bluuebunny/crossref_metadata_2025 huggingface dataset:
Convergent and Transdisciplinary Integration: On the Future of Integrated Modeling of Human‐Water Systems
Authors: Razavi Saman , Duffy Ashleigh , Eamen Leila , Jakeman Anthony J. , Jardine Timothy D. , Wheater Howard , Hunt Randall J. , Maier Holger R. , Abdelhamed Mohamed S. , Ghoreishi Mohammad , Gupta Hoshin , Döll Petra , Moallemi Enayat A. , Yassin Fuad , Strickert Graham , Nabavi Ehsan , Mai Juliane , Li Yanping , Thériault Julie M. , Wu Wenyan , Pomeroy John , Clark Martyn P. , Ferguson Grant , Gober Patricia , Cai Ximing , Reed Maureen G. , Saltelli Andrea , Elshorbagy Amin , Sedighkia Mahdi , Terry Julie , Lindenschmidt Karl‐Erich , Hannah David M. , Li Kailong , Asadzadeh Masoud , Harvey Natasha , Moradkhani Hamid , Grimm Volker
Published: February 2025

The notion of convergent and transdisciplinary integration, which is about braiding together different knowledge systems, is becoming the mantra of numerous initiatives aimed at tackling pressing water challenges. Yet, the transition from rhetoric to actual implementation is impeded by incongruence in semantics, methodologies, and discourse among disciplinary scientists and societal actors. Here, we embrace “integrated modeling”—both quantitatively and qualitatively—as a vital exploratory instrument to advance such integration, providing a means to navigate complexity and manage the uncertainty associated with understanding, diagnosing, predicting, and governing human‐water systems. From this standpoint, we confront disciplinary barriers by offering seven focused reviews and syntheses of existing and missing links across the frontiers distinguishing surface and groundwater hydrology, engineering, social sciences, economics, Indigenous and place‐based knowledge, and studies of other interconnected natural systems such as the atmosphere, cryosphere, and ecosphere. While there are, arguably, no bounds to the pursuit of inclusivity in representing the spectrum of natural and human processes around water resources, we advocate that integrated modeling can provide a focused approach to delineating the scope of integration, through the lens of three fundamental questions: (a) What is the modeling “purpose”? (b) What constitutes a sound “boundary judgment”? and (c) What are the “critical uncertainties” and their compounding effects? More broadly, we call for investigating what constitutes warranted “systems complexity,” as opposed to unjustified “computational complexity” when representing complex natural and human‐natural systems, with careful attention to interdependencies and feedbacks, scaling issues, nonlinear dynamics and thresholds, hysteresis, time lags, and legacy effects.
Infant sleep EEG features at 4 months as biomarkers of neurodevelopment at 18 months
Authors: Ventura Soraia , Mathieson Sean R. , O’Toole John M. , Livingstone Vicki , Murray Deirdre M. , Boylan Geraldine B.
Published: February 2025

Background

Sleep parameters evolve in parallel with neurodevelopment. Sleep participates in synaptic homeostasis and memory consolidation and infant sleep parameters correlate with later aspects of early childhood cognition.

Methods

Typically developing, term-born infants had a diurnal sleep-EEG at 4 months and Griffiths III developmental assessment at 18 months. EEG analysis included sleep macrostructure (i.e. durations of total sleep and sleep stages, and latencies to sleep and REM), sleep spindle features, and quantitative EEG features (qEEG): interhemispheric connectivity and spectral power. We assessed the correlations between these EEG features and Griffiths III quotients.

Results

Sleep recordings from 92 infants were analyzed. Sleep latency was positively associated with the Griffiths III Foundations of Learning subscale and N3 sleep duration was positively correlated with the Personal-Social-Emotional subscale. Sleep spindle synchrony was negatively associated with Eye and Hand Coordination, Personal-Social-Emotional, Gross Motor, and General Development quotients. Sleep spindle duration was negatively associated with the Personal-Social-Emotional and Gross Motor subscales. In some sleep states, delta 1 and 2 EEG spectral power and interhemispheric coherence measures were correlated with subscale quotients.

Conclusion

Certain sleep features in the EEG of 4-month-old infants are associated with neurodevelopment at 18 months and may be useful early biomarkers of neurodevelopment.

Impact

This study shows that the EEG during infant sleep may provide insights into later neurodevelopmental outcomes.

We have examined novel EEG sleep spindle features and shown that spindle duration and synchrony may help predict neurodevelopmental outcomes.

Sleep macrostructure elements such as latency to sleep, N3 duration, and qEEG features such as interhemispheric coherence and spectral power measures at 4 months may be useful for the assessment of future neurodevelopmental outcomes.

Due to exceptional neuroplasticity in infancy, EEG biomarkers of neurodevelopment may support early and targeted intervention to optimize outcomes.
Ketogenic diet suppresses colorectal cancer through the gut microbiome long chain fatty acid stearate
Authors: Tsenkova Mina , Brauer Madita , Pozdeev Vitaly Igorevich , Kasakin Marat , Busi Susheel Bhanu , Schmoetten Maryse , Cheung Dean , Meyers Marianne , Rodriguez Fabien , Gaigneaux Anthoula , Koncina Eric , Gilson Cedric , Schlicker Lisa , Herebian Diran , Schmitz Martine , de Nies Laura , Mayatepek Ertan , Haan Serge , de Beaufort Carine , Cramer Thorsten , Meiser Johannes , Linster Carole L. , Wilmes Paul , Letellier Elisabeth
Published: February 2025

Colorectal cancer (CRC) patients have been shown to possess an altered gut microbiome. Diet is a well-established modulator of the microbiome, and thus, dietary interventions might have a beneficial effect on CRC. An attenuating effect of the ketogenic diet (KD) on CRC cell growth has been previously observed, however the role of the gut microbiome in driving this effect remains unknown. Here, we describe a reduced colonic tumor burden upon KD consumption in a CRC mouse model with a humanized microbiome. Importantly, we demonstrate a causal relationship through microbiome transplantation into germ-free mice, whereby alterations in the gut microbiota were maintained in the absence of continued selective pressure from the KD. Specifically, we identify a shift toward bacterial species that produce stearic acid in ketogenic conditions, whereas consumers were depleted, resulting in elevated levels of free stearate in the gut lumen. This microbial product demonstrates tumor-suppressing properties by inducing apoptosis in cancer cells and decreasing colonic Th17 immune cell populations. Taken together, the beneficial effects of the KD are mediated through alterations in the gut microbiome, including, among others, increased stearic acid production, which in turn significantly reduces intestinal tumor growth.
Current induced electromechanical strain in thin antipolar Ag2Se semiconductor
Authors: Luo Hao , Liang Qi , Guo Anan , Yu Yimeng , Peng Haoyang , Gao Xiaoyi , Hu Yihao , Su Xianli , Uher Ctirad , Zheng Yu , Yang Dongwang , Wang Xiaolin , Zhang Qingjie , Tang Xinfeng , Liu Shi , Van Tendeloo Gustaaf , Zhang Shujun , Wu Jinsong
Published: February 2025

Electromechanical coupling permits energy conversion between electrical and elastic forms, with wide applications1,2. This conversion is usually observed in dielectric materials as piezoelectricity and electrostriction3–7. Electromechanical coupling response has also been observed in semiconductors8, however, the mechanism in semiconductors with a small bandgap remains contentious. Here we present a breakthrough discovery of a giant electromechanical strain triggered by the electric current in thin antipolar Ag2Se semiconductor. This phenomenon is made possible by the alteration of dipoles at a low current density (step I), followed by a phase transition under a moderate current density (step II), leading to a local strain of 6.7% measured by in-situ transmission electron microscopy. Our finding demonstrates that electric current has both thermal and athermal effect (e.g. alteration of dipoles and interaction of dipole vortices with the electric current). This strain allows for the concurrent control of electroelastic deformation and electric conductivity.
Disentangling the feedback loops driving spatial patterning in microbial communities
Authors: Henderson Alyssa , Del Panta Alessia , Schubert Olga T. , Mitri Sara , van Vliet Simon
Published: February 2025

The properties of multispecies biofilms are determined by how species are arranged in space. How these patterns emerge is a complex and largely unsolved problem. Here, we synthesize the known factors affecting pattern formation, identify the interdependencies and feedback loops coupling them, and discuss approaches to disentangle their effects. Finally, we propose an interdisciplinary research program that could create a predictive understanding of pattern formation in microbial communities.
A new approach for improving dynamic fault ride through capability of gridctied based wind turbines
Authors: Dayo Shoaib Ahmed , Memon Ahsanullah , Memon Zeeshan Anjum , Jumani Touqeer Ahmed , Abbas Ghulam , Othmen Salwa , Yousef Amr , Wijaya Andika Aji
Published: February 2025

The Doubly-Fed Induction Generator (DFIG) is preferred for wind turbines (WTs) due to their variable speed capability, reinforcing energy capture efficiency. Despite its advantages, researchers continually face challenges in managing the DFIG, including overshooting, rising time, and stability under fault conditions. The faults in WTs may stem from the grid or different operational disturbances. The crowbar protection mechanism is an efficient strategy to reduce fault impacts on DFIGs. However, the traditional hysteresis-based methods to detect faults and crowbar activation are prone to false triggering, and to address the challenges posed, this paper presents a novel control strategy that increases the low-voltage ride-through (LVRT) capability of the grid-connected DFIG systems by incorporating Fuzzy Logic Control (FLC) to enhance accuracy in fault detection and employs the Salp Swarm Optimization Algorithm (SSA) to refine controller parameters. The SSA algorithm shows a superior dynamic response and stabilizes the DFIG system efficiently. Besides, the SSA algorithm precisely calibrates the proportional-integral (PI) controller gains and DC-link capacitance values to achieve the optimal transient response between Distributed Generation (DG) integration and fluctuating loads. It is evident by the results that the power quality is improved, and the active power overshoot value is decreased from 10.12 × 106 to 3.78 × 106. Moreover, by implementing the SSA algorithm in which the overshoot value is also decreased from 15.01 × 106 to 6.10 × 106, the best results are achieved. The proposed method is validated by comparative analyses with recent studies that showcase its superiority in refining machine dynamics and decreasing overshoots and transients. Henceforth, the obtained results validate the proposed method’s ability to compete against other conventional methods.
An optimized fractional order virtual synchronous generator with superconducting magnetic energy storage unit for microgrid frequency regulation enhancement
Authors: Rajaguru V. , Iyswarya Annapoorani K.
Published: February 2025

The Virtual Synchronous Generator (VSG) provides inertia and damping virtually, which plays a crucial role in enhancing the frequency stability of the microgrid. However, the virtual inertia added in the VSG increases the order of the system, which increases the likelihood of output real power fluctuations in the transient state, which is potentially dangerous for system stability. Hence, this paper introduces a new approach for frequency regulation in an isolated microgrid using a Fractional Order Virtual Synchronous Generator (FOVSG) which involves more degrees of freedom, integrated with a Superconducting Magnetic Energy Storage (SMES) unit. The parameters of the FOVSG and Fractional Order Proportional Integral Derivative (FOPID) controllers are optimized by the African Vulture Optimization Algorithm (AVOA) using the Integral Time Absolute Error criterion. The suggested system is simulated using MATLAB for multiple scenarios, and the outcomes are compared with the frequency regulation model using the traditional VSG with SMES unit. The performance of the suggested controller is confirmed further by utilizing a classical proportional integral derivative controller. From the results, the proposed frequency regulation model using an FOVSG and SMES unit combination with FOPID controller has superior system dynamics than the system using a traditional VSG with SMES unit. Furthermore, the suggested system using a FOVSG with SMES unit enhances the frequency responsiveness by 83.61% and 73.38% in maximum overshoot and settling period, respectively.
Baited traps as flawed proxies for carcass colonization
Authors: Lutz Lena , Amendt Jens , Moreau Gaétan
Published: February 2025

In both fundamental and applied sciences, the use of surrogates to measure phenomena that are challenging to study directly is a common practice. However, this requires validating the appropriateness of the surrogates. This study examines if traps, used to measure flight activity of necrophagous flies, can serve as effective surrogates for predicting oviposition on whole carcasses, a topic still under debate in forensic science. We used three sets, a calibration and validation subsets comprising monitoring data of the flight activity of four necrophagous blow fly species, and a test set comprising the oviposition activity of these species on carcasses. Each set also included measurements of abiotic parameters. Using Random Forest for each species, we quantitatively and qualitatively modeled flight activity as a function of abiotic parameters and validated these models. However, when we examined the extent to which flight activity predicted oviposition on carcasses, the models performed poorly, only explaining a fraction of the variance. As the first study making use of small baited trap data to model oviposition on animal carcasses, this study presents mixed results that suggests that traps, despite their utility in addressing various forensic entomology questions, currently appear to be unreliable proxies for predicting carcass colonization.
Side dominance and eye patches obscuring half of the visual field do not affect walking kinematics
Authors: Négyesi János , Kovács Bálint , Petró Bálint , Salman Diane Nabil , Khandoker Ahsan , Katona Péter , Moussa Mostafa Mohamed , Hortobágyi Tibor , Rácz Kristóf , Pálya Zsófia , Grand László , Kiss Rita Mária , Nagatomi Ryoichi
Published: February 2025

Vision plays a fundamental role in the control of human locomotion, including walking gait. Given that side-dominance is associated with differences in motor control, the present study aimed to determine if patches obscuring half of the visual field affect left- and right-side dominant individuals’ gait kinematics and accompanying leg muscle activation differently. Healthy right- (n = 15, age = 28.2 ± 5.5 years) and left-side (n = 9, age = 27.9 ± 5.8 years) dominant participants performed 10 min of walking trials on a treadmill at a self-selected speed with 5 min of rest between three randomized trials, i.e., wearing clear glasses or glasses with left-or right half-field eye patching. In addition to a set of spatiotemporal and kinematic gait parameters, the average activity during the separated gait cycle phases, and the start and end of muscle activation in % of the gait cycle were calculated from five muscles in three muscle groups. Our results indicate that gait kinematics of left- and right-side dominant participants were similar both in their dominant and non-dominant legs, regardless of half-field eye patching condition. On the other hand, inter-group differences were found in selected kinematic variables. For instance, in addition to larger but less variable step width, our results suggest larger ankle and knee ROM in right- vs. left-sided participants. Furthermore, medial gastrocnemius and biceps femoris muscle activation showed selected differences at certain phases of the gait cycle between participants’ dominant and non-dominant legs. However, it was also unaffected by the half-field eye patching condition. Moreover, the endpoint of medial gastrocnemius activation was affected by side-dominance, i.e., its activation ended earlier in the non-dominant leg of right- as compared to left-side dominant participants. Our results suggest no major differences in walking gait kinematics and accompanying muscle activation between half-field eye patching conditions in healthy adults; nevertheless, side-dominance may affect biomechanical and neuromuscular control strategies during walking gait.
Nature’s Amazing Chemistry
Authors: Freemantle Michael
Published: February 2025

“We have just had a severe cold spell with sub-zero temperatures outside. Cold winds blew south from the Arctic circle for several days. Today, I decide to take a walk along the Roman Road path. Much to my delight I see that snowdrops are beginning to appear in the hedgerow that separates the path from the fields. I love these flowers. They herald the end of winter, the onset of spring, more daylight hours and warmer temperatures. The snowdrops have appeared about this time every year as far back as I can remember.”

Nature’s amazing chemistry has been producing all the raw materials essential for life on Earth for billions of years. The chemistry is, however, diverse and often complex and challenging. It has unfathomable depths that chemists and other scientists around the world are still attempting to probe and understand. Chapters in this book reflect Michael Freemantle’s fascination with nature’s chemistry not only of humans and other animals, but also of plants and minerals. You will discover:

Michael Freemantle is a science writer who has written numerous books and articles on chemistry, the history of science and related topics. They include The Chemists’ War: 1914–1918 published by the Royal Society of Chemistry.
3D-printed electrodes for electrochemical detection of environmental analytes
Authors: Pan Liangliang , Zhou Shijing , Yang Jiaying , Fei Tongyun , Mao Shuduan , Fu Li , Lin Cheng-Te
Published: February 2025

This review explores state-of-the-art 3D-printed electrochemical sensors for environmental monitoring, highlighting advanced materials, manufacturing approaches, and improved detection capabilities.
Ruthenium-catalyzed monodeuterium-methylenation of two indole units with vinylene carbonate as a novel methylene precursor
Authors: Nan Jiang , Xu Lulu , Cao Rui
Published: February 2025

A new example of deuteration, involving ruthenium-catalyzed monodeuterium-methylenation of indole units with vinylene carbonate, is described.
Borenium-catalysed para-selective borylation of alkylarenes
Authors: Tan Xinyue , Wang Huadong
Published: February 2025

A borenium-based catalyst system allows para-selective C–H borylation of arenes, showcasing its complementary selectivity compared to transition metals.
Gas-phase, conformer-specific infrared spectra of 3-chlorophenol and 3-fluorophenol
Authors: Duda Olga A. , Groenenboom Gerrit C. , Horke Daniel A. , Bakker Joost M.
Published: February 2025

Conformer-specific IR spectra of the anti and syn conformers of halogenated phenol derivatives clearly show several bands with isomer-specific frequencies, despite the only structural difference between the conformers being the OH group orientation.
Inorganic nanoparticle-based nanogels and their biomedical applications
Authors: Sonkar Chanchal , Ranjan Rishi , Mukhopadhyay Suman
Published: February 2025

This review covers the design, synthesis, and biomedical applications of gold, silver, and iron nanoparticle-based nanogels. It highlights their multifunctional role in therapy and diagnostics while exploring challenges and future prospects.
Improved stability and electronic homogeneity in perovskite solar cells via a nanoengineered buried oxide interlayer
Authors: Perera W. Hashini K. , Woodgate Tony J. , Kim Dong Kuk , Kilbride Rachel C. , Masteghin Mateus G. , Smith Christopher T. G. , Hinder Steven J. , Wood Sebastian , Jayawardena K. D. G. Imalka , Silva S. Ravi P.
Published: February 2025

Alumina nanoparticles enhance perovskite surface electronic homogeneity, bulk electrical conduction, and device stability when used as a surface modifier on hydrophobic self-assembled monolayers, outperforming widely used polyelectrolytes.
Solar-powered electrocoagulation for the removal of atrazine with and without microplastics
Authors: Biswas Bishwatma , Joshy Anju , Goel Sudha
Published: February 2025

Emerging contaminants, particularly pesticides and microplastics, pose a substantial risk to both human beings and ecosystems. In order to provide clean freshwater sources and preserve aquatic ecosystems, their removal from water matrices is crucial.
Defect modulation of MIL-53(Fe) by Ce doping for PMS activation on the degradation of tetracycline: Singlet oxygen and electron transfer
Authors: Tang Liwen , Huang Yuxin , Lin Jialiang , Li Xiaoman , Cheng Jianhua
Published: February 2025

Removal of organic pollutants through the activation of peroxymonosulfate (PMS) using metal-organic frameworks (MOFs) has exhibited great potential in wastewater treatment. In this study, a one-step solvothermal method was employed...
Spectral and dynamical properties of multiexcitons in semiconductor nanorods
Authors: Kumar Krishan , Wächtler Maria
Published: February 2025

Applying an MCMC sampling approach for global target analysis enables us to determine the contributions of multiple exciton decay via Auger recombination and the contribution of surface exciton states to the observed decay dynamics.
Strategies to Overcome Antibiotic Resistance: Silver Nanoparticles and Vancomycin in Pathogen Eradication
Authors: Khairnar Sakshi , Das Ashish , Oupicky David , Sadykov Marat R , Romanova Svetlana
Published: February 2025

The increasing prevalence of antibiotic resistance presents a significant challenge to public health, undermining the efficacy of conventional antibiotic treatments. Given the scarcity of new antibiotics and efficient preventive strategies,...
Coordination modulation of single-atom Zn sites to boost oxygen reduction performance
Authors: Zhang Siying , Bai Xue , Tang Tianmi , Ruan Weidong , Guan Jingqi
Published: February 2025

A single-atom Zn-NG catalyst with Zn–N4 sites obtained by a rapid heating method exhibits excellent 4e− ORR performance, where the rate-determining step is *OH → * + H2O.
Sensitive determination of valganciclovir via Ni–Co multilayer nanowire-modified carbon paste electrode
Authors: Malekzadeh Maedeh , Rafati Amir Abbas , Bagheri Ahmad
Published: February 2025

This study presents the development of an electrochemical sensor based on a carbon paste electrode modified with nickel–cobalt multilayer nanowires (Co–Ni(MLNW)/CPE) for the detection of valganciclovir, an antiviral drug.
Development of a rapid sensor system for nitrate detection in water using enhanced Raman spectroscopy
Authors: Xia Xintao , Yang Guiyan , Tian Hongwu , Cao Fengjing , Luo Fan , Dong Daming
Published: February 2025

A portable Raman spectrometer combined with enhanced attachment enables sensitive, rapid on-site nitrate detection in water, offering a simple, low-cost solution for environmental water pollution screening.
Functional modification and antibacterial evaluation of orthodontic adhesives with poly (lysine)-derived carbon dots
Authors: Xu Linlin , Zhang Qianqian , Xu Yongzhi , Xu Xuecheng , Hu Mingchang , Xu Jidong , Song Yu , Hao Yuanping
Published: February 2025

PL-CDs are synthesized by one-pot pyrolysis of PL. The PL-CDs modified orthodontic adhesive has excellent antibacterial and color recognition properties.
Machine learning-driven discovery of highly selective antifungal peptides containing non-canonical β-amino acids
Authors: Chang Douglas H. , Richardson Joshua D. , Lee Myung-Ryul , Lynn David M. , Palecek Sean P. , Van Lehn Reid C.
Published: February 2025

We present an iterative workflow that integrates computational modeling with in vitro experiments to discover synthetic α/β-peptides with high selectivities against Candida albicans, a fungal pathogen associated with high mortality rates.
Efficiency boost in perovskite solar cells via TiO2 nanodiscs embedded in the MoSe2 electron transport layer revealed by optoelectronic simulations
Authors: Maleki Javad , Shahrostami Maryam , Huang Siming , Abdi-Jalebi Mojtaba
Published: February 2025

This work introduces a breakthrough metasurface-based design for inverted perovskite solar cells, where TiO2 nanodiscs embedded in a MoSe2 electron transport layer enhances light management and charge transport, boosting efficiency from 15% to 19%.
An FePb-doped RuO2 coupled amorphous/crystalline heterophase for efficient acidic oxygen evolution reaction
Authors: Zhao Yan , Long Yu , Liu Wenwen , Han Zhenyong , Cui Yuteng , Li Zhijun , Wang Wanglei , Duan Zhiyao , Fu Xiaogang
Published: February 2025

A Fe and Pb dual doped RuO2 catalyst with amorphous/crystalline heterostructures demonstrates excellent acidic OER performance and stale operation in PEMWE.
Restriction of silicon aggregation upon enhanced bond cleavage
Authors: Xue Shuyue , Li Peng , Yan Yingchun , Zhang Qinggang , Wang Zhen , Sun Zifei , Zhou Jin
Published: February 2025

With the N–Si inductive effect, silicon nanosheets uniformly embedded in a graphene-like carbon matrix as ultrastable lithium storage electrodes are developed.
Molecular conformational effects on the overall rate constant and the branching ratios of the n-heptane + OH reaction: an ab initio and variational transition state theory study
Authors: Belmekki M. , Monge-Palacios M. , Wang T. , Sarathy S. M.
Published: February 2025

Both the existence of multiple conformers and the deviation from the harmonic oscillator model need to be considered to calculate accurate site-specific rate constants for large and flexible systems such as n-heptane + OH.
Shaken not stirred: procedures in mechanochemical syntheses and how to define them
Authors: Batteas James , Friščić Tomislav
Published: February 2025

James Batteas and Tomislav Friščić outline the need for well-defined reporting methodologies in mechanochemistry.
Evaluating the Effects of Levodopa on the Vestibulo-Ocular Reflex in Parkinson's Disease: A Case Series
Authors: McCaslin Devin L. , Brown Taylor , Barr Jaimie , Roytman Stiven , Kerber Kevin , Bohnen Nicolaas I.
Published: February 2025

Purpose:

Parkinson's disease (PD) is a neurodegenerative disorder primarily affecting individuals over 60 years old. The disorder is characterized by motor symptoms due in large part to the loss of dopamine-producing neurons. The vestibular system, crucial for maintaining balance, may be impacted in PD, contributing to balance issues through dysfunction in the vestibulo-ocular reflex. In this study, we aim to describe differences in vestibular responses before and after use of levodopa (L-DOPA) in patients with PD.

Method:

The study evaluated nine PD patients who underwent videonystagmography, video head impulse testing, and rotational chair testing both on and off their dopaminergic medications. Effect sizes of the mean difference was measured using Cohen's
d
.

Results:

The results revealed a general trend of increase in vestibular responses from the off stage to the on stage across all the vestibular testing mechanisms. The
p
values were all > .05, and the Cohen's
d
95% confidence interval (CI) ranged from small to moderate effects with wide CIs consistent with the small sample.

Conclusions:

In this case series of nine patients with PD, we identified a general trend of a small increase in vestibular responses in the on state of L-DOPA compared with the off state of L-DOPA. The significance and clinical implications of such differences should be evaluated in larger samples.
X-Shooting ULLYSES: Massive stars at low metallicity. XI. Pipeline-determined physical properties of Magellanic Cloud OB stars
Authors: Bestenlehner J.M. , Crowther Paul A. , Hawcroft C. , Sana H. , Tramper F. , Vink J.S. , Brands S.A. , Sander A.A.C. ,   the XShootU collaboration
Published: February 2025

The proximity and low dust extinction of the Magellanic Clouds provides an ideal environment for metal-poor massive stars to be studied in detail. The Hubble Space Telescope ULLYSES initiative has provided exquisite ultraviolet spectroscopy of a large sample of OB stars in the Magellanic Clouds, and its legacy value has been enhanced through the acquisition of optical VLT/XShooter spectroscopy (XShootU). We aim to determine the spectral types and physical properties of 122 LMC and 103 SMC OB stars observed via XShootU. Physical parameters are required for these to serve as templates in spectral libraries of metal-poor massive stars. We also aim to identify double-lined binaries and OeBe stars for which analysis requires non-standard treatment. We have applied a pipeline designed to analyse large spectroscopic samples of hot luminous stars to XShootU spectroscopic datasets, together with grids of synthetic model spectra computed with the non-Local Thermodynamic Equilibrium atmospheric code fastwind at LMC and SMC metallicities. We have determined physical and wind properties of 97 LMC and 77 SMC massive stars, ranging from O2 to B9 subtypes, representing the majority of the XShootU OB sample (OeBe and candidate SB2 systems are excluded). Results are broadly in agreement with previous optical spectroscopic studies, with evolutionary masses spanning $12-117 M_ ⊙ $ in the LMC and $11-74 M_ ⊙ $ in the SMC. We have determined a revised T_ eff-spectral type calibration for Magellanic Cloud stars, identified stars with peculiar radial velocities, and compared wind properties of high luminosity O stars with dense winds, revealing ∼0.27 dex higher wind momenta of LMC stars with respect to SMC counterparts. Incorporating the recent empirical metallicity dependence of Z^0.22 for wind velocities, this suggests a mass-loss dependence of Z^0.5 for luminous O stars. Studies incorporating ultraviolet mass-loss diagnostics are required for OB stars with weak winds and/or low luminosities.
Assessing Skin Cancer Awareness: A Survey on Detection Methods
Authors: Vaishnavi Billa , Nithya Pasupuleti , Haseena Shaik , Sk Sajida Sultana
Published: February 2025

Skin cancer is considered one of the most aggressive cancer types and can be difficult to treat once it spreads to other parts of the body.Early diagnosis of this disease is very crucial, as once skin cancer has metastasized, it cannot be effectively treated. Automated systems for the recognition of skin lesions can thereby help in early diagnosis and thus improve the treatment outcome. The work proposed here concerns the image preprocessing techniques such as resizing and normalization followed by grayscale conversion and Canny edge detection of dermatology images for the preprocessing of data for the CNN classification model. Important features include asymmetry, border irregularity, diameter, color, and texture. The CNN looks for initial features such as edges and textures in the convolutional layers that are then max pooled to downsample and reduce computation. Finally, after several rounds of convolution and pooling, the feature maps are flattened and passed into the dense layers to learn high-level complex patterns. It helps prevent overfitting by generalizing a model to predict data which was never seen before.
Robust Vehicle Number Plate Text Recognition and Data Analysis Using Tesseract Ocr
Authors: Padmaja G. , Pesaru Swetha , Reddy Desidi Narsimha , Kumari D. Anitha , Maram Shiva Prasad
Published: February 2025

To detect the vehicle number plate the system should understand the character and integers determined on vehicles. The proposed methodology holds three phases: pre-process, extraction of features and recognition of text. These phases include some operations like grey scale, adaptive threshold, morphological for extraction of characters and numbers from different quality of the images in pre-processing stage. By transforming the images to grey scale, this can remove the extraneous colours and extracts the appropriate values. In morphological removes the borders and removes the background noises. Adaptive thresholding deals with color around the number plate which can increase the contrast. The outcome was transmitted to feature extraction which helps to identify single characters and numbers which may differentiate among many similar letters and numbers.Text recognition last uses OCR techniques to convert the acquired characteristics into readable alphabetic letters. These methods depend on advanced tools like the Tesseract OCR & OpenCV libraries. Tesseract’s OCR features make sure accurate character recognition, and OpenCV improves image processing and computer vision features.
Real-Time Fire Object Detection System Using Machine Learning
Authors: Akuthota Venkata Bhargavi. , Syed Khadar Basha. , Ramineni Dhanush. , Guduru Vikram.
Published: February 2025

The spread of forest fires presents one of the major concerning ecosystems, human security, and property. This paper introduces a fire object detection system that employs machine learning algorithms to enhance early detection of fire breakout and response to the same. The computer vision and deep learning algorithms allow the system to identify features related to fire objects and actions in images and video feeds. This set of scenarios under various fire conditions, environmental conditions, and backgrounds was curated for training a CNN. In terms of evaluating the model’s robustness in real applications across various settings, the metrics were defined by accuracy, precision, recall, and F1 scores. The proposed system is designed for alerting emergency responders within time so that quicker intervention may be made to possibly mitigate the devastating effects of wildfires. Future research will be the integration of the system into real-time surveillance systems and exploring added sensory data to increase the detection capabilities.
Real-Time Anomaly Detection in Solar Panel Arrays: Integrating Single Shot Multibox Detector (Ssd) With Iot and Edge Computing
Authors: Babu Y. Rajendra , Priyadarsini N. Indira , Sirisha P.G.K. , Reddy C. Ravishankar
Published: February 2025

Convolutional Neural Networks (CNNs) have revolutionized feature extraction for fault detection in solar panels by using hierarchical spatial extraction using convolutional layers These networks reveal important features such as cracks, hotspots, and internal cell anomalies while reducing redundancy. Using pre-trained algorithms such as ResNet and VGGNet enhances transfer learning and accelerates convergence, strengthens model accuracy error detection Noise filtering techniques including a Gaussian filter, mean filtering, and a Fast Fourier transform (FFT) for error detection. Eliminating image noise when storing information which is important for real-time fault detection, the Single Shot Multibox Detector (SSD) efficiently predicts bounding box-class probabilities with its multi-scale feature detection and anchor box mechanism. This simultaneous detection of faults in large solar panel arrays is possible. IoT sensors support these processes by providing real-time assessment of system integrity and environmental conditions, supported by edge computation for minimal latency fault by adaptive unsupervised learning approaches by separation forest algorithms integrated for anomaly detection. The knowledge is further enhanced by integrating these techniques. A comprehensive framework is provided for solar panel analysis, fault detection, and better performancepage margins and justified.
Pioneering Numerical Techniques for Solving Differential Equations - A Comprehensive overview
Authors: Ch Swapna , Balarama Krishna C. , Kiran Kumar T.
Published: February 2025

The field of numerical analysis studies the application of mathematics to solve problems of practical importance. When solving differential equations derived from real-world scenarios, numerical techniques play a crucial role, particularly when a closed-form solution is unavailable or obtaining an exact/accurate solution is challenging. This paper’s main goal is to look into specific numerical techniques for solving ODEs that have initial conditions. With a primary focus on the Adomian Decomposition, Differential Transform, and Multistep approaches, this study investigates a variety of numerical strategies for solving differential equations. Several mathematicians discovered after a thorough examination of their work that these methods have greatly advanced the analysis of differential equations and are widely used in the fundamental sciences, engineering and economics. The study also emphasizes how essential it is to carry out advanced research in this field so as to create numerical approaches for solving differential equations that are more precise and effective. Research has also carried out on the creation of general-purpose numerical techniques and algorithms for solving the problems, with main focus on stability and convergence in multistep approaches. The two-dimensional nonlinear wave equation is solved using the Adomian Decomposition method, and a unique multistep approach is suggested for handling nonlinear differential equations. The results produced by various techniques are contrasted.
Understanding Portosystemic Collateral Anatomy
Authors: McBride Aaron , Wallace Alex , Patel Indravadan , Ozen Merve
Published: February 2025

Portosystemic collateral pathways are a significant concern in interventional radiology, frequently manifesting in patients with cirrhosis or portal vein thrombosis. These pathways can lead to severe clinical complications, including gastrointestinal bleeding, hepatic encephalopathy, and liver failure. A thorough understanding of the anatomy, hemodynamic alterations, and clinical implications of these shunts is crucial for interventional radiologists to provide effective treatment while minimizing risks. This article reviews the clinical presentations associated with portosystemic shunts, explores the anatomical variants and altered flow dynamics, and discusses the latest endovascular treatment strategies to optimize patient outcomes.
Beyond the Surface: Sister Mary Joseph's Nodule in Metastatic Gallbladder Cancer: A Case Report and Review of Literature
Authors: Khadela Avinash , Soni Shruti , Shah Vraj B. , Kothari Rushabh
Published: February 2025

Sister Mary Joseph's nodule (SMJN) is an umbilical nodule occurring because of metastasis of the abdomen and pelvic malignancies. It is a rare physical finding, reported in nearly 3% of patients with gastrointestinal or gynecological cancers. The majority of cases presents at a very advanced stage of the disease, and often results in dismal prognosis. Here, we report the case of a 54-year-old woman with metastatic gallbladder cancer, presenting with SMJN. The patient declined chemotherapeutic intervention following the cancer diagnosis and later arrived with an umbilical nodule, which was identified as SMJN. The patient was advised to take a gemcitabine-cisplatin regimen, but opted solely for palliative care and passed away within a few weeks of SMJN diagnosis. This case report emphasizes how an untreated malignancy can advance quickly and present as an unusual clinical sign. Drawing the attention of health care professionals to this clinical sign will eventually help in the early detection of disease progression and its management to improve survival outcomes.
Alternating magnetic fields enhanced non-magnetic confined-ruthenium nanoparticles for efficient oxygen evolution reaction
Authors: Huang Fujin , Jiang Zhenzhen , Luo Xingfang , Hu Jiayong , Zou Chengwu , Zhou Hang , Hu Ce , Zhou Wenda , Lei Wen , Yuan Cailei
Published: February 2025

Magnetic heating by alternating magnetic field (AMF) is a fascinating solution to break the bottleneck in oxygen evolution reaction (OER) catalyst improvement. However, practical applications of AMF in electrochemistry are always impeded by the inherent characteristics of the catalyst (i.e., non-magnetic nature and oxidizable feature). Here, a self-heating working electrode substrate of C/Fe3O4/C is proposed to be fabricated, on which non-magnetic Ru nanoparticles confined within the amorphous carbon matrix are deposited as the catalytic layer. Under AMF, magnetic Fe3O4 particle can be stimulated and generate the magnetic heating associated with Néel relaxation, which improves the OER efficiency of Ru nanoparticles with the overpotential at 10 mA cm−2 reduced by 72 mV. Together with the high stability rendered by confined structure, the exploitation of AMF on non-magnetic catalyst is confirmed, and the developed strategy offers a general pathway to advance OER catalyst performance in the future.
Effects of turbulence intermittency on wind turbine loads under different atmospheric stability conditions: A multi-time scale analysis
Authors: Wang Ya , Li Fengbin , Cao Feng , Jiang Yao , Chai Yongfen , Wang Yan
Published: February 2025

The intermittent characteristics of turbulent motions can increase fatigue damage and reduce the reliability of wind turbines. However, the impact of intermittent turbulence on the aerodynamic loads of wind turbines under different atmospheric stability conditions has not been fully evaluated. In this study, wind velocity data collected from the Qingtu Lake Observation Array were employed to address this gap. The results indicate that turbulence intermittency in small time scales is strongest under convective boundary layer (CBL) conditions. Under different atmospheric stability conditions, the intermittency of turbulence tends to be consistent with time scales exceeding 48 s. The load intermittency of wind turbines is closely related to atmospheric stability and turbulence time scales. Specifically, intermittent turbulence under CBL conditions leads to the most significant load intermittency at shorter time scales, while its influence gradually weakens on longer time scales. The intermittency of wind turbine thrust is most pronounced when the turbulence time scale is comparable to the blade length. Similarly, the intermittency of the flapwise moment is most significant when the turbulence time scale matches the natural frequency (ft = 1.01 Hz). In contrast, the edgewise moment is less affected by atmospheric stability and turbulence time scales. This study provides new insights into the characteristics of turbulence intermittency under different atmospheric stability conditions and its impact on wind turbine aerodynamic loads, offering a scientific basis for the design and operational optimization of wind turbines.
Impact, analysis, and mitigation of flow instabilities in draft tube of Francis turbines
Authors: Khullar Subodh , Singh Krishna M. , Cervantes Michel J. , Gandhi Bhupendra K.
Published: February 2025

Hydropower is a clean, renewable, and highly efficient energy source and accounts for about 16% of global electricity production. Apart from baseload generation, hydraulic turbines are more and more often subjected to less efficient off-design operating conditions to handle the fluctuating electricity demands and stabilize the power grid. These sub-optimal operations result in flow instabilities such as vortex breakdown and inter-blade vortices, which reduce the overall hydraulic efficiency and produce severe pressure pulsations. This review summarizes various forms of flow instabilities and the theories developed to explain the phenomena. The impact of these instabilities on the turbine operation is discussed. Mathematical models developed to describe the swirling flows downstream of a Francis runner are also presented. Parameters that influence the characteristics of the flow instabilities are outlined. The review concludes with a discussion of various methods developed to alleviate the adverse effects of swirling flows on Francis turbines.
A flexible phototransistor with simultaneous high mobility and detectivity
Authors: Xiao Peng , Lin Jianrong , Zhou Yubu , Tan Haixing , Zhang Haojun , Liu Ziqing , Liu Si , Wu Runfeng , Nie Guozheng , Ng Kar Wei , Chen Jianwen , Zhang Yiping , Liu Baiquan
Published: February 2025

Phototransistors have great application prospects in automotive vehicle, smart home, healthcare, imaging, and display. However, so far, there has been no report of flexible phototransistors that simultaneously achieve both high mobility and detectivity. Additionally, phototransistors are conventionally relied on thick channel layers and previous thin channel layers based devices only show poor performance. Here, we report flexible phototransistors based on ultrathin niobium-doped indium oxide (InNbO, 5 nm)/indium tin oxide (ITO, 3 nm) channel layers, which possess high mobility (49.21 cm2 V−1 s−1) and high detectivity (3.02 × 1014 Jones) simultaneously. Significantly, the devices offer a broad spectral responsivity (from violet to green emissions). We postulate that the high mobility can be ascribed to the diffusion of Sn atoms (from ITO) and conduction band offset (between InNbO and ITO), while the high detectivity originates from the low dark current. To illustrate the capabilities of flexible phototransistors, we demonstrate both a flexible active-matrix organic light-emitting diode display pixel circuit and an imaging system. Our approach unlocks new possibilities to achieve flexible phototransistors with superior performance, which suggest a great potential in next-generation flexible, stretchable, bendable, and low-cost electronics.
Gas-assisted extrusion of viscoelastic polymer flow in direct ink writing additive manufacturing
Authors: Dai Yuande , Miao Zelin , Zhang Haifeng , Duan Lian , Yuan Wenjun , Zhang Ying , Ye Fanghua
Published: February 2025

In this work, direct numerical simulations are carried out to study the gas-assisted extrusion of viscoelastic polymer flow in direct ink writing (DIW) additive manufacturing. The exponential Phan-Thien–Tanner constitutive model is used to characterize the shear-thinning viscoelastic polymer flow, and the gas–polymer interface is captured by the volume of fluid method. The effects of gas inlet velocity and polymer elasticity [denoted by the Weissenberg number (Wi)] on the gas-assisted extrusion of the polymer flow have been investigated. The results show that the auxiliary gas inlet can form a protective layer between the polymer and the nozzle wall, thereby eliminating the effects of wall slip. This mechanism effectively reduces the swell ratio, increases the extrusion speed as well as decreases the internal stress of the polymer. However, this is only applicable to certain gas flow rates, and the gas with too high inlet velocity increases the risk of polymer rupture. Adjusting the gas inlet velocity can minimize the internal stress of the polymer ink, thereby achieving optimal printing quality and forming accuracy. In addition, the polymer with higher elasticity has more significant swelling deformation, which exhibits a larger depression at the gas inlet region, leading to a higher risk of rupture. Higher Wi not only decreases internal stress within the polymer but also results in a larger region with high tr(Θ) values, which indicates a greater degree of ink deformation and thus severely impacts the printing resolution and accuracy. This study benefits to offer guidance to the gas-assisted DIW additive manufacturing.