bluuebunny/crossref_metadata_2025 huggingface dataset:
Health Literacy and Its Association with the Adoption of the Mediterranean Diet: A Cross-Sectional Study
Authors: Duarte Ana , Martins Juliana , Lopes Cristiana , Silva Maria José , Augusto Cláudia , Martins Silvana Peixoto , Rosário Rafaela
Published: July 2024

Health literacy (HL) is a crucial factor influencing health-related decisions, including dietary patterns. The Mediterranean diet is widely recognized as one of the healthiest eating patterns. This study aims to explore the association between HL levels among adults in socially vulnerable contexts and their adoption of the Mediterranean diet. Conducted as part of a cluster-randomized trial in primary schools, the research involved 557 parents of children aged 6 to 10 who consented to participate. HL was assessed using the HLS questionnaire, while adoption of the Mediterranean diet was evaluated using the MEDAS questionnaire. Participants also provided anthropometric and sociodemographic data via a questionnaire, from which BMI was calculated (weight/height2). Education level was categorized as higher education or lower and professional status was classified based on occupational categories. Generalized linear models and logistic regression were employed for analysis. The findings indicate a direct association between HL level and adoption of the Mediterranean diet (B = 0.022, 95% CI 0.010–0.035, p < 0.001), underscoring the influence of HL on dietary choices. Specifically, the healthcare dimension of HL emerges as pivotal in shaping dietary behaviors, particularly towards the Mediterranean diet. These results underscore the importance of policies and programs aimed at enhancing HL, especially among socially vulnerable populations. Prioritizing public health interventions to improve HL is critical for promoting better dietary decision-making.
Knee Extensor Muscle Strength Associated with the Onset of Depression in Older Japanese Women: The Otassha Study
Authors: Ohta Takahisa , Kojima Narumi , Osuka Yosuke , Sasai Hiroyuki
Published: July 2024

We examined whether knee extensor muscle strength can predict the onset of depressive symptoms in older Japanese women living in Tokyo. A baseline comprehensive geriatric examination was conducted to evaluate isometric knee extensor muscle strength and depressive symptoms (using Geriatric Depression Scale [GDS]) in 2017–2019. A free of neurological disease participants received a series of follow-up examinations following an initial evaluation. A GDS score of ≥5 during follow-up marked the onset of depressive symptoms. A logistic regression model was established after adjustment of baseline GDS score for variables including age, body mass index, smoking, alcohol consumption, comorbidities, working status, hobbies, volunteering, years of education, and dietary variety. Of the 1845 recruited individuals, 1409 were eligible to be targeted for follow-up. Among them, 768 women provided two-year follow-up data and contributed the final analysis. After covariate adjustments, the odds ratios (95% confidence interval) for depressive symptoms were 0.68 (0.39, 1.20) and 0.48 (0.26, 0.91) for the middle and highest tertiles of muscle strength, respectively, using the lowest tertile as reference. A dose-response association between muscle strength and depression (p = 0.022) was identified. This study suggests an inverse dose-response relationship between knee extensor muscle strength and the onset of depressive symptoms in older Japanese women.
Insulin-Mimetic Activity of Herbal Extracts Identified with Large-Scale Total Internal Reflection Fluorescence Microscopy
Authors: Neuhauser Cathrina , Schwarzinger Bettina , Schwarzinger Clemens , Feichtinger Michaela , Stadlbauer Verena , Arnaut Verena , Drotarova Ivana , Blank-Landeshammer Bernhard , Weghuber Julian
Published: July 2024

Diabetes mellitus is a spreading global pandemic. Type 2 diabetes mellitus (T2DM) is the predominant form of diabetes, in which a reduction in blood glucose uptake is caused by impaired glucose transporter 4 (GLUT4) translocation to the plasma membrane in adipose and muscle cells. Antihyperglycemic drugs play a pivotal role in ameliorating diabetes symptoms but often are associated with side effects. Hence, novel antidiabetic compounds and nutraceutical candidates are urgently needed. Phytogenic therapy can support the prevention and amelioration of impaired glucose homeostasis. Using total internal reflection fluorescence microscopy (TIRFM), 772 plant extracts of an open-access plant extract library were screened for their GLUT4 translocation activation potential, resulting in 9% positive hits. Based on commercial interest and TIRFM assay-based GLUT4 translocation activation, some of these extracts were selected, and their blood glucose-reducing effects in ovo were investigated using a modified hen’s egg test (Gluc-HET). To identify the active plant part, some of the available candidate plants were prepared in-house from blossoms, leaves, stems, or roots and tested. Acacia catechu (catechu), Pulmonaria officinalis (lungwort), Mentha spicata (spearmint), and Saponaria officinalis (common soapwort) revealed their potentials as antidiabetic nutraceuticals, with common soapwort containing GLUT4 translocation-activating saponarin.
Spontaneous Formation of Strained Anti-Bredt Bridgehead Alkenes upon Computational GeometryOptimization of Bicyclic β-Halo Carbanions
Authors: Breton Gary W. , Ridlehoover Jazmine V.
Published: July 2024

Bridgehead alkenes are polycyclic molecules bearing at least one C=C bond that includes a bridgehead carbon atom. For small bicyclic systems, these bonds are highly strained due to geometric constraints placed on the sp2 hybridized carbon atoms. These small, strained molecules have been termed “anti-Bredt” alkenes. β-halo carbanions have served as convenient precursors to bridgehead alkenes in experimental studies. We observed that upon attempted computational geometric optimizations (ωB97X-D/aug-cc-pVDZ) of the precursors, spontaneous elimination of the halide occurs along with formation of the anti-Bredt alkene in many cases. Such computational eliminations were shown to faithfully mimic experimentally obtained results. Computational elimination was not observed for [1.1.1] or [2.1.1] frameworks, in agreement with predictions that these bridgehead alkenes are too strained to be formed. However, computational elimination from the [2.2.1] framework was observed to form 1-norbornene, a compound suggested in experimental work to be a reactive intermediate. Similarly, [3.1.1] frameworks and higher led to eliminations upon computational geometric optimization, in agreement with experimental findings. Natural bond order (NBO) calculations of the starting geometries proved to be excellent predictors as to whether elimination would take place. Those precursor compounds exhibiting delocalization energies in the order of 10 kcal/mol between the lone-pair electrons of the carbon atom and σ*C-Br were generally found to undergo elimination. Thus, computational optimization of β-halo substituted bicyclic precursor anions can be used to predict whether strained anti-Bredt alkenes are likely to be formed, thereby saving valuable time and costs in the experimental lab.
Oxidative Stress Responses in Obese Individuals Undergoing Bariatric Surgery: Impact on Carcinogenesis
Authors: Ribeiro Daniel Araki , da Silva Glenda Nicioli , Malacarne Ingra Tais , Pisani Luciana Pellegrini , Salvadori Daisy Maria Favero
Published: July 2024

Obesity is a big public health problem that claims several thousand lives every year. Bariatric surgery has arisen as a suitable procedure for treating obesity, particularly morbid obesity. Oxidative stress, genotoxicity, apoptosis, and inflammatory responses are recognized as the most important occurrences in carcinogenesis, as they actively contribute to the multistep process. This study aimed to briefly review the connection between oxidative stress, genotoxicity, apoptosis, and inflammation in obese patients undergoing bariatric surgery, focusing on its impact on carcinogenesis. Regarding oxidative stress, bariatric surgery may inhibit the synthesis of reactive oxygen species. Moreover, a significant reduction in the inflammatory status after weight loss surgery was not observed. Bariatric surgery prevents apoptosis in several tissues, but the maintenance of low body weight for long periods is mandatory for mitigating DNA damage. In conclusion, the association between bariatric surgery and cancer risk is still premature. However, further studies are yet needed to elucidate the real association between bariatric surgery and a reduced risk of cancer.
Local Anaesthesia Techniques in Dogs and Cats: A Review Study
Authors: Margeti Chrysoula , Kostakis Charalampos , Tsioli Vassiliki , Karagianni Konstantina , Flouraki Eugenia
Published: July 2024

The use of multimodal anaesthesia and analgesia is desirable as part of a complete analgesic plan. Analgesic strategies for perioperative pain treatment include combinations of drugs with different means of action to increase their efficacy and to reduce the required doses and adverse effects. Local anaesthetics prevent the transduction and transmission of painful stimuli through their action on neuronal cell membranes. They undergo minimal systemic absorption and are therefore ideal alternatives to drugs that could result in systemic toxicity. Numerous benefits have been recognised for the use of local anaesthesia, such as a decreased need for systemic analgesics and decreased hospitalisation periods. Local anaesthetics have been used in veterinary medicine in several ways. Anatomical landmarks can be used to identify the target nerves and the clinician can employ an electrical nerve stimulator or ultrasound guidance to perform a more accurate injection. Local anaesthetic techniques can implement other drugs, apart from or in combination with local anaesthetics, such as opioids, α2−adrenergic agonists or vasoconstricting agents. This review article presents and discusses the most common techniques of local anaesthetic use in small animals, with the aim of providing the clinician with further and comprehensive information regarding the analgesic options during the perioperative period.
Aronia Berry Extract Modulates MYD88/NF-kB/P-Glycoprotein Axis to Overcome Gemcitabine Resistance in Pancreatic Cancer
Authors: Li Yuan , Xu Caiming , Han Haiyong , Pascual-Sabater Silvia , Fillat Cristina , Goel Ajay
Published: July 2024

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease with poor survival rates, primarily due to the limited effectiveness of gemcitabine (Gem)-based chemotherapy, as well as the acquisition of chemotherapeutic resistance. Aronia berry extracts (ABEs), abundant in phenolic constituents, have been recently recognized for their anticancer properties as well as their encouraging potential to help overcome chemoresistance in various cancers. In the present study, we explored ABE’s potential to overcome Gem resistance in PDAC and identify specific growth regulatory pathways responsible for its anticancer activity. Through a series of in vitro experiments in gemcitabine-resistant (Gem-R) cells, we elucidated the synergistic interactions between Gem and ABE treatments. Using advanced transcriptomic analysis and network pharmacology, we revealed key molecular pathways linked to chemoresistance and potential therapeutic targets of ABE in Gem-R PDAC cells. Subsequently, the findings from cell culture studies were validated in patient-derived 3D tumor organoids (PDOs). The combination treatment of ABE and Gem demonstrated significant synergism and anticancer effects on cell viability, proliferation, migration, and invasion in Gem-R cells. Transcriptomic analysis revealed a correlation between the NF-Κb signaling pathway and Gem-R (p < 0.05), exhibiting a marked upregulation of MYD88. Additionally, MYD88 exhibited a significant correlation with the overall survival rates in patients with PDAC patients in the TCGA cohort (HR = 1.58, p < 0.05). The MYD88/NF-Κb pathway contributes to chemoresistance by potentially upregulating efflux transporters like P-glycoprotein (P-gp). Our findings revealed that the combined treatment with ABE suppressed the NF-Κb pathway by targeting MYD88 and reducing P-gp expression to overcome Gem resistance. Lastly, the combination therapy proved highly effective in PDOs in reducing both their number and size (p < 0.05). Our study offers previously unrecognized insights into the ability of ABE to overcome Gem resistance in PDAC cells through its targeting of the MYD88/NF-κb/P-gp axis, hence providing a safe and cost-effective adjunctive therapeutic strategy to improve treatment outcomes in PDAC.
Poisson’s Ratio Prediction of Injection Molded Thermoplastics Using Differential Scanning Calorimetry
Authors: Takayama Tetsuo , Nagasawa Yuuki
Published: July 2024

In the development of thermoplastic products, it is necessary to conduct the necessary mechanical tests and evaluate the reliability of thermoplastics in each case, because the mechanical properties of the same material vary depending on the molding process conditions and product shape. In order to build a sustainable society, it is expected that the evaluation of the mechanical properties of thermoplastics, which are resource and energy saving, will be required. In this paper, the glass transition temperature and melting point of injection-molded thermoplastics were evaluated by differential scanning calorimetry, and the correlation between Poisson’s ratio and free volume was obtained by applying the theory proposed by Flory et al. A certain correlation was found between the Poisson’s ratio of polymers and the change in free volume determined by the glass transition temperature. It is also clear that this relationship can be approximated by orders of magnitude. The Poisson’s ratio of the core layer tended to be smaller than that of the skin layer. It has also been found that there is a negative correlation between the Young’s modulus and the free volume of the polymer material.
Poly Lactic-co-Glycolic Acid (PLGA) Loaded with a Squaraine Dye as Photosensitizer for Antimicrobial Photodynamic Therapy
Authors: Dereje Degnet Melese , Pontremoli Carlotta , García Ana , Galliano Simone , Colilla Montserrat , González Blanca , Vallet-Regí María , Izquierdo-Barba Isabel , Barbero Nadia
Published: July 2024

Antimicrobial Photodynamic Therapy (aPDT) is an innovative and promising method for combating infections, reducing the risk of antimicrobial resistance compared to traditional antibiotics. Squaraine (SQ) dyes can be considered promising photosensitizers (PSs) but are generally hydrophobic molecules that can self-aggregate under physiological conditions. To overcome these drawbacks, a possible solution is to incorporate SQs inside nanoparticles (NPs). The present work deals with the design and development of innovative nanophotosensitizers based on poly lactic-co-glycolic acid (PLGA) NPs incorporating a brominated squaraine (BrSQ) with potential application in aPDT. Two designs of experiments (DoEs) based on the single emulsion and nanoprecipitation methods were set up to investigate how different variables (type of solvent, solvent ratio, concentration of PLGA, stabilizer and dye, sonication power and time) can affect the size, zeta (ζ)-potential, yield, entrapment efficiency, and drug loading capacity of the SQ-PLGA NPs. SQ-PLGA NPs were characterized by NTA, FE-SEM, and UV-Vis spectroscopy and the ability to produce reactive oxygen species (ROS) was evaluated, proving that ROS generation ability is preserved in SQ-PLGA. In vitro antimicrobial activity against Gram-positive bacteria in planktonic state using Staphylococcus aureus was conducted in different conditions and pH to evaluate the potential of these nanophotosensitizers for aPDT in the local treatment of infections.
Variations in the Thermomechanical and Structural Properties during the Cooling of Shape-Memory R-PETG
Authors: Sava Ștefan-Dumitru , Pricop Bogdan , Comăneci Radu-Ioachim , Cimpoeșu Nicanor , Popa Mihai , Lohan Nicoleta-Monica , Bujoreanu Leandru-Gheorghe
Published: July 2024

One of the useful features of 3D-printed specimens of recycled polyethylene terephthalate glycol (R-PETG) is the ability to repetitively develop free recovery as well as the work-generating, shape-memory effect. This behavior is enabled by the R-PETG’s capacity to stiffen during cooling, thus allowing for a new temporary shape to be induced. Aiming to devise an explanation for the polymer’s stiffening, in this study, the variation in some of the R-PETG’s parameters during cooling are emphasized and discussed. The evolution of an R-PETG filament’s shape was monitored during room-temperature-bending heating–cooling cycles. Straight-shape recovery and the complete loss of stiffness were observed at the start and the end of heating, respectively, followed by the forced straightening of the filament, performed by the operator, around 40 °C, during cooling. The tests performed by dynamic mechanical analysis disclosed the rise of the storage modulus (E’) after 100 °C heating followed by either liquid-nitrogen- or air-cooling to room temperature, in such a way that E’ was always larger after cooling than initially. Static tests emphasized a peculiar stress variation during a heating–cooling cycle applied in air, within the heating chamber of the tensile testing machine. Tensile-failure tests were performed at −10 °C at a rate of 100 mm/min, with specimens printed at various deposition directions between 10 and 40° to the transversal direction. The specimens printed at 40°, which had the largest ultimate strains, were broken with tensile rates between 100 and 500 mm/min. Deformation rate increase favored the shift from crazing to delamination failure modes. The correlation between the structural changes, the sharp E’ increase on heating, and the stiffening induced by cooling represents a novel approach that enables the use of 3D-printed R-PETG for the fabrication of the active parts of low-priced lightweight resettable actuators.
Preparation of 6-Amino-N-hydroxyhexanamide-Modified Porous Chelating Resin for Adsorption of Heavy Metal Ions
Authors: Liu Shaomin , Wang Zihan , He Mingyi , Zhu Jinglin
Published: July 2024

The pollution of water bodies by heavy metal ions has recently become a global concern. In this experiment, a novel chelating resin, D851-6-AHHA, was synthesized by grafting 6-amino-N-hydroxyhexanamide (6-AHHA) onto the (-CH2N-(CH2COOH)2) group of the D851 resin, which contained a hydroxamic acid group, amide group, and some carboxyl groups. This resin was developed for the purpose of removing heavy metal ions, such as Cr(III) and Pb(II), from water. The findings from static adsorption experiments demonstrated the remarkable adsorption effectiveness of D851-6-AHHA resin towards Cr(III) and Pb(II). Specifically, the maximum adsorption capacities for Cr(III) and Pb(II) were determined to be 91.50 mg/g and 611.92 mg/g, respectively. Furthermore, the adsorption kinetics of heavy metal ions by D851-6-AHHA resin followed the quasi-second-order kinetic model, while the adsorption isotherms followed the Langmuir model. These findings suggest that the adsorption process was characterized by monolayer chemisorption. The adsorption mechanism of D851-6-AHHA resin was comprehensively investigated through SEM, XRD, FT-IR, and XPS analyses, revealing a high efficiency of D851-6-AHHA resin in adsorbing Cr(III) and Pb(II). Specifically, the (-C(=O)NHOH) group exhibited a notable affinity for Cr(III) and Pb(II), forming stable multi-elemental ring structures with them. Additionally, dynamic adsorption experiments conducted using fixed-bed setups further validated the effectiveness of D851-6-AHHA resin in removing heavy metal ions from aqueous solutions. In conclusion, the experimental findings underscored the efficacy of D851-6-AHHA resin as a highly efficient adsorbent for remediating water bodies contaminated by heavy metal ions.
The Glucans Mushrooms: Molecules of Significant Biological and Medicinal Value
Authors: Flores Giancarlo Angeles , Cusumano Gaia , Venanzoni Roberto , Angelini Paola
Published: July 2024

Mushroom polysaccharides, key components of fungal cell walls, exhibit various biological properties and hold significant medicinal and industrial value. These polysaccharides are known for their medicinal properties like antitumor, antioxidant, anticancer, immunomodulatory, and antiviral properties. Mushroom polysaccharides, particularly β-glucans, α-glucans, and chitin, have been associated with various health benefits. β-glucans are well studied for their bioactivities, while α-glucans and chitin have gained attention for their prebiotic, antimicrobial, and wound-healing properties. The therapeutic effects of these polysaccharides are closely linked to their chemical structures, including molecular weight, monosaccharide composition, and glycosidic bond types. This work aims to review the studies on mushroom polysaccharides, with a particular focus on their structural composition to deepen medicinal properties of mushroom polysaccharides. Also, the extraction methods and the pharmaceutical application of polysaccharides will be revised in this work.
Assessment of Novel Protein Ingredient Arthrospira platensis and Soybean Genotype Amino Acid and Oil Selection Improvements on Broiler Performance for a 28–42 d Feeding Period
Authors: Wells-Crafton Savannah C. , Nelson Kenneth B. , Mullenix Garrett J. , Maynard Craig W. , Kidd Michael T.
Published: July 2024

Two experiments were conducted to assess the efficiency of including the novel protein ingredient Arthrospira platensis or improved soybean meal in a broiler diet. The first experiment aimed to determine the feeding value of soybean meal produced from varieties of soybeans bred for increased amino acid content (SBAA) and improved oil content (SBO) compared to a conventional soybean variety in an ANOVA design fed to Cobb 500 female broilers for 28–42 d. The SBAA and SBO soybeans contained overall higher amino acid content and lower oligosaccharide content compared to the conventional soybean variety in addition to improved oil quality. The second experiment assessed the novel protein ingredient microalgae, Arthrospira platensis (algae), and was conducted to evaluate algae and corn distillers’ grain (DDGS) inclusion on broiler performance for a 28–42 d feeding period in Cobb CF05 male broilers with a 2 × 2 factorial treatment array. Prior to the experimental period, all birds were reared on common feeds. In Experiment 1, birds were fed a diet containing 20% inclusion of an experimental soybean source in the form of full-fat soybean meal. In Experiment 2, the four dietary treatments consisted of diets containing algae at inclusion levels of either 0 or 2% and DDGS at inclusion levels of 0% and 8%. Diets were fed to 288 female broilers (Experiment 1) and 384 male broilers (Experiment 2), placed in eight replicate pens of twelve birds, and live performance was assessed from d 28 to 42. At d 42, six birds from each pen were randomly selected and processed for evaluation of carcass traits and incidence of woody breast. For Experiment 1, all performance data were analyzed using a one-way ANOVA using JMP Pro 16 software with diet as the fixed effect and block as a random effect. Statistical significance was considered at p ≤ 0.05. No significant responses were observed for any recorded measurement for live performance, carcass traits, or woody breast. All data in Experiment 2 were analyzed as a full factorial with a mixed model using JMP software with algae, DDGS, and algae × DDGS as fixed effects and block as a random effect. The F-protected Fisher’s LSD test was used to separate means when p ≤ 0.05. No significant responses were observed for the algae, DDGS, and algae × DDGS influences on BWG, FI, and FCR or processing characteristics; the ingredient source did not affect bird performance. Experimental soybean lines developed at the University of Arkansas were able to be incorporated into broiler diets without decreasing performance. Algae has the potential to be a protein-contributing ingredient for broilers.
Observations about Holistic Care from the Experience of a Medical Student Shadowing a Chaplain
Authors: Krauss Anna , Carter Robert T.
Published: July 2024

The project was initiated when a medical student expressed interest in shadowing a chaplain during their third-year clinical rotations. The Hospital Library Service supported this inquiry by providing readings about intentional programs and a medical practitioner spiritual screening for both the chaplain and student to review. By coordinating with the student’s medical supervision, different times were found throughout the day such that a variety of pastoral care instances could be observed. As part of the welcome extended to each patient, the chaplain introduced the medical student and obtained consent for them to be present during the care conversations that followed. These visits occurred over two months in the spring of 2024. This experience provided an opportunity for both the chaplain and student to reflect on the process of acknowledging, confirming, affirming, and encouraging patients and their families. Additionally, through these visits and subsequent conversations, a holistic health and wellness model was used to emphasize compassionate and spiritual patient care.
An Improved Underwater Visual SLAM through Image Enhancement and Sonar Fusion
Authors: Qiu Haiyang , Tang Yijie , Wang Hui , Wang Lei , Xiang Dan , Xiao Mingming
Published: July 2024

To enhance the performance of visual SLAM in underwater environments, this paper presents an enhanced front-end method based on visual feature enhancement. The method comprises three modules aimed at optimizing and improving the matching capability of visual features from different perspectives. Firstly, to address issues related to insufficient underwater illumination and uneven distribution of artificial light sources, a brightness-consistency recovery method is proposed. This method employs an adaptive histogram equalization algorithm to balance the brightness of images. Secondly, a method for denoising underwater suspended particulates is introduced to filter out noise from images. After image-level processing, a combined underwater acousto–optic feature-association method is proposed, which associates acoustic features from sonar with visual features, thereby providing distance information for visual features. Finally, utilizing the AFRL dataset, the improved system incorporating the proposed enhancement methods is evaluated for its performance against the OKVIS framework. The system achieves a better trajectory estimation accuracy compared to OKVIS and demonstrates robustness in underwater environments.
DOA Estimation Based on Virtual Array Aperture Expansion Using Covariance Fitting Criterion
Authors: Ma Teng , Yang Minglei , Zhu Hangui , Zhang Yule , Zhou Dingsen
Published: July 2024

Providing higher precision Direction of Arrival (DOA) estimation has become a hot topic in the field of array signal processing for parameter estimation in recent years. However, when the physical aperture of the actual array is small, its aperture limitation means that even with super-resolution estimation algorithms, the achievable estimation precision is limited. This paper takes a novel approach by constructing an optimization algorithm using the covariance fitting criterion based on the array output’s covariance matrix to fit and obtain the covariance matrix of a large aperture virtual array, thereby providing high-precision angular resolution through virtual aperture expansion. The covariance fitting expansion analysis and discussion are unfolded for both uniform linear arrays (ULAs) and sparse linear arrays (SLAs) under four different scenarios. Theoretical analysis and simulation experiments demonstrate that these methods can enhance the effective performance of angle estimation, especially in low signal-to-noise ratios (SNRs) and at small angular intervals by fitting virtual extended aperture data.
Graph Neural Networks in Point Clouds: A Survey
Authors: Li Dilong , Lu Chenghui , Chen Ziyi , Guan Jianlong , Zhao Jing , Du Jixiang
Published: July 2024

With the advancement of 3D sensing technologies, point clouds are gradually becoming the main type of data representation in applications such as autonomous driving, robotics, and augmented reality. Nevertheless, the irregularity inherent in point clouds presents numerous challenges for traditional deep learning frameworks. Graph neural networks (GNNs) have demonstrated their tremendous potential in processing graph-structured data and are widely applied in various domains including social media data analysis, molecular structure calculation, and computer vision. GNNs, with their capability to handle non-Euclidean data, offer a novel approach for addressing these challenges. Additionally, drawing inspiration from the achievements of transformers in natural language processing, graph transformers have propelled models towards global awareness, overcoming the limitations of local aggregation mechanisms inherent in early GNN architectures. This paper provides a comprehensive review of GNNs and graph-based methods in point cloud applications, adopting a task-oriented perspective to analyze this field. We categorize GNN methods for point clouds based on fundamental tasks, such as segmentation, classification, object detection, registration, and other related tasks. For each category, we summarize the existing mainstream methods, conduct a comprehensive analysis of their performance on various datasets, and discuss the development trends and future prospects of graph-based methods.
Multi-Scale Marine Object Detection in Side-Scan Sonar Images Based on BES-YOLO
Authors: Ma Quanhong , Jin Shaohua , Bian Gang , Cui Yang
Published: July 2024

Aiming at the problem of low accuracy of multi-scale seafloor target detection in side-scan sonar images with high noise and complex background texture, a model for multi-scale target detection using the BES-YOLO network is proposed. First, an efficient multi-scale attention (EMA) mechanism is used in the backbone of the YOLOv8 network, and a bi-directional feature pyramid network (Bifpn) is introduced to merge the information of different scales, finally, a Shape_IoU loss function is introduced to continuously optimize the model and improve its accuracy. Before training, the dataset is preprocessed using 2D discrete wavelet decomposition and reconstruction to enhance the robustness of the network. The experimental results show that 92.4% of the mean average accuracy at IoU of 0.5 (mAP@0.5) and 67.7% of the mean average accuracy at IoU of 0.5 to 0.95 (mAP@0.5:0.95) are achieved using the BES-YOLO network, which is an increase of 5.3% and 4.4% compared to the YOLOv8n model. The research results can effectively improve the detection accuracy and efficiency of multi-scale targets in side-scan sonar images, which can be applied to AUVs and other underwater platforms to implement intelligent detection of undersea targets.
On the Impulse Response of Singular Discrete LTI Systems and Three Fourier Transform Pairs
Authors: Zhou Qihou
Published: July 2024

A basic tenet of linear invariant systems is that they are sufficiently described by either the impulse response function or the frequency transfer function. This implies that we can always obtain one from the other. However, when the transfer function contains uncanceled poles, the impulse function cannot be obtained by the standard inverse Fourier transform method. Specifically, when the input consists of a uniform train of pulses and the output sequence has a finite duration, the transfer function contains multiple poles on the unit cycle. We show how the impulse function can be obtained from the frequency transfer function for such marginally stable systems. We discuss three interesting discrete Fourier transform pairs that are used in demonstrating the equivalence of the impulse response and transfer functions for such systems. The Fourier transform pairs can be used to yield various trigonometric sums involving sin⁡πk/Nsin⁡πLk/N, where k is the integer summing variable and N is a multiple of integer L.
Human-Centric Collaboration and Industry 5.0 Framework in Smart Cities and Communities: Fostering Sustainable Development Goals 3, 4, 9, and 11 in Society 5.0
Authors: Adel Amr , HS Alani Noor
Published: July 2024

The necessity for substantial societal transformations to meet the Sustainable Development Goals (SDGs) has become more urgent, especially in the wake of the COVID-19 pandemic. This paper examines the critical role of disruptive technologies, specifically Industry 5.0 and Society 5.0, in driving sustainable development. Our research investigation focuses on their impact on product development, healthcare innovation, pandemic response, and the development of nature-inclusive business models and smart cities. We analyze how these technologies influence SDGs 3 (Good Health and Well-Being), 4 (Quality Education), 9 (Industry, Innovation, and Infrastructure), and 11 (Sustainable Cities and Communities). By integrating these concepts into smart cities, we propose a coordinated framework to enhance the achievement of these goals. Additionally, we provide a SWOT analysis to evaluate this approach. This study aims to guide industrialists, policymakers, and researchers in leveraging technological advancements to meet the SDGs.
Research on the Configuration Paths of Low-Carbon Transformation of Heavily Polluting Enterprises
Authors: Su Xianna , Ding Shujuan
Published: July 2024

In the context of escalating environmental and climate concerns, it is imperative for enterprises to embark on carbon emission reduction initiatives. Exploring the driving pathways for corporate low-carbon transformation is crucial for the development of a green economy. In this paper, various configuration pathways that may drive heavily polluting industrial enterprises towards green and low-carbon transformation were investigated based on the Technology–Organization–Environment (TOE) theoretical framework and the fuzzy set qualitative comparative analysis (fsQCA) method. The results indicated the following: (1) the low-carbon transformation of heavily polluting enterprises is the result of the joint action of multiple factors; (2) there are eight pathways that can promote corporate low-carbon transformation, roughly divided into single-factor driving types (including MEA drive, DT drive, and GI drive), dual-factor driving types (DT–ER drive and DT–ESGR drive), and multi-factor driving types (including GI–DT–MEA–ER drive, GI–FS–ER drive, and GI–FS–ESGR drive). It can be concluded that there can be certain substitutions between green technology innovation and digital transformation, and environmental regulations and ESG ratings. (3) GI and DT are crucial to the low-carbon transformation of heavily polluting enterprises, and the latter has a more significant impact on promoting low-carbon transformation. MEA is also worthy of attention. The research conclusions not only provide theoretical support for the low-carbon transformation of heavily polluting industrial enterprises but also have valuable reference significance for other industry enterprises, and even the whole of society, to achieve green sustainable development.
The Procurement 4.0 Contributions to Circular Economy
Authors: Bueno Robson Elias , Pohlmann Mayara Neves , dos Santos Helton Almeida , Gonçalves Rodrigo Franco
Published: July 2024

This study examines the potential of Procurement 4.0 as a driving force for the circular economy. While the circular economy’s principles are gaining increasing importance, their impact on established procurement practices necessitates exploration. This research investigates how Procurement 4.0 contributes to circularity within business processes. By employing the Delphi Method, the study identifies Industry 4.0 applications that hold promise for optimizing procurement within a circular economy framework. The findings demonstrate that Procurement 4.0, aligned with sustainability goals and leveraging enabling technologies, can enhance business competitiveness in a circular economy context.
Identifying Interest Rate Transmission Mechanism under a Bayesian Network
Authors: Chun Byoung Jo
Published: July 2024

This study examines causal relationships among various short- and long-term interest rates in the Korean financial market to identify transmission channels. Monthly time series data from January 2015 to February 2024 were used, covering nine interest rates, including call rates, commercial paper (CP) rates, bank lending rates, and Treasury bond yields of different maturities. The study employs a Bayesian network to identify an acyclic causal structure between interest rates alongside a vector error correction model (VECM) to capture long-term equilibrium relationships and short-term dynamics. The findings reconfirm the traditional call rate transmission mechanism, aligning with conventional monetary policy views, demonstrating the call rate’s significant influence on bank lending rates, which affects corporate bond spreads and CP rates. Additionally, it reveals that 10-year Treasury bond yields form an independent interest rate transmission pathway, a finding not previously identified in the literature. These results underscore the need for coordinated monetary and fiscal policies due to the distinct transmission pathways of Treasury yields for sustainable macroeconomic management and growth.
Small Autonomous Vehicles in Pedestrian Contexts: A First Analysis of Logistics Performances in Terms of Commercial Speed
Authors: Cepolina Elvezia Maria , Malisetty Venkata Akhil Babu , Bruzzone Agostino
Published: July 2024

There is a lot of talk about autonomous vehicles, and Europe is very much focusing on their use and deployment. However, the field use of these vehicles is still very limited. The proposed research refers to a specific category of autonomous vehicles, that is, small ground autonomous vehicles circulating in pedestrian environments, with a focus on their use in operating logistical services. More precisely, this paper presents data collected during a challenging experiment carried out in the city of Trikala, Greece, in the context of the major European project “SHOW”. A statistical analysis of these sampled data concerning service times, in terms of commercial speed, for collecting organic waste from cafeterias is presented. The aim of this paper is to verify whether data collected from autonomous vehicles used for this service are reliable and whether accurate estimates can be derived from these data to be used as standard parameters of these vehicles. For these reasons, we analyze the operational performance of the service performed by small autonomous vehicles, with particular attention to the interactions between them and pedestrians and the ability of users to load and unload small vehicles. More precisely, we verify whether there is an adaptation period in which human–vehicle interactions become smoother and whether commercial speed varies at different times of day, that is, if there are peak periods in which droid speed is limited because of the intensity of interactions with pedestrians. A statistical analysis of these data is proposed to find answers to these research questions. It made it possible to highlight an adaptation curve of humans to droids and that no peak periods emerged where droid speed was limited because of the intensity of interactions with pedestrians. This result is probably related to the fact that stability of service operation was not achieved. Had the period of experimentation been extended, it would probably have been possible to identify peak and off-peak periods and the relative commercial speeds. However, it is important to note that the achievement of service operation stability takes a long time. The results obtained are interesting and contribute to the current state of knowledge. In fact, data analyzed here are collected on public land, refer to interactions that take place between small autonomous ground vehicles and a heterogeneous population, and therefore constitute a starting point for the development of technologies that facilitate human–driver interactions and thus lead to an improvement in the performance of sustainable logistics services managed by autonomous vehicles and facilitate their dissemination.
A Digital Framework for the Implementation of the Circular Economy in the Construction Sector: Expert Opinions
Authors: Charef Rabia
Published: July 2024

The construction sector plays a significant role in resource consumption and waste generation, making the transition to a circular economy (CE) imperative for sustainability in this sector. This paper focuses on developing a framework for implementing CE principles in the construction sector, guided by expert opinions and insights. The main objective of this study was to enhance existing theoretical frameworks by incorporating feedback from construction experts to improve practical utility and applicability in real-world construction practices. By addressing key areas for enhancement, the revised framework facilitates the adoption of CE practices throughout the asset lifecycle, considering buildings from cradle to cradle. This research’s methodology involved a comprehensive literature review to identify gaps in current frameworks related to CE implementation in the construction sector. Unstructured interviews with twenty construction experts were conducted to gather insights and recommendations for framework improvement. Data analysis highlighted the importance of integrating CE principles at various stages of the asset lifecycle, such as design, construction, and end-of-life phases. The key recommendations from experts include incorporating sustainable approaches, aligning with BIM models, and considering whole-life design aspects to promote circularity in the construction sector. By incorporating expert feedback and industry insights, the framework aims to guide practitioners toward more sustainable and resource-efficient construction practices, contributing to the broader field of CE implementation in the built environment.
A Case Study on the Operational Performance Evaluation of a Manufacturing Process and System (MaPS) Sustainability Analysis Tool for Engineering Education
Authors: Raoufi Kamyar , Haapala Karl R.
Published: July 2024

As the future product and process design decision-makers, students in engineering should have knowledge of sustainability and its application in industry. However, educators are challenged in training students in these concepts. Existing analysis tools are deficient in supporting sustainability assessment by nonexperts. To address this gap, the Manufacturing Process and System (MaPS) Sustainability Analysis tool was developed under the Constructionism in Learning: Sustainable Life Cycle Engineering (CooL:SLiCE) project. The technical aspects of developing a framework and its associated proof-of-concept MaPS Sustainability Analysis tool are reported in a separate study. Herein, the educational aspects of the MaPS Sustainability Analysis tool and its operational performance in terms of ease of use and usefulness to assess its suitability for the classroom are investigated. Undergraduate and graduate engineering students at Tampere University and Oregon State University were recruited to use and evaluate the tool. Through application of the Technology Acceptance Model (TAM), it was determined that the 24 study participants found the tool easy to use and useful in analyzing product design, manufacturing process, and supply chain sustainability performance. To move this proof of concept toward general use, key software operational characteristics and a GUI should be investigated to improve efficiency, effectiveness, satisfaction, and learnability of the MaPS Sustainability Analysis tool.
Symmetry Analysis in Construction Two Dynamic Lightweight S-Boxes Based on the 2D Tinkerbell Map and the 2D Duffing Map
Authors: Khudhair Ala’a Talib , Maolood Abeer Tariq , Gbashi Ekhlas Khalaf
Published: July 2024

The lack of an S-Box in some lightweight cryptography algorithms, like Speck and Tiny Encryption Algorithm, or the presence of a fixed S-Box in others, like Advanced Encryption Standard, makes them more vulnerable to attacks. This proposal presents a novel approach to creating two dynamic 8-bit S-Boxes (16 × 16). The generation process for each S-Box consists of two phases. Initially, the number initialization phase involves generating sequence numbers 1, sequence numbers 2, and shift values for S-Box1 using the 2D Tinkerbell map. Additionally, sequence numbers 3, sequence numbers 4, and shift values for S-Box2 are generated using the 2D Duffing map. Subsequently, the S-Box construction phase involves the construction of S-Box1 and S-Box2. The effectiveness of the newly proposed S-Boxes was evaluated based on various criteria, including the bijective property, balance, fixed points, and strict avalanche criteria. It was observed that S-Box1 achieved a remarkable linear and differential branch number of 4, surpassing any previous studies. Furthermore, it exhibited a non-linearity of 105.50, a differential uniformity of 12, and an algebraic degree of 7. Similarly, S-Box2 also achieved a linear and differential branch number of 4, a non-linearity of 105.25, a differential uniformity of 14, and an algebraic degree of 7. Moreover, the reduction in the number of linear and nonlinear operations for both S-Boxes makes them suitable for lightweight algorithms. The architecture of the proposed S-Boxes demonstrates robustness, with a total of 3.35 × 10504 possible S-Boxes, providing protection against algebraic attacks.
Efficient Stereoselective Biotransformation of Prochiral Carbonyls by Endophytic Fungi from Handroanthus impetiginosus
Authors: dos Santos Valmore Henrique Pereira , de Souza Monielly Vasconcellos Pereira , Victor Maurício Moraes , Riatto Valéria Belli , Silva Eliane Oliveira
Published: July 2024

Endophytic microorganisms are promising sources for new biocatalysts as they must deal with their host plants’ chemicals by developing adaptative strategies, such as enzymatic pathways. As part of our efforts in selecting endophytic strains as biocatalysts, this study describes the screening of endophytic fungi isolated from Handroanthus impetiginosus leaves for selective bioreduction of Acetophenone. The bioreductions were monitored by chiral gas chromatography and conducted to the selection of the endophyte Talaromyces sp. H4 as capable of reducing acetophenone to (S)-1-phenylethanol in excellent conversion and enantiomeric excess rates. The influence of seven parameters on the stereoselective bioreduction of acetophenone by Talaromyces sp. H4 was studied: reaction time, inoculum charge, shaking, pH, temperature, substrate concentration, and co-solvent. The optimal conditions were then used to reduce substituted acetophenones and Acetophenone scale-up, which furnished (S)-1-Phenylethanol in 73% yield and 96% ee. The results highlight the endophytic fungus Talaromyces sp. H4 as an excellent biocatalyst for stereoselective reduction of prochiral carbonyls.
Tropical Fruit Virus Resistance in the Era of Next-Generation Plant Breeding
Authors: Vieira Marcella Silva , Cabral Rafael Lara Rezende , Favaratto Luíza , Maciel Laiane Silva , Xavier André da Silva , Zerbini Francisco Murilo , Fernandes Patricia M. B.
Published: July 2024

Plant viral diseases constitute a major contributor to agricultural production losses, significantly impacting the economies of exporting countries by more than USD 30 billion annually. Understanding and researching the biology and genomics of viruses is crucial for developing virus-resistant genetically edited or genetically modified plants. Genetic modifications can be targeted to specific regions within genes of target plants which are important or essential for the virus to establish a systemic infection, thus fostering resistance or enabling plants to effectively respond to invading agents while preserving their yield. This review provides an overview of viral incidence and diversity in tropical fruit crops and aims to examine the current state of the knowledge on recent research efforts aimed at reducing or eliminating the damage caused by viral diseases, with emphasis on genetically edited products that have reached the market in recent years.