A robust Bayesian analysis of the impact of policy decisions on crop rotations.

We analyse the impact of a policy decision on crop rotations, using the imprecise land use model that was developed by the authors in earlier work. A specific challenge in crop rotation models is that farmer’s crop choices are driven by both policy changes and external non-stationary factors, such as rainfall, temperature and agricultural input and output prices. Such dynamics can be modelled by a non-stationary stochastic process, where crop transition probabilities are multinomial logistic functions of such external factors. We use a robust Bayesian approach to estimate the parameters of our model, and validate it by comparing the model response with a non-parametric estimate, as well as by cross validation. Finally, we use the resulting predictions to solve a hypothetical yet realistic policy problem

The management of peat and alkali soils in Iowa

How to handle peat soils and how to reclaim so-called, alkali spots are real problems to many farmers in north-central Iowa, large numbers of whom have found thru hitter experience the futility of attempting to grow crops on such land without special methods of treatment. While drainage is generally recognized as the basic treatment necessary if these soils are to be successfully cropped, other treatments in addition have been found to be essential if satisfactory crop yields are to be secured on peat and alkali areas. Even with the very best system of management, several years may be required before peat soils can be utilized on a distinctly profitable basis. This is especially true of newly-drained peat land. So-called alkali areas may be more quickly reclaimed and made productive, but even these soils may not give satisfactory crop yields the first year after drainage

Advancing Cancer Prevention Practice Facilitation Work in Rural Primary Care During COVID-19

COVID-19 and the response to slow the virus spread in West Virginia (WV), including a statewide stay-at-home order, presented challenges to rural primary care clinics on the frontlines. These challenges affected critical quality improvement work, including cancer screening services. In this commentary, the authors present the results of a survey of WV primary care practices that highlight potential long-term implications and identifies opportunities for practice facilitators to partner with rural primary care clinics to address them

Language Mapping in Multilingual Patients: Electrocorticography and Cortical Stimulation During Naming

Multilingual patients pose a unique challenge when planning epilepsy surgery near language cortex because the cortical representations of each language may be distinct. These distinctions may not be evident with routine electrocortical stimulation mapping (ESM). Electrocorticography (ECoG) has recently been used to detect task-related spectral perturbations associated with functional brain activation. We hypothesized that using broadband high gamma augmentation (HGA, 60–150 Hz) as an index of cortical activation, ECoG would complement ESM in discriminating the cortical representations of first (L1) and second (L2) languages. We studied four adult patients for whom English was a second language, in whom subdural electrodes (a total of 358) were implanted to guide epilepsy surgery. Patients underwent ECoG recordings and ESM while performing the same visual object naming task in L1 and L2. In three of four patients, ECoG found sites activated during naming in one language but not the other. These language-specific sites were not identified using ESM. In addition, ECoG HGA was observed at more sites during L2 versus L1 naming in two patients, suggesting that L2 processing required additional cortical resources compared to L1 processing in these individuals. Post-operative language deficits were identified in three patients (one in L2 only). These deficits were predicted by ECoG spectral mapping but not by ESM. These results suggest that pre-surgical mapping should include evaluation of all utilized languages to avoid post-operative functional deficits. Finally, this study suggests that ECoG spectral mapping may potentially complement the results of ESM of language

Inorganic carbon and pH dependency of Trichodesmium's photosynthetic rates.

We established the relationship between photosynthetic carbon fixation rates and pH, CO2 and HCO3- concentrations in the diazotroph Trichodesmium erythraeum IMS101. Inorganic 14C-assimilation was measured in TRIS-buffered ASW medium where the absolute and relative concentrations of CO2, pH and HCO3- were manipulated. First, we varied the total dissolved inorganic carbon concentration (TIC) (< 0 to ~ 5 mM) at constant pH, so ratios of CO2 and HCO3- remained relatively constant. Second, we varied pH (~ 8.54 to 7.52) at constant TIC, so CO2 increased whilst HCO3- declined. We found that 14C-assimilation could be described by the same function of CO2 for both approaches but showed different dependencies on HCO3- when pH was varied at constant TIC than when TIC was varied at constant pH. A numerical model of Trichodesmium's CCM showed carboxylation rates are modulated by HCO3- and pH. The decrease in Ci assimilation at low CO2, when TIC was varied, is due to HCO3- uptake limitation of the carboxylation rate. Conversely, when pH was varied, Ci assimilation declined due to a high-pH mediated increase in HCO3- and CO2 leakage rates, potentially coupled to other processes (uncharacterised within the CCM model) that restrict Ci assimilation rates under high-pH conditions

Multi-Regional Adaptation in Human Auditory Association Cortex

In auditory cortex, neural responses decrease with stimulus repetition, known as adaptation. Adaptation is thought to facilitate detection of novel sounds and improve perception in noisy environments. Although it is well established that adaptation occurs in primary auditory cortex, it is not known whether adaptation also occurs in higher auditory areas involved in processing complex sounds, such as speech. Resolving this issue is important for understanding the neural bases of adaptation and to avoid potential post-operative deficits after temporal lobe surgery for treatment of focal epilepsy. Intracranial electrocorticographic recordings were acquired simultaneously from electrodes implanted in primary and association auditory areas of the right (non-dominant) temporal lobe in a patient with complex partial seizures originating from the inferior parietal lobe. Simple and complex sounds were presented in a passive oddball paradigm. We measured changes in single-trial high-gamma power (70–150 Hz) and in regional and inter-regional network-level activity indexed by cross-frequency coupling. Repetitive tones elicited the greatest adaptation and corresponding increases in cross-frequency coupling in primary auditory cortex. Conversely, auditory association cortex showed stronger adaptation for complex sounds, including speech. This first report of multi-regional adaptation in human auditory cortex highlights the role of the non-dominant temporal lobe in suppressing neural responses to repetitive background sounds (noise). These results underscore the clinical utility of functional mapping to avoid potential post-operative deficits including increased listening difficulties in noisy, real-world environments

A robust Bayesian analysis of the impact of policy decisions on crop rotations

We analyse the impact of a policy decision on crop rotations, using the imprecise land use model that was developed by the authors in earlier work. A specific challenge in crop rotation models is that farmer’s crop choices are driven by both policy changes and external non-stationary factors, such as rainfall, temperature and agricultural input and output prices. Such dynamics can be modelled by a non-stationary stochastic process, where crop transition probabilities are multinomial logistic functions of such external factors. We use a robust Bayesian approach to estimate the parameters of our model, and validate it by comparing the model response with a non-parametric estimate, as well as by cross validation. Finally, we use the resulting predictions to solve a hypothetical yet realistic policy problem