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A parallel and efficient transformer deep learning network for continuous estimation of hand kinematics from electromyographic signals
Studying on the efficiency of higher education resource allocation and its influencing factors in the western China using DEA-Malmquist and Tobit models
Optimizing higher education resource allocation in western China is vital for advancing national development through education and talent. This research covers the DEA Malmquist to examine the effectiveness of higher education materials distributed statically and vigorously within twelve provinces in the western part of China. It also studies the internal inequalities in resource distribution effectiveness and employs the Tobit model to identify which the main factors affecting the efficiency of higher education resource allocation. The primarily data sources from the China Education Yearbook (2011–2021). The findings indicate that the comprehensive technical efficiency (TE), pure technical efficiency (PTE), and scale efficiency (SE) have not reached the efficiency frontier in higher education resource allocation in western China. Conversely, the dynamic analysis reveals a decline in overall efficiency in resource allocation for higher education in the western region, with significant variations in efficiency levels among the provinces. Factors such as education expenditure, GDP per capita, total GDP, and the breadth of education significantly impact the efficiency of resource allocation for higher education in the western region. To improve this efficiency, it is essential to boost financial input into education, adjust resource allocation strategies, focus on matching educational quality with market demands, and implement dynamic monitoring and evaluation.
A new method for correcting the refraction angle of starlight under the conditions of 0–$$90^{\circ }$$ zenith distance and 0–200 km observation height
Expertise-driven temporal gaze dynamics during anticipation in volleyball
Perceptual-cognitive comparisons of experts and novices have consistently shown that experts use specific visual strategies to process visual scenes in their domain of expertise, reflected in eye movement metrics such as fixation rates and durations. We present an investigation of the gaze behavior from professional volleyball players (experts; n = 14) during a volleyball anticipation task and compare them to intermediate level volleyball players (amateurs; n = 25) and individuals with only basic volleyball experience (novices; n = 19). The task consisted of the observation of videos, which were recorded during official national level volleyball matches, each showing unique setting situations. Our results replicate previous findings showing lower fixation rates as well as longer fixation durations in relation to higher expertise. Yet, this trend was only present in the later phase of video observation, i.e., during the course of the rally. In the early phase, i.e., during players’ preparation before the service, experts did not differ from amateurs on all fixation metrics, while novices performed comparatively higher rates of fixations. Our findings emphasize the importance of investigating temporal dynamics, as well as using a comprehensive operationalization of perceptual-cognitive processes related to expertise.
Evaluation of implicit motor learning across body segments in Parkinson’s disease vs. healthy controls
The association between serum lipid levels and colorectal cancer risk: A dose-response meta-analysis of 23 studies
Background Colorectal cancer (CRC) ranks as the third most prevalent cancer globally and the second leading cause of cancer-related mortality. Based on recent studies, lipid levels may have a relationship with the risk of CRC. This meta-analysis aims to better understand the association between various serum lipids and CRC risk. Methods A comprehensive search was conducted in Web of Science, PubMed, and Scopus. This meta-analysis, including only prospective cohort studies, performed random-effects meta-analyses using the Restricted Maximum Likelihood (REML) model to assess the association between the highest versus lowest categories of serum triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL), and low-density lipoproteins (LDL) with the risk of CRC, primarily using hazard ratios (HR) as the effect size. Subgroup analyses (e.g., by tumor site, region, and risk of bias) and meta-regression analyses (e.g., for mean age, mean BMI, sex distribution, and duration of follow-up) were conducted to explore heterogeneity. Dose-response analyses were performed utilizing three model types. Results Following the screening of 27,278 articles, 23 articles have been included in this study finally. The associations between TG, TC, HDL, and LDL levels and the risk of CRC, colon, and rectum cancers were examined separately. Higher levels of TC were not significantly associated with the risk of CRC (HR = 1.08; 95% CI: 0.90–1.30; I2 = 50.55%; p = 0.4187) and colon cancer (HR = 1.08; 95% CI: 0.99–1.18; I2 = 35.57%; p = 0.0720), but were significantly associated with an increased risk of rectum cancer (HR = 1.19; 95% CI: 1.08–1.32; I2 = 28.36%; p = 0.0004). Higher levels of TG were associated with an increased hazard of CRC (HR 1.11; 95% CI: 1.044–1.18; I2 = 0.0%; p = 0.0008). For colon cancer, TG showed a marginally significant association (HR 1.23; 95% CI: 0.99–1.55; I2 = 52.0%; p = 0.0576). No significant association was found between TG levels and rectum cancer risk (HR 1.036; 95% CI: 0.69–1.56; I2 = 67.29%; p = 0.8674).Also, higher levels of HDL were not significantly associated with the risk of CRC (HR 0.93; 95% CI: 0.83–1.03; I2 = 28.8%; p = 0.1527), colon cancer (HR 0.94; 95% CI: 0.75–1.19; I2 = 0.0%; p = 0.6243), and rectum cancer (HR: 0.95; 95% CI: 0.66;1.37; I2 = 0.0%; p = 0.7888). For colon cancer, higher LDL level was not significantly associated with risk (HR 0.91; 95% CI: 0.60–1.37; p = 0.21; I2 = 37%; p = 6558). Accordingly quadratic and RCS models represented as lowest AIC for TC (p = 0.026), for TG (p = 0.004), for LDL (p = 0.942) and for HDL (p = 0.295). Conclusion Higher TG level was significantly associated with increased risk of CRC and showed a borderline association with colon cancer (HR 1.23, 95% CI 0.99–1.55; p = 0.0576), while TC, HDL, and LDL showed no significant associations with these cancers. For rectum cancer, higher TC was significantly linked to increased risk, whereas TG, HDL, and LDL showed no significant associations. Future research should prioritize longitudinal studies to investigate the mechanistic roles of hormones and the gut microbiota in modulating colorectal cancer risk, alongside multi-omics studies that integrate lipid metabolism with other biological variables such as inflammatory markers and genetic predispositions. These efforts could clarify causal pathways and inform targeted prevention strategies.
The impact of dual-tasking on mnestic performance in normal ageing
Abstract Multitasking has become a necessity in our daily routines. Older people in developed countries are subject to ever-increasing cognitive demands, and the way they multitask has been raising significant interest. Recent research has focused on the clinical relevance of the motor-cognitive dual-task, partially neglecting the potential of concurrently using two cognitive tasks. Here, we devised a computer-based, cognitive-cognitive dual task to study the relationship between dual-task cost, age, and cognitive efficiency (MoCA) in a group of sixty-one healthy participants (aged 50–77 years). Participants were tested with a primary visual Memory task (free recall or forced choice) and a secondary phonemic Fluency task, either concurrently (dual-tasking) or non-concurrently (single task). As expected, primary and secondary task performance significantly decreased with concurrent task demands and increasing age. Age and cognitive load however did not interact: The dual-tasking cost in visual Memory and in phonemic Fluency was stable across the age range we investigated. Participants with higher mnestic costs had lower performance also in other measures of divided attention (e.g. TMT) while no correlation was found with the MoCA score. This might be compatible with the presence of a core ability allowing to split attention for the parallel processing of information with different nature. In conclusion, cognitive-cognitive dual-tasks provide a sensitive measure of non-pathological age-related changes in cognitive efficiency and could be used as baseline when developing more sensitive tests for the early detection of abnormal patterns possibly indexing cognitive impairments.
Research on the stability of the ballast water tank on the offshore floating platform based on numerical simulation
The study of stabilisation performance is a crucial consideration in the design of offshore floating platforms. For large floating structures, incorporating passive anti-roll tanks is a common technique for roll reduction. To investigate the feasibility of using ballast tanks for roll attenuation on the “Guo Hai Shi 1” platform, this study employs the internal tank theory to analyze the influence of four independent empty tanks, located around the platform, acting as anti-roll tanks with varying ballast water volumes. The results indicate that: (1) Different ballast water volumes within a single tank do not significantly affect the static stability parameters of the platform. (2) In regular wave simulations, the ballast tanks show limited effectiveness in reducing pitch motion along the wave incidence direction but effectively suppress coupled responses in other degrees of freedom. In the resonance case (Case 3), the minimum pitch occurs in Condition 1 at 10.56°, while the maximum pitch reaches 11.45° in Condition 2. Nevertheless, a 40% reduction in roll motion is achieved (3.36° in Condition 4 vs. 5.60° in Condition 1), along with a 24.5% reduction in yaw motion (39.22° in Condition 4 vs. 51.94° in Condition 1). (3) In irregular wave simulations, the ballast tanks effectively reduce the heave amplitude by up to 8.34% in sea state level 4 and 6.06% in sea state level 8, thereby enhancing its wave-following performance in the heave degree of freedom. (4) A CNN_BiLSTM_Attention algorithm is developed using hydrodynamic analysis generated datasets to predict the pitch motion time series of the platform under different ballast water conditions and sea states, while the model has a superior prediction performance (R² = 0.9658, RMSE = 0.5343, MAE = 0.3188, representing a 4.82% increase in R² and 30.31% reduction in RMSE compared to the original model). Future work will further explore the application of ballast tanks on floating platforms, with a focus on performance optimization and the development of advanced neural network models capable of predicting motion responses under various ballast configurations. Moreover, appropriate evaluation metrics will be established to assess the effectiveness of ballast tank designs. Efforts will also be directed towards integrating time-domain motion prediction using neural networks with control theories aimed at dynamically regulating ballast water volume to enhance platform stability.
Hippos still roamed Europe during the last ice age
Engineered phage-silver nanoparticle complexes as a new tool for targeted therapies
Electroacupuncture alleviates pain-like behaviors through modulating DNMT3a/MOR signaling pathway in CCI rats
Neuropathic pain (NP) affects mental health and social functioning of people. Electroacupuncture (EA) has been shown to be effective in relieving NP in clinical practice, but the specific mechanism is still unclear. In our study, we aimed to explore the mechanism of how EA relieving NP by chronic constriction injury (CCI) rat model. EA treatment was performed at acupoints Zusanli (ST36) and Yanglingquan (GB34) after CCI 1 week and after AAV dorsal root ganglion (DRG) injection 3 weeks. EA was performed 30 minutes per day for 7 days. The paw withdrawal threshold (PWT) and paw withdrawal latency (PWL) were checked. The expressions of DNA Methyltransferase 3 Alpha (DNMT3a), Mu opioid receptors (MOR), pain-related signals (Fos, ERK1/2, and pERK1/2) and glial cell activity-related factors (CD11b, Iba1, and GFAP) in spinal cord dorsal horn (SCDH) and DRG were detected by western blotting, quantitative polymerase chain reaction reverse transcription (RT-qPCR). The expressions of DNMT3a and MOR in SCDH and DRG were also observed by immunofluorescence experiments. Our results revealed that CCI increased DNMT3a and decreased MOR expressions in DRG, which could be reversed by EA. EA at Unilateral acupoints Zusanli (ST36) and Yanglingquan (GB34) increased the PWT as well as PWL of the hind paw of CCI rats by down-regulating the expression of pain-related signals (Fos, ERK1/2, and pERK1/2) and glial cell activity-related factors (CD11b, Iba1, and GFAP) in SCDH as well as DRG. EA therapy could produce favorable analgesic results in individuals who experienced pain sensitivity arising from peripheral nerve injury. EA may improve analgesia by increasing MOR expression through the inhibition of DNMT3a in DRG.
PyPlaque is an open-source python package for phenotypic analysis of virus plaque assays
Abstract Virological plaque assays are the primary method for quantifying infectious particles in a suspension, achieved by incubating a serial dilution of the virus with a monolayer of indicator cells. Existing software tools for quantification of plaque assay images lack modularity, show measurements disagreement or are closed-source - a common hurdle in bioimage analysis. We introduce PyPlaque, an open-source Python package focusing on flexibility and modularity rather than a bulky graphic user interface. Unlike previous methods, an abstracted architecture using object-oriented programming allows accommodation of various experimental containers and specimen carriers as data structures while focusing on phenotype-specific information. Aligned with the logical flow of experimental design and desired quantifications, it delivers insights at multiple granularity levels, facilitating detailed analysis. We demonstrate how this approach allows to focus on alleviating the disagreement in measurements. Furthermore, similar design is generalisable to diverse datasets in various biological contexts that fit our structural paradigm.
Development of a validated PROM set for children with tinnitus using the Patient-Reported Outcomes Measurement Information System – Protocol for the ‘Tinnitus in Children’ (TinC) study
Introduction Tinnitus in children remains an underexplored area of research, with limited knowledge about its prevalence and impact on daily lives. Current assessments of the impact of tinnitus in children predominantly rely on open-ended questioning during clinical interviews, inconsistent use of structured tools, and data reported by adult proxies. These methods often fail to fully capture the child’s personal experience of tinnitus, underscoring the need for a standardized, child-centered measure to more accurately assess its impact and improve understanding of children’s experience. To address this gap, this study proposes the development of a validated PROM set using the Patient-Reported Outcomes Measurement Information System (PROMIS). Methods The proposed study is a monocenter, mixed-methods, multi-phase observational study. The study will consist of six consecutive steps: (1) identifying patient-important outcomes through focus groups with children aged 8–18 years; (2) defining the underlying constructs of the outcomes and linking them to relevant PROMIS domains; (3) gathering input form an expert panel to refine the outcomes and domains; (4) discussing the PROM set with the focus groups and assess its feasibility; (5) assessing content validity in the expert panel; and (6) assessing the reliability in a sample of children with tinnitus. Discussion By using the generic PROMIS framework to develop a condition-specific measure, the proposed study aims to create a standardized, child-centered PROM set that captures the specific impact of pediatric tinnitus, while maintaining the ability to compare outcomes across different conditions and populations. This PROM set could ultimately be used in both clinical care and research to evaluate tinnitus impact and assess the effects of treatments.
Left atrial reservoir strain as a predictor for left ventricular filling pressure in patients with sinus rhythm
Beyond health: A machine learning analysis of structural barriers to school attainment in Somalia
In fragile states like Somalia, the link between poor health and educational exclusion is critical yet poorly understood. This study uses a novel machine learning approach to identify and rank the most significant barriers to school attendance. We analyzed nationally representative data from 10,511 children aged 6–18 in the 2022 Somalia Integrated Household Budget Survey (SIHBS). Ten supervised machine learning models were employed to predict school attendance, with the Random Forest model emerging as the top performer (AUC = 0.86). Contrary to conventional wisdom, our findings reveal a clear hierarchy of barriers where structural and demographic factors are the most powerful predictors. A child’s age (non-attendance rises from 6% in 6–10 year-olds to 25% in 15–18 year-olds), geographic region (non-attendance reaches 30.5% in Middle Shabelle), and residence type (nomadic children face triple the non-attendance risk of their peers) were the dominant determinants. These factors significantly outweighed the direct predictive power of individual health status or household poverty. The results indicate that while health is important, educational exclusion in Somalia is more fundamentally driven by where a child lives, how old they are, and their family’s mode of life. Policy interventions must therefore shift from broad, single-sector approaches to geographically-targeted, age-specific strategies. To effectively address the root causes of educational inequality, efforts should prioritize service delivery in marginalized regions and provide tailored support for nomadic and adolescent populations.
Multimorbidity as a driver of heart diseases risk among low socioeconomic older adults population in India
Evaluation of disparities in the incidence, presentation, and treatment of pediatric differentiated thyroid cancer in the United States (2000–2022)
Introduction Rates of pediatric differentiated thyroid cancer (DTC) have been increasing, yet disparities in incidence, diagnosis, and treatment across race and ethnicity have not been fully explored. Methods We assessed temporal trends in the incidence of pediatric DTC using data from 2000–2022 (excluding 2020 due to COVID-19) from the National Childhood Cancer Registry. Annual percent changes (APC) were calculated using joinpoint regression analysis overall and by race, ethnicity, age, and clinical factors. Differences in cancer presentation and treatment by race and ethnicity were evaluated using data from Surveillance, Epidemiology, and End Results (SEER) for 18 registries for 2006–2018, while accounting for socioeconomic status (SES). Results Overall pediatric DTC incidence increased 4.5% annually from 2000−2018 (95%CI: 3.8%−5.8%), then declined (−6.9%) through 2022 (95%CI: −14.5%, −1.2%). Rates of decline appeared sharpest among Non-Hispanic White patients. Incidence rates continued increasing among Non-Hispanic Asian/Pacific Islanders and patients diagnosed with tumors >4 cm. Compared to non-Hispanic White patients, non-Hispanic Black, non-Hispanic Asian/Pacific Islander, and Hispanic children were more likely to be diagnosed with a tumor >4 cm. Conclusion Declines in reported pediatric thyroid cancer incidence, particularly among the smallest tumor sizes, after 2018 may be attributable to application of thyroid cancer management guidelines. However, the continued increase among those presenting with larger tumor sizes may support a true continued increase in incidence among some groups. The greater proportion of non-White children being diagnosed with larger tumors could be due to inequities related to timely access to care, differential application of thyroid management guidelines, differences in cancer subtypes, or other factors. These findings warrant further exploration when additional years of data are available.
Using digital archaeology and machine learning to determine sex in finger flutings
Effectiveness of the U-Niko intervention: Protocol for a cluster randomized controlled trial of a municipal-based tobacco and nicotine cessation intervention for adolescents and young adults
Introduction The use of nicotine products among youth is increasing, while existing cessation services remain underutilized. Thus, the U-Niko intervention has been developed to provide an evidence-based, youth-oriented approach for effective nicotine cessation. Methods This protocol describes a two-arm cluster randomized controlled trial of youth aged 16–25 in 55 municipalities in Denmark. Prior to the study a stratified randomization was carried out using the online randomization program Sealed Envelope, allocating 27 municipalities to the U-Niko intervention group and 28 municipalities to the control group (tobacco and nicotine cessation recruitment and counseling as usual). The primary outcomes will measure the effectiveness of all three focus areas in the intervention group compared to the control group: A) the municipal counselors’ self-efficacy in youth cessation counseling, B) the number of recruited youths for cessation counseling, and C) the self-reported 14-day point prevalence of abstinence of youth at six months follow-up. Secondary outcomes are the number of recruited youths in a municipality compared to the previous year, continuous abstinence, and validated 14-day point prevalence of abstinence at six-months follow-up. Discussion By evaluating all three focus areas of the U-Niko intervention, this study aims to provide robust evidence for improving youth cessation interventions at local and national levels. Trial registration The study was registered in ANZCTR (ACTRN12624001470583) on 18/12/2024. The Universal Trial Number is U1111-13-14-6117.