bluuebunny/crossref_metadata_2025 huggingface dataset:
Interstage feeding and caregiver impact on single ventricle patients
Authors: Momin Nashifa H. , Nelson Jennifer L. , Steiden Camille , Coolidge Nicole , Aljiffry Alaa , Simione Meg
Published: February 2025

Background:

The interstage period is a critical phase for single ventricle infants due to their fragile cardiovascular state. Infants often experience medical and feeding challenges during this period, resulting in caregiver stress. We completed a quality improvement project at Children’s Healthcare of Atlanta to understand these challenges to inform targeted interventions.

Methods:

This single-center project included a medical chart review and a cross-sectional caregiver survey. Data were collected on patient and caregiver demographics and clinical variables. Feeding outcomes were assessed using the Pediatric Functional Oral Intake Scale. Caregiver impact was measured using the Feeding/Swallowing Impact Survey.

Results:

The project included 15 single ventricle patients with a mean (standard deviation) age of 151.73(25.92) days at the time of the second-stage palliation. Forty percent of patients experienced at least one readmission, primarily due to feeding intolerance (20%) and desaturations (26.7%). Milk protein allergy (26.9%) was the most common medical complication, followed by interstage unplanned reinterventions. Pediatric Functional Oral Intake Scale scores demonstrated that 33% consumed minimal volumes or no oral intake at the time of the bidirectional Glenn, and 93.3% of patients did not receive outpatient feeding services during the interstage. Caregiver stress scores resulted in mean scores (standard deviation) of 2.23(1.54), with the highest impact on daily activities. All caregivers affirmed the need for a dedicated multidisciplinary clinic.

Conclusion:

The interstage period for single ventricle patients poses significant medical and feeding challenges, resulting in caregiver stress. Comprehensive, multidisciplinary feeding support during the interstage period may improve patient outcomes and alleviate caregiver burden.
Risk and Realism: Using a Board Game Mobile App to Illustrate an International Relations Theory
Authors: Hendrickson Petra
Published: February 2025

When introducing students to broad theoretical frameworks, simulations and games can help to make theoretical concepts clearer. One example is the use of the mobile app for the board game Risk to illustrate many of the concepts associated with realism. The mobile app has advantages over the physical board game in that the length of the games often is much shorter and allows students to experiment with the number of opponents to determine how that changes the dynamics of the game. Survey results from students in an introduction to international relations course who played Risk in proximity to lessons on realism report that playing iterations of the game clarified realist topics including the balance of power, the security dilemma, and the temporary nature of alliances.
Post-COVID, Digital Societies: Opportunities and Policy Challenges for Human Security in the United Kingdom and South Korea
Authors: Hong Minjun , Lariviere Matthew , Ko Kilkon
Published: February 2025

The article investigates the role and challenges of digital technology adoption during the COVID-19 pandemic through a critical human security lens and comparative analysis between South Korea and the United Kingdom. The pandemic served as motivation for the adoption of digital technology among vulnerable groups, either forcing or encouraging the necessity and utilisation of these technologies. This contributes to enhancing human security, but the persistent exclusion of certain individuals indicates the need for additional attention and policies. The case of both countries highlights the disparities in technology use due to factors like digital literacy and information security concerns, emphasising that rapid technological adoption by governments does not guarantee an effective pandemic response. The study also examines the dual role of digital technologies in enhancing and compromising human security, illustrating the importance of a balanced approach to digitalisation that includes policy support for vulnerable groups and public endorsement of new technologies.
Cultural Influences on Transgender Rights: Examining the Role of Religion
Authors: Williamson Myles
Published: February 2025

Transgender rights are receiving increasingly greater attention in policymaking arenas around the globe. However, few studies empirically investigate the factors that shape the protection of these types of legal rights from a global perspective. Therefore, this article aims to contribute to the literature by examining how one potential correlate – religion – influences countries’ recognition of transgender rights. More specifically, this article distinguishes between the presence of religion in state institutions versus the society, allowing for a more nuanced investigation of the different avenues through which religion may influence a country’s trans-specific laws. Analyzing data from 173 countries between 2000 and 2021, this study finds that while religious influence over society more consistently explains variation in transgender rights, religion in government also plays a significant role. Overall, the findings shed light on an often-understudied population and offer valuable insights into the areas where transgender individuals may be most vulnerable.
The YTHDC1 reader protein recognizes and regulates the lncRNA MEG3 following its METTL3-mediated m6A methylation: a novel mechanism early during radiation-induced liver injury
Authors: Song Gui-yuan , Yu Qing-hua , Xing Xue-kun , Fan Xin-ming , Xu Si-guang , Zhang Wen-bo , Wu Yao-yao , Zhang Nan , Chao Tian-zhu , Wang Fei , Ding Cheng-shi , Guo Cun-yang , Ma Li , Sun Chang-ye , Duan Shu-yan , Xu Ping
Published: February 2025

While apoptotic cell death is known to be central to the pathogenesis of radiation-induced liver injury (RILI), the mechanistic basis for this apoptotic activity remains poorly understood. N6-methyladenosine (m6A) modifications are the most common form of reversible methylation observed on lncRNAs in eukaryotic cells, with their presence leading to pronounced changes in the activity of a range of biological processes. The degree to which m6A modification plays a role in the induction of apoptotic cell death in response to ionizing radiation (IR) in the context of RILI remains to be established. Here, IR-induced apoptosis was found to significantly decrease the levels of m6A present, with a pronounced decrease in the expression of methyltransferase-like 3 (METTL3) at 2 d post radiation in vitro. From a mechanistic perspective, a methylated RNA immunoprecipitation assay found that lncRNA MEG3 was a major METTL3 target. The expression of MEG3 was upregulated via METTL3-mediated m6A in a process that was dependent on YTHDC1, ultimately reversing the miR-20b-mediated inhibition of BNIP2 expression. Together, these findings demonstrate that the responsivity of METTL3 activity to IR plays a role in IR-induced apoptotic cell death, leading to the reverse of miR-20b-mediated BNIP2 inhibition through the YTHDC1-dependent m6A modification of MEG3, suggesting that this process may play a central role in RILI incidence.
Regional autozygosity association with albumin-to-creatinine ratio reveals a novel FTO region in an Indigenous Australian population
Authors: Arunachalam Vignesh , Tran Kim N. , Hoy Wendy , Lea Rodney A. , Nagaraj Shivashankar H.
Published: February 2025

The genetic distinctiveness of Indigenous Australian populations is well established, yet the Tiwi population remains underrepresented in genetic research. Due to their prolonged geographic isolation, these populations are prone to increased runs of homozygosity (ROH). We investigated the genetic diversity of the Tiwi population, isolated from mainland Australia for decades, based on ROH and their associations with clinical traits. We analyzed 455 whole genome sequences to identify population structure via PCA and performed a comparison with UK Biobank, Melanesian, and Polynesian cohorts. ROH assessment and genome-wide and regional measures of homozygosity were used to explore associations between clinical traits and autozygosity. Our analysis revealed distinct genetic characteristics of the Tiwi population that aligned closely with those of the Melanesian cohort. Tiwi individuals exhibited an increased burden of ROH, particularly in LINC0109, FMLN1, and RPL17P45 genes on chromosomes 2, 17, and 18, respectively, indicating prolonged isolation and genetic drift. A positive correlation was observed between genomic F
ROH
and albumin-to-creatinine ratio (ACR) levels, suggesting a potential link between autozygosity and renal health markers. Furthermore, regional autozygosity association analysis revealed an association between elevated ACR and a region in FTO, implicating its role in obesity, kidney disease, and cardiovascular conditions. Importantly, we found that this association is strong under the recessive model. This research lays a robust foundation for further exploration of ROH mapping and its implications for disease susceptibility within Indigenous communities worldwide.
Astrocyte heterogeneity reveals region-specific astrogenesis in the white matter
Authors: Bocchi Riccardo , Thorwirth Manja , Simon-Ebert Tatiana , Koupourtidou Christina , Clavreul Solène , Kolf Keegan , Della Vecchia Patrizia , Bottes Sara , Jessberger Sebastian , Zhou Jiafeng , Wani Gulzar , Pilz Gregor-Alexander , Ninkovic Jovica , Buffo Annalisa , Sirko Swetlana , Götz Magdalena , Fischer-Sternjak Judith
Published: February 2025

Astrocyte heterogeneity has been well explored, but our understanding of white matter (WM) astrocytes and their distinctions from gray matter (GM) astrocytes remains limited. Here, we compared astrocytes from cortical GM and WM/corpus callosum (WM/CC) using single-cell RNA sequencing and spatial transcriptomics of the murine forebrain. The comparison revealed similarities but also significant differences between WM and GM astrocytes, including cytoskeletal and metabolic hallmarks specific to WM astrocytes with molecular properties also shared with human WM astrocytes. When we compared murine astrocytes from two different WM regions, the cortex and cerebellum, we found that they exhibited distinct, region-specific molecular properties, with the cerebellum lacking, for example, a specific cluster of WM astrocytes expressing progenitor and proliferation genes. Functional experiments confirmed astrocyte proliferation in the WM/CC, but not in the cerebellar WM, suggesting that the WM/CC may be a source of continued astrogenesis.
Correlation between gut microbiota dysbiosis, metabolic syndrome and breast cancer
Authors: Abdelqader Eslam M. , Mahmoud Walaa S. , Gebreel Hassan M. , Kamel Mahmoud M. , Abu-Elghait Mohammed
Published: February 2025

Breast cancer is a widespread cancer with a high death rate globally. The incidence of breast cancer is expected to increase, particularly in low and middle-income countries due to environmental factors and lifestyle changes. Several risk factors, such as age, family history, hormonal and reproductive factors, have been identified to influence breast cancer development. Metabolic syndrome, is a metabolic disorder that has also been linked to breast cancer risk. The gut microbiome has been suggested as one of the environmental factors leading to breast cancer. The human microbiome is mainly colonized in the intestine by various bacterial species, including Lactobacillus, Bifidobacterium, and Streptococcus and protect the host against pathogenic microorganisms and regulate the immune system. This study included 50 female breast cancer patients and 50 healthy controls with matched ages. Stool fresh samples were taken from test and control groups and stored at − 20 °C until further investigations. DNA of the bacteria in stool samples was extracted using reverse transcription-quantitative polymerase chain reaction to check for the bacterial 16s rRNA gene. The exclusion criteria included other malignancies, recent intestinal surgery, infectious diarrhea, prolonged use of antibiotics, substance addiction, and pregnancy or lactation. Our findings exhibited that breast cancer patients had a higher incidence of metabolic syndrome (60%) compared to cancer-free controls (40%). Furthermore, breast cancer patients had significantly lower Bifidobacterium and Lactobacillus counts than the controls. No significant difference was found in Streptococcus counts between groups. These findings support the relationship between breast cancer and metabolic syndrome and suggest the potential involvement of Lactobacillus and Bifidobacterium in breast cancer pathophysiology. Our study supports the relation between breast cancer and disorder of metabolic syndrome and suggests the potential involvement of Lactobacillus and Bifidobacterium in breast cancer pathophysiology. Further research is necessary to investigate the complex interactions between genes, the environment, and the gut microbiome in breast cancer development. Understanding these interactions could lead to the progress of novel strategies for breast cancer prevention and treatment.
Research on optimal control design of displaced left turn signal at one two way and three one way traffic intersections
Authors: Han Ning , Cheng Guozhu , Lin Jiadong , Tang Zhiyun , Xie Fei
Published: February 2025

As the nodes of urban road traffic network, intersections serve as an effective means to improve traffic flow efficiency and alleviate traffic congestion through the optimization of reasonable traffic organization and signal schemes for intersections. In recent years, domestic research on unconventional intersections has attracted increasing attention. This paper first summarized the types of single-double traffic intersections and preliminarily discussed the applicability of displaced left-turn (DLT) signal organization. We then constructed a calculation method for determining the important design parameters in the DLT signal traffic organization, based on the design of the channelization form of the intersection of Haihe Road and Xuanqing Street in Harbin City, China. Based on the average delay of vehicles, we established a signal optimization control model with two components: the main signal delay and the pre-signal delay, aiming to minimize the delay of vehicles. The signal optimization control model was established considering both the main signal delay and the pre-signal delay. Finally, the selected examples were compared and verified using VISSIM simulation. The simulation results show that through the design of one two-way and three one-way traffic intersections with DLT signals and signal optimization control, the average vehicle delay at the intersection is significantly reduced, and traffic efficiency is enhanced.
An assessment of machine learning methods to quantify blood lactate from neutrophils phagocytic activity
Authors: Tahir Muhammad Nabeel , Wagner Kurt , Hassan Umer
Published: February 2025

Phagocytosis is a critical component of innate immunity that helps the body defend itself against infection, foreign particles, and cellular debris. Investigating and quantifying phagocytosis can help understand how the immune system identifies foreign particles and how phagocytosis relates to other biomarkers, e.g., cytokines, cell surface receptors, or blood lactate levels. In particular, increased blood lactate levels can be a potential biomarker to study diseases, e.g., septic shock. Establishing a relationship between phagocytosis and lactate levels can serve as an effective tool to monitor the immune response and may help stratify patients. In this study, we use phagocytosis activity data to classify the patients into two groups of blood lactate levels (High and Low) with machine learning models. The neutrophils extracted from the whole blood samples of 19 patients were used to collect data on phagocytosis, where the neutrophils were allowed to internalize IgG coated fluorescent bioparticles. The data collection process involved collecting whole blood samples, neutrophil isolation, adding fluorescent beads, incubating, and imaging the sample using a fluorescence microscope. The phagocytosis assay images were used to generate a numerical dataset by manually counting the number of particles engulfed by each cell. The study first presents an improved understanding by employing hierarchical clustering and heatmaps to generate the graphical representation of phagocytosis data. By comparing the results of heat maps and clustering techniques, it can be observed that the phagocytosis activity data can be used to differentiate blood lactate levels in two groups (control and high-risk). Later, three machine learning models (Decision Tree, k-nearest Neighbor, and Naïve Bayes) were trained on the original and pruned datasets after the outliers were removed. The AI models classified the data into high-risk and low-risk groups of blood lactate levels. A maximum classification accuracy of 78% and an area under the curve of 0.78 was achieved using the trained models.
Super-resolution mapping of anisotropic tissue structure with diffusion MRI and deep learning
Authors: Ordinola Alfredo , Abramian David , Herberthson Magnus , Eklund Anders , Özarslan Evren
Published: February 2025

Diffusion magnetic resonance imaging (diffusion MRI) is widely employed to probe the diffusive motion of water molecules within the tissue. Numerous diseases and processes affecting the central nervous system can be detected and monitored via diffusion MRI thanks to its sensitivity to microstructural alterations in tissue. The latter has prompted interest in quantitative mapping of the microstructural parameters, such as the fiber orientation distribution function (fODF), which is instrumental for noninvasively mapping the underlying axonal fiber tracts in white matter through a procedure known as tractography. However, such applications demand repeated acquisitions of MRI volumes with varied experimental parameters demanding long acquisition times and/or limited spatial resolution. In this work, we present a deep-learning-based approach for increasing the spatial resolution of diffusion MRI data in the form of fODFs obtained through constrained spherical deconvolution. The proposed approach is evaluated on high quality data from the Human Connectome Project, and is shown to generate upsampled results with a greater correspondence to ground truth high-resolution data than can be achieved with ordinary spline interpolation methods. Furthermore, we employ a measure based on the earth mover’s distance to assess the accuracy of the upsampled fODFs. At low signal-to-noise ratios, our super-resolution method provides more accurate estimates of the fODF compared to data collected with 8 times smaller voxel volume.
Pertussis before, during and after Covid-19
Authors: Locht Camille
Published: February 2025

After the Covid-19 pandemic, pertussis has made a spectacular comeback in Europe and many other parts of the world, while during the pandemic it had essentially disappeared because of the social distancing requirements. However, even before the Covid-19 pandemic, the disease was on the rise in many countries, especially those that have replaced whole-cell pertussis vaccines by acellular pertussis vaccines. Several reasons may account for this upsurge, including strain adaptation to escape vaccine-induced immunity, rapid waning of immunity after vaccination and the failure of current vaccines to prevent infection by and transmission of the causative agent Bordetella pertussis. Various strategies have been deployed to control the disease, the most effective of which is maternal vaccination during pregnancy to protect the newborn against the most severe and deadly forms of the disease. However, ultimate control of pertussis likely requires novel vaccines, which prevent infection and transmission, not only disease. One of them is the live attenuated BPZE1 vaccine, which has shown promise in pre-clinical and clinical studies and may therefore perhaps become a gamechanger.
Enhanced in vitro transfection efficiency of mRNA-loaded polyplexes into natural killer cells through osmoregulation
Authors: Song Myeongkwan , Park Ha Yeon , Kim Hyun Jin , Kwon Soonjo
Published: February 2025

High expression of externally injected in vitro transcribed (IVT) mRNA in natural killer (NK) cells is a prerequisite for NK cell-mediated cell therapy. To enhance the transfection efficacy of IVT...
Effects of Cations on the Structure, Dynamics and Vibrational Sum Frequency Generation Spectroscopy of Liquid/Vapor Interfaces of Aqueous Solutions of Monovalent and Divalent Metal Nitrates
Authors: Chandra Abhilash , Saito Shinji , Chandra Amalendu
Published: February 2025

We have employed molecular dynamics (MD) simulations and theoretical vibrational sum frequency generation spectroscopy (VSFG) to investigate the structure and interactions of water and ions at liquid/vapor interfaces of aqueous...
The Effect of H2 Occupancy Modes in Small and Large Cages of H2-Tetrahydrofuran Hydrates on the Hydrates Stability and H2 Storage Capacity
Authors: Zheng Ruyi , Mohammed Sohaib , Jia Yang , HAZRA RITUPARNA , Gadikota Greeshma
Published: February 2025

Hydrogen storage as hydrates is considered as one of the most environmentally benign approaches to store hydrogen as it requires only water and traces of promoters. However, advancing scalable controls...
Automating stochastic antibody–drug conjugation: a self-driving lab approach for enhanced therapeutic development
Authors: Roberts Liam , Reish Matthew E. , Yang Jerrica , Zhang Wenyu , Derasp Joshua S. , Hein Jason E.
Published: February 2025

We introduce a Self-Driving Lab (SDL) for automated stochastic antibody-drug conjugation (ADC) and characterization. The robotic platform performs conjugations and determines drug to antibody ratios from chromatography data, enabling the production of target ADCs iteratively in a closed loop.
Boosting the reduction of CO2 and dimethylamine for C–N bonding to synthesize DMF via modulating the electronic structures of indium single atoms
Authors: Zheng Jingui , Xu Shaohan , Sun Lingzhi , Pan Xun , Xie Qihao , Zhao Guohua
Published: February 2025

The indium single atom of InN3 affects the electronic properties of adsorption of CO2 and HN(CH3)2. This resulted in hydrogen transfer from HN(CH3)2 to CO2, generating the intermediate species of *N(CH3)2 and *COOH that are conducive to C–N coupling.
Nanotechnology-enabled soil management for sustainable agriculture: interactions, challenges, and prospective
Authors: El-Sayed Mohamed , Ayoub Haytham  A. , Helal Mohamed , Sang Wenjing , Shen Zheng , Abdelhafeez Islam Abdelnaser
Published: February 2025

Nanotechnology has a pronounced perspective to improve the quality of life through its applications in numerous fields including the agricultural sector. Recently, many applications of nanotechnology in agriculture including crop...
Nanofiltration membrane from reactive positively charged nanofiber interlayer for recycling lithium from waste batteries
Authors: Cao Shuqing , Wang Jingjing , Cheng Qin , Wu Yi , Xu Jia , Xia Ming , Liu Ke , He Shanshan , Wang Dong
Published: February 2025

With the development of new energy powered vehicles, the shortage of lithium resources has become more urgent. The recovery and extraction of lithium resources from waste lithium iron phosphate batteries...
Tuning biological processes via co-solutes: from single proteins to protein condensates – the case of α-elastin condensation
Authors: König Benedikt , Pezzotti Simone , Schwaab Gerhard , Havenith Martina
Published: February 2025

Protein condensates as membrane-less compartments play a pivotal role in cellular processes. The stabilization of protein condensation can be tuned by cosolutes which directly impact biological function. In this study,...
Responsive hydrogel modulator with self-regulated polyphenol release for accelerating diabetic wound healing via precise immunoregulation
Authors: Tan Yunfei , Ma Lei , Wu Yixuan , Yi Zeng , Ma Xiaomin , Liu Jiaxin , Cao Ye , Li Xudong
Published: February 2025

Responsive hydrogels were capable of achieving the spatiotemporally controlled release of polyphenol that relieved severe oxidative stress and modulated macrophage polarization, thus accelerating diabetic wound healing.
Supramolecular and electrical properties of ruthenium-based organometallic gels
Authors: Eryilmaz Ilknur Hatice , Caytan Elsa , Gallonde William , GALANGAU Olivier , Jeannin Olivier , Camerel Franck , Rigaut Stéphane , Orgiu Emanuele
Published: February 2025

A novel organometallic gel whose molecular building block contains either one (Ru1) or two Ru (Ru2) atoms is presented and for the latter molecule, its supramolecular properties in solution investigated....
Correction: Numerical one-dimensional investigations on a multi-cylinder spark ignition engine using hydrogen/ethanol, hydrogen/methanol and gasoline in dual fuel mode
Authors: Qadiri Ufaith
Published: February 2025

Correction for ‘Numerical one-dimensional investigations on a multi-cylinder spark ignition engine using hydrogen/ethanol, hydrogen/methanol and gasoline in dual fuel mode’ by Ufaith Qadiri, Environ. Sci.: Atmos., 2024, 4, 233–242, https://doi.org/10.1039/D3EA00139C.
Improving Hydrogenation of 4-Nitrophenol using Pd catalysts homogenously anchored on WN-TiO2: A synergistic interaction between WN and Pd nanoparticles
Authors: Dong Yanping , Tian Xiqiang , Liu Enxin , Huang Shoulei , Zahid Muhammad
Published: February 2025

Incorporating a suitable promoter or co-catalyst is an effective strategy to improving the catalytic properties of low-content Pd catalysts. Herein, we report a straightforward method for synthesizing WN-TiO2, characterized by...
Tayler-Spruit dynamo in stably stratified rotating fluids: Application to proto-magnetars
Authors: Barrère P. , Guilet J. , Raynaud R. , Reboul-Salze A.
Published: February 2025

The formation of highly magnetized young neutron stars, called magnetars, is still a strongly debated topic. One promising scenario invokes the amplification of the magnetic field by the Tayler-Spruit dynamo in a proto-neutron star (PNS) that is spun up by fall-back. Our previous numerical study supports this scenario by demonstrating that this dynamo can generate magnetar-like magnetic fields in stably stratified Boussinesq models of a PNS interior. To further investigate the Tayler-Spruit dynamo, we performed 3D magnetohydrodynamic (MHD) numerical simulations with the MagIC code, varying the ratio between the Brunt-V "a is "a l "a frequency and the rotation rate. We first demonstrated that a self-sustained dynamo process can be maintained for a Brunt-V "a is "a l "a frequency about four times higher than the angular rotation frequency. The generated magnetic fields and angular momentum transport follow the scaling laws derived in prior analytical investigations, confirming our earlier results. We also report, for the first time, the existence of an intermittent Tayler-Spruit dynamo. For a typical PNS Brunt-V "a is "a l "a frequency of kHz the axisymmetric toroidal and dipolar magnetic fields range between SI 1.2e15 2e16 G and SI 1.4e13 3e15 G for rotation periods of $1- ms $. Moreover, the total magnetic field remains ≳ e14 G for periods of lesssim ms . Thus, our results suggest that our scenario is promising to form classical fast-rotating magnetars and magnetars with weaker magnetic dipoles for slower rotations. We offer a calibration of the analytical scaling laws based on our simulations, with a dimensionless normalisation factor of the order of SI e-2 . As the Tayler-Spruit dynamo is often invoked for the angular momentum transport in stellar radiative zones, our results are of particular significance to asteroseismology as well.
Time-adaptive PIROCK method with error control for multi-fluid and single-fluid magnetohydrodynamics systems
Authors: Wargnier Q.M. , Vilmart G. , Martinez-Sykora J. , Hansteen V.H. , De Pontieu B.
Published: February 2025

The solar atmosphere is a complex environment characterized by numerous species with varying ionization states, which are particularly evident in the chromosphere, where the significant variations in ionization degree occur. This region transitions from highly collisional to weakly collisional states that exhibit diverse plasma state transitions influenced by varying magnetic strengths and collisional properties. The complexity of processes in the solar atmosphere introduces substantial numerical stiffness in multi-fluid models, leading to severe timestep restrictions in standard time integration methods. To address the computational challenges, new numerical methods are essential. These methods must effectively manage the diverse timescales associated with multi-fluid and multi-physics models, including convection, dissipative effects, and reactions. The widely used time operator splitting technique provides a straightforward approach but necessitates careful timestep management to prevent stability issues and errors. Despite studies on splitting errors, their impact on solar and stellar astrophysics has largely been overlooked. We focus on a multi-fluid multi-species model, which poses significant challenges for time integration. We propose a second-order Partitioned Implicit-Explicit Orthogonal Runge-Kutta (PIROCK) method. This method combines efficient explicit stabilized and implicit integration techniques while employing variable time-stepping with error control. Compared to a standard third-order explicit time integration method and a first-order Lie splitting approach as considered recently, the PIROCK method demonstrates robust advantages in terms of accuracy, numerical stability, and computational efficiency. For the first time, our results reveal PIROCK's capability to effectively solve multi-fluid problems with unprecedented efficiency. Preliminary results on chemical fractionation, combined with this efficient method, represent a significant step toward understanding the well-known first-ionization-potential effect in the solar atmosphere.
Then and now: A new look at the eclipse timing variations of hierarchical triple star candidates in the primordial Kepler field, revisited by TESS
Authors: Borkovits T. , Rappaport S.A. , Mitnyan T. , Biro I.B. , Csanyi I. , Forgacs-Dajka E. , Forro A. , Hajdu T. , Seli B. , Sztakovics J. , Goblyos A. , Pal A.
Published: February 2025

A former analysis of eclipse timing variation (ETV) curves of eclipsing binaries (EBs) observed by the Kepler spacecraft during its ∼4-year-long prime mission has led to the discovery and characterization of 221 hierarchical triple star system with different confidence levels. Although the prime Kepler mission ended in 2013 (a little more than a decade ago), the TESS space telescope has revisited the original Kepler field on several occasions in between 2019 and 2024, thereby extending the time base of high-precision eclipse timing observations for a substantially longer interval. In this paper, we re-analyse the extended ETV curves of the formerly identified triple star candidates and many other Kepler EBs. Besides the confirmations of the former findings and/or the improvements of the triple systems' orbital properties, the extended time base allows us to identify several new, longer outer period triple systems, and it also makes a more detailed study of the dynamical perturbations in the tightest triple stars possible. We extend the ETV curves of the Kepler triples with those mid-eclipse times that can be deduced from the TESS observations and, moreover, from targeted ground-based follow-up observations for a number of the objects. In general, we used the same methods that were applied for the older studies, which are described in the literature. Due to the lower quality of the TESS observations, however, for the fainter systems we averaged light curves of the EBs for 5-20 consecutive cycles, and thereby calculated `normal' minima from these averaged light curves. In conclusion, we identified 243 hierarchical triple star candidates in the Kepler sample. This sample strongly overlaps our former, nine-year-old sample, confirming the older results, or providing new solutions for 193 systems of the 2016 sample. For the remaining 28 hierarchical triple candidates of that former study, we have been unable to find new solutions, either because of the disappearance of the eclipses due to orbital plane precession, or due to instrumental reasons. On the other hand, due to the extended time series, we have been able to identify 50 new, longer-period triple star candidates as well. We briefly discuss the main properties of each individual system and present statistical studies of the results.
A POD Modulation Technique Based Transformer less HERIC Topology for PV Grid Tied-Inverter
Authors: Nireekshana Namburi
Published: February 2025

Transformer-based inverters offer galvanic isolation, which improves safety by physically disconnecting the PV array from the grid. Simultaneously, transformers contribute to extra energy losses as a result of their intrinsic resistance and inductance, resulting in reduced overall system efficiency. Integrating a transformer within the inverter increases its size and weight, which adds complexity to the installation process and necessitates stronger mounting options. Transformers produce excess heat, which requires more advanced cooling methods and may decrease the lifespan of the inverter components owing to thermal strain. Transformers can restrict the inverter’s frequency response, which can impact its capacity to rapidly adjust to variations in load or grid circumstances. Hence, in order to circumvent these intricacies, this article introduces a transformer less full-bridge PV grid structure. The proposed technique is an advanced and efficient technology that con-verts DC voltage generated by photovoltaic (PV) solar panels into AC voltage that can be safely fed into the electrical grid. This inverter employs a HERIC topology. HERIC transformer-less full-bridge PV grid-tied inverters are an advanced and efficient option for converting solar power into electricity. They are very dependable and are ideal for cur-rent PV systems that focus on maximum energy production while reducing installation and operational expenses. This article presents the development of a HERIC transformer-less photovoltaic (PV) grid-tied inverter using insulated-gate bipolar transistor (IGBT) switches in MATLAB Simulink.
Design and Analysis of Floating Solar Panel with SUN Position Tracking
Authors: Guhan K. , Karunanithi K. , Saravanan S. , Ramesh S. , Adesh S. , Kumar Abhishek
Published: February 2025

With the diminishing availability of fossil fuels and the subsequent rise in their costs, alongside their significant contribution to environmental pollution and global warming, the focus has shifted towards renewable energy sources for sustainable power generation. Among these, solar photovoltaic (SPV) systems are emerging as a promising solution for future energy needs. The process of extracting or generating electricity by the use of solar energy in the solar PV system is very simple and the cost of maintenance is very low. The major drawback is the sufficient need of land to accommodate the solar panels and the associated costs are the main issues. I order to solve this problem, a floating solar PV system, a new age in solar electricity is proposed in this research. The solar PV panels can be installed on any form of water, such as a pond, river, lake, etc. The study also explores the use of adjustable solar panels that track the sun’s position to enhance system efficiency. Moreover, this floating system benefits aquatic ecosystems by reducing water evaporation and curbing algae growth, thereby improving water quality. The novelty of this research lies in the dual advantage of increased energy efficiency through sun-tracking panels and environmental sustainability by preserving aquatic ecosystems.
Optimizing Hybrid Supercapacitor-Battery Storage Systems for Efficient Power Management in Rail Systems Integrated with Renewable Energy Sources
Authors: Kumar P. Lokesh , Rajalakshmi B. , Jain Alok , K Smitha , Al-Rubaye Taqi , Bodha K.D.
Published: February 2025

The use of integrated photovoltaic power plants with railway traction circuits form a sustainable practice to meet energy requirements with minimal reliance on conventional power resources. The possibility of this integration is explored further in this paper with the energy storage and utilization using computational models. A lithium-ion battery pack with an average voltage of 115 V and an average Ah capacity of 11.5 Ah was used as the energy store to contain PV power plant energy generated by a 15% efficient photovoltaic surface. Use of train rotations of 400 seconds on the track along with the information on solar irradiation, energy was stored during high solar intensity. Two cases were examined: when the number of train cycles (nc) is equal to 5 and when nc equals 20. It showed that for Value of nc =5, the discharge power was at its highest as it provides for full utilization of the energy production during peak hours of the day. On the other hand, for nc = 20 there was a good control of excess power as the power requirement was met through purchases from distribution network. The cost of the total system was between $11,000 and $20,000. These results show the prospects for further development of integrated solar systems that can provide energy sustainability and operational efficiency in railway systems.
Smart Solar Energy System with IoT-Enabled Tracking
Authors: Neelima K. , Navya Y. , Aishwarya L. , Bhanutej J.N.
Published: February 2025

An Internet of Things-based approach to minimizing energy waste and optimizing solar power generation. PV-based energy systems must include energy monitoring for several compelling reasons, such as rising energy prices, expensive operating expenses, and growing demand. The creation of a real-time, Internet of Things-based solar monitoring system is presented in this study. An all-purpose microcontroller with integrated voltage and current sensors was used to gather the information. An IoT analysis platform determines the amount of electricity generated and displays the aggregate data. The real-time current, voltage, and power are measured using an ammeter, voltmeter, and wattmeter. The measurement error between IoT-based and real measurements is studied under different load conditions. For long-term storage, a small flash memory card has been utilized. Thing Speak is an Internet of Things-based analytics software for analysis and visuals. The performance evaluation shows the conformance between the real and IoT-based measurements based on error calculation. The designed system was validated under conditions of constant humidity and temperature. The model can be evaluated in the future for hybrid PV systems with varying humidity and Temperature conditions.
PO-InC-APSO: An Improved Hybrid MPPT Technique for Grid-Tied Partially Shaded Condition Photovoltaic Systems
Authors: N Shanker , Rao K. Srinivasa , E Srilakshmi
Published: February 2025

Partially shaded condition pose significant challenges for the effective operation of Maximum power point Tracking algorithm in the photovoltaic system.These challenges include the potential for the algorithms to become stuck at local maximum power points (LMPP), extended tracking durations, and power variations while attempting to achieve the global maximum power point (GMPP) for the boost converter. This article contributes to the field by introducing an enhanced APSO-based Hybrid MPPT techniques PO-InC-APSO specifically designed for PS scenarios. Initially, a comprehensive analysis of the traditional APSO-Hybrid MPPT technique is conducted to Boost converter to identify its limitations regarding stability and steady-state performance under PS conditions and subsequently, the necessary criteria for achieving a stable and steadystate response are established. Finally, A novel method, PO-InC-APSO, has been proposed for the implementation of a single-phase grid-connected Inverter and photovoltaic (PV) system operating under partial shading conditions. This approach aims to estimate and regulate the grid voltage and current parameters associated with various loads. It ensures that the values of these parameters, including real and reactive power, remain within permissible limits. Ultimately, the system maintains a unity power factor despite variations in load and the presence of partial shading in the PV systems. This comprehensive study has been conducted using MATLAB/Simulink software.
Integrating AI and Multi-objective Optimization for Enhanced Microgrid Energy Management Using Quadratic Programming
Authors: Agrawal Priyanka , Thethi H. Pal , Mohammad Q. , Gupta Navya , Asha V. , Reddy K. Jyothsna
Published: February 2025

Using the AI approaches and the quadratic programming driven multiobjective optimisation, this paper proposes a universal framework for smart microgrid energy management. It considers its operational preconditions such as the loads demand and the renewable power source availability in order to reduce the microgrid operational cost and emission. An artificial neural network constructed models the predicted loads requirement, one-hours wind power output and solar generation for 24 hours. The simulated machine learning possesses good generalisation capacity and an excellent learning structure. Managing batteries or auxiliary devices in order to maximise microgrid operating efficiency runs counter to the traditional optimisation laws. This study used fuzzy logic advisor network to schedule the battery. Both the fuzzy environment of the microgrid operation as a whole and the uncertainty among the predicted parameters are manageable in the suggested solution. In comparison with microgrid energy management methods acquired from the literature, namely opportunity recharging and inductive schematic alternating battery management, the experimental results yield significant operational cost and emission reduction.
Classification of Music Genres using Multimodal Deep Learning Technique
Authors: Naidu K Purushotam , Rao B. Janardhana , Revathi K. , Gayathri M. Geetha , Jayasri G. Surya
Published: February 2025

The demand for automated music organization and the ever-increasing volume of digital audio recordings has both contributed to a surge in interest in deep learning-based genre classification. The purpose of this research is to examine the feasibility of using CNNs and RNNs, two types of deep learning architectures, for the task of audio track genre classification. The proposed models aim to achieve high accuracy and robustness in genre classification tasks by leveraging features extracted from raw audio signals and spectrogram representations. A comprehensive dataset comprising diverse music genres is utilized for training and evaluation, with performance metrics such as accuracy, precision, and recall assessed to ensure reliability. The results demonstrate that deep learning approaches significantly outperform traditional methods, providing insights into the underlying characteristics of musical styles. Potentially useful in areas such as music discovery platforms, playlist creation, and recommendation services, this study adds to the body of knowledge on automated music classification systems.
IOT enabled pulsed electric field food preservation system for improved food safety and quality
Authors: Naveenkumar K. , Varalakshmi L.M. , Logasundari T. , Sathiyapoobalan S. , Poongothai C.
Published: February 2025

An IoT-enabled Pulsed Electric Field (PEF) food preservation system was developed to enhance food safety and quality. This system integrates a PEF chamber with IoT sensors to monitor and control critical parameters via a cloud-based platform for real-time analysis and remote monitoring. Various food samples were treated under different conditions, achieving a 3-log reduction in microbial load with minimal impact on nutritional and sensory qualities. Real-time monitoring ensured precise control of treatment parameters, delivering consistent results across food types. The IoT-PEF system demonstrated potential for improved preservation, extended shelf life, and preserved nutritional value, surpassing conventional methods. IoT integration enables efficient remote management in industrial settings, making this approach a promising innovation for safer, higher-quality food products.
A flexible privacy-preservation approach for IoT-driven smart Hospital employing diverse distribution methods
Authors: Irin Loretta G. , Settu Ashwini , Prameela M. , Naga Malleswara Rao D.S. , Kalaiyarasi M. , Saravanan S.
Published: February 2025

Internet-based connectivity is commonplace in the modern world. Among the many uses of the Internet of Things (IoT) aimed at improving the efficacy and efficiency of municipal management, smart Hospital figure prominently. Strong privacy protection measures are necessary since IoT devices in these smart Hospital frequently gather sensitive data. Enough privacy protection isn’t offered by the smart Hospital systems now in use. Differential Privacy-Preserving Smart Hospital (DP Smart Hospital) is a novel approach that we introduce to address this. DP Smart Hospital uses Laplace or exponential distributions in differential privacy strategies to protect sensitive data generated by IoT devices. After that, the altered data is delivered to a controller, which then sends it on to an Omada Software controller, the cloud, and finally another controller for more examination. Direct uploads of non-sensitive material to the cloud. Device privacy is difficult for adversaries to undermine in this dynamic privacy-preserving environment. Because the solution only adds 10–18% overhead to IoT devices, it is appropriate for devices that can handle this extra load.
Comparative Analysis of Average Current Mode Control and Sliding Mode Control of Bidirectional CUK Converter for BESS
Authors: Devi V Vimala , Gangikunta Manohar , Kumar Y. Anil
Published: February 2025

This paper presents a comparative study between Average Current Mode Control (ACMC) and Sliding Mode Control (SMC) in the context of a bidirectional Cuk converter powered by a solar PV input. Both control strategies are implemented to regulate the charging and discharging of a VRLA battery while ensuring stable current flow. ACMC is known for its simplicity and effectiveness in maintaining steady current, but it may struggle with system uncertainties and nonlinearities. In contrast, SMC offers robust control with finite-time convergence and insensitivity to nonlinearities, making it well-suited for managing the converter’s complex dynamics. However, SMC introduces the challenge of chattering, a high-frequency oscillation around the desired sliding surface, which can impact system performance. Through simulations and experimental validation, this study evaluates the performance of both control methods, highlighting the trade-offs between the simplicity and stability of ACMC and the robustness and complexity of SMC. The findings demonstrate the conditions under which each control strategy excels, providing insights into their respective advantages and limitations for bidirectional power converter applications.