Automatic assessment of motivational interview with diabetes patients

Diabetes cost the UK NHS £10 billion each year, and the cost pressure is projected to get worse. Motivational Interviewing (MI) is a goal-driven clinical conversation that seeks to reduce this cost by encouraging patients to take ownership of day-to-day monitoring and medication, whose effectiveness is commonly evaluated against the Motivational Interviewing Treatment Integrity (MITI) manual. Unfortunately, measuring clinicians’ MI performance is costly, requiring expert human instructors to ensure the adherence of MITI. Although it is desirable to assess MI in an automated fashion, many challenges still remain due to its complexity. In this thesis, an automatic system to assess clinicians adherence to the MITI criteria using different spoken language techniques was developed. The system tackled the chal- lenges using automatic speech recognition (ASR), speaker diarisation, topic modelling and clinicians’ behaviour code identification. For ASR, only 8 hours of in-domain MI data are available for training. The experiments with different open-source datasets, for example, WSJCAM0 and AMI, are presented. I have explored adaptative training of the ASR system and also the best training criterion and neural network structure. Over 45 minutes of MI testing data, the best ASR system achieves 43.59% word error rate. The i-vector based diarisation system achieves an F-measure of 0.822. The MITI behaviour code classification system with manual transcriptions achieves an accuracy of 78% for Non Question/Question classification, an accuracy of 80% for Open Question/Closed Question classification and an accuracy of 78% for MI Adherence and MI Non-Adherence classification. Topic modelling was applied to track whether the conversation segments were related to ‘diabetes’ or not on manual transcriptions as well as ASR outputs. The full automatic assessment system achieve an Assessment Error Rate of 22.54%. This is the first system that targets the full automation of MI assessment with reasonable performance. In addition, the error analysis from each step is able to guide future research in this area for further improvement and optimisation

The Cooling and Humidifying Effects and the Thresholds of Plant Community Structure Parameters in Urban Aggregated Green Infrastructure

The cooling and humidifying effects of urban aggregated green infrastructure can provide essential services for city ecosystems, regulating microclimates or mitigating the urban heat island effect. However, the optimal thresholds of plant community structure parameters for maximizing the associated cooling and humidifying effects remain unclear. In this paper, we use the method of dummy variable regression to measure plant communities in an urban aggregated green infrastructure. By examining the relationships between the cooling and humidifying effects and plant community structure parameters (i.e., canopy density, porosity, and vegetation type), we introduce optimal thresholds for the parameters. We find that canopy density has a significantly positive correlation with both cooling and humidifying effects, while porosity has a positive correlation with cooling and a negative one with humidifying. Different vegetation types have distinct influences on cooling and humidifying effects. When the canopy density is between 0.81 and 0.85 and the porosity is between 0.31 and 0.35, the cooling and humidifying effects of the plant communities reach their peak. Additionally, the greening coverage rate and spatial types of urban aggregated green infrastructure have influences on cooling and humidifying effects. The findings can help us to better understand the relationships between plant community structure parameters and their temperature regulation functioning for urban aggregated green infrastructure. This study provides guidelines and theoretical references for the plant configuration of future urban green spaces

Direct Access to Highly Functionalized Heterocycles through the Condensation of Cyclic Imines and α‑Oxoesters

A facile, gram-scale preparation of 2-hydroxy-5,6,7,7a-tetrahydro-3<i>H</i>-pyrrolizin-3-ones and 2-hydroxy-6,7,8,8a-tetrahydroindolizin-3­(5<i>H</i>)-ones from a condensation cyclization of α-oxoesters with five- and six-membered cyclic imines, respectively, is reported. This transformation enables a concise, three-step synthesis of the natural products phenopyrrozin and <i>p</i>-hydroxyphenopyrrozin. Further, biologically relevant scaffolds, such as α-quaternary β-homo prolines and β-lactams, are also prepared in two- to three-steps from the versatile 2-hydroxy-5,6,7,7a-tetrahydro-3<i>H</i>-pyrrolizin-3-one core

Membrane Integrated liposome Synthesized by a Liposome Fusion-Induced Membrane Exchange

Biogenic extracellular vesicles (EVs) from mammalian cells and bacteria are assembled by lipid bilayer membrane with carried biologically active cargos such as proteins and mRNA, which received enormous attention due to their various potential applications, including immune therapy, drug delivery system, catalysis, liquid biopsy, microbial fuel cells, and so on. However, scanty EVs produced by biogenesis limited their applicability in the actual condition, and therefore new technologies to enlarge the production of EVs must be developed and remain the challenge. In this study, we created a novel method named LIME (liposome fusion-induced membrane exchange) to acquire a large quantity of biologically active vesicles, in which the excess lipid components fused into the cell’s membrane, thus promoting the process of EVs liberation. This method was first verified in gram-negative bacteria, Shewanella oneidensis MR-1 with c-type cytochrome complex (Cyts) on the outer-membrane and 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine contained liposomes as the lipid donor were used. Interestingly, the significant difference in spectroscopy and heme staining between original liposomes and active membrane-integrated liposomes (MILs) revealed that the electrochemically active Cyts migrate from MR-1 outer-membrane to the liposome successfully. Moreover, MILs with Cyts enabled enhancing the current production from Escherichia coli K-12, demonstrating that the electron transfer activity of Cyts was preserved after the LIME process, and MILs showed massive potential as drug carriers, vaccine, and a tool for strains-crossed membrane proteins migration. Our approach indicates an all-new direction to produce artificial EVs with specific proteins and functions, which will significantly benefit the future development of EVs

Enhancing <i>Monascus</i> Pellet Formation for Improved Secondary Metabolite Production

Filamentous fungi are well-known for their ability to form mycelial pellets during submerged cultures, a characteristic that has been extensively studied and applied. However, Monascus, a filamentous saprophytic fungus with a rich history of medicinal and culinary applications, has not been widely documented for pellet formation. This study aimed to investigate the factors influencing pellet formation in Monascus and their impact on citrinin production, a key secondary metabolite. Through systematic exploration, we identified pH and inoculum size as critical factors governing pellet formation. Monascus exhibited optimal pellet growth within the acidic pH range from 5 to 6, resulting in smaller, more homogeneous pellets with lower citrinin content. Additionally, we found that inoculum size played a vital role, with lower spore concentrations favoring the formation of small, uniformly distributed pellets. The choice of carbon and nitrogen sources also influenced pellet stability, with glucose, peptone, and fishmeal supporting stable pellet formation. Notably, citrinin content was closely linked to pellet diameter, with larger pellets exhibiting higher citrinin levels. Our findings shed light on optimizing Monascus pellet formation for enhanced citrinin production and provide valuable insights into the cultivation of this fungus for various industrial applications. Further research is warranted to elucidate the molecular mechanisms underlying these observations

Overview of the 2017 Spoken CALL Shared Task

We present an overview of the shared task for spoken CALL. Groups competed on a prompt-response task using English-language data collected, through an online CALL game, from Swiss German teens in their second and third years of learning English. Each item consists of a written German prompt and an audio file containing a spoken response. The task is to accept linguistically correct responses and reject linguistically incorrect ones, with “linguistically correct” being defined by a gold standard derived from human annotations; scoring was performed using a metric defined as the ratio of the relative rejection rates on incorrect and correct responses. The task received twenty entries from nine different groups. We present the task itself, the results, a tentative analysis of what makes items challenging, a comparison between different metrics, and suggestions for a continuation

Overview of the 2018 Spoken CALL Shared Task

We present an overview of the second edition of the Spoken CALL Shared Task. Groups competed on a prompt-response task using English-language data collected, through an online CALL game, from Swiss German teens in their second and third years of learning English. Each item consists of a written German prompt and an audio file containing a spoken response. The task is to accept linguistically correct responses and reject linguistically incorrect ones, with "linguistically correct" defined by a gold standard derived from human annotations. Scoring was performed using a metric defined as the ratio of the relative rejection rates on incorrect and correct responses. The second edition received eighteen entries and showed very substantial improvement on the first edition; all entries were better than the best entry from the first edition, and the best score was about four times higher. We present the task, the resources, the results, a discussion of the metrics used, and an analysis of what makes items challenging. In particular, we present quantitative evidence suggesting that incorrect responses are much more difficult to process than correct responses, and that the most significant factor in making a response challenging is its distance from the closest training example