bluuebunny/crossref_metadata_2025 huggingface dataset:
Pathophysiology, Diagnosis and Treatment of Spontaneous Coronary Artery Dissection in Peripartum Women
Authors: Cano-Castellote Marta , Afanador-Restrepo Diego Fernando , González-Santamaría Jhonatan , Rodríguez-López Carlos , Castellote-Caballero Yolanda , Hita-Contreras Fidel , Carcelén-Fraile María del Carmen , Aibar-Almazán Agustín
Published: November 2022

Spontaneous coronary artery dissection (SCAD) is an infrequent cause of nonobstructive ischemic heart disease in previously healthy young women and therefore is not usually considered in differential diagnoses. The overall incidence of SCAD in angiographic series is between 0.28 and 1.1%, with a clear predominance in young, healthy women (70%) of whom approximately 30% are in the postpartum period. In the United Kingdom, between 2008 and 2012, SCAD was the cause of 27% of acute myocardial infarctions during pregnancy, with a prevalence of 1.81 per 100,000 pregnancies. Regarding the mechanism of arterial obstruction, this may be due to the appearance of an intramural hematoma or to a tear in the intima of the arteries, both spontaneously. Although multiple diagnostic methods are available, it is suggested to include an appropriate anamnesis, an electrocardiogram in the first 10 min after admission to the service or the onset of symptoms, and subsequently, a CT angiography of the coronary arteries or urgent coronary angiography if the hemodynamic status of the patient allows it. Treatment should be individualized for each case; however, the appropriate approach is generally based on two fundamental pillars: conservative medical treatment with antiplatelet agents, beta-blockers, and nitrates, and invasive treatment with percutaneous coronary intervention for stent implantation or balloon angioplasty, if necessary.
TEGDMA-Functionalized Dicalcium Phosphate Dihydrate Resin-Based Composites Prevent Secondary Caries in an In Vitro Biofilm Model
Authors: Ionescu Andrei , Hahnel Sebastian , Chiari Marina , König Andreas , Delvecchio Paolo , Braga Roberto , Zambelli Vanessa , Brambilla Eugenio
Published: November 2022

This study evaluated the efficacy of experimental TEGDMA-functionalized dicalcium phosphate dihydrate (T-DCPD) filler-based resin-based composites (RBC) in preventing caries lesions around the restoration margins (secondary caries, SC). Standardized Class-II cavities were made in sound molars with the cervical margin in dentin. Cavities were filled with a commercial resin-modified glass-ionomer cement (RMGIC) or experimental RBCs containing a bisGMA-TEGDMA resin blend and one of the following inorganic fractions: 60 wt.% Ba glass (RBC-0); 40 wt.% Ba glass and 20 wt.% T-DCPD (RBC-20); or 20 wt.% Ba glass and 40 wt.% T-DCPD (RBC-40). An open-system bioreactor produced Streptococcus mutans biofilm-driven SC. Specimens were scanned using micro-CT to evaluate demineralization depths. Scanning electron microscopy and energy-dispersive X-ray spectroscopy characterized the specimen surfaces, and antimicrobial activity, buffering effect, and ion uptake by the biofilms were also evaluated. ANOVA and Tukey’s tests were applied at p < 0.05. RBC-0 and RBC-20 showed SC development in dentin, while RBC-40 and RMGIC significantly reduced the lesion depth at the restoration margin (p < 0.0001). Initial enamel demineralization could be observed only around the RBC-0 and RBC-20 restorations. Direct antibiofilm activity can explain SC reduction by RMGIC, whereas a buffering effect on the acidogenicity of biofilm can explain the behavior of RBC-40. Experimental RBC with CaP-releasing functionalized T-DCPD filler could prevent SC with the same efficacy as F-releasing materials.
Towards a Low-Cost Monitor-Based Augmented Reality Training Platform for At-Home Ultrasound Skill Development
Authors: Shao Marine Y. , Vagg Tamara , Seibold Matthias , Doughty Mitchell
Published: November 2022

Ultrasound education traditionally involves theoretical and practical training on patients or on simulators; however, difficulty accessing training equipment during the COVID-19 pandemic has highlighted the need for home-based training systems. Due to the prohibitive cost of ultrasound probes, few medical students have access to the equipment required for at home training. Our proof of concept study focused on the development and assessment of the technical feasibility and training performance of an at-home training solution to teach the basics of interpreting and generating ultrasound data. The training solution relies on monitor-based augmented reality for displaying virtual content and requires only a marker printed on paper and a computer with webcam. With input webcam video, we performed body pose estimation to track the student’s limbs and used surface tracking of printed fiducials to track the position of a simulated ultrasound probe. The novelty of our work is in its combination of printed markers with marker-free body pose tracking. In a small user study, four ultrasound lecturers evaluated the training quality with a questionnaire and indicated the potential of our system. The strength of our method is that it allows students to learn the manipulation of an ultrasound probe through the simulated probe combined with the tracking system and to learn how to read ultrasounds in B-mode and Doppler mode.
Analysis of Thermal Imaging Performance under Extreme Foggy Conditions: Applications to Autonomous Driving
Authors: Rivera Velázquez Josué Manuel , Khoudour Louahdi , Saint Pierre Guillaume , Duthon Pierre , Liandrat Sébastien , Bernardin Frédéric , Fiss Sharon , Ivanov Igor , Peleg Raz
Published: November 2022

Object detection is recognized as one of the most critical research areas for the perception of self-driving cars. Current vision systems combine visible imaging, LIDAR, and/or RADAR technology, allowing perception of the vehicle’s surroundings. However, harsh weather conditions mitigate the performances of these systems. Under these circumstances, thermal imaging becomes the complementary solution to current systems not only because it makes it possible to detect and recognize the environment in the most extreme conditions, but also because thermal images are compatible with detection and recognition algorithms, such as those based on artificial neural networks. In this paper, an analysis of the resilience of thermal sensors in very unfavorable fog conditions is presented. The goal was to study the operational limits, i.e., the very degraded fog situation beyond which a thermal camera becomes unreliable. For the analysis, the mean pixel intensity and the contrast were used as indicators. Results showed that the angle of view (AOV) of a thermal camera is a determining parameter for object detection in foggy conditions. Additionally, results show that cameras with AOVs 18° and 30° are suitable for object detection, even under thick fog conditions (from 13 m meteorological optical range). These results were extended using object detection software, with which it is shown that, for the pedestrian, a detection rate ≥90% was achieved using the images from the 18° and 30° cameras.
Response of Spatial and Temporal Variations in the Kuroshio Current to Water Column Structure in the Western Part of the East Sea
Authors: Lee Chung-Il , Jung Yong-Woo , Jung Hae-Kun
Published: November 2022

Using geographic sea surface current data, long-term changes in spatial and temporal variations in the Kuroshio Current 1993–2021 were analyzed, and the relationship between the Kuroshio Current and oceanic conditions, such as water column structure and intensity of East Korea Warm Current (EKWC) in the western part of the East Sea (WES), was investigated. Long-term changes in the Kuroshio Current intensity were positively correlated with the Pacific Decadal Oscillation and East Asian Winter Monsoon indices. When the Kuroshio Current was strong, its main axis passing around the Ryukyu Islands moved eastward, and the intensity of EKWC separated from the Kuroshio Current and flowed into the WES, indicating weakened conditions. When the intensity of the EKWC was weakened, its main axis moved away from the inshore area of the WES. As a result, the vertical distribution range of the cold and low saline water mass located in the bottom layer extended to shallower depths in the inshore area of the WES with increasing chlorophyll-a.
Analysis of Cyclic Shear Stress–Displacement Mechanical Properties of Silt–Steel Interface in the Yellow River Delta
Authors: Yu Peng , Dong Jie , Liu Haisong , Xu Rui , Wang Rujie , Xu Meijun , Liu Hongjun
Published: November 2022

Pile foundations of offshore structures are often subjected to cyclic loads under storm loads, thus reducing their vertical bearing capacity. Therefore, studying the cyclic shear behavior of the soil–structure interface is important for maintaining the stability of offshore structures. A series of cyclic shear tests of the silt–steel interface were carried out using a large interface shear apparatus. The effects of various factors (i.e., normal stress, shear displacement amplitude, roughness, and water content) on the shear stress characteristics of the silt–steel interface were investigated. The stress–displacement model of the cyclic shear silt–steel interface was deduced. The results showed that the shear stress at the silt–steel interface was softened, and the type of bulk deformation was shear shrinkage under cyclic shear. With the increase in shear amplitude, the hysteresis curve gradually developed from “parallelogram” to “shuttle” and “hysteresis cake”. With the increase in normal stress and roughness and the decrease in water content, the interfacial shear strength, volume displacements growth rate, and growth rate increased. The stress–displacement mathematical model of the silt–steel interface based on the modified hyperbolic model was in good agreement with the test data.
Development of A Novel Adaptive Range Strain Sensor for Structural Crack Monitoring
Authors: Jia Ziguang , Ma Guangda , Su Xin , Li Yibo , Xing Chenghao , Ye Shuhan , Yi Xuan , Qu Chunxu
Published: November 2022

Ocean platforms that are under complex sea conditions and loads for long periods are prone to fatigue cracks. These cracks may lead to large deformations, even displacement, of the platform, and should be monitored to ensure engineering safety. Cracks are not easily detected in the micro stage and small levels of strain measurement are required to ensure high accuracy. Furthermore, cracks are prone to suddenly developing into large deformations, especially in structural connections in practical engineering. This study developed a novel adaptive range strain sensor for structural crack monitoring that can monitor the whole structural crack propagation process in ocean platforms. The strain sensor is used for micro deformation monitoring through its fiber Bragg grating (FBG) sensor with high sensitivity. The sensor can automatically adapt to crack fractures and provide warnings through an STM32 single-chip microcomputer (SCM) system when the structure suddenly cracks, causing large deformation. The experimental results demonstrate that the device has high precision in micro measurement with the ability to capture structural fractures. The field application shows the high strain sensitivity of the sensor in crack monitoring, which indicates that the adaptive range strain sensor is suitable for the structural crack monitoring of ocean platforms.
Investigating the Impact of Perceived Micro-Level Neighborhood Characteristics on Housing Prices in Shanghai
Authors: Song Qiwei , Liu Yifeng , Qiu Waishan , Liu Ruijun , Li Meikang
Published: November 2022

It is widely accepted that houses in better-designed neighborhoods are found to enjoy a price premium. Prior studies have mainly examined the impact of macro-level neighborhood attributes (e.g., park accessibility using land use data) on housing prices. More recently, research has investigated the micro-level features using street view imagery (SVI) data, though scholars limited the scope to objective indicators such as the green view index and sky view index. The role of subjectively measured street qualities is less discussed due to the lack of large-scale perception data. To provide better explanations of whether and how the micro-level neighborhood environment affects housing prices, this article introduces a framework to collect designers’ perceptions on five subjective urban design perceptions from pairwise SVI rankings in Shanghai with an online visual survey and further predicted through machine learning (ML) algorithms. We also extracted ten important objective features from the scenes. The predictive power of micro-level neighborhood street perceptions (subjective perceptions and objective features) on housing prices was investigated using the hedonic price model (HPM) through ordinary least squares (OLS) and spatial regression, which considers spatial dependence. The findings prove the significance of the value of perceived qualities of the neighborhoods. It reveals that both objective perceived features and subjective perceptions significantly contribute to housing prices; while the objective features show more collective strengths, individual subjective perceptions have more explanatory power, and we argue that these two measures can complement each other. This study provides an important reference for decision makers when selecting street quality indicators to inform city planning, urban design, and community and housing development plans.
Impacts of COVID-19 Lockdown on Use and Perception of Urban Green Spaces and Demographic Group Differences
Authors: Wang Shiqi , Li Ang
Published: November 2022

The COVID-19 pandemic triggered unprecedented travel restrictions around the world and significantly altered people’s daily behaviors. Although previous works have explored the changes in usage and perceptions of urban green spaces (UGS) before and through the pandemic lockdown, there are certain differences in conclusions for various regions, and demographic group differences are not figured out. Our study aimed to evaluate the impacts of the COVID-19 lockdown on the use and perception of urban green spaces in Xuzhou, China and identify the differences across groups through an online survey of 376 respondents. The descriptive statistical results showed that approximately half reduced UGS visits, and one third reported increased importance of UGS’s health benefits, especially in mentality. During the lockdown, the city park and community park were the most common destinations and the well-maintained lawn was regarded as the most valued characteristic, followed by sports facilities and seating facilities. Walking was the most frequent means of travel, while public transport was the least common choice. The regression analysis suggested that age, marriage, living pattern and income have significant influences on usage and perception of UGS. The young and the unmarried were more likely to perceive increased social benefits by visiting UGS compared to before the pandemic. People living alone visited the private garden more frequently, and people from three-generation-families preferred green life streets. Richer people unusually spend more time in UGS, benefited more and had more potential to renew green activities. In addition, more perceived risks related to COVID-19 resulted in higher self-reported health benefits. Finally, the suggestions for encouraging UGS visits during the pandemic lockdown are discussed.
Ecosystem Services Supply from Peri-Urban Landscapes and Their Contribution to the Sustainable Development Goals: A Global Perspective
Authors: Rozas-Vásquez Daniel , Spyra Marcin , Jorquera Felipe , Molina Sebastián , Caló Nica Claudia
Published: November 2022

Peri-urban landscapes (PULs) play an important role in the supply of ecosystem services (ES), which support development and well-being in urban and rural areas. Understanding the impacts of policy actions on the supply of ES and how they might contribute to the achievement of a range of sustainable development goals (SDG) is a key challenge, especially for spatial planning. The aim of this article is to explore the links between the ES supply from PULs and how they support different SDGs from a global perspective. For this, we implemented a review of the literature oriented to identify (1) the most relevant ES provided by PULs at a global level, (2) how they support the achievement of different SDG, and (3) the type of policy interventions and actors related to PULs. We identified the supply of 17 different ES by PULs and a relationship to 12 SDGs. In 58% of the cases, the SDGs were related to two ES sections, where regulation and maintenance was dominant. Pure research was the main type of intervention, mainly at the municipal scale. Increasing the cooperation between science and policy and expanding the scale of analysis beyond municipal boundaries are critical aspects.
Uncovering the Inhibitory Molecular Mechanism of Pomegranate Peel to Urinary Bladder Urothelial Carcinoma Using Proteomics Techniques
Authors: Huang Kuan-Hua , Chang Ching-Ping , Chien Lan-Hsiang , Li Chien-Feng , Tang Ling-Yu , Chan Yu-Yi , Wu Ting-Feng
Published: November 2022

Pomegranate (Punica granatum L.) fruit demonstrates the repressive effectiveness of many tumors. Our previous studies showed that the PEP (pomegranate peel extract) E2 fraction obtained from the ethyl acetate layer of the pomegranate peel’s ethanol extract exhibited the highest inhibitory activities to induce Urinary bladder urothelial carcinoma (UBUC) cell apoptosis. The ethyl acetate layer could lower the volume and weight of T24 tumors and initiate apoptosis in nude mice xenografted bladder tumors. In this study, we intended to clarify the inhibitory molecular process of Taiwanese local pomegranate peel to urinary bladder urothelial carcinoma using a proteomics strategy. Gel-based proteomics (two-dimensional gel electrophoresis coupled with tandem mass spectrometry) was used to get an insight into the molecular mechanisms initiated by PEPE2 to evoke bladder cancer cell apoptosis. We found eleven down-regulated and eight up-regulated proteins in PEPE2-treated T24 cells. Our results implied that these PEPE2-dysregulated proteins belong to cell apoptosis, cell proliferation, death receptor signaling, JAK/STAT signaling, the PPAR pathway, the PPARα/RXR α pathway, Rho family GTPase signaling, and RhoGDI signaling. In addition, HSP90 and PTP1B proteins, associated with apoptosis, were de-regulated in xenografted bladder tumors in nude mice fed with an ethyl acetate layer of ethanol extract. The findings above implied that pomegranate might be a potential chemopreventive resource for UBUC carcinogenesis.
Isomorph Invariance in the Liquid and Plastic-Crystal Phases of Asymmetric-Dumbbell Models
Authors: Attia Eman , Dyre Jeppe C. , Pedersen Ulf R.
Published: November 2022

We present a numerical study of the asymmetric dumbbell model consisting of “molecules” constructed as two different-sized Lennard-Jones spheres connected by a rigid bond. In terms of the largest (A) particle radius, we report data for the structure and dynamics of the liquid phase for the bond lengths 0.05, 0.1, 0.2, and 0.5, and analogous data for the plastic-crystal phase for the bond lengths 0.05, 0.1, 0.2, and 0.3. Structure is probed by means of the AA, AB, and BB radial distribution functions. Dynamics is probed via the A and B particle mean-square displacement as functions of time and via the rotational time-autocorrelation function. Consistent with the systems’ strong virial potential-energy correlations, the structure and dynamics are found to be isomorph invariant to a good approximation in reduced units, while they generally vary considerably along isotherms of the same (20%) density variation. Even the rotational time-autocorrelation function, which due to the constant bond length is not predicted to be isomorph invariant, varies more along isotherms than along isomorphs. Our findings provide the first validation of isomorph-theory predictions for plastic crystals for which isomorph invariance, in fact, is found to apply better than in the liquid phase of asymmetric-dumbbell models.
Evaluation of the Role of Dry and MQL Regimes on Machining and Sustainability Index of Strenx 900 Steel
Authors: Aslan Abdullah , Salur Emin , Kuntoğlu Mustafa
Published: November 2022

Sustainable technologies draw attention in the machining industry thanks to their contributions in many aspects such as ecological, economic, and technological. Minimum quantity lubrication (MQL) is one of these techniques that enable to convey of the high pressurized cutting fluid toward the cutting zone as small oil particulates. This study examines the potency of MQL technology versus dry conditions on the machining quality during the milling of structural Strenx 900 steel within the sustainability index. High strength and toughness properties make this steel a hard-to-cut material providing an important opportunity to test the performances of dry and MQL environments. The outcomes of the experimental data demonstrated that MQL is superior in enhancing the quality of significant machining characteristics namely surface roughness (up to 35%), flank wear (up to 94%), wear mechanisms, cutting energy (up to 28%), and cutting temperatures (up to 14%). Furthermore, after analyzing the main headings of the sustainable indicators, MQL provided the same (+5) desirability value with a dry (+5) medium. This experimental work presents a comparative approach for improved machinability of industrially important materials by questioning the impact of sustainable methods.
Effect of Cellulose Nanofibrils on the Physical Properties and Frost Resistance of Pervious Concrete
Authors: Zhang Xu , Lei Chengbang , Li Zhi , Zhang Aiqin , Zhao Wanfeng , Zhang Wei , Xu Jiarong , Guo Panpan
Published: November 2022

Pervious concrete has good water permeability and, if used in construction, it can alleviate the heat island effect. However, its low strength and poor durability are major obstacles to its use. This study shows that nano-reinforced pervious concrete created by incorporating cellulose nanofibrils (CNFs) can improve the physical properties and increase the durability of pervious concrete. CNFs were added to the concrete mix in proportions ranging from 0.05% to 0.2% by weight of binder. The additions were found to alter matrix rheology. The hydration kinetics of matrix with differing CNF contents were compared and analyzed. The experimental results show the addition of CNFs delayed peak heat flow and maximum cumulative heat. The 28 d compressive strength of pervious concrete increased by up to 26.5% and 28 d flexural strength by up to 25.8% with the addition of 0.05–0.2% CNFs. Addition of 0.1% and 0.2% CNFs increased water permeability. Addition of 0.05–0.15% CNFs decreased mass loss by 73.2–83.7% after 150 freeze–thaw cycles, which corresponded to an increase in frost resistance. Denser matrices and stronger interfacial transition zones were observed using scanning electron microscopy when 0.05–0.2% CNFs were added.
Influences of Separator Thickness and Surface Coating on Lithium Dendrite Growth: A Phase-Field Study
Authors: Li Yajie , Sha Liting , Lv Peili , Qiu Na , Zhao Wei , Chen Bin , Hu Pu , Zhang Geng
Published: November 2022

Li dendrite growth, which causes potential internal short circuit and reduces battery cycle life, is the main hazard to lithium metal batteries. Separators have the potential to suppress dendrite growth by regulating Li+ distribution without increasing battery weight significantly. However, the underlying mechanism is still not fully understood. In this paper, we apply an electrochemical phase-field model to investigate the influences of separator thickness and surface coating on dendrite growth. It is found that dendrite growth under thicker separators is relatively uniform and the average dendrite length is shorter since the ion concentration within thicker separators is more uniform. Moreover, compared to single layer separators, the electrodeposition morphology under particle-coated separators is smoother since the particles can effectively regulate Li ionic flux and homogenize Li deposition. This study provides significant guidance for designing separators that inhibit dendrites effectively.
Vibration Analysis of Two-Stage Helical Gear Transmission with Cracked Fault Based on an Improved Mesh Stiffness Model
Authors: Li Yancong , Yuan Shihua , Wu Wei , Liu Kun , Lian Chunpeng , Song Xintao
Published: November 2022

The crack fault has an important influence on the vibration characteristics of the transmission system. This paper is devoted to analyzing fault mechanism and dynamic characteristics of transmission with gear crack, which provides the basis for crack diagnosis and monitoring of helical gear in two-stage transmission system. For this purpose, an improved calculation method of time-varying meshing stiffness with crack fault is proposed considering the axial force of the helical gear. The influence of crack depths and angles on stiffness is analyzed. Based on this, the dynamic model of the two-stage helical gear transmission system is established using the lumped mass method. The influence of crack parameters on the characteristics of the transmission system is studied. In order to better diagnose the crack fault of the helical gear, the statistical index in time domain is calculated and the sensitivity to crack fault is analyzed. It is shown that the stiffness decreases by 25%, and the vibration acceleration increases by 8.3% after the axial force component is considered into the stiffness of the crack gear pair. The meshing stiffness decreases with the increase of crack depths and crack angles. The dynamic model is verified by rig test. Periodic impact exists in the system. The time of entering meshing of the cracked tooth and the time of complete disengagement is observed in the residual signal. In the frequency domain, there appear sidebands on the mesh frequency of the first gear pairs and its harmonics, the second gear mesh frequency and its harmonic frequencies. There is a little influence on the vibration acceleration of the driven gear of the second-stage. According to the signals in the frequency domain and the time domain, we can tell at which stage the gear is cracked. While through the time required for the crack tooth from engagement to disengagement completely, we can tell which gear is cracked. The sensitivity of skewness, impulse factor and kurtosis to crack fault decreases successively. The results provide theoretical basis for crack fault diagnosis of a two-stage helical gear transmission system.
ERDERP: Entity and Relation Double Embedding on Relation Hyperplanes and Relation Projection Hyperplanes
Authors: Lin Lin , Liu Jie , Guo Feng , Tong Changsheng , Zu Lizheng , Guo Hao
Published: November 2022

Since data are gradually enriched over time, knowledge graphs are inherently imperfect. Thus, knowledge graph completion is proposed to perfect knowledge graph by completing triples. Currently, a family of translation models has become the most effective method for knowledge graph completion. These translation models are modeled to solve the complexity and diversity of entities, such as one-to-many, many-to-one, and many-to-many, which ignores the diversity of relations themselves, such as multiple relations between a pair of entities. As a result, with current translation models, it is difficult to effectively extract the semantic information of entities and relations. To effectively extract the semantic information of the knowledge graph, this paper fundamentally analyzes the complex relationships of the knowledge graph. Then, considering the diversity of relations themselves, the complex relationships are refined as one-to-one-to-many, many-to-one-to-one, one-to-many-to-one, many-to-one-to-many, many-to-many-to-one, one-to-many-to-many, and many-to-many-to-many. By analyzing the complex relationships, a novel knowledge graph completion model, entity and relation double embedding on relation hyperplanes and relation projection hyperplanes (ERDERP), is proposed to extract the semantic information of entities and relations. First, ERDERP establishes a relation hyperplane for each relation and projects the relation embedding into the relation hyperplane. Thus, the semantic information of the relations is extracted effectively. Second, ERDERP establishes a relation projection hyperplane for each relation projection and projects entities into relation projection hyperplane. Thus, the semantic information of the entities is extracted effectively. Moreover, it is theoretically proved that ERDERP can solve antisymmetric problems. Finally, the proposed ERDERP are compared with several typical knowledge graph completion models. The experimental results show that ERDERP is significantly effective in link prediction, especially in relation prediction. For instance, on FB15k and FB15k-237, Hits@1 of ERDERP outperforms TransH at least 30%.
A Discrete-Event Mathematical Model for Resource Allocation Optimization: A Case Study of Vehicle Scheduling in a Signal-Free Intersection
Authors: Hou Yunfeng , Mao Yue , Zhang Yanmei , Li Qingdu , Ji Yunfeng , Li Wei
Published: November 2022

In industrial applications, many systems present serious productivity problems due to limited resources. Generally, the dynamics of resource allocation are inherently discrete-event driven, such as the buffer allocation in production line systems. In this paper, we develop a discrete-event mathematical model for resource allocation optimization. In this work, we consider two crucial optimization objectives, e.g., deadlock-free and efficiency, that originate from the customer’s actual requirements. The main aim is to develop a resource allocation scheme for fulfilling the production process (without deadlock) while ensuring that the cost of the process is minimized. As a case study, we consider the vehicle scheduling problem in a signal-free intersection. The intersection is divided into several disjoint spatial traffic resources, and vehicles need to occupy different traffic resources for passing through the intersection. Thus, the traffic control problem at the signal-free intersection is transformed into a scheduling problem with limited resource constraints. An online control approach is developed to schedule vehicles to go through the intersection safely and efficiently by optimizing the resource allocation order. Simulation results demonstrate the efficiency and robustness of the proposed model and optimization approach.
Influence Maximization under Fairness Budget Distribution in Online Social Networks
Authors: Nguyen Bich-Ngan T. , Pham Phuong N. H. , Le Van-Vang , Snášel Václav
Published: November 2022

In social influence analysis, viral marketing, and other fields, the influence maximization problem is a fundamental one with critical applications and has attracted many researchers in the last decades. This problem asks to find a k-size seed set with the largest expected influence spread size. Our paper studies the problem of fairness budget distribution in influence maximization, aiming to find a seed set of size k fairly disseminated in target communities. Each community has certain lower and upper bounded budgets, and the number of each community’s elements is selected into a seed set holding these bounds. Nevertheless, resolving this problem encounters two main challenges: strongly influential seed sets might not adhere to the fairness constraint, and it is an NP-hard problem. To address these shortcomings, we propose three algorithms (FBIM1, FBIM2, and FBIM3). These algorithms combine an improved greedy strategy for selecting seeds to ensure maximum coverage with the fairness constraints by generating sampling through a Reverse Influence Sampling framework. Our algorithms provide a (1/2−ϵ)-approximation of the optimal solution, and require OkTlog(8+2ϵ)nln2δ+ln(kn)ϵ2, OkTlognϵ2k, and OTϵlogkϵlognϵ2k complexity, respectively. We conducted experiments on real social networks. The result shows that our proposed algorithms are highly scalable while satisfying theoretical assurances, and that the coverage ratios with respect to the target communities are larger than those of the state-of-the-art alternatives; there are even cases in which our algorithms reaches 100% coverage with respect to target communities. In addition, our algorithms are feasible and effective even in cases involving big data; in particular, the results of the algorithms guarantee fairness constraints.
A Study on the Low-Power Operation of the Spike Neural Network Using the Sensory Adaptation Method
Authors: Jeon Mingi , Kang Taewook , Lee Jae-Jin , Lee Woojoo
Published: November 2022

Motivated by the idea that there should be a close relationship between biological significance and low power driving of spike neural networks (SNNs), this paper aims to focus on spike-frequency adaptation, which deviates significantly from existing biological meaningfulness, and develop a new spike-frequency adaptation with more biological characteristics. As a result, this paper proposes the sensoryadaptation method that reflects the mechanisms of the human sensory organs, and studies network architectures and neuron models for the proposed method. Next, this paper introduces a dedicated SNN simulator that can selectively apply the conventional spike-frequency adaptation and the proposed method, and provides the results of functional verification and effectiveness evaluation of the proposed method. Through intensive simulation, this paper reveals that the proposed method can produce a level of training and testing performance similar to the conventional method while significantly reducing the number of spikes to 32.66% and 45.63%, respectively. Furthermore, this paper contributes to SNN research by showing an example based on in-depth analysis that embedding biological meaning in SNNs may be closely related to the low-power driving characteristics of SNNs.
A Q-Learning and Fuzzy Logic-Based Hierarchical Routing Scheme in the Intelligent Transportation System for Smart Cities
Authors: Rahmani Amir Masoud , Naqvi Rizwan Ali , Yousefpoor Efat , Yousefpoor Mohammad Sadegh , Ahmed Omed Hassan , Hosseinzadeh Mehdi , Siddique Kamran
Published: November 2022

A vehicular ad hoc network (VANET) is the major element of the intelligent transportation system (ITS). The purpose of ITS is to increase road safety and manage the movement of vehicles. ITS is known as one of the main components of smart cities. As a result, there are critical challenges such as routing in these networks. Recently, many scholars have worked on this challenge in VANET. They have used machine learning techniques to learn the routing proceeding in the networks adaptively and independently. In this paper, a Q-learning and fuzzy logic-based hierarchical routing protocol (QFHR) is proposed for VANETs. This hierarchical routing technique consists of three main phases: identifying traffic conditions, routing algorithm at the intersection level, and routing algorithm at the road level. In the first phase, each roadside unit (RSU) stores a traffic table, which includes information about the traffic conditions related to four road sections connected to the corresponding intersection. Then, RSUs use a Q-learning-based routing method to discover the best path between different intersections. Finally, vehicles in each road section use a fuzzy logic-based routing technique to choose the foremost relay node. The simulation of QFHR has been executed on the network simulator version 2 (NS2), and its results have been presented in comparison with IRQ, IV2XQ, QGrid, and GPSR in two scenarios. The first scenario analyzes the result based on the packet sending rate (PSR). In this scenario, QFHR gets better the packet delivery rate by 2.74%, 6.67%, 22.35%, and 29.98% and decreases delay by 16.19%, 22.82%, 34.15%, and 59.51%, and lowers the number of hops by 6.74%, 20.09%, 2.68%, and 12.22% compared to IRQ, IV2XQ, QGrid, and GPSR, respectively. However, it increases the overhead by approximately 9.36% and 11.34% compared to IRQ and IV2XQ, respectively. Moreover, the second scenario evaluates the results with regard to the signal transmission radius (STR). In this scenario, QFHR increases PDR by 3.45%, 8%, 23.29%, and 26.17% and decreases delay by 19.86%, 34.26%, 44.09%, and 68.39% and reduces the number of hops by 14.13%, 32.58%, 7.71%, and 21.39% compared to IRQ, IV2XQ, QGrid, and GPSR, respectively. However, it has higher overhead than IRQ (11.26%) and IV2XQ (25%).
On the Global Behaviour of Solutions for a Delayed Viscoelastic-Type Petrovesky Wave Equation with p-Laplacian Operator and Logarithmic Source
Authors: Belhadji Bochra , Alzabut Jehad , Samei Mohammad Esmael , Fatima Nahid
Published: November 2022

This research is concerned with a nonlinear p-Laplacian-type wave equation with a strong damping and logarithmic source term under the null Dirichlet boundary condition. We establish the global existence of the solutions by using the potential well method. Moreover, we prove the stability of the solutions by the Nakao technique. An example with illustrative figures is provided as an application.
Feature Selection Based on Mud Ring Algorithm for Improving Survival Prediction of Children Undergoing Hematopoietic Stem-Cell Transplantation
Authors: El Bakrawy Lamiaa M. , Bailek Nadjem , Abualigah Laith , Urooj Shabana , Desuky Abeer S.
Published: November 2022

The survival prediction of children undergoing hematopoietic stem-cell transplantation is essential for successful transplantation. However, the performance of current algorithms for predicting mortality in this patient group has not improved over recent decades. This paper proposes a new feature selection technique for survival prediction problems using the Mud Ring Algorithm (MRA). Experiments and tests were initially performed on 13 real datasets with varying occurrences to compare the suggested algorithm with other algorithms. After that, the constructed model classification performance was compared to other techniques using the bone marrow transplant children’s dataset. Modern techniques were used to acquire their classification results, which were then compared to the suggested outcomes using a variety of well-known metrics, graphical tools, and diagnostic analysis. This investigation has demonstrated that our suggested approach is comparable and outperformed other methods in terms of results. In addition, the results showed that the constructed model enhanced prediction accuracy by up to 82.6% for test cases.
Robotic-Arm-Assisted Total Hip Arthroplasty: A Review of the Workflow, Outcomes and Its Role in Addressing the Challenge of Spinopelvic Imbalance
Authors: Ogilvie Andrew , Kim Woo Jae , Asirvatham Rhody David , Fontalis Andreas , Putzeys Pierre , Haddad Fares S.
Published: November 2022

Robotic-arm-assisted total hip arthroplasty (RoTHA) offers the opportunity to improve the implant positioning and restoration of native hip mechanics. The concept of individualised, functional implant positioning and how it relates to spinopelvic imbalance is an important yet rather novel consideration in THA. There is mounting evidence that a significant percentage of dislocations occur within the perceived “safe zones”; hence, in the challenging subset of patients with a stiff spinopelvic construct, it is imperative to employ individualised component positioning based on the patients’ phenotype. Restoring the native centre of rotation, preserving offset, achieving the desired combined anteversion and avoiding leg length inequality are all very important surgeon-controlled variables that have been shown to be associated with postoperative outcomes. The latest version of the software has a feature of virtual range of motion (VROM), which preoperatively identifies potential dynamic causes of impingement that can cause instability. This review presents the workflow of RoTHA, especially focusing on pragmatic solutions to tackle the challenge of spinopelvic imbalance. Furthermore, it presents an overview of the existing evidence concerning RoTHA and touches upon future direction.
Breast Cancer Incidence Patterns in the Saudi Female Population: A 17-Year Retrospective Analysis
Authors: Basudan Ahmed
Published: November 2022

Background and Objectives: Breast cancer is considered the most commonly diagnosed type of cancer among women globally and in Saudi Arabia. This study aimed to assess breast cancer incidence patterns and trends among the Saudi female population. Materials and Methods: Breast cancer incidence parameters were obtained from the Saudi Cancer Registry (SCR). The data were retrospectively analyzed for the period from 2001 to 2017 to investigate changes in incidence rates. Temporal trends were also analyzed through joinpoint regression analysis and were dissected by age groups and administrative regions. Results: During the specified period, breast cancer jumped by 55% to constitute 30.9% of all cancer cases among Saudi females. The median age at diagnosis increased to reach 51 years at the end of that period, with an overall increase of 6.3%. The overall Age-Standardized Incidence Rate (ASR) escalated by 151.7% from 11.8/100,000 to 29.7/100,000 population for that period. The Eastern region noticeably had the highest ASR and peaked at 52.2/100,000 population. The joinpoint analysis of the ASR showed increased trends, with an annual percent change (APC) of 5.13% (p < 0.05, [95% CI 4–6.3]). An age-specific analysis was also performed and showed that the age group 70–74 years had the highest trend (APC 10.2%, [95% CI 7.2–13.4], p < 0.05). Region-specific analysis revealed that the Jouf region had the highest trend among the regions (APC 8.8%, [95% CI 3.7–14.2], p < 0.05). Conclusions: Our analysis indicates increased breast cancer incidence in Saudi Arabia with an alarming pace. With the existing trend, it is expected that Saudi Arabia will continue to display an increase in breast cancer incidence. Long-term preventive measures and more effective screening strategies are warranted to alleviate the burden of the disease.
External Cephalic Version—A Chance for Vaginal Delivery at Breech Presentation
Authors: Cobec Ionut Marcel , Varzaru Vlad Bogdan , Kövendy Tamas , Kuban Lorant , Eftenoiu Anca-Elena , Moatar Aurica Elisabeta , Rempen Andreas
Published: November 2022

Background and Objectives: In recent years, the rate of caesarean section (CS) has increased constantly. Although vaginal breech delivery has a long history, breech presentation has become the third most common indication for CS. This study aims to identify factors associated with the success of external cephalic version (ECV), underline the success rate of ECV for breech presentation and highlight the high rate of vaginal delivery after successful ECV. Material and Methods: This retrospective observational study included 113 patients with singleton fetuses in breech presentation, who underwent ECV from January 2016 to March 2021 in the Clinic of Obstetrics and Gynecology, Diakonieklinikum Schwäbisch Hall, Germany. Maternal and fetal parameters and data related to procedure and delivery were collected. Possible predictors of successful ECV were evaluated. Results: The success rate of ECV was 54.9%. The overall rate of vaginal birth was 44.2%, regardless of ECV outcome. The vaginal birth rate after successful ECV was 80.6%. Overall, 79.0% of women with successful ECV delivered spontaneously without complications, 19.4% delivered through CS performed during labor by medical necessity, and 1.6% delivered through vacuum extraction. ECV was performed successfully in three of the four women with history of CS. Gravidity, parity, maternal age, gestational age, fetal weight, and amniotic fluid index (AFI) were significantly correlated with the outcome of ECV. Conclusions: ECV for breech presentation is a safe procedure with a good success rate, thus increasing the proportion of vaginal births. Maternal and fetal parameters can be used to estimate the chances of successful ECV.
Morpho-Constitutional Classification of Urinary Stones as Prospective Approach for the Management of Human Pathological Biomineralization: New Insights from Southern Italy
Authors: Izzo Francesco , Langella Alessio , Germinario Chiara , Grifa Celestino , Varricchio Ettore , Di Meo Maria Chiara , Salzano Luigi , Lotrecchiano Giuseppe , Mercurio Mariano
Published: November 2022

The present investigation exposes the main results raised from an active collaboration started in 2018 with the San Pio Hospital (Benevento, Southern Italy), aiming at a detailed mineralogical investigation of urinary stones of patients from the Campania region. Forty-nine uroliths (both bladder and kidney stones) have been surgically collected from patients admitted between 2018 and 2020 at the Department of Urology of the San Pio Hospital and characterized for clinical purposes and environmental biomonitoring from a mineralogical point of view. Possible causes and environmental implications were inferred according to the morpho-constitutional classification of the uroliths carried out by means of a conventional analytical approach. The mineralogical frequency distribution of uroliths from the Campanian region can be discussed as a function of dietary, socio-demographic, and environmental risk factors. Whewellite [CaC2O4·H2O] and weddellite [CaC2O4·(2+x)H2O], along with anhydrous calcium oxalate, represent the main mineralogical phases forming the biominerals examined here. Worth to note is that the percentage of oxalates in the Campanian region (ca. 51%) is quite comparable to those of other Mediterranean areas. Frequent uricite [C5H4N4O3] (ca. 33%), mainly observed in bladder stones of older male patients, could be related to an incorrect lifestyle and dietary habits. Occurrence of lower percentages of phosphate (i.e., brushite [CaHPO4·2(H2O)] and carbonated apatite [Ca10(PO4CO3)6(OH)8]) and mixed stones (such as, for example, a mixture of ammonium urate [NH4C5H3N4O3] and calcium oxalates) indicates specific etiopathogenetic mechanisms, suggesting proper therapeutical approaches.
Efficient Mesoporous MgO/g-C3N4 for Heavy Metal Uptake: Modeling Process and Adsorption Mechanism
Authors: AbuMousa Rasha A. , Khezami Lotfi , Ismail Mukhtar , Ben Aissa Mohamed Ali , Modwi Abueliz , Bououdina Mohamed
Published: November 2022

Removing toxic metal ions arising from contaminated wastewaters caused by industrial effluents with a cost-effective method tackles a serious concern worldwide. The adsorption process onto metal oxide and carbon-based materials offers one of the most efficient technologies adopted for metal ion removal. In this study, mesoporous MgO/g-C3N4 sorbent is fabricated by ultrasonication method for the uptake Pb (II) and Cd (II) heavy metal ions from an aqueous solution. The optimum conditions for maximum uptake: initial concentration of metal ions 250 mg g−1, pH = 5 and pH = 3 for Pb++ and Cd++, and a 60 mg dose of adsorbent. In less than 50 min, the equilibrium is reached with a good adsorption capacity of 114 and 90 mg g−1 corresponding to Pb++ and Cd++, respectively. Moreover, the adsorption isotherm models fit well with the Langmuir isotherm, while the kinetics model fitting study manifest a perfect fit with the pseudo-second order. The as fabricated mesoporous MgO/g-C3N4 sorbent exhibit excellent Pb++ and Cd++ ions uptake and can be utilized as a potential adsorbent in wastewater purification.