bluuebunny/crossref_metadata_2025_split huggingface dataset:
Suppression of the coffee ring effect with undetectable disturbance of the deposit
Authors: Sheng Shiqi , Fang Zhening , Gao Shiyu , Chen Ruoyang , Wang Ying , Yang Haijun , Fang Haiping 
Published: January 2025

Abstract
Suppressing the coffee ring effect (CRE) of an aqueous suspension through manipulation without affecting the remaining deposit is highly desired for practical applications; clearly such efforts are extremely challenging. Here, we show the CRE suppression with undetectable disturbance of the deposit on carbon-based surfaces. This is achieved by adding ammonium bicarbonate (NH4HCO3), benefited from the dissociation of NH4HCO3 to produce NH4
+, together with its decomposition into NH3 and CO2 molecules. Surprisingly, NH4
+ can also function as Na+/K+ to suppress CRE through the cation- interactions although its hydrate state is only partially positively charged. We further successfully apply this approach to enhance the morphology, resistance, and color uniformity for the deposits of graphene oxide quantum dots, conductive inks, and organic dyes, respectively. Our work provides a practical strategy to improve the performance of the fabricated devices, paving the way for the development of high-accuracy manufacturing techniques in diverse industries.
MAFF-Net: PCB defect detection via feature-enhancement fusion
Authors: Chen Jian , Wang Shouyin , Chen Ziyuan , Huang Wenzhong , Lin Li , Hong Huiqun , Chen Geng , Jiang Zhuwu 
Published: January 2025

Abstract
Defect detection of printed circuit board (PCB) is of significant practical importance to ensure quality control in the production process. However, traditional defect detection methods suffer from limitations such as low detection accuracy and poor generalization ability. To tackle these issues, we propose a novel deep learning-based defect detection method for bare PCBs through multi-attention adaptive feature-enhancement fusion (AFF). First, we utilize ResNext101 as the backbone for feature extractor and embed a normalization-based attention mechanism in a residual structure, aiming at improving the feature extraction capability of the network. Second, we introduce an AFF module, which leverages multi-scale feature extraction and feature fusion to facilitate information interaction and enhance the correlation of feature information between channels. Finally, we incorporate the coordinate attention mechanism into AFF to highlight the target area for boosting detection accuracy. The experimental results demonstrate the effectiveness of the proposed method, which achieves a mean accuracy precision (mAP) of 99.01

%

on a publicly available PCB defect dataset.
Analytic weak-stable manifolds in unfoldings of saddle-nodes*
Authors: Kristiansen Kristian Uldall , Szmolyan Peter 
Published: January 2025

Abstract
Any attracting, hyperbolic and proper node of a two-dimensional analytic vector-field has a unique strong-stable manifold. This manifold is analytic. The corresponding weak-stable manifolds are, on the other hand, not unique, but in the nonresonant case there is a unique weak-stable manifold that is analytic. As the system approaches a saddle-node (under parameter variation), a sequence of resonances (of increasing order) occur. In this paper, we give a detailed description of the analytic weak-stable manifolds during this process. In particular, we relate a ‘flapping-mechanism’, corresponding to a dramatic change of the position of the analytic weak-stable manifold as the parameter passes through the infinitely many resonances, to the lack of analyticity of the centre manifold at the saddle-node. Our work is motivated and inspired by the work of Merle, Raphaël, Rodnianski, and Szeftel, where this flapping mechanism is the crucial ingredient in the construction of

C
∞

-smooth self-similar solutions of the compressible Euler equations.
One-week test–retest stability of heart rate variability during rest and deep breathing
Authors: Schumann Andy , Lukas Franziska , Rieger Katrin , Gupta Yubraj , Bär Karl-Jürgen 
Published: January 2025

Abstract

Objective. Heart rate variability (HRV) is an important indicator of cardiac autonomic function. Given its clinical significance, reliable HRV assessment is crucial. Here, we assessed test–retest stability, as a key aspect of reliability, quantifying the consistency of a measure when repeated under the same conditions. Approach. This observational study includes healthy individuals. A 20 min electrocardiogram was recorded at rest in a supine position and during deep breathing in two lab sessions within one week, at the same time of day. HRV indices from time domain, frequency domain, nonlinear dynamics, and information-theoretic complexity were assessed using a validated toolbox. Additionally, heart rate variations per respiratory cycle were evaluated during deep breathing. Lifestyle factors such as perceived stress, mood, physical activity, sleep quality were assessed prior to both sessions. Intra-class correlation (ICC) and coefficients of variation (CVs) were used to assess the concordance between the two measurements and the relative deviation, respectively. Main results. From 62 screened individuals, 51 participants were recruited from the local community. One participant opted out for personal reasons, and another with frequent premature beats was excluded, leaving a final sample of 49 individuals. Most self-rated psychological and lifestyle indicators showed substantial agreement, though participants reported less stress and better mood in the second session. At rest, ICC of HRV ranged from 0.50 to 0.83, with CV from 5% to 41%. Spectral HRV measures were less reliable than time domain parameters. Nonlinear and time domain features had substantial to nearly perfect agreement. Complexity measures had low CVs but limited test–retest correlation. The stability indices of HRV during deep breathing were not significantly different from those during rest. Test–retest differences in root mean square of the successive beat-to-beat interval difference were not sufficiently explained by lifestyle factors. Significance. Test–retest stability of HRV depends considerably on chosen measures. Our data suggest that HRV can be assessed reliably using time-domain indices at rest.
Destabilizing effects of nonthermal nonextensive particles on electromagnetic Alfvén-cyclotron modes in anisotropic non-equilibrium collision-free plasmas
Authors: Bilal Muhammad , Rehman Aman-ur , Ahmad Mushtaq , Shahzad Muhammad Ahsan , Sarfraz Muhammad 
Published: January 2025

Abstract
This study explores the effects of nonthermal nonextensive particles on the destabilization of Alfvén-cyclotron (AC) modes in collisionless anisotropic non-equilibrium magnetized plasmas. We employ the superextensive and subextensive anisotropic Cairns-Tsallis distribution functions (CTDF) through two distinct theoretical frameworks: model-I (M-I) and model-II (M-II). M-I delineates a temperature model that is invariant with respect to nonthermality and nonextensivity, whereas M-II incorporates a temperature that intrinsically depends on these parameters. Utilizing the linear plasma kinetic theory, we derive the dielectric response function and solve it numerically for AC modes in superextensive and subextensive Cairns-Tsallis distributed plasmas (CTDPs) for both models. Intriguingly, we observe a marked difference in the behavior of AC instability for the two models; M-II significantly augments instability growth in superextensive CTDP compared to M-I, while an opposite trend is manifested in the case of subextensive CTDP. Our investigation further elucidates the impact of pivotal parameters such as plasma beta (β
∥) and ion temperature anisotropy (η

i
) on real and imaginary frequencies of AC modes. This study also offers an in-depth comparative analysis of AC instability in anisotropic CTDP (encompassing both subextensive and superextensive cases), as well as in anisotropic Cairns, and bi-Maxwellian plasmas.
New insights into the diversity of stochastic solutions and dynamical analysis for the complex cubic NLSE with δ-potential through Brownian process
Authors: Rafiq Muhammad Naveed , Rafiq Muhammad Hamza , Alsaud Huda 
Published: January 2025

Abstract
The nonlinear Schrodinger equation is a key tool for modeling wave propagation in nonlinear and dispersive&#xD;media. This study focuses on the complex cubic nonlinear Schrodinger equation with δ-potential,&#xD;explored through the Brownian process. The investigation begins with the derivation of stochastic solitary&#xD;wave solutions using the modified exp(−Ψ(ξ)) expansion method. To illustrate the noise effects, 3D and 2D&#xD;visualizations are displayed for different non-negative values of noise parameter under suitable parameter&#xD;values. Additionally, qualitative analysis of both perturbed and unperturbed dynamical systems is conducted&#xD;using bifurcation and chaos theory. In bifurcation analysis, we analyze the detailed parameter analysis near&#xD;fixed points of the unperturbed system. An external periodic force is applied to perturb the system, leading&#xD;to an investigation of its chaotic behavior. Chaos detection tools are employed to predict the behavior of the&#xD;perturbed dynamical system, with results validated through visual representations. Multistability analysis&#xD;is conducted under varying initial conditions to identify multiple stable states in the perturbed dynamical&#xD;system, contributing to chaotic behavior. Also, sensitivity analysis of the Hamiltonian system is performed&#xD;for different initial conditions. The novelty of this work lies in the significance of the obtained results, which&#xD;have not been previously explored for the considered equation. These findings offer noteworthy insights into&#xD;the behavior of the complex cubic nonlinear Schrodinger equation with δ-potential and its applications in&#xD;fields such as nonlinear optics, quantum mechanics and Bose-Einstein condensates.
A low-cost transhumeral prosthesis operated via an ML-assisted EEG-head gesture control system
Authors: Choi Benjamin J , Liu Ji 
Published: January 2025

Abstract

Objective. Key challenges in upper limb prosthetics include a lack of effective control systems, the often invasive surgical requirements of brain-controlled limbs, and prohibitive costs. As a result, disuse rates remain high despite potential for increased quality of life. To address these concerns, this project developed a low cost, noninvasive transhumeral neuroprosthesis—operated via a combination of electroencephalography (EEG) signals and head gestures. Approach. To address the shortcomings of current noninvasive neural monitoring techniques—namely, single-channel EEG—we leveraged machine learning (ML), creating a neural network-based EEG interpretation algorithm. ML generation was guided by two underlying goals: (1) to improve overall system performance by combining discrete models using a prediction voting scheme, and (2) to favor model diversity within these new neural network ensembles, as opposed to individual model performance. EEG data from eight frequency bands was collected from human subjects to train a ML algorithm employing a hierarchical mixture-of-experts structure. We also implemented head gesture-based control to assist in the generation of additional stable classes for the control system. Main results. The final model performs competitively with existing EEG interpretation systems. Inertial measurement unit (IMU)-based head gestures supplement the neural control system, with 270° actuation of synovial elbow and radial wrist joints driven by intuitive corresponding head gestures. The brain-controlled prosthesis presented in this study costs US$300 to manufacture and achieved competitive performance on a Box and Block Test. Significance. These results suggest proof-of-concept for potential application as an alternative to current prosthetics, but it is important to note that the demonstration in this study remains exploratory. Future work includes broader clinical testing and exploring further uses for the developed ML system.
Design and validation of the PCIe card in a readout system for MAPS based telescope
Authors: Liang Qiming , Lang Lei , Chen Kai , Liu Jun , He Shaoxiang , Xiao Le , Yin Weigang , Yang Chenfei 
Published: January 2025

Abstract
MAPS (Monolithic Active Pixel Sensors) are emerging as the leading technology for inner tracking detectors in future particle physics and nuclear physics experiments. At CCNU (Central China Normal University), the MIC series MAPS ASICs are currently under development. To facilitate the evaluation of these chips and the readout of telescopes with multiple modules, a flexible chip readout and data acquisition system is being developed. This system comprises a front-end kit and a back-end PCIe-based system called PiDAQ. The PiDAQ card, PDQ142, is built with the AMD Versal Prime series FPGA VM1402. Key features of this board include: PCIe Gen4×8 bus supports throughput up to 14.76 GB/s;
on-board memory modules support data buffering with an average throughput exceeding 37.7 GB/s. Furthermore, the board is designed to interface with up to eight front-end modules in speed up to 28 Gb/s per lane, making it ideal for future telescope applications. This paper details the design, hardware, firmware, and preliminary validation of the PDQ142 system.
Chitosan and ibuprofen grafted electrospun polylactic acid/gelatin membrane mitigates inflammatory response
Authors: Ma Qiaolin , Yin Anlin , Wan Xinjian , Sun Binbin , Wang Hongsheng , El-Newehy Mohamed , Abdulhameed Meera Moydeen , Mo Xiumei , Wu Jinglei , Tu Tian 
Published: January 2025

Abstract
Electrospun membranes with biomimetic fibrous structures and high specific surfaces benefit cell proliferation and tissue regeneration but are prone to cause chronic inflammation and foreign body response. To solve these problems, we herein report an approach to functionalize electrospun membranes with antibacterial and anti-inflammatory components to modulate inflammatory responses and improve implantation outcomes. Specifically, electrospun polylactic acid (PLA)/gelatin (Gel) fibers were grafted with chitosan (CS) and ibuprofen (IBU) via carbodiimide chemistry. Our results show that the surface modification strategy endows electrospun membranes with moderate antibacterial activities and sustained release of anti-inflammatory drugs. The electrospun PLA/Gel-CS-IBU membrane showed good antioxidant and anti-inflammatory activity as evidenced by suppressing M1 polarization and promoting M2 polarization of macrophages in vitro. Similarly, it induced significantly milder chronic inflammatory responses in vivo than unmodified electrospun membranes. Given the good anti-inflammatory and antibacterial effects, this strategy might improve the biological performance of electrospun membranes as implants in clinics.
Saving gas through cross-border renewable and nuclear electricity generation
Authors: Halser Christoph , Keles Dogan , Paraschiv Florentina 
Published: January 2025

Abstract
In fossil fuel-driven electricity markets, gas power plants are mostly the price setting technology in peak demand hours. At the same time, gas technology has the role of balancing out the volatility of increasing shares of intermittent renewable generation. This interdependence, coupled with recent fears of supply shortages, raises the question how gas-fired generation can be replaced with carbon-free technologies. Controlling for fundamental supply and demand in the interconnected markets, we quantify the effect of intermittent renewable and nuclear generation in neighboring markets on the use of natural gas for electricity generation in Germany. Findings indicate that cross-border intermittent wind, PV, and nuclear generation significantly reduce the need for German gas. We further show Germany’s dependency on French cross-border nuclear energy to supplement the gas unavailability during the gas crisis period. We argue for larger market coupling and flexible generation alternatives and adaptive demand solutions including cross-border capacities for substituting gas when renewable generation is low across Europe.
The role of technology for green entrepreneurship in southeast asia
Authors: Viona P Y , Febby P C 
Published: January 2025

Abstract
This study aimed to analyze the development of green entrepreneurship in Southeast Asia using bibliometric analysis. This method was used to assess many research works in the fields of “technology,” “entrepreneurship,” and “sustainability” of 2673 publications on green entrepreneurship with digital technology in Southeast Asia from 2000 to 2023. This study investigated the challenges and characteristics of green entrepreneurship research and visualized the bibliometric network using the R Biblioshiny analysis package to identify key clusters and relationships among the publications. Findings revealed a significant surge in academic interest in this topic, primarily focusing on technology’s role in driving innovation and sustainable business growth. The increasing international collaboration highlighted the global significance of this issue. However, the study identified challenges hindering the widespread adoption of green entrepreneurship, such as limited access to finance and adequate infrastructure. While the potential was substantial, adopting digital technology in green businesses is still hampered by entrepreneurs’ lack of awareness and skills. The study recommended several measures to address these challenges, including the implementation of supportive policies, enhancement of educational programs, increased financial accessibility, development of sustainable infrastructure, and strengthened collaboration among stakeholders. Thus, Southeast Asia can fully leverage the potential of green entrepreneurship to achieve sustainable economic growth and address environmental issues.
Harmonizing work behaviour, social equity, and green culture in urban living: the moderating role of sustainable cities green technology
Authors: Judijanto L , Liestyowati D , Andiyan A , Umam R , Indah D Y 
Published: January 2025

Abstract
Green technology is becoming more popular. This article discusses sustainable cities that balance economic opportunity, social equality, and environmental awareness. Sustainable cities prioritize improvements in air quality, efficient waste management, and the provision of essential services. Socioeconomic, environmental, and technical issues impede urban living. Labor, social justice, and ecology are integrated into sustainable cities. Effective urban planning, sustainable technology, and accessible transit are essential. Green technology reduces pollution, conserves resources, and promotes renewable energy. Sustainable behavior needs green technology. A Google Forms poll gathered data from 132 Bandung baristas. The data were analyzed using SEM PLS. This research investigates how work behavior, social equity, and green culture contribute to the development of sustainable cities through the application of green technology. To accomplish economic development and environmental stewardship via green technology, careful planning, community involvement, work behavior, social equality, and green culture must be prioritized. This research provides valuable insights into promoting sustainable urban living through green technology and community engagement. By embracing green technologies and adopting environmentally responsible behaviors, individuals contribute to both societal and environmental sustainability, thereby strengthening the resilience of cities.
Green urban aquaculture: key environmental impacts and conservation strategies – a case study of Jakarta
Authors: Hendarti R , Linggarjati J , Kurnia J C , Fadhilah F I P , Rabbani H S 
Published: January 2025

Abstract
Green aquaculture refers to emerging sustainable practices that minimize environmental impact and optimize efficiency in aquatic food production. It aligns with broader sustainable agriculture goals, focusing on eco-friendly methods, resource efficiency, and responsible management of aquatic ecosystems. This paper presents the influence of urban environments in supporting and enhancing critical aspects of green aquaculture, with a particular emphasis on environmental impact and conservation. Urban aquaculture presents unique challenges and opportunities, especially in densely populated areas, such as Jakarta, where resource management and environmental preservation are critical. Integrating aquaculture into urban settings potentially reduce the environmental footprint of food production while enhancing local food security and economic growth. In addition to environmental conservation, this paper explore the Environmental Impact Assessment (EAI) methodology in analysing the feasibility study of urban aqua culture particularly in Jakarta. The study found that Jakarta’s green aquaculture project involves a multifaceted approach that addresses air quality, flood risks, and water pollution. By systematically assessing these factors and implementing appropriate mitigation strategies, a green aquaculture can be developed sustainably, contributing positively to the local environment and community while minimizing adverse impacts.
Promoting environmental awareness among gen-z in densely populated region. how does social reference matter?
Authors: Kabbaro H , Mashabi N A , Arlianty L S , Amanda L 
Published: January 2025

Abstract
Densely populated areas have a high level of waste contributors. Dealing with waste and environmental quality must be challenging for the Zillennial Generation (Gen-Z), who are familiar with fast and instant processes. This study aims to analyze the influence of social references on environmental awareness in Gen-Z in densely populated areas. The research was conducted in Jakarta and Bandung, Indonesia’s two most populous areas. The study involved 378 Gen-Z in Jakarta and 420 Gen-Z in Bandung. The method used in this research is a survey method using a questionnaire. The simple linear regression test results show that there is a significant influence of social reference variables on environmental awareness (0,000 < 0,05). The regression equation shows that if the social reference variable increases by one unit, the environmental awareness variable increases by 0,815. Increased social referrals are likely to raise environmental awareness in Gen-Z. Developing youth environmental communities in densely populated regions among Gen-Z needs to be encouraged to increase environmental awareness for the nation’s next generation. The government, educators and the private sector need to strengthen the peer group approach to raise the environmental awareness of Gen-Z, which is the largest population category in Indonesia.
Impact of COVID-19 on Aquaculture Sector in Sabah
Authors: Ramli Hazza Roshada , Mamat Zawawi Mohd Fauzan , Jaili Irwandih Mat 
Published: January 2025

Abstract
The COVID-19 pandemic had a direct and indirect impact on the aquaculture sector in Sabah. Therefore, a comprehensive understanding of how this epidemic affects is very important to be used as a reference. The questionnaire involved four sections which are demographics, background, issues and challenges during COVID-19 as well as the impact and knowledge related to COVID-19 on aquaculture activities. A total of 74% of respondents strongly agreed that this COVID-19 had a big impact on aquaculture-related activities in Sabah while 26% of respondents expressed a neutral stance on this issue. Therefore, survey results revealed that pandemic COVID-19 has been affected in different areas of aquaculture sector including the supply of aquaculture stocks, bureaucratic problems and the demand for aquaculture products.