Heterotopic space characteristics of urban village in China: Take Guandongdian district in Beijing as an example

[EN] For the first time in the history of China, more of its mainland population are living in cities than in rural villages. The land acquisition and real estate development have caused rapid disappearance and decline of a large number of traditional villages, resulting in "urban villages" in China. They seem chaotic, but contain rich and colorful social life. The living environment is really harsh, but people always maintain close relationship with each other. They are different from neither the modern urban nor traditional villages, but they have their own unique vitality. Such heterogeneous space is always a symbol of historical change and cultural collision which, according to the French philosopher Michel Foucault, can be called Heterotopias. In order to study this heterotopic phenomenon, the triangular area of Guandongdian district in Beijing has been chosen as the object of this case study. With the in-depth investigation of interviews, observation, statistics and sketches, this paper is trying to interpret the characteristics of the heterotopic state of the urban village from three aspects of social form, urban morphology and architectural feature. Eventually, in order to keep the complexity and diversification of urban village, several strategies are put forward for reference to future transforming practice.Lu, T.; Li, J.; Peng, N. (2018). Heterotopic space characteristics of urban village in China: Take Guandongdian district in Beijing as an example. En 24th ISUF International Conference. Book of Papers. Editorial Universitat Politècnica de València. 385-394. https://doi.org/10.4995/ISUF2017.2017.6034OCS38539

Discrimination and classification of tobacco wastes by identification and quantification of polyphenols with LC–MS/MS

The chemical composition of polyphenols in tobacco waste was identified by HPLC-PDA–ESI/MS/MS and the contents of chlorogenic acids and rutin in 10 varieties of tobacco wastes were determined by HPLC–UV. The relationships between the contents of active polyphenols and the varieties of tobacco wastes were interpreted by hierarchical cluster analysis (HCA) and principal component analysis (PCA). The results showed that 15 polyphenols were identified in a methanolic extract of dried tobacco waste. The tobacco wastes were characterized by high levels of chlorogenic acids (3-CQA, 5-CQA, and 4-CQA) and rutin; their ranges in the 10 tobacco varieties were 0.116–0.196, 0.686–1.781, 0.094–0.192, and 0.413–0.998 %, respectively. According to multivariate statistics models, two active compound variables can be considered important for the discrimination of the varieties of tobacco wastes: chlorogenic acids and rutin. Consequently, samples of 10 tobacco varieties were characterized into three groups by HCA based on the PCA pattern. In conclusion, tobacco waste could be used as a new pharmaceutical material for the production of natural chlorogenic acids and rutin in the ethnopharmacological industry

Explainable, Domain-Adaptive, and Federated Artificial Intelligence in Medicine

Artificial intelligence (AI) continues to transform data analysis in many domains. Progress in each domain is driven by a growing body of annotated data, increased computational resources, and technological innovations. In medicine, the sensitivity of the data, the complexity of the tasks, the potentially high stakes, and a requirement of accountability give rise to a particular set of challenges. In this review, we focus on three key methodological approaches that address some of the particular challenges in AI-driven medical decision making. (1) Explainable AI aims to produce a human-interpretable justification for each output. Such models increase confidence if the results appear plausible and match the clinicians expectations. However, the absence of a plausible explanation does not imply an inaccurate model. Especially in highly non-linear, complex models that are tuned to maximize accuracy, such interpretable representations only reflect a small portion of the justification. (2) Domain adaptation and transfer learning enable AI models to be trained and applied across multiple domains. For example, a classification task based on images acquired on different acquisition hardware. (3) Federated learning enables learning large-scale models without exposing sensitive personal health information. Unlike centralized AI learning, where the centralized learning machine has access to the entire training data, the federated learning process iteratively updates models across multiple sites by exchanging only parameter updates, not personal health data. This narrative review covers the basic concepts, highlights relevant corner-stone and state-of-the-art research in the field, and discusses perspectives.Comment: This paper is accepted in IEEE CAA Journal of Automatica Sinica, Nov. 10 202

Time dependence of the orthotropic compression Young's moduli and Poisson's ratios of Chinese fir wood

The time dependency of the orthotropic compliance for Chinese fir wood [Cunninghamia lanceolata (Lamb.) Hook] has been investigated by performing compressive creep experiments in all orthotropic directions. Time evolution of the creep strain in the axial and lateral directions was recorded by means of the digital image correlation (DIC) technique, to determine the diagonal and nondiagonal elements of the viscoelastic compliance matrix. The results reveal the significant influence of time on the mechanical behavior. The orthotropic nature of the viscoelastic compliance is highlighted by the different time dependency of the Young's moduli and the Poisson's ratios obtained for the individual directions. Differences among the time-dependent stress-strain relationship determined at the 25, 50, and 75% stress levels indicate that the viscoelastic behavior of wood is also load-dependent. A Poisson's ratio values, which are increasing with time in νLR, νLT, νRT, νTR, and decreasing in νRL and νTL, demonstrate that the creep strain is influenced by loading directions. The substantially different time dependency of the nondiagonal elements of the compliance matrix further reveals the orthotropic compliance asymmetry and emphasizes the complexity of the viscoelastic character of wood

LLM-Mini-CEX: Automatic Evaluation of Large Language Model for Diagnostic Conversation

There is an increasing interest in developing LLMs for medical diagnosis to improve diagnosis efficiency. Despite their alluring technological potential, there is no unified and comprehensive evaluation criterion, leading to the inability to evaluate the quality and potential risks of medical LLMs, further hindering the application of LLMs in medical treatment scenarios. Besides, current evaluations heavily rely on labor-intensive interactions with LLMs to obtain diagnostic dialogues and human evaluation on the quality of diagnosis dialogue. To tackle the lack of unified and comprehensive evaluation criterion, we first initially establish an evaluation criterion, termed LLM-specific Mini-CEX to assess the diagnostic capabilities of LLMs effectively, based on original Mini-CEX. To address the labor-intensive interaction problem, we develop a patient simulator to engage in automatic conversations with LLMs, and utilize ChatGPT for evaluating diagnosis dialogues automatically. Experimental results show that the LLM-specific Mini-CEX is adequate and necessary to evaluate medical diagnosis dialogue. Besides, ChatGPT can replace manual evaluation on the metrics of humanistic qualities and provides reproducible and automated comparisons between different LLMs

Rapid Determination of Nine Acrylates in Food Contact Materials by Ultra Performance Convergence Chromatography

Ultra performance convergence chromatography (UPC2) was used to establish a rapid analytical method to determine nine acrylate compounds in plastic food contact materials simultaneously. The samples were extracted with methanol, filtered through an organic membrane, and separated on an ACQUITY UPC2 HSS C18 SB column with gradient elution using a mobile phase consisting of supercritical carbon dioxide and acetonitrile. The photodiode array (PDA) detector was set at 210 nm. Experimental results showed that under the optimal conditions (column temperature, 40 ℃; and back pressure, 13.79 MPa), qualitative and quantitative analysis of the nine acrylates was completed within 4 min. Linear ranges were 0.2–100 mg/L for phenyl methacrylate (PNMA), benzyl methacrylate (BZMA) and ethylene dimethacrylate (EDMA); 0.3–100 mg/L for methacrylic acid (MAA); 0.4–100 mg/L for butyl acrylate (BTA), hydroxyethyl methylacrylate (HEMA) and hydroxyethyl acrylate (HEA); and 0.5–100 mg/L for isobutylmeth acrylate (IBMA) and benzyl acrylate (BZA). The determination coefficients (R2) of the standard curves for all acrylates were higher than 0.998 5, and recoveries obtained at high (30 mg/kg), middle (6 mg/kg) and low (0.2, 0.3, 0.4 and 0.5 mg/kg) spiked concentrations ranged from 89.3% to 109.7%, with relative standard deviations of 0.62% to 3.86% (n = 6). The limits of detection (RSN ≥ 3) were 0.05–0.15 mg/kg, and the limits of quantification (RSN ≥ 10) were 0.2–0.5 mg/kg. The proposed method identified the risk of acrylate residues in 30 batches of actual samples

Integration of Metabolomics and Transcriptomics Reveals the Therapeutic Mechanism Underlying Paeoniflorin for the Treatment of Allergic Asthma

Objectives: Asthma is a chronic airway inflammatory disease, which is characterized by airway remodeling, hyperreactivity and shortness of breath. Paeoniflorin is one of the major active ingredients in Chinese peony, which exerts anti-inflammatory and immune-regulatory effects in multiple diseases. However, it remains unclear whether paeoniflorin treatment can suppress allergic asthma.Methods: In this study, we evaluated the effect of paeoniflorin on lung function and airway inflammation in asthmatic mice. These asthmatic Balb/c mice were first sensitized and constructed through ovalbumin (OVA) motivation. Subsequently, we determined the mechanism of action of paeoniflorin in treating allergic asthma through integrated transcriptomic and metabolomic data sets.Results: Our results demonstrated that many genes and metabolites were regulated in the paeoniflorin-treated mice. Moreover, the potential target proteins of paeoniflorin played important roles in fatty acid metabolism, inflammatory response, oxidative stress and local adhesion.Conclusion: Paeoniflorin has a beneficial effect on asthma, which may be achieved through regulating fatty acid metabolism, inflammatory response and the adhesion pathway at system level

Maternal consumption of fish oil programs reduced adiposity in broiler chicks

Maternal intake of eicosapentaenoic acid (EPA; 20:5 n-3) and docosahexaenoic acid (22:6 n-3) has been associated with reduced adiposity in children, suggesting the possibility to program adipose development through dietary fatty acids before birth. This study determined if enriching the maternal diet in fish oil, the primary source of EPA and DHA, affected adipose development in offspring. Broiler chickens were used because they are obesity-prone, and because fatty acids provided to the embryo can be manipulated through the hen diet. Hens were fed diets supplemented (2.8% wt:wt) with corn oil (CO; n-6) or fish oil (FO; n-3) for 28 d. Chicks from both maternal diet groups were fed the same diet after hatch. Maternal FO consumption enriched chick adipose tissue in EPA and DHA and reduced adiposity by promoting more, but smaller, adipocytes. This adipocyte profile was paralleled by upregulated expression of the adipogenic regulator PPARGand its co-activator PPARGC1B, and reduced expression of LPL. Proteomics identified 95 differentially abundant proteins between FO and CO adipose tissue, including components of glucose metabolism, lipid droplet trafficking, and cytoskeletal organization. These results demonstrate that the maternal dietary fatty acid profile programs offspring adipose development

MicroRNA-646 inhibits the proliferation of ovarian granulosa cells via insulin-like growth factor 1 (IGF-1) in polycystic ovarian syndrome (PCOS)

Introduction: Polycystic ovarian syndrome (PCOS) is a common endocrinopathy in women. MicroRNAs (miRNAs) have been proven to play a crucial role in balancing the proliferation and apoptosis of granulosa cells (GCs) in PCOS. Material and methods: The miRNA of PCOS was screened by bioinformatics analysis, and microRNA 646 (miR-646) was found to be involved in insulin-related pathways by enrichment analysis. The cell counting kit-8 (CCK-8), cell colony formation, and the 5-ethynyl-2’-deoxyuridine (EdU) assays were used to explore the effect of miR-646 on proliferation of GCs, flow cytometry was used to measure the cell cycle and apoptosis, and Western blot and quantitative real-time polymerase chain reaction (qRT-PCR) were used to explore the biological mechanism of miR-646. The human ovarian granulosa cells KGN were selected by measuring the miR-646 and via insulin-like growth factor 1 (IGF-1) levels and used for cell transfection. Results: Overexpressed miR-646 inhibited KGN cell proliferation, and silenced miR-646 advanced it. Most cells were arrested in the S phase of cell cycle with overexpressed-miR-646, while after silencing miR-646, cells were arrested in the G2/M phase. And the miR-646 mimic raised apoptosis in KGN cells. Also, a dual-luciferase reporter proved the regulation effect of miR-646 on IGF-1, miR-646 mimic inhibited IGF-1, and miR-646 inhibitor advanced IGF-1. The cyclin D1, cyclin-dependent kinase 2 (CDK2), and B-cell CLL/lymphoma 2 (Bcl-2) levels were inhibited with overexpressed-miR-646, while silenced-miR-646 promoted their expression, and the bcl-2-like protein 4 (Bax) level was the opposite. This study found that silenced-IGF1 antagonized the promotive effect of the miR-646 inhibitor on cell proliferation. Conclusions: MiR-646 inhibitor treatment can promote the proliferation of GCs by regulating the cell cycle and inhibiting apoptosis, while silenced-IGF-1 antagonizes it