STATISTICAL CONTROL OF PROCESSES AND PRODUCTS IN AGRICULTURE

Osnovni koncept statističke kontrole procesa temelji se na uspoređivanju podataka dobivenih iz procesa s izračunatim kontrolnim granicama te na osnovi toga donošenje zaključaka o samome procesu. Statistička kontrola procesa i kvalitete poljoprivrednih proizvoda koristi se da bi se osigurala kakvoća proizvoda koji će zadovoljiti zahtjeve kupaca, u pogledu kvalitete i u cijeni koštanja istih. U skladu sa standardima ISO 9000, utvrđene su norme kvalitete proizvoda i procesa. Mnoge institucije u Hrvatskoj prihvatile su zadane norme i rade u skladu s njima. Da bi se što više približili zadanim normama i smanjili troškove proizvodnje, pravilna primjena statističke kontrole kvalitete i kontrolnih karata može biti od velike koristi. Za ilustraciju navedenoga, ispitana je kvaliteta rada mlaznice prskalice zahvata osamnaest metara.Fundamental concept of statistical process control is based on decision-making about the process on the basis of comparison of data collected from process with calculated control limits. Statistical process and quality control of agricultural products is used to provide agricultural products that will satisfy customer requirements in a view of quality pretension as well as costumer requirements in a cost price. In accordance with ISO 9000, quality standards for process and products are defined. There are many institutions in Croatia that work in accordance with these standards. Implementation of statistical process control and usage of a control charts can greatly help in convergence to the standards and in decreasing of production costs. To illustrate the above mentioned we tested a work quality of a nozzle at the eighteen meter clutch sprayer

White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group

White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the generalizability of OCD classification based on diffusion white matter estimates remains unclear. Here, we tested classification accuracy using the largest OCD DTI dataset to date, involving 1336 adult participants (690 OCD patients and 646 healthy controls) and 317 pediatric participants (175 OCD patients and 142 healthy controls) from 18 international sites within the ENIGMA OCD Working Group. We used an automatic machine learning pipeline (with feature engineering and selection, and model optimization) and examined the cross-site generalizability of the OCD classification models using leave-one-site-out cross-validation. Our models showed low-to-moderate accuracy in classifying (1) “OCD vs. healthy controls” (Adults, receiver operator characteristic-area under the curve = 57.19 ± 3.47 in the replication set; Children, 59.8 ± 7.39), (2) “unmedicated OCD vs. healthy controls” (Adults, 62.67 ± 3.84; Children, 48.51 ± 10.14), and (3) “medicated OCD vs. unmedicated OCD” (Adults, 76.72 ± 3.97; Children, 72.45 ± 8.87). There was significant site variability in model performance (cross-validated ROC AUC ranges 51.6–79.1 in adults; 35.9–63.2 in children). Machine learning interpretation showed that diffusivity measures of the corpus callosum, internal capsule, and posterior thalamic radiation contributed to the classification of OCD from HC. The classification performance appeared greater than the model trained on grey matter morphometry in the prior ENIGMA OCD study (our study includes subsamples from the morphometry study). Taken together, this study points to the meaningful multivariate patterns of white matter features relevant to the neurobiology of OCD, but with low-to-moderate classification accuracy. The OCD classification performance may be constrained by site variability and medication effects on the white matter integrity, indicating room for improvement for future research

Reply to: New Meta- and Mega-analyses of Magnetic Resonance Imaging Findings in Schizophrenia: Do They Really Increase Our Knowledge About the Nature of the Disease Process?

This work was supported by National Institute of Biomedical Imaging and Bioengineering Grant No. U54EB020403 (to the ENIGMA consortium)

Incident acute coronary syndromes in chronic dialysis patients in the United States11The opinions are solely those of the authors and do not represent an endorsement by the Department of Defense or the National Institutes of Health. This is a U.S. Government work. There are no restrictions on its use.

Incident acute coronary syndromes in chronic dialysis patients in the United States.BackgroundPatients on dialysis have a disproportionately high rate of cardiovascular disease (CVD). However, the incidence and risk factors for incident acute coronary syndromes (ACS) have not been previously assessed in dialysis patients.MethodsWe analyzed the United States Renal Data System (USRDS) Dialysis Morbidity and Mortality Study (DMMS) Wave II in a historical cohort study of ACS. Data from 3374 patients who started dialysis in 1996 with valid follow-up times were available for analysis, censored at the time of renal transplantation and followed until March 2000. Cox regression analysis was used to model factors associated with time to first hospitalization for ACS (ICD9 code 410.x or 411.x) adjusted for comorbidities, demographic factors, baseline laboratory values, blood pressures and cholesterol levels, type of vascular access, dialysis adequacy, and cardioprotective medications (angiotensin-converting enzyme inhibitors, calcium channel blockers, HMG-CoA reductase inhibitors (statins), beta blockers, and aspirin). Follow-up was 2.19 ± 1.14 years.ResultsThe incidence of ACS was 29/1000 person-years. Factors associated with ACS were older age, the extreme high and low ranges of serum cholesterol level, history of coronary heart disease (CHD), male gender, and diabetes. No cardioprotective medications including statins had a significant association with ACS in this study. However, medications known to reduce mortality after ACS were used in less than 50% of patients with known CHD at the start of the study, and statins were used in less than 10% of patients with CHD.ConclusionsDialysis patients had similar risk factors for ACS compared to the general population. Cardioprotective medications were not associated with a significant benefit, possibly due to their striking underutilization in this at-risk population

Positive symptoms associate with cortical thinning in the superior temporal gyrus via the ENIGMA-Schizophrenia consortium

Objective: Based on the role of the superior temporal gyrus (STG) in auditory processing, language comprehension and self-monitoring, this study aimed to investigate the relationship between STG cortical thickness and positive symptom severity in schizophrenia. Method: This prospective meta-analysis includes data from 1987 individuals with schizophrenia collected at seventeen centres around the world that contribute to the ENIGMA Schizophrenia Working Group. STG thickness measures were extracted from T1-weighted brain scans using FreeSurfer. The study performed a meta-analysis of effect sizes across sites generated by a model predicting left or right STG thickness with a positive symptom severity score (harmonized SAPS or PANSS-positive scores), while controlling for age, sex and site. Secondary models investigated relationships between antipsychotic medication, duration of illness, overall illness severity, handedness and STG thickness. Results: Positive symptom severity was negatively related to STG thickness in both hemispheres (left: βstd = −0.052; P = 0.021; right: βstd = −0.073; P = 0.001) when statistically controlling for age, sex and site. This effect remained stable in models including duration of illness, antipsychotic medication or handedness. Conclusion: Our findings further underline the important role of the STG in hallmark symptoms in schizophrenia. These findings can assist in advancing insight into symptom-relevant pathophysiological mechanisms in schizophrenia

White matter microstructure and its relation to clinical features of obsessive–compulsive disorder: findings from the ENIGMA OCD Working Group

Microstructural alterations in cortico-subcortical connections are thought to be present in obsessive–compulsive disorder (OCD). However, prior studies have yielded inconsistent findings, perhaps because small sample sizes provided insufficient power to detect subtle abnormalities. Here we investigated microstructural white matter alterations and their relation to clinical features in the largest dataset of adult and pediatric OCD to date. We analyzed diffusion tensor imaging metrics from 700 adult patients and 645 adult controls, as well as 174 pediatric patients and 144 pediatric controls across 19 sites participating in the ENIGMA OCD Working Group, in a cross-sectional case-control magnetic resonance study. We extracted measures of fractional anisotropy (FA) as main outcome, and mean diffusivity, radial diffusivity, and axial diffusivity as secondary outcomes for 25 white matter regions. We meta-analyzed patient-control group differences (Cohen’s d) across sites, after adjusting for age and sex, and investigated associations with clinical characteristics. Adult OCD patients showed significant FA reduction in the sagittal stratum (d = −0.21, z = −3.21, p = 0.001) and posterior thalamic radiation (d = −0.26, z = −4.57, p < 0.0001). In the sagittal stratum, lower FA was associated with a younger age of onset (z = 2.71, p = 0.006), longer duration of illness (z = −2.086, p = 0.036), and a higher percentage of medicated patients in the cohorts studied (z = −1.98, p = 0.047). No significant association with symptom severity was found. Pediatric OCD patients did not show any detectable microstructural abnormalities compared to controls. Our findings of microstructural alterations in projection and association fibers to posterior brain regions in OCD are consistent with models emphasizing deficits in connectivity as an important feature of this disorder

Smaller spared subcortical nuclei are associated with worse post-stroke sensorimotor outcomes in 28 cohorts worldwide

Up to two-thirds of stroke survivors experience persistent sensorimotor impairments. Recovery relies on the integrity of spared brain areas to compensate for damaged tissue. Deep grey matter structures play a critical role in the control and regulation of sensorimotor circuits. The goal of this work is to identify associations between volumes of spared subcortical nuclei and sensorimotor behaviour at different timepoints after stroke. We pooled high-resolution T1-weighted MRI brain scans and behavioural data in 828 individuals with unilateral stroke from 28 cohorts worldwide. Cross-sectional analyses using linear mixed-effects models related post-stroke sensorimotor behaviour to non-lesioned subcortical volumes (Bonferroni-corrected, P < 0.004). We tested subacute (≤90 days) and chronic (≥180 days) stroke subgroups separately, with exploratory analyses in early stroke (≤21 days) and across all time. Sub-analyses in chronic stroke were also performed based on class of sensorimotor deficits (impairment, activity limitations) and side of lesioned hemisphere. Worse sensorimotor behaviour was associated with a smaller ipsilesional thalamic volume in both early (n = 179; d = 0.68) and subacute (n = 274, d = 0.46) stroke. In chronic stroke (n = 404), worse sensorimotor behaviour was associated with smaller ipsilesional putamen (d = 0.52) and nucleus accumbens (d = 0.39) volumes, and a larger ipsilesional lateral ventricle (d = -0.42). Worse chronic sensorimotor impairment specifically (measured by the Fugl-Meyer Assessment; n = 256) was associated with smaller ipsilesional putamen (d = 0.72) and larger lateral ventricle (d = -0.41) volumes, while several measures of activity limitations (n = 116) showed no significant relationships. In the full cohort across all time (n = 828), sensorimotor behaviour was associated with the volumes of the ipsilesional nucleus accumbens (d = 0.23), putamen (d = 0.33), thalamus (d = 0.33) and lateral ventricle (d = -0.23). We demonstrate significant relationships between post-stroke sensorimotor behaviour and reduced volumes of deep grey matter structures that were spared by stroke, which differ by time and class of sensorimotor measure. These findings provide additional insight into how different cortico-thalamo-striatal circuits support post-stroke sensorimotor outcomes

Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning)