It is important for the research produced by industrial-organizational (I-O) psychologists to be rigorous, relevant, and useful to organizations. However, I-O psychology research is often not used in practice. In this paper, we (both practitioners and academics) argue that engaged scholarship—a particular method of inclusive, collaborative research that incorporates multiple stakeholder perspectives throughout the research process—can help reduce this academic–practice gap and advance the impact of I-O psychology. To examine the current state of the field, we reviewed empirical evidence of the current prevalence of collaborative research by examining the number of articles that contain nonacademic authors across 14 key I-O psychology journals from 2018 to 2023. We then build on these findings by describing how engaged scholarship can be integrated throughout the research process and conclude with a call to action for I-O psychologists to conduct more collaborative research. Overall, our goal is to facilitate a fruitful conversation about the value of collaborative research that incorporates multiple stakeholder perspectives throughout the research process in hopes of reducing the academic–practice gap. We also aim to inspire action in the field to maintain and enhance the impact of I-O psychology on the future world of work.

Among 287 US hospitals reporting data between 2015 and 2018, annual pediatric surgical site infection (SSI) rates ranged from 0% for gallbladder to 10.4% for colon surgeries. Colon, spinal fusion, and small-bowel SSI rates did not decrease with greater surgical volumes in contrast to appendix and ventricular-shunt SSI rates.

The availability of large healthcare datasets offers the opportunity for researchers to navigate the traditional clinical and translational science research stages in a nonlinear manner. In particular, data scientists can harness the power of large healthcare datasets to bridge from preclinical discoveries (T0) directly to assessing population-level health impact (T4). A successful bridge from T0 to T4 does not bypass the other stages entirely; rather, effective team science makes a direct progression from T0 to T4 impactful by incorporating the perspectives of researchers from every stage of the clinical and translational science research spectrum. In this exemplar, we demonstrate how effective team science overcame challenges and, ultimately, ensured success when a diverse team of researchers worked together, using healthcare big data to test population-level substance use disorder (SUD) hypotheses generated from preclinical rodent studies. This project, called Advancing Substance use disorder Knowledge using Big Data (ASK Big Data), highlights the critical roles that data science expertise and effective team science play in quickly translating preclinical research into public health impact.

Developing alternatives to antibiotics is an urgent need in livestock production. Antimicrobial peptides (AMPs) are regarded as powerful antibiotic substitutes (ASs) because AMPs have broad-spectrum antimicrobial activities and growth-promoting ability. Here, we aimed to comprehensively assess the effects of AMPs on the growth performance, diarrhea rate, intestinal morphology and immunity of healthy or challenged piglets, compared with an antibiotics group or negative control group. We performed a set of meta-analyses of feeding trials from database inception to 27 May 2019. Among the 1379 identified studies, 20 were included in our meta-analyses (56 arms and 4067 piglets). The meta-analyses revealed that (1) compared with the negative control group, AMPs significantly improved the healthy piglets’ average daily gain (ADG), average daily feed intake (ADFI), gain : feed ratio (G/F), levels of immune globulin (Ig) IgM and IgG, and intestinal villus height : crypt depth ratio (V/C) (P < 0.05). Meanwhile, AMPs significantly increased the challenged piglets’ ADG, ADFI, G/F and V/C of the jejunum and ileum, and notably deceased the diarrhea rate (P < 0.05); (2) compared with antibiotics group, the effects of AMPs were slightly weaker than those of antibiotics in the healthy piglets, but AMPs have similar effects to those of antibiotics in challenged piglets. In a higher purity, the optimal dose of AMPs may be approximately 0.01%. Our findings indicate that AMPs can improve piglet growth performance, enhance immunity, benefit intestinal morphology and decrease the diarrheal rate. AMPs could be great ASs especially under infection conditions.

The search for life in the Universe is a fundamental problem of astrobiology and modern science. The current progress in the detection of terrestrial-type exoplanets has opened a new avenue in the characterization of exoplanetary atmospheres and in the search for biosignatures of life with the upcoming ground-based and space missions. To specify the conditions favourable for the origin, development and sustainment of life as we know it in other worlds, we need to understand the nature of global (astrospheric), and local (atmospheric and surface) environments of exoplanets in the habitable zones (HZs) around G-K-M dwarf stars including our young Sun. Global environment is formed by propagated disturbances from the planet-hosting stars in the form of stellar flares, coronal mass ejections, energetic particles and winds collectively known as astrospheric space weather. Its characterization will help in understanding how an exoplanetary ecosystem interacts with its host star, as well as in the specification of the physical, chemical and biochemical conditions that can create favourable and/or detrimental conditions for planetary climate and habitability along with evolution of planetary internal dynamics over geological timescales. A key linkage of (astro)physical, chemical and geological processes can only be understood in the framework of interdisciplinary studies with the incorporation of progress in heliophysics, astrophysics, planetary and Earth sciences. The assessment of the impacts of host stars on the climate and habitability of terrestrial (exo)planets will significantly expand the current definition of the HZ to the biogenic zone and provide new observational strategies for searching for signatures of life. The major goal of this paper is to describe and discuss the current status and recent progress in this interdisciplinary field in light of presentations and discussions during the NASA Nexus for Exoplanetary System Science funded workshop ‘Exoplanetary Space Weather, Climate and Habitability’ and to provide a new roadmap for the future development of the emerging field of exoplanetary science and astrobiology.

Solar coronal dimmings have been observed extensively in the past two decades and are believed to have close association with coronal mass ejections (CMEs). Recent study found that coronal dimming is the only signature that could differentiate powerful flares that have CMEs from those that do not. Therefore, dimming might be one of the best candidates to observe the stellar CMEs on distant Sun-like stars. In this study, we investigate the possibility of using coronal dimming as a proxy to diagnose stellar CMEs. By simulating a realistic solar CME event and corresponding coronal dimming using a global magnetohydrodynamics model (AWSoM: Alfvén-wave Solar Model), we first demonstrate the capability of the model to reproduce solar observations. We then extend the model for simulating stellar CMEs by modifying the input magnetic flux density as well as the initial magnetic energy of the CME flux rope. Our result suggests that with improved instrument sensitivity, it is possible to detect the coronal dimming signals induced by the stellar CMEs.

Rabies is one of the major public health problems in China, and the mortality rate of rabies remains the highest among all notifiable infectious diseases. A meta-analysis was conducted to investigate the post-exposure prophylaxis (PEP) vaccination rate and risk factors for human rabies in mainland China. The PubMed, Web of Science, Chinese National Knowledge Infrastructure, Chinese Science and Technology Periodical and Wanfang databases were searched for articles on rabies vaccination status (published between 2007 and 2017). In total, 10 174 human rabies cases from 136 studies were included in this meta-analysis. Approximately 97.2% (95% confidence interval (CI) 95.1–98.7%) of rabies cases occurred in rural areas and 72.6% (95% CI 70.0–75.1%) occurred in farmers. Overall, the vaccination rate in the reported human rabies cases was 15.4% (95% CI 13.7–17.4%). However, among vaccinated individuals, 85.5% (95% CI 79.8%–83.4%) did not complete the vaccination regimen. In a subgroup analysis, the PEP vaccination rate in the eastern region (18.8%, 95% CI 15.9–22.1%) was higher than that in the western region (13.3%, 95% CI 11.1–15.8%) and this rate decreased after 2007. Approximately 68.9% (95% CI 63.6–73.8%) of rabies cases experienced category-III exposures, but their PEP vaccination rate was 27.0% (95% CI 14.4–44.9%) and only 6.1% (95% CI 4.4–8.4%) received rabies immunoglobulin. Together, these results suggested that the PEP vaccination rate among human rabies cases was low in mainland China. Therefore, standardised treatment and vaccination programs of dog bites need to be further strengthened, particularly in rural areas.

PALWEED:WHEAT is a bioeconomic decision model for determining profit-maximizing postemergence herbicide treatments for winter wheat in the Washington–Idaho Palouse region. PALWEED:WHEAT performed relatively well economically in 2 yr of on-farm field tests. However, the model was less sensitive than desired in prescribing postemergence broadleaved herbicides in the presence of high densities of broadleaved weed seedlings. Therefore, PALWEED:WHEAT was revised in response to the field testing. This paper compares the revised model's agronomic and economic performance to the original model in computer simulations. The revised model, PALWEED:WHEAT II, differs from the original model in several respects: (1) exponential functions replace linear functions in predicting weed survival, (2) preplant application of a nonselective herbicide is entered as an exogenous binary variable, (3) separate indices of broadleaved and grass competition are substituted for an aggregate weed competition index in the wheat yield function, (4) hyperbolic replaces logistic functional representation of weed damage to wheat yield, and (5) separate models are estimated for winter wheat after spring dry pea and for winter wheat in all examined crop rotation positions. In simulations including a variety of agronomic and economic conditions, PALWEED:WHEAT II recommended postemergence herbicide types and rates that consistently complied with agronomic and economic theory. Furthermore, the revised model, especially when estimated from the relevant wheat after pea data set, was markedly more balanced in recommending both broadleaved and grass herbicides in response to observed densities of both weed groups. The substantial change in herbicide recommendations in response to changes in model functional specifications following field testing confirms the importance of field testing and revision of bioeconomic decision models.

Based on six years of data from a field experiment near Pullman, WA, a bioeconomic decision model was developed to annually estimate the optimal post-emergence herbicide types and rates to control multiple weed species in winter wheat under various tillage systems and crop rotations. The model name, PALWEED:WHEAT, signifies a Washington-Idaho Palouse region weed management model for winter wheat The model consists of linear preharvest weed density functions, a nonlinear yield response function, and a profit function. Preharvest weed density functions were estimated for four weed groups: summer annual grasses, winter annual grasses, summer annual broadleaves, and winter annual broadleaves. A single aggregated weed competition index was developed from the four density functions for use functions for use in the yield model. A yield model containing a logistic damage function performed better than a model containing a rectangular hyperbolic damage function. Herbicides were grouped into three categories: preplant nonselective, postemergence broadleaf, and postemergence grass. PALWEED:WHEAT was applied to average conditions of the 6-yr experiment to predict herbicide treatments that maximized profit. In comparison to average treatment rates in the 6-yr experiment, the bioeconomic decision model recommended less postemergence herbicide. The weed management recommendations of PALWEED:WHEAT behaved as expected by agronomic and economic theory in response to changes in assumed weed populations, herbicide costs, crop prices, and possible restrictions on herbicide application rates.

Climate change has greatly affected agricultural production, and will lead to further changes in cropping system, varietal type and cultivation techniques for each region. The potential effects of climate change on rice production in Fujian Province, China, were explored in the current study with CERES-Rice model and climate-change scenarios, based on the self-adaptation of rice production. The results indicated that simulated yields of early rice in the double-rice region in south-eastern Fujian under scenarios A2, B2 and A1B increased by 15·9, 18·0 and 19·2%, respectively, and correspondingly those of late rice increased by 9·2, 7·4 and 7·4% when self-adaptation adjustment was considered, compared to scenarios without that consideration. In the double-rice region in north-western Fujian, simulated yields of early rice increased by 21·2, 20·5 and 18·9% and those of late rice by 14·7, 14·8 and 7·2% under scenarios A2, B2 and A1B, respectively, when self-adaptation was considered, compared to without consideration. Similar results were obtained for the single-rice region in the mountain areas of north-western Fujian, correspondingly increasing by 4·9, 5·0 and 2·9% when self-adaptation was considered compared to when it was not. In this single-rice region, double rice might be grown in the future at the Changting site under scenarios A1 and B2. When the self-adaptation adjustment was considered, the simulated overall output of rice crops in Fujian under scenarios A2, B2 and A1B increased by 5·9, 5·2 and 5·1%, respectively. Thus, more optimistic results were obtained when the self-adaptation ability of rice production was considered.

Clomazone has been successfully used for weed control in rice, but crop injury is a potential problem on light-textured soils. Experiments were conducted to determine the effect of soil characteristics and water potential on plant-available clomazone and rice injury. A centrifugal double-tube technique was used to determine plant-available concentration in soil solution (ACSS), total amount available in soil solution (TASS), and Kd values for clomazone on four soils at four water potentials. A rice bioassay was conducted parallel to the plant-available study to correlate biological availability to ACSS, TASS, and Kd. TASS was significantly different in all soils. The order of increasing TASS for the soils studied was Morey < Edna < Nada < Crowley, which correlated well with soil characteristics. The order of increasing TASS after equilibrium was − 90 < − 75 < − 33 < 0 kPa. TASS values at 0 kPa were greater than two times the TASS values at − 90 kPa. It appears that severe rice injury from clomazone on these soils could occur if TASS > 110 ng g−1 and Kd < 1.1 ml g−1. We propose that the double-tube technique provides a more accurate estimate of available herbicide because the solution–soil ratios are < 0.33:1 and would be more representative of a plant root–herbicide relationship. This technique or some variation possibly could be further developed such that clomazone rates could be more clearly defined particularly on lighter-textured soils. TASS may be a better predictor of plant-available herbicide than ACSS when evaluating moderately to highly water-soluble herbicides in a nonsaturated soil environment.

We determined the prevalence and seasonality of infections by Fasciola of goats and bovine species (cattle and water buffalo) in Hubei and Anhui provinces of China. Faecal samples were collected at 2- to 3-month intervals from 200 goats in Hubei province and from 152 bovine species in Anhui province. All faecal samples were examined for the presence of parasites. We determined the nucleotide sequences of the first and second internal transcribed spacers (ITS-1 and ITS-2) of the nuclear ribosomal DNA (rDNA) of 39 Fasciola worms from Anhui province. The prevalence of Fasciola infection in goats ranged between 3.5 and 37.0%, with mean eggs per gram (EPG) ranging between 29.0 and 166.0. Prevalence and EPG exhibited downward trends over time with significant differences. The prevalence of Fasciola infection in cattle ranged between 13.3 and 46.2% (mean EPG, 36.4–100.0), and that of water buffalo ranged between 10.3 and 35.4% (mean EPG, 25.0–89.6), with a higher prevalence of infection and EPG from June to October compared with December to March. Analysis of ITS-1 and ITS-2 sequences revealed that F. hepatica and F. gigantica were present in all bovine species of Anhui province and that F. gigantica mainly infected water buffalo. This is the first demonstration of Fasciola infection in Hubei province and detection of F. hepatica and F. gigantica in Anhui province. The present study of Hubei province shows that mass treatment of livestock with closantel sodium injections in April and August/September controlled Fasciola infection effectively.