bluuebunny/crossref_metadata_2025_split huggingface dataset:
Emisiones de dióxido de carbono y ecoeficiencia del hormigón tradicional y modificado. Revisión de literatura
Authors: Arbelaez-Perez Oscar Felipe , Gómez-Ospina Jorge Hernán , Herrera-Herrera Santiago , Rodríguez-Rojas Cristian Ferney 
Published: October 2024

El impacto ambiental negativo de las emisiones de CO2 provenientes de la industria del hormigón, requiere la sustitución de los materiales tradicionales, por residuos que permitan mejorar las propiedades mecánicas, y disminuir las emisiones de CO2. Esta revisión recopila la información de artículos entre 2000 y 2021 y se analizan las características de diseño y los resultados encontrados en las propiedades mecánicas y en las emisiones de CO2 de los hormigones. Asimismo, se calculó la ecoeficiencia de las mezclas. Se encontró que las emisiones dependen del tipo de sustituto, de su porcentaje de sustitución, y de las condiciones de diseño (relación agua/cemento y resistencia a compresión). Se discuten las perspectivas frente al tema y los desafíos que enfrenta la industria del hormigón. Se espera que esta revisión motive incluir el cálculo de las emisiones y la ecoeficiencia de los hormigones como parámetro para cuantificar su impacto ambiental.
The negative environmental impact of CO2 emissions from the concrete industry requires the substitution of traditional materials with waste materials to improve mechanical properties and reduce CO2 emissions. This review compiles information from articles between 2000 and 2021 and analyzes the design characteristics and the results found in the mechanical properties and CO2 emissions of concrete. Also, the eco-efficiency of the mixes was calculated. It was found that emissions depend on the type of substitute, its substitution percentage, and the design conditions (water/cement ratio and compressive strength). Perspectives on the issue and the challenges facing the concrete industry are discussed. It is expected that this review will motivate to include the calculation of emissions and eco-efficiency of concrete as a parameter to quantify its environmental impact.
Simulasi Rancang Bangun Closed Loop Boost Converter Terintegrasi Solar PV Berbasis Mikrokontroller
Authors: Rahma Nur Amalia  , Wijaya Kusuma  , Ruwah Joto  , Afidah Zuroida  , Hikmah Ariq  
Published: October 2024

Penggunaan solar PV secara konvensional yang memiliki beberapa tantangan dari segi intensitas radiasi cahaya matahari dan temperatur lingkungan menyebabkan tegangan keluaran cenderung fluktuatif. Sebagai langkah mitigasi permasalahan tersebut dibutuhkan aplikasi rangkaian elektronika daya berupa boost converter atau yang dapat disebut dengan step-up DC-DC converter yang sesuai. Pemilihan step-up DC-DC converter jenis boost converter ini memiliki beberapa keunggulan yakni dapat diaplikasikan pada pembangkit energi terbarukan. Pada penelitian ini pemodelan desain boost converter dirancang closed loop dengan menggunakan controller (pengontrol/pengendali) PID (Proportional Integral Derrivative) sehingga tegangan output solar PV yang fluktuatif akibat pengaruh irradiasi matahari ini dapat distabilkan sesuai dengan setpoint yang diinginkan untuk menyupply beban pompa 24 Volt. Tahapan penelitian ini diawali dengan menentukan perencanaan desain rangkaian, penentuan spesfikasi komponen, pembuatan algoritma pemrograman PID Controller dan simulasi rangkaian serta pengujian. Dari hasil pengujian simulasi terbukti bahwa rangakaian prototype boost converter mampu menaikkan tegangan solar PV bervariasi (15.68V-20.87V) dan stabil di tegangan 24 Volt. Penggunaan PID Controller dengan nilai Kp=0,07;Ki=0,05;Kd=0,3 memiliki respon transien yang cepat yakni dengan rise time (tr) 1,62 ms, settling time (ts) 10 ms dan peaktime (tp) sebesar 33,8ms. Nilai maximum overshoot (Mp) juga cenderung rendah sebesar 1,5%.
An assessment framework for smart and sustainable housing for older adults using analytic hierarchy process (AHP)
Authors: Ptak-Wojciechowska Agnieszka , Kort Helianthe , Kasraian Dena , Gawlak Agata 
Published: October 2024

IntroductionWhile there is a call for smart and sustainable housing in general and for older adults in particular, little attention is paid to identifying the determinants of such housing and their extent of influence on the quality of life (QoL) of older adults. This study addresses the above gap by re-defining the criteria for house quality assessment, taking into account new needs of older inhabitants, while concerning digital assistive technologies.MethodsThis research uses various methods to identify and validate housing-related criteria and metrics, resulting in a transparent multi-criteria evaluation framework that accounts for the spatial needs of older adults. These include recommendations for multi-criteria decision-making method (MCDM/A), expert workshop to develop new metrics and validate sub-criteria, expert survey to prioritize criteria and sub-criteria and interviews with three employees in the construction-services sector in the Netherlands, to gain knowledge on smart and healthy environments.Results and DiscussionThe results show that age-friendliness of housing function is the most significant criterion, while availability of housing modifications for seniors most important sub-criterion. Our findings can benefit architects in designing improved age- friendly spaces, older adults in evaluating their dwellings and researchers from the field of architecture in selecting most relevant method for their study.
Efficient phosphate removal from water using ductile cast iron waste: a response surface methodology approach
Authors: Roushdy Mai Hassan , Elkhashab Nada Amr , Osman Ahmed Ibrahim , Ali Dalia Amer 
Published: October 2024

Water scarcity is a critical issue worldwide. This study explores a novel method for addressing this issue by using ductile cast iron (DCI) solid waste as an adsorbent for phosphate ions, supporting the circular economy in water remediation. The solid waste was characterized using XRD, XRF, FTIR, and particle size distribution. Wastewater samples of different phosphate ion concentrations are prepared, and the solid waste is used as an adsorbent to adsorb phosphate ions using different adsorbent doses and process time. The removal percentage is attained through spectrophotometer analysis and experimental results are optimized to get the optimum conditions using Design Expert V13. The pseudo-second order (PSO) kinetics model and Langmuir isotherm were fitted with the experimental results with maximum adsorption capacity (qmax = 0.28 mg/g). The thermodynamic analysis indicated that this adsorption process was spontaneous based on the negative value of Gibbs free energy (∆G). Additionally, the positive values of enthalpy (∆H) indicated the endothermic nature of this adsorption system. It was able to reach the highest adsorption percentage of 98.9 (%) for phosphate ions from aqueous solutions using response surface methodology (RSM) with optimum conditions of 10 mg/L phosphate ion concentration, pH = 8, normal room temperature, 9 min adsorption, and 0.5 g/L adsorbent dosage.
Machine learning derived model for the prediction of bleeding in dual antiplatelet therapy patients
Authors: Qian Yang , Wanlin Lei , Maofeng Wang 
Published: October 2024

ObjectiveThis study aimed to develop a predictive model for assessing bleeding risk in dual antiplatelet therapy (DAPT) patients.MethodsA total of 18,408 DAPT patients were included. Data on patients’ demographics, clinical features, underlying diseases, past history, and laboratory examinations were collected from Affiliated Dongyang Hospital of Wenzhou Medical University. The patients were randomly divided into two groups in a proportion of 7:3, with the most used for model development and the remaining for internal validation. LASSO regression, multivariate logistic regression, and six machine learning models, including random forest (RF), k-nearest neighbor imputing (KNN), decision tree (DT), extreme gradient boosting (XGBoost), light gradient boosting machine (LGBM), and Support Vector Machine (SVM), were used to develop prediction models. Model prediction performance was evaluated using area under the curve (AUC), calibration curves, decision curve analysis (DCA), clinical impact curve (CIC), and net reduction curve (NRC).ResultsThe XGBoost model demonstrated the highest AUC. The model features were comprised of seven clinical variables, including: HGB, PLT, previous bleeding, cerebral infarction, sex, Surgical history, and hypertension. A nomogram was developed based on seven variables. The AUC of the model was 0.861 (95% CI 0.847–0.875) in the development cohort and 0.877 (95% CI 0.856–0.898) in the validation cohort, indicating that the model had good differential performance. The results of calibration curve analysis showed that the calibration curve of this nomogram model was close to the ideal curve. The clinical decision curve also showed good clinical net benefit of the nomogram model.ConclusionsThis study successfully developed a predictive model for estimating bleeding risk in DAPT patients. It has the potential to optimize treatment planning, improve patient outcomes, and enhance resource utilization.
Plasma proteomics and carotid intima-media thickness in the UK biobank cohort
Authors: Chen Ming-Li , Kho Pik Fang , Guarischi-Sousa Rodrigo , Zhou Jiayan , Panyard Daniel J. , Azizi Zahra , Gupte Trisha , Watson Kathleen , Abbasi Fahim , Assimes Themistocles L. 
Published: October 2024

Background and aimsUltrasound derived carotid intima-media thickness (cIMT) is valuable for cardiovascular risk stratification. We assessed the relative importance of traditional atherosclerosis risk factors and plasma proteins in predicting cIMT measured nearly a decade later.MethodWe examined 6,136 UK Biobank participants with 1,461 proteins profiled using the proximity extension assay applied to their baseline blood draw who subsequently underwent a cIMT measurement. We implemented linear regression, stepwise Akaike Information Criterion-based, and the least absolute shrinkage and selection operator (LASSO) models to identify potential proteomic as well as non-proteomic predictors. We evaluated our model performance using the proportion variance explained (R2).ResultThe mean time from baseline assessment to cIMT measurement was 9.2 years. Age, blood pressure, and anthropometric related variables were the strongest predictors of cIMT with fat-free mass index of the truncal region being the strongest predictor among adiposity measurements. A LASSO model incorporating variables including age, assessment center, genetic risk factors, smoking, blood pressure, trunk fat-free mass index, apolipoprotein B, and Townsend deprivation index combined with 97 proteins achieved the highest R2 (0.308, 95% C.I. 0.274, 0.341). In contrast, models built with proteins alone or non-proteomic variables alone explained a notably lower R2 (0.261, 0.228–0.294 and 0.260, 0.226–0.293, respectively). Chromogranin b (CHGB), Cystatin-M/E (CST6), leptin (LEP), and prolargin (PRELP) were the proteins consistently selected across all models.ConclusionPlasma proteins add to the clinical and genetic risk factors in predicting a cIMT measurement. Our findings implicate blood pressure and extracellular matrix-related proteins in cIMT pathophysiology.
Artificial intelligence driven image analysis identifies phenobarbital induced hepatocyte hypertrophy in liver microtissues across species
Authors: Elcombe Matthew , Mathur Ayesha , Wallace Stephanie , Wright Jayne , Plummer Simon 
Published: October 2024

In vivo treatment of rats with phenobarbital (PB) induces liver enzyme induction associated with hepatocyte hypertrophy. In the present study we used a novel microTMA technology coupled with artificial intelligence (AI) driven image analysis and proteomics analysis to test the hypothesis that PB treatment of rat and human liver microtissues could recapitulate hepatocyte hypertrophy in vitro. Human and rat liver microtissues were treated with PB over a range of concentrations (500 uM - 2000 uM). Fixed liver microtissues were embedded in paraffin in a microTMA mold, sectioned and stained on parallel microTMA sections with H&amp;E and cell type specific markers, respectively. An AI algorithm was trained to identify and measure changes in hepatocyte cytoplasmic area on images of H&amp;E stained microtissue sections. Image analysis with this algorithm showed that treatment of human and rat liver microtissues with PB (500 uM) for 96 h caused significant increases (p ≤ 0.08- p &lt; 0.01) in hepatocyte cytoplasmic area, a hallmark of hypertrophy. Proteomics analysis of control and PB treated liver microtissue samples confirmed this treatment also caused phase1 and phase 2 enzyme induction in both human and rat samples. In conclusion AI driven image analysis of H&amp;E stained liver microtissue FFPE sections shows that this model can recapitulate a PB-induced hypertrophy response.
Patient feasibility as a novel approach for integrating IRT and LCA statistical models into patient-centric qualitative data—a pilot study
Authors: Klüglich Matthias , Santy Bert , Tanev Mihail , Hristov Kristian , Mincheva Tsveta 
Published: October 2024

IntroductionClinical research increasingly recognizes the role and value of patient-centric data incorporation in trial design, aiming for more relevant, feasible, and engaging studies for participating patients. Despite recognition, research on analytical models regarding qualitative patient data analysis has been insufficient.AimThis pilot study aims to explore and demonstrate the analytical framework of the “patient feasibility” concept—a novel approach for integrating patient-centric data into clinical trial design using psychometric latent class analysis (LCA) and interval response theory (IRT) models.MethodsA qualitative survey was designed to capture the diverse experiences and attitudes of patients in an oncological indication. Results were subjected to content analysis and categorization as a preparatory phase of the study. The analytical phase further employed LCA and hybrid IRT models to discern distinct patient subgroups and characteristics related to patient feasibility.ResultsLCA identified three latent classes each with distinct characteristics pertaining to a latent trait defined as patient feasibility. Covariate analyses further highlighted subgroup behaviors. In addition, IRT analyses using the two-parameter logistic model, generalized partial credit model, and nominal response model highlighted further distinct characteristics of the studied group. The results provided insights into perceived treatment challenges, logistic challenges, and limiting factors regarding the standard of care therapy and clinical trial attitudes.
The genetic causal effect of hand grip strength on osteoporosis and falling risk: a Mendelian randomization study
Authors: Ma Yanhua , Qiao Jingtao , Wang Zhenxing , Pan Qi , Guo Lixin 
Published: October 2024

BackgroundPatients with osteoporosis (OP) are often associated with decreased hand grip strength and increased risk of falling. It remains unclear whether there is a genetic causal between hand grip strength and OP, falling risk.MethodsThe Mendelian randomization study was used to investigate the genetic causal effect of low hand grip strength on total body bone mineral density (BMD) at different ages, OP, and falling risk. Genes for low hand grip strength, total body BMD at different ages, OP, and falling risk were obtained from published genome-wide association studies. Inverse variance weighted, MR‐Egger, and weighted median were applied to perform the MR analysis. The Cochran’s Q test, MR‐Egger intercept test, MR-PRESSO global test, and leave-one-out analysis were used to detect the pleiotropy or heterogeneity.ResultsThe results showed strong evidence that low hand grip strength was positively associated with OP (OR: 1.006, 95% CI: 1.003-1.010; P= 0.0001) and falling risk (OR: 1.069, 95% CI: 1.013-1.129; P= 0.0160), and could not directly affect the different ages of total body BMD (P&gt; 0.05). There was no heterogeneity or horizontal pleiotropy in the sensitivity analysis (all P&gt; 0.05).ConclusionThe study found a positive causal relationship between low hand grip strength and higher risk of OP and falling, which should be taken into account in the development of future prevention and screening strategies for OP and falling.
Assessment of the spatial-temporal impact of the Longhai Railway transportation corridor on land cover changes and landscape patterns
Authors: Gu Hongliang , Zhang Xiaolong 
Published: October 2024

IntroductionTransportation corridors, as special economic corridors, have a greater impact on land cover and landscape pattern changes.MethodsTherefore, 10 buffer zones were established at 1 km intervals on both sides of the Longhai Railway as the centerline to trace the impact of the railroad corridor on the land use change and regional landscape pattern change of the cities along the line from 1985 to 2020.ResultThe results show that: (1) The land cover changes along the railroad corridor during the 35 years are mainly characterized by the conversion between cropland, grassland, and construction land. Compared with 1985, in 2020, the construction land increased by 161.96%, the grassland area decreased by 11.83%, and the cropland area decreased by 15.83%. (2) The fragmentation of land patches and vegetation coverage is negatively and positively correlated with the buffer zone distance, respectively. In the same year, the comprehensive land-use dynamic degree is smaller as it is further away from the railway. The nighttime light index in the buffer zone is significantly correlated with the land aggregation index and average patch area, and the closer to the railroad, the higher the land aggregation index of construction land. (3) In terms of zoning, the intensity of land cover and landscape pattern changes in the eastern section is higher than that in the western section, with a higher degree of land fragmentation and more agglomeration of construction land, and the transportation corridor has a greater impact on the change of integrated land use motives in this region. The results of the study can provide a scientific basis for optimising the spatial pattern of land and improving the ecological environment in the construction of cross-regional transport corridors.
New perspectives on metagenomic analysis for pathogen monitoring in sustainable freshwater aquaculture production: a systematic review
Authors: Macedo Daralyns Borges , dos Anjos Thais Mayara Castro , De Los Santos Edian Franklin Franco , Rodrigues Marília Danyelle Nunes , Alegria Oscar Victor Cardenas , Ramos Rommel Thiago Jucá 
Published: October 2024

The freshwater and saltwater aquatic food sector has experienced the most significant growth in recent years and is increasingly recognized as a sustainable alternative for fostering prosperous societies self-sufficiently and ecologically. One primary economic and health risk factor in aquaculture production is health control, with potentially more severe impacts observed in tropical and developing countries. While metagenomics holds great promise for application in agro-industrial fields like aquaculture, its adoption remains limited. Consequently, this study aimed to assess the prospects for developing and applying metagenomics in identifying pathogens in freshwater aquaculture. The WIPO database was used to search for patents developed using metagenomics to monitoring pathogens in freshwater aquaculture. Metagenomics methods have been extensively employed in different fields, such as, medicine, veterinary, biotechnology, agriculture, particularly in studies focusing on microbial communities in different ecosystems. In aquaculture, the utilization of metagenomics has predominantly revolved around investigating antibiotic resistance genes, primarily in saltwater farms. Despite this, freshwater aquaculture, particularly in fish and crustacean farming, aligns closely with sustainable development goals, notably (SDGs) 2, 3, 6, and 13. Countries such as the United States of America, South Korea, and Canada stand at the forefront of utilizing metagenomics for disease monitoring in freshwater aquaculture, evidenced by their active patent developments. The metagenomic analysis, coupled with bioinformatics tools and databases, represents a rapid, secure, and non-invasive approach to environmental monitoring for preventive purposes.Systematic review registrationhttps://osf.io/srpyz/, identifier 10.17605/OSF.IO/SRPYZ.
Newborn screening for severe combined immunodeficiency in Malaysia: current status, challenges and progress
Authors: Chang Wai Leng , Mohd Noh Lokman , Abdul Latiff Amir Hamzah , Woo Kent Chee Keen , Ismail Intan Hakimah , Abd Hamid Intan Juliana , Siniah Sangeetha , Zainal Abidin Mohd Azri , Sham Marina , Mat Ripen Adiratna , Baharin Mohd Farid , Abdul Wahab Asrul , Zainudeen Zarina Thasneem , Hashim Ilie Fadzilah , Wong Yee Ming , Ahmad Shawaludin Mohamad Qazreen , Ali Adli 
Published: October 2024

IntroductionEarly diagnosis of Severe Combined Immunodeficiency (SCID) increases survival outcomes and quality of life while significantly minimizing healthcare burden and costs. Despite growing evidence supporting the benefits and cost-effectiveness of SCID detection through newborn screening (NBS), it has yet to be implemented in Malaysia. This study aims to explore experts’ opinions on the current status, challenges, and crucial strategies needed for the successful implementation of SCID NBS.MethodologyA guided, structured interview was employed to explore opinions on the current status, barriers, and strategies for implementing SCID NBS in Malaysia. All 13 invited experts participated in this study, indicating complete participation from the entire Malaysian immunology fraternity (consisting of eight clinical immunologists and five immunopathologists).Key findingsSeveral initiatives are ongoing to establish SCID NBS in Malaysia. Hindrances such as low immunologist-to-patient ratio, unequal placements of immunologists throughout Malaysia, society’s low disease awareness, national health prioritization, lack of stakeholder engagement, and inadequacy of local study/data were highlighted. Pilot research on SCID NBS, advocacy workshops, and promotion materials are among the ongoing activities outlined in the blueprint, paving the way for this nationwide NBS program to be achievable in the near future.ConclusionThis article provides recommendations to policymakers in mandating SCID NBS. Strategies by key stakeholders are underway, particularly in advocacy programs and efforts to increase awareness among clinicians and the public.