bluuebunny/crossref_metadata_2025_split huggingface dataset:
Charge Transport in Halide Perovskite Single Crystals: Experimental and Theoretical Perspectives
Authors: Chen Yan‐Fang , Orgiu Emanuele 
Published: February 2019

AbstractHalide perovskite materials feature strong optical absorption, light carrier masses and, as a consequence, high charge‐carrier mobility, making them one of the candidates for next‐generation optoelectronic devices. This interesting class of materials exhibits unconventional properties that cannot be readily rationalized by traditional concepts. In this regard, single‐crystals of halide perovskites represent an ideal test bench to better understand the intrinsic properties of the material, building the foundation for further investigations of polycrystalline films and related nanoarchitectures. In this Minireview, we analyze charge carrier transport in organic halide perovskite single crystals, summarizing the current literature insights on this matter from theoretical and experimental perspectives.
Visible‐Light‐Driven, One‐pot Amide Synthesis Catalyzed by the B12 Model Complex under Aerobic Conditions
Authors: Tian Hui , Shimakoshi Hisashi , Ono Toshikazu , Hisaeda Yoshio 
Published: February 2019

AbstractInvited for this month's cover is the group of Prof. Dr. Hisashi Shimakoshi at Kyushu University, Japan. The front cover shows “le mariage” of an iridium complex and a vitamin B12 derivative with two wedding rings in the background. This collaboration of two complexes is induced by visible light in the presence of air to achieve green molecular transformations. This protocol was applied to the synthesis of amides from a wide range of trichlorinated organic compounds. Read the full text of the article at 10.1002/cplu.201800522.
Estimating age‐dependent survival when juveniles resemble females: Invasive ring‐necked parakeets as an example
Authors: Senar Juan Carlos , Arroyo Lluïsa , Ortega‐Segalerva Alba , Carrillo José G. , Tomás Xavier , Montalvo Tomas , Sanz‐Aguilar Ana 
Published: February 2019

AbstractMany species only show sexual dimorphism at the age of maturity, such that juveniles typically resemble females. Under these circumstances, estimating accurate age‐specific demographic parameters is challenging. Here, we propose a multievent model parameterization able to estimate age‐dependent survival using capture–recapture data with uncertainty in age and sex assignment of individuals. We illustrate this modeling approach with capture–recapture data from the ring‐necked parakeetPsittacula krameri. We analyzed capture, recapture, and resighting data (439 recaptures/resightings) of 156 ring‐necked parakeets tagged with neck collars in Barcelona city from 2003 to 2016 to estimate the juvenile and adult survival rate. Our models successfully estimated the survival probabilities of the different age classes considered. Survival probability was similar between adults (0.83, 95%CI = 0.77–0.87) and juveniles during their second (0.79, 95%CI = 0.58–0.87) and third winter (0.83, 95%CI = 0.65–0.88). The youngest juveniles (1st winter) showed a slightly lower survival (0.57, 95%CI = 0.37–0.79). Among adults, females showed a slightly higher survival than males (0.87, 95%CI = 0.78–0.93; and 0.80, 95%CI = 0.73–0.86, respectively). These high survival figures predict high population persistence in this species and urge management policies. The analysis also stresses the usefulness of multievent models to estimate juvenile survival when age cannot be fully ascertained.
Quantifying the links between land use and population growth rate in a declining farmland bird
Authors: Paquet Matthieu , Arlt Debora , Knape Jonas , Low Matthew , Forslund Pär , Pärt Tomas 
Published: February 2019

AbstractLand use is likely to be a key driver of population dynamics of species inhabiting anthropogenic landscapes, such as farmlands. Understanding the relationships between land use and variation in population growth rates is therefore critical for the management of many farmland species. Using 24 years of data of a declining farmland bird in an integrated population model, we examined how spatiotemporal variation in land use (defined as habitats with “Short” and “Tall” ground vegetation during the breeding season) and habitat‐specific demographic parameters relates to variation in population growth taking into account individual movements between habitats. We also evaluated contributions to population growth using transient life table response experiments which gives information on contribution of past variation of parameters and real‐time elasticities which suggests future scenarios to change growth rates. LTRE analyses revealed a clear contribution of Short habitats to the annual variation in population growth rate that was mostly due to fledgling recruitment, whereas there was no evidence for a contribution of Tall habitats. Only 18% of the variation in population growth was explained by the modeled local demography, the remaining variation being explained by apparent immigration (i.e., the residual variation). We discuss potential biological and methodological reasons for high contributions of apparent immigration in open populations. In line with LTRE analysis, real‐time elasticity analysis revealed that demographic parameters linked to Short habitats had a stronger potential to influence population growth rate than those of Tall habitats. Most particularly, an increase of the proportion of Short sites occupied by Old breeders could have a distinct positive impact on population growth. High‐quality Short habitats such as grazed pastures have been declining in southern Sweden. Converting low‐quality to high‐quality habitats could therefore change the present negative population trend of this, and other species with similar habitat requirements.
Inferring species richness using multispecies occupancy modeling: Estimation performance and interpretation
Authors: Guillera‐Arroita Gurutzeta , Kéry Marc , Lahoz‐Monfort José J. 
Published: February 2019

AbstractMultispecies occupancy models can estimate species richness from spatially replicated multispecies detection/non‐detection survey data, while accounting for imperfect detection. A model extension using data augmentation allows inferring the total number of species in the community, including those completely missed by sampling (i.e., not detected in any survey, at any site). Here we investigate the robustness of these estimates. We review key model assumptions and test performance via simulations, under a range of scenarios of species characteristics and sampling regimes, exploring sensitivity to the Bayesian priors used for model fitting. We run tests when assumptions are perfectly met and when violated. We apply the model to a real dataset and contrast estimates obtained with and without predictors, and for different subsets of data. We find that, even with model assumptions perfectly met, estimation of the total number of species can be poor in scenarios where many species are missed (>15%–20%) and that commonly used priors can accentuate overestimation. Our tests show that estimation can often be robust to violations of assumptions about the statistical distributions describing variation of occupancy and detectability among species, but lower‐tail deviations can result in large biases. We obtain substantially different estimates from alternative analyses of our real dataset, with results suggesting that missing relevant predictors in the model can result in richness underestimation. In summary, estimates of total richness are sensitive to model structure and often uncertain. Appropriate selection of priors, testing of assumptions, and model refinement are all important to enhance estimator performance. Yet, these do not guarantee accurate estimation, particularly when many species remain undetected. While statistical models can provide useful insights, expectations about accuracy in this challenging prediction task should be realistic. Where knowledge about species numbers is considered truly critical for management or policy, survey effort should ideally be such that the chances of missing species altogether are low.
Covariate and multinomial: Accounting for distance in movement in capture–recapture analyses
Authors: Guéry Loreleï , Rouan Lauriane , Descamps Sébastien , Bêty Joël , Fernández‐Chacón Albert , Gilchrist Grant , Pradel Roger 
Published: February 2019

AbstractMany biological quantities cannot be measured directly but rather need to be estimated from models. Estimates from models are statistical objects with variance and, when derived simultaneously, covariance. It is well known that their variance–covariance (VC) matrix must be considered in subsequent analyses. Although it is always preferable to carry out the proposed analyses on the raw data themselves, a two‐step approach cannot always be avoided. This situation arises when the parameters of a multinomial must be regressed against a covariate. The Delta method is an appropriate and frequently recommended way of deriving variance approximations of transformed and correlated variables. Implementing the Delta method is not trivial, and there is a lack of a detailed information on the procedure in the literature for complex situations such as those involved in constraining the parameters of a multinomial distribution. This paper proposes a how‐to guide for calculating the correctVCmatrices of dependant estimates involved in multinomial distributions and how to use them for testing the effects of covariates in post hoc analyses when the integration of these analyses directly into a model is not possible. For illustrative purpose, we focus on variables calculated in capture–recapture models, but the same procedure can be applied to all analyses dealing with correlated estimates with multinomial distribution and their variances and covariances.
Making use of multiple surveys: Estimating breeding probability using a multievent‐robust design capture–recapture model
Authors: Oosthuizen W. Chris , Pradel Roger , Bester Marthán N. , de Bruyn P. J. Nico 
Published: February 2019

AbstractIncreased environmental stochasticity due to climate change will intensify temporal variance in the life‐history traits, and especially breeding probabilities, of long‐lived iteroparous species. These changes may decrease individual fitness and population viability and is therefore important to monitor. In wild animal populations with imperfect individual detection, breeding probabilities are best estimated using capture–recapture methods. However, in many vertebrate species (e.g., amphibians, turtles, seabirds), nonbreeders are unobservable because they are not tied to a territory or breeding location. Although unobservable states can be used to model temporary emigration of nonbreeders, there are disadvantages to having unobservable states in capture–recapture models. The best solution to deal with unobservable life‐history states is therefore to eliminate them altogether. Here, we achieve this objective by fitting novel multievent‐robust design models which utilize information obtained from multiple surveys conducted throughout the year. We use this approach to estimate annual breeding probabilities of capital breeding female elephant seals (Mirounga leonina). Conceptually, our approach parallels a multistate version of the Barker/robust design in that it combines robust design capture data collected during discrete breeding seasons with observations made at other times of the year. A substantial advantage of our approach is that the nonbreeder state became “observable” when multiple data sources were analyzed together. This allowed us to test for the existence of state‐dependent survival (with some support found for lower survival in breeders compared to nonbreeders), and to estimate annual breeding transitions to and from the nonbreeder state with greater precision (where current breeders tended to have higher future breeding probabilities than nonbreeders). We used program E‐SURGE (2.1.2) to fit the multievent‐robust design models, with uncertainty in breeding state assignment (breeder, nonbreeder) being incorporated via a hidden Markov process. This flexible modeling approach can easily be adapted to suit sampling designs from numerous species which may be encountered during and outside of discrete breeding seasons.
Disease‐structuredN‐mixture models: A practical guide to model disease dynamics using count data
Authors: DiRenzo Graziella V. , Che‐Castaldo Christian , Saunders Sarah P. , Campbell Grant Evan H. , Zipkin Elise F. 
Published: February 2019

AbstractObtaining inferences on disease dynamics (e.g., host population size, pathogen prevalence, transmission rate, host survival probability) typically requires marking and tracking individuals over time. While multistate mark–recapture models can produce high‐quality inference, these techniques are difficult to employ at large spatial and long temporal scales or in small remnant host populations decimated by virulent pathogens, where low recapture rates may preclude the use of mark–recapture techniques. Recently developedN‐mixture models offer a statistical framework for estimating wildlife disease dynamics from count data.N‐mixture models are a type of state‐space model in which observation error is attributed to failing to detect some individuals when they are present (i.e., false negatives). The analysis approach uses repeated surveys of sites over a period of population closure to estimate detection probability. We review the challenges of modeling disease dynamics and describe howN‐mixture models can be used to estimate common metrics, including pathogen prevalence, transmission, and recovery rates while accounting for imperfect host and pathogen detection. We also offer a perspective on future research directions at the intersection of quantitative and disease ecology, including the estimation of false positives in pathogen presence, spatially explicit disease‐structuredN‐mixture models, and the integration of other data types with count data to inform disease dynamics. Managers rely on accurate and precise estimates of disease dynamics to develop strategies to mitigate pathogen impacts on host populations. At a time when pathogens pose one of the greatest threats to biodiversity, statistical methods that lead to robust inferences on host populations are critically needed for rapid, rather than incremental, assessments of the impacts of emerging infectious diseases.
Efficient Bayesian analysis of occupancy models with logit link functions
Authors: Clark Allan E. , Altwegg Res 
Published: February 2019

AbstractOccupancy models (Ecology, 2002; 83: 2248) were developed to infer the probability that a species under investigation occupies a site. Bayesian analysis of these models can be undertaken using statistical packages such as WinBUGS, OpenBUGS, JAGS, and more recently Stan, however, since these packages were not developed specifically to fit occupancy models, one often experiences long run times when undertaking an analysis. Bayesian spatial single‐season occupancy models can also be fit using the R package stocc. The approach assumes that the detection and occupancy regression effects are modeled using probit link functions. The use of the logistic link function, however, is algebraically more tractable and allows one to easily interpret the coefficient effects of an estimated model by using odds ratios, which is not easily done for a probit link function for models that do not include spatial random effects. We develop a Gibbs sampler to obtain posterior samples from the posterior distribution of the parameters of various occupancy models (nonspatial and spatial) when logit link functions are used to model the regression effects of the detection and occupancy processes. We apply our methods to data extracted from the 2nd Southern African Bird Atlas Project to produce a species distribution map of the Cape weaver (Ploceus capensis) and helmeted guineafowl (Numida meleagris) for South Africa. We found that the Gibbs sampling algorithm developed produces posterior samples that are identical to those obtained when using JAGS and Stan and that in certain cases the posterior chains mix much faster than those obtained when using JAGS, stocc, and Stan. Our algorithms are implemented in the R package, Rcppocc. The software is freely available and stored on GitHub (https://github.com/AllanClark/Rcppocc).
An Overview of Portuguese Olive Oils and Table Olives with Protected Designation of Origin
Authors: Albuquerque Tânia Gonçalves , Costa Helena S. , Oliveira Maria Beatriz P. P. 
Published: February 2019

Over the years, consumers’ interest in the diet and health relationship has increased with a demand for high quality foods. To protect consumers, but also producers from unfair practices, European Union (EU) has launched legislation on different EU quality schemes, namely Protected Designation of Origin (PDO), Protected Geographical Indications (PGI), and Traditional Speciality Guaranteed (TSG). This work provides an overview of research concerning Portuguese PDO olive oils and table olives. EU quality schemes applied to agricultural products and foodstuffs are increasing over the years, Portugal being the fourth European country with the highest percentage of registered foods. Up to now, Portugal has registered six olive oils and two table olives as PDO. There is a lack of physicochemical data for Portuguese PDO olive products, especially for table olives. Nonetheless, differences linked to the origin of the olive oils are reported, including within the same region of origin. For instance, a range between 95.9 and 260 mg kg−1 for α‐tocopherol was reported for PDO Azeite de Trás‐os‐Montes, while for PDO Azeites do Norte Alentejano it varied from 92.6 to 198 mg kg−1. Further studies, especially concerning parameters that allow confirming the authenticity and origin of Portuguese PDO olive oils and table olives, are crucial.Practical Applications: Six olive oils and two table olives from Portugal are already registered with PDO. Phytochemical data for these products is scarce. Further studies to evaluate authenticity are needed.Of the table olives and olive oils already registered with Protected Designation of Origin (PDO), there are eight products belonging to the five main regions of Portugal (Trás‐os Montes, Beira Litoral, Beira Interior, Ribatejo, and Alentejo). Furthermore, these PDO products are linked to the history and cultural heritage of these places, being crucial for some local producers and for consumers.
Use of Protease from Seabass Pyloric Caeca in Combination with Repeated Freeze–Thawing Cycles Increases the Production Efficiency of Virgin Coconut Oil
Authors: Patil Umesh , Benjakul Soottawat 
Published: February 2019

Virgin coconut oil (VCO) is separated from coconut milk using partially purified protease from seabass pyloric caeca (PPSP) in combination with different treatments including micro‐fluidization, chill–thawing, and freeze–thawing. The lowest VCO yield is obtained for coconut milk homogenized at 4000 psi, followed by hydrolysis using PPSP at the level of 5 units g−1 proteins. Conversely, the higher VCO yield is obtained from non‐homogenized and unhydrolyzed coconut milk (p < 0.05). Coconut milk hydrolyzed by PPSP at 10 units g−1 protein, followed by freeze–thawing shows the highest yield among all the samples (p < 0.05). VCO yield increases as chill–thawing cycles of hydrolyzed coconut milk increases up to 5 cycles (p < 0.05). A similar trend is found in sample subjected to hydrolysis, followed by freeze–thawing. Hydrolysis by PPSP, followed by freeze–thawing of 5 cycles, yields the highest yield of VCO (98.6%). No marked difference is observed in fatty acid profile, moisture content, free fatty acid content, and oxidative stability of all VCO obtained, regardless of subsequent chill–thawing and freeze–thawing applied. All VCO samples are in the range of APCC standards. Thus, combined treatment including hydrolysis using PPSP followed by freeze–thawing (5 cycles) is a powerful method for extraction of VCO, in which high yield and prime quality could be gained.Practical Applications: In VCO production, the cost of commercial enzyme and yield of VCO are of major concern. Therefore, a cheap source of proteases, particularly fish processing byproducts, can be a promising alternative for VCO production. Additionally, a combined method, especially enzymatic hydrolysis of coconut milk followed by freeze–thawing, can be a practical process to obtain VCO with increased yield. The information on combined methods can be of benefit in manufacturing VCO with reduced cost and high yield.The use of protease from seabass pyloric caeca in combination with repeated freeze‐thawing cycles increases the production efficiency of virgin coconut oil.
Ketamine infusion for 96 hr after thoracotomy: Effects on acute and persistent pain
Authors: Chumbley Gillian M. , Thompson Lindsey , Swatman Joanna E. , Urch Catherine 
Published: February 2019

AbstractIntroductionPain which persists after thoracotomy is well recognized, and activation of the N‐methyl‐d‐aspartate (NMDA) receptor could be a contributing factor. This study sought to establish whether ketamine given peri‐operatively could reduce persistent post‐surgical pain.Trial designDouble‐blind, randomized, placebo‐controlled trial comparing low‐dose intravenous ketamine and saline placebo.MethodsSeventy patients undergoing thoracotomy were randomized to receive either intravenous ketamine (0.1 mg kg−1 hr−1) or saline placebo for 96 hr, starting 10 min prior to surgery. A bolus dose of 0.1 mg/kg of ketamine/placebo was given prior to starting the infusion. Post‐operative analgesia consisted of either an epidural infusion or patient‐controlled analgesia (PCA), +/− a paravertebral infusion of local anaesthetic. Pain scores and opioid consumption were collected at 24 and 48 hr after surgery. Patients completed numeric pain scores (NPS), modified Brief Pain Inventory (BPI), the short form Leeds Assessment of Neuropathic Symptoms and Signs (S‐Lanss) at baseline, 6 weeks, 3, 6 and 12 months after surgery.ResultsThere were no significant differences in post‐operative pain, except the ketamine group reported less pain at rest 48 hr after surgery (p = 0.03). The ketamine group requested significantly less morphine via PCA in the first 24 hr (p = 0.03). There were no differences in pain measures or opioid consumption at 6 weeks, 3, 6 or 12 months. Patients in the ketamine group were more lightheaded (p = 0.02) and experienced more vivid dreams (p = 0.001).ConclusionsKetamine reduced opioid consumption compared to placebo after surgery, but we were unable to detect any differences in persistent post‐surgical pain between the groups.SignificanceThis study adds to the growing body of evidence advocating the use of ketamine to reduce opioid consumption. No previous studies of peri‐operative ketamine have followed patients for a year after thoracotomy. This study found no reduction in persistent post‐surgical pain.