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Objective: Aberrant driving behavior (ADB) decreases road safety and is particularly relevant for urban bus drivers, who are required to drive daily shifts of considerable duration. Although numerous frameworks based on human physiological features have been applied to predict ADB, the research remains at an early stage. This study used heart rate variability (HRV) parameters to establish ADB occurrence prediction models with various machine learning approaches. Methods: Twelve Taiwanese urban bus drivers were recruited for four consecutive days of naturalistic driving data collection (from their routine routes) between March and April 2020; driving behaviors and physiological signals were obtained from provided devices. Weather and traffic congestion information was determined from public data, while sleep quality and professional driving experience were self-reported. To develop the ADB prediction model, several machine learning models—logistic regression, random forest, naive Bayes, support vector machine, and gated recurrent unit (GRU)—were trained and 10-fold cross-validated by using the testing data. Results: Most drivers with ADB reported deficient sleep quality (≤80%), with significantly higher mean scores on the Karolinska Sleepiness Scale and driver behavior questionnaire subcategory of lapses and errors than drivers without ADB. Next, HRV indices significantly differed between the measurement of a pre-ADB event and a baseline. The accuracy of the GRU models ranged from 78.84% ± 1.49% to 89.57% ± 1.31%. Conclusion: Drivers with ADB tend to have inadequate sleep quality, which may increase their fatigue levels and impair driving performance. The established time-series models can be considered for ADB occurrence prediction among urban bus drivers.

Body composition is considered to be associated with obstructive sleep apnea (OSA) severity. This cross-sectional study aimed to examine associations of overnight body composition changes with positional OSA.The body composition of patients diagnosed with non-positional and positional OSA was measured before and after overnight polysomnography. Odds ratios (ORs) of outcome variables between the case (positional OSA) and reference (non-positional OSA) groups were examined for associations with sleep-related parameters and with changes in body composition by a logistic regression analysis.Among 1584 patients with OSA, we used 1056 patients with non-positional OSA as the reference group. We found that a 1-unit increase in overnight changes of total fat percentage and total fat mass were associated with 1.076-fold increased OR (95% confidence interval (CI): 1.014, 1.142) and 1.096-fold increased OR (95% CI: 1.010, 1.189) of positional OSA, respectively (all p 0.05). Additionally, a 1-unit increase in overnight changes of lower limb fat percentage and upper limb fat mass were associated with 1.043-fold increased OR (95% CI: 1.004, 1.084) and 2.638-fold increased OR (95% CI: 1.313, 5.302) of positional OSA, respectively (all p 0.05). We observed that a 1-unit increase in overnight changes of trunk fat percentage and trunk fat mass were associated with 1.056-fold increased OR (95% CI: 1.008, 1.106) and 1.150-fold increased OR (95% CI: 1.016, 1.301) of positional OSA, respectively (all p 0.05).Our findings indicated that nocturnal changes in the body's composition, especially total fat mass, total fat percentage, lower limb fat percentage, upper limb fat mass, trunk fat percentage, and trunk fat mass, may be associated with increased odds ratio of positional OSA compared with non-positional OSA.

Obstructive sleep apnea syndrome (OSAS) has mostly been examined using in-laboratory polysomnography (Lab-PSG), which may overestimate severity. This study compared sleep parameters in different environments and investigated the association between the plasma levels of neurochemical biomarkers and sleep parameters.Thirty Taiwanese participants underwent Lab-PSG while wearing a single-lead electrocardiogram patch. Participants' blood samples were obtained in the morning immediately after the recording. Participants wore the patch for the subsequent three nights at home. Sleep disorder indices were calculated, including the apnea-hypopnea index (AHI), chest effort index, and cyclic variation of heart rate index (CVHRI). The 23 eligible participants' derived data were divided into the normal-to-moderate (N-M) group and the severe group according to American Association of Sleep Medicine (AASM) guidelines (Lab-PSG) and the recommendations of a previous study (Rooti Rx). Spearman's correlation was used to examine the correlations between sleep parameters and neurochemical biomarker levels.The mean T-Tau protein level was positively correlated with the home-based CVHRI (r = 0.53, p 0.05), whereas no significant correlation was noted between hospital-based CVHRI and the mean T-tau protein level (r = 0.25, p = 0.25). The home-based data revealed that the mean T-Tau protein level in the severe group was significantly higher than that in the N-M group (severe group: 24.75 ± 6.16 pg/mL, N-M group: 19.65 ± 3.90 pg/mL; p 0.05). Furthermore, the mean in-hospital CVHRI was higher than the mean at-home values (12.16 ± 13.66 events/h).Severe OSAS patients classified by home-based CVHRI demonstrated the higher T-Tau protein level, and CVHRI varied in different sleep environments.

(a) Objective: Obstructive sleep apnea syndrome (OSAS) is typically diagnosed through polysomnography (PSG). However, PSG incurs high medical costs. This study developed new models for screening the risk of moderate-to-severe OSAS (apnea-hypopnea index, AHI ≥15) and severe OSAS (AHI ≥30) in various age groups and sexes by using anthropometric features in the Taiwan population.(b) Participants: Data were derived from 10,391 northern Taiwan patients who underwent PSG.(c) Methods: Patients' characteristics - namely age, sex, body mass index (BMI), neck circumference, and waist circumference - was obtained. To develop an age- and sex-independent model, various approaches - namely logistic regression, k-nearest neighbor, naive Bayes, random forest (RF), and support vector machine - were trained for four groups based on sex and age (men or women; aged50 or ≥50 years). Dataset was separated independently (training:70%; validation: 10%; testing: 20%) and Cross-validated grid search was applied for model optimization. Models demonstrating the highest overall accuracy in validation outcomes for the four groups were used to predict the testing dataset.(d) Results: The RF models showed the highest overall accuracy. BMI was the most influential parameter in both types of OSAS severity screening models.(e) Conclusion: The established models can be applied to screen OSAS risk in the Taiwan population and those with similar craniofacial features.

Emerging evidence witnesses the association of air pollution exposure with sleep disorders or the risk of obstructive sleep apnea (OSA); however, the results are not consistent. OSA patients with or without a low arousal threshold (LAT) have different pathology and therapeutic schemes. No study has evaluated the potential diverse effects of air pollution on the phenotypes of OSA. The current study aimed to evaluate the associations of short-term and long-term exposure to air pollution with sleep-disordered measures and OSA phenotypes. This cross-sectional study consisted of 4634 participants from a sleep center in Taipei from January 2015 to April 2019. The personal exposure to ambient PM

Purpose: Obstructive sleep apnoea (OSA) is a global health concern, and polysomnography (PSG) is the gold standard for assessing OSA severity. However, the sleep parameters of home-based and in-laboratory PSG vary because of environmental factors, and the magnitude of these discrepancies remains unclear.Methods: We enrolled 125 Taiwanese patients who underwent PSG while wearing a single-lead electrocardiogram patch (RootiRx). After the PSG, all participants were instructed to continue wearing the RootiRx over the 3 subsequent nights. Scores on OSA indexes, namely the apnoea–hypopnea index, chest effort index (CEI), cyclic variation of heart rate index (CVHRI), and combined CVHRI and CEI (Rx index), were determined. The patients were divided into 3 groups based on PSG-determined OSA severity. The variables (various severity groups and environmental measurements) were subjected to mean comparisons and their correlations were examined by Pearson’s correlation coefficient. Results: The hospital-based CVHRI, CEI, and Rx index differed significantly among the severity groups. All 3 groups exhibited a significantly lower percentage of supine sleep time in the home-based assessment relative to in the hospital-based assessment. Significant positive correlations were noted between the variations in the supine percentage (∆Supine%) and the OSA indexes. For the patients with high sleep efficiency (≥ 80%), significant correlations were observed between the ∆Supine% and ∆Rx index.Conclusion: The high supine percentage of sleep may cause OSA indexes’ overestimation in hospital-based PSG. Sleep recording at home with patch-type wearable devices may aid accurate OSA diagnosis.

This study aims to investigate the association of air pollution with overnight change in 4body composition and sleep-related parameters. Body composition of 197 subjects in New Taipei city was measured before and after sleep by bioelectric impedance analysis. Air pollutant data were collected from Taiwan Environmental Protection Administration. Sleep parameters were examined by polysomnography. We observed fine particulate matter (PM2.5) decreased arterial oxygen saturation (SaO2) and increased apnea-hypopnea index (AHI); NO2 increased arousal, AHI, and decreased mean SaO2; and O3 inmcreased mean SaO2. We observed 0.99-μg/m3 increase in PM2.5 was associated with 18.8% increase in changes of right arm fat percentage (95% confidence interval (CI): 0.004, 0.375) and 0.011-kg increase in changes of right arm fat mass (95% CI: 0.000, 0.021). 2.45-ppb increase in NO2 was associated with 0.181-kg decrease in changes of muscle mass (95% CI: -0.147, -0.001), 0.192-kg decrease in changes of fat free mass (95% CI: -0.155, -0.001), 21.1% increase in changes of right leg fat percentage (95% CI: 0.012, 0.160), and 21.3% increase in changes of left leg fat percentage (95% CI: 0.006, 0.168). 1.56-ppb increase in O3 was associated with 29.3% decrease in changes of right leg fat percentage (95% CI: -0.363, -0.013), 0.058-kg increase in changes of right leg fat free mass (95% CI: 0.008, 0.066), and 0.059-kg increase in changes of right leg muscle mass (95% CI: 0.010, 0.066). We observed AHI was associated with overnight changes in fat percentage, total fat mass, muscle mass, bone mass, fat free mass, extracellular water, basal metabolic rate, leg fat percentage, leg fat mass, and trunk fat percentage (p < 0.05). In conclusion, exposure to air pollutants was associated with overnight body composition changes and sleep-related parameters. Nocturnal changes in total muscle mass and leg fat percentage likely contribute to the relationship between air pollution and obstructive sleep apnea.

PurposeObstructive sleep apnea (OSA) is a highly prevalent disease, and positional OSA (pOSA) is a subgroup whose OSA severity is highly affected by sleeping position. This study investigated differences in demographic and sleep characteristics between patients with and without pOSA and developed a simple discrimination model.MethodsWe reviewed polysomnography records of patients admitted to the Sleep Center at Shuang-Ho Hospital between March 2015 and March 2019. They were categorized into pOSA and non-pOSA groups, and their demographic and sleep characteristics were compared. The receiver operating characteristic (ROC) curve was used to estimate the feasibility of discrimination model.ResultsOf the patients, 33% received diagnoses of pOSA; they had smaller neck circumference and waistline and lower weight, body mass index (BMI), OSA severity, heart rate, and snoring and respiratory-related limb movement indexes but higher sleep efficiency and mean oxygen saturation compared with patients without pOSA. Sleep stage analysis revealed that as severity increased, the proportion of sleep time spent in N2, N3, and rapid eye movement stages decreased, but the proportion of time spent in the N1 stage increased in both populations. Sleep position analysis revealed a higher proportion of sleep time in a supine position among patients with pOSA after adjustment for severity. The corresponding area under the ROC curve of our discrimination model was 0.924.ConclusionsDemographic and sleep characteristics differed significantly between patients with and without pOSA. Our model uses readily available measurements such as BMI and waistline and can aid physicians in the timely identification of patients with pOSA.Trial registration numberTMU-JIRB No.: N201911007Date of registration2019/11/12

The relationship between plants and ants is often mediated by the presence of extrafloral nectaries (EFNs) that attract ants and provide rewards by protecting plants from herbivores or parasites. Ficus trees (Moraceae) and their pollinators (Hymenoptera: Agaonidae) are parasitized by many nonpollinating fig wasp species (Hymenoptera: Chalcidoidea) that decrease the reproductive output of the mutualistic partners. Previous studies have shown that ants living on and patrolling Ficus species can efficiently deter parasitic wasps. The aim of this study was to verify the presence of EFNs on figs of Ficus benguetensis and test the hypothetical protection service provided by ants. Figs in different developmental stages were collected from Fu-Yang Eco Park, Taipei, Taiwan. Sugars on the fig surface were collected and analyzed through high-performance anion-exchange chromatography. Moreover, ants were excluded from the figs to determine the effect of ants on the nonpollinating fig wasps. We identified three oligosaccharides whose relative proportions varied with the fig developmental phase. In addition, results showed that the ant-excluded figs were heavily parasitized and produced three times less pollinators than did the control figs. Finally, the specific interactions of Ficus benguetensis with ants and the relationship between figs and ants in general are discussed.

Introduction Previous studies indicated the accumulation of neurodegenerative protein may be caused by higher Obstructive sleep apnea syndrome (OSAS) severity. However, the association between arousal-related parameters induced by OSAS and the amyloid burden remains unclear. The aim of this study is to investigate the association between arousal threshold (ArTH) and neurochemical protein accumulation in OSAS patients. Methods Suspected OSAS participants were performed Mini-mental status examination (MMSE) and full-night polysomnography (PSG) in the sleep center of Taipei Medical University Shuang Ho Hospital, Taiwan. On the same morning, the blood samples were obtained from the participants. The concentrations of total Tau (T-Tau) and amyloid beta peptide 42 (Aβ42) were quantified by ultra-sensitive immunomagnetic reduction assays. An overall of 23 participants were enrolled and classified into Low ArTH group (n=12) and High ArTH group (n=11) based on low ArTH criteria. Regarding the statistical methods, for categorical variables and continuous variables, Fisher’s exact test and Mann-Whitney U test were performed to investigate the differences between groups, respectively. The associations between biomarkers concentrations and PSG parameters were assessed by Spearman’s correlation. Results Regarding the demographic characteristics in two subgroups, significantly lower body-mass index and OSAS severity were noted in Low ArTH group (p Conclusion OSAS patients with low ArTH have higher neurochemical biomarker levels. Also, the significantly positive correlations between arousals and biomarkers were observed in that group. Support (if any)

Although ants are commonly found on Ficus trees, information remains lacking on the pattern and diversity of the ant community visiting these trees. We hypothesize that dynamic changes in the availability and types of food can affect the composition as well as abundance of ant communities occurring on fig trees. To investigate the impact of resource availability, diversity, and variability on the ant community structure, we surveyed and recorded the fig phenology and ant abundance on 17 trees (11 male and six female trees) of Ficus benguetensis in New Taipei City in northern Taiwan from 2011 to 2013. A total of 13 ant species were found on these fig trees, with 6 species more abundant than the others. The composition and relative abundance of the ant species occurring on F. benguetensis trees showed significant variations associated with tree sex, fig abundance, fig developmental phase, as well as temperature. A degree of dietary niche partitioning was also observed. We suggest that sexual differentiation in fig phenology plays a major role in controlling the availability and variance in food resources for ants, thereby shaping the complex ant communities foraging on F. benguetensis.

Background Timing of reproductive events has become central in ecological studies linking success in pollination and seed dispersion to optimizing the probability and periods of encounters with pollinators or dispersers. Obligate plant–insect interactions, especially Ficus–fig wasp mutualisms, offer striking examples of fine-tuned encounter optimization as biological cycles between mutualistic partners are deeply dependent on each other and intertwined over generations. Despite fig flowering phenology being crucial in maintaining Ficus–fig wasp mutualisms, until now, the forces of selection shaping the phenological evolution of dioecious fig trees have received little attention. By conducting a 2-year survey of a population of Ficus benguetensis in Northern Taiwan, we assessed whether environmental factors or other selective pressures shape the phenology of male and female fig trees. Results Constraints by mutualistic pollinating wasps and seed dispersers, rather than climatic factors, appeared to mainly shape fig phenology and allometry in F. benguetensis. We identified a new sexual specialization in dioecious fig trees: the position of fig production. We propose that the continuous male fig production on tree trunks can enhance the survival of pollinating fig wasps through faster localization of receptive figs while reducing the mutualistic conflict between the fig and its obligate pollinators. By contrast, in female trees, fig production is massive in summer, located on the twigs of the foliar crown and seem more related to seed dispersal and germination. Conclusions Identifying variations in the allometry and phenology of dioecious figs provide valuable insights into how monoecious and dioecious species resolve mutualism conflicts and into the emergence of dioecy in fig trees. Electronic supplementary material The online version of this article (doi:10.1186/s40529-015-0113-7) contains supplementary material, which is available to authorized users.

Based on the bead on plate test and the effects of heat input on weld penetration, the equivalence between 2 kW CW (Continuous Wave) Nd:YAG laser power and pulsed GMA(Gas Metal Arc) power and the effect of welding speed on their equivalent ratios in welding carbon steel and Al alloy were studied. The studied results show that 9.8 kW pulsed GMA power is needed to reach the same weld penetration depth with 2 kW CW Nd:YAG laser power for welding of low carbon steel at v=1.2 m/min; for Al alloy, it is 3.92 kW pulsed GMA power. The equivalent ratios of 2 kW Nd:YAG laser power and pulsed GMA power are 4.9~6.4 and 1.85~2.1 times at different welding speed for low carbon steel and Al alloy, respectively. But their equivalent ratios have different variations with welding speed; at which the equivalent ratio of low carbon steel increases with welding speed and that of Al alloy decreases. The studied results offer the experimental boundary of heat input for analyzing the effect of Nd:YAG laser power and pulsed GMA power on laser+pulsed GMA hybrid welding process.

Additional file 1. The supplementary materials display additional methods descriptions such as meteorological data and sampling methods as well as detailed results on average evenness.