bluuebunny/crossref_metadata_2025 huggingface dataset:
Are Imaging Evaluations of Soft-Tissue Masses Before Referral to a Specialized Center Being Performed Properly? A Systematic Review
Authors: Joo Min Wook , Park Chan Jin , Lee Yong-Suk , Cho Yoon Joo , Bernthal Nicholas Matthew , Lee Seul Ki , Kim Hyunho , Lee Joo Hwan , Kim Sung Hwan , Chung Yang-Guk
Published: November 2024

Background/Objectives: Since the initial approach towards the clinical presentation of soft-tissue masses is challenging for frontline physicians, some countries use clinical practice guidelines. Proper imaging work-up is crucial to differentiate between soft-tissue tumors. Recently, ultrasonography and magnetic resonance imaging (MRI) have been widely used. But there is some controversy about whether pre-referral evaluations are being conducted properly. Thus, this study aims to assess whether the ultrasonography investigation of soft-tissue masses prior to referral to the musculoskeletal tumor center is being performed adequately in terms of indications, diagnostic accuracy, and referral interval, and to evaluate whether the pre-referral MRI for soft-tissue masses is being conducted reasonably concerning indications, imaging protocol, reporting, diagnostic accuracy, and cost-effectiveness. Methods: The study protocol was registered. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. We performed a database search of the MEDLINE, Embase, and Cochrane Library. Then, two authors reviewed the studies, and the third author resolved any disagreement between them. A total of nine studies were included. The Risk Of Bias In Non-Randomized Studies-of Interventions was applied. Relevant data were extracted by two authors. Results: This review showed that the way that the imaging investigations are performed in non-specialized centers before referral was generally considered inappropriate. Conclusions: Frontline physicians should regard the alarm symptom as an indication for advanced imaging evaluation. Education and certification may be required for ultrasonography. MRI should be performed and interpreted in a specialized center or by a specialist with relevant expertise. Guidance may help reduce inappropriate imaging.
Casein Kinase 2 Inhibitor, CX-4945, Induces Apoptosis and Restores Blood-Brain Barrier Homeostasis in In Vitro and In Vivo Models of Glioblastoma
Authors: Bova Valentina , Mannino Deborah , Salako Ayomide E. , Esposito Emanuela , Filippone Alessia , Scuderi Sarah A.
Published: November 2024

Background: In oncology, casein kinase 2 (CK2), a serine/threonine kinase, has a dual action, regulating cellular processes and acting as an oncogenic promoter. Methods: This study examined the effect of CX-4945, a selective CK2 inhibitor, in a human U-87 glioblastoma (GBM) cell line, treated with CX-4945 (5, 10, and 15 μM) for 24 h. Similarly, the hCMEC/D3 cell line was used to mimic the blood–brain barrier (BBB), examining the ability of CX-4945 to restore BBB homeostasis, after stimulation with lipopolysaccharide (LPS) and then treated with CX-4945 (5, 10, and 15 μM). Results: We reported that CX-4945 reduced the proliferative activity and modulated the main pathways involved in tumor progression including apoptosis. Furthermore, in confirmation of the in vitro study, performing a xenograft model, we demonstrated that CX-4945 exerted promising antiproliferative effects, also restoring the tight junctions’ expression. Conclusions: These new insights into the molecular signaling of CK2 in GBM and BBB demonstrate that CX-4945 could be a promising approach for future GBM therapy, not only in the tumor microenvironment but also at the BBB level.
Multi-Omic Data Integration Suggests Putative Microbial Drivers of Aetiopathogenesis in Mycosis Fungoides
Authors: Licht Philipp , Mailänder Volker
Published: November 2024

Background: Mycosis fungoides (MF) represents the most prevalent entity of cutaneous T cell lymphoma (CTCL). The MF aetiopathogenesis is incompletely understood, due to significant transcriptomic heterogeneity and conflicting views on whether oncologic transformation originates in early thymocytes or mature effector memory T cells. Recently, using clinical specimens, our group showed that the skin microbiome aggravates disease course, mainly driven by an outgrowing, pathogenic S. aureus strain carrying the virulence factor spa, which was shown by others to activate the T cell signalling pathway NF-κB. Methods: To explore the role of the skin microbiome in MF aetiopathogenesis, we here performed RNA sequencing, multi-omic data integration of the skin microbiome and skin transcriptome using Multi-Omic Factor Analysis (MOFA), virome profiling, and T cell receptor (TCR) sequencing in 10 MF patients from our previous study group. Results: We observed that inter-patient transcriptional heterogeneity may be largely attributed to differential activation of T cell signalling pathways. Notably, the MOFA model resolved the heterogenous activation pattern of T cell signalling after denoising the transcriptome from microbial influence. The MOFA model suggested that the outgrowing S. aureus strain evoked signalling by non-canonical NF-κB and IL-1B, which in turn may have fuelled the aggravated disease course. Further, the MOFA model indicated aberrant pathways of early thymopoiesis alongside enrichment of antiviral innate immunity. In line with this, viral prevalence, particularly of Epstein–Barr virus (EBV), trended higher in both lesional skin and the blood compared to nonlesional skin. Additionally, TCRs in both MF skin lesions and the blood were significantly more likely to recognize EBV peptides involved in latent infection. Conclusions: First, our findings suggest that S. aureus with its virulence factor spa fuels MF progression through non-canonical NF-κB and IL-1B signalling. Second, our data provide insights into the potential role of viruses in MF aetiology. Last, we propose a model of microbiome-driven MF aetiopathogenesis: Thymocytes undergo initial oncologic transformation, potentially caused by viruses. After maturation and skin infiltration, an outgrowing, pathogenic S. aureus strain evokes activation and maturation into effector memory T cells, resulting in aggressive disease. Further studies are warranted to verify and extend our data, which are based on computational analyses.
Neuronal Progenitors Suffer Genotoxic Stress in the Drosophila Clock Mutant per0
Authors: Colonna Romano Nunzia , Marchetti Marcella , Marangoni Anna , Leo Laura , Retrosi Diletta , Rosato Ezio , Fanti Laura
Published: November 2024

The physiological role and the molecular architecture of the circadian clock in fully developed organisms are well established. Yet, we have a limited understanding of the function of the clock during ontogenesis. We have used a null mutant (per0) of the clock gene period (per) in Drosophila melanogaster to ask whether PER may play a role during normal brain development. In third-instar larvae, we have observed that the absence of functional per results in increased genotoxic stress compared to wild-type controls. We have detected increased double-strand DNA breaks in the central nervous system and chromosome aberrations in dividing neuronal precursor cells. We have demonstrated that reactive oxygen species (ROS) are causal to the genotoxic effect and that expression of PER in glia is necessary and sufficient to suppress such a phenotype. Finally, we have shown that the absence of PER may result in less condensed chromatin, which contributes to DNA damage.
How to Use Macrophages Against Cancer
Authors: Kuźnicki Jacek , Janicka Natalia , Białynicka-Birula Barbara , Kuźnicki Wojciech , Chorążyczewska Hanna , Deszcz Iwona , Kulbacka Julita
Published: November 2024

Numerous studies have demonstrated the significant influence of immune cells on cancer development and treatment. This study specifically examines tumor-associated macrophages (TAMs), detailing their characteristics and roles in tumorigenesis and analyzing the impact of the ratio of TAM subtypes on patient survival and prognosis. It is established that TAMs interact with immunotherapy, radiotherapy, and chemotherapy, thereby influencing the efficacy of these treatments. Emerging therapies are explored, such as the use of nanoparticles (NPs) for drug delivery to target TAMs and modify the tumor microenvironment (TME). Additionally, novel anticancer strategies like the use of chimeric antigen receptor macrophages (CAR-Ms) show promising results. Investigations into the training of macrophages using magnetic fields, plasma stimulation, and electroporation are also discussed. Finally, this study presents prospects for the combination of TAM-based therapies for enhanced cancer treatment outcomes.
Design and Experimental Characterization of a Microfluidic Piezoelectric Pump Utilizing P(VDF-TrFE) Film
Authors: Zhao Bei , Li Xiaomeng , Shi Jing , Liu Huiling
Published: November 2024

Advancements in wearable technology and lab-on-chip devices necessitate improved integrated microflow pumps with lower driving voltages. This study examines a piezoelectric pump using a flexible β-phase copolymer poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)) film. Six samples (S1–S6) were fabricated and subjected to a three-step annealing process to optimize their properties. Characterization was conducted via atomic force microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, impedance analysis, and polarization hysteresis loop measurements. The results show that annealing at approximately 135 degrees Celsius produces a β-phase structure with uniform “rice grain”-like crystallites. A microfluidic pump with a nozzle/diffuser structure, using S4 film as the drive layer, was designed and manufactured. Diaphragm deformation and pump performance were assessed, showing a maximum water flow rate of 25 µL/min at 60 Hz with a peak-to-peak voltage (Vpp) of 60 V. The flow rate could be precisely controlled within 0–25 µL/min by adjusting the Vpp and frequency. This study effectively reduced the driving voltage of the piezoelectric pump, showing that it has significant implications for smart wearable devices.
Renormalization of Fermi Velocity and Band Gap in a Two-Dimensional System near a Conducting Plate at Finite Temperature
Authors: Silva Jeferson Danilo L. , Braga Alessandra N. , Pires Wagner P. , Alves Danilo T. , Alves Van Sérgio
Published: November 2024

In a recent work, it was demonstrated within the framework of Pseudo Quantum Electro-dynamics (PQED) at zero temperature that the logarithmic renormalization of the Fermi velocity in a graphene sheet is inhibited by the presence of a single parallel conducting plate. In the present study, aiming for a more general and realistic approach, we explore the renormalization of the Fermi velocity and mass (band gap) in a two-dimensional system influenced by a conducting plate at finite temperature, also in the context of PQED. Our findings refine previous results in the literature and provide valuable insights for future investigations on the effects of external conditions within PQED.
Climate Adaptation of Roads to Flooding Hazards—A Review
Authors: Mushtaq Mehvesh , Corradi Marco , Sikdar Shirsendu
Published: November 2024

Flooding hazards due to climate change are increasingly becoming a frequent global occurrence. The aim of this study is to provide a comprehensive review of the various structural mitigation and adaptation strategies available to engineers and designers at various stages of road construction and rehabilitation to increase the resilience of roads to flooding damage. The criteria for categorising the various strategies available were the time of intervention with respect to the occurrence of the hazard. Thus, all studied strategies were separated into pre-construction design changes, post-construction mitigation and adaptation options like Sustainable Urban Drainage Systems (SuDS). The main findings were that changing the specifications of commonly used materials can provide increased flood resilience, and a preliminary design for flooding can reduce post-flooding rehabilitation. The study can be used as a guide for the different options available to deliver a design that takes flooding into consideration.
Monitoring Microbial Diversity of Biofilms in Domestic Distribution Systems Using an in Situ Device
Authors: Vargha Márta , Szánthó Zoltán , Kós Péter B. , Makk Judit , Khayer Bernadett , Németh Ábel Cs. , Engloner Attila I.
Published: November 2024

Biofilms in drinking water systems hosting diverse microbial communities are potential sources of opportunistic pathogens and taste/odour complaints. Domestic distribution networks are especially prone to biofilm formation due to high surface-to-volume ratio, elevated ambient temperature and intermittent use. Bacterial community diversity and determinants of community structure were investigated in two buildings using a purpose-designed in situ device containing stainless steel and polypropylene coupons and an online biofilm sensor. Next generation sequencing and scanning electron microscopy revealed increasing diversity and complexity over time. Initial biofilms were dominated by Proteobacteria (86–99%, primarily Burkholderiales and Sphingomonadales, core genera Aquabacterium and Blastomonas in month 1, and Rhizobiales in month 3), with an increasing ratio of Actinbacteriota (51–65%, mainly Corynebacteriales) and Bacteroidota (3–5%) by month 6. The impact of the sampling location was secondary to biofilm age in determining microbial diversity, and within-building variation was comparable to differences between facilities. The coupon material had a negligible effect on community structure. Real-time monitoring by online sensors did not yield interpretable data. Important nosocomial pathogens (Mycobacterium, Legionella, Methylobacterium, Bosea) were detected in the biofilm samples that were absent in bulk water, implying that water monitoring alone is not sufficient for estimating the risk of water-related pathogens.
Study on the Relationship Between Species Richness and Morphological Diversity of Higher Categories in Scarabaeoidea
Authors: Qiao Yumeng , Tong Yijie , Tian Zhehao , Liu Ning , Bai Ming
Published: November 2024

Evolutionary biology faces the important challenge of determining how to interpret the relationship between selection pressures and evolutionary radiation of species. The different biodiversity indicators highlight the disparate nature of biodiversity investigations. However, the influence of ecological factors and the specificity of taxonomic phylogeny have led to controversy over the correlation between these indicators. By combining quantitative morphology and statistical methods, here we analyze the biodiversity under the influences of phylogenetic relation factors represented by higher categories. A total of 8508 species of beetles from 1247 genera, 34 subfamilies, and 10 families of the Scarabaeoidea were selected as a test group; 70% of the family-level samples and 60% of the subfamily-level samples were selected at a proportion of 10–30% of the global described species. The taxonomic categories of family and subfamily were selected for phylogenetic representation, and the analysis of geometric morphometrics on the pronotum and elytron, which represent the major aspect of the morphology in dorsal view, was conducted. Through principal component analysis and Spearman correlation coefficient analysis, it was found that: the morphological diversity of the pronotum is higher in most groups of family/subfamily category than in the elytron; the correlation between the morphological diversity and species richness of the pronotum in the superfamily Scarabaeoidea is higher than that of the elytron; correlations between morphological diversity of the pronotum and taxa richness among sub-/families were always found to be consistent, and it was higher than it in the elytron test. This study compares the correlation between the diversity of different characters and the richness of taxa to interpret the phylogenetic impacts of biodiversity and sheds light on a fresh perspective for detailed studies of the selection pressures and formation mechanisms regulating the rise and fall of species.
The Interaction and Implication of Stress-Induced Hyperglycemia and Cytokine Release Following Traumatic Injury: A Structured Scoping Review
Authors: Al-Hassani Ibrahim , Khan Naushad Ahmad , Elmenyar Eman , Al-Hassani Ammar , Rizoli Sandro , Al-Thani Hassan , El-Menyar Ayman
Published: November 2024

Introduction: This is a structured scoping review to assess whether there is a relationship between stress-induced hyperglycemia (SIH), cytokine interactions, and mortality in trauma patients in comparison to non-diabetic normoglycemia [NDN], diabetic normoglycemia [DN], and diabetic hyperglycemia [DH]. Methods: We conducted a literature search of MEDLINE (PubMed) databases from 2000 to 2022 using a search strategy to identify observational studies. Initially, 2879 articles were retrieved. Of these, 2869 were excluded due to insufficient variables, and non-trauma focuses. Results: Nine studies on the interaction between SIH and proinflammatory cytokines were analyzed. SIH was associated with the highest mortality rate (21.3%), followed by DH (5.4%), DN (2.8%), and NDN (2.3%) (p < 0.001). Furthermore, SIH patients exhibited an 11.28-fold higher likelihood of mortality compared to NDN patients (95% CI [9.13–13.93]; p < 0.001) and a 4.72-fold higher likelihood compared to DH patients (OR 4.72; 95% CI [3.55–6.27]; p < 0.001). Conclusions: SIH patients had elevated IL-6 concentrations relative to NDN, DN, and DH patients. SIH is linked to higher mortality in trauma, with greater odds than NDN. However, the robustness of this association is still being determined due to statistical and clinical variability. Uncertainties about injury severity and IL-6 level similarities between SIH and DH patients require further investigation.
Unlocking Chemotherapy Success: The Role of Diffusion Tensor Imaging in Breast Cancer Treatment
Authors: Ciurea Anca Ileana , Bene Ioana , Cheregi Paul , Brad Thea , Ciortea Cristiana Augusta , Rusu Georgeta Mihaela , Ciule Larisa Dorina , Deac Andrada-Larisa , Lenghel Manuela Lavinia
Published: November 2024

Background: This study investigates the role of Diffusion Tensor Imaging (DTI) in predicting the response to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer. Methods: A Diffusion Tensor Imaging magnetic resonance imaging (DTI MRI) sequence, evaluating water diffusion along tissue structures, was performed before and after two chemotherapy cycles. This study included 23 patients with 27 malignant masses, comparing changes in DTI parameters with Residual Cancer Burden (RCB) scores. Results: We found a significant correlation between changes in specific DTI parameters (e.g., λ2, FA, RA) and pathological response, suggesting that DTI could serve as a sensitive marker for early chemotherapy response. However, differences in sensitivity were observed between DTI sequences with 6 and 12 directions, indicating that 12-direction DTI may provide better diagnostic accuracy. The percentage change in DTI parameters, particularly FA, demonstrated a strong ability to predict pathological complete response (pCR) with high sensitivity. Conclusions: As a non-invasive tool, DTI has the potential to assess chemotherapy efficacy, although larger studies with standardized protocols are necessary to validate its clinical utility.
Treatment of Young Permanent Avulsed Teeth with Multidisciplinary Approach—A Case Report
Authors: Rivera-Pimentel Narda Lorena , Campos-Lara Nadia Phenelope , Benítez-Cárdenas Oscar Arturo , Méndez-González Verónica , Comas-García Andreu , Vitales-Noyola Marlen , Torre-Delgadillo Gabriela
Published: November 2024

Background: Dental trauma very commonly comprises lesions that affect the teeth and their supporting structures. In pediatric ages, the main reasons for dental trauma are falls and accidents at school and while practicing recreative activities and sports. Fortunately, dental avulsions are not common; however, they are key factors in the loss of teeth if the issue is not adequately treated in a quick way, so is very important for parents, teachers, or any person that is present with a child during the accident to have knowledge about dental trauma, specifically regarding avulsed teeth, since the best treatment is reimplantation. Methods: In this case of dentoalveolar trauma, concerning two avulsed teeth, it was very interesting that the tooth that was reimplanted more quickly (40 min) had a worse prognosis than the tooth that was reimplanted 2 h later, since the tooth that was reimplanted more quickly was transported in a personal wallet, which was a highly contaminated area, unlike the tooth that was reimplanted later, which was transported in a solution as an alternative means of transport. Conclusions: So, it is very important that this type of trauma is adequately managed in an interdisciplinary way across multiple dentistry specialties.
Multi-Target Tracking with Multiple Unmanned Aerial Vehicles Based on Information Fusion
Authors: Wu Pengnian , Li Yixuan , Xue Dong
Published: November 2024

In high-altitude scenarios, targets tend to occupy a small number of pixels within the UAV’s field of view, resulting in substantial errors when identity recognition is attempted based solely on appearance features during multi-UAV joint tracking. Existing methodologies typically propose projecting multi-view data onto a single plane and leveraging distance information for identity association; however, their accuracy remains low as they are contingent on one-dimensional target information. To address this limitation, this paper introduces the UAVST-HM (UAV Swarm Tracking in High-altitude scenarios for Multiple targets) model, specifically designed to handle the characteristics of targets in the field of view of multiple UAVs at high altitudes. Initially, we develop techniques for extracting targets’ appearance, geometric, and distribution features. Subsequently, adaptive weights, calculated based on the mean of the respective features, are devised to amalgamate these diverse features, thereby constructing a cost matrix for cross-view target identity matching. This matrix is processed through the Hungarian algorithm, and multi-view target identity association is ultimately achieved via threshold filtering. On the MDMT dataset, our method enhances the MDA indicator, which assesses cross-view target identity matching, by 1.78 percentage points compared to the current state of the art. This significant enhancement substantially improves the overall efficacy of multi-UAV joint visual tracking from a high-altitude perspective.
LVGG-IE: A Novel Lightweight VGG-Based Image Encryption Scheme
Authors: Sun Mingliang , Yuan Jie , Li Xiaoyong , Liu Dongxiao , Wei Xinghai
Published: November 2024

Image security faces increasing challenges with the widespread application of computer science and artificial intelligence. Although chaotic systems are employed to encrypt images and prevent unauthorized access or tampering, the degradation that occurs during the binarization process in chaotic systems reduces security. The chaos- and DNA-based image encryption schemes increases its complexity, while the integration of deep learning with image encryption is still in its infancy and has several shortcomings. An image encryption scheme with high security and efficiency is required for the protection of the image. To address these problems, we propose a novel image encryption scheme based on the lightweight VGG (LVGG), referred to as LVGG-IE. In this work, we design an LVGG network with fewer layers while maintaining a high capacity for feature capture. This network is used to generate a key seed, which is then employed to transform the plaintext image into part of the initial value of a chaotic system, ensuring that the chaos-based key generator correlates with the plaintext image. A dynamic substitution box (S-box) is also designed and used to scramble the randomly shuffled plaintext image. Additionally, a single-connected (SC) layer is combined with a convolution layer from VGG to encrypt the image, where the SC layer is dynamically constructed by the secret key and the convolution kernel is set to 1×2. The encryption efficiency is simulated, and the security is analyzed. The results show that the correlation coefficient between adjacent pixels in the proposed scheme achieves 10−4. The NPCR exceeds 0.9958, and the UACI falls within the theoretical value with a significance level of 0.05. The encryption quality, the security of the dynamic S-box and the SC layer, and the efficiency are tested. The result shows that the proposed image encryption scheme demonstrates high security, efficiency, and robustness, making it effective for image security in various applications.
Identifying Ordinal Similarities at Different Temporal Scales
Authors: Zunino Luciano , Porte Xavier , Soriano Miguel C.
Published: November 2024

This study implements the permutation Jensen–Shannon distance as a metric for discerning ordinal patterns and similarities across multiple temporal scales in time series data. Initially, we present a numerically controlled analysis to validate the multiscale capabilities of this method. Subsequently, we apply our methodology to a complex photonic system, showcasing its practical utility in a real-world scenario. Our findings suggest that this approach is a powerful tool for identifying the precise temporal scales at which two distinct time series exhibit ordinal similarity. Given its robustness, we anticipate that this method could be widely applicable across various scientific disciplines, offering a new lens through which to analyze time series data.
Joint Sampling and Transmission Policies for Minimizing Cost Under Age of Information Constraints
Authors: Fountoulakis Emmanouil , Codreanu Marian , Ephremides Anthony , Pappas Nikolaos
Published: November 2024

In this work, we consider the problem of jointly minimizing the average cost of sampling and transmitting status updates by users over a wireless channel subject to average Age of Information (AoI) constraints. Errors in the transmission may occur and a policy has to decide if the users sample a new packet or attempt to retransmission the packet sampled previously. The cost consists of both sampling and transmission costs. The sampling of a new packet after a failure imposes an additional cost on the system. We formulate a stochastic optimization problem with the average cost in the objective under average AoI constraints. To solve this problem, we propose three scheduling policies: (a) a dynamic policy, which is centralized and requires full knowledge of the state of the system and (b) two stationary randomized policies that require no knowledge of the state of the system. We utilize tools from Lyapunov optimization theory and Discrete-Time Markov Chain (DTMC) to provide the dynamic policy and the randomized ones, respectively. Simulation results show the importance of providing the option to transmit an old packet in order to minimize the total average cost.
Perceived School Climate Support Moderates the Relationship Between Teachers’ Growth Mindset and Work Engagement
Authors: Zhang Kai , He Wu-Jing
Published: November 2024

This study examines how perceived school climate support moderates the relationship between teachers’ growth mindset and work engagement. A sample of 353 teachers (56% females) from Shanghai City, China, completed the Growth Mindset Inventory (GMI) and the Utrecht Work Engagement Scale (UWES) to evaluate their growth mindset and work engagement levels, respectively. The School Environment Scale (SES) was used to measure perceived school climate support across five dimensions: collaboration, student relations, decision-making, instructional innovation and school resources. Hierarchical regression analyses were employed to examine the moderating effects of each dimension of perceived school climate support on the relationship between a growth mindset and work engagement. The results indicated that (1) a growth mindset was a positive predictor of work engagement, suggesting that teachers who view their abilities as developable are more engaged in their professional roles, and that (2) all five dimensions of perceived school climate support significantly and positively moderated this relationship, suggesting that perceived school climate support enhances the impact of a growth mindset on work engagement. These findings underscore the importance of targeted environmental factors in maximizing the benefits of growth mindset interventions among teachers, thereby providing actionable insights for educational leaders to improve teacher engagement through focused climate enhancements.
Can Video Lectures on Enthymemes Improve Adult Learners’ Critical Thinking and Clickbait Detection Skills?
Authors: Vlah Ana , Wijnia Lisette , Lutz Christel , Burke Michael , Loyens Sofie M. M.
Published: November 2024

Critical thinking is essential when navigating, evaluating, and interacting with media; therefore, it is important to investigate if adults’ critical thinking skills can be trained. This paper describes an experiment investigating the impact of video lectures about enthymemes and critical thinking skills on participants’ (N = 176) critical thinking skills, measured by the Watson–Glaser Critical Thinking Appraisal (WGCTA) and on their ability to identify clickbait headlines. Participants were adults recruited through the Prolific Platform, and they were randomly assigned to one of three conditions: an enthymeme lecture, a general critical thinking lecture, or a control condition. The results indicated no significant improvement in critical thinking scores across the conditions, as measured by the WGCTA. Similarly, no significant differences were found in the participants’ ability to identify clickbait headlines. However, a significant positive correlation was observed between higher critical thinking scores and better clickbait recognition. These results suggest that a short lecture-based intervention may not be sufficient to significantly improve adult learners’ critical thinking. Perhaps this study indicates the need for more in-depth or interactive interventions to effectively support media literacy. The material presented here is a kind of counterexample of what should be done. For this reason, it may prove useful in future research to avoid certain experimental dead-ends.
Transient Stability-Based Fast Power System Contingency Screening and Ranking
Authors: Kumissa Teshome Lindi , Shewarega Fekadu
Published: November 2024

Today’s power systems are operated closer to their stability limits due to the continuously growing load demands, interface to open markets, and integration of more renewable energies. In order to provide operators with clear insight on the current system situation, near real-time power systems dynamic security assessment tools are required. One of the core elements of near real-time dynamic security assessment tools is contingency screening and ranking. Most of the commercially available tools screen and rank contingencies by using the traditional numerical integration or Transient Energy Functions (TEFs) or hybrid methods. The traditional numerical integration method is accurate but computationally intensive and has a slow assessment speed which makes it difficult to identify any insecure contingency before it happens. Despite the TEF method of transient stability analysis being relatively fast, it develops less accurate results due to models simplification and assumptions. This paper introduces transient stability based on fast and robust contingency screening and ranking using an Adaptive step-size Differential Transformation (AsDTM) method. Based on the most current snapshot from Supervisory Control and Data Accusation (SCADA) data, the proposed method triggers AsDTM-based transient stability simulation for each credible contingency and evaluates Transient Stability Indices (TSI) as the normalized weighted sum of squares of errors derived from state variables and complex bus voltages at every simulation time step. Finally, contingencies are ranked based on these TSI and the worst contingency is identified for the next detail assessment. The method is tested on IEEE 9 bus and 39 bus test systems. Test results reveal that the proposed method is faster, robust, and can be used in near real-time dynamic security assessment sessions.
A Mobile Application to Facilitate Meal Box Sharing in Corporate Environments Using Cloud Infrastructure
Authors: Mohod Priya Tushar , Otuka Richard I. , Ajienka Nemitari , Ihianle Isibor Kennedy , Nwajana Augustine O.
Published: November 2024

Food waste is a pressing global issue, particularly in urban settings, where substantial amounts of surplus food go unused. In corporate environments, this challenge is compounded by the lack of dedicated platforms to facilitate food sharing and reduce waste effectively. This paper examines the current landscape of food waste, existing solutions, and the need for a specialised platform aimed at corporate employees. The proposed solution is the creation of a user-friendly application that enables the sharing of untouched homemade meals. Suppliers can post their meal boxes with details such as location, type of food, and availability status, while consumers can search for and select meal boxes based on their preferences. This paper addresses the gap in solutions for reducing food waste within corporate environments. The meal-box-sharing app provides a practical and sustainable method for minimising food waste and promoting productivity, health, and safety in the workplace.
Enhanced In-Network Caching for Deep Learning in Edge Networks
Authors: Zhang Jiaqi , Liu Wenjing , Zhang Li , Tian Jie
Published: November 2024

With the deep integration of communication technology and Internet of Things technology, the edge network structure is becoming increasingly dense and heterogeneous. At the same time, in the edge network environment, characteristics such as wide-area differentiated services, decentralized deployment of computing and network resources, and highly dynamic network environment lead to the deployment of redundant or insufficient edge cache nodes, which restricts the efficiency of network service caching and resource allocation. In response to the above problems, research on the joint optimization of service caching and resources in the decentralized edge network scenario is carried out. Therefore, we have conducted research on the collaborative caching of training data among multiple edge nodes and optimized the number of collaborative caching nodes. Firstly, we use a multi-queue model to model the collaborative caching process. This model can be used to simulate the in-network cache replacement process on collaborative caching nodes. In this way, we can describe the data flow and storage changes during the caching process more clearly. Secondly, considering the limitation of storage space of edge nodes and the demand for training data within a training epoch, we propose a stochastic gradient descent algorithm to obtain the optimal number of caching nodes. This algorithm entirely takes into account the resource constraints in practical applications and provides an effective way to optimize the number of caching nodes. Finally, the simulation results clearly show that the optimized number of caching nodes can significantly improve the adequacy rate and hit rate of the training data, with the adequacy rate reaching 84% and the hit rate reaching 100%.
A Four-Point Orientation Method for Scene-to-Model Point Cloud Registration of Engine Blades
Authors: Li Duanjiao , Zhang Ying , Jia Ziran , Wang Zhiyu , Fang Qiu , Zhang Xiaogang
Published: November 2024

The use of 3D optical equipment for multi-view scanning is a promising approach to assessing the processing errors of engine blades. However, incomplete scanned point cloud data may impact the accuracy of point cloud registration (PCR). This paper proposes a four-point orientation point cloud registration method to improve the efficiency and accuracy of the coarse registration of turbine blades and prevent PCR failure. First, the point cloud is divided into four labeling blocks based on a principal component analysis. Second, keypoints are detected in each block based on their distance from the plane formed by the principal axes and described with a location-label descriptor based on their position. Third, a keypoint pair set is chosen based on the descriptor, and a suitable keypoint base is selected through singular value decomposition to obtain the final rigid transformation. To verify the effectiveness of the method, experiments are conducted on different blades. The results demonstrate the improved performance and efficiency of the proposed method of coarse registration for turbine blades.
Analysis and Design of Low-Noise Radio-Frequency Power Amplifier Supply Modulator for Frequency Division Duplex Cellular Systems
Authors: Paek Ji-Seon
Published: November 2024

This paper describes an analysis of power supply rejection and noise improvement techniques for an envelope-tracking power amplifier. Although the envelope-tracking technique improves efficiency, its power supply rejection ratio is much lower than that of average power tracking or a fixed-supply power amplifier. In FDD systems with the envelope-tracking technique, the low power supply rejection ratio generates much output noise in the RX band and degrades the receiver’s sensitivity. An SM is designed by using a 130 nm CMOS process, and the chip die area is 2 × 2 mm2 with a 25-pin wafer-level chip-scale package. The designed SM achieved peak efficiencies of 78–83% for LTE signals with a 5.8 dB PAPR and various channel bandwidths. For the low-output-noise-supply modulator, noise reduction techniques using resonant-frequency tuning and a notch filter are employed, and the measured results show maximum 1.8/5/5.3/3.8/3 dB noise reduction in LTE bands B17/B5/B2/B3/B7, respectively.
Improved Deep Learning for Parkinson’s Diagnosis Based on Wearable Sensors
Authors: Yu Jintao , Meng Ke , Liang Tingwei , Liu He , Wang Xiaowen
Published: November 2024

Parkinson’s disease is a neurodegenerative disease that seriously affects the quality of life of patients. In this study, we propose a new Parkinson’s diagnosis method using deep learning techniques. The method takes multi-channel sensor signals as inputs, and the full convolutional and LSTM blocks of the model perceive the same time-series inputs from two different views, and connect the extracted spatial features with temporal features. In order to improve the detection performance, a channel attention mechanism was incorporated into the model, and a data augmentation approach was used to eliminate the effect of unbalanced datasets on model training. The pd vs. hc and pd vs. dd classification tasks were performed, which improved accuracy by 4.25% and 8.03%, respectively, compared to the previous best results. Both improvements were higher than the previous methods using machine learning combined with feature extraction. To utilize the available data resources more effectively, this study conducted the pd vs. hc vs. dd triple classification task for the first time, which improved the model’s ability to identify disease features. In that task, the accuracy rate reached 78.23%. The experimental results fully demonstrated the effectiveness of the proposed deep learning method for Parkinson’s diagnosis.
Multi-Scale Frequency-Spatial Domain Attention Fusion Network for Building Extraction in Remote Sensing Images
Authors: Liu Jia , Chen Hao , Li Zuhe , Gu Hang
Published: November 2024

Building extraction from remote sensing images holds significant importance in the fields of land resource management, urban planning, and disaster assessment. Encoder-decoder deep learning models are increasingly favored due to their advanced feature representation capabilities in image analysis. However, because of the diversity of architectural styles and issues such as tree occlusion, traditional methods often result in building omissions and blurred boundaries when extracting building footprints. Given these limitations, this paper proposes a cutting-edge Multi-Scale Frequency-Spatial Domain Attention Fusion Network (MFSANet), which consists of two principal modules, named Frequency-Spatial Domain Attention Fusion Module (FSAFM) and Attention-Guided Multi-scale Fusion Upsampling Module (AGMUM). FSAFM introduces frequency domain attention and spatial attention separately to enhance the feature maps, thereby strengthening the model’s boundary-detection capabilities and ultimately improving the accuracy of building extraction. AGMUM first resizes and concatenates attention enhancement maps to enhance contextual understanding and applies attention guidance to further improve prediction accuracy. Our model demonstrates superior performance compared to existing semantic segmentation methods on both the WHU building data set and the Inria aerial image data set.
Electrochemical Storage and Flexibility in Transfer Capacities: Strategies and Uses for Vulnerable Power Grids
Authors: Gómez-Ramírez Gustavo Adolfo , García-Santander Luis , Rojas-Morales José Rodrigo , Lazkano-Zubiaga Markel , Meza Carlos
Published: November 2024

The integration of renewable energy sources into electrical power systems presents enormous challenges in technical terms, especially with energy storage. Battery electrochemical storage systems (BESSs) are becoming a crucial solution for reducing the intermittency of renewable energy supply and enhance the stability of power networks. Nonetheless, its extensive implementation confronts constraints, including expense, life expectancy, and energy efficiency. Simultaneously, these technologies present prospects for improved energy management, increase the hosting capacity of renewable energy, and diminish reliance on fossil fuels. This paper investigates the obstacles of integrating electrochemical storage into electrical power systems, explores solutions to use its promise for creating more resilient and sustainable grids, and presents a method for the size estimation and strategic allocation of electrochemical energy storage systems (EESSs). The aim is to improve grid voltage profiles, manage demand response, increase the adoption of renewable energy resources, enhance power transfer among various areas, and subsequently improve the stability of a power system during large disturbances. The methodology utilizes a multi-stage optimization process based on economic considerations supported by dynamic simulation. This methodology was tested employing a validated dynamic model of the Interconnected Electrical System of the Central American Countries (SIEPAC). The system experienced multiple significant blackouts in recent years, primarily due to the increasing amount of renewable energy generation without adequate inertial support and limited power transfer capabilities among countries. Based on the results of using the technique, EESSs can effectively lower the risk of instability caused by an imbalance between power generation and demand during extreme situations, as seen in past event reports. Based on economical constraints, it has been determined that the cost of installing EESSs for the SIEPAC, which amounts to 1200 MWh/200 MW, is 140.91 USD/MWh.
Navigating and Overcoming Barriers to Digital Energy Transition for Carbon Neutrality in China
Authors: Sun Shuao , Ahmed Sheeraz
Published: November 2024

As China strives for carbon neutrality, the transition to digital energy systems presents both significant opportunities and formidable challenges. This study investigates the key barriers hindering this transition and the urgent need for effective strategies to address them, raising the critical research question: What are the main obstacles to digital energy adoption in China, and how can these challenges be overcome? In this study, the fuzzy AHP method has been utilized to prioritize barriers and fuzzy WASPAS to evaluate the strategies. Using fuzzy AHP, we found that stakeholder and governance barriers are the most critical, emphasizing issues like misalignment among stakeholders and governance challenges. Following this, financial constraints and technological limitations emerged as other significant barriers, highlighting the need for improved financing mechanisms and robust infrastructure. Through fuzzy WASPAS analysis, the top strategies identified are enhancing public awareness and capacity-building programs, strengthening governance and anti-corruption measures, and increasing investment in green finance. The results emphasize the importance of tackling governance and financial issues alongside technological advancements. Policy implications and recommendations are provided to guide China’s digital energy transition, with suggestions for future research focused on broader regional comparisons and the integration of emerging technologies.
The Generation Methods and Applications of Cavitating Jet by Using Bubble Collapse Energy
Authors: Zhang Haida , Fan Chenxing , Wang Luyao , Lu Wenjun , Li Deng
Published: November 2024

Cavitation is a dynamic process characterized by the formation, growth, and collapse of vapor or gas vacuoles in liquids or at the liquid–solid interface, initiated by a local pressure drop. This phenomenon releases concentrated energy through microjet impacts and shock waves, leading to a violent exchange of energy with the surrounding environment. While cavitation is often perceived as detrimental, certain aspects can be harnessed for practical applications. Relevant studies have shown that cavitating jets provide high operating efficiencies, reduce energy consumption per unit, and have the potential for waste treatment. This paper presents three types of cavitating jets: central body cavitation, oscillatory cavitation, and shear cavitation. Additionally, the formation process of a cavitating jet and the effects of various factors on jet performance are discussed. Following an in-depth examination of the cavitation phenomena, subsequent chapters explore the applications of cavitating jets in material surface enhancement, cleaning, and energy exploration. Furthermore, recommendations for future research on cavitating jets are provided. This paper provides a comprehensive literature review on cavitating jets.
Influence of Winding Configurations and Stator/Rotor Pole Combinations on Field Back-EMF Ripple in Switched Flux Hybrid Excited Machines
Authors: Yang Zhiyu , Sun Xiaoyong , Han Ruizhao , Shang Ruyu , Chen Zhen , Liu Xiangdong
Published: November 2024

Similar to armature back electromotive force (armature back-EMF), the back-EMF also exists in the field winding of hybrid excited machines. However, the existence of field back electromotive force (field back-EMF) is harmful to the safe and stable operation of machine systems, e.g., higher losses, lower efficiency, higher torque ripple, and reduced control performance. This paper systematically investigates the influence of armature/field winding configurations together with stator/rotor pole combinations on the field back-EMF ripple in hybrid excited machines with switched-flux stators. The two-dimensional (2D) time-stepping finite element modeling and prototyping experiments are used for the research. The investigated field and armature coil pitches equal to 1, i.e., non-overlapped windings. The influential factors that are investigated in this paper mainly include the number of layers of field/armature windings, the number of field/armature coils, and the stator/rotor pole combinations. The results show that the field back-EMF’s harmonic order and peak-to-peak value are closely associated with field/armature winding configurations and stator/rotor pole combinations under various conditions. Finally, for validation of the results predicted by the finite element method, a prototype machine is built and tested. Overall, non-overlapped double-layer armature and field windings are recommended for the hybrid excited switched flux machines with various stator/rotor pole combinations to realize relatively lower field back-EMF under different conditions.