LIVIVO - Search results -

Search results

Result 1 - 10 of total 1653

Search options

Article ; Online: Slow recovery of natural ecosystems as an important factor restricting regional coordinated development

Peng Zhang / Jinhao Shi

Ecological Indicators, Vol 158, Iss , Pp 111435- (2024)

1481

Abstract: Climate change and human activity are the main causes of ecological degradation, placing huge pressure on ecological security and sustainable development (SD) worldwide. As a typical agricultural region and an important industrial base, the contradiction ...

Abstract	Climate change and human activity are the main causes of ecological degradation, placing huge pressure on ecological security and sustainable development (SD) worldwide. As a typical agricultural region and an important industrial base, the contradiction between economic construction and ecological civilization construction in Northeast China has become increasingly acute. However, so far, it has not made much progress. To address this, we synthesized 28 economic, social, and ecological indicators and explored the key drivers and spatial effects of SD and ecosystem services (ESs) in Northeast China. The results show that the development of the ESs level lagged that of SD, with the coupling coordination degree (CCD) increasing by only 33 % from 2005 to 2020, almost equal to that of ESs (+35 %) but far lower than that of the SD level (+133 %). Hence, a small increase in ESs resulted in low CCD levels. Additionally, economic factors (fertilizer use, proportions of built-up land, etc.) and the proportion of forestland were the key factors driving the spatiotemporal variation of the CCD. In terms of the current CCD changes in Northeast China, local stakeholders and policymakers should focus more on industrialization and food security issues by restoring degraded ecosystems and implementing positive ecological measures to increase the CCD. This study provides an explicit analytical framework for clarifying the complex relationship between ESs and SD, which can help scientifically discern the balance between economic and ecological development. Our findings highlight the achievable prospects of a win–win situation in society and nature.
Keywords	Sustainable development ; Ecosystem services ; Coupling coordination degree ; Geographically and temporally weighted regression model ; Driving factors ; Ecology ; QH540-549.5
Subject code	910
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: MGAE-DC

Peng Zhang / Shikui Tu

PLoS Computational Biology, Vol 19, Iss 3, p e

Predicting the synergistic effects of drug combinations through multi-channel graph autoencoders.

2023 Volume 1010951

Abstract: Accurate prediction of synergistic effects of drug combinations can reduce the experimental costs for drug development and facilitate the discovery of novel efficacious combination therapies for clinical studies. The drug combinations with high synergy ... ...

Abstract	Accurate prediction of synergistic effects of drug combinations can reduce the experimental costs for drug development and facilitate the discovery of novel efficacious combination therapies for clinical studies. The drug combinations with high synergy scores are regarded as synergistic ones, while those with moderate or low synergy scores are additive or antagonistic ones. The existing methods usually exploit the synergy data from the aspect of synergistic drug combinations, paying little attention to the additive or antagonistic ones. Also, they usually do not leverage the common patterns of drug combinations across different cell lines. In this paper, we propose a multi-channel graph autoencoder (MGAE)-based method for predicting the synergistic effects of drug combinations (DC), and shortly denote it as MGAE-DC. A MGAE model is built to learn the drug embeddings by considering not only synergistic combinations but also additive and antagonistic ones as three input channels. The later two channels guide the model to explicitly characterize the features of non-synergistic combinations through an encoder-decoder learning process, and thus the drug embeddings become more discriminative between synergistic and non-synergistic combinations. In addition, an attention mechanism is incorporated to fuse each cell-line's drug embeddings across various cell lines, and a common drug embedding is extracted to capture the invariant patterns by developing a set of cell-line shared decoders. The generalization performance of our model is further improved with the invariant patterns. With the cell-line specific and common drug embeddings, our method is extended to predict the synergy scores of drug combinations by a neural network module. Experiments on four benchmark datasets demonstrate that MGAE-DC consistently outperforms the state-of-the-art methods. In-depth literature survey is conducted to find that many drug combinations predicted by MGAE-DC are supported by previous experimental studies. The source code and data are ...
Keywords	Biology (General) ; QH301-705.5
Subject code	571
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Electronic Structure of Single-Atom Alloys and Its Impact on The Catalytic Activities

Ziyi Chen / Peng Zhang

ACS Omega, Vol 7, Iss 2, Pp 1585-

2022 Volume 1594

Keywords	Chemistry ; QD1-999
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	American Chemical Society
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Patterns and Influencing Factors of Express Outlets in China

Xin Li / Peng Zhang

Sustainability, Vol 14, Iss 8061, p

2022 Volume 8061

Abstract: China’s express delivery industry has developed rapidly in the past decade, and the spatial distribution of express delivery outlets can reflect variations in regional development to a certain extent. Previous studies lacked point of interest (POI) data ... ...

Abstract	China’s express delivery industry has developed rapidly in the past decade, and the spatial distribution of express delivery outlets can reflect variations in regional development to a certain extent. Previous studies lacked point of interest (POI) data as the research object to analyze the limitations of express delivery outlets, and also lack a focus on the patterns that specifically occur in China. This study implemented spatial analysis methods such as nearest neighbor index, kernel density, and exploratory spatial data analysis to explore the spatial distribution patterns and characteristics of China’s express outlets, and used geographic detector factor detection to objectively analyze the factors that affect their distribution. The following are the main conclusions of this study: (1) in China, express delivery outlets are more abundant in the east and sparser in the west; (2) the local agglomeration of express outlets presents a concentric structure, and outlier clusters appeared in the northeast and central regions; (3) the distribution of the express outlets resulted from the combined action of multiple factors (e.g., population factors, etc.). Our study not only explores and analyzes the overall situation in China but also broadens the scope of express outlet research.
Keywords	express outlets ; spatial distribution pattern ; influencing factors ; China ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	950
Language	English
Publishing date	2022-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Hybrid-TransCD

Qingtian Ke / Peng Zhang

ISPRS International Journal of Geo-Information, Vol 11, Iss 263, p

A Hybrid Transformer Remote Sensing Image Change Detection Network via Token Aggregation

2022 Volume 263

Abstract: Existing optical remote sensing image change detection (CD) methods aim to learn an appropriate discriminate decision by analyzing the feature information of bitemporal images obtained at the same place. However, the complex scenes in high-resolution (HR) ...

Abstract	Existing optical remote sensing image change detection (CD) methods aim to learn an appropriate discriminate decision by analyzing the feature information of bitemporal images obtained at the same place. However, the complex scenes in high-resolution (HR) remote images cause unsatisfied results, especially for some irregular and occluded objects. Although recent self-attention-driven change detection models with CNN achieve promising effects, the computational and consumed parameters costs emerge as an impassable gap for HR images. In this paper, we utilize a transformer structure replacing self-attention to learn stronger feature representations per image. In addition, concurrent vision transformer models only consider tokenizing single-dimensional image tokens, thus failing to build multi-scale long-range interactions among features. Here, we propose a hybrid multi-scale transformer module for HR remote images change detection, which fully models representation attentions at hybrid scales of each image via a fine-grained self-attention mechanism. The key idea of the hybrid transformer structure is to establish heterogeneous semantic tokens containing multiple receptive fields, thus simultaneously preserving large object and fine-grained features. For building relationships between features without embedding with token sequences from the Siamese tokenizer, we also introduced a hybrid difference transformer decoder (HDTD) layer to further strengthen multi-scale global dependencies of high-level features. Compared to capturing single-stream tokens, our HDTD layer directly focuses representing differential features without increasing exponential computational cost. Finally, we propose a cascade feature decoder (CFD) for aggregating different-dimensional upsampling features by establishing difference skip-connections. To evaluate the effectiveness of the proposed method, experiments on two HR remote sensing CD datasets are conducted. Compared to state-of-the-art methods, our Hybrid-TransCD achieved superior ...
Keywords	change detection ; deep learning ; transformer ; self-attention ; Geography (General) ; G1-922
Subject code	006
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Book ; Online: Maneuver Decision-Making Through Automatic Curriculum Reinforcement Learning Without Handcrafted Reward functions

Hong-Peng, Zhang

2023

Abstract: Maneuver decision-making is the core of unmanned combat aerial vehicle for autonomous air combat. To solve this problem, we propose an automatic curriculum reinforcement learning method, which enables agents to learn effective decisions in air combat ... ...

Abstract	Maneuver decision-making is the core of unmanned combat aerial vehicle for autonomous air combat. To solve this problem, we propose an automatic curriculum reinforcement learning method, which enables agents to learn effective decisions in air combat from scratch. The range of initial states are used for distinguishing curricula of different difficulty levels, thereby maneuver decision is divided into a series of sub-tasks from easy to difficult, and test results are used to change sub-tasks. As sub-tasks change, agents gradually learn to complete a series of sub-tasks from easy to difficult, enabling them to make effective maneuvering decisions to cope with various states without the need to spend effort designing reward functions. The ablation studied show that the automatic curriculum learning proposed in this article is an essential component for training through reinforcement learning, namely, agents cannot complete effective decisions without curriculum learning. Simulation experiments show that, after training, agents are able to make effective decisions given different states, including tracking, attacking and escaping, which are both rational and interpretable.
Keywords	Computer Science - Artificial Intelligence ; Computer Science - Machine Learning ; Computer Science - Robotics
Subject code	006
Publishing date	2023-07-12
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Acupuncture for Crohn’s disease

Daming Liu / Peng Zhang / Qiang Han

BMJ Open, Vol 13, Iss

a protocol for systematic review and meta-analysis

2023 Volume 3

Abstract: Introduction Crohn’s disease (CD) is a chronic inflammatory bowel disease that seriously affects the quality of life. While conventional medicines are of limitations, acupuncture has been shown to be a promising therapy. While no systematic review ... ...

Abstract	Introduction Crohn’s disease (CD) is a chronic inflammatory bowel disease that seriously affects the quality of life. While conventional medicines are of limitations, acupuncture has been shown to be a promising therapy. While no systematic review related has been published, the present study aimed to evaluate the efficacy and safety of acupuncture for CD.Methods and analysis PubMed, the Cochrane Central Register of Controlled Trials and Chinese electronic databases, including China National Knowledge Infrastructure, Wan Fang database, VIP, SinoMed and the Chinese Clinical Trial Registry, will be searched from the establishment of the database until 31 December 2022. Randomised controlled trials evaluating the efficacy and safety of acupuncture/electroacupuncture on patients with CD, controlled by conventional therapies, were included. Outcomes include induction of clinical remission and response, maintenance of remission, and the incidence of adverse events. All articles will be screened and extracted by two reviewers independently. The risk of bias will be evaluated using the revised Cochrane Risk of Bias 2 tool. A fixed effect model or a random effects model will be used based on the assessment of heterogeneity. A subgroup analysis and sensitivity analysis will be carried out if necessary. Publication bias will be analysed, and the strength of the body of evidence for primary outcomes will be graded.Ethics and dissemination There is no necessity for this study to acquire ethical approval, and this review will be disseminated in a peer-reviewed journal or conference presentation.Trial registration number CRD42022356967.
Keywords	Medicine ; R
Subject code	610
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	BMJ Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Study on Flocculation Behavior of Cr(VI) Using a Novel Chitosan Functionalized with Thiol Groups

Yuelong Zhao / Peng Zhang / Wei Zhang / Yali Fan

Polymers, Vol 15, Iss 1117, p

2023 Volume 1117

Abstract: In this study, CTS-GSH was prepared by grafting thiol (–SH) groups onto chitosan (CTS), which was characterized through Fourier Transform Infrared (FT-IR) spectra, Scanning Electron Microscopy (SEM) and Differential Thermal Analysis–Thermogravimetric ... ...

Abstract	In this study, CTS-GSH was prepared by grafting thiol (–SH) groups onto chitosan (CTS), which was characterized through Fourier Transform Infrared (FT-IR) spectra, Scanning Electron Microscopy (SEM) and Differential Thermal Analysis–Thermogravimetric Analysis (DTA-TG). The performance of CTS-GSH was evaluated by measuring Cr(VI) removal efficiency. The –SH group was successfully grafted onto CTS, forming a chemical composite, CTS-GSH, with a rough, porous and spatial network surface. All of the molecules tested in this study were efficient at removing Cr(VI) from the solution. The more CTS-GSH added, the more Cr(VI) removed. When a suitable dosage of CTS-GSH was added, Cr(VI) was almost completely removed. The acidic environment at pH 5–6 was beneficial for the removal of Cr(VI), and at pH 6, the maximum removal efficiency was achieved. Further experimentation showed that with 100.0 mg/L CTS-GSH for the disposal of 5.0 mg/L Cr(VI) solution, the removal rate of Cr(VI) reached 99.3% with a slow stirring time of 8.0 min and sedimentation time of 3 h; the presence of four common ions, including Mg 2+ , Ca 2+ , SO 4 2− and CO 3 2− , had an inhibitory effect on CTS-GSH’s ability to remove Cr(VI) from the aqueous solution, and more CTS-GSH was needed to reduce this inhibiting action. Overall, CTS-GSH exhibited good results in Cr(VI) removal, and thus has good potential for the further treatment of heavy metal wastewater.
Keywords	hexavalent chromium ; chitosan ; reduced glutathione ; chelating agent ; amidation reaction ; flocculation ; Organic chemistry ; QD241-441
Subject code	333
Language	English
Publishing date	2023-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Time-Frequency Feature-Based Seismic Response Prediction Neural Network Model for Building Structures

Peng Zhang / Yiming Li / Yu Lin / Huiqin Jiang

Applied Sciences, Vol 13, Iss 2956, p

2023 Volume 2956

Abstract: Currently, machine learning techniques are widely used in structural seismic response studies. The developed network models for various types of seismic response provide new ways to analyse seismic hazards. However, it is not easy to balance the ... ...

Abstract	Currently, machine learning techniques are widely used in structural seismic response studies. The developed network models for various types of seismic response provide new ways to analyse seismic hazards. However, it is not easy to balance the applicability of the input, accuracy, and computational efficiency for existing network models. In this paper, a neural network model containing an efficient self-adaptive feature extraction module (AFEM) is designed. It can recognize time-frequency features from ground motion (GM) inputs for structural seismic response prediction tasks while considering the model’s computational accuracy and computational cost. The self-adaptive feature extraction module is constructed based on the MFCCs feature extraction process in NLP. AFEM recognizes time-frequency features closely related to structures’ behaviour and response under dynamic loads. Taking the seismic response prediction of a typical building as the target task, the neural network configuration, including a baseline model <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>M</mi><mn>0</mn></msub></semantics></math> and three comparison models ( <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>M</mi><mn>1</mn></msub></semantics></math> , <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>M</mi><mn>2</mn></msub></semantics></math> , and <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>M</mi><mn>3</mn></msub></semantics></math> ) with AFEM, is systematically analysed. The results demonstrate that the proposed <math xmlns="http://www.w3.org/1998/Math/MathML" ...<br />
Keywords	neural network ; seismic response ; self-adaptive feature extraction ; time-frequency features ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	511
Language	English
Publishing date	2023-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Detection and impact of short-range order in medium/high-entropy alloys

Tyler Joe Ziehl / David Morris / Peng Zhang

iScience, Vol 26, Iss 3, Pp 106209- (2023)

2023

Abstract: Summary: Medium/High-entropy alloys (MEAs/HEAs) have attracted much attention during the past two decades and have been studied extensively owing to their excellent physical and mechanical properties. These materials form simple lattice structures and ... ...

Abstract	Summary: Medium/High-entropy alloys (MEAs/HEAs) have attracted much attention during the past two decades and have been studied extensively owing to their excellent physical and mechanical properties. These materials form simple lattice structures and thermodynamically favored single-phase solutions. Despite having a single-phase, the local structure of MEAs/HEAs still contain some degree of order. Recently, short-range order (SRO) has been studied to better understand the local structure of MEAs/HEAs and how this order impacts their properties. Efforts to characterize SRO in high-entropy alloys have included non-imaging methods such as X-ray diffraction and X-ray absorption spectroscopy, as well as imaging methods such as transmission electron microscopy-based techniques. In this perspective, structural studies using non-imaging and imaging techniques to investigate SRO in MEAs/HEAs are discussed. Moreover, the impact of SRO on the physical and mechanical properties of MEAs/HEAs is also covered.
Keywords	Materials science ; Materials chemistry ; Materials synthesis ; Materials property ; Science ; Q
Subject code	669
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

To top

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED