Displaying publications 81 - 100 of 847 in total

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  1. Lu B, Natarajan E, Balaji Raghavendran HR, Markandan UD
    Technol Cancer Res Treat, 2023;22:15330338221145246.
    PMID: 36601658 DOI: 10.1177/15330338221145246
    Breast cancer is the most common malignancy and the second most common cause of cancer-related mortality in women. Triple-negative breast cancers do not express estrogen receptors, progesterone receptors, or human epidermal growth factor receptor 2 and have a higher recurrence rate, greater metastatic potential, and lower overall survival rate than those of other breast cancers. Treatment of triple-negative breast cancer is challenging; molecular-targeted therapies are largely ineffective and there is no standard treatment. In this review, we evaluate current attempts to classify triple-negative breast cancers based on their molecular features. We also describe promising treatment methods with different advantages and discuss genetic biomarkers and other prediction tools. Accurate molecular classification of triple-negative breast cancers is critical for patient risk categorization, treatment decisions, and surveillance. This review offers new ideas for more effective treatment of triple-negative breast cancer and identifies novel targets for drug development.
  2. Huang Z, Wang J, Lu X, Mohd Zain A, Yu G
    Brief Bioinform, 2023 Mar 19;24(2).
    PMID: 36733262 DOI: 10.1093/bib/bbad040
    Single-cell RNA sequencing (scRNA-seq) data are typically with a large number of missing values, which often results in the loss of critical gene signaling information and seriously limit the downstream analysis. Deep learning-based imputation methods often can better handle scRNA-seq data than shallow ones, but most of them do not consider the inherent relations between genes, and the expression of a gene is often regulated by other genes. Therefore, it is essential to impute scRNA-seq data by considering the regional gene-to-gene relations. We propose a novel model (named scGGAN) to impute scRNA-seq data that learns the gene-to-gene relations by Graph Convolutional Networks (GCN) and global scRNA-seq data distribution by Generative Adversarial Networks (GAN). scGGAN first leverages single-cell and bulk genomics data to explore inherent relations between genes and builds a more compact gene relation network to jointly capture the homogeneous and heterogeneous information. Then, it constructs a GCN-based GAN model to integrate the scRNA-seq, gene sequencing data and gene relation network for generating scRNA-seq data, and trains the model through adversarial learning. Finally, it utilizes data generated by the trained GCN-based GAN model to impute scRNA-seq data. Experiments on simulated and real scRNA-seq datasets show that scGGAN can effectively identify dropout events, recover the biologically meaningful expressions, determine subcellular states and types, improve the differential expression analysis and temporal dynamics analysis. Ablation experiments confirm that both the gene relation network and gene sequence data help the imputation of scRNA-seq data.
  3. Yang D, Lee YY, Lu Y, Wang Y, Zhang Z
    Molecules, 2024 Apr 18;29(8).
    PMID: 38675667 DOI: 10.3390/molecules29081847
    The process of lipid crystallization influences the characteristics of lipid. By changing the chemical composition of the lipid system, the crystallization behavior could be controlled. This review elucidates the internal factors affecting lipid crystallization, including triacylglycerol (TAG) structure, TAG composition, and minor components. The influence of these factors on the TAG crystal polymorphic form, nanostructure, microstructure, and physical properties is discussed. The interplay of these factors collectively influences crystallization across various scales. Variations in fatty acid chain length, double bonds, and branching, along with their arrangement on the glycerol backbone, dictate molecular interactions within and between TAG molecules. High-melting-point TAG dominates crystallization, while liquid oil hinders the process but facilitates polymorphic transitions. Unique molecular interactions arise from specific TAG combinations, yielding molecular compounds with distinctive properties. Nanoscale crystallization is significantly impacted by liquid oil and minor components. The interaction between the TAG and minor components determines the influence of minor components on the crystallization process. In addition, future perspectives on better design and control of lipid crystallization are also presented.
  4. Xu F, Jiang SJ, Ge PP, Yang J, Lu S
    Nurs Open, 2024 May;11(5):e2178.
    PMID: 38757435 DOI: 10.1002/nop2.2178
    AIM: This Study Aimed to Assess the Intention to Have a Third Child among Millennial Parents (25-40 years old) with Two Children in a City in Eastern China and to Explore the Influencing Factors Related to Fertility Intention.

    DESIGN: A cross-sectional design study.

    METHODS: A convenience sampling method was used to enrol participants of childbearing age who visited two tertiary hospitals in Hang zhou, a city in eastern China, from June 2021 to March 2022. We conducted a face-to-face questionnaire survey with 520 participants and calculated the prevalence of intention-related factors. Multivariate logistic regression was used to analyse the independent influencing factors of fertility intention.

    RESULTS: In total, 105 (20.2%) participants had the intention to have a third child. The results showed that 'employment status', 'age', 'reasons for wanting a third child', the considered 'biggest barrier to having a third child', 'views on the three-child policy', 'desired free services', 'supporting work policies' and 'assistance policies' were significant independent influencing factors of intention to have a third child (p-value 

  5. Nurgazina Z, Ullah A, Ali U, Koondhar MA, Lu Q
    Environ Sci Pollut Res Int, 2021 Nov;28(42):60195-60208.
    PMID: 34155588 DOI: 10.1007/s11356-021-14930-2
    Globally, the rising concentration of anthropogenic greenhouse gases emission in the atmosphere is extremely detrimental to the environment. The high concentration among all greenhouse gases is carbon dioxide emission. Therefore, this study explores the linkages between energy consumption, trade openness, globalization, urbanization, and carbon dioxide emission for Malaysia over the spans from 1978 to 2018. ARDL bound testing model was employed to investigate involvement in the elevation of carbon dioxide emissions in the economy. The study illustrates that a 1% growth in energy consumption, trade openness, and urbanization will deteriorate the environment by 0.18%, 0.03%, and 2.51% respectively. Further, variance decomposition analysis predicts that all the determinants in the study have significantly caused carbon dioxide emission in Malaysia. The paper presents scientific support for further studies and argues for the use of innovation shocks as a policy instrument for a prosperous future by formulating more successful environmental policies.
  6. Zhou Y, Che CC, Chong MC, Zhao H, Lu Y
    Support Care Cancer, 2023 May 30;31(6):361.
    PMID: 37249639 DOI: 10.1007/s00520-023-07826-z
    PURPOSE: Literature on marital self-disclosure interventions for cancer patients lacks consistency in methodology and content. Moreover, the impact of such interventions on physical and psychological health, marital relationships, and self-disclosure ability is controversial. This review aims to systematically analyze the studies of marital self-disclosure intervention, synthesize the structure and topics of marital self-disclosure, and summarize and evaluate its effects on improving physical and psychological outcomes and marital relationships in cancer patients and their spouses.

    METHOD: This systematic review used the preferred reporting items of Systematic Reviews and Meta-Analyses (PRISMA). We conducted a systematic review of randomized controlled and quasi-experimental studies published from the establishment of the database to October 2022. Marital self-disclosure interventions were conducted with both cancer patients and their spouses. Studies published in a language other than English or Chinese, and studies below a quality grade of C were excluded. Data were extracted through a standardized data collection form, and two reviewers independently extracted and evaluated the data. The quality of the included studies was assessed using the Cochrane Handbook of Systematic Reviews of Interventions, and a third reviewer adjudicated in case of disagreement. The data were synthesized by vote counting based on direction of effect according to the Synthesis Without Meta-analysis (SWiM) reporting guideline.

    RESULTS: Thirteen studies were included in the review. Based on quality evaluation, three studies were categorized as grade A (good), and ten studies were grade B (moderate). Seven studies reported moderate rates of participant refusal and attrition. The structure and topics of marital self-disclosure varied across different studies. The five studies had various prespecified disclosure topics, such as fear of cancer recurrence, benefit finding, and emotional distress. The overall results suggest that marital self-disclosure interventions can improve physical and psychological health, enhance marital relationships, and increase self-disclosure ability.

    CONCLUSION: The limited number of studies, small sample sizes, diverse intervention strategies, and methodological heterogeneity weakened the evidence base for the effectiveness of marital self-disclosure interventions. Therefore, further high-quality randomized controlled trials (RCTs) are recommended to confirm the effectiveness of such interventions. These studies should also evaluate the interventions' long-term impact, analyze optional topics and methods, identify key features, and explore the development of the best intervention program.

  7. Thain BK, Lu R, Fitzpatrick C, Richardson D
    Int J STD AIDS, 2024 Mar;35(3):164-168.
    PMID: 37938931 DOI: 10.1177/09564624231213113
    BACKGROUND: There is little research exploring harm reduction interventions for men who have sex with men (MSM) who engage in chemsex. Beyond-66 is a novel, 132-day, peer-led intervention programme for MSM who are chemsex dependent in Kuala Lumpur, Malaysia. We aimed to evaluate the feasibility, retention and effect of Beyond-66 on: abstinence from chemsex, motivation for abstinence, and mental wellbeing.

    METHOD: We collected data on demographics, retention and completion and abstinence between January 2021-August 2023 in MSM using Beyond-66. Using 10-point Likert scales, we compared motivation to remain abstinent and mental wellbeing at the beginning and end of Beyond-66.

    RESULTS: 25 MSM have either completed or dropped out/referred out of Beyond-66, 12/25(48%) were living with HIV and the median duration of chemsex use was 5 years (IQR = 4-6). 19 (76%) completed programme; 3 were referred out for a psychiatry assessment and 3 dropped out of the programme. 14 (74%) remain abstinent and 5 relapsed. The median motivation for abstinence scores for the 19 completers increased significantly between the pre-programme and post-programme period (7/10 (IQR = 4-8) to 9/10 (IQR = 5-10), p = .04) and the median mental health score (Likert score out of 10 where 10 is poor mental health) reduced significantly (5/10 (IQR = 4-7) to 2/10 (IQR 1-6), p = .008).

    CONCLUSION: This pilot evaluation suggests that MSM using Beyond-66 experience high completion (76%) and abstinence (74%) rates and increased motivation for abstinence and mental wellbeing scores. Further research is needed to design, develop, and deliver peer led interventions for MSM who are chemsex dependant.

  8. Lu AY, Gustin A, Newhouse D, Gale M
    J Virol, 2023 May 31;97(5):e0198222.
    PMID: 37162358 DOI: 10.1128/jvi.01982-22
    Asian lineage Zika virus (ZIKV) strains emerged globally, causing outbreaks linked with critical clinical disease outcomes unless the virus is effectively restricted by host immunity. We have previously shown that retinoic acid-inducible gene-I (RIG-I) senses ZIKV to trigger innate immunity to direct interferon (IFN) production and antiviral responses that can control ZIKV infection. However, ZIKV proteins have been demonstrated to antagonize IFN. Here, we conducted in vitro analyses to assess how divergent prototypic ZIKV variants differ in virologic properties, innate immune regulation, and infection outcome. We comparatively assessed African lineage ZIKV/Dakar/1984/ArD41519 (ZIKV/Dakar) and Asian lineage ZIKV/Malaysia/1966/P6740 (ZIKV/Malaysia) in a human epithelial cell infection model. De novo viral sequence determination identified amino acid changes within the ZIKV/Dakar genome compared to ZIKV/Malaysia. Viral growth analyses revealed that ZIKV/Malaysia accumulated viral proteins and genome copies earlier and to higher levels than ZIKV/Dakar. Both ZIKV strains activated RIG-I/IFN regulatory factor (IRF3) and NF-κB pathways to induce inflammatory cytokine expression and types I and III IFNs. However, ZIKV/Malaysia, but not ZIKV/Dakar, potently blocked downstream IFN signaling. Remarkably, ZIKV/Dakar protein accumulation and genome replication were rescued in RIG-I knockout (KO) cells late in acute infection, resulting in ZIKV/Dakar-mediated blockade of IFN signaling. We found that RIG-I signaling specifically restricts viral protein accumulation late in acute infection where early accumulation of viral proteins in infected cells confers enhanced ability to limit IFN signaling, promoting viral replication and spread. Our results demonstrate that RIG-I-mediated innate immune signaling imparts restriction of ZIKV protein accumulation, which permits IFN signaling and antiviral actions controlling ZIKV infection. IMPORTANCE ZIKV isolates are classified under African or Asian lineages. Infection with emerging Asian lineage-derived ZIKV strains is associated with increased incidence of neurological symptoms that were not previously reported during infection with African or preemergent Asian lineage viruses. In this study, we utilized in vitro models to compare the virologic properties of and innate immune responses to two prototypic ZIKV strains from distinct lineages: African lineage ZIKV/Dakar and Asian lineage ZIKV/Malaysia. Compared to ZIKV/Dakar, ZIKV/Malaysia accumulates viral proteins earlier, replicates to higher levels, and robustly blocks IFN signaling during acute infection. Early accumulation of ZIKV/Malaysia NS5 protein confers enhanced ability to antagonize IFN signaling, dampening innate immune responses to promote viral spread. Our data identify the kinetics of viral protein accumulation as a major regulator of host innate immunity, influencing host-mediated control of ZIKV replication and spread. Importantly, these findings provide a novel framework for evaluating the virulence of emerging variants.
  9. Wang Z, Ghaleb FA, Zainal A, Siraj MM, Lu X
    Sci Rep, 2024 Mar 25;14(1):7054.
    PMID: 38528084 DOI: 10.1038/s41598-024-57691-x
    Many intrusion detection techniques have been developed to ensure that the target system can function properly under the established rules. With the booming Internet of Things (IoT) applications, the resource-constrained nature of its devices makes it urgent to explore lightweight and high-performance intrusion detection models. Recent years have seen a particularly active application of deep learning (DL) techniques. The spiking neural network (SNN), a type of artificial intelligence that is associated with sparse computations and inherent temporal dynamics, has been viewed as a potential candidate for the next generation of DL. It should be noted, however, that current research into SNNs has largely focused on scenarios where limited computational resources and insufficient power sources are not considered. Consequently, even state-of-the-art SNN solutions tend to be inefficient. In this paper, a lightweight and effective detection model is proposed. With the help of rational algorithm design, the model integrates the advantages of SNNs as well as convolutional neural networks (CNNs). In addition to reducing resource usage, it maintains a high level of classification accuracy. The proposed model was evaluated against some current state-of-the-art models using a comprehensive set of metrics. Based on the experimental results, the model demonstrated improved adaptability to environments with limited computational resources and energy sources.
  10. Woi PJ, Lu JYL, Hairol MI, Ibrahim WNA
    Int J Ophthalmol, 2024;17(2):353-358.
    PMID: 38371264 DOI: 10.18240/ijo.2024.02.19
    AIM: To compare the vergence mechanisms between good and poor sleepers in university students.

    METHODS: A total of 64 university students were recruited in this study. The validated Malay version of Pittsburgh Sleep Quality Index questionnaire (PSQI-M) was used to measure the participants' sleep quality over the past month. Participants were categorized as good sleepers (n=32) and poor sleepers (n=32) based on the PSQI-M scores. Heterophoria and fusional vergences were measured at distance and near. Mann-Whitney U test was used to compare heterophoria, negative fusional vergence (NFV), and positive fusional vergence (PFV) at distance and near between good and poor sleepers. Spearman correlation analysis was used to study the relationship between PSQI-M score and PFV at distance.

    RESULTS: Both distance and near heterophorias were not significantly different between good and poor sleepers (P>0.05). There was a difference in distance PFV (P<0.05) between good and poor sleepers, but not in distance NFV, near NFV, and near PFV (P>0.05). Distance PFV was negatively correlated with PSQI-M score (rs=-0.33, P<0.05).

    CONCLUSION: University students with poor sleep quality demonstrates a reduced ability to maintain fusion with increasing convergence demand at distance. Sleep quality assessment during binocular vision examination in university students is recommended.

  11. Ren H, Zhou D, Lu J, Show PL, Sun FF
    Environ Sci Pollut Res Int, 2023 Jul;30(32):78030-78040.
    PMID: 37311860 DOI: 10.1007/s11356-023-27850-0
    Microalgae CO2 sequestration has gained considerable attention in the last three decades as a promising technology to slow global warming caused by CO2 emissions. To provide a comprehensive and objective analysis of the research status, hot spots, and frontiers of CO2 fixation by microalgae, a bibliometric approach was recently chosen for review. In this study, 1561 articles (1991-2022) from the Web of Science (WOS) on microalgae CO2 sequestration were screened. A knowledge map of the domain was presented using VOSviewer and CiteSpace. It visually demonstrates the most productive journals (Bioresource Technology), countries (China and USA), funding sources, and top contributors (Cheng J, Chang JS, and their team) in the field of CO2 sequestration by microalgae. The analysis also revealed that research hotspots changed over time and that recent research has focused heavily on improving carbon sequestration efficiency. Finally, commercialization of carbon fixation by microalgae is a key hurdle, and supports from other disciplines could improve carbon sequestration efficiency.
  12. Lu J, Abd Rahman NA, Wyon M, Shaharudin S
    PLoS One, 2024;19(4):e0301236.
    PMID: 38640093 DOI: 10.1371/journal.pone.0301236
    BACKGROUND: Fundamental physical functions such as postural control and balance are vital in preserving everyday life, affecting an individual's quality of life. Dance is a physical activity that offers health advantages across various life stages. Nevertheless, the effects of dance interventions on physical function, postural control, and quality of life among older adults have remained underexplored. The review aimed to examine the strength of evidence for dance interventions on physical function and quality of life among middle-aged and older adults.

    METHODS: A systematic review was conducted across four databases (PubMed, Cochrane Library, Web of Science, and Medline), focusing on studies involving more than four weeks of dance interventions. MeSH terms [dance or dance intervention or dance rehabilitation or dance movement] and [motor function or functional capacity or postural control or functional mobility or mobility or postural balance or balance or flexibility or gait] and [well-being or quality of life or life satisfaction] were utilized in the search. This review was registered in the PROSPERO database (CRD42023422857). Included studies were assessed using the Cochrane Risk of Bias.

    RESULTS: The search revealed 885 studies, and 16 met the inclusion criteria. The effects of various dance genres on physical functions and quality of life were compared. Most studies showed that dance intervention improved physical function, balance, postural control and quality of life. Dance intervention showed a high level of adherence compared to physiotherapy, self-care, conventional therapy, and aerobic and resistance exercise.

    CONCLUSION: In terms of improving physical function and quality of life, structured dance is a safe and relatively effective alternative to exercise. Note the effect of movement selection and intensity in the dance interventions. Dance with music may increase participants' interest, encouraging more physical activity among middle-aged and older adults.

  13. Zhang Z, Zhang H, Zhang Z, Sandai D, Lu P, Zhang H, et al.
    Front Immunol, 2024;15:1483498.
    PMID: 39555060 DOI: 10.3389/fimmu.2024.1483498
    BACKGROUND: Cell death mechanisms are integral to the pathogenesis of breast cancer (BC), with ATP-induced cell death (AICD) attracting increasing attention due to its distinctive specificity and potential therapeutic applications.

    METHODS: This study employed genomic methodologies to investigate the correlation between drug sensitivity and types of AICD in BC. Initially, data from TCGA were utilized to construct a prognostic model and classification system for AICD. Subsequently, a series of bioinformatics analyses assessed the prognostic and clinical significance of this model within the context of BC.

    RESULTS: Analysis revealed a cohort of 18 genes associated with AICD, exhibiting prognostic relevance. Survival analyses indicated that overall survival rates were significantly lower in high-risk populations compared to their low-risk counterparts. Furthermore, prognostic indicators linked to AICD demonstrated high accuracy in predicting survival outcomes in BC. Immunological assessments indicated heightened expression of anti-tumor infiltrating immune cells and immune checkpoint molecules in low-risk populations, correlating with various anti-tumor immune functions. Ultimately, a comprehensive prognostic model related to AICD was developed through univariate analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis. As Adenosine triphosphate (ATP) concentration increased, the viability of BC cells exhibited a general decline at each time point. Notably, ATP diminished the mitochondrial membrane potential in BC cells while enhancing it in normal breast epithelial cells. Additionally, ATP inhibited the migration of BC cells and promoted their apoptosis. ATP also stimulated reactive oxygen species (ROS) production in MCF-10A cells, with implications for the immune response in BC cells. Compared to the control group, expression levels of CLIC6, SLC1A1, and CEMIP were significantly reduced in the ATP intervention group, whereas ANO6 expression was elevated. ANO6, CEMIP, and CLIC6 share genetic variants with BC, while SLC1A1 does not exhibit genetic causal variation with the disease.

    CONCLUSION: A valuable prognostic model associated with AICD has been established, capable of accurately predicting BC prognosis. The induction of cell death by ATP appears to play a protective role in BC progression. These findings carry significant implications for the implementation of personalized and tailored treatment strategies for BC patients.

  14. Yu X, Lu L, Guo J, Qin H, Ji C
    Comput Math Methods Med, 2022;2022:4168619.
    PMID: 35087601 DOI: 10.1155/2022/4168619
    Since December 2019, a novel coronavirus (COVID-19) has spread all over the world, causing unpredictable economic losses and public fear. Although vaccines against this virus have been developed and administered for months, many countries still suffer from secondary COVID-19 infections, including the United Kingdom, France, and Malaysia. Observations of COVID-19 infections in the United Kingdom and France and their governance measures showed a certain number of similarities. A further investigation of these countries' COVID-19 transmission patterns suggested that when a turning point appeared, the values of their stringency indices per population density (PSI) were nearly proportional to their absolute infection rate (AIR). To justify our assumptions, we developed a mathematical model named VSHR to predict the COVID-19 turning point for Malaysia. VSHR was first trained on 30-day infection records prior to the United Kingdom, Germany, France, and Belgium's known turning points. It was then transferred to Malaysian COVID-19 data to predict this nation's turning point. Given the estimated AIR parameter values in 5 days, we were now able to locate the turning point's appearance on June 2nd, 2021. VSHR offered two improvements: (1) gathered countries into groups based on their SI patterns and (2) generated a model to identify the turning point for a target country within 5 days with 90% CI. Our research on COVID-19's turning point for a country is beneficial for governments and clinical systems against future COVID-19 infections.
  15. Lu W, Liu H, Ma H, Tan TP, Xia L
    Front Hum Neurosci, 2023;17:1280241.
    PMID: 38034069 DOI: 10.3389/fnhum.2023.1280241
    Emotion recognition constitutes a pivotal research topic within affective computing, owing to its potential applications across various domains. Currently, emotion recognition methods based on deep learning frameworks utilizing electroencephalogram (EEG) signals have demonstrated effective application and achieved impressive performance. However, in EEG-based emotion recognition, there exists a significant performance drop in cross-subject EEG Emotion recognition due to inter-individual differences among subjects. In order to address this challenge, a hybrid transfer learning strategy is proposed, and the Domain Adaptation with a Few-shot Fine-tuning Network (DFF-Net) is designed for cross-subject EEG emotion recognition. The first step involves the design of a domain adaptive learning module specialized for EEG emotion recognition, known as the Emo-DA module. Following this, the Emo-DA module is utilized to pre-train a model on both the source and target domains. Subsequently, fine-tuning is performed on the target domain specifically for the purpose of cross-subject EEG emotion recognition testing. This comprehensive approach effectively harnesses the attributes of domain adaptation and fine-tuning, resulting in a noteworthy improvement in the accuracy of the model for the challenging task of cross-subject EEG emotion recognition. The proposed DFF-Net surpasses the state-of-the-art methods in the cross-subject EEG emotion recognition task, achieving an average recognition accuracy of 93.37% on the SEED dataset and 82.32% on the SEED-IV dataset.
  16. Wang Y, Lu Y, Tian X, Liu Y, Ma W
    Heliyon, 2024 Feb 15;10(3):e25060.
    PMID: 38314296 DOI: 10.1016/j.heliyon.2024.e25060
    Previous research has identified a negative association between mobile phone addiction and time management disposition among college students; however, the direction of this relationship remains divergent. This study utilized a cross-lagged panel model to elucidate the directionality of the relationship between mobile phone addiction and time management disposition. A total of 466 college students completed two measures at seven-month intervals. The findings revealed a prevalence of mobile phone addiction at 10.94 % and 13.73 % in the two surveys. Notably, both mobile phone addiction and time management disposition demonstrated stability over time. Furthermore, a discernible negative bidirectional relationship was observed between the two. The present findings underscore the importance of timely intervention for college students facing challenges in mobile phone usage and time management.
  17. Zhang J, Lu G, Skitmore M, Ballesteros-Pérez P
    Environ Sci Pollut Res Int, 2021 Jul;28(27):35392-35405.
    PMID: 34018106 DOI: 10.1007/s11356-021-14467-4
    The current world economy needs to undergo a green transformation. Green total factor productivity provides the basis for judging whether a country or region can attain long-term sustainable development. However, there is little research into the factors that influence green total factor productivity and this has become an obstacle in the transition to a greener economy. On filtering relevant articles and interviews data collected from 2009 to 2019, open decoding, spindle decoding, and selective decoding are carried out to classify research conducted into green total factor productivity. From this analysis, cutting-edge research and knowledge gaps in green total factor productivity are identified. Also, an influencing factor model of green total factor productivity is built. Findings suggest that technical, economic, and government are the three main research streams involved in this transformation process. In particular, technology plays a decisive role, economy plays a guaranteeing role, and government plays a regulatory role. Moreover, the impact of these factors cannot be isolated, as each influence and mediate the other two. Results from this study will help further popularize green total factor productivity and provide a new starting point for reducing energy consumption and environmental pollution.
  18. Yao S, Wu Q, Kang Q, Chen YW, Lu Y
    Risk Anal, 2024 Feb;44(2):459-476.
    PMID: 37330273 DOI: 10.1111/risa.14175
    The Northern Sea Route (NSR) makes travel between Europe and Asia shorter and quicker than a southern transit via the Strait of Malacca and Suez Canal. It provides greater access to Arctic resources such as oil and gas. As global warming accelerates, melting Arctic ice caps are likely to increase traffic in the NSR and enhance its commercial viability. Due to the harsh Arctic environment imposing threats to the safety of ship navigation, it is necessary to assess Arctic navigation risk to maintain shipping safety. Currently, most studies are focused on the conventional assessment of the risk, which lacks the validation based on actual data. In this study, actual data about Arctic navigation environment and related expert judgments were used to generate a structured data set. Based on the structured data set, extreme gradient boosting (XGBoost) and alternative methods were used to establish models for the assessment of Arctic navigation risk, which were validated using cross-validation. The results show that compared with alternative models, XGBoost models have the best performance in terms of mean absolute errors and root mean squared errors. The XGBoost models can learn and reproduce expert judgments and knowledge for the assessment of Arctic navigation risk. Feature importance (FI) and shapley additive explanations (SHAP) are used to further interpret the relationship between input data and predictions. The application of XGBoost, FI, and SHAP is aimed to improve the safety of Arctic shipping using advanced artificial intelligence techniques. The validated assessment enhances the quality and robustness of assessment.
  19. Yang C, Shi L, Lu Y, Wu H, Yu D
    J Sports Sci Med, 2024 Sep;23(1):611-618.
    PMID: 39228782 DOI: 10.52082/jssm.2024.611
    Drop jump (DJ) and squat jump (SJ) exercises are commonly used in rhythmic gymnastics training. However, the acute effects of DJ and SJ on countermovement jump (CMJ) performance have not been investigated. This study aimed to verify the post-activation performance enhancement (PAPE) responses induced by DJ and SJ with optimal power load and evaluate the relationship between peak PAPE effects and strength levels. Twenty female rhythmic gymnasts completed the following exercises in a randomized order on three separate days: 6 repetitions of DJs; 6 repetitions of SJs with optimal power load; and no exercise (control condition). Jump height was assessed before (baseline) and at 30 seconds and 3, 6, and 9 minutes after each exercise. DJs significantly improved jump height by 0.8 cm (effect size (ES) = 0.25; P = 0.003) at 30 seconds post-exercise compared with baseline. Jump height significantly decreased by -0.14 cm (ES = -0.61; P = 0.021) at 9 minutes after the control condition. SJs significantly improved jump height by 1.02 cm (ES = 0.36; P = 0.005) at 9 minutes post-exercise compared to the control condition. Jump height and relative back squat one-repetition maximum were positively related after performing DJs (r = 0.63; P = 0.003) and SJs (r = 0.64; P = 0.002). DJ and SJ exercises effectively improved countermovement jump height. DJ improved jump height early, while SJ produced greater potentiation effects later. Athletes with a higher strength level benefited the most from these exercises.
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