Analysis and discrimination of adhesive species using ATR-FTIR combined with Raman, and HS-GC-IMS together with multivariate statistical analysis.

Identifying the species and origin of adhesives in criminal investigations aids in narrowing inquiry scope and supporting case detection. This study introduces two advanced combined analytical techniques for distinguishing adhesive species, including attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) combined with Raman spectroscopy, and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) together with multivariate statistical analysis. ATR-FTIR categorized seven adhesives into three groups based on the base materials, with further differentiation achieved via Raman spectra. Analysis of volatile components identified 79 volatile organic compounds (VOCs), with esters being the most concentrated. The fingerprint profile clearly illustrated the characteristic fingerprint sequence and unique marker compounds of each adhesive, effectively enabling their differentiation. Multivariate statistical analysis methods, including principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), heatmap, and hierarchical cluster analysis (HCA), were utilized to visually interpret the classification of adhesives. This integrated analytical approach provides a comprehensive analysis of adhesive compositions, facilitating the diversification and precision of adhesive species identification, and broadening the scope for detecting and analyzing trace evidence in forensic science.

Identification of multimodal brain imaging biomarkers in first-episode drugs-naive major depressive disorder through a multi-site large-scale MRI consortium data.

BACKGROUND: Major depressive disorder (MDD) is a severe and common mental illness. The first-episode drugs-naive MDD (FEDN-MDD) patients, who have not undergone medication intervention, contribute to understanding the biological basis of MDD. Multimodal Magnetic Resonance Imaging can provide a comprehensive understanding of brain functional and structural abnormalities in MDD. However, most MDD studies use single-modal, small-scale MRI data. And several multimodal studies of MDD are limited to simple linear combinations of functional and structural features. METHODS: We screened a large sample of FEDN-MDD patients and healthy controlsmultimodal MRI data. Extracting the fractional amplitude of low-frequency fluctuations (fALFF) feature from functional magnetic resonance imaging and the gray matter volume (GMV) feature from structural magnetic resonance imaging. The mCCA-jICA method was used to integrate these two modal features to investigate the functional-structural co-variation abnormalities in MDD. To validate the stability of the extracted functional-structural covariant abnormalities features, we apply them to identify FEDN-MDD patients. RESULTS: The results show that compared to healthy controls, FEDN-MDD patients exhibit joint group-discriminative independent component and modality-specific group-discriminative independent component, suggesting functional-structural covariant abnormalities in MDD patients. Using lightGBM classifier, we achieve a classification accuracy of 99.84 %. LIMITATION: We use GMV and fALFF for multimodal fusion shows promise, but requires further validation with other datasets and exploration of additional multimodal features. CONCLUSIONS: This may indicate that multimodal fusion features can effectively explore information between different modalities and can accurately identify FEDN-MDD patients, suggesting their potential as multimodal brain imaging biomarkers for MDD.

Geochemical exploration for tantalum in coltan-rich pegmatites at Bewadze-Mankoadze area of the Kibi-Winneba Belt, southern Ghana: Constraints from exploratory data analysis.

The Bewadze-Mankoadze pegmatites in the Kibi-Winneba Belt of Ghana host several columbite group minerals (WGM) and wodginite group minerals (WGM) as well as other rare and radioactive elements such as uraninite and cesium. In this study, petrographic studies of rock samples from pegmatite outcrops and statistical analysis of the major and minor elements were conducted to identify the pathfinder elements of a new tantalum deposit in the area. Ten samples were obtained from each town for whole-rock geochemistry and thin sections were prepared from some of the samples taken for petrographic analysis. The petrographic analyses showed the presence of quartz, K-feldspars, plagioclase, muscovite, spodumene, albite, tourmaline, columbite group minerals, and montebrasite, which indicate that the studied samples are granitic pegmatites. The geochemical data of the 10 samples obtained from each town showed high concentrations of Cr, Cs, Rb, Sm, and Ta. The Ta concentrations ranged from 10.5 to 773 ppm with an average value of 260 ppm. Q-Q plots showed outliers and variations from the dataset's normal distribution, which were fixed by centred log-ratio transformation and demonstrated to be normal by the Kolmogorov-Smirnov test and Shapiro-Wilk test for normality. Spearman correlation revealed that Sc, Ga, Nb, and Cs showed a moderate to strong correlation with Ta. Factor analysis indicated elemental association of Ta with Cs, Zn, Nb, MgO, Sc, Ga, and V. Three (3) multi-element relationships were discovered by hierarchical cluster analysis: (1) As, La, Hf, CaO, U, Co, Pb, Ce, Ba and Na2O, (2) V, Nb, Ta, Ga, Sc, Cr, Cu, Nb and MgO, and (3) Ni, SiO2, Cs, Zn, Sm, Rb, K2O, Y, Th, Al2O3 and Fe2O3. Hence, a comparison of the results of the multivariate statistics established Sc, Ga, Nb, and Cs as the pathfinders of tantalum in the Bewadze-Mankoadze area. Geochemical anomalies involving these elements can be observed in the south-western portion of the study area, according to single and multi-element halo mapping. It is therefore recommended that exploration activities for tantalum mineralization should focus on the south-western part of the study area, where the anomalies of the pathfinder elements are located.

Chemical Variability of the Leaf Essential Oil of Two Subspecies of Juniperus oxycedrus L. from Northwestern Algeria.

Thirty-seven essential oil samples have been isolated from leaves of individual plants of Juniperus oxycedrus (subspecies oxycedrus and macrocarpa) growing wild in Tlemcen and Aïn Témouchent provinces (Northwestern Algeria). Analysis of eight selected oil samples by GC(RI), GC/MS and 13C NMR, allowed the identification of 88 components that accounted for 84.4-99.5% of the whole compositions. The 37 compositions were subjected to statistical analysis which suggested the existence of groups and sub-groups I, IIA and IIB. Group I, the most important group with 24 oil samples out of 37, differed from sub-groups IIA and IIB, essentially by the high content of α-pinene (mean value, 69.2%; SD 6.24). Sub-groups IIA and IIB were differentiated by their content of α-pinene (Mean values, 49.7% and 27.3%, respectively) as well as δ-3-carene (10.3%, sub-group IIA), sabinene and (Z)-6-pentadecen-2-one (8.7% and 4.9%, respectively, sub-group IIB).

A narrative review of the relationship between head and neck cancer and obstructive sleep apnea: Clinical studies and statistical analysis.

Obstructive sleep apnea (OSA) is an underestimated and overlooked comorbidity in head and neck cancer (HNC) care. Refining HNC-OSA management requires an improved grasp of the HNC-OSA relationship. Thus, this paper reviews the current course of HNC therapy, causal and associative relationships before and after treatment, and statistical methods quantifying HNC-OSA interactions. This evaluation serves a dual purpose: to support oncologists and sleep physicians in improving the treatment outcomes of patients undergoing HNC treatment by considering OSA as a comorbidity and to assist researchers in selecting suitable analytical models for investigating the correlation between OSA and HNC. The investigation confirms a positive correlation between the apnea-hypopnea index (AHI) and primary tumor size, consistent with prior findings. Case studies also reported new evidence of lipoma and head-neck tumors triggering OSA, and sleep apnea surgery prompting tumor development. This paper provides an overview of existing statistical models and offers suggestions for model selection and a framework for designing experiments that delve into research questions surrounding the link between OSA and HNC across various stages of cancer treatment. Despite progress, understanding the HNC-OSA interplay remains incomplete due to limited histological, molecular, and clinical data. Future studies with longitudinal data are crucial for comprehensive insights.

Radionuclides distribution in soils and radon level assessment in dwellings of Mungo and Nkam Divisions, Cameroon.

Radionuclide and radon levels have been investigated in soil samples and residential environments within the Mungo and Nkam Divisions of the Littoral Region. These analyses employed gamma spectrometry facilitated by a NaI (Tl) detector for soil samples, yielding average activity concentrations of 226Ra, 232Th, and 40 K at 23.8, 72, and 105 Bq kg-1, respectively. Various radiological parameters were calculated to evaluate radiological hazards. Additionally, the indoor radon concentrations were quantified utilizing the CR-39 solid-state nuclear track detector (Radtrack), revealing an average concentration of 25 Bq m-3 and an associated inhalation dose of 0.66 mSv y-1. Risk assessments for lung cancer attributable to indoor radon exposure incorporated models such as the Harley model. An observed moderate correlation between indoor radon levels and external 226Ra concentrations implies that radon intrusion indoors might be substantially influenced by the 226Ra present in the subjacent soil, considering the construction of residential structures directly upon these terrains.

Sustainable Development in Rural Underserved Communities through Improved Responsible Management of Decentralized Wastewater Infrastructure: A Focus on the Alabama Black Belt.

Despite global efforts on meeting sustainable development goals by 2030, persistent and widespread sanitation deficits in rural, underserved communities in high-income countries─including the United States (US)─challenge achieving this target. The recent US federal infrastructure funding, coupled with research efforts to explore innovative, alternative decentralized wastewater systems, are unprecedented opportunities for addressing basic sanitation gaps in these communities. Yet, understanding how to best manage these systems for sustainable operations and maintenance (O&M) is still a national need. Here, we develop an integrated management approach for achieving such sustainable systems, taking into account the utility structure, operational aspects, and possible barriers impeding effective management of decentralized wastewater infrastructure. We demonstrate this approach through a binomial logistic regression of survey responses from 114 public and private management entities (e.g., water and sewer utilities) operating in 27 states in the US, targeting the rural Alabama Black Belt wastewater issues. Our assessment introduces policy areas that support sustainable decentralized wastewater systems management and operations, including privatizing water-wastewater infrastructure systems, incentivizing/mandating the consolidation of utility management of these systems, federally funding the O&M, and developing and retaining water-wastewater workforce in rural, underserved communities. Our discussions give rise to a holistic empirical understanding of effective management of decentralized wastewater infrastructure for rural, underserved communities in the US, thereby contributing to global conversations on sustainable development.

Identifying groundwater characteristics and controlling factors in Jiaozhou Bay's northern coastal region, China: a combined approach of multivariate statistics, isotope analysis, and field empirical investigations.

Explicit identification of hydrochemical processes and their controlling factors within groundwater systems is critical for the sustainable utilization of water resources in coastal urban areas. This study was undertaken in the North Coastal Region of Jiaozhou Bay (NCRJB), located in the eastern part of Shandong Province, China, an area grappling with significant issues of groundwater quality degradation and water scarcity. A total of 105 groundwater samples and 34 surface water samples, collected from 2020 to 2024, were analyzed and studied using various hydrogeological tools, multivariate statistical analyses, and water quality assessment methods. These include the Piper diagram, hydrochemical facies evolution diagram (HFE-D), Principal Components Analysis (PCA), correlation analysis, stable isotope analysis, Water Quality Index (WQI), and USSL diagrams. The results indicated that all surface water and pore groundwater samples were categorized as Na-Cl type, exhibiting high Total Dissolved Solids (TDS) and Electrical Conductivity (EC) values, characteristics that render them poor to unsuitable for drinking and irrigation purposes. The fracture groundwater is predominantly of the Ca-Na-Cl mixed type, with average suitability for irrigation and a limited proportion (22.5%) deemed suitable for drinking. Seawater intrusion, primarily through the surface water system, and the impact of human activities were identified as the predominant controlling factors con-tributing to the degradation of the local groundwater environment. Field empirical investigations further validated the results derived from hydrogeological assessments, multivariate statistical analyses, and isotopic approaches. The long-term shifts in hydrochemical properties, along with the latent threat of seawater intrusion, exhibit an upward trend during the dry season and show a certain degree of mitigation during the wet season. This study highlights that field investigations, in conjunction with hydrochemical tools, multivariate statistical analyses, and stable isotope analysis, can successfully furnish reliable insights into the predominant mechanisms governing regional groundwater evolution within the context of long-term and intricate envi-ronmental settings.

The importance of factorial design on the optimization of biosensor performance: immobilization of glucose oxidase as a case study.

Conventionally, the optimization of glucose biosensors is achieved by varying the concentrations of the individual reagents used to immobilize the enzyme. In this work, the effect and interaction between glucose oxidase enzyme (GOx), ferrocene methanol (Fc), and multi-walled carbon nanotubes (MWCNTs) at different concentrations were investigated by a design of experiments (DoE). For this analysis, a factorial design with three factors and two levels each was used with the software RStudio for statistical analysis. The data were obtained by electrochemical experiments on the immobilization of GOx-Fc/MWCNT at different concentrations. The results showed that the factorial DoE method was confirmed by the non-normality of the residuals and the outliers of the experiment. When examining the effects of the variables, analyzing the half-normal distribution and the effects and contrasts for GOx-Fc/MWCNT, the factors that showed the greatest influence on the electrochemical response were GOx, MWCNT, Fc, and MWCNT:Fc, and there is a high correlation between the factors GOx, MWCNT, Fc, and MWCNT:Fc, as shown by the analysis of homoscedasticity and multicollinearity. With these statistical analyses and experimental designs, it was possible to find the optimal conditions for different factors: 10 mM mL-1 GOx, 2 mg mL-1 Fc, and 15 mg mL-1 MWCNT show a greater amperometric response in the glucose oxidation. This work contributes to advancing enzyme immobilization strategies for glucose biosensor applications. Systematic investigation of DoE leads to optimized immobilization for GOx, enables better performance as a glucose biosensor, and allows the prediction of some outcomes.

Enhanced Synthesis of Poly(1,4-butanediol itaconate) via Box-Behnken Design Optimization.

At present, there are too few organ and tissue donors. Due to the needs of the medical market, scientists are seeking new solutions. Those can be found in tissue engineering by synthesizing synthetic cell scaffolds. We have decided to synthesize a potential UV-crosslinked bio-ink for 3D printing, poly(1,4-butanediol itaconate), in response to emerging needs. Diol polyesters are commonly investigated for their use in tissue engineering. However, itaconic acid makes it possible to post-modify the obtained polymer via UV-crosslinking. This work aims to optimize the synthesis of poly(1,4-butanediol itaconate) in the presence of a catalyst, zinc acetate, without using any toxic reactant. The experiments used itaconic acid and 1,4-butanediol using the Box-Behnken mathematical planning method. The input variables were the amount of the catalyst used, as well as the time and temperature of the synthesis. The optimized output variables were the percentage conversion of carboxyl groups, the percentage of unreacted C=C bonds, and the product's visual and viscosity analysis. The significance of the varying synthesis parameters was determined in each statistical model. The optimum conditions were as follows: amount of catalyst 0.3%nCOOH, reaction time 4 h, and temperature 150 °C. The temperature had the most significant impact on the product characteristics, mainly due to side reactions. Experimentally developed models of the polymerization process enable the effective synthesis of a polymer "tailor-made" for a specific application.

Statistical Analysis of Large Format Additively Manufactured Polyethylene Terephthalate Glycol with 30% Carbon Fiber Tensile Data.

In large format additive manufacturing (LFAM), a keener understanding of the relationship between the manufacture method and material temperature dependency is needed for the production of large polymer parts. Statistical analyses supported by material properties and a meso-structural understanding of LFAM are applied to elucidate tensile data trends. The data from LFAM polyethylene terephthalate glycol with 30% carbon fiber (CF) (PETG CF30%) panels (diagonal, horizontal, and vertical in the x-y print plane) and injection-molded specimens tensile tested at six different testing temperatures (room temperature, 40 °C, 50 °C, 60 °C, 70 °C, and 80 °C) were used for statistical analyses. A standard deviation, a coefficient of variation, and a two-way and one-way analyses of variance (ANOVA) were conducted. The manufacturing method (44.2%) and temperature (47.4%) have a strong effect on the ultimate tensile strength, in which temperature (82.6%) dominates Young's modulus. To explain the difference between the ultimate tensile strength of vertical, diagonal, and horizontal specimens at room temperature, a visual inspection of the specimen failure was conducted and the maximum stress at the crack tip was calculated analytically. The decreased strength in the diagonal specimens resulted from the reliance on interlaminar adhesion strength. Future work will consider the effect of the void space variation on tensile strength variance.

Introducing JOSPT Methods: A Journal Focused on Advancing the Research Methods Applied to the Musculoskeletal Rehabilitation Field.

SYNOPSIS: In 2025, JOSPT will continue its mission to enhance research in the field of musculoskeletal rehabilitation. JOSPT aims to support authors who are working to advance the research methods applied to answer clinical questions in the musculoskeletal rehabilitation field. Using the most robust methods helps authors ensure their studies can have immediate impact on health policies and clinical practice. With this editorial, we introduce a new gold open-access journal, JOSPT Methods, where research will be available to read for free, immediately upon publication. J Orthop Sports Phys Ther 2024;54(10):1-3. doi:10.2519/jospt.2024.12972.

Optimal parameter identification of solid oxide fuel cell using modified fire Hawk algorithm.

An accurate and efficient approach is required to identify the unknown parameters of solid oxide fuel cell (SOFC) mathematical model for a robust design of any energy system considering SOFC. This research study proposes a modified fire hawk algorithm (MFHA) to determine the values of SOFC model parameters. The performance evaluation of MFHA is tested on two case studies. Firstly, the performance of MFHA is tested on commercially available cylindrical cell developed by Siemens at four temperatures. Results reveal that the least value of sum of squared error (SSE) is 1.04E-05, 2.30E-05, 1.03E-05, and 1.60E-05 at 1073 K, 1173 K, 1213 K, and 1273 K respectively. Results obtained using MFHA have been compared with original fire hawk algorithm (FHA) and other well established and recent algorithms. Secondly, MFHA is implemented for estimating unknown parameters of a 5 kW dynamic tabular stack of 96 cells at various pressures and temperatures. The obtained value of SSE at different temperatures of 873 K, 923 K, 973 K, 1023 K and 1073 K is 1.18E-03, 6.12E-03, 2.21E-02, 5.18E-02, and 6.00E-02, respectively whereas, SSE at different pressures of 1 atm, 2 atm, 3 atm, 4 atm, and 5 atm is 6.05E-02, 6.11E-02, 5.53E-02, 5.11E-02, and 6.64E-02 respectively.

Significant impact of the covid-19 pandemic on methane emissions evaluated by comprehensive statistical analysis of satellite data.

The COVID-19 pandemic has significantly influenced various aspects of society, including environmental factors such as methane emissions. This study investigates the changes in methane concentrations in Seoul, South Korea, from 2019 to 2023, using TROPOMI satellite data and rigorous statistical analyses. The normality of the sample data is first assessed using the Shapiro-Wilk (S-W) and Kolmogorov-Smirnov (K-S) tests, indicating that the data can be considered to come from a normal distribution. The S-W test demonstrated superior discriminative power (highest statistical power: 0.8668) compared to the K-S test (highest statistical power: 0.4002), confirming the validity of parametric tests for our data. The S-W test shows better discriminative power than the K-S test in terms of sensitivity to departures from normality, particularly for small sample sizes. Based on this confirmation, parametric tests such as analysis of variance (ANOVA) and post-hoc tests (Bonferroni correction, Tukey's HSD, Scheffe's method) are employed to identify significant differences in methane levels across different years. The ANOVA results show a statistically significant difference in methane concentrations across years (p-value: 2.02 × 10 - 13 , F-value: 26.572). Post-hoc analyses reveal no significant difference in methane concentrations between 2019 and 2020 (p-values: Bonferroni - 0.1045, Tukey's HSD - 0.397, Scheffe's - 0.1045), and no significant difference between 2020 and 2021 (p-values: Bonferroni - 0.917, Tukey's HSD - 0.840, Scheffe's - 0.917). However, a significant increase in methane levels is observed from 2022 to 2023 (p-values: Bonferroni - 0.0001, Tukey's HSD - 0.0002, Scheffe's - 0.0001), correlating with the "new normal" policy implemented in South Korea starting in November 2021 and effectively from the beginning of 2022. This suggests that changes in industrial activities and transportation patterns due to the "new normal" have contributed to higher methane emissions. Student's t-test and Welch's t-test were used to validate the ANOVA results. Permutation tests showed no significant difference between 2019 and 2020 (test statistic: -0.0096, p-values: 0.1191 for Student's and 0.1156 for Welch's). However, a significant difference was found between 2022 and 2023 (test statistic: -0.0172, p-value: 0.0001), confirming ANOVA results that indicated increased methane levels post-pandemic. This study provides a robust quantitative assessment of the pandemic's impact on methane levels and sets a methodological statistical approach for future research in the environmental research community.

Notches and Fatigue on Aircraft-Grade Aluminium Alloys.

The influence of notches and fatigue on the ultimate tensile strength and elongation at break of aluminium alloys (2024-T3, 6061-T4, 6061-T4 uncoated, 6061-T6 uncoated, 7075-T0, and 7076-T6) is presented in this study. A total of 120 specimens were used. On all specimens, notches were made using a CNC machine, with 60 of them subjected to low-cycle fatigue (LCF) before undergoing the tensile test. Based on the statistical examination of the measured data, mathematical prediction models have been established. Compared to their unscratched counterparts, the results indicate a significant decrease in the UTS and elongation at break for both notched and notched-fatigued specimens. The LCF pre-treatment contributes to the negative impacts of the notches, resulting in reduced values for the UTS and elongation at break, thus concluding that surface integrity is critical for maintaining the structural strength of aircraft components.

Exploring the temporal toxicity signature: A baseline evaluation of the heavy metal concentration in estuarine core sediments in the coastal region of cauvery delta, bay of bengal.

Globally, the concentration of heavy metals and sediment toxicity analysis are significant liabilities to aquatic environments. This scrutiny outlines the sediment textures, heavy metals and toxicity status associated with environmental pollution indices in the core sediment of the Cauvery and Vettar estuaries, East coast of India. The impact of rapid industrialization, urbanization, harbour activities and agricultural activities influences on the twain estuary is a significant concern to designate the environment. The contamination status of the sediments affects the potential biodiversity, ecological risks and human health. A total of two core sediments were recovered from the Cauvery and Vettar estuaries in March 2023 to decipher the environmental pollution status. Meticulous observation of the textural studies underscores the prevalence of sand content in Cauvery, and Vettar sediments consist of predominate clay content and minor silt contents. Furthermore, the organic matter is augmented in the Vettar River due to the higher input of waste disposal, seaweeds and algae due to the surrounding landmass. Twain core sediments argue that heavy metal concentration is decreasing in order as Fe > Zn > Ni > Pb > Cu > Cr by using portable X-ray fluorescence (pXRF) spectrometry. Remarkable results of environmental pollution indices such as Igeo, Ef, Cf, Cd and mCd state very highly polluted, extreme enrichments, high contamination and very high degree of contamination. Furthermore, the potential ecological risk indices such as PLI, SQGs, and PERI argue polluted, medium to high toxicity and moderate adverse ecological risk to the estuarine regions. Statistical analysis of the heavy metal affirms the enrichment of Fe metals may derive from lithogenic and/or anthropogenic influences, and the other studied metals such as Cu, Ni, Zn, Pb and Cr may be influenced by the anthropogenic activities in the aspect of point and non-point pollution sources. This could result from both estuaries undergoing higher pollution, in which the Vettar estuary is a considerable environmental risk zone compared to the Cauvery river due to the impact of industrial effluents and rapid urbanization activities. This finding underscores the urgent need for enhanced estuarine sediment quality study and comprehensive assessment of sediment toxicity, regulating the beneficial acumen for the government to follow the suitable remediation on the embellish policy of river and marine environments.

Prevalence and Spatial Distribution Characteristics of Female Stress Urinary Incontinence in Mainland China.

Background and objective: Stress urinary incontinence (SUI) in women is a common condition that affects middle-aged and elderly women. Currently, there are still many limitations in the epidemiological research on SUI. This study aims to address the gap in the prevalence of female SUI in mainland China and provide theoretical support for the prevention and treatment of SUI. Methods: A comprehensive literature search was conducted on the prevalence of female SUI in mainland China, systematically searching Chinese and English databases including PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang Database, and Weipu Database as of April 1, 2024. Detailed criteria for screening and exclusion were established. The prevalence of SUI in the selected studies was synthesized using Stata MP (version 15) software, and a multisubgroup analysis, a sensitivity analysis, and publication bias detection of the prevalence of SUI were also performed using the software. Additionally, ArcGIS software (version 10.8) and Geoda software (version 1.2) were utilized to explore the geographical distribution characteristics of the prevalence of female SUI in mainland China. Key findings and limitations: A total of 688 articles were screened, and finally 85 articles were included. The overall rate of female SUI in mainland China was 24.5% (95% confidence interval: 22.5-26.5%). The heterogeneity of the study is statistically significant (I2 = 99.0%, p < 0.001). Based on significant heterogeneity, a multisubgroup analysis was conducted. The results showed that the prevalence of SUI varies among different publication years, literature quality scores, investigators, study settings, sampling methods, provinces, regions, coastal or inland areas, and rural or urban areas. A spatial econometric analysis indicated that the incidence of SUI in the east-west distribution showed a downward trend, while in the north-south distribution, the incidence rate of SUI showed a trend of first increasing and then decreasing. Additionally, a spatial metrology analysis showed similar trends in the distribution of SUI incidence. Conclusions and clinical implications: The high incidence rate of female SUI in mainland China and the regional differences observed indicate the need for further rigorous epidemiological investigation in the future. Patient summary: Stress urinary incontinence (SUI) is common among middle-aged and elderly women. The high prevalence of SUI in mainland China and the differences across regions emphasize the need for conducting more robust epidemiological studies in the future.

Statistical analysis plan for the SOLUTIONS randomised controlled trial with internal pilot: Solution Focused Brief Therapy (SFBT) in 10-17-year-olds presenting at policy custody.

BACKGROUND: Within England, children and young people entering police custody are referred to Liaison and Diversion (L&D) teams. These teams liaise with healthcare and other support services aiming to divert children and young people away from the criminal justice system. Although targeted psychological interventions are not typically offered to children and young people by L&D teams, evidence suggests that Solution Focused Brief Therapy (SFBT) leads to a reduction in internalising and externalising behaviour problems. METHODS: A two-arm individually randomised controlled trial (RCT) with internal pilot and process evaluation will be conducted with approximately 448 children and young people aged 10-17 years presenting at police custody suites who are referred to the L&D team or recruited via online routes if they have previously presented at any police custody suite in England. The primary outcome is the Self-Report Delinquency Measure (SRDM) at 6 months post-randomisation. Analyses will be performed using intention-to-treat. RESULTS: The statistical analysis plan (SAP) for the trial is described. The plan details of analyses to be undertaken which will be reported in the primary and any secondary publications. The plan was developed and published prior to locking our database and unblinding to treatment allocation. DISCUSSION: This RCT will evaluate the effectiveness of SFBT in reducing offending behaviours in CYP presenting at police custody suites including testing of moderating factors and sensitivity of the primary analyses. TRIAL REGISTRATION: ClinicalTrials.gov ISRCTN14195235. Registered on June 16, 2023.

Comprehensive comparison of two colour varieties of Perillae folium by UHPLC-Q-TOF/MS analysis combining with feature-based molecular networking.

Perillae Folium (PF), the leaf of Perilla frutescens (L.) Britt is extensively used as a culinary vegetable and medicinal herb in many countries. Purple PF (P. frutescens var. arguta) and green PF (P. frutescens var. frutescens) are two of the main varieties. In this study, UHPLC-Q-TOF/MS assisted with feature-based molecular networking (FBMN) was applied for chemical characterization. In total, 82 metabolites, mainly phenolic acid derivatives were identified from PF. With the help of FBMN, five organic acid glucosides together with three N-phenylpropenoyl-L-amino acids (NPAs) were identified in PF for the first time. Multivariate statistical methods were utilized for comprehensive comparison of purple and green PF profiles. 12 compounds with their relative contents varied significantly between purple and green PF were screened out. Overall, the present study offers valuable insights for chemical elucidation of PF which would be helpful for comprehensive utilization of PF resource.

Deciphering the point source carbon footprint puzzle: Land use dynamics and socio-economic drivers.

Point source carbon emissions account for approximately 80 % of total emissions. Investigating the influence of land use and socio-economic indicators on these emissions is crucial for achieving sustainable development goals. Existing research faces challenges such as focusing on specific regions, mixing variables that may exhibit multicollinearity, and lacking sufficient land use information. This study takes China, the largest emitting country, as a case study, utilizing geospatial big data to subdivide land use into 11 categories based on emission sectors. The impacts of land use and socio-economic indicators on different emission sectors are discussed from the perspectives of bivariate and spatial statistical analysis, with spatial hotspots identified. Hierarchical regression is used to evaluate the explanatory power of the indicators and to establish models, and potential carbon reduction strategies are further explored. Key findings reveal: (1) Significant multicollinearity between land use and socio-economic indicators was demonstrated, with land use explaining 57.1 % of emissions compared to 37.4 % explained by socio-economic indicators. The spatial consistency between land use and emissions exceeds 80 %, and the spatiotemporal variability is relatively low, making land use a more advantageous factor in explaining point source carbon emissions. (2) Agricultural mechanization increases emission intensity, but this efficient farming method helps convert surplus plowland, the largest influencing factor (Coefficient = 0.717), into carbon sinks, thereby controlling agricultural emissions. (3) Land intensification helps control industrial land, the main factor influencing industrial emissions (Coefficient = 0.392). It also contributes to the efficient use of carbon reduction technologies and industrial supporting land. (4) Mixed commercial and residential land has the greatest impact on commercial, service, and household emissions. However, its relationship with the economy (Correlation = 0.479) is stronger than its relationship with emissions (Correlation = 0.182), making it more applicable to cities that serve as economic growth hubs.