Default Values Research Articles

Predicting the relative oral bioavailability of naturally occurring As, Cd and Pb from in vitro bioaccessibility measurement: implications for human soil ingestion exposure assessment

Chestnut soils developed over mineralized areas of southwestern Spain are characterized by high baseline concentrations of geogenic trace elements, notably Pb (up to 14,562mgkg-1), As (up to 346mgkg-1) and Cd (up to 319mgkg-1), which could pose an unacceptable risk to the health of the hand-harvest workers who are being exposed to surface soil by incidental ingestion and dermal contact. Oral bioaccessibility, as determined by simulating the human digestion process in a test-tube environment (Unified BARGE Method), followed the increasing order of As (3.1%) < Pb (21.5%) < Cd (35.6%) in the gastric phase, and As (3.4%) < Pb (4.5%) < Cd (13.2%) in the gastrointestinal extract. Relative bioavailability (RBA) of As (3.1-2.1%), Pb (17.8-17.5%) and Cd (34.4-23.3%), predicted from in vitro bioaccessibility measurement through linear regression models, seems to be influenced not only by the pH and composition of digestive solutions but also by geochemical partitioning of trace elements among the soil constituents. The integration of RBA data in the risk calculations had a considerable effect on the site-specific risk estimations. After RBA adjustment, the level of carcinogenic risk associated with As exposure (< 1.5E-06) and the hazard index for non-carcinogens (< 0.4) was within the regulatory limits, indicating that occupational risks are not of concern. Hence, it can be concluded that the use of a default value of 100% for bioavailability may dramatically overestimate the chronic exposure to geologically sourced trace elements.

Effect of airfoil shape on power performance of vertical axis wind turbines in dynamic stall: Symmetric Airfoils

The current design of vertical axis wind turbines (VAWTs) suffers from inevitable change in tip speed ratio, λ, in variant wind conditions due to fixed rotor speed. At relatively high wind speeds, which are promising due to high wind power potential, VAWTs operate at low λ with poor power coefficient. Morphing airfoils can be a potential solution by modifying the airfoil shape to optimal at each λ. The optimal airfoil shape for VAWTs at low λ, where dynamic stall is present, has not yet been studied in the literature, therefore, the present study addresses this gap by focusing on this regime to serve as a step towards designing morphing airfoils for VAWTs by identifying the optimal airfoil shape at low λ. The present study performs a combined analysis of three shape defining parameters, namely the airfoil maximum thickness and its position as well as the leading-edge radius, to reveal the overall design space. The analysis is based on 252 high-fidelity transient CFD simulations of 126 identical airfoil shapes. The simulations are verified and validated with three experiments. The results show that the three shape defining parameters have a fully coupled impact on the turbine power and thrust coefficients. When λ reduces from 3.0 to 2.5, the optimal airfoil changes from NACA0018–4.5/2.75 to NACA0024–4.5/3.5, that is increasing the maximum thickness from 18%c to 24%c and shifting its position from 27.5%c to 35%c, while the leading-edge radius index, I, remains 4.5. In general, reducing I from the default value of 6.0 to 4.5 is found to increase the turbine CP.

The feasibility of heavy battery electric trucks

Summary Research on the decarbonization of transport often concludes that heavy battery electric trucks are infeasible due to the incompatibility of long driving distance with high energy use and low specific energy and high costs of batteries. However, emphasis is often placed on battery electric range matching that of diesel trucks, instead of overall competitiveness. We model battery electric trucks that use high-power fast charging, enabling smaller batteries and showing that the economics of battery electric trucks per ton-kilometer improves with greater weight, driven by increasing load capacity as well as increased energy savings as a function of weight. Furthermore, we show that previous findings that the competitiveness per kilometer is worse for heavy trucks than for lighter trucks are very sensitive to assumptions about the battery cost per kWh and lifetime of the battery pack. Given the rapid development of batteries, we conclude that the economic feasibility of heavy battery electric trucks might have been generally underestimated.

Can a physically-based land surface model accurately represent evapotranspiration partitioning? A case study in a humid boreal forest

One of the roles of Land Surface Models (LSMs) is to partition evapotranspiration (E) into overstory transpiration (ET), understory evapotranspiration (EG), and wet canopy evaporation (EC). Unfortunately, only a handful of studies have evaluated the performance of LSMs with E partitioning. Unlike dry canopies which are dominated by transpiration, wet canopies lead to the evaporation of intercepted water. In this respect, there is no better testing site for LSMs than the humid boreal forest, which is characterized by frequent precipitation and sustained evapotranspiration. This study assesses the performance of the Canadian Land Surface Scheme (CLASS) in simulating evapotranspiration and its components by applying detailed observations of water pathways and residence times in a forest canopy using a variety of methods (eddy covariance; sap flow, throughfall and stemflow measurements; and the stem compression approach). The study site was located in Montmorency Forest in Québec, Canada, a balsam fir boreal forest with ≈1600 mm of annual precipitation. The field campaign was conducted during the summers of 2017 and 2018. To improve the accuracy of the simulations, we adjusted the definition of maximum canopy water storage, S=c×LAI, by using c=0.49 mm instead of the default value of 0.20 mm. This simple modification improved the performance of CLASS when simulating components of evapotranspiration, indicated by the increase in the modified Kling-Gupta efficiency (KGE′) with rises between 0.01 and 0.23. Overall, CLASS performed well in simulating evapotranspiration and overstory transpiration in dry canopy conditions at half-hourly time steps with KGE′ values between 0.67 and 0.81. The contribution of simulated ET,EG, and EC to total E during the two sampling periods were 46%,24%, and 30%, respectively, which were comparable with the field observations (35%,22%, and 25%, respectively). In conclusion, CLASS was able to simulate E partitioning in dry and wet canopy conditions reasonably well at both seasonal and half-hourly time scales.

The Role of Accounting Mechanisms for Bank Governance in Improving the Quality of the Information Content of the Interim Financial Reports

This research aims to highlight the important and appropriate role of the accounting mechanisms for bank governance in improving the quality of the information content of the interim financial reports prepared by the Iraqi private banks operating in the Kurdistan Region / Iraq. The application of bank governance through accounting mechanisms is one of the most important standards that concern investors when they make any investment credit decision. This is done by determining the nature of the relationship between the application of accounting mechanisms for bank governance and the information content of the interim financial reports of private Iraqi banks operating in the Kurdistan Region / Iraq in order to improve The quality of the informational content of these reports. We conclude that governance, and specifically its accounting mechanisms, plays an important role in limiting profit management practices in banks, as well as improving the quality of the information content of the interim financial reports. - The results of the research revealed that there is a relationship and a significant impact of the accounting mechanisms in improving the quality of the information content of the interim financial reports, as the calculated P-value reached (0.000), which is much less than the default value of the level of significance adopted by the research.

How important is the description of soil unsaturated hydraulic conductivity values for simulating soil saturation level, drainage and pasture yield?

Accurate simulation of soil water dynamics is a key factor when using agricultural models for guiding management decisions. However, the determination of soil hydraulic properties, especially unsaturated hydraulic conductivity, is challenging and measured data are scarce. We investigated the use of APSIM (Agricultural Production Simulation Model) with SWIM3 as the water module, based on Richards equation and a bimodal pore system, to determine likely ranges of the hydraulic conductivity at field capacity (K-10; assumed at a matric potential of −10 kPa) for soils representing different drainage characteristics. Hydraulic conductivity measurements of soils with contrasting soil drainage characteristics and values for K-10 were extracted from New Zealand’s national soil database. The K-10 values were then varied in a sensitivity analysis from 0.02 to 5 mm d−1 for well-drained soils, from 0.02 to 1 mm d−1 for moderately well-drained soils, and from 0.008 to 0.25 mm d−1 for poorly drained soils. The value of K-10 had a large effect on the time it took for the soil to drain from saturation to field capacity. In contrast, the saturated hydraulic conductivity value had little effect.Simulations were then run over 20 years using two climatic conditions, either a general climate station for all seven different soils, or site-specific climate stations. Two values for K-10 were used, either the APSIM default value, or the soil-specific measured K-10. The monthly average soil saturation level simulated with the latter has a better correspondence with the morphology of the seven soils. Finally, the effect of K-10 on drainage and pasture yield was investigated. Total annual drainage was only slightly affected by the choice of K-10, but pasture yield varied substantially.

Characterizing soil losses in China using data of 137Cs inventories and erosion plots

A large area of lands are subject to soil erosion, which affects the soil ecosystem service by causing soil degradation and soil organic carbon (SOC) changes. Robust estimations of soil loss rates are of key importance to understand relevant controlling factors as well as reducing soil losses. This study utilized complied data derived from 137Cs inventories and erosion plots to quantify soil loss rates in China as well as investigating controlling factors of soil loss rates. Comparison between results from different methods was also conducted to understand the advantages of each method. Our results showed that soil loss rates of cultivated soils derived from both methods were significantly higher than those of uncultivated soils, and soil loss rates were generally positively correlated with the slope gradient and the slope length. There were discrepancies between soil loss rates derived from 137Cs inventories and those from erosion plots due to the different erosion processes and spatio-temporal scales that these two methods focused on. The 137Cs loss ratio was identified as the largest source of variations in the estimated soil loss rates by conversion models. Existing studies have failed to collect enough soil samples to correctly estimate the reference 137Cs inventory, and considerably overestimated the soil loss rates by assuming a default value of unit for the particle size correction factor.

Detecting Brain Activations in Functional Magnetic Resonance Imaging (fMRI) Experiments with a Maximum Cross-Correlation Statistic

Various statistical models have been proposed to analyze fMRI data. The usual goal is to make inferences about the eects that are related to an external stimulus. The primary focus of this paper is on those statisti- cal methods that enable one to detect 'signicantly activated' regions of the brain due to event-related stimuli. Most of these methods share a common property, requiring estimation of the hemodynamic response function (HRF) as part of the deterministic component of the statistical model. We propose and investigate a new approach that does not require HRF ts to detect 'activated' voxels. We argue that the method not only avoids tting a specic HRF, but still takes into account that the unknown response is delayed and smeared in time. This method also adapts to dierential re- sponses of the BOLD response across dierent brain regions and experimen- tal sessions. The maximum cross-correlation between the kernel-smoothed stimulus sequence and shifted (lagged) values of the observed response is the proposed test statistic. Using our recommended approach we show through realistic simulations and with real data that we obtain better sensitivity than simple correlation methods using default values of SPM2. The simulation experiment incor- porates dierent HRFs empirically determined from real data. The noise models are also dierent AR(3) ts and fractional Gaussians estimated from real data. We conclude that our proposed method is more powerful than simple correlation procedures, because of its robustness to variation in the HRF.

Modeling the hydrodynamics and morphodynamics of sandbar migration events

A number of models are available for science and engineering purposes that numerically simulate nearshore hydrodynamics and the corresponding morphological evolution. However, the models include adjustable coefficients in parameterizations for physical processes that need to be calibrated, and thus there remains room for improvement by including additional physics. One such model is XBeach, which can simulate erosion during storms with proper calibration based on observations. The modeled sediment transport, especially in the cross-shore direction, is sensitive to the adjustable coefficients, with preferred values that are site and event specific. Here, the skill of XBeach is investigated by comparing 1-dimensional (cross-shore) depth-averaged simulations with observations of waves, currents, and sandbar migration across an Atlantic Ocean beach. Calibration of coefficients improved the agreement of the computed results with observed wave heights, offshore-directed mean currents (undertow), the wave-orbital-velocity third moments (skewness and asymmetry), and onshore/offshore sandbar migration although the proposed coefficient values depend on the parameterizations used. For example, including a variable breaking-wave roller energy model resulted in more skillful predictions of undertow than using the default constant coefficient value. Using the calibrated roller coefficients and corresponding undertow, XBeach simulated the observed offshore migration of the sandbar. Onshore transport in XBeach is driven by non-sinusoidal wave-orbital velocities, and proposed values for coefficients depend on the parameterization used to estimate skewness and asymmetry and the associated transport, as well as on incident wave conditions. XBeach calculations of cross-shore sediment transport rates were compared with those estimated by a commonly used sediment transport formula based on laboratory experiments. The inter-comparison suggests that using a wave-induced onshore transport parameter 3 or 4 times larger than the default value may at least in part compensate for the lack of bottom-boundary-layer-streaming-driven-onshore transport in XBeach.

Carbon balance of tropical peat forests at different fire history and implications for carbon emissions.

Accurate assessment of tropical peat forest carbon stocks and impact of fires on carbon pools is required to determine the magnitude of emissions to the atmosphere and to support emissions reduction policies. We assessed total aboveground carbon (AGC) in biomass pools including trees, shrubs, deadwood, litter and char, and peat carbon to develop empirical estimates of peat swamp forest carbon stocks in response to fire and disturbance. In contrast to the common assumption that peat fires combust all AGC, we observed that about half of undisturbed forest AGC, equivalent to about 70Mg C ha-1, remains after one or two recent fires - mainly in dead trees, woody debris and pyrogenic carbon. Both recently burnt and repeatedly burnt peat forests store similar amounts of carbon in the top 10cm of peat when compared with undisturbed forests (70Mg C ha-1), mainly due to increased peat bulk density after fires that compensates for their lower peat C%. The proportion of fuel mass consumed in fire, or combustion factor (CF), is required to make accurate estimates of peat fire emissions for both AGC and peat carbon. This study estimated a CF for AGC (CFAGC) of 0.56, comparable to the default value of the Intergovernmental Panel on Climate Change (IPCC). This study estimated a varying CF for peat (CFPEAT) that ranged from 0.4 to 0.68 as depth of burn increased. This revised CFPEAT is one third to one half of the IPCC default value of 1.0. The current assumption of complete combustion of peat (CF=1.0) is widely acknowledged in the literature as oversimplification and is not supported by our field observations or data. This study provides novel empirical data to improve estimates of peat forests carbon stocks and emissions from tropical peat fires.

Environmental impact assessment of COVID-19 therapeutic solutions. A prospective analysis.

Several medicinal products for human use are currently under consideration as potential treatment for COVID-19 pandemic. As proposals cover also prophylactic use, the treatment could be massive, resulting in unprecedent levels of antiviral emissions to the aquatic environment. We have adapted previous models and used available information for predicting the environmental impact of representative medicinal products, covering the main groups under consideration: multitarget antiparasitic (chloroquines and ivermectin), glucocorticoids, macrolide antibiotics and antiviral drugs including their pharmacokinetic boosters. The retrieved information has been sufficient for conducting a conventional environmental risk assessment for the group of miscellaneous medicines; results suggest low concern for the chloroquines and dexamethasone while very high impact for ivermectin and azithromycin, even at use levels well below the default value of 1% of the population. The information on the ecotoxicity of the antiviral medicines is very scarce, thus we have explored an innovative pharmacodynamic-based approach, combining read-across, quantitative structure-activity relationship (QSAR), US EPA's Toxicity Forecaster (ToxCast) in vitro data, pharmacological modes of action, and the observed adverse effects. The results highlight fish sublethal effects as the most sensitive target and identify possible concerns. These results offer guidance for minimizing the environmental risk of treatment medication for COVID-19.

Are the target exposure index and deviation index used efficiently?

IntroductionExposure index (EI) is important to evaluate correct exposure in radiography and thus important for image quality. The purpose of this study was to evaluate whether the target exposure index (EIT) and deviation index (DI) were used efficiently. MethodsRadiography departments in Iceland, using <10 years old equipment, were invited to participate. For each x-ray unit, admin users were asked about the use of EIT and data was gathered on EIT for five body parts (BP); lumbar spine, chest, hip, knee and hand. For each of the five BP, 100 examinations from the past year were selected randomly (or all, if < 100). The EI from one predefined view was recorded and the corresponding DI calculated. ResultsA total of ten x-ray units, from four manufacturers and located at eight departments, were included in the study. The departments involved are comprised of a university hospital, smaller hospitals, and miscellaneous private departments. Two departments (25%) had not set EIT, five (62.5%) used default values and only one had revised EIT values. In four departments (50%) radiographers favored “acceptable EI range” over DI.The mean EI was significantly different (p < 0.05) from the EIT in the majority of the five BP, in four out of the six departments that had defined EIT. In total 30% of images from all departments combined had DI outside the range of −3.0 < DI < +3.0. The standard deviation of DI was from 1.4 to 2.7. ConclusionThe study shows that the EIT and DI are not used efficiently, regardless of equipment vendor or department characteristics. Implications for practiceCurrent recommendations on targeting the mean DI of 0 need to be reinforced. Theoretical knowledge and training need to be improved.

Investigating high-energy proton-induced reactions on spherical nuclei: Implications for the preequilibrium exciton model

Background: A number of accelerator-based isotope production facilities utilize 100- to 200-MeV proton beams due to the high production rates enabled by high-intensity beam capabilities and the greater diversity of isotope production brought on by the long range of high-energy protons. However, nuclear reaction modeling at these energies can be challenging because of the interplay between different reaction modes and a lack of existing guiding cross-section data.Purpose: A Tri-lab collaboration has been formed among the Lawrence Berkeley, Los Alamos, and Brookhaven National Laboratories to address these complexities by characterizing charged-particle nuclear reactions relevant to the production of established and novel radioisotopes.Method: In the inaugural collaboration experiments, stacked-targets of niobium foils were irradiated at the Brookhaven Linac Isotope Producer (${E}_{p}=200\phantom{\rule{0.28em}{0ex}}\mathrm{MeV}$) and the Los Alamos Isotope Production Facility (${E}_{p}=100\phantom{\rule{0.28em}{0ex}}\mathrm{MeV}$) to measure $^{93}\mathrm{Nb}(p,x)$ cross sections between 50 and 200 MeV. First measurements of the $^{93}\mathrm{Nb}(p,4n)^{90}\mathrm{Mo}$ beam monitor reaction beyond 100 MeV are reported in this work, as part of the broadest energy-spanning dataset for the reaction to date. $^{93}\mathrm{Nb}(p,x)$ production cross sections are additionally reported for 22 other measured residual products. The measured cross-section results were compared with literature data as well as the default calculations of the nuclear model codes TALYS, CoH, EMPIRE, and ALICE.Results: The default code predictions largely failed to reproduce the measurements, with consistent underestimation of the preequilibrium emission. Therefore, we developed a standardized procedure that determines the reaction model parameters that best reproduce the most prominent reaction channels in a physically justifiable manner. The primary focus of the procedure was to determine the best parametrization for the preequilibrium two-component exciton model via a comparison to the energy-dependent $^{93}\mathrm{Nb}(p,x)$ data, as well as previously published $^{139}\mathrm{La}(p,x)$ cross sections.Conclusions: This modeling study revealed a trend toward a relative decrease for internal transition rates at intermediate proton energies (${E}_{p}=20$--60 MeV) in the current exciton model as compared to the default values. The results of this work are instrumental for the planning, execution, and analysis essential to isotope production.

Risk Capital: Theory and Applications

After a brief review of the current theory and practice of risk capital by financial firms, the authors define the concept of risk capital and identify the costs and benefits of using more or less of it. Next, they present their procedure for allocating risk capital to assets and lines of business on the basis of marginal default values, and in a way designed to prevent risk shifting and internal arbitrage. Then, they show how allocations of risk capital are likely to be affected by, and in turn influence, a financial firm's decisions about both the scale and composition of its portfolio of businesses. Finally, the authors present a number of applications and consider their implications for maximizing the value of financial firms.In so doing, the authors also show how their method produces very different allocations of risk capital than those based on two measures that have long been widely used by financial firms: value at risk (VaR) and risk‐adjusted return on capital (RAROC). Moreover, the adjusted present value (APV) rule for evaluating investment opportunities is shown to be workable for nonfinancial as well as financial firms.

Agricultural air pollution in Indonesia: A mini-review

Indonesia is an agricultural country that is a majority of the population consuming rice, corn and sugar cane for daily energy. But farmers tend to do open burning to their agricultural waste. The open burning practice of agricultural waste is filled with PM2.5 which contributes to air pollution. The research of air pollution modelling in Indonesia often uses the default value of global inventory. This gives the modelling results that are less representative of the situation in Indonesia. Therefore, it is necessary to develop a PM2.5 emission inventory from the agriculture sector in Indonesia. In addition, the inventory of PM2.5 emissions from the agricultural sector in Indonesia is still relatively minimal. In addition, most of research in Indonesia still focuses on agricultural burning activities and has not been able to identify the PM2.5 emissions from the preparation of agricultural land activities. In fact, according to international research, the two largest emissions of PM2.5 on the agricultural sector came from agricultural biomass burning activities and the preparation of agricultural land. Therefore, a comprehensive inventory study need to be investigated immediately in order to determine local factor emission as a better representatives input for agricultural air pollution modelling in Indonesia.

Greenhouse gas reporting data improves understanding of regional climate impact on landfill methane production and collection.

A critical examination of the US Environmental Protection Agency’s (US EPA’s) Greenhouse Gas Reporting Program (GHGRP) database provided an opportunity for the largest evaluation to date of landfilled waste decomposition kinetics with respect to different US climate regimes. In this paper, 5–8 years of annual methane collection data from 114 closed landfills located in 29 states were used to estimate site-specific waste decay rates (k) and methane collection potentials (Lc). These sites account for approximately 9% of all landfills required to report GHG emissions to the US EPA annually. The mean methane collection potential (Lc) for the sites located in regions with less than 635 mm (25 in) annual rainfall was significantly (p<0.002) lower than the mean methane collection potential of the sites located in regions with more than 635 mm (25 in) annual precipitation (49 and 73 m3 methane Mg-1 waste, respectively). This finding suggests that a fraction of the in-place biodegradable waste may not be decomposing, potentially due to a lack of adequate moisture content of landfills located in arid regions. The results of this evaluation offer insight that challenges assumptions of the traditional landfill methane estimation approach, especially in arid climates, that all methane corresponding to the total methane generation potential of the buried solid waste will be produced. Decay rates showed a significant correlation with annual precipitation, with an average k of 0.043 year-1 for arid regions (< 508 mm (20 in) year-1), 0.074 year-1 for regions with 508–1,016 mm (20–40 in) annual precipitation, and 0.09 year-1 in wet regions (> 1,016 mm (40 in) year-1). The data suggest that waste is decaying faster than the model default values, which in turn suggests that a larger fraction of methane is produced during a landfill’s operating life (relative to post-closure).

A/B testing as an effective instrument for adaptation of the user interface at the iterative model of developing applications for mobile devices

Changing the user interface always entails risks of decreasing application ergonomics and user churn. The purpose of this work is to find methods for changing the user interface without the need to use and increase the number of active users. Using Alpha/Beta testing and analysis of application metrics, it is possible to include design in each iteration and remotely manage the application configuration, which improves the user interface of the application. The way to integrate the UI modification and adaptation phase into an iterative software development model is proposed in this article. The successful user interface improvement experiments that have improved application metrics are described. In this work, the problem was highlighted, lack of information and control over user purchases, which negatively affected the number of purchases. A hypothesis is put forward that the user must have an effective visualization and control tool in the application. As a result of the experiment, the hypothesis was confirmed by an increase in the number of purchases and user activity. There was also a data security issue in the application, which put users at risk of data loss. An experiment was conducted to change the default value of user settings, which led to an increase of the positive metrics for using the data reservation functionality. The problem of polling users is also considered, which is an important component in the process of improving the ergonomics of an application. The method of remote user polling was used, which allowed to receive quick feedback from users and quickly respond to requests from users. The result of the work is the confirmation of the hypothesis of changes in the user interface in the cycles of the iterative development model, the positive dynamics of application metrics, as well as the satisfaction of users with the changes.

Determination of organophosphorus and synthetic pyrethroid pesticide residues and their variability in large size fruit crops

Variability of pesticide residues in food item plays a key role for the evaluation of consumer food safety. However, variability factors (VFs) derived from the large size fruit crops are still scarce. Therefore, the present work was aimed to quantify pesticide residues and to estimate VFs in large size fruit crops of mango and guava. A total of 140 mango and 130 guava samples from different marketplaces in Bangladesh were collected to estimate the variability of pesticide residues (acephate, diazinon, malathion, fenitrothion, chlorpyrifos, quinalphos, dimethoate and cypermethrin) by in-house validated methods based on modified QuEChERS extraction and gas chromatography coupled with electron capture detector (ECD) and flame thermionic detector (FTD). The method was validated at three fortification levels (0.01, 0.10 and 0.30 mg kg-1 ) and satisfactory recoveries (80-111%) with relative standard deviation (RSDr ) ≤ 13% were achieved. A wide variation of residues was found in the analyzed samples. In the case of mango, the ranges of residues were 0.011-0.314, 0.015-0.04, and 0.05-0.291 mg kg-1 , respectively, for cypermethrin, chlorpyrifos, and dimethoate, while in the case of guava, the ranges were 0.04-0.113, and 0.03-0.290 mg kg-1 , respectively, for cypermethrin and acephate. The average VF for mango was 4.06 and it was 5.70 for guava. VFs originating from the marketed samples of mango and guava are reported in this study for the first time. The estimated VFs were higher than the default value of 3, therefore, the default VFs should be reconsidered when more data are obtained regarding large size crops. © 2021 Society of Chemical Industry.

PCImpact: A modeling tool for forecasting impact of primary care pharmacist services.

The role of the pharmacist in primary care (PC) has expanded to focus on medication optimization and management for chronic conditions. However, identifying the optimal pharmacist practice model to maximize pharmacist workload capacity, patient care quality, and PC provider satisfaction remains a challenge. PC clinical and administrative leaders could benefit from pharmacist impact forecasts to justify initiating new or optimizing/expanding current pharmacist services. (1) To describe the development of a PC pharmacist services modeling tool, PCImpact (2) To discuss the use of PCImpact by PC leaders to initiate, optimize, or expand integrated pharmacist services. PCImpact was developed and internally tested with 6 clinical/administrative leaders within a federally qualified health center and health system-affiliated primary care organization by: (1) identifying pharmacist practice models, (2) obtaining data input values for PCImpact, and (3) calculating PCImpact output values. Two types of pharmacist practice models are defined: population health (PH) and direct patient care (DPC). In the PH models, a centralized pharmacist performs one-time, comprehensive or targeted medication reviews with no direct patient interaction. PC providers review and implement pharmacist recommendations. In DPC models, an embedded pharmacist in a PC practice performs patient visits with or without collaborative practice agreements with PC providers. Default values for all PCImpact data inputs were obtained/tested through literature reviews and discussions with pharmacy and physician leaders, including pharmacist and PC provider time required, and implementation percentage of pharmacist recommendations. PCImpact calculates: (1) pharmacist workload capacity, (2) PC provider time impact, and (3) patient care impact. PCImpact presents a novel method to objectively forecast the impact of PH and DPC pharmacist services in 2PC settings. PCImpact outputs showed that a DPC pharmacist practice model can save PC provider time and impact a greater number of patients compared to a PH pharmacist practice model.

A graph-based algorithm for detecting rigid domains in protein structures

BackgroundConformational transitions are implicated in the biological function of many proteins. Structural changes in proteins can be described approximately as the relative movement of rigid domains against each other. Despite previous efforts, there is a need to develop new domain segmentation algorithms that are capable of analysing the entire structure database efficiently and do not require the choice of protein-dependent tuning parameters such as the number of rigid domains.ResultsWe develop a graph-based method for detecting rigid domains in proteins. Structural information from multiple conformational states is represented by a graph whose nodes correspond to amino acids. Graph clustering algorithms allow us to reduce the graph and run the Viterbi algorithm on the associated line graph to obtain a segmentation of the input structures into rigid domains. In contrast to many alternative methods, our approach does not require knowledge about the number of rigid domains. Moreover, we identified default values for the algorithmic parameters that are suitable for a large number of conformational ensembles. We test our algorithm on examples from the DynDom database and illustrate our method on various challenging systems whose structural transitions have been studied extensively.ConclusionsThe results strongly suggest that our graph-based algorithm forms a novel framework to characterize structural transitions in proteins via detecting their rigid domains. The web server is available at http://azifi.tz.agrar.uni-goettingen.de/webservice/.