Regional differences and sources of organochlorine pesticides in soils surrounding chemical industrial parks

Concentrations of organochlorine pesticides (OCPs; dichlorodiphenyltrichloroethanes (DDTs), hexachlorocyclohexanes (HCHs), hexachlorobenzene (HCB)) were investigated in 105 soil samples collected in vicinity of the chemical industrial parks in Tianjin, China. OCP concentrations significantly varied in the study area, high HCH and DDT levels were found close to the chemical industrial parks. The intensity of agricultural activity and distance from the potential OCP emitters have important influences on the OCP residue distributions. Principal component analysis indicates that HCH pollution is a mix of historical technical HCH and current lindane pollution and DDT pollution input is only due to technical DDT sources. The significant correlations of OCP compounds reveal that HCHs, DDTs and HCB could have some similar sources of origin

Identification of sources of elevated concentrations of polycyclic aromatic hydrocarbons in an industrial area in Tianjin, China

The concentrations of 16 polycyclic aromatic hydrocarbons (PAHs) were determined by gas chromatography equipped with a mass spectrometry detector in 105 topsoil samples from an industrial area around Bohai Bay, Tianjin in the North of China. Results demonstrated that concentrations of PAHs in 104 soil samples from this area ranged from 68.7 to 5,590 ng g (-aEuro parts per thousand 1) dry weight with a mean of a16PAHs 814 +/- 813 ng g (-aEuro parts per thousand 1), which suggests that there exists mid to high levels of PAH contamination. The concentration of a16PAHs in one soil sample from Tianjin Port was exceptionally high (48,700 ng g (-aEuro parts per thousand 1)). Ninety-three of the 105 soil samples were considered to be contaminated with PAHs (> 200 ng g (-aEuro parts per thousand 1)), and 25 were heavily polluted (> 1,000 ng g (-aEuro parts per thousand 1)). The sites with high PAHs concentration are mainly distributed around chemical industry parks and near highways. Two low molecular weight PAHs, naphthalene and phenanthrene, were the dominant components in the soil samples, which accounted for 22.1% and 10.7% of the a16PAHs concentration, respectively. According to the observed molecular indices, house heating in winter, straw stalk combustion in open areas after harvest, and petroleum input were common sources of PAHs in this area, while factory discharge and vehicle exhaust were the major sources around chemical industrial parks and near highways. Biological processes were probably another main source of low molecular weight PAHs

Discussion on Event Horizon and Quantum Ergosphere of Evaporating Black Holes in a Tunnelling Framework

In this paper, with the Parikh-Wilczek tunnelling framework the positions of the event horizon of the Vaidya black hole and the Vaidya-Bonner black hole are calculated respectively. We find that the event horizon and the apparent horizon of these two black holes correspond respectively to the two turning points of the Hawking radiation tunnelling barrier. That is, the quantum ergosphere coincides with the tunnelling barrier. Our calculation also implies that the Hawking radiation comes from the apparent horizon.Comment: 8 page

Investigating the Relationship Between Gender, Interoception, and Body Beliefs

Interoception plays a multifaceted role in mental life. Understanding gender differences in interoception can contribute to explain gender disparities in physical and mental health. To fill the gaps in the literature on the relationship between gender and interoception, the present thesis systematically investigates gender differences across three facets of interoception: interoceptive sensitivity, interoceptive awareness, and metacognitive awareness. In particular, the influence of encultured body beliefs, a gender-relevant sociocultural factor, on any relationship is explored. During the study, participants first completed a heartbeat detection task as measures of interoceptive sensitivity and metacognitive awareness. Participants then completed a series of questionnaires to capture interoceptive awareness and body beliefs. By evaluating the full model using structural equation modeling, no significant relationships were found between gender or body beliefs and any facet of interoception. However, through a follow-up exploratory analysis, I found significant gender differences in several subscales of questionnaires that were used to operationalize interoceptive awareness or body beliefs. These findings collectively suggest that women and men differ in some aspects of their awareness and attitudes towards bodily signals. In response to the nonsignificant findings, I discussed several theoretical and methodological factors that limit previous literature and this present thesis at the end which should be taken into consideration in future studies.Bachelor of Scienc

Deep learning modeling m6A deposition reveals the importance of downstream cis-element sequences.

The N6-methyladenosine (m6A) modification is deposited to nascent transcripts on chromatin, but its site-specificity mechanism is mostly unknown. Here we model the m6A deposition to pre-mRNA by iM6A (intelligent m6A), a deep learning method, demonstrating that the site-specific m6A methylation is primarily determined by the flanking nucleotide sequences. iM6A accurately models the m6A deposition (AUROC = 0.99) and uncovers surprisingly that the cis-elements regulating the m6A deposition preferentially reside within the 50 nt downstream of the m6A sites. The m6A enhancers mostly include part of the RRACH motif and the m6A silencers generally contain CG/GT/CT motifs. Our finding is supported by both independent experimental validations and evolutionary conservation. Moreover, our work provides evidences that mutations resulting in synonymous codons can affect the m6A deposition and the TGA stop codon favors m6A deposition nearby. Our iM6A deep learning modeling enables fast paced biological discovery which would be cost-prohibitive and unpractical with traditional experimental approaches, and uncovers a key cis-regulatory mechanism for m6A site-specific deposition

Evaluating and analyzing student labor literacy in China's higher vocational education: an assessment model approach

IntroductionThis study addresses the gap in evaluating labor literacy amongst vocational students in China's higher vocational education system. It aims to develop a comprehensive framework for assessing essential labor competencies, thereby contributing to a nuanced understanding of vocational education's role in skill development.MethodsEmploying a multifaceted research methodology, this study integrates questionnaire surveys, econometric analyses, and the Delphi method to assess labor literacy among 749 students from three leading vocational institutions. A pioneering labor literacy assessment model is introduced: S = 0.5466B1+0.1816B2+0.1623B3+0.1095B4, where S denotes the overall labor literacy score. Here, B1 represents labor concepts, B2 denotes habits and qualities, B3 signifies knowledge and skills, and B4 encapsulates emotions and attitudes, illustrating a comprehensive approach to measuring labor literacy.ResultsOur findings reveal pronounced disparities in labor literacy across the identified dimensions, with particular deficiencies in labor concepts. The study also identifies six determinants—gender, political profile, academic performance, internship and training base utilization, inclination towards innovation and entrepreneurship, and labor education evaluation mechanisms—that significantly influence labor literacy outcomes.DiscussionHighlighting the imperative for a contextually informed and holistic approach to labor literacy, this study's insights advocate for educational strategies that are both aligned with labor market demands and cognizant of socio-cultural nuances. The developed assessment model not only propels the theoretical discourse in vocational education forward but also provides a pragmatic guide for educators and policy makers, aiming to mitigate disparities and enhance labor competencies through refined educational practices

3DMambaIPF: A State Space Model for Iterative Point Cloud Filtering via Differentiable Rendering

Noise is an inevitable aspect of point cloud acquisition, necessitating filtering as a fundamental task within the realm of 3D vision. Existing learning-based filtering methods have shown promising capabilities on small-scale synthetic or real-world datasets. Nonetheless, the effectiveness of these methods is constrained when dealing with a substantial quantity of point clouds. This limitation primarily stems from their limited denoising capabilities for large-scale point clouds and their inclination to generate noisy outliers after denoising. The recent introduction of State Space Models (SSMs) for long sequence modeling in Natural Language Processing (NLP) presents a promising solution for handling large-scale data. Encouraged by iterative point cloud filtering methods, we introduce 3DMambaIPF, firstly incorporating Mamba (Selective SSM) architecture to sequentially handle extensive point clouds from large scenes, capitalizing on its strengths in selective input processing and long sequence modeling capabilities. Additionally, we integrate a robust and fast differentiable rendering loss to constrain the noisy points around the surface. In contrast to previous methodologies, this differentiable rendering loss enhances the visual realism of denoised geometric structures and aligns point cloud boundaries more closely with those observed in real-world objects. Extensive evaluation on datasets comprising small-scale synthetic and real-world models (typically with up to 50K points) demonstrate that our method achieves state-of-the-art results. Moreover, we showcase the superior scalability and efficiency of our method on large-scale models with about 500K points, where the majority of the existing learning-based denoising methods are unable to handle