bluuebunny/crossref_metadata_2025 huggingface dataset:
LRP10, PGK1 and RPLP0: Best Reference Genes in Periprostatic Adipose Tissue under Obesity and Prostate Cancer Conditions
Authors: Pérez-Gómez Jesús M. , Porcel-Pastrana Francisco , De La Luz-Borrero Marina , Montero-Hidalgo Antonio J. , Gómez-Gómez Enrique , Herrera-Martínez Aura D. , Guzmán-Ruiz Rocío , Malagón María M. , Gahete Manuel D. , Luque Raúl M.
Published: October 2023

Obesity (OB) is a metabolic disorder characterized by adipose tissue dysfunction that has emerged as a health problem of epidemic proportions in recent decades. OB is associated with multiple comorbidities, including some types of cancers. Specifically, prostate cancer (PCa) has been postulated as one of the tumors that could have a causal relationship with OB. Particularly, a specialized adipose tissue (AT) depot known as periprostatic adipose tissue (PPAT) has gained increasing attention over the last few years as it could be a key player in the pathophysiological interaction between PCa and OB. However, to date, no studies have defined the most appropriate internal reference genes (IRGs) to be used in gene expression studies in this AT depot. In this work, two independent cohorts of PPAT samples (n = 20/n = 48) were used to assess the validity of a battery of 15 literature-selected IRGs using two widely used techniques (reverse transcription quantitative PCR [RT-qPCR] and microfluidic-based qPCR array). For this purpose, ΔCt method, GeNorm (v3.5), BestKeeper (v1.0), NormFinder (v.20.0), and RefFinder software were employed to assess the overall trends of our analyses. LRP10, PGK1, and RPLP0 were identified as the best IRGs to be used for gene expression studies in human PPATs, specifically when considering PCa and OB conditions.
Distinct Pro-Inflammatory Mechanisms Elicited by Short and Long Amosite Asbestos Fibers in Macrophages
Authors: Leinardi Riccardo , Petriglieri Jasmine Rita , Pochet Amandine , Yakoub Yousof , Lelong Marie , Lescoat Alain , Turci Francesco , Lecureur Valérie , Huaux François
Published: October 2023

While exposure to long amphibolic asbestos fibers (L > 10 µm) results in the development of severe diseases including inflammation, fibrosis, and mesothelioma, the pathogenic activity associated with short fibers (L < 5 µm) is less clear. By exposing murine macrophages to short (SFA) or long (LFA) fibers of amosite asbestos different in size and surface chemistry, we observed that SFA internalization resulted in pyroptotic-related immunogenic cell death (ICD) characterized by the release of the pro-inflammatory damage signal (DAMP) IL-1α after inflammasome activation and gasdermin D (GSDMD)-pore formation. In contrast, macrophage responses to non-internalizable LFA were associated with tumor necrosis factor alpha (TNF-α) release, caspase-3 and -7 activation, and apoptosis. SFA effects exclusively resulted from Toll-like receptor 4 (TLR4), a pattern-recognition receptor (PRR) recognized for its ability to sense particles, while the response to LFA was elicited by a multifactorial ignition system involving the macrophage receptor with collagenous structure (SR-A6 or MARCO), reactive oxygen species (ROS) cascade, and TLR4. Our findings indicate that asbestos fiber size and surface features play major roles in modulating ICD and inflammatory pathways. They also suggest that SFA are biologically reactive in vitro and, therefore, their inflammatory and toxic effects in vivo should not be underestimated.
Exosomal miR-205-5p Improves Endometrial Receptivity by Upregulating E-Cadherin Expression through ZEB1 Inhibition
Authors: Yu Seong-Lan , Jeong Da-Un , Noh Eui-Jeong , Jeon Hye Jin , Lee Dong Chul , Kang Minho , Kim Tae-Hyun , Lee Sung Ki , Han Ae Ra , Kang Jaeku , Park Seok-Rae
Published: October 2023

Endometrial receptivity is a complex process that prepares the uterine endometrium for embryo implantation; insufficient endometrial receptivity is one of the causes of implantation failure. Here, we analyzed the microRNA expression profiles of exosomes derived from both receptive (RL95-2) and non-receptive (AN3-CA) endometrial epithelial cell (EEC) lines to identify exosomal miRNAs closely linked to endometrial receptivity. Among the 466 differentially expressed miRNAs, miR-205-5p was the most highly expressed in exosomes secreted from receptive RL95-2 cells. miR-205-5p, enriched at the adhesive junction, was closely related to endometrial receptivity. ZEB1, a transcriptional repressor of E-cadherin associated with endometrial receptivity, was identified as a direct target of miR-205-5p. miR-205-5p expression was significantly lower in the endometrial tissues of infertile women than in that of non-infertile women. In vivo, miR-205-5p expression was upregulated in the post-ovulatory phase, and its inhibitor reduced embryo implantation. Furthermore, administration of genetically modified exosomes overexpressing miR-205-5p mimics upregulated E-cadherin expression by targeting ZEB1 and improved spheroid attachment of non-receptive AN3-CA cells. These results suggest that the miR-205-5p/ZEB1/E-cadherin axis plays an important role in regulating endometrial receptivity. Thus, the use of exosomes harboring miR-205-5p mimics can be considered a potential therapeutic approach for improving embryo implantation.
Small Molecule Pytren-4QMn Metal Complex Slows down Huntington’s Disease Progression in Male zQ175 Transgenic Mice
Authors: Merino Marián , González Sonia , Tronch Mª Carmen , Sánchez-Sánchez Ana Virginia , Clares Mª Paz , García-España Antonio , García-España Enrique , Mullor José L.
Published: October 2023

Huntington’s disease (HD) is an inherited neurodegenerative disorder considered a rare disease with a prevalence of 5.7 per 100,000 people. It is caused by an autosomal dominant mutation consisting of expansions of trinucleotide repeats that translate into poly-glutamine enlarged mutant huntingtin proteins (mHTT), which are particularly deleterious in brain tissues. Since there is no cure for this progressive fatal disease, searches for new therapeutic approaches are much needed. The small molecule pytren-4QMn (4QMn), a highly water-soluble mimic of the enzyme superoxide dismutase, has shown in vivo beneficial anti-inflammatory activity in mice and was able to remove mHTT deposits in a C. elegans model of HD. In this study, we assessed 4QMn therapeutic potential in zQ175 neo-deleted knock-in mice, a model of HD that closely mimics the heterozygosity, genetic injury, and progressive nature of the human disease. We provide evidence that 4QMn has good acute and chronic tolerability, and can cross the blood–brain barrier, and in male, but not female, zQ175 mice moderately ameliorate HD-altered gene expression, mHtt aggregation, and HD disease phenotype. Our data highlight the importance of considering sex-specific differences when testing new therapies using animal models and postulate 4QMn as a potential novel type of small water-soluble metal complex that could be worth further investigating for its therapeutic potential in HD, as well as in other polyglutamine diseases.
Local Net Charge State of Collagen Triple Helix Is a Determinant of FKBP22 Binding to Collagen III
Authors: Ishikawa Yoshihiro , Bonna Arkadiusz , Gould Douglas B. , Farndale Richard W.
Published: October 2023

Mutations in the FKBP14 gene encoding the endoplasmic reticulum resident collagen-related proline isomerase FK506 binding protein 22 kDa (FKBP22) result in kyphoscoliotic Ehlers–Danlos Syndrome (EDS), which is characterized by a broad phenotypic outcome. A plausible explanation for this outcome is that FKBP22 participates in the biosynthesis of subsets of collagen types: FKBP22 selectively binds to collagens III, IV, VI, and X, but not to collagens I, II, V, and XI. However, these binding mechanisms have never been explored, and they may underpin EDS subtype heterogeneity. Here, we used collagen Toolkit peptide libraries to investigate binding specificity. We observed that FKBP22 binding was distributed along the collagen helix. Further, it (1) was higher on collagen III than collagen II peptides and it (2) was correlated with a positive peptide charge. These findings begin to elucidate the mechanism by which FKBP22 interacts with collagen.
Mitigating Age-Related Ovarian Dysfunction with the Anti-Inflammatory Agent MIT-001
Authors: Kang Min-Hee , Kim Yu Jin , Cho Min Jeong , Jang JuYi , Koo Yun Dong , Kim Soon Ha , Lee Jae Ho
Published: October 2023

Ovarian aging is a major obstacle in assisted reproductive medicine because it leads to ovarian dysfunction in women of advanced age. Currently, there are no effective treatments to cure age-related ovarian dysfunction. In this study, we investigated the effect of MIT-001 on the function of aged ovaries. Young and old mice were utilized in this study. MIT-001 was intraperitoneally administered, and the number of follicles and oocytes was analyzed. Each group was then retrieved for RNA and protein isolation. Total RNA was subjected to mRNA next-generation sequencing. Protein extracts from ovarian lysates were used to evaluate various cytokine levels in the ovaries. MIT-001 enhanced follicles and the number of oocytes were compared with non-treated old mice. MIT-001 downregulated immune response-related transcripts and cytokines in the ovaries of old mice. MIT-001 modulates the immune complex responsible for generating inflammatory signals and has the potential to restore the function of old ovaries and improve female fertility.
Epitranscriptomics as a New Layer of Regulation of Gene Expression in Skeletal Muscle: Known Functions and Future Perspectives
Authors: Imbriano Carol , Moresi Viviana , Belluti Silvia , Renzini Alessandra , Cavioli Giorgia , Maretti Eleonora , Molinari Susanna
Published: October 2023

Epitranscriptomics refers to post-transcriptional regulation of gene expression via RNA modifications and editing that affect RNA functions. Many kinds of modifications of mRNA have been described, among which are N6-methyladenosine (m6A), N1-methyladenosine (m1A), 7-methylguanosine (m7G), pseudouridine (Ψ), and 5-methylcytidine (m5C). They alter mRNA structure and consequently stability, localization and translation efficiency. Perturbation of the epitranscriptome is associated with human diseases, thus opening the opportunity for potential manipulations as a therapeutic approach. In this review, we aim to provide an overview of the functional roles of epitranscriptomic marks in the skeletal muscle system, in particular in embryonic myogenesis, muscle cell differentiation and muscle homeostasis processes. Further, we explored high-throughput epitranscriptome sequencing data to identify RNA chemical modifications in muscle-specific genes and we discuss the possible functional role and the potential therapeutic applications.
Multicopy Chromosome Integration and Deletion of Negative Global Regulators Significantly Increased the Heterologous Production of Aborycin in Streptomyces coelicolor
Authors: Li Jia-Yi , Liang Jun-Yu , Liu Zhao-Yuan , Yi Yue-Zhao , Zhao Jing , Huang Zhi-Yong , Chen Jun
Published: October 2023

Aborycin is a type I lasso peptide with a stable interlocked structure, offering a favorable framework for drug development. The aborycin biosynthetic gene cluster gul from marine sponge-associated Streptomyces sp. HNS054 was cloned and integrated into the chromosome of S. coelicolor hosts with different copies. The three-copy gul-integration strain S. coelicolor M1346::3gul showed superior production compared to the one-copy or two-copy gul-integration strains, and the total titer reached approximately 10.4 mg/L, i.e., 2.1 times that of the native strain. Then, five regulatory genes, phoU (SCO4228), wblA (SCO3579), SCO1712, orrA (SCO3008) and gntR (SCO1678), which reportedly have negative effects on secondary metabolism, were further knocked out from the M1346::3gul genome by CRISPR/Cas9 technology. While the ΔSCO1712 mutant showed a significant decrease (4.6 mg/L) and the ΔphoU mutant showed no significant improvement (12.1 mg/L) in aborycin production, the ΔwblA, ΔorrA and ΔgntR mutations significantly improved the aborycin titers to approximately 23.6 mg/L, 56.3 mg/L and 48.2 mg/L, respectively, which were among the highest heterologous yields for lasso peptides in both Escherichia coli systems and Streptomyces systems. Thus, this study provides important clues for future studies on enhancing antibiotic production in Streptomyces systems.
Roles of Omega-3 Polyunsaturated Fatty Acids in Managing Cognitive Impairment in Chronic Obstructive Pulmonary Disease: A Review
Authors: Zailani Halliru , Satyanarayanan Senthil Kumaran , Liao Wei-Chih , Hsu Yi-Ting , Huang Shih-Yi , Gałecki Piotr , Su Kuan-Pin , Chang Jane Pei-Chen
Published: October 2023

Chronic obstructive pulmonary disease (COPD) contributes significantly to the death of people worldwide, especially the elderly. An essential feature of COPD is pulmonary inflammation, which results from long-term exposure to noxious substances from cigarette smoking and other environmental pollutants. Pulmonary inflammatory mediators spill over to the blood, leading to systemic inflammation, which is believed to play a significant role in the onset of a host of comorbidities associated with COPD. A substantial comorbidity of concern in COPD patients that is often overlooked in COPD management is cognitive impairment. The exact pathophysiology of cognitive impairment in COPD patients remains a mystery; however, hypoxia, oxidative stress, systemic inflammation, and cerebral manifestations of these conditions are believed to play crucial roles. Furthermore, the use of medications to treat cognitive impairment symptomatology in COPD patients has been reported to be associated with life-threatening adverse effects, hence the need for alternative medications with reduced side effects. In this Review, we aim to discuss the impact of cognitive impairment in COPD management and the potential mechanisms associated with increased risk of cognitive impairment in COPD patients. The promising roles of omega-3 polyunsaturated fatty acids (ω-3 PUFAs) in improving cognitive deficits in COPD patients are also discussed. Interestingly, ω-3 PUFAs can potentially enhance the cognitive impairment symptomatology associated with COPD because they can modulate inflammatory processes, activate the antioxidant defence system, and promote amyloid-beta clearance from the brain. Thus, clinical studies are crucial to assess the efficacy of ω-3 PUFAs in managing cognitive impairment in COPD patients.
Identification of Potential JNK3 Inhibitors: A Combined Approach Using Molecular Docking and Deep Learning-Based Virtual Screening
Authors: Yao Chenpeng , Shen Zheyuan , Shen Liteng , Kadier Kailibinuer , Zhao Jingyi , Guo Yu , Xu Lei , Cao Ji , Dong Xiaowu , Yang Bo
Published: October 2023

JNK3, a member of the MAPK family, plays a pivotal role in mediating cellular responses to stress signals, with its activation implicated in a myriad of inflammatory conditions. While JNK3 holds promise as a therapeutic target for neurodegenerative disorders such as Huntington’s, Parkinson’s, and Alzheimer’s diseases, there remains a gap in the market for effective JNK3 inhibitors. Despite some pan-JNK inhibitors reaching clinical trials, no JNK-targeted therapies have achieved market approval. To bridge this gap, our study introduces a sophisticated virtual screening approach. We begin with an energy-based screening, subsequently integrating a variety of rescoring techniques. These encompass glide docking scores, MM/GBSA, and artificial scoring mechanisms such as DeepDock and advanced Graph Neural Networks. This virtual screening workflow is designed to evaluate and identify potential small-molecule inhibitors with high binding affinity. We have implemented a virtual screening workflow to identify potential candidate molecules. This process has resulted in the selection of ten molecules. Subsequently, these ten molecules have undergone biological activity evaluation to assess their potential efficacy. Impressively, molecule compound 6 surfaced as the most promising, exhibiting a potent kinase inhibitory activity marked by an IC50 of 130.1 nM and a notable reduction in TNF-α release within macrophages. This suggests that compound 6 could potentially serve as an effective inhibitor for the treatment of neuroinflammation and neurodegenerative diseases. The prospect of further medicinal modifications to optimize compound 6 presents a promising avenue for future research and development in this field. Utilizing binding pose metadynamics coupled with molecular dynamics simulations, we delved into the explicit binding mode of compound 6 to JNK3. Such insights pave the way for refined drug development strategies. Collectively, our results underscore the efficacy of the hybrid virtual screening workflow in the identification of robust JNK3 inhibitors, holding promise for innovative treatments against neuroinflammation and neurodegenerative disorders.
Correction: Chen et al. Cytotoxic, Antibacterial, and Antioxidant Activities of the Leaf Extract of Sinningia bullata. Plants 2023, 12, 859
Authors: Chen Pin-Jui , Lin En-Shyh , Su Hsin-Hui , Huang Cheng-Yang
Published: October 2023

The authors would like to supplement some methodology information including the controls in the originally published version of this manuscript [...]
A Higher-Order Singular Value Decomposition-Based Target Localization Algorithm for WiFi Array Systems
Authors: Liu Hongqing , Zhang Heng , Shi Jinmei , Lan Xiang , Wang Wenshuai , Wang Xianpeng
Published: October 2023

Traditional Angle of Arrival (AoA)-based WiFi array indoor localization algorithms do not fuse Channel State Information (CSI) inter-packet data for estimation, which makes WiFi arrays less effective for localization in complex indoor environments. Most algorithms are overburdened leading to inefficient localization. To address these issues, in this article, an indoor positioning algorithm based on Higher-Order Singular Value Decomposition (HOSVD) is proposed. First, the CSI data are reconstructed as a new measurement matrix by borrowing subcarriers, and a third-order tensor is constructed. Next, tensor compression techniques are used to reduce computational complexity and the signal subspace is obtained by HOSVD. Then, the AoA is obtained by the Reduced Dimension Multiple Signal Classification (RD-MUSIC) method. Finally, the coordinates of the target can be obtained by triangulating the AoAs of the three Access Points (APs). According to the simulation experiments, the AoA can be estimated accurately at a low SNR and with low snapshots. In practical experiments, we can successfully estimate the AoA in complex indoor environments with shorter timelines using HOSVD without modifications to commercial hardware and produce a lower AoA error and localization error rates compared to other algorithms. The effectiveness of our proposed algorithm is proven by simulations and practical experiments.
A Cloud-IoT Architecture for Latency-Aware Localization in Earthquake Early Warning
Authors: Pierleoni Paola , Concetti Roberto , Belli Alberto , Palma Lorenzo , Marzorati Simone , Esposito Marco
Published: October 2023

An effective earthquake early warning system requires rapid and reliable earthquake source detection. Despite the numerous proposed epicenter localization solutions in recent years, their utilization within the Internet of Things (IoT) framework and integration with IoT-oriented cloud platforms remain underexplored. This paper proposes a complete IoT architecture for earthquake detection, localization, and event notification. The architecture, which has been designed, deployed, and tested on a standard cloud platform, introduces an innovative approach by implementing P-wave “picking” directly on IoT devices, deviating from traditional regional earthquake early warning (EEW) approaches. Pick association, source localization, event declaration, and user notification functionalities are also deployed on the cloud. The cloud integration simplifies the integration of other services in the architecture, such as data storage and device management. Moreover, a localization algorithm based on the hyperbola method is proposed, but here, the time difference of arrival multilateration is applied that is often used in wireless sensor network applications. The results show that the proposed end-to-end architecture is able to provide a quick estimate of the earthquake epicenter location with acceptable errors for an EEW system scenario. Rigorous testing against the standard of reference in Italy for regional EEW showed an overall 3.39 s gain in the system localization speed, thus offering a tangible metric of the efficiency and potential proposed system as an EEW solution.
A Fine-Grained Semantic Alignment Method Specific to Aggregate Multi-Scale Information for Cross-Modal Remote Sensing Image Retrieval
Authors: Zheng Fuzhong , Wang Xu , Wang Luyao , Zhang Xiong , Zhu Hongze , Wang Long , Zhang Haisu
Published: October 2023

Due to the swift growth in the scale of remote sensing imagery, scholars have progressively directed their attention towards achieving efficient and adaptable cross-modal retrieval for remote sensing images. They have also steadily tackled the distinctive challenge posed by the multi-scale attributes of these images. However, existing studies primarily concentrate on the characterization of these features, neglecting the comprehensive investigation of the complex relationship between multi-scale targets and the semantic alignment of these targets with text. To address this issue, this study introduces a fine-grained semantic alignment method that adequately aggregates multi-scale information (referred to as FAAMI). The proposed approach comprises multiple stages. Initially, we employ a computing-friendly cross-layer feature connection method to construct a multi-scale feature representation of an image. Subsequently, we devise an efficient feature consistency enhancement module to rectify the incongruous semantic discrimination observed in cross-layer features. Finally, a shallow cross-attention network is employed to capture the fine-grained semantic relationship between multiple-scale image regions and the corresponding words in the text. Extensive experiments were conducted using two datasets: RSICD and RSITMD. The results demonstrate that the performance of FAAMI surpasses that of recently proposed advanced models in the same domain, with significant improvements observed in R@K and other evaluation metrics. Specifically, the mR values achieved by FAAMI are 23.18% and 35.99% for the two datasets, respectively.
Fast Recognition and Counting Method of Dragon Fruit Flowers and Fruits Based on Video Stream
Authors: Li Xiuhua , Wang Xiang , Ong Pauline , Yi Zeren , Ding Lu , Han Chao
Published: October 2023

Dragon fruit (Hylocereus undatus) is a tropical and subtropical fruit that undergoes multiple ripening cycles throughout the year. Accurate monitoring of the flower and fruit quantities at various stages is crucial for growers to estimate yields, plan orders, and implement effective management strategies. However, traditional manual counting methods are labor-intensive and inefficient. Deep learning techniques have proven effective for object recognition tasks but limited research has been conducted on dragon fruit due to its unique stem morphology and the coexistence of flowers and fruits. Additionally, the challenge lies in developing a lightweight recognition and tracking model that can be seamlessly integrated into mobile platforms, enabling on-site quantity counting. In this study, a video stream inspection method was proposed to classify and count dragon fruit flowers, immature fruits (green fruits), and mature fruits (red fruits) in a dragon fruit plantation. The approach involves three key steps: (1) utilizing the YOLOv5 network for the identification of different dragon fruit categories, (2) employing the improved ByteTrack object tracking algorithm to assign unique IDs to each target and track their movement, and (3) defining a region of interest area for precise classification and counting of dragon fruit across categories. Experimental results demonstrate recognition accuracies of 94.1%, 94.8%, and 96.1% for dragon fruit flowers, green fruits, and red fruits, respectively, with an overall average recognition accuracy of 95.0%. Furthermore, the counting accuracy for each category is measured at 97.68%, 93.97%, and 91.89%, respectively. The proposed method achieves a counting speed of 56 frames per second on a 1080ti GPU. The findings establish the efficacy and practicality of this method for accurate counting of dragon fruit or other fruit varieties.
A Semantic Topology Graph to Detect Re-Localization and Loop Closure of the Visual Simultaneous Localization and Mapping System in a Dynamic Environment
Authors: Wang Yang , Zhang Yi , Hu Lihe , Wang Wei , Ge Gengyu , Tan Shuyi
Published: October 2023

Simultaneous localization and mapping (SLAM) plays a crucial role in the field of intelligent mobile robots. However, the traditional Visual SLAM (VSLAM) framework is based on strong assumptions about static environments, which are not applicable to dynamic real-world environments. The correctness of re-localization and recall of loop closure detection are both lower when the mobile robot loses frames in a dynamic environment. Thus, in this paper, the re-localization and loop closure detection method with a semantic topology graph based on ORB-SLAM2 is proposed. First, we use YOLOv5 for object detection and label the recognized dynamic and static objects. Secondly, the topology graph is constructed using the position information of static objects in space. Then, we propose a weight expression for the topology graph to calculate the similarity of topology in different keyframes. Finally, the re-localization and loop closure detection are determined based on the value of topology similarity. Experiments on public datasets show that the semantic topology graph is effective in improving the correct rate of re-localization and the accuracy of loop closure detection in a dynamic environment.
Regional Thermal Radiation Characteristics of FY Satellite Remote Sensing Based on Big Data Analysis
Authors: Wen Tao , Wei Congxin , Wang Zhenyi , Wang Linzhu , Yang Zihan , Gu Tingting
Published: October 2023

It is of great significance to study the thermal radiation anomalies of earthquake swarms in the same area in terms of selecting abnormal characteristic determination parameters, optimizing and determining the processing model, and understanding the abnormal machine. In this paper, we investigated short-term and long-term thermal radiation anomalies induced by earthquake swarms in Iran and Pakistan between 2007 and 2016. The anomalies were extracted from infrared remote sensing black body temperature data from the China Geostationary Meteorological Satellites (FY-2C/2E/2F/2G) using the multiscale time-frequency relative power spectrum (MS T-FRPS) method. By analyzing and summarizing the thermal radiation anomalies of series earthquake groups with consistency law through a stable and reliable MS T-FRPS method, we first obtained the relationship between anomalies and ShakeMaps from USGS and proposed the anomaly regional indicator (ARI) to determine seismic anomalies and the magnitude decision factor (MDF) to determine seismic magnitude. In addition, we explored the following discussions: earthquake impact on regional thermal radiation background and the relationship between thermal anomalies and earthquake magnitude and the like. Future research directions using the MS T-FRPS method to characterize regional thermal radiation anomalies induced by strong earthquakes could help improve the accuracy of earthquake magnitude determination.
Effect of Sowing Method on Yield of Different Plants Grown as a Catch Crop
Authors: Wilczewski Edward , Gałęzewski Lech
Published: October 2023

Currently, the most important task of stubble catch crops, as an element of sustainable agriculture, is to provide the soil with organic matter. The basic problem in the implementation of this task is the shortage of precipitation during the sowing period, which, combined with high temperatures in Europe in August, results in the loss of soil water and, consequently, weakening of germination and delay in plant emergence. The development of agrotechnics to increase the reliability of germination of seeds of plants grown as a catch crops is very important for the use of this valuable source of organic matter in regions with low and irregular rainfall, especially in the case of light soils with low water retention capacity. The aim of the study was to evaluate the response to furrow sowing of plants from various botanical groups grown as a stubble catch crop. Field studies were carried out on lessive soil in 2013–2015 at the Research Station in Mochełek near Bydgoszcz. The subject of the research was the sowing method (factor I): furrow sowing versus traditional (row) sowing. Sowing methods were tested for four crops (factor II): white mustard, tansy phacelia, common buckwheat, and common vetch. Certain plants reacted differently to the use of furrow sowing, and this reaction was different in various years of the study. In years with average soil moisture during the sowing period, furrow sowing made it possible to increase the yield of green mass and post-harvest residues of catch crop. In a year with very low soil moisture in this period, the desired effect of this method was not obtained. Furrow sowing allows seeds to be placed in a deeper, more moist soil layer, which can contribute to the acceleration of plant emergence. However, it requires refinement in terms of the precision of covering the sown seeds with soil.
Characteristics That Influence Individuals’ Intentions to Use and Bequeath Common Assets: Time-Perspective Scales and Demographic Attributes
Authors: Tasaki Tomohiro , Yokoo Hide-Fumi , Tajima Ryo , Yamaguchi Rintaro
Published: October 2023

As global environmental problems worsen, there is a concern for future generations who may face an unfairly degraded environment. In this study, we asked individuals from the current generation questions about using and bequeathing a common local asset to future generations in order to identify individual characteristics that influence their intentions to benefit future generations. A total of 960 Japanese individuals ranging from 20 to over 70 years old participated in an online survey. Explanatories include five time-perspective scales based on the psychology literature and demographic attributes such as age, sex, household income, marital status, final education level, and population size. Using logistic regression, we found that altruism was the most significant and positive factor influencing their intentions to benefit future generations. Three other time-perspective scales, namely future neglect, creativity, and generativity, also influenced the intentions, albeit negatively and to a lesser extent. Demographic attributes were generally not found to significantly influence intentions. Finally, we argue that three psychological conditions—time horizon, negative aspects of creativity, and sufficient altruism—could potentially lead people to choose decisions that are more beneficial to future generations.
Wayside Railway Switch and Crossing Monitoring Using Isolation Forest Anomaly Scores
Authors: Zuo Yang , Chandran Praneeth , Odelius Johan , Rantatalo Matti
Published: October 2023

Railway switch and crossing (S&C) systems have complicated moving structures compared with regular rail. They require multiple components that vary in complexity. The complexity of railway S&C, together with the fact that they are discontinuous points of the system, makes them vulnerable to defects such as squats. A squat on the switching rail could potentially cause rail breakage and lead to catastrophic results, such as derailment. In this study, a method based on anomaly scoring was investigated to estimate the status of an S&C system with respect to squat defects. The proposed method was tested in a real environment under controlled measurement sequences. The results show that the methods can differ between an S&C with squats and another one without them.
The Medical Right to Repair: Intellectual Property, the Maker Movement, and COVID-19
Authors: Rimmer Matthew
Published: October 2023

This article considers the strengths and limitations of the use of 3D printing and additive manufacturing for the production of personal protective equipment (PPE) during the COVID-19 public health crisis. It explores the role of the Maker Movement in addressing the shortfall in medical equipment during the public health pandemic. Taking a comparative approach, this article evaluates the responses of both the commercial and amateur sides of the 3D printing community to the COVID-19 public health crisis. In the EU, the Fab Lab Network sought to overcome a breakdown in supply chains. In the US, Dale Dougherty of Make Magazine promoted Plan C, in which volunteers have worked together to produce PPE. In Australia, 3D printing has been used to augment supplies of PPE. In this context, a key issue across jurisdictions has been the tension between intellectual property rights and the right to repair—particularly when 3D printing has been applied to deal with shortages in PPE. Senator Ron Wyden put forward the Critical Medical Infrastructure Right-to-Repair Act of 2020 (US) to try to resolve these tensions. Open licensing has proven to be a helpful mechanism to enable open collaboration and sharing of 3D printing designs for the purposes of health care. Nonetheless, it is argued that there should be stronger recognition of the right to repair—particularly in the context of health-care and medical devices. The COVID-19 crisis has highlighted that there needs to be a broader array of intellectual property flexibilities to deal with public health emergencies—including in respect of the right to repair. As such, this article supports a broad vision of a TRIPS Waiver which includes the right to repair. The recognition of a right to repair will help promote the realization of the Sustainable Development Goals and a COVID-19 recovery. The topic of the medical right to repair has larger implications for sustainability and the Sustainable Development Goals (SDGs), particularly in respect of responsible production and consumption (SDG 12), as well as good health and well-being (SDG 3), innovation (SDG 9), and partnerships for the goals (SDG 17).
Identification of Critical Links in Urban Road Network Based on GIS
Authors: Yuan Jingwen , Wang Hualan , Fang Yannan
Published: October 2023

A GIS-based method is proposed to identify critical links in urban road networks. This study utilizes a geographic information system (GIS) to evaluate the distribution of road infrastructure, road density, and network accessibility at the micro, meso, and macro levels. At the micro level, GIS is used to assess the distribution of public facilities along the roads. At the meso level, a city’s road density distribution is evaluated. At the macro level, a spatial barrier model and a transportation network model are constructed to assess the network accessibility. An inverse distance weighting method is employed to interpolate the accessibility. Furthermore, a network topology is established, and the entropy method is utilized to evaluate the sections comprehensively. The sections are ranked based on the evaluation results to identify the critical links in the urban road network. The road-network data and points of interest (POI) data from the Anning District in Lanzhou are selected for a case study, and the results indicate that the top five critical links have scores of 0.641, 0.571, 0.570, 0.519, and 0.508, respectively. Considering the three indicators enhances the accuracy of critical section identification, demonstrating the effectiveness of the proposed method. Visualizing each indicator using GIS 10.7 provides a new approach to identifying critical links in urban road networks and offers essential theoretical support for urban planning.
The Role of Economic and Innovation Initiatives in Planning a Smart City Strategy in Greece
Authors: Siokas Georgios , Tsakanikas Aggelos
Published: October 2023

As digital technology has become an integral part of urban life’s daily operations, the urban landscape is constantly evolving with the needs of its society. This new reality has allowed municipalities to invest in technologies related to smart cities and to exert a greater influence on the national and local economy. In line with this, the paper aims to understand the mechanisms of planning and implementing a municipality’s strategy in Greece to exploit the smart city benefits and to foster economic development. It is important to identify the role of different factors including strategy during the planning and implementing phases of initiatives concerning the economy and innovation in a smart city. To achieve this, data were collected via a questionnaire and processed using the advanced statistical technique PLS-SEM. The main findings highlight the importance of planning initiatives aligned with the needs of the municipality and the business ecosystem. The existence of a smart city strategy has a catalytic effect on the final impact of the implemented initiatives on the urban ecosystem. A systematic analysis of the smart cities’ dynamics and the new state of the urban ecosystem can help the local actors focus on value creation and public service provision, fostering innovation and profitability.
Blockchain in the Energy Sector for SDG Achievement
Authors: Vaccargiu Matteo , Pinna Andrea , Tonelli Roberto , Cocco Luisanna
Published: October 2023

Blockchain technology finds application in multiple sectors, including renewable energy. Numerous blockchain-based applications aim to provide support in the production, management, distribution, and consumption of green energy. The benefits offered are not only technological but also social, environmental, and economic. The purpose of this study is to examine how the application of blockchain in the energy industry may affect the achievement of the Sustainable Development Goals (SDGs). This study is composed of two parts. The first part concerns the identification and analysis of the most relevant categories of blockchain applications in the energy sector and their ability to contribute to the achievement of the SDGs. A knowledge base, comprising scientific articles, gray literature, and real-world applications, has been created and analyzed. With a keyword-based approach, each application was associated with one or more SDGs. In the second part, the Sustainability Awareness Framework (SuSAF) was used to examine the findings of the first part of the study and discuss them in terms of five dimensions of sustainability. Finally, potential risks associated with the use of blockchain in the energy sector are also covered. Results reveal that tracking energy production and consumption and renewable energy communities are the applications that have the most beneficial effects, and that the benefits linked to blockchain adoption go beyond the energy sector to include the environment, the economy, industry, infrastructure, smart cities, and society.
Calibration of Effective Structural Number and Tensile Strain Models Using Traffic Speed Deflectometer (TSD) Data for Enhanced Project-Level Assessment on Flexible and Composite Pavements
Authors: Mendez Larrain Matias M. , Ali Syed Ashik , Hobson Kenneth , Zaman Musharraf
Published: October 2023

Pavement deterioration models provide the basis for predicting future changes in network conditions, estimating future funding needs, and determining the effectiveness and timing of maintenance and rehabilitation activities. Determining the accurate structural condition of pavements helps identify effective maintenance strategies which enhance the sustainability and service life of pavements. This study aimed to use the Traffic Speed Deflectometer (TSD) and Fast Falling Weight Deflectometer (FFWD) for project-level evaluation of pavements and use pavement properties to calibrate current models that help to predict the structural condition of pavements. Model parameters were calibrated to determine the effective structural number and tensile strains at the bottom of asphalt concrete for asphalt and composite pavements from TSD deflections. Tensile strains from the KENLAYER highlighted varied behaviors for composite pavements. A significant improvement in the calibration was observed for asphalt concrete pavements. While the TSD has higher daily operational costs than FWD, its per-mile cost is significantly lower, making it a viable choice for extensive coverage, even though the quantitative results might differ between the two devices.
The Role of a Community-Based Leisure Program for Older Adults’ Leisure-Time Physical Activity: A Focus on the Social–Ecological Model
Authors: Kang Sangguk , Kim Dong-Han , Lee Jaeseok
Published: October 2023

Objective: The purpose of this study was to identify how a community-based leisure program (CBLP) interacted with older adults’ leisure-time physical activity (LTPA) based on the social–ecological model. Method: Individual semi-structured interviews were completed with 19 older adults who participated in the Tennessee senior games (TSGs). Results: As a type of CBLP and an organizational factor, the TSGs were highly intertwined with intrapersonal factors, interpersonal factors, and community factors that enabled the older adults to easily access and enhance their LTPA. Intrapersonal factors, socioeconomic status, perceived functional ability, and three main motivation factors (i.e., physical health, positive feelings, and competition) emerged for TSG participation. As interpersonal factors, the majority of the older adults encountered the TSGs for the first time through their family, friends, coaches, doctors, or team colleagues. Conclusion: Participants were encouraged to maintain LTPA by interactions with other TSG participants. Community factors provided places and volunteers for a successful CBLP with advertisements (i.e., TV, board at gym).
The Agency of Consumer Value and Behavioral Reasoning Patterns in Shaping Webrooming Behaviors in Omnichannel Retail Environments
Authors: Zafar Sarah , Badghish Saeed , Yaqub Rana Muhammad Shahid , Yaqub Muhammad Zafar
Published: October 2023

With tremendous technological advancements, traditional retailing has progressively been transformed into an omnichannel retail environment. While making an appeal to the behavioral reasoning theory, this paper explicates consumers’ (hedonic and utilitarian) value expectations and behavioral reasoning patterns as key antecedents of the maturing of their webrooming intentions in omnichannel environments. Performing PLS-based structural equation modeling on survey data obtained from 470 consumers, it has been found that both the (perceived) value and behavioral reasoning patterns of the consumers exhibit significant direct and indirect effects on building favorable attitudes toward webrooming that eventually lead to the culmination of pro-webrooming intentions. Besides expanding our understanding of the phenomena of interest, this study offers useful insights to marketers/retailers on how to boost pro-webrooming attitudes, intentions, and behaviors by ensuring a superior alignment with (utilitarian and hedonic) value perceptions and pro- and counter-webrooming reasoning patterns of the consumers.
Nexus between Financial Education, Literacy, and Financial Behavior: Insights from Vietnamese Young Generations
Authors: Pham Khanh Duy , Le Vu Linh Toan
Published: October 2023

This study examines the relationship between financial education, financial literacy, and financial behavior among young Vietnamese adults. Based on survey data from over 1000 participants, this study measures financial literacy through objective and subjective knowledge and financial ability. Financial behavior is assessed in terms of short-term behaviors (emergency funds, spending, overdraft, and budgeting) and long-term behaviors (retirement planning, having a retirement account, investment, and setting financial goals). Logistic and ordered logistic regression models are employed to analyze the data. The findings indicate a significant difference in financial behavior between individuals who have received financial education and those who have not. This study also reveals that financial literacy has a negative impact on short-term financial behaviors but a positive effect on long-term financial behaviors. This novel finding highlights the importance of considering different time horizons when examining the interplay between financial literacy and behaviors. The insights from this study hold implications for policymakers, educators, and financial institutions in developing countries like Vietnam, as they can inform the design of effective financial education programs. Ultimately, this research contributes to enhancing the financial well-being of young adults and supporting the country’s overall economic growth.
Maize Disease Classification System Design Based on Improved ConvNeXt
Authors: Li Han , Qi Mingyang , Du Baoxia , Li Qi , Gao Haozhang , Yu Jun , Bi Chunguang , Yu Helong , Liang Meijing , Ye Guanshi , Tang You
Published: October 2023

Maize diseases have a great impact on agricultural productivity, making the classification of maize diseases a popular research area. Despite notable advancements in maize disease classification achieved via deep learning techniques, challenges such as low accuracy and identification difficulties still persist. To address these issues, this study introduced a convolutional neural network model named Sim-ConvNeXt, which incorporated a parameter-free SimAM attention module. The integration of this attention mechanism enhanced the ability of the downsample module to extract essential features of maize diseases, thereby improving classification accuracy. Moreover, transfer learning was employed to expedite model training and improve the classification performance. To evaluate the efficacy of the proposed model, a publicly accessible dataset with eight different types of maize diseases was utilized. Through the application of data augmentation techniques, including image resizing, hue, cropping, rotation, and edge padding, the dataset was expanded to comprise 17,670 images. Subsequently, a comparative analysis was conducted between the improved model and other models, wherein the approach demonstrated an accuracy rate of 95.2%. Notably, this performance represented a 1.2% enhancement over the ConvNeXt model and a 1.5% improvement over the advanced Swin Transformer model. Furthermore, the precision, recall, and F1 scores of the improved model demonstrated respective increases of 1.5% in each metric compared to the ConvNeXt model. Notably, using the Flask framework, a website for maize disease classification was developed, enabling accurate prediction of uploaded maize disease images.