bluuebunny/crossref_metadata_2025 huggingface dataset:
Biocompatibility Analysis of GelMa Hydrogel and Silastic RTV 9161 Elastomer for Encapsulation of Electronic Devices for Subdermal Implantable Devices
Authors: Dragomir David Catalin , Carbunaru Vlad , Moldovan Carmen Aura , Lascar Ioan , Dontu Octavian , Ristoiu Violeta , Gheorghe Roxana , Oproiu Ana Maria , Firtat Bogdan , Franti Eduard , Dascalu Monica , Neagu Tiberiu Paul , Enescu Dan Mircea , Ionescu Octavian , Ion Marian , Mihailescu Carmen , Costea Ruxandra , Gonciarov Magda , Ionescu Gabriela , Dumitru Adrian , Minca Anca , Niculae Catalin , Raita Stefania , Rosca Ioana , Lazarescu Sorin , Stoica Cristian , Teleanu Raluca Ioana , Teleanu Daniel Mihai
Published: December 2022

The natural differences between human-made electronics and biological tissues constitute a huge challenge in materials and the manufacturing of next-generation bioelectronics. As such, we performed a series of consecutive experiments for testing the biofunctionality and biocompatibility for device implantation, by changing the exterior chemical and physical properties of electronics coating it with silicone or hydrogels. In this article, we present a comparison of the main characteristics of an electronic device coated with either silicone or hydrogel (GelMa). The coating was performed with a bioprinter for accurate silicone and hydrogel deposition around different electronic chips (Step-Down Voltage Regulator U3V15F5 from Pololu Corporation). The results demonstrate that the hydrogel coating presents an augmented biomechanical and biochemical interface and superior biocompatibility, lowers foreign body response, and considerably extends the capabilities for bioelectronic applications.
Long-Term Stability of Novel Crucible Systems for the Growth of Oxygen-Free Czochralski Silicon Crystals
Authors: Sturm Felix , Trempa Matthias , Schuster Gordian , Hegermann Rainer , Goetz Philipp , Wagner Rolf , Barroso Gilvan , Meisner Patrick , Reimann Christian , Friedrich Jochen
Published: December 2022

The replacement of the silica glass crucible by oxygen-free crucible materials in silicon Czochralski (Cz) growth technology could be a key factor to obtaining Cz silicon, with extremely low oxygen contamination < 1 × 1017 at/cm3 required for power electronic applications. So far, isostatic pressed graphite or nitrogen-bonded silicon nitride (NSN) crucible material, in combination with a chemical vapor deposited silicon nitride (CVD-Si3N4) surface coating, could be identified as promising materials by first short-term experiments. However, for the evaluation of their potential for industrial scale Cz growth application, the knowledge about the long-term behavior of these crucible setups is mandatory. For that purpose, the different materials were brought in contact with silicon melt up to 60 h to investigate the infiltration and dissolution behavior. The chosen graphite, as well as the pore-sealed NSN material, revealed a subordinated infiltration-depth of ≤1 mm and dissolution of ≤275 µm by the silicon melt, so they basically fulfilled the general safety requirements for Cz application. Further, the highly pure and dense CVD Si3N4 crucible coating showed no measurable infiltration as well as minor dissolution of ≤50 µm and may further acts as a nucleation site for nitrogen-based precipitates. Consequently, these novel crucible systems have a high potential to withstand the stresses during industrial Cz growth considering that more research on the process side relating to the particle transport in the silicon melt is needed.
Boundary Effect and Critical Temperature of Two-Band Superconducting FeSe Films
Authors: Ye Chenxiao , Che Jiantao , Huang Hai
Published: December 2022

Based on two-band Bogoliubov–de Gennes theory, we study the boundary effect of an interface between a two-gap superconductor FeSe and insulator (or vacuum). New boundary terms are introduced into two-band Ginzburg–Landau formalism, which modifies the boundary conditions for the corresponding order parameters of superconductor. The theory allows for a mean-field calculation of the critical temperature suppression with the decrease in FeSe film thickness. Our numerical results are in good agreement with the experimental data observed in this material.
A Review on Preparation of Superhydrophobic and Superoleophobic Surface by Laser Micromachining and Its Hybrid Methods
Authors: Liu Yang , Wu Mingyi , Guo Chunfang , Zhou Dong , Wu Yucheng , Wu Zhaozhi , Lu Haifei , Zhang Hongmei , Zhang Zhaoyang
Published: December 2022

Functional wetting surfaces have excellent prospects in applications including self-cleaning, anti-fog, anti-icing, corrosion resistance, droplet control, and friction power generation. Laser micromachining technology is an advanced method for preparing such functional surfaces with high efficiency and quality. To fully exploit the potential of laser micromachining and the related hybrid methods, a wide spectrum of knowledge is needed. The present review systematically discusses the process capabilities and research developments of laser micromachining and its hybrid methods considering the research both in basic and practical fields. This paper outlines the relevant literature, summarizes the characteristics of functional wetting surfaces and also the basic scientific requirements for laser micromachining technology. Finally, the challenges and potential applications of superhydrophobic and superoleophobic surface are briefly discussed. This review fills the gap in the research literature by presenting an extended literature source with a wide coverage of recent developments.
Specific Aspects of Immunotherapy for Multiple Sclerosis in Switzerland—A Structured Commentary, Update 2022
Authors: Friedli Christoph , Salmen Anke , Hoepner Robert , Achtnichts Lutz , Bigi Sandra , Derfuss Tobias , Gobbi Claudio , Kamber Nicole , Kamm Christian P. , Kuhle Jens , Lalive Patrice , Müller Stefanie , Papadopoulou Athina , Pot Caroline , Zecca Chiara , Chan Andrew
Published: December 2022

Multiple sclerosis (MS), particularly relapsing MS (RMS), has become a treatable disease in recent decades, and immunotherapies are now able to influence long-term disease course. A wide range of disease-modifying drugs are available, which makes the choice of therapy in individual cases considerably more complex. Due to specific regulatory aspects (partly diverging approvals by Swissmedic compared to the European Medicines Agency (EMA), and an independent evaluation process for the Federal Office of Public Health (FOPH) specialities list (SL)), we issued a consensus recommendation regarding specific aspects of immunotherapy for MS in Switzerland in 2019. Here, we present revised recommendations with an update on newly approved drugs and new safety aspects, also in reference to the risk of COVID-19 infection and vaccination.
Trifluridine/Tipiracil in the Real-World Management of Metastatic Gastric and Gastroesophageal Junction Cancers in Canada
Authors: Ding Philip Q. , Dolley Aastha , Cheung Winson Y.
Published: December 2022

Background: Gastric cancer mortality remains among the highest of all cancers. Trifluridine/tipiracil (FTD/TPI) represents Canada’s first standard-of-care, third-line, systemic therapy for metastatic gastric/gastroesophageal cancer. We characterized real-world treatment patterns in patients enrolled to receive FTD/TPI through Taiho Pharma Canada’s Patient Support Program. Methods: Demographic and clinical information were collected from November 2019 to November 2021 for adult patients with refractory metastatic gastric/gastroesophageal cancer throughout Canada. We examined all variables using descriptive statistics and performed survival and association analyses. Results: 162 patients enrolled to receive FTD/TPI with a median age of 65 years, 12 of whom had HER2 positive disease. Among 123 patients who started FTD/TPI, median follow-up was 3.1 months and median progression-free survival (PFS) was 3.5 months (95% CI 3.2–4.0). Among 121 patients who discontinued FTD/TPI, median treatment duration was 2.39 cycles (IQR 1.14–3.86). A total of 52% discontinued treatment due to disease progression, and 27% had a dose reduction or delay. On multivariable logistic regression, prior FOLFIRI was a statistically significant predictor of treatment modification. Conclusions: Through the Patient Support Program, FTD/TPI is an actively utilized treatment option in heavily pretreated metastatic gastric/gastroesophageal cancer, despite its recent introduction. With longer-than-expected treatment duration and PFS, FTD/TPI likely addresses an important unmet need for effective and tolerable therapies in this setting.
Disparate Time-to-Treatment and Varied Incidence of Actionable Non-Small Cell Lung Cancer Molecular Alterations in British Columbia: A Historical Cohort Study
Authors: Hilzenrat Roy Avraham , Yip Stephen , Melosky Barbara , Ho Cheryl , Laskin Janessa , Sun Sophie , Choi James J. , McGuire Anna L.
Published: December 2022

Background: non-small cell lung cancer (NSCLC) outcomes remain suboptimal for early-stage disease despite emerging advances in systemic therapy for the peri-operative period. Next-generation sequencing (NGS) identifies driver mutations for which targeted therapies have been developed that improve survival. The BC lung cancer screening program, which was initiated in May 2022, is expected to identify people with early and late stages of NSCLC. It is crucial to first understand the molecular epidemiology and patterns of time to initiate treatment across its five health authorities (HA) to optimize the delivery of care for NSCLC in BC. In this way, we may harness the benefits of targeted therapy for more people with NSCLC as novel advances in therapy continue to emerge. Objective: to compare (a) the frequency of actionable NSCLC molecular alterations among HAs and (b) the time to treatment initiation. Methods: a retrospective observational study was conducted with prospectively collected data from the BC CGL Database. Adults with late stage NSCLC who underwent targeted NGS were included for the time period from May 2020 to June 2021. Demographics, actionable molecular alterations, PDL-1 expression, and time to treatment across HAs were examined. Using appropriate statistical tests for comparison among HAs, p>0.05 was deemed significant. Results: 582 patients underwent NGS/IHC and analysis during the study period. The mean age was 71 (10.1), and 326 (56%) patients were female. A significantly higher proportion of all EGFRm+ were identified within Vancouver Coastal Health (VCHA) and Fraser Health Authority (FHA) compared to the other health authorities (p < 0.001). This also holds true for common sensitizing EGFRm+ alone (p < 0.001) and for sensitizing EGFRm+ when adjusted for females and smoker status (OR 0.75; 95% CI 0.62, 0.92; p = 0.005). Patients residing within the Northern, Interior, and Island HAs were less likely to receive treatment at the same rate as those in VCHA and FHA HAs. Conclusion: actionable NSCLC driver mutations are present in all regional HAs, with disparity noted in time to initiate treatment between HAs. This provides evidence for the importance of molecular testing for patients in all BC HAs to guide personalized and timely NSCLC treatment.
Identification of a Two-Gene Signature and Establishment of a Prognostic Nomogram Predicting Overall Survival in Diffuse-Type Gastric Cancer
Authors: Chen Songyao , Xu Jiannan , Yin Songcheng , Wang Huabin , Liu Guangyao , Jin Xinghan , Zhang Junchang , Wang Huijin , Wang Han , Li Huan , Liang Jianming , He Yulong , Zhang Changhua
Published: December 2022

Background: It is widely acknowledged that the molecular biological characteristics of diffuse-type gastric cancer are different from intestinal-type gastric cancer. Notwithstanding that significant progress in high-throughput sequencing technology has been made, there is a paucity of effective prognostic biomarkers for diffuse gastric cancer for clinical practice. Methods: We downloaded four GEO datasets (GSE22377, GSE38749, GSE47007 and GSE62254) to establish and validate a prognostic two-gene signature for diffuse gastric cancer. The TGCA-STAD dataset was used for external validation. The optimal gene signature was established by using Cox regression analysis. Receiver operating characteristic (ROC) methodology was used to find the best prognostic model. Gene set enrichment analysis was used to analyze the possible signaling pathways of the two genes (MEF2C and TRIM15). Results: A total of four differently expressed genes (DEGs) (two upregulated and two downregulated) were identified. After a comprehensive analysis, two DEGs (MEF2C and TRIM15) were utilized to construct a prognostic model. A prognostic prediction model was constructed according to T stage, N stage, M stage and the expression of MEF2C and TRIM15. The area under the time-dependent receiver operator characteristic was used to evaluate the performance of the prognosis model in the GSE62254 dataset. Conclusions: We demonstrated that MEF2C and TRIM15 might be key genes. We also established a prognostic nomogram based on the two-gene signature that yielded a good performance for predicting overall survival in diffuse-type gastric cancer.
Radiation in Early-Stage Breast Cancer: Moving beyond an All or Nothing Approach
Authors: Purswani Juhi M. , Hardy-Abeloos Camille , Perez Carmen A. , Kwa Maryann J. , Chadha Manjeet , Gerber Naamit K.
Published: December 2022

Radiotherapy omission is increasingly considered for selected patients with early-stage breast cancer. However, with emerging data on the safety and efficacy of radiotherapy de-escalation with partial breast irradiation and accelerated treatment regimens for low-risk breast cancer, it is necessary to move beyond an all-or-nothing approach. Here, we review existing data for radiotherapy omission, including the use of age, tumor subtype, and multigene profiling assays for selecting low-risk patients for whom omission is a reasonable strategy. We review data for de-escalated radiotherapy, including partial breast irradiation and acceleration of treatment time, emphasizing these regimens’ decreasing biological and financial toxicities. Lastly, we review evidence of omission of endocrine therapy. We emphasize ongoing research to define patient selection, treatment delivery, and toxicity outcomes for de-escalated adjuvant therapies better and highlight future directions.
LoRaWAN Path Loss Measurements in an Urban Scenario including Environmental Effects
Authors: González-Palacio Mauricio , Tobón-Vallejo Diana , Sepúlveda-Cano Lina M. , Rúa Santiago , Pau Giovanni , Le Long Bao
Published: December 2022

LoRaWAN is a widespread protocol by which Internet of things end nodes (ENs) can exchange information over long distances via their gateways. To deploy the ENs, it is mandatory to perform a link budget analysis, which allows for determining adequate radio parameters like path loss (PL). Thus, designers use PL models developed based on theoretical approaches or empirical data. Some previous measurement campaigns have been performed to characterize this phenomenon, primarily based on distance and frequency. However, previous works have shown that weather variations also impact PL, so using the conventional approaches and available datasets without capturing important environmental effects can lead to inaccurate predictions. Therefore, this paper delivers a data descriptor that includes a set of LoRaWAN measurements performed in Medellín, Colombia, including PL, distance, frequency, temperature, relative humidity, barometric pressure, particulate matter, and energy, among other things. This dataset can be used by designers who need to fit highly accurate PL models. As an example of the dataset usage, we provide some model fittings including log-distance, and multiple linear regression models with environmental effects. This analysis shows that including such variables improves path loss predictions with an RMSE of 1.84 dB and an R2 of 0.917.
Thermal Data of Perfluorinated Carboxylic Acid Functionalized Aluminum Nanoparticles
Authors: Weeks Nathan J. , Martin Bradley , Gazmin Enrique , Iacono Scott T.
Published: December 2022

Improving the performance of composite energetic materials comprised of a solid metal fuel and a source of oxidizer (known as thermites) has long been pursued as thermites for pyrolant flares and rocket propellants. The performance of thermites, involving aluminum as the fuel, can be dramatically improved by utilizing nanometer-sized aluminum particles (nAl) leading to vastly higher reaction velocities, owing to the high surface area of nAl. Despite the benefits of the increased surface area, there are still several problems inherent to nanoscale reactants including particle aggregation, and higher viscosity composited materials. The higher viscosity of nAl composites is cumbersome for processing with inert polymer binder formulations, especially at the high mass loadings of metal fuel necessary for industry standards. In order to improve the viscosity of high mass loaded nAl energetics, the surface of the nAl was passivated with covalently bound monolayers of perfluorinated carboxylic acids (PFCAs) utilizing a novel fluorinated solvent washing technique. This work also details the quantitative binding of these monolayers using infrared spectroscopy, in addition to the energetic output from calorimetric and thermogravimetric analysis.
Active Vibration Control of Timoshenko Sigmoid Functionally Graded Porous Composite Beam with Distributed Piezoelectric Sensor/Actuator in a Thermal Environment
Authors: El Harti Khalid , Saadani Rachid , Rahmoune Miloud
Published: December 2022

This work presents the study of the dynamics and active control of a cantilever sigmoid FGM beam with porosities in a thermal environment. During this study, we considered the Timoshenko beam’s theory combined with the finite element method (FEM). This work also presents a comparative study with an experimental study for the vibration of a functionally graded piezoelectric beam (FGPM) to validate the numerical model. Linear quadratic Gaussian (LQG) optimal control with a Kalman filter was used for the vibration control using piezoelectric sensors and actuators as symmetrical layers to eliminate membrane effects. The controlled and uncontrolled responses are presented, considering the influence of thermal effect, the porosity of the FGM material, and the location of the sensor pair on the smart structure. The results indicate that the porosity effect of the FGM material, as well as the application of the thermal effect, involves an increase in vibration frequencies, in contrast to the increase in the power law index. The study also shows that the thermal and porosity effects result in an increase in vibration amplitudes.
Near-Infrared Transillumination for Occlusal Carious Lesion Detection: A Retrospective Reliability Study
Authors: Mohamed Nur Muna , Vazquez Lydia , Anton Y. Otero Clara , Giacobino Caroline , Krejci Ivo , Abdelaziz Marwa
Published: December 2022

The aim of this study was to assess the reliability of three diagnostic methods (near-infrared transillumination (NIRT), bitewing radiographs (BW), and clinical images (CI)) to detect occlusal carious lesions in a low caries risk population. This retrospective analysis included one hundred and eighty-eight occlusal surfaces, scored as sound surface, early lesion, or distinct lesion. We evaluated the agreement between and within the methods over time. Kappa statistics tested the correlation between the methods. Examiners detected occlusal early lesions more frequently with visual examination and NIRT and the same lesions were confirmed on the 2-year follow-up. Within the limitations of this study, we were able to establish that early occlusal lesions can be detected and monitored over time using NIRT and visual exam, while BW scores showed mostly sound surfaces at both examinations. NIRT combined with clinical examination can be considered appropriate to detect and monitor early enamel caries on the occlusal surface in low caries-risk populations.
Aorticoesophagal Fistula Combined with Upper Gastrointestinal Bleeding after Endovascular Dissection of Thoracic Aortic Aneurysm
Authors: Xu Yongwei , Li Ran , Zhang Kangwei , Xu Shuchang
Published: December 2022

Aortoesophageal fistula (AEF) is a relatively rare and potentially fatal disease. Secondary AEF is rare but is associated with serious complications and high mortality. There are rare cases of esophageal mediastinal fistula after descending aortic aneurysm stent implantation. We report the case of a 76-year-old man who had upper abdominal distension, without obvious inducement, for 3 months and felt fullness after a meal, accompanied by anorexia. A chest computer tomography (CT) examination of the abdomen was performed with the outside hospital. Descending thoracic aortic aneurysm was discovered and was treated with stent implantation. The patient was transferred to our hospital to continue treatment, mainly because of an esophageal mediastinal fistula. Finally, the thoracic aortic aneurysm was diagnosed as AEF after stent implantation, combined with the diagnosis of upper gastrointestinal bleeding. We hope that, through this case, we can explain the possible causes of bronchial mediastinal fistula after stent implantation of descending aortic aneurysm and the mechanism of upper gastrointestinal bleeding.
Laboratory Study of Microsatellite Control Algorithms Performance for Active Space Debris Removal Using UAV Mock-Ups on a Planar Air-Bearing Test Bed
Authors: Kozin Filipp , Akhloumadi Mahdi , Ivanov Danil
Published: December 2022

In this paper, a planar air-bearing test bed with unmanned aerial vehicles (UAV) was used to test a microsatellite motion control system. The UAV mock-ups were controlled by four ventilator actuators that imitated the satellite thrusters and provided the required acceleration vector in the horizontal plane, and torque along the vertical direction. The mock-ups moved almost without friction along the planar air-bearing test bed due to the air cushion between the test bed surface and the flat mock-up base. The motion of the mock-ups motion imitated the motion of satellites in the orbital plane. The problem of space debris can be solved using special microsatellite missions able to dock to space debris objects and change their orbit. In this paper, two control algorithms based on the virtual potentials approach and the State Dependent Ricatti Equation (SDRE) controller, were proposed for docking to a non-cooperative space debris object. The algorithms were tested in a laboratory facility, and the results are presented and analyzed, including their main features demonstrated during the laboratory study. It was shown that the SDRE-based control was faster, although the virtual potential-based control required less characteristic velocity.
Project-Based Unit Development by Middle School Science Teachers: Investigations on Watershed Water Quality
Authors: Krall Rebecca McNall , Wilhelm Jennifer Anne , LeVaughn Justin M.
Published: December 2022

This case study explored changes in seven in-service middle school science teachers’ understandings of project-based learning (PBL) environments after participating in a summer institute on PBL. Of particular interest was their participation in the institute as learners in a PBL unit exploring the effect of land use on water quality in the watershed. We investigated how well teachers were able to apply their understanding of PBL as they designed their own units on water quality in their watershed. Research questions focused the study on how participation in a summer teacher institute on PBL prepared middle school teachers to describe key features of project-based learning environments, and how well they were able to incorporate these features in PBL units. Data collection included a qualitative pre/post PBL survey, teachers’ watershed units, and field notes from the institute. Findings from the pre and post survey showed that teachers demonstrated a vague understanding of essential features of PBL environments pre institute and a detailed understanding of PBL post institute. Teachers’ units varied in the degrees to which PBL features were exhibited. Strengths of the units included driving questions and benchmark lessons. Shortcomings included few opportunities for student-directed investigation of sub-driving questions.
Towards the Mainstreaming of Online Mobility at KU Leuven
Authors: Clement Mieke , Op de Beeck Ilse , Rajagopal Kamakshi
Published: December 2022

Online mobility—learning activities where students engage online with other institutions abroad, while physically remaining at their home institution—has been of interest for several decades in Europe and at KU Leuven. This article describes the journey KU Leuven is going through to bring this form of learning into their mainstream offering to their 60,000+ students. Framed in Educational Design Research, this article presents a study where the authors explore the core needs regarding didactic support and student administration to devise interventions facilitating the university-wide uptake of online mobility. They reflect on the steps taken towards policy-level strategic vision development as well as micro-level sustainable support structures.
Temperature Estimation of HBM2 Channels with Tail Distribution of Retention Errors in FPGA-HBM2 Platform
Authors: Kwon Junhyeong , Wen Shi-Jie , Fung Rita , Baeg Sanghyeon
Published: December 2022

High-bandwidth memory 2 (HBM2) vertically stacks multiple dynamic random-access memory (DRAM) dies to achieve a small form factor and high capacity. However, it is difficult to diagnose HBM2 issues owing to their structural complexity and 2.5D integration with heterogeneous chips. The effects of the temperature at the base logic die (TL), and the refresh interval at the stacked DRAM dies, were experimentally investigated by counting the dynamic retention errors in the eight channels in an HBM2. TL was indirectly controlled by the heatsink temperature (TS). The lognormal distribution represents the distribution of the cell counts with varying refresh times. All Z-magnitudes (multiples of the distribution standard deviation) over the various refresh cycle times (RCTs) up to 2.045 s in a single channel at TL of 70 °C appeared below 4.4, which means that the error bits belong to the tail distribution. The Z-differences in the eight channels were distinctively larger than the Z-differences of the same channels at a constant temperature, demonstrating that the temperature difference in the stacked dies resulted in larger Z-differences. The largest Z-difference was 0.091 for all the channels at an RCT of 1.406 s, which was approximately 4.82 times smaller than the Z-difference between the TL temperatures of 70 °C and 80 °C in a single channel. The Z-difference between the TL temperatures of 70 °C and 72 °C in a single channel was approximately the same as the Z-difference in all the channels at an RCT of 2.045 s.
Electromechanical Properties of a Hybrid Broadband Wind Energy Harvester for Smart Agriculture Monitoring in the Loess Plateau
Authors: Hu Lei , Duan Zhigang , Song Jinsha , Wu Bo , Wang Hui , He Jian
Published: December 2022

Wind, as a ubiquitous energy, is an important power source for intelligent monitoring systems in smart agriculture applications, and its efficient collection can greatly improve the long-term performance of monitoring systems. However, it is difficult to achieve the broadband and efficient harvesting of wind energy using the existing energy collection technology. Herein, a broadband energy conversion device (ECD), consisting of a triboelectric nanogenerator (TENG) and an electromagnetic generator (EMG), is proposed for wind energy collection under different wind speeds. The introduction of an optimized Scotch yoke mechanism greatly improves the utilization of wind energy by the TENG, thus reducing energy dissipation. Moreover, the addition of a deflector into the fan greatly reduces the start-up wind speed and improves the ability of the device to capture breeze energy. By doping multi-walled carbon nanotubes, the output voltage and current of the TENG can be improved by 108.89% and 116.61%, respectively. Furthermore, the adopted all-directional conductive foam can greatly prolong the service life of the ECD. The peak power of the ECD is 68.49 mW at 9.6 m/s, with the EMG and TENG producing approximately 64.80 mW and 3.69 mW, respectively. The proposed ECD provides a new technical strategy for the practical application of wind energy harvesters.
Early-Stage Lung Tumor Detection Based on Super-Wideband Microwave Reflectometry
Authors: Alamro Wasan , Seet Boon-Chong , Wang Lulu , Parthiban Prabakar
Published: December 2022

This paper aims to detect early-stage lung tumors in deep-seated and superficial locations, and to precisely measure the size of the detected tumor using non-invasive microwave reflectometry over a super-wideband (SWB) frequency range. Human lung phantom and lung tumors are modeled using a multi-layer concentric cylinder structure and spherical-shaped inclusions, respectively. Firstly, a study on the dielectric properties of human torso tissues is carried out over an SWB frequency range of 1–25 GHz based on the Cole–Cole dispersion model. Intensive full-wave simulations of the modeled phantom under irradiation by a custom-designed SWB antenna array are then performed. Results show that small tumor sizes from 5 mm radius in both deep-seated and superficial locations of the lung tissue can be detected based on the contrast of reflection coefficients and reconstructed images produced from backscattered signals between normal and anomalous tissues. The potential of using SWB microwave reflectometry to successfully detect the lung tumors in their early stages and at different depths of the lung tissue has been demonstrated.
Analysis of Scale Sensitivity of Ship Detection in an Anchor-Free Deep Learning Framework
Authors: Jiang Yongxin , Huang Li , Zhang Zhiyou , Nie Bu , Zhang Fan
Published: December 2022

Ship detection is an important task in sea surveillance. In the past decade, deep learning-based methods have been proposed for ship detection from images and videos. Convolutional features are observed to be very effective in representing ship objects. However, the scales of convolution often lead to different capacities of feature representation. It is unclear how the scale influences the performance of deep learning methods in ship detection. To this end, this paper studies the scale sensitivity of ship detection in an anchor-free deep learning framework. Specifically, we employ the classical CenterNet as the base and analyze the influence of the size, the depth, and the fusion strategy of convolution features on multi-scale ship target detection. Experiments show that, for small targets, the features obtained from the top-down path fusion can improve the detection performance more significantly than that from the bottom-up path fusion; on the contrary, the bottom-up path fusion achieves better detection performance on larger targets.
6G IoT Tracking- and Machine Learning-Enhanced Blockchained Supply Chain Management
Authors: Liang Wei , Zhang Lei , Kadoch Michel
Published: December 2022

The 6G Internet of Things (IoT) is of utmost importance when it comes to running and controlling contemporary supply chains. Blockchain and machine learning (ML) are two upper-layer technologies that can assist with securing and automating the IoT. First, we propose integrating blockchain technology into modern supply chains to facilitate effective communication among all partners. Second, for inbound logistics task prediction, we develop Multi-Head Attention (MHA)-Based Gated Recurrent Unit (GRU). Finally, numerical findings demonstrate that the MHA-Based GRU model has satisfying fitting efficiency and prediction precision compared to its competitors.
Business Email Compromise Phishing Detection Based on Machine Learning: A Systematic Literature Review
Authors: Atlam Hany F. , Oluwatimilehin Olayonu
Published: December 2022

The risk of cyberattacks against businesses has risen considerably, with Business Email Compromise (BEC) schemes taking the lead as one of the most common phishing attack methods. The daily evolution of this assault mechanism’s attack methods has shown a very high level of proficiency against organisations. Since the majority of BEC emails lack a payloader, they have become challenging for organisations to identify or detect using typical spam filtering and static feature extraction techniques. Hence, an efficient and effective BEC phishing detection approach is required to provide an effective solution to various organisations to protect against such attacks. This paper provides a systematic review and examination of the state of the art of BEC phishing detection techniques to provide a detailed understanding of the topic to allow researchers to identify the main principles of BEC phishing detection, the common Machine Learning (ML) algorithms used, the features used to detect BEC phishing, and the common datasets used. Based on the selected search strategy, 38 articles (of 950 articles) were chosen for closer examination. Out of these articles, the contributions of the selected articles were discussed and summarised to highlight their contributions as well as their limitations. In addition, the features of BEC phishing used for detection were provided, as well as the ML algorithms and datasets that were used in BEC phishing detection models were discussed. In the end, open issues and future research directions of BEC phishing detection based on ML were discussed.
Linear Voltage Stability Indicator (LVSI) for Optimal Placement of SVC Devices to Improve the Voltage Stability Margin in Transmission Systems
Authors: Garrido Christian , Aguila Téllez Alexander , Ortiz Leony
Published: December 2022

This study presents a procedure for placing static var compensators (SVC) in an EPS using the fuzzy c-means clustering technique. For this purpose, the optimal power flow (OPF) is initially quantified to obtain the sensitivity array of the system based on the Jacobian of the system. Then, the attenuation and electrical distance matrices are estimated. Subsequently, the fuzzy c-means clustering algorithm is used with the initially estimated cluster identification criterion to obtain the voltage control areas (VCAs). On the other hand, the criterion of minimizing the installation costs of the SVCs is used in conjunction with the linear voltage stability index (LVSI) for the ideal arrangement of the compensators. This is applied to each VCA created. The technique described is applied to the 14-node and 30-node schemes to check their effectiveness. Additionally, the results obtained are compared with the Power Factory software and with similar studies. Finally, the proposed technique proves to be effective for the creation of VCAs and for the optimal placement of SVC equipment.
Graphene and Two-Dimensional Materials-Based Flexible Electronics for Wearable Biomedical Sensors
Authors: Joe Daniel J. , Park Eunpyo , Kim Dong Hyun , Doh Il , Song Hyun-Cheol , Kwak Joon Young
Published: December 2022

The use of graphene and two-dimensional materials for industrial, scientific, and medical applications has recently received an enormous amount of attention due to their exceptional physicochemical properties. There have been numerous efforts to incorporate these two-dimensional materials into advanced flexible electronics, especially aimed for wearable biomedical applications. Here, recent advances in two-dimensional materials-based flexible electronic sensors for wearable biomedical applications with regard to both materials and devices are presented.
Human Activity Recognition Based on an Efficient Neural Architecture Search Framework Using Evolutionary Multi-Objective Surrogate-Assisted Algorithms
Authors: Wang Xiaojuan , He Mingshu , Yang Liu , Wang Hui , Zhong Yun
Published: December 2022

Human activity recognition (HAR) is a popular and challenging research topic driven by various applications. Deep learning methods have been used to improve HAR models’ accuracy and efficiency. However, this kind of method has a lot of manually adjusted parameters, which cost researchers a lot of time to train and test. So, it is challenging to design a suitable model. In this paper, we propose HARNAS, an efficient approach for automatic architecture search for HAR. Inspired by the popular multi-objective evolutionary algorithm, which has a strong capability in solving problems with multiple conflicting objectives, we set weighted f1-score, flops, and the number of parameters as objects. Furthermore, we use a surrogate model to select models with a high score from the large candidate set. Moreover, the chosen models are added to the training set of the surrogate model, which makes the surrogate model update along the search process. Our method avoids manually designing the network structure, and the experiment results demonstrate that it can reduce 40% training costs on both time and computing resources on the OPPORTUNITY dataset and 75% on the UniMiB-SHAR dataset. Additionally, we also prove the portability of the trained surrogate model and HAR model by transferring them from the training dataset to a new dataset.
Electricity Trading in Energy Market Integration: A Theoretical Review
Authors: Rubanda Muhumuza Ezra , Senyonga Livingstone , Ngoma Mohammed , Adaramola Muyiwa S.
Published: December 2022

This paper surveys theory and practice on how a larger and integrated energy market can propel electricity trading through economies of scale. We make a systematic presentation of theories and methods used by various scholars to generate knowledge on integrated electricity markets. We discuss paradigms, concepts, and practices emanating from the complex topic of a unified electricity market with an intent to identify gaps. We conclude that electricity trading in EMI has a propensity to drive both economic integration and sustainable energy access; that crafting ways and means for integrating cross-border systems without sacrificing the local economy could make the idea of EMI more palatable to partner countries; and that adoption of ex ante studies that are non-data oriented could improve the design of upcoming regional electricity markets.
A Novel Generic Diagnosis Algorithm in the Time Domain Representation
Authors: Dijoux Etienne , Damour Cédric , Benne Michel , Aubier Alexandre
Published: December 2022

The health monitoring of a system remains a major issue for its lifetime preservation. In this paper, a novel fault diagnosis algorithm is proposed. The proposed diagnosis approach is based on a unique variable measurement in the time domain and manages to extract the system behavior evolution. The developed tool aims to be generic to several physical systems with low or high dynamic behavior. The algorithm is depicted in the present paper and two different applications are considered. The performance of the novel proposed approach is experimentally evaluated on a fan considering two different faulty conditions and on a proton exchange membrane fuel cell. The experimental results demonstrated the high efficiency of the proposed diagnosis tool. Indeed, the algorithm can discriminate the two faulty operation modes of the fan from a normal condition and also manages to identify the current system state of health. Regarding the fuel cell state of health, only two conditions are tested and the algorithm is able to detect the fault occurrence from a normal operating mode. Moreover, the very low computational cost of the proposed diagnosis tool makes it especially suitable to be implemented on a microcontroller.
Metal–Organic Frameworks and Gas Hydrate Synergy: A Pandora’s Box of Unanswered Questions and Revelations
Authors: Pandey Jyoti , von Solms Nicolas
Published: December 2022

Recent research on the role of nanomaterials in gas hydrate science and a few review papers have highlighted the positive synergies between gas hydrates and metal–organic frameworks (MOFs) for gas separation and storage. Metal–organic frameworks consist of metal nodes and organic linkers connected by coordination bonds to form programmable modular structures that are symmetric and have tunable properties. Metal–organic frameworks, also known as microporous or nanoporous materials, provide a large pore volume and surface area suitable for capturing, separating and storing gases through physisorption mechanisms. However, water and water interactions within the nanopores, open metal sites, coordination bonds and surface make metal–organic framework usage in water-based technologies an exciting research topic. Water-based gas hydrate technology could be potential technology that can take advantage of MOF tunable properties, such as a large surface area and a high pore volume, to improve its efficiency and formation mechanism. For the authors of this review, the synergy of MOFs and gas hydrates resembles a Pandora’s box of unanswered questions and revelations. Therefore, this review examines the current state of the art, including present research on gas storage and separation using gas hydrates in the presence of a MOF. In addition, critical technical aspects, such as the water stability of MOFs, the nano confinement effect and water properties in the nanopores, are presented to stimulate critical thinking among scientists in hydrate research to fully exploit the synergies between MOFs and hydrates. This review ends with the authors’ opinion on potential research areas, unanswered questions and practical implications and prospects.
A Review of Uncertainty Modelling Techniques for Probabilistic Stability Analysis of Renewable-Rich Power Systems
Authors: Hakami Ali M. , Hasan Kazi N. , Alzubaidi Mohammed , Datta Manoj
Published: December 2022

In pursuit of identifying the most accurate and efficient uncertainty modelling (UM) techniques, this paper provides an extensive review and classification of the available UM techniques for probabilistic power system stability analysis. The increased penetration of system uncertainties related to renewable energy sources, new types of loads and their fluctuations, and deregulation of the electricity markets necessitates probabilistic power system analysis. The abovementioned factors significantly affect the power system stability, which requires computationally intensive simulation, including frequency, voltage, transient, and small disturbance stability. Altogether 40 UM techniques are collated with their characteristics, advantages, disadvantages, and application areas, particularly highlighting their accuracy and efficiency (as both are crucial for power system stability applications). This review recommends the most accurate and efficient UM techniques that could be used for probabilistic stability analysis of renewable-rich power systems.
Comparison of the Carbon Payback Period (CPP) of Different Variants of Insulation Materials and Existing External Walls in Selected European Countries
Authors: Sadowski Kajetan
Published: December 2022

The EU “Fit for 55” legislative package provides for the introduction of regulations enabling the achievement of the emission reduction target by 55%. As part of the necessary actions, it is necessary to increase the energy efficiency of existing buildings. To achieve this, there are plans to increase the pace of the modernization of buildings, from 1% to 3% of buildings annually by 2030. However, this must be done with respect to the principles of sustainable development, circular economy and the conservation of buildings. This article presents a comprehensive comparison and calculation of carbon payback period (CPP) for selected insulation materials, combined with selected typical building partitions, and shows how quickly the payback period of greenhouse gases in the production of insulation materials is completed. Individual insulation materials (stone and glass wool, expanded polystyrene (EPS), extruded polystyrene (XPS), polyurethane (PUR) and cellulose) were analyzed in relation to different types of walls (seven types—including solid wall, diaphragm wall, large panel system (LPS), and concrete), in different locations (Poland, Germany, Czech Republic, Austria, Finland, Europe) and for various energy sources (electricity, gas, oil, biomass, district heating). After taking into account the carbon footprint embodied in the insulation materials, along with the potential reductions in the operational greenhouse gases emissions, the carbon payback period (CPP) was determined, resulting from the use of a given technology, insulation material and location. By comparing the CPPs for different insulations, this paper shows that the results vary significantly between EU countries, which have different embodied carbon factors for energy sources and materials, and that there is still a serious lack in the availability of reliable environmental information, which can limit research results.
Energy Efficiency Policies in Poland and Slovakia in the Context of Individual Well-Being
Authors: Barwińska Małajowicz Anna , Knapková Miroslava , Szczotka Krzysztof , Martinkovičová Miriam , Pyrek Radosław
Published: December 2022

Improving energy efficiency includes a number of measures implemented as part of the greening of the energy industry, which in turn is a prerequisite for the creation of a sustainable energy industry to ensure energy and environmental security for the world. Despite the adoption of the EU directives on energy efficiency, there is still insufficient public awareness in this area in Poland and Slovakia. This is particularly surprising because improving energy efficiency not only brings national and global benefits, but also has a significant impact on the well-being of individuals and households. The main purpose of the paper is to analyze the national policies of Poland and Slovakia, which are based on the European Directive 2012/27/EU on energy efficiency, and which introduce new measures aimed not only at increasing energy efficiency, but also at increasing the well-being of households and individuals. Methods of desk research and content analysis were used. The current situation in both countries is illustrated by case studies that document the administrative process (Slovakia) and the calculation of energy savings (Poland) when using renewable energy sources in the case of family houses.
Deep Reductions in Energy Use: Hobson’s Choice in Climate’s Last-Chance Saloon
Authors: Honnery Damon , Moriarty Patrick
Published: December 2022

In 2022, the record of extreme weather events already includes deep droughts in Sichuan province, China, and California, US; floods inundating a third of Pakistan and serious and repeated flooding in Eastern Australia; heat waves and drought in Europe; and wildfires in Europe and the western US [...]
Joint SOH-SOC Estimation Model for Lithium-Ion Batteries Based on GWO-BP Neural Network
Authors: Zhang Xin , Hou Jiawei , Wang Zekun , Jiang Yueqiu
Published: December 2022

The traditional ampere-hour (Ah) integration method ignores the influence of battery health (SOH) and considers that the battery capacity will not change over time. To solve the above problem, we proposed a joint SOH-SOC estimation model based on the GWO-BP neural network to optimize the Ah integration method. The method completed SOH estimation through the GWO-BP neural network and introduced SOH into the Ah integration method to correct battery capacity and improve the accuracy of state of charge (SOC) estimation. In addition, the method also predicted the SOH of the battery, so the driver could have a clearer understanding of the battery aging level. In this paper, the stability of the joint SOH-SOC estimation model was verified by using different battery data from different sources. Comparative experimental results showed that the estimation error of the joint SOH-SOC estimation model could be stabilized within 5%, which was smaller compared with the traditional ampere integration method.