bluuebunny/crossref_metadata_2025 huggingface dataset:
Self-Healable, Antimicrobial and Conductive Hydrogels Based on Dynamic Covalent Bonding with Silver Nanoparticles for Flexible Sensor
Authors: Qi Te , Liu Xuefeng , Zheng Nan , Huang Jie , Xiang Wenlong , Nie Yujin , Guo Zanru , Cai Baixue
Published: December 2024

Dynamic hydrogels have attracted considerable attention in the application of flexible electronics, as they possess injectable and self-healing abilities. However, it is still a challenge to combine high conductivity and antibacterial properties into dynamic hydrogels. In this work, we fabricated a type of dynamic hydrogel based on acylhydrazone bonds between thermo-responsive copolymer and silver nanoparticles (AgNPs) functionalized with hydrazide groups. The hybrid hydrogels exhibited sol–gel transition, self-healable, injectable and thermo-responsive abilities. The self-healing efficiency was over 92%. Moreover, the hydrogel displayed antimicrobial properties and high conductivity (6.85 S/m). Notably, the fabricated hydrogel-based sensors exhibited strain and temperature sensing (22.05%/°C) and could detect human motion and speech, and electrocardiographic (ECG) and electromyography (EMG) signals. Overall, this work provides a simple strategy to synthesize AgNPs-based dynamic hydrogels with multi-functions, and the hydrogels may find potential applications in antibacterial wearable electronics, health monitoring and speech recognition.
Temperature Profile from Parts Produced by Fused Filament Fabrication (FFF) Measured by In Situ Infrared Thermography
Authors: Conceição Marceli do N. da , Fonseca Henrique M. da , Thiré Rossana M. S. M.
Published: December 2024

Fused Filament Fabrication (FFF) is the most used additive manufacturing (AM) technique. Understanding the behavior of the in situ temperature profile during the cooling stage is crucial to enhancing the mechanical properties of the parts manufactured by FFF since adhesion between printed layers is strongly related to the polymer cooling rate. However, only some studies analyze each layer in detail. For such analysis, infrared thermographic cameras can be used as a tool for non-contact temperature measurement. Numerous variables in constructing the part offer potential for such investigation. This study may lead to the enhancement of the part manufactured and improvements in the 3D printer itself. In addition, the polymer matrix and the manufacturing software can also be optimized. This work aims to systematically evaluate the temperature profile along the deposited layers during the fabrication of three-dimensional parts using poly(lactic acid) (PLA) filament. An infrared camera was used for real-time temperature measurements, and the data were processed with MATLAB® as a function of time and part length. A difference of up to 30 °C was observed between the edges, and non-uniform temperature profiles were also observed at the beginning, middle, and end of the part manufacturing. The highest temperatures were observed at the side where the print nozzle positions itself for the base to descend to the next layer. Several strategies are proposed to enhance the temperature distribution during the cooling process.
Knowledge and Discernment: Reflections on the Integration of Biblical Studies and Spirituality
Authors: Hardin Leslie T.
Published: December 2024

In the introduction to The Violence of the Lamb: Martyrs as Agents of Divine Judgment in the Book of Revelation, Paul Middleton recounts that at the 2008 annual meeting of the Society of Biblical Literature, he was asked about the possible connections between John’s letters to the seven churches of Asia and modern ecclesiastical practice [...]
Old Wine in New Wineskins: Applying Computational Methods in New Testament Hermeneutics
Authors: Vrangbæk Christian Houth , Vrangbæk Eva Elisabeth Houth , Mortensen Jacob
Published: December 2024

New Testament studies has over the past years seen an increase in the use of digital methods, but some of the more advanced methods still lack proper integration. This article explores some of the advantages and disadvantages in employing computational/algorithmic approaches, such as so-called semantic models of word embedding and topic modelling analysis. The article is structured into three main parts. The first part (1) introduces the reader to the field of computational studies in literary, historical, and religious research areas and outlines the computational methods, namely topic modelling and word embedding. The second part, (2) showcases two computational tools in analyzing New Testament narratives. The third part (3) discusses and compares how the methodology of applying computational techniques can maintain and advance a focus on the historical and literary context of New Testament texts. The specific problem the article addresses is how computational methods can be wielded and not sacrifice the contact to the text and the historical context. We argue that applying computational methods in New Testament hermeneutics necessarily involves methodological pros and cons. These computationally assisted analyses can be regarded as old wine in new wineskins—classic, hermeneutical questions can be posed with new methods.
Selfhood and Individuality in Dōgen’s Thought
Authors: Raud Rein
Published: December 2024

The article addresses one of the central issues of Buddhist thought, the status of selfhood and individuality, as they are discussed in the work of the Japanese Zen thinker Dōgen (1200–1253). It discusses critically and rejects the widespread assumption that Dōgen postulates two levels of selfhood, that of the deluded individual and a transcendent True Self to the attainment of which one should aspire. On the basis of rigorous methodological principles, formulated at the outset, the article analyzes in detail the terminology Dōgen uses for selfhood and individuality and provides a comprehensive, coherent interpretational framework for the reading of a number of key passages that have usually been presented in support of the True Self theory.
The Issues of the Sixth Dalai Lama and the Transformation of Qing Information System on Tibet
Authors: Kung Ling-Wei
Published: December 2024

After having been deceived by the Géluk government about the death of the Fifth Dalai Lama for almost 15 years, the Qing empire decided to strengthen its surveillance on Tibet by deploying espionage networks operated by spy lamas based in Xining and Dartsédo on Sino–Tibetan borderlands. Accordingly, the Qing successfully intervened in the reincarnation system of Tibetan Buddhism by taking advantage of the Sixth Dalai Lama’s issues. By establishing a new system of espionage operated by a eunuch lama serving in the imperial court, the Qing finally deposed the Sixth Dalai Lama and secretly murdered him in 1706. The Sixth Dalai Lama’s death embodied the monumental transition that significantly shaped the destiny of Tibet, China, and Inner Asia in the following three centuries. By investigating the Sixth Dalai Lama’s controversies, this article sheds light on how the Qing dynasty embarked on constructing its imperial enterprise in Inner Asia based on intelligence collection and information manipulation. By using multilingual sources in Tibetan, Mongolian, Manchu, and Chinese, the present study shows how the Qing empire overcame the challenges of information deficiency and lingual differences by developing intelligence networks and multilingual mechanisms to consolidate its governance in Inner Asia.
An Ontology of the Word in Catalan Romanesque Culture
Authors: Puigarnau Alfons
Published: December 2024

The history of culture in Catalonia during the Romanesque period (9th–12th centuries) has often been written from a strongly positivist mentality, which is a reductionistic approach. Economic history has distorted this period’s intellectual and cultural history. This article presents a compelling analysis of a series of manuscripts from the monastery of Ripoll in the context of Catalonia’s visual and intellectual culture between the 10th and 12th centuries. These writings demonstrate the pivotal role of the arts of the word (dialectic, rhetoric, and grammar) in this cultural center of great European significance. They also illustrate the formative influence of this institution on Gerbert of Aurillac, who would become Pope Sylvester II and the fruitful period of Abbot Oliba. Other artworks and musical manuscripts contribute to understanding a profound ontology of the word in Catalonia and prepare the ground for its cultural renaissance in the 12th century.
Facies-Constrained Kriging Interpolation Method for Parameter Modeling
Authors: Nie Zhenbo , Feng Bo , Wang Huazhong , Wu Chengliang , Xu Rongwei , Ning Chao
Published: December 2024

In seismic exploration, establishing a reliable parameter model (such as velocity, density, impedance) is crucial for seismic migration imaging and reservoir characterization. The interpolation of well data to obtain a complete spatial model is an important aspect of parameter modeling. However, in practical applications, well data are often sparse and irregularly distributed, which complicates the accurate construction of subsurface parameter models. The Kriging method is an effective interpolation method based on discrete well data, but its theoretical assumptions do not meet the practical requirements in seismic exploration, resulting in low modeling accuracy. This article introduces seismic facies information into the Kriging method and proposes a novel parameter modeling method named the facies-constrained Kriging (FC-Kriging) method. The FC-Kriging method modifies the Euclidean distance metric used in Kriging so that the distance between two points depends not only on their spatial coordinates but also on their associated facies categories. The proposed method is a multi-information fusion method that integrates facies information based on well data, enabling good interpolation results even with a limited number of wells. The parameter modeling results based on the FC-Kriging method are more consistent with geological logic, exhibiting clearer boundary features and higher resolution. Furthermore, the FC-Kriging method does not introduce additional computational complexity, making it convenient to implement in a 3D situation. The FC-Kriging method is applied to the 2D Sigsbee model, the 3D Standford V reservoir model and F3 block field data. The results demonstrate its accuracy and effectiveness.
Climate Warming Controls Vegetation Growth with Increasing Importance of Permafrost Degradation in the Northern Hemisphere During 1982–2022
Authors: Liu Yadong , Wu Xiaodong , Wu Tonghua , Hu Guojie , Zou Defu , Qiao Yongping , Wei Xianhua , Fan Xiaoying , Yan Xuchun
Published: December 2024

In permafrost regions, vegetation growth is influenced by both climate conditions and the effects of permafrost degradation. Climate factors affect multiple aspects of the environment, while permafrost degradation has a significant impact on soil moisture and nutrient availability, both of which are crucial for ecosystem health and vegetation growth. However, the quantitative analysis of climate and permafrost remains largely unknown, hindering our ability to predict future vegetation changes in permafrost regions. Here, we used statistical methods to analyze the NDVI change in the permafrost region from 1982 to 2022. We employed correlation analysis, multiple regression residual analysis and partial least squares structural equation modeling (PLS-SEM) methods to examine the impacts of different environmental factors on NDVI changes. The results show that the average NDVI in the study area from 1982 to 2022 is 0.39, with NDVI values in 80% of the area remaining stable or exhibiting an increasing trend. NDVI had the highest correlation with air temperature, averaging 0.32, with active layer thickness coming in second at 0.25. Climate change plays a dominant role in NDVI variations, with a relative contribution rate of 89.6%. The changes in NDVI are positively influenced by air temperature, with correlation coefficients of 0.92. Although the active layer thickness accounted for only 7% of the NDVI changes, its influence demonstrated an increasing trend from 1982 to 2022. Overall, our results suggest that temperature is the primary factor influencing NDVI variations in this region.
Leaf Water Potential in a Mixed Mediterranean Forest from Machine Learning and Unmanned Aerial Vehicle (UAV)-Based Hyperspectral Imaging
Authors: Fishman Netanel , Yungstein Yehuda , Yaakobi Assaf , Obersteiner Sophie , Rez Laura , Mulero Gabriel , Michael Yaron , Klein Tamir , Helman David
Published: December 2024

Leaf water potential (ψleaf) is a key indicator of plant water status, but its measurement is labor-intensive and limited in spatial coverage. While remote sensing has emerged as a useful tool for estimating vegetation water status, ψleaf remains unexplored, particularly in mixed forests. Here, we use spectral indices derived from unmanned aerial vehicle-based hyperspectral imaging and machine learning algorithms to assess ψleaf in a mixed, multi-species Mediterranean forest comprised of five key woody species: Pinus halepensis, Quercus calliprinos, Cupressus sempervirens, Ceratonia siliqua, and Pistacia lentiscus. Hyperspectral images (400–1000 nm) were acquired monthly over one year, concurrent with ψleaf measurements in each species. Twelve spectral indices and thousands of normalized difference spectral index (NDSI) combinations were evaluated. Three machine learning algorithms—random forest (RF), extreme gradient boosting (XGBoost), and support vector machine (SVM)—were used to model ψleaf. We compared the machine learning model results with linear models based on spectral indices and the NDSI. SVM, using species information as a feature, performed the best with a relatively good ψleaf assessment (R2 = 0.53; RMSE = 0.67 MPa; rRMSE = 28%), especially considering the small seasonal variance in ψleaf (±σ = 0.8 MPa). Predictions were best for Cupressus sempervirens (R2 = 0.80) and Pistacia lentiscus (R2 = 0.49), which had the largest ψleaf variances (±σ > 1 MPa). Aggregating data at the plot scale in a ‘general’ model markedly improved the ψleaf model (R2 = 0.79, RMSE = 0.31 MPa; rRMSE = 13%), providing a promising tool for monitoring mixed forest ψleaf. The fact that a non-species-specific, ‘general’ model could predict ψleaf implies that such a model can also be used with coarser resolution satellite data. Our study demonstrates the potential of combining hyperspectral imagery with machine learning for non-invasive ψleaf estimation in mixed forests while highlighting challenges in capturing interspecies variability.
Low-Coherence Integrated Optical Interferometer for Fibre Optic Sensors
Authors: Volkov Petr , Bobrov Alexander , Vyazankin Oleg , Gorshkov Alexey , Goryunov Alexander , Lemeshevskaya Glafira , Lukyanov Andrey , Nezhdanov Aleksey , Semikov Daniil , Sidorenko Kirill
Published: December 2024

This paper proposes and implements a novel scheme for recording signals from fibre optic sensors based on tandem low-coherence interferometry with an integrated optical reference interferometer. The circuit allows precision control of the phase shift. Additionally, the paper illustrates the potential for detecting vibration and object deformation using fibre optic Fabry–Perot sensors connected to the registration system.
Photoreconfigurable Metasurface for Independent Full-Space Control of Terahertz Waves
Authors: Jiang Zhengxuan , Ding Guowen , Luo Xinyao , Wang Shenyun
Published: December 2024

We present a novel photoreconfigurable metasurface designed for independent and efficient control of electromagnetic waves with identical incident polarization and frequency across the entire spatial domain. The proposed metasurface features a three-layer architecture: a top layer incorporating a gold circular split ring resonator (CSRR) filled with perovskite material and dual C-shaped perovskite resonators; a middle layer of polyimide dielectric; and a bottom layer comprising a perovskite substrate with an oppositely oriented circular split ring resonator filled with gold. By modulating the intensity of a laser beam, we achieve autonomous manipulation of incident circularly polarized terahertz waves in both transmission and reflection modes. Simulation results demonstrate that the metasurface achieves a cross-polarized transmission coefficient of 0.82 without laser illumination and a co-polarization reflection coefficient of 0.8 under laser illumination. Leveraging the geometric phase principle, adjustments to the rotational orientation of the reverse split ring and dual C-shaped perovskite structures enable independent control of transmission and reflection phases. Furthermore, the proposed metasurface induces a +1 order orbital angular momentum in transmission and +2 order in reflection, facilitating beam deflection through metasurface convolution principles. Imaging using metasurface digital imaging technology showcases patterns “NUIST” in reflection and “LOONG” in transmission, illustrating the metasurface design principles via the proposed metasurface. The proposed metasurface’s capability for full-space control and reconfigurability presents promising applications in advanced imaging systems, dynamic beam steering, and tunable terahertz devices, highlighting its potential for future technological advancements.
Implantable Passive Sensors for Biomedical Applications
Authors: Kassanos Panagiotis , Hourdakis Emmanouel
Published: December 2024

In recent years, implantable sensors have been extensively researched since they allow localized sensing at an area of interest (e.g., within the vicinity of a surgical site or other implant). They allow unobtrusive and potentially continuous sensing, enabling greater specificity, early warning capabilities, and thus timely clinical intervention. Wireless remote interrogation of the implanted sensor is typically achieved using radio frequency (RF), inductive coupling or ultrasound through an external device. Two categories of implantable sensors are available, namely active and passive. Active sensors offer greater capabilities, such as on-node signal and data processing, multiplexing and multimodal sensing, while also allowing lower detection limits, the possibility to encode patient sensitive information and bidirectional communication. However, they require an energy source to operate. Battery implantation, and maintenance, remains a very important constraint in many implantable applications even though energy can be provided wirelessly through the external device, in some cases. On the other hand, passive sensors offer the possibility of detection without the need for a local energy source or active electronics. They also offer significant advantages in the areas of system complexity, cost and size. In this review, implantable passive sensor technologies will be discussed along with their communication and readout schemes. Materials, detection strategies and clinical applications of passive sensors will be described. Advantages over active sensor technologies will be highlighted, as well as critical aspects related to packaging and biocompatibility.
Gold–Mercury–Platinum Alloy for Light-Enhanced Electrochemical Detection of Hydrogen Peroxide
Authors: Wei Yunping , Li Runze , Lin Meng
Published: December 2024

In this study, a simple and easy synthesis strategy to realize the modification of AuHgPt nanoalloy materials on the surface of ITO glass at room temperature is presented. Gold nanoparticles as templates were obtained by electrochemical deposition, mercury was introduced as an intermediate to form an amalgam, and then a galvanic replacement reaction was utilized to successfully prepare gold–mercury–platinum (AuHgPt) nanoalloys. The obtained alloys were characterized by scanning electron microscopy, UV–Vis spectroscopy, X-ray photoelectron spectroscopy and X-ray diffraction techniques. The electrochemical sensing performance of the AuHgPt-modified electrode for hydrogen peroxide was evaluated by cyclic voltammetry and chronoamperometry. Under light conditions, the AuHgPt-modified electrode exhibited a desirable current response in the detection of hydrogen peroxide due to the synergistic effect of the localized surface plasmon resonance effect inherent in gold nanoparticles, and this synergistic effect improved the sensitivity of hydrogen peroxide detection. Meanwhile, the AuHgPt-modified electrode also exhibited better stability and reproducibility, which makes the modified electrode have great potential for various applications in the field of electrochemical sensing.
Predicting Sensory and Affective Tactile Perception from Physical Parameters Obtained by Using a Biomimetic Multimodal Tactile Sensor
Authors: Ikejima Toshiki , Mizukoshi Koji , Nonomura Yoshimune
Published: December 2024

Tactile perception plays a crucial role in the perception of products and consumer preferences. This perception process is structured in hierarchical layers comprising a sensory layer (soft and smooth) and an affective layer (comfort and luxury). In this study, we attempted to predict the evaluation score of sensory and affective tactile perceptions of materials using a biomimetic multimodal tactile sensor that mimics the active touch behavior of humans and measures physical parameters such as force, vibration, and temperature. We conducted sensory and affective descriptor evaluations on 32 materials, including cosmetics, textiles, and leather. Using the physical parameters obtained by the biomimetic multimodal tactile sensor as explanatory variables, we predicted the scores of the sensory and affective descriptors in 10 regression models. The bagging regressor demonstrated the best performance, achieving a coefficient of determination (R2) of >0.6 for fourteen of nineteen sensory and eight of twelve affective descriptors. The present model exhibited particularly high prediction accuracy for sensory descriptors such as “moist” and “elastic”, and for affective descriptors such as “pleasant” and “like”. These findings suggest a method to support efficient tactile design in product development across various industries by predicting tactile descriptor scores using physical parameters from a biomimetic tactile sensor.
Hybrid Materials Based on Carbon Nanotubes and Tetra- and Octa-Halogen-Substituted Zinc Phthalocyanines: Sensor Response Toward Ammonia from the Quantum-Chemical Point of View
Authors: Krasnov Pavel , Ivanova Victoria , Klyamer Darya , Bonegardt Dmitry , Fedorov Aleksandr , Basova Tamara
Published: December 2024

This paper presents the results of quantum-chemical modeling performed by the Density Functional-Based Tight Binding (DFTB) method to investigate the change in the band structure of hybrid materials based on carbon nanotubes and unsubstituted, tetra-, or octa-halogen-substituted zinc phthalocyanines upon the adsorption of ammonia molecules. The study showed that the electrical conductivity of these materials and its changes in the case of interaction with ammonia molecules depend on the position of the impurity band formed by the orbitals of macrocycle atoms relative to the forbidden energy gap of the hybrids. The sensor response of the hybrids containing halogenated phthalocyanines was lower by one or two orders of magnitude, depending on the number of substituents, compared to the hybrid with unsubstituted zinc phthalocyanine. This result was obtained by calculations performed using the nonequilibrium Green’s functions (NEGF) method, which demonstrated a change in the electrical conductivity of the hybrids upon the adsorption of ammonia molecules. The analysis showed that in order to improve the sensor characteristics of CNT-based hybrid materials, preference should be given to those phthalocyanines in which substituents contribute to an increase in HOMO energy relative to the unsubstituted macrocycles.
Road Traffic Gesture Autonomous Integrity Monitoring Using Fuzzy Logic
Authors: Ampadu Kwame Owusu , Huebner Michael
Published: December 2024

Occasionally, four cars arrive at the four legs of an unsignalized intersection at the same time or almost at the same time. If each lane has a stop sign, all four cars are required to stop. In such instances, gestures are used to communicate approval for one vehicle to leave. Nevertheless, the autonomous vehicle lacks the ability to participate in gestural exchanges. A sophisticated in-vehicle traffic light system has therefore been developed to monitor and facilitate communication among autonomous vehicles and classic car drivers. The fuzzy logic-based system was implemented and evaluated on a self-organizing network comprising eight ESP32 microcontrollers, all operating under the same program. A single GPS sensor connects to each microcontroller that also manages three light-emitting diodes. The ESPNow broadcast feature is used. The system requires no internet service and no large-scale or long-term storage, such as the driving cloud platform, making it backward-compatible with classical vehicles. Simulations were conducted based on the order and arrival direction of vehicles at three junctions. Results have shown that autonomous vehicles at four-legged intersections can now communicate with human drivers at a much lower cost with precise position classification and lane dispersion under 30 s.
A Bibliometric Review of Brain–Computer Interfaces in Motor Imagery and Steady-State Visually Evoked Potentials for Applications in Rehabilitation and Robotics
Authors: Chio Nayibe , Quiles-Cucarella Eduardo
Published: December 2024

In this paper, a bibliometric review is conducted on brain–computer interfaces (BCI) in non-invasive paradigms like motor imagery (MI) and steady-state visually evoked potentials (SSVEP) for applications in rehabilitation and robotics. An exploratory and descriptive approach is used in the analysis. Computational tools such as the biblioshiny application for R-Bibliometrix and VOSViewer are employed to generate data on years, sources, authors, affiliation, country, documents, co-author, co-citation, and co-occurrence. This article allows for the identification of different bibliometric indicators such as the research process, evolution, visibility, volume, influence, impact, and production in the field of brain–computer interfaces for MI and SSVEP paradigms in rehabilitation and robotics applications from 2000 to August 2024.
Predictive Forwarding Rule Caching for Latency Reduction in Dynamic SDN
Authors: Um Doosik , Park Hyung-Seok , Ryu Hyunho , Park Kyung-Joon
Published: December 2024

In mission-critical environments such as industrial and military settings, the use of unmanned vehicles is on the rise. These scenarios typically involve a ground control system (GCS) and nodes such as unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs). The GCS and nodes exchange different types of information, including control data that direct unmanned vehicle movements and sensor data that capture real-world environmental conditions. The GCS and nodes communicate wirelessly, leading to loss or delays in control and sensor data. Minimizing these issues is crucial to ensure nodes operate as intended over wireless links. In dynamic networks, distributed path calculation methods lead to increased network traffic, as each node independently exchanges control messages to discover new routes. This heightened traffic results in internal interference, causing communication delays and data loss. In contrast, software-defined networking (SDN) offers a centralized approach by calculating paths for all nodes from a single point, reducing network traffic. However, shifting from a distributed to a centralized approach with SDN does not inherently guarantee faster route creation. The speed of generating new routes remains independent of whether the approach is centralized, so SDN does not always lead to faster results. Therefore, a key challenge remains: determining how to create new routes as quickly as possible even within an SDN framework. This paper introduces a caching technique for forwarding rules based on predicted link states in SDN, which was named the CRIMSON (Cashing Routing Information in Mobile SDN Network) algorithm. The CRIMSON algorithm detects network link state changes caused by node mobility and caches new forwarding rules based on predicted topology changes. We validated that the CRIMSON algorithm consistently reduces end-to-end latency by an average of 88.96% and 59.49% compared to conventional reactive and proactive modes, respectively.
Electrochemical Detection of Cadmium Using a Bismuth Film Deposited on a Brass Electrode
Authors: Radovanović Milan B. , Petrović Mihajlović Marija B. , Simonović Ana T. , Tasić Žaklina , Antonijević Milan M.
Published: December 2024

Cadmium is one of the most dangerous pollutants found in the environment, where it exists mainly due to human activities. High cadmium concentrations can cause serious problems, which is why the detection and determination of Cd is one of the most important tasks. Electroanalytical methods provide rapid and accurate results in the detection of cadmium in various solutions. In this study, the possibility of using a bismuth film electrode deposited on a brass surface and electroanalytical techniques for the detection of cadmium is investigated. The bismuth film was deposited on the surface of the brass electrode using a chronoamperometric technique. Cyclic voltammetry and electrochemical impedance spectroscopy were used to characterize the synthesized bismuth film electrode. The current peaks obtained by anodic square-wave stripping voltammetry under optimized conditions showed a linear relationship in the investigated concentration range of cadmium. The study of the interference of different cations (Cr3+, Mn2+, Zn2+, Ca2+, K+, Mg2+ and Na+) showed that the tested cations have no influence on the determination of Cd2+ ions in the investigated solution. This finding provides a good opportunity for the use of the synthesized electrode in real samples.
Three-Dimensional Reconstruction of Road Structural Defects Using GPR Investigation and Back-Projection Algorithm
Authors: Wang Lutai , Liu Zhen , Gu Xingyu , Wang Danyu
Published: December 2024

Ground-Penetrating Radar (GPR) has demonstrated significant advantages in the non-destructive detection of road structural defects due to its speed, safety, and efficiency. This paper proposes a three-dimensional (3D) reconstruction method for GPR images, integrating the back-projection (BP) imaging algorithm to accurately determine the size, location, and other parameters of road structural defects. Initially, GPR detection images were preprocessed, including direct wave removal and wavelet denoising, followed by the application of the BP algorithm to effectively restore the defect’s location and size. Subsequently, a 3D data set was constructed through interpolation, and the effective reflection data were extracted by using a clustering algorithm. This algorithm distinguished the effective reflection data from the background data by determining the distance threshold between the data points. The 3D imaging of the defect was then performed in MATLAB. The proposed method was validated using both gprMax simulations and laboratory test models. The experimental results indicate that the correlation between the reconstructed and actual defects was approximately 0.67, demonstrating the method’s efficacy in accurately achieving the 3D reconstruction of road structural defects.
Partial Attention in Global Context and Local Interaction for Addressing Noisy Labels and Weighted Redundancies on Medical Images
Authors: Nguyen Minh Tai Pham , Phan Tran Minh Khue , Nakano Tadashi , Tran Thi Hong , Nguyen Quoc Duy Nam
Published: December 2024

Recently, the application of deep neural networks to detect anomalies on medical images has been facing the appearance of noisy labels, including overlapping objects and similar classes. Therefore, this study aims to address this challenge by proposing a unique attention module that can assist deep neural networks in focusing on important object features in noisy medical image conditions. This module integrates global context modeling to create long-range dependencies and local interactions to enable channel attention ability by using 1D convolution that not only performs well with noisy labels but also consumes significantly less resources without any dimensionality reduction. The module is then named Global Context and Local Interaction (GCLI). We have further experimented and proposed a partial attention strategy for the proposed GCLI module, aiming to efficiently reduce weighted redundancies. This strategy utilizes a subset of channels for GCLI to produce attention weights instead of considering every single channel. As a result, this strategy can greatly reduce the risk of introducing weighted redundancies caused by modeling global context. For classification, our proposed method is able to assist ResNet34 in achieving up to 82.5% accuracy on the Chaoyang test set, which is the highest figure among the other SOTA attention modules without using any processing filter to reduce the effect of noisy labels. For object detection, the GCLI is able to boost the capability of YOLOv8 up to 52.1% mAP50 on the GRAZPEDWRI-DX test set, demonstrating the highest performance among other attention modules and ranking second in the mAP50 metric on the VinDR-CXR test set. In terms of model complexity, our proposed GCLI module can consume fewer extra parameters up to 225 times and has inference speed faster than 30% compared to the other attention modules.
Design and Evaluation of a Low-Cost Mount for Attaching a Laser Tracker’s SMR to a Robot Flange
Authors: Stöckl Florian , Müller Silvan , Strand Marcus , Gardill Markus
Published: December 2024

Robot calibration and modelling measurements are commonly performed using a laser tracker. To capture three-dimensional positions, a SMR is attached to the robot. While some researchers employ adhesive bonds for this purpose, such methods often result in inaccurate, unstable and non-repeatable SMR positioning, adversely affecting measurement precision and the traceability of research outcomes. To address these challenges, we investigated alternative methods for attaching an SMR to a robot’s flange to achieve both accuracy and repeatability. Additionally, we analysed measurement errors introduced when using a tool to attach the SMR to the flange. As a solution, we developed a 3D-printed mount designed for attachment to the flange. The mount’s accuracy was evaluated by assessing its eccentricity and the repeatability of the SMR placement. Experimental results demonstrated that the mount achieved an eccentricity radius of 0.35 mm and repeatability inaccuracies of X=0.075mm, Y=0.328mm, and Z=0.485mm. These values indicate that the mount provides sufficient accuracy to support calibration processes, ensures research traceability, and serves as a viable replacement for adhesive bonds.
Development of a Comprehensive Approach to Quality Control of Dermorphin Derivative—Representative of Synthetic Opioid Peptides with Non-Narcotic Type of Analgesia
Authors: Sukhanova Vasilisa A. , Uspenskaya Elena V. , Ainaz Safdari , Quynh Hoang Thi Ngoc , Timofeev Aleksey A.
Published: December 2024

Peptides occupy a significant share of the pharmaceutical market and are among the top-200 selling drugs in the group of non-insulin drugs with analgesic, antibacterial and cardiovascular effects. The aim of this work is to develop a comprehensive analytical approach for quality control of novel synthetic peptides with non-narcotic types of analgesia and to provide docking simulations of dermorphin complex formation at the μ-opioid receptor (MOR) binding site. The materials and methods used include the pharmaceutical substance dermorphin tetrapeptide (DMTP) (tyrosyl-D-arginyl-phenylalanyl-glycinamide); Fourier transform infrared spectroscopy (FT-IR); static and dynamic laser light scattering (DLS, LALLS); scanning optical microscopy (SEM); X-ray fluorescence elements analysis; polarimetry for optical activity determining; and Spirotox method for sample biotesting. FT-IR-Spectra indicated specific amino acid chemical groups in the tetrapeptide sequence at 3300–2700 cm−1, 1670 cm−1. UV-absorption spectra of aqueous solutions of dermorphin tetrapeptide showed an absorption maximum at 275 nm, which is in good agreement with the presented spectrum of the bovine serum albumin (BSA) standard; the Pearson’s r of calibration line “A-C%” in 0.0125% to 0.0500% concentration range is 0.999; and the calculated specific extinction value E1cm 1% = 18.38 ± 0.23. Of the 11 elements detected by X-rays, the elements copper (Cu) and cobalt (Co) have the highest X-ray intensity. Dispersion characteristics of dermorphin solutions were studied in the submicron and micron range. Conglomerates and druzes were detected by SEM, ranging in size from 2 µm to 100 µm. The specific optical activity index was calculated αD20 = +36.18 ± 2.04 [°·mL·g−1·dm−1], according to Biot’s Law. Additionally, the orientation and conformation of the dermorphin molecule in the active binding site of the 8E0G receptor were predicted using molecular modeling, revealing that the contact area affects the key amino acid residue arginine (ARG 182). This comprehensive approach to analytical methods for qualitative and quantitative analysis of dermorphin tetrapeptide can be applied in pharmacies to enhance the understanding of its biological activity and aid in the development of regulatory documentation for a new, non-narcotic analgesic based on the dermorphin tetrapeptide.
CO2/CH4 and CO2/CO Selective Pebax-1657 Based Composite Hollow Fiber Membranes Prepared by a Novel Dip-Coating Technique
Authors: Karousos Dionysios S. , Theodorakopoulos George V. , Chiesa Francesco , Barbe Stéphan , Bouroushian Mirtat , Favvas Evangelos P.
Published: December 2024

A novel and innovative method was developed to fabricate defect-free composite hollow fiber (HF) membranes using drop-casting under continuous flow. The synthesized Pebax-1657—based membranes were examined for gas separation processes, focusing on the separation of CO2 from CH4 and CO gases. The separation performance of the membranes was rigorously assessed under realistic binary gas mixture conditions to evaluate their selectivity and performance. The effect of pressure on separation performance was systematically investigated, with transmembrane pressures up to 10 bar being applied at a temperature of 298 K. Remarkable CO2/CH4 selectivities of up to 110 and CO2/CO selectivities of up to 48 were achieved, demonstrating the robustness and effectiveness of these composite HF membranes, suggesting their suitability for high-performance gas separation processes under varying operational conditions. Overall, this study introduces a novel approach for scaling up the fabrication of HF membranes and provides valuable insights into their application in CO2 separation technologies, offering the potential for advancements in areas such as natural gas processing and carbon capture from CO-containing streams.
Kinetics of Supercritical CO2 Extraction from Burrito (Aloysia polystachya) Leaves and Sucupira-Preta (Bowdichia virgilioides) Seeds
Authors: Vieira Gabrielle Vaz , Souza Michel Rubens dos Reis , Hiranobe Carlos Toshiyuki , Goncalves José Eduardo , Moritz Cristiane Mengue Feniman , Sakai Otávio Akira , e Silva Leila Maria Sotocorno , da Silva Michael Jones , da Silva Erivaldo Antônio , dos Santos Renivaldo José , da Silva Edson Antônio , Cardozo-Filho Lucio , Ferreira-Pinto Leandro
Published: December 2024

This study investigated the application of supercritical carbon dioxide (CO2) for the extraction of essential oils from plant materials with anxiolytic potential, focusing on the leaves of burrito (Aloysia polystachya) and the seeds of sucupira-preta (Bowdichia virgilioides). The supercritical extraction technique was chosen for its ability to produce high-purity extracts without residual solvents and to reduce the environmental impact. This study evaluated the influence of temperature (40 °C, 50 °C, and 60 °C) and pressure (22 MPa, 25 MPa, and 28 MPa) on extraction efficiency using a 22 factorial design with triplicates at the central point. The maximum yields were 1.2% for burrito leaves and 4.2% for sucupira-preta seeds. Despite their relatively low yields, the extracts contained a diverse range of chemical compounds, including fatty acids (oleic, linoleic, and palmitic acids), squalene, β-carotene, vitamin E, and other bioactive molecules with antioxidant, anti-inflammatory, and immunomodulatory properties. Statistical analysis demonstrated that pressure was the most influential factor affecting yield, whereas temperature played a secondary role. The Sovová kinetic model provided a good fit for the extraction curves, with determination coefficients (R2) above 0.95, thus validating the efficiency of the method. These results highlight the pharmaceutical potential of these extracts, particularly for therapeutic and anxiolytic purposes.
¿Dónde Vive la Ciencia en su Comunidad?: How a Community Is Using Photovoice to Reclaim Local Green Spaces
Authors:   Espacio: Familias y Comunidad
Published: December 2024

The ¿Dónde Vive la Ciencia en su Comunidad? (where does science live in your community?) photovoice project is a community-based participatory research project that investigates the presence and influence of science within local environments. In collaboration with researchers, science, technology, engineering, mathematics (STEM) educators, and community members from the Latine community in Corona, Queens, the project investigated where science is found in our communities. Community researchers used photography to document their surroundings and identified key themes related to the role of science through technology, community health, safety, and wellness. The photovoice method elevated social justice issues through critical dialog, creating opportunities for change through collective action. Among the critical issues discussed were urban planning, specifically the impacts of gentrification on the local community and the possibilities that greening offered as a site of agency, multigenerational learning, and resistance through ways of knowing. Community researchers examined the dual nature of STEM as both a tool of control and a means for justice, interrogating whose voices and experiences are prioritized in decision-making processes. Establishing shared green spaces emerged as an act of epistemic disobedience and resistance for sustaining community health and cultural identity. The project highlights how collaborative, community-led initiatives promote the reclamation of political power through collective action and disrupt colonizing forces, offering actionable recommendations for policy, research, and practice to guide justice-oriented change.
Biased Perception of Macroecological Findings Triggered by the IPCC—The Example of Wildfires
Authors: Hobohm Carsten , Müller-Benedict Volker
Published: December 2024

Global change and disturbance ecology, including the risks and benefits of wildfires for humans, sustainability of ecosystems and biodiversity, is a current research topic in applied science. Fires and their impacts are often considered in the context of climate change, carbon dioxide emissions and air pollution. Despite a significant decline in wildfires at the global scale in recent decades (cf. Global Wildfire Information System (GWIS)), it is a widespread conviction that the burned area is increasing due to global warming. In an attempt to identify how this discrepancy has arisen, we analysed IPCC reports from 2018–2023 via text mining including word frequency analyses and compared considerations about wildfires and fire weather with findings from ecology and public information on the internet. Both a negativity bias and repetition bias were identified. Numerous examples of disasters and models indicating a global increase of wildfires are composed of alarming messages. Examples of decreasing wildfires and the global decline are much less frequently communicated. Important facts are ignored, especially in summaries for policymakers. Measured against fire-ecological conditions and benefits for the nature, alarming trends and risks due to climate change are exaggerated. We therefore call for a comprising and differentiated reflection of ecological conditions and processes in the future.
The Role and Drivers of Cooperation in Managing Hydraulic Infrastructures for Sustainable Mangrove Rice Production in Guinea-Bissau
Authors: Leunda Martiarena Merlin , Céspedes Jesus , Varanda Marta , Merkohasanaj Matilda , dos Santos Bissanagha Antonio , Temudo Marina Padrão
Published: December 2024

Mangrove Swamp Rice is a unique labour-, time-, and knowledge-intensive farming system across West Africa requiring a complex water management through dikes, canals, and pipes. Cooperation is crucial in the socio-spatial and temporal organisation of water management, helping mitigate risks like saltwater intrusion, prolonged submersion, and drying of paddies, particularly intensified by climate change. We adopted a mixed-methods approach integrating grounded theory with case study design and multi-level analysis and employed several tools, such as social network analysis, a land tenure register, a digital elevation model, and a machine learning model. This research strategy allowed us to gain an in-depth understanding of the complex socio-ecological system in water management. Our study examined the benefits of cooperation for water infrastructure management, highlighting its critical role in routine monitoring and repair, specialised technical advice, and annual belt dike maintenance. Within the large array of factors influencing cooperation, key drivers, such as spatial proximity and farmers’ technical knowledge, labour ethics, and fame, emerged and are discussed. Our findings provide important insights into the social organisation of “traditional” societies and offer valuable guidance for development practitioners, emphasising the importance of involving reputed farmers for sustainable socio-technical adaptation.
Life Cycle CO2 Emissions and Techno-Economic Analysis of Wood Pellet Production and CHP with Different Plant Scales and Sawdust Drying Processes
Authors: Koido Kenji , Konno Daichi , Sato Michio
Published: December 2024

This study presents a life cycle assessment (LCA) and economic analysis of wood pellet production and utilisation in gasification combined heat and power (CHP) systems, focusing on optimising the drying process and evaluating the impacts of varying plant scales. In line with Japan’s target of achieving net-zero emissions by 2050, the research examines primary energy demand (PED), CO2 emissions, and financial viability across the wood pellet production (gate-to-gate) and CHP energy generation (gate-to-grave) stages. The results reveal that the drying process accounts for 35–39% of the total energy consumption in wood pellet production, with the heat source significantly influencing PED and CO2 emissions. Systems employing wood-fired boilers and wood pellet CHP for drying achieve reductions in PED by 12–26% and CO2 emissions by 14–31% compared to the conventional grid-supplied drying process. Economic analysis reveals that scaling up production enhances financial performance, with net income increasing by up to 20% and payback periods reducing to approximately 10 years in facilities producing 2.5 tons of wood pellets per hour. These findings highlight the critical role of optimised drying processes, plant scalability, and efficient supply chains in advancing sustainable wood pellet-based bioenergy systems that support Japan’s renewable energy targets.