bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Carbon Emission Characteristics and Mitigation Pathways in the Vehicle Fuel Cycle: A Case Study of Guangdong Province
Authors: Liu Jianjun , Luo Yinping , Zhu Qianru , Li Yixi , Luo Yutao
Published: December 2023

This study presents a comprehensive analysis of vehicle ownership, energy consumption, and carbon emissions in Guangdong Province, China, from 2020 to 2035 under different scenarios. Key findings highlight the province’s pursuit of carbon peak goals and provide valuable insights into strategies to achieve them. Vehicle ownership in Guangdong is projected to exceed 48 million by 2035, which represents a doubling from 2020. Under both scenarios, internal combustion engine vehicle ownership will peak around 2030 and then gradually decline, while under the enhanced scenario, electric vehicle ownership will exceed 40% by 2035. Enhanced vehicle energy efficiency and reduced annual mileage will lead to a 17% reduction in gasoline and diesel consumption by 2035 in both scenarios. At the same time, there will be a substantial five- to six-fold increase in electricity consumption for vehicles compared to 2020. Both scenarios peak in carbon emissions before 2030, with the enhanced scenario achieving this peak a year earlier. The enhanced scenario outperforms the baseline, reducing carbon emissions by about 21.2% from the peak and 8% relative to 2020. Pure electric vehicles exhibit a significant advantage in reducing carbon emissions per vehicle compared to their internal combustion engine counterparts. Encouraging new energy vehicles, especially pure electric ones, accelerates the carbon emissions peak and lowers overall peak emissions. Accelerating the adoption of electric vehicles, reducing per-vehicle fuel consumption and annual average mileage, and optimizing transportation modes are crucial for carbon peaking from the vehicle fuel cycle. Policy recommendations focus on promoting new energy vehicles, optimizing transportation, and advancing research and technology.
A Deep Learning Method of Human Identification from Radar Signal for Daily Sleep Health Monitoring
Authors: Chen Ken , Duan Yulong , Huang Yi , Hu Wei , Xie Yaoqin
Published: December 2023

Radar signal has been shown as a promising source for human identification. In daily home sleep-monitoring scenarios, large-scale motion features may not always be practical, and the heart motion or respiration data may not be as ideal as they are in a controlled laboratory setting. Human identification from radar sequences is still a challenging task. Furthermore, there is a need to address the open-set recognition problem for radar sequences, which has not been sufficiently studied. In this paper, we propose a deep learning-based approach for human identification using radar sequences captured during sleep in a daily home-monitoring setup. To enhance robustness, we preprocess the sequences to mitigate environmental interference before employing a deep convolution neural network for human identification. We introduce a Principal Component Space feature representation to detect unknown sequences. Our method is rigorously evaluated using both a public data set and a set of experimentally acquired radar sequences. We report a labeling accuracy of 98.2% and 96.8% on average for the two data sets, respectively, which outperforms the state-of-the-art techniques. Our method excels at accurately distinguishing unknown sequences from labeled ones, with nearly 100% detection of unknown samples and minimal misclassification of labeled samples as unknown.
Insight into Steroid-Induced ONFH: The Molecular Mechanism and Function of Epigenetic Modification in Mesenchymal Stem Cells
Authors: Huang Chengxiong , Qing Liming , Xiao Yu , Tang Juyu , Wu Panfeng
Published: December 2023

Osteonecrosis of the femoral head (ONFH) is a common refractory orthopedic disease, which is one of the common causes of hip pain and dysfunction. ONFH has a very high disability rate, which is associated with a heavy burden to patients, families, and society. The pathogenesis of ONFH is not completely clear. At present, it is believed that it mainly includes coagulation dysfunction, abnormal lipid metabolism, an imbalance of osteogenic/adipogenic differentiation, and poor vascularization repair. The prevention and treatment of ONFH has always been a great challenge for clinical orthopedic surgeons. However, recent studies have emphasized that the use of mesenchymal stem cells (MSCs) to treat steroid-induced ONFH (SONFH) is a promising therapy. This review focuses on the role and molecular mechanism of epigenetic regulation in the progress of MSCs in the treatment of SONFH, and discusses the significance of the latest research in the treatment of SONFH from the perspective of epigenetics.
Differential Expression of Insulin Growth Factor 1 (IGF-1) Isoforms in Different Types of Endometriosis: Preliminary Results of a Single-Center Study
Authors: Blontzos Nikolaos , Mavrogianni Despoina , Ntzeros Konstantinos , Kathopoulis Nikolaos , Moustogiannis Athanasios , Philippou Anastassios , Koutsilieris Michael , Protopapas Athanasios
Published: December 2023

Endometriosis is a benign, estrogen-dependent gynecological condition with an uncertain exact pathogenetic mechanism. The aim of this study was to evaluate the potential differential expression of Insulin Growth Factor 1 (IGF-1) isoforms in deeply infiltrating endometriotic (DIE) lesions, in ovarian endometriomas, and in the eutopic endometrium of the same endometriosis patients and to compare their expression with that in the eutopic endometrium of women without endometriosis. A total of 39 patients were included: 28 with endometriosis, of whom 15 had endometriomas only, 7 had DIE nodules only, and 6 had both DIE and endometriomas, and 11 without endometriosis served as controls. We noticed a similar pattern of expression between IGF-1Ea and IGF-1Ec, which differed from that of the IGF-1Eb isoform, possibly implying differential biological actions of different isoforms in DIE subtypes. We observed a tendency of lower expression of IGF-1Ea and IGF-1Ec in endometriomas without DIE compared to endometriomas with concurrent DIE or in DIE nodules. In conclusion, differential expression of IGF-1 isoforms may indicate that DIE with its associated ovarian lesions and simple ovarian endometriosis should be considered as two forms of the disease developing under different molecular pathways.
Mesenchymal Stem Cell-Based Therapies in the Post-Acute Neurological COVID Syndrome: Current Landscape and Opportunities
Authors: León-Moreno Lilia Carolina , Reza-Zaldívar Edwin Estefan , Hernández-Sapiéns Mercedes Azucena , Villafaña-Estarrón Erika , García-Martin Marina , Ojeda-Hernández Doddy Denise , Matias-Guiu Jordi A. , Gomez-Pinedo Ulises , Matias-Guiu Jorge , Canales-Aguirre Alejandro Arturo
Published: December 2023

One of the main concerns related to SARS-CoV-2 infection is the symptoms that could be developed by survivors, known as long COVID, a syndrome characterized by persistent symptoms beyond the acute phase of the infection. This syndrome has emerged as a complex and debilitating condition with a diverse range of manifestations affecting multiple organ systems. It is increasingly recognized for affecting the Central Nervous System, in which one of the most prevalent manifestations is cognitive impairment. The search for effective therapeutic interventions has led to growing interest in Mesenchymal Stem Cell (MSC)-based therapies due to their immunomodulatory, anti-inflammatory, and tissue regenerative properties. This review provides a comprehensive analysis of the current understanding and potential applications of MSC-based interventions in the context of post-acute neurological COVID-19 syndrome, exploring the underlying mechanisms by which MSCs exert their effects on neuroinflammation, neuroprotection, and neural tissue repair. Moreover, we discuss the challenges and considerations specific to employing MSC-based therapies, including optimal delivery methods, and functional treatment enhancements.
Genes Associated with Altered Brain Structure and Function in Obstructive Sleep Apnea
Authors: Huang Yijie , Shen Chong , Zhao Wei , Shang Youlan , Wang Yisong , Zhang Hui-Ting , Ouyang Ruoyun , Liu Jun
Published: December 2023

Obstructive sleep apnea (OSA) has been widely reported to cause abnormalities in brain structure and function, but the genetic mechanisms behind these changes remain largely unexplored. Our research aims to investigate the relationship between sleep characteristics, cognitive impairments, genetic factors, and brain structure and function in OSA. Using structural and resting-state functional magnetic resonance imaging data, we compared cortical morphology and spontaneous brain activity between 28 patients with moderate-to-severe OSA and 34 healthy controls (HCs) utilizing voxel-based morphology (VBM) and the amplitude of low-frequency fluctuations (ALFF) analyses. In conjunction with the Allen Human Brain Atlas, we used transcriptome-neuroimaging spatial correlation analyses to investigate gene expression patterns associated with changes in gray matter volume (GMV) and ALFF in OSA. Compared to the HCs, the OSA group exhibited increased ALFF values in the left hippocampus (t = 5.294), amygdala (t = 4.176), caudate (t = 4.659), cerebellum (t = 5.896), and decreased ALFF values in the left precuneus (t = −4.776). VBM analysis revealed increased GMV in the right inferior parietal lobe (t = 5.158) in OSA. Additionally, functional enrichment analysis revealed that genes associated with both ALFF and GMV cross-sampling were enriched in gated channel activity and synaptic transmission, glutamatergic synapse, and neuron.
Impact of Shunt Placement on CSF Dynamics
Authors: Capel Cyrille , Owashi Kimi , Metanbou Serge , Peltier Johann , Balédent Olivier
Published: December 2023

Background: CSF dynamics are disturbed in chronic hydrocephalus (NPH). We hypothesise that these alterations reflect a disturbance of intracranial compliance. The aim of our study is to investigate the variations in intracranial hydrodynamics in NPH after ventricular shunt surgery. Patients and method: We included 14 patients with definite NPH. All patients improved after ventriculoperitoneal shunting. The patients underwent an analysis of intracranial haemodynamics by phase-contrast MRI (pcMRI) preoperatively, at 6 months postoperatively, and at 1 year postoperatively. We analysed the dynamics of intraventricular CSF at the level of the aqueduct of Sylvius (SVAQU) and CSF at the level of the high cervical subarachnoid spaces (SVCERV). We calculated the ratio between SVAQU and SVCERV, called CSFRATIO, which reflects the participation of intraventricular pulsatility in overall intracranial CSF pulsatility. Results: SVAQU significantly (p = 0.003) decreased from 240 ± 114 μL/cc to 214 ± 157 μL/cc 6 months after shunt placement. Six months after shunt placement, SVCERV significantly (p = 0.007) decreased from 627 ± 229 μL/cc to 557 ± 234 μL/cc. Twelve months after shunt placement, SVCERV continued to significantly (p = 0.001) decrease to 496 ± 234 μL/cc. CSFRATIO was not changed by surgery. Conclusions: CSF dynamics are altered by shunt placement and might be a useful marker of the shunt’s effectiveness—especially if pressure values start to rise again. The detection of changes in CSF dynamics would require a reference postoperative pcMRI measurement for each patient.
Enhanced Empathic Pain by Facial Feedback
Authors: Lee Seoyoung , Yoo Yeonjoo , Moon Heeyoung , Lee In-Seon , Chae Younbyoung
Published: December 2023

The facial feedback hypothesis states that feedback from cutaneous and muscular afferents affects our emotion. Based on the facial feedback hypothesis, the purpose of this study was to determine whether enhancing negative emotion by activating a facial muscle (corrugator supercilii) increases the intensity of cognitive and emotional components of empathic pain. We also assessed whether the muscle contraction changed the pupil size, which would indicate a higher level of arousal. Forty-eight individuals completed 40 muscular contraction and relaxation trials while looking at images of five male and five female patients with neutral and painful facial expressions, respectively. Participants were asked to rate (1) how much pain the patient was in, and (2) how unpleasant their own feelings were. We also examined their facial muscle activities and changes in pupil size. No significant differences in pain or unpleasantness ratings were detected for the neutral face between the two conditions; however, the pain and unpleasantness ratings for the painful face were considerably higher in the contraction than relaxation condition. The pupils were considerably larger in the contraction than relaxation condition for both the painful and neutral faces. Our findings indicate that, by strengthening the corrugator supercilii, facial feedback can affect both the cognitive evaluative and affective sharing aspects of empathic pain.
Digital Leadership’s Influence on Individual Creativity and Employee Performance: A View through the Generational Lens
Authors: Öngel Volkan , Günsel Ayşe , Gençer Çelik Gülşah , Altındağ Erkut , Tatlı Hasan Sadık
Published: December 2023

Today’s digitalized business atmosphere places significant emphasis on digital leadership, as digital transformation can only be successful for leaders who are capable of overseeing the entire digitalization process. In this study, we examine the employee-level outputs of digital leadership in terms of individual creativity and employee performance. Based on the data of 348 employees and by using PLS-SEM, we find that (i) digital leadership is a significant antecedent of individual creativity, and (ii) individual creativity fully mediates the relationship between digital leadership and employee performance. When digital leadership abilities are a matter of concern, it becomes necessary to mention the importance of generational differences between those leaders, as OB studies also underline the generational differences toward new technologies. Hence, we also conducted a multigroup analysis (MGA) to determine if those interrelationships among digital leadership, individual creativity, and employee performance differ due to the generations of the managers. Surprisingly, the MGA results reveal minor differences. The findings of this study highlight the importance of embracing digital leadership in fostering a creative and high-performing work environment and provide insights for organizations aiming to harness the unique strengths and talents of their multigenerational workforce. Digital leaders who foster a culture of innovation, adaptability, and open communication can inspire employees to think creatively and come up with novel ideas. By leveraging digital tools and providing a supportive environment, digital leaders can also enhance employee creativity and performance.
Experimental Study on Crack Width of HRB600 Grade High-Strength Steel Bar Reinforced Concrete Beams
Authors: Hu Xiaoyi , Zeng Liang , Wu Hao , Djerrad Abderrahim , Yang Chenhan , Zhang Dekai
Published: December 2023

High-strength reinforcement is an important direction in the development of civil engineering. In order to fill the gap that the current concrete structure code GB50010 has no standard regulations applicable to HRB600-grade high-strength reinforcement, this paper conducted an experimental investigation on the crack width of eight concrete beams reinforced with HRB600-grade high-strength reinforcement. The study examined various parameters to understand the crack development process, crack spacing, and factors influencing crack width in the pure bending section. The results revealed that the damage mode and crack development process of high-strength reinforced concrete beams were similar to those observed in ordinary reinforced concrete bending members. The crack spacing in the pure bending section was independent of the concrete strength, and the average crack width in the pure bending section exhibited a proportional relationship with the reinforcement strain. Moreover, both were mathematically related to the ratio of reinforcement diameter and ratio. A calculation formula for the maximum crack width suitable for HRB600-grade reinforced concrete beams was developed and fit. The HRB600-grade high-strength reinforcement had an obvious yield stage and good ductility, and the test study provides a powerful reference for promoting the application of high-strength reinforcement in concrete structures.
Development of an Algorithm for Crane Trajectory Distance Calculation for Erection of Precast Concrete Members
Authors: Kim Sunkuk , Oh Jinhyuk , Lim Jeeyoung
Published: December 2023

Reducing the construction time for large logistics buildings can result in reduced construction management costs and economic gains from early operation. A large logistics building with a heavy load and long spans was constructed as a precast concrete (PC) structure, which required the use of a sizable crane to lift heavy PC members. A basic analytical approach was employed to resolve potential errors in the planning of PC member erection and to build a systematic erection plan. Calculation techniques for the trajectory distance that use the crane location were applied to select an erection plan that minimizes crane work. A crane trajectory distance calculation algorithm for sustainable PC member erection in large logistics buildings with heavy loads and long spans has been developed. The developed model aids in creating simulation and optimization models to ensure the minimal usage of cranes in the future and in determining the cost, construction time, CO2 emissions, and energy use for each erection plan.
Shear Bearing Capacity of Steel-Fiber-Reinforced Concrete Shear Wall under Low-Cycle Repeated Loading Based on the Softened Strut-and-Tie Model
Authors: You Peibo , Zhang Jie , Wang Binyu , Wang Yi , Yang Qingjie , Li Li
Published: December 2023

In this paper, the loading mechanism of steel-fiber-reinforced concrete (SFRC) shear wall (SW) under low-cycle repeated loading is analyzed, and the softened strut-and-tie model (SSTM) of SFRC SW composed of horizontal and vertical resistant members and diagonal strut is proposed, in which the contributions of distributed web reinforcement, concrete, and steel fiber (SF) to the shear bearing capacity (SBC) of SFRC SW is identified. Furthermore, a new algorithm to obtain the SBC of SFRC SW is established, and then it is validated by using the test results of steel-fiber-reinforced high-strength concrete (SFHSC) SW and SFRC SW under low-cycle repeated loading. The results show that the calculated values are in good agreement with the experimental values for the 11 SFRC SWs, and the average strength ratio between calculated and experimental values (Vjh,t/Vjh,c) is 0.958. Therefore, the proposed calculation method is scientific and accurate for analyzing and predicting the SBC of SFRC SW. In addition, the proposed calculation method can scientifically and accurately analyze and predict the SBC of SFRC SW.
Evaluating the Effects of RA on the Rheological Properties and Aging Susceptibility of RAM Asphalt
Authors: Yang Qifeng , Liu Zhen , Wang Rui , Sun Lijun , Zhang Runhua
Published: December 2023

Recycling agents (RAs) can mitigate the adverse effects of reclaimed asphalt pavement (RAP) on recycled asphalt, which can result in more RAP being added. To explore the effects of four RAs on recycled asphalt, this study used asphalt rheological performance experiments, including the bending beam rheometer (BBR) test, the dynamic shear rheological (DSR) test, and the indirect tensile asphalt cracking test (IDEAL-CT), to study the performance grade (PG), cracking resistance, and cracking susceptibility of recycled asphalt. In addition, an aging model for asphalt was used, and short-term and long-term aging sensitivities were evaluated according to this model. Results showed that US Soybean significantly enhanced the high-temperature and low-temperature performance grade (PGLT) and cracking resistance and reduced cracking sensitivity of the recycled asphalt. In addition, the short-term aging sensitivity was the lowest. It showed the best regeneration effect. However, the recycled asphalt with US Soybean showed the highest long-term aging sensitivity, suggesting that longer aging time results in poorer performance. Ingevity’s PG, cracking resistance, and cracking sensitivity are slightly lower than that of US Soybean, and Ingevity demonstrated the second lowest short-term aging sensitivity. However, its prolonged aging sensitivity was much lower than that of US Soybean. Asphalt and Wax Innovations and Georgia Pacific agents slightly improved recycled asphalt properties. The long-term aging sensitivity of recycled asphalt with four Ras was higher than that of recycled asphalt without Ras. These results indicated that the recycled asphalt’s performance with Ras worsened as aging time increased compared to the original recycled asphalt.
Deciphering Urogenital Cancers through Proteomic Biomarkers: A Systematic Review and Meta-Analysis
Authors: Khan Aafaque Ahmad , Al-Mahrouqi Nahad , Al-Yahyaee Aida , Al-Sayegh Hasan , Al-Harthy Munjid , Al-Zadjali Shoaib
Published: December 2023

Urogenital cancers, which include prostate, bladder, and kidney malignancies, exert a substantial impact on global cancer-related morbidity and mortality. Proteomic biomarkers, emerging as valuable tools, aim to enhance early detection, prognostic accuracy, and the development of personalized therapeutic strategies. This study undertook a comprehensive systematic review and meta-analysis of the existing literature investigating the role and potential of proteomic biomarkers in plasma, tissue, and urine samples in urogenital cancers. Our extensive search across several databases identified 1879 differentially expressed proteins from 37 studies, signifying their potential as unique biomarkers for these cancers. A meta-analysis of the significantly differentially expressed proteins was executed, accentuating the findings through visually intuitive volcano plots. A functional enrichment analysis unveiled their significant involvement in diverse biological processes, including signal transduction, immune response, cell communication, and cell growth. A pathway analysis highlighted the participation of key pathways such as the nectin adhesion pathway, TRAIL signaling pathway, and integrin signaling pathways. These findings not only pave the way for future investigations into early detection and targeted therapeutic approaches but also underscore the fundamental role of proteomics in advancing our understanding of the molecular mechanisms underpinning urogenital cancer pathogenesis. Ultimately, these findings hold remarkable potential to significantly enhance patient care and improve clinical outcomes.
VDR and PDIA3 Are Essential for Activation of Calcium Signaling and Membrane Response to 1,25(OH)2D3 in Squamous Cell Carcinoma Cells
Authors: Nowak Joanna I. , Olszewska Anna M. , Wierzbicka Justyna M. , Gebert Magdalena , Bartoszewski Rafał , Żmijewski Michał A.
Published: December 2023

The genomic activity of 1,25(OH)2D3 is mediated by vitamin D receptor (VDR), whilst non-genomic is associated with protein disulfide isomerase family A member 3 (PDIA3). Interestingly, our recent studies documented that PDIA3 is also involved, directly or indirectly, in the modulation of genomic response to 1,25(OH)2D3. Moreover, PDIA3 was also shown to regulate cellular bioenergetics, possibly through the modulation of STAT signaling. Here, the role of VDR and PDIA3 proteins in membrane response to 1,25(OH)2D3 and calcium signaling was investigated in squamous cell carcinoma A431 cell line with or without the deletion of VDR and PDIA3 genes. Calcium influx was assayed by Fura-2AM or Fluo-4AM, while calcium-regulated element (NFAT) activation was measured using a dual luciferase assay. Further, the levels of proteins involved in membrane response to 1,25(OH)2D3 in A431 cell lines were analyzed via Western blot analysis. The deletion of either PDIA3 or VDR resulted in the decreased baseline levels of Ca2+ and its responsiveness to 1,25(OH)2D3; however, the effect was more pronounced in A431∆PDIA3. Furthermore, the knockout of either of these genes disrupted 1,25(OH)2D3-elicited membrane signaling. The data presented here indicated that the VDR is essential for the activation of calcium/calmodulin-dependent protein kinase II alpha (CAMK2A), while PDIA3 is required for 1,25(OH)2D3-induced calcium mobilization in A431 cells. Taken together, those results suggest that both VDR and PDIA3 are essential for non-genomic response to this powerful secosteroid.
Brain Region Differences in α1- and α5-Subunit-Containing GABAA Receptor Proteomes Revealed with Affinity Purification and Blue Native PAGE Proteomics
Authors: Chen Miao , Koopmans Frank , Gonzalez-Lozano Miguel A. , Smit August B. , Li Ka Wan
Published: December 2023

GABAA receptors are the major inhibitory receptors in the brain. They are hetero-pentamers with a composition of predominantly two α, two β, and one γ or δ subunit. Of the six α subunit genes, the α5 subunit displays a limited spatial expression pattern and is known to mediate both phasic and tonic inhibition. In this study, using immunoaffinity-based proteomics, we identified the α5 subunit containing receptor complexes in the hippocampus and olfactory bulb. The α1–α5 interaction was identified in both brain regions, albeit with significantly different stoichiometries. In line with this, reverse IPs using anti-α1 antibodies showed the α5–α1 co-occurrence and validated the quantitative difference. In addition, we showed that the association of Neuroligin 2 with α1-containing receptors was much higher in the olfactory bulb than in the hippocampus, which was confirmed using blue native gel electrophoresis and quantitative mass spectrometry. Finally, immunocytochemical staining revealed a co-localization of α1 and α5 subunits in the post-synaptic puncta in the hippocampus.
Primer on Reproducible Research in R: Enhancing Transparency and Scientific Rigor
Authors: Siraji Mushfiqul Anwar , Rahman Munia
Published: December 2023

Achieving research reproducibility is a precarious aspect of scientific practice. However, many studies across disciplines fail to be fully reproduced due to inadequate dissemination methods. Traditional publication practices often fail to provide a comprehensive description of the research context and procedures, hindering reproducibility. To address these challenges, this article presents a tutorial on reproducible research using the R programming language. The tutorial aims to equip researchers, including those with limited coding knowledge, with the necessary skills to enhance reproducibility in their work. It covers three essential components: version control using Git, dynamic document creation using rmarkdown, and managing R package dependencies with renv. The tutorial also provides insights into sharing reproducible research and offers specific considerations for the field of sleep and chronobiology research. By following the tutorial, researchers can adopt practices that enhance the transparency, rigor, and replicability of their work, contributing to a culture of reproducible research and advancing scientific knowledge.
Investigation of High-Temperature Oxidation of Homogeneous and Gradient Ni-Cr-Al Coatings Obtained by Detonation Spraying
Authors: Rakhadilov Bauyrzhan , Sulyubayeva Laila , Maulet Meruyert , Sagdoldina Zhuldyz , Buitkenov Dastan , Issova Ainur
Published: December 2023

The high-temperature oxidation of homogeneous and gradient coatings based on Ni-Cr-Al obtained by detonation spraying is investigated. To assess the resistance to high-temperature oxidation of Ni-Cr-Al coatings, cyclic tests were carried out at a temperature of 1000 °C for 50 cycles. The assessment of high-temperature oxidizing ability was carried out by measuring the weight gain of samples after each cycle. After high-temperature oxidation tests, the morphology and chemical composition of the coating structure in the cross-section were investigated using SEM/EDS. The phase composition of the samples was studied by X-ray diffraction (XRD) phase analysis. Visual analysis of the sample surface under study after high-temperature oxidation showed that the surface of homogeneous or gradient Ni-Cr-Al coatings remained undamaged. The results of X-ray phase analysis showed the peaks of Al2O3 in Ni-Cr-Al gradient coatings are more expressed and intense compared to homogeneous coatings of Ni-Cr-Al. Gradient coatings also retain an increased chromium content compared to homogeneous Ni-Cr-Al coatings. This increased chromium content can slow down mixing or diffusion between different phases of the material at their boundary, which, in turn, contributes to increasing the resistance of the gradient coating to oxidation.
Deep Learning Model Based on You Only Look Once Algorithm for Detection and Visualization of Fracture Areas in Three-Dimensional Skeletal Images
Authors: Jeon Young-Dae , Kang Min-Jun , Kuh Sung-Uk , Cha Ha-Yeong , Kim Moo-Sub , You Ju-Yeon , Kim Hyeon-Joo , Shin Seung-Han , Chung Yang-Guk , Yoon Do-Kun
Published: December 2023

Utilizing “You only look once” (YOLO) v4 AI offers valuable support in fracture detection and diagnostic decision-making. The purpose of this study was to help doctors to detect and diagnose fractures more accurately and intuitively, with fewer errors. The data accepted into the backbone are diversified through CSPDarkNet-53. Feature maps are extracted using Spatial Pyramid Pooling and a Path Aggregation Network in the neck part. The head part aggregates and generates the final output. All bounding boxes by the YOLO v4 are mapped onto the 3D reconstructed bone images after being resized to match the same region as shown in the 2D CT images. The YOLO v4-based AI model was evaluated through precision–recall (PR) curves and the intersection over union (IoU). Our proposed system facilitated an intuitive display of the fractured area through a distinctive red mask overlaid on the 3D reconstructed bone images. The high average precision values (>0.60) were reported as 0.71 and 0.81 from the PR curves of the tibia and elbow, respectively. The IoU values were calculated as 0.6327 (tibia) and 0.6638 (elbow). When utilized by orthopedic surgeons in real clinical scenarios, this AI-powered 3D diagnosis support system could enable a quick and accurate trauma diagnosis.
Assessment of Deep Learning Models for Cutaneous Leishmania Parasite Diagnosis Using Microscopic Images
Authors: Abdelmula Ali Mansour , Mirzaei Omid , Güler Emrah , Süer Kaya
Published: December 2023

Cutaneous leishmaniasis (CL) is a common illness that causes skin lesions, principally ulcerations, on exposed regions of the body. Although neglected tropical diseases (NTDs) are typically found in tropical areas, they have recently become more common along Africa’s northern coast, particularly in Libya. The devastation of healthcare infrastructure during the 2011 war and the following conflicts, as well as governmental apathy, may be causal factors associated with this catastrophic event. The main objective of this study is to evaluate alternative diagnostic strategies for recognizing amastigotes of cutaneous leishmaniasis parasites at various stages using Convolutional Neural Networks (CNNs). The research is additionally aimed at testing different classification models employing a dataset of ultra-thin skin smear images of Leishmania parasite-infected people with cutaneous leishmaniasis. The pre-trained deep learning models including EfficientNetB0, DenseNet201, ResNet101, MobileNetv2, and Xception are used for the cutaneous leishmania parasite diagnosis task. To assess the models’ effectiveness, we employed a five-fold cross-validation approach to guarantee the consistency of the models’ outputs when applied to different portions of the full dataset. Following a thorough assessment and contrast of the various models, DenseNet-201 proved to be the most suitable choice. It attained a mean accuracy of 0.9914 along with outstanding results for sensitivity, specificity, positive predictive value, negative predictive value, F1-score, Matthew’s correlation coefficient, and Cohen’s Kappa coefficient. The DenseNet-201 model surpassed the other models based on a comprehensive evaluation of these key classification performance metrics.
A Deep Neural Network Regularization Measure: The Class-Based Decorrelation Method
Authors: Zhang Chenguang , Liu Tian , Du Xuejiao
Published: December 2023

In response to the challenge of overfitting, which may lead to a decline in network generalization performance, this paper proposes a new regularization technique, called the class-based decorrelation method (CDM). Specifically, this method views the neurons in a specific hidden layer as base learners, and aims to boost network generalization as well as model accuracy by minimizing the correlation among individual base learners while simultaneously maximizing their class-conditional correlation. Intuitively, CDM not only promotes diversity among the hidden neurons, but also enhances their cohesiveness among them when processing samples from the same class. Comparative experiments conducted on various datasets using deep models demonstrate that CDM effectively reduces overfitting and improves classification performance.
Novel Low-Loss Reverse-Conducting Insulated-Gate Bipolar Transitor with Collector-Side Injection-Enhanced Structure
Authors: Zhang Peijian , Qiu Sheng , Zhu Kunfeng , Chen Wensuo
Published: December 2023

In this paper, a new concept of low-loss Reverse-Conducting Insulated-Gate Bipolar Transistor with Collector-side Injection-Enhanced structure (RC-IGBT-CIE) is proposed and investigated using simulations. In reverse conduction (the on state of the diode mode), the CIE structure enhances the collector-side carrier concentration of the proposed RC-IGBT-CIE, which results in low reverse-conducting voltage (VF). The low reverse recovery loss and low turn-on loss using an inductive load circuit are obtained by using the modified carrier concentration profile resulted from both the CIE effect and the low-injection-efficiency p-emitter. Simulation results show that, with the same sum of turn-on loss and reverse recovery loss (Eon + Erec), when compared to conventional RC-IGBT with anti-parallel thyristor (RC-IGBT-thyristor), the RC-IGBT-CIE reduces VF by 9.2%, and meanwhile, with the same total conducting voltage (Von, sat + VF), the total switching loss (Eoff + Eon + Erec) is reduced by 20.9% but does not sacrifice short-circuit capability.
CMOS Wireless Hybrid Transceiver Powered by Integrated Photodiodes for Ultra-Low-Power IoT Applications
Authors: Nikseresht Sasan , Fernández Daniel , Cosp-Vilella Jordi , Selin-Lorenzo Irina , Madrenas Jordi
Published: December 2023

In this article, a communication platform for a self-powered integrated light energy harvester based on a wireless hybrid transceiver is proposed. It consists of an optical receiver and a reconfigurable radio frequency (RF) transmitter. The hybrid optical/RF communication approach improves load balancing, energy efficiency, security, and interference reduction. A light beam for communication in the downlink, coupled with a 1 MHz radio frequency signal for the uplink, offers a small area and ultra-low-power consumption design for Smart Dust/IoT applications. The optical receiver employs a new charge-pump-based technique for the automatic acquisition of a reference voltage, enabling compensation for comparator offset errors and variations in DC-level illumination. On the uplink side, the reconfigurable transmitter supports OOK/FSK/BPSK data modulation. Electronic components and the energy harvester, including integrated photodiodes, have been designed, fabricated, and experimentally tested in a 0.18 µm triple-well CMOS technology in a 1.5 × 1.3 mm2 chip area. Experiments show the correct system behavior for general and pseudo-random stream input data, with a minimum pulse width of 50 µs and a data transmission rate of 20 kb/s for the optical receiver and 1 MHz carrier frequency. The maximum measured power of the signal received from the transmitter is approximately −18.65 dBm when using a light-harvested power supply.
Failure Identification Method of Sound Signal of Belt Conveyor Rollers under Strong Noise Environment
Authors: Ban Yuxuan , Liu Chunyang , Yang Fang , Guo Nan , Ma Xiqiang , Sui Xin , Huang Yan
Published: December 2023

Accurately extracting faulty sound signals from belt conveyor rollers within the high-noise environment of coal mine operations presents a formidable challenge. To address this issue, this study introduces an innovative fault diagnosis method that merges the variational modal de-composition (VMD) model with the Swin Transformer deep learning network model. First, the study employed the adaptive VMD method to eliminate intense noise from the original signal of the rollers, while also assessing the reconstruction accuracy of the VMD signal across different modal components. Subsequently, we delved into the impact of the parameter structure of the Swin Transformer network model on the fault diagnosis accuracy. Finally, the accuracy of the method was validated using a sound test dataset from the rollers. The results indicated that optimizing the K-value of the VMD method effectively reduced the noise in the reconstructed signal, and the Swin Transformer excelled in extracting both local and global features. Specifically, on the conveyor roller sound dataset, it was shown that, after the VMD reconstruction of the signal so that the highest Pearson correlation coefficient corresponded to a modal component of 3 and adjusting the parameters of the Swin Transformer coding layer, the combination of the VMD+Swin-S model achieved an accuracy of 99.36%, while the VMD+Swin-T model achieved an accuracy of 98.6%. Meanwhile, the accuracy of the VMD+Swin-S model was higher than that of the VMD + CNN model combination, with 95.4% accuracy, and the VMD+ViT model, with 97.68% accuracy. In the example application experiments, compared with other models the VMD+Swin-S model achieved the highest accuracy rate at all three speeds, with 98.67%, 98.32%, and 97.65%, respectively. Overall, this approach demonstrated high accuracy and robustness, rendering it an optimal choice for diagnosing conveyor belt roller faults within environments characterized by strong noise.
Adaptive Streaming Transmission Optimization Method Based on Three-Dimensional Caching Architecture and Environment Awareness in High-Speed Rail
Authors: Guo Jia , Zhu Yexuan , Zhu Jinqi , Shen Fan , Gao Hui , Tian Ye
Published: December 2023

In high-mobility scenarios, a user’s media experience is severely constrained by the difficulty of network channel prediction, the instability of network quality, and other problems caused by the user’s fast movement, frequent base station handovers, the Doppler effect, etc. To this end, this paper proposes a video adaptive transmission architecture based on three-dimensional caching. In the temporal dimension, video data are cached to different base stations, and in the spatial dimension video data are cached to base stations, high-speed trains, and clients, thus constructing a multilevel caching architecture based on spatio-temporal attributes. Then, this paper mathematically models the media stream transmission process and summarizes the optimization problems that need to be solved. To solve the optimization problem, this paper proposes three optimization algorithms, namely, the placement algorithm based on three-dimensional caching, the video content selection algorithm for caching, and the bitrate selection algorithm. Finally, this paper builds a simulation system, which shows that the scheme proposed in this paper is more suitable for high-speed mobile networks, with better and more stable performance.
Efficient Microgrid Management with Meerkat Optimization for Energy Storage, Renewables, Hydrogen Storage, Demand Response, and EV Charging
Authors: Jokar Hossein , Niknam Taher , Dehghani Moslem , Sheybani Ehsan , Pourbehzadi Motahareh , Javidi Giti
Published: December 2023

Within microgrids (MGs), the integration of renewable energy resources (RERs), plug-in hybrid electric vehicles (PHEVs), combined heat and power (CHP) systems, demand response (DR) initiatives, and energy storage solutions poses intricate scheduling challenges. Coordinating these diverse components is pivotal for optimizing MG performance. This study presents an innovative stochastic framework to streamline energy management in MGs, covering proton exchange membrane fuel cell–CHP (PEMFC-CHP) units, RERs, PHEVs, and various storage methods. To tackle uncertainties in PHEV and RER models, we employ the robust Monte Carlo Simulation (MCS) technique. Challenges related to hydrogen storage strategies in PEMFC-CHP units are addressed through a customized mixed-integer nonlinear programming (MINLP) approach. The integration of intelligent charging protocols governing PHEV charging dynamics is emphasized. Our primary goal centers on maximizing market profits, serving as the foundation for our optimization endeavors. At the heart of our approach is the Meerkat Optimization Algorithm (MOA), unraveling optimal MG operation amidst the intermittent nature of uncertain parameters. To amplify its exploratory capabilities and expedite global optima discovery, we enhance the MOA algorithm. The revised summary commences by outlining the overall goal and core algorithm, followed by a detailed explanation of optimization points for each MG component. Rigorous validation is executed using a conventional test system across diverse planning horizons. A comprehensive comparative analysis spanning varied scenarios establishes our proposed method as a benchmark against existing alternatives.
Optimal Power Flow for Unbalanced Three-Phase Microgrids Using an Interior Point Optimizer
Authors: Siratarnsophon Piyapath , Kim Woosung , Barry Nicholas , Chatterjee Debjyoti , Santoso Surya
Published: December 2023

Optimal power flow (OPF) analysis enables the in-depth study and examination of islanded microgrid design and operation. The development of the analysis framework, including modeling, formulating, and selecting effective OPF solvers, however, is a nontrivial task. As a result, this paper presents a tutorial on an OPF modeling framework, offering a mathematical model that can be readily implemented using established open-source software tools such as OpenDSS, Pyomo, and IPOPT. The framework is versatile, capable of representing single-phase and unbalanced three-phase islanded microgrids. Various inverter models, such as those of grid forming and following equipped with their operating characteristics, can be incorporated. The efficacy of the proposed framework is demonstrated in studying the OPF of single-phase and three-phase microgrids.
A Comparative Study on the Removal of Microcystis and Cylindrospermopsis Blooms in Two Lakes by Flocculation–Filtration Treatment
Authors: Zhou Cheng , Deng Sisi , Xu Lei , Liu Xiang , Wang Chunbo , Chang Junjun
Published: December 2023

Dianchi Lake and Yilong Lake, two prominent plateau lakes in Yunnan Province, China, have suffered from Microcystis and Cylindrospermopsis blooms for decades. While cyanobacteria harvest boats utilizing cationic polyacrylamide (CPAM) flocculation and screen filtration have been proven effective for harvesting Microcystis biomass in Dianchi Lake, they struggle against Cylindrospermopsis blooms in Yilong Lake. This study systematically compared the removal of Microcystis and Cylindrospermopsis blooms using flocculation–filtration treatment, aiming to identify key factors influencing flocculation and propose enhancements to improve treatment efficiency for Cylindrospermopsis blooms. The reduction of turbidity, OD680, biovolume and phytoplankton density all revealed significantly better treatment efficiency for Microcystis blooms compared to Cylindrospermopsis blooms. In Dianchi Lake, 1 mg/L CPAM achieved a 95% turbidity reduction, while in Yilong Lake, even with 4.0 mg/L CPAM, the removal efficiency remained below 90%. Post-treatment, Dianchi Lake’s water quality showed substantial improvements, including over 50% reductions in total nitrogen, total phosphorus, permanganate index, and chemical oxygen demand. Conversely, nutrient level reductions were limited in Yilong Lake’s treated water. The average molecular weight of dissolved organic matters (DOM) in Yilong Lake was notably smaller than in Dianchi Lake. The treatment selectively removed high molecular weight, microbial-sourced, and protein-like DOM components, leading to a decrease in average molecular weight and an increase in humification index (HIX) in both lakes. Excessive humic matters in the water of Yilong Lake was found to hamper algae flocculation significantly. Introducing additional acidic polysaccharides or oxidants emerged as potential strategies to enhance Yilong Lake’s treatment efficiency.
How to Promote Sustainable Bamboo Forest Management: An Empirical Study from Small-Scale Farmers in China
Authors: Huang Yuan , Hou Yilei , Ren Jie , Yang Jie , Wen Yali
Published: December 2023

Bamboo is an important agroforestry and forest plant managed and utilized by rural communities in some countries in the Asia Pacific region, which can generate various benefits to meet social and environmental needs. In rural areas of China, as a large number of forest land management rights have been allocated to small-scale farmers, the willingness of small-scale farmers to reinvest in bamboo forest management has become a key factor for bamboo forest ecosystems to be able to sustainably supply quality ecosystem services. Therefore, it is necessary to answer the question of how to enhance small-scale farmers’ willingness to reinvest in bamboo forest management in the current policy and market context. Combining the prospect theory, the mindsponge theory, the theory of planned behavior (TPB), and the technology acceptance model (TAM), this study constructs theoretical models of perceived property rights security, perceived bamboo forest certification, government support, group decision making, risk perception, perceived value, geographic conditions, and resource endowment affecting willingness to reinvest in bamboo forest management. Based on 1090 questionnaires from a field study in Fujian, China, in 2021, structural equation modeling (SEM) was used to test the theoretical model. The results show that, under the current policy and market environment, government support is the key to enhance small-scale farmers’ willingness to reinvest in bamboo forest management, and their perception of ecological certification also has a facilitating effect on small-scale farmers’ willingness to reinvest in bamboo forest management, in which risk perception plays a significant mediating role. The government can enhance small-scale farmers’ willingness to reinvest in bamboo forest management by maintaining stable land property rights policies, increasing the publicity and promotion of bamboo forest certification, and enhancing information exchange among farmers.