bluuebunny/crossref_metadata_2025 huggingface dataset:
Temporary Skeletal Anchorage Devices and Cone Beam Tomography in Orthodontics—Current Application and New Directions of Development
Authors: Aebisher David , Serafin Iga , Bartusik-Aebisher Dorota
Published: June 2024

Continuous progress in dentistry and orthodontics is crucial to ensuring high-quality diagnosis and treatment of patients, especially since malocclusions occur in up to half of the population. In addition to limiting the physiological functions of the masticatory system, they are often an aesthetic defect that may directly affect the well-being and even self-esteem of patients, especially in their teenage years and early adulthood. A holistic model of perceiving and treating orthodontic diseases, such as the Biocreative Orthodontic Strategy, focusing not only on the correction of the defect itself but also taking into account the least possible interference in the physiology of the masticatory system, limiting the use of appliances to a minimum, and taking into account the patient’s preferences, is a special alternative to conventional therapeutic models. In this review, we are presenting the current knowledge regarding the applications of temporary skeletal anchorage devices (TSAD) and cone beam computed tomography (CBCT) in orthodontics.
Swiss Round Selection Algorithm for Multi-Robot Task Scheduling
Authors: Fu Xing , Zhang Gongxue , Yuan Hai , Wang Weijun , Wang Jian , Huang Zucheng
Published: June 2024

Efficient and stable control and task assignment optimization in electronic commerce logistics and warehousing systems involving multiple robots executing multiple tasks is highly challenging. Hence, this paper proposes a Swiss round selection algorithm for multi-robot task allocation to address the challenges mentioned. Firstly, based on the shipping process of electronic commerce logistics and warehousing systems, the tasks are divided into packaging and sorting stages, and a grid model for the electronic commerce warehousing system is established. Secondly, by increasing the probabilities of crossover and mutation in the population and adopting a full crossover and full mutation approach, the search scope of the population is expanded. Then, a Swiss round selection mechanism with burst probability is proposed, which ensures the smooth inheritance of high-quality individuals while improving the diversity of the population. Finally, 12 comparative experiments are designed with different numbers of robots and tasks. The experimental results demonstrate that the Swiss round selection algorithm outperforms the genetic algorithm in terms of maximum task completion time and convergence time to reach the optimal value. Thus, the effectiveness of the Swiss round selection algorithm in solving the multi-robot task allocation problem is verified.
The Experimental Characterization of Iron Ore Tailings from a Geotechnical Perspective
Authors: Coelho Paulo , Camacho David
Published: June 2024

The mining industry produces large amounts of tailings which are disposed of in deposits, which neglects their potential value and represents important economic, social and environmental risks. Consequently, implementing circular economy principles using these unconventional geomaterials may decrease the wide-ranging impacts of raw material extraction. This paper presents an experimental characterization of iron ore tailings, which are the most abundant type of mining waste. The characterization includes various aspects of behavior that are relevant to different types of use as a building material, including physical and identification properties, compaction behavior and stress–strain properties under undrained monotonic and cyclic triaxial loading. The tailings tested can be described as low-plasticity silty sand materials with an average solids density of 4.7, a maximum dry unit weight close to 3 g/cm3 and a higher angle of friction and liquefaction resistance than common granular materials. The experimental results highlight the particular features of the behavior of iron ore tailings and emphasize the potentially promising combination of high shear resistance and high density that favors particular geotechnical applications. Overall, the conclusions provide the basis for promoting the use of mining wastes in the construction of sustainable geotechnical works and underpin the advanced analysis of tailings storage facilities’ safety founded on an open-minded geotechnical approach.
Assessment of Landslide Susceptibility in the Moxi Tableland of China by Using a Combination of Deep-Learning and Factor-Refinement Methods
Authors: He Zonghan , Zhang Wenjun , Cai Jialun , Fan Jing , Xu Haoming , Feng Hui , Luo Xinlong , Wu Zhouhang
Published: June 2024

Precisely assessing the vulnerability of landslides is essential for effective risk assessment. The findings from such assessments will undoubtedly be in high demand, providing a solid scientific foundation for a range of critical initiatives aimed at disaster prevention and control. In the research, authors set the ancient core district of Sichuan Moxi Ancient Town as the research object; they conduct and give the final result of the geological survey. Fault influences are commonly utilized as key markers for delineating strata in the field of stratigraphy, and the slope distance, slope angle, slope aspect, elevation, terrain undulation, plane curvature, profile curvature, mean curvature, relative elevation, land use type, surface roughness, water influence, distance of the catchment, cumulative water volume, and the Normalized Vegetation Index (NDVI) are used along roads to calculate annual rainfall. With the purpose of the establishment of the evaluation system, there are 17 factors selected in total. Through the landslide-susceptibility assessment by the coupled models of DNN-I-SVM and DNN-I-LR nine factors had been selected; it was found that the Area Under the Curve (AUC) value of the Receiver Operating Characteristic Curve (ROC) was high, and the accuracy of the model is relatively high. The coupler, DNN-I-LR, gives 0.875 of an evaluation accuracy of AUC, higher than DNN-I-SVM, which yielded 0.860. It is necessary to note that, in this region, compared to the DNN-I-SVM model, the DNN-I-LR coupling model has better fitting and prediction abilities.
Precise Obstacle Avoidance Movement for Three-Wheeled Mobile Robots: A Modified Curvature Tracking Method
Authors: Wen Xiangrong , Zhou Yusheng
Published: June 2024

This paper proposes a precise motion control strategy for a three-wheeled mobile robot with two driven rear wheels and one steered front wheel so that an obstacle avoidance motion task is able to be well implemented. Initially, the motion laws under nonholonomic constraints are expounded for the three-wheeled mobile robot in order to facilitate the derivation of its dynamic model. Subsequently, a prescribed target curve is converted into a speed target through the nonholonomic constraint of zero lateral speed. A modified dynamical tracking target that is aligned with the dynamic model is then developed based on the relative curvature of the prescribed curve. By applying this dynamical tracking target, path tracking precision is enhanced through appropriate selection of a yaw motion speed target, thus preventing speed errors from accumulating during relative curvature tracking. On this basis, integral sliding mode control and feedback linearization methods are adopted for designing robust controllers, enabling the accurate movement of the three-wheeled mobile robot along a given path. A theoretical analysis and simulation results corroborate the effectiveness of the proposed trajectory tracking control strategy in preventing off-target deviations, even with significant speed errors.
C. elegans Germline as Three Distinct Tumor Models
Authors: Jones Mariah , Norman Mina , Tiet Alex Minh , Lee Jiwoo , Lee Myon Hee
Published: June 2024

Tumor cells display abnormal growth and division, avoiding the natural process of cell death. These cells can be benign (non-cancerous growth) or malignant (cancerous growth). Over the past few decades, numerous in vitro or in vivo tumor models have been employed to understand the molecular mechanisms associated with tumorigenesis in diverse regards. However, our comprehension of how non-tumor cells transform into tumor cells at molecular and cellular levels remains incomplete. The nematode C. elegans has emerged as an excellent model organism for exploring various phenomena, including tumorigenesis. Although C. elegans does not naturally develop cancer, it serves as a valuable platform for identifying oncogenes and the underlying mechanisms within a live organism. In this review, we describe three distinct germline tumor models in C. elegans, highlighting their associated mechanisms and related regulators: (1) ectopic proliferation due to aberrant activation of GLP-1/Notch signaling, (2) meiotic entry failure resulting from the loss of GLD-1/STAR RNA-binding protein, (3) spermatogenic dedifferentiation caused by the loss of PUF-8/PUF RNA-binding protein. Each model requires the mutations of specific genes (glp-1, gld-1, and puf-8) and operates through distinct molecular mechanisms. Despite these differences in the origins of tumorigenesis, the internal regulatory networks within each tumor model display shared features. Given the conservation of many of the regulators implicated in C. elegans tumorigenesis, it is proposed that these unique models hold significant potential for enhancing our comprehension of the broader control mechanisms governing tumorigenesis.
Neuroprotective Effect of Marrubium vulgare Extract in Scopolamine-Induced Cognitive Impairment in Rats: Behavioral and Biochemical Approaches
Authors: Lazarova Maria , Stefanova Miroslava , Denev Petko , Taseva Teodora , Vassileva Valya , Tasheva Krasimira
Published: June 2024

The potential of Marrubium vulgare to alleviate scopolamine (Sco)-induced deficits in spatial working memory has drawn considerable scientific interest. This effect is partly attributed to its potent antioxidant and acetylcholinesterase inhibitory (AChEI) activities. This study examined the effects of M. vulgare extract, standardized to marrubiin content, on recognition memory in healthy and Sco-treated rats. Male Wistar rats (200–250 g) were divided into four groups. The extract was orally administered for 21 days and Sco (2 mg/kg) was intraperitoneally injected for 11 consecutive days. Memory performance was assessed using the novel object recognition test. Levels of acetylcholine (ACh), noradrenaline (NA), serotonin (Sero), and brain-derived neurotrophic factor (BDNF) and the phosphorylation of cAMP response element-binding protein (p-CREB) were evaluated in the cortex and hippocampus via ELISA. BDNF and CREB expression levels were assessed using RT-PCR. The results showed that M. vulgare significantly alleviated Sco-induced memory impairment, preserved cholinergic function in the hippocampus, increased NA levels in the brain, and restored pCREB expression in the cortex following Sco-induced reduction. In healthy rats, the extract upregulated BDNF, pCREB, and Bcl2 expression. Our findings indicate that the neuroprotective effects of M. vulgare may be linked to the modulation of cholinergic function, regulation of NA neurotransmission, and influence on key memory-related molecules.
Design and Fabrication of a Biomimetic Smart Material for Electrochemical Detection of Carbendazim Pesticides in Real Samples with Enhanced Selectivity
Authors: Maia Júnior Francisco Franciné , Sales Junior Rui , Barbosa Geovani Ferreira , Hussain Sajjad , Jara-Cornejo Eduardo , Khan Sabir
Published: June 2024

Agricultural products are vitally important for sustaining life on earth and their production has notably grown over the years worldwide in general and in Brazil particularly. Elevating agricultural practices consequently leads to a proportionate increase in the usage of pesticides that are crucially important for enhanced crop yield and protection. These compounds have been employed excessively in alarming concentrations, causing the contamination of soil, water, and air. Additionally, they pose serious threats to human health. The current study introduces an innovative tool for producing appropriate materials coupled with an electrochemical sensor designed to measure carbendazim levels. The sensor is developed using a molecularly imprinted polymer (MIP) mounted on a glassy carbon electrode. This electrode is equipped with multi-walled carbon nanotubes (MWCNTs) for improved performance. The combined system demonstrates promising potential for accurately quantifying carbendazim. The morphological characteristics of the synthesized materials were investigated using field emission scanning electron microscopy (FESEM) and the Fourier-transform infrared (FTIR) technique. The analytical curve was drawn using the electrochemical method in the range of 2 to 20 ppm while for HPLC 2–12 ppm; the results are presented as the maximum adsorption capacity of the MIP (82.4%) when compared with NIP (41%) using the HPLC method. The analysis conducted using differential pulse voltammetry (DPV) yielded a limit of detection (LOD) of 1.0 ppm and a repeatability of 5.08% (n = 10). The results obtained from the analysis of selectivity demonstrated that the proposed electrochemical sensor is remarkably efficient for the quantitative assessment of carbendazim, even in the presence of another interferent. The sensor was successfully tested for river water samples for carbendazim detection, and recovery rates ranging from 94 to 101% were obtained for HPLC and 94 to 104% for the electrochemical method. The results obtained show that the proposed electrochemical technique is viable for the application and quantitative determination of carbendazim in any medium.
The Main Barriers Limiting the Development of Smart Buildings
Authors: Affonso Estefany O. T. , Branco Robson R. , Menezes Osvaldo V. C. , Guedes André L. A. , Chinelli Christine K. , Haddad Assed N. , Soares Carlos A. P.
Published: June 2024

Smart buildings play a key role in the complex ecosystem of cities and are often subject to barriers that limit their development. Although identifying these barriers is fundamental to creating an enabling environment for this segment’s expansion, few works aim to identify these challenges. This work has two main objectives: (1) to research the main barriers limiting the development of new smart building projects and (2) to prioritize these barriers from the perspective of professionals with experience in the field. We adopted an exploratory approach common in research that focuses on identifying and prioritizing variables related to a phenomenon, which is based on two main actions: obtaining information through a careful literature review and consulting professionals who work in the concerned field. The results showed that professionals assessed the 23 barriers identified through bibliographic research as important, with the most important being related to lack of qualified professionals, shortage of government policies, higher initial and construction costs, macroeconomic barriers and access to financing, high cost of intelligent systems and technologies, regulatory barriers, lack of knowledge about the current and potential benefits of smart buildings, and more complex design and construction.
Study on Dynamic Characteristics of Long-Span Highway-Rail Double-Tower Cable-Stayed Bridge
Authors: Guo Shijie , Jiang Yuhang , Zhang Wenli , Zeng Yong
Published: June 2024

The long-span dual-purpose highway-rail double-tower cable-stayed bridge has the characteristics of a large span and large load-bearing capacity. Compared with the traditional cable-stayed bridge, its wind resistance and seismic resistance are weaker, and the dynamic characteristics of the bridge are closely related to the wind resistance and seismic bearing capacity of the bridge. This study investigated the influence of the variations of bridge member parameters on the dynamic characteristics of the bridge and then improved the dynamic characteristics of the bridge. To provide the necessary experimental theory for the research work of the long-span dual-purpose highway-rail double-tower cable-stayed bridges, this paper takes the world’s longest span of the dual-purpose highway-rail double-tower cable-stayed bridge as the background, using the finite element analysis software Midas Civil 2022 v1.2 to establish a three-dimensional model of the whole bridge by changing the steel truss beam stiffness, cable stiffness, pylon stiffness, and auxiliary pier position, as well as study the influence of parameter changes on the dynamic characteristics of the bridge. The results show that the dynamic characteristics of the bridge can be enhanced by increasing the stiffness of the steel truss beam, the cable, and the tower. The stiffness of the steel truss beam mainly affects the transverse bending stiffness and flexural coupling stiffness of the bridge. The influence of cable stiffness is weak. The tower stiffness can comprehensively affect the flexural stiffness and torsional stiffness of the bridge. The position of auxiliary piers should be determined comprehensively according to the site conditions. In practical engineering, the stiffness of components can be enhanced according to the weak links of bridges to improve the dynamic characteristics of bridges and save costs.
Toward Cost-Effective Timber Shell Structures through the Integration of Computational Design, Digital Fabrication, and Mechanical Integral ‘Half-Lap’ Joints
Authors: Porras Emerson , Esenarro Doris , Chang Lidia , Morales Walter , Vargas Carlos , Sucasaca Joseph
Published: June 2024

In a global context, where the construction industry is a major source of CO2 emissions and resource use, is dependent on concrete and its risks, and lags behind in digitalization, a clear need arises to direct architecture towards more practical, efficient, and sustainable practices. This research introduces an alternative technique for building timber space structures, aiming to expand its applications in areas with limited access to advanced technologies such as CNCs with more than five axes and industrial robotic arms. This involves reconfiguring economic and ecological constraints to maximize the structural and architectural advantages of these systems. The method develops a parametric tool that integrates computational design and manufacturing based on two-axis laser cutting for shells with segmented hexagonal plywood plates. It uses a modified ‘half-lap joint’ mechanical joint, also made of plywood and without additional fasteners, ensuring a precise and robust connection. The results demonstrate the compatibility of the geometry with two-axis CNC machines, which simplifies manufacturing and reduces the cuts required, thus increasing economic efficiency. The prototype, with a span of 1.5 m and composed of 63 plywood panels and 163 connectors, each 6 mm thick, supported a point load of 0.8 kN with a maximum displacement of 5 mm, weighing 15.1 kg. Assembly and disassembly, carried out by two students, took 5 h and 1.45 h, respectively, highlighting the practicality and accessibility of the method. In conclusion, the technique for building timber shells based on two-axis CNC is feasible and effective, proven by practical experimentation and finite element analysis.
Strategies to Prepare Chitin and Chitosan-Based Bioactive Structures Aided by Deep Eutectic Solvents: A Review
Authors: Durante-Salmerón D. Alonzo , Fraile-Gutiérrez Isabel , Gil-Gonzalo Rubén , Acosta Niuris , Aranaz Inmaculada , Alcántara Andrés R.
Published: June 2024

Chitin and chitosan, abundant biopolymers derived from the shells of crustaceans and the cell walls of fungi, have garnered considerable attention in pharmaceutical circles due to their biocompatibility, biodegradability, and versatile properties. Deep eutectic solvents (DESs), emerging green solvents composed of eutectic mixtures of hydrogen bond acceptors and donors, offer promising avenues for enhancing the solubility and functionality of chitin and chitosan in pharmaceutical formulations. This review delves into the potential of utilizing DESs as solvents for chitin and chitosan, highlighting their efficiency in dissolving these polymers, which facilitates the production of novel drug delivery systems, wound dressings, tissue engineering scaffolds, and antimicrobial agents. The distinctive physicochemical properties of DESs, including low toxicity, low volatility, and adaptable solvation power, enable the customization of chitin and chitosan-based materials to meet specific pharmaceutical requirements. Moreover, the environmentally friendly nature of DESs aligns with the growing demand for sustainable and eco-friendly processes in pharmaceutical manufacturing. This revision underscores recent advances illustrating the promising role of DESs in evolving the pharmaceutical applications of chitin and chitosan, laying the groundwork for the development of innovative drug delivery systems and biomedical materials with enhanced efficacy and safety profiles.
Moderate SCRIB Expression Levels Correlate with Worse Prognosis in OPSCC Patients Regardless of HPV Status
Authors: Lulić Lucija , Šimić Ivana , Božinović Ksenija , Pešut Ena , Manojlović Luka , Grce Magdalena , Dediol Emil , Sabol Ivan , Tomaić Vjekoslav
Published: June 2024

Head and neck cancers rank as the sixth most prevalent cancers globally. In addition to traditional risk factors such as smoking and alcohol use, human papillomavirus (HPV) infections are becoming a significant causative agent of head and neck cancers, particularly among Western populations. Although HPV offers a significant survival benefit, the search for better biomarkers is still ongoing. In the current study, our objective was to investigate whether the expression levels of three PDZ-domain-containing proteins (SCRIB, NHERF2, and DLG1), known HPV E6 cellular substrates, influence the survival of HNSCC patients treated by primary surgery (n = 48). Samples were derived from oropharyngeal and oral cancers, and HPV presence was confirmed by PCR and p16 staining. Clinical and follow-up information was obtained from the hospital database and the Croatian Cancer registry up to November 2023. Survival was evaluated using the Kaplan–Meier method and Cox proportional hazard regression. The results were corroborated through the reanalysis of a comparable subset of TCGA cancer patients (n = 391). In conclusion, of the three targets studied, only SCRIB levels were found to be an independent predictor of survival in the Cox regression analysis, along with tumor stage. Further studies in a more typical Western population setting are needed since smoking and alcohol consumption are still prominent in the Croatian population, while the strongest association between survival and SCRIB levels was seen in HPV-negative cases.
Patient-Derived Conditionally Reprogrammed Cells in Prostate Cancer Research
Authors: Elbialy Abdalla , Kappala Deepthi , Desai Dhruv , Wang Peng , Fadiel Ahmed , Wang Shang-Jui , Makary Mina S. , Lenobel Scott , Sood Akshay , Gong Michael , Dason Shawn , Shabsigh Ahmad , Clinton Steven , Parwani Anil V. , Putluri Nagireddy , Shvets Gennady , Li Jenny , Liu Xuefeng
Published: June 2024

Prostate cancer (PCa) remains a leading cause of mortality among American men, with metastatic and recurrent disease posing significant therapeutic challenges due to a limited comprehension of the underlying biological processes governing disease initiation, dormancy, and progression. The conventional use of PCa cell lines has proven inadequate in elucidating the intricate molecular mechanisms driving PCa carcinogenesis, hindering the development of effective treatments. To address this gap, patient-derived primary cell cultures have been developed and play a pivotal role in unraveling the pathophysiological intricacies unique to PCa in each individual, offering valuable insights for translational research. This review explores the applications of the conditional reprogramming (CR) cell culture approach, showcasing its capability to rapidly and effectively cultivate patient-derived normal and tumor cells. The CR strategy facilitates the acquisition of stem cell properties by primary cells, precisely recapitulating the human pathophysiology of PCa. This nuanced understanding enables the identification of novel therapeutics. Specifically, our discussion encompasses the utility of CR cells in elucidating PCa initiation and progression, unraveling the molecular pathogenesis of metastatic PCa, addressing health disparities, and advancing personalized medicine. Coupled with the tumor organoid approach and patient-derived xenografts (PDXs), CR cells present a promising avenue for comprehending cancer biology, exploring new treatment modalities, and advancing precision medicine in the context of PCa. These approaches have been used for two NCI initiatives (PDMR: patient-derived model repositories; HCMI: human cancer models initiatives).
Renal Vein Thrombosis Secondary to Pyelonephritis: Targeting a Thrombo-Inflammatory Entity
Authors: Kounatidis Dimitris , Papadimitropoulos Vasileios , Vallianou Natalia , Poulaki Aikaterini , Dimitriou Krystalia , Tsiara Ioanna , Avramidis Konstantinos , Alexopoulou Alexandra , Vassilopoulos Dimitrios
Published: June 2024

Renal vein thrombosis (RVT) is a relatively uncommon condition that is most frequently observed in individuals with nephrotic syndrome. While rare, pyelonephritis (PN) may serve as a predisposing factor for secondary RVT. In such cases, one should consider the possibility of RVT when patients fail to respond to appropriate antibiotic treatment. Typically, these patients require additional anticoagulation therapy for a duration of 3 to 6 months, with a generally favorable prognosis. In this report, we present the case of a 74-year-old female who developed RVT due to Klebsiella pneumoniae PN. Additionally, we reviewed 11 cases of PN complicated by RVT, which were documented in the PubMed database over a span of 40 years, emphasizing key elements in diagnostic and therapeutic approaches. Lastly, we elaborated upon the role of thrombo-inflammation, especially in the context of sepsis.
The Wannier-Mott Exciton, Bound Exciton, and Optical Phonon Replicas of Single-Crystal GaSe
Authors: Le Long V. , Huong Tran Thi Thu , Nguyen Tien-Thanh , Nguyen Xuan Au , Nguyen Thi Huong , Cho Sunglae , Kim Young Dong , Kim Tae Jung
Published: June 2024

We report the absorption and photoluminescence spectra of GaSe single crystals in the near-edge region. The temperatures explored the range from 17 to 300 K. Specifically, at a temperature of 17 K, the photoluminescence spectrum reveals an interesting phenomenon: the Wannier-Mott exciton separates into two states. These states are a triplet state with an energy of 2.103 eV and a singlet state with an energy of 2.109 eV. The energy difference between these two states is 6 meV. Furthermore, the bound exciton (BX) can be localized at an energy of 2.093 eV. It is worth noting that its phonon replicas (BX-nLO) can be clearly distinguished up to the fourth order. Interestingly, the energy gaps between these replicas exhibit a consistent spacing of 7 ± 0.5 meV. This intriguing finding suggests a high-quality crystalline structure as well as a strong coupling between the phonon and BX-nLO. Additionally, at low temperatures, both the ground state (n = 1) at 2.11 eV and the excited state (n = 2) at 2.127 eV of free excitons can be observed.
A Comprehensive Review and Insights into the New Entity of Differentiated High-Grade Thyroid Carcinoma
Authors: Harahap Agnes Stephanie , Roren Regina Stefani , Imtiyaz Shofiyya
Published: June 2024

Differentiated high-grade thyroid carcinoma (DHGTC) is a new subset within the spectrum of thyroid malignancies. This review aims to provide a comprehensive overview of DHGTC, focusing on its historical perspective, diagnosis, clinical characteristics, molecular profiles, management, and prognosis. DHGTC demonstrates an intermediate prognosis that falls between well-differentiated thyroid carcinoma and anaplastic thyroid carcinoma. Previously unenumerated, this entity is now recognized for its significant impact. Patients with DHGTC often present at an older age with advanced disease and exhibit aggressive clinical behavior. Molecularly, DHGTC shares similarities with other thyroid malignancies, harboring driver mutations such as BRAFV600E and RAS, along with additional late mutations. The unique behavior and histologic features of DHGTC underscore the necessity of precise classification for prognostication and treatment selection. This highlights the critical importance of accurate diagnosis and recognition by pathologists to enrich future research on this entity further.
Incidence of Carotid Blowout Syndrome in Patients with Head and Neck Cancer after Radiation Therapy: A Cohort Study
Authors: Jiang Jian-Lin , Chang Joseph Tung-Chieh , Yeh Chih-Hua , Chang Ting-Yu , Huang Bing-Shen , Sung Pi-Shan , Lin Chien-Yu , Fan Kang-Hsing , Wei Yi-Chia , Liu Chi-Hung
Published: June 2024

Carotid blowout syndrome (CBS) is a rare yet life-threatening complication that occurs after radiation therapy (RT). This study aimed to determine the incidence of CBS in patients with head and neck cancer (HNC) undergoing contemporary RT and to explore potential discrepancies in the risk of CBS between nasopharyngeal cancer (NPC) and non-NPC patients. A total of 1084 patients with HNC who underwent RT between 2013 and 2023 were included in the study. All patients were under regular follow-ups at the radio-oncology department, and underwent annual contrast-enhanced computed tomography and/or magnetic resonance imaging for cancer recurrence surveillance. Experienced neuroradiologists and vascular neurologists reviewed the recruited patients’ images. Patients were further referred to the neurology department for radiation vasculopathy evaluation. The primary outcome of this study was CBS. Patients were categorized into NPC and non-NPC groups and survival analysis was employed to compare the CBS risk between the two groups. A review of the literature on CBS incidence was also conducted. Among the enrolled patients, the incidence of CBS in the HNC, NPC, and non-NPC groups was 0.8%, 0.9%, and 0.7%, respectively. Kaplan–Meier analysis revealed no significant difference between the NPC and non-NPC groups (p = 0.34). Combining the findings for our cohort with those of previous studies revealed that the cumulative incidence of CBS in patients with HNC is 5% (95% CI = 3–7%) after both surgery and RT, 4% (95% CI = 2–6%) after surgery alone, and 5% (95% CI = 3–7%) after RT alone. Our findings indicate a low incidence of CBS in patients with HNC undergoing contemporary RT. Patients with NPC may have a CBS risk close to that of non-NPC patients. However, the low incidence of CBS could be a potentially cause of selection bias and underestimation bias.
Derivation of Bose’s Entropy Spectral Density from the Multiplicity of Energy Eigenvalues
Authors: Spalvieri Arnaldo
Published: June 2024

The modern textbook analysis of the thermal state of photons inside a three-dimensional reflective cavity is based on the three quantum numbers that characterize photon’s energy eigenvalues coming out when the boundary conditions are imposed. The crucial passage from the quantum numbers to the continuous frequency is operated by introducing a three-dimensional continuous version of the three discrete quantum numbers, which leads to the energy spectral density and to the entropy spectral density. This standard analysis obscures the role of the multiplicity of energy eigenvalues associated to the same eigenfrequency. In this paper we review the past derivations of Bose’s entropy spectral density and present a new analysis of energy spectral density and entropy spectral density based on the multiplicity of energy eigenvalues. Our analysis explicitly defines the eigenfrequency distribution of energy and entropy and uses it as a starting point for the passage from the discrete eigenfrequencies to the continuous frequency.
Code Similarity Prediction Model for Industrial Management Features Based on Graph Neural Networks
Authors: Li Zhenhao , Lei Hang , Ma Zhichao , Zhang Fengyun
Published: June 2024

The code of industrial management software typically features few system API calls and a high number of customized variables and structures. This makes the similarity of such codes difficult to compute using text features or traditional neural network methods. In this paper, we propose an FSPS-GNN model, which is based on graph neural networks (GNNs), to address this problem. The model categorizes code features into two types, outer graph and inner graph, and conducts training and prediction with four stages—feature embedding, feature enhancement, feature fusion, and similarity prediction. Moreover, differently structured GNNs were used in the embedding and enhancement stages, respectively, to increase the interaction of code features. Experiments with code from three open-source projects demonstrate that the model achieves an average precision of 87.57% and an F0.5 Score of 89.12%. Compared to existing similarity-computation models based on GNNs, this model exhibits a Mean Squared Error (MSE) that is approximately 0.0041 to 0.0266 lower and an F0.5 Score that is 3.3259% to 6.4392% higher. It broadens the application scope of GNNs and offers additional insights for the study of code-similarity issues.
Promoting Social Skills among Generation Alpha Learners with Special Needs
Authors: Flavian Heidi
Published: June 2024

Since digital learning and communication tools are ubiquitous, educators no longer need to teach Generation Alpha (GA) learners how to approach and use them. Nevertheless, while digital tools provide numerous advantages, researchers claim that the development of social skills is challenging for GA learners, given their lack of social experiences and interactions. These challenges are greater among learners with special needs (SNs). This study examines teachers’ attitudes toward the integration of digital tools promoting social skills among GA learners with SNs, rather than focusing on academic skills. Twenty-one semi-structured interviews underwent qualitative analysis. Participants emphasized both the advantages and challenges of using digital tools and shared their perspectives regarding the possible effective use of these tools among learners with SNs.
“Two Sides of the Same Coin”: Benefits of Science–Art Collaboration and Field Immersion for Undergraduate Research Experiences
Authors: Sandrin Susannah , Ball Becky , Arora Ishanshika
Published: June 2024

This study examined how incorporating art into an upper-level undergraduate field-based ecology research course influenced students’ communication and collaboration skills, their career goals, and how they conceptualized the scientific method. Student pairs designed an independent research study that used artwork and a scientific research poster to disseminate their findings at an end-of-term exhibit. Students enrolled in either a local or a (subsidized) travel abroad section of the course. Students in both sections found new or deeper connections between art and science, developed a more sophisticated understanding of the science method, became more confident with their science skills, and reported an expanded perspective on their future careers (often including field work and a wider geographic job search). Science–art student teams indicated they wanted more opportunities for collaborative work in the future, and that their final products were more professional due to their collaborations, as compared to science–science teams. Additionally, the travel abroad students benefitted from experiencing new ecosystems and cultures, from working with science and art professionals from other countries, and from working in an isolated field station without distractions.
A Long-Term Study on the Effect of a Professional Development Program on Science Teachers’ Inquiry
Authors: Tsaliki Christina , Papadopoulou Penelope , Malandrakis Georgios , Kariotoglou Petros
Published: June 2024

In this study we explore the effect of a professional development (PD) program on four science teachers’ views and practices nearly a year after its completion, regarding inquiry implementation in everyday school practice. The PD program aimed to familiarize participants with current trends in science education (SE), putting emphasis on the inquiry approach. The basic research question guiding this study is whether science teachers’ inquiry practices and views changed, and to which extent, long after their participation in the PD program. Teachers’ practices were recorded, both during and after the PD, through non-participatory observation and were analysed through a semi-quantitative method. Teachers’ views were also recorded both during and after PD through structured questionnaires and reflective interviews, producing qualitative data that were analysed. Findings are encouraging concerning the preservation of guided inquiry practices obtained during the program, while more open inquiry practices proved to be limited. Teachers’ views concerning inquiry remained positive, also maintaining their innovative character.
“I Tell Them Generics, but Not the Specifics”: Exploring Tensions Underlying Familial Support for First-Generation Latinx Undergraduate Students
Authors: Cuevas Stephany
Published: June 2024

Families continue to play an essential role in the experiences of first-generation Latinx undergraduate students and can serve as powerful partners to support student retention and socioemotional wellbeing. This qualitative phenomenological study uses the notion of emerging adulthood to explore how first-generation Latinx undergraduate students (n = 16) conceptualize their families’ role in their college education. Specifically, this study shows that while students describe feeling supported by their families, they also experience distinct and unique tensions tied to this support, which students associate with their first-generation student status. These tensions include (1) the family’s unfamiliarity with college culture; (2) bidirectional behaviors of protection from stress and worry; and (3) continued family interactions. These findings, or tensions, are essential to understand and address. Doing so can improve the nature of familial support for first-generation Latinx undergraduate students by leading to better family—student relationships, family—institutional relationships, and student academic and non-academic outcomes.
Folded Narrow-Band and Wide-Band Monopole Antennas with In-Plane and Vertical Grounds for Wireless Sensor Nodes in Smart Home IoT Applications
Authors: Honari Mohammad Mahdi , Javadi Seyed Parsa , Mirzavand Rashid
Published: June 2024

This article presents two monopole antennas with an endfire radiation pattern in the UHF band that can be installed on dry walls or metallic cabinets as a part of wireless sensor nodes, making them a suitable choice for smart home applications, such as the wireless remote control of house appliances. Two different antennas are proposed to cover the RFID bands of North America (902–928 MHz) and worldwide (860–960 MHz). The antennas have wide horizontal radiation patterns that provide great reading coverage in their communication with a base station placed at a certain distance from the antennas. The structures have two ground planes, one in-plane and the other vertical. The vertical ground helps the antenna to have a directive radiation and also makes it easily installed on walls. The antenna feeding line lies over the vertical ground substrate. The maximum dimensions of the narrow-band antenna are L × W = 0.3λ × 0.14λ, and those for the wide-band antenna are L × W = 0.39λ × 0.14λ. The measured results show that the bandwidth of the proposed antennas for the North America and worldwide RFID bands are from 902 MHz to 939 MHz and 822 MHz to 961 MHz, with maximum gains of 4.2 dBi and 4.9 dBi, respectively.
Full-Duplex Unmanned Aerial Vehicle Communications for Cellular Spectral Efficiency Enhancement Utilizing Device-to-Device Underlaying Structure
Authors: Zhou Yuetian , Li Yang
Published: June 2024

Unmanned aerial vehicle (UAV) communications have gained recognition as a promising technology due to their unique characteristics of rapid deployment and flexible configuration. Meanwhile, device-to-device (D2D) and full-duplex (FD) technologies have emerged as promising methods for enhancing spectral efficiency and offloading traffic. One significant advantage of UAVs is their ability to partition suitable D2D pairs to increase cell capacity. In this paper, we present a novel network model in which UAVs are considered D2D pairs underlaying cellular networks, integrating FD into the communication links between UAVs to improve spectral efficiency. We then investigate a resource allocation problem for the proposed FD-UAV D2D underlaying structure model, with the objective of maximizing the system’s sum rate. Specifically, the UAVs in our model operate in full-duplex mode as D2D users (DUs), allowing the reuse of both the uplink and downlink subcarrier resources of cellular users (CUs). This optimization challenge is formulated as a mixed-integer nonlinear programming problem, known for its NP-hard and intractable nature. To address this issue, we propose a heuristic algorithm (HA) that decomposes the problem into two steps: power allocation and user pairing. The optimal power allocation is solved as a nonlinear programming problem by searching among a finite set, while the user pairing problem is addressed using the Kuhn–Munkres algorithm. The numerical results indicate that our proposed FD-MaxSumCell-HA (full-duplex UAVs maximizing the cell sum rate with a heuristic algorithm) scheme for FD-UAV D2D underlaying models outperforms HD-UAV underlaying cellular networks, with improved access rates for UAVs in FD-MaxSumCell-HA compared to HD-UAV networks.
Designing Multifunctional Multiferroic Composites for Advanced Electronic Applications
Authors: Pereira Lilian Nunes , Pastoril Julio Cesar Agreira , Dias Gustavo Sanguino , Santos Ivair Aparecido dos , Guo Ruyan , Bhalla Amar S. , Cotica Luiz Fernando
Published: June 2024

This paper presents a novel approach for the fabrication of magnetoelectric composites aimed at enhancing cross-coupling between electrical and magnetic phases for potential applications in intelligent sensors and electronic components. Unlike previous methodologies known for their complexity and expense, our method offers a simple and cost-effective assembly process conducted at room temperature, preserving the original properties of the components and avoiding undesired phases. The composites, composed of PZT fibers, cobalt (CoFe2O4), and a polymeric resin, demonstrate the uniform distribution of PZT-5A fibers within the cobalt matrix, as demonstrated by scanning electron microscopy. Detailed morphological analyses reveal the interface characteristics crucial for determining overall performance. Dielectric measurements indicate stable behaviors, particularly when PZT-5A fibers are properly poled, showcasing potential applications in sensors or medical devices. Furthermore, H-dependence studies illustrate strong magnetoelectric interactions, suggesting promising avenues for enhancing coupling efficiency. Overall, this study lays the basic work for future optimization of composite composition and exploration of its long-term stability, offering valuable insights into the potential applications of magnetoelectric composites in various technological domains.
Fusing Design and Machine Learning for Anomaly Detection in Water Treatment Plants
Authors: Raman Gauthama , Mathur Aditya
Published: June 2024

Accurate detection of process anomalies is crucial for maintaining reliable operations in critical infrastructures such as water treatment plants. Traditional methods for creating anomaly detection systems in these facilities typically focus on either design-based strategies, which encompass physical and engineering aspects, or on data-driven models that utilize machine learning to interpret complex data patterns. Challenges in creating these detectors arise from factors such as dynamic operating conditions, lack of design knowledge, and the complex interdependencies among heterogeneous components. This paper proposes a novel fusion detector that combines the strengths of both design-based and machine learning approaches for accurate detection of process anomalies. The proposed methodology was implemented in an operational secure water treatment (SWaT) testbed, and its performance evaluated during the Critical Infrastructure Security Showdown (CISS) 2022 event. A comparative analysis against four commercially available anomaly detection systems that participated in the CISS 2022 event revealed that our fusion detector successfully detected 19 out of 22 attacks, demonstrating high accuracy with a low rate of false positives.
Advanced Wireless Sensor Networks: Applications, Challenges and Research Trends
Authors: Kandris Dionisis , Anastasiadis Eleftherios
Published: June 2024

A typical wireless sensor network (WSN) contains wirelessly interconnected devices, called sensor nodes, which have sensing, processing, and communication abilities and are disseminated within an area of interest [...]
Polarization-Based Two-Stage Image Dehazing in a Low-Light Environment
Authors: Zhang Xin , Wang Xia , Yan Changda , Jiao Gangcheng , He Huiyang
Published: June 2024

Fog, as a common weather condition, severely affects the visual quality of images. Polarization-based dehazing techniques can effectively produce clear results by utilizing the atmospheric polarization transmission model. However, current polarization-based dehazing methods are only suitable for scenes with strong illumination, such as daytime scenes, and cannot be applied to low-light scenes. Due to the insufficient illumination at night and the differences in polarization characteristics between it and sunlight, polarization images captured in a low-light environment can suffer from loss of polarization and intensity information. Therefore, this paper proposes a two-stage low-light image dehazing method based on polarization. We firstly construct a polarization-based low-light enhancement module to remove noise interference in polarization images and improve image brightness. Then, we design a low-light polarization dehazing module, which combines the polarization characteristics of the scene and objects to remove fog, thereby restoring the intensity and polarization information of the scene and improving image contrast. For network training, we generate a simulation dataset for low-light polarization dehazing. We also collect a low-light polarization hazy dataset to test the performance of our method. Experimental results indicate that our proposed method can achieve the best dehazing effect.
Effective Denoising Algorithms for Converting Indoor Blueprints Using a 3D Laser Scanner
Authors: Yoon Sehyeon , Choi Sanghyun , An Jhonghyun
Published: June 2024

This paper focuses on converting complex 3D maps created by LiDAR and SLAM technology into simple 2D maps to make them easier to understand. While 3D maps provide a lot of useful details for robots and computer programs, they can be difficult to read for humans who are used to flat maps. We developed a new system to clean up these 3D maps and convert them into intuitive and accurate 2D maps. The system uses three steps designed to correct different kinds of errors found in 3D LiDAR scan data: clustering-based denoising, height-based denoising, and Statistical Outlier Removal. In particular, height-based denoising is the method we propose in this paper, an algorithm that leaves only indoor structures such as walls. The paper proposes an algorithm that considers the entire range of the point cloud, rather than just the points near the ceiling, as is the case with existing methods, to make denoising more effective. This makes the final 2D map easy to understand and useful for building planning or emergency preparedness. Our main goal is to map the interior of buildings faster and more effectively, creating 2D drawings that reflect accurate and current information. We want to make it easier to use LiDAR and SLAM data in our daily work and increase productivity.