Tag: statistics

Phys Rev Lett. 2022 Apr 22;128(16):162001. doi: 10.1103/PhysRevLett.128.162001.

ABSTRACT

Two narrow resonant states are observed in the Λ_{b}^{0}K^{-}π^{+} mass spectrum using a data sample of proton-proton collisions at a center-of-mass energy of 13 TeV, collected by the LHCb experiment and corresponding to an integrated luminosity of 6 fb^{-1}. The minimal quark content of the Λ_{b}^{0}K^{-}π^{+} system indicates that these are excited Ξ_{b}^{0} baryons. The masses of the Ξ_{b}(6327)^{0} and Ξ_{b}(6333)^{0} states are m[Ξ_{b}(6327)^{0}]=6327.28_{-0.21}^{+0.23}±0.12±0.24 and m[Ξ_{b}(6333)^{0}]=6332.69_{-0.18}^{+0.17}±0.03±0.22 MeV, respectively, with a mass splitting of Δm=5.41_{-0.27}^{+0.26}±0.12 MeV, where the uncertainties are statistical, systematic, and due to the Λ_{b}^{0} mass measurement. The measured natural widths of these states are consistent with zero, with upper limits of Γ[Ξ_{b}(6327)^{0}]<2.20(2.56) and Γ[Ξ_{b}(6333)^{0}]<1.60(1.92) MeV at a 90% (95%) credibility level. The significance of the two-peak hypothesis is larger than nine (five) Gaussian standard deviations compared to the no-peak (one-peak) hypothesis. The masses, widths, and resonant structure of the new states are in good agreement with the expectations for a doublet of 1D Ξ_{b}^{0} resonances.

PMID:35522517 | DOI:10.1103/PhysRevLett.128.162001

Phys Rev Lett. 2022 Apr 22;128(16):160601. doi: 10.1103/PhysRevLett.128.160601.

ABSTRACT

We analytically compute the full counting statistics of charge transfer in a classical automaton of interacting charged particles. Deriving a closed-form expression for the moment generating function with respect to a stationary equilibrium state, we employ asymptotic analysis to infer the structure of charge current fluctuations for a continuous range of timescales. The solution exhibits several unorthodox features. Most prominently, on the timescale of typical fluctuations the probability distribution of the integrated charge current in a stationary ensemble without bias is distinctly non-Gaussian despite diffusive behavior of dynamical charge susceptibility. While inducing a charge imbalance is enough to recover Gaussian fluctuations, we find that higher cumulants grow indefinitely in time with different exponents, implying singular scaled cumulants. We associate this phenomenon with the lack of a regularity condition on moment generating functions and the onset of a dynamical critical point. In effect, the scaled cumulant generating function does not, irrespectively of charge bias, represent a faithful generating function of the scaled cumulants, yet the associated Legendre dual yields the correct large-deviation rate function. Our findings hint at novel types of dynamical universality classes in deterministic many-body systems.

PMID:35522513 | DOI:10.1103/PhysRevLett.128.160601

J Environ Qual. 2022 May 6. doi: 10.1002/jeq2.20366. Online ahead of print.

ABSTRACT

Nitrate in subsurface tile drainage from Midwestern USA corn (Zea mays L.)-soybean [Glycine max (L.) Merr] systems is detrimental to water quality at local and national scales. The objective of this replicated plot study in Northwest Iowa, 2015-2020, was to investigate the influence of nitrogen (N) fertilizer timing on crop production and NO₃ load in subsurface (tile) drainage discharge. Four treatments applied to corn included fall anhydrous ammonia with a nitrification inhibitor (F), spring anhydrous ammonia (S), split-banded urea at planting and mid-vegetative growth (SS), and no N fertilizer (0N). Across crops and years, NO₃ -N concentration in subsurface drainage discharge was the same 11.7 mg L^-1 for F and S applied anhydrous ammonia (AA). Concentration was statistically lower with SS urea (10 mg L^-1 ) than F and S, and 0N was lower than SS at 8.3 mg L^-1 . Average annual NO₃ -N loads were not different between any treatments due to plot variability in drainage discharge. Corn responded to N application, with overall mean yield the same for F, S, and SS. There were no agronomic or water quality benefits for applying AA in the spring compared to fall, where the F included a nitrification inhibitor and was applied to cold soils. Split-applied urea had a small positive water quality impact but no crop yield enhancement. This study shows that there were improvements to NO₃ -N concentration in subsurface drainage discharge, but more nutrient reduction practices are needed than fertilizer N management alone to reduce nitrate load to surface water systems. This article is protected by copyright. All rights reserved.

PMID:35522457 | DOI:10.1002/jeq2.20366

JMIR Form Res. 2022 May 6;6(5):e34960. doi: 10.2196/34960.

ABSTRACT

BACKGROUND: Mobile health technologies can be useful for providing disease self-management information and support to people with inflammatory bowel disease (IBD).

OBJECTIVE: The aim of this study was to test a self-management SMS text messaging intervention for people with IBD. Our goal was to examine intervention feasibility, acceptability, and engagement and to preliminarily evaluate improvements in certain self-reported health outcomes among participants.

METHODS: We developed an SMS text messaging program called Text4IBD. The program sent daily support messages and resources about disease self-management over the course of a 2-week, single-group, pretest-posttest intervention to participants (N=114) diagnosed with IBD. We examined intervention feasibility, acceptability, and engagement through Text4IBD message topic recall and use of resources (ie, visiting supplemental websites recommended by the Text4IBD program). We also assessed pretest-posttest measures of IBD-related distress, self-efficacy, perceived support, use of coping strategies, and medication adherence. Analyses examined participants’ evaluations of the intervention and compared pretest-posttest changes in secondary outcomes using paired-samples statistics.

RESULTS: Approximately all participants who completed the intervention (n=105) were receptive to Text4IBD and viewed the program as feasible and acceptable. In addition, most participants (103/105, 98.1%) recalled at least one of the message topics sent by the program, and 79% (83/105) of them self-reported engaging with at least one of the external self-management resources recommended by the Text4IBD program. Pretest-posttest results showed reduced IBD-related distress (mean 3.33, SD 0.68 vs mean 2.86, SD 0.73; P<.001) and improvements in most other secondary outcomes.

CONCLUSIONS: Findings from this study highlight the value of SMS text messaging as a useful digital medium for providing support to people with IBD, particularly to those who may struggle with disease-related distress. Text4IBD was highly feasible and acceptable and may help people self-manage their IBD. Future studies should aim to evaluate this program in a randomized controlled trial in clinical settings.

PMID:35522471 | DOI:10.2196/34960

Br J Community Nurs. 2022 May 2;27(5):232-241. doi: 10.12968/bjcn.2022.27.5.232.

ABSTRACT

This systematic review and meta-analysis estimates the prevalence of common comorbid health disorders in adults with rheumatoid arthritis (RA). A multi-database search strategy was undertaken. Screening, data extraction and quality assessment were carried out by two independent reviewers. A meta-analysis and meta-regression were used to generate a pooled prevalence estimate and identify relevant moderators. After study selection, 33 studies (74633 participants) were included in the meta-analysis. Some 31 studies were judged to be of low risk of bias, and two studies were judged to be at moderate risk of bias. The three most common comorbidities in RA were anxiety disorders (62.1%, 95% Cl: 43.6%; 80.6%), hypertension (37.7%, 95% Cl: 29.2%; 46.2%) and depression (32.1%, 95% Cl: 21.6%; 42.7%). There was substantial statistically significant heterogeneity for all comorbidities (I2 ≥77%). Meta-regression identified that the covariate of mean age (unit increase) had a statistically significant effect on the prevalence of hypertension (+2.3%, 95% Cl: 0.4%; 4.2%), depression (-0.5%, 95% Cl: -0.6%; -0.4%) and cancer (0.5%, 95% Cl: 0.2%; 0.8%) in adults with RA. A country’s income was identified to have a statistically significant effect on the prevalence of depression, with low-to moderate-income countries having 40% (95% Cl: 14.0%; 66.6%) higher prevalence than high-income countries. No studies consider health inequalities. It is concluded that comorbidities are prevalent among people with RA, particularly those associated with mental health and circulatory conditions. Provision of health services should reflect the importance of such multimorbidity and the consequences for quality and length of life.

PMID:35522453 | DOI:10.12968/bjcn.2022.27.5.232

Environ Sci Pollut Res Int. 2022 May 6. doi: 10.1007/s11356-022-20379-8. Online ahead of print.

ABSTRACT

INTRODUCTION: Recent studies demonstrated that living in areas with high ambient air pollution may have adverse effects on pregnancy outcomes, but few studies have investigated its association with spontaneous abortion. Further investigation is needed to explore the acute effect and lag effect of air pollutants exposure on spontaneous abortion.

OBJECTIVE: To investigate the acute effect and lag effect between exposure to ambient air pollutants and spontaneous abortion.

METHODS: Research data of spontaneous abortion were collected from the Chongqing Health Center for Women and Children (CQHCWC) in China. The daily ambient air pollution exposure measurements were estimated for each woman using inverse distance weighting from monitoring stations. A time-stratified, case-crossover design combined with distributed lag linear models was applied to assess the associations between spontaneous pregnancy loss and exposure to each of the air pollutants over lags 0-7 days, adjusted for temperature and relative humidity.

RESULTS: A total of 1399 women who experienced spontaneous pregnancy loss events from November 1, 2016, to September 30, 2019, were selected for this study. Maternal exposure to particulate matter 2.5 (PM_2.5), particle matter 10 (PM₁₀) nitrogen dioxide (NO₂), and sulfur dioxide (SO₂) exhibited a significant association with spontaneous abortion. For every 20 μg/m³ increase in PM_2.5, PM₁₀, NO₂, and SO₂, the RRs were 1.18 (95% CI: 1.06, 1.34), 1.12 (95% CI, 1.04-1.20), 1.15 (95% CI: 1.02, 1.30), and 1.92 (95% CI: 1.18, 3.11) on lag day 3, lag day 3, lag day 0, and lag day 3, respectively. In two-pollutant model combined with PM_2.5 and PM₁₀, a statistically significant increase in spontaneous abortion incidence of 18.0% (RR = 1.18, 95% CI: 1.06, 1.32) was found for a 20 μg/m³ increase in PM_2.5 exposure, and 11.2% (RR = 1.11, 95% CI: 1.03, 1.20) for a 20 μg/m³ increase in PM₁₀ exposure on lag day 3, similar to single-pollutant model analysis.

CONCLUSION: Maternal exposure to high levels of PM_2.5, PM₁₀, NO₂, and SO₂ during pregnancy may increase the risk of spontaneous abortion for acute effects and lag effects. Further research to explore sensitive exposure time windows is needed.

PMID:35522417 | DOI:10.1007/s11356-022-20379-8

Environ Sci Pollut Res Int. 2022 May 6. doi: 10.1007/s11356-022-20196-z. Online ahead of print.

ABSTRACT

Coronavirus (COVID-19) is a highly contagious virus (SARS-CoV-2) that has caused a global pandemic since January 2020. Scientists around the world are doing extensive research to control this disease. They are working tirelessly to find out the origin and causes of the disease. Several studies and experiments mentioned that there are some meteorological parameters which are highly correlated with COVID-19 transmission. In this work, we studied the effects of 11 meteorological parameters on the transmission of COVID-19 in Bangladesh. We first applied statistical analysis and observed that there is no significant effect of these parameters. Therefore, we proposed a novel technique to analyze the insight effects of these parameters by using a combination of Random Forest, CART, and Lasso feature selection techniques. We observed that 4 parameters are highly influential for COVID-19 where [Formula: see text] and Cloud have positive association whereas WS and AQ have negative impact. Among them, Cloud has the highest positive impact which is 0.063 and WS has the highest negative association which is [Formula: see text]. Moreover, we have validated our performance using DLNM technique. The result of this investigation can be used to develop an alert system that will assist the policymakers to know the characteristics of COVID-19 against meteorological parameters and can impose different policies based on the weather conditions.

PMID:35522407 | DOI:10.1007/s11356-022-20196-z

Psicol Reflex Crit. 2022 May 6;35(1):10. doi: 10.1186/s41155-022-00212-4.

ABSTRACT

The transition from on-paper to on-screen reading seems to make it necessary to raise some considerations, as a greater attentional effort has been claimed for print texts than digital ones. Not surprisingly, most university students prefer this digital medium. This research aims to examine reading times by contextualizing this phenomenon into two processes: namely, word recognition and reading comprehension task on paper and on screen. Thus, two different tasks-counterbalanced into digital and print mediums-were carried out per each participant with a preference for a digital medium: a reading comprehension task (RCT) and a lexical decision task (LDT) after reading a specific story. Participants were slower reading print texts and no statistically significant differences were found in RCT accuracy. This result suggests that the task required more cognitive resources under the print medium for those with a worse comprehension performance in reading, and a more conservative pattern in digital RCT for those with a better performance.

PMID:35522338 | DOI:10.1186/s41155-022-00212-4

Neurosurg Rev. 2022 May 6. doi: 10.1007/s10143-022-01802-7. Online ahead of print.

ABSTRACT

Spontaneous intracerebral hemorrhage (ICH) has an increasing incidence and a worse outcome in elderly patients. The ability to predict the functional outcome in these patients can be helpful in supporting treatment decisions and establishing prognostic expectations. We evaluated the performance of a machine learning (ML) model to predict the 6-month functional status in elderly patients with ICH leveraging the predictive value of the clinical characteristics at hospital admission. Data were extracted by a retrospective multicentric database of patients ≥ 70 years of age consecutively admitted for the management of spontaneous ICH between January 1, 2014 and December 31, 2019. Relevant demographic, clinical, and radiological variables were selected by a feature selection algorithm (Boruta) and used to build a ML model. Outcome was determined according to the Glasgow Outcome Scale (GOS) at 6 months from ICH: dead (GOS 1), poor outcome (GOS 2-3: vegetative status/severe disability), and good outcome (GOS 4-5: moderate disability/good recovery). Ten features were selected by Boruta with the following relative importance order in the ML model: Glasgow Coma Scale, Charlson Comorbidity Index, ICH score, ICH volume, pupillary status, brainstem location, age, anticoagulant/antiplatelet agents, intraventricular hemorrhage, and cerebellar location. Random forest prediction model, evaluated on the hold-out test set, achieved an AUC of 0.96 (0.94-0.98), 0.89 (0.86-0.93), and 0.93 (0.90-0.95) for dead, poor, and good outcome classes, respectively, demonstrating high discriminative ability. A random forest classifier was successfully trained and internally validated to stratify elderly patients with spontaneous ICH into prognostic subclasses. The predictive value is enhanced by the ability of ML model to identify synergy among variables.

PMID:35522333 | DOI:10.1007/s10143-022-01802-7

Skeletal Radiol. 2022 May 6. doi: 10.1007/s00256-022-04070-0. Online ahead of print.

ABSTRACT

OBJECTIVE: We aimed to perform an external validation of an existing commercial AI software program (BoneView™) for the detection of acute appendicular fractures in pediatric patients.

MATERIALS AND METHODS: In our retrospective study, anonymized radiographic exams of extremities, with or without fractures, from pediatric patients (aged 2-21) were included. Three hundred exams (150 with fractures and 150 without fractures) were included, comprising 60 exams per body part (hand/wrist, elbow/upper arm, shoulder/clavicle, foot/ankle, leg/knee). The Ground Truth was defined by experienced radiologists. A deep learning algorithm interpreted the radiographs for fracture detection, and its diagnostic performance was compared against the Ground Truth, and receiver operating characteristic analysis was done. Statistical analyses included sensitivity per patient (the proportion of patients for whom all fractures were identified) and sensitivity per fracture (the proportion of fractures identified by the AI among all fractures), specificity per patient, and false-positive rate per patient.

RESULTS: There were 167 boys and 133 girls with a mean age of 10.8 years. For all fractures, sensitivity per patient (average [95% confidence interval]) was 91.3% [85.6, 95.3], specificity per patient was 90.0% [84.0,94.3], sensitivity per fracture was 92.5% [87.0, 96.2], and false-positive rate per patient in patients who had no fracture was 0.11. The patient-wise area under the curve was 0.93 for all fractures. AI diagnostic performance was consistently high across all anatomical locations and different types of fractures except for avulsion fractures (sensitivity per fracture 72.7% [39.0, 94.0]).

CONCLUSION: The BoneView™ deep learning algorithm provides high overall diagnostic performance for appendicular fracture detection in pediatric patients.

PMID:35522332 | DOI:10.1007/s00256-022-04070-0