bluuebunny/crossref_metadata_2025 huggingface dataset:
Robust Superhydrophilic/Underwater Superoleophobic Surface with Anti-Abrasion and Anti-Corrosion Performances Based on Laser Ablation
Authors: Fang Duoxun , Al-akhali Adham , Cao Molin , Liu Jiahao , Tang Zhengqiang
Published: June 2023

Preparing underwater superoleophobic surface is an effective method to solve the problems of oil adhesion on the underwater surfaces and oil spill in water. However, the underwater superoleophobic surfaces at present are not reliable in practical application due to their poor stability under corrosion and abrasion. Herein, we proposed a facile method to fabricate a robust superhydrophilic/underwater superoleophobic surface. The surface is combined with micro honeycomb frame structure and nanostructure, which was fabricated by laser ablation. The surface with the honeycomb pattern shows strong hydrophilicity with a water contact angle of 0° and stable underwater oil repellency with an underwater oil contact angle of 164.9°. Furthermore, it can maintain its excellent underwater superoleophobic performance after 120 cycles of abrasion and corrosion of 6 h at pH = 1–14.
Corrosion Performance of Ti6Al7Nb Alloy in Simulated Body Fluid for Implant Application Characterized Using Macro- and Microelectrochemical Techniques
Authors: Abreu-García Andrea , Souto Ricardo M. , Izquierdo Javier
Published: June 2023

In this paper, the applicability of Ti6Al7Nb as a more biocompatible alternative for bone and dental implants than Ti6Al4V and pure titanium in terms of corrosion resistance and electrochemical inertness is investigated. The chemical inertness and corrosion resistance of the Ti6Al7Nb biomaterial were characterized by a multi-scale electrochemical approach during immersion in simulated physiological environments at 37 °C comparing its behavior to that of c.p. Ti, Ti6Al4V, and stainless steel. The establishment of a passive regime for Ti6Al7Nb results from the formation of a thin layer of metal oxide on the surface of the material which prevents the action of aggressive species in the physiological medium from direct reaction with the bulk of the alloy. Conventional electrochemical methods such as potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) provide quantified information on the surface film resistance and its stability domain that encompasses the potential range experienced in the human body; unfortunately, these methods only provide an average estimate of the exposed surface because they lack spatial resolution. Although local physiological environments of the human body are usually simulated using different artificial physiological solutions, and changes in the electrochemical response of a metallic material are observed in each case, similar corrosion resistances have been obtained for Ti6Al7Nb in Hank’s and Ringer’s solutions after one week of immersion (with a corrosion resistance of the order of MΩ cm2). Additionally, scanning electrochemical microscopy (SECM) provides in situ chemical images of reactive metal and passive dielectric surfaces to assess localized corrosion phenomena. In this way, it was observed that Ti6Al7Nb exhibits a high corrosion resistance consistent with a fairly stable passive regime that prevents the electron transfer reactions necessary to sustain the metal dissolution of the bulk biomaterial. Our results support the proposition of this alloy as an efficient alternative to Ti6Al4V for biomaterial applications.
Enhancement of Photoelectric Performance Based on Ultrathin Wide Spectrum Solar Absorption in Cruciform Microstructure Germanium Solar Cells
Authors: Zhou Ziyou , Liu Wenfeng , Huang Hailong , Ding Xiaolong , Li Xintian
Published: June 2023

In this paper, the solar absorption level of PEDOT:PSS/Ge organic and inorganic hybrid solar cells (HSCs) with different parameters of cruciform microstructure (CM) is studied, using the finite-difference time domain (FDTD) method. The light absorption in HSCs with CM is above 90% in the range of 300 nm to 1300 nm. Under the AM1.5 solar spectrum, the average absorptivity of solar energy is also at a very high level. At the same time, we use DEVICE software to calculate the electrical properties, such as the open-circuit voltage (Voc), short-circuit current density (Jsc), and maximum power density (Pmax). The electrical simulation results show that the Pmax of HSCs with CM improves to 72.16% from the planar HSCs. Besides, in order to study the mechanism of solar energy absorption in HSCs containing CM, the logarithmic plots of electric field intensity of HSCs with CM and planar HSCs, are analyzed at different wavelengths. The work shows that the CM shows an excellent light-trapping effect, which reduces the surface reflectivity of HSCs, and greatly improves the photoelectric conversion efficiency of Ge solar cells.
An Analysis of Neighbor Discovery Protocol Attacks
Authors: Najjar Firas , Bsoul Qusay , Al-Refai Hasan
Published: June 2023

Neighbor Discovery Protocol (NDP) is a network protocol used in IPv6 networks to manage communication between neighboring devices. NDP is responsible for mapping IPv6 addresses to MAC addresses and discovering the availability of neighboring devices on the network. The main risk of deploying NDP on public networks is the potential for hackers or attackers to launch various types of attacks, such as address spoofing attacks, denial-of-service attacks, and man-in-the-middle attacks. Although Secure Neighbor Discovery (SEND) is implemented to secure NDP, its complexity and cost hinder its widespread deployment. This research emphasizes the potential hazard of deploying IPv6 networks in public spaces, such as airports, without protecting NDP messages. These risks have the potential to crash the entire local network. To demonstrate these risks, the GNS3 testbed environment is used to generate NDP attacks and capture the resulting packets using Wireshark for analysis. The analysis results reveal that with just a few commands, attackers can execute various NDP attacks. This highlights the need to protect against the potential issues that come with deploying IPv6 on widely accessible public networks. In addition, the analysis result shows that NDP attacks have behavior that can be used to define various NDP attacks.
Study on Growth Interface of Large Nd:YAG Crystals
Authors: Quan Jiliang , Ke Guanzhen , Zhang Yali , Liu Jian , Huang Jinqiang
Published: June 2023

A study was performed on the growth interface of a large-diameter 1 at% neodymium-doped yttrium aluminum garnet (Nd:YAG) single crystal grown using the Czochralski method. Red parallel light and an orthogonal polarizing system were used to observe the distribution of the central and lateral cores of the crystal at different growth interfaces. The solid–liquid interface of large-diameter Nd:YAG crystal growth was mainly determined via the interaction between natural and forced convection. The shape of the solid–liquid interface was mainly controlled via maintaining the crystal rotation rate and the temperature field. Interface inversion generally occurred during the shoulder-expanding stage and late stages of the growth of the cylindrical portion of the crystal. The occurrence of interface inversion is directly related to the temperature field, process parameters, and diameter of the crystal. The growth shape of the crystal interface determined the size and distribution of the central and lateral cores of the crystal. The area of the central and lateral cores was reduced via adjusting the temperature gradient of the solid–liquid interface and crystal rotation speed.
Integrated Analysis of the RASH Study with the Use of the “Burden of Therapy” (BOTh®TM) Methodology—A Novel Tool for Assessing Adverse Events in Metastatic Pancreatic Cancer
Authors: Dorman Klara , Boeck Stefan , Snijder Robert J. , Siveke Jens T. , Schenk Michael , Mayerle Julia , Caca Karel , Freiberg-Richter Jens , Fischer von Weikersthal Ludwig , Kullmann Frank , Reinacher-Schick Anke , Fuchs Martin , Kanzler Stephan , Kunzmann Volker , Ettrich Thomas J. , Zhang Danmei , Held Swantje , Abdul-Ahad Ayad , von Bergwelt-Baildon Michael , Heinemann Volker , Haas Michael
Published: June 2023

This analysis of the RASH trial (NCT01729481) aimed at gaining a better understanding of the “Burden of Therapy” (BOTh®TM) in pancreatic ductal adenocarcinoma (PDAC). In the RASH study, 150 patients with newly diagnosed metastatic PDAC were treated with gemcitabine plus erlotinib (gem/erlotinib) for four weeks. Patients who developed a skin rash during this four-week run-in phase continued with the gem/erlotinib treatment, while rash-negative patients were switched to FOLFIRINOX. The study demonstrated a 1-year survival rate of rash-positive patients who received gem/erlotinib as first-line treatment that was comparable to previous reports of patients receiving FOLFIRINOX. To understand whether these comparable survival rates may be accompanied by better tolerability of the gem/erlotinib treatment compared to FOLFIRINOX, the BOTh®TM methodology was used to continuously quantify and depict the burden of therapy generated by treatment emergent events (TEAEs). Sensory neuropathy was significantly more common in the FOLFIRINOX arm, and prevalence as well as severity increased over time. In both arms, the BOTh®TM associated with diarrhea decreased over the course of treatment. The BOTh®TM caused by neutropenia was comparable in both arms but decreased in the FOLFIRINOX arm over time, possibly due to chemotherapy dose reductions. Overall, gem/erlotinib was associated with a slightly higher overall BOTh®TM, but the difference was not statistically significant (p = 0.6735). In summary, the BOTh®TM analysis facilitates the evaluation of TEAEs. In patients fit for intense chemotherapeutic regimens, FOLFIRINOX is associated with a lower BOTh®TM than gem/erlotinib.
The Stigma Surrounding Opioid Use as a Barrier to Cancer-Pain Management: An Overview of Experiences with Fear, Shame, and Poorly Controlled Pain in the Context of Advanced Cancer
Authors: Harsanyi Hannah , Cuthbert Colleen , Schulte Fiona
Published: June 2023

Cancer-related pain affects a majority of patients with advanced cancer and is often undertreated. The treatment of this pain is largely reliant on the use of opioids, which are essential medicines for symptom management and the maintenance of quality of life (QoL) for patients with advanced cancer. While there are cancer-specific guidelines for the treatment of pain, widespread publication and policy changes in response to the opioid epidemic have drastically impacted perceptions of opioid use. This overview therefore aims to investigate how manifestations of opioid stigma impact pain management in cancer settings, with an emphasis on the experiences of patients with advanced cancer. Opioid use has been widely stigmatized in multiple domains, including public, healthcare, and patient populations. Physician hesitancy in prescribing and pharmacist vigilance in dispensing were identified as barriers to optimal pain management, and may contribute to stigma in the context of advanced cancer. Evidence in the literature suggests that opioid stigma may result in patient deviations from prescription instructions, which generally leads to pain undertreatment. Patients reflected on experiencing shame and fear surrounding their prescription opioid use and feeling uncomfortable communicating with their healthcare providers on these topics. Our findings indicate that future work is required to educate patients and providers in order to de-stigmatize opioid use. Through alleviating stigma, patients may be better able to make decisions regarding their pain management which lead to freedom from cancer-related pain and improved QoL.
Lymph Node Staging in Perihilar Cholangiocarcinoma: The Key to the Big Picture
Authors: Rogacka Nina A. , Benkö Tamas , Saner Fuat H. , Malamutmann Eugen , Kaths Moritz , Treckmann Juergen W. , Hoyer Dieter Paul
Published: June 2023

Klatskin tumors have a bad prognosis despite aggressive therapy. The role and extent of lymph node dissection during surgery is a matter of discussion. This retrospective study analyzes our current experience of surgical treatments in the last decade. Patients and Methods: A retrospective single-center analysis of patients (n = 317) who underwent surgical treatment for Klatskin tumors. Univariable and multivariable logistic regression and Cox proportional analysis were performed. The primary endpoint was to investigate the role of lymph node metastasis for patient survival after complete tumor resection. The secondary endpoint was the prediction of lymph node status and long-term survival from preoperatively available parameters. Results: In patients with negative resection margins, a negative lymph node status was the prognosis-determining factor with a 1-, 3-, and 5-year survival rate of 87.7%, 37%, and 26.4% compared with 69.5%, 13.9%, and 9.3% for lymph-node-positive patients, respectively. Multivariable logistic regression for complete resection and negative lymph node status demonstrated only Bismuth type 4 (p = 0.01) and tumor grading (p = 0.002) as independent predictors. In multivariate Cox regression analysis, independent predictors of survival after surgery were the preoperative bilirubin level (p = 0.03), intraoperative transfusion (p = 0.002), and tumor grading (G) (p = 0.001). Conclusion: Lymph node dissection is of utmost importance for adequate staging in patients undergoing surgery for perihilar cholangiocarcinoma. In spite of extensive surgery, long-term survival is clearly associated with the aggressiveness of the disease.
Spatial Patterns of Neutral and Functional Genetic Variations along Dendritic Networks of Riverscape in Brown Trout Populations
Authors: Gouthier Laurine , Duval Eloïse , Blanchet Simon , Loot Géraldine , Veyssière Charlotte , Galan Maxime , Quéméré Erwan , Jacquin Lisa
Published: June 2023

Understanding how environmental gradients shape the spatial patterns of intraspecific genetic diversity is a central issue in ecological and evolutionary sciences. In riverine ecosystems, there is generally an increase in neutral genetic diversity downstream, as well as an increase in genetic differentiation among upstream populations. However, selective pressures may vary markedly along the upstream–downstream gradient, which could modify these patterns, but this has rarely been tested empirically. Here, we investigated how environmental gradients in a river network could shape the spatial patterns of intraspecific genetic diversity and differentiation in both neutral SNP markers and functional genetic markers putatively under natural selection (candidate SNPs associated with physiological functions and immune Major Histocompatibility Complex (MHC) loci) in wild brown trout populations. First, we showed that both the distance from the confluence and the centrality on the river network could explain the variation in genetic diversity and differentiation. Second, we found that both neutral and functional markers followed a similar pattern, with a higher genetic diversity and a lower genetic differentiation among populations that were more central and/or near to the confluence. This study highlights the importance of considering both the spatial and hydrological factors of a river network to understand and predict the role of dendritic connectivity in the spatial patterns of genetic diversity and differentiation in wild fish populations.
Nutrient Supplementation to Arboreal Ants: Effects on Trophic Position, Thermal Tolerance, Community Structure and the Interaction with the Host-Tree
Authors: Zuanon Lino A. , Leão Ruthe E. O. S. , Quero Adilson , Neves Karen C. , Vasconcelos Heraldo L.
Published: June 2023

Carbohydrates and proteins are essential to maintain the basic functions of animals. Over the course of one year we conducted a factorial experiment to determine the influence of carbohydrate (sucrose) and protein supplementation on the thermal tolerance, trophic position, overall abundance, species richness and composition, and on the strength of the protective effects of arboreal ants on their host tree (Caryocar brasiliense). Using Azteca ants as a model we found evidence of dietary and thermal plasticity among arboreal ants as colonies supplied with protein increased their trophic level relative to colonies that received no protein. Colonies that received sucrose increased their thermal tolerance on average by 1.5 °C over a six-month period, whereas those that did not receive sucrose did not change their thermal tolerance. Overall ant abundance was lower in control trees than in those that received any nutrient addition treatment. Species richness was also lower in control trees, but those receiving sucrose presented more species than those receiving only protein. There was greater similarity in species composition between the trees that received sucrose than between these and those receiving only protein or just water as control. Trees whose ant colonies received sucrose presented lower levels of leaf damage than those that did not. Overall, these results indicate that food resources can modulate the population and community ecology of arboreal ants as well as their interaction with the host trees. Interestingly, although arboreal ants are thought to be N-limited, it was the supplementation of sucrose—not protein—that elicited most of the responses.
Design and Development of a Non-Contact ECG-Based Human Emotion Recognition System Using SVM and RF Classifiers
Authors: Alam Aftab , Urooj Shabana , Ansari Abdul Quaiyum
Published: June 2023

Emotion recognition becomes an important aspect in the development of human-machine interaction (HMI) systems. Positive emotions impact our lives positively, whereas negative emotions may cause a reduction in productivity. Emotionally intelligent systems such as chatbots and artificially intelligent assistant modules help make our daily life routines effortless. Moreover, a system which is capable of assessing the human emotional state would be very helpful to assess the mental state of a person. Hence, preventive care could be offered before it becomes a mental illness or slides into a state of depression. Researchers have always been curious to find out if a machine could assess human emotions precisely. In this work, a unimodal emotion classifier system in which one of the physiological signals, an electrocardiogram (ECG) signal, has been used is proposed to classify human emotions. The ECG signal was acquired using a capacitive sensor-based non-contact ECG belt system. The machine-learning-based classifiers developed in this work are SVM and random forest with 10-fold cross-validation on three different sets of ECG data acquired for 45 subjects (15 subjects in each age group). The minimum classification accuracies achieved with SVM and RF emotion classifier models are 86.6% and 98.2%, respectively.
Developing an Artificial Intelligence-Based Representation of a Virtual Patient Model for Real-Time Diagnosis of Acute Respiratory Distress Syndrome
Authors: Barakat Chadi S. , Sharafutdinov Konstantin , Busch Josefine , Saffaran Sina , Bates Declan G. , Hardman Jonathan G. , Schuppert Andreas , Brynjólfsson Sigurður , Fritsch Sebastian , Riedel Morris
Published: June 2023

Acute Respiratory Distress Syndrome (ARDS) is a condition that endangers the lives of many Intensive Care Unit patients through gradual reduction of lung function. Due to its heterogeneity, this condition has been difficult to diagnose and treat, although it has been the subject of continuous research, leading to the development of several tools for modeling disease progression on the one hand, and guidelines for diagnosis on the other, mainly the “Berlin Definition”. This paper describes the development of a deep learning-based surrogate model of one such tool for modeling ARDS onset in a virtual patient: the Nottingham Physiology Simulator. The model-development process takes advantage of current machine learning and data-analysis techniques, as well as efficient hyperparameter-tuning methods, within a high-performance computing-enabled data science platform. The lightweight models developed through this process present comparable accuracy to the original simulator (per-parameter R2 > 0.90). The experimental process described herein serves as a proof of concept for the rapid development and dissemination of specialised diagnosis support systems based on pre-existing generalised mechanistic models, making use of supercomputing infrastructure for the development and testing processes and supported by open-source software for streamlined implementation in clinical routines.
Paget’s Disease of the Bone and Lynch Syndrome: An Exceptional Finding
Authors: Gheorghe Ana-Maria , Stanescu Laura-Semonia , Petrova Eugenia , Carsote Mara , Nistor Claudiu , Ghemigian Adina
Published: June 2023

Our objective is to present an exceptional case of a patient diagnosed with Paget’s disease of the bone (PDB) while being confirmed with Lynch syndrome (LS). A 44-year-old woman was admitted for progressive pain in the left forearm 2 years ago, and was partially relieved since admission by non-steroidal anti-inflammatory drugs. Suggestive imaging findings and increased blood bone turnover markers helped the diagnosis of PDB. She was offered zoledronate 5 mg. She had two more episodes of relapse, and a decision of new medication was taken within the following years (a second dose of zoledronate, as well as denosumab 60 mg). Her family history showed PDB (mother) and colorectal cancer (father). Whole exome sequencing was performed according to the manufacturer’s standard procedure (Ion AmpliSeq™ Exome RDY S5 Kit). A heterozygous pathogenic variant in the SQSTM1 gene (c.1175C>T, p.Pro392Leu) was confirmed, consistent with the diagnosis of PDB. Additionally, a heterozygous pathogenic variant of MSH2 gene (c.2634+1G>T) was associated with LS. The patient’s first-degree relatives (her brother, one of her two sisters, and her only daughter) underwent specific genetic screening and found negative results, except for her daughter, who tested positive for both pathogenic variants while being clinically asymptomatic. The phenotype influence of either mutation is still an open issue. To our current knowledge, no similar case has been published before. Both genetic defects that led to the two conditions appeared highly transmissible in the patient’s family. The patient might have an increased risk of osteosarcoma and chondrosarcoma, both due to PDB and LS, and a review of the literature was introduced in this particular matter. The phenotypic expression of the daughter remains uncertain and is yet to be a lifelong follow-up as the second patient harbouring this unique combination of gene anomalies.
A Prospective Analysis of the Retinopathy of Prematurity Correlated with the Inflammatory Status of the Extremely Premature and Very Premature Neonates
Authors: Borțea Claudia Ioana , Enatescu Ileana , Dima Mirabela , Pantea Manuela , Iacob Emil Radu , Dumitru Catalin , Popescu Alin , Stoica Florina , Heredea Rodica Elena , Iacob Daniela
Published: June 2023

Retinopathy of Prematurity (ROP) is a major cause of blindness in premature infants. This study aimed to evaluate the association between inflammatory markers and ROP development in extremely premature and very premature neonates and identify potential inflammatory biomarkers for ROP risk prediction. This prospective study was conducted from January 2021 to January 2023 in two clinical hospitals associated with the “Victor Babes” University of Medicine and Pharmacy Timisoara. The study population comprised neonates with a gestational age of less than 32 weeks. Various inflammatory markers, including total white blood cell count, polymorphonuclear leukocytes, C-reactive protein, interleukin-6, and lactate dehydrogenase, were analyzed from blood samples collected at birth and three days postnatally. ROP was diagnosed and classified following the International Classification of Retinopathy of Prematurity. The study included 48 neonates, 12 Extremely Premature Infants (EPI), and 36 Very Premature Infants (VPI). The EPI group had significantly higher mean interleukin-6 and lactate dehydrogenase levels at birth and three days postnatally than the VPI group. C-reactive protein levels at three days were significantly higher in the VPI group. Umbilical cord inflammation and ROP severity were found to have a statistically significant positive correlation. Half of the EPIs had moderate to severe ROP, significantly more than in the VPI group. The duration of oxygen supplementation, mechanical ventilation, Continuous Positive Airway Pressure (CPAP), gestational age less than 28 weeks, and umbilical cord inflammation at or above stage 3 were significant risk factors for developing ROP stage 2 or above. Elevated CRP and IL-6 were also significantly associated with an increased risk of developing ROP stage 2 or above, highlighting their potential as biomarkers for ROP risk prediction. This study suggests a significant association between inflammatory markers and ROP development in extremely premature and very premature neonates. These findings could contribute to the identification of potential inflammatory biomarkers for ROP risk prediction, improving early diagnosis and intervention strategies for this condition.
A Novel Hybrid Approach for Classifying Osteosarcoma Using Deep Feature Extraction and Multilayer Perceptron
Authors: Aziz Md. Tarek , Mahmud S. M. Hasan , Elahe Md. Fazla , Jahan Hosney , Rahman Md Habibur , Nandi Dip , Smirani Lassaad K. , Ahmed Kawsar , Bui Francis M. , Moni Mohammad Ali
Published: June 2023

Osteosarcoma is the most common type of bone cancer that tends to occur in teenagers and young adults. Due to crowded context, inter-class similarity, inter-class variation, and noise in H&E-stained (hematoxylin and eosin stain) histology tissue, pathologists frequently face difficulty in osteosarcoma tumor classification. In this paper, we introduced a hybrid framework for improving the efficiency of three types of osteosarcoma tumor (nontumor, necrosis, and viable tumor) classification by merging different types of CNN-based architectures with a multilayer perceptron (MLP) algorithm on the WSI (whole slide images) dataset. We performed various kinds of preprocessing on the WSI images. Then, five pre-trained CNN models were trained with multiple parameter settings to extract insightful features via transfer learning, where convolution combined with pooling was utilized as a feature extractor. For feature selection, a decision tree-based RFE was designed to recursively eliminate less significant features to improve the model generalization performance for accurate prediction. Here, a decision tree was used as an estimator to select the different features. Finally, a modified MLP classifier was employed to classify binary and multiclass types of osteosarcoma under the five-fold CV to assess the robustness of our proposed hybrid model. Moreover, the feature selection criteria were analyzed to select the optimal one based on their execution time and accuracy. The proposed model achieved an accuracy of 95.2% for multiclass classification and 99.4% for binary classification. Experimental findings indicate that our proposed model significantly outperforms existing methods; therefore, this model could be applicable to support doctors in osteosarcoma diagnosis in clinics. In addition, our proposed model is integrated into a web application using the FastAPI web framework to provide a real-time prediction.
Congenital Anterior Dislocation of the Sacrococcygeal Bone in a Newborn
Authors: Fabijan Artur , Polis Bartosz , Zakrzewski Krzysztof , Zawadzka-Fabijan Agnieszka , Korabiewska-Pluta Sara , Nowosławska Emilia
Published: June 2023

We present a case of a child who was transported to the Neurosurgery Clinic from another hospital for the purpose of performing a surgical procedure of the spinal myelomeningocele. On the first day of the stay, a set of tests was performed, including an anterior-posterior (AP) projection X-ray, which clearly showed a developmental defect in the lumbar-sacral section of the spine. In the follow-up physical examination, there was a depression of the skin on the right side of the surgical scar after closing the open myelomeningocele. In the follow-up MRI of the lumbar-sacral section, an extremely rare congenital anterior dislocation of the sacrococcygeal bone was unexpectedly visualized. Despite recommendations for further diagnostics, the patient did not attend the required follow-up examinations. In the final section, we provide a general summary of the literature on rare developmental defects of the spine in children.
Near-to-Far Field RCS Calculation Using Correction Optimization Technique
Authors: Huang Jinhai , Zhou Jianjiang , Deng Yao
Published: June 2023

Radar cross section (RCS) is a scattering measure of an object that scatters to the radar. However, existing methods for near-field (NF) measurement and data processing rarely extract amplitude characteristics, and there is a lack of effective verification of far-field (FF) data in the process of NF to FF transformation, which leads to inaccuracies in FF prediction accuracy. In this paper, we propose a method to establish the relationship between the NF and FF RCS using the state space method (SSM), which is based on accurate estimation of the NF amplitude in NF measurement, and then deriving the FF RCS from the NF scattering signal convolved with a near-to-far kernel. The proposed solution to address the uncertainty issue in reference FF data involves using the geometric theory of diffraction (GTD) scattering center model as the reference FF data and establishing a linear equation with the derived FF model. The negative gradient search (NGS) system identification concept is used to optimize the FF model in order to reduce the discrepancy between the reference and derived values. Finally, the corrected RCS error is provided as additional proof of the effectiveness of these techniques in enhancing near-to-far transformation accuracy by examining the outcomes of three experiments.
Reconfigurable Antennas for RF Energy Harvesting Application: Current Trends, Challenges, and Solutions from Design Perspective
Authors: Behera Bikash Ranjan , Mishra Sanjeev Kumar , Alsharif Mohammed H. , Jahid Abu
Published: June 2023

Due to the widespread use of low-power embedded devices in both industrial and consumer applications, research into the use of alternate energy sources has been sparked by the requirement for continuous power. Due to its accessibility and ability to be implanted, RF energy is always taken into consideration among the traditional energy sources that are currently available. There is a significant necessity for efficient RF front-ends, which must provide effective circular polarization (CP) features, effectiveness, feasibility from a design standpoint, and optimal usage of ambient RF signals accessible in the environment. So, for understanding their utilization in RF energy harvesting, a metasurface reflector-inspired CP-printed reconfigurable antenna integrated with a Greinacher voltage divider (GVD) rectifier circuit is reported. It offers broadband CP with fractional bandwidth > 25%, CP gain > 8.35 dBic, and directional radiation with the 3 dB angular beamwidth > 100° in the 3.5/5 GHz bands. With the integration of the rectifier circuit, a theoretical DC output > 4.8 V at 12 dBm is obtained. The acceptable impedance bandwidth, axial ratio bandwidth, antenna gain, antenna efficiency, and directional radiation with a 3 dB angular beamwidth value are studied and subsequently matched with the trade-offs (usage of diodes, complexity of DC biasing circuits, and attainment of polarization reconfigurability) obtained from the state of the art. A comprehensive study of the reconfigurable antennas is reported to highlight the findings as a widespread solution for these limitations in RF energy harvesting application.
A Transformer-Based Cross-Window Aggregated Attentional Image Inpainting Model
Authors: Chen Mingju , Liu Tingting , Xiong Xingzhong , Duan Zhengxu , Cui Anle
Published: June 2023

To overcome the fault of convolutional networks, which can be over-smooth, blurred, or discontinuous, a novel transformer network with cross-window aggregated attention is proposed. Our network as a whole is constructed as a generative adversarial network model, and by embedding the Window Aggregation Transformer (WAT) module, we improve the information aggregation between windows without increasing the computational complexity and effectively obtain the image long-range dependencies to solve the problem that convolutional operations are limited by local feature extraction. First, the encoder extracts the multi-scale features of the image with convolution kernels of different scales; second, the feature maps of different scales are input into a WAT module to realize the aggregation between feature information and finally, these features are reconstructed by the decoder, and then, the generated image is input into the global discriminator, in which the discrimination between real and fake images is completed. It is experimentally verified that our designed Transformer window attention network is able to make the structured texture of the restored images richer and more natural when performing the restoration task of large broken or structurally complex images.
Overview of Signal Processing Problems in Power Electronic Control Circuits
Authors: Sozański Krzysztof
Published: June 2023

This paper examines various aspects related to digital signal processing in digital control circuits used in power electronics. The discussion focuses on several common issues, including the sampling rate of signals (including phenomena such as aliasing and synchronization), coherent sampling, jitter of sampling pulses, sequential versus simultaneous sampling in multichannel systems, signal resolution (including signal-to-noise ratio, noise-shaping circuits, and changes in sampling speed), interpolation and decimation, and the conversion of analog circuits into digital form. One of the key contributions of this paper is the introduction of a new formula for calculating the resultant signal-to-noise ratio for three-stage digital control circuits. By carefully considering and correcting for sources of error, it is possible to increase the signal-to-noise ratio and minimize distortion components. This, in turn, leads to improved output/input current and voltage parameters, which can have a positive impact on the overall quality of energy processing in power electronic circuits.
Detailed Wideband Impedance Modeling and Resonance Analysis of Grid-Connected Modular Multilevel Converter
Authors: Yan Zheng , Xu Jianyuan , Yu Gaole , Bai Enming , Chen Weidong
Published: June 2023

Modular multilevel converter (MMC) tends to cause resonance instability in interconnected systems. Current studies on the stability of MMC mainly focus on high-voltage and large-capacity power systems, while the impedance modeling process of MMC ignores the harmonics of the submodule (SM) capacitor voltages and the influence of voltage feedforward control. The applicability of the MMC impedance model with fewer submodules is doubtful. According to the circuit structure and control mode, the AC-side sequence impedance model of the MMC is established, which takes into account the capacitor voltage balance control of submodules and voltage feedforward control. Based on the RT-Lab control hardware-in-loop (CHIL) test platform, the MMC impedance frequency scanning was carried out to verify the accuracy of the impedance modeling method. The influence of control parameters in different frequency bands on the impedance characteristics of MMC was studied. The AC terminal voltage feedforward causes phase lag in the mid-/high-frequency range and increases the risk of resonance. In the low-frequency range, the dynamics and control of capacitor voltages reduce the impedance magnitude of MMC. Using the resonance phenomenon of an MMC connected to a weak grid as an example, the high-frequency resonance mechanism caused by control parameters is analyzed from the perspective of the negative damping effect. The simulation results show that the detailed wideband impedance model can improve the accuracy of the stability analysis results.
Two-Stage Dry Reforming Process for Biomass Gasification: Product Characteristics and Energy Analysis
Authors: Gao Yang , Xie Huaqing , Yu Zhenyu , Qin Mengxin , Wu Zhenguo , Wang Panlei , Zhao Xi , Zhang Shiyi
Published: June 2023

The utilization of biomass can not only alleviate the energy crisis but also reduce the pollution of fossil fuels to the environment. Biomass gasification is one of the main utilization methods, which can effectively convert biomass into high-value and wide-use gasification gas. However, this process inevitably produces the by-product tar, which affects the yield of syngas. In order to solve this problem, a two-stage process combining biomass pyrolysis and CO2 catalytic reforming is proposed in this paper, which is used to prepare high calorific value syngas rich in H2 and CO and reduce the by-product tar of biomass gasification while realizing the resource utilization of CO2. The effects of the reforming temperature and CO2/C ratio on the gas yield and calorific value of biomass were investigated by catalytic gasification reforming device, and the system energy consumption was analyzed. With the increase of reforming temperature, the yield of CO increased, and the yield of H2 and the calorific value of gas increased first and then decreased. Increasing the CO2/C ratio within a proper range is beneficial to the formation of syngas. When the reforming temperature is 900 °C and the CO2/C ratio is 1, syngas with a high gas calorific value is obtained, which of is 2.75 MJ/kg is obtained. At this time, the yield of H2 and CO reached the maximums, which were 0.46 Nm3/kg and 0.28 Nm3/kg, respectively. Under these conditions, the total energy consumption of the system is 0.68 MJ/kg, slightly more than 0, and does not require too much external heat.
A Novel Renewable Smart Grid Model to Sustain Solar Power Generation
Authors: Abdul Baseer Mohammad , Alsaduni Ibrahim
Published: June 2023

The stability performance of smart grid power systems is critical and requires special attention. Additionally, the combination of Battery Energy Storage (BES) systems, Solar Photovoltaic (SPV), and wind systems in the intelligent grid model provides utilities with excellent efficiency and dependability. However, a coordination grid with PV and other resources frequently results in severe issues, such as outages or power disruptions. A power outage in the grid might result in a power loss in the delivery system. As a result, the distributed grid model’s dependable performance is intended for integrated wind energy, SPV arrays, and BE systems. This paper proposes a renewable intelligent grid model to sustain solar power generation. The model incorporates a boost converter to optimize the performance of solar panels by converting the DC power generated by the panels into AC power for use in the grid. The boost converter is optimized using a novel Horse Herd Optimization Algorithm (HOA) method. In this case, the HOA method is used to optimize the control parameters of the boost converter, such as the duty cycle and the inductor and capacitor values. According to the final results, the proposed method has reduced the Total Harmonic Deformation (THD) and power loss. Additionally, the proposed method outperformed existing strategies related to the Expected Energy Not Supplied (EENS), Loss of Load Probability (LOLP), and Loss of Load Expected (LOLE), indicating the sustainability of power generation.
Adaptive Control of a Virtual Synchronous Generator with Multiparameter Coordination
Authors: Ren Bixing , Li Qiang , Fan Zhiyuan , Sun Yichao
Published: June 2023

This paper proposes an adaptive strategy of co-regulating the three parameters—P/ω droop coefficient, virtual inertia, and damping coefficient—for the virtual synchronous generator (VSG). This approach is able to solve the uncoordinated performance between the virtual inertia and the damping using the conventional adaptive control in which the system may experience serious frequency fluctuations. Through the mathematical modeling of the VSG grid-connected system, the segmental analysis of the VSG transient process is carried out, and the parameter adjustment law of each stage is obtained. The VSG angular velocity change and the angular velocity instantaneous change rate are associated with the inertia to realize the adaptive adjustment of the inertia, and the adaptive adjustment of the P/ω droop coefficient is carried out in real time according to the VSG angular velocity change. A functional relationship is established between the P/ω droop coefficient, virtual inertia, and damping coefficient so that the P/ω droop coefficient, virtual inertia, and damping coefficient are coordinated to keep the system in the best damping ratio state all the time. Finally, the superiority of the proposed strategy is proved by simulation comparison.
An Exploratory Study on Swedish Stakeholders’ Experiences with Positive Energy Districts
Authors: Mattsson Moa , Olofsson Thomas , Lundberg Liv , Korda Olga , Nair Gireesh
Published: June 2023

Positive energy district (PED) is a novel idea aimed to have an annual surplus of renewable energy and net zero greenhouse gas emissions within an area. However, it is still an ambiguous concept, which might be due to the complexity of city district projects with interconnected infrastructures and numerous stakeholders involved. This study discusses various aspects of PED implementation and presents practitioners’ experiences with the PED concept, challenges, and facilitators they have faced with real projects. The study is based on interviews with ten Swedish professionals. The major challenges reported for PED implementation were local energy production and energy flexibility, sub-optimization, legislation, suitable system boundaries, and involvement of stakeholders. Most of the interviewees mentioned improved collaboration, integrated innovative technology, political support, and climate change mitigation goals as important facilitators. The interviewees highlighted the importance of a local perspective and considered each city’s preconditions when developing a PED project. The study emphasizes that to facilitate PED implementation and replication in cities, more knowledge and clarity is required about PED such as on the definition and system boundaries.
Mitigating Technological Anxiety through the Application of Natural Interaction in Mixed Reality Systems
Authors: Sun Yiming , Nakajima Tatsuo
Published: June 2023

Technology anxiety contributes to an increased cognitive load and reduces user adoption of novel technologies. An illustrative example of this phenomenon is observed in the field of smart homes.To address this issue, we have identified an interaction paradigm known as natural interaction, which enables humans to engage with technology in a way that closely resembles natural human behavior and communication. This approach offers more user-friendly interactions that users are already familiar with, potentially reducing their cognitive load. In this paper, we present a case study of a smart lock system where we implement natural interaction and deploy it on a mixed reality (MR) device. By leveraging advanced features offered by MR head-mounted displays, we recreate the experience of people opening locks in everyday life. We conduct a user study comparing this interaction with traditional WIMP interaction in a mixed-reality environment. Through the analysis of collected data and user feedback, we examine the advantages and limitations of our proposed system.
Discrete Fracture Network (DFN) Analysis to Quantify the Reliability of Borehole-Derived Volumetric Fracture Intensity
Authors: Ojeda Pedro , Elmo Davide , Rogers Steve , Brzovic Andres
Published: June 2023

Volumetric fracture intensity (P32) is a parameter that plays a major role in the mechanical and hydraulic behaviour of rock masses. While methods such as Ground Penetrating Radar (GPR) are available to map the 3D geometrical characteristics of the fractures, the direct measurement of P32 at a resolution compatible with geotechnical applications is not yet possible. As a result, P32 can be estimated from the borehole and surface data using either simulation or analytical solutions. In this paper, we use Discrete Fracture Network (DFN) models to address the problem of estimating P32 using information from boreholes (1D data). When calculating P32 based on Terzaghi Weighting, it is common practice to use drill run lengths and limit the minimum angle between the borehole and the intersected fractures. The analysis presented in this paper indicated that limiting the minimum angle of intersection would result in an underestimation of the calculated P32. Additionally, the size of the interval has a significant impact on the variability of the calculated P32. We propose a methodology to calculate P32 using variable lengths, depending on the angle between the fractures and the borehole. This methodology allows the capture of the spatial variation in intensity and simultaneously avoids artificially increasing or decreasing the intensity sampled along borehole intervals. Additionally, this work has addressed the impact of boundary effects in DFN models and proposes a methodology to mitigate them.
Concentration of Trace Elements in Cryoconites of Mountain and Polar Regions of the World
Authors: Abakumov Evgeny , Tembotov Rustam , Polyakov Vyacheslav , Ivanov Mikhail , Mavlyudov Bulat , Kushnov Ivan , Nizamutdinov Timur , Yaneva Rositsa , Zhiyanski Miglena
Published: June 2023

The surface of mountain glaciers is a place of accumulation of various biogenic organomineral and mineral compounds. As a result of intensive mass deglaciation of glaciers due to climate change and anthropogenic activity, this material can significantly affect the transformation of the landscape in the periglacial zone. Thus, this work considers the contamination of the surface of the Arctic, Antarctic, and Caucasian glaciers by priority pollutants. Atomic absorption spectroscopy was used to analyze trace elements (Cu, Zn, Ni, Cd, Pb) from cryoconite deposits. It was revealed that the cryoconite dust on the Ray-Iz glacier (Polar Urals) has a high level of nickel contamination, which comes to the glacier from local rock materials as a result of their weathering. The lowest concentrations of trace elements are found in one of the Arctic plots located at Mushketov and Aldegonda glaciers, the Caucasus, and the Antarctic, which is due to their relatively low content in the composition of rocks and the relatively low contribution of long-range transport of matter to the polar regions. Contamination of moraine sediments in the periglacial zone can make a significant contribution to the formation of the soil cover of these territories, the pollution of water bodies near the glacier, as well as affect the quality of life of the people living in the immediate vicinity of the mountain areas.