bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Bath Composition on Titanium Anodization Using the Constant-Current Approach: A Crystallographic and Morphological Study
Authors: Gabellini Lapo , Calisi Nicola , Martinuzzi Stefano Mauro , Taurino Rosa , Innocenti Massimo , Bacci Tiberio , Borgioli Francesca , Galvanetto Emanuele , Caporali Stefano
Published: July 2023

Porous TiO2 thin films were prepared via electrochemical anodization of commercial-grade titanium foils in baths containing variable amounts of ethylene glycol. X-Ray diffraction, scanning electron microscopy, and UV/visible spectroscopy were employed to assess the effect of ethylene glycol on the nature of TiO2 layers. Emphasis is given to the modification of pore size and anatase-to-rutile ratio since these characteristics strongly affect the catalytic performance of TiO2. To simplify the scaling up of the process, a single-step anodization process was employed on a commercial grade 2 titanium foil in constant-current mode without the use of fluorides—conditions that are easily replicable on an industrial scale. We point out some interesting relationships among operating parameters, such as bath composition and current densities, and the characteristics of the anodization layers evidence that the pore size and anatase-to-rutile ratio can be strictly controlled. Increasing the amount of ethylene glycol stimulated the formation of a thinner and less porous TiO2 layer, richer in rutile phase, and characterized by reduced-diameter pores. These results demonstrate the effectiveness and, to some extent, the tunability of the morphology and mineralogic composition of titanium anodization in fluoride-free and ethylene-glycol-bearing acidic solutions.
Synthesis and Characterization of Cadmium Ion-Imprinted/Natural Sand Composite and Research on Its Adsorption Properties
Authors: Murat Aray , Gao Shuaibing , Wang Lingling , Chai Linlin , Abliz Shawket , Yimit Abliz
Published: July 2023

Cadmium is a common heavy metal that can cause serious harm to human health, even in trace amounts. Therefore, it is of great significance to develop environmentally friendly, inexpensive, and readily available adsorbent materials with high selectivity. By preparing ion-imprinted composites on the surface of a suitable carrier through surface imprinting, the number of effective adsorption sites can be increased, and target ions can be more quickly identified. In this study, we synthesized a cadmium ion-imprinted/natural sand composite material (NS/Cd-IIP) using natural sand as the carrier, Cd(II) as the template ion, and acrylamide as the functional monomer. A series of characterization techniques were employed to confirm the composite. Static and dynamic adsorption experiments were conducted to investigate various factors affecting its adsorption performance. The optimum adsorption pH was found to be 7, and the adsorption equilibrium time was determined to be 105 min. The imprinted composites exhibited a static adsorption saturation capacity of 33.84 mg·g−1, which was significantly higher than that of the non-imprinted composites. The adsorption behavior of composites followed Langmuir isotherm and quasi-second-order kinetic. Thermodynamic parameters indicated that the adsorption process of NS/Cd-IIP for Cd(II) was exothermic, entropic, and spontaneous. The selectivity of NS/Cd-IIP towards Cd(II) was significantly higher than that towards other ions. By optimizing the dynamic adsorption conditions, the maximum adsorption capacity of NS/Cd-IIP was determined to be 3.77 mg·g−1, and the adsorption behavior conformed to the Thomas model. NS/Cd-IIP was used as a solid-phase extractant for trace determination of Cd(II) in tap water, achieving a recovery rate exceeding 101%.
The Synthesis of C70 Fullerene Nanowhiskers Using the Evaporating Drop Method
Authors: Bakhramov Sagdulla A. , Makhmanov Urol K. , Aslonov Bobirjon A.
Published: July 2023

Semiconductor nanowhiskers, particularly nanostructured whiskers based on zero-dimensional (0D) C70 fullerene, are being actively discussed due to the great potential of their application in modern electronics. For the first time, we proposed and implemented a method for the synthesis of nanostructured C70 fullerene whiskers based on the self-organization of C70 molecules during the thermal evaporation of C70 droplets on the substrate surface. We found that the onset of the synthesis of C70 nanowhiskers upon the evaporation of drops of a C70 solution in toluene on the substrate surface depends on the substrate temperature. We have provided experimental evidence that an increase in both the C70 concentration in the initial drop and the substrate temperature leads to an increase in the geometric dimensions of C70 nanowhiskers. The obtained results provide useful vision on the role of solute concentration and substrate temperature in the synthesis of one-dimensional materials.
Associations between Socio-Demographic Characteristics and Maternal Attitudes towards Childhood Vaccination in Cyprus—A Cross-Sectional Survey
Authors: Kyprianidou Maria , Fakonti Georgia , Tzira Eleana , Pylli Magdalini , Giannakou Konstantinos
Published: July 2023

Background: As vaccination acceptance is dynamic, the current COVID-19 pandemic may have changed maternal perceptions towards childhood vaccination and influenced their decision to vaccinate their children. This study aimed to examine the associations between socio-demographic characteristics and maternal attitudes towards childhood vaccination at the beginning of the COVID-19 pandemic in Cyprus. Methods: A web-based cross-sectional study was conducted between April and June 2020 using a self-administered survey. Adult mothers with at least one child under the age of 18 were included in this study. Results: Overall, 703 mothers were included, with the majority of them strongly agreeing or agreeing that all vaccinations included in the National Vaccination Program should be available to children (89.3%), recognizing the usefulness of vaccines (91.4%) and their ability to provide protection (90%), acknowledging that the benefits of vaccination outweigh potential risks (86.6%), and being aware that some vaccines may cause adverse reactions (84.1%). Socio-demographic factors, particularly marital status, single-parent status, and employment status, have a significant impact on maternal attitudes and perceptions regarding childhood vaccination. Conclusions: Public health policies should be designed to overcome structural and healthcare system barriers specifically related to socio-demographic factors, ensuring effective and comprehensive strategies to improve childhood vaccination uptake.
Anomalous Ferromagnetic Phase in the Gd1−xErxB4 Series: Crystal Growth, Thermal, and Magnetic Properties
Authors: Masunaga Sueli H. , Barbeta Vagner B. , Abud Fábio , Torikachvili Milton S. , Jardim Renato F.
Published: July 2023

Rare-earth tetraborides RB4 are of great interest due to the occurrence of geometric magnetic frustration and corresponding unusual magnetic properties. While the Gd3+ spins in GdB4 align along the ab plane, Er3+ spins in the isomorphic ErB4 are confined to the c–axis. The magnetization in the latter exhibits a plateau at the midpoint of the saturation magnetization. Therefore, solid solutions of (Gd, Er)B4 provide an excellent playground for exploring the intricate magnetic behavior in these compounds. Single crystals of Gd1−xErxB4 (x = 0, 0.2, and 0.4) were grown in aluminum flux. X-ray diffraction scans revealed single-phase materials, and a drop in the unit cell volume with increasing Er content, suggesting the partial substitution of Er at the Gd sites. Heat capacity measurements indicated a systematic decrease of the Néel temperature (TN) with increasing Er content. The effective magnetic moment determined from the magnetization measurement agreed with the calculated free ion values for Gd3+ and Er3+, providing further evidence for the successful substitution of Er for Gd. The partial substitution resulted in an anomalous ferromagnetic phase below TN, exhibiting significant anisotropy, predominantly along the c-axis. This intriguing behavior merits further studies of the magnetism in the Gd1−xErxB4 borides.
Drivers of Species Distribution and Niche Dynamics for Ornamental Plants Originating at Different Latitudes
Authors: Zhou Jing , Tang Qianhong , Zong Donglin , Hu Xiaokang , Wang Bingru , Wang Tao
Published: July 2023

Human activities provide migration opportunities for many ornamental plants and make them become a new potential invasion risk, threatening the local ecosystem. However, ornamental plants come from a wide range of sources, and there is still a lack of understanding on the distribution driving factors, ecological niche dynamics and invasion ability of ornamental plants based on the origin of different latitudes to evaluate their potential invasion risks. In this study, an ensemble of ecological niche model and a niche dynamic model were used to analyze the invasion potential of herbaceous and woody ornamental plants originating from different latitudes. The results showed that there were significant differences in environmental factors driving the distribution of plants originating from different latitudes, and climate-related factors were the primary driving force for each plant in the native and introduced regions. Urban land was the most influential factor in the introduced areas of most plants, potentially reflecting the importance of human activities in the distribution of ornamental plants. Additionally, only woody plants originating from mid-latitudes showed greater diffusivity than those originating in high latitudes and low latitudes, and the niche widths of all the herbaceous plants in the introduced regions nearly exceeded those in the native regions. This phenomenon was observed only in woody plants with mid-latitude origins. The niche similarity of all plant species between the introduced and native regions was high, indicating that all species in the introduced regions inherited niche characteristics from plants in the native regions.
Bortezomib-Induced Reticular Eruption in Patient with Multiple Myeloma
Authors: Han Joseph , Owji Shayan , Agarwal Aneesh , Kamat Samir , Luu Yen , Mubasher Adnan , Niedt George , Ray Chloe , Cho Hearn Jay , Gulati Nicholas , Lamb Angela
Published: July 2023

Bortezomib is the first proteasome inhibitor to treat a variety of malignancies and is currently part of the standard of care regimen for the initial treatment of patients with newly diagnosed multiple myeloma. While bortezomib is generally well tolerated, it has been associated with various side effects, which have limited its use in some patients. Here, we describe a unique case with histological confirmation of a reticular eruption that appeared at the site of a subcutaneous administration of bortezomib in a 62-year-old male who was newly diagnosed with IgG kappa multiple myeloma. A skin biopsy was performed, which revealed superficial perivascular dermatitis predominantly composed of lymphocytes with rare eosinophils. The patient was successfully treated with betamethasone dipropionate 0.05% cream. When consulted, dermatologists should advise the oncology team of multiple myeloma patients treated with bortezomib to maintain a high threshold before discontinuing the drug when a patient experiences an atypical, reticular rash following subcutaneous administration. Additionally, potent topical corticosteroids, such as betamethasone dipropionate 0.05% cream, should be considered in managing the cutaneous reticular eruptions related to bortezomib administration, in order to maintain an optimal treatment regimen for patients with multiple myeloma.
Implementing a Produce Prescription Program at Three Federally Qualified Health Centers to Help Patients Manage Their Diabetes or Prediabetes: A Qualitative Assessment of Clinic Staff Experiences in Los Angeles County, California, USA
Authors: Ayala Victoria , Caldwell Julia I. , Darwish-Elsherbiny Fatinah , Shah Dipa , Kuo Tony
Published: July 2023

Through a partnership with three Federally Qualified Health Centers (FQHCs), the local health department in Los Angeles County implemented a produce prescription program (PPR) to increase fresh fruit and vegetable purchases among patients with diabetes or prediabetes. The PPR, which began in 2020, provided eligible patients with a USD 40 voucher every month for 6 months to promote the purchase of fresh produce at large-chain grocery stores. To address gaps in current practice and program delivery, this qualitative assessment describes staff experiences with the PPR, documenting the facilitators and barriers they encountered while implementing the program. Fifteen clinic staff (i.e., PPR implementers) were interviewed for this assessment. Thematic analysis and coding were conducted using the ATLAS.ti software; the coding was carried out by two separate coders. Interviewees discussed the importance of having preexisting partnerships and programs to support the PPR at their clinic site. Hidden costs related to implementing the program included a large and unexpected amount of staff time devoted to enrolling patients into the program. Collecting quality data and having limited expertise to rigorously evaluate the program were other challenges. Because patients often share their food with their family, the monthly USD 40 incentive was generally not enough to support their needs; interviewees suggested giving a higher inventive amount to those with a larger household. Future PPR efforts and similar food incentive programs should consider these and other facilitators and barriers to implementation and sustainability, especially when making adjustments to these programs to improve services and access to food resources.
Reagent Effects on the Activated Partial Thromboplastin Time Clot Waveform Analysis: A Multi-Centre Study
Authors: Wong Wan Hui , Tan Chuen Wen , Abdul Khalid Nabeelah Binti , Dalimoenthe Nadjwa Zamalek , Yip Christina , Tantanate Chaicharoen , Lim Rodelio D. , Kim Ji Hyun , Ng Heng Joo
Published: July 2023

(1) Background: The activated partial thromboplastin time (APTT)- based clot waveform analysis (CWA) quantitatively extends information obtained from the APTT waveform through its derivatives. However, pre-analytical variables including reagent effects on the CWA parameters are poorly understood and must be standardized as a potential diagnostic assay. (2) Methods: CWA was first analysed with patient samples to understand reagent lot variation in three common APTT reagents: Pathromtin SL, Actin FS, and Actin FSL. A total of 1055 healthy volunteers were also recruited from seven institutions across the Asia-Pacific region and CWA data were collected with the Sysmex CS analysers. (3) Results: CWA parameters varied less than 10% between lots and the linear mixed model analysis showed few site-specific effects within the same reagent group. However, the CWA parameters were significantly different amongst all reagent groups and thus reagent-specific 95% reference intervals could be calculated using the nonparametric method. Post-hoc analysis showed some degree of influence by age and gender with weak correlation to the CWA (r < 0.3). (4) Conclusions: Reagent type significantly affects APTT-based CWA with minimal inter-laboratory variations with the same coagulometer series that allow for data pooling across laboratories with more evidence required for age- and gender-partitioning.
The Associations among Dental Anxiety, Self-Esteem, and Oral Health-Related Quality of Life in Children: A Cross-Sectional Study
Authors: Alharbi Amjad , Humphris Gerry , Freeman Ruth
Published: July 2023

Background: The current evidence on the relationships among child oral health-related quality of life, dental anxiety, and self-esteem indicates that we need to investigate these relationships to improve our understanding of the associations. Therefore, the current research aimed to enhance this evidence and provide an overview of the participating children’s oral-health-related quality of life (as measured by the CPQ8–10), self-esteem (as measured by the Coopersmith SEI-SF), and dental anxiety (as measured by the CFSS_DS) and how these child-related outcome measures interacted and were related to one another. Method: A cross-sectional survey was conducted on a random sample of school children (n = 1900) aged 8 to 10 years. The questionnaire was collected through validated self-report measures: dental anxiety, COHRQoL, and self-esteem. Structural equation modelling (SEM) was used to test the strength of the association of our model to explore the relationships among these three psychological constructs. The moderating effects of age, gender, location, and the educational board were analysed for their possible influence on these relationships. Results: Significant relationships between COHRQoL and child dental anxiety and between COHRQoL and SE were detected. The relationship subscale between COHRQoL and child dental anxiety was 0.24, (p < 0.001). A stronger correlation between COHRQoL, and SE was found, with B = −0.77, (p < 0.001). Although the association between CDA and SE was small, it was statistically significant (p = 0.03). These findings provide some important background information for designing effective educational programs for children.
Modified Siamese Network Based on Feature Enhancement and Dynamic Template for Low-Light Object Tracking in UAV Videos
Authors: Sun Lifan , Kong Shuaibing , Yang Zhe , Gao Dan , Fan Bo
Published: July 2023

Unmanned aerial vehicles (UAVs) visual object tracking under low-light conditions serves as a crucial component for applications, such as night surveillance, indoor searches, night combat, and all-weather tracking. However, the majority of the existing tracking algorithms are designed for optimal lighting conditions. In low-light environments, images captured by UAV typically exhibit reduced contrast, brightness, and a signal-to-noise ratio, which hampers the extraction of target features. Moreover, the target’s appearance in low-light UAV video sequences often changes rapidly, rendering traditional fixed template tracking mechanisms inadequate, and resulting in poor tracker accuracy and robustness. This study introduces a low-light UAV object tracking algorithm (SiamLT) that leverages image feature enhancement and a dynamic template-updating Siamese network. Initially, the algorithm employs an iterative noise filtering framework-enhanced low-light enhancer to boost the features of low-light images prior to feature extraction. This ensures that the extracted features possess more critical target characteristics and minimal background interference information. Subsequently, the fixed template tracking mechanism, which lacks adaptability, is enhanced by dynamically updating the tracking template through the fusion of the reference and base templates. This improves the algorithm’s capacity to address challenges associated with feature changes. Furthermore, the Average Peak-to-Correlation Energy (APCE) is utilized to filter the templates, mitigating interference from low-quality templates. Performance tests were conducted on various low-light UAV video datasets, including UAVDark135, UAVDark70, DarkTrack2021, NAT2021, and NAT2021L. The experimental outcomes substantiate the efficacy of the proposed algorithm in low-light UAV object-tracking tasks.
Digital Twin Development for the Airspace of the Future
Authors: Souanef Toufik , Al-Rubaye Saba , Tsourdos Antonios , Ayo Samuel , Panagiotakopoulos Dimitrios
Published: July 2023

The UK aviation industry is committed to achieving net zero emissions by 2050 through sustainable measures and one of the key aspects of this effort is the implementation of Unmanned Traffic Management (UTM) systems. These UTM systems play a crucial role in enabling the safe and efficient integration of unmanned aerial vehicles (UAVs) into the airspace. As part of the Airspace of the Future (AoF) project, the development and implementation of UTM services have been prioritised. This paper aims to create an environment where routine drone services can operate safely and effectively. To facilitate this, a digital twin of the National Beyond Visual Line of Sight Experimentation Corridor has been created. This digital twin serves as a virtual replica of the corridor and allows for the synthetic testing of unmanned traffic management concepts. The implementation of the digital twin involves both simulated and hybrid flights with real drones. Simulated flights allow for the testing and refinement of UTM services in a controlled environment. Hybrid flights, on the other hand, involve the integration of real drones into the airspace to assess their performance and compatibility with the UTM systems. By leveraging the capabilities of UTM systems and utilising the digital twin for testing, the AoF project aims to advance the development of safer and more efficient drone operations. The Experimentation Corridor has been developed to simulate and test concepts related to managing unmanned traffic. The paper provides a detailed account of the implementation of the digital twin for the AoF project, including simulated and hybrid flights involving real drones.
The Impact of COVID-19 on the Volatility of Copper Futures
Authors: Melo-Vega-Angeles Oscar , Chuquillanqui-Lichardo Bryan
Published: July 2023

The COVID-19 pandemic has introduced significant uncertainty across various economic sectors, most notably in the industrial sector due to the high volatility in copper futures markets. These markets play a crucial role in the construction, electrical networks, electronic products, and industrial machinery industries. Therefore, the aim of this study is to evaluate the impact of the COVID-19 pandemic on the volatility of copper futures returns from 2 January 2018 to 30 December 2022 using an extended ARMA(m,n)–GARCH(p,q) framework. According to the results, the occurrence of the pandemic nearly doubled the long-run equilibrium volatility of returns compared to the values obtained in the pre-pandemic period. Hence, we conclude that the COVID-19 pandemic has a significant influence on the volatility in the copper futures market.
Deaf and Hard of Hearing Students with Disabilities: An Evolving Landscape
Authors: Bowen Sandy K. , Probst Kristi M.
Published: July 2023

The population of students who are d/Deaf or hard of hearing (d/Dhh) with a disability have unique educational needs. Various terms have been used to describe this population, including “deaf plus”, “deaf with additional disabilities”, and most recently, “deaf with disabilities (DWD)”. Currently, there is no agreement on the percentage of DWD students in PreK-21 settings but is considered to comprise at least 40–50%. An individual who is DWD has a hearing loss and one or more disabilities, including (but not limited to) visual impairment or blindness, autism spectrum disorder, intellectual or developmental disabilities, specific learning disabilities, health impairments, etc. The critical consideration is that the interaction between hearing loss and the disability(ies) is not simply additive but rather multiplicative, impacting communication, cognition, social development, and behavior. Furthermore, the presence of hearing loss may decrease accurate identification of other disabilities and vice versa. Although the incidence of students who are DWD is quite high, there is inadequate research as these students are often excluded from studies focused on children who are d/Dhh. This article explores what we currently know about DWD students, and the knowledge and skills needed by teachers in the 21st century to meet the needs of these students and their families.
‘Let’s Teach as We Preach’: The Design of a Professional Development Initiative to Support Teacher Educators’ Responsiveness to Diversity
Authors: Ponet Benjamin , Vantieghem Wendelien , Tack Hanne , Vanderlinde Ruben
Published: July 2023

(1) Background: In preparing the next generation of teachers, teacher educators are key actors in fostering diversity-responsive education. However, evidence-informed professional development initiatives (PDIs) are needed to raise teacher educators’ awareness and increase their diversity-responsive practices. This study provides insight into the design of a PDI that addresses this need. (2) Methods: After consulting the educational literature to define PDI objectives and general design principles, a participatory design process was initiated at two teacher education institutions to create a tailored PDI. Therefore, semi-structured interviews were conducted with a key policy-maker of each institution (n = 2) and with all participating teacher educators (n = 19). (3) Results: The participatory design process resulted in (1) the identification of both institutional contexts and participant groups’ needs and (2) the subsequent design of a PDI to support teacher educators’ diversity-responsive practices. Particularly, a three-phased PDI was designed, of which the overall and context-tailored design choices are discussed. (4) Conclusions: This contextualised PDI is a unique and concrete contribution to the teacher educator literature. Moreover, three new design principles are proposed for teacher educator PDIs in general. This article might inspire policy-makers and teacher educators to design their own PDIs to foster responsiveness to diversity.
Using the DREAM Methodology for Course Assessment in the Field of ICT-Enabled Education for Sustainability
Authors: Makrakis Vassilios
Published: July 2023

This study explores the application of the DREAM methodology for course assessment in three South East Asian universities aiming to embed sustainability and sustainable development goals (SDGs) in multiple academic disciplines enabled by information and communication technologies (ICTs). A mixing of content and thematic analysis was used, which aligns with the underpinning philosophy of the Diagnosing, Reviewing/Reflecting, Explaining, Assessing, Managing (DREAM) methodology. The DREAM methodology integrates five processes, starting from diagnosing, to reviewing/reflecting, explaining, assessing, and, finally, managing. Results show that merging semantic and latent themes has contributed to uncovering what messages students’ narratives convey and provided a space for focusing both on the surface and explicit meanings of the data as well as on theory building and policy making. They also show the effectiveness of the DREAM methodology in constructing new knowledge and generating meaningful interpretations and suggestions to teacher educators and other academic teaching staff, as well as higher education institutions’ policymakers and planners.
Ethical Challenges in the Development of Virtual Assistants Powered by Large Language Models
Authors: Piñeiro-Martín Andrés , García-Mateo Carmen , Docío-Fernández Laura , López-Pérez María del Carmen
Published: July 2023

Virtual assistants (VAs) have gained widespread popularity across a wide range of applications, and the integration of Large Language Models (LLMs), such as ChatGPT, has opened up new possibilities for developing even more sophisticated VAs. However, this integration poses new ethical issues and challenges that must be carefully considered, particularly as these systems are increasingly used in public services: transfer of personal data, decision-making transparency, potential biases, and privacy risks. This paper, an extension of the work presented at IberSPEECH 2022, analyzes the current regulatory framework for AI-based VAs in Europe and delves into ethical issues in depth, examining potential benefits and drawbacks of integrating LLMs with VAs. Based on the analysis, this paper argues that the development and use of VAs powered by LLMs should be guided by a set of ethical principles that prioritize transparency, fairness, and harm prevention. The paper presents specific guidelines for the ethical use and development of this technology, including recommendations for data privacy, bias mitigation, and user control. By implementing these guidelines, the potential benefits of VAs powered by LLMs can be fully realized while minimizing the risks of harm and ensuring that ethical considerations are at the forefront of the development process.
Pedestrian Detection Method Based on Two-Stage Fusion of Visible Light Image and Thermal Infrared Image
Authors: Zhang Yugui , Zhai Bo , Wang Gang , Lin Jianchu
Published: July 2023

Pedestrian detection has important research value and practical significance. It has been used in intelligent monitoring, intelligent transportation, intelligent therapy, and automatic driving. However, in the pixel-level fusion and the feature-level fusion of visible light images and thermal infrared images under shadows during the daytime or under low illumination at night in actual surveillance, missed and false pedestrian detection always occurs. To solve this problem, an algorithm for the pedestrian detection based on the two-stage fusion of visible light images and thermal infrared images is proposed. In this algorithm, in view of the difference and complementarity of visible light images and thermal infrared images, these two types of images are subjected to pixel-level fusion and feature-level fusion according to the varying daytime conditions. In the pixel-level fusion stage, the thermal infrared image, after being brightness enhanced, is fused with the visible image. The obtained pixel-level fusion image contains the information critical for accurate pedestrian detection. In the feature-level fusion stage, in the daytime, the previous pixel-level fusion image is fused with the visible light image; meanwhile, under low illumination at night, the previous pixel-level fusion image is fused with the thermal infrared image. According to the experimental results, the proposed algorithm accurately detects pedestrian under shadows during the daytime and low illumination at night, thereby improving the accuracy of the pedestrian detection and reducing the missed rate and false rate in the detection of pedestrians.
A Multi-Modal Modulation Recognition Method with SNR Segmentation Based on Time Domain Signals and Constellation Diagrams
Authors: Duan Ruifeng , Li Xinze , Zhang Haiyan , Yang Guoting , Li Shurui , Cheng Peng , Li Yonghui
Published: July 2023

Deep-learning-based automatic modulation recognition (AMR) has recently attracted significant interest due to its high recognition accuracy and the lack of a need to manually set classification standards. However, it is extremely challenging to achieve a high recognition accuracy in increasingly complex channel environments and balance the complexity. To address this issue, we propose a multi-modal AMR neural network model with SNR segmentation called M-LSCANet, which integrates an SNR segmentation strategy, lightweight residual stacks, skip connections, and an attention mechanism. In the proposed model, we use time domain I/Q data and constellation diagram data only in medium and high signal-to-noise (SNR) regions to jointly extract the signal features. But for the low SNR region, only I/Q signals are used. This is because constellation diagrams are very recognizable in the medium and high SNRs, which is conducive to distinguishing high-order modulation. However, in the low SNR region, excessive similarity and the blurring of constellations caused by heavy noise will seriously interfere with modulation recognition, resulting in performance loss. Remarkably, the proposed method uses lightweight residuals stacks and rich ski connections, so that more initial information is retained to learn the constellation diagram feature information and extract the time domain features from shallow to deep, but with a moderate complexity. Additionally, after feature fusion, we adopt the convolution block attention module (CBAM) to reweigh both the channel and spatial domains, further improving the model’s ability to mine signal characteristics. As a result, the proposed approach significantly improves the overall recognition accuracy. The experimental results on the RadioML 2016.10B public dataset, with SNR ranging from −20 dB to 18 dB, show that the proposed M-LSCANet outperforms existing methods in terms of classification accuracy, achieving 93.4% and 95.8% at 0 dB and 12 dB, respectively, which are improvements of 2.7% and 2.0% compared to TMRN-GLU. Moreover, the proposed model exhibits a moderate parameter number compared to state-of-the-art methods.
Low-Profile High-Efficiency Transmitarray Antenna for Beamforming Applications
Authors: Lee Jae-Gon , Lee Jeong-Hae
Published: July 2023

A low-profile high-efficiency transmitarray antenna (TA) for beamforming applications is proposed and investigated in this paper. The partial H-plane waveguide slot array antenna is employed as the compact low-profile feeding structure of the beamforming TA. The designed TA can achieve a high taper efficiency due to the multi-array sources and the compactness of the partial H-plane waveguide. Moreover, the proposed TA can inherently have a high spillover efficiency because the frequency selective surface (FSS) for beamforming is located just above the radiating slot. The FSS with a transmission phase variation of 2π is designed by a square patch array and used to manipulate the wave-front of the transmitted electromagnetic wave instead of a complicated feed network and phase shifters. To verify its beamforming characteristic, three types of FSSs to operate a forming angle of −40°, −20°, 0°, +20°, and +40° are designed at 12 GHz. The distance between the FSS and the slot array antenna is 0.1λ0, and the aperture efficiency is measured to be about 69%. The measured results, such as the reflection coefficient and the far-field radiation pattern, are in good agreement with the simulated results. From the measured results, the proposed TA is confirmed to have good beamforming characteristics and high aperture efficiency.
ClueReader: Heterogeneous Graph Attention Network for Multi-Hop Machine Reading Comprehension
Authors: Gao Peng , Gao Feng , Wang Peng , Ni Jian-Cheng , Wang Fei , Fujita Hamido
Published: July 2023

Multi-hop machine reading comprehension is a challenging task in natural language processing as it requires more reasoning ability across multiple documents. Spectral models based on graph convolutional networks have shown good inferring abilities and lead to competitive results. However, the analysis and reasoning of some are inconsistent with those of humans. Inspired by the concept of grandmother cells in cognitive neuroscience, we propose a heterogeneous graph attention network model named ClueReader to imitate the grandmother cell concept. The model is designed to assemble the semantic features in multi-level representations and automatically concentrate or alleviate information for reasoning through the attention mechanism. The name ClueReader is a metaphor for the pattern of the model: it regards the subjects of queries as the starting points of clues, takes the reasoning entities as bridge points, considers the latent candidate entities as grandmother cells, and the clues end up in candidate entities. The proposed model enables the visualization of the reasoning graph, making it possible to analyze the importance of edges connecting entities and the selectivity in the mention and candidate nodes, which is easier to comprehend empirically. Evaluations on the open-domain multi-hop reading dataset WikiHop and drug–drug interaction dataset MedHop proved the validity of ClueReader and showed the feasibility of its application of the model in the molecular biology domain.
Designs of Array Multipliers with an Optimized Delay in Quantum-Dot Cellular Automata
Authors: Yan Aibin , Li Xuehua , Liu Runqi , Huang Zhengfeng , Girard Patrick , Wen Xiaoqing
Published: July 2023

Quantum-dot cellular automata (QCA) has been considered as a novel nano-electronic technology. With the advantages of low power consumption, high speed, and high integration, QCA has been treated as the potential replacement technology of the CMOS (complementary metal oxide semiconductor) which is currently used in the industry. This paper presents a QCA-based array multiplier with an optimized delay. This type of circuit is the basic building block of many arithmetic logic units and electronic communication systems. Compared to the existing array multipliers, the proposed multipliers have the smallest cell count and area. The proposed designs used a compact clock scheme to reduce the carry delay of the signals. The 2 × 2 array multiplier clock delay was reduced by almost 65% compared to the existing designs. Moreover, since the multiplier exhibits a good scalability, for further proof, we proposed a 3 × 3 array multiplier. Simulation results asserted the feasibility of the proposed multipliers. Extensive comparison results demonstrated that when the design scaling was increased, our proposed designs still displayed an efficient overhead in terms of the delay, cell count, and area. The QCADesigner tool was employed to validate the proposed array multipliers. The QCADesigner-E was used to measure the power dissipation of the alternative compared solutions.
A Multi-Path Inpainting Forensics Network Based on Frequency Attention and Boundary Guidance
Authors: Wang Hongquan , Zhu Xinshan , Sun Hao , Qian Tongyu , Chen Ying
Published: July 2023

With the continuous advancement of image-editing technologies, it is particularly important to develop image forensics methods for digital information security. In this study, a deep neural network called multi-path inpainting forensics network (MPIF-Net) was developed to locate the inpainted regions in an image. The interaction of shallow and deep features between different paths was established, which not only preserved detailed information but also allowed for the further mining of deep features. Meanwhile, an improved residual dense block was employed as the deep feature extraction module of each path, which can enhance the feature extraction ability of the model by introducing a frequency domain attention mechanism. In addition, a boundary guidance module was constructed to alleviate the prediction distortion in the boundaries of the inpainted region. Finally, extensive experimental results regarding various deep inpainting datasets demonstrated that the proposed network can accurately locate inpainted regions, exhibit excellent generalization and robustness, and verify the effectiveness of the designed module.
Optimal Sizing of Photovoltaic/Energy Storage Hybrid Power Systems: Considering Output Characteristics and Uncertainty Factors
Authors: Liu Ye , Zhong Yiwei , Tang Chaowei
Published: July 2023

The integration of PV and energy storage systems (ESS) into buildings is a recent trend. By optimizing the component sizes and operation modes of PV-ESS systems, the system can better mitigate the intermittent nature of PV output. Although various methods have been proposed to optimize component size and achieve online energy management in PV-ESS systems, the optimal interconnection between them has received less attention. In order to maximize the effectiveness of systems with limited component sizes and address the impact of uncertainty on the system, an optimization framework is proposed for determining the optimal size of the PV-ESS system. The proposed framework consists of five parts: determination of optimal size, analysis of component output characteristics, system state prediction, parameter calibration of energy management strategies, and update of system components output features, and it considers uncertain factors, including climate, different components, and battery degradation caused by irregular charging and discharging, to establish the model for energy saving. To validate the results, four different climates in a year were considered. The obtained results indicate that the proposed framework can effectively achieve the optimal working state of the system, realizing a matching degree of 94.55% between the offline size optimization and online management strategy. The proposed framework’s universality and effectiveness were demonstrated through simulation analysis across four cities with different climates in China.
Fungi in a One Health Perspective
Authors: Simões Daniela , de Andrade Eugénia , Sabino Raquel
Published: July 2023

Fungi constitute a diverse group with highly positive and negative impacts in different environments, having several natural roles and beneficial applications in human life, but also causing several concerns. Fungi can affect human health directly, but also indirectly by being detrimental for animal and plant health, influencing food safety and security. Climate changes are also affecting fungal distribution, prevalence, and their impact on different settings. Searching for sustainable solutions to deal with these issues is challenging due to the complex interactions among fungi and agricultural and forestry plants, animal production, environment, and human and animal health. In this way, the “One Health” approach may be useful to obtain some answers since it recognizes that human health is closely connected to animal and plant health, as well as to the shared environment. This review aims to explore and correlate each of those factors influencing human health in this “One Health” perspective. Thus, the impact of fungi on plants, human, and animal health, and the role of the environment as an influencing factor on these elements are discussed.
Comprehensive Evaluation of the Design of a New National Park Using the Quintuple Helix Model
Authors: Sloup Roman , Riedl Marcel , Machoň Miloslav
Published: July 2023

Protected areas serve as stepping stones for the preservation of biodiversity, and can provide economic and social benefits to communities. National parks aim to limit human intervention to safeguard natural communities and processes. This study analyzes the impacts of transforming the Křivoklátsko Protected Landscape Area into the proposed Křivoklátsko National Park in the Czech Republic, which is a program promoted by political parties. Using the quintuple helix model, it assesses the change from a sustainable development perspective. The analysis considers economic, social, and environmental aspects, including the impact on the local inhabitants, the economy, forestry, business activities, and regional development. The existing management in the Křivoklátsko region exemplifies sustainable multifunctional forest management. Based on the evaluation, the study finds insufficient arguments for declaring the Křivoklátsko National Park. The study emphasizes the need to balance the social demand for nature protection with the awareness of existing measures and specific area conditions. Nature protection should integrate itself into all human activities within the culturally and historically created landscape, rather than solely pursuing political goals. Participatory forestry management plays a crucial role in landscape transformation. The study highlights the importance of sustainable landscape development and the interactions between the university, government, industry, and civil sector actors with the environment.
Effects of Heavy Metals on Nitrogen in Soils of Different Ecosystems in the Karst Desertification of South China
Authors: Zhang Le , Xiong Kangning , Wan Panteng
Published: July 2023

Nitrogen, as a crucial limiting nutrient in terrestrial ecosystems, plays a vital role in determining land quality. Heavy metals, as drivers of soil substance transformation, are important indicators for assessing ecosystem function. Currently, the relationship between soil nitrogen and heavy metals in karst desertification areas remains unclear. Therefore, this study focuses on the soil of grassland, forest, and agroforestry ecosystems in a karst desertification area to investigate the relationship between heavy metals and nitrogen distribution using ecological stoichiometry. The findings revealed the following: (i) Total nitrogen (TN) and available nitrogen (AN) exhibited the trend of agroforestry * > forest > grassland, while soil microbial biomass nitrogen (SMBN) showed the trend of forest * > grassland * >> agroforestry; (ii) Chromium (Cr), Ferrum (Fe), Niccolum (Ni), and Plumbum (Pb) showed the trend of agroforestry * > grassland > forest, while Cuprum (Cu) demonstrated the trend of agroforestry > grassland > forest, and Zincum (Zn) exhibited the trend of grassland > forest * >> agroforestry. The Nemerow comprehensive pollution index were 0.77 for grassland, 0.69 for forest, and 0.94 for agroforestry; (iii) The sensitivity of soil nitrogen and heavy metals ranked as grassland > agroforestry > forest. The research findings aim to provide a scientific reference for karst desertification control, ecological protection and restoration, and enhancement of ecosystem function.
Aroma Formation and Dynamic Changes during Sichuan Black Tea Processing by GC–MS-Based Metabolomics
Authors: Jiang Bin , Yang Liran , Luo Xueping , Huang Rongyan , Jiao Wenwen , Zhong Xiaoxue , Li Lixia , Wang Qi , Liu Mingli , Liu Kunyi
Published: July 2023

Sichuan black tea (SCBT) is well known for its pleasant sweet and citrus-like aroma. However, the origin of this distinctive aroma remains unknown. Herein, the aroma characteristics of SCBT during processing were comprehensively investigated by sensory evaluation, gas chromatography–mass spectrometry, and odor activity value (OAV). A total of 764 volatile compounds were identified and grouped into 16 categories. Notably, terpenoids, heterocyclic compounds, and esters comprised 19.35%, 16.34%, and 16.08% of total volatile compounds produced during processing, respectively. Moreover, the fermentation and second drying stages exhibited the most striking variations, with 99 and 123 volatile compounds being significantly altered. In addition, the OAV analysis led to the identification of 17 volatile compounds as key differential volatile compounds (DVCs): these included citronellol, linalool, p-cymene, (E)-linalool oxide (furanoid), etc. Among them, (3Z)-3,7-dimethylocta-1,3,6-triene and D-limonene that exhibited a grassy aroma decreased during processing, while linalool and p-cymene that had a sweet and citrus aroma increased. Thus, based on a correlation between characteristic aroma data and descriptive sensory analysis data, linalool and p-cymene were identified as the primary volatiles responsible for the sweet and citrus-like aroma. In conclusion, this study improves our understanding of the components and formation mechanism of the sweet and citrus-like aroma of SCBT.
Valorisation of Waste Bread for the Production of Yeast Biomass by Yarrowia lipolytica Bioreactor Fermentation
Authors: Carsanba Erdem , Agirman Bilal , Papanikolaou Seraphim , Fickers Patrick , Erten Huseyin
Published: July 2023

The increase in the wastage of bread, representing 12.5 million tons per year, causes ecological problems, such as the production of methane and CO2, when that waste bread (WB) is improperly managed. To reduce this ecological footprint, a more sustainable system of WB management must be set up. Based on its chemical composition, WB has a high potential to be used as feedstock for microbial growth and conversion into value-added bio products. The microbial valorisation of WB is a novel biotechnological approach to upgrading a waste into a renewable feedstock for bio-based industry, thus favouring the circular economy concept. Based on this, the aim of this study was to test WB as a feedstock for biomass production by Yarrowia lipolytica, which can be considered as a promising supplement for animal and human dietary products. The enzymatic hydrolysis of WB was primarily optimized for large-scale production in a bioreactor. The biomass production of Y. lipolytica strain K57 on WB hydrolysate-based media in batch bioreactor culture was then investigated. As a result, a very high starch to glucose conversion yield of 97% was obtained throughout optimised hydrolysis. At the end of 47 h of batch culture, a biomass higher than 62 g/L, specific growth rate of 0.37 h−1 and biomass yield of 0.45 g/g were achieved from a WB hydrolysate. Therefore, this study demonstrates that WB hydrolysate has a promising potential to be used as a feedstock for biomass production by Y. lipolytica strain K57 for food and animal diet applications.