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It is uncertain if long-term levels of low-density lipoprotein-cholesterol (LDL-C) affect cognition in middle age. We examined the association of LDL-C levels over 25 years with cognitive function in a prospective cohort of black and white US adults.
Lipids were measured at baseline (1985–1986; age: 18–30 years) and at serial examinations conducted over 25 years. Time-averaged cumulative LDL-C was calculated using the area under the curve for 3,328 participants with ≥3 LDL-C measurements and a cognitive function assessment. Cognitive function was assessed at the Year 25 examination with the Digit Symbol Substitution Test [DSST], Rey Auditory Visual Learning Test [RAVLT], and Stroop Test. A brain magnetic resonance imaging (MRI) sub-study (N = 707) was also completed at Year 25 to assess abnormal white matter tissue volume (AWMV) and gray matter cerebral blood flow volume (GM-CBFV) as secondary outcomes.
There were 15.6%, 32.9%, 28.9%, and 22.6% participants with time-averaged cumulative LDL-C <100 mg/dL, 101–129 mg/dL, 130–159 mg/dL, and ≥160 mg/dL, respectively. Standardized differences in all cognitive function test scores ranged from 0.16 SD lower to 0.09 SD higher across time-averaged LDL-C categories in comparison to those with LDL-C < 100 mg/dL. After covariate adjustment, participants with higher versus lower time-averaged LDL-C had a lower RAVLT score (p-trend = 0.02) but no differences were present for DSST, Stroop Test, AWMV, or GM-CBFV.
Cumulative LDL-C was associated with small differences in memory, as assessed by RAVLT scores, but not other cognitive or brain MRI measures over 25 years of follow-up.
There is compelling evidence for gradient effects of household income on school readiness. Potential mechanisms are described, yet the growth curve trajectory of maternal mental health in a child's early life has not been thoroughly investigated. We aimed to examine the relationships between household incomes, maternal mental health trajectories from antenatal to the postnatal period, and school readiness.
Prospective data from 505 mother–child dyads in a birth cohort in Singapore were used, including household income, repeated measures of maternal mental health from pregnancy to 2-years postpartum, and a range of child behavioural, socio-emotional and cognitive outcomes from 2 to 6 years of age. Antenatal mental health and its trajectory were tested as mediators in the latent growth curve models.
Household income was a robust predictor of antenatal maternal mental health and all child outcomes. Between children from the bottom and top household income quartiles, four dimensions of school readiness skills differed by a range of 0.52 (95% Cl: 0.23, 0.67) to 1.21 s.d. (95% CI: 1.02, 1.40). Thirty-eight percent of pregnant mothers in this cohort were found to have perinatal depressive and anxiety symptoms in the subclinical and clinical ranges. Poorer school readiness skills were found in children of these mothers when compared to those of mothers with little or no symptoms. After adjustment of unmeasured confounding on the indirect effect, antenatal maternal mental health provided a robust mediating path between household income and multiple school readiness outcomes (χ2 126.05, df 63, p < 0.001; RMSEA = 0.031, CFI = 0.980, SRMR = 0.034).
Pregnant mothers with mental health symptoms, particularly those from economically-challenged households, are potential targets for intervention to level the playing field of their children.
Previous studies have revealed associations of meteorological factors with tuberculosis (TB) cases. However, few studies have examined their lag effects on TB cases. This study was aimed to analyse nonlinear lag effects of meteorological factors on the number of TB notifications in Hong Kong. Using a 22-year consecutive surveillance data in Hong Kong, we examined the association of monthly average temperature and relative humidity with temporal dynamics of the monthly number of TB notifications using a distributed lag nonlinear models combined with a Poisson regression. The relative risks (RRs) of TB notifications were >1.15 as monthly average temperatures were between 16.3 and 17.3 °C at lagged 13–15 months, reaching the peak risk of 1.18 (95% confidence interval (CI) 1.02–1.35) when it was 16.8 °C at lagged 14 months. The RRs of TB notifications were >1.05 as relative humidities of 60.0–63.6% at lagged 9–11 months expanded to 68.0–71.0% at lagged 12–17 months, reaching the highest risk of 1.06 (95% CI 1.01–1.11) when it was 69.0% at lagged 13 months. The nonlinear and delayed effects of average temperature and relative humidity on TB epidemic were identified, which may provide a practical reference for improving the TB warning system.
An acute gastroenteritis (AGE) outbreak caused by a norovirus occurred at a hospital in Shanghai, China, was studied for molecular epidemiology, host susceptibility and serological roles. Rectal and environmental swabs, paired serum samples and saliva specimens were collected. Pathogens were detected by real-time polymerase chain reaction and DNA sequencing. Histo-blood group antigens (HBGA) phenotypes of saliva samples and their binding to norovirus protruding proteins were determined by enzyme-linked immunosorbent assay. The HBGA-binding interfaces and the surrounding region were analysed by the MegAlign program of DNAstar 7.1. Twenty-seven individuals in two care units were attacked with AGE at attack rates of 9.02 and 11.68%. Eighteen (78.2%) symptomatic and five (38.4%) asymptomatic individuals were GII.6/b norovirus positive. Saliva-based HBGA phenotyping showed that all symptomatic and asymptomatic cases belonged to A, B, AB or O secretors. Only four (16.7%) out of the 24 tested serum samples showed low blockade activity against HBGA-norovirus binding at the acute phase, whereas 11 (45.8%) samples at the convalescence stage showed seroconversion of such blockade. Specific blockade antibody in the population played an essential role in this norovirus epidemic. A wide HBGA-binding spectrum of GII.6 supports a need for continuous health attention and surveillance in different settings.
Maternal antenatal depression strongly influences child mental health but with considerable inter-individual variation that is, in part, linked to genotype. The challenge is to effectively capture the genotypic influence. We outline a novel approach to describe genomic susceptibility to maternal antenatal depression focusing on child emotional/behavioral difficulties. Two cohorts provided measures of maternal depression, child genetic variation, and child mental health symptoms. We constructed a conventional polygenic risk score (PRS) for attention-deficit/hyperactivity disorder (ADHD) (PRSADHD) that significantly moderated the association between maternal antenatal depression and internalizing problems at 60 months (p = 2.94 × 10−4, R2 = .18). We then constructed an interaction PRS (xPRS) based on a subset of those single nucleotide polymorphisms from the PRSADHD that most accounted for the moderation of the association between maternal antenatal depression and child outcome. The interaction between maternal antenatal depression and this xPRS accounted for a larger proportion of the variance in child emotional/behavioral problems than models based on any PRSADHD (p = 5.50 × 10−9, R2 = .27), with similar findings in the replication cohort. The xPRS was significantly enriched for genes involved in neuronal development and synaptic function. Our study illustrates a novel approach to the study of genotypic moderation on the impact of maternal antenatal depression on child mental health and highlights the utility of the xPRS approach. These findings advance our understanding of individual differences in the developmental origins of mental health.
We describe here efforts to create and study magnetized electron–positron pair plasmas, the existence of which in astrophysical environments is well-established. Laboratory incarnations of such systems are becoming ever more possible due to novel approaches and techniques in plasma, beam and laser physics. Traditional magnetized plasmas studied to date, both in nature and in the laboratory, exhibit a host of different wave types, many of which are generically unstable and evolve into turbulence or violent instabilities. This complexity and the instability of these waves stem to a large degree from the difference in mass between the positively and the negatively charged species: the ions and the electrons. The mass symmetry of pair plasmas, on the other hand, results in unique behaviour, a topic that has been intensively studied theoretically and numerically for decades, but experimental studies are still in the early stages of development. A levitated dipole device is now under construction to study magnetized low-energy, short-Debye-length electron–positron plasmas; this experiment, as well as a stellarator device that is in the planning stage, will be fuelled by a reactor-based positron source and make use of state-of-the-art positron cooling and storage techniques. Relativistic pair plasmas with very different parameters will be created using pair production resulting from intense laser–matter interactions and will be confined in a high-field mirror configuration. We highlight the differences between and similarities among these approaches, and discuss the unique physics insights that can be gained by these studies.
Gravitational waves from coalescing neutron stars encode information about nuclear matter at extreme densities, inaccessible by laboratory experiments. The late inspiral is influenced by the presence of tides, which depend on the neutron star equation of state. Neutron star mergers are expected to often produce rapidly rotating remnant neutron stars that emit gravitational waves. These will provide clues to the extremely hot post-merger environment. This signature of nuclear matter in gravitational waves contains most information in the 2–4 kHz frequency band, which is outside of the most sensitive band of current detectors. We present the design concept and science case for a Neutron Star Extreme Matter Observatory (NEMO): a gravitational-wave interferometer optimised to study nuclear physics with merging neutron stars. The concept uses high-circulating laser power, quantum squeezing, and a detector topology specifically designed to achieve the high-frequency sensitivity necessary to probe nuclear matter using gravitational waves. Above 1 kHz, the proposed strain sensitivity is comparable to full third-generation detectors at a fraction of the cost. Such sensitivity changes expected event rates for detection of post-merger remnants from approximately one per few decades with two A+ detectors to a few per year and potentially allow for the first gravitational-wave observations of supernovae, isolated neutron stars, and other exotica.
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.
There seems to be geographical differences in decisions about breast conserving surgery (BCS) in breast cancer patients. This study was to evaluate patients’ attitude to BCS and to assess the factors affecting cancer practice in West China.
A structured questionnaire was distributed to 184 patients, eliciting information about the patients’ characteristics, occupation, education, family life, recognition of illness, knowledge about BCS, the main means of gaining surgery information, selecting surgery approaches, preferences to breast reservation.
In all, 163 patients completed the questionnaire. The results indicated that only 7.4% of patients received BCS and 23% of the remaining patients desired to have BCS and the affecting factors were significantly associated with their family life, recognition of illness and the main means of gaining surgery information (P < 0.05). No associations were between BCS selecting and the other variables studied. The most frequent reasons for selecting BCS were keeping the female shape and improving quality of life (71%), the second most were postoperative recovery, minimal influence of physical function (47%) and patients’ knowledge about BCS (42%). The most frequent reasons for not selecting BCS were uncertainty about BCS results and worry about recurrence (81%), the second most was the elderly age unnecessary for BCS (40%).
The findings indicate that breast cancer patients in West China do not take BCS as the first choice as the best treatment method. It is warranted that further study of more patients, attitude of patients’ partners and physicians to BCS.
Effectiveness of medication treatment is determined by three components: treatment efficacy (symptom reduction), tolerability/safety, and adherence. Compared with efficacy and safety, research into adherence has been lacking. Nevertheless, medication non-adherence is a risk factor for relapse and for aggressive behavior in association with substance abuse in schizophrenia patients. Non-adherence has been estimated to cause approximately 40% of relapses in patients with schizophrenia. High rates of treatment discontinuation in all arms of the CATIE study illustrate the widespread nature of non-adherence. Most of previous research has defined non-adherence as a complete discontinuation of medication. However, many schizophrenia patients show partial adherence: they do not completely discontinue their medication, but they do not take all that has been prescribed. Partial adherence is more difficult to define and study than complete non-adherence.
e had the opportunity to study partial adherence in the context of a randomized, double-blind, 8-week, fixed-dose study comparing olanzapine 10mg/d, 20 mg/d and 40 mg/d for patients with schizophrenia or schizoaffective disorder (N=599). Medication non-adherence was measured by pill counts. Baseline characteristics including demographics, illness history and symptom severity were investigated as potential risk factors for treatment non-adherence.
Results and conclusion
Approximately 1/3 of patients were non-adherent with their medication at least once during the 8-week study. These non-adherent patients had significantly less improvement compared to adherent patients. Adherent patients had greater weight gain than the non-adherent ones. Among the available baseline measures, greater baseline depression severity appeared to be a significant risk factor for non-adherence.
Many family characteristics were reported to increase the risk of bipolar disorder (BPD). The development of BPD may be mediated through different pathways, involving diverse risk factor profiles. We evaluated the associations of family characteristics to build influential causal-pie models to estimate their contributions on the risk of developing BPD at the population level. We recruited 329 clinically diagnosed BPD patients and 202 healthy controls to collect information in parental psychopathology, parent-child relationship, and conflict within family. Other than logistic regression models, we applied causal-pie models to identify pathways involved with different family factors for BPD. The risk of BPD was significantly increased with parental depression, neurosis, anxiety, paternal substance use problems, and poor relationship with parents. Having a depressed mother further predicted early onset of BPD. Additionally, a greater risk for BPD was observed with higher numbers of paternal/maternal psychopathologies. Three significant risk profiles were identified for BPD, including paternal substance use problems (73.0%), maternal depression (17.6%), and through poor relationship with parents and conflict within the family (6.3%). Our findings demonstrate that different aspects of family characteristics elicit negative impacts on bipolar illness, which can be utilized to target specific factors to design and employ efficient intervention programs.
Depression is a common mental disorder that substantially impairs a client's functioning. the aim of this study is to examine the predictive factors of quality of life (QOL) for depression from longitudinal perspectives. 237 outpatients with depression were recruited in the study. They were from a psychiatric outpatient clinic in northern Taiwan. All subjects were tested on the baseline and followed up twice during 3-year period. the average age of subjects was 47.1 years. Most subjects were female, married and lived with their spouses.Seventy subjects participated in both follow ups (T2 and T3). there were no significant differences on the demographic characteristics at T1 between the respondents (N = 70) and non-respondents (N = 167) except for gender. the subjects were tested on the WHOQOL-BREF-Taiwan version, occupational self assessment, mastery, social support and Center of Epidemiology Study-Depression Scale (CESD). the data were analyzed by mixed effect model using SAS computer program.The severity of depression could predict overall QOL, overall health and 13 items of QOL. the type of antidepressants had significant impact on the subjects’ QOL in 10 items. the occupational competence and sense of mastery predicted 13 items (50%) and 14 items (53.8%), respectively.In order to advance the treatment outcomes, the professionals should pay more attention on the enhancement of the sense of competence and mastery. We suggested that treatments should target at improving adaptive skills, lifestyle, and occupational competence.
Previous studies showed that persons with mental illness had poorer quality of life than persons with the other medical conditions. We developed a manualized treatment - Quality of Life Enhancement Program (QOLEP) based on literature review and clinical experiences. the contents of the program include 4 sessions of ‘occupational life scheduling’ and 4 sessions of ‘coping skills’ provided by an occupational therapist during a 4-week period (2 times/week) which each session lasts for one to two hours.
Twenty-one subjects were recruited from community mental health rehabilitation centers in northern Taiwan. They were randomly assigned to either treatment group (N=11) or control group (N=10). the subjects in the control group received general supportive therapy over the phone twice a week for 4 weeks. Both groups were evaluated at baseline and posttreatment. the mixed-effects linear model was applied to analyze the efficacy of the treatment.
The results showed that the subjects who participated in the QOLEP had significantly better physical QOL than that of control group (-9.66+4.24, p< .05). the suicidal ideation of the subjects for both groups decreased over time (2.64+3.16, p< .05). Most of the participants indicated that the activities were easily understood, helpful to them, and are willing to participate in the program again.
With the program developed based on concept of occupational engagement, we were able to demonstrate the efficacy of specific treatment on quality of life and used it as evidence to support future development in mental health area.
Persistent gaming, despite acknowledgment of its negative consequences, is a major criterion for individuals with Internet gaming disorder (IGD). This study evaluated the adaptive decision-making, risky decision, and decision-making style of individuals with IGD.
We recruited 87 individuals with IGD and 87 without IGD (matched controls). All participants underwent an interview based on the Diagnostic and Statistical Manual of Mental Disorders (5th Edition) diagnostic criteria for IGD and completed an adaptive decision-making task; the Preference for Intuition and Deliberation Scale, Chen Internet Addiction Scale, and Barratt Impulsivity Scale were also assessed on the basis of the information from the diagnostic interviews.
The results demonstrated that the participants in both groups tend to make more risky choices in advantage trials where their expected value (EV) was more favorable than those of the riskless choice. The tendency to make a risky choice in advantage trials was stronger among IGD group than that among controls. Participants of both groups made more risky choices in the loss domain, a risky option to loss more versus sure loss option, than they did in the gain domain, a risky option to gain more versus sure gain. Furthermore, the participants with IGD made more risky choices in the gain domain than did the controls. Participants with IGD showed higher and lower preferences for intuitive and deliberative decision-making styles, respectively, than controls and their preferences for intuition and deliberation were positively and negatively associated with IGD severity, respectively.
These results suggested that individuals with IGD have elevated EV sensitivity for decision-making. However, they demonstrated risky preferences in the gain domain and preferred an intuitive rather than deliberative decision-making style. This might explain why they continue Internet gaming despite negative consequences. Thus, therapists should focus more on decision-making styles and promote deliberative thinking processes to mitigate the long-term negative consequences of IGD.
While a body of research has evidenced the role of pain coping in chronic pain adjustment, the role of coping flexibility in chronic pain adjustment has received little research attention. Coping flexibility can be conceptualized with two dimensions, cognitive and behavioral. The cognitive dimension of coping flexibility (or coping appraisal flexibility) refers to one's appraisal of pain experience when changing coping strategies whereas the behavioral dimension of coping flexibility denotes the variety of coping responses individuals use in dealing with stressful demands.
The aim of this paper is to present preliminary findings on the role of coping flexibility in chronic pain adjustment by assessing 3 competing models of pain coping flexibility (see Figs. 1–3).
Patients with chronic pain (n = 300) completed a battery of questionnaire assessing pain disability, discriminative facility, need for closure, pain coping behavior, coping flexibility, and pain catastrophizing. The 3 hypothesized models were tested using structural equation modeling (SEM). In all models tested, need for closure and discriminative facility were fitted as the dispositional cognitive and motivational factors respectively underlying the coping mechanism, whereas pain catastrophizing and pain intensity were included as covariates.
Results of SEM showed that the hierarchical model obtained the best data-model fit (CFI = 0.96) whereas the other two models did not attain an accept fit (CFI ranging from 0.70–0.72).
Our results lend tentative support for the hierarchical model of pain coping flexibility that coping variability mediated the effects of coping appraisal flexibility on disability.
Disclosure of interest
The authors have not supplied their declaration of competing interest.
Research evidenced the association of pain coping strategies with short-term and long-term adjustments to chronic pain. Yet, previous studies mainly assessed the frequency of coping strategies when pain occurs whilst no data is available on one's flexibility/rigidity in using different pain coping strategies, i.e., pain coping variability, in dealing with different situations.
This study aimed to examine the multivariate association between pain coping variability and committed action in predicting concurrent pain-related disability. Specifically, we examined the independent effects of pain coping variability and committed action in predicting concurrent pain-related disability in a sample of Chinese patients with chronic pain.
Chronic pain patients (n = 287) completed a test battery assessing pain intensity/disability, pain coping strategies and variability, committed action, and pain catastrophizing. Multiple regression modeling compared the association of individual pain coping strategies and pain coping variability with disability (Models 1–2), and examined the independent effects of committed action and pain coping variability on disability (Model 3).
Of the 8 coping strategies assessed, only guarding (std β = 0.17) was emerged as significant independent predictor of disability (Model 1). Pain coping variability (std β = −0.10) was associated with disability after controlling for guarding and other covariates (Model 2) and was emerged as independent predictor of disability (Model 3: std β = −0.11) (all P < 0.05) (Tables 1 and 2).
Our data offers preliminary support for the multivariate association between pain coping variability and committed action in predicting concurrent pain-related disability, which supplements the existing pain coping data that are largely based on assessing frequency of coping.
Disclosure of interest
The authors have not supplied their declaration of competing interest.
We present a detailed overview of the cosmological surveys that we aim to carry out with Phase 1 of the Square Kilometre Array (SKA1) and the science that they will enable. We highlight three main surveys: a medium-deep continuum weak lensing and low-redshift spectroscopic HI galaxy survey over 5 000 deg2; a wide and deep continuum galaxy and HI intensity mapping (IM) survey over 20 000 deg2 from
$z = 0.35$
to 3; and a deep, high-redshift HI IM survey over 100 deg2 from
$z = 3$
to 6. Taken together, these surveys will achieve an array of important scientific goals: measuring the equation of state of dark energy out to
$z \sim 3$
with percent-level precision measurements of the cosmic expansion rate; constraining possible deviations from General Relativity on cosmological scales by measuring the growth rate of structure through multiple independent methods; mapping the structure of the Universe on the largest accessible scales, thus constraining fundamental properties such as isotropy, homogeneity, and non-Gaussianity; and measuring the HI density and bias out to
$z = 6$
. These surveys will also provide highly complementary clustering and weak lensing measurements that have independent systematic uncertainties to those of optical and near-infrared (NIR) surveys like Euclid, LSST, and WFIRST leading to a multitude of synergies that can improve constraints significantly beyond what optical or radio surveys can achieve on their own. This document, the 2018 Red Book, provides reference technical specifications, cosmological parameter forecasts, and an overview of relevant systematic effects for the three key surveys and will be regularly updated by the Cosmology Science Working Group in the run up to start of operations and the Key Science Programme of SKA1.
We aimed to investigate the heterogeneity of seasonal suicide patterns among multiple geographically, demographically and socioeconomically diverse populations.
Weekly time-series data of suicide counts for 354 communities in 12 countries during 1986–2016 were analysed. Two-stage analysis was performed. In the first stage, a generalised linear model, including cyclic splines, was used to estimate seasonal patterns of suicide for each community. In the second stage, the community-specific seasonal patterns were combined for each country using meta-regression. In addition, the community-specific seasonal patterns were regressed onto community-level socioeconomic, demographic and environmental indicators using meta-regression.
We observed seasonal patterns in suicide, with the counts peaking in spring and declining to a trough in winter in most of the countries. However, the shape of seasonal patterns varied among countries from bimodal to unimodal seasonality. The amplitude of seasonal patterns (i.e. the peak/trough relative risk) also varied from 1.47 (95% confidence interval [CI]: 1.33–1.62) to 1.05 (95% CI: 1.01–1.1) among 12 countries. The subgroup difference in the seasonal pattern also varied over countries. In some countries, larger amplitude was shown for females and for the elderly population (≥65 years of age) than for males and for younger people, respectively. The subperiod difference also varied; some countries showed increasing seasonality while others showed a decrease or little change. Finally, the amplitude was larger for communities with colder climates, higher proportions of elderly people and lower unemployment rates (p-values < 0.05).
Despite the common features of a spring peak and a winter trough, seasonal suicide patterns were largely heterogeneous in shape, amplitude, subgroup differences and temporal changes among different populations, as influenced by climate, demographic and socioeconomic conditions. Our findings may help elucidate the underlying mechanisms of seasonal suicide patterns and aid in improving the design of population-specific suicide prevention programmes based on these patterns.
Although numerous studies have investigated the individual effects of salinity, irrigation and fertilization on soil microbial communities, relatively less attention has been paid to their combined influences, especially using molecular techniques. Based on the field of orthogonal designed test and deoxyribonucleic acid sequencing technology, the effects of saline water irrigation amount, salinity level of irrigation water and nitrogen (N) fertilizer rate on soil bacterial community structure were investigated. The results showed that the irrigation amount was the most dominant factor in determining the bacterial richness and diversity, followed by the irrigation water salinity and N fertilizer rate. The values of Chao1 estimator, abundance-based coverage estimator and Shannon indices decreased with an increase in irrigation amount while increased and then decreased with an increase in irrigation water salinity and N fertilizer rate. The highest soil bacterial richness and diversity were obtained under the least irrigation amount (25 mm), medium irrigation water salinity (4.75 dS/m) and medium N fertilizer rate (350 kg/ha). However, different bacterial phyla were found to respond distinctively to these three factors: irrigation amount significantly affected the relative abundances of Proteobacteria and Chloroflexi; irrigation water salinity mostly affected the members of Actinobacteria, Gemmatimonadetes and Acidobacteria; and N fertilizer rate mainly influenced the Bacteroidetes' abundance. The results presented here revealed that the assessment of soil microbial processes under combined irrigation and fertilization treatments needed to be more careful as more variable consequences would be established by comparing with the influences based on an individual factor, such as irrigation amount or N fertilizer rate.