Browse Articles

Research on the reliability of the overall structure of submerged radial steel gate

The safety assessment of steel gate structures holds significant social importance and economic advantages. The safety of steel gate structure is influenced by numerous random factors, so it is necessary to carry out the reliability analysis of steel gate structure. Currently, research on the reliability of steel gate structures predominantly focuses on individual components, cross-sections, or localized areas, and there are relatively few studies on the reliability of the overall structure of the steel gate. Furthermore, most of the studies only consider the role of hydrostatic pressure load, often underestimating the impact of other dynamic load combinations. Therefore, this study calculates the strength and stiffness of the overall submerged radial steel gate structure under various loading conditions, including hydrostatic pressure, hydrodynamic pressure and sediment pressure. Additionally, it conducts the analysis of the reliability regarding the overall structure of the submerged radial steel gate. The results indicate that the maximum stress and displacement values conform to the allowable limits established by relevant design codes, with the maximum stress occurring at the support hinge. The reliability analysis of the submerged radial steel gate structure was performed by considering different load combinations and material parameters as random variables, and the structure was safe at a 95% confidence level. Additionally, the sensitivity analysis of the steel gate structure was conducted, and the results showed that the hydrodynamic pressure and elastic modulus had a higher degree of influence on the results of displacement calculations, while other parameters had a relatively low degree of influence. Similarly, the hydrodynamic pressure had a greater influence on the results of stress calculations, while other parameters had a relatively small influence.

Zhuang-Mandarin bilingual children in rural China and the role of grandparental input in early bilingualism

Linguistic properties of bilingual input and their relations with acquisition outcomes are being intensively studied in current research on early bilingual development. Motivated by emerging interests in grandparental input and the unique language profile of Zhuang-Mandarin bilinguals in rural China, this article reports an exploratory study investigating bilingual input-outcome relations in two groups of age-matched kindergarteners who were primarily cared for by Zhuang-speaking grandmothers (GRA group, n = 4) and by Zhuang-Mandarin bilingual mothers (MOT group, n = 5) respectively. Through (grand)parental questionnaires, caregiver-child interaction recordings and direct assessments of the children, we collected two waves of data around the beginning and the end of Mandarin-medium kindergarten, focusing on the input and the outcomes respectively (Time 1/Time 2 design). Our findings show that at both times, the grandparents spoke considerably larger proportions of Zhuang to the children than the mothers, who had completely shifted to Mandarin by Time 2. Both groups of children were dominant in Mandarin at Time 2, demonstrating quantitatively and qualitatively similar production performance, but only the GRA children were able to produce words and narratives in Zhuang. It is argued that early sequential bilingualism actively promoting and supporting grandparental input in Zhuang in addition to school input in Mandarin is beneficial to the preservation of Zhuang as a minority language and mastery of the national majority language. Implications for language intervention and planning concerning minority languages in rural China are discussed.

Who is on RFK Jr’s new vaccine panel — and what will they do?

Investigating immune amnesia after measles virus infection in two West African countries: A study protocol

“Investigation of Immune Amnesia Following Measles Infection in Select African Regions” (ClinicalTrials.gov Identifier: NCT06153979) is a prospective, observational, longitudinal study being conducted in two West African countries; Guinea and Mali. Acute measles virus (MeV) infection has been shown to result in a loss of pre-existing immunity (immune amnesia). MeV-induced immune amnesia has not been studied in West Africa where continual MeV outbreaks occur. Additionally previous studies have relied on naturally occurring exposures to viruses to examine the immune systems ability to create antibodies. Thus, the overall goal of this protocol is to investigate the impact of MeV infection on pre-existing immunity to endemic pathogens in West Africa, observe the effect of a subsequent exposure to a novel pathogen (rabies vaccine), and measure the frequency of subsequent healthcare visits. A total of 256 children aged 1–15 years are being enrolled into one of two study arms: those with acute MeV infection (cases) as confirmed by laboratory testing and without (controls). Controls must be immune to MeV (have IgG). Blood samples are collected at multiple time points including screening (Day 0), at an optional visit to repeat IgM serology for inconclusive or negative Day 0 results (Day 7–10), and during follow-up visits on Day 14, Week 13, and Week 52. These blood samples will be tested to evaluate both humoral and cellular immune responses to a panel of viruses, bacteria, and parasites, including pathogens endemic to West Africa. To explore how recent MeV infection may affect the child’s ability to respond to a new exposure, all participants will receive a rabies vaccine (as a controlled stimulus) at one of two timepoints post Day 0 visit. Biological samples will be collected after vaccination to assess if the rabies vaccine response differs: 1) between cases and controls, and 2) based on the time since acute MeV infection. In addition, the study team will collect information on healthcare encounters during the year-long follow-up to determine if there is a difference in the number of encounters by study group. The findings of this study will further the understanding of the MeV immune amnesia phenotype by understanding its impact on endemic pathogens and subsequent immune response following infection.

Cheat-proof random numbers generated from quantum entanglement

Probing phonon transport dynamics across an interface by electron microscopy

Abstract Understanding thermal transport mechanisms across material interfaces is crucial for advancing semiconductor technologies, particularly in miniaturized devices operating under extreme power densities 1,2 . Although the interface phonon-mediated processes are theoretically established 3–6 as the dominant mechanism for interfacial thermal transport in semiconductors 7 , their nanoscale dynamics remain experimentally elusive owing to challenges in measuring the temperature and non-equilibrium phonon distributions across the buried interface 8–11 . Here we overcome these limitations by using in situ vibrational electron energy-loss spectroscopy (EELS) in an electron microscope to nanoscale profile temperature gradients across the AlN–SiC interface during thermal transport and map its non-equilibrium phonon occupations at sub-nanometre resolution. We observe a sharp temperature drop within about 2 nm across the interface, enabling direct extraction of relative interfacial thermal resistance (ITR). During thermal transport, the mismatch of phonon modes’ thermal conductivity at the interface causes substantial non-equilibrium phonons nearby, making the populations of interface modes different under forward and reverse heat flow and also leading to marked changes in the modal temperature of AlN optical phonons within about 3 nm of the interface. These results reveal the phonon transport dynamics at the (sub-)nanoscale and establish the inelastic phonon scattering mechanism involved by interface modes, offering valuable insights into the engineering of thermal interfaces.

A new Mongolian tyrannosauroid and the evolution of Eutyrannosauria

Traceable random numbers from a non-local quantum advantage

Effects of pension eligibility expansion on men’s memory decline and dementia probability: Findings from the HAALSI cohort in rural South Africa, 2014–2021

Alzheimer’s disease and related dementias (ADRD) are a growing global health concern, with burdens projected to expand rapidly in the coming decades. Since cognitive decline typically precedes ADRD, it is crucial to identify interventions that may help slow cognitive decline and reduce ADRD risk. We used a quasi-experimental design, exploiting exogenous expansions of South Africa’s Older Persons Grant for men, to estimate its impact on memory decline and ADRD risk in the rural Mpumalanga province of South Africa. We found that expanded pension eligibility was associated with slower memory decline for men who were eligible to receive the pension 5 years earlier [β = 0.027 SD, 95% CI = 0.023, 0.031], as well as for men who were eligible to receive the pension 1−4 years earlier [β = 0.009 SD, 95% CI = 0.004, 0.013]. We also found a 5.2 percentage point lower probability of dementia for men who were eligible for pension 5 years earlier [95% CI = −0.062, −0.032] and a 4.8 percentage point lower probability of dementia for men who became eligible to receive pension 1−4 years earlier [95% CI = −0.062, −0.032]. These findings demonstrate that beyond the policy intent of cash transfers to strengthen individual and household livelihoods, an important further benefit lies in promoting healthy cognitive aging in low- and middle- income countries.

A crowding free digital interface to help French-speaking children learn to read

Learning to read is a challenging task for first-graders. Letter crowding in the peripheral visual field has been identified as a key interference process during reading acquisition. To reduce crowding and enhance selective attention, we designed a new way to read (Digit-tracking) in which words and sentences appear blurred. By sliding the index finger along the blurred text, the letters just above the finger position appear unblurred and are seen in foveal vision. We hypothesized that this approach might facilitate orthographic decoding and promote reading skills. Using a tablet device, two groups of first-grade children (N = 54) were trained on digit-tracking exercises and paper exercises using a crossover design. Results showed that performance in letter, syllable and meaningless text-reading was significantly higher after digit-tracking training compared to paper-based training. Using the recorded finger trajectories as a proxy for eye movements, we found that text scanning patterns (saccade length, landing position, regressive saccades) predicted children’s decoding and fluency. We conclude that training with the digit-tracking procedure accelerates decoding and reading fluency in school beginners and may provide a sensitive metric of reading competence.

The influence of hydrogel stiffness on axonal regeneration after spinal cord injury

The core challenge in spinal cord injury(SCI) treatment is promoting axonal regeneration and forming new neural connections in damaged areas. However, mature CNS neurons have limited regenerative capacity, causing long-term dysfunction. Axonal regeneration involves elongating axons guided by growth cones, which sense and respond to external mechanical signals, integrating them into cytoskeleton reconstruction. After injury, growth cones experience altered mechanical forces due to changes in ECM stiffness. However, systematic studies on matrix stiffness’s impact on axonal regeneration post-SCI remain insufficient. This study investigates the influence of hydrogel stiffness on axonal regeneration following SCI. Using gelatin methacryloyl (GelMA) hydrogels with varying stiffness levels, we cultured dorsal root ganglia (DRG) neurons in vitro and applied the hydrogels to a complete transection SCI mouse model. Results demonstrated that higher stiffness GelMA (15% w/v) significantly enhanced axonal extension and sensory functional recovery compared to lower stiffness (7.5% w/v). The study highlights the critical role of ECM stiffness in regulating axonal regeneration and suggests that optimizing hydrogel stiffness can promote neural regeneration and functional recovery after SCI. These findings provide valuable insights for developing therapeutic strategies in SCI treatment.

TLINet: A defects detection method for insulators of overhead transmission lines using partially transformer block

The defects of insulators exhibit characteristics such as complex backgrounds, multi-scale variations, and small object sizes. Therefore, accurately focusing on these defects in dynamic and complex natural environments while maintaining inference speed remains a pressing challenge. To address this issue, this paper proposes an innovative insulator defect detection network, TLINet. First, a Multi-Branch Partially Transformer Block (MBPTB) is designed to enhance the backbone’s capability in capturing global features. Next, a Dynamic Downsampling Module (DyDown) is introduced to mitigate the issue of small-scale defect information blurring. Furthermore, considering the multi-scale variations of insulator defects, this paper proposes a Context-Guided Feature Fusion Network (CGFFN). This module enables fine-grained fusion of features at different scales, allowing the model to generate adaptive responses to defects of various sizes. Compared to the baseline model, the proposed method improves mAP50 by 5.3% on our self-constructed Insulator-DET dataset. On CPLID-D and CPLID-N, it achieves mAP50-95 improvements of 7.9% and 12.1%, respectively. Additionally, to verify the robustness of the proposed algorithm, TLINet is evaluated on the VOC07 + 12 dataset. Compared to the baseline model, TLINet improves mAP50 by 0.4% while reducing the number of parameters by 1/6. These results demonstrate the effectiveness of TLINet in addressing the complexities of insulator defect detection in power transmission lines. The code is available at https://github.com/mazilishang/TLINet.

Does darkness increase the risk of certain types of crime? A registered report article

Evidence about the relationship between lighting and crime is mixed. Although a review of evidence found that improved road/ street lighting was associated with reductions in crime, these reductions occurred in daylight as well as after dark, suggesting any effect was not due only to changes in visual conditions. One limitation of previous studies is that crime data are reported in aggregate and thus previous analyses were required to make simplifications concerning types of crimes or locations. We addressed this issue by working with a UK police force to access records of individual crimes. We used these data to determine whether the risk of crime at a specific time of day is greater after dark than during daylight, using a case and control approach to analyse ten years of crime data. We compared counts of crimes in ‘case’ hours, that are in daylight and darkness at different times of the year, and ‘control’ hours, that are in daylight throughout the year. From these counts we calculated odds ratios as a measure of the effect of darkness on risk of crime. The results supported our three hypotheses: 1) The risk of overall crime occurring after dark was greater than during daylight (OR: 1.28, 95%CI: 1.23–1.34); 2) The risk of crime occurring after dark varied depending on crime category, with five out of fourteen crime categories having odds ratios greater than 1.0; and 3) The risk of crime occurring after dark varied depending on geographical area, with 25 out of 172 Middle Super Output Areas in South Yorkshire having odds ratios greater than 1.0. Our results suggest darkness increases the risk of Bicycle Theft, Burglary, Criminal damage, Robbery – personal, and Vehicle offences, and that some areas may be at more risk of crime occurring after dark than others. These findings suggest the crime types where outdoor lighting may help reduce the risk of crime after dark.

Paromomycin is a more effective selection agent than kanamycin in Arabidopsis harboring the neomycin phosphotransferase II transgene

Neomycin phosphotransferase II (nptII) is a selectable marker gene that is commonly used in plant molecular genetics and crop improvement, helping researchers to identify and select transgenically modified plants. The NPTII enzyme binds to and phosphorylates the aminoglycoside family of antibiotics, which are known translation inhibitors. Once the aminoglycoside is phosphorylated it is unable to bind to the ribosome and can no longer disrupt translation. Currently, the most widely used selection agent for screening NPTII expressing seedlings is kanamycin. Because the nptII transgene is frequently silenced epigenetically, kanamycin can be too toxic to seedlings that weakly express NPTII, leading to false negatives and making it harder to accurately identify transgenic plants. In this study we investigate the related aminoglycoside, paromomycin, as an alternative, non-lethal, selection agent to kanamycin across a series of transgenic Arabidopsis lines with varying NPTII expression. We investigated phenotypes of transgenic seedlings during and after antibiotic exposure. Seedling pigmentation and size are useful phenotypes for selecting seedlings with low nptII expression. Additionally, monitoring the photosynthetic efficiency and flowering time can help reduce the risk of false-positive results when treating seedlings with paromomycin.

Associations between dietary microbe intake and mortality risk in individuals with sleep disorders: Evidence from NHANES

Objective To investigate the association between dietary microbial intake, sleep patterns, and all-cause and cardiovascular mortality among U.S. adults. Methods This study is conducted using data from the 2005–2014 National Health and Nutrition Examination Survey (NHANES). Kaplan-Meier curves are used to preliminarily explore the relationship between dietary microbial intake, sleep disorders, and all-cause and cardiovascular mortality in the population. The Cox proportional hazards model is applied for both individual and combined analyses to examine the relationship between dietary microbial intake, sleep disorders, and mortality risk, with subgroup and sensitivity analyses performed to assess model stability. Results This study included 21,233 participants, among whom 2,814 all-cause deaths and 877 cardiovascular deaths were documented. Kaplan-Meier survival analysis revealed a significant association between low dietary microbial intake or sleep disorders and elevated mortality. Cox proportional hazards modeling showed that, among individuals with sleep disorders, those with moderate dietary microbe intake had a lower mortality hazard ratio compared to those with low intake. Conversely, the combination of low dietary microbe intake and sleep disorders was associated with the highest all-cause and cardiovascular mortality. Subgroup and sensitivity analyses demonstrated consistent associations across prespecified strata, with the inverse relationship between dietary live microbe intake and sleep disorder–related mortality remaining robust after adjustment for confounders. Conclusion Low dietary microbial intake and sleep disorders were independently and jointly associated with higher rates of all-cause and cardiovascular mortality in population. The observed inverse association between higher dietary microbial intake and mortality outcomes, particularly among individuals with sleep disorders, suggests a potential protective trend.

Optical coherence tomography analysis at initial diagnosis in patients with retinitis pigmentosa and associated cystoid macular edema

This retrospective study analyzed optical coherence tomography (OCT) findings in 130 eyes of 130 patients with retinitis pigmentosa (RP) at initial diagnosis, including 42 with cystoid macular edema (CME) and 88 without, between September 2016 and March 2024. The CME group exhibited increased central macular thickness (CMT) (257.50 ± 104.98 µm vs. 171.40 ± 73.15 µm, p = 0.000), whereas the non-CME group had greater subfoveal choroidal thickness (SCT) (294.52 ± 122.85 µm vs. 246.98 ± 87.31 µm, p = 0.043), total choroidal area (TCA) (4.64 ± 1.98 mm² vs. 3.82 ± 1.34 mm², p = 0.031), stromal area (SA) (1.85 ± 0.76 mm² vs. 1.53 ± 0.54 mm², p = 0.025), luminal area (LA) (2.79 ± 1.22 mm² vs. 2.30 ± 0.81 mm², p = 0.033), and foveal avascular zone in the superficial capillary plexus (FAZ_SCP) (0.42 ± 0.31 mm² vs. 0.27 ± 0.12 mm², p = 0.022). The CME group had more moderate stage cases (47.62% vs. 26.14%, p = 0.015), while the non-CME group had more advanced cases (39.77% vs. 9.52%, p = 0.000). Visual acuity (logMAR) worsened in advanced stages for both groups (CME: 1.62 ± 0.79, p = 0.003; Non-CME: 1.12 ± 0.80, p = 0.000). In the CME group, FAZ in the deep capillary plexus (FAZ_DCP) enlarged from moderate to advanced stages (0.28 ± 0.12 mm² to 0.64 ± 0.09 mm², p = 0.025), and vessel density in the deep capillary plexus (VD_DCP) decreased from early to moderate stages (31.83 ± 3.94% to 28.75 ± 2.71%, p = 0.036), whereas superficial capillary plexus vessel density (VD_SCP) remained stable across stages (early: 32.82 ± 2.59%, moderate: 31.04 ± 2.37%, advanced: 31.52 ± 1.26%, all p > 0.1). The non-CME group exhibited progressive declines in CMT (early: 226.27 ± 38.60 µm, moderate: 195.04 ± 52.56 µm, advanced: 108.83 ± 59.72 µm, all p < 0.01) and choroidal vascularity index (CVI) (early: 0.61 ± 0.02, moderate: 0.60 ± 0.02, advanced: 0.58 ± 0.04, all p < 0.05). In the CME group, visual acuity (logMAR) was positively correlated with cyst area (p = 0.019, rho = 0.361) and FAZ_DCP (p = 0.002, rho = 0.564). These findings suggest that RP-CME may be associated with choroidal atrophy regardless of disease stage and could have a compensatory mechanism to SCP. Cyst area and FAZ_DCP may serve as indicators of visual acuity in RP-CME.

Comparative mRNA profile analysis from NAc of adolescent male mice after binge-like alcohol exposure eliciting deficits in context fear extinction learning

Introduction Stressor-related disorders frequently co-occur with alcohol use disorder (AUD). This necessitates an understanding of the physiological and genetic factors contributing to this relationship. Binge drinking is the most common method of alcohol consumption among adolescent males and significantly increases the risk of developing comorbid stressor-related disorders and AUD. In experiments modeling the effects of a single binge-like alcohol exposure in male adolescent mice, we observed a clear deficit in context extinction learning. This exposure led to a significant initial increase in subsequent voluntary drinking on day one, as measured by the every-other-day (EOD) two-bottle choice drinking assay, which normalized thereafter. Methods For this study we performed an mRNASeq analysis of mice nucleus accumbens (NAc), a region intricately involved in regulating both aversive contextual fear responses and reward, after EOD to profile the differential expression of mRNAs within this region. We also used immunohistochemistry of coronal brain slices to characterize expression of proteins associated with stress-related disorders and molecular alcohol tolerance, such as FKBP5, GSK3ß, and ß-catenin, within the striatum, nucleus accumbens (NAc), hippocampus, and basolateral amygdala (BLA). Results Comparative mRNA profile analysis reveals significant long-term changes in gene expression induced by binge-like alcohol exposure, even 30 days after the initial exposure. Immunohistochemistry showed a full recovery of previously observed altered levels of target proteins prior to EOD. Conclusions These findings suggest that the temporal activation of specific gene subsets plays a crucial role in the comorbidity of AUD and stressor-related diseases. Understanding these mechanisms can help develop more effective, integrated treatment approaches to improve outcomes for affected individuals.

Correction: Research and application of digital measure management and control technology for characteristic low-efficiency gas wells in Gas Field A

Prevalence of symptom exaggeration among North American independent medical evaluation examinees: A systematic review of observational studies

Background Independent medical evaluations (IMEs) are commonly acquired to provide an assessment of impairment; however, these assessments show poor inter-rater reliability. One potential contributor is symptom exaggeration by patients, who may feel pressure to emphasize their level of impairment to qualify for incentives. This study explored the prevalence of symptom exaggeration among IME examinees in North America, which if common may represent an important consideration for improving the reliability of IMEs. Methods We searched CINAHL, EMBASE, MEDLINE and PsycINFO from inception to July 08, 2024. We included observational studies that used a known-group design or multi-modal determination method. Paired reviewers independently assessed risk of bias and extracted data. We performed a random-effects model meta-analysis to estimate the overall prevalence of symptom exaggeration and explored potential subgroup effects for sex, age, education, clinical condition, and confidence in the reference standard. We used the GRADE approach to assess the certainty of evidence. Results We included 44 studies with 46 cohorts and 9,794 patients. The median of the mean age was 40 (interquartile range [IQR] 38–42). Most cohorts included patients with traumatic brain injuries (n = 31, 67%) or chronic pain (n = 11, 24%). Prevalence of symptom exaggeration across studies ranged from 17% to 67%. We found low certainty evidence suggesting that studies with a greater proportion of women (≥40%) may be associated with higher rates of exaggeration (47%, 95%CI 36–58) vs. studies with a lower proportion of women (<40%) (31%, 95%CI 28–35; test of interaction p = 0.02). Possible explanations include biological differences, greater bodily awareness, or higher rates of negative affectivity. We found no significant subgroup effects for type of clinical condition, confidence in the reference standard, age, or education. Conclusion Symptom exaggeration may occur in almost 50% of women and in approximately a third of men undergoing IMEs. The high prevalence of symptom exaggeration among IME attendees provides a compelling rationale for clinical evaluators to formally explore this issue. Future research should establish the reliability and validity of evaluation criteria for symptom exaggeration and develop a structured IME assessment approach.

Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction

Precise forecasting of cancer outcomes is essential for medical professionals to assess the well-being of patients and develop customized therapeutic plans. Despite its importance, achieving precise forecasts remains a formidable challenge. To tackle this issue, we present an innovative method that harmonizes the Grey Wolf Optimizer (GWO) with Levy flight to optimize the weights and biases of a Backpropagation (BP) neural network—a prominent machine learning model extensively employed in classification tasks. Our novel approach, LGWO-BP, is tailored to augment the precision of cancer prognosis predictions. We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. The experimental results show the exceptional strengths of the proposed LGWO-BP method, particularly its accuracy and reliability compared to GWO-BP, and show that it achieves comparative results against state-of-the-art (SOTA) methods. Our assessment of the LGWO-BP technique’s efficacy involved undertaking empirical tests across half a dozen openly accessible datasets. For the early-stage diabetes dataset, LGWO-BP achieved an accuracy of 0.92, a recall of 0.93, a precision of 0.88, an F1-score of 0.91, and an AUC of 0.95. Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. For the diabetes health indicators dataset, LGWO-BP achieved an accuracy of 0.9 and an AUC of 1. Leveraging data from The Cancer Genome Atlas (TCGA) — a U.S.-led initiative conducting in-depth molecular research to elucidate the causative mechanisms of cancer — this study focuses on three specific cancer types within the dataset: lung, breast, and esophageal cancers. TCGA provides a rich repository of genomic, transcriptomic, epigenomic, and patient-specific clinical data across 33 cancer types. In evaluating the prognostic performance of the LGWO-BP (Lévy flight-enhanced Grey Wolf Optimizer integrated with Back Propagation) model, we observed AUC (Area Under the Curve) scores of 0.70 for miRNA expression, 0.72 for gene expression, and 0.72 for DNA methylation. Regarding precision, the model achieved accuracies of 0.67, 0.69, and 0.66 for miRNA expression, gene expression, and DNA methylation, respectively. For recall, the corresponding values were 0.71, 0.61, and 0.62. Notably, the F1-scores, which balance precision and recall, were 0.69 for miRNA expression, 0.65 for gene expression, and 0.62 for DNA methylation. This research not only advances the application of machine learning in medical prognosis but also offers crucial guidance for clinicians in developing more precise and reliable prognostic tools for cancer patients. By enhancing the efficacy of machine learning-driven cancer prognosis, our proposed LGWO-BP approach has the potential to improve patient care and treatment outcomes significantly.