bluuebunny/crossref_metadata_2025 huggingface dataset:
The Mechanical and Self-Sensing Performance of Reactive Powder Cement Concrete with Nano-Stainless Steel Powder
Authors: Xu Feng , Zhou Jiwei , Chang Rencai , Zhang Dongling , Wang Hui , Tian Xiaoning
Published: June 2023

In order to prepare cement concrete with high mechanical properties and durability, nano-stainless steel powder reactive powder cement concrete (RPC) was manufactured. The dosage of nano-stainless steel powder ranged from 0% to 1.2% by the total volume of the RPC. In this study, the compressive and flexural strengths of the RPC with nano-stainless steel powder were determined, the dry shrinkage rate of the RPC was tested and the electrical resistance and alternating current (AC) impedance spectrum of the RPC were measured; moreover, the corresponding strain-sensing properties were investigated, and the scanning electron microscope (SEM) was used for observing the microstructures of the RPC. The results showed that the RPC with 1.0% nano-stainless steel powder exhibited the threshold values of the mechanical strengths. The maximum flexural strength and compressive strength were 16.1% and 14.2% higher than the minimum values. The addition of the nano-stainless steel powders reduced the dry shrinkage rate by 12.1%–39.8%. The electrical resistance of the RPC decreased in the form of the cubic function with the volume fraction of the stainless steel powders. The 1.0% nano-stainless steel powder was the threshold value for the electrical resistance and piezoresistive performance. The relationship between the electrical reactance and electrical resistance fitted well with the quadratic function. As obtained from the SEM results, the addition of the nano-stainless steel powder could effectively improve the compactness of the hydration products.
Compressibility of a Cambisol Submitted to Periods of Rotational Grazing and Strategies to Avoid Additional Soil Compaction
Authors: Suzuki Luis Eduardo Akiyoshi Sanches , Bitencourt Junior Darcy , Pauletto Eloy Antonio , Miola Ezequiel Cesar Carvalho , Rostirolla Pablo , Strieder Gilberto
Published: June 2023

Soil compaction is one of the main causes of soil degradation, and some parameters have been used to characterize it, like those related to compressibility and the degree of compactness. To evaluate the rotational grazing time during winter and the presence and absence of grazing, on the compressibility and degree of compactness of a Cambisol, an experiment was installed and consisted of corn planting for silage, a fallow and pasture planting period, with two treatments evaluating the amount of rotational grazing (two and three times in a period of, respectively, 2 and 3 months), subdivided into the presence and absence of dairy cattle grazing. The mean bulk density value of 1.47 Mg/m3 separates the occurrence (plastic deformation) or not (elastic deformation) of additional soil compaction, while the traffic of machinery and animal trampling should occur with soil moisture lower than 0.23 kg/kg, when the soil has a larger load-bearing capacity. For the conservation of soil structure, our study recommends the permanence of cattle in the plots for 30 to 40 min/day and an exit when the pasture height is 0.07 to 0.10 m, with two or three grazing in a period of, respectively, 2 and 3 months.
Surface Groups and Dielectric Properties of Ti3C2Tx MXene Nanosheets after NH3·H2O Solvothermal Treatment under Different Temperatures
Authors: Liu Zhiwei , Li Guanlong , Zhao Yan , Chen Xiangbao
Published: June 2023

The rapid development of electronic technology has brought convenience and efficiency to the lives of modern people, while emphasizing the need for novel materials with designability and excellent dielectric properties at the same time. In this work, Ti3C2Tx MXene nanosheets (MNSs) underwent NH3·H2O solvothermal treatment at temperatures of 40 °C, 60 °C, 80 °C, 100 °C, 120 °C, 140 °C, 160 °C, and 180 °C. The changes in the surface groups and dielectric properties after the solvothermal treatment were studied. The solvothermal treatment increased the proportion of surface -OH groups, which was beneficial to the permittivity of the MNSs. However, as the treating temperature increased, the amount of -OH on the surface of the MNSs showed a reducing trend, according to XPS spectra. As the treating temperature rose from 40 °C to 80 °C, the real part of the permittivity of MNS sample showed a significant decrease, eventually remaining approximately stable in the 80 °C to 180 °C samples. The results of electromagnetic characterization were in line with the group proportion, as determined via the XPS O1s spectra, supporting the previous conclusion that the -OH group played an important role in the permittivity.
Synthesis of Nano-Crystalline Whiskers of Cheese and Their Efficacy against Cadmium Toxicity
Authors: Awad Manal A. , Alanazi Meznah M. , A. Hendi Awatif , Virk Promy , Alrowaily Albandari W. , Bahlool Taghreed , Al-Abbas Fatimah , Aouaini Fatma , Ortashi Khalid M. O.
Published: June 2023

Context and objective: A novel method of fabricating probiotic nanowhiskers—using pure cheese as a source of probiotics, sans metal/chemical surfactants—is reported in the present study. Materials and methods: This was followed by an extensive characterization; FTIR spectroscopy, X-ray diffraction, particle size measurements, and transmission electron microscopy. Thermal analysis via differential scanning calorimetry (DSC) and n screening of the volatile compounds via gas chromatography/mass spectroscopy (GC-MS) was used to assess the purity of the nano-crystalline whiskers. Additionally, the anti-oxidant status and the metal-chelating effect of the nanowhiskers was evaluated in Wistar rats exposed to cadmium chloride hydrate (70 ppm) for 35 days. Group I was the positive control and groups II and III were exposed to Cd, with group III being treated with the cheese nanowhiskers (100 mL/L) in drinking water. Results: The nanoparticles were 112 nm in size (PDI 0.484) with the illustrated whisker/elongated shape being crystalline in nature. Lipid peroxidation was significantly enhanced followed by a marked bioaccumulation of Cd in the target organs. Discussion: Co-treatment with cheese nanowhiskers led to a marked reversal in the Cd-induced modulations in the endpoints evaluated. Conclusions: It is suggested that a dietary intervention in the form of a nano-probiotic supplement such as cheese is a prospective remedy for heavy metal toxicity/oxidative damage, being safe and efficacious.
Artificial Intelligence Applied to a First Screening of Naevoid Melanoma: A New Use of Fast Random Forest Algorithm in Dermatopathology
Authors: Cazzato Gerardo , Massaro Alessandro , Colagrande Anna , Trilli Irma , Ingravallo Giuseppe , Casatta Nadia , Lupo Carmelo , Ronchi Andrea , Franco Renato , Maiorano Eugenio , Vacca Angelo
Published: June 2023

Malignant melanoma (MM) is the “great mime” of dermatopathology, and it can present such rare variants that even the most experienced pathologist might miss or misdiagnose them. Naevoid melanoma (NM), which accounts for about 1% of all MM cases, is a constant challenge, and when it is not diagnosed in a timely manner, it can even lead to death. In recent years, artificial intelligence has revolutionised much of what has been achieved in the biomedical field, and what once seemed distant is now almost incorporated into the diagnostic therapeutic flow chart. In this paper, we present the results of a machine learning approach that applies a fast random forest (FRF) algorithm to a cohort of naevoid melanomas in an attempt to understand if and how this approach could be incorporated into the business process modelling and notation (BPMN) approach. The FRF algorithm provides an innovative approach to formulating a clinical protocol oriented toward reducing the risk of NM misdiagnosis. The work provides the methodology to integrate FRF into a mapped clinical process.
Diversity of Diatom Algae in the Lena Delta Nature Reserve and the Adjacent Territory in the Specific Ecological Factors of the Arctic
Authors: Barinova Sophia , Gabyshev Viktor , Genkal Sergey
Published: June 2023

A total of 413 diatom taxa were known for aquatic habitats of the Lena Delta Nature Reserve. We identified 385 taxa in 14 small tundra lakes near the reserve that significantly enriched the diatom diversity of the region (666 taxa including definitions to the genus level). Thus, the species composition of diatoms in the reserve and adjacent territories was increased by 278 species. We showed that the species of the genera Pinnularia (57) and Eunotia (51) have predominance at the family and generic levels. The index of intraspecific variability Ssp./Sp. for the lakes of the reserve was 1.11, and that for the lakes of the Tiksi region 1.14, which is typical for high-latitude and high-mountain communities. The number of rare or endangered species varied in different lakes from 1 to 10, totaling 42 species for the entire study area. Bioindication has shown that potentially threatened species prefer moderate temperatures, and slightly acidic or neutral environments free from organic pollution. A comparative analysis of the species composition of diatoms in the vicinity of the Lena Delta and other northern water bodies of Yakutia and the Arctic Islands showed that the species composition of each lake in the Arctic has a discernably different species distribution. The indicator characteristics show a certain response of the species composition of diatoms to changes in salinity, pH, and organic pollution. Regularities in the spatial distribution of diatoms in the study area were revealed in connection with the environmental variables of their habitat. Statistical mapping of diatom diversity data and bioindicators revealed a pronounced response to point pollution, and also let us assume the influence of summer northeast winds on species composition of the studied lake communities. We suggest that the high diversity inherent in the diatom lakes of the Tiksi coastal zone, which can even be updated in further studies, can be considered as a property of coastal biota inherent in ecotones. Since it is in the coastal Tiksi region that a surge in the number of species is observed, this region can be considered not only an ecotone, but also a hotspot of diatom diversity. The results of the study are important for developing the basis for monitoring biodiversity under the conditions of anthropogenic and climatic changes in the Arctic.
New Insights into the Taxonomy of Myotis Bats in China Based on Morphology and Multilocus Phylogeny
Authors: Liu Tong , Jia Jiachen , Liu Lingyu , Wang Jie , Chen Wenjie , Miao Guiyin , Niu Yilin , Guo Wei , Zhang Kangkang , Sun Keping , Yu Wenhua , Zhou Jiang , Feng Jiang
Published: June 2023

The genus Myotis is one of the most diverse and widely distributed mammals, providing a good model for studies of speciation and diversification across large geographic scales. However, the classification within this genus has long been chaotic. Taxonomic revisions based on multiple data sources are essential and urgent. In this study, morphometrics and genetic markers with different modes of inheritance were used to clarify the taxonomy of Myotis distributed in China. Based on 173 mitochondrial Cytb sequences and five morphological characteristics, 114 specimens collected nationwide over the past 20 years were assigned to 11 Myotis species. All Chinese samples classified into M. davidii and M. longipes were revised to M. alticraniatus and M. laniger. Then, two nuclear fragments (Rag2 and Chd1) and Cytb sequences from representative individuals of Chinese Myotis were used for multilocus phylogeny reconstruction and genetic divergence evaluation. The phylogenetic relationships were clearly demonstrated in the species tree: M. alticraniatus and M. laniger; M. fimbriatus, M. pilosus, M. macrodactylus, and M. petax; and M. pequinius, M. chinensis, and M. blythii formed three strongly supported monophyletic clades. Mitochondrial divergence was almost 10 times that of nuclear divergence, with interspecific K2P distances ranging from 8% to 20% for Cytb and 0.3% to 2.3% for concatenated nuclear genes. Low levels of genetic divergence were observed between M. alticraniatus and M. laniger, as well as M. fimbriatus and M. pilosus. These results provide new insights into the taxonomy and phylogeny of Myotis bats in China and are important for the future research and conservation of Chinese Myotis.
The Use of Respiratory Effort Improves an ECG-Based Deep Learning Algorithm to Assess Sleep-Disordered Breathing
Authors: Xie Jiali , Fonseca Pedro , van Dijk Johannes P. , Long Xi , Overeem Sebastiaan
Published: June 2023

Background: Sleep apnea is a prevalent sleep-disordered breathing (SDB) condition that affects a large population worldwide. Research has demonstrated the potential of using electrocardiographic (ECG) signals (heart rate and ECG-derived respiration, EDR) to detect SDB. However, EDR may be a suboptimal replacement for respiration signals. Methods: We evaluated a previously described ECG-based deep learning algorithm in an independent dataset including 198 patients and compared performance for SDB event detection using thoracic respiratory effort versus EDR. We also evaluated the algorithm in terms of apnea-hypopnea index (AHI) estimation performance, and SDB severity classification based on the estimated AHI. Results: Using respiratory effort instead of EDR, we achieved an improved performance in SDB event detection (F1 score = 0.708), AHI estimation (Spearman’s correlation = 0.922), and SDB severity classification (Cohen’s kappa of 0.62 was obtained based on AHI). Conclusion: Respiratory effort is superior to EDR to assess SDB. Using respiratory effort and ECG, the previously described algorithm achieves good performance in a new dataset from an independent laboratory confirming its adequacy for this task.
Diagnosis and Management of Severe Water-Related Skin and Soft Tissue Sepsis: A Summative Review of the Literature
Authors: Naidoo Shanisa , Zwane Arnold M. , Paruk Ahmed , Hardcastle Timothy Craig
Published: June 2023

Background: Skin and soft tissue infections (SSTIs) are common presentations in the emergency department. However, this is less common after contact with contaminated saltwater or freshwater. This review presents the diagnosis and management of water-related soft tissue sepsis in this vulnerable and difficult-to-treat subgroup of necrotizing soft tissue sepsis. Methods: A summative literature overview is presented regarding bacterial and fungal SSTI after contact with contaminated water, with practical diagnostic and management aspects. Results: The literature indicates that these wounds and infections remain difficult to treat. An approach using appropriate diagnostic tools with both medical and surgical management strategies is provided. Conclusions: SSTIs due to water contamination of wounds involve unusual organisms with unusual resistance patterns, and require a nuanced and directed diagnostic approach with an adaptation of the usual antibiotic or antifungal selection to achieve a successful cure, along with aggressive debridement and wound care.
Kawasaki Disease and Inborn Errors of Immunity: Exploring the Link and Implications
Authors: Sharma Saniya , Nadig Pallavi , Pilania Rakesh , Sharma Kaushal , Dhaliwal Manpreet , Rawat Amit , Singh Surjit
Published: June 2023

The exact etiopathogenesis of Kawasaki disease (KD), the most common childhood vasculitis, remains unknown; however, an aberrant immune response, possibly triggered by an infectious or environmental agent in genetically predisposed children, is believed to be the underlying pathogenetic mechanism. Patients with inborn errors of immunity (IEI) are predisposed to infections that trigger immune dysregulation due to an imbalance in various arms of the immune system. KD may develop as a complication in both primary and secondary immunodeficiencies. KD may occur either at disease presentation or have a later onset in IEIs. These include X-linked agammaglobulinemia (XLA), selective IgA deficiency, transient hypogammaglobulinemia of infancy; Wiskott–Aldrich syndrome (WAS), hyper IgE syndrome (HIES); chronic granulomatous disease (CGD), innate and intrinsic immunity defects, and autoinflammatory diseases, including PFAPA. Hitherto, the association between KD and IEI is confined to specific case reports and case series and, thus, requires extensive research for a comprehensive understanding of the underlying pathophysiological mechanisms. IEIs may serve as excellent disease models that would open new insights into the disease pathogenesis of children affected with KD. The current review highlights this critical association between KD and IEI supported by published literature.
Additional Value of PET and CT Image-Based Features in the Detection of Occult Lymph Node Metastases in Lung Cancer: A Systematic Review of the Literature
Authors: Guglielmo Priscilla , Marturano Francesca , Bettinelli Andrea , Sepulcri Matteo , Pasello Giulia , Gregianin Michele , Paiusco Marta , Evangelista Laura
Published: June 2023

Lung cancer represents the second most common malignancy worldwide and lymph node (LN) involvement serves as a crucial prognostic factor for tailoring treatment approaches. Invasive methods, such as mediastinoscopy and endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA), are employed for preoperative LN staging. Among the preoperative non-invasive diagnostic methods, computed tomography (CT) and, recently, positron emission tomography (PET)/CT with fluorine-18-fludeoxyglucose ([18F]FDG) are routinely recommended by several guidelines; however, they can both miss pathologically proven LN metastases, with an incidence up to 26% for patients staged with [18F]FDG PET/CT. These undetected metastases, known as occult LN metastases (OLMs), are usually cases of micro-metastasis or small LN metastasis (shortest radius below 10 mm). Hence, it is crucial to find novel approaches to increase their discovery rate. Radiomics is an emerging field that seeks to uncover and quantify the concealed information present in biomedical images by utilising machine or deep learning approaches. The extracted features can be integrated into predictive models, as numerous reports have emphasised their usefulness in the staging of lung cancer. However, there is a paucity of studies examining the detection of OLMs using quantitative features derived from images. Hence, the objective of this review was to investigate the potential application of PET- and/or CT-derived quantitative radiomic features for the identification of OLMs.
Somatostatin Receptor Targeted PET-CT and Its Role in the Management and Theranostics of Gastroenteropancreatic Neuroendocrine Neoplasms
Authors: Adnan Aadil , Basu Sandip
Published: June 2023

Somatostatin receptor (SSTR) agonist-based Positron Emission Tomography-Computed Tomography (PET-CT) imaging is nowadays the mainstay for the assessment and diagnostic imaging of neuroendocrine neoplasms (NEN), especially in well-differentiated neuroendocrine tumors (NET) (World Health Organization (WHO) grade I and II). Major clinical indications for SSTR imaging are primary staging and metastatic workup, especially (a) before surgery, (b) detection of unknown primary in metastatic NET, (c) patient selection for theranostics and appropriate therapy, especially peptide receptor radionuclide therapy (PRRT), while less major indications include treatment response evaluation on and disease prognostication. Dual tracer PET-CT imaging using SSTR targeted PET tracers, viz. [68Ga]Ga-DOTA-Tyr3-Octreotate (DOTA-TATE) and [68Ga]Ga-DOTA-NaI3-Octreotide (DOTA-NOC), and fluorodeoxyglucose (FDG), have recently gained widespread acceptance for better assessment of whole-body tumor biology compared to single-site histopathology, in terms of being non-invasive and the ability to assess inter- and intra-tumoral heterogeneity on a global scale. FDG uptake has been identified as independent adverse risk factor in various studies. Recently, somatostatin receptor antagonists have been shown to be more sensitive and specific in detecting the disease. The aim of this review article is to summarize the clinical importance of SSTR-based imaging in the clinical management of neuroendocrine and related tumors.
Deep Learning Architecture to Improve Edge Accuracy of Auto-Contouring for Head and Neck Radiotherapy
Authors: Gifford Ryan , Jhawar Sachin R. , Krening Samantha
Published: June 2023

Deep learning (DL) methods have shown great promise in auto-segmentation problems. However, for head and neck cancer, we show that DL methods fail at the axial edges of the gross tumor volume (GTV) where the segmentation is dependent on information closer to the center of the tumor. These failures may decrease trust and usage of proposed auto-contouring systems. To increase performance at the axial edges, we propose the spatially adjusted recurrent convolution U-Net (SARC U-Net). Our method uses convolutional recurrent neural networks and spatial transformer networks to push information from salient regions out to the axial edges. On average, our model increased the Sørensen–Dice coefficient (DSC) at the axial edges of the GTV by 11% inferiorly and 19.3% superiorly over a baseline 2D U-Net, which has no inherent way to capture information between adjacent slices. Over all slices, our proposed architecture achieved a DSC of 0.613, whereas a 3D and 2D U-Net achieved a DSC of 0.586 and 0.540, respectively. SARC U-Net can increase accuracy at the axial edges of GTV contours while also increasing accuracy over baseline models, creating a more robust contour.
Human–Machine Collaboration in Diagnostics: Exploring the Synergy in Clinical Imaging with Artificial Intelligence
Authors: Pirrera Antonia , Giansanti Daniele
Published: June 2023

Advancements in artificial intelligence (AI), thanks to IT developments during the COVID-19 pandemic, have revolutionized the field of diagnostics, particularly in clinical imaging [...]
The Impact of MiR-33a-5p Inhibition in Pro-Inflammatory Endothelial Cells
Authors: Huang Kun , Pitman Mark , Oladosu Olanrewaju , Echesabal-Chen Jing , Vojtech Lucia , Esobi Ikechukwu , Larsen Jessica , Jo Hanjoong , Stamatikos Alexis
Published: June 2023

Evidence suggests cholesterol accumulation in pro-inflammatory endothelial cells (EC) contributes to triggering atherogenesis and driving atherosclerosis progression. Therefore, inhibiting miR-33a-5p within inflamed endothelium may prevent and treat atherosclerosis by enhancing apoAI-mediated cholesterol efflux by upregulating ABCA1. However, it is not entirely elucidated whether inhibition of miR-33a-5p in pro-inflammatory EC is capable of increasing ABCA1-dependent cholesterol efflux. In our study, we initially transfected LPS-challenged, immortalized mouse aortic EC (iMAEC) with either pAntimiR33a5p plasmid DNA or the control plasmid, pScr. We detected significant increases in both ABCA1 protein expression and apoAI-mediated cholesterol efflux in iMAEC transfected with pAntimiR33a5p when compared to iMAEC transfected with pScr. We subsequently used polymersomes targeting inflamed endothelium to deliver either pAntimiR33a5p or pScr to cultured iMAEC and showed that the polymersomes were selective in targeting pro-inflammatory iMAEC. Moreover, when we exposed LPS-challenged iMAEC to these polymersomes, we observed a significant decrease in miR-33a-5p expression in iMAEC incubated with polymersomes containing pAntimR33a5p versus control iMAEC. We also detected non-significant increases in both ABCA1 protein and apoAI-mediated cholesterol in iMAEC exposed to polymersomes containing pAntimR33a5p when compared to control iMAEC. Based on our results, inhibiting miR-33a-5p in pro-inflammatory EC exhibits atheroprotective effects, and so precisely delivering anti-miR-33a-5p to these cells is a promising anti-atherogenic strategy.
WNT-β Catenin Signaling as a Potential Therapeutic Target for Neurodegenerative Diseases: Current Status and Future Perspective
Authors: Ramakrishna Kakarla , Nalla Lakshmi Vineela , Naresh Dumala , Venkateswarlu Kojja , Viswanadh Matte Kasi , Nalluri Buchi N. , Chakravarthy Guntupalli , Duguluri Sajusha , Singh Payal , Rai Sachchida Nand , Kumar Ashish , Singh Veer , Singh Santosh Kumar
Published: June 2023

Wnt/β-catenin (WβC) signaling pathway is an important signaling pathway for the maintenance of cellular homeostasis from the embryonic developmental stages to adulthood. The canonical pathway of WβC signaling is essential for neurogenesis, cell proliferation, and neurogenesis, whereas the noncanonical pathway (WNT/Ca2+ and WNT/PCP) is responsible for cell polarity, calcium maintenance, and cell migration. Abnormal regulation of WβC signaling is involved in the pathogenesis of several neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), amyotrophic lateral sclerosis (ALS), multiple sclerosis (MS), and spinal muscular atrophy (SMA). Hence, the alteration of WβC signaling is considered a potential therapeutic target for the treatment of neurodegenerative disease. In the present review, we have used the bibliographical information from PubMed, Google Scholar, and Scopus to address the current prospects of WβC signaling role in the abovementioned neurodegenerative diseases.
A Drone-Powered Deep Learning Methodology for High Precision Remote Sensing in California’s Coastal Shrubs
Authors: Detka Jon , Coyle Hayley , Gomez Marcella , Gilbert Gregory S.
Published: June 2023

Wildland conservation efforts require accurate maps of plant species distribution across large spatial scales. High-resolution species mapping is difficult in diverse, dense plant communities, where extensive ground-based surveys are labor-intensive and risk damaging sensitive flora. High-resolution satellite imagery is available at scales needed for plant community conservation across large areas, but can be cost prohibitive and lack resolution to identify species. Deep learning analysis of drone-based imagery can aid in accurate classification of plant species in these communities across large regions. This study assessed whether drone-based imagery and deep learning modeling approaches could be used to map species in complex chaparral, coastal sage scrub, and oak woodland communities. We tested the effectiveness of random forest, support vector machine, and convolutional neural network (CNN) coupled with object-based image analysis (OBIA) for mapping in diverse shrublands. Our CNN + OBIA approach outperformed random forest and support vector machine methods to accurately identify tree and shrub species, vegetation gaps, and communities, even distinguishing two congeneric shrub species with similar morphological characteristics. Similar accuracies were attained when applied to neighboring sites. This work is key to the accurate species identification and large scale mapping needed for conservation research and monitoring in chaparral and other wildland plant communities. Uncertainty in model application is associated with less common species and intermixed canopies.
Defining the Perception of Energy Security: An Overview
Authors: Siksnelyte-Butkiene Indre
Published: June 2023

Energy security is recognized as a key element for the successful functioning of an entire energy system. However, the perception of energy security is contextual and there is no universally accepted definition of the concept. The current global concerns about climate change, human welfare and energy market challenges due to the COVID-19 pandemic, military conflicts, various geopolitical issues and scarcity of energy resources have affected the perception of the energy security concept as well. The research aims to define how energy security is perceived amid current global concerns and to identify the essential components. The four-tiered research methodology was developed and applied to determine the current perception of energy security. While the systematic literature review was conducted according to the SALSA (Search, Appraisal, Synthesis and Analysis) framework, it was found that the current perception of energy security consists of seven main components, these are: Availability, Affordability, Environmental Impact, Social Impact, Geopolitical Relationships, Government Effectiveness and Technological Development. The paper contributes to discourse development and clarification of perception of energy security and will be useful for further research, both dealing with the concept of energy security itself and developing composite indicators for energy security assessment.
Effects of Game-Enhanced Supplemental Fraction Curriculum on Student Engagement, Fraction Knowledge, and STEM Interest
Authors: Hunt Jessica H. , Taub Michelle , Marino Matthew , Duarte Alejandra , Bentley Brianna , Holman Kenneth , Kuhlman Adrian
Published: June 2023

People with disabilities are underrepresented in STEM as well as information, communication, and technology (ICT) careers. The underrepresentation of individuals with disabilities in STEM may reflect systemic issues of access. Curricular materials that allow students to demonstrate their current fraction knowledge through multiple means and provide opportunities to share and explain their thinking with others may address issues of access students face in elementary school. In this study, we employed a sequential mixed-methods design to investigate how game-enhanced fraction intervention impacts students’ fraction knowledge, engagement, and STEM interests. Quantitative results revealed statistically significant effects of the program on students’ fraction understanding and engagement but not their STEM interest. Qualitative analyses revealed three themes—(1) Accessible, Enjoyable Learning, (2) Can’t Relate, and (3) Dreaming Bigger—that provided contextual backing for the quantitative results. Implications for future research and development are shared.
On the Relationship between a Student Association’s Endeavors to Foster a Social–Academic Climate on Campus, Students’ Self-Efficacy, and Academic Motivation
Authors: Davidovitch Nitza , Dorot Ruth
Published: June 2023

The current study is a case study examining a student association’s endeavors to foster a social–academic climate on campus, grant students a sense of self-efficacy, and even contribute to students’ motivation. The research literature lacks empirical knowledge on the activity of student associations and their contribution to institutions of higher education and their students. Moreover, academic institutions see student associations at times as a burden, a type of labor union to be placated by the faculty and the academic institution. The research sample consisted of 122 students from a university in Israel (38 men and 84 women; mean age 25). Several questionnaires were administered to the respondents: a questionnaire on the social–academic climate on the academic campus, a questionnaire on students’ academic motivation, a questionnaire on students’ self-efficacy, and a sociodemographic questionnaire. From the research findings, it is evident that the activities of the student associations on the academic campus play a meaningful role in fostering students’ academic motivation and self-efficacy. The research findings indicate that the scope of student association activities is positively related to the students’ academic motivation and self-efficacy. Moreover, students living in student dorms were found to evaluate the activities of the student association as higher than did students who were not living in student dorms. These findings constitute a preliminary foundation for future studies on the importance of student associations in academic institutions and their contribution to the students. Furthermore, these findings highlight the need to boost and increase student associations’ activities to provide students with adapted and efficient solutions to their challenges. The student association can be transformed from a burden to an asset for the academic institution.
Adapting Geo-Indistinguishability for Privacy-Preserving Collection of Medical Microdata
Authors: Song Seungmin , Kim Jongwook
Published: June 2023

In the era of the Fourth Industrial Revolution, the increasing demand for data collection and sharing for analysis purposes has raised concerns regarding privacy violations. Protecting individual privacy during the collection and dissemination of sensitive information has emerged as a critical concern. In this paper, we propose a privacy-preserving framework for collecting users’ medical microdata, utilizing geo-indistinguishability (Geo-I), a concept based on well-known differential privacy. We adapt Geo-I, originally designed for protecting location information privacy, to collect medical microdata while minimizing the reduction in data utility. To mitigate the reduction in data utility caused by the perturbation mechanism of Geo-I, we propose a novel data perturbation technique that utilizes the prior distribution information of the data being collected. The proposed framework enables the collection of perturbed microdata with a distribution similar to that of the original dataset, even in scenarios that demand high levels of privacy protection, typically requiring significant perturbations to the original data. We evaluate the performance of our proposed algorithms using real-world data and demonstrate that our approach significantly outperforms existing methods, ensuring user privacy while preserving data utility in medical data collection.
Three-Stage Cross-Chain Protocol Based on Notary Group
Authors: Chen Longfei , Yao Zhongyuan , Si Xueming , Zhang Qian
Published: June 2023

With the continuous development of blockchain technology and economy, blockchain applications have been well developed in multiple key areas. The demand for interoperability between different blockchains is also increasing. Cross-chain protocol has become a major approach to solve cross-chain problems by defining a series of cross-chain processes and standards. In response to the problems of long transaction time, high transaction costs, and high degree of centralization in most cross-chain protocols, this paper proposes a three-stage cross-chain protocol based on transaction notary groups and verification notary groups. Without increasing transaction costs and transaction time, the centralization problem of notary mechanism cross-chain technology is solved, realizing secure and fast interaction between different blockchains. Experimental results show that as long as malicious nodes in the notary group do not exceed one-third, the three-stage cross-chain protocol can effectively ensure the security of cross-chain transactions and solve the centralization problem.
Wood Chip Production Efficiency Depending on Chipper Type
Authors: Stolarski Jakub , Wierzbicki Sławomir , Nitkiewicz Szymon , Stolarski Mariusz Jerzy
Published: June 2023

Solid biofuels, including wood chips, are still the most important feedstock in the structure of primary energy production from renewable energy sources. Wood chips are derived mainly from forests and the wood industry, including sawmills. However, the considerable diversity of chipper types results in great differences in their final production efficiency. The objective of this study was to analyze and evaluate the efficiency of three mobile chippers used in wood chip production by determining their throughput rate, diesel fuel and energy consumption, cost of chipping and greenhouse gas emission, as well as the quality of the chips. By far shortest time (0.82 min. Mg−1) of producing 1 Mg of wood chips was found for the Albach 565 kW chipper. Moreover, the mean time needed for the production of 1 Mg of chips with a chipper of the same make but with a smaller engine (Albach 515 kW) was 8.8% longer. This time was 284.9% longer than when the Bruks chipper was used. However, the highest mean effectiveness of diesel fuel use (expressed as the lowest diesel fuel consumption of 1.41 dm3 Mg−1), the lowest energy consumption (52.02 MJ Mg−1), the lowest cost of diesel fuel use (2.28 € Mg−1) and the lowest GHG emission (4.27 kg Mg−1 CO2eq) in wood chip production were determined for the Albach 515 kW chipper. In contrast, the poorest parameters were determined for the Bruks chipper.
Challenges of Application of Green Ammonia as Fuel in Onshore Transportation
Authors: Chorowski Maciej , Lepszy Michał , Machaj Krystian , Malecha Ziemowit , Porwisiak Dominika , Porwisiak Paweł , Rogala Zbigniew , Stanclik Michał
Published: June 2023

The main purpose of the article is to present a comprehensive and critical review of the challenges and risks associated with the use of green ammonia as an alternative fuel in land transport. The review is motivated by the clear trend toward phasing out fossil fuel vehicles and replacing them with emission-free alternatives. Topics covered include safety aspects such as safety of powering of vehicles, the production of green ammonia, the use of ammonia in the context of various fuel solutions (combustion engines and fuel cell engines), and the discussion of ammonia-powered vehicles in the context of air pollution. The paper offers new insights into identifying the challenges and obstacles that may arise in the case of the massive use of green ammonia as a fuel for land transport. In addition, the review presents the latest information on the technological readiness of the necessary infrastructure for the production, transport, storage, and utilization of green ammonia in internal combustion or electric engines.
An Overview of Small Nuclear Power Plants for Clean Energy Production: Comparative Analysis of Distributed Generation Technologies and Future Perspectives
Authors: Rogalev Nikolay , Rogalev Andrey , Kindra Vladimir , Zlyvko Olga , Osipov Sergey
Published: June 2023

There is a steady trend in the world to increase the share of distributed generation. The volume of self-generated energy commissioning is constantly growing, with projected increases in growth rates in the future. At the same time, demands for efficiency and environmental safety in new power plants are constantly increasing. In this regard, one of the promising areas for the development of distributed energy is the transition to small nuclear power plants (SNPPs). As in the case of wind and solar power plants, SNPP operations are not accompanied by emissions of toxic substances or greenhouse gases into the atmosphere. In addition, SNPPs consume a much smaller volume and mass of fuel compared to conventional small-capacity fossil fuel power plants. This paper describes the characteristics of the main types of distributed generation. The key technical and economic characteristics of existing and prospective small-capacity nuclear fuel facilities are systematized. The results of a comparative analysis of the cost of electricity produced by SNPPs and competing power plants are also presented. In addition, a number of promising regions of the Russian Federation for the introduction of SNPPS have been identified, and a review of the methods of energy storage for SNPPS, which are necessary when working in an isolated power system, has been carried out.
Data-Driven Minute-Ahead Forecast of PV Generation with Adjacent PV Sector Information
Authors: Kang Jimyung , Lee Jooseung , Lee Soonwoo
Published: June 2023

This paper proposes and validates a data-driven minute-ahead forecast model for photovoltaic (PV) generation, which is essential for real-time micro-grid scheduling. Unlike day-ahead PV forecasts that heavily rely on weather forecast information, our proposed model does not require such data as it operates in an ultra-short-term time domain. Instead, the model leverages the generation data of the target PV sector and its adjacent sectors to capture short-term factors that affect electricity generation, such as the movement of clouds. The proposed model employs a long short-term memory (LSTM) network to process the data. By conducting experiments with real PV site data, we demonstrate that the information from adjacent PV sectors improves the accuracy of minute-ahead PV generation forecasts by 3.66% in the mean squared error index and 1.19% in the mean absolute error index compared to the model without adjacent sector information.
Can Small-Scale Dairy Farm Profitability Increase with the Use of Solar Energy Technology? An Experimental Study in Central Tunisia
Authors: Zlaoui Meriem , Dhraief Mohamed Zied , Hilali Muhi El-Dine , Dhehibi Boubaker , Ben Salem Mondher , Jebali Oussama , Rekik Mourad
Published: June 2023

The dairy sector in Tunisia is based on small-scale farms, with 81% of the breeders owning less than five cows. On these farms, milk is stored in plastic containers, resulting in post-production losses estimated at 10% in the studied region. Due to high temperatures, the present paper aims to study the implementation of an innovative solar-powered milk cooling system in Central Tunisia and assess its profitability for dairy farmers. The methodology is based on a comparison of three small-scale farm business models: a farm without any milk cooling equipment, a farm using an innovative milk cooling technology, and a farm using an electrical cooling tank. Results showed the significance of milk cooling in reducing milk rejection to 0%, leading to a total production of 6400 L per cow by the fifth year. Additionally, milk sales were found to increase due to the premium of 0.010 TND/L for cooled milk paid. In addition, farms utilizing solar-powered milk cooling technology exhibited superior profitability in terms of financial indicators. This research offers a sustainable energy solution for milk cooling on small farms, specifically addressing the challenges faced by these farms located in isolated areas where access to electricity is limited and the availability of milk cooling equipment is lacking.
Numerical Tracking of Natural Gas Migration in Underground Gas Storage with Multilayered Sandstone and Fault-Bearing Caprocks
Authors: Ban Shengnan , Liu Hejuan , Mao Haijun , Shi Xilin , Qiu Xiaosong , Liu Mancang , Min Zhongshun , Song Yujia , Wei Xinxing
Published: June 2023

The structure of caprocks is often greatly altered by different scales of faults or fissures in long-term geological tectonic evolution, and the sealing performance may be deteriorated. In this paper, a simplified geological model characterized as multilayered sandstone and fault-bearing caprocks extracted from the Shuang 6 underground gas storage located in the Liaohe oilfield was established. Different fault geometry (e.g., fault length, fault dip angle, and fault type) and seepage attributes (porosity and permeability) were considered to illustrate their impacts on natural gas migration during the cyclic high rate of injection and production of natural gas. The results showed that the seepage anisotropy and the natural gas front are strongly affected by the formation properties and, especially, are hindered by the low permeability sandstone layers. The difference in the lateral migration distance of natural gas in different layers can reach 110 m at the end of the injection period, with an annual injection volume of 108 m3. The migration of natural gas along the fault zone is mainly controlled by the permeability of faults, followed by fault scale, fault dip angle, and fault type. The sealing failure of caprocks in the fault zone does not occur based on the simulated gas migration distribution, showing that a very limited amount of natural gas migrates into the caprocks.
Unstable Convection in a Vertical Double–Layer Porous Slab
Authors: Lazzari Stefano , Celli Michele , Barletta Antonio , Brandão Pedro Vayssière
Published: June 2023

A convective stability analysis of the flow in a vertical fluid-saturated porous slab made of two layers with different thermophysical properties is presented. The external boundaries are isothermal with one of them impermeable while the other is open to an external fluid reservoir. This study is a development of previous investigations on the onset of thermal instability in a vertical heterogeneous porous slab where the heterogeneity may be either continuous or piecewise as determined by a multilayer structure. The aim of this paper is investigating whether a two-layer structure of the porous slab may lead to the onset of cellular convection patterns. The linear stability analysis is carried out under the assumption that one porous layer has a thermal conductivity much higher than the other layer. This assumption may be justified for the model of a heat transfer enhancement system involving a saturated metal foam. A flow model for the natural convection based on Darcy’s momentum transfer in a porous medium is adopted. The buoyancy-induced basic flow state is evaluated analytically. Small-amplitude two-dimensional perturbations of the basic state are introduced, thus leading to a linear set of governing equations for the disturbances. A normal mode analysis allows one to formulate the stability eigenvalue problem. The numerical solution of the stability eigenvalue problem provides the onset conditions for the thermal instability. Moreover, the results evidence that the permeability ratio of the two layers is a key parameter for the critical conditions of the instability.
Improvement and Assessment of Convolutional Neural Network for Tree Species Identification Based on Bark Characteristics
Authors: Cui Zhelin , Li Xinran , Li Tao , Li Mingyang
Published: June 2023

Efficient tree species identification is of great importance in forest inventory and management. As the textural properties of tree barks vary less notably as a result of seasonal change than other tree organs, they are more suitable for the identification of tree species using deep learning models. In this study, we adopted the ConvNeXt convolutional neural network to identify 33 tree species using the BarkNetV2 dataset, compared the classification accuracy values of different tree species, and performed visual analysis of the network’s visual features. The results show the following trends: (1) the pre-trained network weights exhibit up to 97.61% classification accuracy for the test set, indicating that the network has high accuracy; (2) the classification accuracy values of more than half of the tree species can reach 98%, while the confidence level of correct identification (probability ratio of true labels) of tree species images is relatively high; and (3) there is a strong correlation between the network’s visual attractiveness and the tree bark’s biological characteristics, which share similarities with humans’ organization of tree species. The method suggested in this study has the potential to increase the efficiency of tree species identification in forest resources surveys and is of considerable value in forest management.
The Green Space Availability in Ufa City Metropolis
Authors: Rakhmatullina Irina , Rakhmatullin Zagir , Zaitsev Gleb , Davydychev Alexandr , Gilmanova Galia , Komissarov Mikhail
Published: June 2023

For the administrative districts of the city of Ufa (the capital of the Republic of Bashkortostan, Russia), the distribution of green spaces, including public green spaces, the degree of greening, and the accessible green spaces per resident, were analysed. Green spaces were estimated to be available for the citizens within 400 m (for multi-story building areas), 800 m (for low-rise building areas), and 1250 m (for all residential areas). The analysis relies on open geographic system tools and open spatial data. Data are compared with existing governmental regulations and recommendations. Green stands to cover approximately 35% of the city area (indicating that Ufa is one of the greenest among the 16 million-plus Russian cities), and most forest sites are located outside the city centre. Meanwhile, public green spaces cover less than 5% of the city and are unevenly spread across administrative urban districts. The major recreation facilities are situated in the city centre. Despite the high level of greening in Ufa on the whole, access to public areas in multi-story building areas within a 400 m radius and low-rise building areas within an 800 m radius is not guaranteed for city residents.