bluuebunny/crossref_metadata_2025 huggingface dataset:
Lyophilized Polyvinyl Alcohol and Chitosan Scaffolds Pre-Loaded with Silicon Dioxide Nanoparticles for Tissue Regeneration
Authors: Niebles Navas Andrés Felipe , Araujo-Rodríguez Daniela G. , Valencia-Llano Carlos-Humberto , Insuasty Daniel , Delgado-Ospina Johannes , Navia-Porras Diana Paola , Zapata Paula A. , Albis Alberto , Grande-Tovar Carlos David
Published: August 2024

Materials with a soft tissue regenerative capacity can be produced using biopolymer scaffolds and nanomaterials, which allow injured tissue to recover without any side effects or limitations. Four formulations were prepared using polyvinyl alcohol (PVA) and chitosan (CS), with silicon dioxide nanoparticles (NPs-SiO2) incorporated using the freeze-drying method at a temperature of −50 °C. TGA and DSC showed no change in thermal degradation, with glass transition temperatures around 74 °C and 77 °C. The interactions between the hydroxyl groups of PVA and CS remained stable. Scanning electron microscopy (SEM) indicated that the incorporation of NPs-SiO2 complemented the freeze-drying process, enabling the dispersion of the components on the polymeric matrix and obtaining structures with a small pore size (between 30 and 60 μm) and large pores (between 100 and 160 μm). The antimicrobial capacity analysis of Gram-positive and Gram-negative bacteria revealed that the scaffolds inhibited around 99% of K. pneumoniae, E. cloacae, and S. aureus ATCC 55804. The subdermal implantation analysis demonstrated tissue growth and proliferation, with good biocompatibility, promoting the healing process for tissue restoration through the simultaneous degradation and formation of type I collagen fibers. All the results presented expand the boundaries in tissue engineering and regenerative medicine by highlighting the crucial role of nanoparticles in optimizing scaffold properties.
Comparison of Eco-Friendly Ionic Liquids and Commercial Bio-Derived Lubricant Additives in Terms of Tribological Performance and Aquatic Toxicity
Authors: He Xin , Stevenson Louise M. , Kumara Chanaka , Mathews Teresa J. , Luo Huimin , Qu Jun
Published: August 2024

Approximately half of the lubricants sold globally find their way into the environment. The need for Environmentally Acceptable Lubricants (EALs) is gaining increased recognition. A lubricant is composed of a base oil and multiple functional additives. The literature has been focused on EAL base oils, with much less attention given to eco-friendly additives. This study presents the tribological performance and aquatic toxicity of four short-chain phosphonium-phosphate and ammonium-phosphate ionic liquids (ILs) as candidate anti-wear and friction-reducing additives for EALs. The results are benchmarked against those of four commercial bio-derived additives. The four ILs, at a mere 0.5 wt% concentration in a synthetic ester, demonstrated a 30–40% friction reduction and >99% wear reduction, superior to the commercial baselines. More impressively, all four ILs showed significantly lower toxicity than the bio-derived products. In an EPA-standard chronic aquatic toxicity test, the sensitive model organism, Ceriodaphnia dubia, had 90–100% survival when exposed to the ILs but 0% survival in exposure to the bio-derived products at the same concentration. This study offers scientific insights for the future development of eco-friendly ILs as lubricant additives.
Maximizing Bioactive Compound Extraction from Mandarin (Citrus reticulata) Peels through Green Pretreatment Techniques
Authors: Kalompatsios Dimitrios , Ionescu Alexandra-Ioana , Athanasiadis Vassilis , Chatzimitakos Theodoros , Mantiniotou Martha , Kotsou Konstantina , Bozinou Eleni , Lalas Stavros I.
Published: August 2024

This study explored the use of mandarin peels as an important source of health-promoting compounds by utilizing green methods (i.e., pulsed electric field and ultrasound-assisted extraction), along with conventional stirring. The impact of several extraction parameters, such as extraction duration, temperature, and solvent composition, on the recovery of bioactive compounds was evaluated through a response surface methodology. To identify the most effective conditions for all assays, a partial least-squares analysis was implemented. It was revealed that a combination of the above techniques was optimal at 80 °C for 30 min, with 75% v/v of ethanol in water as the extraction solvent. The concentration of bioactive compounds in the optimum extract had a total polyphenol content of 18.69 mg of gallic acid equivalents (GAE) per gram of dry weight (dw), and an ascorbic acid concentration of 18.25 mg/g dw. However, correlation analyses revealed a rather negative relationship between these bioactive compounds. The chromatographic analysis of optimum extracts supported this result by quantifying 20.53 mg/g dw of total individual polyphenols, with hesperidin being the dominant compound (13.98 mg/g dw). The antioxidant assays, including ferric-reducing antioxidant power and DPPH• inhibition activity, were measured at 123.21 and 65.12 μmol of ascorbic acid equivalents (AAE) per gram of dw, respectively. This research enhances the valorization of mandarin peels as a renewable source of bioactive compounds, providing the opportunity to generate high-added-value products from food waste in the food and pharmaceutical sectors.
Central Nervous System Disorders of Marine Mammals: Models for Human Disease?
Authors: Di Guardo Giovanni
Published: August 2024

This article deals with Central Nervous System (CNS) disorders of marine mammals as putative neuropathology and neuropathogenesis models for their human and, to some extent, their animal “counterparts” in a dual “One Health” and “Translational Medicine” perspective. Within this challenging context, special emphasis is placed upon Alzheimer’s disease (AD), provided that AD-like pathological changes have been reported in the brain tissue of stranded cetacean specimens belonging to different Odontocete species. Further examples of potential comparative pathology interest are represented by viral infections and, in particular, by “Subacute Sclerosing Panencephalitis” (SSPE), a rare neurologic sequela in patients infected with Measles virus (MeV). Indeed, Cetacean morbillivirus (CeMV)-infected striped dolphins (Stenella coeruleoalba) may also develop a “brain-only” form of CeMV infection, sharing neuropathological similarities with SSPE. Within this framework, the global threat of the A(H5N1) avian influenza virus is another major concern issue, with a severe meningoencephalitis occurring in affected pinnipeds and cetaceans, similarly to what is seen in human beings. Finally, the role of Brucella ceti-infected, neurobrucellosis-affected cetaceans as putative neuropathology and neuropathogenesis models for their human disease counterparts is also analyzed and discussed. Notwithstanding the above, much more work is needed before drawing the conclusion marine mammal CNS disorders mirror their human “analogues”.
The Casimir Effect in Finite-Temperature and Gravitational Scenarios
Authors: Bezerra Valdir Barbosa , Mota Herondy Francisco Santana , Lima Augusto P. C. M. , Alencar Geová , Muniz Celio Rodrigues
Published: August 2024

In this paper, we review some recent findings related to the Casimir effect. Initially, the thermal corrections to the vacuum Casimir energy density are calculated, for a quantum scalar field, whose modes propagate in the (3+1)-dimensional Euclidean spacetime, subject to a nontrivial compact boundary condition. Next, we analyze the Casimir effect induced by two parallel plates placed in a weak gravitational field background. Finally, we review the three-dimensional wormhole solutions sourced by the Casimir density and pressures associated with the quantum vacuum fluctuations of the Yang-Mills field.
Proteotoxicity and Apical Toxicity of Nicosulfuron to Danio rerio Embryos: A Comprehensive Assessment at Different Temperatures and pH
Authors: Li Zequn , Köhler Heinz-R. , Triebskorn Rita
Published: August 2024

In the present study, the toxicity of nicosulfuron to Danio rerio embryos was evaluated in three experiments through standardized toxicity tests according to OECD TG236 guidelines. In the first experiment, six concentrations of nicosulfuron (0, 0.1, 1, 10, 100, 1000 mg/L) were tested under optimal conditions (26 °C, pH 7.0) to assess the general sensitivity of zebrafish embryos to nicosulfuron. The second and third experiment examined the effects of different pH levels (5.0 and 9.0) and temperatures (21 °C and 31 °C) on the toxicity at four nicosulfuron concentrations (0, 10, 100, 1000 mg/L). Additionally, the sub-organismic effects of nicosulfuron on stress protein levels (Hsp70) of fish embryos were analyzed. Throughout the embryo experiments, no malformations were observed in all experiments. The survival rate exceeded 80% in all groups except for the 21 °C (pH 7.0) treatment groups. No significant effect of nicosulfuron on the survival rate was found at the same temperature or pH (p > 0.05). No significant difference in the heart rate was found among all nicosulfuron groups (p > 0.05) at 21 °C. The heart rate of fish embryos at 31 °C, pH 5.0 and pH 9.0 increased with nicosulfuron concentrations. Except for the pH 5.0 (26 °C) and 21 °C (pH 7.0) treatment groups, nicosulfuron was found to increase the hatching rate of embryos in other treatments; however, the corresponding times of action were different. At 21 °C (pH 7.0), the embryos did not hatch until 144 h post-fertilization. In terms of proteotoxicity, nicosulfuron was found to be more toxic to zebrafish embryos in the 21 °C, pH 5.0 and pH 9.0 treatment groups. However, at 31 °C, no significant difference in Hsp70 levels was found among all the different nicosulfuron concentrations (p > 0.05). Our results show that nicosulfuron exerts a weak toxicity to zebrafish embryos; however, this toxicity is amplified by inappropriate pH or temperature conditions.
Layer-by-Layer Assembling and Capsule Formation of Polysaccharide-Based Polyelectrolytes Studied by Whispering Gallery Mode Experiments and Confocal Laser Scanning Microscopy
Authors: Wagner Stefan , Olszyna Mateusz , Domac Algi , Heinze Thomas , Gericke Martin , Dähne Lars
Published: August 2024

The layer-by-layer (LbL) assembling of oppositely charged polyelectrolytes was studied using semi-synthetic polysaccharide derivatives, namely the polycations 6-aminoethylamino-6-deoxy cellulose (ADC) and cellulose (2-(ethylamino)ethylcarbamate (CAEC), as well as the polyanion cellulose sulfate (CS). The synthetic polymers poly(allylamine) (PAH) and poly(styrene sulfonate) (PSS) were employed as well for comparison. The stepwise adsorption process was monitored by whispering gallery mode (WGM) experiments and zeta-potential measurements. Distinct differences between synthetic- and polysaccharide-based assemblies were observed in terms of the quantitative adsorption of mass and adsorption kinetics. The LbL-approach was used to prepare µm-sized capsules with the aid of porous and non-porous silica particle templates. The polysaccharide-based capsule showed a switchable permeability that was not observed for the synthetic polymer materials. At ambient pH values of 7, low-molecular dyes could penetrate the capsule wall while no permeation occurred at elevated pH values of 8. Finally, the preparation of protein-loaded LbL-capsules was studied using the combination of CAEC and CS. It was shown that high amounts of protein (streptavidin and ovomucoid) can be encapsulated and that no leaking or disintegration of the cargo macromolecules occurred during the preparation step. Based on this work, potential use in biomedical areas can be concluded, such as the encapsulation of bioactive compounds (e.g., pharmaceutical compounds, antibodies) for drug delivery or sensing purposes.
Research on Modeling Method for Optimal Allocation of Wellhead Targets in Large Well Clusters
Authors: Wang Liupeng , Duan Haonan , Liu Zhikun , Peng Yuanchao , Liu Xuyang
Published: August 2024

The paper proposes a genetic ant colony algorithm that integrates genetic and ant colony algorithms, enhancing the heuristic function of the latter, to address target point distribution issues in large well clusters. This algorithm utilizes genetic algorithms for initial pheromone distribution and employs the ant colony algorithm to achieve rapid convergence. Introducing genetic operators in each iteration addresses the ant colony system’s drawbacks, including scarcity of initial pheromones, susceptibility to local optima, and slow convergence speed. The model aims to minimize the sum of horizontal displacement and intersections in line connections from wellheads to target points as its dual-objective function. It validates the effectiveness of the genetic ACO algorithm in optimizing target point allocation at wellheads through a case study, highlighting its advantages over traditional methods in reducing displacement, ensuring result stability, and preventing collisions.
The Moderating Role of Psychological Needs on the Relationship between Eudaimonia and Mental Health
Authors: Marcinko Ivana , Brdar Nina
Published: August 2024

Cultivating an eudaimonic lifestyle benefits mental health. However, it is not known under which circumstances the benefits of eudaimonia are the most pronounced. This cross-sectional study aimed to examine psychological needs (autonomy, competence, and relatedness) as the moderators of the effects eudaimonia has on mental health (general mental health, positive and negative mental health). In total, 328 young adults took part in this study, of which 36.6% were males, whose ages ranged between 18 and 30, with a median of 19 years (SD = 1.32). Questionnaires were used to measure eudaimonia (The Eudaimonia Scale from The Hedonic and Eudaimonic Motives for Activities), psychological needs (The Basic Psychological Needs Scale), and mental health (The Mental Health Inventory). To analyze the data, hierarchical regression analyses and analyses of variance have been performed. The results revealed that of all psychological needs, only the need for relatedness moderated the relationship between eudaimonia and general mental health and eudaimonia and negative mental health. Individuals with high eudaimonia and a highly satisfied need for relatedness had good general mental health and fewer mental health disturbances. The findings suggest that if one practices meaningful behaviors, the positive change in the mental health domain is greatest when those actions benefit not only this individual but others as well.
We Are Conscious of Caste, but Do We Live Our Lives through It? A Case Study of Gendered Caste Marginality
Authors: Kaur Parvinder
Published: August 2024

Despite the strict rejection of casteism by the Sikh faith, caste-based hierarchies are still a prevalent factor amongst Sikh diasporas within the UK. On the basis of ethnographic fieldwork amongst women whose caste is considered to occupy a lower status, this paper examines their experiences and explores how, over time, this has contributed to the construction of their identity. This article situates the women within a nexus of complex social and cultural factors, illuminating the representations of caste, gender and intergenerational change within Nottingham. An intersectional standpoint provided an analytical value in accentuating the sites where gender, caste and the mediation of honour intersected. The research shows a heterogeneity in the self-positioning of women vis-à-vis caste identity and shows a marked difference in attitudes between generations, denoting a depreciation in the significance of caste. Ultimately, while the respondents were conscious of their caste and of the historical prejudice against their caste, it is significant that they did not live their lives through it, as they internalised Sikhi as their core identity.
Rev. Dr. Muriel M. Spurgeon Carder (1922–2023): A Canadian Baptist Renaissance Woman
Authors: Heath Gordon L.
Published: August 2024

“Renaissance Woman” is a colloquial expression for someone who excels above and beyond normal in a wide variety of tasks, and Rev. Dr. Muriel Spurgeon Carder (1922–2023) deserves that title, for she was an ordained Canadian Baptist missionary who worked in churches, schools, and hospitals in India and Canada, as well as served as a professor, New Testament scholar, Bible translator (into Telegu), and hospital chaplain. She also published academic articles on textual issues related to New Testament manuscripts, on a biblical theology of sin, as well as on issues surrounding physical and mental challenges. Her personal accomplishments are striking among Baptists in India but also her Canadian denomination, the Baptist Convention of Ontario and Quebec (BCOQ). Carder recently passed away at the age of 100, and this research is an introduction to her life and legacy. There is much more to be explored regarding Carder, and my hope is that this brief article provides some impetus for more detailed and comprehensive research on such an iconic figure in the BCOQ. That said, this article does more than merely provide a summary of her life and legacy. It also aims at using the experience of Carder to explore some common assumptions about Canadian women in ministry, identifying when she reinforces some and undermines others. In other words, the example of Carder complexifies what can be assumed about the experience of women in the church and warns against universal generalizations surrounding their experience. In 2008, the denomination changed its name to Canadian Baptists of Ontario and Quebec (CBOQ), and for the sake of simplicity and clarity, CBOQ will be used throughout this article.
SPTrack: Spectral Similarity Prompt Learning for Hyperspectral Object Tracking
Authors: Guo Gaowei , Li Zhaoxu , An Wei , Wang Yingqian , He Xu , Luo Yihang , Ling Qiang , Li Miao , Lin Zaiping
Published: August 2024

Compared to hyperspectral trackers that adopt the “pre-training then fine-tuning” training paradigm, those using the “pre-training then prompt-tuning” training paradigm can inherit the expressive capabilities of the pre-trained model with fewer training parameters. Existing hyperspectral trackers utilizing prompt learning lack an adequate prompt template design, thus failing to bridge the domain gap between hyperspectral data and pre-trained models. Consequently, their tracking performance suffers. Additionally, these networks have a poor generalization ability and require re-training for the different spectral bands of hyperspectral data, leading to the inefficient use of computational resources. In order to address the aforementioned problems, we propose a spectral similarity prompt learning approach for hyperspectral object tracking (SPTrack). First, we introduce a spectral matching map based on spectral similarity, which converts 3D hyperspectral data with different spectral bands into single-channel hotmaps, thus enabling cross-spectral domain generalization. Then, we design a channel and position attention-based feature complementary prompter to learn blended prompts from spectral matching maps and three-channel images. Extensive experiments are conducted on the HOT2023 and IMEC25 data sets, and SPTrack is found to achieve state-of-the-art performance with minimal computational effort. Additionally, we verify the cross-spectral domain generalization ability of SPTrack on the HOT2023 data set, which includes data from three spectral bands.
Global Context Relation-Guided Feature Aggregation Network for Salient Object Detection in Optical Remote Sensing Images
Authors: Li Jian , Li Chuankun , Zheng Xiao , Liu Xinwang , Tang Chang
Published: August 2024

With the rapid development of deep neural networks, salient object detection has achieved great success in natural images. However, detecting salient objects from optical remote sensing images still remains a challenging task due to the diversity of object types, scale, shape and orientation variations, as well as cluttered backgrounds. Therefore, it is impractical to directly leverage methods designed for natural images to detect salient objects in optical remote sensing images. In this work, we present an end-to-end deep neural network for salient object detection in optical remote sensing images via global context relation-guided feature aggregation. Since the objects in remote sensing images often have a scattered distribution, we design a global context relation module to capture the global relationships between different spatial positions. In order to effectively integrate low-level appearance features as well as high-level semantic features for enhancing the final performance, we develop a feature aggregation module with the global context relation information as guidance and embed it into the backbone network to refine the deep features in a progressive manner. Instead of using traditional binary cross entropy as a training loss which treats all pixels equally, we design a weighted binary cross entropy to capture local surrounding information of different pixels. Extensive experiments on three public datasets are conducted to validate the efficiency of the proposed network and the results demonstrate that our proposed method consistently outperforms other competitors.
Evaluation of Sentinel-5P TROPOMI Methane Observations at Northern High Latitudes
Authors: Lindqvist Hannakaisa , Kivimäki Ella , Häkkilä Tuomas , Tsuruta Aki , Schneising Oliver , Buchwitz Michael , Lorente Alba , Martinez Velarte Mari , Borsdorff Tobias , Alberti Carlos , Backman Leif , Buschmann Matthias , Chen Huilin , Dubravica Darko , Hase Frank , Heikkinen Pauli , Karppinen Tomi , Kivi Rigel , McGee Erin , Notholt Justus , Rautiainen Kimmo , Roche Sébastien , Simpson William , Strong Kimberly , Tu Qiansi , Wunch Debra , Aalto Tuula , Tamminen Johanna
Published: August 2024

The Arctic and boreal regions are experiencing a rapid increase in temperature, resulting in a changing cryosphere, increasing human activity, and potentially increasing high-latitude methane emissions. Satellite observations from Sentinel-5P TROPOMI provide an unprecedented coverage of a column-averaged dry-air mole fraction of methane (XCH4) in the Arctic, compared to previous missions or in situ measurements. The purpose of this study is to support and enhance the data used for high-latitude research through presenting a systematic evaluation of TROPOMI methane products derived from two different processing algorithms: the operational product (OPER) and the scientific product (WFMD), including the comparison of recent version changes of the products (OPER, OPER rpro, WFMD v1.2, and WFMD v1.8). One finding is that OPER rpro yields lower XCH4 than WFMD v1.8, the difference increasing towards the highest latitudes. TROPOMI product differences were evaluated with respect to ground-based high-latitude references, including four Fourier Transform Spectrometer in the Total Carbon Column Observing Network (TCCON) and five EM27/SUN instruments in the Collaborative Carbon Column Observing Network (COCCON). The mean TROPOMI–TCCON GGG2020 daily median XCH4 difference was site-dependent and varied for OPER rpro from −0.47 ppb to 22.4 ppb, and for WFMD v1.8 from 1.2 ppb to 19.4 ppb with standard deviations between 13.0 and 20.4 ppb and 12.5–15.0 ppb, respectively. The TROPOMI–COCCON daily median XCH4 difference varied from −26.5 ppb to 5.6 ppb for OPER rpro, with a standard deviation of 14.0–28.7 ppb, and from −5.0 ppb to 17.2 ppb for WFMD v1.8, with a standard deviation of 11.5–13.0 ppb. Although the accuracy and precision of both TROPOMI products are, on average, good compared to the TCCON and COCCON, a persistent seasonal bias in TROPOMI XCH4 (high values in spring; low values in autumn) is found for OPER rpro and is reflected in the higher standard deviation values. A systematic decrease of about 7 ppb was found between TCCON GGG2014 and GGG2020 product update highlighting the importance of also ensuring the reliability of ground-based retrievals. Comparisons to atmospheric profile measurements with AirCore carried out in Sodankylä, Northern Finland, resulted in XCH4 differences comparable to or smaller than those from ground-based remote sensing.
Detailed Investigation on Ambiguity Validation of Long-Distance RTK
Authors: Ji Shengyue , Wang Jing , Weng Duojie , Chen Wu
Published: August 2024

Long-distance Real-Time Kinematic (RTK) positioning is crucial for applications in remote areas, such as maritime environments. Achieving 2–3 cm accuracy with RTK requires successful ambiguity resolution, which involves two main steps: identifying the best integer ambiguity candidate and confirming its validity. While previous research has largely concentrated on the first step, including the development of Cascading Ambiguity Resolution methods, and reducing tropospheric delay, studies on the validation of ambiguity for long-distance RTK are limited. This study conducts a thorough examination of ambiguity validation for long-distance RTK, focusing on two prevalent methods: the theoretical success rate and the R-ratio test. The results reveal several key insights. Firstly, the six commonly used bounds for the theoretical success rate are not an accurate reflection of the actual success rate, making them unsuitable for long-distance RTK applications. Secondly, the R-ratio test proves to be dependable when the threshold is set above 1.7, assuming there is a minimum observation period of one minute and at least ten satellites are visible. However, the probability of successfully resolving ambiguities with the R-ratio test does not surpass 50%. Additionally, if ambiguity resolution is not achieved within 20 min, simply prolonging the observation time is generally unproductive. To improve the performance of ambiguity resolution in practical situations that require extended observation times, this research proposes a novel ambiguity validation method. This new approach is based on the duration for which an integer ambiguity resolution candidate maintains the best status. This method aims to provide a reliable means of validating ambiguities in cases where the R-ratio test fails.
Intelligent Detection Method of Atrial Fibrillation by CEPNCC-BiLSTM Based on Long-Term Photoplethysmography Data
Authors: Wang Zhifeng , Fan Jinwei , Dai Yi , Zheng Huannan , Wang Peizhou , Chen Haichu , Wu Zetao
Published: August 2024

Atrial fibrillation (AF) is the most prevalent arrhythmia characterized by intermittent and asymptomatic episodes. However, traditional detection methods often fail to capture the sporadic and intricate nature of AF, resulting in an increased risk of false-positive diagnoses. To address these challenges, this study proposes an intelligent AF detection and diagnosis method that integrates Complementary Ensemble Empirical Mode Decomposition, Power-Normalized Cepstral Coefficients, Bi-directional Long Short-term Memory (CEPNCC-BiLSTM), and photoelectric volumetric pulse wave technology to enhance accuracy in detecting AF. Compared to other approaches, the proposed method demonstrates faster preprocessing efficiency and higher sensitivity in detecting AF while effectively filtering out false alarms from photoplethysmography (PPG) recordings of non-AF patients. Considering the limitations of conventional AF detection evaluation systems that lack a comprehensive assessment of efficiency and accuracy, this study proposes the ET-score evaluation system based on F-measurement, which incorporates both computational speed and accuracy to provide a holistic assessment of overall performance. Evaluated with the ET-score, the CEPNCC-BiLSTM method outperforms EEMD-based improved Power-Normalized Cepstral Coefficients and Bi-directional Long Short-term Memory (EPNCC-BiLSTM), Support Vector Machine (SVM), EPNCC-SVM, and CEPNCC-SVM methods. Notably, this approach achieves an outstanding accuracy rate of up to 99.2% while processing PPG recordings within 5 s, highlighting its potential for long-term AF monitoring.
Concrete Surface Crack Detection Algorithm Based on Improved YOLOv8
Authors: Dong Xuwei , Liu Yang , Dai Jinpeng
Published: August 2024

Concrete surface crack detection is a critical research area for ensuring the safety of infrastructure, such as bridges, tunnels and nuclear power plants, and facilitating timely structural damage repair. Addressing issues in existing methods, such as high cost, lengthy processing times, low efficiency, poor effectiveness and difficulty in application on mobile terminals, this paper proposes an improved lightweight concrete surface crack detection algorithm, YOLOv8-Crack Detection (YOLOv8-CD), based on an improved YOLOv8. The algorithm integrates the strengths of visual attention networks (VANs) and Large Convolutional Attention (LCA) modules, introducing a Large Separable Kernel Attention (LSKA) module for extracting concrete surface crack and local feature information, adapted for features such as fracture susceptibility, large spans and slender shapes, thereby effectively emphasizing crack shapes. The Ghost module in the YOLOv8 backbone efficiently extracts essential information from original features at a minimal cost, enhancing feature extraction capability. Moreover, replacing the original convolution structure with GSConv in the neck network and employing the VoV-GSCSP module adapted for the YOLOv8 framework reduces floating-point operations during feature channel fusion, thereby lowering computational complexity whilst maintaining model accuracy. Experimental results on the RDD2022 and Wall Crack datasets demonstrate the improved algorithm increases in mAP50 by 15.2% and 12.3%, respectively, and in mAP50-95 by 22.7% and 17.2%, respectively, whilst achieving a reduced model computational load of only 7.9 × 109, a decrease of 3.6%. The algorithm achieves a detection speed of 88 FPS, enabling real-time and accurate detection of concrete surface crack targets. Comparison with other mainstream object detection algorithms validates the effectiveness and superiority of the proposed approach.
User Evaluation of a Shared Robot Control System Combining BCI and Eye Tracking in a Portable Augmented Reality User Interface
Authors: Dillen Arnau , Omidi Mohsen , Ghaffari Fakhreddine , Romain Olivier , Vanderborght Bram , Roelands Bart , Nowé Ann , De Pauw Kevin
Published: August 2024

This study evaluates an innovative control approach to assistive robotics by integrating brain–computer interface (BCI) technology and eye tracking into a shared control system for a mobile augmented reality user interface. Aimed at enhancing the autonomy of individuals with physical disabilities, particularly those with impaired motor function due to conditions such as stroke, the system utilizes BCI to interpret user intentions from electroencephalography signals and eye tracking to identify the object of focus, thus refining control commands. This integration seeks to create a more intuitive and responsive assistive robot control strategy. The real-world usability was evaluated, demonstrating significant potential to improve autonomy for individuals with severe motor impairments. The control system was compared with an eye-tracking-based alternative to identify areas needing improvement. Although BCI achieved an acceptable success rate of 0.83 in the final phase, eye tracking was more effective with a perfect success rate and consistently lower completion times (p<0.001). The user experience responses favored eye tracking in 11 out of 26 questions, with no significant differences in the remaining questions, and subjective fatigue was higher with BCI use (p=0.04). While BCI performance lagged behind eye tracking, the user evaluation supports the validity of our control strategy, showing that it could be deployed in real-world conditions and suggesting a pathway for further advancements.
Simulating Error Due to Acquired Thermoelectric Inhomogeneity
Authors: Li Zida , Chen Jingliang
Published: August 2024

The best method to prevent error due to inhomogeneity is to use a new thermocouple design—the thermocouple with controlled temperature field (TCTF). It uses the auxiliary furnace to control the temperature field along its legs. Such a design allows setting and maintaining the temperature field along the thermocouple (TC) legs for the sensor. Error due to inhomogeneity of TCs cannot appear in a stable temperature field. However, the auxiliary furnace and TCs, to control the temperature field, have errors, so the temperature field along the main TC is maintained with some error. This leads to residual error due to acquired inhomogeneity of the TCTF. We constructed the mathematical models to fit the experimental data of error due to drift for the type K TC. The authors used the constructed models to study error due to inhomogeneity of the TCTF and the conventional type K TC under considerable changes in temperature field. The main results of modelling are as follows: (i) if the changes in temperature field exceed 7 °C, error due to inhomogeneity of the TCTF is lesser than that of the conventional TC; (ii) the maximum error due to inhomogeneity of the conventional type K TC is 10.75 °C; (iii) the maximum error due to inhomogeneity of the TCTF is below 0.2 °C.
Impact of Measurement Uncertainty on Fault Diagnosis Systems: A Case Study on Electrical Faults in Induction Motors
Authors: Mari Simone , Bucci Giovanni , Ciancetta Fabrizio , Fiorucci Edoardo , Fioravanti Andrea
Published: August 2024

Classification systems based on machine learning (ML) models, critical in predictive maintenance and fault diagnosis, are subject to an error rate that can pose significant risks, such as unnecessary downtime due to false alarms. Propagating the uncertainty of input data through the model can define confidence bands to determine whether an input is classifiable, preferring to indicate a result of unclassifiability rather than misclassification. This study presents an electrical fault diagnosis system on asynchronous motors using an artificial neural network (ANN) model trained with vibration measurements. It is shown how vibration analysis can be effectively employed to detect and locate motor malfunctions, helping reduce downtime, improve process control and lower maintenance costs. In addition, measurement uncertainty information is introduced to increase the reliability of the diagnosis system, ensuring more accurate and preventive decisions.
DEIT-Based Bone Position and Orientation Estimation for Robotic Support in Total Knee Arthroplasty—A Computational Feasibility Study
Authors: Schrott Jakob , Affortunati Sabrina , Stadler Christian , Hintermüller Christoph
Published: August 2024

Total knee arthroplasty (TKA) is a well-established and successful treatment option for patients with end-stage osteoarthritis of the knee, providing high patient satisfaction. Robotic systems have been widely adopted to perform TKA in orthopaedic centres. The exact spatial positions of the femur and tibia are usually determined through pinned trackers, providing the surgeon with an exact illustration of the axis of the lower limb. The drilling of holes required for mounting the trackers creates weak spots, causing adverse events such as bone fracture. In the presented computational feasibility study, time differential electrical impedance tomography is used to locate the femur positions, thereby the difference in conductivity distribution between two distinct states s0 and s1 of the measured object is reconstructed. The overall approach was tested by simulating five different configurations of thigh shape and considered tissue conductivity distributions. For the cylinder models used for verification and reference, the reconstructed position deviated by about ≈1 mm from the actual bone centre. In case of models mimicking a realistic cross section of the femur position deviated between 7.9 mm 24.8 mm. For all models, the bone axis was off by about φ=1.50° from its actual position.
Options for Intensification of Cropping System in Coastal Saline Ecosystem: Inclusion of Grain Legumes in Rice-Based Cropping System
Authors: Sarkar Sukamal , Brahmachari Koushik , Gaydon Donald S. , Dhar Anannya , Dey Saikat , Mainuddin Mohammed
Published: August 2024

The coastal saline zone of West Bengal in India is the home to millions of the world’s poorest and most vulnerable people. Due to a gradual increase in salt accumulation on soils of the coastal saline zone of West Bengal in India from winter to summer days, cultivation of the second crop in the winter season becomes possible in a limited area. To address these issues, field experiments was conducted in rainy and winter seasons of 2016–17 and 2017–18 at the farmer’s field of the coastal saline zone (CSZ) of West Bengal, India. The experiment was carried out to study the system productivity, nutrient uptake, and profitability vis-à-vis salinity dynamics of the crops in rice-pulse-based cropping systems under different land elevations (medium upland and medium lowland). The experiment was conducted in a strip-split plot design having horizontal factors namely, Factor A: Six dates of sowing of rice at an interval of one week (2nd week of June to 3rd week of July), Factor B: Two land situations (medium upland and medium lowland) and Two Cropping Systems (Rice-Lathyrus and Rice-Lentil) as vertical factor, replicated four times. The results suggest that irrespective of land situation, early sown rice (15 June to 21 June) produces higher dry matter and grain yield compared to late sown crops. This early sowing of rice also facilitated the better performance of subsequent lathyrus and lentil, by avoiding the worst situation of the salinity build-up and drought stress later in the winter. Moreover, significantly higher productions were obtained from medium-lowland situations for both the cropping systems. Sowing date has also significantly influenced macro-nutrient uptake (NPK) by rice and pulse grains. It may be concluded that early sowing of rice may be a potential option for intensification of rice-pulse-based cropping systems under CSZ of West Bengal, India.
Correction: Kumar et al. Sustainable Intensification of Cropping Systems under Conservation Agriculture Practices: Impact on Yield, Productivity and Profitability of Wheat. Sustainability 2023, 15, 7468
Authors: Kumar Arun , Saini Kulvir Singh , Dasila Hemant , Kumar Rakesh , Devi Kavita , Bisht Yashpal Singh , Yadav Manish , Kothiyal Shivani , Chilwal Aaradhana , Maithani Damini , Kaushik Prashant
Published: August 2024

Affiliation Update: [...]
Research on Impact Mechanism of Organizational Resilience on Sustainable Competitive Advantage of Enterprises
Authors: Liu Xi , Zhang Dan
Published: August 2024

This study is the first to comprehensively investigate the impact mechanism of organizational resilience on the sustainable competitive advantage of enterprises based on dynamic capability theory, social network theory, and resource dependence theory. It systematically analyzes the multidimensional effects of organizational resilience and reveals the moderating effect of the network digital atmosphere and environmental dynamism on strategic capabilities. Herein, six basic hypotheses and 19 sub-hypotheses are proposed. Through the analyses of 386 valid questionnaires in the Yangtze River Delta and Pearl River Delta regions, the results show that organizational resilience has a positive impact on the sustainable competitive advantage of enterprises, and strategic capability plays a mediating role through two dimensions, which are strategic formulation capability and resource integration capability. In addition, the network digital atmosphere and environmental dynamics regulate the relationship between organizational resilience and strategic capability in different dimensions. The research results provide empirical support for strengthening corporate strategic capabilities, responding to environmental changes, maintaining competitive advantages, and achieving the sustainable development of enterprises.
Linked Links—A Research Project: The Multiple Superimposed Soft Networks as Network Profiles
Authors: Minati Gianfranco
Published: August 2024

This article, based on network science, aims to contribute to overcoming its geometric and technological phases. The novelty consists in considering links of networks as linked by superimposed networks, termed here multiple superimposed soft networks (MSSN), which is introduced as a research issue. Such links of links (termed here as passive links) concern, for instance, correspondences, incompatibilities, and temporal synchronizations between the occurrences of pairs of active links of effective networks, such as those based on electrical and telecommunication. A possible constitutive mechanism of such passive linkage consists of linkage representations for practices and histories of use expressed by their validating statistical reoccurrences. We consider the possible emergent nature of the passive linkage. The reason for introducing the design and usage of MSSN properties as a research issue involves making new approaches to profile and manage networks available. Correspondence between active linkage and MSSN properties should be a matter for an experiential, machine-learning approach. Research issues relate their possible usage on the active linkage such as for classification, comparations, detection of criticalities, diagnosis, performance evaluation, and regulatory as weak forces. Furthermore, the possible identification of standard corresponding configurations of passive and active linkage is finalized to avoid their establishment or, conversely, in facilitating their establishment and keeping their replication in different contexts (or partially and in combinations) and identifying related standardized approaches (also for classes of configurations having significant levels of equivalence). This research project has methodological generalizing aspects of trans-disciplinarity. We conclude by mentioning related research issues.
Safety and Efficacy of Primary EUS-Guided Choledochoduodenostomy for Malignant Distal Biliary Obstruction: A Systematic Review and Meta-Analysis
Authors: Annor Eugene , Gopakumar Harishankar , Vohra Ishaan , Puli Srinivas R.
Published: August 2024

Background: Endoscopic retrograde cholangiopancreatography (ERCP) is preferred for biliary drainage in malignant distal biliary obstruction (MDBO). Endoscopic ultrasound-guided choledochoduodenostomy (EUS-CDS) is considered a rescue therapy for failed ERCP. This study aims to evaluate the safety and efficacy of this technique as the primary modality for MDBO biliary drainage. Methods: An electronic database search was conducted following PRISMA guidelines to identify studies on EUS-CDS for primary biliary drainage in MDBO. A meta-analysis was performed using random and fixed effects models. Results: We extracted data from 10 eligible studies comprising 519 patients. The mean age for the study was 70 years ± SD 2.66. The pooled technical success rate was 92.36% (95% CI = 88.39–95.56), and the clinical success rate was 88.91% (95% CI = 85.22–92.13). The pooled stent dysfunction rate was 13.66% (95% CI = 7.47–21.35), and the reintervention rate was 15.91% (95% CI = 11.00–21.54) of patients. The mean stent patency duration was 229.20 days ± SD 113.9. The total pooled adverse events rate was 17.50% (95% CI = 12.90–22.64), and 9.03% (95% CI = 4.43–15.05) was considered moderate to severe. Procedure-related pancreatitis had a pooled rate of 0%. The pooled adverse event rate of acute cholangitis was 6.84% (95% CI = 3.69–10.88), and for acute cholecystitis it was 2.61% (95% CI = 1.06–4.83). Conclusions: EUS-CDS demonstrates favorable outcomes when used as a primary approach in MDBO. With a long stent patency duration and no procedure-related acute pancreatitis, it may be considered the primary technique when expertise is available.
Machine Learning and Deep Learning Approaches in Lifespan Brain Age Prediction: A Comprehensive Review
Authors: Wu Yutong , Gao Hongjian , Zhang Chen , Ma Xiangge , Zhu Xinyu , Wu Shuicai , Lin Lan
Published: August 2024

The concept of ‘brain age’, derived from neuroimaging data, serves as a crucial biomarker reflecting cognitive vitality and neurodegenerative trajectories. In the past decade, machine learning (ML) and deep learning (DL) integration has transformed the field, providing advanced models for brain age estimation. However, achieving precise brain age prediction across all ages remains a significant analytical challenge. This comprehensive review scrutinizes advancements in ML- and DL-based brain age prediction, analyzing 52 peer-reviewed studies from 2020 to 2024. It assesses various model architectures, highlighting their effectiveness and nuances in lifespan brain age studies. By comparing ML and DL, strengths in forecasting and methodological limitations are revealed. Finally, key findings from the reviewed articles are summarized and a number of major issues related to ML/DL-based lifespan brain age prediction are discussed. Through this study, we aim at the synthesis of the current state of brain age prediction, emphasizing both advancements and persistent challenges, guiding future research, technological advancements, and improving early intervention strategies for neurodegenerative diseases.
Pre-Exposure Prophylaxis to Prevent Hematophagous Bat-Mediated Rabies Outbreaks in Remote Amazon Communities: Lessons from a Pilot for Public Health Policy
Authors: Rocha Felipe , Vargas Alexander , Abreu Elke Maria Nogueira de , Pompei Julio Cesar Augusto , Vigilato Marco Antonio Natal , Lima Daniel Magalhães , Vianna Raphael Schneider , Cosivi Ottorino , Recuenco Sergio E. , Costa Wagner Augusto , Hardt Luciana , Ferreira Karin Correa Scheffer , Neto Rene dos Santos Cunha , Chaves Luciana Botelho , Silva Andrea de Cassia Rodrigues da , Begot Alberto Lopes , Andrade Jorge Alberto Azevedo , Marcos Weber , Rocha Silene Manrique , Junior Francisco Edilson Ferreira Lima , Wada Marcelo Yoshito
Published: August 2024

In 2018, an outbreak of human rabies caused by the hematophagous bat Desmodus rotundus hit the Brazilian Amazon Basin community of Melgaço, Brazil, resulting in the death of 10 people, 9 of them children. The incidence of rabies has been on the rise among populations in conditions of vulnerability in this ecosystem due to human expansion into sylvatic environments and limited access to public health services. To address this issue, in September 2019, a collaborative effort from national, local, and international institutions promoted and executed a pilot for pre-exposure prophylaxis of a population in high-risk areas for hematophagous bat-mediated rabies. This measure is usually only implemented in response to outbreaks. The pilot was conducted in Portel, in a nearby location to the previous outbreak, with the use of fluvial transportation, and 2987 individuals in 411 dwellings were successfully vaccinated. It established a methodology for pre-exposure prophylaxis for populations in conditions of vulnerability, identifying logistics and costs, as well as characterizing the target riverine population regarding risk factors associated with bites by hematophagous bats. This approach offers a proactive measure to prevent future outbreaks and provides valuable insights into how to address the issue of rabies in remote and difficult-to-reach areas.
Tuberculosis Infection in People Living with Human Immunodeficiency Virus: Challenges and Solutions
Authors: Ilaiwy Ghassan , Thomas Tania A.
Published: August 2024

The findings by Pipitò et al [...]