we obtain for the first time an analytic expression for the two-loop amplitude for para-positronium decay to two photons at two loops

Why we forget our dreams : acetylcholine and norepinephrine in wakefulness and REM sleep

The ascending fibers releasing norepinephrine and acetylcholine are highly active during wakefulness. In contrast, during rapid-eye-movement sleep, the neocortical tone is sustained mainly by acetylcholine. By comparing the different physiological features of the norepinephrine and acetylcholine systems in the light of the GANE (glutamate amplifies noradrenergic effects) model, we suggest how to interpret some functional differences between waking and rapid-eye-movement sleep

dynamic modeling of wind turbines experimental tuning of a multibody model

Abstract This work is part of a research project funded by the Italian Ministry of the University and Research (MIUR), under the call for "National Interest Research Projects 2015 (PRIN 2015)", titled "Smart Optimized Fault Tolerant WIND turbines (SOFTWIND)". Within this project, the research unit of the University of Perugia (UniPG) aims to develop dynamic modeling and simulation methodologies and fatigue behavior evaluation ones for wind turbine as a whole. The development of these methodologies will be aimed at predicting the life of generic wind turbines, also providing important and fundamental parameters for optimizing their control, aimed at reducing the failures of these machines. In the present paper, a small turbine, developed at the Department of Engineering of the University of Perugia, will be analyzed. The multibody modeling technique adopted and the experimental activity conducted in the wind tunnel of UniPG, needed for the tuning of the model, will be described. The analysis of both model behavior and experimental data has allowed for the definition of a robust multibody modeling technique that adopts a freeware code (NREL - FAST), universally considered to be a reference in this field. The goodness of the model guarantees the capabilities of the simulation environment to analyze the real load scenario and the fatigue behavior of this kind of device

Finding a Bounded-Degree Expander Inside a Dense One

It follows from the Marcus-Spielman-Srivastava proof of the Kadison-Singer conjecture that if $G=(V,E)$ is a $\Delta$-regular dense expander then there is an edge-induced subgraph $H=(V,E_H)$ of $G$ of constant maximum degree which is also an expander. As with other consequences of the MSS theorem, it is not clear how one would explicitly construct such a subgraph. We show that such a subgraph (although with quantitatively weaker expansion and near-regularity properties than those predicted by MSS) can be constructed with high probability in linear time, via a simple algorithm. Our algorithm allows a distributed implementation that runs in $\mathcal O(\log n)$ rounds and does \bigO(n) total work with high probability. The analysis of the algorithm is complicated by the complex dependencies that arise between edges and between choices made in different rounds. We sidestep these difficulties by following the combinatorial approach of counting the number of possible random choices of the algorithm which lead to failure. We do so by a compression argument showing that such random choices can be encoded with a non-trivial compression. Our algorithm bears some similarity to the way agents construct a communication graph in a peer-to-peer network, and, in the bipartite case, to the way agents select servers in blockchain protocols

Two-neutron transfer in nuclei close to the dripline

We investigate the two-neutron transfer modes induced by (t,p) reactions in neutron-rich oxygen isotopes. The nuclear response to the pair transfer is calculated in the framework of continuum-Quasiparticle Random Phase Approximation (cQRPA). The cQRPA allows a consistent determination of the residual interaction and an exact treatment of the continuum coupling. The (t,p) cross sections are calculated within the DWBA approach and the form factors are evaluated by different methods : macroscopically, following the Bayman and Kallio method, and fully microscopically. The largest cross section corresponds to a high-lying collective mode built entirely upon continuum quasiparticle states.Comment: 12 pages, 7 figure