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“Pet effect” patterns: Dynamics of animal presence and caregiver affect across (tele)work and non-work contexts
Human-animal interactions (HAI) may relate to animal caregivers’ affect, also referred to as the “pet effect”. However, studies have not explored these associations in work contexts or evaluated longitudinal patterns of HAI with other activities across work and non-work contexts, and their associations with caregiver emotions. We therefore assess momentary associations between HAI during (tele)work and non-work time and positive and negative caregiver affect (PA/NA), identify person-level patterns of longitudinal HAI state trajectories, and analyze cross-level moderating effects of these patterns on momentary associations between HAI and PA/NA. First, we evaluated associations between momentary HAI and caregiver PA/NA including the moderating role of momentary work state (teleworking vs. not working). Second, using a data-driven approach, we applied sequence analysis to determine heterogeneity in state trajectories amongst caregivers using working activity and animal presence in five possible states (working at work/teleworking with animal/teleworking without animal/not working with animal/not working without animal), which we labelled as animal-work constellations. Similar trajectories of animal-work constellations across caregivers were grouped into clusters with recognizable patterns. Third, we assessed whether such patterns moderated momentary associations between HAI and caregiver PA/NA. Caregivers (Npersons = 324) completed ecological momentary survey data during five days with 10 prompts per day (Nobservations = 16,127) between 2017 and 2024. Results showed that momentary associations between HAI and affect were moderated by momentary work state and person-level animal-work constellation pattern, contextualizing the “pet effect”. Our results highlight the importance of microlevel investigations of animal-work constellations and validates the novel use of sequence analysis to explore the role of context and time.
A clustering fractional-order grey model in short-term electrical load forecasting
Evaluating patient experience in maternity services using a Bayesian belief network model
Pregnancy and childbirth are commonly seen as positive experiences, but they can also pose distinct challenges and risks, especially when care is insufficient. This study investigates the factors influencing maternity patient experience by exploring the complex interactions among these factors. Using data from the 2021 maternity patient survey by the National Health Services (NHS) in England, we implemented a Bayesian Belief Network (BBN) to model these interactions. Three structural learning models were created, namely Bayesian Search (BS), Peter-Clark (PC), and Greedy Thick Thinning (GTT). Further, sensitivity analysis was conducted to quantify interactions among the influencing factors and identify the most influential factor affecting the outcome. The results underscore the importance of recognizing the interdependencies among the eight key domains of the survey, which collectively shape maternity care experiences. These factors include the start of care in pregnancy, antenatal check-ups, care during pregnancy, labour and birth, staff caring, care in the hospital, feeding the baby, and care after birth. These findings can guide healthcare managers and decision-makers in developing proactive strategies to mitigate factors impacting maternity patient experiences. Ultimately, this study contributes to the ongoing efforts to enhance the quality of maternity care and improve outcomes for mothers and their infants.
Enhancing the electrochemical performance of high-voltage LiNi0.5Mn1.5O4 batteries with a multifunctional inorganic MgHPO4 electrolyte additive
Effects of high-intensity interval training versus moderate-intensity continuous training on cardiorespiratory and exercise capacity in patients with coronary artery disease: A systematic review and meta-analysis
Background With the increasing utilization of cardiac rehabilitation in clinical treatment and prognosis for patients with cardiovascular diseases, exercise training has become a crucial component. High-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) are commonly employed in rehabilitating patients with cardiovascular diseases. However, further investigation is required to determine whether HIIT and MICT can effectively enhance the prognosis of patients with coronary artery disease. Therefore, this study aims to assess the effectiveness of HIIT and MICT interventions, optimal intervention duration for different intensity levels of training, as well as effective training modalities that improve cardiorespiratory function and exercise capacity among patients. Methods We conducted a comprehensive search of the Cochrane Library, PubMed, EMbase, Web of Science, and CINAHL databases for randomized controlled trials (RCTs) pertaining to high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) interventions in patients with coronary artery disease from inception until publication on September 26, 2024. Two independent researchers assessed articles that met the inclusion criteria and analyzed the results using Sata 17.0 software. Forest plots were employed to evaluate the impact of HIIT and MICT on outcome indicators. Sensitivity analysis and funnel plot assessment were performed to examine publication bias. Subgroup analysis was conducted to determine optimal intervention duration and training methods. Results A total of 22 studies with 1364 patients were included in the study, including the HIIT group (n = 685) and the MICT group (n = 679). The results showed that compared to MICT, HIIT significantly increased PeakVO2(Peak oxygen uptake)[WMD = 1.42mL /kg/min 95%CI (0.87, 1.98), P = 0.870, I2 = 0%], 6MWT(6-minute walk test)[WMD = 18.60m 95%CI (2.29, 34.92), P = 0.789, I2 = 0%], PHR(Peak heart rate)[WMD = 4.21bpm 95%CI (1.07, 7.36), P = 0.865, I2 = 0%], DBP(diastolic blood pressure)[WMD = 3.43mmHg 95%CI (1.09, 5.76), P = 0.004, I2 = 60.2%]. However, in LVEF(left- ventricular ejection fraction)[WMD = 0.32mL 95%CI (-1.83, 2.46), P = 0.699, I2 = 0%], LVEDV(left ventricular end-diastolic volume)[WMD = 0.91 ml 95%CI (-1.83, 2.46), P = 0.995, I2 = 0%] and SBP(systolic blood pressure)[WMD = 1.85mmHg 95%CI (-0.23, 3.93),P = 0.266, I2 = 18.2%], there was no significant difference between HIIT and MICT. Conclusion Based on the findings of this systematic review, HIIT demonstrates superior efficacy compared to MICT in enhancing PeakVO2, PHR, 6MWT and DBP. However, no significant differences were observed in LVEF, LVEDV, and SBP. In summary, HIIT exhibits potential for improving cardiopulmonary function and exercise capacity among patients with coronary artery disease.
Design and evaluation of children’s education interactive learning system based on human computer interaction technology
Federico Mayor Zaragoza obituary: former UNESCO chief who championed neonatal screening
A map of the rubisco biochemical landscape
Abstract Rubisco is the primary CO 2 -fixing enzyme of the biosphere 1 , yet it has slow kinetics 2 . The roles of evolution and chemical mechanism in constraining its biochemical function remain debated 3,4 . Engineering efforts aimed at adjusting the biochemical parameters of rubisco have largely failed 5 , although recent results indicate that the functional potential of rubisco has a wider scope than previously known 6 . Here we developed a massively parallel assay, using an engineered Escherichia coli 7 in which enzyme activity is coupled to growth, to systematically map the sequence–function landscape of rubisco. Composite assay of more than 99% of single-amino acid mutants versus CO 2 concentration enabled inference of enzyme velocity and apparent CO 2 affinity parameters for thousands of substitutions. This approach identified many highly conserved positions that tolerate mutation and rare mutations that improve CO 2 affinity. These data indicate that non-trivial biochemical changes are readily accessible and that the functional distance between rubiscos from diverse organisms can be traversed, laying the groundwork for further enzyme engineering efforts.
Diagnostic yield of endoscopic ultrasound-guided fine-needle aspiration-based cytology for distinguishing malignant and benign pancreatic cystic lesions: A systematic review and meta-analysis
Background Preoperative diagnosis of malignancy in patients with pancreatic cystic lesions (PCLs) remains challenging. The aim of this study was to assess the sensitivity, specificity, and positive and negative likelihood ratios (LRs) of endoscopic ultrasound-guided fine needle aspiration (EUS-FNA)-based cytology in differentiating malignant PCLs from benign PCLs. Methods A comprehensive search was performed in multiple databases in November 2023. Studies differentiating benign and malignant PCLs via EUS-FNA-based cytology, in which the results were compared with those of surgical excision histopathology, were included in this meta-analysis. Data from the selected studies were pooled to summarize the sensitivity, specificity, positive and negative LRs, diagnostic odds ratios and summary receiver operating characteristic (SROC) curves. Results We included 755 patients from 15 distinct studies who underwent EUS-FNA-based cytology and had a histopathological diagnosis. The pooled sensitivity and specificity in diagnosing malignant PCLs were 0.62 (95% CI, 0.42–0.78) and 0.96 (95% CI, 0.91–0.98), respectively. The positive and negative LRs for diagnosing malignant PCLs were 16.3 (95% CI, 7.2–37.0) and 0.40 (95% CI, 0.25–0.64), respectively. The area under the curve (AUC) was 0.94 (95% CI, 0.91–0.95). Conclusions EUS-FNA-based cytology has overall high specificity, medium sensitivity and good diagnostic accuracy in differentiating malignant from benign PCLs. Further research is needed to improve the overall sensitivity of EUS-FNA-based cytology for the diagnosis of malignant PCLs.
The relationship between dietary index for gut microbiota and diabetes
Correction: An international consensus on effective, inclusive, and career-spanning short-format training in the life sciences and beyond
Characterization and potential usage of selected eggshell species
A personalized reinforcement learning recommendation algorithm using bi-clustering techniques
Recommender systems have become a core component of various online platforms, helping users get relevant information from the abundant digital data. Traditional RSs often generate static recommendations, which may not adapt well to changing user preferences. To address this problem, we propose a novel reinforcement learning (RL) recommendation algorithm that can give personalized recommendations by adapting to changing user preferences. However, a significant drawback of RL-based recommendation systems is that they are computationally expensive. Moreover, these systems often fail to extract local patterns residing within dataset which may result in generation of low quality recommendations. The proposed work utilizes biclustering technique to create an efficient environment for RL agents, thus, reducing computation cost and enabling the generation of dynamic recommendations. Additionally, biclustering is used to find locally associated patterns in the dataset, which further improves the efficiency of the RL agent’s learning process. The proposed work experiments eight state-of-the-art biclustering algorithms to identify the appropriate biclustering algorithm for the given recommendation task. This innovative integration of biclustering and reinforcement learning addresses key gaps in existing literature. Moreover, we introduced a novel strategy to predict item ratings within the RL framework. The validity of the proposed algorithm is evaluated on three datasets of movies domain, namely, ML100K, ML-latest-small and FilmTrust. These diverse datasets were chosen to ensure reliable examination across various scenarios. As per the dynamic nature of RL, some specific evaluation metrics like personalization, diversity, intra-list similarity and novelty are used to measure the diversity of recommendations. This investigation is motivated by the need for recommender systems that can dynamically adjust to changes in customer preferences. Results show that our proposed algorithm showed promising results when compared with existing state-of-the-art recommendation techniques.
Comprehensive analysis of mitochondrial-related gene signature for prognosis, tumor immune microenvironment evaluation, and candidate drug development in colon cancer
Mechanical properties of lithium slag recycled aggregate concrete subject to high temperature
In attempting to enhance the mechanical properties of recycled concrete after high temperature and solve the problem of large stacking of lithium slag (LS), this paper proposes lithium slag recycled concrete (LSRAC). In this research, LS was used to replace part of the cement (γL = 10%, 20%, and 30%), recycled coarse aggregate (RCA) completely replaced the natural aggregate (γR = 100%), and the heated temperatures were 200°C, 400°C, and 600°C. This paper carried out the heating test and the strength tests. The test results indicated, for the same heating temperature, the loss of strength of LSRAC was less than that of RAC and the compressive strengths and splitting strength of LSRAC with 20% lithium slag replacement rate were improved by 33.9%, 36.5% and 34.5%, respectively. The increase in flexural strength of LSRAC with 10% lithium slag dosage reached 24.1%. The results indicate LSRAC can effectively improve the bearing capacity of structural concrete subject to high temperature. The strength retention equations of LSRAC were established by comparing the strengths of 20°C. The calculation results of the strength retention formula for post-high-temperature LSRAC matched the measured results well. Therefore, this paper provided reliable experimental basis and theoretical guidance for on-site rescue, post-disaster assessment and reinforcement of RAC used for pavement base and public facilities constructions, and the eco-friendly way for sustainable development.
A 3D medical image segmentation network based on gated attention blocks and dual-scale cross-attention mechanism
Active power filter control strategy based on repetitive quasi-proportional resonant control with linear active disturbance rejection control
Active power filter (APF) is a new type of harmonic mitigation device, and its harmonic mitigation capability mainly depends on the control strategies of current inner loop and voltage outer loop. Traditional proportional integral (PI) control methods cannot track harmonic currents without steady-state error, thereby it leads to the poor tracking accuracy of the harmonic current and is difficult to achieve high-performance harmonic compensation. Thus, in this paper, a repetitive quasi-proportional resonant (QPR) with linear active disturbance rejection control (LADRC) is proposed. Firstly, QPR control is introduced to replace PI control. QPR control can eliminate steady-state error and realize no static error tracking of harmonic current. Meanwhile, QPR control can coordinate control of various frequency components and enhance APF’s ability to suppress specific harmonics. Then, the introduction of repetitive control optimizes the QPR control, so that the dynamic performance of the system does not change while further improving the tracking accuracy of the APF system for harmonic current. Finally, LADRC control is used to observe and compensate for the coupled parts of the system. Thereby, it can achieve high-performance decoupling without adding additional sensors. In addition, in order to ensure the stability of the DC-side voltage and enhance its dynamic performance, this paper also designs a voltage outer loop controlled by QPR. The proposed method is verified by real-time digital simulation system (RTDS). The simulation results show that compared with the double closed-loop PI control, the repetitive quasi-proportional resonant with linear active disturbance rejection control (repetitive QPR-LADRC) and QPR double closed-loop control proposed in this paper can not only increase the harmonic current tracking accuracy of APF system, but also improve the dynamic performance of APF system and significantly enhance the harmonic suppression ability of APF.
Association between sleep quality and premenstrual syndrome in young women in a cross-sectional study
Seroprevalence and associated factors for hepatitis B and hepatitis C viral infection among patients with diabetes mellitus in Northern Tanzania
Background The coexistence of viral hepatitis with diabetes mellitus (DM) significantly escalates the risk of severe outcomes. This study aimed to determine the seroprevalence and associated factors of hepatitis B (HBV) and hepatitis C (HCV) viral infections among DM patients in northern Tanzania. Materials and methods Conducted between February 2023 and May 2023, this hospital-based cross-sectional study enrolled 189 patients with DM from the Diabetic Clinic of Kilimanjaro Christian Medical Centre. A structured questionnaire captured relevant clinical information, and plasma blood sample was assessed for hepatitis B surface antigen and anti-hepatitis C antibody seropositivity. Data analysis employed SPSS v26, and a chi-square test was used to determine the statistical difference of HBV and HCV among patients with DM. Logistic regression was performed to determine factors associated with HBV and HCV. Results Among the 189 patients with DM, the seroprevalence of HBV and HCV infections stood at 2.1% and 0.5%, respectively. Males constituted a significant majority (80%) of those affected by viral hepatitis. Furthermore, 60% of affected patients were in non-union relationships (single, widowed, or divorced), and 40% reported multiple sexual partners. However, the study found no significant association between traditional associated factors and viral infection acquisition. Conclusion The study’s findings reveal a relatively low prevalence of HBV and HCV infections among patients with DM compared to the general population, with no significant association among factors. Nonetheless, the results underscore the importance of early screening and vaccination for HBV and HCV in patients with DM. Such efforts are crucial for curbing infection spread and reducing the risk of hepatocellular carcinoma development in this vulnerable population.