bluuebunny/crossref_metadata_2025 huggingface dataset:
Durability Improvement of Cement Using Amphiphilic Calcium Carbonate Nanoparticles
Authors: Yan Han , Shu Xin , Zhou Dongliang , Yang Yong , Chen Lu , Ran Qianping
Published: September 2022

The durability of cementitious materials is significant concerning long-term performance. Nanomaterials are promising candidates for deep refinement of cement durability. Hydrophobic calcium carbonate is a widely applied and easily accessible nanomaterial. However, its hydrophobicity and poor dispersity in water prohibit its direct application in cementitious materials. In this study, hydrophobic calcium carbonate nanoparticles (HbCC) were modified using a novel amphiphilic comb-shaped dispersant that is capable of laurinol release. The modification was conducted to improve the dispersity of HbCC and their compatibility with hydration products. The dispersion-improved calcium carbonate particles (AmphCC) were characterized and tested for cement durability improvement performance. According to the results, the AmphCC particles showed a pronounced effect on improving permeation resistance of cement mortars, with water absorption and chloride penetration considerably lowered. Moreover, the introduction of AmphCC in cement did not show significant adverse effects on strength development. Compared with AmphCC, a single addition of the unmodified HbCC and the dispersant cannot achieve equivalent effects. The superior effect of AmphCC is due to the synergistic effect of good particle dispersion and controlled release of the hydrophobic molecules, which is achieved by dispersion of HbCC with binding of the dispersant.
Ideas Inspired by Nature to Combat Marine Biofouling and Corrosion
Authors: Tian Wei , Jin Huichao , Tian Limei
Published: September 2022

Given the increasingly worrying situation regarding available energy, all countries worldwide have agreed to actively develop marine resources [...]
Correction: Park, K.; Withey, P. General View of Rhenium-Rich Particles along Defect Grain Boundaries Formed in Nickel-Based Single-Crystal Superalloy Turbine Blades: Formation, Dissolution and Comparison with Other Phases. Crystals 2021, 11, 1201
Authors: Park KeeHyun , Withey Paul
Published: September 2022

There was an error in the original publication [...]
Optimization of Parameters in Laser Powder Bed Fusion TA15 Titanium Alloy Using Taguchi Method
Authors: Liu Yang , Wu Zichun , Wang Qing , Zhao Lizhong , Zhang Xichen , Gao Wei , Xu Jing , Song Yufeng , Song Xiaolei , Zhang Xuefeng
Published: September 2022

In this work, laser powder bed fusion (LPBF) was explored to fabricate TA15 (Ti-6Al-2Zr-1Mo-1V) titanium alloy based on the experimental design obtained by using the Taguchi method. The impact of processing parameters (including laser power, scanning speed, and scanning interval) on the density and microhardness of the as-LPBFed TA15 titanium alloy was analyzed using the Taguchi method and analysis of variance (ANOVA). The interaction among parameters on the density of the as-LPBFed TA15 titanium alloy was indicated by a response surface graph (RSR). When the laser energy density was adjusted to 100 J/mm3, the highest relative density could reach 99.7%. The further increase in the energy input led to the reduction in relative density, due to the formation of tiny holes caused by the vaporization of material at a high absorption of heat. Furthermore, in order to better reveal the correlation between relative density and processing parameters, the regression analysis was carried out for relative density. The results showed that the experimental and predicted values obtained by the regression equation were nearly the same.
Bis-Citrullinato Copper(II) Complex: Synthesis, Crystal Structure, and Non-Covalent Interactions
Authors: Ramírez-Contreras Diego , García-García Amalia , Sánchez-Gaytán Brenda L. , Serrano-de la Rosa Laura E. , Melendez Francisco J. , Choquesillo-Lazarte Duane , Rodríguez-Diéguez Antonio , Castro María Eugenia , González-Vergara Enrique
Published: September 2022

Citrulline (C6H13N3O3) is a non-protein amino acid found in watermelon. In physiological conditions, it is almost entirely present as a zwitterion, so its carboxylic and amine groups can act as Lewis donors, chelating metallic cations. In addition, Citrulline possesses a terminal ureide group of the aliphatic chain, which appears to be non-innocent. Although Citrulline is similar to other classical amino acids, only one coordination complex has been reported in the Cambridge Crystallographic Database. As part of our search for Casiopeina® analogs, we synthesized and characterized the copper bis-citrullinato complex, [Cu(Citr)2]n. The compound was described using UV-Vis, Infrared, and Raman spectroscopy, together with single-crystal X-ray diffraction. Computational tools were also used. The optimized structure, MEP map, IR and Raman spectra, and 1H and 13C chemical shifts were obtained with functional mPW1PW91 using 6-31G(d) basis set for N, O, C, and H atoms, and LANL2DZ basis set and ECP=LANL2DZ for the Cu atom. TD-mPW1PW91 calculations generated the UV-Vis spectrum. Finally, AIM and Hirshfeld surface analysis were used to examine non-covalent interactions. Previous investigations suggest Casiopeina®-like complexes can interact with DNA/RNA, creating potential anticancer chemicals. The [Cu(Citr)2]n complex’s polymeric nature and insolubility make it difficult for such purposes. However, the facile synthesis of D-Citrulline could be a novel way to find new applications for this interesting amino acid.
Microstructure Evolution of AZ91 Magnesium Alloy Welded Joint under Magnetic Field and NiCl2 Activated Flux
Authors: Zhang Guiqing , Ren Yinglei , Su Yunhai
Published: September 2022

As the lightest engineering materials, magnesium alloys have been widely used. Because of the specific chemical and physical characteristics, the weldability of magnesium alloy is poor. Adopting suitable welding technology and improving the quality of magnesium alloy welded joints is key to their successful application. According to previous research data, it was found that the combined action of magnetic field and activated flux has a positive effect on improving-welding efficiency and improving the properties of a welded joint, butanalysis of microstructure evolution is insufficient. In this paper, AZ91 magnesium alloy was welded by TIG welding with activated flux and external longitudinal AC magnetic field. The phase composition and microstructure evolution were investigated. The experimental results revealed that the phase composition of welded joint was not changed due to the introduction of the magnetic field and activated flux, the growth patterns of grain in the weld seam and heat-affected zone were different. When the activated flux amount was 3 mg/cm2 with the effect of the magnetic field, the grain size of the weld seam was the finest, which was 18.96 μm. However, the grain size of the weld seam was larger than that of base metal. The crystallographic characteristics of grain boundaries in the weld seam and base metal were both LAGBs. The microstructure of the weld seam was messier than the base metal due to the larger misorientation angle. Under the combined action of the magnetic field and activated flux, the crystallization nucleation condition of the molten pool was changed, the formation of twins was promoted, and the crystal could selectively grow parallel with the (0001) basal plane.
Amphibian Diversity of the Yucatan Peninsula: Representation in Protected Areas and Climate Change Impacts
Authors: Castaño-Quintero Sandra Milena , Escobar-Luján Jazmín , Villalobos Fabricio , Ochoa-Ochoa Leticia Margarita , Yáñez-Arenas Carlos
Published: September 2022

Knowledge about the dynamics of regional diversity patterns is a foundation on which measures aimed to protect diversity dimensions in the light of climate change can be constructed. Here, we describe taxonomic, phylogenetic, and functional diversity patterns of amphibians in the Yucatan Peninsula and their representation in the current protected area system. We stacked current and future potential distribution models to estimate taxonomic diversity and, based on the most recent amphibian phylogeny and nine functional traits, we measured phylogenetic and functional diversity. Independent phylogenetic and functional metrics were obtained by applying null models that allowed us to identify the presumably signature mechanisms underlying assemblage formation. We evaluated the effectiveness of the protected areas in protecting diversity dimensions across scenarios. We found phylogenetic and functional clustering as a result of environmental filters that have allowed only recently diverged species with converged functional traits to establish. Nevertheless, random assemblages are more widespread possibly due to the opposite directions in which competition and environmental filtering are acting. Overall, a decrease in all diversity dimensions is projected under future climate change scenarios compared with the current time. None of the protected areas evaluated were effective in protecting diversity dimensions, stressing the need to complete the existing protected areas network.
The Spatial Pattern of the Two Genetic Lineages of the Field Vole in Lithuania
Authors: Prakas Petras , Butkauskas Dalius , Vaišvilienė Jevgenija , Balčiauskienė Laima , Balčiauskas Linas
Published: September 2022

The phylogeography of the filed vole (Microtus agrestis) in Eurasia was thoroughly examined using mitochondrial DNA (mtDNA) of the cytochrome b (cytb) gene. However, the former conclusions about genetic variability and the contact zone of eastern and western genetic lineages in Lithuania were based on the analysis of a very limited number of individuals. In the present study, we examined 74 M. agrestis individuals trapped in four sites in the eastern, northern, and western parts of the country using sequence analysis of cytb and D-loop. Totals of 25 new cytb haplotypes and 19 new D-loop haplotypes were identified for this species. Higher nucleotide diversity was observed for D-loop (π = 0.01147 ± 0.00070) as compared to cytb (π = 0.00694 ± 0.00039). The phylogenetic analysis based on both loci revealed the presence of two genetic lineages, i.e., the eastern and western ones, which were mixed in Lithuanian samples, with the exception of the Rusnė site in the west of the country. Only the western lineage was observed in this island population of M. agrestis; the sample differed in low genetic variability and genetic differentiation from other investigated samples. We found D-loop to be an appropriate locus for the evaluation of the genetic variability of M. agrestis.
Comparability between Computed Tomography Morphological Vascular Parameters and Echocardiography for the Assessment of Pulmonary Hypertension in Patients with Severe Aortic Valve Stenosis—Results of a Multi-Center Study
Authors: Boxhammer Elke , Scharinger Bernhard , Kaufmann Reinhard , Brandtner Herwig , Schmidbauer Lukas , Kammler Jürgen , Kellermair Jörg , Reiter Christian , Akbari Kaveh , Hammerer Matthias , Blessberger Hermann , Steinwender Clemens , Hergan Klaus , Hoppe Uta C. , Lichtenauer Michael , Hecht Stefan
Published: September 2022

Background: Computed tomography (CT) of the aorta and cardiac vessels, which is performed in patients with severe aortic valve stenosis (AS) before transcatheter aortic valve replacement (TAVR), offers the possibility of non-invasive detection of pulmonary hypertension (PH), for example, by determining the diameter of the main pulmonary artery (PA), the right pulmonary artery (RPA) or the left pulmonary artery (LPA). An improvement of the significance of these radiological parameters is often achieved by indexing to the body surface area (BSA). The aim of this study was to compare different echocardiographic systolic pulmonary artery pressure (sPAP) values with radiological data in order to define potential clinical cut-off values for the presence or absence of PH. Methods: A total of 138 patients with severe AS undergoing TAVR underwent pre-interventional transthoracic echocardiography with determination of sPAP values and performance of CT angiography (CTA) of the aorta and femoral arteries. Radiologically, the PA, RPA, LPA, and ascending aorta (AA) diameters were obtained. Vascular diameters were not only indexed to BSA but also ratios were created with AA diameter (for example PA/AA-ratio). From these CT-derived vascular parameters, AUROC curves were obtained regarding the prediction of different sPAP values (sPAP 40–45–50 mmHg) and finally correlation analyses were calculated. Results: The best AUROC and correlation analyses were generally obtained at an sPAP ≥ 40 mmHg. When considering diameters alone, the PA diameter was superior to the RPA and LPA. Indexing to BSA generally increased the diagnostic quality of the parameters, and finally, in a synopsis of all results, PA/BSA had the best AUC 0.741 (95% CI 0.646–0. 836; p < 0.001; YI 0.39; sensitivity 0.87; specificity 0.52) and Spearman’s correlation coefficient (r = 0.408; p < 0.001) at an sPAP of ≥40 mmHg. Conclusions: Features related to pulmonary hypertension are fast and easily measurable on pre-TAVR CT and offer great potential regarding non-invasive detection of pulmonary hypertension in patients with severe AS and can support the echocardiographic diagnosis. In this study, the diameter of the main pulmonary artery with the additionally determined ratios were superior to the values of the right and left pulmonary artery. Additional indexing to body surface area and thus further individualization of the parameters with respect to height and weight can further improve the diagnostic quality.
Contracture Knots vs. Trigger Points. Comment on Ball et al. Ultrasound Confirmation of the Multiple Loci Hypothesis of the Myofascial Trigger Point and the Diagnostic Importance of Specificity in the Elicitation of the Local Twitch Response. Diagnostics 2022, 12, 321
Authors: Dommerholt Jan , Gerwin Robert D.
Published: September 2022

A recent study published in Diagnostics attempted to visualize trigger points and contracture knots with high-definition ultrasound. Based on their findings, the authors reversed the commonly understood meaning of the two terms. However, they did so without providing any convincing evidence. The authors maintained that their sonography images represented trigger points within contracture knots, supporting the multiple loci hypothesis. On review of the paper, both conclusions seem premature and rather speculative.
Interhemispheric Pediatric Meningioma, YAP1 Fusion-Positive
Authors: Esposito Silvia , Marucci Gianluca , Antonelli Manila , Miele Evelina , Modena Piergiorgio , Giagnacovo Marzia , Massimino Maura , Biassoni Veronica , Taddei Matilde , Schiariti Marco , Doniselli Fabio , Moscatelli Marco , Chiapparini Luisa , Pollo Bianca
Published: September 2022

Meningiomas are uncommon in children and usually arise in the context of tumor-predisposing syndromes. Recently, YAP1-fusions have been identified for the first time as potential NF2-independent oncogenic drivers in the development of meningiomas in pediatric patients. We report a case of a YAP1-fusion-positive atypical meningioma in a young child and compare it with the previous ones reported. Extending the clinico-pathological features of YAP1-fused meningiomas, we suggest additional clues for diagnosis and emphasize the urgent need for an integrated multilayered diagnostic approach, combining data from histological and molecular analyses, neuroradiology, and clinical findings.
Clinical Management of Herpes Simplex Virus Keratitis
Authors: Labib Bisant A. , Chigbu DeGaulle I.
Published: September 2022

Herpes simplex virus (HSV) keratitis is one of the leading causes of blindness worldwide. Additionally, up to 90% of the population in some countries is seropositive for HSV. HSV can cause a wide spectrum of ocular disease ranging from blepharitis to retinitis. Although the initial clinical expressions of HSV-1 and HSV-2 are similar, HSV-2 has been reported more frequently in association with recurrent HSV disease. Besides irreversible vision loss from keratitis, HSV also causes encephalitis and genital forms of the disease. Despite these statistics, there remains no vaccine against HSV. Current treatment therapies for related ocular diseases include the use of oral and topical antivirals and topical corticosteroids. While effective in many cases, they fail to address the latency and elimination of the virus, making it ineffective in addressing recurrences, a factor which increases the risk of vision loss. As such, there is a need for continued research of other potential therapeutic targets. This review utilized several published articles regarding the manifestations of HSV keratitis, antiviral immune responses to HSV infection, and clinical management of HSV keratitis. This review will summarize the current knowledge on the host–virus interaction in HSV infections, as well as highlighting the current and potential antiviral therapeutics.
Diagnosis and Management of Button Battery Ingestion Complicated by Tracheo-Esophageal and Aorto-Esophageal Fistulas
Authors: Lanzafame Ludovica R. M. , Blandino Alfredo , Cicero Giuseppe , Romeo Placido , Agati Salvatore , Zanai Rosanna , Celona Antonio , Booz Christian , Koch Vitali , Mazziotti Silvio , D’Angelo Tommaso
Published: September 2022

Button battery ingestion (BBI) is common in children and its prevalence has increased in the last decades. BBI can be responsible for very severe and potentially fatal complications if not promptly detected. We describe the successful management of two cases of BBI that occurred in two previously healthy infants. Both patients presented with vague symptoms and no witness of foreign body ingestion. The prolonged time of exposure to the corrosive effects of disk batteries was responsible for the development of tracheo-esophageal fistula (TEF) and aorto-esophageal fistula (AEF). We demonstrate how prompt diagnosis and management are crucial for the infants’ survival.
Application of a Deep Learning Algorithm for Combined Super-Resolution and Partial Fourier Reconstruction Including Time Reduction in T1-Weighted Precontrast and Postcontrast Gradient Echo Imaging of Abdominopelvic MR Imaging
Authors: Wessling Daniel , Herrmann Judith , Afat Saif , Nickel Dominik , Almansour Haidara , Keller Gabriel , Othman Ahmed E. , Brendlin Andreas S. , Gassenmaier Sebastian
Published: September 2022

Purpose: The purpose of this study was to test the technical feasibility and the impact on the image quality of a deep learning-based super-resolution reconstruction algorithm in 1.5 T abdominopelvic MR imaging. Methods: 44 patients who underwent abdominopelvic MRI were retrospectively included, of which 4 had to be subsequently excluded. After the acquisition of the conventional volume interpolated breath-hold examination (VIBEStd), images underwent postprocessing, using a deep learning-based iterative denoising super-resolution reconstruction algorithm for partial Fourier acquisitions (VIBESR). Image analysis of 40 patients with a mean age of 56 years (range 18–84 years) was performed qualitatively by two radiologists independently using a Likert scale ranging from 1 to 5, where 5 was considered the best rating. Results: Image analysis showed an improvement of image quality, noise, sharpness of the organs and lymph nodes, and sharpness of the intestine for pre- and postcontrast images in VIBESR compared to VIBEStd (each p < 0.001). Lesion detectability was better for VIBESR (p < 0.001), while there were no differences concerning the number of lesions. Average acquisition time was 16 s (±1) for the upper abdomen and 15 s (±1) for the pelvis for VIBEStd, and 15 s (±1) for the upper abdomen and 14 s (±1) for the pelvis for VIBESR. Conclusion: This study demonstrated the technical feasibility of a deep learning-based super-resolution algorithm including partial Fourier technique in abdominopelvic MR images and illustrated a significant improvement of image quality, noise, and sharpness while reducing TA.
Obstructive Sleep Apnea and Auditory Dysfunction—Does Snoring Sound Play a Role?
Authors: Lu Chun-Ting , Lee Li-Ang , Lee Guo-She , Li Hsueh-Yu
Published: September 2022

The objective of the study was to investigate the relationship between obstructive sleep apnea (OSA) and auditory dysfunction, and to clarify the role of snoring sounds in contributing to auditory dysfunction. A comprehensive assessment of OSA and the auditory system was performed, including overnight polysomnography, detection of the intra-ear canal snoring sound energy (SSE), pure tone average (PTA), tinnitus pitch matching, the tinnitus handicap inventory (THI), and the Epworth sleepiness scale (ESS). The patients were identified as having tinnitus if their THI score was higher than zero or their tinnitus pitches were matched to specific frequencies. The median age, body mass index, and apnea–hypopnea index score were 41 years, 26.4 kg/m2, and 29.9 events/h, respectively. Among the 50 participants, 46 (92%) had a normal PTA, and only 4 (8%) patients had mild hearing loss. There was no significant difference in PTA among OSA severities (p = 0.52). Among the 50 participants, 33 patients (66%) were identified as having tinnitus. In the tinnitus group (n = 33), the ESS score (p = 0.01) and intra-ear canal SSE of 851–1500 Hz (p = 0.04) were significantly higher than those in the non-tinnitus group (n = 17). OSA patients with a higher ESS score had a higher risk of tinnitus (odds ratio 1.22 [95% CI: 1.01–1.46]). OSA-related auditory dysfunction emerged in tinnitus rather than in hearing impairment. OSA patients with daytime sleepiness had a higher risk of tinnitus. High-frequency SSE can jeopardize cochlea and is a potential mechanism contributing to tinnitus. Detection of snoring sounds through an intra-ear canal device may be more precise in assessing acoustic trauma from snoring sounds to vulnerable auditory system and thus warrants further research.
Awareness and Attitudes of Dental Students toward Older Adults in Indonesia
Authors: Rahardjo Anton , Firdaus Fakhira Hanna Safira , Andreas Peter , Wimardhani Yuniardini Septorini , Maharani Diah Ayu
Published: September 2022

In this study, we aimed to analyse the awareness and attitudes of dental students (DS) toward older adults (OAs) in Indonesia. Compromised oral health (OH) among OAs is a significant public health problem that is a global health burden. Furthermore, appropriate education can provide DS with information about strategic and efficient treatments for OAs. An online invitation was provided to every dental student in Indonesia in the third to sixth year of study to answer a web-based questionnaire as a part of a survey on awareness and attitudes (14 questions) towards OAs. From 1288 valid forms submitted, it was evident that most students (87%) expressed a positive attitude toward OAs. Female students showed a more positive attitude compared to males, with an odds ratio of 1.539 (p = 0.036), and students who had a connection to an older adult demonstrated a more positive attitude than those who did not (OR = 2.076; p < 0.001). The majority of the DS (98%) were conscious of the importance of geriatrics in dentistry, with female students showing more awareness than their male counterparts (OR = 2.553; p = 0.033). Positive awareness and attitudes must be accompanied by knowledge so that DS can offer appropriate and effective oral care to geriatric patients.
Investigative Activities for Statistics Learning with 1st Grade Portuguese Students
Authors: Silva Ana Catarina , Viseu Floriano , Aires Ana Paula , Neto Teresa B.
Published: September 2022

The relevance of data exploration in mathematics programmes at all levels of education led us to develop a learning experience with 1st grade students with the aim of investigating the contribution of investigative activities in the learning of statistics. To achieve this objective, the following research questions were outlined: How do students implement investigative activities when learning statistics? What difficulties do students have in carrying out investigative activities when learning statistics? Adopting a qualitative and interpretative approach, data were collected through students’ written records, the reflections of the teacher, and a written test applied before and after the learning experience. The results obtained suggest that students were able to carry out investigative activities when learning statistics although with some weaknesses, namely defining the topic and research questions, and analysing the data due to the greater complexity of the research proposed by them. Students were able to formulate conclusions, although in some groups the conclusions were underdeveloped. Students were most confident in data collection, organization, and representation activities, with limitations typical of their young age (e.g., written communication). Students also showed difficulties in managing group work and knowledge of statistics, notably concerning strategies of data organization and representation and statistical measures.
Workloads and Emotional Factors Derived from the Transition towards Online and/or Hybrid Teaching among Postgraduate Professors: Review of the Lessons Learned
Authors: Bravo Isabel del Arco , Flores-Alarcia Òscar , González-Rubio Janeth , Araneda Daniel Serey , Olivos Carlos Lagos
Published: September 2022

The objective of the present study was to discover which tasks resulted in a higher workload, leading to a higher anxiety of postgraduate professors at different Ibero-American universities, when dealing with the transition from face-to-face teaching to a virtual one. A questionnaire was constructed that was completed by 125 professors once validated. The results showed that with respect to tasks that required a higher workload, the professors had to re-think methodological strategies and activities, correct the student’s work, provide tutoring, and search for materials. As for the degree of anxiety, it was higher, given the increased number of hours in front of the computer, the lack of immediate feedback from the students, the feeling of not reaching all the students, having to look for activities to invigorate the online classes, and the need to prepare more materials and the assessment tasks. The results were the same irrespective of the university, thereby enabling us to conclude that this phenomenon was globalized, and the workload and anxiety were replicated in different contexts. Therefore, it is necessary to implement formative proposals that help manage online or hybrid teaching, beyond the mere transfer of the face-to-face teaching models to virtual ones.
Physical Contamination Detection in Food Industry Using Microwave and Machine Learning
Authors: Darwish Ali , Ricci Marco , Zidane Flora , Vasquez Jorge A. Tobon , Casu Mario R. , Lanteri Jerome , Migliaccio Claire , Vipiana Francesca
Published: September 2022

The detection of contaminants in food products after packaging by a non-invasive technique is a serious need for companies operating in the food industry. In recent years, many technologies have been investigated and developed to overcome the intrinsic drawbacks of the currently employed techniques, such as X-rays and metal detector, and to offer more appropriate solutions with respect to techniques developed in the academic domain in terms of acquisition speed, cost, and the penetration depth (infrared, hyperspectral imaging). A new method based on MW sensing is proposed to increase the degree of production quality. In this paper, we are going to present a novel approach from measurements setup to a binary classification of food products as contaminated or uncontaminated. The work focuses on combining MW sensing technology and ML tools such as MLP and SVM in a complete workflow that can operate in real time in a food production line. A very good performance accuracy that reached 99.8% is achieved using the non-linear SVM algorithm, while the accuracy of the performance of the MLP classifier reached 99.3%.
Research on Structured Extraction Method for Function Points Based on Event Extraction
Authors: Han Delong , Gu Xungang , Zheng Chengpeng , Li Gang
Published: September 2022

Software size is a significant input for software cost estimation, and the implementation of software size estimation dramatically affects the results and efficiency of cost estimation. Traditionally, the software size estimation is implemented by strictly trained experts and is more labor-intensive for large software projects, which is relatively expensive and inefficient. Function Point Analysis is a widely used method for software size estimation, supported by several international standards. We propose a structured and automated function point extraction method based on event extraction in natural language processing to address the problem of complex and inefficient manual recognition for function point recognition. This approach has been validated in 10 industrial cases. Experimental results show that our method can identify more than 70% of the function points, which significantly improves the efficiency of Function Point Analysis implementation. This paper could be a guide on the application of artificial intelligence techniques to software cost estimation.
Intelligent Vehicle Trajectory Tracking Control Based on VFF-RLS Road Friction Coefficient Estimation
Authors: Nie Yanxin , Hua Yiding , Zhang Minglu , Zhang Xiaojun
Published: September 2022

This paper proposes an autonomous vehicle trajectory tracking system that fully considers road friction. When an intelligent vehicle drives at high speed on roads with different friction coefficients, the difficulty of its trajectory tracking control lies in the fast and accurate identification of road friction coefficients. Therefore, an improved strategy is designed based on traditional recursive least squares (RLS), which is utilized for accurate identification of the friction coefficient. First, the tire force and slip rate required for the estimation of the road friction coefficient by constructing the vehicle dynamics model and tire effective model are calculated. In this paper, a variable forgetting factor recursive least squares (VFF-RLS) method is proposed for the construction of the friction coefficient estimator. Second, the identified results are output to the model predictive controller (MPC) constructed in this paper as a way to improve tire slip angle constraints, to realize the trajectory tracking of the intelligent vehicle. Finally, the joint simulation test results of Carsim and Matlab/Simulink show that the trajectory tracking system based on the VFF-RLS friction coefficient estimator has outstanding tracking performance.
Efficient Elliptic Curve Operators for Jacobian Coordinates
Authors: Eid Wesam , Al-Somani Turki F. , Silaghi Marius C.
Published: September 2022

The speed up of group operations on elliptic curves is proposed using a new type of projective coordinate representation. These operations are the most common computations in key exchange and encryption for both current and postquantum technology. The boost this improvement brings to computational efficiency impacts not only encryption efforts but also attacks. For maintaining security, the community needs to take note of this development as it may need to operate changes in the key size of various algorithms. Our proposed projective representation can be viewed as a warp on the Jacobian projective coordinates, or as a new operation replacing the addition in a Jacobian projective representation, basically yielding a new group with the same algebra elements and homomorphic to it. Efficient algorithms are introduced for computing the expression Pk+Q where P and Q are points on the curve and k is an integer. They exploit optimized versions for particular k values. Measurements of the numbers of basic computer instructions needed for operations based on the new representation show clear improvements. The experiments are based on benchmarks selected using standard NIST elliptic curves.
A Novel Target Tracking Scheme Based on Attention Mechanism in Complex Scenes
Authors: Wang Yu , Yang Zhutian , Yang Wei , Yang Jiamin
Published: September 2022

In recent years, target tracking algorithms based on deep learning have realized significant progress, especially the Siamese neural network structure, which has a simple structure and excellent scalability. Although these methods provide excellent generalization capabilities, they fail to perform the task of learning target information discrimination smoothly due to being affected by distractors such as background clutter, occlusion, and target size. To solve this problem, in this paper we propose a newly improved Siamese network target tracking algorithm based on an attention mechanism. We introduce a channel attention module and a spatial attention module into the original network to improve the problem of insufficient semantic extraction ability of the convolutional layer of the tracking algorithm in complex environments. A channel attention mechanism enhances the feature extraction ability by using the network to learn the importance of each channel and establish the relationship between channels, while a spatial attention mechanism strengthens the feature extraction ability by establishing the importance of spatial position in locating the target or carrying out a certain degree of deformation. In this paper, the above two models are combined to improve the robustness of trackers without sacrificing tracking speed. We conduct a comprehensive experiment on the Object Tracking Benchmark dataset. The experimental results show that our algorithm outperforms other real-time trackers in both accuracy and robustness in most complex environments.
Adaptive Two-Index Fusion Attribute-Weighted Naive Bayes
Authors: Zhou Xiaoliang , Wu Donghua , You Zitong , Wu Dongyang , Ye Ning , Zhang Li
Published: September 2022

Naive Bayes (NB) is one of the essential algorithms in data mining. However, it is rarely used in reality because of the attribute independence assumption. Researchers have proposed many improved NB methods to alleviate this assumption. Among these methods, due to its high efficiency and easy implementation, the filter-attribute-weighted NB methods have received great attentions. However, there still exist several challenges, such as the poor representation ability for a single index and the fusion problem of two indexes. To overcome the above challenges, we propose a general framework of an adaptive two-index fusion attribute-weighted NB (ATFNB). Two types of data description category are used to represent the correlation between classes and attributes, the intercorrelation between attributes and attributes, respectively. ATFNB can select any one index from each category. Then, we introduce a regulatory factor β to fuse two indexes, which can adaptively adjust the optimal ratio of any two indexes on various datasets. Furthermore, a range query method is proposed to infer the optimal interval of regulatory factor β. Finally, the weight of each attribute is calculated using the optimal value β and is integrated into an NB classifier to improve the accuracy. The experimental results on 50 benchmark datasets and a Flavia dataset show that ATFNB outperforms the basic NB and state-of-the-art filter-weighted NB models. In addition, the ATFNB framework can improve the existing two-index NB model by introducing the adaptive regulatory factor β. Auxiliary experimental results demonstrate the improved model significantly increases the accuracy compared to the original model without the adaptive regulatory factor β.
Mixed-Variable Bayesian Optimization for Analog Circuit Sizing through Device Representation Learning
Authors: Touloupas Kostas , Sotiriadis Paul Peter
Published: September 2022

In this work, a deep representation learning method is proposed to build continuous-valued representations of individual integrated circuit (IC) devices. These representations are used to render mixed-variable analog circuit sizing problems as continuous ones and to apply a low-budget black box Bayesian optimization (BO) variant to solve them. By transforming the initial search spaces into continuous-valued ones, the BO’s Gaussian process models (GPs), which typically operate on real-valued spaces, can be used to guide the optimization search towards the global optimum. The proposed Device Representation Learning approach involves using device simulation data and training a composite model of a Variational Autoencoder (VAE) and a dense Neural Network. The latent variables of the trained VAE model serve as the representations of the integrated device and replace the discrete-valued parametrizations of particular devices. A thorough explanation of the proposed methodology’s mathematical formulation is given and example sizing applications on real-world analog circuits and integrated devices underline its efficiency.
A Performance-Oriented Optimization Framework Combining Meta-Heuristics and Entropy-Weighted TOPSIS for Multi-Objective Sustainable Supply Chain Network Design
Authors: Guo Yurong , Shi Quan , Guo Chiming
Published: September 2022

The decision-making of sustainable supply chain network (SSCN) design is a strategy capacity for configuring network facility and product flow. When optimizing conflicting economic, environmental, and social performance objectives, it is difficult to select the optimal scheme from obtained feasible decision schemes. In this article, according to the triple bottom line of sustainability, a multi-objective sustainable supply chain network optimization model is developed, and a novel performance-oriented optimization framework is proposed. This framework, referred to as performance-oriented optimization framework, integrates multi-objective meta-heuristic algorithms and entropy-weighted technique for order preference by similarity to an ideal solution (EW-TOPSIS). The optimization framework can comprehensively evaluate the performance of overall SSCN by EW-TOPSIS and guide the evolution process of algorithms. In this framework, decision-makers can obtain the feasible schemes calculated by meta-heuristics and determine the optimal one according to the performance value evaluated by EW-TOPSIS. This article combines three performance evaluation strategies with four meta-heuristic algorithms, namely, non-dominated Sorting Genetic Algorithm-II (NSGA-2), multi-objective differential evolutionary (MODE), multi-objective particle swarm optimization (MOPSO), and multi-objective gray wolr optimization (MOGWO), for verifying the effectiveness of the performance-oriented optimization framework. The results validate that the proposed framework has much better sustainability performance than the traditional optimization algorithms and evaluation methods. Furthermore, the proposed performance-oriented optimization framework can provide managers with a special optimal scheme with the best sustainability performance. Finally, some research prospects are presented such as more multi-criteria decision making methods.
New Sliding Mode Control Based on Tracking Differentiator and RBF Neural Network
Authors: Qu Chunyu , Hu Yongzhuang , Guo Ziqi , Han Fangxu , Wang Xiuping
Published: September 2022

In order to solve the problem that the control system of permanent magnet synchronous motor (PMSM) is difficult to meet the high control accuracy due to the influence of non-repeated disturbances such as external disturbance, system parameter variation, and friction force during operation, a novel sliding mode control (NSMC) method based on tracking differentiator (TD) and radial basis (RBF) neural network was proposed. Firstly, a new sliding mode reaching law is proposed by adding the state variables to the traditional exponential reaching law, which can effectively reduce the chattering of the system. Then, the speediest tracking differentiator is designed to estimate the given speed signal and its differential signal, to realize the novel sliding mode variable structure algorithm. Finally, the RBF neural network is used to compensate for the uncertainty and external interference of the system; the robustness of the system is further improved by adaptive weight updating. The simulation results show that, by comparing with the traditional exponential approach law, the overshoot of 22 r/min is reduced by the control method based on the new hybrid reaching law, the speed decrease amplitude is reduced by 77.1% under load disturbance, and the speed recovery time is shortened by 0.059 s. After the optimization of the new sliding mode control method based on tracking differentiator and RBF neural network, the overshoot of 86 r/min is further reduced, the speed decrease amplitude of load disturbance is reduced again by 48.5%, and the speed recovery time is shortened again by 0.073 s.
Sharing Voltage and Current of an Input-Series–Output-Parallel Boost-LLC Converter
Authors: Zhang Bo , Huang Jin , Song Yongfeng , Liu Xinbo , Ren Jiahui , Kang Chengwei , Ma Yingtao , Sun Shijie , Diao Lijun
Published: September 2022

Modular input-series–output-parallel (ISOP) converters are very suitable for high-voltage and high-power applications. In order to ensure the normal operation of ISOP converters, it is necessary to realize the input-voltage and output-current equalization of each submodule. However, there are few studies on the input-voltage and output-current equalization performance of the ISOP system. In this paper, the input-voltage and output-current equalization characteristics of a Boost + LLC modular ISOP converter are studied based on the small-signal model. In this paper, the small-signal model of an ISOP system is first established, and then the input-voltage and output-current equalization performance of the ISOP system under the condition of inconsistent submodule parameters are analyzed. Finally, simulations and experiments are reported to verify the results. The experimental results show that the ISOP system composed of a Boost + LLC cascaded module has excellent voltage and current self-equalization performance.
Evaporation, Autoignition and Micro-Explosion Characteristics of RP-3 Kerosene Droplets under Sub-Atmospheric Pressure and Elevated Temperature
Authors: Huang Jie , Zhang Hongtao , He Yong , Zhu Yanqun , Wang Zhihua
Published: September 2022

The evaporation, autoignition and micro-explosion characteristics of RP-3 kerosene droplets under sub-atmospheric pressure (0.2–1.0 bar) and elevated temperature (473–1023 K) were experimentally investigated using high-speed camera technology. The results showed that the droplet evaporation rate increased monotonically with increasing temperature and pressure under 573–873 K and 0.2–1.0 bar. The decrease of temperature and pressure was obviously detrimental to the successful autoignition of droplets and increased the ignition delay time. Autoignitions at 0.2 bar were very difficult and required an ambient temperature of at least 973 K, which was about 150 K higher than the minimum ignition temperature at 1.0 bar. Sub-atmospheric pressure environment significantly inhibits the formation of soot particle clusters during the autoignition of droplet. Reducing pressure was also discovered to reduce the likelihood of micro-explosions at 673, 773 and 823 K but increase the bubble growth rate and droplet breakage intensity. Strong micro-explosions with droplet breakage time close to 1 ms were observed at 0.6 bar and 773/823 K, showing the characteristic of bubble inertia control growth.
The Associations of Young Poles with Green Energy in the Context of Self-Assessment of Their Relevant Knowledge and the Importance Attached to the Energy Sources Used
Authors: Baruk Agnieszka Izabela , Goliszek Anna
Published: September 2022

The aim of this article is to identify the associations that young Polish recipients have with green energy, considering their self-assessment of the level of knowledge about green energy and the importance attributed to the energy sources they use on a daily basis. An analysis of the world literature on the subject indicates that there is a cognitive and research gap in the level of market awareness of individual recipients regarding green energy and its sources. This issue has been neglected even more among young people in the context of their associations with this type of energy. To eliminate these research gaps, five hypotheses were formulated. To this end, primary research was carried out using the survey method to collect data. The research covered 311 individual representatives of recipients in Poland aged between 18 and 24. The primary data collected was subjected to quantitative analysis, using specific tests and statistical analysis. Among other things, the following was discovered: (1) the dependence between the self-assessment of the level of knowledge about green energy and the importance attributed to the sources of energy used; (2) the dependence between the self-assessment of the level of knowledge about green energy and the associations with it (mainly negative ones); (3) the dependence between the importance assigned to the sources of energy used and the associations with green energy (mainly positive ones); and (4) that there were sets of recipients characterized by identical associations with green energy within the groups of people selected among the total respondents and among respondents assessing their level of knowledge as low or high, as well as among respondents attributing high or low importance to energy sources. The research results and the conclusions drawn have significant cognitive value and practical application.
Framework for Energy-Averaged Emission Mitigation Technique Adopting Gasoline-Methanol Blend Replacement and Piston Design Exchange
Authors: Mishra Prakash Chandra , Gupta Anand , Samanta Saikat , Ishaq Rihana B. , Khoshnaw Fuad
Published: September 2022

Measurement to mitigate automotive emission varies from energy content modification of fuel to waste energy recovery through energy system upgradation. The proposed energy-averaged emission mitigation technique involves interfacing piston design exchange and gasoline–methanol blend replacement with traditional gasoline for low carbon high energy content creation. Here, we interlinked the CO, CO2, NOx, O2, and HC to different design exchanges of coated pistons through the available brake power and speed of the engine. We assessed the relative effectiveness of various designs and coating thicknesses for different gasoline–methanol blends (0%,5%,10%, and 15%). The analysis shows the replacement of 5%, 10%, and 15% by volume of gasoline with methanol reduces the fuel carbon by 4.167%, 8.34%, and 12.5%, respectively. The fuel characteristics of blends are comparable to gasoline, hence there is no energy infrastructure modification required to develop the same amount of power. The CO and HC reduced significantly, while CO2 and NOx emissions are comparable. Increasing the coating thickness enhances the surface temperature retention and reduces heat transfer. The Type_C design of the steel piston and type_A design of the AlSi piston show temperature retention values of 582 °C and 598 °C, respectively. Type_A and type_B pistons are better compared to type_C and the type_D piston design for emission mitigation due to decarbonization of fuel through gasoline-methanol blend replacement. Surface response methodology predicts Delastic, σvon Mises, and Tsurface with percentage errors of 0.0042,0.35, and 0.9, respectively.