Outsourcing and Volatility

While outsourcing of production from the U.S. to Mexico has been hailed in Mexico as a valuable engine of growth, recently there have been misgivings regarding its fickleness and volatility. This paper is among the first in the trade literature to study the second moment properties of outsourcing. We begin by documenting a new stylized fact: the maquiladora outsourcing industries in Mexico experience fluctuations in value added that are roughly twice as volatile as the corresponding industries in the U.S. A difference-in-difference method is extended to second moments to verify the statistical significance of this finding. We then develop a stochastic model of outsourcing with heterogeneous firms that can explain this volatility. The model employs two novel mechanisms: an extensive margin in outsourcing which responds endogenously to transmit shocks internationally, and translog preferences which modulate firm entry.

Ecosystem respiration: Drivers of daily variability and background respiration in lakes around the globe

We assembled data from a global network of automated lake observatories to test hypotheses regarding the drivers of ecosystem metabolism. We estimated daily rates of respiration and gross primary production (GPP) for up to a full year in each lake, via maximum likelihood fits of a free‐water metabolism model to continuous high‐frequency measurements of dissolved oxygen concentrations. Uncertainties were determined by a bootstrap analysis, allowing lake‐days with poorly constrained rate estimates to be down‐weighted in subsequent analyses. GPP and respiration varied considerably among lakes and at seasonal and daily timescales. Mean annual GPP and respiration ranged from 0.1 to 5.0 mg O2 L−1 d−1 and were positively related to total phosphorus but not dissolved organic carbon concentration. Within lakes, significant day‐to‐day differences in respiration were common despite large uncertainties in estimated rates on some lake‐days. Daily variation in GPP explained 5% to 85% of the daily variation in respiration after temperature correction. Respiration was tightly coupled to GPP at a daily scale in oligotrophic and dystrophic lakes, and more weakly coupled in mesotrophic and eutrophic lakes. Background respiration ranged from 0.017 to 2.1 mg O2 L−1 d−1 and was positively related to indicators of recalcitrant allochthonous and autochthonous organic matter loads, but was not clearly related to an indicator of the quality of allochthonous organic matter inputs

Timing and spectral studies of the transient X-ray pulsar EXO 053109-6609.2 with ASCA and Beppo-SAX

We report timing and spectral properties of the transient Be X-ray pulsar EXO 053109--6609.2 studied using observations made with the ASCA and BeppoSAX observatories. Though there must have been at least one spin-down episode of the pulsar since its discovery, the new pulse period measurements show a monotonic spin-up trend since 1996. The pulse profile is found to have marginal energy dependence. There is also evidence for strong luminosity dependence of the pulse profile, a single peaked profile at low luminosity that changes to a double peaked profile at high luminosity. This suggests a change in the accretion pattern at certain luminosity level. The X-ray spectrum is found to consist of a simple power-law with photon index in the range of 0.4--0.8. At high intensity level the spectrum also shows presence of weak iron emission line.Comment: 12 pages, 8 figures, Accepted for publication in Ap

Potential of Double-crested Cormorants (\u3ci\u3ePhalacrocorax auritus\u3c/i\u3e), American White Pelicans (\u3ci\u3ePelecanus erythrorhynchos\u3c/i\u3e), and Wood Storks (\u3ci\u3eMycteria americana\u3c/i\u3e) to Transmit a Hypervirulent Strain of \u3ci\u3eAeromonas hydrophila\u3c/i\u3e between Channel Catfish Culture Ponds

Aeromonas hydrophila is a Gramnegative bacterium ubiquitous to freshwater and brackish aquatic environments that can cause disease in fish, humans, reptiles, and birds. Recent severe outbreaks of disease in commercial channel catfish (Ictalurus punctatus) aquaculture ponds have been associated with a hypervirulent Aeromonas hydrophila strain (VAH) that is genetically distinct from less virulent strains. The epidemiology of this disease has not been determined. Given that research has shown that Great Egrets (Ardea alba) can shed viable hypervirulent A. hydrophila after consuming diseased fish, we hypothesized that Doublecrested Cormorants (Phalacrocorax auritus), American White Pelicans (Pelecanus erythrorhynchos), and Wood Storks (Mycteria americana) could also serve as a reservoir for VAH and spread the pathogen during predation of fish in uninfected catfish ponds. All three species, when fed VAH-infected catfish, shed viable VAH in their feces, demonstrating their potential to spread VAH

Fate of Allochthonous Dissolved Organic Carbon in Lakes: A Quantitative Approach

Inputs of dissolved organic carbon (DOC) to lakes derived from the surrounding landscape can be stored, mineralized or passed to downstream ecosystems. The balance among these OC fates depends on a suite of physical, chemical, and biological processes within the lake, as well as the degree of recalcintrance of the allochthonous DOC load. The relative importance of these processes has not been well quantified due to the complex nature of lakes, as well as challenges in scaling DOC degradation experiments under controlled conditions to the whole lake scale. We used a coupled hydrodynamic-water quality model to simulate broad ranges in lake area and DOC, two characteristics important to processing allochthonous carbon through their influences on lake temperature, mixing depth and hydrology. We calibrated the model to four lakes from the North Temperate Lakes Long Term Ecological Research site, and simulated an additional 12 ‘hypothetical’ lakes to fill the gradients in lake size and DOC concentration. For each lake, we tested several mineralization rates (range: 0.001 d−1 to 0.010 d−1) representative of the range found in the literature. We found that mineralization rates at the ecosystem scale were roughly half the values from laboratory experiments, due to relatively cool water temperatures and other lake-specific factors that influence water temperature and hydrologic residence time. Results from simulations indicated that the fate of allochthonous DOC was controlled primarily by the mineralization rate and the hydrologic residence time. Lakes with residence times <1 year exported approximately 60% of the DOC, whereas lakes with residence times >6 years mineralized approximately 60% of the DOC. DOC fate in lakes can be determined with a few relatively easily measured factors, such as lake morphometry, residence time, and temperature, assuming we know the recalcitrance of the DOC

Improved frame synchronization schemes for INMARSAT-B/M SCPC and TDM channels

This paper proposes faster, more robust, frame synchronization schemes for various Inmarsat-B and Inmarsat-M communication and signalling channels. Equations are developed which permit frame synchronization strategies of the type specified by Inmarsat to be evaluated in terms of average true lock time, average false maintenance time, and average search time. Evaluation of the currently specified framing schemes shows that a significant performance improvement is obtained by optimizing the threshold parameters of the scheme. The optimization seeks a compromise between the conflicting requirements of maximizing true lock time and minimizing search time

Determining the probability of cyanobacterial blooms: the application of Bayesian networks in multiple lake systems

A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply. Physicochemical, biological, and meteorological observations were collated from 20 lakes located at different latitudes and characterized by a range of sizes and trophic states. Using these data, we built a Bayesian network to (1) analyze the sensitivity of cyanobacterial bloom development to different environmental factors and (2) determine the probability that cyanobacterial blooms would occur. Blooms were classified in three categories of hazard (low, moderate, and high) based on cell abundances. The most important factors determining cyanobacterial bloom occurrence were water temperature, nutrient availability, and the ratio of mixing depth to euphotic depth. The probability of cyanobacterial blooms was evaluated under different combinations of total phosphorus and water temperature. The Bayesian network was then applied to quantify the probability of blooms under a future climate warming scenario. The probability of the "high hazardous" category of cyanobacterial blooms increased 5% in response to either an increase in water temperature of 0.8°C (initial water temperature above 24°C) or an increase in total phosphorus from 0.01 mg/L to 0.02 mg/L. Mesotrophic lakes were particularly vulnerable to warming. Reducing nutrient concentrations counteracts the increased cyanobacterial risk associated with higher temperatures

Nature-Guided Cognitive Evolution for Predicting Dissolved Oxygen Concentrations in North Temperate Lakes

Predicting dissolved oxygen (DO) concentrations in north temperate lakes requires a comprehensive study of phenological patterns across various ecosystems, which highlights the significance of selecting phenological features and feature interactions. Process-based models are limited by partial process knowledge or oversimplified feature representations, while machine learning models face challenges in efficiently selecting relevant feature interactions for different lake types and tasks, especially under the infrequent nature of DO data collection. In this paper, we propose a Nature-Guided Cognitive Evolution (NGCE) strategy, which represents a multi-level fusion of adaptive learning with natural processes. Specifically, we utilize metabolic process-based models to generate simulated DO labels. Using these simulated labels, we implement a multi-population cognitive evolutionary search, where models, mirroring natural organisms, adaptively evolve to select relevant feature interactions within populations for different lake types and tasks. These models are not only capable of undergoing crossover and mutation mechanisms within intra-populations but also, albeit infrequently, engage in inter-population crossover. The second stage involves refining these models by retraining them with real observed labels. We have tested the performance of our NGCE strategy in predicting daily DO concentrations across a wide range of lakes in the Midwest, USA. These lakes, varying in size, depth, and trophic status, represent a broad spectrum of north temperate lakes. Our findings demonstrate that NGCE not only produces accurate predictions with few observed labels but also, through gene maps of models, reveals sophisticated phenological patterns of different lakes