bluuebunny/crossref_metadata_2025 huggingface dataset:
The Recovery of Mediterranean Soils After Post-Fire Management: The Role of Biocrusts and Soil Microbial Communities
Authors: García-Carmona Minerva , García-Orenes Fuensanta , Arcenegui Victoria , Mataix-Solera Jorge
Published: June 2023

Although Mediterranean ecosystems are adapted to fire disturbances, soils are prone to degradation. Therefore, post-fire forest management is a critical step for ecosystem recovery: it can either reduce soil degradation or add a new disturbance. Post-fire management in Mediterranean burnt forests includes interventions with contrasting approaches, including the management of burnt trees, soil protection, or practices devoted to ecosystem restoration via the improvement of components or processes in the affected ecosystem. The consequences of forest management on soils are complex, thereby, in the context of the intensification of fire events and climate change, understanding the response of key soil components in managed ecosystems is critical for prioritizing soil conservation. One interesting component in the early post-fire stages is moss biocrust. The rapid colonization of biocrust-forming mosses in early successional stages post-disturbance stabilizes soils in their most vulnerable period. However, it is completely unknown further implications as active agents in the recovery and resilience of soils, in the transient stage before vascular vegetation regrowth. In combination with the biocrust, the response of soil microbial communities to forest management is crucial for evaluating the soil recovery progress, given their active role in fundamental ecosystem functions. The additive consequences of fires and forest management on biocrust emergence or microbial composition and functionality are usually neglected in the investigation of post-fire systems, although of major relevance to support strategies to preserve soils against functionality loss.
Nontarget Site-Based Resistance to Fenoxaprop-P-ethyl and Candidate Genes Involved in Alopecurus japonicus
Authors: Xu Hongle , Ye Xiaofan , Liang Shaoqi , Cheng Jingping , Leng Qiuli , Sun Lanlan , Su Wangcang , Xue Fei , Dong Liyao , Wu Renhai
Published: June 2023

Nontarget-site resistance (NTSR) is a complex multigenic trait that is associated with the potential mechanisms of herbicide resistance which pose a serious threat to global crop protection. However, the NTSR mechanisms of Alopecurus japonicus, a malignant weed infesting wheat fields, are less characterized. In this study, we used RNA-sequencing transcriptome and enzyme activity detection to investigate the NTSR mechanisms and candidate genes involved in fenoxaprop-P-ethyl (FE) in a previously identified resistant population compared to the sensitive population of A. japonicus. Transcriptome analysis identified nine upregulated genes, which were constitutively overexpressed and upregulated by FE application in the resistant population, and the results were validated using quantitative real-time PCR. These genes including one cytochrome P450 monooxygenase (P450) gene (CYP75B4), one ATP-binding cassette (ABC) transporter gene (ABCG36), one laccase (LAC) gene (LAC15), one 9-cis-epoxycarotenoid dioxygenase (NCED) gene (NCED5), two purple acid phosphatase (PAP) genes (PAP4, PAP15), one sucrose phosphate synthase (SPS) gene (SPS3), one protein related to disease resistance gene (RGA3) and one immune protein gene (R1B-17). The activity assay of LAC, NCED, PAP and SPS revealed that the activities of these enzymes in the resistant population were significantly higher than those in the sensitive population at 0 h and after FE application at 12 h, 24 h and 72 h. Nevertheless, whether LAC, NCED, PAP and SPS genes were involved in herbicide metabolism needs to be further validated. Our results revealed that CYP, ABC transporter and LAC genes may participate in A. japonicus resistance. These genes identified in the present study provide new insights into the resistance mechanism of weeds in response to herbicide. Our study also implies the complexity of the NTSR mechanisms of weeds.
Effects of Rice Husk Biochar and Compost Amendments on Soil Phosphorus Fractions, Enzyme Activities and Rice Yields in Salt-Affected Acid Soils in the Mekong Delta, Viet Nam
Authors: Linh Doan Thi Truc , Khoi Chau Minh , Ritz Karl , Sinh Van Nguyen , Phuong Nguyen Thi Kim , My Huynh Mach Tra , Linh Tran Ba , Minh Dang Duy , Linh Thi Tu , Toyota Koki
Published: June 2023

Given that rice husk biochar has been shown to modulate salinity in salt-affected acid soils, the objective of this study was to investigate the effects of organic amendment of salinized acid soils on P fractions, enzyme activities, and associated rice yield. Four treatments, viz. Rice–Rice–Rice, [RRR]; Fallow–Rice–Rice, [FRR]; Fallow–Rice–Rice + 3 Mg ha−1 of compost [FRR + Comp]; and Fallow–Rice–Rice + 10 Mg ha−1 of biochar [FRR + BC] were established at Ben Tre and Kien Giang sites, Viet Nam, over six consecutive crops. Soil properties at harvest of the sixth crop showed that there were diverse patterns of fractionation between P forms with respect to treatment. Overarchingly, biochar increased labile and moderately labile inorganic P and organic P by 30% to 70%, respectively, whilst compost had a relatively modest effect on these pools. Soil phosphatase activities at crop tillering increased following the FRR + Comp and FRR + BC treatments compared with those in RRR, except for acid phosphatase at Ben Tre. At harvest, there were no significant differences between the enzyme activities among the treatments. Rice yield was positively correlated with the more labile forms of P, soil C, and acid phosphatase activity. In the absence of organic amendments, there was no effect of triple versus double rice crops being grown in one-year cycle. Repeated application of biochar (10 Mg ha−1 × 5 times) showed potential to increase grain yields and total soil C in salt-affected acid soils, via modulation of P transformations to more plant-available forms.
Tea Tree Oil: Properties and the Therapeutic Approach to Acne—A Review
Authors: Nascimento Tânia , Gomes Diana , Simões Ricardo , da Graça Miguel Maria
Published: June 2023

Acne vulgaris is an inflammatory dermatological pathology that affects mostly young people. However, it can also appear in adulthood, mainly in women. It has a high psychosocial impact, not only at the time of active lesions but also due to the consequences of lesions such as scarring and hyperpigmentation. Several factors are involved in the physiopathology of acne and the constant search for active ingredients is a reality, namely phytotherapeutic ingredients. Tea tree oil is an essential oil extracted from Melaleuca alternifolia (Maiden & Betch) Cheel with known antibacterial, anti-inflammatory, and antioxidant properties, making it a candidate for the treatment of acne. This review aims to describe the various properties of tea tree oil that make it a possible ingredient to use in the treatment of acne and to present several human studies that have evaluated the efficacy and safety of using tea tree oil in the treatment of acne. It can be concluded that tea tree oil has good antibacterial, anti-inflammatory, and antioxidant properties that result in a decrease in the number of inflammatory lesions, mainly papules, and pustules. However, given the diversity of study designs, it is not possible to draw concrete conclusions on the efficacy and safety of this oil in the treatment of acne.
Progress of Machine Vision Technologies in Intelligent Dairy Farming
Authors: Zhang Yongan , Zhang Qian , Zhang Lina , Li Jia , Li Meian , Liu Yanqiu , Shi Yanyu
Published: June 2023

The large-scale and precise intelligent breeding mode for dairy cows is the main direction for the development of the dairy industry. Machine vision has become an important technological means for the intelligent breeding of dairy cows due to its non-invasive, low-cost, and multi-behavior recognition capabilities. This review summarizes the recent application of machine vision technology, machine learning, and deep learning in the main behavior recognition of dairy cows. The authors summarized identity recognition technology based on facial features, muzzle prints, and body features of dairy cows; motion behavior recognition technology such as lying, standing, walking, drinking, eating, rumination, estrus; and the recognition of common diseases such as lameness and mastitis. Based on current research results, machine vision technology will become one of the important technological means for the intelligent breeding of dairy cows. Finally, the author also summarized the advantages of this technology in intelligent dairy farming, as well as the problems and challenges faced in the next development.
Interactive Guiding Sparse Auto-Encoder with Wasserstein Regularization for Efficient Classification
Authors: Lee Haneum , Hur Cheonghwan , Ibrokhimov Bunyodbek , Kang Sanggil
Published: June 2023

In the era of big data, feature engineering has proved its efficiency and importance in dimensionality reduction and useful information extraction from original features. Feature engineering can be expressed as dimensionality reduction and is divided into two types of methods, namely, feature selection and feature extraction. Each method has its pros and cons. There are a lot of studies that combine these methods. The sparse autoencoder (SAE) is a representative deep feature learning method that combines feature selection with feature extraction. However, existing SAEs do not consider feature importance during training. It causes extracting irrelevant information. In this paper, we propose an interactive guiding sparse autoencoder (IGSAE) to guide the information by two interactive guiding layers and sparsity constraints. The interactive guiding layers keep the main distribution using Wasserstein distance, which is a metric of distribution difference, and it suppresses the leverage of guiding features to prevent overfitting. We perform our experiments using four datasets that have different dimensionalities and numbers of samples. The proposed IGSAE method produces a better classification performance compared to other dimensionality reduction methods.
Pulse Cycle Dependent Nondipole Effects in Above-Threshold Ionization
Authors: Dar Danish Furekh , Fritzsche Stephan
Published: June 2023

In this study, we employ strong field approximation (SFA) to investigate the influence of the number of pulse cycles on above-threshold ionization within the framework of nondipole theory. The SFA enables the analysis of the ionization process under the dominance of the electric field, compared to other factors such as the binding potential of an atom. Nondipole effects, including higher-order multipole fields, can significantly impact ionization dynamics. However, the interaction between nondipole effects and pulse cycles remains unclear. Therefore, we investigate the pulse cycle dependence of ionization and examine peak shifts in Kr and Ar atoms. Our findings have implications for comprehensively understanding the effects of electromagnetic fields on electron behavior. The insights gained from this study provide valuable guidance for future research in strong field ionization.
Optimization of Hempseed-Added Kombucha for Increasing the Antioxidant Capacity, Protein Concentration, and Total Phenolic Content
Authors: Reyes-Flores Samanta , Pereira Taísa Sabrina Silva , Ramírez-Rodrigues Milena Maria
Published: June 2023

To enhance the effects of kombucha’s beneficial compounds and their functional properties, studies on kombucha fermentation using alternatives ingredients are needed. The aim of this study was to formulate and optimize kombucha using hempseed as a high antioxidant, phenolic compound, and protein contributor. An experimental central composite design (CCD) with response surface methodology (RSM) was used for maximizing the antioxidant capacity (AC), total phenolic content (TPC), and protein concentrations (PC) of this product. The optimized infusion concentrations were observed at 0.017% of hempseeds and 0.00046% of black tea leaves. AC was determined by the DPPH+ assay in microplate. TPC was determined in microplate using the Folin–Ciocalteu method. PC was determined by Peterson’s modification of the micro-Lowry method. The optimized kombucha results were 0.134 ± 0.002 mg Trolox Eq/mL for AC, 0.473 ± 0.027 mg GA Eq/mL for TPC, and 6.535 ± 0.477 μg/mL of PC. RSM can be developed to optimize the formulation of kombuchas to increase the amounts of desirables compounds. This study demonstrated that hempseeds added to kombucha have a higher antioxidant capacity, total phenolic content, and protein concentration than traditional kombucha.
AHANet: Adaptive Hybrid Attention Network for Alzheimer’s Disease Classification Using Brain Magnetic Resonance Imaging
Authors: Illakiya T. , Ramamurthy Karthik , Siddharth M. V. , Mishra Rashmi , Udainiya Ashish
Published: June 2023

Alzheimer’s disease (AD) is a progressive neurological problem that causes brain atrophy and affects the memory and thinking skills of an individual. Accurate detection of AD has been a challenging research topic for a long time in the area of medical image processing. Detecting AD at its earliest stage is crucial for the successful treatment of the disease. The proposed Adaptive Hybrid Attention Network (AHANet) has two attention modules, namely Enhanced Non-Local Attention (ENLA) and Coordinate Attention. These modules extract global-level features and local-level features separately from the brain Magnetic Resonance Imaging (MRI), thereby boosting the feature extraction power of the network. The ENLA module extracts spatial and contextual information on a global scale while also capturing important long-range dependencies. The Coordinate Attention module captures local features from the input images. It embeds positional information into the channel attention mechanism for enhanced feature extraction. Moreover, an Adaptive Feature Aggregation (AFA) module is proposed to fuse features from the global and local levels in an effective way. As a result of incorporating the above architectural enhancements into the DenseNet architecture, the proposed network exhibited better performance compared to the existing works. The proposed network was trained and tested on the ADNI dataset, yielding a classification accuracy of 98.53%.
Exploring the Possibility of Measuring Vertebrae Bone Structure Metrics Using MDCT Images: An Unpaired Image-to-Image Translation Method
Authors: Jin Dan , Zheng Han , Yuan Huishu
Published: June 2023

Bone structure metrics are vital for the evaluation of vertebral bone strength. However, the gold standard for measuring bone structure metrics, micro-Computed Tomography (micro-CT), cannot be used in vivo, which hinders the early diagnosis of fragility fractures. This paper used an unpaired image-to-image translation method to capture the mapping between clinical multidetector computed tomography (MDCT) and micro-CT images and then generated micro-CT-like images to measure bone structure metrics. MDCT and micro-CT images were scanned from 75 human lumbar spine specimens and formed training and testing sets. The generator in the model focused on learning both the structure and detailed pattern of bone trabeculae and generating micro-CT-like images, and the discriminator determined whether the generated images were micro-CT images or not. Based on similarity metrics (i.e., SSIM and FID) and bone structure metrics (i.e., bone volume fraction, trabecular separation and trabecular thickness), a set of comparisons were performed. The results show that the proposed method can perform better in terms of both similarity metrics and bone structure metrics and the improvement is statistically significant. In particular, we compared the proposed method with the paired image-to-image method and analyzed the pros and cons of the method used.
Clinical and Molecular Aspects Associated with Defects in the Transcription Factor POU3F4: A Review
Authors: Bernardinelli Emanuele , Huber Florian , Roesch Sebastian , Dossena Silvia
Published: June 2023

X-linked deafness (DFNX) is estimated to account for up to 2% of cases of hereditary hearing loss and occurs in both syndromic and non-syndromic forms. POU3F4 is the gene most commonly associated with X-linked deafness (DFNX2, DFN3) and accounts for about 50% of the cases of X-linked non-syndromic hearing loss. This gene codes for a transcription factor of the POU family that plays a major role in the development of the middle and inner ear. The clinical features of POU3F4-related hearing loss include a pathognomonic malformation of the inner ear defined as incomplete partition of the cochlea type 3 (IP-III). Often, a perilymphatic gusher is observed upon stapedectomy during surgery, possibly as a consequence of an incomplete separation of the cochlea from the internal auditory canal. Here we present an overview of the pathogenic gene variants of POU3F4 reported in the literature and discuss the associated clinical features, including hearing loss combined with additional phenotypes such as cognitive and motor developmental delays. Research on the transcriptional targets of POU3F4 in the ear and brain is in its early stages and is expected to greatly advance our understanding of the pathophysiology of POU3F4-linked hearing loss.
Phase Angle in Head and Neck Cancer: A Sex-Differential Analysis from Biological and Clinical Behavior to Health-Related Quality of Life
Authors: Martínez-Herrera Brenda-Eugenia , Gutiérrez-Rodríguez Leonardo-Xicotencatl , Trujillo-Hernández Benjamín , Muñoz-García Michelle-Guadalupe , Cervantes-González Luz-María , José Ochoa Laura-Liliana , González-Rodríguez Javier-Andrés , Solórzano-Meléndez Alejandro , Gómez-Sánchez Eduardo , Carrillo-Nuñez Gabriela-Guadalupe , Salazar-Páramo Mario , Nava-Zavala Arnulfo-Hernán , Velázquez-Flores Martha-Cecilia , Nuño-Guzmán Carlos-M. , Mireles-Ramírez Mario-Alberto , Balderas-Peña Luz-Ma.-Adriana , Sat-Muñoz Daniel
Published: June 2023

Head and neck cancer (H&NC) is a diverse category of tumors related to malignancies in the common aerodigestive pathway, with high metabolic rate, poor nutritional and treatment outcomes, and elevated mortality despite the best standard treatment. Herein, we focus on determining how the phase angle (PA) differs across sex as a predictor of poor prognosis, low quality-of-life (QoL) scores, and mortality in patients with head and neck cancer. This follow-up study presents a sex-differential analysis in a prospective cohort of 139 head and neck cancer patients categorized by sex as male (n = 107) and female (n = 32). Patients were compared in terms of nutritional, biochemical, and quality-of-life indicators between low and normal PA in women (<3.9° (n = 14, 43.75%) and ≥3.9°) and men (<4.5° (n = 62, 57.9%) and ≥4.5°). Our results show that most patients were in locally advanced clinical stages (women: n = 21 (65.7%); men: n = 67 (62.6%)) and that patients with low PA had a lower punctuation in parameters such as handgrip strength, four-meter walking speed, albumin, C-reactive protein (CRP), and CRP/albumin ratio (CAR), as well as the worst QoL scores in functional and symptomatic scales in both the male and female groups. A comparison between sexes revealed significant disparities; malnourishment and tumor cachexia related to an inflammatory state was more evident in the women’s group.
Vitamin D Role in Childhood Mite Allergy and Allergen Immunotherapy (AIT)
Authors: Petrarca Claudia , Viola Davide
Published: June 2023

The post hoc analysis presented here aimed to address the influence of endogenous vitamin D in the immunological mechanism underlying effective mite allergoid immunotherapy (AIT). Previously, we have shown that in allergic children, after 12 months of this immunoactive treatment, functionally potentiated memory regulatory T cells are identified. Indeed, AIT is the only known treatment that is able to reshape the detrimental immune response against the allergen into a non-noxious one. Besides, VD is widely considered an immunoregulatory molecule that is endogenously produced and exogenously provided by foods and supplements that might interact with the AIT mechanism, thus affecting its outcome. Therefore, a post hoc analysis of the clinical and immunological data from three different cohorts of allergic patients was performed. One cohort (N = 70) was on a standard symptom-controlling pharmacological treatment, while the other two (N = 60 and N = 35) were treated with AIT for 12 months. In the first cohort, a lower mean endogenous VD level (<22 ng/mL) was observed along with worse symptoms and a greater use of medications. Remarkably, the comparison between two sub-cohorts of patients with a serum VD level above (N = 32) or below (N = 28) a cut-off value set at the mean value (27 ng/mL) revealed that optimal improvement of all clinical and immune parameters was achieved (as expected from effective AIT), irrespective of the VD level. Notably, the third analysis, carried out on one cohort of AIT patients that were also concomitantly taking VD3 as a food supplement (N = 19), was distinguished by an uppermost overall treatment outcome (the amelioration of symptoms, the lowest medication requirements, and a reduction in the total and allergen-specific IgE levels), as well as an increase in the allergen-specific tolerogenic memory T regulatory cells. These findings suggest that the endogenous VD level affects the allergy severity and allergen immunotherapy effectiveness. In addition, VD3 might be investigated as an add-on supplement to obtain the best out of immunotherapy in VD-deficient/-insufficient allergic patients. The immunogenic, but low-allergenic, mite allergoid used as the bioactive agent might have contributed to minimizing the allergic response and highlighting the immunological effects described here.
Examining the Impact of Gender Discriminatory Practices on Women’s Development and Progression at Work
Authors: Fitong Ketchiwou Gaelle , Dzansi Lineo
Published: June 2023

Although there has been a worldwide cry for gender equity within organizations, gender discriminatory practices continue to be a challenge. Many women still suffer from gender discrimination and remain at the bottom of organizational structures despite their efforts to ascend. This paper seeks to examine the link between gender discriminatory practices and women’s skill development and progression within the workplace. The study espoused a quantitative approach. A questionnaire survey was self-administered online to 412 women through a convenient non-probability sampling method. Descriptive tendencies, test normality, validity, reliability, and regression analysis were performed using the statistical package for the social sciences (SPSS), AMOS 27. The results reveal that women’s skill development is impacted by workplace gender discriminatory practices, and the career progression of women is linked to their skill development. Yet it rejects the claim that workplace gender discriminatory practices impact women’s career progression. While having a gender-friendly work environment is applaudable, developing women’s skills and promoting their advancement at work will require more effort from companies. Organizations need to be deliberate about the skills development and career progression of women and institutionalize initiatives that directly encourage women to engage in developmental activities as well as initiatives geared towards promoting women’s career advancement.
Dental Loupe’s Role in Detection of Caries of Molars in Children by Student and Dentists
Authors: Blumer Sigalit , Zidani Siwar , Peretz Benjamin , Kats Lazar , Azem Hanaa , Naishlos Sarit , Kharouba Johnny
Published: June 2023

Purpose: The objectives of this study were to examine the effectiveness of diagnosing occlusal caries in molar teeth in children under the use of loupes and, secondarily, to examine whether there is a difference in the diagnosis between permanent and primary teeth using dental loupes. In addition, to check whether the student’s diagnosis using loupes improves caries diagnosis compared to dentists’ diagnosis in both methods. Methods: The data were collected from 163 patients aged 6–14 who sought treatment in the Pedodontic Department of the Faculty of Dentistry at Tel-Aviv University during 2020–2021. The first and second permanent molars and second primary molars with deep groves were examined. A student and dentists made the diagnosis with and without loupes while using the ICDAS criteria. Results: The student’s examinations without the loupes detected no caries in 60% of the cases compared to 76.9% in the examinations with the loupes and found initial caries without cavitation (ICDAS1) in only 17.6% of teeth without loupes examination compared to 33% using loupes. The dentist correctly diagnosed no caries (ICDAS0) in 82.1% of cases without loupes and initial caries without cavitation (ICDAS1) in 62.5% of cases. The dentist correctly diagnosed distinct caries without cavitation (ICDAS2) in 90.8% of cases. No differences were observed in caries diagnosis between primary and permanent teeth when the examiner was a specialist/intern using loupes; however, there was a statistically significant difference (p = 0.047) when the diagnosis was made by a student using loupes. Clinical significance: The use of dental loupes is an effective method for the correct and early diagnosis of occlusal caries lesions in children’s molar teeth by both dentists and students, and this is in accordance with the principle of minimally invasive dentistry. There is a justification for the use of dental loupes for the diagnosis of initial occlusal caries in primary and permanent molars in children in a precise way. Using loupes especially improves the correct diagnosis of initial caries in primary teeth by students.
Cytokine Storm Syndrome Triggered by Extracorporeal Membrane Oxygenation in Pediatric Patients
Authors: Reiff Daniel D. , Cron Randy Q.
Published: June 2023

Cytokine storm syndrome (CSS) is a serious and potentially life-threatening condition caused by severe systemic inflammation, immune activation, and a positive feedback loop of cytokine release. Typically triggered by systemic infection, malignancy, monogenic or rheumatic disease, similar patterns of hyper-inflammation have been seen in patients undergoing cardiopulmonary bypass (CPB) and in patients treated with extracorporeal membrane oxygenation (ECMO). Typical treatments used for the prevention and treatment of CPB/ECMO-induced hyper-inflammation have not been shown to be substantially effective. Two patients suffering from ECMO-related CSS were identified by their severe hyper-inflammatory profile and life-threatening sequelae of vasodilatory shock and respiratory failure. Anakinra, an interleukin-1 receptor antagonist, was employed as specific cytokine-directed therapy for the treatment of CSS in these two patients to good effect, with significant improvement in hyper-inflammation and cardiorespiratory status. The use of cytokine-directed therapies in CPB/ECMO-related CSS has great potential to improve the treatment and outcomes of this serious condition.
Feasibility of Endotracheal Extubation Evaluation Form in Predicting Successful Extubation in Neonatal Intensive Care Units: A Retrospective Study
Authors: Liu Yung-Cheng , Yeh Ching-Yi , Yang Shu-Ting , Chung Wei-Chan , Hsu Tuan-Jung , Sheu Chau-Chyun , Chen Hsiu-Lin
Published: June 2023

Given the limited availability of evidence-based methods for assessing the timing of extubation in intubated preterm infants, we aimed to standardize the extubation protocol in this single-center, retrospective study. To accomplish this, we established an extubation evaluation form to assess the suitability of extubation in preterm infants. The form comprises six indicators: improved clinical condition, spontaneous breath rate ≥ 30 breaths per minute, peak inspiratory pressure (PIP) ≤ 15 cmH2O, fraction of inspired oxygen (FiO2) ≤ 30%, blood pH ≥ 7.2, and mixed venous carbon dioxide tension (PvCO2) < 70 mmHg. Each positive answer is given one point, indicating a maximum of six points. We enrolled 41 intubated preterm infants (gestational age < 32 weeks, birth weight < 1500 g) who were receiving mechanical ventilation support for over 24 h. Among them, 35 were successfully extubated, and 6 were not. After completing the extubation evaluation form and adjusting for birth weight and postextubation device, we observed that the total score of the form was significantly associated with successful extubation; the higher the score, the greater the chance of successful extubation. Thus, we infer that the extubation evaluation form may provide a more objective standard for extubation assessment in preterm infants.
A Novel Self-Assessment Method for Training Access Cavity on 3D Printed Endodontic Models
Authors: Meglioli Matteo , Mergoni Giovanni , Artioli Francesco , Ghezzi Benedetta , Manfredi Maddalena , Macaluso Guido Maria , Lumetti Simone
Published: June 2023

Background: New technologies can facilitate the transition from pre-clinical to clinical settings. We investigate students’ satisfaction with a novel learning method adopted in access cavity exercises. Methods: Students performed their access cavity on inexpensive, in-house 3D printed teeth. Their performances were evaluated by scanning the prepared teeth with an intraoral scanner and visualized using a mesh processing software. Then, the same software was used to align the tooth prepared by the student and the teacher’s one for self-assessment purposes. Students were asked to answer a questionnaire about their experiences with this new learning method. Results: From the teacher’s perspective, this novel learning approach was easy, straightforward and affordable. Overall, student feedback was positive: 73% found that access cavity assessment by scanning was more useful compared to a visual inspection under magnification and 57% reported that they had a better understanding of errors and mishaps. On the other hand, students pointed out that the material used to print teeth was too soft. Conclusion: The use of in-house 3D printed teeth in pre-clinical training is a simple way to overcome some of the drawbacks associated with extracted teeth, such as limited availability, variability, cross-infection control, and ethical constraints. The use of intraoral scanners and mesh processing software could improve student self-assessment.
Decentralized Learning and Model Averaging Based Automatic Modulation Classification in Drone Communication Systems
Authors: Ma Min , Xu Yunhe , Wang Zhi , Fu Xue , Gui Guan
Published: June 2023

Automatic modulation classification (AMC) is a promising technology to identify the modulation mode of the received signal in drone communication systems. Recently, benefiting from the outstanding classification performance of deep learning (DL), various deep neural networks (DNNs) have been introduced into AMC methods. Most current AMC methods are based on a local framework (LocalAMC) where there is only one device, or a centralized framework (CentAMC) where multiple local devices (LDs) upload their data to only one central server (CS). LocalAMC may not achieve ideal results due to insufficient data and finite computational power. CentAMC carries a significant risk of privacy leakage and the final data for training model in CS are quite massive. In this paper, we propose a practical and light AMC method based on decentralized learning with residual network (ResNet) in drone communication systems. Simulation results show that the ResNet-based decentralized AMC (DecentAMC) method achieves similar classification performance to CentAMC while improving training efficiency and protecting data privacy.
A New Correlation Measure for Belief Functions and Their Application in Data Fusion
Authors: Zhang Zhuo , Wang Hongfei , Zhang Jianting , Jiang Wen
Published: June 2023

Measuring the correlation between belief functions is an important issue in Dempster–Shafer theory. From the perspective of uncertainty, analyzing the correlation may provide a more comprehensive reference for uncertain information processing. However, existing studies about correlation have not combined it with uncertainty. In order to address the problem, this paper proposes a new correlation measure based on belief entropy and relative entropy, named a belief correlation measure. This measure takes into account the influence of information uncertainty on their relevance, which can provide a more comprehensive measure for quantifying the correlation between belief functions. Meanwhile, the belief correlation measure has the mathematical properties of probabilistic consistency, non-negativity, non-degeneracy, boundedness, orthogonality, and symmetry. Furthermore, based on the belief correlation measure, an information fusion method is proposed. It introduces the objective weight and subjective weight to assess the credibility and usability of belief functions, thus providing a more comprehensive measurement for each piece of evidence. Numerical examples and application cases in multi-source data fusion demonstrate that the proposed method is effective.
Burnout of Greek Teachers: Measurement Invariance and Differences across Individual Characteristics
Authors: Gkontelos Angelos , Vaiopoulou Julie , Stamovlasis Dimitrios
Published: June 2023

Burnout (BT) is a vital determinant of work effectiveness and a well-studied psychological construct. The dominant theoretical perspectives have defined BT via the proposed dimensional structures and have provided the corresponding instruments for measuring them. The present endeavor adopts the Oldenburg Burnout Inventory (OLBI), as its purpose is to examine the psychometric properties of a short version for the Greek teachers and to find differences across their individual characteristics. The Greek short version of OLBI comprises two dimensions: Disengagement (four items) and Exhaustion (five items), with reliability measures utilizing Cronbach’s alpha and McDonald’s omega: Exhaustion (α = 0.810/ω = 0.823) and Disengagement (α = 0.742/ω = 0.756). Confirmatory factor analysis showed an adequate fit of the measurement model: χ2 = 320.291, df = 26, p < 0.001; CFI = 0.970; TLI = 0.958; RMSEA = 0.068; 90% CI of RMSEA = [0.062; 0.075]; SRMR = 0.067; NFI = 0.967; GFI = 0.986]. The proposed model is extracted after two studies (N1 = 134, N2 = 2437). The novel aspect of this endeavor is the measurement invariance explored across selected demographic variables. The findings supporting the measurement invariance make an essential contribution to the field, and the implications for educational research are provided along with a concise presentation of theoretical issues.
An Integrated Transformer with Collaborative Tokens Mining for Fine-Grained Recognition
Authors: Yang Weiwei , Yin Jian
Published: June 2023

Fine-grained recognition mainly classifies subclass images into hundreds of subcategorical labels by locating the discriminative regions (e.g., Cape May warbler or Magnolia warbler bird). Due to the high complexity and non-differentiation of region locations through the traditional backbone architecture, most existing approaches utilize multi-level reinforcement learning to distinguish the similar appearance among sub-categories. These methods explore incomplete information through only the intra-class informative regions in one image or the inter-class and intra-class relationship in pairwise images, leading to the tendency for overlapped region locations. Since the inter-class correlations and new backbone with complete contextual semantic information play important roles in distinguishing fine-grained classes, we propose a novel transformer with the collaborative token mining (TCTM) scheme by fully exploiting the relationships between inter-class and intra-class regions. The proposed TCTM scheme with a new transformer backbone consists of two modules that collaboratively explore the spatially aware tokens: the Pyramid Tokens Multiplication (PTM) module which exploits the integrated multi-stage inter-class and intra-class correlations from new transformer architecture and the Tokens Proposals Generation (TPG) module which captures two groups of top-four discriminative tokens. The two PTMs extract contrastive tokens for each image and learn to rank these tokens, assuming that those from the same class and the same module should have smaller distances. The TPGs further sort and update the candidate tokens from the extracted attention tokens by ranking their probabilities with ground truth subcategorical labels. Through the collaboration between the PTM and TPG, our TCTM scheme can take the integrated correlations into account and mine the discriminative tokens for final fine-grained classification. Extensive experiments on four popular benchmarks show that our proposed TCTM outperforms the state-of-the-art methods by a large margin.
Enhancing Low-Pass Filtering Detection on Small Digital Images Using Hybrid Deep Learning
Authors: Agarwal Saurabh , Jung Ki-Hyun
Published: June 2023

Detecting image manipulation is essential for investigating the processing history of digital images. In this paper, a novel scheme is proposed to detect the use of low-pass filters in image processing. A new convolutional neural network with a reasonable size was designed to identify three types of low-pass filters. The learning experiences of the three solvers were combined to enhance the detection ability of the proposed approach. Global pooling layers were employed to protect the information loss between the convolutional layers, and a new global variance pooling layer was introduced to improve detection accuracy. The extracted features from the convolutional neural network were mapped to the frequency domain to enrich the feature set. A leaky Rectified Linear Unit (ReLU) layer was discovered to perform better than the traditional ReLU layer. A tri-layered neural network classifier was employed to classify low-pass filters with various parameters into two, four, and ten classes. As detecting low-pass filtering is relatively easy on large-dimension images, the experimental environment was restricted to small images of 30 × 30 and 60 × 60 pixels. The proposed scheme achieved 80.12% and 90.65% detection accuracy on ten categories of images compressed with JPEG and a quality factor 75 on 30 × 30 and 60 × 60 images, respectively.
Evaluation and Comparison of Lattice-Based Cryptosystems for a Secure Quantum Computing Era
Authors: Sabani Maria E. , Savvas Ilias K. , Poulakis Dimitrios , Garani Georgia , Makris Georgios C.
Published: June 2023

The rapid development of quantum computing devices promises powerful machines with the potential to confront a variety of problems that conventional computers cannot. Therefore, quantum computers generate new threats at unprecedented speed and scale and specifically pose an enormous threat to encryption. Lattice-based cryptography is regarded as the rival to a quantum computer attack and the future of post-quantum cryptography. So, cryptographic protocols based on lattices have a variety of benefits, such as security, efficiency, lower energy consumption, and speed. In this work, we study the most well-known lattice-based cryptosystems while a systematic evaluation and comparison is also presented.
µFuncCache: A User-Side Lightweight Cache System for Public FaaS Platforms
Authors: Li Bao , Li Zhe , Luo Jun , Tan Yusong , Lu Pingjing
Published: June 2023

Building cloud-native applications based on public “Function as a Service” (FaaS) platforms has become an attractive way to improve business roll-out speed and elasticity, as well as reduce cloud usage costs. Applications based on FaaS are usually designed with multiple different cloud functions based on their functionality, and there will be call relationships between cloud functions. At the same time, each cloud function may depend on other services provided by cloud providers, such as object storage services, database services, and file storage services. When there is a call relationship between cloud functions, or between cloud functions and other services, a certain delay will occur, and the delay will increase with the length of the call chain, thereby affecting the quality of application services and user experience. Therefore, we introduce μFuncCache, a user-side lightweight caching mechanism to speed up data access for public FaaS services, fully utilizing the container delay destruction mechanism and over-booked memory commonly found in public FaaS platforms, to reduce function call latency without the need to perceive and modify the internal architecture of public clouds. Experiments in different application scenarios have shown that μFuncCache can effectively improve the performance of FaaS applications by consuming only a small amount of additional resources, while achieving a maximum reduction of 97% in latency.
An Autonomous Humanoid Robot Designed to Assist a Human with a Gesture Recognition System
Authors: Lindner Tymoteusz , Wyrwał Daniel , Milecki Andrzej
Published: June 2023

This paper presents the design of an autonomous humanoid robot designed to optimize and enrich customer service in showrooms, e.g., electronic equipment, mobile network operators, and generally in stores with various articles. The proposed humanoid robot design is distinguished by two key components: a sensor-equipped mobile platform with drives and a body featuring a head outfitted with a touch tablet and an RGBD camera. The control system enables autonomous navigation in both known and uncharted environments, with a special focus on diverse, crowded, and cluttered spaces. To enhance its adaptability, this robot is not only fitted with LIDAR sensors but also cliff and ultrasonic sensors. While the interactive ability with humans is an expected functionality, this paper brings forth certain distinct innovations in humanoid robot design for customer service. One of these unique aspects includes the robot’s ability to physically alter its configuration, such as rotating its head and adjusting the height of its torso to maintain line-of-sight with the customer. This capability signifies a novel degree of spatial responsiveness that exceeds static interaction. Moreover, the proposed robot is equipped with a user-friendly gesture recognition system, uniquely designed to detect and recognize simple human hand gestures. This attribute paves the way for understanding simple commands such as requests for assistance. Upon recognizing a request, the robot tailors its services by following the person around the showroom, effectively assisting and answering customer queries or displaying requisite information on its screen. This active assistance model, specifically tailored for human interaction, showcases the robot’s unique capability to respond proactively and dynamically to human inputs.
Real-Time Control of Gas Supply System for a PEMFC Cold-Start Based on the MADDPG Algorithm
Authors: Pan Lei , Zhang Tong , Gao Yuan
Published: June 2023

During the cold-start process of a PEMFC, the supply of air and hydrogen in the gas supply system has a great influence on the cold-start performance. The cold-start of a PEMFC is a complex nonlinear coupling process, and the traditional control strategy is not sensitive to the real-time characteristics of the system. Inspired by the strong perception and decision-making abilities of deep reinforcement learning, this paper proposes a cold-start control strategy for a gas supply system based on the MADDPG algorithm, and designs an air supply controller and a hydrogen supply controller based on this algorithm. The proposed strategy can optimize the control parameters of the gas supply system in real time according to the temperature rise rate of the stack during the cold-start process, the fluctuation of the OER, and the voltage output characteristics. After the strategy is trained offline according to the designed reward function, the detailed in-loop simulation experiment results are given and compared with the traditional control strategy for the gas supply system. From the results, it can be seen that the proposed MADDPG control strategy has a more effective coordination control effect.
Sustainability Aspects of Drone-Assisted Last-Mile Delivery Systems—A Discrete Event Simulation Approach
Authors: Balassa Boglárka Eisinger , Koteczki Réka , Lukács Bence , Buics László
Published: June 2023

The goal of this article is to examine the advantages and disadvantages of the application of drones in last-mile delivery systems from a sustainability point of view regarding CO2 emissions and energy consumption. As commercial drones are developing rapidly, the application of such tools in the field of last-mile delivery and transportation can offer many opportunities to increase service flexibility, reduce delivery time and decrease CO2 emissions and energy consumption. In this article, a discrete event simulation is applied to examine how the assistance of drones in parcel delivery services can influence the sustainability aspects of such services regarding CO2 emissions and energy consumption in an urban environment. Based on factory parameters, a vehicle-based delivery scenario is compared to a drone-assisted scenario under ideal conditions. According to the results, within the simulation parameters with the assistance of drones, a decrease in CO2 emissions and energy consumption is possible in last-mile delivery services, but more environmental, technological and financial limitations should also be addressed and incorporated to determine whether such a development is worthwhile from a last-mile delivery company’s point of view.
Three Wind Farm Developments, Three Different Planning Difficulties: Cases from Denmark
Authors: Borch Kristian , Kirkegaard Julia Kirch , Nyborg Sophie
Published: June 2023

The aim of this paper is to provide a new perspective on the conditions for the multiple dimensions of concerns and to understand why some wind power projects run smoothly, while others lead to unexpected outcomes due to local resistance. The paper considers three Danish wind farm developments with different planning difficulties, from “smooth” to intensified resistance and conflicts between local communities and the planning authority. To better understand the different planning pathways, we use a research framework where social acceptance is viewed from a conflict management theory perspective, with a focus on the uniqueness and different dimensions of conflicts. The paper discusses how the framing of the planning system considers specific types of tangible concerns, while more intangible concerns are neglected, and how this leads to escalating conflicts. The paper is concluded with several policy recommendations on how to avoid conflicts and how authorities and politicians should reflect on their own agency in provoking conflicts, which can be avoided by proactively involving affected communities at early stages.
Review of Coupling Methods of Compressed Air Energy Storage Systems and Renewable Energy Resources
Authors: Guo Huan , Kang Haoyuan , Xu Yujie , Zhao Mingzhi , Zhu Yilin , Zhang Hualiang , Chen Haisheng
Published: June 2023

With the strong advancement of the global carbon reduction strategy and the rapid development of renewable energy, compressed air energy storage (CAES) technology has received more and more attention for its key role in large-scale renewable energy access. This paper summarizes the coupling systems of CAES and wind, solar, and biomass energies from the perspective of system topology, and points out the advantages and limitations of each system. It is shown that the coupling of wind energy and CAES is mainly combined in series and in parallel, and sometimes part of the wind power can be converted into thermal energy when coupled to CAES. The coupling between solar heat and CAES is an important form of coupling between solar energy and CAES. Solar-heat-coupled CAES mainly uses solar energy to heat expander inlet air. The coupling forms of solar energy and CAES are based on various CAES forms, various heat heating sequences, reheating, bottom cycle, and other factors. The combination of biomass and CAES is generally based on biomass gasification power generation technology. In the future, a wind–solar–CAES multiple coupling system is expected to become a promising large-scale form for the utilization of renewable energy, and this integrated system has great potential as a system configuration, but has some technical challenges.