The Technology Bias in Entrepreneur-Investor Negotiations

Entrepreneur-investor negotiations are pivotal for ventures in need of funding. Yet, to date, little is known about the dynamics of these negotiations. We investigate a critical feature of this phenomenon by examining the role of technology, via cognitive heuristics, in shaping entrepreneur and investor perceptions as well as subsequent negotiation outcomes. In a controlled laboratory setting, we simulated 103 negotiations between entrepreneurs and investors. We hypothesize and find that there is a pervasive technology bias that influences the perceptions of both parties of the negotiation, and consequently negotiation outcomes. Our findings offer unique insights into the relationships of technology, cognitive heuristics, and negotiations. We discuss the implications for both practitioners and theoreticians in the areas of technology, decision making, negotiations, and entrepreneurial financing

Converting Land from Poplar Tree Bioenergy Planting to Cropland: An Example

Many landowners ask about the process and costs for returning land to crop production after trees are cut for biomass. A field on the Squaw Creek bottom, Story County, Iowa was planted to hybrid poplar trees in spring 2000. The trees were planted in rows with a 10-ft spacing. The trees were cut in spring 2010. The resulting field was four acres, and this is the account of the first corn crop in 2011 on the area

Lessons from the Congested Clique Applied to MapReduce

The main results of this paper are (I) a simulation algorithm which, under quite general constraints, transforms algorithms running on the Congested Clique into algorithms running in the MapReduce model, and (II) a distributed $O(\Delta)$-coloring algorithm running on the Congested Clique which has an expected running time of (i) $O(1)$ rounds, if $\Delta \geq \Theta(\log^4 n)$; and (ii) $O(\log \log n)$ rounds otherwise. Applying the simulation theorem to the Congested-Clique $O(\Delta)$-coloring algorithm yields an $O(1)$-round $O(\Delta)$-coloring algorithm in the MapReduce model. Our simulation algorithm illustrates a natural correspondence between per-node bandwidth in the Congested Clique model and memory per machine in the MapReduce model. In the Congested Clique (and more generally, any network in the $\mathcal{CONGEST}$ model), the major impediment to constructing fast algorithms is the $O(\log n)$ restriction on message sizes. Similarly, in the MapReduce model, the combined restrictions on memory per machine and total system memory have a dominant effect on algorithm design. In showing a fairly general simulation algorithm, we highlight the similarities and differences between these models.Comment: 15 page

Minimally-invasive debulking of ovarian cancer in the rat pelvis by means of photodynamic therapy using the pegylated photosensitizer PEG-m-THPC

Interstitial photodynamic therapy (PDT) using the pegylated photosensitizer PEG-m-THPC was evaluated as a minimally-invasive procedure to selectively debulk unrespectable pelvic ovarian cancer (NuTu-19) in immunocompetent rats. To assess tumour selectivity, PEG-m-THPC at dosages of 0.3, 3.0 and 30 mg kg−1 body weight was administered intravenously to 30 rats 4 weeks following tumour induction. Eight days later laser light at 652 nm and optical doses ranging from 100 to 900 J cm−1 diffuser-length was delivered by an interstitial cylindrical diffusing fibre inserted blindly into the pelvis. Three days following light application, the volume of necrosis was measured and the damage to pelvic organs was assessed histologically on cross sections. For analysis of survival, 20 tumour-bearing rats received PDT using drug doses of 3 or 9 mg kg−1 body weight and an optical dose of 900 J cm−1 diffuser-length, whereas ten untreated tumour-bearing rats served as controls. The histological assessment of PDT induced necrosis showed a non-linear dose–response for both the photosensitizer dose and the optical dose. The lowest drug dose activated with the highest optical dose did not induce more necrosis than seen in tumour-bearing control animals. The same optical dose induced necrosis of 17 mm in diameter using 30 mg kg−1 and 11 mm using 3 mg kg−1 photosensitizer. The optical threshold for induction of significant necrosis was between 100 and 300 J cm−1 diffuser-length for 30 mg kg−1 and between 300 and 500 J cm−1 for 3 mg kg−1 PEG-m-THPC. Significant damage to normal pelvic organs was only seen if 30 mg kg−1 photosensitizer was activated with optical doses of 700 J cm−1 or more. In the survival study, all treated animals survived PDT for at least 2 weeks and the intestinal and urinary tract remained functional. No clinical signs of blood vessel or nerve injury were observed. Mean overall survival of untreated tumour-bearing rats was 25.0 ± 4.5 days compared to 38.4 ± 3.8 days and 40.0 ± 3.6 days for rats treated with 3 mg kg−1 or 9 mg kg−1 PEG-m-THPC mediated PDT respectively (P < 0.05). We conclude that PEG-m-THPC mediated PDT has a favourable therapeutic window and that this minimally-invasive procedure can reduce pelvic cancer bulks effectively and selectively. © 1999 Cancer Research Campaig

Optical tweezers escape forces

With suitable calibration, optical tweezers can be used to measure forces. If the maximum force that can be exerted is of interest, calibration can be performed using viscous drag to remove a particle from the trap, typically by moving the stage. The stage velocity required to remove the particle then gives the escape force. However, the escape force can vary by up to 30% or more, depending on the particle trajectory. This can have significant quantitative impact on measurements. We describe the variation of escape force and escape trajectory, using both experimental measurements and simulations, and discuss implications for experimental measurement of forces

On Convergence of the Inexact Rayleigh Quotient Iteration with the Lanczos Method Used for Solving Linear Systems

For the Hermitian inexact Rayleigh quotient iteration (RQI), the author has established new local general convergence results, independent of iterative solvers for inner linear systems. The theory shows that the method locally converges quadratically under a new condition, called the uniform positiveness condition. In this paper we first consider the local convergence of the inexact RQI with the unpreconditioned Lanczos method for the linear systems. Some attractive properties are derived for the residuals, whose norms are $\xi_{k+1}$'s, of the linear systems obtained by the Lanczos method. Based on them and the new general convergence results, we make a refined analysis and establish new local convergence results. It is proved that the inexact RQI with Lanczos converges quadratically provided that $\xi_{k+1}\leq\xi$ with a constant $\xi\geq 1$. The method is guaranteed to converge linearly provided that $\xi_{k+1}$ is bounded by a small multiple of the reciprocal of the residual norm $\|r_k\|$ of the current approximate eigenpair. The results are fundamentally different from the existing convergence results that always require $\xi_{k+1}<1$, and they have a strong impact on effective implementations of the method. We extend the new theory to the inexact RQI with a tuned preconditioned Lanczos for the linear systems. Based on the new theory, we can design practical criteria to control $\xi_{k+1}$ to achieve quadratic convergence and implement the method more effectively than ever before. Numerical experiments confirm our theory.Comment: 20 pages, 8 figures. arXiv admin note: text overlap with arXiv:0906.223

The martyrdom effect : when pain and effort increase prosocial contributions

Most theories of motivation and behavior (and lay intuitions alike) consider pain and effort to be deterrents. In contrast to this widely held view, we provide evidence that the prospect of enduring pain and exerting effort for a prosocial cause can promote contributions to the cause. Specifically, we show that willingness to contribute to a charitable or collective cause increases when the contribution process is expected to be painful and effortful rather than easy and enjoyable. Across five experiments, we document this “martyrdom effect,” show that the observed patterns defy standard economic and psychological accounts, and identify a mediator and moderator of the effect. Experiment 1 showed that people are willing to donate more to charity when they anticipate having to suffer to raise money. Experiment 2 extended these findings to a non-charity laboratory context that involved real money and actual pain. Experiment 3 demonstrated that the martyrdom effect is not the result of an attribute substitution strategy (whereby people use the amount of pain and effort involved in fundraising to determine donation worthiness). Experiment 4 showed that perceptions of meaningfulness partially mediate the martyrdom effect. Finally, Experiment 5 demonstrated that the nature of the prosocial cause moderates the martyrdom effect: the effect is strongest for causes associated with human suffering. We propose that anticipated pain and effort lead people to ascribe greater meaning to their contributions and to the experience of contributing, thereby motivating higher prosocial contributions. We conclude by considering some implications of this puzzling phenomenon. Copyright © 2011 John Wiley & Sons, Ltd