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Article ; Online: Recent Advances in Polymer-Based Biosensors for Food Safety Detection

Binhui Wang / Da Huang / Zuquan Weng

Polymers, Vol 15, Iss 3253, p

2023 Volume 3253

Abstract: The excessive use of pesticides and drugs, coupled with environmental pollution, has resulted in the persistence of contaminants on food. These pollutants tend to accumulate in humans through the food chain, posing a significant threat to human health. ... ...

Abstract	The excessive use of pesticides and drugs, coupled with environmental pollution, has resulted in the persistence of contaminants on food. These pollutants tend to accumulate in humans through the food chain, posing a significant threat to human health. Therefore, it is crucial to develop rapid, low-cost, portable, and on-site biosensors for detecting food contaminants. Among various biosensors, polymer-based biosensors have emerged as promising probes for detection of food contaminants in recent years, due to their various functions such as target binding, enrichment, and simple signal reading. This paper aims to discuss the characteristics of five types of food pollutants—heavy metals, pesticide residues, pathogenic bacteria, allergens, and antibiotics—and their adverse effects on human health. Additionally, this paper focuses on the principle of polymer-based biosensors and their latest applications in detecting these five types of food contaminants in actual food samples. Furthermore, this review briefly examines the future prospects and challenges of biosensors for food safety detection. The insights provided in this review will facilitate the development of biosensors for food safety detection.
Keywords	polymer ; food contaminants ; food safety ; biosensors ; Organic chemistry ; QD241-441
Subject code	590
Language	English
Publishing date	2023-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Research on Ensemble Learning-Based Feature Selection Method for Time-Series Prediction

Da Huang / Zhaoguo Liu / Dan Wu

Applied Sciences, Vol 14, Iss 1, p

2023 Volume 40

Abstract: Feature selection has perennially stood as a pivotal concern in the realm of time-series forecasting due to its direct influence on the efficacy of predictive models. Conventional approaches to feature selection predominantly rely on domain knowledge and ...

Abstract	Feature selection has perennially stood as a pivotal concern in the realm of time-series forecasting due to its direct influence on the efficacy of predictive models. Conventional approaches to feature selection predominantly rely on domain knowledge and experiential insights and are, therefore, susceptible to individual subjectivity and the resultant inconsistencies in the outcomes. Particularly in domains such as financial markets, and within datasets comprising time-series information, an abundance of features adds complexity, necessitating adept handling of high-dimensional data. The computational expenses associated with traditional methodologies in managing such data dimensions, coupled with vulnerability to the curse of dimensionality, further compound the challenges at hand. In response to these challenges, this paper advocates for an innovative approach—a feature selection method grounded in ensemble learning. The paper explicitly delineates the formal integration of ensemble learning into feature selection, guided by the overarching principle of “good but different”. To operationalize this concept, five feature selection methods that are well suited to ensemble learning were identified, and their respective weights were determined through K-fold cross-validation when applied to specific datasets. This ensemble method amalgamates the outcomes of diverse feature selection techniques into a numeric composite, thereby mitigating potential biases inherent in traditional methods and elevating the precision and comprehensiveness of feature selection. Consequently, this method improves the performance of time-series prediction models.
Keywords	ensemble learning ; feature selection ; time-series prediction ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	004
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Bladder malignancy as a cause of spontaneous bladder rupture: A systematic review.

Da Huang, Johnson / Shao, Emily Ximin / Tham, Chui Ming / Chung, Eric / Rhee, Handoo

BJUI compass

2023 Volume 5, Issue 1, Page(s) 12–16

Abstract: Objectives: To characterise cases of spontaneous rupture of the urinary bladder in the context of bladder cancer.: Methods: A systematic review was performed to characterise cases of spontaneous bladder rupture in patients with bladder cancer. The ... ...

Abstract	Objectives: To characterise cases of spontaneous rupture of the urinary bladder in the context of bladder cancer. Methods: A systematic review was performed to characterise cases of spontaneous bladder rupture in patients with bladder cancer. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) system was utilised, with databases being searched for relevant cases. Patient characteristics were extracted, including age, sex, presenting signs and symptoms, management modalities, tumour histology and mortality. Results: Thirty cases were included. Seventeen (57%) were male, and the median age of presentation was 59. Abdominal pain and peritonism were the most common presenting symptoms, in 80% and 60% of patients, respectively. Most patients ( Conclusion: Spontaneous bladder perforation in the context of bladder cancer is a rare cause of acute abdomen. The diagnosis is associated with high mortality, highlighting the aggressive nature of the malignancies that cause spontaneous bladder rupture. This raises important questions about the role of emergency cystectomy, the timing of systemic therapy and the appropriate involvement of palliative care.
Language	English
Publishing date	2023-08-30
Publishing country	United States
Document type	Journal Article ; Review
ISSN	2688-4526
ISSN (online)	2688-4526
DOI	10.1002/bco2.281
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: An Optimization Route Selection Method of Urban Oversize Cargo Transportation

Da Huang / Mei Han

Applied Sciences, Vol 11, Iss 5, p

2021 Volume 2213

Abstract: In order to select the optimal transportation route among alternative transportation routes more accurately and objectively, the choice of urban oversize cargo transportation routes was studied by taking the optimization weight–TOPSIS combination method ... ...

Abstract	In order to select the optimal transportation route among alternative transportation routes more accurately and objectively, the choice of urban oversize cargo transportation routes was studied by taking the optimization weight–TOPSIS combination method for specific calculations. This model, based on an entropy weight method, cloud model, and TOPSIS method, combines the superiority of the cloud model for reflecting the randomness and discreteness of subjective evaluation with the advantages of the TOPSIS method in dealing with the problem of multi-objective programming. Through selecting and classifying several the main road influencing factors of urban oversize cargo transportation, based on the data of four urban roads, the entropy weight method is used to initially determine the weights of each influencing factor, the cloud model is used to optimize weights, the TOPSIS method is used to compare and evaluate the paths, and the optimal transportation route is selected on this basis. The results showed that the optimization weight–TOPSIS method is scientific and accurate for the multi-objective planning of oversize cargo transportation route selection, and solves the problem of the impact of subjective factors in existing methods and the difficulty of processing multiple influencing factors. The Pearson consistency test results show that the Pearson correlation coefficient between the proposed method and the actual oversize cargo transportation route selection is 0.995, which is higher than the calculation results without using the combination weight.
Keywords	TOPSIS ; entropy weight method ; cloud model ; urban freight transport ; oversize cargo ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	380
Language	English
Publishing date	2021-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Research on Evaluation Method of Freight Transportation Environmental Sustainability

Da Huang / Mei Han

Sustainability, Vol 13, Iss 5, p

2021 Volume 2913

Abstract: As an important part of daily economic activities, freight transportation produces various pollutions during the transportation process, which will have a negative effect on the sustainable development of the environment. In this paper, the entropy ... ...

Abstract	As an important part of daily economic activities, freight transportation produces various pollutions during the transportation process, which will have a negative effect on the sustainable development of the environment. In this paper, the entropy weight technique for order of preference by similarity to ideal solution (TOPSIS) combination method was used for specific calculations, in order to judge whether transportation is environmentally sustainable. On the basis of selecting and classifying several the important factors of freight transportation, the entropy weight method was used to calculate and analyze the data of inland river transportation over 8 recent years. The weight of each influencing factor was determined, then the TOPSIS method was used to compare the environmental data of 8 years, and the environmental sustainability of the target river transport section was calculated by comparing the results. The method proposed in this paper is the first example of using the entropy weight–TOPSIS combination method to evaluate environmental sustainability in the field of freight transportation, also solving the problems of the impact of subjective factors in existing methods and the difficulty of dealing with multiple factors.
Keywords	TOPSIS ; entropy weight method ; freight transportation ; sustainability ; environment ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	333
Language	English
Publishing date	2021-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Research on a Time Series Data Prediction Model Based on Causal Feature Weight Adjustment

Da Huang / Qihang Zhang / Zhuoer Wen / Mingjie Hu / Weixia Xu

Applied Sciences, Vol 13, Iss 10782, p

2023 Volume 10782

Abstract: As the Information Age brings people an amount of data, research on data prediction has been widely concerned. Time series data, a sequence of data points collected over an interval of time, are very common in many areas such as weather forecasting, ... ...

Abstract	As the Information Age brings people an amount of data, research on data prediction has been widely concerned. Time series data, a sequence of data points collected over an interval of time, are very common in many areas such as weather forecasting, stock markets, and so on. Thus, research on time series data prediction is of great significance. Traditional prediction methods are usually based on correlations between data points, but correlations do not always reflect the relationship exactly within the data. In this paper, we propose the LiNGAM Weight Adjust–LSTM (LWA-LSTM) algorithm, which combines a causality discovery algorithm, feature weight adjustment, and a deep neural network for time series data prediction. Several stocks in the Chinese stock market were selected and the algorithm was used to predict the stock price. Comparing the prediction effect of the model with that of the LSTM model alone, the results show that the LWA-LSTM model can find the stable relationship between the data better and has fewer prediction errors.
Keywords	causal discovery ; time series data ; stock price forecast ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	310
Language	English
Publishing date	2023-09-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Cannabis Use Is Associated With Lower COVID-19 Susceptibility but Poorer Survival

Da Huang / Roubing Xu / Rong Na

Frontiers in Public Health, Vol

2022 Volume 10

Abstract: ObjectivesTo investigate the impact of cannabis use on the infection and survival outcomes of COVID-19.Study DesignCross-sectional study based on the UK Biobank (UKB) dataset.MethodsWe identified 13,099 individuals with cannabis smoking history in the ... ...

Abstract	ObjectivesTo investigate the impact of cannabis use on the infection and survival outcomes of COVID-19.Study DesignCross-sectional study based on the UK Biobank (UKB) dataset.MethodsWe identified 13,099 individuals with cannabis smoking history in the UKB COVID-19 Serology Study. The Charlson-Quan Comorbidity Index was estimated using inpatient ICD-10 records. Multivariable logistic regression characterized features associated with COVID-19 infection. Cox models determined the hazard ratios (HR) for COVID-19-related survival.ResultsCannabis users were more likely to getting COVID-19 (odds ratio: 1.22, P = 0.001) but multivariable analysis showed that cannabis use was a protective factor of COVID-19 infection (adjusted odds ratio: 0.81, P = 0.001). Regular cannabis users, who smoked more than once per month, had a significantly poorer COVID-19-related survival, after adjusting for known risk factors including age, gender, smoking history, and comorbidity (adjusted hazard ratio: 2.81, P = 0.041).ConclusionsThe frequency of cannabis use could be considered as a candidate predictor for mortality risk of COVID-19.
Keywords	cannabis ; COVID-19 ; survival ; susceptibility ; Comorbidity Index ; Public aspects of medicine ; RA1-1270
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Quality Control for Ocean Current Measurement Using High-Frequency Direction-Finding Radar

Shuqin He / Hao Zhou / Yingwei Tian / Da Huang / Jing Yang / Caijun Wang / Weimin Huang

Remote Sensing, Vol 15, Iss 23, p

2023 Volume 5553

Abstract: High-frequency radars (HFRs) are important for remote sensing of the marine environment due to their ability to provide real-time, wide-coverage, and high-resolution measurements of the ocean surface current, wave height, and wind speed. However, due to ... ...

Abstract	High-frequency radars (HFRs) are important for remote sensing of the marine environment due to their ability to provide real-time, wide-coverage, and high-resolution measurements of the ocean surface current, wave height, and wind speed. However, due to the intricate multidimensional processing demands (e.g., time, Doppler, and space) for internal data and effective suppression of external noise, conducting quality control (QC) on radar-measured data is of great importance. In this paper, we first present a comprehensive quality evaluation model for both radial current and synthesized vector current obtained by direction-finding (DF) HFRs. In the proposed model, the quality factor (QF) is calculated for each current cell to evaluate its reliability. The QF for the radial current depends on the signal-to-noise ratio (SNR) and DF factor of the first-order Bragg peak region in the range–Doppler (RD) spectrum, and the QF for the synthesized vector current can be calculated using an error propagation model based on geometric dilution of precision (GDOP). A QC method is then proposed for processing HFR-derived surface current data via the following steps: (1) signal preprocessing is performed to minimize the effect of unwanted external signals such as radio frequency interference and ionospheric clutter; (2) radial currents with low QFs and outliers are removed; (3) the vector currents with low QFs are also removed before spatial smoothing and interpolation. The proposed QC method is validated using a one-month-long dataset collected by the Ocean State Monitoring and Analyzing Radar, model S (OSMAR-S). The improvement in the current quality is proven to be significant. Using the buoy data as ground truth, after applying QC, the correlation coefficients (CCs) of the radial current, synthesized current speed, and synthesized current direction are increased by 4.33~102.91%, 1.04~90.74%, and 1.20~62.67%, respectively, and the root mean square errors (RMSEs) are decreased by 2.51~49.65%, 7.86~27.22%, and 1.68~28.99%, ...
Keywords	direction finding ; high-frequency radar ; geometric dilution of precision ; radio frequency interference ; quality control ; quality factor ; Science ; Q
Subject code	551
Language	English
Publishing date	2023-11-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Research on Freight Transportation Carbon Emission Reduction Based on System Dynamics

Da Huang / Mei Han / Yuanting Jiang

Applied Sciences, Vol 11, Iss 5, p

2021 Volume 2041

Abstract: In order to solve the environmental protection problem of carbon emissions in the field of freight transportation, this article proposes to promote the transfer of road freight transportation to railway transportation within a reasonable range by levying ...

Abstract	In order to solve the environmental protection problem of carbon emissions in the field of freight transportation, this article proposes to promote the transfer of road freight transportation to railway transportation within a reasonable range by levying carbon emission taxes. To propose an applicable solution, this paper establishes a comprehensive carbon emission system model in the field of road transportation and railway transportation to simulate a closed-loop system as comprehensively as a real transportation system, determines the system elements according to the actual situation, reasonably develops the model hypothesis scheme, and draws out the causal network. On this basis, the system flow diagram and corresponding structural equations are constructed, and the model parameters are estimated. Finally, the paper uses actual data to verify and simulate the system model. A reasonable carbon levy interval has been obtained, and the carbon levy within this interval can promote the transfer of road freight transportation to railway transportation, so as to achieve the purpose of decreasing total carbon emissions of road–rail transportation systems in an orderly way. The innovation of this paper is to construct the carbon emissions of the road–rail system systematically for the first time, and to conduct research and exploration of carbon levies on this basis.
Keywords	carbon levy ; road transportation ; rail transportation ; environmental protection ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	380
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Hemostasis Strategies and Recent Advances in Nanomaterials for Hemostasis

Jian Du / Jingzhong Wang / Tao Xu / Hai Yao / Lili Yu / Da Huang

Molecules, Vol 28, Iss 5264, p

2023 Volume 5264

Abstract: The development of materials that effectively stop bleeding and prevent wound adhesion is essential in both military and medical fields. However, traditional hemostasis methods, such as cautery, tourniquets, and gauze, have limitations. In recent years, ... ...

Abstract	The development of materials that effectively stop bleeding and prevent wound adhesion is essential in both military and medical fields. However, traditional hemostasis methods, such as cautery, tourniquets, and gauze, have limitations. In recent years, new nanomaterials have gained popularity in medical and health fields due to their unique microstructural advantages. Compared to traditional materials, nanomaterials offer better adhesion, versatility, and improved bioavailability of traditional medicines. Nanomaterials also possess advantages such as a high degree and stability, self-degradation, fewer side effects, and improved wound healing, which make them ideal for the development of new hemostatic materials. Our review provides an overview of the currently used hemostatic strategies and materials, followed by a review of the cutting-edge nanomaterials for hemostasis, including nanoparticles and nanocomposite hydrogels. The paper also briefly describes the challenges faced by the application of nanomaterials for hemostasis and the prospects for their future development.
Keywords	effective hemostasis ; hemostasis strategies ; nanomaterials ; wound healing ; nanotechnology ; Organic chemistry ; QD241-441
Subject code	339
Language	English
Publishing date	2023-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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