Statistical Analysis Of Data Research Articles

H-Wave® Device Stimulation for Chronic Neck Pain: A Patient-Reported Outcome Measures (PROMs) Study.

Chronic neck pain (cNP) is one of the leading causes of disability worldwide, often being refractory to conventional forms of treatment. Various forms of electrical stimulation have been proposed to decrease pain and improve function. Patient-reported outcome measures (PROMs) for treatment of cNP have rarely been published. An independent retrospective statistical analysis of PROMs data for users of H-Wave® device stimulation (HWDS), prospectively collected by the device manufacturer over a 4-year period, was conducted. Final surveys for 34,192 pain management patients were filtered for pain chronicity limited to 3-24months and device use of 22-365days, resulting in 11,503 patients with "all diagnoses"; this number was further reduced to 1482 patients with cNP, sprain, or strain. Neck pain was reduced by 3.13 points (0-10 pain scale), with significant (≥20%) relief in 86.6%. Function/activities of daily living (ADL) improved in 96.19%, while improved work performance was reported in 84.76%. Medication use decreased or stopped in 65.42% and sleep improved in 60.39%. Over 95% reported having expectations met or exceeded, service satisfaction, and confidence in device use, while no adverse events were reported. Subgroup analyses found positive benefit associations with longer duration of device use. Near-equivalent outcomes were self-reported by cNP HWDS patients as for (previously published) chronic low back pain (cLBP) patients. HWDS provided effective and safe cNP relief, improvements in function and ADL, along with additional benefits including decreased medication use, better sleep, and improved work performance.

Analysis of Multiple Scattering Characteristics of Cable-Stayed Bridges with Multi-band SAR

Abstract. Accurate localization of multi-scattering features of cable-stayed bridges in multi-band Synthetic Aperture Radar (SAR) imagery is crucial for intelligent recognition of bridge targets within images, as well as for precise water level extraction. This study focuses on the Badong Yangtze River Bridge, utilizing Unmanned Aerial Vehicle (UAV) LiDAR data of the bridge, and analyzes the multi-scattering characteristics of different bridge structural targets based on Geometric Optics (GO) methods and the Range-Doppler principle. Furthermore, the study integrates LiDAR data of the bridge's cable-stays to examine their multi-scattering phenomena, finding that the undulations of the Yangtze River's surface waves significantly contribute to the pronounced double scattering features of the bridge's cable-stays. Additionally, statistical analysis of multi-source SAR data indicates that this phenomenon is not directly correlated with radar wavelength, implying no direct connection to surface roughness. Utilizing LiDAR point cloud data from the bridge's street lamps, this paper proposes a novel method for estimating water level elevation by identifying the center position of spots formed by double scattering from lamp posts. The results show that using TerraSAR ascending and descending orbit images, this method achieves a water level elevation accuracy of approximately 0.2 meters.

COSGAP: COntainerized statistical genetics analysis pipelines

Abstract The collection and analysis of sensitive data in large-scale consortia for statistical genetics is hampered by multiple challenges, due to their non-shareable nature. Time-consuming issues in installing software frequently arise due to different operating systems, software dependencies, and limited internet access. For federated analysis across sites, it can be challenging to resolve different problems, including format requirements, data wrangling, setting up analysis on high-performance computing facilities, etc. Easier, more standardized, automated protocols and pipelines can be solutions to overcome these issues. We have developed one such solution for statistical genetic data analysis using software container technologies. This solution, named COSGAP: “COntainerized Statistical Genetics Analysis Pipelines”, consists of already established software tools placed into Singularity containers, alongside corresponding code and instructions on how to perform statistical genetic analyses, such as genome-wide association studies, polygenic scoring, LD score regression, Gaussian Mixture Models, and gene-set analysis. Using provided helper scripts written in Python, users can obtain auto-generated scripts to conduct the desired analysis either on HPC facilities or on a personal computer. COSGAP is actively being applied by users from different countries and projects to conduct genetic data analyses without spending much effort on software installation, converting data formats, and other technical requirements. Availability COSGAP is freely available on GitHub (https://github.com/comorment/containers) under the GPLv3 license.

New statistical framework for interlaboratory evaluation of anti-doping testing results by WADA

AbstractThe World Anti-doping Agency (WADA) International Standard for Laboratories (ISL), developed as part of the World Anti-Doping Program, requires satisfactory laboratory performance in the WADA External Quality Assessment Scheme (EQAS) in order to obtain and maintain WADA accreditation. Under this mandate, WADA regularly distributes urine and blood test samples to anti-doping laboratories to continuously monitor their proficiency. Over the years, WADA has employed classical, generic statistical methods, in accordance to ISO 13528, to evaluate quantitative EQAS results. Here, we set out the rationale for a modern statistical approach that recognizes and addresses the particular features of the measurement results typically obtained in such tests and present an approach involving Bayesian measurement models and statistical data analysis that is tailored specifically to anti-doping testing.

Use possibility analysis for wind energy in autonomous car interior heating

Introduction. When driving cars in winter on intercity routes, problems may arise if the highways are covered with snow as a result of heavy snowfalls, which can last for several days or more, and movement during this period becomes impossible. An analysis of statistical data on weather events in winter has shown that in many regions, the closure of trails as a result of prolonged snowfalls can reach up to fifteen percent. In this case, an autonomous energy source, which it receives through the use of environmental properties, can provide significant assistance in improving the situation and increasing safety. The paper considers the technical solution and carries out a theoretical analysis of its characteristics aimed at solving the problem of autonomous power supply of the car interior in severe weather conditions.Materials and methods. The paper presents a technical solution and a theoretical analysis of its characteristics aimed at solving the problem of autonomous power supply of the car interior in severe weather conditions.Results. Based on the results of the information search, the design of a compact low-power wind power plant is proposed. The calculation of the heat loss of the car interior, the characteristics of a compact wind power plant was performed and the generated power required to heat the car interior in an extreme situation was determined.Discussion and conclusions. It has been established that the presented design of a low-power wind power plant can be used as a prototype for the development of an industrial design of an autonomous energy source for heating a car in extreme conditions. Similar installations can be used in other industries, for example, tourism, agriculture, and geological exploration.

A Comprehensive Approach to Azo Dichlorotriazine Dye Treatment: Assessing the Impact of Physical, Chemical, and Biological Treatment Methods through Statistical Analysis of Experimental Data

This exploration investigates integrated treatment systems combining advanced oxidation processes (Fenton and photo-Fenton) with biological methods for the effective elimination of stubborn organic compounds in simulated textile wastewater composed of azo Dichlorotriazine dye. A comprehensive optimization of key process factors including catalyst dosage, hydrogen peroxide quantity, irradiation duration, etc. was systematically conducted for both Fenton and photo-Fenton processes to realize maximum COD and color removal. Under ideal conditions (0.4 g/L photocatalyst, 1 mL/L H2O2, and 75-Watt UV intensity for 60 min), the photo-Fenton process realized 80% COD elimination and complete decolorization, meeting industrial discharge limits without needing extra biological treatment. Statistical models correlating process parameters to treatment efficiency were developed, giving important design insights. For Fenton, effluent COD exceeded discharge thresholds, so a post-biological treatment using activated sludge was essential to comply with regulations. This integrated Fenton–biological scheme utilizes synergism between chemical and biological processes for enhanced overall treatment. Notable economic benefits were achieved by photo-Fenton over conventional UV-only and UV/H2O2 methods regarding energy consumption and operating costs. Overall, this pioneering work successfully proves integrated advanced oxidation–biological systems as a superior, sustainable alternative to traditional techniques for economically removing obstinate pollutants, such as azo Dichlorotriazine dye, as it is a simulated textile wastewater treatment used to satisfy environmental standards.

Co-seismic deformation and related hazards associated with the 2022 Mw 5.6 Cianjur earthquake in West Java, Indonesia: insights from combined seismological analysis, DInSAR, and geomorphological investigations

IntroductionOn November 21, 2022, a magnitude Mw 5.6 earthquake struck Cianjur Regency in the West Java Province of Indonesia. It was followed by at least 512 aftershocks that persisted from November to June 2023. This seismic event occurred in an area previously unrecognized as an active fault zone. The consequences of this earthquake in Cianjur were severe, leading to both loss of life and extensive structural damage. The substantial damage to buildings was likely a result of abrupt alterations in the local topography due to surface deformation effects.ObjectivesThis research endeavor aims to spatially determine the patterns of ground surface deformation and its relationship with local geomorphological setting due to earthquakes in Cianjur in 2022.MethodsIn this study we conduct seismological analysis of 45 seismic stations, statistical analysis of mainshock and aftershocks data, RADAR Sentinel-1 imagery and employed the DInSAR methodology. Field survey was also conducted to determine the geomorphological characteristics in the study area.ResultsThe outcomes disclosed that the deformation encompassed both subsidence and uplift. The results signify that there was subsidence deformation in the vicinity of Cianjur and its environs during the primary earthquake on November 21, 2022, with an average deformation value of approximately -5 cm. In contrast, the measured deformation during the aftershocks exhibited uplift deformation, with an average value of 10 cm. The examination of deformation patterns amid the 2022 Cianjur earthquake sequence detects elevated deformation values in the vicinity of Cugenang district, with an orientation running from northwest to southeast. The geomorphological investigation conducted indicates that the region of Cianjur encompasses a variety of landforms, such as volcanic, structural, fluvial, and denudational. These landforms exhibit distinct responses to seismic activities. Co-seismic hazards, such as landslides frequently occur as a consequence of seismic events in mountainous terrain.Main ConclusionsSpatio-temporal variation of ground deformation could arise from various causes, such as the number and distribution of aftershocks, stress redistribution, fault interactions, secondary effects, and local geological settings. The mainshocks release accumulated stress along a fault, resulting in particular types of deformation, whereas aftershocks may redistribute stress exhibiting on adjacent faults. Secondary effects triggered by aftershocks, coupled with local geological and geomorphological conditions, further contribute to the diverse patterns of ground deformation observed during seismic events. The results of the study revealed that ground deformation had the greatest impact on fluvial, volcanic, and denudational processes, resulting in notable subsidence and uplift in specific regions. The occurrence and magnitude of co-seismic landslides were triggered by both mainshock and aftershock events, which occurred on weathered geological materials. These effects were further amplified by the simultaneous presence of the rainy season.ImplicationsThe knowledge gained from this research can be applied to evaluate the impacts of earthquakes and to proactively reduce future risks.

Effectiveness of language-related Youtube videos on EFL learning motivation

YouTube is a widely popular platform that offers a vast array of video content. This study aimed to explore the elements of YouTube videos that contribute to sustaining learners’ motivation. A survey was conducted among 349 young adult Indonesian learners. Statistical data analysis revealed that three types of language-related YouTube videos—language lessons, language tips, and language immersions—significantly influenced learners’ motivation to study English. However, language immersion videos exhibited a modestly lower level of effectiveness compared to the other video types. Additionally, it was observed that non-native English-speaker (NNES) videos were more effective in maintaining motivation across all proficiency levels, except for advanced learners, who responded better to native English speaker (NES) videos. Furthermore, the study concluded that videos ranging from 5 to 15 minutes were more effective in sustaining learners’ motivation, as opposed to shorter or longer videos. These findings explain that teachers consider incorporating explicit instruction or tips in their content to enhance learners’ motivation. The findings also indicate that teachers and designers should utilize NNES videos for beginners and intermediate learners, while NES videos may be more effective for advanced learners. Lastly, when choosing instructional videos, the video length should be considered to ensure that learners remain motivated.

Analisis Perbandingan Kinerja Perusahaan Sebelum dan Sesudah Employee Stock Option Program (ESOP) (Studi Empiris pada Perusahaan Manufaktur yang Listing di Bursa Efek Indonesia Tahun 2017-2020)

Implementation of the Employee Stock Option Program in this study aims to compare the company's performance both before and after the implementation of the Employee Stock Option Program for manufacturing companies listed on the IDX in 2017-2020. This research is a manufacturing issuer with as many as 193 companies. Purposive Sampling used in the sampling technique, so that a sample of 11 companies. Available analytical methods include descriptive statistical data analysis, normality test which also uses other tests (paired sample t test), and hypothesis testing with the Paired Sample Test and Wilcoxon test. The results of the study concluded that there were no differences in ROA, ROE, NPM, and TATO before and after the implementation of ESOP in manufacturing companies listed on the IDX for the 2017-2020 period.

The Comparison of Physical and Chemical Properties of Pellets and Briquettes from Hemp (Cannabis sativa L.)

The Comparison of Physical and Chemical Properties of Pellets and Briquettes from Hemp (Cannabis sativa L.)

Planning For Resilience: Examining Gaps in Cyclone Preparedness and Impacts on Marginalized Communities in India's East coast cities

Cyclones and associated storm surges pose a major threat to coastal communities in India, especially along the Bay of Bengal where their intensity is higher. This paper examines cyclone resilience planning in four coastal cities - Visakhapatnam, Puri, Rameshwaram, and Velankanni. A multi-dimensional analysis is undertaken to focus on disaster preparedness, tourism economy contributions, socio-economic inclusion, and sustainability principles. The key objective is to study the integration of cyclone resilience with equitable, tourism-based development to strengthen vulnerable communities through conceptual modeling. The research methodology employs a mixed methods approach combining literature review, secondary data analysis of resilience infrastructure and tourism statistics, and conceptual model development. Findings highlight continued infrastructure and preparedness gaps alongside persisting socio-economic disparities limiting resilience access for marginalized groups. While progress is visible on early warnings, shelters, and evacuations, constraints exist regarding storm-proofing of amenities, customized enterprise support, secure housing, and risk financing tools. The study concludes that resilient, sustainable outcomes require planning processes that engage tourism-dependent communities through bottom-up participation. Coupled with hazard-resilient land use standards, customized livelihood protection schemes, resilient affordable housing programs, and coherent governance; tourism-centric coastal cities can enhance capacities to absorb cyclone impacts and enable inclusive rebuilding. Key Words: Cyclone resilience, Coastal city planning, Socio-economic vulnerabilities, Tourism economies

The Influence of Commitment and Job Satisfaction on Employee Performance in Megamendung Bogor

The aim of this research is to determine the effect of commitment and job satisfaction on employee performance in the Bogor Megamendung detective training. This research uses a quantitative method, namely a research method that is post-positivism, namely researching a certain population or sample, where data collection uses research instruments and statistical data analysis with the aim of testing the hypotheses that have been determined so that direct or indirect relationships between variables can be identified. The number of respondents taken was 55 people. Several data collection methods were used, namely questionnaires, direct observation, literature study, documentation. Technical data analysis uses a Likert scale and regression method through the SPSS program. The research results show data that commitment has a positive effect on employee performance, job satisfaction has a positive effect on employee performance, commitment and job satisfaction have a positive effect on employee performance.

The effect of lean tool on research culture and research performance in Indonesia’s higher education institutions

Quality Assurance in higher education is a lean tool to improve the quality and performance of HEIs, including lecturer research performance. This study examines the effect of implementing Quality Assurance in higher education as a lean tool on the research culture and research performance of lecturers at Indonesia’s private HEIs. The data represent respondents’ perceptions of the research variable indicators. 184 questionnaires were suitable for processing. Data were collected from 184 lecturers from approximately 25 private HEIs in Jakarta, Indonesia. A 5-point Likert scale was used to measure indicators of research variables. Statistical data analysis was carried out using Structural Equation Modeling with the Smart-PLS ™ program. The results show that Quality Assurance as a lean tool has a significant impact on research performance (β = 0.643; p = 0.000) and research culture (β = 0.361; p = 0.000). Research culture affected research performance significantly (β = 0.281; p = 0.000), and research culture significantly mediates the effect of Quality Assurance as a lean tool on the research performance (β = 0.102; p = 0.010), and the effect is strong (Ѵ = 0.181). Research findings reveal that the successful implementation of Quality Assurance as a lean tool is determined more by organizational readiness than individual readiness; this is reflected in the existence of effective research centers. An effective research center will support the standardization of research processes through continuous improvement so that lecturers behave more actively in scientific activities and perform research more productively.

The screening of cannabis addiction using machine learning, MoCA, and anxiety/depression tests

A new cannabis addiction screening approach is developed based on the use of Machine Learning (ML) alongside with psychological and cognitive assessment tests. The Hospital Anxiety and Depression (HAD) test is used to determine the Absence of Anxiety and Depression “No Disorder” or the presence of “Anxiety Only”, “Depression Only”, and both “Anxiety and Depression”. These features are considered to evaluate the psychological effects of cannabis use. In addition to that, the Montreal Cognitive Assessment (MoCA) test is chosen as a feature to assess the cognitive state of the participants. Also, the Age of First Cannabis Use (AFCU) is included as a feature to incorporate participants with no prior cannabis use alongside with those who have used cannabis before. The portion of participants with prior experience consuming cannabis comprises a subset containing passive users and a subset of users that have developed cannabis addiction. This 6-month study was conducted in Marrakech, Morocco in a center affiliated to the National Association of Drug-Risk Reduction of Morocco known as RdR-Maroc with the participation of 146 subjects. The participants in this study are grouped into two groups of 73 participants each. Both case and control groups were clinically assessed by a professional. In this paper, the classical statistical data analysis for the AFCU (M=15.6; SD=2.4), MoCA (M=25.0; SD=2.4), and HAD (58 cases with no disorder, 88 cases with disorder) failed to separate between the two classes. Also, the feature selection for modeling is performed using Spearman correlation, Kendall correlation, and the Odds Ratio (OR). These statistics showed that the selected features were associated to addiction except for “Anxiety Only”. Moreover, ML models such as Logistic Regression (LR), Support Vector Machine (SVM), Artificial Neural Network (ANN), kth-Nearest Neighbor (KNN), and Decision Tree (DT) were used to classify participants into two categories (Addict vs. Non-Addict) based on the selected features mentioned earlier. The Receiver Operating Characteristic (ROC) curve is used to overview the quality of the models and showed that they all captured the nonlinearities underlined in the data. On the other hand, the Area Under the Curve (AUC) allowed the ranking of these models and indicated that the SVM model outperformed all other models with an AUC of 0.97. After that, the SVM model was compared to the Cannabis Use Disorder (CUD) based screening method issued by the fifth edition of the Diagnostic and Statistical Manual of mental disorders (DSM-5). The SVM model's accuracy of 96.6 % outperformed the CUD questionnaires accuracy of 87.7 %. The validity of the proposed approach was investigated where the SVM model presented high validity characteristics (sensitivity=1, specificity=0.93) compared to the CUD questionnaire (sensitivity=0.75, specificity=1). Hence, the proposed approach provided satisfactory results compared to current adopted CUD based screening test. Our findings expand current research on the development of simple and powerful tools for cannabis addiction screening with the purpose of early detection in order to establish preventive and therapeutic strategies that could potentially mitigate the prevalence of cannabis addiction.

Abstract PO4-20-01: A PROSPECTIVE PILOT STUDY OF MAMMOGRAPHIC PREDICTION OF WOMEN’S RISK (M-POWER) IN NIGERIA

Abstract Background There have been no sustained efforts at stemming the rising incidence and mortality from breast cancer in sub-Saharan African countries like Nigeria. Mammography is the gold standard for breast cancer screening and is associated with improved survival particularly among women 50 to 69. Reports from various parts of Nigeria show very low mammography screening uptake. Causes include lack of geographical access, financial issues (less than 5% of the population is covered by the National Health Insurance Scheme), lack of awareness and the increasing expertise gap from the continued brain drain, despite the already low number of radiologists in the country. Given these obstacles, our long-term goal is to devise a rational basis for identifying mammographic risk categories so that this resource can be deployed cost-effectively. We propose to carry out a 5-year prospective mammographic study in Nigerian women and to use machine learning to develop a risk prediction algorithm, so that following a single screening mammogram, the appropriate frequency of subsequent mammograms can be determined. Our immediate goal is to examine the feasibility of performing such a study. To this end, we have initiated a cross-sectional pilot study that will recruit up to 2000 women in multiple urban centers in Nigeria. Objective: To explore feasibility of creating a digital mammography image database representative of the radiological features of the breast of Nigerian women. Objective: To explore feasibility of creating a database that can be used to inform a predictive mammographic risk model for breast cancer and identify the appropriate population that will benefit from breast cancer screening in Nigeria. Design This is a prospective, open-label, cross-sectional pilot study in 2000 eligible women in Nigeria and will include a single screening mammography examination. The mammography images will be read by the study radiologist. The Pilot phase will determine the feasibility and aid in the design of the of the Extension phase in which up to 20,000 participants will undergo yearly mammography examination for 5 years. Incident cases of breast cancer during the study period will permit the development of deep learning algorithms for predicting the risk of breast cancer in this population. Main Eligibility Criteria: Inclusion Criteria All consecutive women aged ≥40 years and < 65 years presenting for screening mammography at the participating institutions will be eligible. Signed study-specific written informed consent. Exclusion Criteria Complaint of a focal dominant lump or a bloody or clear nipple discharge. History of breast implants. Any woman who is pregnant or has reason to believe that she might be pregnant. Statistical Methods Analyses of continuous data will be summarized using descriptive statistics where the following parameters will be reported: Number of observations, Number of missing observations, Mean, Median, Standard deviation (SD), Minimum (Min), Maximum (Max) Categorical data will be presented with absolute and relative frequency (n and %). Present Accrual and Target accrual Two hundred ninety-six women have been enrolled and screening digital mammographic images using GE Digital mammography equipment have been obtained on all participants at 2 study sites in 2 cities in Southern Nigeria. The target accrual is 2000 participants over 12 months. Conclusion Our preliminary experience to date suggests the feasibility of proceeding with a larger prospective study to define mammographic risk groups in Nigerian women which will permit the rational allocation of resources for breast cancer prevention activities in this underserved population. Contact Information: Dr Toyin Shonukan at tshonukan@yemanjacancercare.org Citation Format: Oluwatoyin Shonukan, Hyelakumi Ibrahim, Esther Udoh, Wahab Egbeolu, Kanyinsola Oyeyinka, Jonas Haggstrom. A PROSPECTIVE PILOT STUDY OF MAMMOGRAPHIC PREDICTION OF WOMEN’S RISK (M-POWER) IN NIGERIA [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-20-01.

Abstract PO4-16-12: Patient initiated centricity towards improved communication, side effect management and follow-up care by Real World Evidence Survey from patients for patients – Preview of the Breast BRIDGister Platform

Abstract Background Treatment adherence is crucial for outcome improvement. Still up to 50% of patients interrupt e.g. endocrine treatment or other effective treatment choices due to side effects or miscommunication. Reasons may include limited time spent for patient information in daily routine and the intrinsic barriers to frankly tell the truth to the attending physicians. Therefore, a patient initiated survey has been compiled to comprehensively address all clinical, diagnostic and critical aspects of importance for patients by decentral data capture from patients at home via smart devices in a pseudonymized & interactive fashion to refocus on challenges regarding patients needs, fears and wishes to support evidence based statistical analysis of Real World Data. Materials and Methods Establishing a cloud-based IT Platform enabling nationwide, decentral data entry using Climedo clinical trial software tools without the need of any commercial app utilities and therefore obeying GDPR conform standards to create an interconnected online platform integrating 36 interconnected surveys comprising >1.200 singular questions has been set up between 2020 and 2022 based on patients content elaboration & wishes. The questionnaires address all Real World experiences e.g. at initial diagnosis, during primary treatment and all subsequent lines as well as side effect management with complementary medicine and follow up care realities. After 100 patients a preplanned statistical analysis has been performed to evaluate the feasibility of the patient oriented ePRO approach and demonstrate relevance of proof-of-concept results before entering international trial expansion. Descriptive analysis by Excel as well as Correlation analysis; Chi square and Partitioning tests using the SAS JMP® 9.0.0 software were performed. Results Despite in depth complexity > 85% of patients completed the whole survey. Age distribution of the pilot cohort revealed comparably younger patient age (28% between 30-39 years, 40% between 40-49 years, 24% between 50-59 and 10% being above 60 years) and dominance of Triple Negative Patients (~39%) participating the online survey in the pilot cohort. 97% of patients were treated in certified breast centers (50% in larger centers of bigger towns,15% in central clinics, 23% in university sites, 5% in local hospitals and 7% at office based doctors). Interestingly, 25% of patients did not or only partially understand their diagnosis and upcoming treatment. Time spent for communicating initial breast cancer diagnosis was less than 10 minutes for 25% of patients, while 13% did not remember. Exclusively one treatment option was discussed with 86% of patients. 78% have been informed about their initial breast cancer diagnosis in personal meetings, while 21% were informed by phone calls. 37% of patients had been informed about their patient rights. At preplanned interim analysis 38% of patients were lymphnode positive and 6% metastasized at initial diagnosis. 56% of patients were satisfied with their guideline conform follow-up-care, while 42% did pay for additional follow up care on their own. 85% of patients wished to have a risk-adopted, more individualized follow-up care. Conclusion Despite complexity and lengthiness > 85% of patients did complete the survey. There is an apparent need to have more time for initial confrontation with diagnosis and treatment options. Patients are frequently not informed about alternative treatment options as well as patient rights. Patients frequently feel under pressure in their life threatening situation and suffer substantial lack of information as well as appropriate personal communication. Patient centricity should focus on elaborated communication and information systems that support treatment decision acceptance and adherence. Further details analysis will become available in upcoming subanalysis of the Breast BRIDGister platform survey. Citation Format: Cornelia Stuewe, Ralph Wirtz, Christa Gress, Lena Schmidt, Veronika Schweighart, Sebastian Eidt, Claudia Schumacher, Julia Habraschka, Heidi Lehmann, Katrin Schuere. Patient initiated centricity towards improved communication, side effect management and follow-up care by Real World Evidence Survey from patients for patients – Preview of the Breast BRIDGister Platform [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-16-12.

The relationship between orthodontic and orthopaedic interventions in the influence of postural position on the bite

OBJECTIVE: In orthodontic treatment, the influence of posture on the bite plays a significant role in achieving stable results. With modern lifestyles, posture problems are becoming more common. The aim of this study was to comprehensively analyze the relationship between orthodontics, orthopedics, and the influence of posture on bite. The study reviewed statistics on the growth and popularity of orthodontic treatment methods and identified the importance of a comprehensive medical approach, especially for concomitant spine, posture, and flat feet problems. METHODS: The following methods were used to achieve the objective: collection and analysis of statistical data on the popularity of orthodontic treatment; review of studies; clinical observations; and a comparative analysis of the effectiveness of different treatment methods. RESULTS: The study revealed a high degree of correlation between orthodontics, orthopedics, and the effect of posture on bite formation. A detailed analysis of the statistical data confirmed the increased interest in orthodontic treatment, including the use of modern technologies such as braces and eliners. This relevance is particularly noticeable in cases where there are concomitant problems with the spine, posture, and flat feet. CONCLUSION: One of the significant findings of the study was the confirmation of the urgent need for the convergence of orthodontic and orthopedic techniques to optimize the quality of care for patients suffering from combined posture and bite problems.

Statistical assessment of the factors influencing fly ash reactivity

Siliceous fly ash is a pozzolanic supplementary cementitious material often used in cement and concrete production. The influence of the chemical, mineralogical and physical properties of 75 siliceous fly ashes on their reactivity was examined in this study. The reactivity was analyzed by relative mortar compressive strength and a rapid screening test (a version of the R³ test). A statistical data analysis was carried out to evaluate the factors influencing the reactivity of the ash. The screening test was found to be able to predict the reactivity within short periods of time, while the relative strength is not a good measure for reactivity. It was also found that the TiO2 and chloride content of the fly ash can serve as an indicator for its reactivity.

The First International eDNA Workshop in Hong Kong: A beginner's guide for the next‐generation eDNA researcher

AbstractThe field of environmental DNA (eDNA) has rapidly advanced in recent years, providing a non‐invasive and time‐saving method for assessing biodiversity. The First International Environmental DNA (eDNA) Workshop in Hong Kong was held from 16 to 27 October 2023 and provided early career professionals with hands‐on training and collaboration opportunities in eDNA research. With support from The Croucher Foundation Limited (Hong Kong), the workshop covered all stages of an eDNA‐based research project, including study design, field sampling, eDNA extraction, library preparation, bioinformatics, statistical data analysis, and ethics in scientific research. Participants gained insights into the principles and practical applications of eDNA technology, emphasizing the importance of careful experimental design and data interpretation. The workshop also highlighted the need for standardized protocols, comprehensive and local DNA reference databases, and careful selection of primer sets to overcome current issues and limitations. Workshop participants expressed enthusiasm for the potential of eDNA metabarcoding as a valuable tool for ecological monitoring, biodiversity assessment, and conservation decision‐making. The future of eDNA research looks promising overall, with continued advancements in technology, collaboration among researchers, and the integration of eDNA into large‐scale ecological monitoring. Future iterations of the Hong Kong International eDNA workshop will continue to provide hands‐on training and collaboration opportunities for early career professionals interested in eDNA research, focusing on addressing current limitations and challenges in the field.

Stem cell research in Indonesia from 2003 to 2022: A bibliometrics analysis

Context: Stem cell research has become popular in Indonesia for more than a decade. The scope of research involves in vitro to animal studies as well as human trials. However, no evidence proved its trend. Aims: To analyze the trends and patterns of stem cell research in Indonesia from 2003 to 2022 using a bibliometric analysis of the Scopus database. Methods: The data for the paper were retrieved from Scopus and then analyzed using bibliometrics. Statistical data analysis was performed. Results: The results showed that stem cell research in Indonesia has been increasing steadily over the years, with the majority of publications focusing on “Medicine”, “Biochemistry, Genetics, and Molecular Biology” and “Pharmacology, Toxicology, and Pharmaceutics”. It was found that a total of 260 related articles had been published. Rantam was identified as the most productive author, and the authorship network analysis identified nine clusters of authors. The keywords “stem cells”, “culture”, “proliferation”, “differentiation”, and “tissue engineering” were the most frequently used in the publications analyzed. Conclusions: Overall, this study provides valuable insights into the development of stem cell research in Indonesia and may inform future research and funding decisions in this field.