Sampling Duration Research Articles

Comparative analysis of free SMAS fold flap and ADM in facial depression after parotidectomy.

This study aimed to analyze the effects of anterior descending mandible (ADM) and free superior mesenteric artery (SMAS) folding flaps on post-parotidectomy facial depression. This retrospective study examined the effects of sex, age, surgical sample size, method, duration, and blood loss on postoperative complications in 65 patients. No significant differences involving sex, age, or sample size for surgical resection were observed between the two groups. The incidence of Frey syndrome (P = 0.175) and the locations of facial nerve injuries and tumors were not significantly different between the two groups. However, a statistically significant difference was observed in postoperative facial depression between the groups (P = 0.045, P < 0.05). No significant difference was found between facial nerve injury and Frey's sign in subgroup analysis of facial depression deformities. Within the facial depression group, tumor locations were significantly different (P = 0.021, P < 0.05). In the cases of facial depression after partial parotid resection, no significant difference was observed between ADM implantation and SMAS flap placement. A significant difference was noted between the ADM implantation and SMAS flap groups in the total parotidectomy group (P = 0.046 and P < 0.05, respectively). Women are more likely to experience facial depression after parotid surgery. Facial depression is most likely to occur after parotid resection if the tumor is located in the deep lobes of the parotid gland. The use of SMAS flaps can prevent facial depression, and both ADM and SMAS flaps can prevent Frey's syndrome. Partial parotid resection reduces the risk of facial nerve injury and facial depression.

Air DNA forensics: Novel air collection method investigations for human DNA identification.

Modern techniques can generate highly discriminatory DNA profiles from minuscule biological samples, providing valuable information in criminal investigations and court proceedings. However, trace and touch DNA samples, due to their nature, often have lower success rates than other biological materials, such as blood. Further, forensically aware criminals can utilize gloves and meticulously clean the crime scene to remove DNA traces of themselves from contacted surfaces. Air sampling offers a novel approach to the collection of human DNA that has the potential to bypass some of these issues. This study reports on the results of research into the prevalence and persistence of human DNA in the air. The ability to collect human DNA from the air was investigated with the use of an AirPrep Cub Sampler ACD220 in different spaces, with and without the presence of individuals for various durations of sample collection. Results of this study demonstrate that level of occupation and sampling duration each have an influence on quantity and quality of DNA recovered from the air whereas the effects of orientation and distance of participants from the collection device as well as sequence of occupation remain unclear and require further investigation.

Research on frequency shift signal detection algorithm for jointless track circuits based on improved relaxation algorithm

The accuracy of ZPW-2000 frequency shift signal demodulation is related to the safety and efficiency of high-speed trains. This paper proposed a kind of ZPW-2000 frequency-shift signal detection algorithm based on improved Relaxation algorithm (ZFSD-IR) to address the issue of low accuracy in detecting ZPW-2000 frequency shift signal under strong noise interference, as the traditional fast Fourier transform (FFT) spectrum analysis methods are susceptible to fence effects and spectrum leakage effects. Firstly, the principle of ZPW-2000 jointless track circuit was analyzed, and then the ideal and simplified models of ZPW-2000 frequency shift signal were established, respectively. Finally, the simulation experiments were conducted on ZPW-2000 frequency shift signal detection under different sampling durations and signal-to-noise ratios (SNR). The effectiveness of the proposed algorithm was verified through comparative analysis with the traditional algorithms. The research results indicated that the ZFSD-IR algorithm has better accuracy in carrier-frequency and low-frequency estimation than traditional algorithms, and can achieve accurate detection of ZPW-2000 frequency shift signal under the lower SNR conditions. It has high detection accuracy and good anti-interference ability, ensuring the safe operation of high-speed trains.

A fast solid-phase microextraction scheme for in vivo monitoring of bio-accumulation and bio-transformation of arbidol in living plants

Large quantity of the antiviral drug arbidol is used for resisting virus infection like the Corona Virus Disease 2019 and influenza, resulting in unanticipated environmental pollution. Herein, to investigate the environmental risks of the unanticipated arbidol contamination, a novel in vivo sampling probe was developed based on a bromo-substituted porous organic polymer (Br-POP) and then adopted for tracking the bio-accumulation and bio-transformation of arbidol in living plants by coupling with a nano-electrospray ionization fourier-transform ion cyclotron resonance mass spectrometry (Nano-ESI-FT-ICR-MS) method. The established method showed good extraction performance towards arbidol with limit of detection (LOD) of 0.48 ng g−1, and relative standard deviation (RSD) of single-and multiple- probe of 2.2 and 14 %. Owing to the interactions between the Br-POP and the target analytes, as well as the fast analysis process of Nano-ESI-FT-ICR-MS, <6 min was cost for total sampling and analysis duration, achieving hourly tracking of arbidol and its metabolites in this work. During 21-d in vivo tracking, the concentration of arbidol in living plant stems increased rapidly within 6 h and peaked at 413.93 ± 47.09 ng g−1. Meanwhile, it was found that dissolved organic matters (DOM) had significant effect on arbidol behaviors in living plants, resulting in a decrease of the maximum concentration of arbidol in plant stems (152.70 ± 42.44 ng g−1) and the change of dominant metabolite of arbidol that the S-oxidation rather than N-demethylation product of arbidol was dominant with DOM participation. Additionally, the plant root secretion was found to be significantly altered by arbidol exposure. To summarized, the combination of in vivo SPME and the FT-ICR-MS analysis provide new and important information regarding arbidol contamination and related alternation of plant root metabolism.

Low-Cost Electronic Nose for Robusta and Arabica Coffee Classification Using 1-D Convolutional Neural Networks

Abstract The use of an electronic nose (e-nose) employing MQ-series sensors has become increasingly popular due to its cost-effectiveness. However, the impact of varying sampling durations on its performance, particularly in distinguishing between Robusta and Arabica coffee, has not been extensively studied. This research investigates how different sampling durations affect the e-nose’s classification accuracy. The study utilizes a 1D Convolutional Neural Network (1D-CNN) and a Support Vector Machine (SVM), with both models enhanced by a Savitzky-Golay filter to reduce noise and improve data quality. Feature selection techniques are applied to address data complexity and improve model performance. The experimental results indicate that the 1D-CNN model achieves optimal accuracy of up to 100% at a sampling duration of 200 seconds, while the SVM reaches approximately 92% accuracy under the same conditions. Notably, for applications requiring faster processing times, the SVM proves to be more effective, achieving 70% accuracy at a 20-second sampling interval, compared to 60% for the 1D-CNN. The study demonstrates that integrating MQ sensors in e-nose systems can yield effective classification results for coffee varieties, even with shorter sampling times. These findings have the potential to influence the development of cost-effective e-nose devices, making them more accessible to small and medium-sized industrial enterprises.

Accounting for effects of growth rate when measuring ecological stability in response to pulse perturbations.

Ecological stability is a vital component of natural ecosystems that can inform effective conservation and ecosystem management. Furthermore, there is increasing interest in making comparisons of stability values across sites, systems and taxonomic groups, often using comparative synthetic approaches, such as meta-analysis. However, these synthetic approaches often compare/contrast systems where measures of stability mean very different things to the taxa involved. Here, we present results from theoretical models and empirical data to illustrate how differences in growth rates among taxa influence four widely used metrics of ecological stability of species abundances responding to pulse perturbations: resilience, recovery, resistance and temporal stability. We refer to these classic growth-rate-dependent metrics as 'realised' stability. We show that realised resilience and realised temporal stability vary as a function of organisms' growth rates; realised recovery depends on the relation between growth rate and sampling duration; and realised resistance depends on the relation between growth rate and sampling interval. To account for these influences, we introduce metrics intended to be more independent of growth rates, which we refer to as 'intrinsic' stability. Intrinsic stability can be used to summarise the overall effects of a disturbance, separately from internal recovery processes - thereby allowing more general comparisons of disturbances across organisms and contexts. We argue that joint consideration of both realised and intrinsic stability is important for future comparative studies.

Exploring the Relationship between Data Sample Size and Traffic Flow Prediction Accuracy

Efficiently extracting and analyzing large urban traffic data, accurately predicting traffic conditions, and improving urban traffic management require careful selection of an appropriate data sample size. The suitable size of data sample assumes paramount importance in fostering sustainable transportation development. This paper investigates the relationship between traffic flow prediction performance and data sample size, considering data sample missing rates, duration, and road segment coverage. Real traffic flow data from 13 road sections in Changsha, China, are analyzed using the Decision Tree, Support Vector Machine, Gaussian Process Regression and Artificial Neural Network models. Some key findings include: Lower data sample loss rates improve prediction accuracy by capturing traffic flow patterns effectively, while higher loss rates decrease accuracy; an optimal data sample duration of around 7 days balances prediction accuracy and data stability, with longer durations providing more historical data but risking complexity; Broader road segment coverage gives a more comprehensive traffic flow information, but excessive coverage introduces noise and impacts the improvement of prediction accuracy. The results highlight the significant impact of data sample size on prediction performance. Enhancing reliability can be achieved by reducing data loss, selecting suitable durations, and considering appropriate road segment coverage, supporting improved traffic management and route planning.

Sensitivity analysis of a multi-scale biofuel primary atomization simulation tool

The purpose is to produce a benchmarked commercial Volume of Fluid (VOF)-to-Discrete Phase Modeling (DPM) numerical algorithm using an experimental study of high-viscosity jet fuel blend C-3. Where the mesh resolution was too coarse to resolve sufficient gas-liquid interfacial curvature, the solver automatically converted VOF biofuel phase mass, momentum, and energy into the equivalent DPM biofuel phase at the sub-grid scale level. Particular attention herein was given to the sensitivity of the results to various numerical degrees of freedom related to the local criteria for conversion of a biofuel from VOF to DPM. The proliferation of commercial simulation tools mandates detailed parametric evaluations. It was found that, while instantaneous conversion rates were extremely sensitive to conversion criteria, atomization physics were not sensitive to the conversion rate effects. Also, this flow system exhibited an outstanding dependence on simulated azimuthal angle, rendering lower order models ineffective. Data sampling methods and durations, along with mesh resolution, were explored such that a particular set of parameters provided a validated model.

The nutritional impact of metallic taste in head and neck cancer patients: explorations and clinical implications.

Metallic taste (MT) is frequently observed during head and neck cancer treatments, but very little is known about its impact on nutritional status. The aim of this study was to explore the impact of MT on the quality of life and nutritional status in patients with head and neck cancer expressing MT. Questionnaires on quality of life, MT, weight, and food intake were filled out by 44 patients with head and neck cancer before, during, and up to 1year after their treatment. Patients were divided into two groups based on their reported experience of MT. MT was commonly observed (n = 12, 27.2%), always during the treatment phase, and mostly linked with radiotherapy or radiochemotherapy. Reported MT intensity was moderate (n = 6, 40%) to high (n = 4, 26.7%). MT had a significant negative impact on quality of life linked to dysgeusia (p = 0.025). The negative impacts of MT on food intake and on weight were not significant, possibly due to a combination of sample size, dropouts, and duration of observation. Further research in this area could provide additional insights into how to better address the issue related to MT and enhance the quality of care provided to this patient population. Metallic taste, experienced by 27.2% of the 44 patients with head and neck cancer, contributes to dysgeusia and results in a significant decline in quality of life associated with dysgeusia. ClinicalTrials.gov trial registration number: NCT03558789.

The Role of Multidisciplinary Rehabilitation in Enhancing Comprehensive Cancer Care: A Descriptive Review

Objective: This review aims to highlight the effectiveness of various forms of cancer rehabilitation in improving physical, emotional, and social outcomes for patients with cancer. It evaluates the impact of cancer rehabilitation on physical function, psychological health, and social reintegration while identifying barriers and facilitators in the implementation of cancer rehabilitation programs. Methods: A literature search was conducted from December 2023 to February 2024, using two electronic databases: MEDLINE (via PubMed) and Google Scholar. After screening the titles and abstracts, the study selected 34 articles, including RCTs, clinical trials, observational studies, and systematic reviews. The study did not include letters to the editor, editorials, special and short communications, animal-based research, and non-English language publications. There were no restrictions on geographical distribution, age of the sample population, type, severity, duration, and outcome of cancer, or the year range from which the studies were selected. Results: Rehabilitation interventions were effective in different cancer types, including breast, prostate, lung, and colorectal cancers. These interventions addressed common treatment-related challenges such as fatigue, pain, lymphedema, incontinence, and psychological issues, improving patients' quality of life and physical functioning. However, challenges such as physical limitations, emotional distress, access to care, financial barriers, and coordination of services were frequently noted. This highlights the need for tailored, accessible, and well-coordinated rehabilitation programs. Conclusion: Multidisciplinary and coordinated cancer rehabilitation has the potential to improve mobility, quality of life and physical functioning across various cancer types, but challenges in accessibility and coordination must be addressed.

DIGITAL SOLUTION FOR OPTIMIZATION OF FORMATION TESTING DESIGN

Evaluation of pumping time to receive a clean sample during fluid sampling job with wireline formation tester as well as evaluation of pumping scenarios to minimize sampling duration under existing constrains (reservoir and sandface constrains, safety etc.) are actual problems especially for fluid sampling in low-permeability formation. The article describes the digital solution allowing to simulate mud filtrate invasion in near-wellbore zone during well drilling and mud filtrate displacement by reservoir fluid during fluid sampling job with taking into account a formation damage dynamics. In this way, the software is able to evaluate depth of mud filtrate invasion and simulate both the multiphase inflow dynamics and the skin-factor dynamics during sampling job and predict sampling duration. To take into account a complex, essentially non-1D geometry of multiphase fluid flow in near-wellbore zone during fluid sampling, the special upscaling technique was developed. This upscaling technique is based on modification of 1D model by introduction of «effective» mud filtrate invasion profile and «geometry factor» which depend on ratio of vertical to horizontal permeabilities. The correlations between empirical model parameters and ratio of vertical to horizontal permeabilities were obtained by matching results of «pseudo 2D» simulations of pumping dynamics with results of 2D / 3D simulations conducted using commercial simulators ECLIPSE® and COMSOL Multiphysics®. The developed «pseudo 2D» model is computationally fast ones that allows to effectively conduct sensitivity study as well as adjust the model parameters and sampling scenario in real time in accordance with the real-time wireline formation tester measurements.

Application of a high-performance grey prediction model to predict the cardiovascular disease mortality in elderly Chinese residents

With the acceleration of urbanization and aging process, an increasing number of Chinese senior citizens are suffering from cardiovascular diseases (CVDs). Therefore, reducing the prevalence and mortality of CVD has become one of the priorities of the public health department. And the scientific prediction of CVD morality is of great significance in the prevention and treatment of CVD among the elderly. Given the characteristics of “small sample, complex causes and long duration” of CVD among the senior citizens, grey prediction models which aim at handling the data with “small sample, poor information” are more feasible in forecasting its developing trend. In this paper, a new discrete grey prediction model is designed to forecast the CVD morality among Chinese senior citizens, in which a non-linear function is introduced to expand the model structure and the order and background value coefficient are optimized. In all the three sets of experiments, the errors of the new model are close to but smaller than those of the other three mainstream grey prediction models, indicating that the simulation and prediction performance of the new model is more accurate and stable. The research provides a new modelling approach to predicting the CVD mortality among Chinese senior citizens, which is conducive to the prevention of CVD prevalence and the sustainable development of public health.

Deep Learning System for User Identification Using Sensors on Doorknobs.

Door access control systems are important to protect the security and integrity of physical spaces. Accuracy and speed are important factors that govern their performance. In this paper, we investigate a novel approach to identify users by measuring patterns of their interactions with a doorknob via an embedded accelerometer and gyroscope and by applying deep-learning-based algorithms to these measurements. Our identification results obtained from 47 users show an accuracy of 90.2%. When the sex of the user is used as an input feature, the accuracy is 89.8% in the case of male individuals and 97.0% in the case of female individuals. We study how the accuracy is affected by the sample duration, finding that is its possible to identify users using a sample of 0.5 s with an accuracy of 68.5%. Our results demonstrate the feasibility of using patterns of motor activity to provide access control, thus extending with it the set of alternatives to be considered for behavioral biometrics.

Glucose detection: In-situ colorimetric analysis with double-layer hydrogel microneedle patch based on polyvinyl alcohol and carboxymethyl chitosan

Skin interstitial fluid (ISF) has emerged as a significant reservoir of biomarkers for disease diagnosis and prevention. Microneedle (MN) patches are regarded as an optimal platform for ISF extraction from the skin due to their non-invasive nature. However, challenges such as prolonged sampling durations and complex detection procedures impede timely metabolic analysis. In this investigation, we amalgamated MN technology with immobilized enzyme technology to fabricate a dual-layer MN patch integrating sampling and detection functionalities, thereby enabling in-situ colorimetric detection of hyperglycemia. The tip layer of the patch, comprising polyvinyl alcohol/carboxymethyl chitosan (PVA/CMCS) MN, was synthesized utilizing a chemical crosslinking approach for the first time, with glucose oxidase (GOx) being incorporated. The hydrophilicity of CMCS expedited the extraction process, facilitating the retrieval of approximately 10 mg of ISF within 10 min. The backing layer consisted of an immobilized polyvinyl alcohol-chitosan-horseradish peroxidase (PVA-CS-HRP) hydrogel film loaded with 3,3′, 5,5′-tetramethylbenzidine (TMB). Incorporating macromolecular polymer PVA and CS for HRP immobilization addressed the issue of poor stability associated with traditional natural enzymes, thereby enhancing the sensitivity of the reaction system. The in-situ colorimetric sensor facilitated minimally invasive ISF extraction and swift conversion of glucose levels into detectable color changes.

Confirming the Suitability of a Gentamicin Dosing Strategy in Neonates Using the Population Pharmacokinetic Approach with Truncated Sampling Duration.

(1) Background: Gentamicin is known to be nephrotoxic and ototoxic. Although gentamicin dosage guidelines have been established for preterm and term neonates, reports do show attainment of recommended peak concentrations but toxic gentamicin concentrations are common in this age group. (2) Methods: This was a prospective, observational study conducted in Namibia with 52 neonates. A dose of 5 mg/kg gentamicin was administered over 3-5 s every 24 h in combination with benzylpenicillin 100,000 IU/kg/12 h or ampicillin 50 mg/kg/8 h. Two blood samples were collected from each participant using a truncated pharmacokinetic sampling schedule. (3) Results: The one-compartment linear pharmacokinetic model best described the data. Birthweight, postnatal age, and white blood cell count were predictive of clearance (CL), while birthweight was predictive of volume (V). For the typical neonate (median weight 1.57 kg, median postnatal age 4 days (0.011 years), median log-transformed WBC of 2.39), predicted CL and V were 0.069 L/h and 0.417 L, respectively-similar to literature values. Simulated gentamicin concentrations varied with respect to postnatal age and bodyweight. (4) Conclusions: A 5 mg/kg/24 h dosage regimen yielded simulated gentamicin concentrations with respect to age and birthweight similar to those previously reported in the literature to be safe and efficacious, confirming its appropriateness.

Sampling-rate calibration vs. equilibrium calibration for in vivo solid-phase microextraction: Analysis of neonicotinoids in bananas

In vivo solid-phase microextraction (in vivo SPME) is an emerging fascinating sample pretreatment technique, but its quantitative correction method is different from the traditional correction methods, which has become a bottleneck limiting its development. At present, the sampling-rate calibration and equilibrium calibration are mainly used, however, their characteristics and applicability are not clear. In this study, the sampling-rate calibration and equilibrium calibration were evaluated in the case of the determination of neonicotinoids in bananas by in vivo SPME. The factors that affect the sampling rate (Rs), such as the matrix states, sampling durations, and individual differences were studied, and they all had impacts on Rs. Conversely, the equilibrium distribution coefficient (Kfs) remained constant after extraction equilibrium and the individual differences were smaller. The highest accuracy and precision were achieved by equilibrium calibration, and the relative recoveries were in the range of 83.2 %-104.3 % with the relative standard deviations below 8.1 % compared to a standard QuEChERS-based method. The lower limits of quantification for 4 neonicotinoids in bananas were below 5 ng g−1, lower than the standard method and the maximum residue levels in China and the European Union. This work clarifies the characteristics, rules and performance of the sampling-rate calibration and equilibrium calibration, which is of crucial importance for the development and application of in vivo SPME. The developed method is convenient, sensitive, and accurate for the determination of pesticide residues, which is of great significance to guide the safe use of pesticides in the field and prevent products with excessive pesticide residues from entering the market.

Does uncertainty affect the limits of arbitrage? Evidence from the U.S. stock markets

This study analyzes how uncertainty affects the correction process of mispricing. We extract stock market data from the United States spanning from January 1976 to December 2016, and discover that uncertainty exerts a notable impact on traders’ decision-making processes. Various robustness tests have been conducted to validate the credibility of our findings. Notably, the extension of the sample duration until December 2022, encompassing the disruptive COVID-19 pandemic, serves to fortify the cohesion and reliability of our primary analysis, with the findings exhibiting consistency. Additionally, we examine how investor sentiment affects future returns under different uncertainty and overpricing ranks. An inverse relation between investor sentiment and uncertainty is also detected. We contribute to the existing literature by revealing potential features that affect the limits of arbitrage. Our results provide insights in designing arbitrage mechanisms and assist arbitrageurs in strategizing their operations with stocks under different magnitudes of uncertainty.

Protein level alteration and micronuclei induction in Channa punctatus fish exposed to chlorpyrifos and their alleviation by Melissa officinalis and Mentha piperita extracts

Aim: To assess alteration in the protein levels of major organs and induction of micronuclei in the freshwater fish, Channa punctatus following exposure to chlorpyrifos, while also investigating the potential mitigating effects of extracts from Melissa officinalis and Mentha piperita on the adverse impacts induced by this pesticide. Methodology: Two weeks of acclimatized healthy fish were divided into four different groups. Group G1 served as the control group, while G2 contained chlorpyrifos (LC50/10, 96 hr). Group G3 was exposed to chlorpyrifos (LC50/10, 96 hr) along with 8 mg l-1 of Melissa officinalis ethanolic extract, and similarly, G4 contained chlorpyrifos (LC50/10, 96 hr) along with 8 mg l-1 ethanolic extract of Mentha piperita. Sampling was conducted over various durations of 7, 14, 21, and 28 days. The ethanolic extracts of Melissa officinalis and Mentha piperita were used as remedial compounds as they are rich in several bioactive compounds, primarily polyphenols. Results: The investigation revealed a notable decrease in the total protein content of kidney, liver, gills and muscles following exposure to chlorpyrifos after each sampling duration. While, upon exposure to remedies containing the ethanolic extracts of Melissa officinalis and Mentha piperita, the protein levels exhibited a significant recovery (p &lt; 0.05) in a duration-dependent manner, compared to the control group. This suggests a promising ameliorative capability of Melissa officinalis and Mentha piperita against chlorpyrifos toxicity. Further, the induction of micronuclei by chlorpyrifos and their subsequent recovery through the application of phytoextracts Melissa officinalis and Mentha piperita displayed a similar pattern, indicating the potential protective effects of these extracts against chlorpyrifos-induced genotoxicity. Interpretation: It is plausible to conclude that standardized doses of Melissa officinalis and Mentha piperita hold the potential to enhance aquaculture practices and safeguard fish production in agriculturally contaminated water bodies. These findings emphasize their valuable contribution in sustaining fish health amidst toxic environments. Key words: Channa punctatus, Chlorpyrifos, Melissa officinalis, Mentha piperita

The Impact of Kundalini Yoga on Cognitive Function and Memory: A Systematic Review of Randomized Controlled Trials.

Cognitive decline and dementia are significant public health challenges influenced by various modifiable and non-modifiable risk factors. Kundalini yoga (KY) has emerged as a promising non-pharmacological intervention to enhance cognitive function and memory in older adults at risk of cognitive decline. This systematic review aims to evaluate the effects of KY on cognitive function, memory impairment, and related neurobiological and psychological outcomes in older adults. A comprehensive literature search was conducted across PubMed, MEDLINE, Scopus, Web of Science, and the Cochrane Library, covering studies published from January 2000 to December 2023. Randomised controlled trials (RCTs) were included to compare KY with other cognitive enhancement strategies, such as memory enhancement training (MET) and psychoeducation. Five RCTs with 215 participants met the inclusion criteria. The studies varied in sample size (11 to 81 participants) and duration (12 to 24 weeks). The participants were older adults (≥55 years) with mild cognitive impairment (MCI) or subjective cognitive decline (SCD). The interventions compared KY with MET or psychoeducation. KY consistently improved memory performance and executive function. Significant mood enhancements, increased hippocampal volume, and better neural connectivity were observed. KY also reduced pro-inflammatory cytokines and altered ageing-related gene expression, demonstrating both cognitive and neurobiological benefits. KY appears to be a promising intervention for enhancing cognitive function, mood, and neurobiological health in older adults at risk of cognitive decline and dementia. While further research with more extensive, well-designed RCTs is needed to confirm these findings and optimise intervention strategies, the existing evidence supports the integration of KY into cognitive health programmes. Practitioners should ensure proper training and gradual progression to maximise benefits and minimise risks.

Rapid determination of germanium in lignite coal and coal-related solid byproducts by graphite furnace digestion inductively coupled plasma emission spectroscopy

This study developed a rapid and efficient graphite furnace digestion combined with inductively coupled plasma emission spectrometry (ICP-OES) method, enabling precise quantification of germanium (Ge) in coal and various coal-derived metallurgical byproducts across a broad concentration level (∼ppm-n%). The graphite furnace digestion conditions were examined intensively as a function of the acid amounts of HNO3 and HF (5–10 mL), temperature (80–180 °C), time (1–5 h), and acid drive methods (H3BO3 neutralization versus heating). Coal references including SARM 19, SARM 20, NIST SRM 1632e, and fly ash standard NIST SRM 2689 were tested. The optimum recovery of germanium was obtained when the HNO3 dosage, HF dosage, solid sample mass, temperature, and duration time were 10 mL, 5 mL, 0.1 g, 80 °C and 1 h. Agreement of 95.15–96.54 % between the measured and certified value was obtained under the optimum conditions. The spiked recovery was 103.23–103.54 %, indicating the matrix-analytes interactions were negligible. Boric acid neutralization reduced the recovery rates to 47.2–49.3 % and was not be appropriate for driving HF. The optimal spectral line for determining Ge is at a wavelength of 265.117 nm, at which the limit of detect and the limit of quantification were 0.46 μg L−1 and 1.53 μg L−1, respectively. The applicability of the method was validated by quantifying Ge in Ge-rich lignite, fly ashes (FA), and chlorinated distillation residue (CR) samples. The concentration of Ge in coals was 44.75–225.41 μg g−1, the content in FA was 0.68%–2.3 %, and the content in CR was 0.18 %, with the uncertainty of the method obtained being less than 0.5 %. X-ray fluorescence spectrometer (XRF) was used to verify the results. The difference between XRF data and ICP-OES data was less than 5 %, confirming the accuracy and reproductivity of the analytical method.