bluuebunny/crossref_metadata_2025 huggingface dataset:
Craniofacial Cephalometric Characteristics and Open Bite Deformity in Individuals with Amelogenesis Imperfecta—A Systematic Review and Meta-Analysis
Authors: Messaoudi Yassine , Kiliaridis Stavros , Antonarakis Gregory S.
Published: June 2023

Background: Individuals with amelogenesis imperfecta (AI) often present with malocclusions, especially a dental or skeletal anterior open bite (AOB). Objectives: To evaluate the craniofacial characteristics in individuals with AI. Material and methods: A systematic literature search was conducted with the PubMed, Web of Science, Embase and Google Scholar databases to identify studies relating to the cephalometric characteristics of individuals with AI, without any language or publication date restrictions. The grey literature was searched using Google Scholar, Opengrey and Worldcat. Only studies with a suitable control group for comparison were included. Data extraction and a risk of bias assessment were carried out. A meta-analysis was performed using the random effects model for cephalometric variables that were evaluated in at least three studies. Results: The initial literature search yielded 1857 articles. Following the removal of duplicates and a screening of the records, seven articles were included in the qualitative synthesis, representing a total of 242 individuals with AI. Four studies were included in the quantitative synthesis. The meta-analysis results showed that individuals with AI present a smaller SNB angle and larger ANB angle than those of control groups in the sagittal plane. In the vertical plane, those with AI present a smaller overbite and larger intermaxillary angle than those without AI. No statistically significant differences were found for the SNA angle when comparing the two groups. Conclusions: Individuals with AI seem to present with more vertical craniofacial growth, leading to an increased intermaxillary angle and decreased overbite. This possibly leads to a more retrognathic mandible with a larger ANB angle due to an anticipated posterior mandibular rotation.
Guided Bone Regeneration Using a Novel Magnesium Membrane: A Literature Review and a Report of Two Cases in Humans
Authors: Blašković Marko , Butorac Prpić Ivana , Blašković Dorotea , Rider Patrick , Tomas Matej , Čandrlić Slavko , Botond Hangyasi David , Čandrlić Marija , Perić Kačarević Željka
Published: June 2023

Guided bone regeneration (GBR) is a common procedure used to rebuild dimensional changes in the alveolar ridge that occur after extraction. In GBR, membranes are used to separate the bone defect from the underlying soft tissue. To overcome the shortcomings of commonly used membranes in GBR, a new resorbable magnesium membrane has been developed. A literature search was performed via MEDLINE, Scopus, Web of Science and PubMed in February 2023 for research on magnesium barrier membranes. Of the 78 records reviewed, 16 studies met the inclusion criteria and were analyzed. In addition, this paper reports two cases where GBR was performed using a magnesium membrane and magnesium fixation system with immediate and delayed implant placement. No adverse reactions to the biomaterials were detected, and the membrane was completely resorbed after healing. The resorbable fixation screws used in both cases held the membranes in place during bone formation and were completely resorbed. Therefore, the pure magnesium membrane and magnesium fixation screws were found to be excellent biomaterials for GBR, which supports the findings of the literature review.
How to Continue? New Approaches to Investigating the Effects of Adaptive Math Learning Programs on Students’ Performance, Self-Concept, and Anxiety
Authors: Hilz Anna , Guill Karin , Roloff Janina , Sommerhoff Daniel , Aldrup Karen
Published: June 2023

Math learning programs were expected to revolutionize students’ learning, but their effects so far have mostly been disappointing. Following the debate about why to continue research on math learning programs, we aimed to reformulate this question into how to continue this research. Investigations to date have neither considered a sufficiently wide set of outcome variables nor differentiated between performance measures (e.g., measuring addition and subtraction performance separately) and affective-motivational variables. Moreover, as students can only benefit from a program if they use it, researchers need to take practice behavior into account. Thus, we investigated whether the adaptive arithmetic learning program Math Garden fostered students’ addition and subtraction performance, their math self-concept, and a reduction of their math anxiety. We also investigated how practice behavior (practiced tasks/weeks) affected these outcomes. We used a randomized pretest-posttest control group design with 376 fifth-grade students in Germany. Students in the experimental condition practiced with Math Garden for 20.7 weeks and had an increase in math self-concept. The more subtraction tasks the students practiced, the more they improved their subtraction performance. We found no effects on math anxiety. The results are discussed in terms of providing a starting point for new directions in future research.
Who Wants to Enhance Their Cognitive Abilities? Potential Predictors of the Acceptance of Cognitive Enhancement
Authors: Grinschgl Sandra , Berdnik Anna-Lena , Stehling Elisabeth , Hofer Gabriela , Neubauer Aljoscha
Published: June 2023

With advances in new technologies, the topic of cognitive enhancement has been at the center of public debate in recent years. Various enhancement methods (e.g., brain stimulation, smart drugs, or working memory training) promise improvements in one’s cognitive abilities such as intelligence and memory. Although these methods have been rather ineffective so far, they are largely available to the general public and can be applied individually. As applying enhancement might be accompanied by certain risks, it is important to understand which individuals seek to enhance themselves. For instance, individuals’ intelligence, personality, and interests might predict their willingness to get enhanced. Thus, in a preregistered study, we asked 257 participants about their acceptance of various enhancement methods and tested predictors thereof, such as participants’ psychometrically measured and self-estimated intelligence. While both measured and self-estimated intelligence as well as participants’ implicit beliefs about intelligence, did not predict participants’ acceptance of enhancement; a younger age, higher interest in science-fiction, and (partially) higher openness as well as lower conscientiousness did. Thus, certain interests and personality traits might contribute to the willingness to enhance one’s cognition. Finally, we discuss the need for replication and argue for testing other potential predictors of the acceptance of cognitive enhancement.
Improving Significant Wave Height Prediction Using a Neuro-Fuzzy Approach and Marine Predators Algorithm
Authors: Ikram Rana Muhammad Adnan , Cao Xinyi , Sadeghifar Tayeb , Kuriqi Alban , Kisi Ozgur , Shahid Shamsuddin
Published: June 2023

This study investigates the ability of a new hybrid neuro-fuzzy model by combining the neuro-fuzzy (ANFIS) approach with the marine predators’ algorithm (MPA) in predicting short-term (from 1 h ahead to 1 day ahead) significant wave heights. Data from two stations, Cairns and Palm Beach buoy, were used in assessing the considered methods. The ANFIS-MPA was compared with two other hybrid methods, ANFIS with genetic algorithm (ANFIS-GA) and ANFIS with particle swarm optimization (ANFIS-PSO), in predicting significant wave height for multiple lead times ranging from 1 h to 1 day. The multivariate adaptive regression spline was investigated in deciding the best input for prediction models. The ANFIS-MPA model generally offered better accuracy than the other hybrid models in predicting significant wave height in both stations. It improved the accuracy of ANFIS-PSO and ANFIS-GA by 8.3% and 11.2% in root mean square errors in predicting a 1 h lead time in the test period.
On Detection of Anomalous VHF Propagation over the Adriatic Sea Utilising a Software-Defined Automatic Identification System Receiver
Authors: Valčić Sanjin , Brčić David
Published: June 2023

This paper represents observations on detection of Very High Frequency (VHF) anomalous propagation over the area of the Adriatic Sea. During the research campaign, a Software Defined Radio (SDR) Automatic Identification System (AIS) receiver was employed for collection of AIS data packets at a fixed location in the Northern Adriatic. Data were collected during the 24-h period (25 February 2023 15:32 LT to 26 February 2023 15:32 LT), providing information from 115 AIS targets, or 159 965 AIS packets with 54.3% Packet Error Rate (PER), respectively. Subsequent analysis and post-processing of successfully demodulated signals and decoded packets was presented further. In certain instances, the SDR AIS receiver detected, received and decoded data packets from AIS targets distant several orders of magnitude larger than the VHF nominal ranges. To determine the magnitude of line-of-sight and over-the-horizon radio waves propagation, the great circle distances between the SDR AIS receiver antenna and AIS packets’ decoded positions were calculated, revealing hundreds of Nautical Miles (NM). Possible reasons for these occurrences, including tropospheric scattering, diffraction, ionospheric sporadic E layer and refraction were discussed and evaluated, in accordance, among others, with the previous research. By exclusion criteria and neglection of possible causes, it was concluded that the enhanced, over-the-horizon propagation of AIS signals occurred as a result of refraction effects, namely trapping/ducting, subrefraction and superrefraction. Data from nine World Meteorological Organization (WMO) radiosondes surrounding the greater reception area were collected for the same observation periods. Atmospheric profiles were created using Advanced Refractive Effects Prediction System (AREPS) program, and analysed for each individual station measurement. The results confirmed anomalous, over-the-horizon enhanced propagation and their probable origins, i.e., the occurrence of refractive conditions in the atmosphere over the Adriatic Sea area. These findings provide a solid foundation for further research in the area of propagation of VHF signals and their anomalous features caused by the atmospheric phenomenon effects.
Reliability Assessment of NPP Safety Class Equipment Considering the Manufacturing Quality Assurance Process
Authors: Khalaquzzaman Mohammad , Lee Seung Jun , Hossen Muhammed Mufazzal
Published: June 2023

Quality and safety are intensely related and go hand in hand. Quality of the safety-grade equipment is very important for the safety of a nuclear power plant (NPP) and achieving production goals. During manufacturing of plant components or equipment, deviation from the design might occur at different stages of manufacturing for various reasons, such as a lack of skilled manpower, deviation of materials, human errors, malfunction of equipment, violation of manufacturing procedure, etc. These deviations can be assessed cautiously and taken into consideration in the final safety analysis report (FSAR) before issuing an operating license. In this paper, we propose a Bayesian belief network for quality assessment of safety class equipment of NPPs with a few examples. The proposed procedure is a holistic approach for estimation of equipment failure probability considering manufacturing deviations and errors. Case studies for safety-class dry transformers and reactor pressurizers employing the proposed method are also presented in this article. This study provides insights for probabilistic safety assessment engineers and nuclear plant regulators for improved assessment of NPP safety.
Delineating Housing Submarkets Using Space–Time House Sales Data: Spatially Constrained Data-Driven Approaches
Authors: Chen Meifang , Chun Yongwan , Griffith Daniel A.
Published: June 2023

With the increasing availability of large volumes of space–time house data, delineating space–time housing submarkets is of interest to real estate agents, homebuyers, urban policymakers, and spatial researchers, among others. Appropriately delineated housing submarkets can help nurture submarket monitoring and housing policy developments. Although submarkets are often expected to represent areas with similar houses, neighborhoods, and amenities characteristics, delineating spatially contiguous areas with virtually no fragmented small areas remains challenging. Furthermore, housing submarkets can potentially change over time along with concomitant urban transformations, such as urban sprawl, gentrification, and infrastructure improvements, even in large metropolitan areas, which can complicate delineating submarkets with data for lengthy time periods. This study proposes a new method for integrating a random effects model with spatially constrained data-driven approaches in order to identify stable and reliable space–time housing submarkets, instead of their dynamic changes. This random effects model specification is expected to capture time-invariant spatial patterns, which can help identify stable submarkets over time. It highlights two spatially constrained data-driven approaches, ClustGeo and REDCAP, which perform equally well and produce similar space–time housing submarket structures. This proposed method is utilized for a case study of Franklin County, Ohio, using 19 years of space–time private house transaction data (2001–2019). A comparative analysis using a hedonic model demonstrates that the resulting submarkets generated by the proposed method perform better than popular alternative submarket creators in terms of model performances and house price predictions. Enhanced space–time housing delineation can furnish a way to better understand the sophisticated housing market structures, and to help enhance their modeling and housing policy. This paper contributes to the literature on space–time housing submarket delineations with enhanced approaches to effectively generate spatially constrained housing submarkets using data-driven methods.
Incorporating High-Speed Rail Development Scenario for Tourism Land Use Simulation: A Case Study of Xinxing County, China
Authors: Jiao Zhenzhi , Li Shaoying , Lin Zhangping , Lai Zhipeng , Wu Zhuo , Liu Lin
Published: June 2023

High-speed rail (HSR) has been proven to drive the development of regional tourism. However, few studies paid attention to the impact of HSR on future tourism land use. In this study, points of interest (POI) were used to obtain the locations and types of tourism facilities, and high-resolution remote sensing images helped us determine the spatial extents of the tourism facilities, so that tourism land could be identified. A system dynamics (SD) model was coupled with the patch-generating land use simulation (PLUS) model to simulate future tourism land by considering two scenarios, including HSR-led development (HRD) and the historical development pattern (HD) scenario. The SD model was employed to project the amount of tourism land and determine the HSR effects via empirical analysis. The PLUS model was applied to simulate the spatial distribution of tourism land and model the HSR effect by adopting a planned tourism area as the development area. The study area is Xinxing County in Guangdong Province, China, a county dominated by rural tourism, with the HSR expected to open in 2025. The results revealed that the SD-PLUS model has great advantages in simulating tourism land use change, and the HRD scenario leads to major changes in the sources of tourism land growth. This research provides new insights for policymakers on making countermeasures for the sustainability of tourism and rural revitalization at the county level.
Assessing the Rural–Urban Transition of China during 1980–2020 from a Coordination Perspective
Authors: Zhang Shiwei , Zhao Jinghui , Jiang Yanfeng , Cheshmehzangi Ali , Zhou Wenbin
Published: June 2023

Under the context of global rapid urbanization, exploring the dynamics of rural–urban transition in China can provide valuable experience for the Global South. In this study, we evaluate the rural–urban transition in China, from 1980 to 2020, based on socioeconomic data and a rural–urban transition coordination model by constructing a rural–urban development and integration index system. We identify the state and transition types, and we present optimization paths. The results show that, since the reform and opening-up, the rural–urban development index (URDI) in China has gradually expanded among regions while the rural–urban integrated index (URII) has experienced a trend of decline followed by an increase. Over the past 40 years, the spatial distribution characteristics of the ΔURDI have been “south high–north low”, while the ΔURII has had a balanced spatial distribution. Over the first two decades of the past 40 years, the rural–urban transition in eastern coastal China was more coordinated, while regions with less coordination showed a two-tiered distribution pattern; over the last two decades, the coordination degree has increased. Over the past 40 years, the spatial distribution of high coordination presents “T-shaped” coastal and riverside characteristics. The transition types and coupling relationships of state regions are identified. Finally, optimization pathways are proposed for each type to further promote rural–urban integration.
Characterizing Sprawl Development in Urban China: A Perspective from Urban Amenity
Authors: Zhang Dinglin , Wu Yangyi , Liu Meitong
Published: June 2023

Urban sprawl in China presents unique characteristics that differ from those commonly studied in Western contexts, an aspect not fully explored in previous studies. Therefore, taking Wuhan, Hubei as an example and integrating population data, remote sensing data, and POI data, this research offers a perspective on sprawl development in urban China. By incorporating population, urban land use, and urban amenities, this study measures their dynamics to classify urban spaces and employs spatial regression models to identify the characteristics of sprawl development with spatial effects controlled. It further applies geographically weighted regression to examine the underlying spatial heterogeneity. The findings indicate that population growth and urban land expansion do not align perfectly, and further exploration identifies the various trends of sprawl development in urban core and periphery areas. On the other hand, some suburban areas show compact development trends, but the growth of local amenities may be limited due to the historical sprawl development legacies. Regression results reveal specific characteristics of this sprawl development. Key findings include the following: (1) shaped by the triple process of sprawl development of urban renewal, suburbanization, and rural revitalization, Wuhan shows a significant core-periphery structure with the trend of polycentricity; (2) overcrowding in central urban districts is the primary driver of sprawl development; (3) most traditional suburbs in Wuhan have emerged as a consequence of rapid urbanization with a legacy of sprawl development; (4) spatial heterogeneity across urban spaces highlights the necessity for locally tailored approaches to regulating sprawl development.
Optimization of Airplane Landing in Crosswind Conditions for Minimum Tire Wear
Authors: Cacciola Stefano , Riboldi Carlo , Generali Edoardo
Published: June 2023

Being one of the most critical phases of a flight, landing deserves specific attention, especially when the aircraft is subject to external disturbances such as wind. A notable concern associated with touchdown events, especially when crosswind is present, is tire wear. This work is aimed first at developing a nonlinear flight simulator able to handle the entire landing maneuver in non-null wind conditions, considering the airborne phase, the ground run, and the transition between them. Then, the simulator is included in an optimal process to define the landing technique associated with the minimum tire wear. The methodology is tested in a simulation environment with a realistic model of a reference aircraft, showing that a significant reduction in tire wear can be obtained by optimizing the sideslip angle at touchdown and the lateral–directional controls after the airplane touches the runway with both legs of the main landing gear. The amount of the reduction is highly variable and depends on the landing conditions, e.g., the velocity and glide path angle. It may range from some percentage points up to 45%.
Construction Method of Digital Twin System for Thin-Walled Workpiece Machining Error Control Based on Analysis of Machine Tool Dynamic Characteristics
Authors: Zhao Wenkai , Li Rongyi , Liu Xianli , Ni Jun , Wang Chao , Li Canlun , Zhao Libo
Published: June 2023

In the intelligent optimization process of aerospace thin-walled parts, there are issues such as solidification of core knowledge base, high system coupling degree, and real-time evaluation and optimization feedback required for the knowledge base. These problems make it difficult to expand the functions of the digital twin system and meet the growing processing needs, ultimately hindering the application of digital twin technology. To address these issues, a digital twin system for controlling processing errors in thin-walled parts was built using a microservices architecture. In addition, a method for building a digital twin system at the processing unit level with the best coupling degree was proposed, mainly targeting the dynamic characteristics analysis knowledge base of thin-walled parts. Furthermore, to meet the requirements for backward compatibility of the processing unit level digital twin system, a comprehensive solution including the construction, operation, evaluation, optimization, and visualization of a knowledge base for the dynamic characteristics of the processing unit was proposed, providing guidance for the digital transformation and upgrading of CNC machine tools and the optimization of processing technology based on digital twin technology.
Modeling of the Variation Propagation for Complex-Shaped Workpieces in Multi-Stage Machining Processes
Authors: Yang Fuyong , Zhang Peiyue , Zhang Xiaobing , Cao Juyong , Xing Yanfeng
Published: June 2023

Variation prediction and quality control for complex-shaped workpieces in automotive and aerospace fields with multi-stage machining processes have drawn significant attention because of the widespread application and increasing diversity of these kinds of workpieces. To finish the final workpieces with complex shapes, multiple setups and operations are often applied in machining processes. However, sources of geometric error, such as fixture error, datum error, machine tool path error, and the dimensional quality of the product, interact complicatedly at different stages. These complex interactions pose significant challenges to final product error prediction and reduction. Manufacturing error prediction based on stream of variation is an effective way to control the machining quality. However, there are few integrated models that can describe the interactions among types of geometric error sources from different stages for different kinds of complex workpieces. This paper proposes a modified error prediction model to systematically capture the interactions of different error sources among different operations for complex-shaped workpieces in multi-stage machining processes. Using differential motion vectors, the connection of all key variations from machine, fixture, and workpiece is established. This modified model can not only handle general fixture layouts for complex workpieces, but also introduce machining-induced variations. Based on this model, the main error sources identification method and error compensation method are proposed. In order to evaluate the effectiveness of the proposed method, engine blocks are used to be machined as an example. Compared with a machining process without a compensating strategy, the average machining error of the key feature is reduced by 80.5% after compensating for the main error sources.
Lifetime Extension Method for Three-Phase Voltage Source Converters Using Discontinuous PWM Scheme with Hybrid Offset Voltage
Authors: Kim Jaechang , Nguyen Minh-Hoang , Kwak Sangshin , Choi Seungdeog
Published: June 2023

This paper proposes a lifespan extension technique for three-phase voltage inverters using hybrid offset voltage. The proposed method lengthens the inverter lifetime by independently adjusting the switching frequency of the three phases in accordance with the aging degree. To reduce the switching operation of the phase with the shortest lifetime, the proposed technique injects the offset voltage for generalized discontinuous pulse-width modulation PWM (GDPWM) into the reference voltage in the region where the switching operation of the shortest lifespan phase can be stopped. When the switching operation does not need to be stopped, the offset voltage for space vector PWM (SVPWM) is injected into the reference voltage for high inverter load current quality. An offset voltage that varies according to the need to stop the switching operation is the proposed hybrid offset voltage. Using the proposed hybrid offset voltage, the switching frequencies of the three phases are independently controllable. In addition, since only the switching operation of the phase having the shortest lifespan is reduced, the load current quality in accordance with the switching operation reduction is good compared to the conventional method to simultaneously diminish all phase switching frequencies. The proposed method significantly increases the reliability of the three-phase voltage inverter, where the thermal stress of the phase having the shortest lifespan is decreased up to 55%, whereas the inverter lifetime can be increased by 10 times. The proposed technique was verified by simulations and experiments.
Research on Multiphase Flow and Nozzle Wear in a High-Pressure Abrasive Water Jet Cutting Head
Authors: Zou Xiang , Fu Liandong , Wu Lin , Zuo Wenhao
Published: June 2023

Research on the mixing process of gas–liquid–solid multiphase flow in a high-pressure abrasive water jet (HP-AWJ) is of great significance in improving the performance of water jet cutting. In this paper, the Euler method-VOF model, a computational fluid dynamics (CFD) simulation method, is used to solve the multiphase flow of air–water in an abrasive water jet (AWJ). The Euler–Lagrange method is further used to study the multiphase flow of abrasive particles. The method considers the shape factor of the particle, uses the Rosin–Rammler function, and defines an effective model for the particle-to-wall wear model. By solving the velocity of the continuous phase and particulate phase in the AWJ cutting head, the problem of nozzle wear caused by particles is studied. Finally, the exit velocity of the AWJ and particle wear are investigated by varying the model’s parameters. The results show that the double abrasive tube model effectively improved the problem of one-sided wear inside the nozzle, and the tangential velocity of the air affected the acceleration process of the abrasive inside the nozzle, with smaller abrasive velocity resulting in less wear on the model. Simultaneously, the effects of the abrasive inlet tube and mixing chamber size on abrasive exit velocity and nozzle wear are analyzed. The results obtained provide valuable guidance for addressing the multiphase flow mixing issues in the AWJ, improving the abrasive acceleration process and extending the nozzle’s lifetime.
Dendrimers: Synthesis, Encapsulation Applications and Specific Interaction with the Stratum Corneum—A Review
Authors: Bacha Katia , Chemotti Catherine , Mbakidi Jean-Pierre , Deleu Magali , Bouquillon Sandrine
Published: June 2023

Dendrimers are increasingly being studied in the context of encapsulation. Many potential applications of dendrimers are based on their properties. They are used in drug delivery systems, cosmetics, food and chemistry. This review is first devoted to different synthesis approaches for dendrimers and to their ability to encapsulate active molecules. Their applications in different fields, as well as their cytotoxicity, are then detailed. To conclude this review, the main works on the interaction of dendrimers with the stratum corneum (SC) are also presented.
Grey Wolf Optimizer for RES Capacity Factor Maximization at the Placement Planning Stage
Authors: Bramm Andrey M. , Eroshenko Stanislav A. , Khalyasmaa Alexandra I. , Matrenin Pavel V.
Published: June 2023

At the current stage of the integration of renewable energy sources into the power systems of many countries, requirements for compliance with established technical characteristics are being applied to power generation. One such requirement is the installed capacity utilization factor, which is extremely important for optimally placing power facilities based on renewable energy sources and for the successful development of renewable energy. Efficient placement maximizes the installed capacity utilization factor of a power facility, increasing energy efficiency and the payback period. The installed capacity utilization factor depends on the assumed meteorological factors relating to geographical location and the technical characteristics of power generation. However, the installed capacity utilization factor cannot be accurately predicted, since it is necessary to know the volume of electricity produced by the power facility. A novel approach to the optimization of placement of renewable energy source power plants and their capacity factor forecasting was proposed in this article. This approach combines a machine learning forecasting algorithm (random forest regressor) with a metaheuristic optimization algorithm (grey wolf optimizer). Although the proposed approach assumes the use of only open-source data, the simulations show better results than commonly used algorithms, such as random search, particle swarm optimizer, and firefly algorithm.
Hybrid Fuzzy Rule Algorithm and Trust Planning Mechanism for Robust Trust Management in IoT-Embedded Systems Integration
Authors: Reddy Nagireddy Venkata Rajasekhar , Padmaja Pydimarri , Mahdal Miroslav , Seerangan Selvaraj , Vimal Vrince , Talasila Vamsidhar , Cepova Lenka
Published: June 2023

The Internet of Things (IoT) is rapidly expanding and becoming an integral part of daily life, increasing the potential for security threats such as malware or cyberattacks. Many embedded systems (ESs), responsible for handling sensitive data or facilitating secure online activities, must adhere to stringent security standards. For instance, payment processors employ security-critical components as distinct chips, maintaining physical separation from other network components to prevent the leakage of sensitive information such as cryptographic keys. Establishing a trusted environment in IoT and ESs, where interactions are based on the trust model of communication nodes, is a viable approach to enhance security in IoT and ESs. Although trust management (TM) has been extensively studied in distributed networks, IoT, and ESs, significant challenges remain for real-world implementation. In response, we propose a hybrid fuzzy rule algorithm (FRA) and trust planning mechanism (TPM), denoted FRA + TPM, for effective trust management and to bolster IoT and ESs reliability. The proposed system was evaluated against several conventional methods, yielding promising results: trust prediction accuracy (99%), energy consumption (53%), malicious node detection (98%), computation time (61 s), latency (1.7 ms), and throughput (9 Mbps).
Multilingual Multiword Expression Identification Using Lateral Inhibition and Domain Adaptation
Authors: Avram Andrei-Marius , Mititelu Verginica Barbu , Păiș Vasile , Cercel Dumitru-Clementin , Trăușan-Matu Ștefan
Published: June 2023

Correctly identifying multiword expressions (MWEs) is an important task for most natural language processing systems since their misidentification can result in ambiguity and misunderstanding of the underlying text. In this work, we evaluate the performance of the mBERT model for MWE identification in a multilingual context by training it on all 14 languages available in version 1.2 of the PARSEME corpus. We also incorporate lateral inhibition and language adversarial training into our methodology to create language-independent embeddings and improve its capabilities in identifying multiword expressions. The evaluation of our models shows that the approach employed in this work achieves better results compared to the best system of the PARSEME 1.2 competition, MTLB-STRUCT, on 11 out of 14 languages for global MWE identification and on 12 out of 14 languages for unseen MWE identification. Additionally, averaged across all languages, our best approach outperforms the MTLB-STRUCT system by 1.23% on global MWE identification and by 4.73% on unseen global MWE identification.
Generating Representative Phrase Sets for Text Entry Experiments by GA-Based Text Corpora Sampling
Authors: Ljubic Sandi , Salkanovic Alen
Published: June 2023

In the field of human–computer interaction (HCI), text entry methods can be evaluated through controlled user experiments or predictive modeling techniques. While the modeling approach requires a language model, the empirical approach necessitates representative text phrases for the experimental stimuli. In this context, finding a phrase set with the best language representativeness belongs to the class of optimization problems in which a solution is sought in a large search space. We propose a genetic algorithm (GA)-based method for extracting a target phrase set from the available text corpus, optimizing its language representativeness. Kullback–Leibler divergence is utilized to evaluate candidates, considering the digram probability distributions of both the source corpus and the target sample. The proposed method is highly customizable, outperforms typical random sampling, and exhibits language independence. The representative phrase sets generated by the proposed solution facilitate a more valid comparison of the results from different text entry studies. The open source implementation enables the easy customization of the GA-based sampling method, promotes its immediate utilization, and facilitates the reproducibility of this study. In addition, we provide heuristic guidelines for preparing the text entry experiments, which consider the experiment’s intended design and the phrase set to be generated with the proposed solution.
A Semantic Representation Method of Building Codes Applied to Compliance Checking
Authors: Li Yuchao , Yang Mingsong , Zhao Qin , Li Zongjian , Ma Zhaoxi , Liu Yunhe , Hei Xinhong
Published: June 2023

Compliance checking is a very important step in engineering construction. With the development of information technology, automated compliance checking (ACC) has been paid more and more attention by researchers. One of the most important steps in automated compliance checking is the representation of the code information. However, the relationship constraint is often ignored in the code information and spatial geometric relationship is challenging to represent. The general code representation method does not have enough ability to identify the situation that does not meet the checking conditions because it is easy to cause semantic ambiguity in the checking results. This paper proposes a code representation method, and the building code information is represented in five parts. Relationships in the engineering domain and spatial relationships can be represented in constraint mode; different spatial relationship constraint-checking methods are also explicated. Constraint subject and constraint item can distinguish checking conditions and requirements, which supports semantic checking results. The mapping between the building information ontology and the code concepts is established, which can be used to automatically generate reasoning rules for compliance checking. Finally, the proposed method is verified by the representation of the China Metro Design Code and the application of the actual Metro model.
Divide and Conquer: A Location-Allocation Approach to Sectorization
Authors: Lopes Cristina , Rodrigues Ana Maria , Romanciuc Valeria , Ferreira José Soeiro , Öztürk Elif Göksu , Oliveira Cristina
Published: June 2023

Sectorization is concerned with dividing a large territory into smaller areas, also known as sectors. This process usually simplifies a complex problem, leading to easier solution approaches to solving the resulting subproblems. Sectors are built with several criteria in mind, such as equilibrium, compactness, contiguity, and desirability, which vary with the applications. Sectorization appears in different contexts: sales territory design, political districting, healthcare logistics, and vehicle routing problems (agrifood distribution, winter road maintenance, parcel delivery). Environmental problems can also be tackled with a sectorization approach; for example, in municipal waste collection, water distribution networks, and even in finding more sustainable transportation routes. This work focuses on sectorization concerning the location of the area’s centers and allocating basic units to each sector. Integer programming models address the location-allocation problems, and various formulations implementing different criteria are compared. Methods to deal with multiobjective optimization problems, such as the ϵ-constraint, the lexicographic, and the weighted sum methods, are applied and compared. Computational results obtained for a set of benchmarking instances of sectorization problems are also presented.
Rolling Horizon Robust Real-Time Economic Dispatch with Multi-Stage Dynamic Modeling
Authors: Wang Luyu , Xiong Houbo , Shi Yunhui , Guo Chuangxin
Published: June 2023

A multi-stage robust real-time economic dispatch model (MRRTD) for power systems is proposed in this paper. The MRRTD takes the dynamic form of multi-stage robust optimization as the framework to naturally simulate the operation of equipment that is temporally coupled, e.g., utility-level energy storage systems. For normal systems, the MRRTD can work directly in short time slots with a rolling horizon. For large-scale systems, the MRRTD expands the time-slot scale and generates optimal dispatch policies. With this guidance, the real-time dispatch decision can be swiftly made thereafter. In addition, a dynamic uncertainty set based on deep learning is proposed, which can dynamically refine the covering ability for probable occurred wind power scenarios. To efficiently solve the MRRTD, a novel fast robust dual dynamic programming method is employed. The effectiveness of the proposed model and solution algorithm, especially the improved scalability compared to several other dynamic economic dispatch methods, are demonstrated by simulation results from six benchmark test cases ranging from a modified IEEE 6-bus system to a 6495-bus system.
Performance Analysis of the CHAID Algorithm for Accuracy
Authors: Yang Yeling , Yi Feng , Deng Chuancheng , Sun Guang
Published: June 2023

The chi-squared automatic interaction detector (CHAID) algorithm is considered to be one of the most used supervised learning methods as it is adaptable to solving any kind of problem at hand. We are keenly aware of the non-linear relationships among CHAID maps, and they can empower predictive models with stability. However, we do not precisely know how high its accuracy. To determine the perfect scope the CHAID algorithm fits into, this paper presented an analysis of the accuracy of the CHAID algorithm. We introduced the causes, applicable conditions, and application scope of the CHAID algorithm, and then highlight the differences in the branching principles between the CHAID algorithm and several other common decision tree algorithms, which is the first step towards performing a basic analysis of CHAID algorithm. We next employed an actual branching case to help us better understand the CHAID algorithm. Specifically, we used vehicle customer satisfaction data to compare multiple decision tree algorithms and cited some factors that affect the accuracy and some corresponding countermeasures that are more conducive to obtaining accurate results. The results showed that CHAID can analyze the data very well and reliably detect significantly correlated factors. This paper presents the information required to understand the CHAID algorithm, thereby enabling better choices when the use of decision tree algorithms is warranted.
On the Rate of Convergence of Greedy Algorithms
Authors: Temlyakov Vladimir
Published: June 2023

In this paper, a new criterion for the evaluation of the theoretical efficiency of a greedy algorithm is suggested. Using this criterion, we prove some results on the rate of convergence of greedy algorithms, which provide expansions. We consider both the case of Hilbert spaces and the more general case of Banach spaces. The new component of this paper is that we bound the error of approximation by the product of two norms—the norm of f and the A1-norm of f. Typically, only the A1-norm of f is used. In particular, we establish that some greedy algorithms (Pure Greedy Algorithm (PGA) and its modifications) are as good as the Orthogonal Greedy Algorithm (OGA) in this new sense of the rate of convergence, while it is known that the PGA is much worse than the OGA in the standard sense. Our new results provide better bounds for the accuracy than known results in the case of small ∥f∥.
Next-Generation Sequencing Data-Based Association Testing of a Group of Genetic Markers for Complex Responses Using a Generalized Linear Model Framework
Authors: Xu Zheng , Yan Song , Wu Cong , Duan Qing , Chen Sixia , Li Yun
Published: June 2023

To study the relationship between genetic variants and phenotypes, association testing is adopted; however, most association studies are conducted by genotype-based testing. Testing methods based on next-generation sequencing (NGS) data without genotype calling demonstrate an advantage over testing methods based on genotypes in the scenarios when genotype estimation is not accurate. Our objective was to develop NGS data-based methods for association studies to fill the gap in the literature. Single-variant testing methods based on NGS data have been proposed, including our previously proposed single-variant NGS data-based testing method, i.e., UNC combo method. The NGS data-based group testing method has been proposed by us using a linear model framework which can handle continuous responses. In this paper, we extend our linear model-based framework to a generalized linear model-based framework so that the methods can handle other types of responses especially binary responses which is a common problem in association studies. To evaluate the performance of various estimators and compare them we performed simulation studies. We found that all methods have Type I errors controlled, and our NGS data-based methods have better performance than genotype-based methods for other types of responses, including binary responses (logistics regression) and count responses (Poisson regression), especially when sequencing depth is low. We have extended our previous linear model (LM) framework to a generalized linear model (GLM) framework and derived NGS data-based methods for a group of genetic variables. Compared with our previously proposed LM-based methods, the new GLM-based methods can handle more complex responses (for example, binary responses and count responses) in addition to continuous responses. Our methods have filled the literature gap and shown advantage over their corresponding genotype-based methods in the literature.
A Neglected Extensor Hallucis Longus Tendon Rupture Caused by Arthritic Adhesion
Authors: Won Sung Hun , Kim Sung Hwan , Lee Young Koo , Chun Dong-Il , Lee Byung-Ryul , Kim Woo-Jong
Published: June 2023

Extensor hallucis longus tendon injury is relatively rare and is principally caused by a laceration when a sharp object is dropped on the instep. Primary suturing is possible if the injury is acute, but if the tear is chronic, tendon contracture causes the space between the edges of the tear to widen, disrupting the end-to-end connection. In particular, a claw toe or checkrein foot deformity may develop over time due to adhesion of the lower leg tendons near the fracture site or scar. We report on a 44-year-old man who visited our outpatient clinic complaining of pain in the right foot and a hindered ability to extend his great toe. He had enjoyed playing soccer during his schooldays; since that time, the extension of that toe had become somewhat difficult. T2-weighted sagittal magnetic resonance imaging revealed that the continuity of the extensor hallucis longus tendon had been lost at the distal phalangeal base attachment site, and that the region of the proximal tendon was retracted to level of the middle shaft of the proximal phalanx. The findings allowed us to diagnose extensor hallucis longus tendon rupture accompanying osteoarthritic changes in the joint and soft tissues. We performed surgical tenorrhaphy and adhesiolysis. This is a rare case of extensor hallucis longus tendon rupture caused by minor trauma. Arthritis that developed at a young age caused the adhesions. If patients with foot and ankle arthritis show tendon adhesion at the arthritic site, tendon rupture can develop even after minor trauma or intense stretching.
Giant Echinococcosis of the Liver with Suppuration: A Case Report and Review of the Literature
Authors: Kosmidis Christoforos S. , Papadopoulos Konstantinos , Mystakidou Chrysi Maria , Sevva Christina , Koulouris Charilaos , Varsamis Nikolaos , Mantalovas Stylianos , Lagopoulos Vasileios , Magra Vasiliki , Theodorou Vasiliki , Ouzouni Styliani , Iason Katsios Nikolaos , Axi Paraskevi , Sapalidis Konstantinos , Kesisoglou Isaak
Published: June 2023

Purpose: Cystic echinococcosis (CE) is a common, complex parasitic disease that constitutes a major public health concern. CE demonstrates high endemicity in areas where dogs are used for herding or where animal husbandry practices involve close contact with livestock. It can clinically manifest with a variety of signs and symptoms, such as cholangitis, jaundice, pancreatitis, external biliary fistula, inferior vena cava obstruction, portal hypertension, and superinfection. The latter can notably be related to suppuration, either by rupture or bacteremia. The aim of this study is to report our 76-year-old patient who presented with a primarily infected giant-suppurated hydatid cyst of the liver and its surgical management. Methods: In this case, the diagnosis was based primarily on clinical presentation, computed tomography (CT) scan, and magnetic resonance imaging (MRI) of the patient’s abdomen. The surgical procedure of choice was the partial retaining of the pericystic membrane and drainage of the cystic contents (partial pericystectomy). Results: The surgical management and meticulous long-term follow-up of our patient produced a positive outcome without any post-operative complications.