bluuebunny/crossref_metadata_2025 huggingface dataset:
Kidney Injury in Children after Hematopoietic Stem Cell Transplant
Authors: James Vinson , Angelo Joseph , Elbahlawan Lama
Published: March 2023

Hematopoietic cell transplant (HCT), used for treatment of many malignant and non-malignant pediatric diseases, is associated with serious complications, limiting this therapy’s benefit. Acute kidney injury (AKI), seen often after HCT, can occur at different stages of the transplant process and contributes to morbidity and mortality after HCT. The etiology of AKI is often multifactorial, including kidney hypoperfusion, nephrotoxicity from immunosuppressive and antimicrobial agents, and other transplant-related complications such as transplant-associated thrombotic microangiopathy and sinusoidal obstructive syndrome. Early recognition of AKI is crucial to prevent further AKI and associated complications. Initial management includes identifying the etiology of AKI, preventing further kidney hypoperfusion, adjusting nephrotoxic medications, and preventing fluid overload. Some patients will require further support with kidney replacement therapy to manage fluid overload and AKI. Biomarkers of AKI, such as neutrophil gelatinase-associated lipocalin can aid in detecting AKI before a rise in serum creatinine, allowing earlier intervention. Long-term kidney dysfunction is also prominent in this population. Therefore, long-term follow-up and monitoring of renal function (glomerular filtration rate, microalbuminuria) is required along with management of hypertension, which can contribute to chronic kidney disease.
Analysis of the Genetic Diversity of the European Bison (Bison bonasus) Population in Lithuania
Authors: Lapickis Romualdas , Griciuvienė Loreta , Kibiša Artūras , Lipatova Indrė , Aleksandravičienė Asta , Ražanskė Irma , Wojciechowska Marlena , Kloch Marta , Olech Wanda , Paulauskas Algimantas
Published: March 2023

The European bison is a species well known for its low genetic variability due to historical bottleneck incidents. Restoration of the European bison population in Lithuania began at the end of the 20th century, and the Lithuanian population was re-established with ten individuals from the Prioksko-Terrasny reserve in Russia and one free-roaming individual captured in Lithuania. This research focused on the genetic diversity and genetic structure of European bison in Lithuania based on microsatellite markers and mtDNA sequences. The results of the microsatellite analysis revealed that the Lithuanian population (n = 34) has a different genetic structure to individuals in Poland (n = 16), Germany (n = 10), and Sweden (n = 6). The analysis of the mtDNA sequences showed a low level of variation, with two haplotypes observed in the Lithuanian bison population. H1 was more frequent and was also found in Poland, Romania, and Russia. The results of this investigation show that individuals should be continuously genetically monitored, registering their migrations and relocations for the successful management of the species in Lithuania.
Biodiversity in Karst Landscapes: Introduction to the Special Issue
Authors: Mičetić Stanković Vlatka
Published: March 2023

Karst landscapes are a set of various features built of rocks that are soluble in water [...]
Exploring More on Dictyosporiaceae: The Species Geographical Distribution and Intriguing Novel Additions from Plant Litter
Authors: Tennakoon Danushka S. , de Silva Nimali I. , Maharachchikumbura Sajeewa S. N. , Bhat Darbhe J. , Kumla Jaturong , Suwannarach Nakarin , Lumyong Saisamorn
Published: March 2023

Five fungal taxa collected from plant litter in Chiang Mai province, Thailand, are described with illustrations. The maximum likelihood, maximum parsimony, and Bayesian analyses of combined loci of the internal transcribed spacer (ITS), large subunit nuclear ribosomal DNA (LSU), and translation extension factor 1-α (tef1-α) region were used for phylogeny analyses. Dictyocheirospora acaciae is introduced as a new species from Acacia dealbata. Based on size differences in conidiomata, conidia, and DNA sequence data, it is separated from the other species in the genus. Four new host records, Dictyocheirospora garethjonesii, Di. taiwanense, Dictyosporium digitatum, and Pseudocoleophoma zingiberacearum are also reported from Bismarkia nobilis, Ficus benjamina, Cyperus aggregatus, and Hedychium spicatum, respectively. Detailed descriptions, microphotographs, and phylogenetic information were provided, and all the species were compared to similar taxa. It is noted that there is still a necessity for a collective worldwide account of the distribution of Dictyosporiaceae species. Therefore, we compiled the geographical distributions and host species associations of all the so far known Dictyosporiaceae species and discussed them here.
Reproductive Biology and Pollination Ecology of Fritillaria michailovskyi Fomin (Liliaceae), Endemic to East Anatolia (Turkey)
Authors: Aslay Meral , Yıldız Faruk , Kaya Ozkan , Bita-Nicolae Claudia
Published: March 2023

Fritillaria is highly endangered in their natural habitats, and these species are perennial bulbous plants with an important medicinal and ornamental value whose reproductive strategies and adaptive evolution mechanisms are still not fully clear. Therefore, the reproductive strategies of endemic species, like Fritillaria michailovskyi Fomin are important to detect the community structure and the diversity patterns of ornamental plants. The current paper on the reproductive strategy of F. michailovskyi, a rare endemic species, was carried out at the Erzincan Horticultural Research Institute, Turkey. Our results indicate that the flowering stages of F. michailovskyi may be divided into eight phases. According to pollination experiments and the pollen/ovule ratio, and the self-incompatibility index (SII) in an ex-situ population, F. michailovskyi indicated high levels of xenogamy and self-incompatibility. It was determined that the pollination of F. michailovskyi mostly depended on pollen vectors, and the effective pollinators of F. michailovskyi were Apis mellifera and Bombus terrestris. In addition, average seed number, seed germination, and average seed viability were found as 144, 46%, and 67%, respectively. The stigma receptivity, pollen grains, and pollen viability were detected as 83%, 252,000, and 95%, respectively. Our study is the first report providing a detailed explanation of the reproductive strategy of this rare endemic species, which could aid in the genetic evolution and conservation of this valuable taxa.
Endoparasitic Gall Mites: Two New Novophytoptus Species (Eriophyoidea, Phytoptidae) from Southern African Sedges (Cyperaceae, Carex) and New Hypotheses on the Phylogeny of Novophytoptines
Authors: Chetverikov Philipp E. , Craemer Charnie , Gankevich Vladimir D. , Kremenetskaya Maria V. , Kuzmin Igor V. , Zhuk Anna S.
Published: March 2023

Eriophyoid mites (Acariformes, Eriophyoidea) are microscopic chelicerates morphologically greatly preadapted to endoparasitism on plants. Members of at least six phylogenetically distant eriophyoid genera from two families homoplastically transitioned to endoparasitism and acquired the ability to penetrate under the plant epidermis and feed on parenchymatous cells, usually causing necrosis. Theoretically, endoparasites are expected to show patterns of codivergence with hosts more than ectoparasites. Novophytoptus Roivainen 1947 is the only eriophyoid genus comprising exclusively endoparasitic species living in subepidermal tissues of herbaceous monocots of three families of the order Poales: Cyperaceae, Juncaceae, and Poaceae. Here, we described two new endoparasitic species, N. limpopoensis n. sp. and N. zuluensis n. sp., from southern African sedges Carex spicatopaniculata Boeckeler ex C.B.Clarke and C. zuluensis C.B.Clarke, respectively, and investigated the Cox1 phylogeny of Novophytoptus. Contrary to expectations, molecular phylogenetics did not recover host-specific mite clades associated with Cyperaceae and Juncaceae, but revealed geographical groups of Novophytoptus species from Africa and Eurasia. Our results provide a substantial basis for future coevolutionary studies on novophytoptines, which will be possible when more species and sequences of Novophytoptus from geographically remote regions and from diverse hosts representing all major clades of Poales become available for analyses.
Impacts of Climate Change on Densities of the Urchin Centrostephanus rodgersii Vary among Marine Regions in Eastern Australia
Authors: Davis Tom R. , Knott Nathan A. , Champion Curtis , Przeslawski Rachel
Published: March 2023

The urchin Centrostephanus rodgersii is expanding its range southward in eastern Australia, which has been associated with negative ecological impacts, including shifts from kelp forests to barrens. However, limited analyses are available that examine the factors influencing its abundance and distribution across the entirety of this range. Here, we utilise data from 13,085 underwater visual census surveys, from 1992 to 2022, to develop an urchin density model for C. rodgersii across its historical and extending geographical range. We apply this model to examine whether C. rodgersii densities are increasing and to project future urchin densities by 2100 under IPCC climate scenario RCP 8.5. Significant increases in C. rodgersii densities were detected in data for the South-east marine region of Australia, which encompasses Tasmania, Victoria, and the far south coast of New South Wales (NSW) over the last 30 years. In the Temperate East marine region (encompassing Queensland and NSW waters to 36.6° S), however, no significant increases in densities were observed. Future projections indicated that further substantial increases in C. rodgersii densities are likely to occur in the South-east marine region and substantial reductions in most of the Temperate East marine region by 2100. Importantly, results indicate that current and future changes to C. rodgersii densities in Australia vary among marine regions. Therefore, the future ecological impacts of urchins on temperate ecosystems, including the formation of barrens, will also vary among regions. Consequently, management actions will need to differ among these regions, with the South-east marine region requiring mitigation of the impacts of increasing C. rodgersii densities, whereas the Temperate East marine region may need actions to preserve declining C. rodgersii populations.
Functional Traits and Local Environmental Conditions Determine Tropical Rain Forest Types at Microscale Level in Southern Ecuador
Authors: Cabrera Omar , Ramón Pablo , Stimm Bernd , Gunter Sven , Mosandl Reinhard
Published: March 2023

The main objective of this study was to determine the heterogeneity of tropical mountain rain forests along a micro-altitudinal gradient scale, integrating species functional traits in the separation of communities. To achieve this, a forest area of 13 ha in the Biological Reserve of San Francisco was monitored. First, we performed non-metric multidimensional analyses, and afterwards, we looked for correlations between plot altitude and characteristics of the forest (basal area, the number of species, the number of trees ≥20 cm diameter at breast height, per hectare, the forest canopy opening) were associated. To determine which characteristics significantly influence the separation of forest “communities”, we used a multivariate canonical correspondence analysis (CCA). Finally, we carried out the “Four Corners” analysis, combining abundance matrices, traits and environmental variables. We confirmed that the altitude and some associated characteristics are the key factors for the formation of two forest types. In addition, we determined that the inclusion of species functional traits confirms the separation of forest communities, and that elevation and its associated environmental variables function over relatively small areas and scales.
Infection with SARS-CoV-2 Is Associated with Elevated Levels of IP-10, MCP-1, and IL-13 in Sepsis Patients
Authors: Eichhorn Tanja , Huber Silke , Weiss René , Ebeyer-Masotta Marie , Lauková Lucia , Emprechtinger Robert , Bellmann-Weiler Rosa , Lorenz Ingo , Martini Judith , Pirklbauer Markus , Orth-Höller Dorothea , Würzner Reinhard , Weber Viktoria
Published: March 2023

Immunothrombosis, an excessive inflammatory response with simultaneous overactivation of the coagulation system, is a central pathomechanism in sepsis and COVID-19. It is associated with cellular activation, vascular damage, and microvascular thrombosis, which can lead to multiple organ failure and death. Here, we characterized factors related to immunothrombosis in plasma samples from 78 sepsis patients. In the course of routine clinical testing, SARS-CoV-2 was detected in 14 of these patients. Viral infection was associated with a higher mortality. Both, COVID-19 negative and COVID-19 positive sepsis patients showed increased levels of effectors of immunothrombosis, including platelet factor 4, D-dimer, nucleosomes, citrullinated histone H3, high mobility group box-1 protein, as well as phosphatidylserine-expressing platelet-derived extracellular vesicles, compared to healthy controls (n = 25). Using a 27-plex cytokine bead array, we found that Interleukin (IL)-1ra, IL-6, IL-8, IL-13, tumor necrosis factor (TNF)-α, interferon inducible protein (IP)-10, monocyte chemotactic protein (MCP)-1, macrophage inflammatory protein (MIP)-1α, and granulocyte-colony stimulating factor (G-CSF) were elevated in both, COVID-19 negative and COVID-19 positive sepsis patients, as compared to healthy controls. SARS-CoV-2 infection was associated with elevated levels of IP-10, MCP-1, and IL-13, while all other mediators widely overlapped between COVID-19 negative and COVID-19 positive patients.
Using an Artificial Intelligence Approach to Predict the Adverse Effects and Prognosis of Tuberculosis
Authors: Liao Kuang-Ming , Liu Chung-Feng , Chen Chia-Jung , Feng Jia-Yih , Shu Chin-Chung , Ma Yu-Shan
Published: March 2023

Background: Tuberculosis (TB) is one of the leading causes of death worldwide and a major cause of ill health. Without treatment, the mortality rate of TB is approximately 50%; with treatment, most patients with TB can be cured. However, anti-TB drug treatments may result in many adverse effects. Therefore, it is important to detect and predict these adverse effects early. Our study aimed to build models using an artificial intelligence/machine learning approach to predict acute hepatitis, acute respiratory failure, and mortality after TB treatment. Materials and Methods: Adult patients (age ≥ 20 years) who had a TB diagnosis and received treatment from January 2004 to December 2021 were enrolled in the present study. Thirty-six feature variables were used to develop the predictive models with AI. The data were randomly stratified into a training dataset for model building (70%) and a testing dataset for model validation (30%). These algorithms included XGBoost, random forest, MLP, light GBM, logistic regression, and SVM. Results: A total of 2248 TB patients in Chi Mei Medical Center were included in the study; 71.7% were males, and the other 28.3% were females. The mean age was 67.7 ± 16.4 years. The results showed that our models using the six AI algorithms all had a high area under the receiver operating characteristic curve (AUC) in predicting acute hepatitis, respiratory failure, and mortality, and the AUCs ranged from 0.920 to 0.766, 0.884 to 0.797, and 0.834 to 0.737, respectively. Conclusions: Our AI models were good predictors and can provide clinicians with a valuable tool to detect the adverse prognosis in TB patients early.
Next-Generation Sequencing Analysis of Pancreatic Cancer Using Residual Liquid Cytology Specimens from Endoscopic Ultrasound—Guided Fine-Needle Biopsy: A Prospective Comparative Study with Tissue Specimens
Authors: Iwaya Hiromichi , Tanimoto Akihide , Toyodome Koshiro , Kojima Issei , Hinokuchi Makoto , Tanoue Shiroh , Hashimoto Shinichi , Kawahira Machiko , Arima Shiho , Kanmura Shuji , Akahane Toshiaki , Higashi Michiyo , Suzuki Shinsuke , Ueno Shinichi , Ohtsuka Takao , Ido Akio
Published: March 2023

This study evaluated the feasibility and clinical utility of liquid-based cytology (LBC) specimens via endoscopic ultrasound–guided fine-needle biopsy (EUS-FNB) for next-generation sequencing (NGS) of pancreatic cancer (PC). We prospectively evaluated the performance of DNA extraction and NGS using EUS-FNB samples obtained from PC. Thirty-three consecutive patients with PC who underwent EUS-FNB at our hospital were enrolled. DNA samples were obtained from 96.8% of the patients. When stratified with a variant allele frequency (VAF) > 10% tumor burden, the NGS success rate was 76.7% (n = 23) in formalin-fixed paraffin-embedded (FFPE), 83.3% (n = 25) in LBC, and 76.7% (n = 23) in frozen samples. The overall NGS success rate was 86.7% (n = 26) using FFPE, LBC, or frozen samples. The detection rates for the main mutated genes were as follows: 86.7% for KRAS, 73.3% for TP53, 66.7% for CDKN2A, 36.7% for SMAD4, and 16.7% for ARID1A. LBC had the highest median value of VAF (23.5%) for KRAS and TP53. PC mutation analysis using NGS was successfully performed using LBC compared with FFPE and frozen samples. This approach provides an alternative and affordable source of molecular testing materials.
Therapeutic Management and Prognostic Factors for Ovarian Malignant Tumours in Adolescents: A Comprehensive Review of Current Guidelines
Authors: Margioula-Siarkou Chrysoula , Petousis Stamatios , Margioula-Siarkou Georgia , Mavromatidis George , Chatzinikolaou Fotios , Hatzipantelis Emmanouel , Guyon Frédéric , Dinas Konstantinos
Published: March 2023

Background: Ovarian malignant tumours are rarely diagnosed in adolescents but may have a significant impact on their survival, future fertility and quality of life. The management of such cases is rather complex and requires expertise and careful planning according to scarce existing evidence and recommendations. Objective: The aim of this study was to review and compare recommendations from published guidelines regarding the diagnosis, prognosis and treatment of malignant ovarian tumours in adolescents. Evidence acquisition: A comparative descriptive/narrative review of guidelines issued by L’Observatoire des Tumeurs Malignes Rares Gynécologiques, the British Society for Paediatric & Adolescent Gynaecology, the European Society for Medical Oncology, the European Society of Gynecological Oncology-European Society for Paediatric Oncology and the European Cooperative Study Group for Pediatric Rare Tumors was conducted. Results: All guidelines recommend a thorough diagnostic work-up, consisting of both imaging tests and serum tumour marker measurement, as well as the use of immunohistochemical methods to confirm the diagnosis and complete surgical staging prior to constructing the treatment plan. There is a lack of recommendations regarding the assessment of prognostic factors, with only one guideline providing detailed information. Treatment strategies, as suggested by the majority of guidelines and with only a few discrepancies between them, should include both surgery and adjuvant therapies, mainly chemotherapy, with great emphasis on fertility preservation when it is considered oncologically safe and on the significance of regular and long-term follow-up. Conclusions: There is a significant degree of agreement among recommendations of existing guidelines. The reported differences, although limited, highlight the need for the adoption of an international consensus in order to further improve the management of adolescent ovarian cancer.
Performance of Quantum Heat Engines Enhanced by Adiabatic Deformation of Trapping Potential
Authors: Xiao Yang , Li Kai , He Jizhou , Wang Jianhui
Published: March 2023

We present a quantum Otto engine model alternatively driven by a hot and a cold heat reservoir and consisting of two isochoric and two adiabatic strokes, where the adiabatic expansion or compression is realized by adiabatically changing the shape of the potential. Here, we show that such an adiabatic deformation may alter operation mode and enhance machine performance by increasing output work and efficiency, even with the advantage of decreasing work fluctuations. If the heat engine in the sudden limit operates under maximal power by optimizing the control parameter, the efficiency shows certain universal behavior, η*=ηC/2+ηC2/8+O(ηC3), where ηC=1−βhr/βcr is the Carnot efficiency, with βhr(βcr) being the inverse temperature of the hot (cold) reservoir. However, such efficiency under maximal power can be produced by our machine model in the regimes where the machine without adiabatic deformation can only operate as a heater or a refrigerator.
PLDP-FL: Federated Learning with Personalized Local Differential Privacy
Authors: Shen Xiaoying , Jiang Hang , Chen Yange , Wang Baocang , Gao Le
Published: March 2023

As a popular machine learning method, federated learning (FL) can effectively solve the issues of data silos and data privacy. However, traditional federated learning schemes cannot provide sufficient privacy protection. Furthermore, most secure federated learning schemes based on local differential privacy (LDP) ignore an important issue: they do not consider each client’s differentiated privacy requirements. This paper introduces a perturbation algorithm (PDPM) that satisfies personalized local differential privacy (PLDP), resolving the issue of inadequate or excessive privacy protection for some participants due to the same privacy budget set for all clients. The algorithm enables clients to adjust the privacy parameters according to the sensitivity of their data, thus allowing the scheme to provide personalized privacy protection. To ensure the privacy of the scheme, we have conducted a strict privacy proof and simulated the scheme on both synthetic and real data sets. Experiments have demonstrated that our scheme is successful in producing high-quality models and fulfilling the demands of personalized privacy protection.
Comparative Analysis of Preference in Contemporary and Earlier Texts Using Entropy Measures
Authors: Mohseni Mahdi , Redies Christoph , Gast Volker
Published: March 2023

Research in computational textual aesthetics has shown that there are textual correlates of preference in prose texts. The present study investigates whether textual correlates of preference vary across different time periods (contemporary texts versus texts from the 19th and early 20th centuries). Preference is operationalized in different ways for the two periods, in terms of canonization for the earlier texts, and through sales figures for the contemporary texts. As potential textual correlates of preference, we measure degrees of (un)predictability in the distributions of two types of low-level observables, parts of speech and sentence length. Specifically, we calculate two entropy measures, Shannon Entropy as a global measure of unpredictability, and Approximate Entropy as a local measure of surprise (unpredictability in a specific context). Preferred texts from both periods (contemporary bestsellers and canonical earlier texts) are characterized by higher degrees of unpredictability. However, unlike canonicity in the earlier texts, sales figures in contemporary texts are reflected in global (text-level) distributions only (as measured with Shannon Entropy), while surprise in local distributions (as measured with Approximate Entropy) does not have an additional discriminating effect. Our findings thus suggest that there are both time-invariant correlates of preference, and period-specific correlates.
Quantum Chaos and Level Dynamics
Authors: Zakrzewski Jakub
Published: March 2023

We review the application of level dynamics to spectra of quantally chaotic systems. We show that the statistical mechanics approach gives us predictions about level statistics intermediate between integrable and chaotic dynamics. Then we discuss in detail different statistical measures involving level dynamics, such as level avoided-crossing distributions, level slope distributions, or level curvature distributions. We show both the aspects of universality in these distributions and their limitations. We concentrate in some detail on measures imported from the quantum information approach such as the fidelity susceptibility, and more generally, geometric tensor matrix elements. The possible open problems are suggested.
Multiscale Correlation Analysis between Wind Direction and Meteorological Parameters in Guadeloupe Archipelago
Authors: Plocoste Thomas , Sankaran Adarsh
Published: March 2023

In this paper, the wind direction (WD) behaviour with respect to the variability of other meteorological parameters (i.e., rainfall (R), temperature (T), relative humidity (Rh), solar radiation (SR) and wind speed (U)) was studied in a multi-scale way. To carry out this study, the Hilbert–Huang transform (HHT) framework was applied to a Guadeloupe archipelago dataset from 2016 to 2021. Thus, the time-dependent intrinsic correlation (TDIC) analysis based on multivariate empirical mode decomposition (MEMD) was performed. For time scales between ∼3 days and ∼7 months, the localized positive and negative correlations between WD and the meteorological parameters have been identified. The alternation between these correlations was more significant for T and Rh. With regard to SR and U, there was a dominance of a negative correlation with WD. We assumed that the micro-climate previously identified in the literature for the study area plays a key role in these behaviours. A strong positive correlation between WD and R was found from ∼7 months to ∼2.5 years. At the annual scale, the relationships between WD and all meteorological parameters were long range and no significant transition in correlation was observed showing the impact of the Earth’s annual cycle on climatic variables. All these results clearly show the influence of R-T-Rh-SR-U on WD over different time scales.
Hardware Emulation of Step-Down Converter Power Stages for Digital Control Design
Authors: Kirei Botond Sandor , Farcas Calin-Adrian , Chira Cosmin , Ilie Ionut-Alin , Neag Marius
Published: March 2023

This paper proposes a methodology of delivering the emulation hardware of several step-down converter power stages. The generalized emulator design methodology follows these steps: first, the power stage is described using an ordinary differential equation system; second, the ordinary differential equation system is solved using Euler’s method, and thus an accurate time-domain model is obtained; next, this time-domain model can be described using either general-purpose programming language (MATLAB, C, etc.) or hardware description language (VHDL, Verilog, etc.). As a result, the emulator has been created; validation of the emulator may be carried out by comparing it to SPICE transient simulations. Finally, the validated emulator can be implemented on the preferred target technology, either in a general-purpose processor or a field programmable gate array. As the emulator relies on the ordinary differential equation system of the power stage, it has better behavioral accuracy than the emulators based on average state space models. Moreover, this paper also presents the design methodology of a manually tuned proportional–integrative–derivative controller deployed on a field programmable gate array.
Object Detection Algorithm of UAV Aerial Photography Image Based on Anchor-Free Algorithms
Authors: Hu Qi , Li Lin , Duan Jin , Gao Meiling , Liu Gaotian , Wang Zhiyuan , Huang Dandan
Published: March 2023

Aiming at the problems of the difficult extraction of small target feature information, complex background, and variable target scale in unmanned aerial vehicle (UAV) aerial photography images. In this paper, an anchor-free target detection algorithm based on fully convolutional one-stage object detection (FCOS) for UAV aerial photography images is proposed. For the problem of complex backgrounds, the global context module is introduced in the ResNet50 network, which is combined with feature pyramid networks (FPN) as the backbone feature extraction network to enhance the feature representation of targets in complex backgrounds. To address the problem of the difficult detection of small targets, an adaptive feature balancing sub-network is designed to filter the invalid information generated at all levels of feature fusion, strengthen multi-layer features, and improve the recognition capability of the model for small targets. To address the problem of variable target scales, complete intersection over union (CIOU) Loss is used to optimize the regression loss and strengthen the model’s ability to locate multi-scale targets. The algorithm of this paper is compared quantitatively and qualitatively on the VisDrone dataset. The experiments show that the proposed algorithm improves 4.96% on average precision (AP) compared with the baseline algorithm FCOS, and the detection speed is 35 frames per second (FPS), confirming that the algorithm has satisfactory detection performance, real-time inference speed, and has effectively improved the problem of missed detection and false detection of targets in UAV aerial images.
A Deep-Ensemble-Learning-Based Approach for Skin Cancer Diagnosis
Authors: Shehzad Khurram , Zhenhua Tan , Shoukat Shifa , Saeed Adnan , Ahmad Ijaz , Sarwar Bhatti Shahzad , Chelloug Samia Allaoua
Published: March 2023

Skin cancer is one of the widespread diseases among existing cancer types. More importantly, the detection of lesions in early diagnosis has tremendously attracted researchers’ attention. Thus, artificial intelligence (AI)-based techniques have supported the early diagnosis of skin cancer by investigating deep-learning-based convolutional neural networks (CNN). However, the current methods remain challenging in detecting melanoma in dermoscopic images. Therefore, in this paper, we propose an ensemble model that uses the vision of both EfficientNetV2S and Swin-Transformer models to detect the early focal zone of skin cancer. Hence, we considerthat the former architecture leads to greater accuracy, while the latter model has the advantage of recognizing dark parts in an image. We have modified the fifth block of the EfficientNetV2S model and have included the Swin-Transformer model. Our experiments demonstrate that the constructed ensemble model has attained a higher level of accuracy over the individual models and has also decreased the losses as compared to traditional strategies. The proposed model achieved an accuracy score of 99.10%, a sensitivity of 99.27%, and a specificity score of 99.80%.
Open-Circuit Switch Fault Diagnosis and Accommodation of a Three-Level Interleaved Buck Converter for Electrolyzer Applications
Authors: Yodwong Burin , Sikkabut Suwat , Guilbert Damien , Hinaje Melika , Phattanasak Matheepot , Kaewmanee Wattana , Vitale Gianpaolo
Published: March 2023

This article proposes a novel open-circuit switch fault diagnosis method (FDM) for a three-level interleaved buck converter (TLIBC) in a hydrogen production system based on the water electrolysis process. The control algorithm is suitably modified to ensure the same hydrogen production despite the fault. The TLIBC enables the interfacing of the power source (i.e., low-carbon energy sources) and electrolyzer while driving the hydrogen production of the system in terms of current or voltage. On one hand, the TLIBC can guarantee a continuity of operation in case of power switch failures because of its interleaved architecture. On the other hand, the appearance of a power switch failure may lead to a loss of performance. Therefore, it is crucial to accurately locate the failure in the TLIBC and implement a fault-tolerant control strategy for performance purposes. The proposed FDM relies on the comparison of the shape of the input current and the pulse width modulation (PWM) gate signal of each power switch. Finally, an experimental test bench of the hydrogen production system is designed and realized to evaluate the performance of the developed FDM and fault-tolerant control strategy for TLIBC during post-fault operation. It is implemented with a real-time control based on a MicroLabBox dSPACE (dSPACE, Paderborn, Germany) platform combined with a TI C2000 microcontroller. The obtained simulation and experimental results demonstrate that the proposed FDM can detect open-circuit switch failures in one switching period and reconfigure the control law accordingly to ensure the same current is delivered before the failure.
Nonuniform Transmission Line Model for Electromagnetic Radiation in Free Space
Authors: Xiao Gaobiao , Hu Mengxia
Published: March 2023

An equivalent nonuniform transmission line model for electromagnetic radiation in free space is developed. By properly defining a voltage and a current associated with the transverse component of the mode fields, a kind of telegrapher’s equation is derived for each spherical harmonic mode in frequency domain. Based on the equivalent distribution inductance and capacitance, the local characteristic impedance and phase velocity are derived. For each spherical mode, a cutoff spherical surface and an associated cutoff radius are introduced to separate the space into an evanescent region and a propagating region. A spherical mode field decays approximately exponentially in the evanescent region and experience local reflection in the propagating region. The proposed model may provide an intuitive illustration for the radiation process in free space.
Downlink Spectral Efficiency of Massive MIMO Systems with Mutual Coupling
Authors: Liu Yiru , Ai Bo , Zhang Jiayi
Published: March 2023

Massive multiple-input multiple-output (MIMO) is a profitable technique to greatly boost spectral efficiency, which has been embraced by the fifth-generation (5G) and sixth-generation (6G) mobile communication systems. By exploiting appropriate downlink precoding algorithms, base stations (BSs) equipped with a large number of antennas are able to provide service to multiple users as well as several cells at the same time and frequency. However, the mutual coupling effect due to the compact antenna array gives misleading results in massive MIMO communication systems. In this paper, we focus on the mutual coupling effect for massive MIMO systems with maximal ratio transmission (MRT), zero-forcing (ZF), regularize ZF (RZF), and minimum mean square error (MMSE) precoding to solve the mutual coupling problem. Additionally, we construct the closed-form expressions of the spectral efficiency (SE) to evaluate the effect of mutual coupling on system performance. Simulation results validate the effectiveness of the proposed mutual coupling effect assessment method and demonstrate the significant impacts of mutual coupling on massive MIMO system performance.
A Future with Machine Learning: Review of Condition Assessment of Structures and Mechanical Systems in Nuclear Facilities
Authors: Sandhu Harleen Kaur , Bodda Saran Srikanth , Gupta Abhinav
Published: March 2023

The nuclear industry is exploring applications of Artificial Intelligence (AI), including autonomous control and management of reactors and components. A condition assessment framework that utilizes AI and sensor data is an important part of such an autonomous control system. A nuclear power plant has various structures, systems, and components (SSCs) such as piping-equipment that carries coolant to the reactor. Piping systems can degrade over time because of flow-accelerated corrosion and erosion. Any cracks and leakages can cause loss of coolant accident (LOCA). The current industry standards for conducting maintenance of vital SSCs can be time and cost-intensive. AI can play a greater role in the condition assessment and can be extended to recognize concrete degradation (chloride-induced damage and alkali–silica reaction) before cracks develop. This paper reviews developments in condition assessment and AI applications of structural and mechanical systems. The applicability of existing techniques to nuclear systems is somewhat limited because its response requires characterization of high and low-frequency vibration modes, whereas previous studies focus on systems where a single vibration mode can define the degraded state. Data assimilation and storage is another challenging aspect of autonomous control. Advances in AI and data mining world can help to address these challenges.
Exploring the Impact of Regional Integrated Energy Systems Performance by Energy Storage Devices Based on a Bi-Level Dynamic Optimization Model
Authors: Jin Baohong , Liu Zhichao , Liao Yichuan
Published: March 2023

In the context of energy transformation, the importance of energy storage devices in regional integrated energy systems (RIESs) is becoming increasingly prominent. To explore the impact of energy storage devices on the design and operation of RIESs, this paper first establishes a bi-level dynamic optimization model with the total system cost as the optimization objective. The optimization model is used to optimize the design of three RIESs with different energy storage devices, including System 1 without an energy storage device, System 2 with a thermal energy storage (TES) device, and System 3 with TES and electrical energy storage (EES) devices. According to the design and operation results, the impact of energy storage devices on the operational performance of RIESs is analyzed. The results show that under the design conditions, energy storage devices can significantly increase the capacity of the combined heating and power units and absorption chillers in System 2 and System 3 and reduce the capacity of the ground source heat pumps and gas boilers; the impact of the TES device on System 3 is more significant. Affected by systems’ configuration, the operating cost, carbon tax, and total cost of System 2 are reduced by 2.9%, 5.5%, and 1.5% compared with System 1, respectively. The EES device can more significantly reduce the operating cost of System 3, with a reduced rate of 5.7% compared with that in System 1. However, the higher equipment cost makes the total cost reduction rate of System 3 less than that of System 1, which is 1.75%. Similar to the design conditions, under the operation conditions, the TES device can effectively reduce the carbon tax, operating cost, and total cost of System 2, while System 3 with an EES device can significantly reduce its operating cost regardless of whether the energy price changes or not. To some extent, this study systematically elucidated the impact of TES and EES devices on the optimal design and operation performance of RIESs and provided a certain reference for the configuration of energy storage devices.
Optimizing Renewable Injection in Integrated Natural Gas Pipeline Networks Using a Multi-Period Programming Approach
Authors: Ogbe Emmanuel , Almansoori Ali , Fowler Michael , Elkamel Ali
Published: March 2023

In this paper, we propose an optimization model that considers two pathways for injecting renewable content into natural gas pipeline networks. The pathways include (1) power-to-hydrogen or PtH, where off-peak electricity is converted to hydrogen via electrolysis, and (2) power-to-methane, or PtM, where carbon dioxide from different source locations is converted into renewable methane (also known as synthetic natural gas, SNG). The above pathways result in green hydrogen and methane, which can be injected into an existing natural gas pipeline network. Based on these pathways, a multi-period network optimization model that integrates the design and operation of hydrogen from PtH and renewable methane is proposed. The multi-period model is a mixed-integer non-linear programming (MINLP) model that determines (1) the optimal concentration of hydrogen and carbon dioxide in the natural gas pipelines, (2) the optimal location of PtH and carbon dioxide units, while minimizing the overall system cost. We show, using a case study in Ontario, the optimal network structure for injecting renewable hydrogen and methane within an integrated natural gas network system provides a $12M cost reduction. The optimal concentration of hydrogen ranges from 0.2 vol % to a maximum limit of 15.1 vol % across the network, while reaching a 2.5 vol % at the distribution point. This is well below the maximum limit of 5 vol % specification. Furthermore, the optimizer realized a CO2 concentration ranging from 0.2 vol % to 0.7 vol %. This is well below the target of 1% specified in the model. The study is essential to understanding the practical implication of hydrogen penetration in natural gas systems in terms of constraints on hydrogen concentration and network system costs.
Linear Model of a Turboshaft Aero-Engine Including Components Degradation for Control-Oriented Applications
Authors: Castiglione Teresa , Perrone Diego , Strafella Luciano , Ficarella Antonio , Bova Sergio
Published: March 2023

The engine fuel control system plays a crucial role in engine performance and fuel economy. Fuel control, in traditional engine control systems, is carried out by means of sensor-based control methods, which correct the fuel flow rate through correlations or scheduled parameters in order to reduce the error between a measured parameter and its desired value. In the presence of component degradation, however, the relationship between the engine measurable parameters and performance may lead to an increase in the control error. In this research, linear models for advanced control systems and for direct fuel control in the presence of components degradation are proposed, with the main objective being to directly predict and correct fuel consumption in the presence of degradation instead of adopting measurable parameters. Two techniques were adopted for model linearization: Small Perturbation and System Identification. Results showed that both models are characterized by high accuracy in predicting the output engine variables, with the mean errors between model prediction and data below 1%. The maximum errors, recorded for shaft power, were about 6% for Small Perturbation and lower than 3% for System Identification. A simple correlation between engine performance and components degradation was also demonstrated; in particular, the achieved results allow one to conclude that the Small Perturbation approach is the best candidate for controller development when a prediction of components degradation is included.
Enhancing Smart Home Design with AI Models: A Case Study of Living Spaces Implementation Review
Authors: Almusaed Amjad , Yitmen Ibrahim , Almssad Asaad
Published: March 2023

The normal development of “smart buildings,” which calls for integrating sensors, rich data, and artificial intelligence (AI) simulation models, promises to usher in a new era of architectural concepts. AI simulation models can improve home functions and users’ comfort and significantly cut energy consumption through better control, increased reliability, and automation. This article highlights the potential of using artificial intelligence (AI) models to improve the design and functionality of smart houses, especially in implementing living spaces. This case study provides examples of how artificial intelligence can be embedded in smart homes to improve user experience and optimize energy efficiency. Next, the article will explore and thoroughly analyze the thorough analysis of current research on the use of artificial intelligence (AI) technology in smart homes using a variety of innovative ideas, including smart interior design and a Smart Building System Framework based on digital twins (DT). Finally, the article explores the advantages of using AI models in smart homes, emphasizing living spaces. Through the case study, the theme seeks to provide ideas on how AI can be effectively embedded in smart homes to improve functionality, convenience, and energy efficiency. The overarching goal is to harness the potential of artificial intelligence by transforming how we live in our homes and improving our quality of life. The article concludes by discussing the unresolved issues and potential future research areas on the usage of AI in smart houses. Incorporating AI technology into smart homes benefits homeowners, providing excellent safety and convenience and increased energy efficiency.
Investigation of Smart Grid Operation Modes with Electrical Energy Storage System
Authors: Miroshnyk Oleksandr , Moroz Oleksandr , Shchur Taras , Chepizhnyi Andrii , Qawaqzeh Mohamed , Kocira Sławomir
Published: March 2023

The paper considers the issues of maintaining an equality of flow in generated and consumed electric energy in an electric network incorporating an electric power storage system. An analysis of ways to equalize the energy and power balance was carried out, and the advantages of using electricity storage systems in electrical networks was assessed. Upon simulation using the Power Factory program, we noted that, after switching on the load, a transient process occurs, characterized by a jump in active power, which was caused by the need for time to initiate the electric energy storage system. However, immediately after this, the process of issuing the accumulated energy to the electrical network and compensating for energy consumption began. Moreover, when the load was disconnected, there is a certain dip in the active power curve and a further increase in consumption. This was found to be due to the transition of the electricity storage system to the modes of energy storage and battery charging. As a result of this simulation, data on the charging and discharging time of the electricity storage system were obtained. The studies show that the use of electricity storage systems in electrical networks allows for the stable operation of all main generators, and thus increases the safety and reliability of the entire system.
Real-Time Integrated Energy Management Strategy Applied to Fuel Cell Hybrid Systems
Authors: Matignon Matthieu , Azib Toufik , Mcharek Mehdi , Chaibet Ahmed , Ceschia Adriano
Published: March 2023

Integrating hydrogen fuel cell systems (FCS) remains challenging in the expanding electric vehicle market. One of the levers to meet this challenge is the relevance of energy supervisors. This paper proposes an innovative energy management strategy (EMS) based on the integrated EMS (iEMS) concept. It uses a nested approach combining the best of the three EMS categories (optimization-based (OBS), rules-based (RBS), and learning-based (LBS) strategies) to overcome the real-time operating condition limitations of the fuel cell hybrid electric vehicle (FCHEV). Through a fuel cell/battery hybrid architecture, the purpose is to improve hydrogen consumption and manage the battery state of charge (SOC) under real-time driving conditions. The proposed iEMS approach is based on an OBS with optimal control to make the energy-optimal decision. However, it requires the adaptations of real-time operating conditions and a dynamic SOC horizon management. These requirements are supported by combining an RBS based on expert and fuzzy rules to compute the SOC target on each sliding window and an LBS based on fuzzy C-mean clustering to enhance the cooperative environment data processing and adapt it to the FHCEV topology. Our approach obtained simple and realistic system behaviors while having an acceptable computing time suitable for real time constraint. It was then designed and validated using a 27-h real-time measured database. The results show the effectiveness of the proposed iEMS concept with an excellent performance close to the optimal offline strategy (an under 2% consumption gap).