bluuebunny/crossref_metadata_2025 huggingface dataset:
Promising Outcomes of Modified ALPPS for Staged Hepatectomy in Cholangiocarcinoma
Authors: Mehrabi Arianeb , Golriz Mohammad , Ramouz Ali , Khajeh Elias , Hammad Ahmed , Hackert Thilo , Müller-Stich Beat , Strobel Oliver , Ali-Hasan-Al-Saegh Sadeq , Ghamarnejad Omid , Al-Saeedi Mohammed , Springfeld Christoph , Rupp Christian , Mayer Philipp , Mieth Markus , Goeppert Benjamin , Hoffmann Katrin , Büchler Markus W.
Published: November 2023

Associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) is a two-stage procedure that can potentially cure patients with large cholangiocarcinoma. The current study evaluates the impact of modifications on the outcomes of ALPPS in patients with cholangiocarcinoma. In this single-center study, a series of 30 consecutive patients with cholangiocarcinoma (22 extrahepatic and 8 intrahepatic) who underwent ALPPS between 2011 and 2021 was evaluated. The ALPPS procedure in our center was modified in 2016 by minimizing the first stage of the surgical procedure through biliary externalization after the first stage, antibiotic administration during the interstage phase, and performing biliary reconstructions during the second stage. The rate of postoperative major morbidity and 90-day mortality, as well as the one- and three-year disease-free and overall survival rates were calculated and compared between patients operated before and after 2016. The ALPPS risk score before the second stage of the procedure was lower in patients who were operated on after 2016 (before 2016: median 6.4; after 2016: median 4.4; p = 0.010). Major morbidity decreased from 42.9% before 2016 to 31.3% after 2016, and the 90-day mortality rate decreased from 35.7% before 2016 to 12.5% after 2016. The three-year survival rate increased from 40.8% before 2016 to 73.4% after 2016. Our modified ALPPS procedure improved perioperative and postoperative outcomes in patients with extrahepatic and intrahepatic cholangiocarcinoma. Minimizing the first step of the ALPPS procedure was key to these improvements.
Clonal Neoantigen: Emerging “Mechanism-based” Biomarker of Immunotherapy Response
Authors: Nemunaitis John , Stanbery Laura , Willoughby David , Bognar Ernest , Brun Scott , Walter Adam , Monk Bradley J. , Rocconi Rodney P. , Choucair Khalil , Coleman Robert L.
Published: November 2023

Clonal mutations represent the initiating molecular defects related to cellular transition of a normal phenotype to a malignant phenotype. Molecular genomic assessment utilizing next generation and whole exome sequencing is now being increasingly applied to biomarker determination to refine the use of targeted immune therapies. Case examples followed by retrospective study assessment have convincingly demonstrated clonal neoantigens provide a relevant predictor of response to checkpoint inhibition. A meta-analysis, by Litchfield et al., of over 1000 cancer patients from 12 landmark trials demonstrated no clinical benefit to checkpoint inhibitor (CPI) therapy in correlation to high subclonal tumor mutational burden (TMB), whereas high clonal TMB was found to be significantly correlated with better overall survival (p = 0.000000029). We discuss the mechanism of clonal vs. subclonal neoantigen targeting relationship to homologous recombination proficient (HRP) profile, evidence of preclinical and clinical benefit related to clonal neoantigens, and review a novel developing therapy called Vigil®, designed to expand the clonal neoantigen targeting effector cell populations. Vigil® is an autologous cellular immunotherapy which is designed to carry the full set of personal clonal neoantigens. Phase 2b results demonstrate a durable recurrence-free survival (RFS) and overall survival (OS) advantage for Vigil® in a subset ovarian cancer population with an HRP cancer profile.
Facing Pediatric Rheumatic Diseases: The Role of Disease Activity and Parental Emotion Regulation Strategy in Parents’ and Children’s Psychological Adjustment
Authors: Del Giudice Emanuela , Lubrano Riccardo , Bramanti Sonia Monique , Babore Alessandra , Trumello Carmen , De Maria Sara Giovanna , Dilillo Anna , Marcellino Alessia , Martucci Vanessa , Sanseviero Mariateresa , Bloise Silvia , Ventriglia Flavia , Manippa Valerio
Published: November 2023

Background: Pediatric rheumatic diseases (PRDs) are a group of chronic disorders that start in childhood and are characterized by periodic exacerbations and remissions of symptoms, with limitations in family, school, and social activities. The aim of this study was to detect differences in parents’ psychological adjustment and emotion regulation strategies, and parent-reported children’s adjustments in families of children with active and inactive PRDs. Methods: Fifty-four parents (38 mothers and 16 fathers) of children with PRD were recruited from a pediatric unit. Disease activity was evaluated by their pediatric rheumatologist, while parents’ depressive and anxiety symptoms, emotion regulation strategies, and children’s emotional difficulties and hyperactivity–inattention symptoms were assessed through a web-based survey. Results: Parents of children with active PRDs reported higher levels of their child’s emotional difficulties and hyperactivity–inattention symptoms. Linear regression analysis demonstrated that having a child in the active phases of PRD and lower use of cognitive reappraisal lead to higher children’s emotional symptoms, while active disease, low use of cognitive reappraisal, and greater expressive suppression were associated with higher hyperactivity–inattention symptoms. Our study highlights that children with PRDs and their parents may be at increased risk for psychological problems, especially during the active disease phase, highlighting the importance of a multidisciplinary approach.
Motor Development in Children with Cerebral Palsy in Sweden—A Population-Based Longitudinal Register Study
Authors: Lidbeck Cecilia , Häbel Henrike , Martinsson Caroline , Pettersson Katina , Löwing Kristina
Published: November 2023

The aim was to explore longitudinal motor development in children with cerebral palsy (CP) in Sweden with respect to the Gross Motor Function Classification System (GMFCS). In this national CP registry-based study, 2138 children aged 0.5–19 years participated (42% girls). The distribution with respect to GMFCS was I: 49%, II: 16%, III: 10%, IV: 14%, and V: 11%. In total, 5538 assessments (mean 2.7, min–max: 1–9) with the Gross Motor Function Measure-66 were included. Data were analysed using non-linear mixed-effects regression models, and the Stable Limit Model was selected to fit data. Five distinct curves of predicted gross motor development with respect to GMFCS levels were obtained. The achieved motor development was maintained over time. The estimated average GMFM-66 limit and the average age when 90% of the expected limits were reached were at GMFCS I: 88 at age 4.5; GMFCS II: 71 at age 4.2; GMFCS III: 54 at age 3.1; GMFCS IV: 38 at age 2.6, and at GMFCS V: 18 at age 0.9. In conclusion, this is the first national population-based study following motor development in CP. Five distinct curves reported in previous controlled research studies were confirmed. Our study adds knowledge about motor development captured in children’s everyday context.
In Silico Structural Protein Evaluation of the Phenylalanine Hydroxylase p.(Tyr77His) Variant Associated with Benign Hyperphenylalaninemia as Identified through Mexican Newborn Screening
Authors: Vela-Amieva Marcela , Alcántara-Ortigoza Miguel Angel , González-del Angel Ariadna , Ibarra-González Isabel , Fernández-Hernández Liliana , Guillén-López Sara , López-Mejía Lizbeth , Fernández-Lainez Cynthia
Published: November 2023

Hyperphenylalaninemia (HPA), which includes phenylketonuria (PKU), is a genetic autosomal recessive disorder arising from a deficiency in the enzyme named phenylalanine hydroxylase (PAH). Affected patients can experience severe and irreversible neurological impairments when phenylalanine (Phe) blood concentration exceeds 360 μmol/L (6 mg/dL). Here, we describe a female HPA patient who was born in Mexico to Cuban non-consanguineous parents and identified by newborn screening, and who bears the previously unreported PAH NM_000277.3(PAH):c.[229T>C];[1222C>T] or p.[Tyr77His];[Arg408Trp] genotype. At diagnosis, the patient showed a Phe blood level of 321 μmol/L (5.3 mg/dL), indicative of mild HPA. Neither of the PAH variants found in this patient had been previously reported in the mutational PAH spectrum of the Mexican population. The c.229T>C or p.(Tyr77His) PAH variant was previously related to mild HPA in the Swedish population. Our in silico structural analysis and molecular docking showed that mutated His 77 residue is located in the allosteric site of PAH at the interface of the two monomers. The PDBsum in silico tool predicted that this variant would cause minimal structural disturbance of the protein interface in the presence of Phe at the allosteric site. Docking studies revealed that these structural changes might be attenuated by the allosteric effect of Phe. Given the classic PKU phenotype conditioned by the “Celtic” or c.[1222C>T] or p.(Arg408Trp) PAH variant, which is the second variant in this patient, we propose that p.(Tyr77His) has a hypomorphic feature that could explain her mild HPA phenotype. Our results show the importance of following up on cases detected by NBS and the value of genetic studies and in silico tools that aid in the establishment of correct therapeutic strategies.
Testing a Home Solution for Preparing Young Children for an Awake MRI: A Promising Smartphone Application
Authors: Geuens Sam , Lemiere Jurgen , Nijs Jessica , Treunen Marlies , Aertsen Michael , Toelen Jaan , Pauwels Greet , Sauer Kate , Potoms Marlies , Van Cauter Sofie , Wouters Leen , Hohlbaum Kathrin , Sjölinder Marie , Ståhl Olov , Buyse Gunnar , Demaerel Philippe , Weyn Barbara
Published: November 2023

Thanks to its non-invasive nature and high-resolution imaging capabilities, magnetic resonance imaging (MRI) is a valuable diagnostic tool for pediatric patients. However, the fear and anxiety experienced by young children during MRI scans often result in suboptimal image quality and the need for sedation/anesthesia. This study aimed to evaluate the effect of a smartphone application called COSMO@home to prepare children for MRI scans to reduce the need for sedation or general anesthesia. The COSMO@home app was developed incorporating mini-games and an engaging storyline to prepare children for learning goals related to the MRI procedure. A multicenter study was conducted involving four hospitals in Belgium. Eligible children aged 4–10 years were prepared with the COSMO@home app at home. Baseline, pre-scan, and post-scan questionnaires measured anxiety evolution in two age groups (4–6 years and 7–10 years). Eighty-two children participated in the study, with 95% obtaining high-quality MRI images. The app was well-received by children and parents, with minimal technical difficulties reported. In the 4–6-year-old group (N = 33), there was a significant difference between baseline and pre-scan parent-reported anxiety scores, indicating an increase in anxiety levels prior to the scan. In the 7–10-year-old group (N = 49), no significant differences were observed between baseline and pre-scan parent-reported anxiety scores. Overall, the COSMO@home app proved to be useful in preparing children for MRI scans, with high satisfaction rates and successful image outcomes across different hospitals. The app, combined with minimal face-to-face guidance on the day of the scan, showed the potential to replace or assist traditional face-to-face training methods. This innovative approach has the potential to reduce the need for sedation or general anesthesia during pediatric MRI scans and its associated risks and improve patient experience.
Investigation of Evolution of Microstructure, Mechanical Properties, and Corrosion Resistance of Novel Al-Mg-Si-Ag Alloy
Authors: Liu Tao , Wu Yanli , Wang Huan , Guo Cheng
Published: November 2023

In this paper, the evolution of the microstructure, mechanical properties, and intergranular corrosion (IGC) resistance of an Al-Mg-Si-Ag alloy is systematically investigated. For the as-cast alloy, the microstructure consists of the Mg2Si phase and Mg32(Al, Ag)49 phase. In the isothermal aging process, the novel alloy presents a significant age hardening effect. The ultimate tensile strength (UTS) and yield strength (YS) of the peak-aged alloy are 342 MPa and 231 MPa, respectively, which are 53 MPa and 84 MPa higher than that of the as-quenched alloy. The main strengthening phase at the peak-aged stage of the alloy is the MgAg phase, which has a body-centered cubic structure with a lattice constant of a = 0.33 nm. In addition, the IGC resistance of the peak-aged alloy is worse than that of other aged alloys. The corresponding microstructure of GBPs of the peak-aged alloy is more consecutive, and this is the main reason for the deterioration of IGC resistance of the alloy.
Adjuvant Sorafenib for Postoperative Patients with Hepatocellular Carcinoma and Macrovascular Invasion
Authors: Chang Che-Jui , Hsu Wei-Fan , Jeng Long-Bin , Lai Hsueh-Chou , Hsu Shih-Chao , Chen Te-Hung , Wang Hung-Wei , Peng Cheng-Yuan
Published: November 2023

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality in Taiwan. Some patients with HCC are diagnosed with macrovascular invasion (MVI), which is associated with a poorer prognosis. In Taiwan, sorafenib is the first-line therapy for patients with advanced HCC. However, the efficacy of adjuvant sorafenib therapy remains unclear for the subset of patients with HCC and MVI who are eligible for surgery. Therefore, we investigated the potential benefit of adjuvant sorafenib therapy for patients with HCC and MVI after surgery. Our study showed that the lack of improved PFS or OS of adjuvant sorafenib challenged the therapeutic benefit of postoperative sorafenib. Alcohol consumption and an α-fetoprotein level of ≥400 ng/mL were independent predictors of overall survival (OS); however, adjuvant sorafenib therapy was not a predictor of progression-free survival (PFS) or OS. In conclusion, our study indicated that adjuvant sorafenib therapy did not provide PFS or OS benefits in patients with HCC and MVI.
Artificial Intelligence and Diagnostics in Medicine and Forensic Science
Authors: Lefèvre Thomas , Tournois Laurent
Published: November 2023

Diagnoses in forensic science cover many disciplinary and technical fields, including thanatology and clinical forensic medicine, as well as all the disciplines mobilized by these two major poles: criminalistics, ballistics, anthropology, entomology, genetics, etc. A diagnosis covers three major interrelated concepts: a categorization of pathologies (the diagnosis); a space of signs or symptoms; and the operation that makes it possible to match a set of signs to a category (the diagnostic approach). The generalization of digitization in all sectors of activity—including forensic science, the acculturation of our societies to data and digital devices, and the development of computing, storage, and data analysis capacities—constitutes a favorable context for the increasing adoption of artificial intelligence (AI). AI can intervene in the three terms of diagnosis: in the space of pathological categories, in the space of signs, and finally in the operation of matching between the two spaces. Its intervention can take several forms: it can improve the performance (accuracy, reliability, robustness, speed, etc.) of the diagnostic approach, better define or separate known diagnostic categories, or better associate known signs. But it can also bring new elements, beyond the mere improvement of performance: AI takes advantage of any data (data here extending the concept of symptoms and classic signs, coming either from the five senses of the human observer, amplified or not by technical means, or from complementary examination tools, such as imaging). Through its ability to associate varied and large-volume data sources, but also its ability to uncover unsuspected associations, AI may redefine diagnostic categories, use new signs, and implement new diagnostic approaches. We present in this article how AI is already mobilized in forensic science, according to an approach that focuses primarily on improving current techniques. We also look at the issues related to its generalization, the obstacles to its development and adoption, and the risks related to the use of AI in forensic diagnostics.
CO2 Laser for Esthetic Healing of Injuries and Surgical Wounds with Small Parenchymal Defects in Oral Soft Tissues
Authors: Daigo Yuki , Daigo Erina , Fukuoka Hiroshi , Fukuoka Nobuko , Idogaki Jun , Taniguchi Yusuke , Tsutsumi Takashi , Ishikawa Masatsugu , Takahashi Kazuya
Published: November 2023

A number of studies have recently demonstrated the effectiveness of CO2 laser irradiation for the repair and regeneration of scar tissue from injuries or surgical wounds. However, such studies of the oral mucosa are highly limited. Previous studies using CO2 laser irradiation have indicated that two factors contribute to esthetic healing, namely, artificial scabs, which are a coagulated and carbonized blood layer formed on the wound surface, and photobiomodulation therapy (PBMT) for suppressing wound scarring and promoting wound healing. This review outlines basic research and clinical studies of esthetic healing with the use of a CO2 laser for both artificial scab formation by high-intensity laser therapy and PBMT in the treatment of injuries and surgical wounds with small parenchymal defects in oral soft tissues. The results showed that the wound surface was covered by an artificial scab, enabling the accumulation of blood and the perfusion necessary for tissue regeneration and repair. Subsequent PBMT also downregulated the expression of transformation growth factor-b1, which is involved in tissue scarring, and decreased the appearance of myofibroblasts. Taken together, artificial scabs and PBMT using CO2 lasers contribute to the suppression of scarring in the tissue repair process, leading to favorable esthetic and functional outcomes of wound healing.
Fluorescence and Near-Infrared Light for Detection of Secondary Caries: A Systematic Review
Authors: Spagopoulos Dimitrios , Michou Stavroula , Gizani Sotiria , Pappa Eftychia , Rahiotis Christos
Published: November 2023

Background: Early detection of secondary caries near dental restorations is essential to prevent further complications. This systematic review seeks to evaluate the sensitivity of fluorescence and near-infrared (NIR) imaging techniques for detecting secondary caries and to provide insight into their clinical utility. Methods: A comprehensive search strategy was used to select studies from seven databases, emphasizing diagnostic accuracy studies of secondary caries detection using fluorescence and NIR imaging techniques. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) instrument assessed bias risk and practicality. Two evaluators performed data extraction, screening, and quality assessment independently. Results: From 3110 initial recordings, nine studies were selected for full-text analysis. Wide variations in sensitivity (SE) and specificity (SP) values were reported across the studies. These studies exhibited variable SE and SP values, and the findings highlighted the importance of method selection based on clinical context. This systematic review underlines the potential for fluorescence and NIR imaging to detect secondary caries. However, results from different studies vary, indicating the need to consider additional variables such as restoration materials. Conclusions: Although these technologies exhibit potential for detecting caries, our research underscores the complex procedure of identifying secondary caries lesions. It is a continuous necessity for progress in dental diagnostics to promptly identify secondary caries lesions, particularly those in proximity to tooth-colored ones.
Solar Flare 1/f Fluctuations from Amplitude-Modulated Five-Minute Oscillation
Authors: Morikawa Masahiro , Nakamichi Akika
Published: November 2023

We first report that the solar flare time sequence exhibits a fluctuation characterized by its power spectral density being inversely proportional to the signal frequency. This is the 1/f fluctuation, or pink noise, observed ubiquitously in nature. Using GOES16 data, we found that low-energy flares (E≤Emean) display 1/f fluctuations, whereas high-energy flares (E>Emean) show a flat spectrum. Furthermore, we found that the timing sequence of the flares reveals clearer 1/f fluctuations. These observations suggest that the solar flare 1/f fluctuations are associated with low-energy phenomena. We investigated the origin of these 1/f fluctuations based on our recent hypothesis: 1/f fluctuations arise from amplitude modulation and demodulation. We propose that this amplitude modulation is encoded by the resonance with the solar five-minute oscillation (SFO) and demodulated by magnetic reconnections. We partially demonstrate this scenario by analyzing the SFO eigenmodes resolving the frequency degeneration in the azimuthal order number m using the solar rotation and resonance. Given the robust nature of 1/f fluctuations, we speculated that the solar flare 1/f fluctuations may be inherited by the various phenomena around the Sun, such as the sunspot numbers and cosmic rays. In addition, we draw parallels between solar flares and earthquakes, both exhibiting 1/f fluctuations. Interestingly, the analysis applied to solar flares can also be adapted to earthquakes if we read the SFO as Earth’s free oscillation and magnetic reconnections as fault ruptures. Moreover, we point out the possibility that the same analysis also applies to the activity of a black hole/disk system if we read the SFO as the quasi-periodic oscillation of a black hole.
Recent Advanced Applications of Virtual Industrial Informatics and Robotics
Authors: Mourtzis Dimitris , Boboc Răzvan Gabriel , Godina Radu , Smalcerz Albert
Published: November 2023

In recent years, there has been a concerted effort to revolutionize industrial production through the integration of digital technologies, leading to the emergence of Industry 4 [...]
Simulation of an Ultrafast Charging Station Operating in Steady State
Authors: Blanch-Fortuna Alexandra , Zambrano-Prada David , Gállego-Casals Martín , Martinez-Salamero Luis
Published: November 2023

This report presents the analysis, study, and simulation of an ultrafast charging station (UFCS) for electric vehicles (EVs) operating in steady state. The electrical architecture of the charging station uses an ac bus plus two dc buses and it is supported by a storage system based on batteries and super-capacitors. The power demand of the EVs is established taking into account the electric characteristics of their batteries and the availability of the station charging points. The analysis introduces a supervisory control based on a state machine description for different operating modes, which eventually facilitates fault detection in the electrical architecture. In addition, the study proposes different methods to handle the required energy for the charging demand and a procedure for the correct sizing of both the energy storage system and the input transformer. In laboratory experiments in a reduced-scale storage system, a SCADA supervision with CAN communication has proved successful in gathering data corresponding to modes of charge and discharge in batteries and super-capacitors, and subsequently displaying them on a computer screen.
An SAR Imaging and Detection Model of Multiple Maritime Targets Based on the Electromagnetic Approach and the Modified CBAM-YOLOv7 Neural Network
Authors: Peng Peng , Wang Qingkuan , Feng Weike , Wang Tong , Tong Chuangming
Published: November 2023

This paper proposes an Synthetic Aperture Radar (SAR) imaging and detection model of multiple targets at the maritime scene. The sea surface sample is generated according to the composite rough surface theory. The SAR imaging model is constructed based on a hybrid EM calculation approach with the fast ray tracing strategy and the modified facet Small Slope Approximation (SSA) solution. Numerical simulations calculate the EM scattering and the SAR imaging of the multiple cone targets above the sea surface, with the scattering mechanisms analyzed and discussed. The SAR imaging datasets are then set up by the SAR image simulations. A modified YOLOv7 neural network with the Spatial Pyramid Pooling Fast Connected Spatial Pyramid Convolution (SPPFCSPC) module, Convolutional Block Attention Module (CBAM), modified Feature Pyramid Network (FPN) structure and extra detection head is developed. In the training process on our constructed SAR datasets, the precision rate, recall rate, mAP@0.5 and mAP@0.5:0.95 are 97.46%, 90.08%, 92.91% and 91.98%, respectively, after 300 rounds of training. The detection results show that the modified YOLOv7 has a good performance in selecting the targets out of the complex sea surface and multipath interference background.
Finding a Needle in a Haystack: Faint and Small Space Object Detection in 16-Bit Astronomical Images Using a Deep Learning-Based Approach
Authors: Jiang Yunxiao , Tang Yijun , Ying Chenchen
Published: November 2023

With the increasing interest in space science exploration, the number of spacecraft in Earth’s orbit has been steadily increasing. To ensure the safety and operational integrity of active satellites, advanced surveillance and early warning of unknown space objects such as space debris are crucial. The traditional threshold-based filter for space object detection heavily relies on manual settings, leading to limitations such as poor flexibility, high false alarm rates, and weak target detection capability in low signal-to-noise ratios. Therefore, detecting faint and small objects against a complex starry background remains a formidable challenge. To address this challenge, we propose a novel, intelligent, and accurate detection method called You Only Look Once for Space Object Detection (SOD-YOLO). Our method includes the following novel modules: Multi-Channel Histogram Truncation (MHT) enhances feature representation, CD-ELAN based on Central Differential Convolution (CDC) facilitates learning contrast information, the Space-to-Depth (SPD) module replaces pooling layer to prevent small object feature loss, a simple and parameter-free attention module (SimAM) expands receptive field for Global Contextual Information, and Alpha-EIoU optimizes the loss function for efficient training. Experiments on our SSOD dataset show SOD-YOLO has the ability to detect objects with a minimum signal-to-noise ratio of 2.08, improves AP by 11.2% compared to YOLOv7, and enhances detection speed by 42.7%. Evaluation on the Spot the Geosynchronous Orbit Satellites (SpotGEO) dataset demonstrates SOD-YOLO’s comparable performance to state-of-the-art methods, affirming its generalization and precision.
Financial Aspects of Energy Investments in the Era of Shaping Stable Energy Development in Poland: A Case Study
Authors: Olkiewicz Marcin , Dyczkowska Joanna Alicja , Olkiewicz Anna Maria
Published: November 2023

Investments in green energy are necessary due to, among other reasons, the growing expectations of stakeholders, climate change, limited natural resources, and improved quality of life. Unfortunately, the costs of implementing pro-environmental activities related to investing in technologies using alternative methods of obtaining energy are significant, which is why more and more entities are analyzing their profitability. The aim of this study, as part of a case study, is to assess the energy investment in PV panels in the logistics center (LC) being built in Central Pomerania. The analyzed investment fits into the activities of the development perspective of the renewable energy sources sector and is also very important from the perspective of shaping the conditions and stable development of the energy industry in Poland. The study proved that such a large investment, taking into account various forms of financing, will pay off within 15 years, which is a very good result from the point of view of its durability. The best variant of capital involvement is the option 20 (own capital)/80 (outsourced capital), which, among other things, confirms (in thousands of euros) NPV = 4.43, NPV (TGeBase) = 0.04, and NPV (CAPEX) = 4.32.
Electromagnetic Performance Analysis of a Multichannel Permanent Magnet Synchronous Generator
Authors: Korkosz Mariusz , Sztajmec Elżbieta , Prokop Jan
Published: November 2023

In this paper, we present an analysis of the properties of the prototype three-phase Multichannel Permanent Magnet Synchronous Generator (MCPMSG) prototype designed and constructed by the authors. Each channel of the generator has electrically separated windings, which allows us to create an island system of electricity generation. The analyzed MCPMSG is intended for critical applications, and it is designed for four-channel operation. The purpose of this work is to analyze various configurations of the generator channels to improve the redundancy of the electricity generation system. The MCPMSG operation with one or two independent sources of energy consumption in the case of a dual-channel or double dual-channel operation was investigated. For the analyzed cases, the original mathematical models of the three-phase MCPMSG were developed. On the basis of numerical and laboratory tests, the influence of individual configurations on the MCPMSG output parameters was determined. An original method for diagnosing the operation of the MCPMSG channels was developed. Numerical and laboratory tests of the proposed diagnostic method based on a single voltage signal were carried out. As part of the laboratory tests, selected operating states under conditions of full winding symmetry and internal asymmetry were analyzed. The advantage of the proposed diagnostic method is the control of the operating state of the channels both under load and in the de-energized state. The proposed diagnostic method for control of the individual channel requires measurement of only one voltage signal.
Thermodynamic Investigation and Economic Evaluation of a High-Temperature Triple Organic Rankine Cycle System
Authors: Li Pengcheng , Shu Chengxing , Li Jing , Wang Yandong , Chen Yanxin , Ren Xiao , Jie Desuan , Liu Xunfen
Published: November 2023

Triple organic Rankine cycle (TORC) is gradually gaining interest, but the maximum thermal efficiencies (around 30%) are restricted by low critical temperatures of common working fluids (<320 °C). This paper proposes a high-temperature (up to 400 °C) TORC system to ramp up efficiency. A near-azeotropic mixture biphenyl/diphenyl oxide (BDO), which has a stellar track record in the high-temperature ORC applications, is innovatively adopted as the top and middle ORC fluid simultaneously. Four conventional organic fluids are chosen for the bottom ORC. A mixing heat exchanger connects the top and middle ORCs to reduce irreversible loss. Thermodynamic analysis hints that the optimal performance is achieved on the use of benzene as the bottom fluid. The maximum thermal and exergy efficiencies are respectively 40.86% and 74.14%. The largest exergy destruction occurs inside the heat exchanger coupling the middle and bottom ORCs, accounting for above 30% of the total entropy generation. The levelized energy cost (LEC) is 0.0368 USD/kWh. Given the same heat source condition, the TORC system can boost the efficiency by 1.02% and drive down LEC by 0.0032 USD/kWh compared with a BDO mixture-based cascade ORC. The proposed system is promising in solar thermal power generation and Carnot battery applications using phase change materials for storage.
A Feasibility Study of Profiting from System Imbalance Using Residential Electric Vehicle Charging Infrastructure
Authors: Tomašov Marián , Straka Milan , Martinko Dávid , Braciník Peter , Buzna Ľuboš
Published: November 2023

Residential chargers are going to become the standard in the near future. Their operational cycles are closely tied to users’ daily routines, and the power consumption fluctuates between zero and peak levels. These types of installations are particularly challenging for the grid, especially concerning the balance of electricity production and consumption. Using battery storage in conjunction with renewable sources (e.g., photovoltaic power plants) represents a flexible solution for grid stabilization, but it is also associated with additional costs. Nowadays, grid authorities penalize a destabilization of the grid resulting from an increased imbalance between electricity generation and consumption and reward contributions to the system balance. Hence, there is a motivation for larger prosumers to make use of this mechanism to reduce their operational costs by better aligning their energy needs with the grid. This study explores the possibility of utilizing battery storage when it is not needed to fulfil its primary function of supporting charging electric vehicles, to generate some additional profit from providing a counter-imbalance. To test this idea, we develop an optimization model that maximizes the economic profit, considering system imbalance penalties/rewards, photovoltaic production, electric vehicle charging demand, and battery storage utilization. By means of computer simulation, we assess the overall operational costs while varying key installation parameters such as battery capacity and power, the installed power of photovoltaic panels and the prediction model’s accuracy. We identify conditions when counter-imbalance has proven to be a viable way to reduce installation costs. These conditions include temporal distribution of charging demand, electricity prices and photovoltaic production. For the morning time window, with a suitable setting of the installation parameters, the cost reduction reaches up to 14% compared to the situation without counter-imbalance.
Numerical Simulation of Environmental Characteristics of Containment in Severe Accident of Marine Nuclear Power Plant
Authors: Xu Zhiyong , Liu Jialei , Chen Yuqing , Li Ang
Published: November 2023

With the reliance on ocean resources, the nuclear power powers have set their sights on marine nuclear power plants to break through the bottleneck of energy supply for the development of ocean resources. In this paper, the computational fluid dynamics software ANSYS CFX 2021 is used to simulate the TOSQAN benchmark experiment. Three different turbulence models, the k−ε model, RNG k−ε model, and SST model, are selected to analyze the adaptability of the turbulence model. The simulation results are compared with the benchmark experimental results, and the selected numerical calculation model is used to analyze the influence of vapor on the pressure, temperature, hydrogen distribution, and hydrogen risk in the containment space when a hypothetical serious accident occurs in a marine nuclear power plant. The results show that the results simulated with the k−ε turbulence model are closer to the benchmark experimental results. Vapor has no obvious effect on the response speed of pressure balance at each position in the closed containment space, and the condensation of the vapor wall can effectively reduce the pressure peak in the closed containment space. The existence of vapor and the increase in vapor concentration will increase the temperature in the closed containment space. The condensation of vapor on the wall surface will cause the temperature in the containment space to have a peak value, which can effectively reduce the temperature in the containment space. Vapor will promote the mixing of gas in the containment space and make the hydrogen distribution tend to be uniform. The presence of vapor and the increase in vapor concentration can reduce the hydrogen risk in the containment space, but the condensation of vapor may increase the hydrogen risk in the containment space.
Power Supply Reliability Analysis of Distribution Systems Considering Data Transmission Quality of Distribution Automation Terminals
Authors: Luo Fengzhang , Ge Nan , Xu Jing
Published: November 2023

A distribution automation system is the integration of physical power distribution systems and information systems. Its information system guarantees the safe operation and reliable power supply of physical systems by monitoring, collecting and transmitting information. In the information system, the remote terminal unit of distribution automation is the hub of the information system, connecting it to the physical power system. Considering the unreliability of terminal information transmission in the information system, this paper aims to build a model to quantitatively evaluate the impact of unreliable transmission information on the power supply reliability of distribution systems. Firstly, the m-segment and n-connection unit model of distribution feeders is established, and then, the power supply reliability indices in the process of handling feeder terminal unit error are analyzed and calculated under the configuration modes of “three-remote” and “two-remote” of remote terminals. Then, considering the impact of a transmission error in the information system, the reliability index calibration model under the condition of unreliable information transmission is established. Finally, a case study is presented to illustrate how the proposed model is implemented.
Analytical Approach for Estimating the Average Torque of Synchronous Motors by Using the Flux Density in the Air Gap
Authors: Li Zheng-Feng , Huang Lin-Wei , Chen Shih-Gang , Hsu Yu-Tse , Hsu Jun-Ming , Huang Ming-Shi
Published: November 2023

In this study, a generalized torque estimation method is proposed for synchronous motors, including surface permanent magnet synchronous motors (SPMSMs), synchronous reluctance motors (SynRMs), and interior permanent magnet synchronous motors (IPMSMs) for building the analytical motor model. The average motor torque is estimated using the Lorentz force by the generated flux density in the air gap to determine the relationships among torque, flux density, and injected current. In the proposed method, the generated flux density is derived step by step by considering the effects of magnetic flux saturation, the stator slot, the rotor barrier, and permanent magnets (PMs) to ensure that the generated average torque complies with the operating condition of the motor. To verify the proposed method, the output torque of finite element analysis (FEA), Maxwell 2D, is compared to the proposed method in a SPMSM. Moreover, a phasor diagram is plotted to determine the mechanism through which torque is generated in SynRMs and IPMSMs. A SynRM and an IPMSM with ferrites PMs are analyzed using the proposed method, FEA, and the experimental results of this study indicate the effectiveness.
The Effects of Forest Walking on Physical and Mental Health Based on Exercise Prescription
Authors: Kim Choyun , Kim Juhyeon , Song Injoon , Yi Yunjeong , Park Bum-Jin , Song Chorong
Published: November 2023

This study aimed to verify the effects of prescribed personalized forest walking by considering individuals’ characteristics. To prescribe individualized exercise programs, we developed an algorithm to calculate exercise intensity based on each participant’s age, regular exercise, fatigue level, and chronic disease type, if any. To investigate the effects of forest walking on physical and mental health based on exercise prescription, we recruited 59 participants (average age: 39.1 ± 19.0 years old) aged 18 years or older. Physiological and psychological responses were compared before and after walking in the forest. Systolic blood pressure, diastolic blood pressure, percent body fat, negative affect, and emotional exhaustion significantly decreased, while the pulse rate significantly increased following the forest walking. Additionally, we investigated the effects of exercise relative to successfully maintaining one’s target heart rate and found that these effects were even greater when success score of maintaining the target heart rate while walking improved. Comparison of the groups relative to successfully achieving the target heart rate indicated that the high-achievement group had significant reductions in systolic and diastolic blood pressure, body fat mass, percent body fat, negative affect, and emotional exhaustion, and a significant increase in pulse rate. However, the low-achievement group only showed a significant reduction in emotional exhaustion. This study showed that prescribed forest walking has a positive impact on human health and is expected to have a positive effect on the motivation to start and continue exercising.
Enhancing Forest Security through Advanced Surveillance Applications
Authors: Buchman Danny , Krilavičius Tomas , Maskeliūnas Rytis
Published: November 2023

Forests established through afforestation are one of the most precious natural resources, especially in harsh and desert-biased conditions. Trees are often exposed to various threats that need to be addressed. Some of the threats are igniting fires, illegal lumberjacking, hunting, using, and crossing prohibited areas, etc. This article delves into the combination of advanced technologies, such as radars, thermal imaging, remote sensing, artificial intelligence, and biomass monitoring systems, in the field of forestry and natural resource security. By examining the parametric assurance technologies described in this paper, the potentials of real-time monitoring, early detection of threats, and rapid response capabilities are examined, which significantly improves the efficiency of forest protection efforts. This article deals with the presentation of advanced algorithms that include radar, thermal cameras, and artificial intelligence, which enable the automatic identification and classification of potential threats with a false alarm rate (FAR) as low as possible. The article presents a systemic solution that optimizes the answer for a parametric security system that is required to work in a complex environment with multiple triggers that can cause false alarms. In addition to this, a presented system is required to be easy to assemble and have the ability to integrate into natural areas and serve as a vulnerable aid in nature as much as possible. In conclusion, this study highlights the transformative potential of security applications in improving forest and natural reserve security while taking into account the complexity of the environment.
A Survey on IoT-Edge-Cloud Continuum Systems: Status, Challenges, Use Cases, and Open Issues
Authors: Gkonis Panagiotis , Giannopoulos Anastasios , Trakadas Panagiotis , Masip-Bruin Xavi , D’Andria Francesco
Published: November 2023

The rapid growth in the number of interconnected devices on the Internet (referred to as the Internet of Things—IoT), along with the huge volume of data that are exchanged and processed, has created a new landscape in network design and operation. Due to the limited battery size and computational capabilities of IoT nodes, data processing usually takes place on external devices. Since latency minimization is a key concept in modern-era networks, edge servers that are in close proximity to IoT nodes gather and process related data, while in some cases data offloading in the cloud might have to take place. The interconnection of a vast number of heterogeneous IoT devices with the edge servers and the cloud, where the IoT, edge, and cloud converge to form a computing continuum, is also known as the IoT-edge-cloud (IEC) continuum. Several key challenges are associated with this new computing systems’ architectural approach, including (i) the design of connection and programming protocols aimed at properly manipulating a huge number of heterogeneous devices over diverse infrastructures; (ii) the design of efficient task offloading algorithms aimed at optimizing services execution; (iii) the support for security and privacy enhancements during data transfer to deal with the existent and even unforeseen attacks and threats landscape; (iv) scalability, flexibility, and reliability guarantees to face the expected mobility for IoT systems; and (v) the design of optimal resource allocation mechanisms to make the most out of the available resources. These challenges will become even more significant towards the new era of sixth-generation (6G) networks, which will be based on the integration of various cutting-edge heterogeneous technologies. Therefore, the goal of this survey paper is to present all recent developments in the field of IEC continuum systems, with respect to the aforementioned deployment challenges. In the same context, potential limitations and future challenges are highlighted as well. Finally, indicative use cases are also presented from an IEC continuum perspective.
Effect of Different Pre-Growth Temperatures on the Survival Kinetics of Salmonella enterica and Listeria monocytogenes in Fresh-Cut Salad during Refrigerated Storage
Authors: Kaur Avninder , Yemmireddy Veerachandra
Published: November 2023

The effect of the pre-growth temperature of bacterial cultures on their subsequent survival kinetics in fresh-cut produce during refrigerated storage was investigated in this study. Three-strain cocktails of Listeria monocytogenes and Salmonella enterica, cultured at different growth temperatures (4, 21, and 37 °C) were inoculated on fresh-cut mixed salad and on individual produce in the mixed salad. The inoculated samples were stored at 4 °C and 80 ± 2% relative humidity (RH) for up to 72 h and the growth, survival, or death kinetics were determined at regular intervals. The results indicate that depending upon the type of pathogen tested, the pre-growth temperature(s) and the type of produce showed a significant (p ≤ 0.05) effect on the survival kinetics. Among the tested produce, mixed salad showed the highest reduction in L. monocytogenes pre-grown at 37 °C (1.33 log CFU/g) followed by red cabbage (0.56 log CFU/g), iceberg lettuce (0.52 log CFU/g), and carrot (−0.62 log CFU/g), after 72 h, respectively. In the case of Salmonella, carrot showed the highest reduction (1.07 log CFU/g for 37 °C pre-grown culture) followed by mixed salad (0.78 log CFU/g for 37 °C pre-grown culture), cabbage (0.76 log CFU/g for 21 °C pre-grown culture), and lettuce (0.65 log CFU/g for 4 °C pre-grown culture), respectively. Among the tested ComBase predictive models, the Baranyi–Roberts model better fitted the experimental data. These findings indicate that the appropriate selection of pre-growth environmental conditions is critical to better understand the kinetics of foodborne pathogens.
DPF-Nutrition: Food Nutrition Estimation via Depth Prediction and Fusion
Authors: Han Yuzhe , Cheng Qimin , Wu Wenjin , Huang Ziyang
Published: November 2023

A reasonable and balanced diet is essential for maintaining good health. With advancements in deep learning, an automated nutrition estimation method based on food images offers a promising solution for monitoring daily nutritional intake and promoting dietary health. While monocular image-based nutrition estimation is convenient, efficient and economical, the challenge of limited accuracy remains a significant concern. To tackle this issue, we proposed DPF-Nutrition, an end-to-end nutrition estimation method using monocular images. In DPF-Nutrition, we introduced a depth prediction module to generate depth maps, thereby improving the accuracy of food portion estimation. Additionally, we designed an RGB-D fusion module that combined monocular images with the predicted depth information, resulting in better performance for nutrition estimation. To the best of our knowledge, this was the pioneering effort that integrated depth prediction and RGB-D fusion techniques in food nutrition estimation. Comprehensive experiments performed on Nutrition5k evaluated the effectiveness and efficiency of DPF-Nutrition.