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The objective of this paper is to predict the possible trajectory of coronavirus spread in the US. Prediction and severity ratings of COVID-19 are essential for pandemic control and economic reopening in the US.
In this paper, we apply the Logistic and Gompertz model to evaluate possible turning points of COVID-19 pandemic in different regions of the US. By combining uncertainty and severity factors, this paper constructed an indicator to assess the severity of the coronavirus outbreak in various states of the US.
Based on the index of severity ratings, different regions of the US are classified into four categories. The result shows that it is possible to identify the first turning point in Montana and Hawaii. It is unclear when the rest of the states in the US will reach the first peak. However, it can be inferred that 75% of regions in the US won’t reach the first peak of coronavirus before August 2, 2020.
It is still essential for the majority of states in the US to take proactive steps to fight against COVID-19 before August 2, 2020.
The purpose of this study was to evaluate whether loss of consciousness (LOC), retrograde amnesia (RA), and anterograde amnesia (AA) independently influence a particular aspect of post-concussion cognitive functioning—across-test intra-individual variability (IIV), or cognitive dispersion.
Concussed athletes (N = 111) were evaluated, on average, 6.04 days post-injury (SD = 5.90; Mdn = 4 days; Range = 1–26 days) via clinical interview and neuropsychological assessment. Primary outcomes of interest included two measures of IIV—an intra-individual standard deviation (ISD) score and a maximum discrepancy (MD) score—computed from 18 norm-referenced variables.
Analyses of covariance (ANCOVAs) adjusting for time since injury and sex revealed a significant effect of LOC on the ISD (p = .018, ηp2 = .051) and MD (p = .034, ηp2 = .041) scores, such that athletes with LOC displayed significantly greater IIV than athletes without LOC. In contrast, measures of IIV did not significantly differ between athletes who did and did not experience RA or AA (all p > .05).
LOC, but not RA or AA, was associated with greater variability, or inconsistencies, in cognitive performance acutely following concussion. Though future studies are needed to verify the clinical significance of these findings, our results suggest that LOC may contribute to post-concussion cognitive dysfunction and may be a risk factor for less efficient cognitive functioning.
As tugboats interact very closely with ships in restricted waters, the possibility of accidents increases in these operations. Despite the high accident possibility, there is a gap in studies on tugboat accidents. This study aims to analyse accidents involving tugboats using data mining. For this purpose, a tugboat accidents dataset consisting of a total of 496 accident records for the period from 2008 to 2019 was collected. Logistic regression and decision tree algorithms were implemented to the dataset. The results revealed that tugboat propulsion type is the most important and influential factor in the severity of tugboat accidents. The inferences drawn from these results could be beneficial for tugboat operators and port authorities in enhancing their awareness of the factors affecting tugboat accidents. In addition, the outputs of this study can be a reference for management units in developing strategies for preventing tugboat accidents and can also be used in effective planning for practicable prevention programmes and practices.
The increase in mortality and total prehospital time (TPT) seen in Qatar appear to be realistic. However, existing reports on the influence of TPT on mortality in trauma patients are conflicting. This study aimed to explore the impact of prehospital time on the in-hospital outcomes.
A retrospective analysis of data on patients transferred alive by Emergency Medical Services (EMS) and admitted to Hamad Trauma Center (HTC) of Hamad General Hospital (HGH; Doha, Qatar) from June 2017 through May 2018 was conducted. This study was centered on the National Trauma Registry database. Patients were categorized based on the trauma triage activation and prehospital intervals, and comparative analysis was performed.
A total of 1,455 patients were included, of which nearly one-quarter of patients required urgent and life-saving care at a trauma center (T1 activations). The overall TPT was 70 minutes and the on-scene time (OST) was 24 minutes. When compared to T2 activations, T1 patients were more likely to have been involved in road traffic injuries (RTIs); experienced head and chest injuries; presented with higher Injury Severity Score (ISS: median = 22); and had prolonged OST (27 minutes) and reduced TPT (65 minutes; P = .001). Prolonged OST was found to be associated with higher mortality in T1 patients, whereas TPT was not associated.
In-hospital mortality was independent of TPT but associated with longer OST in severely injured patients. The survival benefit may extend beyond the golden hour and may depend on the injury characteristics, prehospital, and in-hospital settings.
The objective of this study was to evaluate the effectiveness of a 911 trauma re-triage protocol implemented at a new community hospital in a region with a high volume of trauma and frequent transports by private vehicle.
This retrospective cohort study included all trauma patients ≥15 years old transferred via 911 trauma re-triage from a new community hospital over a 10-month period from August 2015 through April 2016. Criteria for 911 trauma re-triage were developed with input from local Emergency Medical Services (EMS) and trauma experts. An educational module, along with the criteria and implementation steps, was distributed to the emergency department (ED) personnel at the community hospital. Data were abstracted from the regional trauma registry, and the EMS patient care records were reviewed. Primary outcomes were: (1) median total transport time; and (2) proportion of patients who met the 911 re-triage criteria.
During the study period, 32 patients with traumatic injuries were transferred via 911 re-triage to the closest trauma center (TC). The median age of patients was 31 years (IQR 24-45 years) with 78% male and 66% suffering from a penetrating mechanism. The median prehospital provider scene time was 10 minutes (IQR 8-12 minutes) and transport time was seven minutes (IQR 6-9 minutes). Median total transport time was 17 minutes (IQR 15-20 minutes). Seventeen patients (53%) met 911 re-triage criteria as determined by study investigators. The most common criteria met was “penetrating injury to the head, neck, or torso” in 14 cases.
This study demonstrated that 911 re-triage was a feasible strategy to expeditiously transfer critical trauma patients to a TC within a mature trauma system in an urban-suburban setting with a median total transport time of 17 minutes.
Corona Virus Disease 2019 (COVID-19) has presented an unprecedented challenge to the health-care system across the world. The current study aims to identify the determinants of illness severity of COVID-19 based on ordinal responses. A retrospective cohort of COVID-19 patients from four hospitals in three provinces in China was established, and 598 patients were included from 1 January to 8 March 2020, and divided into moderate, severe and critical illness group. Relative variables were retrieved from electronic medical records. The univariate and multivariate ordinal logistic regression models were fitted to identify the independent predictors of illness severity. The cohort included 400 (66.89%) moderate cases, 85 (14.21%) severe and 113 (18.90%) critical cases, of whom 79 died during hospitalisation as of 28 April. Patients in the age group of 70+ years (OR = 3.419, 95% CI: 1.596–7.323), age of 40–69 years (OR = 1.586, 95% CI: 0.824–3.053), hypertension (OR = 3.372, 95% CI: 2.185–5.202), ALT >50 μ/l (OR = 3.304, 95% CI: 2.107–5.180), cTnI >0.04 ng/ml (OR = 7.464, 95% CI: 4.292–12.980), myohaemoglobin>48.8 ng/ml (OR = 2.214, 95% CI: 1.42–3.453) had greater risk of developing worse severity of illness. The interval between illness onset and diagnosis (OR = 1.056, 95% CI: 1.012–1.101) and interval between illness onset and admission (OR = 1.048, 95% CI: 1.009–1.087) were independent significant predictors of illness severity. Patients of critical illness suffered from inferior survival, as compared with patients in the severe group (HR = 14.309, 95% CI: 5.585–36.659) and in the moderate group (HR = 41.021, 95% CI: 17.588–95.678). Our findings highlight that the identified determinants may help to predict the risk of developing more severe illness among COVID-19 patients and contribute to optimising arrangement of health resources.
The generalized linear model (GLM) is a statistical model which has been widely used in actuarial practices, especially for insurance ratemaking. Due to the inherent longitudinality of property and casualty insurance claim datasets, there have been some trials of incorporating unobserved heterogeneity of each policyholder from the repeated observations. To achieve this goal, random effects models have been proposed, but theoretical discussions of the methods to test the presence of random effects in GLM framework are still scarce. In this article, the concept of Bregman divergence is explored, which has some good properties for statistical modeling and can be connected to diverse model selection diagnostics as in Goh and Dey [(2014) Journal of Multivariate Analysis, 124, 371–383]. We can apply model diagnostics derived from the Bregman divergence for testing robustness of a chosen prior by the modeler to possible misspecification of prior distribution both on the naive model, which assumes that random effects follow a point mass distribution as its prior distribution, and the proposed model, which assumes a continuous prior density of random effects. This approach provides insurance companies a concrete framework for testing the presence of nonconstant random effects in both claim frequency and severity and furthermore appropriate hierarchical model which can explain both observed and unobserved heterogeneity of the policyholders for insurance ratemaking. Both models are calibrated using a claim dataset from the Wisconsin Local Government Property Insurance Fund which includes both observed claim counts and amounts from a portfolio of policyholders.
Eating-disorder severity indicators should theoretically index symptom intensity, impairment, and level of needed treatment. Two severity indicators for binge-eating disorder (BED) have been proposed (categories of binge-eating frequency and shape/weight overvaluation) but have mixed empirical support including modest clinical utility. This project uses structural equation model (SEM) trees – a form of exploratory data mining – to empirically determine the precise levels of binge-eating frequency and/or shape/weight overvaluation that most significantly differentiate BED severities.
Participants were 788 adults with BED enrolled in BED treatment studies. Participants completed interviews and self-report measures assessing eating-disorder and comorbid symptoms. SEM Tree analyses were performed by specifying an outcome model of BED severity and then recursively partitioning the outcome model into subgroups. Subgroups were split based on empirically determined values of binge-eating frequency and/or shape/weight overvaluation. SEM Forests also quantified which variable contributed more improvement in model fit.
SEM Tree analyses yielded five subgroups, presented in ascending order of severity: overvaluation <1.25, overvaluation = 1.25–2.74, overvaluation = 2.75–4.24, overvaluation ⩾4.25 with weekly binge-eating frequency <4.875, and overvaluation ⩾4.25 with weekly binge-eating frequency ⩾4.875. SEM Forest analyses revealed that splits that occurred on shape/weight overvaluation resulted in much more improvement in model fit than splits that occurred on binge-eating frequency.
Shape/weight overvaluation differentiated BED severity more strongly than binge-eating frequency. Findings indicate a nuanced potential BED severity indicator scheme, based on a combination of cognitive and behavioral eating-disorder symptoms. These results inform BED classification and may allow for the provision of more specific and need-matched treatment formulations.
Apathy is common in Parkinson's disease (PD) but its underlying white matter (WM) architecture is not well understood. Moreover, how apathy affects cognitive functions in PD remains unclear. We investigated apathy-related WM network alterations and the impact of apathy on cognition in the context of PD.
Apathetic PD patients (aPD), non-apathetic PD patients (naPD), and matched healthy controls (HCs) underwent brain scans and clinical assessment. Graph-theoretical and network-based analyses were used for group comparisons of WM features derived from diffusion spectrum imaging (DSI). Path analysis was used to determine the direct and indirect effects of apathy and other correlates on different cognitive functions.
The aPD group was impaired on neural integration measured by global efficiency (p = 0.009) and characteristic path length (p = 0.04), executive function (p < 0.001), episodic memory (p < 0.001) and visuospatial ability (p = 0.02), and had reduced connectivity between the bilateral parietal lobes and between the putamen and temporal regions (p < 0.05). In PD, executive function was directly impacted by apathy and motor severity and indirectly influenced by depression; episodic memory was directly and indirectly impacted by apathy and depression, respectively; conversely, visuospatial ability was not related to any of these factors. Neural integration, though being marginally correlated with apathy, was not associated with cognition.
Our results suggest compromised neural integration and reduced structural connectivity in aPD. Apathy, depression, and motor severity showed distinct impacts on different cognitive functions with apathy being the most influential determinant of cognition in PD.
Chronic obstructive pulmonary disease (COPD) is a chronic respiratory disease that may have a negative impact on both patients’ quality of life and survival. Patients with COPD frequently suffer from heart failure (HF), likely owing to several shared risk factors.
To evaluate the differences in treatment of COPD with and without HF comorbidity according to COPD severity in the general practitioner setting.
We conducted an observational, retrospective study using data obtained from the Italian Health Search Database, which collects information generated by the routine activity of general practitioners. The study sample included 225 patients with COPD, alone or combined with HF.
It has been found that the prevalence of some comorbidities such as diabetes and HF significantly increases with the severity of COPD. Regarding pharmacological treatment, a reduction in the prescription of individually administered long-acting β 2-agonists (LABAs) and long-acting anticholinergics (LAMAs) has been observed with increasing severity of the disease. Moreover, an increase in the prescription of both the combination of the two bronchodilators (LABA + LAMA) and their association with inhaled corticosteroids has been observed with increasing severity of COPD. The prescription of β-blockers in patients with COPD suffering from HF comorbidity decreases from 100% in stage I to less than 50% in the other stages of COPD. This study shows that general practitioners do not follow the guidelines recommendations for the management of patients with COPD in the different stages of the disease, with and without HF comorbidity, as well as in the management of HF. Further efforts must be made to ensure adequate treatment for these patients.
Hypertension is a common comorbidity in COVID-19 patients. However, the association of hypertension with the severity and fatality of COVID-19 remain unclear. In the present meta-analysis, relevant studies reported the impacts of hypertension on SARS-CoV-2 infection were identified by searching PubMed, Elsevier Science Direct, Web of Science, Wiley Online Library, Embase and CNKI up to 20 March 2020. As the results shown, 12 publications with 2389 COVID-19 patients (674 severe cases) were included for the analysis of disease severity. The severity rate of COVID-19 in hypertensive patients was much higher than in non-hypertensive cases (37.58% vs 19.73%, pooled OR: 2.27, 95% CI: 1.80–2.86). Moreover, the pooled ORs of COVID-19 severity for hypertension vs. non-hypertension was 2.21 (95% CI: 1.58–3.10) and 2.32 (95% CI: 1.70–3.17) in age <50 years and ⩾50 years patients, respectively. Additionally, six studies with 151 deaths of 2116 COVID-19 cases were included for the analysis of disease fatality. The results showed that hypertensive patients carried a nearly 3.48-fold higher risk of dying from COVID-19 (95% CI: 1.72–7.08). Meanwhile, the pooled ORs of COVID-19 fatality for hypertension vs. non-hypertension was 6.43 (95% CI: 3.40–12.17) and 2.66 (95% CI: 1.27–5.57) in age <50 years and ⩾50 years patients, respectively. Neither considerable heterogeneity nor publication bias was observed in the present analysis. Therefore, our present results provided further evidence that hypertension could significantly increase the risks of severity and fatality of SARS-CoV-2 infection.
The A1 allele of the D2 dopamine receptor (DRD2) gene has been associated with alcohol dependence. However, the expression of this allele risk on the severity of drinking behavior in patients with alcohol dependence has not been systematically explored. The present study examines the association between DRD2 A1+(A1/A1 and A1/A2 genotypes) and A1– (A2/A2 genotype) allele status and key drinking parameters in alcohol-dependent patients. A sample of Caucasian adults was recruited from an alcohol detoxification unit. A clinical interview and the Alcohol Dependence Scale (ADS) questionnaire provided data on consumption, dependence, chronology of drinking and prior detoxification. A1+ allele compared to A1– allele patients consumed higher quantities of alcohol, commenced problem drinking at an earlier age, experienced a shorter latency between first introduction to alcohol to the onset of problem drinking and had higher ADS scores. Moreover, A1+ allele patients had more detoxification attempts than their A1– allele counterparts. In sum, alcohol-dependent patients with the DRD2 A1 allele compared to patients without this allele are characterized by greater severity of their disorder across a range of problem drinking indices. The implications of these findings are discussed.
Prevalence of psychotic depression, and comparison between psychotic and nonpsychotic depression, were studied in 203 consecutive unipolar and bipolar outpatients presenting for treatment of depression in a private practice. Prevalence was 14%. Of the variables investigated (unipolar/bipolar diagnosis, age at baseline/onset, gender, recurrences, atypical features, comorbidity, chronicity, duration of illness, baseline severity) bipolar I diagnosis was significantly more common, and severity of depression was significantly greater in psychotic vs nonpsychotic depression. Discordant findings in the literature may be related to the different samples studied.
This study evaluates the relationship between stress of captivity and subsequent presence of Post Traumatic Stress Disorder (PTSD) has been evaluated in a homogeneous population of 817 Alsatian World War II veterans who were imprisoned in the USSR during and after the war. Data were collected in 1988 by a questionnaire structured to investigate the presence of DSM-III-R criteria for PTSD as well as events experienced in captivity. The presumptive diagnosis of PTSD was found to be significantly associated with longer internment and with higher scores on a severity of POW experience index.
The influence of severity of personality disorder on outcome of depression is unclear. Four hundred and ten patients with depression in 9 urban and rural communities in Finland, Ireland, Norway, Spain and the United Kingdom, were randomised to individual problem-solving treatment (n = 121), group sessions on depression prevention (n = 106) or treatment as usual (n = 183). Depressive symptoms were recorded at baseline, 6 and 12 months. Personality assessment was performed using the Personality Assessment Schedule and analysed by severity (no personality disorder, personality difficulty, simple personality disorder, complex personality disorder). Complete personality assessments were performed on 301 individuals of whom 49.8% had no personality disorder; 19.3% had personality difficulties; 13.0% had simple personality disorder; and 17.9% had complex personality disorder. Severity of personality disorder was correlated with Beck Depression Inventory (BDI) scores at baseline (Spearman's r = 0.21; p < 0.001), 6 months (r = 0.14; p = 0.02) and 12 months (r = 0.21; p = 0.001). On multi-variable analysis, BDI at baseline (p < 0.001) and type of treatment offered (individual therapy, group therapy, treatment as usual) (p = 0.01) were significant independent predictors of BDI at 6 months. BDI at baseline was the sole significant independent predictor of BDI at 12 months (p < 0.001). There was no interaction between personality disorder and treatment type for depression.
While multi-variable analyses indicate that depressive symptoms at baseline are the strongest predictor of depressive symptoms at 6 and 12 months, the strong correlations between severity of personality disorder and depressive symptoms make it difficult to establish the independent effect of personality disorder on outcome of depression.
The objective of the present study was to examine the association between ADHD severity and the lifetime prevalence of comorbid depressive episodes and anxiety disorders in adults with ADHD.
Subjects/materials and methods:
Analyses were based on data of the Conner's Adult ADHD Rating Scale (CAARS) and a parent study examining the epidemiology of adult ADHD in 17 GP practices in Budapest, Hungary. Subjects between 18 and 60 years were included in the screening phase (n = 3529). Out of 279 positively screened subjects 161 participated in a clinical interview and completed the CAARS to confirm the diagnosis. We applied four diagnostic criteria: “DSM-IV”; “No-onset” (DSM-IV criteria without the specific requirement for onset); “Symptoms-only” (DSM-IV symptom criterion only); and “Reduced symptoms-only” (DSM-IV symptom criterion with a reduced threshold for symptom count). The MINI PLUS 5.0 was used to assess psychiatric comorbidity.
ADHD severity, as measured by the CAARS ADHD Index, showed a significant positive association with the prevalence of comorbid depressive episodes in all but the “ADHD_No-onset” group (“DSM-IV”: F[1.23] = 8.39, P = 0.0081; “No-onset”: F(1.27) = 0.97, P = 0.3346; “Symptoms-only”: F[1.55] = 30.79, P < 0.0001; “Reduced symptoms-only”: F(1.62) = 26.69, P < 0.0001).
Discussion and conclusion:
Results indicate that ADHD symptom severity increases in association with lifetime comorbidity with depression.
Since approximately 70% of adult patients with attention-deficit/hyperactivity disorder (ADHD) have at least one comorbid disorder, rating of impairment specifically attributable to ADHD is a hard task. Despite the evidence linking environmental adversities with negative outcomes in ADHD, life events measures have not been used to rate the disorder impairment. The present study tested for the first time the hypothesis that increased ADHD severity is associated with an increase in negative recent life events, independently of comorbidity status. The psychiatric diagnoses of 211 adult ADHD outpatients were based on DSM-IV criteria assessed through structured interviews (K-SADS-E for ADHD and ODD, MINI for ASPD and SCID-IV-R for other comorbidities). ADHD severity was evaluated with the Swanson, Nolan and Pelham rating scale (SNAP-IV) and recent life events with the Life Experience Survey. Higher SNAP-IV inattention and hyperactivity scores, female gender, lower socioeconomic status and the presence of comorbid mood disorders were associated with negative life events. Poisson regression models with adjustment for possible confounders confirmed the effect of inattention and hyperactivity severity on negative life events. Our results suggest that the negative life events experienced by these patients are associated to the severity of ADHD independently from comorbid psychiatric disorders.
The links between ADHD and addictive disorders have been the subject of a large number of studies showing a high prevalence rate of ADHD in substance abusing populations as well as an increased risk of substance use disorder (SUD) in ADHD patients that may be independent of other psychiatric conditions. High prevalence of ADHD has also been highlighted among individuals suffering from other addictive disorders such as pathological gambling. Adequate diagnosis of ADHD in SUD patients is challenged by phenomenological aspects of addiction and by frequently associated other psychiatric disorders that overlap with key symptoms of ADHD. A detailed comprehensive search for child and adult symptoms including the temporal relationship of ADHD, substance use and other psychiatric disorders should maximize the validity and the reliability of adult ADHD diagnosis in this population. Further, a follow-up evaluation of ADHD symptoms during treatment of SUD may reduce the likelihood of misdiagnosis. Finally, it should be noticed that when SUD occurs with ADHD, it is associated with a greater severity of SUD compared to other SUD patients. This has been shown with an earlier age at onset, antisocial behavior, risk for depression, chronicity of substance use, need for hospitalization and likelihood of a complicated course. Recent data suggest that the effects of ADHD on SUD outcomes are independent of other psychiatric comorbidities. This highlights the need of an earlier implementation of preventive interventions for substance use or behavioral addiction in children/adolescents with ADHD and the necessity to consider this disorder in the treatment of addictive disorders. Benefices and risk of MPH in adult patients with addiction and ADHD are discussed.
Deliberate self-harm (DSH) causes important concern in prison inmates as it worsens morbidity and increases the risk for suicide. The aim of the present study is to investigate the prevalence and correlates of DSH in a large sample of male prisoners.
A cross-sectional study evaluated male prisoners aged 18+ years. Current and lifetime psychiatric diagnoses were assessed with the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders - DSM-IV Axis I and Axis II Disorders and with the Addiction Severity Index-Expanded Version. DSH was assessed with The Deliberate Self-Harm Inventory. Multivariable logistic regression models were used to identify independent correlates of lifetime DSH.
Ninety-three of 526 inmates (17.7%) reported at least 1 lifetime DSH behavior, and 58/93 (62.4%) of those reported a DSH act while in prison. After multivariable adjustment (sensitivity 41.9%, specificity 96.1%, area under the curve = 0.854, 95% confidence interval CI = 0.811–0.897, P < 0.001), DSH was significantly associated with lifetime psychotic disorders (adjusted Odds Ratio aOR = 6.227, 95% CI = 2.183–17.762, P = 0.001), borderline personality disorder (aOR = 6.004, 95% CI = 3.305–10.907, P < 0.001), affective disorders (aOR = 2.856, 95% CI = 1.350–6.039, P = 0.006) and misuse of multiple substances (aOR = 2.024, 95% CI = 1.111–3.687, P = 0.021).
Borderline personality disorder and misuse of multiple substances are established risk factors of DSH, but psychotic and affective disorders were also associated with DSH in male prison inmates. This points to possible DSH-related clinical sub-groups, that bear specific treatment needs.
Previous studies have demonstrated that family history is associated with earlier age at onset, severity of positive and negative symptoms, and the duration of untreated illness. Hereditary factors may contribute a vulnerability for antisocial and/or violent behaviour per se, and for other stable characteristics such as aggressive behaviour.
To analyze the impact of family history of schizophrenia and aggressive behavior among members of family on severity of disease and aggressive behavior of patients.
The study population consisted of 120 male schizophrenic patients classified into non-aggressive (n = 60) and aggressive (n = 60) groups, based on indication for admission in hospital (aggression/anything else but aggression). For severity of disease, we assessed psychopathology using the Positive and Negative Syndrome Scale (PANSS), the number of hospitalizations and the total equivalent dose of therapy (collected from medical record). The presence of a family history and aggression in family was assessed using a semi-structured interview of patients and, when available, family members.
Twenty-seven (22.5%) participants were determined to have at least one family member with schizophrenia or another psychotic disorder, with no difference between aggressive (10%) and non-aggressive (12.5%) group. There was no significant interaction between family history and severity of disease (PANSS, number of hospitalizations, total equivalent dose of therapy). Aggressive behaviour in first-degree family member had no influence on aggressive behaviour of patients with schizophrenia.
Family history of schizophrenia does not affect the severity of disease nor aggressive behaviour.
Disclosure of interest
The authors have not supplied their declaration of competing interest.