What does it cost to travel in Sydney? Spatial and equity contrasts across the metropolitan region

There is a strong belief, often perceptual, that residents in the outer suburbs of Sydney are at a transport disadvantage in terms of the generalised cost of daily travel in absolute terms, and in relation to the percentage of income, personal and household, spent each day on travel. This paper investigates this claim using the Sydney Household Travel Survey, an annual survey of randomly selected individuals, from June 1997 to June 2008, a total of 92,413 respondents. We pool the entire data set, adjusting costs for different years, and undertake a spatial interrogation of the data, initially for 13 sub-regions, and then drill down to postcodes to identify sources of systematic variation in the daily generalised cost of travel for individuals and households. In assessing the evidence, we compare public transport outlays with car outlays, where the latter is defined in terms of marginal outlays (i.e., fuel and parking) and all costs (i.e., marginal outlay plus car ownership costs). Given the cost of using public transport (i.e., fares) we speculate that the provision of improved public transport services (and switching from car to some extent) is likely to result in a lower monetary cost of travel, but only if individuals and/or households dispose of vehicles. This seems to apply even where public transport offers a lower travel time, which is not sufficient to compensate for retention of the car. If they retain their cars, then given the lower marginal cost of car use compared to public transport, the contribution of improve public transport translated into a switch of usage from car to public transport will have little impact on accessibility and equity. Hence the entire argument hinges on what response will be made to car ownership in the presence of a non-marginal injection of investment in public transport. The paper also cautions about making statements on mobility equity at a highly spatially aggregate level (i.e., a sub-region), in contrast to establishing the causal links at a more spatially disaggregate level (i.e., the postcode)

Vesper: A Compact and Effective Pretrained Model for Speech Emotion Recognition

This paper presents a paradigm that adapts general large-scale pretrained models (PTMs) to speech emotion recognition task. Although PTMs shed new light on artificial general intelligence, they are constructed with general tasks in mind, and thus, their efficacy for specific tasks can be further improved. Additionally, employing PTMs in practical applications can be challenging due to their considerable size. Above limitations spawn another research direction, namely, optimizing large-scale PTMs for specific tasks to generate task-specific PTMs that are both compact and effective. In this paper, we focus on the speech emotion recognition task and propose an improved emotion-specific pretrained encoder called Vesper. Vesper is pretrained on a speech dataset based on WavLM and takes into account emotional characteristics. To enhance sensitivity to emotional information, Vesper employs an emotion-guided masking strategy to identify the regions that need masking. Subsequently, Vesper employs hierarchical and cross-layer self-supervision to improve its ability to capture acoustic and semantic representations, both of which are crucial for emotion recognition. Experimental results on the IEMOCAP, MELD, and CREMA-D datasets demonstrate that Vesper with 4 layers outperforms WavLM Base with 12 layers, and the performance of Vesper with 12 layers surpasses that of WavLM Large with 24 layers.Comment: 13 pages, 5 figures, 8 table

A Simple Classroom Experiment on Money Demand

This simple classroom experiment is designed to help students to better understand the concept and the theory of money demand. By simulating what households face in real life, the experiment allows students to reflect on the cost and benefit of holding money and understand how money demand is affected by various factors. The experiment is suitable for an undergraduate macroeconomics course at the introductory or intermediate level. The paper also presents evidence of student learning resulting from the experiment, controlling for student characteristics

Prediction of papillary thyroid metastases to the central compartment: proposal of a model taking into consideration other thyroid conditions

ObjectiveTo construct risk prediction models for cervical lymph node metastasis (CLNM) of papillary thyroid carcinoma (PTC) under different thyroid disease backgrounds and to analyze and compare risk factors among different groups.MethodsThis retrospective study included 518 patients with PTC that was pathologically confirmed post-operatively from January 2021 to November 2021. Demographic, ultrasound and pathological data were recorded. Univariate and multivariate logistic regression analyses were performed to identify factors associated with CLNM in the whole patient cohort and in patients grouped according to diagnoses of Hashimoto’s thyroiditis (HT), nodular goiter (NG), and no background disease. Prediction models were constructed for each group, and their performances were compared.ResultsAnalysis of the whole PTC patient cohort identified NG as independently associated with CLNM. The independent risk factors for patients with no background disease were the maximum thyroid nodule diameter and American College of Radiology Thyroid Imaging Reporting & Data System score; those for patients with HT were the maximum thyroid nodule diameter, ACR TI-RADS score, and multifocality; and those for patients with NG were the maximum thyroid nodule diameter, ACR TI-RADS score, multifocality and gender.ConclusionBackground thyroid disease impacts CLNM in PTC patients, and risk factors for CLNM vary among PTC patients with different background diseases. Ultrasound is useful for diagnosing background thyroid disease, which can inform treatment planning. Different prediction models are recommended for PTC cases with different thyroid diseases

Polyethylene glycol combined with lactulose has better efficacy than polyethylene glycol alone in bowel preparation before colonoscopy: A meta-analysis

Background: The accuracy of diagnosis and the safety of treatment in colonoscopy depends largely on the quality of bowel cleansing. This study aimed to compare the efficacy and adverse reactions of Polyethylene Glycol (PEG) combined with lactulose with that of PEG alone in bowel preparation before colonoscopy. Methods: The authors searched a number of databases including EMBASE, MEDLINE, Cochrane Library, and China Academic Journals Full-text Database. The authors screened according to literature inclusion and exclusion criteria, assessed the quality of the included literature, and extracted the data. The meta-analysis of included literature used RevMan 5.3 and Stata 14.0 software. Results: A total of 18 studies, including 2274 patients, were enrolled. The meta-analysis showed that PEG combined with lactulose had a better efficacy (OR = 3.87, 95% CI 3.07‒4.87, p = 0.000, and I2 = 36.2% in the efficiency group; WMD = 0.86, 95% CI 0.69‒1.03, p = 0.032 and I2 = 0% in the BBPS score group) in bowel preparation for patients with or without constipation. Moreover, PEG combined with lactulose had fewer adverse reactions, including abdominal pain (OR = 1.42, 95% CI 0.94‒2.14, p = 0.094), nausea (OR = 1.60, 95% CI 1.13‒2.28, p = 0.009) and vomiting (OR = 1.77, 95% CI 1.14‒2.74, p = 0.011), than PEG alone. No significant reduction in the incidence of abdominal distention was observed. Conclusion: PEG combined with lactulose may be a better choice for bowel preparation before colonoscopy compared with PEG alone

Baculovirus superinfection: a probable restriction factor on the surface display of proteins for library screening

In addition to the expression of recombinant proteins, baculoviruses have been developed as a platform for the display of complex eukaryotic proteins on the surface of virus particles or infected insect cells. Surface display has been used extensively for antigen presentation and targeted gene delivery but is also a candidate for the display of protein libraries for molecular screening. However, although baculovirus gene libraries can be efficiently expressed and displayed on the surface of insect cells, target gene selection is inefficient probably due to super-infection which gives rise to cells expressing more than one protein. In this report baculovirus superinfection of Sf9 cells has been investigated by the use of two recombinant multiple nucleopolyhedrovirus carrying green or red fluorescent proteins under the control of both early and late promoters (vAcBacGFP and vAcBacDsRed). The reporter gene expression was detected 8 hours after the infection of vAcBacGFP and cells in early and late phases of infection could be distinguished by the fluorescence intensity of the expressed protein. Simultaneous infection with vAcBacGFP and vAcBacDsRed viruses each at 0.5 MOI resulted in 80% of infected cells coexpressing the two fluorescent proteins at 48 hours post infection (hpi), and subsequent infection with the two viruses resulted in similar co-infection rate. Most Sf9 cells were re-infectable within the first several hours post infection, but the reinfection rate then decreased to a very low level by 16 hpi. Our data demonstrate that Sf9 cells were easily super-infectable during baculovirus infection, and super-infection could occur simultaneously at the time of the primary infection or subsequently during secondary infection by progeny viruses. The efficiency of super-infection may explain the difficulties of baculovirus display library screening but would benefit the production of complex proteins requiring co-expression of multiple polypeptides

Current status and prospect of PET-related imaging radiomics in lung cancer

Lung cancer is highly aggressive, which has a high mortality rate. Major types encompass lung adenocarcinoma, lung squamous cell carcinoma, lung adenosquamous carcinoma, small cell carcinoma, and large cell carcinoma. Lung adenocarcinoma and lung squamous cell carcinoma together account for more than 80% of cases. Diverse subtypes demand distinct treatment approaches. The application of precision medicine necessitates prompt and accurate evaluation of treatment effectiveness, contributing to the improvement of treatment strategies and outcomes. Medical imaging is crucial in the diagnosis and management of lung cancer, with techniques such as fluoroscopy, computed radiography (CR), digital radiography (DR), computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET)/CT, and PET/MRI being essential tools. The surge of radiomics in recent times offers fresh promise for cancer diagnosis and treatment. In particular, PET/CT and PET/MRI radiomics, extensively studied in lung cancer research, have made advancements in diagnosing the disease, evaluating metastasis, predicting molecular subtypes, and forecasting patient prognosis. While conventional imaging methods continue to play a primary role in diagnosis and assessment, PET/CT and PET/MRI radiomics simultaneously provide detailed morphological and functional information. This has significant clinical potential value, offering advantages for lung cancer diagnosis and treatment. Hence, this manuscript provides a review of the latest developments in PET-related radiomics for lung cancer