bluuebunny/crossref_metadata_2025_split huggingface dataset:
Blockchain Solutions for Global Adoption Systems: Enhancing Transparency, Security, and Support for Adoptive Families and Children’s Rights
Authors: Anbari Mahdi , Rahman Mohd Nazri Bin Abdul 
Published: November 2024

Abstract

Objective
This study explores blockchain technology’s potential to address key challenges in global adoption systems, including bureaucratic inefficiencies, documentation issues, data privacy concerns, and gaps in postadoption support. It evaluates blockchain’s capacity to enhance transparency, security, and accountability in adoption processes.
Methods
This exploratory design combines qualitative data from a phenomenological study of Iranian adoptive families with findings from a systematic review of adoptees' behavioral challenges. The blockchain’s core features—immutability, smart contracts, and self-sovereign identity—are analyzed for their capacity to address legal, privacy, and postadoption support issues in adoption systems.
Results
Blockchain provides immutable adoption records, preventing document tampering and enhancing trust and transparency. Its encryption protocols ensure that sensitive data are secure and accessible only to authorized individuals. Additionally, smart contracts can automate legal agreements and track postadoption services, ensuring accountability and reducing delays in providing essential counseling and healthcare.
Conclusion
Blockchain technology offers a novel solution to systemic issues in adoption systems by improving transparency, safeguarding data privacy, and ensuring consistent postadoption support. Future research should focus on real-world applications and address ethical considerations surrounding data protection and adoptee rights.
The effects of child marriages on academic performance of marginalized girls in Secondary Schools of Central Province in Zambia
Authors: Sharper Sikota , Evans Chikumbe Sanhkwa , Mwiya Mufalali Simasiku , Bowa Mwila 
Published: November 2024

Abstract

Zambia's education sector faces significant challenges, particularly for female students who are affected by poverty, cultural attitudes, and early marriage. Despite efforts to improve educational access, many girls struggle with enrollment and academic performance. This study aimed to analyze the effects of child marriages on the academic performance of marginalized girls in Secondary Schools in selected secondary schools in the Central Province of Zambia. Adopting a phenomenological approach, the study conducted focus group discussions and interviews with key stakeholders, including marginalized girls, out-of-school girls, school staff, and community leaders. Thematic analysis of qualitative data, collected through structured notes and NVivo software, was used to explore participants' lived experiences and perspectives. The findings indicated that sponsorship initiatives help reduce dropout rates, increase access to education for girls, and improve child safety in schools and communities. Nonetheless, challenges such as poverty, cultural attitudes, inadequate parental support, early marriage, and restrictive gender norms are prevalent. The intricate interplay of poverty, socio-cultural norms, and enduring gender inequalities poses a significant barrier to educational attainment for marginalized girls. Financial constraints and poverty forces families to prioritize survival over education, leaving girls susceptible to early marriage, school dropout, and risky behaviors as coping mechanisms.
Practical Implementation of Discrete Wavelet Transform-based Sensing using Software Defined Radio
Authors: Yahya Zhraa Zuheir , Ali Dia Mohamad 
Published: November 2024

Abstract

Spectrum sensing techniques are vital in both spectrum utilization and spectrum scarcity solutions. This paper proposes a wide band spectrum sensing method using discrete wavelet transform with Daubechies4 function to distinguish between the primary user spectrum and white spaces. The proposed model is validated through simulation using LabVIEW NXG software. Then, it is practically implemented in real-time and in a real environment using a universal software-defined radio peripheral (USRP) platform, which is a software-defined radio (SDR) at 2 GHz radio frequency. Long-short-term memory (LSTM), a deep learning approach, is used to evaluate the system's performance. Simulation and practical results show the system's efficiency in terms of the probability of detection in additive white Gaussian noise (AWGN) channels at various signal-to-noise ratios (SNRs). Furthermore, the proposed LSTM network achieves 99% classification accuracy.
Analysis of Postoperative Atrial Fibrillation and Its Associated Factors in Morrow Procedures with Cardiopulmonary Bypass
Authors: Hu Zhibin , Mao Wenshuai , Guo Lijun , Liu Zhiwei , Hu Xujie , Cui Yong 
Published: November 2024

Abstract

Background
The factors influencing the onset of new atrial fibrillation following the Morrow procedure due to cardiopulmonary bypass are unclear. This study investigated the cardiopulmonary bypass (CPB)-related factors associated with postoperative atrial fibrillation (POAF) in patients undergoing minimally invasive ventricular septal myectomy (Morrow procedure) to optimize CPB strategies, reduce the incidence of POAF, and enhance recovery.
Methods
A retrospective clinical data analysis was conducted on 139 patients who underwent minimally invasive Morrow procedures from January to December 2023. The patients were divided into two groups based on whether they developed new-onset atrial fibrillation after surgery, and a comparative study was performed. Multivariate regression analysis and other statistical methods were used to assess factors potentially influencing POAF during CPB.
Results
Fifty (35.97%) patients developed POAF. Comparisons between the POAF group and the non-POAF group revealed significant differences in preoperative hypertension (38.0% vs. 14.6%, p = 0.002), coronary artery disease (40.0% vs. 20.2%, p = 0.012), history of heart failure (44.0% vs. 22.5%, p = 0.008), age (55.16 ± 14.11 vs. 46.28 ± 14.55, p = 0.001), the preoperative systemic immune-inflammation index (SII) (418.26 ± 243.97 vs. 330.24 ± 152.89, p = 0.016), the left atrial volume index (LAVI) (36.79 ± 12.08 vs. 32.24 ± 10.78, p = 0.024), CPB time (129.80 ± 39.58 vs. 116.96 ± 28.80, p = 0.035), CPB weaning time (25.68 ± 22.56 vs. 19.49 ± 6.78, p = 0.021), re-CPB rate (14.0% vs. 3.4%, p = 0.020), rate of ultrafast-track cardiac anaesthesia (UFTCA) (78.0% vs. 98.9%, p = 0.000), and postoperative SII (3292.84 ± 2921.82 vs. 2312.09 ± 1584.15, p = 0.024) (P < 0.05). All patients were discharged, but the ICU (2.07 ± 2.91 vs. 1.38 ± 0.78, p = 0.046) and postoperative hospital stays (11.84 ± 7.50 vs. 9.13 ± 2.62, p = 0.002) were significantly prolonged. Age is an independent risk factor for POAF, and the UFTCA is an independent protective factor (p < 0.001). POAF occurrence is closely related to preoperative hypertension (OR = 3.777, 95% CI: 1.599–8.920), a history of heart failure (OR = 2.858, 95% CI: 1.294–6.313), LAVI (OR = 1.035, 95% CI: 1.002–1.069), CPB weaning time (OR = 1.051, 95% CI: 1.001–1.103), re-CPB (OR = 5.035, 95% CI: 1.169–21.840), and postoperative SII (OR = 1.000, 95% CI: 1.000-1.001) (p < 0.05).
Conclusion
UFTCA is an independent protective factor against POAF. CPB weaning time and re-CPB are risk factors for the occurrence of POAF after the Morrow procedure. Actively implementing UFTCA, shortening the CPB weaning time, and avoiding the re-CPB are expected to lower the risk of POAF, shortening the ICU and hospital stays and enhancing recovery.
The Relationship Between Physiological Risk Factors and Stroke: A Mendelian Randomization Study
Authors: Fan Li , wang suzhen 
Published: November 2024

Abstract

Objective: Physiological risk factors play a crucial role in stroke development and prognosis. However, traditional epidemiological research methods cannot clearly establish a causal relationship between the physiological risk factors and stroke. Mendelian Randomization (MR) has recently emerged as a method of
studying causal relationships. This study used a two-sample MR to explore the causal relationship between
physiological risk factors and stroke.
Methods: The four most commonly used MR methods were used in this analysis. All statistical analyses were performed using the "TwoSampleMR 0.5.7" package in R. The outcome variable was stroke (ischemic and hemorrhagic stroke), and the exposure factors were the five common physiological risk factors analyzed in the 2019 GBD study, including body mass index, fasting blood glucose, systolic blood pressure, LDL cholesterol, and renal dysfunction. The instrumental variables were genetic loci associated with ischemic or hemorrhagic stroke as derived from GWAS studies.
Results: The results showed that there was a significant causal association between body mass index and ischemic stroke (OR = 1.21, 95% CI: 1.14~1.30, P = 3.55×10^-5), systolic blood pressure (OR = 1.61.04, 95% CI: 1.50~1.74, P = 8.26 Ã–10^-36), and cholesterol (OR = 1.71, 95% CI: 1.12~2.62, P = 1.26×10^-6) with significant causal associations. There was also a significant causal association between body mass index and hemorrhagic stroke (OR = 1.45, 95% CI: 1.23~1.71, P = 1.27 × 10^-5), and systolic blood pressure (OR = 1.65, 95% CI: 1.38~1.97, P = 2.84 × 10^-8).
Conclusion: Genetic variation-predicted physiological risk factor indicators, such as body mass index, systolic blood pressure, and cholesterol, were significantly associated with an increased risk of ischemic and hemorrhagic stroke and significantly increased the risk of stroke. Additionally, cholesterol is significantly associated with an increased risk of ischemic stroke but not with an increased risk of hemorrhagic stroke. Early detection and active management of body mass index, systolic blood pressure, and cholesterol are crucial for stroke prevention and prognosis and are important measures for preventing and controlling stroke. These risk factors can be effectively controlled by adjusting lifestyle and medical treatment, thereby reducing the risk of stroke.
Wide-row cereal cultivation as a tool to promote brown hare (Lepus europaeus) populations: a performance assessment
Authors: Weber Darius , Roth Tobias 
Published: November 2024

Abstract

For pre-weaning leverets (Lepus europaeus), cereals are low risk crops because predators rarely hunt there and agricultural machinery is only used once during the harvest. However, the dense stand of cereals hinders hares to enter from May until harvest in July, the months with the highest numbers of leverets. Making cereal fields accessible to hares in spring and summer by sewing them in wider rows than usual may improve the survival of young hares and thus could increase hare populations. Here, we assessed the impact of a recent change in cereal cultivation that has been introduced in Switzerland specifically to promote brown hares: the cultivation of cereals in wide rows. We surveyed hare densities between spring and autumn and assessed whether the seasonal increase in density (i.e. the hare population growth rate) depended on the proportion of cereals in wide rows, arable land, cereals and fallow land as well as on hare density in spring using mixed linear models. A total of 32 study areas with an average size of 376 ha were surveyed. Of the four land-use variables, only the proportion of cereals in wide rows had a significant positive effect (p = 0.02) on the hare population growth rate. A 1% increase in cereals in wide rows results in an average increase in hare growth rate of 3.6%. This effect was weaker in areas with a high hare density in spring. We conclude that cereals in wide rows is a useful tool to increase brown hare densities.
Optimization of High-Rise Building Retrofitting Against Wind Loads
Authors: Samir Rania , Abdel-Hameed Mohamed , Eraky Atef , Salama Abdallah 
Published: November 2024

Abstract

As the height of any structure increases, it becomes slenderer and more sensitive to wind loads. So, any increase in the structure height that was not considered during the initial stages of the design process will cause many structural issues. For such a problem, structural retrofitting is suggested to resist wind loads and satisfy safety and serviceability requirements. The strategy of retrofitting includes adding structural steel wind-resisting systems in the openings of the structural plan. This paper proposes an optimization technique for steel systems used to retrofit high-rise buildings, which aims to reduce the weight of the steel system keeping the building meeting the constraints of lateral displacement at the top of the building using Genetic Algorithm (GA) as an optimization algorithm. Integrated with CSI ETABS, the Visual Basic application is designed to perform this task. The proposed technique is applied to two cases of reinforced concrete buildings that are vulnerable to wind loads. The first case depicts a sense of consistency within buildings, while the second case exemplifies instances of irregularity in architectural design. Both cases are studied at heights of 15, 18, 21, 24, and 27 stories. The results show that strengthening a building using the optimized steel-braced frame is an efficient technique. The stiffness distribution of the optimum retrofitting system is concluded and formulas describing this distribution are derived.
Age, parental exposure, mass media, and sexual behaviour related to adolescents' level of future readiness in Indonesia
Authors: Rahmadewi Rahmadewi , Ekawati Rindang , Rahayuwati Laili , Nasution Sri Lilestina , Agustina Habsyah Saparidah , Rahayu Endah , Amelia Vira 
Published: November 2024

Abstract

Adolescents are a productive age group that will play an important role in achieving the demographic bonus in Indonesia by 2030. Problems that can be encountered in adolescents include knowledge, attitudes and sexual behaviour related to reproductive health. Their sexual behaviour can reflect their understanding as adolescents regarding their level of future readiness (e.g., long, healthy, happy, prosperous life). This research aims to analyse the relationship between family roles, sexual behaviour and the level of future readiness among adolescents in Indonesia. This research uses secondary data from the 2019 Program Performance and Accountability Survey results from the National Population and Family Planning Agency, the Central Statistics Agency, and universities in 34 provinces in Indonesia. The sample was young men and women aged 10–24 who were unmarried for the last six months and were registered as family members in selected households in Indonesia. Data were analysed using descriptive, bivariate and multivariate analysis with logistic regression. The result showed that the individual factors associated with adolescents' level of future readiness are age group (0.000), gender (0.018), education (0.000), and adolescent reproductive health (ARH) knowledge (0.000). Family factors associated with adolescents' level of future readiness are parental exposure to ARH (0.000) and implementation of family roles (0.000). The environmental factors associated with adolescents' level of future readiness are the source of ARH information through mass media (0.000) and the source of population information through mass media (0.000). Implementing family roles is the most dominant factor influencing adolescents' level of future readiness.
Fabrication and characterization of Curcumin and Piperine loaded CMTG/rGO Electrospun for breast cancer treatment
Authors: Orsu Prabhakar , CH Vasavi 
Published: November 2024

Abstract

The development of multi-drug-loaded electrospun nanocomposites with superior biomimetic properties and controlled release capabilities is critical for advancing breast cancer treatment. In this study, we introduce electrospun nanocomposite fibers composed of reduced graphene oxide (rGO) and carboxymethyl tamarind gum (CMTG), which are coated with curcumin and piperine to achieve targeted and controlled drug delivery at tumor sites. Both rGO and CMTG act as stabilizing agents with potent antioxidant activity and enhanced biocompatibility. The synthesized rGO/CMTG nanocomposite was extensively characterized using functional, crystallographic, and surface morphology analyses, confirming the formation of an amorphous structure. In vitro drug release studies demonstrated the nanocomposite’s high drug loading efficiency and sustained release profile. Additionally, cytotoxicity assays using MDA-MB-231 human breast cancer cells revealed that the rGO/CMTG nanocomposite effectively induced cell death with a favorable IC50 value. These findings suggest that rGO/CMTG nanofiber-based systems hold significant promise as a therapeutic platform for breast cancer treatment.
Exploring iron deposition patterns using light and electron microscopy in the mouse brain across aging and Alzheimer’s disease pathology conditions
Authors: Lau Victor , VanderZwaag Jared , Murray Colin , Tremblay Marie-Ève 
Published: November 2024

Abstract

Alzheimer’s disease (AD) involves cognitive decline, possibly via multiple concurrent pathologies associated with iron accumulation. To investigate if iron accumulation in AD is more likely due to pathological iron-rich compartments, or a compensatory response of iron within oligodendrocytes to disease progression, we sought to quantify iron-rich staining (via Perl’s diaminobenzidine; DAB). Healthy wild-type (WT) and APPSwe-PS1Δe9 (APP-PS1; amyloid-beta overexpressing) male mice were examined during midde-age, at 14 months. The prefrontal cortex, a brain region affected over the course of dementia progression, was investigated. Iron-rich compartments were found across genotypes, including oligodendrocytes, and immune cells at the blood-brain barrier, and exclusively amyloid plaques in the APP-PS1 genotype. A semi-automated approach was employed to quantify staining intensity of iron-rich compartments with light microscopy. Mouse prefrontal cortex of each genotype was also assessed qualitatively and ultrastructurally with scanning electron microscopy, to novelly discern and confirm iron-rich staining (via Perl’s DAB). We found parenchymal iron staining corresponding to oligodendrocytes, pericytes, astrocytes, microglia and/or infiltrating macrophages, and amyloid plaques; increased iron deposition and clustering were detected in middle-aged male APP-PS1 vs WT prefrontal cortex, supporting that AD pathology may involve greater brain iron levels and local clustering. Unexpectedly, iron-rich cells were enriched at the central nervous system (CNS) interface and perivascular space in control and APP-PS1 mouse models, with ultrastructural examination revealing examples of these cells loaded with many secretory granules containing iron. Together, our results provide novel exploration and confirmation of iron-rich cells/compartments in scanning electron microscopy and reinforce literature that iron deposition is relatively increased in AD over healthy cognitive aging and involves greater local clusters of iron burden. Increased iron burden along the aging trajectory, regardless of cognitive status, may also be attributed to novelly-discovered iron-rich cells secreting granules along the CNS border.
Overcoming Recurrent Pregnancy Loss with Advanced Fertility Techniques: A Case Report on Combined Stem Cell Therapy, In-vitro Activation and Lymphocyte immunotherapy
Authors: Patel Niket , Patel Nayana , Patel Molina , Bhadarka Harsha , Ghoghari Paresh , Dhaduk Sachin , Chudasama Piyush , Vyas Kairavi 
Published: November 2024

Abstract

Infertility continues to be one of the most challenging issues that affects a significant number of people worldwide and is often accompanied by advanced maternal age and poor ovarian reserve. These factors also contribute significantly to recurrent miscarriage and secondary infertility. The traditional fertility treatment proves to be a failure in cases where the women have clinically low AMH (anti-Müllerian hormone) levels and multiple miscarriages. Novel therapeutic approaches are required to address such complex case scenarios. A 46-year-old woman with a history of secondary infertility and four miscarriages presented with an AMH level of 0.88. Traditional fertility treatments had previously failed to yield successful outcomes. the patient underwent a combined therapy involving Bone marrow-derived stem cell therapy, laparoscopy and hysteroscopy, lymphocyte immunotherapy (LIT) and in vitro activation. Post-treatment, the woman conceived and delivered a normal baby who previously faced infertility and Recurrent Pregnancy Loss. This case indicates the potential of an innovative combined approach using Bone marrow-derived stem cell therapy, In-vitro Activation and LIT in the treatment of complex fertility problems, especially in women with diminished ovarian reserve and Recurrent Pregnancy Loss.
Machine Learning in Healthcare Citizen Science: A Scoping Review
Authors: Baminiwatte Ranga , Torsu Blessing , Scherbakov Dmitry , Mollalo Abolfazl , Obeid Jihad S. , Alekseyenko Alexander V. , Lenert Leslie A. 
Published: November 2024

Abstract

Objectives: This scoping review aims to clarify the definition and trajectory of citizen-led scientific research (so-called citizen science) within the healthcare domain, examine the degree of integration of machine learning (ML) and the participation levels of citizen scientists in health-related projects.
Materials and Methods: In January and September 2024 we conducted a comprehensive search in PubMed, Scopus, Web of Science, and EBSCOhost platform for peer-reviewed publications that combine citizen science and machine learning (ML) in healthcare. Articles were excluded if citizens were merely passive data providers or if only professional scientists were involved.
Results: Out of an initial 1,395 screened, 56 articles spanning from 2013 to 2024 met the inclusion criteria. The majority of research projects were conducted in the U.S. (n=20, 35.7%), followed by Germany (n=6, 10.7%), with Spain, Canada, and the UK each contributing three studies (5.4%). Data collection was the primary form of citizen scientist involvement (n=29, 51.8%), which included capturing images, sharing data online, and mailing samples. Data annotation was the next most common activity (n=15, 26.8%), followed by participation in ML model challenges (n=8, 14.3%) and decision-making contributions (n=3, 5.4%). Mosquitoes (n=10, 34.5%) and air pollution samples (n=7, 24.2%) were the main data objects collected by citizens for ML analysis. Classification tasks were the most prevalent ML method (n=30, 52.6%), with Convolutional Neural Networks being the most frequently used algorithm (n=13, 20%).
Discussion and Conclusions: Citizen science in healthcare is currently an American and European construct with growing expansion in Asia. Citizens are contributing data, and labeling data for ML methods, but only infrequently analyzing or leading studies. Projects that use “crowd-sourced” data and “citizen science” should be differentiated depending on the degree of involvement of citizens.