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The performance of an automatic steering system based on an absolute positioning global positioning system (GPS) and a magnetic marker reference system during emergency situations is examined in this paper, as it is a vital safety issue in highway automation. Robust control technique in the form of parameter space approach in an invariance plane is utilized for lateral controller design based on a higher order nonlinear vehicle model. In addition, the control system incorporates an exponential smoothing algorithm based on road curvature preview for vehicle-handling enhancement. The proposed estimation and control system is shown, in computer simulations, to be effective in handling vehicle emergency situations. Index Terms--Gain scheduling, invariance plane, nonlinear vehicle model, parameter space approach, robust control, steering control.

Steering control for passenger cars on automated highways is analyzed. Feasibility of an automatic steering system based on absolute positioning global positioning system (GPS) and a magnetic marker guidance system has been evaluated using computer simulations. State estimation and control algorithm issues are examined for such control system. By use of GPS and a magnetic marker sensor, an accurate and real-time estimation of the vehicle's lateral displacements with respect to the road can be accomplished. A steering control algorithm based on road curvature preview for achieving good road tracking and providing ride comfort is also presented. The proposed estimation and control system are validated by simulation results. Index Terms--Global positioning system (GPS), magnetic markers, state estimation, steering control.

Project-based learning (PBL) follows an inductive learning approach by which students are taught to undertake a materials self-study after the need has been identified through a project's context. It has been used in many senior capstone and freshman design courses to enhance students' competences in design and other outcomes required by ABET. In most engineering programs, engineering analysis is still taught mainly through sequences of traditional lecture-based courses. Is it possible to use an independent project course to effectively teach engineering analysis and the challenging technical concepts that it involves? This paper presents the results of a study on the effectiveness of teaching engineering analysis of mechanical systems through a stand-alone project course. Our approach introduces the technical topics in the traditional academic manner prior to introducing the students to the project details. The model-rocket project was carefully and very specifically designed such that the technical topics of the pre-project lectures had direct and meaningful applications and were essential to its success. Based on this approach, the results demonstrated that the predictive success of the students' theoretical models of their rocket systems' behavior reached as high as 92%. Identical pre- and post-project tests showed consistent performance improvement reaching as high as 35%. This data suggests that it is possible to effectively utilize the PBL approach to teach the challenging technical subjects associated with engineering analysis. The main ingredient is the specific design of the projects such that the predictive capability of theoretical models is essential in evaluating students' project success. [ABSTRACT FROM AUTHOR]

Abstract: A series of phenoxyisoquinolines, N-phenoxyethyl-1-(2-nitrophenyl)-1,2,3,4-THIQs 3a–3d, N-phenoxyethyl-1-benzyl-1,2,3,4-THIQ 3e, N-phenoxyethyl-1-(2-aminophenyl)-1,2,3,4-THIQs 5f–5i, N-phenoxyethyl-1-(2-phenoxyethylaminophenyl)-1,2,3,4-THIQs 5f′–5i′, have been synthesized and tested in isolated rat vas deferens α-adrenoreceptors. Comparison of pA2 values for these compounds in the presence of phenylephrine confirms that α1-adrenoceptor blocking activity of 3a–3d (–NO2 series) is more active than 6a–6c (–NH2 series) in the aortic rings isolated from SD rats. On the other hand, the electron-donating group at the 6-position of isoquinoline ring either increases or decreases the α1-adrenoceptor blocking activity. [Copyright &y& Elsevier]

Background Cluster headache is a disorder characterized by intermittent, severe unilateral head pain accompanied by cranial autonomic symptoms. Most cases of CH are episodic, manifesting as “in-bout” periods of frequent headache separated by month-to-year-long “out-of-bout” periods of remission. Previous imaging studies have implicated the hypothalamus and pain matrix in the pathogenesis of episodic CH. However, the pathophysiology driving the transition between in- and out-of-bout periods remains unclear. Methods The present study provides a narrative review of previous neuroimaging studies on the pathophysiology of episodic CH, addressing alterations in brain structures, metabolism, and structural and functional connectivity occurring between bout periods. Results Although the precise brain structures responsible for episodic CH are unknown, major roles are indicated for the posterior hypothalamus (especially in acute attacks), the pain neuromatrix with an emphasis on central descending pain modulation, and non-traditional pain processing networks including the occipital, cerebellar, and salience networks. These areas are potentially related to dynamic transitioning between in- and out-of-bout periods. Conclusion Recent progress in magnetic resonance imaging of episodic CH has provided additional insights into dynamic bout-associated structural and functional connectivity changes in the brain, especially in non-traditional pain processing network areas. These areas warrant future investigations as targets for neuromodulation in patients with CH. [ABSTRACT FROM AUTHOR]

Background Previous imaging studies on the pathogenesis of cluster headache (CH) have implicated the hypothalamus and multiple brain networks. However, very little is known regarding dynamic bout-associated, large-scale resting state functional network changes related to CH. Methods Resting-state functional magnetic resonance imaging data were obtained from CH patients and matched controls. Data were analyzed using independent component analysis for exploratory assessment of the changes in intrinsic brain networks and their relationship between in-bout and out-of-bout periods, as well as correlations with clinical observations. Results Compared to healthy controls, CH patients had functional connectivity (FC) changes in the temporal, frontal, salience, default mode, somatosensory, dorsal attention, and visual networks, independent of bout period. Compared to out-of-bout scans, in-bout scans showed altered FC in the frontal and dorsal attention networks. Lower frontal network FC correlated with longer duration of CH. Conclusions The present findings suggest that episodic CH with dynamic bout period shifts may involve bout-associated FC changes in multiple discrete cortical areas within networks outside traditional pain processing areas. Dynamic changes in FC in frontal and dorsal attention networks between bout periods could be important for understanding episodic CH pathophysiology. [ABSTRACT FROM AUTHOR]

Introduction: Previous studies have shown that stroke patients exhibit greater neuroimaging-derived biological "brain age" than control subjects. This difference, known as the brain age gap (BAG), is calculated by comparing the chronological age with predicted brain age and is used as an indicator of brain health and aging. However, whether stroke accelerates the process of brain aging in patients with small-volume infarcts has not been established. By utilizing longitudinal data, we aimed to investigate whether small-volume infarctions can significantly increase the BAG, indicating accelerated brain aging., Methods: A total of 123 stroke patients presenting with small-volume infarcts were included in this retrospective study. The brain age model was trained via established protocols within the field of machine learning and the structural features of the brain from our previous study. We used t -tests and regression analyses to assess longitudinal brain age changes after stroke and the associations between brain age, acute stroke severity, and poststroke outcome factors., Results: Significant brain aging occurred between the initial and 6-month follow-ups, with a mean increase in brain age of 1.04 years ( t  = 3.066, p  < 0.05). Patients under 50 years of age experienced less aging after stroke than those over 50 years of age ( p  = 0.245). Additionally, patients with a National Institute of Health Stroke Scale score >3 at admission presented more pronounced adverse effects on brain aging, even after adjusting for confounders such as chronological age, sex, and total intracranial volume ( F 1,117  = 7.339, p  = 0.008, η 2  = 0.059). There were significant differences in the proportional brain age difference at 6 months among the different functional outcome groups defined by the Barthel Index ( F 2,118  = 4.637, p  = 0.012, η 2  = 0.073)., Conclusion: Stroke accelerates the brain aging process, even in patients with relatively small-volume infarcts. This phenomenon is particularly accentuated in elderly patients, and both stroke severity and poststroke functional outcomes are closely associated with accelerated brain aging. Further studies are needed to explore the mechanisms underlying the accelerated brain aging observed in stroke patients, with a particular focus on the structural alterations and plasticity of the brain following minor strokes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Peng, Kuo, Chang, Lin and Tsai.)

Background: Multidomain interventions have demonstrable benefits for promoting healthy aging, but self-empowerment strategies to sustain long-term gains remain elusive., Objective: This study evaluated the effects of digital somatosensory dance game participation on brain imagery changes as primary outcomes and other physical and mental health measures as secondary outcomes related to healthy aging., Methods: Between August 31, 2020, and June 27, 2021, this randomized controlled trial recruited 60 eligible participants older than 55 years with no recent engagement in digital dance games. A computer-generated randomization sequence was used to allocate participants 1:1, without stratification, to an intervention group (n=30) who underwent digital somatosensory dance game training or a control group (n=30). An anonymized code masked the intervention allocations from the investigators, and individuals who assigned the interventions were not involved in analyzing the study data. The intervention entailed two 30-minute dance game sessions per week for 6 months, and the control group received healthy aging education. Primary outcomes were brain imagery changes. All variables were measured at baseline and the 6-month follow-up, and intervention effects were estimated using t tests with intention-to-treat analyses., Results: Compared with the control group, intervention participants had significantly different brain imagery in the gray matter volume (GMV) of the left putamen (estimate 0.016, 95% CI 0.008 to 0.024; P<.001), GMV of the left pallidum (estimate 0.02, 95% CI 0.006 to 0.034; P=.004), and fractional amplitude of low frequency fluctuations of the left pallidum (estimate 0.262, 95% CI 0.084 to 0.439; P=.004). Additionally, the intervention group had different imagery in the cerebellum VI GMV (estimate 0.011, 95% CI 0.003 to 0.02; P=.01). The intervention group also had improved total Montreal Cognitive Assessment scores (estimate 1.2, 95% CI 0.27 to -2.13; P<.01), quality of life (estimate 7.08, 95% CI 2.35 to 11.82; P=.004), and time spent sitting on weekdays (estimate -1.96, 95% CI -3.33 to -0.60; P=.005). Furthermore, dance performance was significantly associated with cognitive performance (P=.003), health status (P=.14), resilience (P=.007), and demoralization (P<.001)., Conclusions: Digital somatosensory dance game participation for 6 months was associated with brain imagery changes in multiple regions involving somatosensory, motor, visual, and attention functions, which were consistent with phenotypic improvements associated with healthy aging., Trial Registration: ClinicalTrials.gov NCT05411042; https://clinicaltrials.gov/study/NCT05411042., (©Heng-Hsin Tung, Chen-Yuan Kuo, Pei-Lin Lee, Chih-Wen Chang, Kun-Hsien Chou, Ching-Po Lin, Liang-Kung Chen. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 30.07.2024.)

Introduction: Atherosclerotic cardiovascular disease (ASCVD) is prevalent worldwide including Taiwan, however widely accepted tools to assess the risk of ASCVD are lacking in Taiwan. Machine learning models are potentially useful for risk evaluation. In this study we used two cohorts to test the feasibility of machine learning with transfer learning for developing an ASCVD risk prediction model in Taiwan., Methods: Two multi-center observational registry cohorts, T-SPARCLE and T-PPARCLE were used in this study. The variables selected were based on European, U.S. and Asian guidelines. Both registries recorded the ASCVD outcomes of the patients. Ten-fold validation and temporal validation methods were used to evaluate the performance of the binary classification analysis [prediction of major adverse cardiovascular (CV) events in one year]. Time-to-event analyses were also performed., Results: In the binary classification analysis, eXtreme Gradient Boosting (XGBoost) and random forest had the best performance, with areas under the receiver operating characteristic curve (AUC-ROC) of 0.72 (0.68-0.76) and 0.73 (0.69-0.77), respectively, although it was not significantly better than other models. Temporal validation was also performed, and the data showed significant differences in the distribution of various features and event rate. The AUC-ROC of XGBoost dropped to 0.66 (0.59-0.73), while that of random forest dropped to 0.69 (0.62-0.76) in the temporal validation method, and the performance also became numerically worse than that of the logistic regression model. In the time-to-event analysis, most models had a concordance index of around 0.70., Conclusions: Machine learning models with appropriate transfer learning may be a useful tool for the development of CV risk prediction models and may help improve patient care in the future., Competing Interests: All the authors declare no conflict of interest.

Background Previous imaging studies on the pathogenesis of cluster headache (CH) have implicated the hypothalamus and multiple brain networks. However, very little is known regarding dynamic bout-associated, large-scale resting state functional network changes related to CH. Methods Resting-state functional magnetic resonance imaging data were obtained from CH patients and matched controls. Data were analyzed using independent component analysis for exploratory assessment of the changes in intrinsic brain networks and their relationship between in-bout and out-of-bout periods, as well as correlations with clinical observations. Results Compared to healthy controls, CH patients had functional connectivity (FC) changes in the temporal, frontal, salience, default mode, somatosensory, dorsal attention, and visual networks, independent of bout period. Compared to out-of-bout scans, in-bout scans showed altered FC in the frontal and dorsal attention networks. Lower frontal network FC correlated with longer duration of CH. Conclusions The present findings suggest that episodic CH with dynamic bout period shifts may involve bout-associated FC changes in multiple discrete cortical areas within networks outside traditional pain processing areas. Dynamic changes in FC in frontal and dorsal attention networks between bout periods could be important for understanding episodic CH pathophysiology.

Background/aims: Laparoscopic cholecystectomy is considered as a standard procedure for symptomatic gallstones. However, the incidence of iatrogenic bile duct injury is higher that the conventional cholecystectomy. In the present study was analyzed the results in 6 patients with iatrogenic bile duct injury during laparoscopic cholecystectomy with restenotic hepaticojejunostomy treated with self-modified Gianturco-Rosch stents., Methodology: Data were collected retrospectively on May 2000 to October 2008 on six patients with major bile duct injury secondary to cholecystectomy. All patients underwent surgical reconstruction with a Roux-en-Y hepaticojejunostomy and presented clinically as obstructive jaundice. Percutaneous transhepatic and/or endoscopic retrograde cholangiography, cholangioplasty by balloon dilation and biliary catheter placement were done in each patient prior to stents placement. Modified Gianturco-Rosch stents with 3cm length and 10mm diameter were used. Follow-up was obtained with direct patients contact or hospital records., Results: Metallic stents were successfully implanted in all 6 patients and the mean patency rate was 46.5 months (range = 14-101 months). One patient required percutaneous recanalization procedure for recurrent cholangitis and obstruction., Conclusions: Gianturco-Rosch stents placement should be considered in patient with post-hepaticojejunostomy restenosis that repeat surgery is not feasible.