bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design and Simulation of a Sustainable Green DC-DC Multi-Outlet Electric Vehicle Charger
Authors: Somefun T. E. , Longe O. M. 
Published: December 2024

Abstract
This paper presents the design and simulation of a DC-DC charger with four outlets, utilising both outer and inner loop control strategies to efficiently charge lithium-ion batteries of varying nominal voltages and capacities. To manage the charging process of electric vehicles (EVs), the authors investigated single converter switching mode (SCSM) and double converter switching mode (DCSM). SCSM uses one insulated-gate bipolar transistor (IGBT) for buck converter switching, while DCSM uses two IGBTs. The proposed system is designed to handle four different battery configurations (12 V, 1000 Ah; 24 V, 1500 Ah; 48 V, 2000 Ah; 96 V, 2500 Ah) and operate from a 400 V DC source. Simulation results validate the effectiveness of the control strategies and indicate that SCSM achieves a steady charging and discharging operation process over all the switching stages compared to the DCSM. This work further presents the comparative analysis of SCSM and DCSM in a multi-outlet EV charger, and the result shows an average percentage increase in charging rate of 0.002% for both SCSM and DCSM. This study provides a foundation for developing advanced EV charger capable of handling diverse battery configurations with improved performance. The charger is modelled using 2024a Matlab/Simulink software, and simulation results ascertain a good operation performance of the EV charger.
Rainfall variability: implication for flood occurrence in Ibadan and Ikeja, south-west Nigeria
Authors: Ayinla Titilope Olubunmi , Arijaje Theophilus Emuobor 
Published: December 2024

Abstract
Rainfall in Nigeria varies in distribution and amount at temporal and spatial scales. One of the risks associated with rainfall variability is flood. Flood is a natural phenomenon that causes havoc to lives, properties, economic, cultural heritage and environment in a flood-prone region. Literature has revealed that the major determinant of this natural phenomenon is rainfall. Reoccurrence of floods in some parts of southwest (SW) Nigeria has demanded investigation into the distribution of rainfall for proper monitoring of its increment. Rainfall distribution data covering Ikeja and Ibadan from year 2005 to 2011 were obtained from the Nigerian Meteorological Agency, Nigeria. The obtained data were used to compute monthly and annual average rainfall occurrences in the two locations using a semi-automated technique. Basic statistics were performed on the data to know the trend in the rainfall pattern, which could be used for flood prediction and management in the study area. The maximum annual rainfall recorded in Ikeja during the period of investigation ranged from 327.6 to 476.9 mm, while that of Ibadan ranged from 234.1 to 373.4 mm. The driest years in Ibadan and Ikeja were 2007 and 2009, while the wettest years in the two locations were 2008, respectively. The correlation between the monthly variations in each year across the two locations showed positive correlation, which are significant at 1% level. The trend of rainfall occurrence in SW Nigeria revealed that for every dry year, there is always subsequent wet year, which could generate flood. Proper data acquisition, management and analysis of rainfall data would assist to mitigate the occurrence of flood disaster in our environment, which is directed towards actualizing sustainable cities and communities.
Unveiling the therapeutic benefits and potentials of Water Hyacinth in promoting a sustainable healthy living: an overview
Authors: Uamai I. J. , Ayanda I. O. , Omohinmin C. A. 
Published: December 2024

Abstract
Water hyacinth (Eicchornia crassipes) is a notorious aquatic weed with an extraordinary proliferation rate globally, it can grow in different aquatic ecosystem types and varying climatic conditions, outcompete other indigenous plants, and establish to endanger biodiversity, shelter pests, clog fresh waterways, increase evapotranspiration, and hinder waterways traffic; but a little is known about the importance of its wide range of metabolites. The Nigerian health sector is faced with setbacks in meeting its increasing population’s basic health (medicine) needs. This situation has led to a call for the exploration of herbal plants as alternatives to synthetic drugs, primarily due to their availability and affordability. Despite the negative impacts of the invasive hydrophyte, water hyacinth, on the economy, ecology, and society, it remains an untapped bioactive resource. Given to the United Nations Development Goal of Good Health and Wellbeing (SDG 3), this review aims to highlight the bioactive components of water hyacinth and their potential for various therapeutic applications in improving human health, instilling a sense of hope for the future. Literatureswere sourced from databases including; Scopus, ScienceDirect, Google, and Google Scholar. Water hyacinth is a natural, easily accessible reservoir of various bioactive compounds comprising those that have been used for therapeutic purposes which include: the treatment of specific fungi and bacteria-related infections, malaria, cancer, ulceration, and malnutrition in various parts of the world. This plant therefore offers a promising sustainable supplementary solution in meeting the health sector’s needs.
Path Loss Prediction on Earth-Space Link Using Statistical and Time Series Approach at Ka-Band in Abuja, North Central Nigeria
Authors: Arijaje T. E. , Omotosho T. V. , Aizebeokhai A. P. 
Published: December 2024

Abstract
Predictive path loss modelling is essential in designing wireless communication systems. However, the empirical methods of path loss prediction are inaccurate as the empirical models cannot be implemented outside the area or region where they are developed. This study focuses on improving the prediction of path loss using statistical approaches such as multiple linear regression (MLR) and time series models using eight (2014 – 2021) data retrieved from the global precipitation measuring mission (GPM) at Ka-band. The step-wise selected method was adopted for the multiple linear regression (MLR). In the exponential smoothing method, weighting is carried out exponentially, decreasing in the direction of the older values. The MLR analysis revealed that the MLR model performs well, with an accuracy of 99.52%. The R2 value of 99.52% indicated a strong correlation between the estimated and predicted path loss in the model. PL = 18.706-0.98459Pr
+1.60027Pt
+0.99808Gr
The P-value of the regression model is 0.000, indicating that the model estimated by the MLR procedure is statistically significant at a level of 0.05. Also, the results showed that the transmitted antenna gain is the most contributed predictor in the path loss with a value of 1.60027 dB. Likewise, the results from the exponential smoothing models revealed that the single exponential smoothing (SES) model performs better than the double exponential smoothing model with a mean absolute percentage error (MAPE) of 14.47%, indicating that the model’s performance is good because the MAPE value falls within 10 – 20%. The mean absolute deviation (MAD), mean square deviation (MSD), and smoothing constant are 0.3215, 0.2313, and 0.9685, respectively. Striking a balance, the application of MLR and the SES models will improve wireless communication systems in Abuja, the North Central region of Nigeria, at Ka-band. Therefore, engineers and policymakers in the Nigerian telecommunication industry should assess the impacts of path loss within the study locations towards sustainable telecommunications and infrastructure (SDG goal 9) for planning and setting radiowave propagation technologies in the study locations and Nigeria at large.
Habit-inspired methods for embodied intelligence
Authors: Kuske Nicolas , Roehrbein Florian 
Published: December 2024

Abstract
Algorithms that employ habitual processing may be characterized as context-contingent input-output pairings. They learn to relate recurring patterns with swift and effective responses, relying on minimal computational resources. While habits have been extensively researched in the fields of psychology, cognition, and neuroscience, they have yet to be systematically investigated in computer science. Data volumes are expanding at an exponential rate, and there is often a requirement for this data to be processed in real-time. Against this backdrop, principles of habitual cognition present a promising alternative to resource-intensive planning algorithms. We propose that future research focus on algorithmic and neuronal models of the neurocognitive foundations of habits to develop new perspectives on artificial intelligence and robotics.
Embodied Intelligence in Additive Manufacturing
Authors: Xu Jie , Xie Yue , Iida Fumiya 
Published: December 2024

Abstract
Embodied intelligence reflects the ability of an agent to interact with its environment through its body to gain intelligence and autonomy. Such a concept has become popular in recent years for the design of robotic systems. This paper generalises the embodied intelligence concept to Additive Manufacturing (AM) to provide a new understanding of the technology with inspirations from biological production processes including organism growth and animal construction. Morphology-based embodied intelligence is analysed on the design and manufacturing aspects for delivering intelligent products (including robots) while embodied artificial intelligence (AI) (foundation models) is discussed for the printer itself. The paper opens a new perspective for AM research.
Evaluation of The Stochasticity in The Collective Bernoulli-ball System as A Physical Reservoir Computer
Authors: Ye Fan , Abdulali Arsen , Iida Fumiya 
Published: December 2024

Abstract
Reservoir computing is a type of machine learning approach that uses a fixed, randomly generated dynamic system called a reservoir to process input data for prediction and classification tasks. The performance of a reservoir computer is highly dependent on the properties of its physical reservoir, particularly its stochasticity. Currently, there is no practical guide for selecting an appropriate reservoir to accomplish desired tasks. In this paper, we utilized the collective Bernoulli-ball system as the reservoir and investigated the effect of stochasticity on its performance in a non-linear prediction task. Additionally, we examined other properties of the reservoir computer, such as the input delay, input gain, n-samples average, and prediction target delay. This paper reveals how stochasticity affects the prediction performance of a reservoir and provides some possible methods of adjusting the parameters mentioned above to mitigate the drawbacks of stochasticity. Our findings show that in low-noise cases the reservoir output follows the trend of the target, but sometimes jumps to a significant offset. For high-level noise, the system remains stable, but the trend information in the output is compressed since noises cover the effect of input, which finally makes the reservoir computer useless for the task.
Variable Value Alignment by Design; averting risks with robot religion
Authors: White Jeffrey 
Published: December 2024

Abstract
One approach to alignment with human values in AI and robotics is to engineer artificial systems isomorphic with human beings. The idea is that robots so designed may autonomously align with human values through similar developmental processes, to realize project ideal conditions through iterative interaction with social and object environments just as humans do, such as are expressed in narratives and life stories. One persistent problem with human value orientation is that different human beings champion different values as ideal, meaning that the values to which an AI should be aligned are ambiguous. Prior work considered human development of purpose and source of meaning in life in terms of project ideal conditions, in effect establishing lifelong value orientations according to which intermediate situations are evaluated. The present work compares views on motivating values from St. Augustine and from popular cognitive science. These accounts are described as divergent error theories which present to their proponents as mutually exclusive yet accurate accounts of personal experience due to differential development of variable innate potentials. Specifically, the hypothesis proposed is that differential development of spindle neural projections establishes enduring connections between prior established relatively immediate routine processes entrained during childhood and prioritized in popular cognitive science, and later developing higher-level social and self-processes entrained during adolescence and emphasized in Augustine’s account, with these projections hard-wiring lifelong motivating value orientations more or less inaccessible to modification through material interaction. Robot experiments informed by this study may evaluate variable value orientation by design, with for example autonomous robots developing motivating associations with temporally distal project ideal conditions through love for humanity, as described by Augustine, and others pursuing adaptive fit to passing norms consistent with popular contemporary accounts.
Exploring the dynamic and thermo-mechanical behavior of Banana/Kenaf/Jute epoxy hybrid biocomposites: impact of stacking sequences
Authors: Jeyaguru Sangilimuthukumar , Thiagamani Senthil Muthu Kumar , Pulikkalparambil Harikrishnan , Siengchin Suchart , Hashem Mohamed , Fouad Hassan 
Published: December 2024

Abstract
This study investigates the thermal behavior and thermo-mechanical properties of banana, jute, and kenaf fiber-reinforced epoxy composites, focusing on the impact of different layering sequences and hybrid configurations. The novelty of the work lies in the tailored stacking of natural fibers to optimize composite performance, a topic of growing significance in sustainable engineering. Thermal analysis revealed the highest endothermic peak at 72 °C in BJKKJBE hybrid composites, while jute fiber-reinforced composites exhibited a marginally higher peak at 73 °C. Dynamic mechanical analysis highlighted kenaf fiber-reinforced composites as having superior storage modulus values, reaching 152 MPa at 10 Hz, followed by the BJKKJBE hybrid, which achieved 137 MPa. Additionally, banana fiber-reinforced composites and neat epoxy recorded the highest loss modulus values (52 MPa and 51 MPa), indicating excellent energy dissipation. Neat epoxy and kenaf fiber reinforced composites displayed the highest tan delta values, with BJKKJBE hybrids also showing notable damping behavior, suggesting effective vibration attenuation. On the other hand, jute-based composites demonstrated the lowest tan delta, reflecting increased stiffness. A significant outcome is the thermal expansion behavior, where BJKKJBE composites exhibited the highest shrinkage (0.3%), while the KBJJBKE reinforcement, with kenaf as a skin layer, recorded the highest coefficient of thermal expansion (257 ppm °C−1). These findings present new opportunities for optimizing fiber-reinforced epoxy composites in applications requiring tailored thermal and thermo-mechanical performance, contributing to advancements in sustainable materials design for engineering applications.
Closed form expressions for CTEs of composite materials by the thermo-elastic micromechanics approach
Authors: M V Peereswara Rao , Harursampath Dineshkumar , M V V S Murthy 
Published: December 2024

Abstract
An analytical thermo-elastic micromechanics model is developed to estimate the homogenized Coefficients of Thermal Expansion (CTEs) properties of a composite material. This model is based on the Concentric Cylinder Model (CCM), using Variational Asymptotic Method (VAM). Closed form expressions for both axial and transverse CTEs of composite materials are derived, satisfying the displacement continuity and the transverse stress equilibria conditions at the interface between the reinforcement and the matrix material. The resulting expressions are functions of fiber material properties, matrix material properties and their volume fractions. The results obtained through these derived closed form expressions of CTEs are compared with those available in literature and the experimentally measured CTEs. Further, closed form expressions for the calculation of 3D displacement, strains and stresses of both the reinforcement and matrix are derived. The results obtained by the use of the developed expressions are validated with the results obtained through 3D Finite Element analysis of a composite beam like structure for a given temperature load.
Central vs. Brachial Blood Pressure and Pulse Pressure Amplification for Mortality Risk Prediction in Patients Undergoing Coronary Angiography
Authors: Daschner Clara , Kleber Marcus E , Ayasse Niklas , Stach Ksenija , Yücel Gökhan , Husain-Syed Faeq , Niessner Alexander , Krüger Bernd , März Winfried , Krämer Bernhard K , Yazdani Babak 
Published: December 2024

Abstract

BACKGROUND
Arterial hypertension is a significant risk factor for cardiovascular (CV) morbidity and mortality. Although central blood pressure (BP) evaluation is considered the gold standard, the reliability of non-invasive measurements remains unclear. Therefore, we compared the predictive value of invasively measured central BP with non-invasively measured brachial BP and analyzed pulse pressure (PP) amplification (delta-PP; the difference between central and peripheral PP) as an independent predictor of mortality.

METHODS
We analyzed systolic BP (SBP), diastolic BP (DBP), mean arterial BP (MAP), PP, and delta-PP as predictors of CV and all-cause mortality in the Ludwigshafen Risk and Cardiovascular Health (LURIC) study, involving 3,316 patients referred for coronary angiography.

RESULTS
All brachial BP parameters, except DBP, were significantly linked to all-cause and CV mortality in a univariate analysis. A 10 mm Hg increase in SBP, MAP, and PP corresponded to increased risks of all-cause (11%, 10%, and 19%) and CV mortality (11%, 11%, and 18%). Central SBP and PP showed similar, but numerically weaker, associations with increased risks of all-cause (5% and 10%) and CV mortality (4% and 8%). After adjusting for age, sex, body mass index, diabetes mellitus, and eGFR, only delta-PP independently predicted mortality with a 10 mm Hg increase linked to a 4% reduction in all causes and a 6% reduction in CV mortality.

CONCLUSIONS
Neither brachial nor centrally measured BP parameters were independent mortality predictors in contrast to PP amplification, which remained an independent predictor of mortality in multivariate analysis, in a cohort with a medium to high CV risk profile. As PP amplification decreased, mortality increased.
Evaluation of the validity of a perfluorooctane sulfonic acid exposure reconstruction using a measured serum concentration among workers with a wide range of exposure
Authors: Campbell Jerry L , Linakis Matthew W , Porter Anna K , Rosen Emma M , Logan Perry W , Kleinschmidt Sarah E , Andres Kara L , Chang Sue , Taiwo Oyebode A , Olsen Geary W , Clewell Harvey J , Longnecker Matthew P 
Published: December 2024

Abstract

Background
Studies among workers with a wide range of exposure to perfluoroalkyl substances inform risk assessments. Perfluorooctane sulfonate (PFOS), a ubiquitous environmental contaminant, was recently examined in relation to mortality and cancer incidence in an occupationally exposed population by Alexander et al. in 2024. In that study, cumulative occupational exposure (mg/m3 PFOS-equivalents in air) was reconstructed using a job-exposure matrix and individual work history. While the exposure reconstruction had good face validity, an assessment of its performance in relation to serum PFOS levels would allow improved interpretation of the occupational epidemiology findings.

Objective
The objective of this study was to assess the validity of the exposure reconstruction used by Alexander et al. (2024).

Methods
A previous study by Olsen et al. (2003) measured serum PFOS levels in 1998 for 260 workers and because these workers were included in the epidemiologic study by Alexander et al. (2024), the study reported herein compared serum PFOS levels to those predicted using a simple compartmental pharmacokinetic model.

Results
The Pearson correlation coefficient between the observed and pharmacokinetic model-predicted serum PFOS concentration was 0.80 (95% confidence interval, 0.75 to 0.84). The median ratio of predicted to observed serum concentrations was 12 (i.e. actual exposure was significantly less than predicted). The predicted serum PFOS concentrations were not sensitive to the parameters used in the pharmacokinetic model other than exposure concentration or absorption.

Conclusions
The model did not predict absolute exposure well, probably because of personal protective equipment use not being accounted for and absorption of PFOS or precursors being lower than modeled. On the other hand, the model did a reasonably good job of ranking the workers’ exposure, thus classification of workers according to relative amount of cumulative PFOS-equivalents was reasonably accurate in the study by Alexander et al. (2024) when validated using the measured serum PFOS data.
Acute kidney injury with hypernatremia and major adverse kidney events
Authors: Zaragoza Jose J , Gómez-Fregoso Juan A , Hernández-Barajas Eduardo M , Andrade-Jorge Zarahi , de Leon Juarez Correa- , Granado Rolando Claure-Del , Padilla-Armas Jorge L , Ornelas-Ruvalcaba R Lizzete , Cabrera-Aguilar J Said , Chávez-Alonso Gael , Villalvazo-Maciel Estefania , Orozco-Chan Carlos E , Cárdenas-Mercado Carlos B , Rodríguez-García Gonzalo , Navarro-Blackaller Guillermo , Medina-González Ramón , Gallardo-González Alejandro Martínez , Alcantar-Vallin Luz , Abundis-Mora Gabriela J , García-García Guillermo , Chávez-Iñiguez Jonathan S 
Published: December 2024

ABSTRACT

Introduction
Consequences of hypernatremia in akute kidney injury (AKI-hyperNa) is poorly understood. We analyzed the risk of major adverse kidney events (MAKE) in comparison with AKI and normal serum sodium (AKI-normalNa). Such data could help in understanding this complex interaction.

Methods
In this retrospective cohort we compared the AKI-hyperNa with the AKI-normalNa regarding the risk of MAKE, which include death, new dialysis requirement, and worsening kidney function (≥25% decrease in estimated glomerular filtration rate), at 10 (MAKE10) and at 30–90 days (MAKE30–90) using multivariate logistic regression and area under the curve (AUC) analysis. The association between serum sodium levels (per 1 mEq/l increase) and the number of days with hypernatremia was also compared.

Results
A total of 357 patients were included (78 with AKI-hyperNa and 279 with AKI-normalNa). Compared to the AKI-normalNa, AKI-hyperNa were predominantly male (73% versus 59%), experienced hypernatremia for a longer duration (3 days versus 0 days), and took 5 days to normalize serum sodium levels. After multivariate regression analysis, the AKI-hyperNa group had higher risk of MAKE10 [odds ratio (OR) 5.7, confidence interval (CI) 2.5 to 12.89, p &lt; 0.001] with an AUC of 0.79. Also its components such as mortality and decreased estimated glomerular filtration rate (OR 2.13, CI 1.11 to 4.07, p = 0.021 and OR 20.14, CI 7.69 to 10.03, p = 0.001, respectively). A similar trend was found for MAKE30–90 (OR 4.17, CI 1.73 to 10.03, p ≤ 0.001). A gradual increase in serum sodium was associated with a higher risk of MAKE (OR 1.07, CI 1.04 to 1.11, p ≤ 0.001), as was the number of days spend with hypernatremia (OR 1.51, CI 1.22 to 1.87, p = 0.001).

Conclusions
In this cohort, AKI-hyperNa compared with AKI-normalNa had a fivefold risk of short- and long-term MAKE. This event was more frequently observed as serum sodium increased and it was closely related to the number of days that hypernatremia persisted.