bluuebunny/crossref_metadata_2025 huggingface dataset:
The Motor Optimality Score—Revised Improves Early Detection of Unilateral Cerebral Palsy in Infants with Perinatal Cerebral Stroke
Authors: Bertoncelli Natascia , Corso Lucia , Bedetti Luca , Della Casa Elisa Muttini , Roversi Maria Federica , Toni Greta , Pugliese Marisa , Guidotti Isotta , Miselli Francesca , Lucaccioni Laura , Rossi Cecilia , Berardi Alberto , Lugli Licia
Published: August 2024

Background: Neonatal cerebral stroke includes a range of focal and multifocal ischemic and hemorrhagic brain lesions, occurring in about one of 3000 live births. More than 50% of children with neonatal stroke develop adverse outcomes, mainly unilateral cerebral palsy. Asymmetries in segmental movements at three months have been proven to be an early sign of CP in infants with unilateral brain damage. Recognition of additional early signs could enhance prognostic assessment and enable an early and targeted intervention. Aim: The aim of the study was to assess early signs of CP in infants with arterial cerebral stroke through the General Movements Assessment and the Motor Optimality Score—Revised (MOS-R). Method: Twenty-four infants born at term (12 females and 12 males) diagnosed with ACS, and 24 healthy infants (16 females and 8 males) were assessed. The GMs (fidgety movements) and MOS-R were assessed from videos recorded at 11–14 weeks of post-term age. Cognitive and motor outcomes were assessed at 24 months using the Griffiths III developmental quotient and Amiel-Tison neurological examination. The gross motor function classification system expanded and revised (GMFCS-E&R) was adopted to categorize CP. Results: Among infants with ACS, 21 (87.5%) developed unilateral CP. Most of them showed non-disabling CP (14 had GMFCS-E&R grade 1 [66.6%], 6 grade 2 [28.6%], and 1 grade 5 [4.8%]). Fidgety movements (FMs) were absent in 17 (70.8%), sporadic in 4 (16.7%) infants, and normal in 3 (12.5%). Segmental movement asymmetry was found in 22/24 (91.7%). According to the MOS-R, motor items (kicking, mouth movements), postural patterns (midline centered head, finger posture variability), and movement character (monotonous and stiff) were statistically different among infants with ACS and healthy infants. The MOS-R median global score was lower in the group with ACS compared to the control group (6 vs 26; p < 0.01). FMs, segmental movement asymmetry, and MOS-R global score were significantly correlated with abnormal outcome. MOS-R global scores less than or equal to 13 had 100% specificity and sensitivity in predicting GMFCS-E&R grade ≥ 2 CP in infants with ACS. Conclusions: The rate of CP was high among infants with ACS, but in most cases it showed low GMFCS-E&R grades. The study highlighted a significant correlation between MOS-R, together with absent FMs and unilateral CP in infants with ACS. Moreover, the MOS-R showed high sensitivity and specificity in the prediction of CP. Combined assessment of FMs and MOS-R could help to better identify infants at high risk of developing UCP in a population of infants with ACS. Early identification of precocious signs of unilateral CP is fundamental to providing an early individualized intervention.
A Prediction about Radio Frequency Envelope Detectors for Implementing a 2.4 GHz Rectenna for IEEE 802.15.4 with MOS Transistors
Authors: Barboni Leonardo
Published: August 2024

This study introduces a rectenna, functioning as an RF envelope detector, utilizing a 16 nm bulk MOS transistor (metal-oxide-semiconductor field-effect transistor) for nonlinear detection. A circuit architecture is presented alongside a detailed design methodology and simulations. The detector efficiently demodulates a 2.4 GHz OOK (On/Off Keying) encoded signal, comprising a 32-bit word, within 320 μs. Remarkably, the circuit operates passively, requiring no voltage supply or bias current, and functions effectively with −53 dBm input power at the antenna. This capability enables the decoding of 32-bit unsigned integer radio packets as a wakeup radio event. The effectiveness of the envelope detector is substantiated through comprehensive simulations.
Influence of Graphite and Zirconia Addition on the Tribological Properties of Plasma-Sprayed Alumina Coatings
Authors: Marcinauskas Liutauras , Ratautaitė Karina , Kavaliauskas Žydrūnas , Žunda Audrius , Kėželis Romualdas , Aikas Mindaugas
Published: August 2024

Al2O3, Al2O3-graphite and Al2O3-ZrO2 coatings were formed on the C45 steel rolls using atmospheric plasma spraying. The influence of graphite and zirconia addition on the surface morphology, phase composition and tribological properties under dry sliding conditions using 30 N load were analyzed. It was found that the addition of graphite or ZrO2 slightly affected the fraction of the α-Al2O3 and γ-Al2O3 phases in the alumina coatings. The highest mass loss rate (~8.84 × 10−4 g/s) was obtained for the friction pair of C45 steel roll and steel plate. The friction coefficient of the Al2O3-graphite coating was slightly lower (up to 7%) compared to the coating of Al2O3-ZrO2. However, the friction pair of Al2O3-ZrO2 coating and steel plate demonstrated the highest wear resistance under dry sliding conditions. The increase in the wear resistance of the Al2O3-graphite and Al2O3-ZrO2 coatings is due to the formation of tribofilm in the sliding contact zone.
Data-Driven Optimization of Plasma Electrolytic Oxidation (PEO) Coatings with Explainable Artificial Intelligence Insights
Authors: Fernández-López Patricia , Alves Sofia A. , Rogov Aleksey , Yerokhin Aleksey , Quintana Iban , Duo Aitor , Aguirre-Ortuzar Aitor
Published: August 2024

PEO constitutes a promising surface technology for the development of protective and functional ceramic coatings on lightweight alloys. Despite its interesting advantages, including enhanced wear and corrosion resistances and eco-friendliness, the industrial implementation of PEO technology is limited by its relatively high energy consumption. This study explores the development and optimization of novel PEO processes by means of machine learning (ML) to improve the coating thickness. For this purpose, ML models random forest and XGBoost were employed to predict the thickness of the developed PEO coatings based on the key process variables (frequency, current density, and electrolyte composition). The predictive performance was significantly improved by including the composition of the used electrolyte in the models. Furthermore, Shapley values identified the pulse frequency and the TiO2 concentration in the electrolyte as the most influential variables, with higher values leading to increased coating thickness. The residual analysis revealed a certain heteroscedasticity, which suggests the need for additional samples with high thickness to improve the accuracy of the model. This study reveals the potential of artificial intelligence (AI)-driven optimization in PEO processes, which could pave the way for more efficient and cost-effective industrial applications. The findings achieved further emphasize the significance of integrating interactions between variables, such as frequency and TiO2 concentration, into the design of processing operations.
The Effect of Proportional, Proportional-Integral, and Proportional-Integral-Derivative Controllers on Improving the Performance of Torsional Vibrations on a Dynamical System
Authors: Alluhydan Khalid , EL-Sayed Ashraf Taha , El-Bahrawy Fatma Taha
Published: August 2024

The primary goal of this research is to lessen the high vibration that the model causes by using an appropriate vibration control. Thus, we begin by implementing various controller types to investigate their impact on the system’s reaction and evaluate each control’s outcomes. The controller types are presented as proportional (P), proportional-integral (PI), and proportional-integral-derivative (PID) controllers. We employed PID control to regulate the torsional vibration behavior on a dynamical system. The PID controller aims to increase system stability after seeing the impact of P and PI control. This kind of control ensures that there are no unstable components in the system. By using the multiple time scale perturbation (MTSP) technique, a first-order approximate solution has been obtained. Using the frequency response function approach, the stability and steady-state response of the system at the primary resonance scenario (Ω1≅ω1,Ω2≅ω2) are considered as the worst resonance and addressed. Additionally examined are the nonlinear dynamical system’s chaotic response and the numerical solution for various parameter values. The MATLAB programs are utilized to attain simulation outcomes.
Force-Directed Immersive 3D Network Visualization
Authors: Brezani Alexander , Kostolny Jozef , Zabovsky Michal
Published: August 2024

Network visualization, in mathematics often referred to as graph visualization, has evolved significantly over time, offering various methods to effectively represent complex data structures. New methods and devices advance the possibilities of visualization both from the point of view of the quality of displayed information and of the possibilities of visualizing a larger amount of data. Immersive visualization includes the user directly in presented visual representation but requires a native 3D environment for direct interaction with visualized information. This article describes an approach to creating a force-directed immersive 3D network visualization algorithm available for application in immersive environments, such as a cave automatic virtual environment or virtual reality. The algorithm aims to address the challenge of creating visually appealing and easily interpretable visualizations by utilizing 3D space and the Unity engine. The results show successfully visualized data and developed interactive visualization methods, overcoming limitations of basic force-directed implementations. The main contribution of the presented research is the force-directed algorithm with springs and controlled placement as an immersive visualization technique that combines the use of springs and attractive forces to stabilize a network in a 3D environment.
Synthesis and Characterization of Iron–Sillenite for Application as an XRD/MRI Dual-Contrast Agent
Authors: Vistorskaja Diana , Yang Jen-Chang , Wu Yu-Tzu , Chang Liang-Yu , Lu Po-Wen , Zarkov Aleksej , Grigoraviciute Inga , Kareiva Aivaras
Published: August 2024

In the present work, iron–sillenite (Bi25FeO40) was synthesized using a simple solid-state reaction method and characterized. The effects of the synthesis conditions on the phase purity of Bi2O3/Fe3O4, morphological features, and possible application as an XRD/MRI dual-contrast agent were investigated. For the synthesis, the stoichiometric amounts of Bi2O3 and Fe3O4 were mixed and subsequently milled in a planetary ball mill for 10 min with a speed of 300 rpm. The milled mixture was calcined at various temperatures (550 °C, 700 °C, 750 °C, 800 °C, and 850 °C) for 1 h in air at a heating rate of 5 °C/min. For phase identification, powder X-ray diffraction (XRD) analysis was performed and infrared (FTIR) spectra were recorded. The surface morphology of synthesized samples was studied by field-emission scanning electron microscopy (FE-SEM). For the radiopacity measurements, iron–sillenite specimens were synthesized at different temperatures and mixed with different amounts of BaSO4 and Laponite solution. It was demonstrated that iron–sillenite Bi25FeO40 possessed sufficient radiopacity and could be a potential candidate to meet the requirements of its application as an XRD/MRI dual-contrast agent.
Influence of Graphene Oxide Concentration and Ultrasonication Energy on Fracture Behavior of Nano-Reinforced Cement Pastes
Authors: Ríos José D. , Leiva Carlos , Martinez de la Concha Antonio , Ariza María Pilar , Cifuentes Héctor
Published: August 2024

The aim of this study is twofold. First, to assess the effect of the sonication process on the optimal dispersion of GO sheets for nanostructural reinforcement of cement pastes, as there is currently no clear criterion on this effect in the literature. For this purpose, in the first stage, the GO content in distilled water was fixed at 0.03% by weight, and the sheets were dispersed using different levels of ultrasonic energy, ranging from 0 J/mL to 2582 J/mL. In the second stage, to analyze the modification of pore structure due to the addition of GO sheets in different ratios (0–0.06% by weight) and its relationship with the mechanical and fracture properties of reinforced cement pastes. According to the results, it has been determined that the incorporation of GO sheets into the matrix alters the mechanical and fracture behavior, varying depending on matrix pore size and GO particle size. The addition of GO leads to a reduction in the average size of macropores (greater than 8 µm) of 13% for a dosage of 0.45% in weight and micropores (between 8 and 0.5 µm) in a 64% for the same composition with non-sonicated GO, although the total volume of pores in these ranges only decreased slightly. This reduction is more pronounced when the GO has not been sonicated and has larger particle size. Sonicated GO primarily modifies the range of capillary pores (<0.5 µm). The addition of GO with the highest degree of dispersion (465 nm) did not show significant improvements in compressive strength or Young’s modulus, as the cement used contains a significant volume of macropores that are not substantially reduced in any composition. Adding 0.030% ultrasonicated GO achieved a 7.8% increase in fracture energy, while an addition of 0.045% resulted in a 13.3% decrease in characteristic length, primarily due to the effect of capillary and micropores.
An Enhanced Deep Learning-Based Pharmaceutical Crystal Detection with Regional Filtering
Authors: Kang Yanlei , Duan Zhenyu , Tong Tianlei , Hu Xiurong , Zhang Xiongtao , Hu Hailong , Li Zhong
Published: August 2024

In the process of pharmaceutical crystallization, the automatic detection of crystal shapes in images is important since controlling the morphology of the crystals improves the quality of pharmaceutical crystals. In this paper, a novel image detection method called RECDet is proposed. It leverages an automatically adapted binary image to bypass background regions, thereby reducing the detection field. In addition, the method greatly reduces the training time while improving the detection accuracy by using a specially designed detection box for the crystal shape. The performance of our model is evaluated through experimental analysis on a publicly available glutamate crystal dataset and a self-made entecavir pharmaceutical crystal dataset. Experimental results show that RECDet improves the accuracy of prediction bounding boxes by more than 2% compared to other popular models and achieves a classification accuracy of 98%. It can be used as a promising tool in the application of pharmaceutical crystallization control.
Variation in Phenology and Morphological Traits of Seed-Propagated Laggera alata and Laggera crispata Forms
Authors: Nkosi Noluthando Nonjabulo , Zharare Godfrey Elijah , Zimudzi Clemence , Stedje Brita , Ntuli Nontuthuko Rosemary
Published: August 2024

The phenological and morphological variation studies among forms of Laggera Sch. Bip. Ex. Benth. and Hook species are limited, despite the medicinal use of the genus. Therefore, this study aimed to document phenology and morphological variation in cultivated populations of Laggera alata and Laggera crispata forms from seedling to maturity. The forms were categorized as Laggera alata with a small capitulum (LA-SC), Laggera alata with a large capitulum (LA-BC), Laggera crispata from South Africa (LC-SA), and Laggera crispata from Zimbabwe (LC-ZIM). Seeds were germinated in Petri dishes, transplanted to plug trays, and later to field plots at 60 days. Phenological events were recorded when observed in at least one plant. Twelve qualitative and four morphometric traits were measured monthly on five plants per Laggera form. Analysis of variance and Tukey’s Honestly Significant Difference test (p < 0.05) were used for data analysis. Results indicated significant variation in phenology, qualitative traits, leaf traits, plant height, and stem diameter both within and between L. crispata and L. alata forms. Morphometric traits, such as leaf size and the number of leaves per plant, were identified as key descriptors for differentiating L. alata forms. These findings provide a foundation for the introduction of Laggera forms into farming systems for medicinal and commercial purposes.
Resprouting Control of Ailanthus altissima by Means of Cut and Stump Covering: Experimental Evidence for a Promising Technique
Authors: Arduini Iduna , Pampana Silvia , Alessandrini Viola
Published: August 2024

Ailanthus altissima is an invasive tree threatening the biodiversity in natural and disturbed habitats of temperate regions, primarily because of its high resprouting vigor. To test the effect of light exclusion on stem and root sprouting, black covers were applied on the cut stumps of 3-year-old saplings grown in pots. The treatments were as follows: SL, stumps exposed to light; SH, only stumps covered; SPH, the entire pot covered; C, intact control plants. The covers were removed when the root sprouts appeared. The emergence of stem and root sprouts was checked weekly, and their number and biomass were determined at the growth peak (cut I and III) and the end (cut II and IV) of two seasons after cutting. Stem sprouts were produced only in the first growth season in SL and SH and never in SPH and the controls. The number and biomass of the root sprouts were the highest in SH at cut I and in SL in the following cuts. In SH, the sprouting ceased completely after cut I, suggesting a rapid consumption of root reserves, while in SL and SPH, repeated cutting progressively reduced the sprouting vigor. We concluded that covering the stems after cutting is a promising technique to control ailanthus resprouting without the use of herbicides.
Hoefkenia hunsrueckensis, a New Genus and Species from Europe, and the Identity of Virescentia vogesiaca (F.W.Schultz ex Skuja) Necchi, D.C.Agostinho & M.L.Vis (Batrachospermales, Rhodophyta)
Authors: Fischer Eberhard , Killmann Dorothee , Gerlach Johanna , Schütte Claudia , Leh Burkhard , Müller Kai , Quandt Dietmar
Published: August 2024

Freshwater red algae from Hunsrück-Hochwald National Park previously identified as Virescentia vogesiaca are described as Hoefkenia hunsrueckensis gen. et sp. nov. They cluster in the phylogenetic tree together with Kumanoa and form its sister clade. Virescentia is rendered monophyletic by exclusion of these samples. The taxonomic history of Virescentia vogesiaca is described. The species was named by Skuja referring to the description of Batrachospermum vagum var. flagelliforme Sirodot and the specimens all come from Western France and Spain. The name Batrachospermum vogesiacum was erroneously applied referring to a specimen from the North Vosges close to Germany collected and annotated by F.W. Schultz and representing the new Hoefkenia hunsrueckensis. However, this specimen was never cited in the protologue of Virescentia vogesiaca. We provide evidence that the real Virescentia vogesiaca is endemic to Western France and Spain, and that Hoefkenia hunsrueckensis is restricted to Eastern Belgium, Eastern France and SW Germany, differing in morphological and molecular characters.
The Importance of Topographical Recognition of Pulmonary Arteries in Diagnostics and Treatment of CTEPH, Based on an Analysis of a Dissected Case Model—A Pilot Study
Authors: Zicans Matiss , Kazoka Dzintra , Pilmane Mara , Skride Andris
Published: August 2024

Background: Knowledge of the anatomy of pulmonary arteries is essential in many invasive procedures concerning pulmonary circulation. In the diagnosis and treatment of chronic thromboembolic pulmonary hypertension (CTEPH), two-dimensional (2D) pulmonary angiography is used. Recognizing the topographic course of the pulmonary arteries and understanding the status in three dimensions (3D) is paramount. This study aimed to evaluate and describe the branching variant of pulmonary arteries in a single case, as well as morphological parameters of the segmental arteries, like length, diameter and branching angles. Methods: One pair of embalmed human cadaver lungs was dissected by a scalpel and surgical forceps and was measured up to the subsegmental arteries. Results: The diameters (ranging from 3.04 to 9.29 mm) and lengths (ranging from 9.09 to 53.91 mm) of the pulmonary segmental arteries varied. The proximal branching angles were wide and close to perpendicular, while distally, the angles between the segmental and subsegmental arteries were narrower (30–45°). Upon evaluating the branching, rare variations were identified and delineated, notably in the lower lobes of both lungs. Conclusions: Utilizing knowledge and data in clinical settings is instrumental for effectively diagnosing and treating CTEPH. Further research is required to explore the complications in invasive procedures related to various anatomical variations.
A 10-Year Retrospective Cohort Study of Endometrial Cancer Outcomes and Associations with Lymphovascular Invasion: A Single-Center Study from Germany
Authors: Nienhaus Alexandra , Rajakulendran Rahavie , Bernad Elena
Published: August 2024

This 10-year retrospective cohort study at a single-center clinic in Germany aimed to analyze the outcomes of endometrial cancer patients and explore the impact of lymphovascular invasion (LV) on patient outcomes and disease-free survival (DFS). Identifying correlations among demographic data, tumor characteristics, treatment modalities, and survival outcomes could enhance patient management and improve survival rates. The study encompassed patients diagnosed and treated for endometrial cancer from January 2010 to December 2020. Clinical and pathological data were extracted from medical records for 311 patients, focusing on variables such as age, histological type, tumor grade, type of surgical treatment, and adjuvant therapies. Survival analysis was conducted using the Kaplan–Meier method and multivariate Cox proportional hazard models to identify factors independently associated with survival. The study demonstrated that lymphovascular invasion significantly impacted survival outcomes on Kaplan–Meier analysis (log-rank p-value = 0.0058). Patients with LV showed a marked decrease in DFS compared to those without LV invasion, with a median DFS of 3.2 years and a hazard ratio of 2.18 (95% CI: 1.56–3.04, p < 0.001). Furthermore, high-grade tumors and p53 positivity were strongly associated with reduced DFS, with hazard ratios of 1.93 (p = 0.001) and 2.11 (p < 0.001), respectively. Patients with distant metastasis exhibited the most significant decline in survival, with a hazard ratio of 5.56 (95% CI: 2.45–10.18, p < 0.001). Despite comprehensive surgical and adjuvant therapies, these high-risk factors dictated poorer outcomes. The presence of lymphovascular invasion, high-grade tumors, and genetic markers like MSI and p53 are pivotal in predicting the course of endometrial cancer. This study underscores the necessity for aggressive management strategies in patients exhibiting these high-risk features to potentially improve prognosis and survival outcomes. The findings advocate for enhanced therapeutic strategies tailored to the biological behavior of the tumor, thereby aiming to elevate the overall survival rates for women diagnosed with endometrial cancer.
Hybrid Feature Mammogram Analysis: Detecting and Localizing Microcalcifications Combining Gabor, Prewitt, GLCM Features, and Top Hat Filtering Enhanced with CNN Architecture
Authors: Hernández-Vázquez Miguel Alejandro , Hernández-Rodríguez Yazmín Mariela , Cortes-Rojas Fausto David , Bayareh-Mancilla Rafael , Cigarroa-Mayorga Oscar Eduardo
Published: August 2024

Breast cancer is a prevalent malignancy characterized by the uncontrolled growth of glandular epithelial cells, which can metastasize through the blood and lymphatic systems. Microcalcifications, small calcium deposits within breast tissue, are critical markers for early detection of breast cancer, especially in non-palpable carcinomas. These microcalcifications, appearing as small white spots on mammograms, are challenging to identify due to potential confusion with other tissues. This study hypothesizes that a hybrid feature extraction approach combined with Convolutional Neural Networks (CNNs) can significantly enhance the detection and localization of microcalcifications in mammograms. The proposed algorithm employs Gabor, Prewitt, and Gray Level Co-occurrence Matrix (GLCM) kernels for feature extraction. These features are input to a CNN architecture designed with maxpooling layers, Rectified Linear Unit (ReLU) activation functions, and a sigmoid response for binary classification. Additionally, the Top Hat filter is used for precise localization of microcalcifications. The preprocessing stage includes enhancing contrast using the Volume of Interest Look-Up Table (VOI LUT) technique and segmenting regions of interest. The CNN architecture comprises three convolutional layers, three ReLU layers, and three maxpooling layers. The training was conducted using a balanced dataset of digital mammograms, with the Adam optimizer and binary cross-entropy loss function. Our method achieved an accuracy of 89.56%, a sensitivity of 82.14%, and a specificity of 91.47%, outperforming related works, which typically report accuracies around 85–87% and sensitivities between 76 and 81%. These results underscore the potential of combining traditional feature extraction techniques with deep learning models to improve the detection and localization of microcalcifications. This system may serve as an auxiliary tool for radiologists, enhancing early detection capabilities and potentially reducing diagnostic errors in mass screening programs.
Compressed SENSitivity Encoding (SENSE): Qualitative and Quantitative Analysis
Authors: Picchi Eliseo , Minosse Silvia , Pucci Noemi , Di Pietro Francesca , Serio Maria Lina , Ferrazzoli Valentina , Da Ros Valerio , Giocondo Raffaella , Garaci Francesco , Di Giuliano Francesca
Published: August 2024

Background. This study aimed to qualitatively and quantitatively evaluate T1-TSE, T2-TSE and 3D FLAIR sequences obtained with and without Compressed-SENSE technique by assessing the contrast (C), the contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR). Methods. A total of 142 MRI images were acquired: 69 with Compressed-SENSE and 73 without Compressed-SENSE. All the MRI images were contoured, spatially aligned and co-registered using 3D Slicer Software. Two radiologists manually drew 12 regions of interests on three different structures of CNS: white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF). Results. C values were significantly higher in Compressed-SENSE T1-TSE compared to No Compressed-SENSE T1-TSE for three different structures of the CNS. C values were also significantly lower for Compressed-SENSE 3D FLAIR and Compressed-SENSE T2-TSE compared to the corresponding No Compressed-SENSE scans. While CNR values did not significantly differ in GM-WM between Compressed-SENSE and No Compressed-SENSE for the 3D FLAIR and T1-TSE sequences, the differences in GM-CSF and WM-CSF were always statistically significant. Conclusion. Compressed-SENSE for 3D T2 FLAIR, T1w and T2w sequences enables faster MRI acquisition, reducing scan time and maintaining equivalent image quality. Compressed-SENSE is very useful in specific medical conditions where lower SAR levels are required without sacrificing the acquisition of helpful diagnostic sequences.
Anatomical Factors of the Anterior and Posterior Maxilla Affecting Immediate Implant Placement Based on Cone Beam Computed Tomography Analysis: A Narrative Review
Authors: Vasiljevic Milica , Selakovic Dragica , Rosic Gvozden , Stevanovic Momir , Milanovic Jovana , Arnaut Aleksandra , Milanovic Pavle
Published: August 2024

Background: The aim of this narrative review was to provide insights into the influence of the morphological characteristics of the anatomical structures of the upper jaw based on cone beam computed tomography (CBCT) analysis on the immediate implant placement in this region. Material and Methods:To conduct this research, we used many electronic databases, and the resulting papers were chosen and analyzed. From the clinical point of view, the region of the anterior maxilla is specific and can be difficult for immediate implant placement. Findings: Anatomical structures in the anterior maxilla, such as the nasopalatine canal and accessory canals, may limit and influence the implant therapy outcome. In addition to the aforementioned region, immediate implant placement in the posterior maxilla may be challenging for clinicians, especially in prosthetic-driven immediate implant placement procedures. Data presented within the recently published materials summarize the investigations performed in order to achieve more reliable indicators that may make more accurate decisions for clinicians. Conclusion: The possibility for immediate implant placement may be affected by the NPC shape in the anterior maxilla, while the presence of ACs may increase the incidence of immediate implant placement complications. The variations in IRS characteristics may be considered important criteria for choosing the implant properties required for successful immediate implant placement.
Oral Health-Related Quality of Life of Hong Kong Kindergarten Children Receiving Silver Diamine Fluoride Therapy
Authors: Chai Hollis Haotian , Sun Ivy Guofang , Duangthip Duangporn , Gao Sherry Shiqian , Lo Edward Chin Man , Chu Chun Hung
Published: August 2024

The objective of this prospective 12-month observational study is to examine the oral health-related quality of life (OHRQoL) among Hong Kong young children aged 3–4 years old receiving silver diamine fluoride (SDF) therapy for carious upper anterior primary teeth. A parental questionnaire was used to collect each child’s sociodemographic background and oral health habits at baseline. Data on parents’ satisfaction with their child’s dental aesthetics were collected at baseline and during a 12-month visit. The Chinese Early Childhood Oral Health Impact Scale (C-ECOHIS) was used to measure OHRQoL. A trained dentist performed examinations and recorded caries experience (dmft) and oral hygiene (visible plaque index) at baseline and 12 months. SDF was applied to the carious lesions. Out of 286 invited children, 248 (87%, 248/286) participated, and 211 (85%, 211/248) attended the 12-month examination. All SDF-treated carious lesions were discoloured at the 12-month examination. Regression analysis showed that the baseline C-ECOHIS score was associated with dmft (p < 0.001). The baseline and 12-month C-ECOHIS scores were 4.6 ± 5.5 and 5.0 ± 5.6, respectively (p = 0.42). The scores for parental satisfaction with dental aesthetics at baseline and 12 months were 59% to 46% (p < 0.001). Satisfaction was negatively associated with the number of discoloured upper anterior teeth (p < 0.001). In conclusion, SDF discoloured the carious upper anterior teeth of the Hong Kong kindergarten children. However, the discoloured lesions had no significant effects on the OHRQoL of these children. However, more parents became dissatisfied with their child’s dental aesthetics after SDF therapy. Hence, clinicians should inform parents well before they perform SDF therapy on children.
Non-Line-of-Sight Positioning Method for Ultra-Wideband/Miniature Inertial Measurement Unit Integrated System Based on Extended Kalman Particle Filter
Authors: Hou Chengzhi , Liu Wanqing , Tang Hongliang , Cheng Jiayi , Zhu Xu , Chen Mailun , Gao Chunfeng , Wei Guo
Published: August 2024

In the field of unmanned aerial vehicle (UAV) control, high-precision navigation algorithms are a research hotspot. To address the problem of poor localization caused by non-line-of-sight (NLOS) errors in ultra-wideband (UWB) systems, an UWB/MIMU integrated navigation method was developed, and a particle filter (PF) algorithm for data fusion was improved upon. The extended Kalman filter (EKF) was used to improve the method of constructing the importance density function (IDF) in the traditional PF, so that the particle sampling process fully considers the real-time measurement information, increases the sampling efficiency, weakens the particle degradation phenomenon, and reduces the UAV positioning error. We compared the positioning accuracy of the proposed extended Kalman particle filter (EKPF) algorithm with that of the EKF and unscented Kalman filter (UKF) algorithm used in traditional UWB/MIMU data fusion through simulation, and the results proved the effectiveness of the proposed algorithm through outdoor experiments. We found that, in NLOS environments, compared with pure UWB positioning, the accuracy of the EKPF algorithm in the X- and Y-directions was increased by 35% and 39%, respectively, and the positioning error in the Z-direction was considerably reduced, which proved the practicability of the proposed algorithm.
SLAKA-IoD: A Secure and Lightweight Authentication and Key Agreement Protocol for Internet of Drones
Authors: Xiao Yuelei , Tao Yu
Published: August 2024

The existing authentication and key agreement (AKA) schemes for the internet of drones (IoD) still suffer from various security attacks and fail to ensure required security properties. Moreover, drones generally have limited memory and computation capability. Motivated by these issues, a secure and lightweight AKA protocol for IoD (SLAKA-IoD) is proposed based on physical unclonable function (PUF), “exclusive or” (XOR) operation and hash function, which are simple cryptographic operations and functions that can provide better performance. In the SLAKA-IoD protocol, a drone and the ground station (GS) perform mutual authentication and establish a secure session key between them, and any two drones can also perform mutual authentication and establish a secure session key between them. Via informal security analysis, formal security analysis using the strand space model, and security verification based on the Scyther tool, the SLAKA-IoD protocol is proven to resist various security attacks and ensure required security properties. Further comparative analysis shows that the SLAKA-IoD protocol can provide more security features, and is generally lightweight as compared with these related AKA protocols for IoD, so it is suitable for IoD.
Aerial Map-Based Navigation by Ground Object Pattern Matching
Authors: Kim Youngjoo , Back Seungho , Song Dongchan , Lee Byung-Yoon
Published: August 2024

This paper proposes a novel approach to map-based navigation for unmanned aircraft. The proposed approach employs pattern matching of ground objects, not feature-to-feature or image-to-image matching, between an aerial image and a map database. Deep learning-based object detection converts the ground objects into labeled points, and the objects’ configuration is used to find the corresponding location in the map database. Using the deep learning technique as a tool for extracting high-level features reduces the image-based localization problem to a pattern-matching problem. The pattern-matching algorithm proposed in this paper does not require altitude information or a camera model to estimate the horizontal geographical coordinates of the vehicle. Moreover, it requires significantly less storage because the map database is represented as a set of tuples, each consisting of a label, latitude, and longitude. Probabilistic data fusion with the inertial measurements by the Kalman filter is incorporated to deliver a comprehensive navigational solution. Flight experiments demonstrate the effectiveness of the proposed system in real-world environments. The map-based navigation system successfully provides the position estimates with RMSEs within 3.5 m at heights over 90 m without the aid of the GNSS.
Understanding the Economic Drivers of Climate Change in Southeast Asia: An Econometric Analysis
Authors: Suwandaru Agung , Sudiyono Widhiyo , Shawdari Ahmed , Fristin Yuntawati
Published: August 2024

This study analyses macroeconomic trends in Southeast Asian countries and their implications for climate change, focusing on urbanisation, GDP per capita, energy intensity, FDI, inflation, and trade. Using panel data from 1970 to 2020, we investigate climate change drivers across Indonesia, Malaysia, the Philippines, Singapore, and Thailand through panel ARDL with PMG and MG analyses, along with Hausman tests. Our results highlight the need for tailored urbanisation policies for sustainability, as the consistent positive correlation between GDPs per capita and emissions, underscores the challenge of decoupling economic growth from emissions. Urbanisation’s varying impact calls for proactive planning, and mixed FDI results suggest nuanced investment approaches aligned with sustainability. Inflation’s negative impact hints at environmental benefits during price increases, necessitating integrated economic and climate policies. The positive relationship between trade openness and emissions emphasises the need for eco-conscious trade agreements to mitigate emissions from industrial activity. Our study stresses the importance of considering macroeconomic heterogeneity in crafting climate policies. Policymakers must adopt multifaceted approaches that prioritise sustainability across economic growth, energy efficiency, technology adoption, and trade to balance development with environmental preservation. This approach enables Southeast Asian countries to contribute effectively to global climate change mitigation.
Cross-Cultural Validation of Teachers Social Self-Efficacy Scale: Insights from Cyprus, Greece, and Portugal
Authors: Vatou Anastasia , Gregoriadis Athanasios , Evagelou-Tsitiridou Maria , Manolitsis George , Mouzaki Angeliki , Kypriotaki Maria , Oikonomidis Vasileios , Lemos Ana , Piedade Filipe , Alves Diana , Cadima Joana , Michael Demos , Charalambous Vicky , Agathokleous Andri , Vrasidas Charalambos , Grammatikopoulos Vasilis
Published: August 2024

The main aim of this study is to explore early childhood teachers’ social self-efficacy in Cyprus, Greece, and Portugal. In addition, this study examines the validity of the factorial structure of the Teachers’ Social Self-Efficacy Scale (TSSES). A sample of 349 early childhood teachers across the three countries participated in this study. An exploratory analysis and then a confirmatory factor analysis were employed to reveal the structure of the TSSES. Configural and metric invariance were established for the one-factor structure of the TSSES. The results showed that teachers in Portugal and Cyprus experience high levels of social self-efficacy, whereas Greek teachers experience moderate to high levels of social self-efficacy. The TSSES seems to be a reliable instrument for assessing social self-efficacy beliefs. Possible implications for practice are also discussed.
Scared, Bored or Happy? Latent Profile Analyses of Primary School Students’ Academic Emotions about Math
Authors: Radišić Jelena , Peixoto Francisco , Caetano Teresa , Mata Lourdes , Campos Mafalda , Krstić Ksenija
Published: August 2024

Emotions and motivation are central to learning. Control–value theory (CVT) and expectancy–value theory (EVT) explain how emotions and expectations of success affect students’ task engagement. Supported by these two frameworks, this study investigates the emotion profiles for maths among fourth- and fifth-grade students (N = 6778) from three European countries and their links to motivation and achievement. Methods: Using latent profile analysis (LPA), we analysed the emotional profiles in students, as well as their associations with gender, country, grade, motivation and maths achievement. Results: Five profiles emerged in the grade 4 data (Bored, Bored and Anxious, Moderate, Happy and Anxious). All five profiles were visible in the grade 5 data, coupled with an additional sixth profile, which appeared only in grade 5 (i.e., Apprehensive–Happy). Girls were found more commonly in the Anxious profile and were less likely to appear in the Happy profile. Norwegian students were more prominent in the Bored and Moderate profiles. Conversely, Portuguese students stood out more in the Anxious profile and were less present in the Bored and Moderate profiles. The Serbian dataset did not stand out, with a particular pattern observed in grade 4. Nevertheless, Serbian fifth graders were overly visible in the Bored and Anxious profile and less present in the Happy and Apprehensive–Happy groups. The Happy profile had higher scores for all task values except for cost and was, along with the Moderate profile, associated with higher achievement; the Bored and Anxious profile was associated with higher scores of cost value and lower achievement. Conclusions: A person-centred approach allowed for a more diverse view of how students experience emotions. These findings highlight the complex interplay between emotions, motivation and achievement, which is affected by cultural and educational contexts.
Design and Development of a Teaching–Learning Sequence about Deterministic Chaos Using Tracker Software
Authors: Parlati Alessio , Giuliana Giovanni , Testa Italo
Published: August 2024

In this paper, we present the design, development, and pilot implementation of a Teaching–Learning Sequence (TLS) about the physics of deterministic chaos. The main aim of the activities is to let students become aware of two key ideas about deterministic chaos: (1) the role of initial conditions and (2) the graphical representation in a momentum–position graph. To do so, the TLS is based on the observation and analysis of the trajectory of the free end of a double pendulum through the modeling software Tracker. In particular, the Tracker-based activities help students understand that, by modifying the well-known simple pendulum dynamic system into a double pendulum, long-time-scale predictability is lost, and a completely new behavior appears. The TLS was pilot tested in a remote teaching setting with about 70 Italian high school students (16–17 years old). The pretest analysis shows that before participating in the activities, students held typical misconceptions about chaotic behavior. Analysis of the written responses collected during and after implementation shows that the proposed activities allowed students to grasp the two key ideas about nondeterministic chaos. A possible integration of the TLS with an online simulation is finally discussed.
Optimizing Sensor Placement and Machine Learning Techniques for Accurate Hand Gesture Classification
Authors: Chaplot Lakshya , Houshmand Sara , Martinez Karla Beltran , Andersen John , Rouhani Hossein
Published: August 2024

Millions of individuals are living with upper extremity amputations, making them potential beneficiaries of hand and arm prostheses. While myoelectric prostheses have evolved to meet amputees’ needs, challenges remain related to their control. This research leverages surface electromyography sensors and machine learning techniques to classify five fundamental hand gestures. By utilizing features extracted from electromyography data, we employed a nonlinear, multiple-kernel learning-based support vector machine classifier for gesture recognition. Our dataset encompassed eight young nondisabled participants. Additionally, our study conducted a comparative analysis of five distinct sensor placement configurations. These configurations capture electromyography data associated with index finger and thumb movements, as well as index finger and ring finger movements. We also compared four different classifiers to determine the most capable one to classify hand gestures. The dual-sensor setup strategically placed to capture thumb and index finger movements was the most effective—this dual-sensor setup achieved 90% accuracy for classifying all five gestures using the support vector machine classifier. Furthermore, the application of multiple-kernel learning within the support vector machine classifier showcases its efficacy, achieving the highest classification accuracy amongst all classifiers. This study showcased the potential of surface electromyography sensors and machine learning in enhancing the control and functionality of myoelectric prostheses for individuals with upper extremity amputations.
Improving Data Utility in Privacy-Preserving Location Data Collection via Adaptive Grid Partitioning
Authors: Kim Jongwook
Published: August 2024

The widespread availability of GPS-enabled devices and advances in positioning technologies have significantly facilitated collecting user location data, making it an invaluable asset across various industries. As a result, there is an increasing demand for the collection and sharing of these data. Given the sensitive nature of user location information, considerable efforts have been made to ensure privacy, with differential privacy (DP)-based schemes emerging as the most preferred approach. However, these methods typically represent user locations on uniformly partitioned grids, which often do not accurately reflect the true distribution of users within a space. Therefore, in this paper, we introduce a novel method that adaptively adjusts the grid in real-time during data collection, thereby representing users on these dynamically partitioned grids to enhance the utility of the collected data. Specifically, our method directly captures user distribution during the data collection process, eliminating the need to rely on pre-existing user distribution data. Experimental results with real datasets show that the proposed scheme significantly enhances the utility of the collected location data compared to the existing method.
Detection of Stress Distribution in Surrounding Rock of Coal Seam Roadway Based on Charge Induction Principle
Authors: Wang Gang , Du Lulu , Fan Dewei , Wang Aiwen , Shi Tianwei , Dai Lianpeng
Published: August 2024

Rock burst is a worldwide prevention and control problem, and the main reason for its occurrence is the concentration of stress in the surrounding rock of the coal roadway. Therefore, it is of great significance to realize the rapid and accurate detection of the stress distribution in the surrounding rock of the roadway for the prevention and control of rock burst. Based on the principle of charge induction, this paper adopts a research method combining theoretical analysis and indoor and field tests to carry out a study on the charge induction detection of stress distribution of surrounding rock in coal seam roadways using the self-developed coal rock charge induction monitor. A theoretical analysis of the charge induction intensity in relation to the stress level is carried out. Indoor tests on the law of charge induction for graded loading of large sized coal samples are carried out. Field detection tests of the charge induction law at different drilling depths on the solid coal side and the large coal pillar side of the coal seam roadway are carried out. The results show a positive correlation between the charge signal intensity and the stress magnitude. The induced charge of coal samples has a tendency to increase with the increase in graded loading stress level. The magnitude of the induced charge can reflect the stress level of the coal body. On the solid coal side, the induced charge has a tendency of increasing and then decreasing with the increase in detection depth. The final results are in good agreement with the results of the drill chip method, which better reflects the distribution of the lateral support pressure of the roadway. On the side of the large coal pillar, the induced charge has a tendency to increase, then decrease, and then increase with the increase in probing depth, which is in good agreement with the distribution of lateral support pressure formed in the elastic core area of the large coal pillar. Therefore, the charge induction technology can be used as a fast, non-contact detection means for the partitioning and stress distribution of the roadway enclosure, which can provide guidance for the target prevention and controlling rock burst and for designing roadway support.