Search results for: Yanbin Tang

Authors: Chang Liu, Rui Xing, Liyan Tang, Guohong Wang

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Entrepreneurial actions are based on entrepreneurial decisions. The quality of decisions influences entrepreneurial activities and subsequent new venture performance. Uncertainty of surroundings put heightened demands on the team as a whole, and each team member. Diverse team composition provides rich information, which a team can draw when making complex decisions. However, team heterogeneity may cause emotional conflicts, which is adverse to team outcomes. Thus, the effects of team heterogeneity on team outcomes are complex. Although team heterogeneity is an essential factor influencing entrepreneurial decision-making, there is a lack of empirical analysis on under what conditions team heterogeneity plays a positive role in promoting decision-making quality. Entrepreneurial teams always struggle with complex tasks. How a team shapes its teamwork is key in resolving constant issues. As a collective regulatory process, team reflexivity is characterized by continuous joint evaluation and discussion of team goals, strategies, and processes, and adapt them to current or anticipated circumstances. It enables diversified information to be shared and overtly discussed. Instead of hostile interpretation of opposite opinions team members take them as useful insights from different perspectives. Team reflexivity leads to better integration of expertise to avoid the interference of negative emotions and conflict. Therefore, we propose that team reflexivity is a conditional factor that influences the impact of team heterogeneity on high-quality entrepreneurial decisions. In this study, we identify team heterogeneity as a crucial determinant of entrepreneurial decision quality. Integrating the literature on decision-making and team heterogeneity, we investigate the relationship between team heterogeneity and entrepreneurial decision-making quality, treating team reflexivity as a moderator. We tested our hypotheses using the hierarchical regression method and the data gathered from 63 teams and 205 individual members from 45 new firms in China's first-tier cities such as Beijing, Shanghai, and Shenzhen. This research found that both teams' education heterogeneity and teams' functional background heterogeneity were significantly positively related to entrepreneurial decision-making quality, and the positive relation was stronger in teams with a high level of team reflexivity. While teams' specialization of education heterogeneity was negatively related to decision-making quality, and the negative relationship was weaker in teams with a high level of team reflexivity. We offer two contributions to decision-making and entrepreneurial team literatures. Firstly, our study enriches the understanding of the role of entrepreneurial team heterogeneity in entrepreneurial decision-making quality. Different from previous entrepreneurial decision-making literatures, which focus more on decision-making modes of entrepreneurs and the top management team, this study is a significant attempt to highlight that entrepreneurial team heterogeneity makes a unique contribution to generating high-quality entrepreneurial decisions. Secondly, this study introduced team reflexivity as the moderating variable, to explore the boundary conditions under which the entrepreneurial team heterogeneity play their roles.

Keywords: decision-making quality, entrepreneurial teams, education heterogeneity, functional background heterogeneity, specialization of education heterogeneity

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Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yonggang Qian, Ning Wang

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Knowledge of land surface temperature (LST) is of crucial important in energy balance studies and environment modeling. Satellite thermal infrared (TIR) imagery is the primary source for retrieving LST at the regional and global scales. Due to the combination of atmosphere and land surface of received radiance by TIR sensors, atmospheric effect correction has to be performed to remove the atmospheric transmittance and upwelling radiance. Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) provides measurements every 15 minutes in 12 spectral channels covering from visible to infrared spectrum at fixed view angles with 3km pixel size at nadir, offering new and unique capabilities for LST, LSE measurements. However, due to its high temporal resolution, the atmosphere correction could not be performed with radiosonde profiles or reanalysis data since these profiles are not available at all SEVIRI TIR image acquisition times. To solve this problem, a two-part six-parameter semi-empirical diurnal temperature cycle (DTC) model has been applied to the temporal interpolation of ECMWF reanalysis data. Due to the fact that the DTC model is underdetermined with ECMWF data at four synoptic times (UTC times: 00:00, 06:00, 12:00, 18:00) in one day for each location, some approaches are adopted in this study. It is well known that the atmospheric transmittance and upwelling radiance has a relationship with water vapour content (WVC). With the aid of simulated data, the relationship could be determined under each viewing zenith angle for each SEVIRI TIR channel. Thus, the atmospheric transmittance and upwelling radiance are preliminary removed with the aid of instantaneous WVC, which is retrieved from the brightness temperature in the SEVIRI channels 5, 9 and 10, and a group of the brightness temperatures for surface leaving radiance (Tg) are acquired. Subsequently, a group of the six parameters of the DTC model is fitted with these Tg by a Levenberg-Marquardt least squares algorithm (denoted as DTC model 1). Although the retrieval error of WVC and the approximate relationships between WVC and atmospheric parameters would induce some uncertainties, this would not significantly affect the determination of the three parameters, td, ts and β (β is the angular frequency, td is the time where the Tg reaches its maximum, ts is the starting time of attenuation) in DTC model. Furthermore, due to the large fluctuation in temperature and the inaccuracy of the DTC model around sunrise, SEVIRI measurements from two hours before sunrise to two hours after sunrise are excluded. With the knowledge of td , ts, and β, a new DTC model (denoted as DTC model 2) is accurately fitted again with these Tg at UTC times: 05:57, 11:57, 17:57 and 23:57, which is atmospherically corrected with ECMWF data. And then a new group of the six parameters of the DTC model is generated and subsequently, the Tg at any given times are acquired. Finally, this method is applied to SEVIRI data in channel 9 successfully. The result shows that the proposed method could be performed reasonably without assumption and the Tg derived with the improved method is much more consistent with that from radiosonde measurements.

Keywords: atmosphere correction, diurnal temperature cycle model, land surface temperature, SEVIRI

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Authors: Ofelia Loani Elvir Lazo, Roya Yumul, Sevan Komshian, Ruby Wang, Jun Tang

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Background: Monitoring the anti-nociceptive drug effect is useful because a sudden and strong nociceptive stimulus may result in untoward autonomic responses and muscular reflex movements. Monitoring the anti-nociceptive effects of perioperative medications has long been desiredas a way to provide anesthesiologists information regarding a patient’s level of antinociception and preclude any untoward autonomic responses and reflexive muscular movements from painful stimuli intraoperatively.To this end, electroencephalogram (EEG) based tools includingBIS and qCON were designed to provide information about the depth of sedation whileqNOXwas produced to informon the degree of antinociception.The goal of this study was to compare the reliability of qCON/qNOX to BIS asspecific indicators of response to nociceptive stimulation. Methods: Sixty-two patients undergoing general anesthesia with LMA were included in this study. Institutional Review Board(IRB) approval was obtained, and informed consent was acquired prior to patient enrollment. Inclusion criteria included American Society of Anesthesiologists (ASA) class I-III, 18 to 80 years of age, and either gender. Exclusion criteria included the inability to consent. Withdrawal criteria included conversion to endotracheal tube and EEG malfunction. BIS and qCON/qNOX electrodes were simultaneously placed o62n all patientsprior to induction of anesthesia and were monitored throughout the case, along with other perioperative data, including patient response to noxious stimuli. All intraoperative decisions were made by the primary anesthesiologist without influence from qCON/qNOX. Student’s t-distribution, prediction probability (PK), and ANOVA were used to statistically compare the relative ability to detect nociceptive stimuli for each index. Twenty patients were included for the preliminary analysis. Results: A comparison of overall intraoperative BIS, qCON and qNOX indices demonstrated no significant difference between the three measures (N=62, p> 0.05). Meanwhile, index values for qNOX (62±18) were significantly higher than those for BIS (46±14) and qCON (54±19) immediately preceding patient responses to nociceptive stimulation in a preliminary analysis (N=20, * p= 0.0408). Notably, certain hemodynamic measurements demonstrated a significant increase in response to painful stimuli (MAP increased from74±13 mm Hg at baseline to 84± 18 mm Hg during noxious stimuli [p= 0.032] and HR from 76±12 BPM at baseline to 80±13BPM during noxious stimuli[p=0.078] respectively). Conclusion: In this observational study, BIS and qCON/qNOX provided comparable information on patients’ level of sedation throughout the course of an anesthetic. Meanwhile, increases in qNOX values demonstrated a superior correlation to an imminent response to stimulation relative to all other indices.

Keywords: antinociception, bispectral index (BIS), general anesthesia, laryngeal mask airway, qCON/qNOX

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Authors: Chang Liu, Hanwen Zhang, Vikash Sharma, Don Eliseo Lucerno-Prisno III, Emmanuel Yujuico, Maulik Chokshi, Prashanthi Krishnakumar, Bach Xuan Tran, Giang Thu Vu, Kamilla Anna Pinter, Shenglan Tang

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Background and Aims: Globally, many health systems focus on hospital-based healthcare models targeting acute care and disease treatment, which are not effective in addressing the challenges of ageing populations, chronic conditions, multi-morbidities, and increasingly unhealthy lifestyles. Recently, integrated care programs on chronic diseases have been developed, piloted, and implemented to meet such challenges. However, integrated care programs in the Asia-Pacific region vary in the levels of integration from linkage to coordination to full integration. This study aims to identify and analyze existing cases of integrated care in the Asia-Pacific region and identify the facilitators and barriers in order to improve existing cases and inform future cases. Methods: The study is a comparative study, with a combination approach of desk-based research and key informant interviews. The selected countries included in this study represent a good mix of lower-middle income countries (the Philippines, India, Vietnam, and Fiji), upper-middle income country (China), and high-income country (Singapore) in the Asia-Pacific region. Existing integrated care programs were identified through the scoping review approach. Trigger, history, general design, beneficiaries, and objectors were summarized with barriers and facilitators of integrated care based on key informant interviews. Representative case(s) in each country were selected and comprehensively analyzed through deep-dive case studies. Results: A total of 87 existing integrated care programs on chronic diseases were found in all countries, with 44 in China, 21 in Singapore, 12 in India, 5 in Vietnam, 4 in the Philippines, and 1 in Fiji. 9 representative cases of integrated care were selected for in-depth description and analysis, with 2 in China, the Philippines, and Vietnam, and 1 in Singapore, India, and Fiji. Population aging and the rising chronic disease burden have been identified as key drivers for almost all the six countries. Among the six countries, Singapore has the longest history of integrated care, followed by Fiji, the Philippines, and China, while India and Vietnam have a shorter history of integrated care. Incentives, technologies, education, and performance evaluation would be crucial for developing strategies for implementing future programs and improve already existing programs. Conclusion: Integrated care is important for addressing challenges surrounding the delivery of long-term care. To date, there is an increasing trend of integrated care programs on chronic diseases in the Asia-Pacific region, and all six countries in our study set integrated care as a direction for their health systems transformation.

Keywords: integrated healthcare, integrated care delivery, chronic diseases, Asia-Pacific region

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Authors: Yixin Zhu, Lishengsa Yue, Jian Sun, Lanyue Tang

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Modeling driving distraction in microscopic traffic simulation is crucial for enhancing simulation accuracy. Current driving distraction models are mainly derived from physical motion constraints under distracted states, in which distraction-related error terms are added to existing microscopic driver models. However, the model accuracy is not very satisfying, due to a lack of modeling the cognitive mechanism underlying the distraction. This study models driving distraction based on the Queueing Network Human Processor model (QN-MHP). This study utilizes the queuing structure of the model to perform task invocation and switching for distracted operation and control of the vehicle under driver distraction. Based on the assumption of the QN-MHP model about the cognitive sub-network, server F is a structural bottleneck. The latter information must wait for the previous information to leave server F before it can be processed in server F. Therefore, the waiting time for task switching needs to be calculated. Since the QN-MHP model has different information processing paths for auditory information and visual information, this study divides driving distraction into two types: auditory distraction and visual distraction. For visual distraction, both the visual distraction task and the driving task need to go through the visual perception sub-network, and the stimuli of the two are asynchronous, which is called stimulus on asynchrony (SOA), so when calculating the waiting time for switching tasks, it is necessary to consider it. In the case of auditory distraction, the auditory distraction task and the driving task do not need to compete for the server resources of the perceptual sub-network, and their stimuli can be synchronized without considering the time difference in receiving the stimuli. According to the Theory of Planned Behavior for drivers (TPB), this study uses risk entropy as the decision criterion for driver task switching. A logistic regression model is used with risk entropy as the independent variable to determine whether the driver performs a distraction task, to explain the relationship between perceived risk and distraction. Furthermore, to model a driver’s perception characteristics, a neurophysiological model of visual distraction tasks is incorporated into the QN-MHP, and executes the classical Intelligent Driver Model. The proposed driving distraction model integrates the psychological cognitive process of a driver with the physical motion characteristics, resulting in both high accuracy and interpretability. This paper uses 773 segments of distracted car-following in Shanghai Naturalistic Driving Study data (SH-NDS) to classify the patterns of distracted behavior on different road facilities and obtains three types of distraction patterns: numbness, delay, and aggressiveness. The model was calibrated and verified by simulation. The results indicate that the model can effectively simulate the distracted car-following behavior of different patterns on various roadway facilities, and its performance is better than the traditional IDM model with distraction-related error terms. The proposed model overcomes the limitations of physical-constraints-based models in replicating dangerous driving behaviors, and internal characteristics of an individual. Moreover, the model is demonstrated to effectively generate more dangerous distracted driving scenarios, which can be used to construct high-value automated driving test scenarios.

Keywords: computational cognitive model, driving distraction, microscopic traffic simulation, psychological-physical constraints

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Authors: Nazila Dehbari, Javad Tavakoli, Yakani Kambu, Youhong Tang

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Superabsorbent hydrogels (SAP), as an enviro-sensitive material have been widely used for industrial and biomedical applications due to their unique structure and capabilities. Poor mechanical properties of SAPs - which is extremely related to their large volume change – count as a great weakness in adopting for high-tech applications. Therefore, improving SAPs’ mechanical properties via toughening methods by mixing different types of cross-linked polymer or introducing energy-dissipating mechanisms is highly focused. In this work, in order to change the intrinsic brittle character of commercialized Poly Acrylic Acid (here as SAP) to be semi-ductile, a commercial available highly branched tree-like dendritic polymers with numerous –OH end groups known as hyper-branched polymer (HB) has been added to PAA-SAP system in a single step, cost effective and environment friendly solvent casting method. Samples were characterized by FTIR, SEM and TEM and their physico-chemical characterization including swelling capabilities, hydraulic permeability, surface tension and thermal properties had been performed. Toughness energy, stiffness, elongation at breaking point, viscoelastic properties and samples extensibility were mechanical properties that had been performed and characterized as a function of samples lateral cracks’ length in different HB concentration. Addition of HB to PAA-SAP significantly improved mechanical and surface properties. Increasing equilibrium swelling ratio by about 25% had been experienced by the SAP-HB samples in comparison with SAPs; however, samples swelling kinetics remained without changes as initial rate of water uptake and equilibrium time haven’t been subjected to any changes. Thermal stability analysis showed that HB is participating in hybrid network formation while improving mechanical properties. Samples characterization by TEM showed that, the aggregated HB polymer binders into nano-spheres with diameter in range of 10–200 nm. So well dispersion in the SAP matrix occurred as it was predictable due to the hydrophilic character of the numerous hydroxyl groups at the end of HB which enhance the compatibility of HB with PAA-SAP. As the profused -OH groups in HB could react with -COOH groups in the PAA-SAP during the curing process, the formation of a 2D structure in the SAP-HB could be attributed to the strong interfacial adhesion between HB and the PAA-SAP matrix which hinders the activity of PAA chains (SEM analysis). FTIR spectra introduced new peaks at 1041 and 1121 cm-1 that attributed to the C–O(–OH) stretching hydroxyl and O–C stretching ester groups of HB polymer binder indicating the incorporation of HB polymer into the SAP structure. SAP-HB polymer has significant effects on the final mechanical properties. The brittleness of PAA hydrogels are decreased by introducing HB as the fracture energies of hydrogels increased from 8.67 to 26.67. PAA-HBs’ stretch ability enhanced about 10 folds while reduced as a function of different notches depth.

Keywords: superabsorbent polymer, toughening, viscoelastic properties, hydrogel network

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Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

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Authors: Rishana Bilimoria, Selina Tang, Sajni Shah, Marianne Henien, Christopher Sproat

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Temporomandibular disorders (TMD) may affect up to a third of the general population, and there is evidence demonstrating the majority of Myofascial TMD cases improve after education and conservative measures. In 2015 our department implemented a modified care pathway for myofascial TMD patients in an attempt to improve the patient journey. This involved the use of an interactive group therapy approach to deliver education, reinforce conservative measures and promote self-management. Patient reported experience measures from the new group clinic revealed 71% patient satisfaction. This service is efficient in improving aspects of health status while reducing health-care costs and redistributing clinical time. Since its’ establishment, 52 hours of clinical time, resources and funding have been redirected effectively. This Quality Improvement Project was initiated because it was felt that this new service was being underutilised by our surgical teams. The ‘Plan-Do-Study-Act cycle’ (PDSA) framework was employed to analyse utilisation of the service: The ‘plan’ stage involved outlining our aims: to raise awareness amongst clinicians of the unified care pathway and to increase referral to this clinic. The ‘do’ stage involved collecting data from a sample of 96 patients over 4 month period to ascertain the proportion of Myofascial TMD patients who were correctly referred to the designated clinic. ‘Suitable’ patients who weren’t referred were identified. The ‘Study’ phase involved analysis of results, which revealed that 77% of suitable patients weren’t referred to the designated clinic. They were reviewed on other clinics, which are often overbooked, or managed by junior staff members. This correlated with our original prediction. Barriers to referral included: lack of awareness of the clinic, individual consultant treatment preferences and patient, reluctance to be referred to a ‘group’ clinic. The ‘Act’ stage involved presenting our findings to the team at a clinical governance meeting. This included demonstration of the clinical effectiveness of the care-pathway and explaining the referral route and criteria. In light of the evaluation results, it was decided to keep the group clinic and maximize utilisation. The second cycle of data collection following these changes revealed that of 66 Myofascial TMD patients over a 4 month period, only 9% of suitable patients were not seen via the designated pathway; therefore this QIP was successful in meeting the set objectives. Overall, employing the PDSA cycle in this QIP resulted in appropriate utilisation of the modified care pathway for patients with myofascial TMD in Guy’s Oral Surgery Department. In turn, this leads to high patient satisfaction with the service and effectively redirected 52 hours of clinical time. It permitted adoption of a collaborative working style with oral surgery colleagues to investigate problems, identify solutions, and collectively raise standards of clinical care to ensure we adopt a unified care pathway in secondary care management of Myofascial TMD patients.

Keywords: myofascial, quality Improvement, PDSA, TMD

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Authors: Diane Ghanem, Arjun Gupta, Rohan Vijayan, Ali Uneri, Babar Shafiq

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Introduction: Ankle sprains and fractures often result in syndesmosis injuries. Unstable syndesmotic injuries result from relative motion between the distal ends of the tibia and fibula, anatomic juncture which should otherwise be rigid, and warrant operative management. Clinical and radiological evaluations of intraoperative syndesmosis stability remain a challenging task as traditional 2D fluoroscopy is limited to a uniplanar translational displacement. The purpose of this pilot cadaveric study is to compare the 2D fluoroscopy and 3D cone beam computed tomography (CBCT) stress-induced syndesmosis displacements. Methods: Three fresh-frozen lower legs underwent 2D fluoroscopy and 3D CIOS CBCT to measure syndesmosis position before dissection. Syndesmotic injury was simulated by resecting the (1) anterior inferior tibiofibular ligament (AITFL), the (2) posterior inferior tibiofibular ligament (PITFL) and the inferior transverse ligament (ITL) simultaneously, followed by the (3) interosseous membrane (IOM). Manual external rotation and Cotton stress test were performed after each of the three resections and 2D and 3D images were acquired. Relevant 2D and 3D parameters included the tibiofibular overlap (TFO), tibiofibular clear space (TCS), relative rotation of the fibula, and anterior-posterior (AP) and medial-lateral (ML) translations of the fibula relative to the tibia. Parameters were measured by two independent observers. Inter-rater reliability was assessed by intraclass correlation coefficient (ICC) to determine measurement precision. Results: Significant mismatches were found in the trends between the 2D and 3D measurements when assessing for TFO, TCS and AP translation across the different resection states. Using 3D CBCT, TFO was inversely proportional to the number of resected ligaments while TCS was directly proportional to the latter across all cadavers and ‘resection + stress’ states. Using 2D fluoroscopy, this trend was not respected under the Cotton stress test. 3D AP translation did not show a reliable trend whereas 2D AP translation of the fibula was positive under the Cotton stress test and negative under the external rotation. 3D relative rotation of the fibula, assessed using the Tang et al. ratio method and Beisemann et al. angular method, suggested slight overall internal rotation with complete resection of the ligaments, with a change < 2mm - threshold which corresponds to the commonly used buffer to account for physiologic laxity as per clinical judgment of the surgeon. Excellent agreement (>0.90) was found between the two independent observers for each of the parameters in both 2D and 3D (overall ICC 0.9968, 95% CI 0.995 - 0.999). Conclusions: The 3D CIOS CBCT appears to reliably depict the trend in TFO and TCS. This might be due to the additional detection of relevant rotational malpositions of the fibula in comparison to the standard 2D fluoroscopy which is limited to a single plane translation. A better understanding of 3D imaging may help surgeons identify the precise measurements planes needed to achieve better syndesmosis repair.

Keywords: 2D fluoroscopy, 3D computed tomography, image processing, syndesmosis injury

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Authors: Jenson George, Thoa Nguyen, Garth Sanewski, Craig Hardner, Heather Eunice Smyth

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Pineapple (Ananas comosus), with its unique sweet flavour, is one of the most popular tropical, non-climacteric fruits consumed worldwide. It is also the third most important tropical fruit in world production. In Australia, 99% of the pineapple production is from the Queensland state due to the favourable subtropical climatic conditions. The flavourful fruit is known to contain around 500 volatile organic compounds (VOC) at varying concentrations and greatly contribute to the flavour quality of pineapple fruit by providing distinct aroma sensory properties that are sweet, fruity, tropical, pineapple-like, caramel-like, coconut-like, etc. The aroma of pineapple is one of the important factors attracting consumers and strengthening the marketplace. To better understand the aroma of Australian-grown pineapples, the matrix-matched Gas chromatography–mass spectrometry (GC-MS), Head Space - Solid-phase microextraction (HS-SPME), Stable-isotope dilution analysis (SIDA) method was developed and validated. The developed method represents a significant improvement over current methods with the incorporation of multiple external reference standards, multiple isotopes labeled internal standards, and a matching model system of pineapple fruit matrix. This method was employed to quantify 28 key aroma compounds in more than 200 genetically diverse pineapple varieties from a breeding program. The Australian pineapple cultivars varied in content and composition of free volatile compounds, which were predominantly comprised of esters, followed by terpenes, alcohols, aldehydes, and ketones. Using selected commercial cultivars grown in Australia, and by employing the sensorial analysis, the appearance (colour), aroma (intensity, sweet, vinegar/tang, tropical fruits, floral, coconut, green, metallic, vegetal, fresh, peppery, fermented, eggy/sulphurous) and texture (crunchiness, fibrousness, and juiciness) were obtained. Relationships between sensory descriptors and volatiles were explored by applying multivariate analysis (PCA) to the sensorial and chemical data. The key aroma compounds of pineapple exhibited a positive correlation with corresponding sensory properties. The sensory and volatile data were also used to explore genetic diversity in the breeding population. GWAS was employed to unravel the genetic control of the pineapple volatilome and its interplay with fruit sensory characteristics. This study enhances our understanding of pineapple aroma (flavour) compounds, their biosynthetic pathways and expands breeding option for pineapple cultivars. This research provides foundational knowledge to support breeding programs, post-harvest and target market studies, and efforts to optimise the flavour of commercial pineapple varieties and their parent lines to produce better tasting fruits for consumers.

Keywords: Ananas comosus, pineapple, flavour, volatile organic compounds, aroma, Gas chromatography–mass spectrometry (GC-MS), Head Space - Solid-phase microextraction (HS-SPME), Stable-isotope dilution analysis (SIDA).

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Authors: Ting Wu, Feiting Hu, Xinyue Zhang, Shuxin Tang, Xiaoyun Xu

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As a by-product of yuba, processing wastewater of Yuba (PWY) contains many bioactive components such as soybean isoflavones, soybean polysaccharides and soybean oligosaccharides, which is a good source of prebiotics and has a potential of high value utilization. The use of Lactobacillus plantarum to ferment PWY can be considered as a potential biogenic element, which can regulate the balance of intestinal microbiota. In this study, firstly, Lactobacillus plantarum was used to ferment PWY to improve its content of active components and antioxidant activity. Then, the health effect of fermented processing wastewater of yuba (FPWY) was measured in vitro. Finally, microencapsulation technology was used applied to improve the sustained release of FPWY and reduce the loss of active components in the digestion process, as well as to improving the activity of FPWY. The main results are as follows: (1) FPWY presented a good antioxidant capacity with DPPH free radical scavenging ability (0.83 ± 0.01 mmol Trolox/L), ABTS free radical scavenging ability (7.47 ± 0.35 mmol Trolox/L) and iron ion reducing ability (1.11 ± 0.07 mmol Trolox/L). Compared with non-fermented processing wastewater of yuba (NFPWY), there was no significant difference in the content of total soybean isoflavones, but the content of glucoside soybean isoflavones decreased, and aglyconic soybean isoflavones increased significantly. After fermentation, PWY can effectively reduce the soluble monosaccharides, disaccharides and oligosaccharides, such as glucose, fructose, galactose, trehalose, stachyose, maltose, raffinose and sucrose. (2) FPWY can significantly enhance the growth of beneficial bacteria such as Bifidobacterium, Ruminococcus and Akkermansia, significantly inhibit the growth of harmful bacteria E.coli, regulate the structure of intestinal microbiota, and significantly increase the content of short-chain fatty acids such as acetic acid, propionic acid, butyric acid, isovaleric acid. Higher amount of lactic acid in the gut can be further broken down into short chain fatty acids. (3) In order to improve the stability of soybean isoflavones in FPWY during digestion, sodium alginate and chitosan were used as wall materials for embedding. The FPWY freeze-dried powder was embedded by the method of acute-coagulation bath. The results show that when the core wall ratio is 3:1, the concentration of chitosan is 1.5%, the concentration of sodium alginate is 2.0%, and the concentration of calcium is 3%, the embossing rate is 53.20%. In the simulated in vitro digestion stage, the release rate of microcapsules reached 59.36% at the end of gastric digestion and 82.90% at the end of intestinal digestion. Therefore, the core materials with good sustained-release performance of microcapsules were almost all released. The structural analysis results of FPWY microcapsules show that the microcapsules have good mechanical properties. Its hardness, springness, cohesiveness, gumminess, chewiness and resilience were 117.75± 0.21 g, 0.76±0.02, 0.54±0.01, 63.28±0.71 g·sec, 48.03±1.37 g·sec, 0.31±0.01, respectively. Compared with the unembedded FPWY, the infrared spectrum results showed that the microcapsules had embedded effect on the FPWY freeze-dried powder.

Keywords: processing wastewater of yuba, lactobacillus plantarum, intestinal microbiota, microcapsule

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Authors: F. Tang, S. Boskovich, A. Raheja, Z. Aliyazicioglu, S. Bhandari, N. Tsuchiya

Abstract:

Calpoly Autonomous Transportation Experience (CATE) is a driverless vehicle that we are developing to provide safe, accessible, and efficient transportation of passengers throughout the Cal Poly Pomona campus for events such as orientation tours. Unlike the other self-driving vehicles that are usually developed to operate with other vehicles and reside only on the road networks, CATE will operate exclusively on walk-paths of the campus (potentially narrow passages) with pedestrians traveling from multiple locations. Safety becomes paramount as CATE operates within the same environment as pedestrians. As driverless vehicles assume greater roles in today’s transportation, this project will contribute to autonomous driving with pedestrian traffic in a highly dynamic environment. The CATE project requires significant interdisciplinary work. Researchers from mechanical engineering, electrical engineering and computer science are working together to attack the problem from different perspectives (hardware, software and system). In this abstract, we describe the software aspects of the project, with a focus on the requirements and the major components. CATE shall provide a GUI interface for the average user to interact with the car and access its available functionalities, such as selecting a destination from any origin on campus. We have developed an interface that provides an aerial view of the campus map, the current car location, routes, and the goal location. Users can interact with CATE through audio or manual inputs. CATE shall plan routes from the origin to the selected destination for the vehicle to travel. We will use an existing aerial map for the campus and convert it to a spatial graph configuration where the vertices represent the landmarks and edges represent paths that the car should follow with some designated behaviors (such as stay on the right side of the lane or follow an edge). Graph search algorithms such as A* will be implemented as the default path planning algorithm. D* Lite will be explored to efficiently recompute the path when there are any changes to the map. CATE shall avoid any static obstacles and walking pedestrians within some safe distance. Unlike traveling along traditional roadways, CATE’s route directly coexists with pedestrians. To ensure the safety of the pedestrians, we will use sensor fusion techniques that combine data from both lidar and stereo vision for obstacle avoidance while also allowing CATE to operate along its intended route. We will also build prediction models for pedestrian traffic patterns. CATE shall improve its location and work under a GPS-denied situation. CATE relies on its GPS to give its current location, which has a precision of a few meters. We have implemented an Unscented Kalman Filter (UKF) that allows the fusion of data from multiple sensors (such as GPS, IMU, odometry) in order to increase the confidence of localization. We also noticed that GPS signals can easily get degraded or blocked on campus due to high-rise buildings or trees. UKF can also help here to generate a better state estimate. In summary, CATE will provide on-campus transportation experience that coexists with dynamic pedestrian traffic. In future work, we will extend it to multi-vehicle scenarios.

Keywords: driverless vehicle, path planning, sensor fusion, state estimate

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Authors: Amber Dhoot, Tarush Gupta, Andrea Gurr, William Jenkins, Sandro Pietrunti, Alexis Tang

Abstract:

Background: The COVID-19 pandemic has driven pharmacovigilance towards a new paradigm. Nowadays, more people than ever before are recognising and reporting adverse reactions from medications, treatments, and vaccines. In the modern era, with over 3.8 billion users, social media has become the most accessible medium for people to voice their opinions and so provides an opportunity to engage with more patient-centric and accessible pharmacovigilance. However, the pharmaceutical industry has been slow to incorporate social media into its modern pharmacovigilance strategy. This project aims to make social media a more effective tool in pharmacovigilance, and so reduce drug costs, improve drug safety and improve patient outcomes. This will be achieved by firstly uncovering and categorising the barriers facing the widespread adoption of social media in pharmacovigilance. Following this, the potential opportunities of social media will be explored. We will then propose realistic, practical recommendations to make social media a more effective tool for pharmacovigilance. Methodology: A comprehensive systematic literature review was conducted to produce a categorised summary of these barriers. This was followed by conducting 11 semi-structured interviews with pharmacovigilance experts to confirm the literature review findings whilst also exploring the unpublished and real-life challenges faced by those in the pharmaceutical industry. Finally, a survey of the general public (n = 112) ascertained public knowledge, perception, and opinion regarding the use of their social media data for pharmacovigilance purposes. This project stands out by offering perspectives from the public and pharmaceutical industry that fill the research gaps identified in the literature review. Results: Our results gave rise to several key analysis points. Firstly, inadequacies of current Natural Language Processing algorithms hinder effective pharmacovigilance data extraction from social media, and where data extraction is possible, there are significant questions over its quality. Social media also contains a variety of biases towards common drugs, mild adverse drug reactions, and the younger generation. Additionally, outdated regulations for social media pharmacovigilance do not align with new, modern General Data Protection Regulations (GDPR), creating ethical ambiguity about data privacy and level of access. This leads to an underlying mindset of avoidance within the pharmaceutical industry, as firms are disincentivised by the legal, financial, and reputational risks associated with breaking ambiguous regulations. Conclusion: Our project uncovered several barriers that prevent effective pharmacovigilance on social media. As such, social media should be used to complement traditional sources of pharmacovigilance rather than as a sole source of pharmacovigilance data. However, this project adds further value by proposing five practical recommendations that improve the effectiveness of social media pharmacovigilance. These include: prioritising health-orientated social media; improving technical capabilities through investment and strategic partnerships; setting clear regulatory guidelines using multi-stakeholder processes; creating an adverse drug reaction reporting interface inbuilt into social media platforms; and, finally, developing educational campaigns to raise awareness of the use of social media in pharmacovigilance. Implementation of these recommendations would speed up the efficient, ethical, and systematic adoption of social media in pharmacovigilance.

Keywords: adverse drug reaction, drug safety, pharmacovigilance, social media

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Authors: Aisling Gough, Ruth F. Hunter, Jianjun Tang, Sarah F. Brennan, Oliver Smith, Mark A. Tully, Chris Patterson, Alberto Longo, George Hutchinson, Lindsay Prior, David French, Jean Adams, Emma McIntosh, Frank Kee

Abstract:

Background: As a large proportion of the UK workforce is employed in sedentary occupations, worksite interventions have the potential to contribute significantly to the health of the population. The UK Government is currently encouraging the use of financial incentives to promote healthier lifestyles but there is a dearth of evidence regarding the effectiveness and sustainability of incentive schemes to promote physical activity in the workplace. Methods: A large cluster RCT is currently underway, incorporating nested behavioural economic field experiments and process evaluation, to evaluate the effectiveness of a Physical Activity Loyalty Scheme. Office-based employees were recruited from large public sector organisations in Lisburn and Belfast (Northern Ireland) and randomised to an Intervention or Control group. Participants in the Intervention Group were encouraged to take part in 150 minutes of physical activity per week through provision of financial incentives (retailer vouchers) to those who met physical activity targets throughout the course of the 6 month intervention. Minutes of physical activity were monitored when participants passed by sensors (holding a keyfob) placed along main walking routes, parks and public transport stops nearby their workplace. Participants in the Control Group will complete the same outcome assessments (waiting-list control). The primary outcome is steps per day measured via pedometers (7 days). Secondary outcomes include health and wellbeing (Short Form-8, EuroQol-5D-5L, Warwick Edinburgh Mental Well Being Scale), and work absenteeism and presenteeism. Data will be collected at baseline, 6, 12 and 18 months. Information on PAL card & website usage, voucher downloads and redemption of vouchers will also be collected as part of a comprehensive process evaluation. Results: In total, 853 participants have been recruited from 9 workplaces in Lisburn, 12 buildings within the Stormont Estate, Queen’s University Belfast and Belfast City Hospital. Participants have been randomised to intervention and control groups. Baseline and 6-month data for the Physical Activity Loyalty Scheme has been collected. Findings regarding the effectiveness of the intervention from the 6-month follow-up data will be presented. Discussion: This study will address the gap in knowledge regarding the effectiveness and cost-effectiveness of a workplace-based financial incentive scheme to promote a healthier lifestyle. As the UK workforce is increasingly sedentary, workplace-based physical activity interventions have significant potential in terms of encouraging employees to partake in physical activity during the working day which could lead to substantial improvements in physical activity levels overall. Implications: If a workplace based physical activity intervention such as this proves to be both effective and cost-effective, there is great potential to contribute significantly to the health and wellbeing of the workforce in the future. Workplace-based physical activity interventions have the potential to improve the physical and mental health of employees which may in turn lead to economic benefits for the employer, such as reduction in rates of absenteeism and increased productivity.

Keywords: behaviour change, cluster randomised controlled trial, loyalty scheme, physical activity

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Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

Abstract:

The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

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