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Unmanned aerial vehicles (UAVs), commonly known as drones, are being increasingly deployed throughout the globe as a means to streamline monitoring, inspection, mapping, and logistic routines. When dispatched on autonomous missions, drones require an intelligent decision-making system for trajectory planning and tour optimization. Given the limited capacity of their onboard batteries, a key design challenge is to ensure the underlying algorithms can efficiently optimize the mission objectives along with recharging operations during long-haul flights. With this in view, the present work undertakes a comprehensive study on automated tour management systems for an energy-constrained drone: (1) We construct a machine learning model that estimates the energy expenditure of typical multi-rotor drones while accounting for real-world aspects and extrinsic meteorological factors. (2) Leveraging this model, the joint program of flight mission planning and recharging optimization is formulated as a multi-criteria Asymmetric Traveling Salesman Problem (ATSP), wherein a drone seeks for the time-optimal energy-feasible tour that visits all the target sites and refuels whenever necessary. (3) We devise an efficient approximation algorithm with provable worst-case performance guarantees and implement it in a drone management system, which supports real-time flight path tracking and re-computation in dynamic environments. (4) The effectiveness and practicality of the proposed approach are validated through extensive numerical simulations as well as real-world experiments.

Acute myocardial infarction (AMI) is a major cause of death worldwide. In the USA, there are approximately 0.8 million persons suffering from AMI annually with a death rate of 27%. The risk factors of AMI include hypertension, family history, smoking habits, diabetes, serenity, obesity, cholesterol, alcoholism, coronary artery disease, and so forth. In this study, data acquired from a subset of the National Health Insurance Research Database (NHIRD) of Taiwan were used to develop a clinical decision support system (CDSS) to predict AMI. The integrated genetic algorithm and support vector machine (IGS) and deep neural network (DNN) were both applied to design the predictive models. A balanced dataset (6087 AMI patients and 6087 non-AMI patients) and an imbalanced dataset (6,087 AMI patients and 12,174 non-AMI patients) with each patient record including 74 features were retrieved to design the predictive models. Tenfold cross-validation was used to obtain the optimal model with best prediction performance during training. The experimental results showed that the CDSSs reached a prediction performance with accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of 79.75–84.4%, 68.29–83.7%, 82.45–92.07%, and 0.8424–0.9089, respectively, for models designed based on the balanced dataset, as well as 81.86–86.27%, 52.65–81.22%, 84.29–96.47%, and 0.8503–0.9098, respectively, for models implemented based on the imbalanced dataset. The IGS and DNN algorithms and a combination of age, presence of related comorbidities, and other comorbidity-related features, including diagnosed age and annual physician visits of individual comorbidities, have been shown to be promising in designing strong predictive models in detecting patients who are more likely to develop AMI in the near future as well as for realizing mobile-health (m-Health) systems in managing their comorbidities to prevent occurrence of AMI events. Future work will focus on realizing an ensemble model by combining the model designed based on the long-term NHIRD dataset and the model based on the short-term EMR data and the real-time IoT sensor data, as well as implementing a transfer learning model by transferring the knowledge learned from the long-term model for training the short-term model, so that the predictive performance can be enhanced.

Carbon-based mesoscopic perovskite solar cells (PSCs) are promising for printable next-generation photovoltaic applications, but the optical properties of their carbon layer limit their light harvesting efficiency. We developed solution-processable indium-tin-oxide (ITO) nanoparticles to replace carbon electrodes for mesoscopic lead-free tin-based PSCs. The ITO electrodes were fabricated via screen printing with 1, 2, 4, 6 and 8 layers corresponding to the thicknesses of 2.1–14.3 μm; tin perovskite (GA0.2FA0.8SnI3) with SnF2 (20%) and EDAI2 (15%) (GA represents guanidinium; EDAI2 represents ethylenediammonium diiodide) was drop-casted on the device to produce a mesoporous structure of FTO/TiO2/perovskite/Al2O3/ITO. The best device achieved a power conversion efficiency of 5.4% with great stability. These solution-processed ITO electrodes are a landmark to shed light on new paths for the commercialization of lead-free PSCs.

Electron bombardment of aniline (PhNH

The rate of patient readmissions within a short period after discharge is a significant indicator for the healthcare quality of a hospital. Readmissions may result in an increased cost of a healthcare organization. Design of a model for predicting readmission would benefit on solving the above issues. This study aims to develop a clinical decision support system (CDSS) for predicting readmission of the patient with ischemic stroke (IS) after discharge. The IGS method, which integrates genetic algorithm (GA) and support vector machine (SVM), accompanied with three objective functions, was adopted to develop the CDSS. The data, retrieved from the National Health Insurance Research Database (NHIRD), including 4351 patients (462 with readmission and 3889 without readmission) diagnosed with IS (ICD-9-CM Code 433–435), aged 20 years old and older, treated within 30 days of hospital admission and then discharged to outpatient treatment between Jan. 2007 and Dec. 2009, were used for designing the predictive models. The statistical analysis of demographics (gender and age) and other candidate variables (28) between patients with and without readmission is presented. Twelve of these 30 variables are significantly different (p < 0.05). CDSS models designed using three objective functions achieved predictive performances of accuracy, sensitivity, specificity, and area under ROC curve (AUC) equaling 65.9-66.77%, 58.22-66.66%, 66.88-73.59%, and 0.6773-0.7183, respectively. Future work will focus on improving the predictive performance by including more effective risk factors and comorbidities, as well as integrating GA with more effective AI methods such as deep neural network to increase the predictive performance.

Background: Acute gastroenteritis (AGE) accompanied by seizures is not a rare scenario in childhood. We investigated the clinical features of children with febrile or afebrile seizures during AGE and aimed to identify the impact of fever in this situation-related seizure. Methods: We retrospectively reviewed the medical charts of children admitted due to seizures associated with mild AGE between January 2008 and December 2017. These consecutive patients were divided into two groups: an "afebrile group" whose diagnosis was compatible with "benign convulsion with mild gastroenteritis (CwG)" and a "febrile group" who had a fever within 24 h of the onset of an AGE-related seizure. We compared the two groups' clinical and laboratory characteristics, electroencephalograms (EEG), neuroimaging, and outcomes. Results: Of the children suffering from AGE and seizures, 41 were afebrile and 30 were febrile, with a mean age of 32.2 ± 27.6 months. The gender, seizure semiology, frequency, duration of seizures, the time interval between AGE symptoms onset and first seizure, and levels of serum sodium, and hepatic enzymes were significantly different between the two groups. The most frequently identified enteropathogen was rotavirus (33%), especially in the male and febrile subjects. Afebrile patients had more EEG abnormalities initially, but all returned to normal later. All cases had an uneventful outcome. Of note, seizure clusters (≥2 episodes) occurred more frequently in the afebrile patients who had a duration of AGE symptoms lasting 2 days or more, or white blood cell counts ≥ 10,000/μL (p-values: 0.05 and 0.04, respectively). In comparison with seven similar studies, all showed more seizure clusters, partial seizures, and a shorter interval between AGE onset and seizures in afebrile patients than in febrile patients. Contrarily, afebrile patients had longer seizure duration and lower serum hepatic transaminases than febrile patients. Conclusion: Although fever partially influenced the clinical features of AGE-related seizures, febrile CwG might have pathophysiology distinctly different from that of febrile seizures. Comprehensive knowledge in discerning febrile and afebrile CwG can help to avoid unnecessary diagnostics tests, and anticonvulsants use.

Ion-coincidence momentum imaging of Coulomb explosion of formaldehyde (H2CO) in femtosecond intense laser fields (800 nm, 1.3 × 1015 W/cm2) is performed with two different laser pulse durations (7 fs and 35 fs). In the 7-fs laser fields, the full fragmentation pathway from H2CO4+ → H+ + H+ + C+ + O+ is identified. The angles between the fragment momenta are well reproduced by a simple Coulomb explosion model from the geometry of neutral formaldehyde, showing that the molecular structure is virtually frozen along the bending coordinates during the multiple ionization. Three-body Coulomb explosion pathways from triply charged states, H2CO3+ → H+ + H+ + CO+ and H+ + CH+ + O+, are observed in both the 7-fs and 35-fs laser fields. Significant changes in the momentum angle distribution and asymmetric energy partitioning between two H+ ions are observed in the 35-fs case, which are attributed to structural deformation prior to the Coulomb explosion in the longer pulse.

Objective To assess effectiveness of the video-based m-health system providing videos dictated by physicians for health education and symptom self-management for patients with Interstitial cystitis/bladder pain syndrome (IC/BPS). Methods An m-health system was designed to provide videos for weekly health education and symptom flare self-management. O'Leary-Sant index and visual analogue scale as well as SF-36 health survey were administrated to evaluate the disease severity and quality of life (QoL), respectively. A total of 60 IC/BPS patients were recruited and randomly assigned to either control group (30 patients) or study group (30 patients) in sequence depending on their orders to visit our urological clinic. Patients in both control and study groups received regular treatments, while those in the study group received additional video-based intervention. Statistical analyses were conducted to compare the outcomes between baseline and postintervention for both groups. The outcomes of video-based intervention were also compared with the text-based intervention conducted in our previous study. Results After video-based intervention, patients in the study group exhibited significant effect manifested in all disease severity and QoL assessments except the pain visual analogue scale, while no significance was found in the control group. Moreover, the study group exhibited more significant net improvements than the control group in 7 SF-36 constructs, except the mental health. The limitations include short intervention duration (8 weeks) and different study periods between text-based and video-based interventions. Conclusion Video-based intervention is effective in improving the QoL of IC/BPS patients and outperforms the text-based intervention even in a short period of intervention.

The advent of abundant on-board sensors and electronic devices in vehicles populates the paradigm of participatory sensing to harness crowd-sourced data gathering for intelligent transportation applications, such as distance-to-empty prediction and eco-routing. While participatory sensing can provide diverse driving data, there lacks a systematic study of effective utilization of the data for personalized prediction. There are considerable challenges on how to interpolate the missing data from a sparse dataset, which often arises from participatory sensing. This paper presents and compares various approaches for personalized vehicle energy consumption prediction, including a blackbox framework that identifies driver/vehicle/environment-dependent factors and a collaborative filtering approach based on matrix factorization. Furthermore, a case study of distance-to-empty prediction for electric vehicles by participatory sensing data is conducted and evaluated empirically, which shows that our approaches can significantly improve the prediction accuracy., Comment: To appear in IEEE Transactions on Intelligent Transportation Systems

Acute myocardial infarction (AMI) is a major cause of death worldwide. There are around 0.8 million persons suffered from AMI annually in the US and the death rate reaches 27%. The risk factors of AMI were reported to include hypertension, family history, smoking habit, diabetes, serenity, obesity, cholesterol, alcoholism, coronary artery disease, etc. In this study, data acquired from a subset of the National Health Insurance Research Database (NHIRD) of Taiwan were used to develop the clinical decision support system (CDSS) for predicting AMI. Support vector machine integrated with genetic algorithm (IGS) was adopted to design the AMI prediction models. Data of 6087 AMI patients and 6087 non-AMI patients, each includes 50 features, were acquired for designing the predictive models. Tenfold cross validation and three objective functions were used for obtaining the optimal model with best prediction performance during training. The experimental results show that the CDSSs reach a prediction performance with accuracy, sensitivity, specificity, and area under ROC curve (AUC) of 81.47–84.11%, 75.46–80.94%, 86.48–88.21%, and 0.8602–0.8935, respectively. The IGS algorithm and comorbidity-related features are promising in designing strong CDSS models for predicting patients who may acquire AMI in the near future.

UV-excited aromatic molecules with N-H/O-H moieties often possess an important nonradiative relaxation pathway, from an optically bright ππ

We demonstrate an analytical approach to monitor the effect of pH on protein tertiary structure. An autocatalytic enzyme reaction is used to stimulate refolding of proteins during real-time analysis. The method takes advantage of a nonlinear pH ramp generated by the urea-urease clock reaction. In this study, alterations to the structures of model proteins were monitored by mass spectrometry (charge pattern shift) and fluorometry (tryptophan fluorescence quenching). The pH measurements were conducted at different points of the sample flow line by different methods to minimize artifacts. Interestingly, different protein ions (corresponding to native and unfolded proteins) show distinct temporal mass spectral profiles, which reveal gradual refolding and concomitant deprotonation of higher charge state ions in the course of the clock reaction. Every multiply charged ion of a protein is characterized with its own "clock time". This approach does not require major modification of standard instrumentation. It enables determination of "high sensitivity" pH intervals for small and large molecules within a single experiment. Thus, it can be useful for characterizing the protein folding in response to pH change.

We characterized a cohort of patients with posterior reversible encephalopathy syndrome with spinal cord involvement. We encountered 2 children and identified an additional 19 patients from the internet databases. Of the 21 patients analyzed, 8 were children. The mean peak systolic blood pressure in adults was significantly higher than in children (221.8 ± 14.3 vs 191.4 ± 31.3 mm Hg; P < .01). Regardless of age, the most common clinical symptom was headache (90%) and the least common clinical symptom was seizures (28%). Atypical neuroimaging was more common in children (63%) than in adults (8%). Abnormal cerebrospinal fluid results were frequently found in children (83%). All children recovered uneventfully, but 3 adults had sequelae. A broader clinicoradiologic spectrum makes the diagnosis of children more complex than in adults. Awareness of the atypical features with a meticulous management of hypertension is imperative to avoid unnecessary invasive workups and to achieve an uneventful recovery.

Much research has demonstrated that speeding is the most common offense among car drivers. However, few studies have focused on this offense among drivers of large trucks. This paper investigates the factors that lead to speeding offenses for drivers of large trucks in Taiwan. The study sample consisted of information for 2101 male large-truck drivers from a national survey in 2012. The results revealed that drivers’ daily working hours ranged from 2 to 15 h with a mean of 9.67 h, and that they worked for approximately 25.23 days – and rested only 4.77 days – per month. Among these observed drivers, 11.6% reported having at least one speeding offense over a one-year period. The results of a logistic regression model presented that the factors that influenced speeding offense were not related to job experience. Rather, the driver’s demographics (age and education), mental condition (sleep quality), and driving status (yearly distance driven and driving late at night) were significantly linked to speeding offenses.

Estimating the states of a cold-forging die is challenging when trying to extract the features from load-stroke signals during the long-term process. To solve this problem, this paper proposes a diagnosis learning model with an autoencoder and a support vector machine to distinguish the die states from the load-stoke signals. The autoencoder is utilized to extract the encoded features that serve as the input of the support vector machine to cluster die states. With timely indication of the current die state estimated by the learning model, the proposed die diagnosis system is promising to achieve the goal of reducing time for die maintenance.

Phenol can serve as a model for examining the deactivation of the aromatic amino acid tyrosine following UV excitation, which mainly occurs through a repulsive πσ

Near-edge X-ray absorption fine structure spectra of pyrimidine and purine at the carbon and nitrogen K-edges were measured using synchrotron radiation and a reflectron time-of-flight mass spectrometer. Spectrum assignments based on the time-dependent density functional theory calculation were presented. From the comparison of the experimental and theoretical results, the nature of various core-excitation transitions and the chemical shifts in the absorption energies were elucidated. The dissociation fragments following the core excitation were analyzed, and the enhancements on the fragment branching ratios were observed. The possible identities and dissociation mechanisms of the major fragments were discussed.

Females choosing taxi driving as a career is rare, therefore, investigating such samples is often difficult. Speeding is one of the most common driving violations, however, there has been no research looking into female taxi drivers’ speeding issue. This study explores the factors of female taxi drivers’ speeding offenses in Taiwan. Data is based on a national survey and includes 235 professional female taxi drivers. The results indicate that female taxi drivers work approximately 27.37 days per month, at a mean of 9.76 h per day. Of the female taxi drivers represented in this study, 22.8% reported at least one speeding offense over a one-year period. The results of a logistic regression model reveal that the determinant factors associated with female taxi drivers’ speeding offenses are significantly related to age, educational level and mileage driven. However, job experience, business operating style, and vehicle engine size are not associated with committing speeding offenses. Practical implications for traffic safety of female taxi drivers are also discussed.

In recent years, the development of autonomous surface vehicles has been a field of increasing research interest. There are two major areas in this field: control theory and path planning. This study focuses on path planning, and two objectives are discussed: path planning for Unmanned Surface Vehicles (USVs) and implementation of path planning in a real map. In this paper, satellite thermal images are converted into binary images which are used as the maps for the Finite Angle A * algorithm (FAA *), an advanced A * algorithm that is used to determine safer and suboptimal paths for USVs. To plan a collision-free path, the algorithm proposed in this article considers the dimensions of surface vehicles. Furthermore, the turning ability of a surface vehicle is also considered, and a constraint condition is introduced to improve the quality of the path planning algorithm, which makes the traveled path smoother. This study also shows a path planning experiment performed on a real satellite thermal image, and the path planning results can be used by an USV

The original ion imaging technique has low velocity resolution, and currently, photodissociation is mostly investigated using velocity map ion imaging. However, separating signals from the background (resulting from undissociated excited parent molecules) is difficult when velocity map ion imaging is used for the photodissociation of large molecules (number of atoms ≥ 10). In this study, we used the photodissociation of phenol at the S1 band origin as an example to demonstrate how our multimass ion imaging technique, based on modified spatial map ion imaging, can overcome this difficulty. The photofragment translational energy distribution obtained when multimass ion imaging was used differed considerably from that obtained when velocity map ion imaging and Rydberg atom tagging were used. We used conventional translational spectroscopy as a second method to further confirm the experimental results, and we conclude that data should be interpreted carefully when velocity map ion imaging or Rydberg atom tagging is used in the photodissociation of large molecules. Finally, we propose a modified velocity map ion imaging technique without the disadvantages of the current velocity map ion imaging technique.

Electric drones have a wide range of applications due to the convenience and agility. One of the main hurdles for their wide deployment and full automation is the battery life limitation and the need for manual intervention for charging. In this work, we present a solar powered charging system capable of automatically charging battery-powered drones in remote locations. We developed a tethered robotic rover equipped with a 2D Lidar sensor to detect and localize a drone, and a robotic arm equipped with an inductive charging pad. The charging pad senses current measurements from individual inductive coils, and adjusts accordingly the robotic arm position to maximize charging rate. Such system, in principal, can cater for arbitrary drone shapes and landing positions and is less susceptible to external lighting and environmental conditions by the use of Lidar and current sensors instead of computer vision. We remark that our system can be also applied to charging other small electric vehicles.

This paper examines the viability of electric taxis, namely whether it will be profitable for taxi drivers to adopt electric taxis, in comparison with conventional taxis with internal combustion engines. This paper provides a data analytic investigation using a large dataset of real-world taxi trips in New York City. We model the taxi service strategy by Markov Decision Process. Under this model, we observe that in order to enable an electric taxi driver (using Nissan Leaf) to reach a comparable profit with a conventional taxi driver, the minimum required battery capacity is 45 kWh, more than that of the existing one. We observe that the potential profit of the electric taxi driver can be 3% higher than that of a median conventional taxi driver with sufficient battery capacity, despite nowadays low gas price.

We characterized a cohort of patients with posterior reversible encephalopathy syndrome with spinal cord involvement. We encountered 2 children and identified an additional 19 patients from the internet databases. Of the 21 patients analyzed, 8 were children. The mean peak systolic blood pressure in adults was significantly higher than in children (221.8 ± 14.3 vs 191.4 ± 31.3 mm Hg; P.01). Regardless of age, the most common clinical symptom was headache (90%) and the least common clinical symptom was seizures (28%). Atypical neuroimaging was more common in children (63%) than in adults (8%). Abnormal cerebrospinal fluid results were frequently found in children (83%). All children recovered uneventfully, but 3 adults had sequelae. A broader clinicoradiologic spectrum makes the diagnosis of children more complex than in adults. Awareness of the atypical features with a meticulous management of hypertension is imperative to avoid unnecessary invasive workups and to achieve an uneventful recovery.

The ionization mechanism of ultraviolet matrix-assisted laser desorption/ionization (UV-MALDI) was investigated by measuring the total cation intensity (not including sodiated and potasiated ions) as a function of analyte concentration (arginine, histidine, and glycine) in a matrix of 2,4,6-trihydroxyacetophenone (THAP). The total ion intensity increased up to 55 times near the laser fluence threshold as the arginine concentration increased from 0% to 1%. The increases were small for histidine, and a minimal increase occurred for glycine. Time-resolved fluorescence intensity was employed to investigate how analytes affected the energy pooling of the matrix. No detectable energy pooling was observed for pure THAP and THAP/analyte mixtures. The results can be described by using a thermal proton transfer model, which suggested that thermally induced proton transfer is crucial in the primary ion generation in UV-MALDI.

UV-excited aromatic molecules with N–H/O–H moieties often possess an important nonradiative relaxation pathway, from an optically bright ππ* state to a dark dissociative πσ* state. We apply a new time-selected photofragment translational spectroscopy method to disclose a previously unknown triplet-mediated N–H dissociation of aniline prevented by the multiphoton dissociative ionization in conventional methods. We further determined the branching fractions of aniline dissociated in the πσ*, triplet, and ground states at 248 nm. Additionally, we selectively captured the population changes in the singlet and triplet states with ionization from different laser wavelengths, 355 or 266 nm, in time-resolved photoion yields. The combination of experimental data enables us to uniquely determine the relative ionization cross sections of the singlet and triplet states at an ionization laser wavelength of 266 nm and allows us to extensively measure the rate constants of intersystem crossing and the branching fractions at various excitation wavelengths.

A time-of-flight mass spectrometer with orthogonal acceleration and soft X-rays from synchrotron radiation were utilized to measure near-edge X-ray absorption fine structure (NEXAFS) spectra of carbon and oxygen in phenol and the corresponding ionic fragments following core excitation. The photon energies were in the range of 284−298 eV for the carbon K-edge and 529.5−554.5 eV for the oxygen K-edge. The total ion yield, ion intensity for each ionic fragment, and ion intensity ratio, defined as ion intensity divided by total ion yield, were measured as a function of photon energy. Possible mechanisms of dissociation are proposed and enhancements of specific products of dissociation are reported. In general, the enhancement of these specific products is small in the carbon K-edge region but is clear for some products at the oxygen K-edge. In particular, elimination of the H atom from the hydroxyl group was observed only at the oxygen K-edge. One remarkable result is that an excitation of a core-level electron of oxygen greatly enhanced the cleavage of specifi cC −C bonds.

RATIONALE: Energy pooling has been suggested as the key process for generating the primary ions during ultraviolet matrix-assisted laser desorption/ionization (UV-MALDI). In previous studies, decreases in fluorescence quantum yields as laser fluence increased for 2-aminobenzoic acid, 2,5-dihydroxybenzoic acid (2,5-DHB), and 3-hydroxypicolinic acid were used as evidence of energy pooling. This work extends the research to other matrices and addresses whether energy pooling is a universal property in UV-MALDI. METHODS: Energy pooling was investigated in a time-resolved fluorescence experiment by using a short laser pulse (355 nm, 20 ps pulse width) for excitation and a streak camera (1 ps time resolution) for fluorescence detection. RESULTS: The excited-state lifetime of 2,5-DHB decreased with increases in laser fluence. This suggests that a reaction occurs between two excited molecules, and that energy pooling may be one of the possible reactions. However, the excited-state lifetime of 2,4,6-trihydroxyacetophenone (THAP) did not change with increases in laser fluence. The upper limit of the energy pooling rate constant for THAP is estimated to be approximately 100–500 times smaller than that of 2,5-DHB. CONCLUSIONS: The small energy pooling rate constant for THAP indicates that the potential contribution of the energy pooling mechanism to the generation of THAP matrix primary ions should be reconsidered. Copyright © 2013 John Wiley & Sons, Ltd.

Speeding is the most common driving violation and a determinant factor contributing to both the number and severity of accidents. This study explored speeding violations based on a national cohort of 8129 adult male drivers in the one-year period of 2008. The analysis focused on the relationships between self-reported speeding violations and social-economic attributes: age, educational attainment, income level, yearly driving distance and the most frequent driving purpose (major driving purpose such as commuting and leisure or shopping). Of the 8129 observed drivers, 19.1% (1552 drivers) were ticketed at least once for a speeding violation. Drivers aged 40–49 possess the lowest speeding risk (speeding tickets per million kilometers), and both younger and older drivers have relatively higher speeding risk. The results of the logistic regression model revealed that speeding violations were significantly associated with the attributes of age, education, income, yearly driving distance and the most frequent driving purposes. The most frequent driving purposes for business (odds = 1.930, p = 0.016) and leisure (odds = 1.566, marginally significant p = 0.096) were associated with a higher speeding risk compared with the most frequent driving purpose for shopping.

The purpose of the present study was to verify the motivational factors underlying the theory of planned behavior (TPB) predicting the driving behavior of lifetime driving license revoked offenders. Of a total of 639 drivers whose licenses had been permanently revoked, 544 offenders completed a questionnaire constructed to measure attitudes toward behaviors, subjective norms, perceived behavioral control, behavioral intentions (the key constructs of the TPB), and previous driving habit strength. The finding of the study revealed that an offenders' driving behavior after a lifetime license revocation was significantly correlated to behavioral intention (R=0.60, p0.01), perceived behavioral control (R=0.61, p0.01), previous driving habit (R=0.44, p0.01), and attitude (R=0.41, p0.01). There was no evidence that subjective norms including road regulation, society ethics, and people important to offenders had an influence on driving behavior (R=0.03). Low driving habit strength offenders are motivated to drive because of behavioral intention, whereas strong driving habit strength offenders are motivated to drive because of perceived behavioral control. Previous driving habit strength is a moderator in the intention-behavior relationship. The model appeared successful when previous habits were weak, but less successful when previous habits were strong.

The paradigm of crowd-sourced data collection (also known as participatory sensing) has been bolstered by the extensive availability of on-board sensors and electronic devices in nowadays vehicles, which can be applied in a wide range of transportation applications. Distance-to-empty (DTE) is the distance an electric vehicle (EV) or internal-combustion engine (ICE) vehicle can reach before its battery/fuel is exhausted, which is determined by a variety of uncertain factors, such as driving behavior, terrain, types of road, traffic, and vehicle specification. Eco-routing aims to optimize the route selection with lower energy consumption. The accuracy of DTE prediction and eco-routing can be enhanced substantially by the crowd-sourced data collected from diverse drivers and vehicles. However, a critical concomitant issue for crowd-sourced data collection is privacy, because the personal travel history may be misused without consents from the contributing users. To encourage large-scale adoption and contributions of crowd-sourced data collection from end users, this paper addresses the issue of privacy and proposes possible solutions to tackle the challenges. In particular, we discuss a solution of matrix factorization from collaborative filtering to enhance the privacy of crowd-sourced data collection in the context of transportation applications, such as DTE prediction and eco-routing.

While the data extraction through the On-Board Diagnostics (OBD) port for internal combustion engine vehicles follows an industry standard, electric vehicles are not constrained by such a standard. In this paper, we demonstrate how to extract data from the OBD port of electric vehicles. We discuss the general techniques, and apply specifically to Nissan Leaf and Chevrolet Volt. We continue to present an application of carbon footprint evaluation by analyzing the data extracted from the OBD port to obtain parameters of interest. Furthermore, the methodology that can be used in various ways to evaluate the carbon footprint of electric vehicles by building synthetic driving cycles is presented.

Plug-in hybrid electric vehicles (PHEVs) are a viable energy-efficient means of transportation, which enjoy both convenience of fuel refilling and cheap electrical energy. But PHEVs have complex dynamics of orchestrating hybrid energy sources. While many prior results in energy management consider the internal optimization processes of PHEVs, this paper focuses on a driver-centric approach that enables the drivers to select the appropriate drive modes for minimizing fuel consumption. Drive modes are driver-selectable pre-set profiles of configurations of powertrain and vehicle parameters. Typical PHEVs have options of drive modes, for example, electric vehicle (EV) mode (that draws fully on battery) and charge sustaining (CS) mode (that utilizes internal combustion engine to charge battery while propelling the vehicle). We develop optimization algorithms that optimize drive mode selection based on trip information, and integrated with path planning to consider intermediate filling and charging stations. We also provide an online algorithm that requires minimal a-priori trip information. We implement our system and evaluate the results empirically on a Chevrolet Volt, which can enable a significant improvement in fuel efficiency.

Spontaneous hemopneumothorax (SHP) is a rare potentially life-threatening condition that occurs in predominantly young adolescents. The resultant massive hemorrhage leading to hypovolemic shock can be a surgical emergency. It constitutes 1-12% of all spontaneous pneumothoraces and presents with two cardinal features, chest pain and dyspnea. However, the pain of SHP may be confined to the abdomen secondary to the irritation of diaphragmatic pleura, which produces signs simulating an acute abdomen. SHP masquerading as an abdominal affection is apparently regarded as extremely rare. We present a case of a 16-year-old male with SHP presenting features simulating acute gallbladder disease. After prompt diagnosis with appropriate surgical intervention, he had an uneventful recovery. Our experience emphasizes the importance of careful and thorough chest examination for each child with atypical pictures for abdominal pain to exclude possible extra-abdominal lesions, even rare as SHP.

This study explored the at-fault accident risk of tour bus drivers based on 2023 drivers in Taiwan. Of the observed drivers, 4.1% had at least one accident in a year period, of these, 68.7% were at-fault for the accident. The results of logistic regression model revealed that a driver’s driving experience was the most influential factor (Wald = 32.291, p = 0.000) leading to at-fault accident risk. Drivers whose driving experience was from 6 to 8 years possessed the lowest at-fault accident rate (0.9%), which was lower than the over-all average at-fault accident rate of 2.8%. Novice drivers whose driving experience less than 3 years had the highest at-fault accident rate (12.4%). The driver’s yearly driving distance and the use of an Automatic Vehicle Location (AVL) system were also significantly associated with a driver’s at-fault accident. However, a driver’s age and educational level were not significantly associated with at-fault accident.

In this study, numerical analysis was carried out by using the finite element method to construct the first mode shape of damaged stiffened plates, and the damage locations were detected with two-dimensional discrete wavelet analysis. In the experimental analysis, four different damaged stiffened structures were observed. Firstly, each damaged structure was hit with a shaker, and then accelerometers were used to measure the vibration responses. Secondly, the first mode shape of each structure was obtained by using the wavelet packet, and the location of cracks were also determined by two-dimensional discrete wavelet analysis. The results of the numerical analysis and experimental investigation reveal that the proposed method is applicable to detect single crack or multi-cracks of a stiffened structure. The experimental results also show that fewer measurement points are required with the proposed technique in comparison to those presented in previous studies.

Postobstructive pulmonary edema is life-threatening, and results from a sudden episode of upper airway obstruction. Croup is generally thought to be a benign condition, but occasionally it can develop into postobstructive pulmonary edema. We present a case of a 5-year-old boy with recurrent croup, who was diagnosed with postobstructive pulmonary edema. Our experience alerts pediatricians to this easily misdiagnosed disease.

This article proposes the matrix of relationships among service quality, perceived risk, and customer value in the banking industry. Functional value was found to be affected mainly by reliable cues and accuracy of service quality and negatively affected by financial, functional, and physical risks, whereas conditional values are influenced by responsiveness of service quality and negatively influenced by temporal risk. Furthermore, emotional value was found to be affected mainly by empathy of service quality and negatively affected by psychological risk, whereas social values are influenced by tangible cues of service quality and negatively influenced by social risk. Finally, exact epistemic value is affected by responsiveness of service quality and negatively affected by psychological risk.

Phenol can serve as a model for examining the deactivation of the aromatic amino acid tyrosine following UV excitation, which mainly occurs through a repulsive πσ* state along the O-H bond. The reaction barrier formed by the conical intersection between the optically bright S1 (ππ*) state and the dissociative S2 (πσ*) state does not inhibit O-H bond rupture even though the excitation energy is below the barrier height. To examine the O-H bond-rupture dynamics in association with the initial excited vibrational modes, we used a picosecond laser to investigate the vibrational-mode-dependent excited-state lifetime of phenol under the S1/S2 conical intersection. Unexpectedly short lifetimes were observed in the S1 state for a″ symmetric vibrational modes (including v4, v16a, τOH, and v5). These results clarify recent theoretical calculations showing that the relaxation from S1 to S2 either occurs via symmetry-allowed non-adiabatic transitions or is topographically linked to a lower energy minimum on the multidimensional potential energy surface.

Photodissociation experiments employing molecular beams of N-methylindole, N-methylpyrrole, and anisole at 193 and 248 nm, respectively, have been conducted using multimass ion imaging techniques. We find that CH3 elimination is the sole dissociation channel for the studied molecules at both 193 and 248 nm. The photofragment translational energy distribution of anisole is found to contain both fast and slow components at the two wavelengths. On the other hand, a fast component (large recoil velocity) is dominant for N-methylindole at 248 nm, and a slow component (small recoil velocity) is dominant at 193 nm. The absorption coefficient of N-methylpyrrole is too weak for study at 248 nm. The photofragment translational energy distribution at 193 nm includes a large portion of the slow component and a small portion of the fast component. The findings indicate that the fast component corresponds to dissociation from the repulsive excited state and the slow component corresponding to dissociation from the ground electronic state. A comparison with the photodissociation dynamics of phenol, pyrrole, and indole suggests that replacement of the H atom by CH3 does not change the dissociation channels on the excited state. However, the respective dissociation channels for anisole and N-methylpyrrole on the ground state differ significantly from that for phenol and pyrrole.

Marketing promotions with public issue dimensions are becoming mainstream as practitioners respond to higher consumer expectations of corporate social responsibility. However, when consumers decide to buy a product or service, they usually consider service quality and perceived risk about the product or service. The general consensus of most research is that customer-perceived value determines customer loyalty. Does social marketing influence customer-perceived value by service quality or perceived risk? Somewhat surprisingly, little evidence exists that directly addresses this issue. This study elucidates how public-issue-promoted and revenue-related social marketing, service quality, and perceived risk are related, and explores the influence of service quality and perceived risk on customer-perceived value. The results indicate that public-issue-promoted social marketing makes a great impact on customer-perceived value in two ways: It affects customer-perceived value by increasing perceived ser...

Photodissociation of 2,5-dihydroxyacetophenone (DHAP), an important matrix compound in matrix-assisted laser desorption/ionization (MALDI), was studied in a molecular beam at 193 nm using multimass ion imaging techniques. Two major dissociation channels were observed, including (1) C(6)H(3)(OH)(2)COCH(3) --> OC(6)H(3)(OH)COCH(3) + H and (2) C(6)H(3)(OH)(2)COCH(3) --> C(6)H(3)(OH)(2) + COCH(3). The minor channels include C(6)H(3)(OH)(2)COCH(3) --> C(6)H(3)(OH)(2)CO + CH(3) and/or C(6)H(3)(OH)(2)COCH(3) --> C(6)H(3)(OH)(2) + CO + CH(3). The photofragment translational energy distribution suggests that reaction 1 occurs at an excited state in which the potential along the O-H bond distance is repulsive. Comparison to the branching ratios from RRKM calculations suggests that reaction 2 does not occur at either the ground state or the triplet state or that if it does occur at one of these states it must not follow the RRKM model. A comparison to the photodissociation dynamics of acetophenone and phenol and its derivatives was made.

The photodissociation of 1-naphthol at 193 and 248 nm was studied using multimass ion imaging techniques under collisionless conditions. Only one dissociation channel was observed, i.e. H atom elimination. The translational energy distributions show two components at both wavelengths. The slow component corresponds to the dissociation from the ground electronic state after internal conversion, and the fast component results from the dissociation on the electronic excited state. Comparison with the photodissociation of phenol was made.

Drive modes are driver-selectable pre-set configurations of powertrain and certain vehicle parameters. Plug-in hybrid electric vehicles (PHEVs) typically feature special options of drive modes that can affect the hybrid energy source management system, for example, electric vehicle (EV) mode (that draws fully on battery) and charge sustaining (CS) mode (that utilizes internal combustion engine to charge battery while propelling the vehicle). This paper studies an optimization problem to enable the driver to select the appropriate drive modes for fuel minimization. We develop optimization algorithms that optimize the decisions of drive modes based on trip information, and integrated with path planning to find an optimal path, considering intermediate filling and charging stations. We further provide an online algorithm that is based on the revealed trip information. We evaluate our algorithms empirically on a Chevrolet Volt, which shows significant fuel savings., Comment: To appear in IEEE Transactions on Intelligent Transportation Systems

The photodissociation dynamics of various aromatic molecules, studied using multimass ion imaging techniques, is reviewed. The experimental data reveals new isomerization and dissociation mechanisms. Our investigation of benzene, pyridine, and pyrimidine finds that H-atom elimination thresholds remain the same for the three molecules. We also notice that ring-opening dissociation thresholds decrease rapidly with the increase of the number of nitrogen atoms in the aromatic ring. Hydrogen atom elimination is the sole dissociation channel for benzene at 193 nm. Along with H-atom elimination, we observe five distinct ring-opening dissociation channels for pyridine at 193 nm. No dissociation channels were observed for benzene and pyridine at 248 nm. Ring-opening dissociation channels are the major channels for pyrimidine, which dissociates at 193 nm and also at 248 nm. A six-membered to seven-membered ring isomerization was observed for photodissociation processes involving toluene, m-xylene, aniline, 4-methylpyridine, alpha-fluorotoluene, and 4-fluorotoluene, indicating a general isomerization mechanism for all such aromatic molecules. What is significant, is that during the isomerization, atoms (i.e., carbon, nitrogen, fluorine, and hydrogen) belonging to respective alkyl or amino groups are involved in an exchange with atoms within the aromatic ring. This type of isomerization is not observed in other aromatic isomerization mechanisms. For small tyrosine chromophores, such as phenol, 4-methylphenol, and 4-ethylphenol, H-atom elimination from a repulsive excited state plays a key role. However, dissociation is quenched in large chromophores like 4-(2-aminoethyl)-phenol. Our work demonstrates the capability and high sensitivity of multimass ion imaging techniques in the study of aromatic compounds.

The photodissociation of phenol at 193 and 248 nm was studied using multimass ion-imaging techniques and step-scan time-resolved Fourier-transform spectroscopy. The major dissociation channels at 193 nm include cleavage of the OH bond, elimination of CO, and elimination of H(2)O. Only the former two channels are observed at 248 nm. The translational energy distribution shows that H-atom elimination occurs in both the electronically excited and ground states, but elimination of CO or H(2)O occurs in the electronic ground state. Rotationally resolved emission spectra of CO (1or= vor= 4) in the spectral region of 1860-2330 cm(-1) were detected upon photolysis at 193 nm. After a correction for rotational quenching, CO (vor= 4) shows a nascent rotational temperature of approximately 4600 K. The observed vibrational distribution of (v = 1)/(v = 2)/(v = 3)/(v = 4) = 64.3/22.2/9.1/4.4 corresponds to a vibrational temperature of 3350 +/- 20 K. An average rotational energy of 6.9 +/- 0.7 kcal mol(-1) and vibrational energy of 3.8 +/- 0.7 kcal mol(-1) are observed for the CO product. The dissociation channels, translational energy distributions of the photofragment, and vibrational and rotational energies of product CO are consistent with potential energy surfaces from quantum chemical calculations and the branching ratios from an RRKM calculation.

The photodissociation of p-methylphenol, p-ethylphenol, and p-(2-aminoethyl)phenol, chromophores of the amino acid tyrosine, was studied separately for each compound in a molecular beam at 248 nm using multimass ion imaging techniques. They show interesting side-chain size-dependent dissociation properties. Only one dissociation channel, that is, H atom elimination, was observed for both p-methylphenol and p-ethylphenol. The photofragment translational energy distributions and potential energy surfaces from ab initio calculation suggest that H atom elimination occurs from a repulsive excited state. On the other hand, the H atom elimination channel is quenched completely by internal conversion and/or intersystem crossing in p-(2-aminoethyl)phenol. Only C-C bond cleavage was observed from p-(2-aminoethyl)phenol. The photofragment translational energy distribution shows a slow component and a fast component. The fast component results from dissociation on an electronic excited state, but the slow component occurs only after the internal conversion to the ground electronic state. Comparison with the photodissociation of phenol and ethylbenzene is made.

The ability to track joint positions for Microsoft Kinect is useful for rehabilitation in both clinical and home settings. Unfortunately, most available commercial Kinect video games are not developed for rehabilitation purposes. In this study, a low-cost rehabilitation game training system has been developed for patients with movement disorders, it is suitable for use at home under the distant supervision of a therapist. This research explores the potential and the limitations of the Kinect-based system in the applications of e-rehabilitation. A prototypic system including 4 video games was developed for e-rehabilitation. In order to test the usefulness and effectiveness of the Kinect Virtual Rehabilitation System (KVRS), the Balance Recovery game was used to train patients with stroke to recover their balance abilities. It was demonstrated that balance training using the Kinect e-rehabilitation system exhibited a significant effect in recovering balance function for the stroke patients. Additionally, the outcome of questionnaire survey revealed that the KVRS video game was perceived as effective and easy in operation.

Participatory sensing is an emerging concept that integrates crowd-sourced data collection and knowledge discovery of collective behavior. Capitalizing on the advent of abundant sensors and information collection systems in near-future vehicles, we develop a participatory sensing based system and its methodologies for driving energy efficiency applications. Distance-to-empty (DTE) is the distance an electric or internal-combustion engine (ICE) vehicle can reach before its energy/fuel is exhausted, which is determined by a variety of uncertain factors, such as driving behavior, terrain, types of road, traffic, and vehicle specification. Green telematics aims to optimize the route selection with lower energy consumption. In this paper, we explore an effective approach that integrates the vehicle data gathered from participatory sensing to provide more accurate personalized DTE prediction and green telematics. Our approach relies on extracting the driver/vehicle/route dependent features and discovering correlations from collective driving data. We also present concrete case studies of our results, such as (1) DTE prediction for EVs based on the data of ICE vehicles, (2) classification and recommendations of energy-efficient driving behavior, and (3) route-level energy consumption geo-fencing and planning.