bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Preheating Parameters on Extrusion Welding of High-Density Polyethylene Materials
Authors: Lee Chungwoo , Woo Suseong , Kwon Sooyeon , Kim Jisun
Published: October 2024

High-density polyethylene (HDPE) has emerged as a promising alternative to fiber-reinforced plastic (FRP) for small vessel manufacturing due to its durability, chemical resistance, lightweight properties, and recyclability. However, while thermoplastic polymers like HDPE have been extensively used in gas and water pipelines, their application in large, complex marine structures remains underexplored, particularly in terms of joining methods. Existing techniques, such as ultrasonic welding, laser welding, and friction stir welding, are unsuitable for large-scale HDPE components, where extrusion welding is more viable. This study focuses on evaluating the impact of key process parameters, such as the preheating temperature, hot air movement speed, and nozzle distance, on the welding performance of HDPE. By analyzing the influence of these variables on heat distribution during the extrusion welding process, we aim to conduct basic research to derive optimal conditions for achieving strong and reliable joints. The results highlight the critical importance of a uniform temperature distribution in preventing defects such as excessive melting or thermal degradation, which could compromise weld integrity. This research provides valuable insights into improving HDPE joining techniques, contributing to its broader adoption in the marine and manufacturing industries.
Micro–Macro Coupling Study on the Mechanical Properties of Continuous Fiber-Reinforced Composites
Authors: Wang Na , Li Zhihua , Peng Yubao , Jiang Zhuang , Li Hongbin
Published: October 2024

As a key and weak point of continuous fiber-reinforced composites (CFRCs), the interface between the fiber and the matrix is vulnerable to failure under external loads, with its performance directly affecting the overall properties of CFRCs. Hence, a micro–macro coupling method that considered the microscopic properties of the interface was utilized to analyze and predict the mechanical properties of CFRCs more accurately. The microscopic mechanical parameters of the fiber–matrix interface, which were obtained using molecular dynamics, were transferred to the representative volume element (RVE). The stiffness matrix of the CFRC, required for the macroscopic finite element model, was then calculated using a unified periodic homogenization method based on the RVE and assigned to the finite element model for a macroscopic simulation. Nylon/continuous carbon fiber specimens were fabricated through additive manufacturing, with the tensile and bending strengths of the specimens obtained through tensile and three-point bending tests. The tensile strength of the experimental specimen was 200.1 MPa, while the result of the simulation containing the interface was 205.5 MPa, indicating a difference of less than 5% between the two. In contrast, the result of the simulation without an interface was 317.7 MPa, representing a high error of 58.7% compared with the experimental results. Moreover, the bending strength, Young’s modulus, and flexural modulus results with and without an interface showed the same trend as that for the tensile strength. This illustrates the effectiveness of the proposed micro–macro coupling method for analyzing and predicting the mechanical properties of CFRCs.
Adjustment of Mechanical Properties of 3D Printed Continuous Carbon Fiber-Reinforced Thermoset Composites by Print Parameter Adjustments
Authors: Rahman Md Atikur , Gibbon Luke , Islam Md Zahirul , Hall Eric , Ulven Chad A.
Published: October 2024

Reinforcing thermoset polymers with continuous carbon fiber (CF) tow has emerged as a promising avenue to overcome the thermal and mechanical performance limitations of 3D printed polymeric structures for load-bearing applications. Unlike traditional methods, manufacturing continuous fiber-reinforced composites by 3D printing has the unique capability of locally varying the mechanical properties of the composites. In this study, continuous CF thermoset composite specimens were printed with varying line spacing, resin flow rate, and nozzle sizes. The resin flow rates for different line spacings and nozzle sizes were optimized by topographic analysis. Printed composite mechanical properties were evaluated, and their trends were correlated with the trend of print parameter changes. Results showed that tensile strength and modulus could be altered and improved by ~50% by adjusting the printing process parameters. Higher composite strength and modulus were obtained by shortening the line spacing and nozzle diameter.
Novel Strategy of Treating 2-Nitrobenzoic Acid Crystals with Energetic N2 Neutrals Using Cold Plasma
Authors: Aravinthraj M. , Udayaseelan J. , Amarnath P. , Yugeswaran S. , Gayathri V. , Sinha Suraj Kumar , Perumal M.
Published: October 2024

The organic adduct compounds of 2-nitrobenzoic acid crystals were grown as optically transparent crystals using the conventional slow evaporation solution technique. The crystals were powdered and irradiated with cold plasma. Cell parameter analysis confirmed the formation of a new crystalline material that resides in the triclinic P crystal system with space group P1. Fourier transform infrared spectra were recorded using the KBr pellet technique to determine the vibrational functional groups in the compound. Powder X-ray diffraction analysis was used to reveal the crystalline orientation of the powdered samples of the grown crystals. The obtained full width at half maximum for the (001) plane in the XRD spectrum indicates the excellent crystalline quality of the 2-nitrobenzoic acid crystals. The recorded UV–Vis absorption spectra reveal that the grown powdered crystal samples possess cut-off edges wavelengths at 428 and 428 nm and 353 and 354 nm for pure and plasma-treated samples, respectively. The optical energy bandgaps were found to be 2.0, 2.25, 4.06, and 4.02 eV for the pure and plasma-treated samples, respectively. The photoluminescence spectra show the blue emissions of the crystal. The FE-SEM images show the morphological modifications in which rounded platelets appear on the surfaces of the treated crystals.
Niobium Metal–Organic Framework Is an Efficient Catalytic Support for the Green Hydrogen Evolution Process from Metal Hydride
Authors: Coelho Lorrayne Ohana , Sperandio Gabriel Henrique , Chagas da Silva Renê , Lopes Moreira Renata Pereira , de Jesus Jemmyson Romário
Published: October 2024

Herein, the development of a niobium-based metal–organic framework (Nb-MOF) designed to serve as a catalytic support for the production of hydrogen (H2) from sodium borohydride (NaBH4) is reported. The Nb-MOF was synthesized via a solvothermal method using niobium ammoniacal oxalate (AmOxaNb) as the metal source and 1,4-benzenedicarboxylic acid (BDC) as the ligand. The resulting MOF was characterized by Fourier transform infrared (FT-IR) spectroscopy, thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS). The characterization study confirmed the successful synthesis of Nb-MOF. The catalytic activity was optimized by examining five key factors: (i) platinum (Pt) and cobalt (Co) bimetallic compositions (ranging from 1:0 to 0:1 mmol), (ii) NaBH4 concentration (0.2, 0.3, 0.4, and 0.5 mol L−1), (iii) the Nb-MOF/Pt–Co catalyst dose (0.05, 0.10, 0.20, and 0.40 mmol), (iv) sodium hydroxide (NaOH) concentration (0.01, 0.05, 0.1, and 0.2 mol L−1), and (v) system temperature (293.15, 298.15, 303.15, 313.15, and 323.15 K). The optimal catalyst was identified as Nb-MOF supporting a Pt-Co bimetallic composition in a 0.4:0.6 mmol ratio, achieving a hydrogen generation rate (HGR) of 1473 mL min−1 gcat−1 and an activation energy of 19.2 kJ mol−1. Furthermore, this catalyst maintained its efficiency over 20 cycles, demonstrating significant potential as a sustainable solution for H2 evolution from NaBH4.
Shallow-Depth Quantum Circuit for Unstructured Database Search
Authors: Zhan Junpeng
Published: October 2024

Grover’s search algorithm (GSA) offers quadratic speedup in searching unstructured databases but suffers from exponential circuit depth complexity. Here, we present two quantum circuits called HX and Ry layers for the searching problem. Remarkably, both circuits maintain a fixed circuit depth of two and one, respectively, irrespective of the number of qubits used. When the target element’s position index is known, we prove that either circuit, combined with a single multi-controlled X gate, effectively amplifies the target element’s probability to over 0.99 for any qubit number greater than seven. To search unknown databases, we use the depth-1 Ry layer as the ansatz in the Variational Quantum Search (VQS), whose efficacy is validated through numerical experiments on databases with up to 26 qubits. The VQS with the Ry layer exhibits an exponential advantage, in circuit depth, over the GSA for databases of up to 26 qubits.
Decolonizing Forest: The Myth of Panjurli and Guliga in Kantara (2022)
Authors: Saraswat Anandita , Das Aratrika
Published: October 2024

Colonial ideologies reduce nature to a repository of extractable resources and portray the Indigenous communities’ religious understanding of nature as primitive and unscientific. Decolonization foregrounds the silenced Indigenous epistemes that critique exceptional human paradigms of colonial modernity. This paper examines how traditional religious rituals function as a method of decolonization and discusses their exclusion from Western academia. It focuses on Kantara’s cinematic representation of the Indigenous ritual of Bhoota Kola and the worship of forest deities, Panjurli and Guliga, in the coastal areas of southern Karnataka and Kerala. These rituals emphasize the agency of the environment, where the forest, humans, and deities are porous and permeable. This non-anthropocentric understanding of humans questions the dominance of the secular narratives of posthuman theories in Western academia. Rituals foster ecological behaviours and highlight multispecies relationality, providing alternatives for sustainable futures. In emphasizing Indigenous religious practices, the paper undisciplines the Eurocentric study of religion and questions the disciplinary boundaries between scientific thought and Indigenous knowledge. Thus, this paper argues for the inclusion of regional cinemas from the Global South in Western academia to foreground Indigenous epistemes that undiscipline the study of religion and science.
Oven-Dried Cupuaçu and Bacuri Fruit Pulps as Amazonian Food Resources
Authors: Barbosa-Carvalho Anna Paula Pereira , da Silva Pena Rosinelson , Chisté Renan Campos
Published: October 2024

The Amazon is one of the largest and most diverse biomes on the planet. Cupuaçu (Theobroma grandiflorum (Willd. ex Spreng.) Schum) and bacuri (Platonia insignis Mart.) are Amazonian fruit species appreciated for their sensory characteristics and promising availability of bioactive compounds. However, high moisture levels (>80%) make these pulps susceptible to deterioration during storage. In this study, the oven-drying process was monitored to produce dry and more stable pulps. The process was monitored at 40 °C, 55 °C and 70 °C, and the bioactive compounds and antioxidant capacity were determined as quality indicators. In general, drying at 70 °C for 340 min produced dried cupuaçu and bacuri pulps with high levels of total phenolic compounds: 288 and 652 mg gallic acid equivalents/100 g, respectively. The hygroscopic evaluation suggested that both of the dried pulps should be stored at a relative humidity of <40% to avoid rapid water adsorption and it is advised to carry out the oven-drying process until up to 12% moisture is reached for cupuaçu and 9% for bacuri to avoid unnecessary energy consumption. Thus, this study expands the potential of bacuri and cupuaçu pulps for application in food industries, contributing to the economic and social development of the Amazon region.
Using Adjoint-Based Forecast Sensitivity to Observation to Evaluate a Wind Profiler Data Assimilation Strategy and the Impact of Data on Short-Term Forecasts
Authors: Wang Cheng , Huang Xiang-Yu , Chen Min , Chen Yaodeng , Zhong Jiqin , Yin Jian
Published: October 2024

A wind profiler radar detects fine spatiotemporal resolution dynamical information, enabling the capture of meso- and micro-scale systems. Experience gained from observing system experiments (OSEs) studies confirms that reasonable profiler assimilation techniques can achieve improved short-term forecasts. This study further applies the adjoint-based forecast sensitivity to observation (FSO) method to investigate the quantitative impact of a profiler data assimilation strategy on short-term forecasts, and the results are consistent with those obtained from OSEs, further demonstrating that FSO and OSEs can be used to evaluate the effect of data assimilation techniques from different perspectives. Considering the unique advantage that the FSO can quantify the interactions between various observing systems and the impact on improving the model forecasts according to specific needs without costly additional calculations, we further diagnose in detail the observation impacts from multiple perspectives, including the observation platform, observation variables, and spatial distribution. And the results show that dynamical variables are more significant in improving forecasts compared to the other observed variables. Meanwhile, the dense profiler observations resulted in a more significant impact when radiosonde observations were not detected. The upper-level single winds monitored by profiler radars play a more important role in improving forecast skill. The FSO method measures the impact of an individual observing system, which can be used to enrich the evaluation of data assimilation schemes, efficiently calculate the impacts of multisource observations, and contribute to future development in adaptive observation, observation quality control, and observation error optimization.
Interferometric Synthetic Aperture Radar Phase Linking with Level 2 Coregistered Single Look Complexes: Enhancing Infrastructure Monitoring Accuracy at Algeciras Port
Authors: Sánchez-Fernández Jaime , Fernández-Landa Alfredo , Hernández Cabezudo Álvaro , Molina Sánchez Rafael
Published: October 2024

This paper presents an advanced workflow for processing radar imagery stacks using Persistent Scatterer and Distributed Scatterer Interferometry (PSDS) to enhance spatial coherence and improve displacement detection accuracy. The workflow leverages Level 2 Coregistered Single Look Complex (L2-CSLC) images generated by the open-source COMPASS (Coregistered Multi-temporal Sar SLC) framework in combination with the Combined eigenvalue maximum likelihood Phase Linking (CPL) approach implemented in MiaplPy. Starting the analysis directly from Level 2 products offers a significant advantage to end-users, as they simplify processing by being pre-geocoded and ready for immediate analysis. Additionally, the open-source nature of the workflow and the use of L2-CSLC products simplify the processing pipeline, making it easier to distribute directly to users for practical applications in monitoring infrastructure stability in dynamic environments. The ISCE3-MiaplPy workflow is compared against ISCE2-MiaplPy and the European Ground Motion Service (EGMS) to assess its performance in detecting infrastructure deformations in dynamic environments, such as the Algeciras port. The results indicate that ISCE3-MiaplPy delivers denser measurements, albeit with increased noise, compared to its counterparts. This higher resolution enables a more detailed understanding of infrastructure stability and surface dynamics, which is critical for environments with ongoing human activity or natural forces.
Two-Dimensional Coherent Polarization–Direction-of-Arrival Estimation Based on Sequence-Embedding Fusion Transformer
Authors: Wu Zihan , Wang Jun , Zhou Zhiquan
Published: October 2024

Addressing the issue of inadequate convergence and suboptimal accuracy in classical data-driven algorithms for coherent polarization–direction-of-arrival (DOA) estimation, a novel high-precision two-dimensional coherent polarization–DOA estimation method utilizing a sequence-embedding fusion (SEF) transformer is proposed for the first time. Drawing inspiration from natural language processing (NLP), this approach employs transformer-based multitasking text inference to facilitate joint estimation of polarization and DOA. This method leverages the multi-head self-attention mechanism of the transformer to effectively capture the multi-dimensional features within the spatial-polarization domain of the covariance matrix data. Additionally, an SEF module was proposed to fuse the spatial-polarization domain features from different dimensions. The module is a combination of a convolutional neural network (CNN) with local information extraction capabilities and a feature dimension transformation function, serving to improve the model’s ability to fuse information about features in the spatial-polarization domain. Moreover, to enhance the model’s expressive capacity, we designed a multi-task parallel output mode and a multi-task weighted loss function. Simulation results demonstrate that our method outperforms classical data-driven approaches in both accuracy and generalization, and the estimation accuracy of our method is improved relative to the traditional model-driven algorithm.
Evolution and Drivers of Embodied Energy in Intermediate and Final Fishery Trade Between China and Maritime Silk Road Countries
Authors: Zhao Liangshi , Jiang Jiaxi
Published: October 2024

Fishery plays an important role in world trade; however, the embodied energy associated with fishery remains incompletely quantified. In this study, we applied the multi-regional input-output (MRIO) model and logarithmic mean Divisia index (LMDI) approach to understand the evolution and drivers of embodied energy in the intermediate and final fishery trade between China and countries along the 21st century Maritime Silk Road (MSR) from 2006 to 2021. The findings are as follows: (1) Embodied energy in the intermediate fishery trade averaged 92.2% of embodied energy from the total fishery trade. China has gradually shifted from being a net exporter to a net importer of embodied energy in intermediate, final, and total fishery trade with countries along the MSR. (2) From a regional perspective, the embodied energy in China’s fishery trade with Japan, South Korea, and Southeast Asia comprises the majority of the embodied energy from China’s total fishery trade (82.0% on average annually). From a sectoral perspective, petroleum, chemical and non-metallic mineral products, and transport equipment were prominent in the embodied energy of China’s intermediate fishery trade (64.0% on average annually). (3) Economic output increases were the main contributors to the increasing embodied energy in all types of fishery trade in China. The improvement in energy efficiency effectively reduced the embodied energy in all types of fishery trade in China, but its negative driving force weakened in recent years owing to minor energy efficiency improvements. Understanding the embodied energy transactions behind the intermediate and final fishery trade with countries along the MSR can provide a theoretical reference for China to optimize its fishery trade strategy and save energy.
Highly Sensitive Gas Pressure Sensing with Temperature Monitoring Using a Slightly Tapered Fiber with an Inner Micro-Cavity and a Micro-Channel
Authors: Sun Changwei , Yu Fen , Chen Huifang , Wang Dongning , Xu Ben
Published: October 2024

A highly sensitive optical fiber gas pressure sensor with temperature monitoring is proposed and demonstrated. It is based on a slightly tapered fiber with an inner micro-cavity forming an in-fiber Mach–Zehnder interferometer (MZI), and a micro-channel is drilled into the lateral wall of the in-fiber micro-cavity using a femtosecond laser to allow gas to flow in. Due to the dependence of the refractive index (RI) of air inside the micro-cavity on its gas pressure and the high RI sensitivity of the MZI, the device is extremely sensitive to gas pressure. To prevent fiber breakage, the MZI is housed in a silicate capillary tube with an air inlet. Multiple modes are excited by slightly tapering the inner micro-cavity, and the resonance dips in the sensor’s transmission spectrum feature different linear gas pressure and temperature responses, so a sensitivity matrix algorithm can be used to achieve simultaneous demodulation of two parameters, thus resolving the temperature crosstalk. As expected, the experimental results demonstrated the reliability of the matrix algorithm, with pressure sensitivity reaching up to ~−12.967 nm/MPa and temperature sensitivity of ~89 pm/°C. The features of robust mechanical strength and high air pressure sensitivity with temperature monitoring imply that the proposed sensor has good practical and application prospects.
Real-Time Indoor Environmental Quality (IEQ) Monitoring Using an IoT-Based Wireless Sensing Network
Authors: Tsang Tsz-Wun , Mui Kwok-Wai , Wong Ling-Tim , Chan Angus Chun-Yu , Chan Ricky Chi-Wai
Published: October 2024

In recent years, our time spent indoors has risen to around 90% and to maintain an occupant’s comfort and well-being, Indoor Environmental Quality (IEQ) is monitored. Concerned with inhabitant’s satisfaction and health, the adoption of smart solutions for IEQ monitoring and improvement has expanded. The solution this study explores is an occupant-centric approach involving the implementation of an Internet of Things (IoT) IEQ sensing network in a prominent office skyscraper in Hong Kong. Over the course of 15 months, real-time IEQ data were collected from 12 locations within the building. The data were collected at 1-min time intervals and consisted of readings of indoor air temperature, radiant temperature, relative humidity, air velocity, carbon dioxide (CO2), particulate matter (PM10 and PM2.5), horizontal illuminance levels, and sound pressure levels, which served as the basis of the assessment made about the qualities of thermal comfort, indoor air quality (IAQ), aural comfort, and visual comfort. Compared to traditional periodic surveys, this IoT-based sensing network captured instantaneous environmental variations, providing valuable insights into the indoor environment’s spatial characterization and temporal dynamics. This smart solution also assisted facility management in terms of identifying sources of discomfort and developing effective mitigation strategies accordingly. This study presents an occupant-centric approach to improve occupant comfort and energy efficiency within office buildings. By customizing the built environment to enhance occupants’ well-being, comfort, and productivity, an emphasis is placed on a more personalized and occupant-focused design strategy. This approach integrates technical design with human experience, highlighting the importance of real-time physical and subjective surveys for achieving optimal results.
Multi-Sensor Soil Probe and Machine Learning Modeling for Predicting Soil Properties
Authors: Grunwald Sabine , Murad Mohammad Omar Faruk , Farrington Stephen , Wallace Woody , Rooney Daniel
Published: October 2024

We present a data-driven, in situ proximal multi-sensor digital soil mapping approach to develop digital twins for multiple agricultural fields. A novel Digital Soil CoreTM (DSC) Probe was engineered that contains seven sensors, each of a distinct modality, including sleeve friction, tip force, dielectric permittivity, electrical resistivity, soil imagery, acoustics, and visible and near-infrared spectroscopy. The DSC System integrates the DSC Probe, DSC software (v2023.10), and deployment equipment components to sense soil characteristics at a high vertical spatial resolution (mm scale) along in situ soil profiles up to a depth of 120 cm in about 60 s. The DSC Probe in situ proximal data are harmonized into a data cube providing vertical high-density knowledge associated with physical–chemical–biological soil conditions. In contrast, conventional ex situ soil samples derived from soil cores, soil pits, or surface samples analyzed using laboratory and other methods are bound by a substantially coarser spatial resolution and multiple compounding errors. Our objective was to investigate the effects of the mismatched scale between high-resolution in situ proximal sensor data and coarser-resolution ex situ soil laboratory measurements to develop soil prediction models. Our study was conducted in central California soil in almond orchards. We collected DSC sensor data and spatially co-located soil cores that were sliced into narrow layers for laboratory-based soil measurements. Partial Least Squares Regression (PLSR) cross-validation was used to compare the results of testing four data integration methods. Method A reduced the high-resolution sensor data to discrete values paired with layer-based soil laboratory measurements. Method B used stochastic distributions of sensor data paired with layer-based soil laboratory measurements. Method C allocated the same soil analytical data to each one of the high-resolution multi-sensor data within a soil layer. Method D linked the high-density multi-sensor soil data directly to crop responses (crop performance and behavior metrics), bypassing costly laboratory soil analysis. Overall, the soil models derived from Method C outperformed Methods A and B. Soil predictions derived using Method D were the most cost-effective for directly assessing soil–crop relationships, making this method well suited for industrial-scale precision agriculture applications.
Multi-UAV Escape Target Search: A Multi-Agent Reinforcement Learning Method
Authors: Liao Guang , Wang Jian , Yang Dujia , Yang Junan
Published: October 2024

The multi-UAV target search problem is crucial in the field of autonomous Unmanned Aerial Vehicle (UAV) decision-making. The algorithm design of Multi-Agent Reinforcement Learning (MARL) methods has become integral to research on multi-UAV target search owing to its adaptability to the rapid online decision-making required by UAVs in complex, uncertain environments. In non-cooperative target search scenarios, targets may have the ability to escape. Target probability maps are used in many studies to characterize the likelihood of a target’s existence, guiding the UAV to efficiently explore the task area and locate the target more quickly. However, the escape behavior of the target causes the target probability map to deviate from the actual target’s position, thereby reducing its effectiveness in measuring the target’s probability of existence and diminishing the efficiency of the UAV search. This paper investigates the multi-UAV target search problem in scenarios involving static obstacles and dynamic escape targets, modeling the problem within the framework of decentralized partially observable Markov decision process. Based on this model, a spatio-temporal efficient exploration network and a global convolutional local ascent mechanism are proposed. Subsequently, we introduce a multi-UAV Escape Target Search algorithm based on MAPPO (ETS–MAPPO) for addressing the escape target search difficulty problem. Simulation results demonstrate that the ETS–MAPPO algorithm outperforms five classic MARL algorithms in terms of the number of target searches, area coverage rate, and other metrics.
Multi-Stimuli Responsive Viologen-Imprinted Polyvinyl Alcohol and Tricarboxy Cellulose Nanocomposite Hydrogels
Authors: Al-Qahtani Salhah D. , Al-Senani Ghadah M. , Alrasheedi Muneera , Mohammed Ard elshifa M. E.
Published: October 2024

Photochromic inks have shown disadvantages, such as poor durability and high cost. Self-healable hydrogels have shown photostability and durability. Herein, a viologen-based covalent polymer was printed onto a paper surface toward the development of a multi-stimuli responsive chromogenic sheet with thermochromic, photochromic, and vapochromic properties. Viologen polymer was created by polymerizing a dialdehyde-based viologen with a hydroxyl-bearing dihydrazide in an acidic aqueous medium. The viologen polymer was well immobilized as a colorimetric agent into a polyvinyl alcohol (PVA)/tricarboxy cellulose (TCC)-based self-healable hydrogel. The viologen/hydrogel nanocomposite films were applied onto a paper surface. The coloration measurements showed that when exposed to ultraviolet light, the orange layer printed on the paper surface switched to green. The photochromic film was used to develop anti-counterfeiting prints using the organic hydrogel composed of a PVA/TCC composite and a viologen polymer. Reversible photochromism with strong photostability was observed when the printed papers were exposed to UV irradiation. A detection limit was monitored in the range of 0.5–300 ppm for NH3(aq). The exposure to heat (70 °C) was found to reversibly initiate a colorimetric change.
Review of Authentication, Blockchain, Driver ID Systems, Economic Aspects, and Communication Technologies in DWC for EVs in Smart Cities Applications
Authors: Rajamanickam Narayanamoorthi , Vishnuram Pradeep , Abraham Dominic Savio , Gono Miroslava , Kacor Petr , Mlcak Tomas
Published: October 2024

The rapid advancement and adoption of electric vehicles (EVs) necessitate innovative solutions to address integration challenges in modern charging infrastructure. Dynamic wireless charging (DWC) is an innovative solution for powering electric vehicles (EVs) using multiple magnetic transmitters installed beneath the road and a receiver located on the underside of the EV. Dynamic charging offers a solution to the issue of range anxiety by allowing EVs to charge while in motion, thereby reducing the need for frequent stops. This manuscript reviews several pivotal areas critical to the future of EV DWC technology such as authentication techniques, blockchain applications, driver identification systems, economic aspects, and emerging communication technologies. Ensuring secure access to this charging infrastructure requires fast, lightweight authentication systems. Similarly, blockchain technology plays a critical role in enhancing the Internet of Vehicles (IoV) architecture by decentralizing and securing vehicular networks, thus improving privacy, security, and efficiency. Driver identification systems, crucial for EV safety and comfort, are analyzed. Additionally, the economic feasibility and impact of DWC are evaluated, providing essential insights into its potential effects on the EV ecosystem. The paper also emphasizes the need for quick and lightweight authentication systems to ensure secure access to DWC infrastructure and discusses how blockchain technology enhances the efficiency, security, and privacy of IoV networks. The importance of driver identification systems for comfort and safety is evaluated, and an economic study confirms the viability and potential benefits of DWC for the EV ecosystem.
Re-Designing Secure Children’s Homes Through a Child-First Lens
Authors: Andow Caroline , Kleipoedszus Stefan , Dunn Rachel , Wake Nicola , Arthur Raymond , Shafi Adeela , Gibson David
Published: October 2024

This article explores existing learning gaps concerning optimal ways to support children within and beyond secure care in England and Wales, with a specific focus on Secure Children’s Homes (SCHs). Insights from key stakeholders working in SCHs are often omitted from research despite being fundamental to understanding both challenges and best-practice initiatives. The Children’s Residential Care Research Network, which is a collaboration between the authors, aims to develop novel research with stakeholders working across the secure children’s estate and expand the extant literature to inform the design and build of future Secure Children’s Homes (SCH) through a Child-First lens. The research presented here involves a mixed-methods approach gathering rich qualitative data from participants across the sector. Fifty-three participants engaged in participatory methodologies, focus groups, and interviews, which led to a large data set. Thematic analysis identified three key themes to inform the design and build of new SCHs. SCHs should (i) be close to home to enable family involvement and continuity of care, (ii) feel like a home, and (iii) be flexible and adaptive to changing needs. These findings are feeding into the design of two new homes in England as well as the refurbishment of existing provision and can also influence future expansion of the secure estate. The research also contributes to knowledge about how the Child-First tenets can be engaged to improve outcomes for children deprived of their liberty, both in and outside the youth justice system.
Neglect, School Violence, and Internalizing Behaviors in Children from Multicultural Families in Korea
Authors: Kim Dami
Published: October 2024

Children from multicultural families (i.e., families with at least one parent from a foreign country other than Korea) in South Korea face increased risks of adverse life conditions at home and school. However, few studies have investigated the cumulative effects of family and school adversities, especially internalizing behaviors in this population. This study examined the association between neglect and internalizing behaviors (i.e., depression and social withdrawal) and whether victimization from school violence amplifies the impact of neglect. Data were drawn from the second wave of the Multicultural Adolescents Panel Study (MAPS), which was constructed by the National Youth Policy Institute (NYPI) and included 1500 fifth-graders surveyed in 2012. We first examined the moderating effect of school violence victimization on the association between neglect and depression and subsequently tested the same model to predict social withdrawal. This study showed that neglect significantly increased depression and social withdrawal. Additionally, the impact of neglect on depression and social withdrawal intensified when school violence coexisted. The findings of this study suggest that children from multicultural families exposed to co-occurring adversities require more attention. Assessment of polyvictimization and psychological counseling are necessary for supporting these children who have suffered violence at home and school.
reflimLOD: A Modified reflimR Approach for Estimating Reference Limits with Tolerance for Values Below the Lower Limit of Detection (LOD)
Authors: Klawonn Frank , Hoffmann Georg , Holdenrieder Stefan , Trulson Inga
Published: October 2024

Reference intervals are indispensable for the interpretation of medical laboratory results to distinguish “normal” from “pathological” values. Recently, indirect methods have been published, which estimate reference intervals from a mixture of normal and pathological values based on certain statistical assumptions on the distribution of the values from the healthy population. Some analytes face the problem that a significant proportion of the measurements are below the limit of detection (LOD), meaning that there are no quantitative data for these values, only the information that they are smaller than the LOD. Standard statistical methods for reference interval estimation are not designed to incorporate values below the LOD. We propose two variants of the indirect method reflimR—a quantile- and maximum likelihood-based estimator—that are able to cope with values below the LOD. We show, based on theoretical analyses, simulation experiments, and real data, that our approach yields good estimates for the reference interval, even when the values below the LOD contribute a substantial proportion to the data.
Residual Assessment of Emerging Pesticides in Aquatic Sinks of Lahore, Pakistan
Authors: Iqbal Hafiza Hira , Qadir Abdul , Ahmad Sajid Rashid , Riaz Muhammad Ahsan , Riaz Ayesha , Shahid Naeem , Arslan Muhammad
Published: October 2024

In recent decades, the use of pesticides has become fundamental to agricultural growth. However, the persistent and toxic nature of pesticides has led to significant concerns regarding their ecological and human health consequences. Therefore, for a better understanding of pesticide contamination and its potential risks, here we assessed the levels of five emerging pesticides—acetochlor, imidacloprid, MCPA, atrazine, and allethrin—in soil samples from ponds used for irrigation and in drinking water samples from nearby areas in Lahore, Pakistan. Our findings revealed that 100% of the samples were contaminated, posing substantial ecological and human health risks. Based on the toxic units (TUsum), all the soil samples showed higher toxic pressure, exceeding acute and chronic toxicity thresholds for earthworms, while 100% of water samples posed chronic toxicity risks to crustaceans and 10% to algae. Pollution index (PI) analysis further classified 100% of the soil samples and 10% of the water samples as highly polluted. These findings show high-pesticide residues in both soil and water and highlight immediate risk assessment and mitigation measures to protect non-target organisms. This preliminary information can be used to adopt risk assessment monitoring programmes and help higher authorities in making policies and guidelines to mitigate the escalating risk for ecology and humans.
Corporate Digital Transformation and the Internationalization of R&D
Authors: Li Yaru , Zhang Qifan
Published: October 2024

In the context of digital transformation and economic globalization, R&D (research and development) internationalization is essential for enterprises to utilize global resources and achieve technological innovation. This study examines Chinese A-share-listed industrial companies with active overseas R&D from 2010 to 2022 using a Poisson panel fixed-effects model to assess how digital transformation influences R&D internationalization. The findings confirm that digital transformation significantly enhances the depth and breadth of R&D internationalization, even when controlling for endogeneity. The analysis identifies financing constraints and information communication efficiency as key mediators in this process. Additionally, the impact varies by the type of digital technology and the geographical location of the enterprises. This research not only deepens understanding of the link between digital transformation and R&D internationalization but also aids policy formulation for governments and businesses.
The Relationship Standardized Precipitation Evapotranspiration Index (SPEI) and Forage Value of Rubus Species Collected from Türkiye’s Flora
Authors: Topçu Gülcan Demiroğlu , Koç Koyun Nur , Korkmaz Ayşegül
Published: October 2024

The increasing drought caused by climate change makes it difficult for rural areas reliant on pasture-based livestock farming to sustain their agricultural practices. Blackberries, a spreading species, have been selected as the material for this study due to their perennial shrub nature and their tolerance to adverse environmental conditions. Türkiye, the gene center for blackberries, is part of the Mediterranean belt and is located at the intersection of three flora regions—Mediterranean, Euro-Siberian, and Irano-Turanian. This study aims to determine the forage value of the Rubus species and other shrub/tree species (Quercus, Pistacia, and Rosa) collected and identified from these flora regions. Furthermore, a linear regression analysis established a relationship between the forage values and the SPEI, a drought index, considering the combined effects of rainfall and temperature in the collection regions. Among the Rubus species, the highest organic matter content (887.8 g kg−1) was obtained from R. pruinosus. In comparison, the highest protein content (240.1 g kg−1) was found in cultivated blackberries in the Euro-Siberian flora region. P. lentiscus had the highest Ca content (14.4 g kg−1) and offered feed at the “Prime” level with 154 of RFV. The SPEI explained 87% of the variation in fructan, 89% in Mg, and 92% in ADF. Due to the perennial nature of the species studied, a strong relationship was found between their growth and forage values over a 48-month time scale using the SPEI. Consequently, the equations related to ADF, Mg, and fructan content obtained in this study can be recommended for woody species.
How Financial Development Is Driving the Growth and Environmental Dimensions of Sustainable Development in Africa: Heterogeneous Analyses
Authors: Ibrahim Ridwan Lanre , Alomair Abdulrahman , Al Naim Abdulaziz S.
Published: October 2024

Globally, we face a policy dilemma between desiring more economic growth and safeguarding the deteriorating ecosystem, which have an apparent trade-off. Consequently, financing growth often comes with strong concerns for the ecological implications, which is yet to be empirically resolved. Hence, the current study examined the growth and environmental effects of financial development from three angles, each with a robust indicator, comprising financial development index, financial institution index, and financial market index. The scope of this study was financial development in 30 selected African countries from 1996 to 2021. This study extends the frontier of knowledge by estimating the moderating roles of regulatory quality and digitalization coupled with other control variables: renewable and nonrenewable energy, government expenditure, trade openness, and foreign direct investment. The empirical evidence relies on estimators such as common correlated effects (mean group), the system-generalized method of moment, and method of moment quantile regression. The findings from this study reveal that financial development propels economic growth but to the detriment of the ecosystem. However, when the interactive effects of regulatory quality and digitalization are considered, the negative externalities of growth-induced financial development are reduced. Furthermore, control variables such as renewable energy and foreign direct investment promote growth without escalating ecological damage. This is in contrast to nonrenewable energy, government expenditure, and trade openness, which propel economic growth at the expense of the ecological system. Policy recommendations that balance the trade-off between the two measures are put forward based on the research outcomes.
Impact of Biodiversity Loss on Pollen Allergies: A Bibliometric Analysis
Authors: Braun Karoline , Haluza Daniela
Published: October 2024

The incidence of allergic respiratory diseases has increased in recent decades, with declining biodiversity identified as a potential contributing factor. While directly linking this increase to biodiversity loss is challenging, the research on pollen offers crucial insights into how environmental changes impact patients with pollen allergies. This paper explores the complex relationship between declining biodiversity and type 1 pollen allergies from 1998 to 2022 by synthesizing the scientific insights using the mapping software VOSviewer version 1.6.19. The graphical representation provides a visual overview of the evolution of the research on pollen and biodiversity aspects combined, showing a shift from localized studies to global, interdisciplinary approaches. The research in this field has expanded significantly, particularly since 2010, with European countries leading the scholarly contributions. Pollen allergy has become a key intersection of public health and environmental science. This bibliometric review underscores the critical need for enhanced interdisciplinary research and international collaboration to address these interconnected challenges, promoting sustainable solutions in a rapidly advancing field.
Effects of Working Capital Management on Small-Sized Businesses in Competitive Environments with Economic Policy Uncertainty—A Case Study Applied to Chilean Companies
Authors: Gallegos Mardones Juan Alejandro , Moraga-Flores Hugo Alejandro , Briones Soto Vanessa Paulina
Published: October 2024

Working capital is a strategic resource that not only enhances financial performance but also ensures the long-term sustainability of organizations, especially SMEs. In the context of evolving economic policies and the challenges of gender equity affecting Chilean companies, this study explores how economic policy risk (EPU) and CEO characteristics influence working capital, which are essential investments for sustainable growth. The analysis covers 12,839 SMEs from 2014 to 2019. Using a fixed-effects panel data model, the findings reveal that firms tend to increase their investment in working capital in response to rising economic policy uncertainty. However, the relationship follows a non-linear inverted U-shaped pattern, which suggests the existence of an investment optimum between working capital and the EPU. Considering the level of competition, companies increase their investment in working capital when the level of competition is higher. Regarding the gender and age of CEOs, it is observed that women invest less in working capital, as do young CEOs. These results underscore the importance of EPU, along with the gender and age of CEOs, as key factors in promoting sustainable working capital management.
Integrating Biofertilizers with Organic Fertilizers Enhances Photosynthetic Efficiency and Upregulates Chlorophyll-Related Gene Expression in Rice
Authors: Mthiyane Pretty , Aycan Murat , Mitsui Toshiaki
Published: October 2024

Biofertilizers offer a sustainable method for improving rice growth and productivity, yet their effects on the interaction between plant growth, photosynthetic activity, and gene expression remain under-researched. This study examines how biofertilizer influences rice physiology, focusing on photosynthetic regulation and expression of chlorophyll-related genes. Eight fertilizer treatments were applied: control (CNT), biofertilizer (BF), deactivated biofertilizer (DABF), rice straw (RS), rice straw with biofertilizer (RS+BF), organic fertilizer (OF), organic fertilizer with biofertilizer (OF+BF), and inorganic fertilizer (IOF). Plant height, tiller number, SPAD, NDVI, chlorophyll content, and photosynthesis rates were measured, while gene expression analysis was conducted using RT-qPCR. The OF+BF treatment produced the most significant results, leading to a 31% increase in plant height, a 135% increase in tiller number, and a 42% increase in chlorophyll content (SPAD values) compared to the control. Additionally, OF+BF enhanced photosynthetic efficiency by 74%, with the highest net photosynthetic rate of 48.23 μmol CO2 m−2 s−1. Gene expression analysis revealed that OF+BF upregulated key photosynthesis-related genes, such as OsChlD and OsCHLM, showing a 70% and 90% increase in expression. These findings highlight the potential of integrating biofertilizers with organic fertilizers to sustainably boost rice growth and productivity, contributing to global food security and climate change mitigation.
Comparing Confidence Intervals for the Mean of Symmetric and Skewed Distributions
Authors: Veljkovic Kristina
Published: October 2024

In context-aware decision analysis, mean can be an important measure, even when the distribution is skewed. Previous comparative studies showed that it is a real challenge to construct a confidence interval that performs well for highly skewed data. In this study, we propose new confidence intervals for the population mean based on Edgeworth expansion that include both skewness and kurtosis corrections. We compared existing and newly proposed confidence intervals for a range of samples from symmetric and skewed distributions of varying levels of kurtosis. Using Monte Carlo simulations, we evaluated the performance of these intervals based on the coverage probability, mean length, and standard deviation of the length. The proposed bootstrap Edgeworth-based confidence interval outperformed other confidence intervals in terms of coverage probability for both symmetric and skewed distributions and can be recommended for general use in practice.