Cumulative Counts Research Articles

Mechanical properties and damage characterization of cracked granite after cyclic temperature action

Due to the unique geographical environment of the plateau, large-scale damage and destruction of fractured surrounding rock often occur during geotechnical engineering construction as a result of high-temperature cycles. Therefore, this study aims to investigate the mechanical properties and damage characteristics of fractured granite under the influence of cyclic temperature, uniaxial compression tests were conducted on granite specimens with pre-existing fractures at cyclic temperatures of 30 °C, 50 °C, 70 °C, 100 °C, and 130 °C. The study integrated analyses of characteristic stress, acoustic emission parameters, damage variables, fractal dimensions, and SEM to explore the mechanical properties and damage features of granite. The results indicated that at a 45° fracture inclination and a temperature of 70 °C, granite exhibited a distinct turning point in mechanical properties and damage characteristics. At the same cyclic temperature, granite with a 45° pre-existing fracture showed significant decreases in peak stress, elastic modulus, and σci/σm ratios, with the AE b-value drop point noticeably earlier, and both cumulative AE ring count and total energy reduced. The damage variable quickly reached its maximum, and the development of internal microcracks in the specimen is highly orderly. At the same fracture inclination, peak stress, elastic modulus, and σci/σm slightly increased at 70 °C, while AE ring counts and total energy were lower, indicating the degree of internal thermal damage in the specimen has significantly decreased, and the development of internal microcracks in the specimen has shown a marked reduction in orderliness. These findings provide theoretical insight into the meso-damage and failure mechanisms of granite influenced by different cyclic temperatures and fracture inclinations.

AI-Driven IoT And Blockchain Integration In Industry 5.0 A Systematic Review Of Supply Chain Transformation

The integration of Artificial Intelligence (AI), the Internet of Things (IoT), and Blockchain technologies in Industry 5.0 has revolutionized supply chain management, offering unprecedented opportunities for efficiency, transparency, and sustainability. This systematic review, which analyzed 120 peer-reviewed articles published between 2018 and 2024, provides a comprehensive exploration of the transformative potential of these technologies. The findings reveal that the convergence of AI-driven predictive analytics, IoT-enabled real-time monitoring, and Blockchain's decentralized ledger enhances decision-making, streamlines operations, and fosters trust across supply chain networks. Moreover, the study highlights the critical role of these technologies in achieving Environmental, Social, and Governance (ESG) compliance, with applications in sustainable sourcing, ethical practices, and carbon footprint reduction. However, challenges such as scalability, interoperability, and organizational resistance remain significant barriers to adoption, underscoring the need for innovative solutions and interdisciplinary approaches. The review also identifies emerging opportunities, including the integration of quantum computing and digital twins, which promise to address existing limitations and redefine supply chain capabilities. By synthesizing insights from over 120 studies with a cumulative citation count exceeding 30,000, this research provides valuable perspectives on the current state, challenges, and future directions of integrated supply chain technologies in Industry 5.0, offering actionable insights for researchers and practitioners aiming to advance the field.

COVID-19 latent age-specific mortality in US states: a county-level spatio-temporal analysis with counterfactuals.

During the COVID-19 pandemic, which spanned much of 2020-2023 and beyond, daily case and death counts were recorded globally. In this study, we examined available mortality counts and associated case counts, with a focus on the estimation missing information related to age distributions. In this paper, we explored a model-based paradigm for generating age distributions of mortality counts in a spatio-temporal context. We pursued this aim by employing Bayesian spatio-temporal lagged dependence models for weekly mortality at the county level. We compared three US states at the county level: South Carolina (SC), Ohio, and New Jersey (NJ). Models were developed for mortality counts using Bayesian spatio-temporal constructs, incorporating both dependence on current and cumulative case counts and lagged dependence on previous deaths. Age dependence was predicted based on total deaths in proportion to population estimates. This latent age field was generated as counterfactuals and then compared to observed deaths within age groups. The optimal retrospective space-time models for weekly mortality counts were those with lagged dependence and a function of caseload. Added random effects were found to vary across states: Ohio favored a spatially correlated model, while SC and NJ favored a simpler formulation. The generation of age-specific latent fields was performed for SC only and compared to a 15-month, 13-county data set of observed >65 age population. It is possible to model spatio-temporal variations in mortality at the county level with lagged dependencies, spatial effects, and case dependencies. In addition, it is also possible to generate latent age-specific fields based on estimates of death risk (using population proportions or more sophisticated modeling approaches). More detailed data will be needed to make more calibrated comparisons for future epidemic monitoring. The proposed discrepancy tool could serve as a useful resource for public health planners in tailoring interventions during epidemic situations.

Evaluation of pitolisant, sodium oxybate, solriamfetol, and modafinil for the management of narcolepsy: a retrospective analysis of the FAERS database.

Narcolepsy, a rare neurological disorder believed to have an autoimmune etiology, necessitates lifelong management. This study aimed to provide evidence supporting the safety of pharmacological treatment for narcolepsy. Five-year data on pitolisant, sodium oxybate, solriamfetol, and modafinil were extracted from the FDA Adverse Event Reporting System (FAERS) self-reporting database for the period spanning from 2019 to 2023. Various statistical methods, including the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network analysis (BCPNN), and multi-item gamma Poisson shrinker (MGPS), were employed to quantify the signals. Finally, a comparative analysis was conducted between demographic data, outcomes, and inherent associations among the medications and the signals. After data analysis, we obtained 50 signals (a cumulative count of 762 cases) for pitolisant, 640 signals (corresponding to 46,962 cases) for sodium oxybate, 40 signals (equivalent to 1,228 cases) for solriamfetol, and finally, 72 signals (representing 632 cases) for modafinil. The majority of these patients were female. Psychiatric and nervous system disorders were identified as the predominant adverse drug events (ADEs). For sodium oxybate, it is crucial to consider psychiatric disorders (such as suicidal ideation), respiratory disorders (including sleep apnea syndrome and respiratory depression), and signs of pregnancy and congenital familial diseases. For solriamfetol, noteworthy new ADEs include drug inefficacy, suicidal ideation, restless legs syndrome, and somnambulism. Furthermore, a relationship has been observed between modafinil use and restricted fetal growth, spontaneous abortion, cognitive disorders, and drug inefficacy and abuse. The majority of observed adverse reactions in this study were consistent with those listed in the product instructions. However, potential novel or notable ADE signals were identified through real-world pharmacovigilance analysis. It is anticipated that this paper will offer additional information regarding safe and rational medication for narcolepsy.

How user language affects conflict fatality estimates in ChatGPT

OpenAI’s ChatGPT language model has gained popularity as a powerful tool for problem-solving and information retrieval. However, concerns arise about the reproduction of biases present in the language-specific training data. In this study, we address this issue in the context of the Israeli–Palestinian and Turkish–Kurdish conflicts. Using GPT-3.5, we employed an automated query procedure to inquire about casualties in specific airstrikes, in both Hebrew and Arabic for the former conflict and Turkish and Kurdish for the latter. Our analysis reveals that GPT-3.5 provides 34 ± 11% lower fatality estimates when queried in the language of the attacker than in the language of the targeted group. Evasive answers denying the existence of such attacks further increase the discrepancy. A simplified analysis on the current GPT-4 model shows the same trends. To explain the origin of the bias, we conducted a systematic media content analysis of Arabic news sources. The media analysis suggests that the large-language model fails to link specific attacks to the corresponding fatality numbers reported in the Arabic news. Due to its reliance on co-occurring words, the large-language model may provide death tolls from different attacks with greater news impact or cumulative death counts that are prevalent in the training data. Given that large-language models may shape information dissemination in the future, the language bias identified in our study has the potential to amplify existing biases along linguistic dyads and contribute to information bubbles.

Remaining useful life prediction of flax fibre biocomposites under creep load by acoustic emission and deep learning

Natural fibre composites are increasingly explored for structural applications due to improvements in mechanical performance. For this, damage prognostics are crucial. We integrate acoustic emission (AE) and deep learning techniques to predict the remaining useful life of a flax fibre composite under long-term creep load. Derivatives of cumulative AE features with respect to time, such as cumulative hit and count rates, are introduced to reflect the performance degradation rate of the materials. These proposed features seem more relevant for creep lifespan than traditional AE features. Long short-term memory networks and temporal convolutional networks are adopted to estimate the composite’s remaining useful life. The two models' normalized root mean square errors are below 0.11, less than 20% of the error of a statistical Weibull-distribution benchmark model. Our study demonstrates that AE-based data-driven models can predict the performance degradation of composite materials subject to sustained load.

Annealing impact on mechanical performance and failure analysis assisted with acoustic inspection of carbon fiber reinforced poly‐ether‐ketone‐ketone composites under flexural and compressive loads

AbstractThis study investigates the effect of the annealing treatment for carbon fiber reinforced Polyether‐ketone‐ketone (CF/PEKK) composite structures under flexural and compressive loadings through reference, pre‐damaged, and annealed sample sets. Significant recovery of pre‐existing damage is observed after the annealing process, following both flexural and compressive loading. Acoustic emission (AE) inspection is employed to monitor the failure behavior and assess the impact of pre‐damage and annealing on CF/PEKK composite. Initially, AE inspection reveals that the reference CF/PEKK material exhibits a notable fiber‐related failure with 85% of cumulative AE counts under flexural load, whereas matrix‐related failures are more pronounced with 92% cumulative AE counts under compressive load. Pre‐damages in the matrix alter the cumulative count percentages and initiation time that are related to matrix, interface, and fiber‐related failures, under flexural and compressive loadings. After annealing, each cumulative AE count percentages are comparable to reference sample values, due to changes in microstructure and relieving of residual stresses. The annealing effect is further validated through dynamic scanning calorimetry (DSC) analysis results with increased glass transition temperature (Tg) and degree of crystallization (Xc). Overall, these findings indicate that annealing treatment effectively restores structural integrity and improves the mechanical performance of CF/PEKK composites.Highlights Annealing aims for damage recovery in CF/PEKK under flexural and compressive loads. Significant damage recovery in CF/PEKK is seen after annealing. Annealing raises Tg and crystallinity, and enhances CF/PEKK structural integrity.

Model Test on Acoustic Emission Monitoring of Loess Slope Failure.

The three stages of loess collapse are characterized by notable concealment and sudden onset due to the sudden nature of loess collapse and the prolonged duration of the peristaltic deformation stage. Traditional displacement monitoring methods struggle to detect early signals of instability and failure, leading to poor timeliness in disaster warnings. This project begins by examining non-force field information related to the loess collapse process. It focuses on acoustic emission monitoring and employs model tests to identify effective waveguide rods for monitoring loess collapse. Additionally, the project investigates the evolution anomalies of acoustic emission parameters before and after loess collapse failure, aiming to establish early warning criteria for loess collapse based on acoustic emission. This work provides a theoretical basis for monitoring and early warning of loess collapses. This study evaluates five parameters of the active waveguide system: sensor installation method, filling material, waveguide rod wall thickness, outer wrapping material, and outer wrapping wall thickness. The densities of the filler materials were tested using the optimal parameters derived from the tests to identify the best configurations for active acoustic emission (AE) waveguide systems suitable for monitoring loess collapse. Subsequently, a one-sided connected loess collapse model was employed for indoor tests, integrating real-time AE monitoring with the active waveguide method. This model facilitates the exploration of AE response characteristics during loess collapse and the analysis of destructive forms of loess collapse and time-sequence evolution of AE ringing counts throughout the deformation and destruction process. Results indicate that using filler materials with high elasticity modulus, high compactness, and low Poisson's ratio, along with thin outer wrapping and waveguide rod walls, leads to strong AE signals. As deformation damage of loess collapse intensifies, the number of AE ringing counts notably increases. A rapid rise in cumulative ringing counts can indicate a "sudden increase", or the b-value may stabilize, providing precursor information for loess collapse.

ASW^2DF: Census of the obscured star formation in a galaxy cluster in formation at z=2.2

We report the results of the deep and wide Atacama Large Millimeter/submillimeter Array (ALMA) 1.2\,mm mapping of the Spiderweb protocluster at $z=2.16$. The observations were divided into six contiguous fields covering a survey area of 19.3\,arcmin$^2$. With sim 13h of on-source time, the final maps in the six fields reach the 1sigma rms noise in a range of $40.3-57.1\ at a spatial resolution of $0 By using different source extraction codes and careful visual inspection, we detected 47 ALMA sources at a significance higher than 4sigma . We constructed the differential and cumulative number counts down to $ after the correction for purity and completeness obtained from Monte Carlo simulations. The ALMA 1.2\,mm number counts of dusty star-forming galaxies (DSFGs) in the Spiderweb protocluster are overall two times that of general fields, with some regions showing even higher overdensities (more than a factor of three). This is consistent with the results from previous studies over a larger scale using single-dish instruments. Comparison of the spatial distributions between different populations indicates that our ALMA sources are likely drawn from the same distribution as CO(1-0) emitters from the COALAS large program but are distinct from that of Halpha emitters. The cosmic star formation rate density of the ALMA sources is consistent with previous results (e.g., LABOCA 870\,mu m observations) after accounting for the difference in volume. We show that molecular gas masses estimates from dust measurements are not consistent with the ones derived from CO(1-0) and thus have to be taken with caution. The multiplicity fraction of single-dish DSFGs is higher than that of the field. Moreover, two extreme concentrations of ALMA sources were found on the outskirts of the Spiderweb protocluster, with an excess of more than 12 times that of the general fields. These results indicate that the ALMA-detected DSFGs are supplied through gas accretion along filaments and are triggered by intense star formation by accretion shocks before falling into the cluster center. The identified two galaxy groups are likely falling into the protocluster center and will trigger new merger events eventually, as indicated in simulations.

Evolution and Characterization of Uniaxial Compression Damage of Coal Measure Rock

In order to study the evolution law of uniaxial compression damage and its characterization method, three kinds of rocks with different lithology that commonly exist in coal measure rock were taken as the research objects to explore the relationship between their mineral composition, microstructure and mechanical properties, and the feasibility of acoustic emission (AE) characteristic parameters and AE spatial location to characterize the evolution process of uniaxial compression damage of rocks was compared and analyzed. A damage constitutive model based on AE cumulative ringing count was established and verified by numerical simulation. The results show that the differences in the micromorphology and mineral composition of coal measures with different lithology directly affect their physical and mechanical properties and load damage characteristics. AE characteristic ringing count can effectively represent the damage evolution process of rock during loading. Based on rock porosity characteristics and AE cumulative ringing count during loading, a constitutive model considering initial damage and cumulative damage was established. The theoretical analysis results of the damage constitutive model are in good agreement with the results of laboratory experiments and numerical simulation, which can be used to analyze the damage process of coal measure rock under load.

Adverse Childhood Experiences and Health Conditions and Risk Behaviors Among High School Students - Youth Risk Behavior Survey, United States, 2023.

Adverse childhood experiences (ACEs) are preventable, potentially traumatic events occurring before age 18 years. Data on ACEs among adolescents in the United States have primarily been collected through parent report and have not included important violence-related ACEs, including physical, sexual, and emotional abuse. This report presents the first national prevalence of self-reported ACEs among U.S. high school students aged <18 years, estimates associations between ACEs and 16 health conditions and risk behaviors, and calculates population-attributable fractions of ACEs with these conditions and behaviors using cross-sectional, nationally representative 2023 Youth Risk Behavior Survey data. Exposures were lifetime prevalence of individual (emotional, physical, and sexual abuse; physical neglect; witnessed intimate partner violence; household substance use; household poor mental health; and incarcerated or detained parent or guardian) ACEs and cumulative ACEs count (zero, one, two or three, or four or more). Health conditions and risk behaviors included violence risk factors, substance use, sexual behaviors, weight and weight perceptions, mental health, and suicidal thoughts and behaviors. Bivariate analyses assessed associations between individual and cumulative ACEs and demographics. Adjusted prevalence ratios assessed associations between cumulative ACEs and health conditions and risk behaviors, accounting for demographics. Population-attributable fractions were calculated to determine the potential reduction in health conditions and risk behaviors associated with preventing ACEs. ACEs were common, with approximately three in four students (76.1%) experiencing one or more ACEs and approximately one in five students (18.5%) experiencing four or more ACEs. The most common ACEs were emotional abuse (61.5%), physical abuse (31.8%), and household poor mental health (28.4%). Students who identified as female; American Indian or Alaska Native; multiracial; or gay or lesbian, bisexual, questioning, or who describe their sexual identity in some other way experienced the highest number of ACEs. Population-attributable fractions associated with experiencing ACEs were highest for suicide attempts (89.4%), seriously considering attempting suicide (85.4%), and prescription opioid misuse (84.3%). ACEs are prevalent among students and contribute substantially to numerous health conditions and risk behaviors in adolescence. Policymakers and public health professionals can use these findings to understand the potential public health impact of ACEs prevention to reduce adolescent suicidal behaviors, substance use, sexual risk behaviors, and other negative health conditions and risk behaviors and to understand current effects of ACEs among U.S. high school students.

Bending properties and damage evolution of fiber-reinforced aeolian sand backfill materials

Backfilling is a promising measure for controlling surface subsidence in mined-out areas and disposing solid wastes from the mineral processing, there are increasing demands of enhanced toughness and anti-cracking properties of backfill materials to prolong the service life under the complex loads. In this study, polypropylene (PP) fibers were employed to improve performance of backfills, four-point bending and uniaxial compression tests were conducted to investigate the failure process and damage evolution of fiber-reinforced aeolian-sand backfill materials (FABs) using Digital Image Correlation (DIC) and Acoustic Emission (AE) techniques. The results show that the compressive strength tends to decrease with the increasing fiber volume fractions, while the four-point bending strength shows a tendency to increase initially and then decrease, and the optimum volume fraction of PP fiber is 0.6%. At the optimal fiber volume fraction, PP fibers with lengths of 3 mm and 9 mm resulted in a 65.25% and 81.62% increase in the four-point bending strength of FABs, respectively. As indicated by DIC measurements, PP fibers with a length of 9 mm were more effective in controlling the horizontal and vertical displacements of FABs under four-point bending loads than that of 3 mm, and the cracks developed more slowly at the same deflection. In addition, PP fibers with a length of 9 mm have stronger crack extension delay characteristics due to longer effective anchorage distance, as evidenced by more frequent acoustic emission ringing counts and higher cumulative ringing counts. The results of the study may provide a theoretical basis for the application of FABs materials in backfilling.

Impact of motivational feedback on levels of physical activity and quality of life by activity monitoring following knee arthroplasty surgery—protocol for a randomized controlled trial nested in a prospective cohort (Knee-Activity)

BackgroundEvidence on how to improve daily physical activity (PA) levels following total knee arthroplasty (TKA) or medial uni-compartmental knee arthroplasty (mUKA) by motivational feedback is lacking. Moreover, it is unknown whether a focus on increased PA after discharge from the hospital improves rehabilitation, physical function, and quality of life. The aim of this randomized controlled trial (RCT) nested in a prospective cohort is (a) to investigate whether PA, physical function, and quality of life following knee replacement can be increased using an activity monitoring device including motivational feedback via a patient app in comparison with activity monitoring without feedback (care-as-usual), and (b) to investigate the potential predictive value of PA level prior to knee replacement for the length of stay, return to work, and quality of life.MethodsThe study is designed as a multicenter, parallel-group, superiority RCT with balanced randomization (1:1) and blinded outcome assessments. One hundred and fifty patients scheduled for knee replacement (TKA or mUKA) will be recruited through Odense University Hospital, Denmark, Vejle Hospital, Denmark and Herlev/Gentofte Sygehus, Denmark. Patients will be randomized to either 12 weeks of activity monitoring and motivational feedback via a patient app by gamification or 'care-as-usual,' including activity monitoring without motivational feedback. The primary outcome is the between-group change score from baseline to 12-week follow-up of cumulative daily accelerometer counts, which is a valid proxy for average objectively assessed daily PA.DiscussionImproving PA through motivational feedback following knee replacement surgery might improve post-surgical function, health-related quality of life, and participation in everyday life.Trial registrationClinicalTrials.gov, ID: NCT06005623. Registered on 2023–08-22.Trial statusRecruiting.

Study on Failure Characteristics and Acoustic Emission Laws of Rock-like Specimens under Uniaxial Compression

Complex underground conditions make it challenging to conduct extensive coring, and it is difficult for laboratories to carry out a large number of rock mechanics experiments due to the limited number of cores. Rock-like specimens are commonly used in the laboratory to replace coal-rock specimens. In this paper, rock-like specimens with different proportions are produced to study the mechanical properties, failure characteristics, and acoustic emission laws of rock-like specimens under uniaxial compression. The results show that when the rock-like specimen does not contain gypsum, the stress of the specimen decreases rapidly after reaching the peak stress, which is similar to the mechanical properties of hard brittle rock. When the rock-like specimen contains gypsum, the stress of the specimen decreases slowly after reaching the compressive limit, and the failure of the specimen is gentle, which is similar to the mechanical properties of soft rock. When the specimen lacks gypsum, the strength of the rock-like specimen is larger, and the strength of the specimen is positively correlated with the proportion of cement. When the specimen contains gypsum, the strength of the rock-like specimen decreases sharply, and the strength of the rock-like specimen is negatively correlated with the proportion of gypsum. The maximum acoustic emission ringing count increases with higher cement content but decreases with increased gypsum content. The cumulative count change of acoustic emissions approximately underwent four stages, aligning well with the four stages of uniaxial compression failure observed in typical rock. The research results have important reference value for the selection of rock-like materials to replace the original rock materials for laboratory research.

Impact of short abstinence versus testicular sperm on sperm DNA fragmentation: a systematic review and meta-analysis.

Optimal sperm DNA integrity is essential for fertilization and embryo health. Research indicates that testicular sperm (TS), obtained via TESA or TESE, typically show lower sperm DNA fragmentation (SDF) than ejaculated sperm after standard abstinence. Shortening abstinence to less than 2days might reduce SDF, offering a less invasive and more cost-effective alternative to surgical sperm retrieval. Yet, no studies have directly compared the efficacy of shorter abstinence against TS extraction for lowering SDF. Our meta-analysis aims to address this gap by comparing SDF levels in TS to those in ejaculated sperm after a short abstinence period. Meta-analysis of 16 randomized controlled and prospective observational studies included 4 on TS and 12 on short abstinence ejaculation. The meta-analysis followed MOOSE guidelines, scrutinizing databases including Cochrane Library, Web of Science, Embase, MEDLINE(R), and PUMBED up to November 16, 2023. The analysis was conducted using RevMan. The observational studies' methodological quality was assessed using the Newcastle-Ottawa Scale, and the overall evidence quality was evaluated following the GRADE criteria. To compare short ejaculation duration and TS (are not directly compared in the literature) for SDF levels, we analyzed relevant data from studies of each method. We adjusted the participant numbers in the TS group by 1/3 and included each TS study three times, to perform a comparison against the short duration studies which were in a ratio of 1:3. This approach maintained an unaltered cumulative subject count for the meta-analysis of TS studies. A total of 641 patients were included, comprising 120 and 521 patients with SDF measurements following TS and ejaculation after a short abstinence period, respectively. The studies had varied inclusion criteria, with not all patients having an initial elevated SDF. Some studies had incomplete details on age and other demographics. However, the mean ± SD age of 93 TS patients was 38.15 ± 5.48 years vs. 37.7 ± 6.0 years of 444 short abstinence patients, demonstrating no significant difference (P = 0.544). Short abstinence durations ranged from 1 to 48h. Diverse DNA fragmentation tests were used: TUNEL assay in three testicular sperm studies, SCD assay in one, and in the short abstinence group, four used TUNEL and six used SCD assays, along with one each using SCSA and Halosperm. The mean ± SD SDF was lower in the TS group than in the short abstinence group (mean difference - 9.48, 95%CI -12.45 to -6.52, P < 0.001, I2 = 85%). Sensitivity analysis revealed that no single study significantly influenced the results. Employing the GRADE criteria, the initial assessment categorized the overall quality of evidence as low due to the observational nature of the acquired data. All studies were of medium to high quality. This study suggests testicular sperm may be better than ejaculated sperm for improving SDF in infertility cases. Direct comparisons are needed, before deeming short abstinence less effective. Future research should directly compare reproductive outcomes using both methods.

The Influence of Women’s Empowerment on The Preference for Contraceptive Methods in Indonesia: A Multinomial Logistic Regression Modelling

The concept of women's empowerment encompasses enabling women to take control of their own lives, independently make choices, and fulfill their complete capabilities. Numerous research studies examined the correlation between the empowerment of women and their reproductive health. In Indonesia, female labor force participation is relatively low. As a result, research on the influence of empowering women on contraceptive method preference in Indonesia makes sense. This research aims to find the multinomial logistic regression model in choosing contraceptive methods for married women in Indonesia and to identify the women’s empowerment traits that most impact contraceptive method choice. For this study, the researchers utilized secondary data obtained from the 2017 Indonesian Demographic and Health Survey (IDHS). The participants consisted of women between the ages of 15 and 49 who were married. The total number of respondents sampled was 49,216. Variables that significantly affect contraceptive method use include the respondent's current employment, the respondent has bank account or other financial institution accounts, the cumulative count of offspring previously born and beating justified if the wife argues with her husband. The analysis is obtained using the multinomial logistic regression test, independency, multicollinearity, and parameter test, and the selection is made by considering either the smallest value of Akaike's information criterion or the option that achieves the highest level of accuracy. Findings highlight four significant variables: Firstly, employed women are more likely to use contraceptives than the unemployed. Secondly, access to banking services correlates with a higher likelihood of contraceptive use. Thirdly, women with more children tend to prefer long-acting reversible contraceptives. Lastly, endorsement of spousal violence justifiability is linked to conventional contraceptive selection. These results emphasize the roles of employment, financial access, family size, and gender-based violence perceptions in shaping contraceptive choices in Indonesia. Model 3 emerges as the most accurate predictor of preferences after eliminating six variables based on rigorous testing and multicollinearity considerations. These findings underscore the importance of addressing economic empowerment and gender-related issues in Indonesian reproductive health programs and policies. Such a comprehensive approach can enhance women's autonomy, enabling them to make crucial life choices and ultimately improving their overall well-being.

Prominent Neuroprotective Potential of Indole-2-N-methylpropargylamine: High Affinity and Irreversible Inhibition Efficiency towards Monoamine Oxidase B Revealed by Computational Scaffold Analysis

Background: Monoamine oxidases (MAO) are flavoenzymes that metabolize a range of brain neurotransmitters, whose dysregulation is closely associated with the development of various neurological disorders. This is why MAOs have been the central target in pharmacological interventions for neurodegeneration for more than 60 years. Still, existing drugs only address symptoms and not the cause of the disease, which underlines the need to develop more efficient inhibitors without adverse effects. Methods: Our drug design strategy relied on docking 25 organic scaffolds to MAO-B, which were extracted from the ChEMBL20 database with the highest cumulative counts of unique member compounds and bioactivity assays. The most promising candidates were substituted with the inactivating propargylamine group, while further affinity adjustment was made by its N-methylation. A total of 46 propargylamines were submitted to the docking and molecular dynamics simulations, while the best binders underwent mechanistic DFT analysis that confirmed the hydride abstraction mechanism of the covalent inhibition reaction. Results: We identified indole-2-propargylamine 4fH and indole-2-N-methylpropargylamine 4fMe as superior MAO-B binders over the clinical drugs rasagiline and selegiline. DFT calculations highlighted 4fMe as more potent over selegiline, evident in a reduced kinetic requirement (ΔΔG‡ = −2.5 kcal mol−1) and an improved reaction exergonicity (ΔΔGR = −4.3 kcal mol−1), together with its higher binding affinity, consistently determined by docking (ΔΔGBIND = −0.1 kcal mol−1) and MM-PBSA analysis (ΔΔGBIND = −1.5 kcal mol−1). Conclusions: Our findings strongly advocate 4fMe as an excellent drug candidate, whose synthesis and biological evaluation are highly recommended. Also, our results reveal the structural determinants that influenced the affinity and inhibition rates that should cooperate when designing further MAO inhibitors, which are of utmost significance and urgency with the increasing prevalence of brain diseases.

FE-based machine learning model for predictive damage assessment in bonded composite joints via acoustic emission

This study systematically evaluated the mechanical performance of bonded composite single-lap joints with varying overlap lengths under tensile load. By integrating Acoustic Emission (AE) signals with Finite Element (FE) modeling, this study established a predictive machine learning model to enhance the understanding and prediction of failure mechanisms. Firstly, AE signal features were extracted and utilized as inputs for a hierarchical clustering model to classify AE signals into matrix cracking, fiber breakage, and adhesive debonding. AE signals classified as adhesive debonding were further analyzed by accumulating counts, amplitude, and energy. A cohesive zone-based Finite Element (FE) model was developed to simulate progressive debonding damage in the adhesive layer. After calibration with experimental results, various physical quantities such as stress, the damage initiation indicator, and the stiffness degradation indicator were extracted for correlation analysis. The experiments and simulations unravel the missing relationship between the AE and FE data. A strong correlation was observed between the cumulative count and cumulative amplitude with the damage initiation indicator, and between cumulative energy with the damage propagation indicator. Finally, based on the disclosed relationship between AE and FE data, a Support Vector Regression (SVR) model was established to predict the damage indicator. The developed model accurately predicted testing datasets within low absolute error ranges, underscoring its high predictive accuracy. Comprehensive stress analysis proposed a quantitative damage initiation indicator of 0.32 for structural fractures and a damage indicator of 0.12 for allowable stress levels. Consequently, combining AE techniques with FE modeling provided an effective tool for evaluating damage evolution in bonded composite joints.

Study on the Weibull distribution function-based stochastic damage evolution law for uniaxial compression in high-performance concrete with full aeolian sand

The issues of environmental degradation due to natural sand overextraction are becoming increasingly severe. In desert regions, utilizing aeolian sand as a substitute for natural sand in construction projects facilitates the resource economization and the effective management of desertification. The concrete industry is expected to significantly contribute to this objective, as high-performance concrete with full aeolian sand (FA-HPC) has demonstrated excellent mechanical properties. However, current researches have yet to establish a rational damage evolution law for uniaxial compression in FA-HPC from the perspective of damage characteristics. In this study, uniaxial compression tests were conducted on FA-HPC with different mixture proportions. Simultaneously, the stress-strain behavior was examined, and acoustic emission (AE) signals were collected and localized. Based on the Weibull distribution function-based stochastic damage evolution law for uniaxial compression, regression analyses of the stress-strain and AE cumulative ringing count for FA-HPC were performed. Damage evolution model for effective stress and damage variable were established and validated with experimental data to confirm their applicability. The scale and shape parameters of the model were predicted using the mixture proportions as independent variables. The results show that the rationality of the damage evolution law assumption was validated through AE source localization. The goodness of fit values for damage variable and effective stress equation range from 0.87 to 0.98, with the ascending segment and the vicinity of the peak point closely matching the experimental data, indicating that the Weibull distribution function-based stochastic damage model for uniaxial compression is applicable for FA-HPC. The predicted values of the damage evolution model parameters based on the mixture proportions align well with the measured values, achieving a goodness of fit of 0.99, thereby guiding the study of FA-HPC's compressive characteristics prior to the formation of primary cracks. Notably, there remains a need to propose corrective equations to enhance the correlation between regression curves and experimental data in the late failure stages of FA-HPC in future research, achieving precise predictions by considering the interactions of multiple factors.

Mechanical properties and acoustic emission characteristics of basalt fiber reinforced cemented silty sand subjected to freeze–thaw cycles

Freeze–thaw (F–T) cycling poses a significant challenge in seasonally frozen zones, notably affecting the mechanical properties of soil, which is a critical consideration in subgrade engineering. Consequently, a series of unconfined compressive strength tests were conducted to evaluate the influence of various factors, including fiber content, fiber length, curing time, and F–T cycles on the unconfined compression strength (UCS) of fiber-reinforced cemented silty sand. In parallel, acoustic emission (AE) testing was conducted to assess the AE characteristic parameters (e.g., cumulative ring count, cumulative energy, energy, amplitude, RA, and AF) of the same material under F–T cycles, elucidating the progression of F–T-induced damage. The findings indicated that UCS initially increased and then declined as fiber content increased, with the optimal fiber content identified at 0.2%. UCS increased with prolonged curing time, while increases in fiber length and F–T cycles led to a reduction in UCS, which then stabilized after 6 to 10 cycles. Stable F–T cycles resulted in a strength loss of approximately 30% in fiber-reinforced cemented silty sand. Furthermore, AE characteristic parameters strongly correlated with the stages of damage. F–T damage was segmented into three stages using cumulative ring count and cumulative energy. An increase in cumulative ring count to 0.02 × 104 times and cumulative energy to 0.03 × 104 mv·μs marked the emergence of critical failure points. A sudden shift in AE amplitude indicated a transition in the damage stage, with an amplitude of 67 dB after 6 F–T cycles serving as an early warning of impending failure.