Strong Positive Bias Research Articles

Coupling the Common Land Model to ECHAM5 Atmospheric General Circulation Model

The ECHAM5 model is coupled with the widely used Common Land Model (CoLM). ECHAM5 is a state-of-the-art atmospheric general circulation model incorporated into the integrated weather and climate model of the Chinese Academy of Meteorological Sciences (CAMS-CSM). Land surface schemes in ECHAM5 are simple and do not provide an adequate representation of the vegetation canopy and snow/frozen soil processes. Two AMIP (Atmosph-eric Model Intercomparison Project)-type experiments using ECHAM5 and ECHAM5-CoLM are run over 30 yr and the results are compared with reanalysis and observational data. It is found that the pattern of land surface temperature simulated by ECHAM5-CoLM is significantly improved relative to ECHAM5. Specifically, the cold bias over Eurasia is removed and the root-mean-square error is reduced in most regions. The seasonal variation in the zonal mean land surface temperature and the in situ soil temperature at 20- and 80-cm depths are both better simulated by ECHAM5-CoLM. ECHAM5-CoLM produces a more reasonable spatial pattern in the soil moisture content, whereas ECHAM5 predicts much drier soils. The seasonal cycle of soil moisture content from ECHAM5-CoLM is a better match to the observational data in six specific regions. ECHAM5-CoLM reproduces the observed spatial patterns of both sensible and latent heat fluxes. The strong positive bias in precipitation over land is reduced in ECHAM5-CoLM, especially over the southern Tibetan Plateau and middle–lower reaches of the Yangtze River during the summer monsoon rainy season.

Bias in estimates of the classic and incidence-based Jaccard similarity indices: insights from assemblage simulation

Similarity indices are often used for measuring b-diversity and as the starting point of multivariate analysis. In this study, I used simulation to examine the direction and amount of bias in estimates of two similarity indices, Jaccard Coefficient (J) and incidence-based J (J). I design a novel simulation to generate three sets of assemblages that vary in species richness, species-occurrence distributions, and b-diversity. I characterized assemblage differences with the ratio of [proportion of rare species in all shared species / proportion of rare species in all unshared species] (i.e., PRss/PRus) and the Pearson’s correlation in the probabilities of shared species between two assemblages (i.e., share-species correlation). I found that J was subject to strong positive or negative bias, depending on PRss/PRus. J was mainly subject to negative bias, which varied with share-species correlation. In both indices, bias varied substantially from one pair of assemblages to another and among datasets. The high variation in the bias across different comparisons of assemblages may compromise b-diversity estimation established at low sampling efforts based on the two indices or their variants.

Invited Commentary

Invited Commentary

Evaluation of a Chemiluminescent Immunoassay for Measurement of Equine Insulin

BackgroundMany diagnostic tests for insulin dysregulation use reference intervals established with an insulin radioimmunoassay (RIA) that is no longer available. A chemiluminescent immunoassay (CLIA) is commonly used for the measurement of serum insulin concentration in clinical practice but requires further validation, especially at clinically relevant reference intervals.ObjectivesTo evaluate the CLIA for measurement of equine insulin and compare it to the previously validated, but now unavailable RIA.SamplesEquine serum samples (n = 78) from clinical and experimental studies.MethodsIn this experimental study, performance of the CLIA was evaluated using standard variables, including comparison with the RIA. Continuous and binary outcomes were analyzed.ResultsThe CLIA showed good intra‐assay (coefficient of variation [CV], 1.8–2.4%) and interassay (CV, 3–7.1%) precision. Acceptable recovery on dilution (100 ± 10%) was achieved only at dilutions <1:1. Recovery on addition was acceptable. Comparison of the CLIA and RIA showed strong positive correlation (r = 0.91–0.98), with fixed and proportional bias. At 3 diagnostic cutoffs, sensitivity of CLIA compared with RIA ranged from 67 to 100% and specificity from 96 to 100%.Conclusions and Clinical ImportanceThe CLIA is a highly repeatable assay which is suitable for within‐ and between‐horse comparisons. Dilution of high concentration samples should be performed with charcoal‐stripped serum (CSS) and at the lowest dilution factor possible. At concentrations commonly used for diagnosis of insulin dysregulation (≤100 μIU/mL), results from the CLIA tend to be lower than from the RIA and should be interpreted accordingly. Further standardization of equine insulin assays is required.

AerGOM, an improved algorithm for stratospheric aerosol extinction retrieval from GOMOS observations – Part 2: Intercomparisons

Abstract. AerGOM is a retrieval algorithm developed for the GOMOS instrument onboard Envisat as an alternative to the operational retrieval (IPF). AerGOM enhances the quality of the stratospheric aerosol extinction retrieval due to the extension of the spectral range used, refines the aerosol spectral parameterization, the simultaneous inversion of all atmospheric species as well as an improvement of the Rayleigh scattering correction. The retrieval algorithm allows for a good characterization of the stratospheric aerosol extinction for a wide range of wavelengths.In this work, we present the results of stratospheric aerosol extinction comparisons between AerGOM and various spaceborne instruments (SAGE II, SAGE III, POAM III, ACE-MAESTRO and OSIRIS) for different wavelengths. The aerosol extinction intercomparisons for λ &lt; 700 nm and above 20 km show agreements with SAGE II version 7 and SAGE III version 4.0 within ±15 % and ±45 %, respectively. There is a strong positive bias below 20 km at λ &lt; 700 nm, which suggests that cirrus clouds at these altitudes have a large impact on the extinction values. Comparisons performed with GOMOS IPF v6.01 alongside AerGOM show that at short wavelengths and altitudes below 20 km, IPF retrievals are more accurate when evaluated against SAGE II and SAGE III but are much less precise than AerGOM. A modified aerosol spectral parameterization can improve AerGOM in this spectral and altitude range and leads to results that have an accuracy similar to IPF retrievals. Comparisons of AerGOM aerosol extinction coefficients with OSIRIS and SAGE III measurements at wavelengths larger than 700 nm show a very large negative bias at altitudes above 25 km. Therefore, the use of AerGOM aerosol extinction data is not recommended for λ &gt; 700 nm.Due to the unique observational technique of GOMOS, some of the results appear to be dependent on the star occultation parameters such as star apparent temperature and magnitude, solar zenith angle and latitude of observation. A systematic analysis is carried out to identify biases in the dataset, using the various spaceborne instruments as references. The quality of the aerosol retrieval is mainly influenced by the star magnitude, as well as star temperature to a lesser degree. To ensure good-quality profiles, we suggest to select occultations performed with star magnitude M &lt; 2.5 and star temperature T &gt; 6 × 103 K. Stray-light contamination is negligible for extinction coefficients below 700 nm using occultations performed with a solar zenith angle &gt; 110° but becomes important at larger wavelengths. Comparison of AerGOM results in the tropics shows an enhanced bias below 20 km that seem to confirm cirrus clouds as its cause. There are also differences between mid-latitude and tropical observations that cannot yet be explained, with a bias difference of up to 25 %.This bias characterization is extremely important for data users and might prove valuable for the production of unbiased long-term merged dataset.

A surface reflectance scheme for retrieving aerosol optical depth over urban surfaces in MODIS Dark Target retrieval algorithm

Abstract. The MODerate resolution Imaging Spectroradiometer (MODIS) instruments, aboard the two Earth Observing System (EOS) satellites Terra and Aqua, provide aerosol information with nearly daily global coverage at moderate spatial resolution (10 and 3 km). Almost 15 years of aerosol data records are now available from MODIS that can be used for various climate and air-quality applications. However, the application of MODIS aerosol products for air-quality concerns is limited by a reduction in retrieval accuracy over urban surfaces. This is largely because the urban surface reflectance behaves differently than that assumed for natural surfaces. In this study, we address the inaccuracies produced by the MODIS Dark Target (MDT) algorithm aerosol optical depth (AOD) retrievals over urban areas and suggest improvements by modifying the surface reflectance scheme in the algorithm. By integrating MODIS Land Surface Reflectance and Land Cover Type information into the aerosol surface parameterization scheme for urban areas, much of the issues associated with the standard algorithm have been mitigated for our test region, the continental United States (CONUS). The new surface scheme takes into account the change in underlying surface type and is only applied for MODIS pixels with urban percentage (UP) larger than 20 %. Over the urban areas where the new scheme has been applied (UP &gt; 20 %), the number of AOD retrievals falling within expected error (EE %) has increased by 20 %, and the strong positive bias against ground-based sun photometry has been eliminated. However, we note that the new retrieval introduces a small negative bias for AOD values less than 0.1 due to the ultra-sensitivity of the AOD retrieval to the surface parameterization under low atmospheric aerosol loadings. Global application of the new urban surface parameterization appears promising, but further research and analysis are required before global implementation.

Publication Bias in the Returns to R&amp;D Literature

The returns to R&D literature is large and has been surveyed on several occasions. We complement previous surveys by using formal meta analytic techniques to analyse publication bias. We find evidence consistent with a strong positive bias in the part of the literature that controls for unobserved firm fixed effects. The reason may be that fixed effects specifications are particularly susceptible to measurement errors and therefore have a high probability of producing implausibly low return estimates. Implausible estimates are likely to be filtered out before being reported, and our analysis suggest that 26% of a hypothetical complete literature is missing. Future reviews should take into account that the full effect of negative specifications biases may be masked by reporting and publication bias.

Tropical Indian Ocean surface salinity bias in Climate Forecasting System coupled models and the role of upper ocean processes

In the present study sea surface salinity (SSS) biases and seasonal tendency over the Tropical Indian Ocean (TIO) in the coupled models [Climate Forecasting System version 1 (CFSv1) and version 2 (CFSv2)] are examined with respect to observations. Both CFSv1 and CFSv2 overestimate SSS over the TIO throughout the year. CFSv1 displays improper SSS seasonal cycle over the Bay of Bengal (BoB), which is due to weaker model precipitation and improper river runoff especially during summer and fall. Over the southeastern Arabian Sea (AS) weak horizontal advection associated with East Indian coastal current during winter limits the formation of spring fresh water pool. On the other hand, weaker Somali jet during summer results for reduced positive salt tendency in the central and eastern AS. Strong positive precipitation bias in CFSv1 over the region off Somalia during winter, weaker vertical mixing and absence of horizontal salt advection lead to unrealistic barrier layer during winter and spring. The weaker stratification and improper spatial distribution of barrier layer thickness (BLT) in CFSv1 indicate that not only horizontal flux distribution but also vertical salt distribution displays large discrepancies. Absence of fall Wyrtki jet and winter equatorial currents in this model limit the advection of horizontal salt flux to the eastern equatorial Indian Ocean. The associated weaker stratification in eastern equatorial Indian Ocean can lead to deeper mixed layer and negative Sea Surface Temperature (SST) bias, which in turn favor positive Indian Ocean Dipole bias in CFSv1. It is important to note that improper spatial distribution of barrier layer and stratification can alter the air–sea interaction and precipitation in the models. On the other hand CFSv2 could produce the seasonal evolution and spatial distribution of SSS, BLT and stratification better than CFSv1. However CFSv2 displays positive bias in evaporation over the whole domain and negative bias in precipitation over the BoB and equatorial Indian Ocean, resulting net reduction in the fresh water availability. This net reduction in fresh water forcing and the associated weaker stratification lead to deeper (than observed) mixed layer depth and is primarily responsible for the cold SST bias in CFSv2. However overall improvement of mean salinity distribution in CFSv2 is about 30 % and the mean error has reduced by more than 1 psu over the BoB. This improvement is mainly due to better fresh water forcing and model physics. Realistic run off information, better ocean model and high resolution in CFSv2 contributed for the improvement. Further improvement can be achieved by reducing biases in the moisture flux and precipitation.

The contribution of context and contour to perceived belief in polar questions

In the past decades, we have advanced significantly in our knowledge of intonational meaning, but few studies have tested experimentally the way in which discourse contexts affect intonational meaning. In this work we were specifically interested in how listeners use both intonation and discourse context to infer information about speaker belief states. We examined the effect of five bias types on two intonation contours used for polar questions (PQs) in Puerto Rican Spanish (PRS). The bias types consisted of unbiased, mild positive bias, strong positive bias and mismatch bias contexts. The intonation contours had been previously claimed to differ in the belief state information they convey – ¡H*L% is known to mark utterances as PQs without encoding specific belief state on the part of the speaker, while L*HL% is known to convey a state of disbelief on the part of the speaker (Armstrong, 2010). We hypothesized that the lack of belief and the presence of disbelief for these contours, respectively, would be perceived by listeners when these contours were heard in an unbiased context. We also predicted that listeners would rely on contextual bias more for the ¡H*L% contour than the L*HL% contour, and that the disbelief meaning would persist regardless of discourse context. Perceived belief scores were analyzed, and results show that different bias types affected perceived belief scores in different ways. Mild positive bias did not seem to affect perceived belief for the two contours, while strong positive bias and mismatch bias did. Since L*HL% conventionally conveys disbelief, a reversal effect was shown when it was heard in the strong belief context. Participants’ comments indicate that in such cases, an ironic interpretation of the contour is available. These results, in addition to the comments provided by participants, show that perceived belief will depend both on the type of contextual bias, as well as the type of information conveyed intonationally. This work provides more evidence for the dynamic relationship between specific context types and intonation contours that differ in terms of the amount and type of meaning they convey.

Regional climate hindcast simulations within EURO-CORDEX: evaluation of a WRF multi-physics ensemble

Abstract. In the current work we present six hindcast WRF (Weather Research and Forecasting model) simulations for the EURO-CORDEX (European Coordinated Regional Climate Downscaling Experiment) domain with different configurations in microphysics, convection and radiation for the time period 1990–2008. All regional model simulations are forced by the ERA-Interim reanalysis and have the same spatial resolution (0.44°). These simulations are evaluated for surface temperature, precipitation, short- and longwave downward radiation at the surface and total cloud cover. The analysis of the WRF ensemble indicates systematic temperature and precipitation biases, which are linked to different physical mechanisms in the summer and winter seasons. Overestimation of total cloud cover and underestimation of downward shortwave radiation at the surface, mostly linked to the Grell–Devenyi convection and CAM (Community Atmosphere Model) radiation schemes, intensifies the negative bias in summer temperatures over northern Europe (max −2.5 °C). Conversely, a strong positive bias in downward shortwave radiation in summer over central (40–60%) and southern Europe mitigates the systematic cold bias over these regions, signifying a typical case of error compensation. Maximum winter cold biases are over northeastern Europe (−2.8 °C); this location suggests that land–atmosphere rather than cloud–radiation interactions are to blame. Precipitation is overestimated in summer by all model configurations, especially the higher quantiles which are associated with summertime deep cumulus convection. The largest precipitation biases are produced by the Kain–Fritsch convection scheme over the Mediterranean. Precipitation biases in winter are lower than those for summer in all model configurations (15–30%). The results of this study indicate the importance of evaluating not only the basic climatic parameters of interest for climate change applications (temperature and precipitation), but also other components of the energy and water cycle, in order to identify the sources of systematic biases, possible compensatory or masking mechanisms and suggest pathways for model improvement.

Fluidized bed desliming in fine particle flotation – Part III flotation of difficult to clean coal

A novel flotation system was used to process fine coal feeds supplied from coal preparation plants. The system consisted of an inverted fluidized bed arranged above a system of inclined channels. High fluidization (wash water) fluxes were imposed through a distributor enclosing the free-surface, producing strong positive bias of up to 2.4cm/s, ideal for desliming. High gas fluxes of up to 2.6cm/s, in excess of the flooding condition, were also imposed. The presence of the inclined channels prevented the entrainment of gas bubbles into the tailings stream. This paper, which is the third in a series, examines, for the first time, the hydrodynamic performance of this system on two actual plant feeds, each known to be difficult to wash. The first feed was a poorly liberated coal with particle size <260μm and 69% feed ash. The second was a well liberated coal with nominal size <125μm and 83% less than 38μm. The product ash was shown to decrease significantly with an increasing fluidization flux to gas flux ratio. The single stage flotation system demonstrated a performance capable of matching the Tree Flotation Curve with some cases in fact surpassing this result.

An Observation-Based Investigation of Nudging in WRF for Downscaling Surface Climate Information to 12-km Grid Spacing

AbstractPrevious research has demonstrated the ability to use the Weather Research and Forecasting model (WRF) and contemporary dynamical downscaling methods to refine global climate modeling results to a horizontal grid spacing of 36 km. Environmental managers and urban planners have expressed the need for even finer resolution in projections of surface-level weather to take into account local geophysical and urbanization patterns. In this study, WRF as previously applied at 36-km grid spacing is used with 12-km grid spacing with one-way nesting to simulate the year 2006 over the central and eastern United States. The results at both resolutions are compared with hourly observations of surface air temperature, humidity, and wind speed. The 12- and 36-km simulations are also compared with precipitation data from three separate observation and analysis systems. The results show some additional accuracy with the refinement to 12-km horizontal grid spacing, but only when some form of interior nudging is applied. A positive bias in precipitation found previously in the 36-km results becomes worse in the 12-km simulation, especially without the application of interior nudging. Model sensitivity testing shows that 12-km grid spacing can further improve accuracy for certain meteorological variables when alternate physics options are employed. However, the strong positive bias found for both surface-level water vapor and precipitation suggests that WRF as configured here may have an unbalanced hydrologic cycle that is returning moisture from land and/or water bodies to the atmosphere too quickly.

The ability of two age composition error distributions to estimate selectivity and spawning stock biomass in simulated stock assessments

A simulation study was conducted that examined two different error distributions for age composition data; the multinomial and the adjusted lognormal. Across 24 different simulation cases, and 4800 total data inputs, the multinomial error distribution consistently outperformed the adjusted lognormal error distribution, even when the true error was generated from the adjusted lognormal distribution. Both error distributions had a tendency to overestimate spawning stock biomass, but the bias was more severe for the adjusted lognormal. The only scenario in which the adjusted lognormal performed better was when selectivity was mis-specified; in this circumstance, the strong positive bias associated with the adjusted lognormal compensated for model runs that forced flat selectivity when selectivity was truly domed. Model selection criteria were overly sensitive when using the adjusted lognormal error. The utility of the adjusted lognormal error distribution in stock assessments is significantly diminished by the biased nature of the estimator, high variability of estimates, and inability to properly identify the correct selectivity pattern. Stock assessments that estimate domed selectivity patterns should have simulations conducted to evaluate if this bias is present. This can be accomplished by simulating data according to the error distributions used within the stock assessment and evaluating biases in estimates of selectivity and spawning stock biomass.

Fluidized bed desliming in fine particle flotation – Part I

This is the first of a series of publications concerned with a novel system that transforms the hydrodynamics of flotation. This system, referred to as a Reflux Flotation Cell, consists of a vertical flotation zone, with a system of parallel inclined channels below. The system is enclosed at the top by a fluidization distributor, while a central port is used to discharge the overflow product. The inclined channels located below the vertical section enhance the segregation of the bubbles from the tailings flow, permitting separations to be conducted at bubble surface fluxes well beyond the normal flooding condition, while also permitting extreme wash water fluxes. The system hydrodynamics produces spherical bubbly-foam, with a bubble volume fraction of order 0.5, ideal for counter-current washing, and hence desliming.This paper addresses two objectives. The first concerns the fluidization boundary condition at the top of the device. We identify for the first time a conundrum that arises when Drift Flux theory and fluidization theory are used to describe the effect of wash water addition in flotation. A subtle but nevertheless significant change in the predicted bias flux arises when the system is formally fluidized, resulting in the wash water reporting with the overflow, and hence failing to provide the desired desliming. Our experimental work, however, demonstrated that the applied fluidization leads to strong positive bias, with a downwards liquid flux and in turn powerful desliming of hydrophilic particles. Indeed the system behaved as though the wash water was introduced below rather than at the upper boundary.The second, and most important objective was to assess the system hydrodynamics with respect to extreme gas and wash water fluxes using firstly a particle-free system, and secondly assess the desliming achievable using a system containing hydrophilic particles. Thus in Part I the system was free of hydrophobic particles. The enhanced bubble–liquid segregation arising from the system of inclined channels permitted very high gas fluxes, sufficient to achieve a bubble surface flux of 144m2/m2s, well beyond the theoretical flooding limit of ~100m2/m2s (Wace et al., 1968). This high bubble surface flux was especially significant given this occurred during the application of extreme bias fluxes, as high as 2.5cm/s passing downwards. Experiments involving a silica feed were used to quantify the performance of the desliming, covering extreme gas and fluidization (wash) water fluxes. Silica rejection from the product exceeded 99%.

Space-based passive microwave soil moisture retrievals and the correction for a dynamic open water fraction

Abstract. The large observation footprint of low-frequency satellite microwave emissions complicates the interpretation of near-surface soil moisture retrievals. While the effect of sub-footprint lateral heterogeneity is relatively limited under unsaturated conditions, open water bodies (if not accounted for) cause a strong positive bias in the satellite-derived soil moisture retrieval. This bias is generally assumed static and associated with large, continental lakes and coastal areas. Temporal changes in the extent of smaller water bodies as small as a few percent of the sensor footprint size, however, can cause significant and dynamic biases. We analysed the influence of such small open water bodies on near-surface soil moisture products derived from actual (non-synthetic) data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) for three areas in Oklahoma, USA. Differences between on-ground observations, model estimates and AMSR-E retrievals were related to dynamic estimates of open water fraction, one retrieved from a global daily record based on higher frequency AMSR-E data, a second derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and a third through inversion of the radiative transfer model, used to retrieve soil moisture. The comparison demonstrates the presence of relatively small areas (&lt;0.05) of open water in or near the sensor footprint, possibly in combination with increased, below-critical vegetation density conditions (optical density &lt;0.8), which contribute to seasonally varying biases in excess of 0.2 (m3 m−3) soil water content. These errors need to be addressed, either through elimination or accurate characterisation, if the soil moisture retrievals are to be used effectively in a data assimilation scheme.

Mobility, Context and Cloud

In this paper we pursue the context-aware paradigm in a distributed mobile environment. Context-awareness plays a significant role in the domain of implicit human computer interaction and we present an intelligent context-aware meeting room application. The distributed mobile application consists of multiple mobile operating system clients, a Google Android based presenter that, through proximity technology, communicates with a server in the meeting room, and a Google Cloud backend server. Over 40 users have evaluated the application. Results show that the context aware meeting room was well received by users who displayed a strong positive bias towards cloud integration and, in particular, automatic meeting-note push. We conclude that our context-aware meeting assistant can provide valuable assistance to end users and that there is promise for such use of heterogeneous mobile context-aware platforms.

Determination of 3‐MCPD esters in edible oil – methods of analysis and comparability of results

AbstractThe discovery of fatty acid esters of 3‐chloropropane‐1,2‐diol (3‐MCPD) in edible oil products initiated food monitoring campaigns in many EU Member States. As the determination of 3‐MCPD esters was new to most laboratories, questions on the reliability of the produced analysis data were raised. In response to this, the Institute for Reference Materials and Measurements (IRMM) of the European Commission's Joint Research Centre (JRC) organised a proficiency test on the determination of 3‐chloropropane‐1,2‐diol esters (3‐MCPD esters) in edible oils. The aim of this proficiency test was to scrutinise the capabilities of official food control laboratories, private food control laboratories as well as laboratories from food industry to determine the 3‐MCPD esters content of edible oils. The study was carried out in accordance with “The International Harmonised Protocol for the Proficiency Testing of Analytical Chemistry Laboratories” and ISO Guide 43. The test materials dispatched to the participants were: refined palm oil, extra virgin olive oil spiked with 3‐chloropropane‐1,2‐dioleate and 3‐MCPD standard solution in sodium chloride. Altogether 41 laboratories from 11 EU Member States, Switzerland and Macedonia subscribed for participation in the study. The analysis task was to determine the 3‐MCPD esters content as total 3‐MCPD content of the test samples. Participants were free to choose their analysis methods. In total, 34 laboratories reported results to the organisers of the study. The performance of laboratories in the determination of 3‐MCPD esters in edible oils was expressed by z‐scores. About 56% of the participants performed satisfactorily in the determination of 3‐MCPD esters in palm oil and 85% for the spiked extra virgin olive oil test sample. The study revealed that the direct transesterification of the sample without the prior removal of glycidol esters might lead to strong positive bias.

Serotonin transporter gene polymorphism and psychiatric disorders: Is there a link?

Though still in infancy, the field of psychiatric genetics holds great potential to contribute to the development of new diagnostic and therapeutic options to treat these disorders. Among a large number of existing neurotransmitter systems, the serotonin system dysfunction has been implicated in many psychiatric disorders and therapeutic efficacy of many drugs is also thought to be based on modulation of serotonin. Serotonin transporter gene polymorphism is one of the most extensively studied polymorphisms in psychiatric behavioral genetics. In this article, we review the status of evidence for association between the serotonin gene polymorphism and some common mental disorders like affective disorders, post-traumatic stress disorder, obsessive-compulsive disorder, suicide, autism, and other anxiety and personality disorders. Going beyond traditional association studies, gene-environment interaction, currently gaining momentum, is also discussed in the review. While the existing information of psychiatric genetics is inadequate for putting into practice genetic testing in the diagnostic work-up of the psychiatric patient, if consistent in future research attempts, such results can be of great help to improve the clinical care of a vast majority of patients suffering from such disorders.

Health Risk Perception, Optimistic Bias, and Personal Satisfaction

To examine change in risk perception and optimistic bias concerning behavior-linked health threats and environmental health threats between adolescence and young adulthood and how these factors related to personal satisfaction. In 1996 and 2002, 1624 adolescents responded to a mailed questionnaire. Adolescents showed strong positive optimistic bias concerning behaviorlinked risks, and this optimistic bias increased with age. Increase in optimistic bias over time predicted increase in personal satisfaction. The capacity to process and perceive potential threats in a positive manner might be a valuable human ability positively influencing personal satisfaction and well-being.

Effect of HbS in the determination of HbA2 with the Menarini HA‐8160 analyzer and comparison with other instruments

It is known that the presence of hemoglobin S (HbS) affects the determination of hemoglobin A(2) (HbA(2)) levels in clinical samples. We quantitated this effect using the Menarini HA-8160 analyzer and compared with other instruments (HELENA beta-thal quik column, TOSOH HLC-723G7 and BIORAD Variant II) using the HELENA SAS-MX alkaline gel electrophoresis kit as the reference method. The %HbA(2) values from the HA-8160 analyzer and the alkaline gel electrophoresis show a good linear correlation in the absence of HbS. A strong positive bias in the %HbA(2) values from the HA-8160 is apparent in the presence of HbS in the samples, when compared with the alkaline electrophoresis. The analytical imprecision and bias of the three HPLC instruments are comparable both in the presence and absence of HbS. The manual column method shows a lower bias in the absence of HbS but is more affected when HbS is present in the samples.