Two-dimensional ferroelectricity in a single-element bismuth monolayer.

Ferroelectric materials are fascinating for their non-volatile switchable electric polarizations induced by the spontaneous inversion-symmetry breaking. However, in all of the conventional ferroelectric compounds, at least two constituent ions are required to support the polarization switching1,2. Here, we report the observation of a single-element ferroelectric state in a black phosphorus-like bismuth layer3, in which the ordered charge transfer and the regular atom distortion between sublattices happen simultaneously. Instead of a homogenous orbital configuration that ordinarily occurs in elementary substances, we found the Bi atoms in a black phosphorous-like Bi monolayer maintain a weak and anisotropic sp orbital hybridization, giving rise to the inversion-symmetry-broken buckled structure accompanied with charge redistribution in the unit cell. As a result, the in-plane electric polarization emerges in the Bi monolayer. Using the in-plane electric field produced by scanning probe microscopy, ferroelectric switching is further visualized experimentally. Owing to the conjugative locking between the charge transfer and atom displacement, we also observe the anomalous electric potential profile at the 180° tail-to-tail domain wall induced by competition between the electronic structure and electric polarization. This emergent single-element ferroelectricity broadens the mechanism of ferroelectrics and may enrich the applications of ferroelectronics in the future.

Prediction of gestational diabetes mellitus at the first trimester: machine-learning algorithms.

PURPOSE: Short- and long-term complications of gestational diabetes mellitus (GDM) involving pregnancies and offspring warrant the development of an effective individualized risk prediction model to reduce and prevent GDM together with its associated co-morbidities. The aim is to use machine learning (ML) algorithms to study data gathered throughout the first trimester in order to predict GDM. METHODS: Two independent cohorts with forty-five features gathered through first trimester were included. We constructed prediction models based on three different algorithms and traditional logistic regression, and deployed additional two ensemble algorithms to identify the importance of individual features. RESULTS: 4799 and 2795 pregnancies were included in the Xinhua Hospital Chongming branch (XHCM) and the Shanghai Pudong New Area People's Hospital (SPNPH) cohorts, respectively. Extreme gradient boosting (XGBoost) predicted GDM with moderate performance (the area under the receiver operating curve (AUC) = 0.75) at pregnancy initiation and good-to-excellent performance (AUC = 0.99) at the end of the first trimester in the XHCM cohort. The trained XGBoost showed moderate performance in the SPNPH cohort (AUC = 0.83). The top predictive features for GDM diagnosis were pre-pregnancy BMI and maternal abdominal circumference at pregnancy initiation, and FPG and HbA1c at the end of the first trimester. CONCLUSION: Our work demonstrated that ML models based on the data gathered throughout the first trimester achieved moderate performance in the external validation cohort.

Convolutional Neural Networks for Classifying Cervical Cancer Types Using Histological Images.

Cervical cancer is the most common cancer among women worldwide. The diagnosis and classification of cancer are extremely important, as it influences the optimal treatment and length of survival. The objective was to develop and validate a diagnosis system based on convolutional neural networks (CNN) that identifies cervical malignancies and provides diagnostic interpretability. A total of 8496 labeled histology images were extracted from 229 cervical specimens (cervical squamous cell carcinoma, SCC, n = 37; cervical adenocarcinoma, AC, n = 8; nonmalignant cervical tissues, n = 184). AlexNet, VGG-19, Xception, and ResNet-50 with five-fold cross-validation were constructed to distinguish cervical cancer images from nonmalignant images. The performance of CNNs was quantified in terms of accuracy, precision, recall, and the area under the receiver operating curve (AUC). Six pathologists were recruited to make a comparison with the performance of CNNs. Guided Backpropagation and Gradient-weighted Class Activation Mapping (Grad-CAM) were deployed to highlight the area of high malignant probability. The Xception model had excellent performance in identifying cervical SCC and AC in test sets. For cervical SCC, AUC was 0.98 (internal validation) and 0.974 (external validation). For cervical AC, AUC was 0.966 (internal validation) and 0.958 (external validation). The performance of CNNs falls between experienced and inexperienced pathologists. Grad-CAM and Guided Gard-CAM ensured diagnoses interpretability by highlighting morphological features of malignant changes. CNN is efficient for histological image classification tasks of distinguishing cervical malignancies from benign tissues and could highlight the specific areas of concern. All these findings suggest that CNNs could serve as a diagnostic tool to aid pathologic diagnosis.

Coordination of Intraoperative Neurophysiologic Monitoring Technologist and Surgery Schedules.

Resource coordination in surgical scheduling remains challenging in health care delivery systems. This is especially the case in highly-specialized settings such as coordinating Intraoperative Neurophysiologic Monitoring (IONM) resources. Inefficient coordination yields higher costs, limited access to care, and creates constraints to surgical quality and outcomes. To maximize utilization of IONM resources, optimization-based algorithms are proposed to effectively schedule IONM surgical cases and technologists and evaluate staffing needs. Data with 10 days of case volumes, their surgery durations, and technologist staffing was used to demonstrate method effectiveness. An iterative optimization-based model that determines both optimal surgery and technologist start time (operational scenario 4) was built in an Excel spreadsheet along with Excel's Solver settings. It was compared with current practice (operational scenario 1) and optimization solution on only surgery start time (operational scenario 2) or technologist start time (operational scenario 3). Comparisons are made with respect to technologist overtime and under-utilization time. The results conclude that scenario 4 significantly reduces overtime by 74% and under-utilization time by 86% as well as technologist needs by 10%. For practices that do not have flexibility to alter surgeon preference on surgery start time or IONM technologist staffing levels, both scenarios 2 and 3 also result in substantial reductions in technologist overtime and under-utilization. Moreover, IONM technologist staffing options are discussed to accommodate technologist preferences and set constraints for surgical case scheduling. All optimization-based approaches presented in this paper are able to improve utilization of IONM resources and ultimately improve the coordination and efficiency of highly-specialized resources.

Reduce Patient Treatment wait time in a Proton Beam Facility - A Gatekeeper Approach.

Patient wait time can negatively impact treatment quality in a proton therapy center, where multiple treatment rooms share one proton beam. Wait time increases patient discomfort that can lead to patient motion, dissatisfaction, and longer treatment delay. This study was to develop a patient call-back model that reduced patient wait while efficiently utilizing the proton beam. A "Gatekeeper" logic allowing therapists to adjust the time of a patient's call-back to the treatment room was developed. It uses a two-pronged approach to minimize overlap of long treatment and the possibility of excessive wait in the queue to receive the proton beam. The goal was to reduce the maximum wait time to less than eight minutes per field for a four-room facility. The effectiveness of this logic was evaluated through simulation, and five scenarios were compared. Four scenarios implementing various levels of gatekeeper logic were compared with the original scenario without the logic. The best performing model provided a reduction of the maximum field wait by 26% and met the predefined goal. Adjusting call-back extended the treatment day length by an average of 6 min and a maximum of 12 min in total. The use of this gatekeeper logic significantly reduces patient field wait with minimal impact on treatment day length for a four-room proton facility. A sample interface that adopts this logic for therapists to make informed decision on patient call-back time is demonstrated.

An Algorithm for Pairing Interventionalists and Surgeons for the TAVR Procedure.

The Transcatheter Aortic Valve Replacement (TAVR) procedure requires an initial consultation and a subsequent procedure by an interventionalist (IC) and surgeon. The IC-surgeon pair coordination is extremely challenging, especially at Mayo Clinic due to provider time commitments distributed across practice, research, and education activities. Current practice aims to establish the coordination manually, resulting in a scheduling process that is cumbersome and time consuming for the schedulers. We develop an algorithm for pairing ICs and surgeons that minimizes the lead time (days elapsed between the clinic consult and procedure). As compared to current practice, this algorithm is able to reduce average lead time by 59% and increase possible IC-surgeon pairs by 7%. The proposed algorithm is shown to be flexible enough to incorporate practice variations such as lead time upper bound and two procedure days for a single consult day. Algorithm alternatives are also presented for practices who may find the proposed algorithm infeasible for their practice.

High-Energy Gain Upconversion in Monolayer Tungsten Disulfide Photodetectors.

Photodetectors usually operate in the wavelength range with photon energy above the bandgap of channel semiconductors so that incident photons can excite electrons from valence band to conduction band to generate photocurrent. Here, however, we show that monolayer WS2 photodetectors can detect photons with energy even lying 219 meV below the bandgap of WS2 at room temperature. With the increase of excitation wavelength from 620 to 680 nm, photoresponsivity varies from 551 to 59 mA/W. This anomalous phenomenon is ascribed to energy upconversion, which is a combination effect of one-photon excitation and multiphonon absorption through an intermediate state created most likely by sulfur divacancy with oxygen adsorption. These findings will arouse research interests on other upconversion optoelectronic devices, photovoltaic devices, for example, of monolayer transition metal dichalcogenides (TMDCs).

The organic-2D transition metal dichalcogenide heterointerface.

Since the first isolation of graphene, new classes of two-dimensional (2D) materials have offered fascinating platforms for fundamental science and technology explorations at the nanometer scale. In particular, 2D transition metal dichalcogenides (TMD) such as MoS2 and WSe2 have been intensely investigated due to their unique electronic and optical properties, including tunable optical bandgaps, direct-indirect bandgap crossover, strong spin-orbit coupling, etc., for next-generation flexible nanoelectronics and nanophotonics applications. On the other hand, organics have always been excellent materials for flexible electronics. A plethora of organic molecules, including donors, acceptors, and photosensitive molecules, can be synthesized using low cost and scalable procedures. Marrying the fields of organics and 2D TMDs will bring benefits that are not present in either material alone, enabling even better, multifunctional flexible devices. Central to the realization of such devices is a fundamental understanding of the organic-2D TMD interface. Here, we review the organic-2D TMD interface from both chemical and physical perspectives. We discuss the current understanding of the interfacial interactions between the organic layers and the TMDs, as well as the energy level alignment at the interface, focusing in particular on surface charge transfer and electronic screening effects. Applications from the literature are discussed, especially in optoelectronics and p-n hetero- and homo-junctions. We conclude with an outlook on future scientific and device developments based on organic-2D TMD heterointerfaces.

Chemotherapy scheduling template development using an optimization approach.

PURPOSE: The purpose of this paper is to develop a chemotherapy scheduling template that accounts for nurse resource availability and patient treatment needs to alleviate the mid-day patient load and provide quality services for patients. DESIGN/METHODOLOGY/APPROACH: Owing to treatment complexity in chemotherapy administration, nurses are required at the beginning, end and during treatment. When nurses are not available to continue treatment, the service is compromised, and the resource constraint is violated, which leads to inevitable delay that risks service quality. Consequently, an optimization method is used to create a scheduling template that minimizes the violation between resource assignment and treatment requirements, while leveling patient load throughout a day. A case study from a typical clinic day is presented to understand current scheduling issues, describe nursing resource constraints, and develop a constraint-based optimization model and leveling algorithm for the final template. FINDINGS: The approach is expected to reduce the variation in the system by 24 percent and result in five fewer chemo chairs used during peak hours. Adjusting staffing levels could further reduce resource constraint violations and more savings on chair occupancy. The actual implementation results indicate a 33 percent reduction on resource constraint violations and positive feedback from nursing staff for workload. RESEARCH LIMITATIONS/IMPLICATIONS: Other delays, including laboratory test, physician visit and treatment assignment, are potential research areas. ORIGINALITY/VALUE: The study demonstrates significant improvement in mid-day patient load and meeting treatment needs using optimization with a unique objective.

Gender differences in effects of obesity and asthma on adolescent lung function: Results from a population-based study.

OBJECTIVE: To investigate lung function associated with asthma and body mass index (BMI) among adolescents at 96 northern Taiwan junior high schools participating in an asthma screening program. METHODS: The questionnaires and lung function test results measured for 3669 boys and 3523 girls were included in this study for data analysis. Measures of forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1) and FEV1/FVC ratio were compared by sex, asthma status and BMI. RESULTS: Overall mean FVC levels were similar between students with and without asthma, 3.71 L vs. 3.71 L for boys (p = 0.991) and 2.79 vs. 2.78 for girls (p = 0.517). The overall mean FEV1 levels were also similar between girls with and without asthma. Asthmatic boys had lower FEV1 than non-asthmatic boys. Mean FEV1/FVC was significantly lower in students with asthma than those without asthma. Mean FVC and FEV1 increased with BMI in both sexes. A lower mean FEV1/FVC was observed among students with asthma and high BMI, and was more pronounced in boys than in girls. Multivariable regression analysis also showed that FEV1/FVC ratios were negatively associated with asthma and high BMI, stronger in boys than in girls for asthma (ß = -2.176 (standard errors (SE) = 0.268) vs. -1.085 (SE = 0.258) and for BMI (ß = -0.309 (SE = 0.025) vs. -0.218 (SE = 0.029)). CONCLUSION: This northern Taiwan study suggests that FEV1/FVC is negatively associated with asthma and high BMI in adolescents, stronger for boys than for girls.

Gap States at Low-Angle Grain Boundaries in Monolayer Tungsten Diselenide.

Two-dimensional (2D) transition metal dichalcogenides (TMDs) have revealed many novel properties of interest to future device applications. In particular, the presence of grain boundaries (GBs) can significantly influence the material properties of 2D TMDs. However, direct characterization of the electronic properties of the GB defects at the atomic scale remains extremely challenging. In this study, we employ scanning tunneling microscopy and spectroscopy to investigate the atomic and electronic structure of low-angle GBs of monolayer tungsten diselenide (WSe2) with misorientation angles of 3-6°. Butterfly features are observed along the GBs, with the periodicity depending on the misorientation angle. Density functional theory calculations show that these butterfly features correspond to gap states that arise in tetragonal dislocation cores and extend to distorted six-membered rings around the dislocation core. Understanding the nature of GB defects and their influence on transport and other device properties highlights the importance of defect engineering in future 2D device fabrication.

Seasonal distribution and prevalence of diarrheagenic Escherichia coli in different aquatic environments in Taiwan.

Diarrheagenic Escherichia coli (DEC) are the most common agents of diarrhea. Waterborne DEC could pose a potential health risk to human through agricultural, household, recreational, and industrial use. There are few published reports on the detection of DEC and its seasonal distribution in aquatic environments. The presence of DEC in different types of aquatic environments was investigated in this study. Water samples were collected from major rivers, water reservoirs, and recreational hot springs throughout Taiwan. Moreover, an intensive water sampling plan was carried out along Puzih River. The detection of DEC target genes was used to determine the presence of enterotoxigenic E. coli (ETEC), enteropathogenic E. coli (EPEC), and Shiga toxin-producing E. coli (STEC). Among the 383 water samples analyzed, DEC was found in 122 (31.8%) samples. The detection rate varied by genotype, raging from 3.6% for STEC to 17.2% for EPEC. The DEC detection rate was higher from river waters than reservoirs and hot springs. In addition, DEC was detected at a higher rate in spring and summer. The presence of EPEC was significantly associated with total coliform levels among hot spring samples. Moreover, the presence of ETEC in river water samples was associated with heterotrophic plate counts. Water with EPEC differed significantly in pH from Puzih River samples. These results suggest that seasonal characteristics may affect the presence of DEC in different aquatic environments, and water quality indicators may be indicative of the presence of DEC.

Appointment standardization evaluation in a primary care facility.

Purpose - The purpose of this paper is to evaluate the performance on standardizing appointment slot length in a primary care clinic to understand the impact of providers' preferences and practice differences. Design/methodology/approach - The treatment time data were collected for each provider. There were six patient types: emergency/urgent care (ER/UC), follow-up patient (FU), new patient, office visit (OV), physical exam, and well-child care. Simulation model was developed to capture patient flow and measure patient wait time, provider idle time, cost, overtime, finish time, and the number of patients scheduled. Four scheduling scenarios were compared: scheduled all patients at 20 minutes; scheduled ER/UC, FU, OV at 20 minutes and others at 40 minutes; scheduled patient types on individual provider preference; and scheduled patient types on combined provider preference. Findings - Standardized scheduling among providers increase cost by 57 per cent, patient wait time by 83 per cent, provider idle time by five minutes per patient, overtime by 22 minutes, finish time by 30 minutes, and decrease patient access to care by approximately 11 per cent. An individualized scheduling approach could save as much as 14 per cent on cost and schedule 1.5 more patients. The combined preference method could save about 8 per cent while the number of patients scheduled remained the same. Research limitations/implications - The challenge is to actually disseminate the findings to medical providers and adjust scheduling systems accordingly. Originality/value - This paper concluded standardization of providers' clinic preference and practice negatively impact clinic service quality and access to care.

Time dependent patient no-show predictive modelling development.

Purpose - The purpose of this paper is to develop evident-based predictive no-show models considering patients' each past appointment status, a time-dependent component, as an independent predictor to improve predictability. Design/methodology/approach - A ten-year retrospective data set was extracted from a pediatric clinic. It consisted of 7,291 distinct patients who had at least two visits along with their appointment characteristics, patient demographics, and insurance information. Logistic regression was adopted to develop no-show models using two-thirds of the data for training and the remaining data for validation. The no-show threshold was then determined based on minimizing the misclassification of show/no-show assignments. There were a total of 26 predictive model developed based on the number of available past appointments. Simulation was employed to test the effective of each model on costs of patient wait time, physician idle time, and overtime. Findings - The results demonstrated the misclassification rate and the area under the curve of the receiver operating characteristic gradually improved as more appointment history was included until around the 20th predictive model. The overbooking method with no-show predictive models suggested incorporating up to the 16th model and outperformed other overbooking methods by as much as 9.4 per cent in the cost per patient while allowing two additional patients in a clinic day. Research limitations/implications - The challenge now is to actually implement the no-show predictive model systematically to further demonstrate its robustness and simplicity in various scheduling systems. Originality/value - This paper provides examples of how to build the no-show predictive models with time-dependent components to improve the overbooking policy. Accurately identifying scheduled patients' show/no-show status allows clinics to proactively schedule patients to reduce the negative impact of patient no-shows.

Increased serum 2-oxoglutarate associated with high myocardial energy expenditure and poor prognosis in chronic heart failure patients.

Myocardial energy expenditure (MEE) and 2-oxoglutarate are elevated in chronic heart failure (CHF) patients compared with healthy controls. To explore whether 2-oxoglutarate could reflect the levels of MEE and predict the prognosis of CHF, 219 CHF patients and 66 healthy controls were enrolled. 2-Oxoglutarate was assayed with Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (LC/MS/MS). CHF patients were divided into 4 groups according to interquartile range of MEE and followed for death or recurrent hospital admission due to CHF for the mean follow-up time 6.64±0.16months. 2-Oxoglutarate was increased in CHF patients compared with controls (P<0.01) and correlated with estimated glomerular filtration rate (r=0.142, P=0.036), age (r=-0.269, P<0.01) and MEE levels (r=0.307, P<0.01) in a multiple linear correlation analysis in CHF patients. Furthermore, 2-oxoglutarate (OR=3.470, 95% CI=1.557 to 7.730, P=0.002), N-terminal pro-B-type natriuretic peptide (OR=4.013, 95% CI=1.553 to 10.365, P=0.004), age (OR=1.611, 95% CI=1.136 to 2.283, P=0.007) and left ventricular ejection fraction (OR=7.272, 95% CI=3.110 to 17.000, P<0.001) were independently associated with MEE on multiple logistic regression analysis. Kaplan-Meier event curves showed that high 2-oxoglutarate levels were associated with adverse outcomes (Log Rank, Chi(2)=4.026, P=0.045). This study showed that serum 2-oxoglutarate is associated with MEE levels, which can be used as potential biomarkers for MEE, and it can reflect the clinical severity and short-term outcome of CHF.

Understanding the adsorption of CuPc and ZnPc on noble metal surfaces by combining quantum-mechanical modelling and photoelectron spectroscopy.

Phthalocyanines are an important class of organic semiconductors and, thus, their interfaces with metals are both of fundamental and practical relevance. In the present contribution we provide a combined theoretical and experimental study, in which we show that state-of-the-art quantum-mechanical simulations are nowadays capable of treating most properties of such interfaces in a quantitatively reliable manner. This is shown for Cu-phthalocyanine (CuPc) and Zn-phthalocyanine (ZnPc) on Au(111) and Ag(111) surfaces. Using a recently developed approach for efficiently treating van der Waals (vdW) interactions at metal/organic interfaces, we calculate adsorption geometries in excellent agreement with experiments. With these geometries available, we are then able to accurately describe the interfacial electronic structure arising from molecular adsorption. We find that bonding is dominated by vdW forces for all studied interfaces. Concomitantly, charge rearrangements on Au(111) are exclusively due to Pauli pushback. On Ag(111), we additionally observe charge transfer from the metal to one of the spin-channels associated with the lowest unoccupied π-states of the molecules. Comparing the interfacial density of states with our ultraviolet photoelectron spectroscopy (UPS) experiments, we find that the use of a hybrid functionals is necessary to obtain the correct order of the electronic states.

Evaluation of diarrheagenic E. coli in riversheds by quantitative PCR in combination with enrichment.

Diarrheagenic Escherichia coli (DEC) is a group of the most common agents of diarrhea. Highly virulent DEC strains could cause illness with dozens of organisms. Waterborne DEC may be detected using polymerase chain reaction (PCR); however, environmental contaminants can interfere with PCR reaction, thus causing the prevalence of DEC to be underestimated. In this study, we propose an approach to efficiently quantify trace amounts of DEC. An enrichment procedure was performed to amplify total E. coli including DEC in the water samples. By normalizing the number of pathotype-specific genes to the amplification rate of a housekeeping gene in all E. coli, the quantity of DEC in original samples could be assessed. This method allows detection of trace amounts of DEC in receiving waters. The results showed that the presence of DEC in water samples was partially associated with riverside settlement. The DEC concentration was substantially higher at a few sampling sites, suggesting that evaluation of DEC along the river may help identify previously unknown pollution sources. Although the sustainability of DEC in the receiving waters may be low, the risk of DEC infection from the watershed warrants further examination.

Predicting Provider Workload Using Predicted Patient Risk Score and Social Determinants of Health in Primary Care Setting.

BACKGROUND: Provider burnout due to workload is a significant concern in primary care settings. Workload for primary care providers encompasses both scheduled visit care and non-visit care interactions. These interactions are highly influenced by patients' health conditions or acuity, which can be measured by the Adjusted Clinical Group (ACG) score. However, new patients typically have minimal health information beyond social determinants of health (SDOH) to determine ACG score. OBJECTIVES: This study aims to assess new patient workload by first predicting the ACG score using SDOH, age, and gender and then using this information to estimate the number of appointments (scheduled visit care) and non-visit care interactions. METHODS: Two years of appointment data were collected for patients who had initial appointment requests in the first year and had the ACG score, appointment, and non-visit care counts in the subsequent year. State-of-art machine learning algorithms were employed to predict ACG scores and compared with current baseline estimation. Linear regression models were then used to predict appointments and non-visit care interactions, integrating demographic data, SDOH, and predicted ACG scores. RESULTS: The machine learning methods showed promising results in predicting ACG scores. Besides the decision tree, all other methods performed at least 9% better in accuracy than the baseline approach which had an accuracy of 78%. Incorporating SDOH and predicted ACG scores also significantly improved the prediction for both appointments and non-visit care interactions. The R 2 values increased by 95.2 and 93.8%, respectively. Furthermore, age, smoking tobacco, family history, gender, usage of injection birth control, and ACG were significant factors for determining appointments. SDOH factors such as tobacco usage, physical exercise, education level, and group activities were strongly correlated with non-visit care interactions. CONCLUSION: The study highlights the importance of SDOH and predicted ACG scores in predicting provider workload in primary care settings.

Ancillary service impact on outpatient scheduling.

PURPOSE: The paper aims to provide a simulation optimization solution to improve patient scheduling that accounts for varying ancillary service time such as x-ray to minimize patient wait time. DESIGN/METHODOLOGY/APPROACH: The two-step approach is to: identify patients' needs for ancillary services while scheduling appointments; and propose an algorithm to determine ancillary service time via simulation optimization. The main aim is to provide sufficient time between arrival at the clinic and the actual examination time for a patient to complete pre-visit activities without contributing significantly to patient wait time. Two case studies are included to demonstrate the approach. FINDINGS: Triaging at the appointment-scheduling time saves an average 17 minutes for physician's first consultation in a clinic day, and a 7 percent reduction on current average patient wait time for case 1. Case 2 results in a 9 percent reduction on average patient wait time. The scheduled ancillary service time depends on the frequency and the ancillary service time, and appointment slot design. RESEARCH LIMITATIONS/IMPLICATIONS: One limitation is the impact of modeling error on the account of ancillary service times and the modeling assumptions. PRACTICAL IMPLICATIONS: The proposed approach provides a studying method for clinic staff to account for ancillary services prior to physicians' visits for a better patient care. Two case studies demonstrated the practicability and promising results on reducing patient waiting. ORIGINALITY/VALUE: This article presents a unique approach to considering the required ancillary services in outpatient scheduling system that minimizes patient wait times. The approach will strengthen the existing scheduling methods to allow the time for ancillary services.

Application of passive sampling on assessment of concentration distribution and health risk of volatile organic compounds at a high-tech science park.

The objectives of this study are to investigate the volatile organic compound (VOC) distribution using passive samplers and to assess the resulting health risks in a high-tech science industrial park. With the advantages of passive sampling techniques, long-term and wide-area samples are collected. The results show TVOC concentrations in summer, fall, winter, and spring are 7.14 ± 5.66 ppb, 18.17 ± 5.81 ppb, 10.30 ± 3.54 ppb, and 14.56 ± 4.53 ppb, respectively; those on weekdays and weekends are 14.36 ± 6.80 ppb and 9.87 ± 4.86 ppb, respectively; and those in industrial and residential zones are 12.97 ± 0.39 ppb and 11.13 ± 0.68 ppb, respectively. Based on concentration variations, and benzene, toluene, ethylbenzene, and xylene ratios, we can resolve the source origins. Health risks are assessed based on the resulting concentrations. In the case of non-cancer chronic effects, long-term exposure to these concentrations does not support there is a risk of adverse health effects. However, potential cancer risks of exposure to these concentrations may occur, especially to carbon tetrachloride and benzene. By applying this study's procedures, information on VOC concentration distribution, source identification, and health assessment can be obtained and they are applicable to similar studies.