Miracle-dz/UniFAR-FTUs huggingface dataset:
“HYPER-EARLY” Tracheostomy within 48 hours has less Complications and Better Prognosis Compared to Traditional Tracheostomy

Introduction Tracheostomies may be performed “early” or “late. ” There is no agreement on the best timing for tracheostomy. This study compares tracheostomies and complications when performed within 48 hours with those performed from 48 hours to 21 days. Methods Patients who underwent tracheostomy in the 2017-2018 National Trauma Data Bank (NTDB) were categorized into 2 groups: early tracheostomy (≤48 hours) and late tracheostomy (>48 hours to 21 days). Primary outcome measured was mortality. Chi square models, Mann-Whitney U Test, and multivariate logistics were used for data analysis. Results 843 patients had tracheostomy performed, of which 16% underwent early tracheostomy. Majority were male in both early (84%) and late (74%) tracheostomy groups. Mortality was not statically significant in early (13%) or late (9%) (P = .151). Total duration of ventilation in early tracheostomy group was less (5 days) compared to late tracheostomy group (16 days, P < .001). Patients with late tracheostomy had almost 18% cases of ventilator-associated pneumonia (VAP) when compared to early tracheostomy patients (7%, P < .001). Early tracheostomy patients also had shorter hospital length of stay (HLOS) (13 vs 27 days) and intensive care unit (ICU) length of stay (LOS) (7 vs 20 days) than late tracheostomy patients (P<.001). Early tracheostomy patients also had shorter hospital length of stay (HLOS) (13 vs 27 days) and intensive care unit (ICU) length of stay (LOS) (7 vs 20 days) than late tracheostomy patients (P < .001). Conclusion Tracheostomy performed as early as 48 hours is beneficial as it demonstrates a decrease time on ventilator, decreased HLOS, as well as lower VAP rates. Our data shows “hyper-early” tracheostomies might be more beneficial that the current national practice.
Self-made transparent optoacoustic detector for measurement of skin lesion thickness in vivo

In skin cancer diagnosis and treatment, one of the key factors is tumor depth, which is connected to the severity and the required excision depth. Optoacoustical (OA) imaging is a relatively popular technique that provides information based on the optical absorption of the sample. Although often demonstrated with ex vivo measurements or in vivo imaging on parts of small animals, in vivo measurements on humans are more challenging. This is presumably because it is too time consuming and the required excitation pulse energies and their number exceed the allowed maximum permissible exposure (MPE). Here, we demonstrate thickness measurements with a transparent optoacoustical detector of different suspicious skin lesions in vivo on patients. We develop the signal processing technique to automatically convert the raw signal into thickness via deconvolution with the impulse response function. The transparency of the detector allows optical excitation with the pulsed laser to be performed perpendicularly on the lesion, in contrast to the conventional illumination from the side. For validation, the measured results were compared to the histological thickness determined after excision. We show that this simple transparent detector allows to determine the thickness of a lesion and thus, aid the dermatologist to estimate the excision depth in the future.
Field testing and numerical investigation of streetscape vehicular anti-ram barriers under vehicular impact using FEM-only and coupled FEM-SPH simulations

This article presents two field-scale crash tests of Streetscape Vehicle Anti-Ram barrier systems and LS-DYNA simulations to predict the global response of each system under vehicular impact. Tests 1 and 2 consisted of a five-post welded bus stop and a welded bollard, respectively; both were in a steel and concrete composite foundation embedded in compacted American Association of State Highway and Transportation Officials aggregate. Test 1 resulted in a P1 rating, where minimal foundation uplift and rotation were observed. Test 2 failed to result in a P1 rating, where significant foundation uplift, rotation, concrete cracking, and large deformation of surrounding soil were observed. For each test, two LS-DYNA models, namely, a finite element method–only model and a hybrid finite element method–smoothed particle hydrodynamics model, were created to predict the global response of the system. In the finite element method–only model, traditional finite element method approach was used for the entire soil region; in the hybrid finite element method–smoothed particle hydrodynamics model, the near-field soil region was modeled using the smoothed particle hydrodynamics approach, whereas the far-field soil region was modeled using the finite element method approach. For Test 1, both the finite element method–only model and the hybrid finite element method–smoothed particle hydrodynamics model were able to match the recorded global response of the system. For Test 2, however, the finite element method–only approach was not able to accurately predict the global response of the system; on the other hand, the hybrid finite element method–smoothed particle hydrodynamics approach was able to capture the global response including the bollard pullout, soil upheaval, and vehicle override. This research suggests that the hybrid finite element method–smoothed particle hydrodynamics approach is more appropriate in simulating the field performance of embedded structures under impact loading when large deformation of the surrounding soil is expected.
The influence of social support on self-care is mediated by self-efficacy and depression in chronic illness: key findings from the ‘SODALITY’ observational study

Abstract Objectives: Family is a major source of support for older chronically-ill patients and known to be associated with better self-care. Depression and self-care self-efficacy are associated with healthy behaviors and thus may serve as mechanisms by which family support influences self-care. We explored depression and self-care self-efficacy as mediators of the relationship between perceived family support and self-care. Methods: Five hundred forty-one older adults with multiple chronic illnesses were recruited from outpatients and community settings. Three structural equation models (SEM) were fit on cross-sectional data. We measured perceived family support (subscale of the Multidimensional Scale of Perceived Social Support, scores range 1-7), depression (Patient Health Questionnaire, scores range 0-27), selfcare self-efficacy (Self-Care Self Efficacy Scale, standardized scores range 0-100), and self-care maintenance, monitoring, and management (Self-care of Chronic Illness Inventory, standardized scores range 0-100). Results: Participants (mean age = 76.6±7.3 yrs) were predominantly females (55.6%). In the full sample, depression and self-care self-efficacy mediated the relationship between perceived family support and self-care; in the gender-stratified SEM, men’s depression was no longer a significant mediator. Depression and self-care self-efficacy were significant mediators of the relation between perceived family support and self-care. Conclusion: In older chronically-ill patients, interventions addressing perceived family support may facilitate a rapid improvement in self-care self-efficacy and a decrease in depressive symptoms, particularly among women.
Production and productivity of maize subjected to modern and traditional methods of weed control options in Federal Capital Territory, Nigeria

This study was designed to evaluate the implications of using alternative weed control options on viability, production and productivity of maize crop in the Federal Capital Territory (FCT), Nigeria. Data were collected using a structured questionnaire from 451 randomly selected smallholder farmers. Gross margins, regression and correlation analysis were used to analyze the data. About 72% of farmers who grew maize practiced manual weed control while 40% used integrated modern and manual weed control. Results revealed that viability was higher in maize subjected to integrated (119,664.38 naira/ha) than in manual (4211.63 naira/ha) weed control. Seed rate (β = 0.155), variety (β = 0.283), herbicides (β = 0.593), fertilizer (β = 0.100) and labour (β = 0.535) were positive and significant determinants of maize output with a coefficient of determination of 0.823. Productivity of seed, labour, and fertilizer were higher under integrated weed control option than manual weed control. There was a positive association between use of herbicides and resource productivity (seed quantity (r = 0.607), herbicides (r = 0.526), fertilizer (r = 0.347) and labour (r = 0.770). Farmers were therefore encouraged adopt herbicides to improve viability, production and resource productivity. There was need for further research to identify intervention areas for inducing adoption of herbicides by farmers.
End-to-end sensor fusion and classification of atrial fibrillation using deep neural networks and smartphone mechanocardiography

Objective. The purpose of this research is to develop a new deep learning framework for detecting atrial fibrillation (AFib), one of the most common heart arrhythmias, by analyzing the heart’s mechanical functioning as reflected in seismocardiography (SCG) and gyrocardiography (GCG) signals. Jointly, SCG and GCG constitute the concept of mechanocardiography (MCG), a method used to measure precordial vibrations with the built-in inertial sensors of smartphones. Approach. We present a modified deep residual neural network model for the classification of sinus rhythm, AFib, and Noise categories from tri-axial SCG and GCG data derived from smartphones. In the model presented, pre-processing including automated early sensor fusion and spatial feature extraction are carried out using attention-based convolutional and residual blocks. Additionally, we use bidirectional long short-term memory layers on top of fully-connected layers to extract both spatial and spatiotemporal features of the multidimensional SCG and GCG signals. The dataset consisted of 728 short measurements recorded from 300 patients. Further, the measurements were divided into disjoint training, validation, and test sets, respectively, of 481 measurements, 140 measurements, and 107 measurements. Prior to ingestion by the model, measurements were split into 10 s segments with 75 percent overlap, pre-processed, and augmented. Main results. On the unseen test set, the model delivered average micro- and macro-F1-score of 0.88 (0.87–0.89; 95% CI) and 0.83 (0.83–0.84; 95% CI) for the segment-wise classification as well as 0.95 (0.94–0.96; 95% CI) and 0.95 (0.94–0.96; 95% CI) for the measurement-wise classification, respectively. Significance. Our method not only can effectively fuse SCG and GCG signals but also can identify heart rhythms and abnormalities in the MCG signals with remarkable accuracy.
Benchmarking Medication Error Rates in Palliative Care Services: Not as Simple as It Seems

Medication errors are a leading cause of medical errors in palliative care services. Palliative care services frequently prescribe medications to control symptoms, including high risk medications such as opioids. There is an ever present inherent safety risk to all patients due to the complexity of the medication processes. Medication errors could potentially cause harm and death, particularly in patients with multiple comorbidities and limited physiological reserves. Medication errors could compromise effectiveness of symptom control, impact quality of life, incur additional resource utilisation and cause distress to patients and caregivers. While there is no standardised definition of medication error, the National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP), whose medication error categorisation system is commonly used by many healthcare organisations, had defined medication error as ‘any preventable event that may cause or lead to inappropriate medication use or patient harm while the medication is in the control of the health care professional, patient, or consumer’. Medication errors need to be differentiated from adverse drug events. Adverse drug events are defined as any injury due to medications. While adverse drug events are often caused by medication errors, there are adverse drug events that are not medication errors because they are not preventable. For example, a patient who had an allergic reaction to a medication that the patient was not previously known to be allergic to. Conversely, not all medication errors result in adverse drug events because in some cases, the patients were not harmed or the medication did not reach the patient. Many healthcare institutions, including palliative care services, use medication error incidence rate as a measure of medication safety. There have been recent initiatives to track and benchmark medication error rates as part of a set of quality measures, for example, Hospice UK Clinical Benchmarking and National Hospice and Palliative Care Organization (NHPCO) Measures of Excellence. A benchmark is a point of comparison which reflects best practice, against which organisations are compared. While it is important to monitor and benchmark medication error rates for quality assurance, there appears to be little data on rates of medication errors in palliative care services. Moreover, the definition of medication error and detection methods differ. With insufficient data and inconsistent definitions, it is difficult to make reliable comparison of medication error rates. In view of the important policy implications on how to measure and benchmark medication error rates in palliative care services so as to best reflect medication safety and quality of care, we conducted a systematic review to determine what data is available in peer reviewed literature on medication error rates in palliative care services.
Multiple Adverse Weather Conditions Adaptation for Object Detection via Causal Intervention

Most state-of-the-art object detection methods have achieved impressive perfomrace on several public benchmarks, which are trained with high definition images. However, existing detectors are often sensitive to the visual variations and out-of-distribution data due to the domain gap caused by various confounders, e.g. the adverse weathre conditions. To bridge the gap, previous methods have been mainly exploring domain alignment, which requires to collect an amount of domain-specific training samples. In this paper, we introduce a novel domain adaptation model to discover a weather condition invariant feature representation. Specifically, we first employ a memory network to develop a confounder dictionary, which stores prototypes of object features under various scenarios. To guarantee the representativeness of each prototype in the dictionary, a dynamic item extraction strategy is used to update the memory dictionary. After that, we introduce a causal intervention reasoning module to explore the invariant representation of a specific object under different weather conditions. Finally, a categorical consistency regularization is used to constrain the similarities between categories in order to automatically search for the aligned instances among distinct domains. Experiments are conducted on several public benchmarks (RTTS, Foggy-Cityscapes, RID, and BDD 100K) with state-of-the-art performance achieved under multiple weather conditions.
The development and psychometric assessment of communication skills checklist for 6- to 24-month-old Persian children

Abstract Prelinguistic skills play an important role in children’s communication development. These skills are considered as significant bases for language acquisition and function conductive to later social development. Means of communication, communicative functions, skills with cognitive bases, and language comprehension are important prelinguistic skills. There is a critical period for acquiring prelinguistic skills and early identification of communication deficits is an important issue to be considered. The present study aimed to develop a communication skills checklist for Persian children aged 6- to 24-month-old and evaluate its psychometric properties. Parents of 277 Persian children aged 6- to 24-month-old participated in the current study. A checklist was first developed after an extensive literature review and various psychometric analyses in addition to regression analyses were carried out to determine its validity and reliability. The final checklist contained 36 items with high face validity and content validity (CVI > 0.62, CVR > 0.79). Also, the checklist demonstrated a high association with the CNCS (Pearson’s correlation coefficient = 0.85, p < 0.001), and the construct validity showed significant differences between the four age groups (F-test = 197.881, p < 0.001). The results of the internal consistency measurement (Cronbach’s alpha coefficient = 0.952) and the test-retest reliability test (ICC = 0.933, p < 0.001) revealed excellent reliability of the checklist. In conclusion, based on the psychometric assessment, this checklist is a promising tool for assessing communication skills in Persian children aged 6 to 24 months.
The influence of anthropogenic noise on the behavior of male mantled howler monkeys

Anthropogenic noise is increasingly disturbing natural soundscapes and affecting the physiology, behavior, and fitness of wildlife. However, our knowledge about the impact of anthropogenic noise on wild primates is scant. Here, we assess the effects of anthropogenic noise on the behavior of male mantled howler monkeys (Alouatta palliata). Specifically, we describe the types, rates, and sound pressure level (SPL) of anthropogenic noise that occurs in areas inhabited by mantled howler monkeys and determine if the behavioral responses of males to anthropogenic noise are influenced by noise attributes. For 1 year (1753 h), we characterized anthropogenic noise in the Los Tuxtlas Biosphere Reserve (Veracruz, Mexico) and studied the behavior of males belonging to five groups. Anthropogenic noise was common, diverse, and varied among areas in terms of rate, type, and SPL. Males did not display behavioral responses toward most (60%) anthropogenic noises, but were more likely to respond to certain noise types (e.g., aerial traffic) and toward noise with high SPL. Group identity influenced the likelihood of displaying behavioral responses to noise. The most common behavioral responses were vocalizations and vigilance. Males vocalized in response to noise with high SPL, although this relationship depended on group identity. The effect of the number of noises on vocalizations also varied among groups. Males were more likely to display vigilance toward high SPL and infrequent noise, but, again, these relationships varied among groups. In sum, anthropogenic noise is pervasive in areas inhabited by mantled howler monkeys and influences male behavior. Experience and frequency of exposure may modulate the behavioral responses of male mantled howler monkeys to noise and explain the group differences.
Atmospheric levels, distribution, sources, correlation with meteorological parameters and other pollutants and health risk of PAHs bound in PM2.5 and PM10 in Burgas, Bulgaria – a case study

Abstract The quality of atmospheric air of Burgas city, Bulgaria was analyzed in relation to PAHs in two particulate matter fractions – 2.5 μm and 10 μm. It was found that PAHs registered in PM10 represent entirely the ones registered in PM2.5 – an indication that the particulate PAHs in ambient air of Burgas for the sampling period are associated with the fine PM fraction. The PAH compounds with highest concentrations are mainly associated with coal combustion, diesel and gasoline vehicle and biomass burning, which is further confirmed by the calculated diagnostic ratios. The combustion-derived PAHs represent on average 86.6 ± 2.8% of total PAHs concentration. The linear regression analysis showed strong and statistically meaningful correlations between PM fractions and PAHs indicating the influence of similar local events and emission sources of pollution. PM2.5 or PM10 relationships with PAHs were significant but lower correlation coefficients were observed for low-molecular weight (LMW) PAHs in comparison to middle-molecular weight (MMW) and higher-molecular weight (HMW) PAHs, due to their lower presence in particulates and higher partition in gaseous atmospheric phase. Further significant correlations were found with wind speed, solar radiation and atmospheric pressure as well as NO2 and O3 ambient concentration. The calculated excess cancer risks are twice as much as acceptable limit.
Intergenerational Socioeconomic Mobility and Cognitive Impairment Among Chinese Older Adults: Gender Differences

This study examined the impact of intergenerational socioeconomic mobility on the risk of cognitive impairment in a cohort of Chinese older adults aged 60 years and older. Data were derived from the 2014 wave of the Chinese Longitudinal Healthy Longevity Survey. Logistic regression models were performed to assess the impact of three dimensions of socioeconomic mobility (occupational mobility, educational mobility, and residential mobility) on the risk of cognitive impairment. We found that men who were stable with non-professional jobs across generations had a higher risk of cognitive impairment than their counterparts who experienced upward occupational mobility compared to their father. This pattern was not observed in women. There was little evidence that educational mobility or residential mobility affected cognitive impairment in later life. The findings have implications for advancing supportive policies and practices related to maximizing the benefits of education and career advancements for cognition in later life.
A newly emerging alphasatellite affects banana bunchy top virus replication, transcription, siRNA production and transmission by aphids

Banana bunchy top virus (BBTV) is a six-component ssDNA virus (genus Babuvirus, family Nanoviridae) transmitted by aphids, infecting monocots (mainly species in the family Musaceae) and likely originating from South-East Asia where it is frequently associated with self-replicating alphasatellites. Illumina sequencing analysis of banana aphids and leaf samples from Africa revealed an alphasatellite that should be classified in a new genus, phylogenetically related to alphasatellites of nanoviruses infecting dicots. Alphasatellite DNA was encapsidated by BBTV coat protein and accumulated at high levels in plants and aphids, thereby reducing helper virus loads, altering relative abundance (formula) of viral genome components and interfering with virus transmission by aphids. BBTV and alphasatellite clones infected dicot Nicotiana benthamiana, followed by recovery and symptomless persistence of alphasatellite, and BBTV replication protein (Rep), but not alphasatellite Rep, induced leaf chlorosis. Transcriptome sequencing revealed 21, 22 and 24 nucleotide small interfering (si)RNAs covering both strands of the entire viral genome, monodirectional Pol II transcription units of viral mRNAs and pervasive transcription of each component and alphasatellite in both directions, likely generating double-stranded precursors of viral siRNAs. Consistent with the latter hypothesis, viral DNA formulas with and without alphasatellite resembled viral siRNA formulas but not mRNA formulas. Alphasatellite decreased transcription efficiency of DNA-N encoding a putative aphid transmission factor and increased relative siRNA production rates from Rep- and movement protein-encoding components. Alphasatellite itself spawned the most abundant siRNAs and had the lowest mRNA transcription rate. Collectively, following African invasion, BBTV got associated with an alphasatellite likely originating from a dicot plant and interfering with BBTV replication and transmission. Molecular analysis of virus-infected banana plants revealed new features of viral DNA transcription and siRNA biogenesis, both affected by alphasatellite. Costs and benefits of alphasatellite association with helper viruses are discussed.