Capacity precommitment and price competition yield cournot outcomes

We study an industry of a homogeneous good where n firms with identical technology compete by first building capacity, and then, after observing the capacity decisions, choosing a "reservation price" at which they are willing to sell their entire capacities. We show that every pure strategy equilibrium yields the Cournot outcome, and that the Cournot outcome can be sustained by a pure strategy subgame perfect equilibrium

Capacity precommitment and price competition yield the Cournot outcome

We introduce a simple model of oligopolistic competition where firms first build capacity, and then, after observing the capacity decisions, choose a reservation price at which they are willing to supply their capacities. This model describes many markets more realistically than the model of Kreps and Scheinkman [Kreps, D., Scheinkman, J., 1983. Quantity precommitment and Bertrand competition yield Cournot outcomes. Bell J. Econ. 14, 326–337]. We show that in this new model every pure strategy equilibrium yields the Cournot outcome, and that the Cournot outcome can be sustained by a pure strategy subgame perfect equilibrium.Publicad

Current threats faced by amphibian populations in the southern cone of South America

In this work, we update and increase knowledge on the severity and extent of threats affecting 57 populations of 46 amphibian species from Chile and Argentina in southern South America. We analyzed the intrinsic conservation problems that directly impact these populations. We shared a questionnaire among specialists on threats affecting target amphibian populations with information on i) range, ii) historical occurrence and abundance, iii) population trends, iv) local extinctions, v) threats, and vi) ongoing and necessary conservation/research. We assessed association patterns between reported threats and population trends using multiple correspondence analysis. Since 2010, 25 of 57 populations have declined, while 16 experienced local extinctions. These populations were affected by 81% of the threat categories analyzed, with those related to agricultural activities and/or habitat modifications being the most frequently reported. Invasive species, emerging diseases, and activities related to grazing, ranching, or farming were the threats most associated with population declines. Low connectivity was the most frequent intrinsic conservation problem affecting 68% of the target populations, followed by low population numbers, affecting 60%. Ongoing monitoring activity was conducted in 32 (56%) populations and was the most frequent research activity. Threat mitigation was reported in 27 (47%) populations and was the most frequent ongoing management activity. We found that habitat management is ongoing in 5 (9%) populations. At least 44% of the amphibian populations surveyed in Chile and Argentina are declining. More information related to the effect of management actions to restore habitats, recover populations, and eliminate threats such as invasive species is urgently needed to reverse the conservation crisis facing amphibians in this Neotropical region.Fil: Kacoliris, Federico Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Zoología de Vertebrados. Sección Herpetología; ArgentinaFil: Berkunsky, Igor. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto Multidisciplinario de Ecosistemas y Desarrollo Sustentable; ArgentinaFil: Acosta, Juan Carlos. Universidad Nacional de San Juan. Facultad de Ciencias Exactas Físicas y Naturales. Departamento de Biología; ArgentinaFil: Acosta, Rodrigo. Universidad Nacional de San Juan. Facultad de Ciencias Exactas Físicas y Naturales. Departamento de Biología; ArgentinaFil: Agostini, Maria Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; ArgentinaFil: Akmentins, Mauricio Sebastián. Universidad Nacional de Jujuy. Instituto de Ecorregiones Andinas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Ecorregiones Andinas; ArgentinaFil: Arellano, María Luz. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Zoología de Vertebrados. Sección Herpetología; ArgentinaFil: Azat, Claudio. Universidad Andrés Bello; ChileFil: Bach, Nadia Carla. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis; ArgentinaFil: Blanco, Mirta Blanco. Universidad Nacional de San Juan. Facultad de Ciencias Exactas Físicas y Naturales. Departamento de Biología; ArgentinaFil: Calvo, Rodrigo. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Zoología de Vertebrados. Sección Herpetología; ArgentinaFil: Charrier, Andres. Pontificia Universidad Católica de Chile; ChileFil: Corbalán, Valeria Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Provincia de Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Universidad Nacional de Cuyo. Instituto Argentino de Investigaciones de las Zonas Áridas; ArgentinaFil: Correa, Claudio. Universidad de Concepción. Facultad de Ciencias Naturales y Oceanografía. Departamento de Zoología; ChileFil: Cuello, Maria Elena. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche; ArgentinaFil: Deutsch, Camila. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; ArgentinaFil: Di Pietro, Diego Omar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Zoología de Vertebrados. Sección Herpetología; ArgentinaFil: Gastón, María Soledad. Universidad Nacional de Jujuy. Instituto de Ecorregiones Andinas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Ecorregiones Andinas; ArgentinaFil: Gomez Alez, Rodrigo. Universidad Nacional de San Juan. Facultad de Ciencias Exactas Físicas y Naturales. Departamento de Biología; ArgentinaFil: Kaas, Camila. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Zoología de Vertebrados. Sección Herpetología; ArgentinaFil: Kaas, Nicolas. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Zoología de Vertebrados. Sección Herpetología; ArgentinaFil: Lobos, Gabriel. Universidad de Chile; ChileFil: Martínez, Tomás Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ciencias Exactas Físicas y Naturales. Departamento de Biología; ArgentinaFil: Martínez Aguirre, Tomás. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Zoología de Vertebrados. Sección Herpetología; ArgentinaFil: Mora, Marta. Vida Nativa NGO; ChileFil: Nieva Cocilio, Rodrigo Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ciencias Exactas Físicas y Naturales. Departamento de Biología; ArgentinaFil: Pastore, Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Administración de Parques Nacionales; ArgentinaFil: Pérez Iglesias, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Química de San Luis. Universidad Nacional de San Luis. Facultad de Química, Bioquímica y Farmacia. Instituto de Química de San Luis; Argentina. Universidad Nacional de San Luis. Facultad de Química, Bioquímica y Farmacia. Laboratorio de Biología; ArgentinaFil: Piaggio Kokot, Lia Elena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ciencias Exactas Físicas y Naturales. Departamento de Biología; ArgentinaFil: Rabanal, Felipe. Universidad Austral de Chile; ChileFil: Rodríguez Muñoz, Melina Jesús. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ciencias Exactas Físicas y Naturales. Departamento de Biología; ArgentinaFil: Sanchez, Laura Cecilia. Provincia de Entre Ríos. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción. Universidad Autónoma de Entre Ríos. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción; ArgentinaFil: Tala, Charif. Ministerio del Medio Ambiente de Chile; ChileFil: Ubeda, Carmen Adria. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche; ArgentinaFil: Vaira, Marcos. Universidad Nacional de Jujuy. Instituto de Ecorregiones Andinas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Ecorregiones Andinas; ArgentinaFil: Velasco, Melina Alicia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Zoología de Vertebrados. Sección Herpetología; ArgentinaFil: Vidal, Marcela. Universidad del Bio Bio. Facultad de Ciencias. Departamento de Ciencias Basicas; ChileFil: Williams, Jorge Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. División Zoología de Vertebrados. Sección Herpetología; Argentin

Cut-offs and response criteria for the Hospital Universitario la Princesa Index (HUPI) and their comparison to widely-used indices of disease activity in rheumatoid arthritis

Objective To estimate cut-off points and to establish response criteria for the Hospital Universitario La Princesa Index (HUPI) in patients with chronic polyarthritis. Methods Two cohorts, one of early arthritis (Princesa Early Arthritis Register Longitudinal PEARL] study) and other of long-term rheumatoid arthritis (Estudio de la Morbilidad y Expresión Clínica de la Artritis Reumatoide EMECAR]) including altogether 1200 patients were used to determine cut-off values for remission, and for low, moderate and high activity through receiver operating curve (ROC) analysis. The areas under ROC (AUC) were compared to those of validated indexes (SDAI, CDAI, DAS28). ROC analysis was also applied to establish minimal and relevant clinical improvement for HUPI. Results The best cut-off points for HUPI are 2, 5 and 9, classifying RA activity as remission if =2, low disease activity if >2 and =5), moderate if >5 and <9 and high if =9. HUPI''s AUC to discriminate between low-moderate activity was 0.909 and between moderate-high activity 0.887. DAS28''s AUCs were 0.887 and 0.846, respectively; both indices had higher accuracy than SDAI (AUCs: 0.832 and 0.756) and CDAI (AUCs: 0.789 and 0.728). HUPI discriminates remission better than DAS28-ESR in early arthritis, but similarly to SDAI. The HUPI cut-off for minimal clinical improvement was established at 2 and for relevant clinical improvement at 4. Response criteria were established based on these cut-off values. Conclusions The cut-offs proposed for HUPI perform adequately in patients with either early or long term arthritis

The comparative responsiveness of Hospital Universitario Princesa Index and other composite indices for assessing rheumatoid arthritis activity

Objective To evaluate the responsiveness in terms of correlation of the Hospital Universitario La Princesa Index (HUPI) comparatively to the traditional composite indices used to assess disease activity in rheumatoid arthritis (RA), and to compare the performance of HUPI-based response criteria with that of the EULAR response criteria. Methods Secondary data analysis from the following studies: ACT-RAY (clinical trial), PROAR (early RA cohort) and EMECAR (pre-biologic era long term RA cohort). Responsiveness was evaluated by: 1) comparing change from baseline (Delta) of HUPI with Delta in other scores by calculating correlation coefficients; 2) calculating standardised effect sizes. The accuracy of response by HUPI and by EULAR criteria was analyzed using linear regressions in which the dependent variable was change in global assessment by physician (Delta GDA-Phy). Results Delta HUPI correlation with change in all other indices ranged from 0.387 to 0.791); HUPI's standardized effect size was larger than those from the other indices in each database used. In ACT-RAY, depending on visit, between 65 and 80% of patients were equally classified by HUPI and EULAR response criteria. However, HUPI criteria were slightly more stringent, with higher percentage of patients classified as non-responder, especially at early visits. HUPI response criteria showed a slightly higher accuracy than EULAR response criteria when using Delta GDA-Phy as gold standard. Conclusion HUPI shows good responsiveness in terms of correlation in each studied scenario (clinical trial, early RA cohort, and established RA cohort). Response criteria by HUPI seem more stringent than EULAR''s

A study of CP violation in B-+/- -&gt; DK +/- and B-+/- -&gt; D pi(+/-) decays with D -&gt; (KSK +/-)-K-0 pi(-/+) final states

A first study of CP violation in the decay modes $B^\pm\to [K^0_{\rm S} K^\pm \pi^\mp]_D h^\pm$ and $B^\pm\to [K^0_{\rm S} K^\mp \pi^\pm]_D h^\pm$, where $h$ labels a $K$ or $\pi$ meson and $D$ labels a $D^0$ or $\overline{D}^0$ meson, is performed. The analysis uses the LHCb data set collected in $pp$ collisions, corresponding to an integrated luminosity of 3 fb$^{-1}$. The analysis is sensitive to the CP-violating CKM phase $\gamma$ through seven observables: one charge asymmetry in each of the four modes and three ratios of the charge-integrated yields. The results are consistent with measurements of $\gamma$ using other decay modes

Measurement of CP asymmetry in B-s(0) -&gt; D-s(-/+) K--/+ decays

We report on measurements of the time-dependent CP violating observables in $B^0_s\rightarrow D^{\mp}_s K^{\pm}$ decays using a dataset corresponding to 1.0 fb$^{-1}$ of pp collisions recorded with the LHCb detector. We find the CP violating observables $C_f=0.53\pm0.25\pm0.04$, $A^{\Delta\Gamma}_f=0.37\pm0.42\pm0.20$, $A^{\Delta\Gamma}_{\bar{f}}=0.20\pm0.41\pm0.20$, $S_f=-1.09\pm0.33\pm0.08$, $S_{\bar{f}}=-0.36\pm0.34\pm0.08$, where the uncertainties are statistical and systematic, respectively. We use these observables to make the first measurement of the CKM angle $\gamma$ in $B^0_s\rightarrow D^{\mp}_s K^{\pm}$ decays, finding $\gamma$ = (115$_{-43}^{+28}$)$^\circ$ modulo 180$^\circ$ at 68% CL, where the error contains both statistical and systematic uncertainties.We report on measurements of the time-dependent CP violating observables in B$_{s}^{0}$  → D$_{s}^{∓}$ K$^{±}$ decays using a dataset corresponding to 1.0 fb$^{−1}$ of pp collisions recorded with the LHCb detector. We find the CP violating observables C$_{f}$ = 0.53±0.25±0.04, A$_{f}^{ΔΓ}$  = 0.37 ± 0.42 ± 0.20, ${A}_{\overline{f}}^{\varDelta \varGamma }=0.20\pm 0.41\pm 0.20$ , S$_{f}$ = −1.09±0.33±0.08, ${S}_{\overline{f}}=-0.36\pm 0.34\pm 0.08$ , where the uncertainties are statistical and systematic, respectively. Using these observables together with a recent measurement of the B$_{s}^{0}$ mixing phase −2β$_{s}$ leads to the first extraction of the CKM angle γ from B$_{s}^{0}$  → D$_{s}^{∓}$ K$^{±}$ decays, finding γ = (115$_{− 43}^{+ 28}$ )° modulo 180° at 68% CL, where the error contains both statistical and systematic uncertainties.We report on measurements of the time-dependent CP violating observables in $B^0_s\rightarrow D^{\mp}_s K^{\pm}$ decays using a dataset corresponding to 1.0 fb$^{-1}$ of pp collisions recorded with the LHCb detector. We find the CP violating observables $C_f=0.53\pm0.25\pm0.04$, $A^{\Delta\Gamma}_f=0.37\pm0.42\pm0.20$, $A^{\Delta\Gamma}_{\bar{f}}=0.20\pm0.41\pm0.20$, $S_f=-1.09\pm0.33\pm0.08$, $S_{\bar{f}}=-0.36\pm0.34\pm0.08$, where the uncertainties are statistical and systematic, respectively. Using these observables together with a recent measurement of the $B^0_s$ mixing phase $-2\beta_s$ leads to the first extraction of the CKM angle $\gamma$ from $B^0_s \rightarrow D^{\mp}_s K^{\pm}$ decays, finding $\gamma$ = (115$_{-43}^{+28}$)$^\circ$ modulo 180$^\circ$ at 68% CL, where the error contains both statistical and systematic uncertainties

Measurement of Upsilon production in collisions at root s=2.76 TeV

The production of $\Upsilon(1S)$, $\Upsilon(2S)$ and $\Upsilon(3S)$ mesons decaying into the dimuon final state is studied with the LHCb detector using a data sample corresponding to an integrated luminosity of 3.3 $pb^{-1}$ collected in proton-proton collisions at a centre-of-mass energy of $\sqrt{s}=2.76$ TeV. The differential production cross-sections times dimuon branching fractions are measured as functions of the $\Upsilon$ transverse momentum and rapidity, over the ranges $p_{\rm T} Upsilon(1S) X) x B(Upsilon(1S) -> mu+mu-) = 1.111 +/- 0.043 +/- 0.044 nb, sigma(pp -> Upsilon(2S) X) x B(Upsilon(2S) -> mu+mu-) = 0.264 +/- 0.023 +/- 0.011 nb, sigma(pp -> Upsilon(3S) X) x B(Upsilon(3S) -> mu+mu-) = 0.159 +/- 0.020 +/- 0.007 nb, where the first uncertainty is statistical and the second systematic

Study of forward Z + jet production in pp collisions at √s=7 TeV

A measurement of the $Z(\rightarrow\mu^+\mu^-)$+jet production cross-section in $pp$ collisions at a centre-of-mass energy $\sqrt{s} = 7$ TeV is presented. The analysis is based on an integrated luminosity of $1.0\,\text{fb}^{-1}$ recorded by the LHCb experiment. Results are shown with two jet transverse momentum thresholds, 10 and 20 GeV, for both the overall cross-section within the fiducial volume, and for six differential cross-section measurements. The fiducial volume requires that both the jet and the muons from the Z boson decay are produced in the forward direction ($2.0<\eta<4.5$). The results show good agreement with theoretical predictions at the second-order expansion in the coupling of the strong interaction.A measurement of the $Z(\rightarrow\mu^+\mu^-)$+jet production cross-section in $pp$ collisions at a centre-of-mass energy $\sqrt{s} = 7$ TeV is presented. The analysis is based on an integrated luminosity of $1.0\,\text{fb}^{-1}$ recorded by the LHCb experiment. Results are shown with two jet transverse momentum thresholds, 10 and 20 GeV, for both the overall cross-section within the fiducial volume, and for six differential cross-section measurements. The fiducial volume requires that both the jet and the muons from the Z boson decay are produced in the forward direction ($2.0<\eta<4.5$). The results show good agreement with theoretical predictions at the second-order expansion in the coupling of the strong interaction