bluuebunny/crossref_metadata_2025 huggingface dataset:
From 1D to 2D to 3D: Electrospun Microstructures towards Wearable Sensing
Authors: Zhang Jiahan , Sun Xidi , Wang Haitao , Li Jiean , Guo Xin , Li Sheng , Wang Yaqun , Cheng Wen , Qiu Hao , Shi Yi , Pan Lijia
Published: May 2023

Wearable sensors open unprecedented opportunities for long-term health monitoring and human–machine interaction. Electrospinning is considered to be an ideal technology to produce functional structures for wearable sensors because of its unique merits to endow devices with highly designable functional microstructures, outstanding breathability, biocompatibility, and comfort, as well as its low cost, simple process flow, and high productivity. Recent advances in wearable sensors with one-, two-, or three-dimensional (1D, 2D, or 3D) electrospun microstructures have promoted various applications in healthcare, action monitoring, and physiological information recognition. Particularly, the development of various novel electrospun microstructures different from conventional micro/nanofibrous structures further enhances the electrical, mechanical, thermal, and optical performances of wearable sensors and provides them with multiple detection functions and superior practicality. In this review, we discuss (i) the principle and typical apparatus of electrospinning, (ii) 1D, 2D, and 3D electrospun microstructures for wearable sensing and their construction strategies and physical properties, (iii) applications of microstructured electrospun wearable devices in sensing pressure, temperature, humidity, gas, biochemical molecules, and light, and (iv) challenges of future electrospun wearable sensors for physiological signal recognition, behavior monitoring, personal protection, and health diagnosis.
Springback Control in Complex Sheet-Metal Forming Based on Advanced High-Strength Steel
Authors: Lu Zipeng , Li Di , Cao Linlin , Cui Hongjian , Xu Jiachuan
Published: May 2023

Sheet-metal forming is one of the most important manufacturing processes in the automotive industry. This study proposes a multiobjective optimisation scheme that controls both sheet-metal formability and springback. First, the mechanical properties of DP590 steel were characterised to obtain the mechanical parameters and forming limit diagram (FLD) of DP590. Then, the FLD, thinning rate, and average springback were selected as forming quality evaluation indices. Response surface tests were then conducted for different process parameters for the A-pillar side-stiffener drawing process to analyse the DP590 steel’s formability and springback. The optimal process parameters for the drawing process were obtained using a multiobjective optimisation algorithm based on an improved particle swarm method. Finally, a springback compensation scheme was proposed based on the results of the multiprocess simulation. The scheme was applied experimentally to the A-pillar side-stiffener drawing process, and the formability and springback compensation performances verified that the scheme successfully and efficiently eliminated springback and rupture in formed DP590 steel.
Application of Magnesium Hydroxide/Diphenoxy Phosphate in Silicone Rubber Flame Retardant Cable Material
Authors: Wang Wei , Yang Fan , Lu Yunlai , Luo Zhi , Li Fangya , Wu You , Zhang Jianbing , Xiao Zufeng , Li Wei , Qin Caiqin
Published: May 2023

Deketoxime–type room–temperature vulcanized silicone rubber cable materials were prepared using α, ω–dihydroxy polydimethylsiloxane, carbon black, calcium carbonate, magnesium hydroxide, piperazine bis (diphenoxy phosphate) salt (PBDP), and melamine diphenoxy phosphate (MDP). The effects of carbon black and flame retardants on the mechanical properties, flame–retardant properties, and electrical insulation properties of silicone cable coatings were investigated. The research results showed that the products obtained had good mechanical and electrical insulation properties, with tensile strength greater than 3.0 MPa, dielectric strength greater than 22 kV/mm, and volume resistivity higher than 6.5 × 1014 Ω·cm. When 30 parts of Mg(OH)2:MDP = 2:1 are added to 100 parts of resin, the flame–retardant performance of wire and cable materials can be significantly improved. Under the thermal radiation illumination of 50 kW/m2, the ignition time (TTI) of the Mg(OH)2/MDP coating increased by 16 s, and the maximum heat release rate (pkHRR) and total heat release rate (THR) decreased by 29.7% and 68.8%, respectively, compared with silicone rubber without flame retardant. The silicone rubber coatings prepared were flame retardant up to the FV–1 level.
A Locally Disordered Metamaterial for Directing and Trapping Water Waves
Authors: Sun Wei-Qi , Wang Yu-Han , Xu Zhu-Long , Fang Xiang , Chuang Kuo-Chih
Published: May 2023

Manipulating the flow of water wave energy is crucial for ocean wave energy extraction or coastal protection, and the emergence of metamaterials paves a potential way for controlling water waves. In this work, by introducing a local disorder in a cavity-type metamaterial constructed by split-tube resonators, we show that water waves can be guided in an open channel with multiple energy flow paths formed merely by surrounded disconnected concurrent resonators that can serve as invisible walls without the requirement of a whole array system such as general periodic structures or waveguides. Specifically, we numerically and experimentally validate that a T-shaped metamaterial can achieve free guiding of water waves in a narrow band and a band-edge state along a distinct path. This open-space water waveguiding is found to be dominated by Fano-type interference and Fabry–Pérot resonance. Two distinct propagating modes, a low-frequency “trapping mode” and a high-frequency “following mode”, are identified. By simply rotating two configuration-dependent unit cells at the intersection of the metamaterial, we achieve a variety of water waveguiding paths tuning along rectilinear or bending (splitting or turning) directions, which rely on the two different propagating modes.
Impact of Input Signal Characteristics on Energy-Localization Performance of a Phononic Crystal with a Defect: A Comparative Study of Burst and Continuous Wave Excitation
Authors: Jo Soo-Ho
Published: May 2023

This study examines the energy-localization performance of a one-dimensional phononic crystal (PnC) with a defect when exposed to burst waves of different cycle numbers under longitudinal waves. Using the finite element method, band structures of the defect-introduced PnC were calculated, revealing a phononic band-gap range, defect-band frequencies, and corresponding defect-mode shapes. The transient analysis examined the longitudinal displacement at the center of this defect in the time domain for various burst-wave scenarios. The results indicate that energy-localization performance inside the defect highly depended on the number of cycles. Energy-localization performance was better with larger cycles or continuous waves, although burst waves with a small number of cycles also showed some improvement, albeit limited. Moreover, burst waves with a small number of cycles did not clearly induce fixed-like boundary conditions (in other words, nodal points in standing waves) within the defect-introduced PnC, leading to obscure energy-localized behaviors. Key messages from this work can be summarized as follows. First, comparing the energy-localization performance under incident burst waves with different cycle numbers for different systems might not be appropriate. Second, the physically reasonable formation of defect-mode-enabled energy localization requires burst waves with a large (in the case study, over 500) number of cycles.
Heterochlamydomonas uralensis sp. nov. (Chlorophyta, Chlamydomonadaceae), New Species Described from the Mountain Tundra Community in the Subpolar Urals (Russia)
Authors: Novakovskaya Irina Vladimirovna , Boldina Olga Nikolaevna , Shadrin Dmitry Mikhailovich , Patova Elena Nikolaevna
Published: May 2023

This paper describes a new species from the class Chlorophyceae, Heterochlamydomonas uralensis sp. nov., isolated from the soil of the carex-moss-lichen tundra in the Subpolar Urals Mountains, Russia. The taxon is studied using morphological methods and DNA identification. Heterochlamydomonas uralensis differs from other Heterochlamydomonas spp. by cellular morphology, detected on light and ultrastructural levels, and 18S and ITS2 rDNA sequences. These results support the separation of the species Heterochlamydomonas uralensis sp. nov. This study is important for connecting data from DNA metabarcoding with species described on the basis of morphological characteristics.
Acoustic-Based Deep Learning Architectures for Lung Disease Diagnosis: A Comprehensive Overview
Authors: Sfayyih Alyaa Hamel , Sabry Ahmad H. , Jameel Shymaa Mohammed , Sulaiman Nasri , Raafat Safanah Mudheher , Humaidi Amjad J. , Kubaiaisi Yasir Mahmood Al
Published: May 2023

Lung auscultation has long been used as a valuable medical tool to assess respiratory health and has gotten a lot of attention in recent years, notably following the coronavirus epidemic. Lung auscultation is used to assess a patient’s respiratory role. Modern technological progress has guided the growth of computer-based respiratory speech investigation, a valuable tool for detecting lung abnormalities and diseases. Several recent studies have reviewed this important area, but none are specific to lung sound-based analysis with deep-learning architectures from one side and the provided information was not sufficient for a good understanding of these techniques. This paper gives a complete review of prior deep-learning-based architecture lung sound analysis. Deep-learning-based respiratory sound analysis articles are found in different databases including the Plos, ACM Digital Libraries, Elsevier, PubMed, MDPI, Springer, and IEEE. More than 160 publications were extracted and submitted for assessment. This paper discusses different trends in pathology/lung sound, the common features for classifying lung sounds, several considered datasets, classification methods, signal processing techniques, and some statistical information based on previous study findings. Finally, the assessment concludes with a discussion of potential future improvements and recommendations.
Review of Retinal Imaging Modalities for Hydroxychloroquine Retinopathy
Authors: Cheong Kai , Ong Charles , Chandrasekaran Priya , Zhao Jinzhi , Teo Kelvin , Mathur Ranjana
Published: May 2023

This review provides an overview of conventional and novel retinal imaging modalities for hydroxychloroquine (HCQ) retinopathy. HCQ retinopathy is a form of toxic retinopathy resulting from HCQ use for a variety of autoimmune diseases, such as rheumatoid arthritis and systemic lupus erythematosus. Each imaging modality detects a different aspect of HCQ retinopathy and shows a unique complement of structural changes. Conventionally, spectral-domain optical coherence tomography (SD-OCT), which shows loss or attenuation of the outer retina and/or retinal pigment epithelium–Bruch’s membrane complex, and fundus autofluorescence (FAF), which shows parafoveal or pericentral abnormalities, are used to assess HCQ retinopathy. Additionally, several variations of OCT (retinal and choroidal thickness measurements, choroidal vascularity index, widefield OCT, en face imaging, minimum intensity analysis, and artificial intelligence techniques) and FAF techniques (quantitative FAF, near-infrared FAF, fluorescence lifetime imaging ophthalmoscopy, and widefield FAF) have been applied to assess HCQ retinopathy. Other novel retinal imaging techniques that are being studied for early detection of HCQ retinopathy include OCT angiography, multicolour imaging, adaptive optics, and retromode imaging, although further testing is required for validation.
Painless Capillary Blood Collection: A Rapid Evaluation of the Onflow Device
Authors: Noble Lara Dominique , Dixon Caitlin , Moran Alison , Trottet Charlotte , Majam Mohammed , Ismail Shameema , Msolomba Vanessa Tiyamike , Mathobela Kegomoditswe , Queval Arthur , George Jaya , Scott Lesley Erica , Stevens Wendy Susan
Published: May 2023

Blood-based diagnostics are critical for many medical decisions, but mostly rely on venepuncture, which can be inconvenient and painful. The Onflow Serum Gel (Loop Medical SA, Vaud, Lausanne, Switzerland) is a novel blood collection device that utilises needle-free technology to collect capillary blood. In this pilot study, 100 healthy participants were enrolled and provided two Onflow collected specimens and one venous blood specimen. Five chemistry analytes (AST, ALT, LDH, potassium, creatinine) and haemolysis were measured per specimen, and laboratory analyte results were compared. Onflow was found to be more acceptable than venepuncture with lower pain ratings, and 96.5% of participants would use the Onflow method again. All phlebotomists (100%) found Onflow intuitive and user-friendly, with ~1 mL of Onflow blood successfully collected from 99% of participants in <12 min (mean: 6 min, 40 s) and 91% collected on the first attempt. ALT and AST analytes showed no difference in performance, while creatinine generated a negative bias (−5.6 µmol/L), and increased variability was noted with potassium (3.6%CV) and LDH (6.7%CV), although none were clinically relevant. These differences may be due to 35% of Onflow collected specimens having “mild” haemolysis. Onflow is a promising alternative blood collection device that should now be evaluated in participants with expected abnormal chemistries and as an option for self-collection.
Analysis of Temperatures Generated during Conventional Laser Irradiation of Root Canals—A Finite Element Study
Authors: Stănuși Adrian , Popa Dragoş , Ionescu Mihaela , Cumpătă Cristian , Petrescu Gabriel , Ţuculină Mihaela , Dăguci Constantin , Diaconu Oana , Gheorghiță Lelia , Stănuşi Andreea
Published: May 2023

The success of endodontic treatment is dependent on the removal of bacteria. A modern strategy to reduce bacterial load is laser irradiation. During this procedure, there is a local increase in temperature with possible side effects. The aim of this study was to determine the thermal behavior of a maxillary first molar when performing the conventional irradiation technique using a diode laser. For this study, a 3D virtual model of a maxillary first molar was created. The preparation of the access cavity, the rotary instrumentation of the palatal root canal and the laser irradiation protocol were simulated. The model was exported in a finite element analysis program where the temperature and heat flux were studied. Temperature and heat flux maps were obtained, and the temperature increase on the internal wall of the root canal was analyzed. The maximum temperature value exceeded 400 °C and was maintained for less than 0.5 s. The obtained temperature maps support the bactericidal effect of diode laser and the limitation of damage to surrounding tissues. On internal root walls, the temperature reached several hundred degrees Celsius, but for very short durations. Conventional laser irradiation is an adjuvant method of decontamination of the endodontic system.
Inferior Vena Cava (IVC) Resections without Reconstruction in Renal Tumors: Two Case Reports
Authors: Moldovan Bogdan , Costache Victor S. , Modrigan Irina , Farcas Felix , Banu Eugeniu , Untaru Vlad , Stoica Doly , Crisan Madalina , Popianas Andreea , Pisica Radu-Mihai , Tohatan Calin-Cristian , Adam Iris-Iuliana , Vecerzan Liliana
Published: May 2023

(1) Background: We aim to present our experience with resection of the inferior vena cava (IVC) without reconstruction in two patients diagnosed with renal tumors. (2) Case Report: The first case was diagnosed with right renal vein sarcoma and the second case was diagnosed with clear cell renal carcinoma; both presented signs of invasion and thrombosis of the IVC at infrarenal and cruoric levels, along with the development of collateral circulation with the help of the paravertebral plexus. In both patients, en bloc right nephrectomy was performed along with the resection of the thrombosed IVC without further reconstruction. In the case of the patient with right vein sarcoma, preservation of the left renal and caval intrahepatic vein was possible, whilst in the second case diagnosed with clear cell renal carcinoma, the associated left renal thrombosis also enforced the resection of the left renal vein. (3) Discussion: Postoperative evolution was favorable in both cases and did not exhibit major complications. Antibiotic therapy, analgesics, and anticoagulant medication were administered at therapeutic doses after surgery in both cases. The histopathological examination of the surgical specimen confirmed the diagnoses of renal vein sarcoma in the first case and clear cell renal carcinoma in the second case. Surgical treatment and adjuvant chemotherapy prolonged survival for two years for the first case and for two months, up until this moment, for the second case. The survival of clear cell renal carcinoma is currently at two months. (4) Conclusions: The resection of the inferior vena cava, without subsequent reconstruction in cases presenting diffused distal thrombosis, can represent an alternative to IVC reconstruction, which might lead to a major ulterior risk of thrombosis. In some cases, this can result in long-term survival.
Towards Predicting Length of Stay and Identification of Cohort Risk Factors Using Self-Attention-Based Transformers and Association Mining: COVID-19 as a Phenotype
Authors: Alam Fakhare , Ananbeh Obieda , Malik Khalid Mahmood , Odayani Abdulrahman Al , Hussain Ibrahim Bin , Kaabia Naoufel , Aidaroos Amal Al , Saudagar Abdul Khader Jilani
Published: May 2023

Predicting length of stay (LoS) and understanding its underlying factors is essential to minimizing the risk of hospital-acquired conditions, improving financial, operational, and clinical outcomes, and better managing future pandemics. The purpose of this study was to forecast patients’ LoS using a deep learning model and to analyze cohorts of risk factors reducing or prolonging LoS. We employed various preprocessing techniques, SMOTE-N to balance data, and a TabTransformer model to forecast LoS. Finally, the Apriori algorithm was applied to analyze cohorts of risk factors influencing hospital LoS. The TabTransformer outperformed the base machine learning models in terms of F1 score (0.92), precision (0.83), recall (0.93), and accuracy (0.73) for the discharged dataset and F1 score (0.84), precision (0.75), recall (0.98), and accuracy (0.77) for the deceased dataset. The association mining algorithm was able to identify significant risk factors/indicators belonging to laboratory, X-ray, and clinical data, such as elevated LDH and D-dimer levels, lymphocyte count, and comorbidities such as hypertension and diabetes. It also reveals what treatments have reduced the symptoms of COVID-19 patients, leading to a reduction in LoS, particularly when no vaccines or medication, such as Paxlovid, were available.
A Resource-Friendly Certificateless Proxy Signcryption Scheme for Drones in Networks beyond 5G
Authors: Khan Muhammad Asghar , Alhakami Hosam , Ullah Insaf , Alhakami Wajdi , Mohsan Syed Agha Hassnain , Tariq Usman , Innab Nisreen
Published: May 2023

Security and privacy issues were long a subject of concern with drones from the past few years. This is due to the lack of security and privacy considerations in the design of the drone, which includes unsecured wireless channels and insufficient computing capability to perform complex cryptographic algorithms. Owing to the extensive real-time applications of drones and the ubiquitous wireless connection of beyond 5G (B5G) networks, efficient security measures are required to prevent unauthorized access to sensitive data. In this article, we proposed a resource-friendly proxy signcryption scheme in certificateless settings. The proposed scheme was based on elliptic curve cryptography (ECC), which has a reduced key size, i.e., 80 bits, and is, therefore, suitable for drones. Using the random oracle model (ROM), the security analysis of the proposed scheme was performed and shown to be secure against well-known attacks. The performance analysis of the proposed scheme was also compared to relevant existing schemes in terms of computation and communication costs. The findings validate the practicability of the proposed scheme.
Dynamical Analysis of Hyper-ILSR Rumor Propagation Model with Saturation Incidence Rate
Authors: Mei Xuehui , Zhang Ziyu , Jiang Haijun
Published: May 2023

With the development of the Internet, it is more convenient for people to obtain information, which also facilitates the spread of rumors. It is imperative to study the mechanisms of rumor transmission to control the spread of rumors. The process of rumor propagation is often affected by the interaction of multiple nodes. To reflect higher-order interactions in rumor-spreading, hypergraph theories are introduced in a Hyper-ILSR (Hyper-Ignorant–Lurker–Spreader–Recover) rumor-spreading model with saturation incidence rate in this study. Firstly, the definition of hypergraph and hyperdegree is introduced to explain the construction of the model. Secondly, the existence of the threshold and equilibrium of the Hyper-ILSR model is revealed by discussing the model, which is used to judge the final state of rumor propagation. Next, the stability of equilibrium is studied by Lyapunov functions. Moreover, optimal control is put forward to suppress rumor propagation. Finally, the differences between the Hyper-ILSR model and the general ILSR model are shown in numerical simulations.
Teaching and Learning Optics in High School: From Fermat to Feynman
Authors: Otero Maria Rita , Arlego Marcelo Fabian
Published: May 2023

In this article, we analyze the basis of a proposal that allows teaching the notions of reflection, refraction, interference and diffraction from a unified perspective, using Fermat’s variational principle, recovered by Richard Feynman in his formulation of the paths sum for quantum mechanics. This allows reconsidering the notions of geometrical and physical optics, using the probabilistic and unified model of quantum mechanics by means of mathematical notions that are accessible to high school students.
Effectiveness of Digital Storytelling in Teaching Economics
Authors: Nunvarova Jana , Poulova Petra , Prazak Pavel , Klimova Blanka
Published: May 2023

Digital storytelling is one of the teaching methods that aims to improve motivation of students, critical thinking and learning outcomes. The results of previous research show the successful use of this method in education, but its use in some subjects is still questionable. The aim of the pedagogical experiment, which was conducted in 2021 at six business academies in the Czech Republic, was to discover whether or not digital storytelling contributes to better study results in business subjects taught at high school. A total number of 856 students were randomly divided into two independent groups. In the experimental group, the digital storytelling method was used in the process of teaching. The students in the control group were taught with the standard teaching method—the teacher’s explanation with the support of the presentation. By comparing the results from the pre-tests and post-tests of the experimental and control groups, the findings reveal that the students from the experimental group reached higher mean values in the post-test than the students from the control group did.
The Work-Related Stress and Well-Being of Teachers—An Exploratory Study within Primary Schools in Italy
Authors: Arbia Giulia , Carbone Agostino , Stanzione Irene , Szpunar Giordana
Published: May 2023

This study analyzes the critical aspects of the professional life of primary school teachers in a southern European context. The social changes of the last two decades have profoundly impacted teachers’ well-being, putting a strain on their ability to adapt to sometimes unfair working conditions. For this purpose, we interviewed twenty teachers (M = 38.85; DS = 9.17) from different areas of Italy and analyzed data using the grounded theory method. Through a data analysis, we summarized and emphasized eight core themes. The results show the effects of the gradual impoverishment of the recognition for the role of the teacher, highlighting the difficulty for teachers in renegotiating more flexible workload assessments and reinforcing psycho-emotional skills for developing a teaching methodology that is attentive to the psycho-emotional needs of their pupils. Schools emerge as a rigid working context where a competent organizational function is often absent. The practical psychological implications of this are discussed.
Enhancing Cultural Empathy in International Social Work Education through Virtual Reality
Authors: Rambaree Komalsingh , Nässén Nessica , Holmberg Jörgen , Fransson Göran
Published: May 2023

School-based bullying is a major global social problem affecting societies around the world. It is argued that Virtual Reality (VR) offers benefits and possibilities in social work education. Within this context, a study was carried out with the aim of analysing students’ experiences with a school-based bullying scenario through Head-Mounted Display Virtual Reality (HMD VR), and exploring the pedagogical potential of this technology to support the enhancement of cultural empathy in international social work education. Using cultural competence and social constructivist perspectives focused on empathy theory, this article addresses the following research questions: How do the research participants describe experiencing the bullying scene with HMD VR? How do the research participants account for their HMD VR experiences in connection with empathy? How can the pedagogical use of HMD VR enhance international social work students’ cultural empathic skills? Data for the study were gathered through four Focus Group Discussions (FGDs) with 38 volunteer research participants based on their postexposure to a scenario on school-based bullying through HMD VR. ATLAS.ti v.23 software (Atlas.ti, Berlin, Germany) was used to undertake a deductive thematic analysis. The findings reveal that HMD VR plays an important role in enhancing different dimensions of empathy, which is an essential element in transformative learning in social work education. The overall implications of using HMD VR in international social work education for enhancing cultural empathy are discussed. The article concludes that HMD VR has a promising role; however, several ethical, practical, and pedagogical aspects need to be considered for this technology tool to provide the sought-after pedagogical value in social work education.
A Spatio-Temporal Hybrid Neural Network for Crowd Flow Prediction in Key Urban Areas
Authors: He Du , Jia Jing , Wang Yaoqing , You Lan , Chen Zhijun , Li Jiawen , Wu Qiyao , Wang Yongsen
Published: May 2023

The prediction of crowd flow in key urban areas is an important basis for city informatization development and management. Timely understanding of crowd flow trends can provide cities with data support in epidemic prevention, public security management, and other aspects. In this paper, the model uses the Node2Vec graph embedding algorithm combined with LSTM (NDV-LSTM) to predict crowd flow. The model first analyzes the correspondence between key areas and grid centers, and the Node2Vec graph embedding algorithm was used to extract spatial features. At the same time, considering urban region type, weather, temperature, and other crowd flow data features, the long short-term memory (LSTM) network model was used for unified modeling. The model uses the crowd flow of the previous three days to predict the crowd flow of the next day. The model was evaluated on the 2020 CCF crowd density competition data set. The experimental results show that the NDV-LSTM model can capture the features of the region association digraph and various crowd flow correlation factors well, and the mean square error of the prediction of the crowd flow in key areas is reduced to 1.5194.
ModDiff: Modularity Similarity-Based Malware Homologation Detection
Authors: Sun Huaqi , Shu Hui , Kang Fei , Guang Yan
Published: May 2023

In recent years, the number and scale of malicious codes have grown exponentially, posing an increasing threat to cybersecurity. Hence, it is of great research value to quickly identify variants of malware and master their family information. Binary code similarity detection, as a key technique in reverse analysis, plays an indispensable role in malware analysis. However, most existing methods focus on similarity at the function or basic block level, ignoring the modular composition of malware. Implementing similarity detection among malware modules would greatly improve the efficiency and accuracy of homology detection. Inspired by the successful application of deep-learning techniques in program analysis, we propose a binary code module similarity detection method called ModDiff. It abstracts malware into attribute graphs, clusters functions using graph-embedded clustering algorithms to decompose malware into function-based modules, and calculates module similarity using graph-matching algorithms and natural language processing-based function similarity detection algorithms. The experimental results indicated that ModDiff improves the accuracy of module partitioning by 10.8% compared with previous work, and the highest F1 score of 89% is achieved in malware homologation detection. These results demonstrate the effectiveness of ModDiff in detecting and analyzing malware with important application value and development prospects.
Thirteen-Level Switching Capacitor Inverter with Six Times Boost and Self-Balancing Capability
Authors: Li Shengqing , Liu Li , Wu Qiang , He Weihua , Deng Na
Published: May 2023

A thirteen-level inverter based on switching capacitor is proposed in order to improve the boost capacity and output power quality of inverter in renewable energy power generation system. The proposed topology is composed of one DC input power supply, three capacitors and 14 switching devices, and achieves thirteen-level output with six times voltage boost. It has smaller volume, lower cost and output harmonic content. Moreover, it can realize inverter without H bridge and reduce the voltage stress of switching tube. In addition, the proposed inverter can achieve self-balancing capacitor voltage without any auxiliary method, simplifying the complexity of control. The superiority of the proposed topology is verified by comparing with other traditional multilevel inverters. The simulation and experimental verification on the simulation and prototype platform show that the inverter has good performance in both steady and dynamic conditions.
Transmission and Distribution Real-Time Analysis Software for Monitoring and Control: Design and Simulation Testing
Authors: Zhu Dan , Dilek Murat , Zhong Max , Parchure Abhineet , Broadwater Robert , Cincotti Nicholas , Kutchen Timothy , Placide Scott , Watson Luan
Published: May 2023

The US electric grid is facing operational, stability, and security challenges. Transmission system operators need some measure of visibility into distribution system renewable generation. Distribution system generation needs to support transmission system voltage. The grid is experiencing an expansion in measurement systems. How to take full advantage of this expansion and defend against attacks, both cyber and physical, poses additional challenges. This paper introduces software designed to meet these challenges. At the center of the software is an Integrated System Model (ISM) that spans from transmission to secondary distribution. The ISM is employed in real-time abnormality detection, voltage stability forecasting, and multi-mode control. The software architecture along with selected analysis modules is presented. Testing results are presented for: 1—attacks on utility infrastructure; 2—energy savings from optimal control; 3—distribution system control response during a low voltage transmission system event; 4—cyber-attacks on PV inverters, where physical inverters are used in hardware-in-the-simulation-loop studies. Contributions of this work include real-time analysis that spans from three-phase transmission through secondary distribution; an approach for detecting abnormalities that employs measurements from three independent measurement systems; and a multi-mode distribution system control that responds to cyber-attacks, physical attacks, equipment failures, and transmission system needs.
Comparative Life Cycle Assessment of Carbon Dioxide Mineralization Using Industrial Waste as Feedstock to Produce Cement Substitutes
Authors: Digulla Finn-Erik , Bringezu Stefan
Published: May 2023

The mineralization of carbon dioxide offers a way to permanently sequester carbon while producing construction materials, combining the concepts of carbon capture and utilization (CCU) and carbon capture and storage (CSS). However, it is important to evaluate different mineralization processes in terms of their environmental impact. This study provides the first comparative life cycle assessment (LCA) analysis that focuses on the utilization of industrial waste materials. We analyzed the climate and material footprint of six mineralization pathways from cradle to gate using steel slag, concrete waste, municipal solid waste incineration (MSWI) ash, and olivine as feedstock. A sensitivity analysis was used to identify the factors with the greatest impact on environmental performance. Our results show that all processes generate significantly negative values for the global warming impact (GWI) and raw material input (RMI), ranging from −0.6 to −1.3 kgCO2eq.kgfeed−1 and −0.6 to −1.6 kgkgfeed−1, when cement substitute is considered as product. Five out of six processes produce negative values for these factors when sand is considered as a product. When operated as a CCS technology without product use, the processes result in GWI values ranging from −0.13 to 0.01 kgCO2eq.kgfeed−1. Our study confirms that industrial mineralization is a promising technology for reducing carbon dioxide emissions. Future process development should focus on replacing carbon dioxide-intensive products while balancing energy and chemical demand with process efficiency.
Eco-Driving Optimization Based on Variable Grid Dynamic Programming and Vehicle Connectivity in a Real-World Scenario
Authors: Pulvirenti Luca , Tresca Luigi , Rolando Luciano , Millo Federico
Published: May 2023

In a context in which the connectivity level of last-generation vehicles is constantly on the rise, the combined use of Vehicle-To-Everything (V2X) connectivity and autonomous driving can provide remarkable benefits through the synergistic optimization of the route and the speed trajectory. In this framework, this paper focuses on vehicle ecodriving optimization in a connected environment: the virtual test rig of a premium segment passenger car was used for generating the simulation scenarios and to assess the benefits, in terms of energy and time savings, that the introduction of V2X communication, integrated with cloud computing, can have in a real-world scenario. The Reference Scenario is a predefined Real Driving Emissions (RDE) compliant route, while the simulation scenarios were generated by assuming two different penetration levels of V2X technologies. The associated energy minimization problem was formulated and solved by means of a Variable Grid Dynamic Programming (VGDP), that modifying the variable state search grid on the basis of the V2X information allows to drastically reduce the DP computation burden by more than 95%. The simulations show that introducing a smart infrastructure along with optimizing the vehicle speed in a real-world urban route can potentially reduce the required energy by 54% while shortening the travel time by 38%. Finally, a sensitivity analysis was performed on the biobjective optimization cost function to find a set of Pareto optimal solutions, between energy and travel time minimization.
Tight Sandstone Reservoir Characteristics and Controlling Factors: Outcrops of the Shanxi Formation, Liujiang River Basin, North China
Authors: Zhou Tianqi , Yuan Hongqi , Xu Fengming , Wu Rigen
Published: May 2023

Tight sandstone reservoirs are of interest due to their potentially favorable prospects for hydrocarbon exploration. A better understanding of tight sandstone outcrop reservoir characteristics and their influencing factors is thus needed. By laboratory observation, thin section analysis, and experimental analysis, the current work carried out a detailed investigation of densely sampled tight sandstone outcrops of the Shanxi Formation in the Liujiang River Basin, paving the way for further research on rock types, reservoir spatial distribution, physical properties, and their key controlling factors. The application of the Pressure Pulse Attenuation Method made it possible to determine the porosity and permeability, as well as the analysis of debris composition and filling content. The findings indicate that the main rock type of the tight sandstone outcrop reservoirs in the Shanxi Formation in the Liujiang River Basin is lithic quartz sandstone, some of which contains fine sand-bearing argillaceous siltstone, giving them very low porosity (average porosity of 4.34%) and low permeability (average permeability of 0.023 mD) reservoirs. Secondary pores—mostly dissolved pores among and in grains—are widely developed in the target region. In addition, diagenesis primarily includes mechanical compaction, cementation, and dissolution. The main controlling factors of tight sandstone reservoirs in the target region are sedimentation, diagenesis, and tectonics, whereby sedimentation affects reservoir physical properties that become better as the clast size increases, reservoir properties are negatively impacted by compaction and cementation, and reservoir properties are somewhat improved due to dissolution and the impact of tectonism. In addition, the tilt of the crust will produce faults during the tectonic action, generating reservoir cracks that improve the reservoir’s physical properties. This study tends to be helpful in the prediction of high-quality reservoirs in the Permian Shanxi Formation in North China and can also be used for analogy of high-quality reservoirs in similar areas with complete outcrops.
Overview of Various Voltage Control Technologies for Wind Turbines and AC/DC Connection Systems
Authors: Wu Yuan-Kang , Gau Deng-Yue , Tung Trinh-Duc
Published: May 2023

Wind power generation is one of the mainstream renewable energy resources. Voltage stability is as important as the frequency stability of a power system with a high penetration of wind power generation. The advantages of high-voltage direct current (HVDC) transmission systems become more significant with the increase of both installed capacity and transmission distance in offshore wind farms. Therefore, this study discusses various voltage control methods for wind turbines and HVDC transmission systems. First, various voltage control methods of a wind farm were introduced, and they include QV control and voltage droop control. The reactive power of a wind turbine varies with active power, while the active power from each wind turbine may be different owing to wake effects. Thus, QV and voltage droop control with varying gain values are also discussed in this paper. Next, the voltage control methods for an HVDC transmission system, such as power factor control, voltage control, and Vac-Q control, are also summarized and tested in this study. When a three-phase short circuit fault occurs or a sudden reactive power load increases, the system voltage would drop immediately. Thus, various voltage control methods for wind turbines or HVDC can make the system’s transient response more stable. Therefore, this study implemented the simulation scenarios, including a three-phase short circuit fault at the point of common coupling (PCC) or a sudden increase of reactive power load, and adopted various voltage control methods, which aim to verify whether additional voltage control methods are effective to improve the performance of transient voltage. The voltage control method has been implemented in PSCAD/EMTDC, and the simulation results show that the QV control performs better than the droop control. In addition, when applying the voltage control technique during a three-phase fault, transient voltage nadir can be improved through either an HVDC transmission system or an AC transmission system.
Short-Term Power Load Forecasting Based on Feature Filtering and Error Compensation under Imbalanced Samples
Authors: Wan Zheng , Li Hui
Published: May 2023

There are many influencing factors present in different situations of power load. There is also a strong imbalance in the number of load samples. In addition to examining the problem of low training efficiency of existing algorithms, this paper proposes a short-term power load prediction method based on feature selection and error compensation under imbalanced samples. After clustering the load data, we expand some sample data to balance the sample categories and input the load data and filtered feature sequences into the improved GRU for prediction. At the same time, the errors generated during the training process are used as training data. An error correction model is constructed and trained, and the results are used for error compensation to further improve prediction accuracy. The experimental results show that the overall prediction accuracy of the model has increased by 80.24%. After expanding a few samples, the prediction accuracy of the region where the samples are located increased by 59.41%. Meanwhile, due to the improvement of the algorithms, the running time was reduced by approximately 14.92%.
Multicriteria Optimisation of the Structure of a Hybrid Power Supply System for a Single-Family Housing Estate in Poland, Taking into Account Different Electromobility Development Scenarios
Authors: Tomczewski Andrzej , Mikulski Stanisław , Piotrowski Adam , Sowa Sławomir , Wróbel Krzysztof
Published: May 2023

This article focuses on determining the optimum structure for a hybrid generation and storage system designed to power a single-family housing estate, taking into account the different number of electric vehicles in use and an assumed level of self-consumption of the generated energy. In terms of generation, two generation sections—wind and solar—and a lithium-ion container storage system will be taken into account. With regards to energy consumption, household load curves, determined on the basis of the tariff for residential consumers and modified by a random disturbance, will be taken into account, as well as the processes for charging electric cars with AC chargers, with power outputs ranging between 3.6 and 22 kW. Analyses were carried out for three locations in Poland—the Baltic Sea coast (good wind conditions), the Lublin Uplands (the best insolation in Poland) and the Carpathian foothills (poor wind and insolation conditions). The mathematical and numerical model of the system and the MOPSO (multiobjective particle swarm optimisation) algorithm were implemented in the Matlab environment. The results include Pareto fronts (three optimisation criteria: minimisation of energy storage capacity, minimisation of energy exchanged with the power grid and maximisation of the self-consumption rate) for the indicated locations and three electromobility development scenarios with determined NPVs (net present values) for a 20-year lifetime. The detailed results relate to the inclusion of an additional expert criterion in the form of a coupled payback period of no more than 10 years, a maximum NPV in the last year of operation and a self-consumption rate of at least 80%. The economic calculations take into account the decrease in PV installation capacity as a function of the year of operation, as well as changes in electricity and petrol prices and variations in energy prices at purchase and sale.
Performance Optimization of CsPb(I1–xBrx)3 Inorganic Perovskite Solar Cells with Gradient Bandgap
Authors: Wang Luning , Yang Sui , Xi Tingting , Yang Qingchen , Yi Jie , Li Hongxing , Zhong Jianxin
Published: May 2023

In recent years, inorganic perovskite solar cells (PSCs) based on CsPbI3 have made significant progress in stability compared to hybrid organic–inorganic PSCs by substituting the volatile organic component with Cs cations. However, the cubic perovskite structure of α-CsPbI3 changes to the orthorhombic non-perovskite phase at room temperature resulting in efficiency degradation. The partial substitution of an I ion with Br ion benefits for perovskite phase stability. Unfortunately, the substitution of Br ion would enlarge bandgap reducing the absorption spectrum range. To optimize the balance between band gap and stability, introducing and optimizing the spatial bandgap gradation configuration is an effective method to broaden the light absorption and benefit the perovskite phase stability. As the bandgap of the CsPb(I1–xBrx)3 perovskite layer can be adjusted by I-Br composition engineering, the performance of CsPb(I1–xBrx)3 based PSCs with three different spatial variation Br doping composition profiles were investigated. The effects of uniform doping and gradient doping on the performance of PSCs were investigated. The results show that bandgap (Eg) and electron affinity(χ) attributed to an appropriate energy band offset, have the most important effects on PSCs performance. With a positive conduction band offset (CBO) of 0.2 eV at the electron translate layer (ETL)/perovskite interface, and a positive valence band offset (VBO) of 0.24 eV at the hole translate layer (HTL)/perovskite interface, the highest power conversion efficiency (PCE) of 22.90% with open–circuit voltage (VOC) of 1.39 V, short–circuit current (JSC) of 20.22 mA/cm2 and filling factor (FF) of 81.61% was obtained in uniform doping CsPb(I1–xBrx)3 based PSCs with x = 0.09. By carrying out a further optimization of the uniform doping configuration, the evaluation of a single band gap gradation configuration was investigated. By introducing a back gradation of band gap directed towards the back contact, an optimized band offset (front interface CBO = 0.18 eV, back interface VBO = 0.15 eV) was obtained, increasing the efficiency to 23.03%. Finally, the double gradient doping structure was further evaluated. The highest PCE is 23.18% with VOC close to 1.44 V, JSC changes to 19.37 mA/cm2 and an FF of 83.31% was obtained.