Displaying publications 1 - 20 of 60 in total

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  1. Fulltext Attitude of youth towards self-employment: Evidence from university students in Yemen
    Al-Qadasi N, Zhang G, Al-Jubari I
    PLoS One, 2021;16(9):e0257358.
    PMID: 34516592 DOI: 10.1371/journal.pone.0257358
    This study assesses whether final-year undergraduate students at Sana'a University, Yemen intend to start their own business. The study employs the theory of planned behaviour and two environmental factors to explore whether the theory's behavioural factors and the contextual factors of Lüthje & Franke's model have an impact on students' intentions to start their own business. A questionnaire survey with a random sample of 335 final-year university students from the largest public university in Yemen has been conducted. Data has been analysed using descriptive statistics, Pearson's correlation and structural equation modelling. The findings indicate that students' perceptions of entrepreneurship have a strong, direct impact on self-employment intention, excluding social norms and entrepreneurial self-efficacy. Students' self-employment intention is directly affected by perceived barriers and support factors in the entrepreneurship-related context. To increase their entrepreneurial abilities, university students require more training and education to be able to start new businesses. Developing entrepreneurial skills among citizens may improve the societal norms of business. The outcomes provide significant implications for policymakers, academic communities and international bodies.
  2. Fulltext Research on the Factors Affecting the Adoption of Smart Aged-Care Products by the Aged in China: Extension Based on UTAUT Model
    Wang X, Lee CF, Jiang J, Zhang G, Wei Z
    Behav Sci (Basel), 2023 Mar 21;13(3).
    PMID: 36975302 DOI: 10.3390/bs13030277
    With the rapid development of network technology and smart technology, smart aged-care products are becoming increasingly valued for their ability to help the aged actively cope with the challenges of aging. However, seniors face challenges in using smart aged-care products for many reasons, which reduces their willingness to adopt them. As a result, the sustainable development of smart aged-care products is constrained. This study combined the unified theory of technology acceptance and use, perceived risk theory and perceived cost theory, and reconstructed a research model that investigated the adoption of smart aged-care products by the elderly in China. Questionnaires were given to older Chinese adults in this study, and 386 valuable responses were received. The findings of the structural equation model (SEM) analysis are as follows: (1) performance expectancy, effort expectancy, and social influence were positively related to the behavioral intention of seniors to use smart aged-care products; (2) perceived cost and perceived risk were negatively related to the behavioral intention of seniors to use smart aged-care products; (3) perceived risk indirectly affected use behavior through behavioral intentions; (4) facilitating conditions did not have a significant impact on the use behavior of seniors in adopting smart aged-care products. Based on the empirical results, this study sought to improve the use behavior of the aged in relation to the adoption of smart aged-care products, and provided suggestions to improve the overall service quality and sustainability of those products.
  3. Fulltext Research on land cover classification of multi-source remote sensing data based on improved U-net network
    Zhang G, Roslan SNAB, Wang C, Quan L
    Sci Rep, 2023 Sep 28;13(1):16275.
    PMID: 37770628 DOI: 10.1038/s41598-023-43317-1
    In recent years, remote sensing images of various types have found widespread applications in resource exploration, environmental protection, and land cover classification. However, relying solely on a single optical or synthetic aperture radar (SAR) image as the data source for land cover classification studies may not suffice to achieve the desired accuracy in ground information monitoring. One widely employed neural network for remote sensing image land cover classification is the U-Net network, which is a classical semantic segmentation network. Nonetheless, the U-Net network has limitations such as poor classification accuracy, misclassification and omission of small-area terrains, and a large number of network parameters. To address these challenges, this research paper proposes an improved approach that combines both optical and SAR images in bands for land cover classification and enhances the U-Net network. The approach incorporates several modifications to the network architecture. Firstly, the encoder-decoder framework serves as the backbone terrain-extraction network. Additionally, a convolutional block attention mechanism is introduced in the terrain extraction stage. Instead of pooling layers, convolutions with a step size of 2 are utilized, and the Leaky ReLU function is employed as the network's activation function. This design offers several advantages: it enhances the network's ability to capture terrain characteristics from both spatial and channel dimensions, resolves the loss of terrain map information while reducing network parameters, and ensures non-zero gradients during the training process. The effectiveness of the proposed method is evaluated through land cover classification experiments conducted on optical, SAR, and combined optical and SAR datasets. The results demonstrate that our method achieves classification accuracies of 0.8905, 0.8609, and 0.908 on the three datasets, respectively, with corresponding mIoU values of 0.8104, 0.7804, and 0.8667. Compared to the traditional U-Net network, our method exhibits improvements in both classification accuracy and mIoU to a certain extent.
  4. Fulltext Environmentally specific servant leadership and voluntary pro-environmental behavior in the context of green operations: A serial mediation path
    Zafar H, Tian F, Ho JA, Zhang G
    Front Psychol, 2022;13:1059523.
    PMID: 36420384 DOI: 10.3389/fpsyg.2022.1059523
    Green operations of organizations and enhancement of corporate social responsibility hinges upon leaders. This study investigated the influential role performed by environmentally specific servant leadership in provoking voluntary pro-environmental behavior of employees. The findings illuminate a serial chain mediation model that originates as a result of environmentally specific servant leadership and leads toward psychological empowerment, and organizational identity, ultimately leading toward voluntary pro-environmental behavior. Data from the textile sector of Pakistan uncovered that environmentally specific servant leadership prompted the voluntary pro-environmental behavior of employees. Moreover, environmentally specific servant leadership was significantly linked with voluntary pro-environmental behavior through psychological empowerment. The study supports the serial mediation of psychological empowerment and organizational identity in stirring voluntary pro-environmental behavior. An organizational psychological mechanism has been unraveled that can help organizations achieve a high level of sustainability and can serve as a catalyst for organizational green operations.
  5. Organochlorine pesticides in the atmosphere and surface water from the equatorial Indian Ocean: enantiomeric signatures, sources, and fate
    Huang Y, Xu Y, Li J, Xu W, Zhang G, Cheng Z, et al.
    Environ Sci Technol, 2013;47(23):13395-403.
    PMID: 24251554 DOI: 10.1021/es403138p
    Nineteen pairs of gaseous and surface seawater samples were collected along the cruise from Malaysia to the south of Bay of Bengal passing by Sri Lanka between April 12 and May 4, 2011 on the Chinese research vessel Shiyan I to investigate the latest OCP pollution status over the equatorial Indian Ocean. Significant decrease of α-HCH and γ-HCH was found in the air and dissolved water phase owing to global restriction for decades. Substantially high levels of p,p'-DDT, o,p'-DDT, trans-chlordane (TC), and cis-chlordane (CC) were observed in the water samples collected near Sri Lanka, indicating fresh continental riverine input of these compounds. Fugacity fractions suggest equilibrium of α-HCH at most sampling sites, while net volatilization for DDT isomers, TC and CC in most cases. Enantiomer fractions (EFs) of α-HCH and o,p'-DDT in the air and water samples were determined to trace the source of these compounds in the air. Racemic or close to racemic composition was found for atmospheric α-HCH and o,p'-DDT, while significant depletion of (+) enantiomer was found in the water phase, especially for o,p'-DDT (EFs = 0.310 ± 0.178). 24% of α-HCH in the lower air over the open sea of the equatorial Indian Ocean is estimated to be volatilized from local seawater, indicating that long-range transport is the main source.
  6. Deep parallel sequencing reveals conserved and novel miRNAs in gill and hepatopancreas of giant freshwater prawn
    Tan TT, Chen M, Harikrishna JA, Khairuddin N, Mohd Shamsudin MI, Zhang G, et al.
    Fish Shellfish Immunol, 2013 Oct;35(4):1061-9.
    PMID: 23816854 DOI: 10.1016/j.fsi.2013.06.017
    MicroRNAs (miRNAs) are ~20-22 nucleotides, non protein-coding RNA regulatory genes that post-transcriptionally regulate many protein-coding genes, influencing critical biological and metabolic processes. While the number of known microRNA is increasing, there is currently no published data for miRNA from giant freshwater prawns, Macrobrachium rosenbergii (M. rosenbergii), a commercially cultured and economically important food species. In this study, we identified novel miRNAs in the gill and hepatopancreas of M. rosenbergii. Through a deep parallel sequencing analysis and an in silico data analysis approach, 327 miRNA families were identified from small RNA libraries with reference to both the de novo transcriptome of M. rosenbergii obtained from RNA-Seq and to miRBase (Release 18.0, November 2012). Based on the identified mature miRNA and recovered precursor sequences that form appropriate hairpin structures, three conserved miRNA (miR125, miR750, miR993) and 27 novel miRNA candidates encoding messenger-like non-coding RNA were identified. miR-125, miR-750, G-m0002/H-m0009, G-m0005, G-m0008/H-m0016, G-m0011/H-m0027 and G-m0015 were selected for experimental validation with stem-loop quantitative RT-PCR and were found to be coherent with the expression profile of deep sequencing data as evaluated with Pearson's correlation coefficient (r = 0.835178 for miRNA in gill, r = 0.724131 for miRNA in hepatopancreas). Using a combinatorial approach of pathway enrichment analysis and inverse expression relationship of miRNA and mRNA, four co-expressed novel miRNA candidates (G-m0005, G-m0008/H-m0016, G-m0011/H-m0027, and G-m0015) were found to be associated with energy metabolism. In addition, the expression of the three novel miRNA candidates (G-m0005, G-m0008/H-m0016, and G-m0011/H-m0027) were also found to be significantly reduced at 9 and 24 h post infection in M. rosenbergii challenged with infectious hypodermal and hematopoietic necrosis virus, suggesting a functional role of these miRNAs in crustacean immune defense.
  7. Fulltext Draft genome of Brugia pahangi: high similarity between B. pahangi and B. malayi
    Lau YL, Lee WC, Xia J, Zhang G, Razali R, Anwar A, et al.
    Parasit Vectors, 2015;8:451.
    PMID: 26350613 DOI: 10.1186/s13071-015-1064-2
    Efforts to completely eradicate lymphatic filariasis from human population may be challenged by the emergence of Brugia pahangi as another zoonotic lymphatic filarial nematode. In this report, a genomic study was conducted to understand this species at molecular level.
  8. ADA-SR: Activity detection and analysis using security robots for reliable workplace safety
    Zhang G, Jing W, Tao H, Rahman MA, Salih SQ, Al-Saffar A, et al.
    Work, 2021;68(3):935-943.
    PMID: 33612535 DOI: 10.3233/WOR-203427
    BACKGROUND: Human-Robot Interaction (HRI) has become a prominent solution to improve the robustness of real-time service provisioning through assisted functions for day-to-day activities. The application of the robotic system in security services helps to improve the precision of event detection and environmental monitoring with ease.

    OBJECTIVES: This paper discusses activity detection and analysis (ADA) using security robots in workplaces. The application scenario of this method relies on processing image and sensor data for event and activity detection. The events that are detected are classified for its abnormality based on the analysis performed using the sensor and image data operated using a convolution neural network. This method aims to improve the accuracy of detection by mitigating the deviations that are classified in different levels of the convolution process.

    RESULTS: The differences are identified based on independent data correlation and information processing. The performance of the proposed method is verified for the three human activities, such as standing, walking, and running, as detected using the images and sensor dataset.

    CONCLUSION: The results are compared with the existing method for metrics accuracy, classification time, and recall.

  9. Impact of biochar and compost amendment on soil quality, growth and yield of a replanted apple orchard in a 4-year field study
    Safaei Khorram M, Zhang G, Fatemi A, Kiefer R, Maddah K, Baqar M, et al.
    J Sci Food Agric, 2019 Mar 15;99(4):1862-1869.
    PMID: 30264414 DOI: 10.1002/jsfa.9380
    BACKGROUND: Numerous studies have addressed the positive effects of organic amendments on soil and plant productivity under short-term field studies. However, to date, few studies have been conducted on the effects of organic amendment on the orchards where high nutrient bioavailability is required. This study deals with the effects of biochar and compost on soil quality, growth and yield of a replanted apple orchard in the northeast of Iran.

    RESULTS: Biochar+compost application resulted in 37% and 300% higher soil total organic carbon and available phosphorus content, respectively, during the first 3 years of experimentation compared to control. Similarly, trunk diameter and shoot number of apple trees increased 23-26% by the end of the first year. Nevertheless, there were no significant changes in fruitfulness, fruit weight or starch pattern index as productivity indices.

    CONCLUSION: Biochar and compost were beneficial in improving soil quality, mainly by increasing soil nutrient content and decreasing soil bulk density, and in increasing plant growth at early growth stages of apple orchards. However, they failed to enhance overall yield and fruit quality, most likely due to their limited ability to suppress apple replant disease. © 2018 Society of Chemical Industry.

  10. Anthropogenic impacts on sulfonamide residues and sulfonamide resistant bacteria and genes in Larut and Sangga Besar River, Perak
    Lye YL, Bong CW, Lee CW, Zhang RJ, Zhang G, Suzuki S, et al.
    Sci Total Environ, 2019 Oct 20;688:1335-1347.
    PMID: 31726563 DOI: 10.1016/j.scitotenv.2019.06.304
    The environmental reservoirs of sulfonamide (SA) resistome are still poorly understood. We investigated the potential sources and reservoir of SA resistance (SR) in Larut River and Sangga Besar River by measuring the SA residues, sulfamethoxazole resistant (SMXr) in bacteria and their resistance genes (SRGs). The SA residues measured ranged from lower than quantification limits (LOQ) to 33.13 ng L-1 with sulfadiazine (SDZ), sulfadimethoxine (SDM) and SMX as most detected. Hospital wastewater effluent was detected with the highest SA residues concentration followed by the slaughterhouse and zoo wastewater effluents. The wastewater effluents also harbored the highest abundance of SMXr-bacteria (107 CFU mL-1) and SRGs (10-1/16S copies mL-1). Pearson correlation showed only positive correlation between the PO4 and SMXr-bacteria. In conclusion, wastewater effluents from the zoo, hospital and slaughterhouse could serve as important sources of SA residues that could lead to the consequent emergence of SMXr-bacteria and SRGs in the river.
  11. Effect of walnut shell biochars on soil quality, crop yields, and weed dynamics in a 4-year field experiment
    Safaei Khorram M, Zhang G, Fatemi A, Kiefer R, Mahmood A, Jafarnia S, et al.
    Environ Sci Pollut Res Int, 2020 May;27(15):18510-18520.
    PMID: 32198685 DOI: 10.1007/s11356-020-08335-w
    The introduction of biochar has been extensively tested under short-term greenhouse or field studies mainly in sandy or acidic soils, while its effects on soil properties, crop plants, and weed species especially in neutral or alkaline soils are still not well understood. Therefore, this study focused on relatively long effects of two walnut shell biochars (5 t ha-1) on soil nutrient dynamics, two crop plants (wheat and lentil) growth and developments, and weed growth dynamics over 4 years (2014-2017). Applied biochar added once at the beginning of the experiment while planted crops were supplied with macro-nutrients and sprayed with pesticides according to conventional requirements of the region. Biochars improved soil properties by 10-23% during the first and second years while positive effects of biochars on weed growth were drastically higher (60-78% higher weed density) during the whole period of this study most likely due to increase in bioavailability of nutrient shortly after biochar amendment and indirect positive effects of biochars on soil physical properties as well. Consequently, biochar macro- and micro-nutrient will be utilized by weed plants with higher efficacy compared with crop plants.
  12. Fulltext Multi Frequency Controllable In-Band Suppressions in a Broad Bandwidth Microstrip Filter Design for 5G Wi-Fi and Satellite Communication Systems Utilizing a Quad-Mode Stub-Loaded Resonator
    Zhang G, Basit A, Khan MI, Daraz A, Saqib N, Zubir F
    Micromachines (Basel), 2023 Apr 17;14(4).
    PMID: 37421099 DOI: 10.3390/mi14040866
    The key elements used for receiving and processing signals in communication systems are the bandpass filters. Initially, a common operating mechanism was applied for the design of broadband filters, i.e., by cascading low-pass filters or high-pass filters using multiple line resonators with length quarter-half- or full-wavelength with central frequency, but using these approaches, the design topology becomes expensive and complex. The above mechanisms can be possibly overcome using a planar microstrip transmission line structure due to its simple design fabrication procedure and low cost. So, pointing out the above problems in bandpass filters such as low-cost, low insertion loss, and good out-of-band performance, this article presents a broadband filter with multifrequency suppression capability at 4.9 GHz, 8.3 GHz, and 11.5 GHz using a T-shaped shorted stub-loaded resonator with a central square ring coupled to the basic broadband filter. Initially, the C-shaped resonator is utilized for the formation of a stopband at 8.3 GHz for a satellite communication system, and then a shorted square ring resonator is added to the existing C-shaped structure for the realization of two more stopbands at 4.9 GHz and 11.5 GHz for 5G (WLAN 802.11j) communication, respectively. The overall circuit area covered with the proposed filter is 0.52 λg × 0.32 λg (λg is the wavelength of the feed lines at frequency 4.9 GHz). All the loaded stubs are folded in order to save the circuit area, which is an important requirement of next-generation wireless communication systems. The proposed filter has been analyzed using a well-known transmission line theory, even-odd-mode, and simulated with the 3D software HFSS. After the parametric analysis, some attractive features were obtained, i.e., compact structure, simple planar topology, low insertion losses of 0.4 dB over the entire band, good return loss greater than 10 dB, and independently controlled mutli stopbands, which make the proposed design unique and can be used in various wireless communication system applications. Finally, a Rogers RO-4350 substrate is selected for the fabrication of the prototype using an LPKF S63 ProtoLaser machine and then measured using a ZNB20 vector network analyzer for matching the simulated and measured results. After testing the prototype, a good agreement was found between the results.
  13. Functional transcriptome reveals hepatopancreatic lipid metabolism during the molting cycle of the Chinese mitten crab Eriocheir sinensis
    Li Z, Zhang G, Pan K, Niu X, Shu-Chien AC, Chen T, et al.
    Comp Biochem Physiol A Mol Integr Physiol, 2023 Oct;284:111474.
    PMID: 37406959 DOI: 10.1016/j.cbpa.2023.111474
    Crustacean molting is highly related to energy and lipid metabolism. This study was conducted to detect the changes of total lipids (TL), triacylglyceride (TAG), phospholipid (PL) and lipid droplets in hepatopancreas, and then to investigate the gene expression patterns related to hepatopancreatic lipid metabolism during the molting cycle of Chinese mitten crab Eriocheir sinensis. Hepatopancreatic TL and TAG increased significantly from post-molt stage to pre-molt stage, then decreased significantly from pre-molt stage to ecdysis stage, which is consistent to the changes of neutral lipid-rich adipocytes in hepatopancreas. By transcriptomic analysis, 65,325 transcripts were sequenced and assembled, and 28,033 transcripts were annotated. Most genes were related to energy metabolism, and the enriched genes were involved in carbohydrate and lipid metabolism and biosynthesis, especially in de novo synthesis of fatty acids and TAG, and ketone body production. Compared to the inter-molt stages, acetyl-CoA carboxylase, fatty acid synthase and other genes related to the synthesis of fatty acids were upregulated in the pre-molt stage. TAG synthesis related genes, including Glycerol-3-phosphate acyltransferase and 1-acylglycerol-3-phosphate acyltransferases, were upregulated in the post-molt stage compared to the inter-molt stage. The expression of ketone body-related genes had no significant changes during the molting cycle. Compared to the TAG synthetic pathway, ketone body biosynthesis may contribute less/secondarily to fatty acid metabolic processes, which could be involved in the other physiological processes or metabolism. In conclusion, these results showed that TAG is the major lipid deposition during inter- and pre-molt stages, and the most genes are related to the fatty acids and TAG metabolism in the hepatopancreas during the molting cycle of E. sinensis.
  14. Phylogenetic classification and palm-inflorescence anthophily of the Colocasiomyia zeylanica species group (Diptera: Drosophilidae), with descriptions of five new species
    Zhang G, Gao JJ, Takano KT, Yafuso M, Suwito A, Meleng PA, et al.
    Zootaxa, 2023 May 05;5278(2):201-238.
    PMID: 37518286 DOI: 10.11646/zootaxa.5278.2.1
    The zeylanica group is one of the six species groups of the anthophilic genus Colocasiomyia de Meijere in the family Drosophilidae. In addition to two known species, five morphospecies have been recognized as members of this species group but left undescribed formally. In this study, species delimitation of these putatively new species was determined by barcoding of the mitochondrial COI (cytochrome c oxydase subunit I) gene and morphological comparison. Phylogenetic relationships within the genus Colocasiomyia were inferred by a cladistic analysis of 89 morphological characters. Based on the results of these analyses, we redefined the zeylanica species group and established two subgroups within it: the zeylanica subgroup comprised of C. zeylanica, C. nepalensis, C. pinangae sp. nov., C. besaris sp. nov. and C. luciphila sp. nov., and the oligochaeta subgroup of C. oligochaeta sp. nov. and C. grimaldii sp. nov. In addition, we briefly address the anthophilic habits of drosophilid flies using palm (Arecaceae) inflorescences, especially of the zeylanica group, compiling scattered collection records from the Oriental and Papuan regions.
  15. Fulltext A bibliometric of publication trends in medical image segmentation: Quantitative and qualitative analysis
    Zhang B, Rahmatullah B, Wang SL, Zhang G, Wang H, Ebrahim NA
    J Appl Clin Med Phys, 2021 Oct;22(10):45-65.
    PMID: 34453471 DOI: 10.1002/acm2.13394
    PURPOSE: Medical images are important in diagnosing disease and treatment planning. Computer algorithms that describe anatomical structures that highlight regions of interest and remove unnecessary information are collectively known as medical image segmentation algorithms. The quality of these algorithms will directly affect the performance of the following processing steps. There are many studies about the algorithms of medical image segmentation and their applications, but none involved a bibliometric of medical image segmentation.

    METHODS: This bibliometric work investigated the academic publication trends in medical image segmentation technology. These data were collected from the Web of Science (WoS) Core Collection and the Scopus. In the quantitative analysis stage, important visual maps were produced to show publication trends from five different perspectives including annual publications, countries, top authors, publication sources, and keywords. In the qualitative analysis stage, the frequently used methods and research trends in the medical image segmentation field were analyzed from 49 publications with the top annual citation rates.

    RESULTS: The analysis results showed that the number of publications had increased rapidly by year. The top related countries include the Chinese mainland, the United States, and India. Most of these publications were conference papers, besides there are also some top journals. The research hotspot in this field was deep learning-based medical image segmentation algorithms based on keyword analysis. These publications were divided into three categories: reviews, segmentation algorithm publications, and other relevant publications. Among these three categories, segmentation algorithm publications occupied the vast majority, and deep learning neural network-based algorithm was the research hotspots and frontiers.

    CONCLUSIONS: Through this bibliometric research work, the research hotspot in the medical image segmentation field is uncovered and can point to future research in the field. It can be expected that more researchers will focus their work on deep learning neural network-based medical image segmentation.

  16. Fulltext Highly Diverse Synechococcus Pigment Types in the Eastern Indian Ocean
    Zhang X, Cheung S, Wang J, Zhang G, Wei Y, Liu H, et al.
    Front Microbiol, 2022;13:806390.
    PMID: 35283844 DOI: 10.3389/fmicb.2022.806390
    Marine picocyanobacteria Synechococcus exhibit highly diverse pigment types (PTs) and hence possess great advantage to utilize different spectrum of light effectively and to occupy a wide range of light niches. In this study, we explored the diversity of Synechococcus PTs in the eastern Indian Ocean (EIO), surface water of Strait of Malacca (SSM), and coastal waters of Sri Lanka (SSL). All the detected PTs were phycourobilin (PUB) containing PT 3 and showed distinct distribution patterns. Low PUB PT 3a and partial chromatic acclimater PT 3eA dominated in coastal and shallow waters (SSM and SSL). In contrast, high PUB and chromatic acclimaters PT 3dA and PT 3c/3dB were mainly distributed in open ocean (EIO). PT 3dA and PT 3c/3dB occurred at similar depths of the lower euphotic layers but showed distinct distribution pattern that are partially exclusive, indicating that they compete with each other for the same light niche. Interestingly, the newly described PT 3f was detected with high relative abundances at all stations and particularly dominated in the upper euphotic layer in EIO, which was confirmed with PT-specific quantitative polymerase chain reaction (qPCR). The relative abundance of PT 3f was negatively correlated with nutrient level, implying that PT 3f is adapted to oligotrophic waters. Pronounced niche partition of different PTs was observed in the upper and lower layers of euphotic zone in EIO and SSM/SSL. Light, nutrients, and strong stratification may play important roles in the niche partition of different PTs. Further analysis about ecologically significant taxonomic units revealed high diversity within each PT at different locations, which provided insights for understanding specific PT with wide range of niches.
  17. Fulltext Temperature vegetation dryness index (TVDI) for drought monitoring in the Guangdong Province from 2000 to 2019
    Chen A, Jiang J, Luo Y, Zhang G, Hu B, Wang X, et al.
    PeerJ, 2023;11:e16337.
    PMID: 38130929 DOI: 10.7717/peerj.16337
    Drought monitoring is crucial for assessing and mitigating the impacts of water scarcity on various sectors and ecosystems. Although traditional drought monitoring relies on soil moisture data, remote sensing technology has have significantly augmented the capabilities for drought monitoring. This study aims to evaluate the accuracy and applicability of two temperature vegetation drought indices (TVDI), TVDINDVI and TVDIEVI, constructed using the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) vegetation indices for drought monitoring. Using Guangdong Province as a case, enhanced versions of these indices, developed through Savitzky-Golay filtering and terrain correction were employed. Additionally, Pearson correlation analysis and F-tests were utilized to determine the suitability of the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) in correlation with TVDINDVI and TVDIEVI. The results show that TVDINDVI had more meteorological stations passing both significance test levels (P 
  18. Alzheimer's disease prediction algorithm based on de-correlation constraint and multi-modal feature interaction
    Cheng J, Wang H, Wei S, Mei J, Liu F, Zhang G
    Comput Biol Med, 2024 Mar;170:108000.
    PMID: 38232453 DOI: 10.1016/j.compbiomed.2024.108000
    Alzheimer's disease (AD) is a neurodegenerative disease characterized by various pathological changes. Utilizing multimodal data from Fluorodeoxyglucose positron emission tomography(FDG-PET) and Magnetic Resonance Imaging(MRI) of the brain can offer comprehensive information about the lesions from different perspectives and improve the accuracy of prediction. However, there are significant differences in the feature space of multimodal data. Commonly, the simple concatenation of multimodal features can cause the model to struggle in distinguishing and utilizing the complementary information between different modalities, thus affecting the accuracy of predictions. Therefore, we propose an AD prediction model based on de-correlation constraint and multi-modal feature interaction. This model consists of the following three parts: (1) The feature extractor employs residual connections and attention mechanisms to capture distinctive lesion features from FDG-PET and MRI data within their respective modalities. (2) The de-correlation constraint function enhances the model's capacity to extract complementary information from different modalities by reducing the feature similarity between them. (3) The mutual attention feature fusion module interacts with the features within and between modalities to enhance the modal-specific features and adaptively adjust the weights of these features based on information from other modalities. The experimental results on ADNI database demonstrate that the proposed model achieves a prediction accuracy of 86.79% for AD, MCI and NC, which is higher than the existing multi-modal AD prediction models.
  19. Fulltext Frequency regulation of interconnected hybrid power system with Assimilation of electrical vehicles
    Daraz A, Khan IA, Basit A, Malik SA, AlQahtani SA, Zhang G
    Heliyon, 2024 Mar 30;10(6):e28073.
    PMID: 38524527 DOI: 10.1016/j.heliyon.2024.e28073
    Recent widespread connections of renewable energy resource (RESs) in place of fossil fuel supplies and the adoption of electrical vehicles in place of gasoline-powered vehicles have given birth to a number of new concerns. The control architecture of linked power networks now faces an increasingly pressing challenge: tie-line power fluctuations and reducing frequency deviations. Because of their nature and dependence on external circumstances, RESs are analogous to continually fluctuating power generators. Using a fractional order-based frequency regulator, this work presents a new method for improving the frequency regulation in a two-area interconnected power system. In order to deal with the frequency regulation difficulties of the hybrid system integrated with RES, the suggested controller utilizes the modified form of fractional order proportional integral derivative (FOPID) controller known as FOI-PDN controller. The new proposed controllers are designed using the white shark optimizer (WSO), a current powerful bioinspired meta heuristic algorithm which has been motivated by the learning abilities of white sharks when actively hunting in the environment. The suggested FOI-PDN controller's performance was compared to that of various control methodologies such as FOPID, and PID. Furthermore, the WSO findings are compared to those of other techniques such as the salp swarm algorithm, sine cosine algorithm and fitness dependent optimizer. The recommended controller and design approach have been tested and validated at different loading conditions and different circumstances, as well as their robustness against system parameter suspicions. The simulation outcomes demonstrate that the WSO-based tuned FOI-PDN controller successfully reduces peak overshoot by 73.33%, 91.03%, and 77.21% for region-2, region-1, and link power variation respectively, and delivers minimum undershoot of 89.12%, 83.11%, and 78.10% for both regions and tie-line. The obtained findings demonstrate the new proposed controller's stable function and frequency controlling performance with optimal controller parameters and without the requirement for a sophisticated design process.
  20. Fulltext Metabolic Response in Rats following Electroacupuncture or Moxibustion Stimulation
    Xu J, Lin X, Cheng KK, Zhong H, Liu M, Zhang G, et al.
    Evid Based Complement Alternat Med, 2019;2019:6947471.
    PMID: 31186665 DOI: 10.1155/2019/6947471
    Electroacupuncture and moxibustion are traditional Chinese medicine practices that exert therapeutic effects through stimulation of specific meridian acupoints. However, the biological basis of the therapies has been difficult to establish; thus the current practices still rely on ancient TCM references. Here, we used a rat model to study perturbations in cortex, liver, and stomach metabolome and plasma hormones following electroacupuncture or moxibustion treatment on either stomach meridian or gallbladder meridian acupoints. All treatment groups, regardless of meridian and mode of treatment, showed perturbation in cortex metabolome and increased phenylalanine, tyrosine, and branched-chain amino acids in liver. In addition, electroacupuncture was found to increase ATP in cortex, creatine, and dimethylglycine in stomach and GABA in liver. On the other hand, moxibustion increased plasma enkephalin concentration, as well as betaine and fumarate concentrations in stomach. Furthermore, we had observed meridian-specific changes including increased N-acetyl-aspartate in liver and 3-hydroxybutyrate in stomach for gallbladder meridian stimulation and increased noradrenaline concentration in blood plasma following stimulation on stomach meridian. In summary, the current findings may provide insight into the metabolic basis of electroacupuncture and moxibustion, which may contribute towards new application of acupoint stimulation.
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