bluuebunny/crossref_metadata_2025 huggingface dataset:
Multicenter 18F-PI-2620 PET for In Vivo Braak Staging of Tau Pathology in Alzheimer’s Disease
Authors: Rullmann Michael , Brendel Matthias , Schroeter Matthias L. , Saur Dorothee , Levin Johannes , Perneczky Robert G. , Tiepolt Solveig , Patt Marianne , Mueller Andre , Villemagne Victor L. , Classen Joseph , Stephens Andrew W. , Sabri Osama , Barthel Henryk ,   on behalf of the German Imaging Initiative for Tauopathies (GII4T)
Published: March 2022

Tau aggregates accumulate in the Alzheimer’s disease (AD) brain according to the established Braak staging scheme and spread from transentorhinal over limbic regions to the neocortex. To impact the management of AD patients, an in vivo tool for tau Braak staging is needed. First-generation tau tracers have limited performance in detecting early stages of tau. Therefore, we tested the corresponding capability of the next-generation tau tracer, 18F-PI-2620. We analyzed 18F-PI-2620 multicenter PET data from 37 beta-amyloid-positive AD dementia patients and those from 26 healthy controls. We applied kinetic modeling of the 0–60 min p.i. PET data using MRTM2 with the lower cerebellum as the reference region to extract Braak stage-dependent distribution volume ratios, whereas controls were used to define Braak stage PET positivity thresholds. Stage-dependent PET positivity widely followed the Braak scheme (except Braak stage III) presenting descending frequency of PET positivity from Braak I (43%), II (38%), III (49%), IV (35%), V (30%) to VI (14%). A strictly hierarchical model was met by 64% of AD dementia cases. Nineteen percent showed a hippocampal sparing tauopathy pattern. Thus, we could assign 87% to the six-stage hierarchical Braak model including tauopathy variants. 18F-PI-2620 PET appears to be able to perform Braak tau staging of AD in vivo.
Biomarkers Analysis and Clinical Manifestations in Comorbid Creutzfeldt–Jakob Disease: A Retrospective Study in 215 Autopsy Cases
Authors: Jankovska Nikol , Rusina Robert , Keller Jiri , Kukal Jaromir , Bruzova Magdalena , Parobkova Eva , Olejar Tomas , Matej Radoslav
Published: March 2022

Creutzfeldt–Jakob disease (CJD), the most common human prion disorder, may occur as “pure” neurodegeneration with isolated prion deposits in the brain tissue; however, comorbid cases with different concomitant neurodegenerative diseases have been reported. This retrospective study examined correlations of clinical, neuropathological, molecular-genetic, immunological, and neuroimaging biomarkers in pure and comorbid CJD. A total of 215 patients have been diagnosed with CJD during the last ten years by the Czech National Center for Prion Disorder Surveillance. Data were collected from all patients with respect to diagnostic criteria for probable CJD, including clinical description, EEG, MRI, and CSF findings. A detailed neuropathological analysis uncovered that only 11.16% were “pure” CJD, while 62.79% had comorbid tauopathy, 20.47% had Alzheimer’s disease, 3.26% had frontotemporal lobar degeneration, and 2.33% had synucleinopathy. The comorbid subgroup analysis revealed that tauopathy was linked to putaminal hyperintensity on MRIs, and AD mainly impacted the age of onset, hippocampal atrophy on MRIs, and beta-amyloid levels in the CSF. The retrospective data analysis found a surprisingly high proportion of comorbid neuropathologies; only 11% of cases were verified as “pure” CJD, i.e., lacking hallmarks of other neurodegenerations. Comorbid neuropathologies can impact disease manifestation and can complicate the clinical diagnosis of CJD.
Immunosuppressive Signaling Pathways as Targeted Cancer Therapies
Authors: Setlai Botle Precious , Hull Rodney , Bida Meshack , Durandt Chrisna , Mulaudzi Thanyani Victor , Chatziioannou Aristotelis , Dlamini Zodwa
Published: March 2022

Immune response has been shown to play an important role in defining patient prognosis and response to cancer treatment. Tumor-induced immunosuppression encouraged the recent development of new chemotherapeutic agents that assists in the augmentation of immune responses. Molecular mechanisms that tumors use to evade immunosurveillance are attributed to their ability to alter antigen processing/presentation pathways and the tumor microenvironment. Cancer cells take advantage of normal molecular and immunoregulatory machinery to survive and thrive. Cancer cells constantly adjust their genetic makeup using several mechanisms such as nucleotide excision repair as well as microsatellite and chromosomal instability, thus giving rise to new variants with reduced immunogenicity and the ability to continue to grow without restrictions. This review will focus on the central molecular signaling pathways involved in immunosuppressive cells and briefly discuss how cancer cells evade immunosurveillance by manipulating antigen processing cells and related proteins. Secondly, the review will discuss how these pathways can be utilized for the implementation of precision medicine and deciphering drug resistance.
Intra-Articular Injections of Autologous Adipose Tissue or Platelet-Rich Plasma Comparably Improve Clinical and Functional Outcomes in Patients with Knee Osteoarthritis
Authors: Kaszyński Jakub , Bąkowski Paweł , Kiedrowski Bartosz , Stołowski Łukasz , Wasilewska-Burczyk Anna , Grzywacz Kamilla , Piontek Tomasz
Published: March 2022

The use of biologic therapies for the management of knee osteoarthritis (OA) has largely increased in recent years. The purpose of this study was to evaluate the efficiency and the therapeutic potential of platelet-rich plasma (PRP) and autologous adipose tissue (AAT) injections as a treatment for knee OA. Sixty participants were enrolled in the study: 20 healthy ones and 40 with minimal to moderate knee OA (KL I-III). The OA patients were randomly assigned either to the PRP or to the AAT group. The PRP samples showed a low expression level of NF-κB-responsive gene CCL5 and high expression levels of classic inflammatory and TNF-l INF responses. The AAT injection product was prepared using a Lipogems device, and its regenerative potential as well as the ability for expansion of mesenchymal stem cells were tested in the cell culture conditions. The patient assessments were carried out five times. Significant improvement was observed regardless of the treatment method in the VAS, KOOS, WOMAC and IKDC 2000 subjective evaluations as well as in the functional parameters. Intra-articular injections of AAT or PRP improved pain, symptoms, quality of life and functional capacity with a comparable effectiveness in the patients with mild to moderate knee osteoarthritis.
Targeting CDK4/6 for Anticancer Therapy
Authors: Qi Jiating , Ouyang Zhuqing
Published: March 2022

Cyclin-dependent kinase 4/6 (CDK4/6) are key regulators of the cell cycle and are deemed as critical therapeutic targets of multiple cancers. Various approaches have been applied to silence CDK4/6 at different levels, i.e., CRISPR to knock out at the DNA level, siRNA to inhibit translation, and drugs that target the protein of interest. Here we summarize the current status in this field, highlighting the mechanisms of small molecular inhibitors treatment and drug resistance. We describe approaches to combat drug resistance, including combination therapy and PROTACs drugs that degrade the kinases. Finally, critical issues and perspectives in the field are outlined.
Bête Noire of Chemotherapy and Targeted Therapy: CAF-Mediated Resistance
Authors: De Pradip , Aske Jennifer , Sulaiman Raed , Dey Nandini
Published: March 2022

In tumor cells’ struggle for survival following therapy, they resist treatment. Resistance to therapy is the outcome of well-planned, highly efficient adaptive strategies initiated and utilized by these transformed tumor cells. Cancer cells undergo several reprogramming events towards adapting this opportunistic behavior, leading them to gain specific survival advantages. The strategy involves changes within the transformed tumors cells as well as in their neighboring non-transformed extra-tumoral support system, the tumor microenvironment (TME). Cancer-Associated Fibroblasts (CAFs) are one of the components of the TME that is used by tumor cells to achieve resistance to therapy. CAFs are diverse in origin and are the most abundant non-transformed element of the microenvironment in solid tumors. Cells of an established tumor initially play a direct role in the establishment of the CAF population for its own microenvironment. Like their origin, CAFs are also diverse in their functions in catering to the pro-tumor microenvironment. Once instituted, CAFs interact in unison with both tumor cells and all other components of the TME towards the progression of the disease and the worst outcome. One of the many functions of CAFs in influencing the outcome of the disease is their participation in the development of resistance to treatment. CAFs resist therapy in solid tumors. A tumor–CAF relationship is initiated by tumor cells to exploit host stroma in favor of tumor progression. CAFs in concert with tumor cells and other components of the TME are abettors of resistance to treatment. Thus, this liaison between CAFs and tumor cells is a bête noire of therapy. Here, we portray a comprehensive picture of the modes and functions of CAFs in conjunction with their role in orchestrating the development of resistance to different chemotherapies and targeted therapies in solid tumors. We investigate the various functions of CAFs in various solid tumors in light of their dialogue with tumor cells and the two components of the TME, the immune component, and the vascular component. Acknowledgment of the irrefutable role of CAFs in the development of treatment resistance will impact our future strategies and ability to design improved therapies inclusive of CAFs. Finally, we discuss the future implications of this understanding from a therapeutic standpoint and in light of currently ongoing and completed CAF-based NIH clinical trials.
Novel Perspectives in Immune Checkpoint Inhibitors and the Management of Non-Alcoholic Steatohepatitis-Related Hepatocellular Carcinoma
Authors: Chan Landon L. , Chan Stephen L.
Published: March 2022

Immune checkpoint inhibitors have revolutionised the systemic treatment of advanced hepatocellular carcinoma. Although phase III trials, testing single agent nivolumab and pembrolizumab, failed to meet their primary endpoints, the combination of atezolizumab and bevacizumab has demonstrated a remarkable objective response and unprecedented survival benefits, replacing sorafenib as the standard first-line treatment for advanced hepatocellular carcinoma. Despite these successes observed in immune checkpoint inhibitors in the management of advanced hepatocellular carcinoma, not all patients responded to treatment, which has led to the search of risk factors and biomarkers that could predict the response to immune checkpoint inhibitors. Recent translational studies have begun to shed light on the impact of an underlying liver disease, namely NASH, which might affect the response to immune checkpoint inhibitors. In addition, antidrug-antibody and gene expression assays have demonstrated promises in predicting the response to immune checkpoint inhibitors. In this article, we will provide an overview of the use of ICI in the management of advanced HCC, review the evidence that surrounds the recent controversy regarding NASH-HCC, and discuss potential biomarkers that predict the response to immune checkpoint inhibitors.
Is There a Role for Epigenetic Therapies in Modulating DNA Damage Repair Pathways to Enhance Chemotherapy and Overcome Drug Resistance?
Authors: Garner Ian Matthew , Brown Robert
Published: March 2022

Epigenetic therapies describe drug molecules such as DNA methyltransferase, histone methyltransferase and histone acetylase/deacetylase inhibitors, which target epigenetic mechanisms such as DNA methylation and histone modifications. Many DNA damage response (DDR) genes are epigenetically regulated in cancer leading to transcriptional silencing and the loss of DNA repair capacity. Epigenetic marks at DDR genes, such as DNA methylation at gene promoters, have the potential to be used as stratification biomarkers, identifying which patients may benefit from particular chemotherapy treatments. For genes such as MGMT and BRCA1, promoter DNA methylation is associated with chemosensitivity to alkylating agents and platinum coordination complexes, respectively, and they have use as biomarkers directing patient treatment options. In contrast to epigenetic change leading to chemosensitivity, DNA methylation of DDR genes involved in engaging cell death responses, such as MLH1, are associated with chemoresistance. This contrasting functional effect of epigenetic modification on chemosensitivity raises challenges in using DNA-demethylating agents, and other epigenetic approaches, to sensitise tumours to DNA-damaging chemotherapies and molecularly targeted agents. Demethylation of MGMT/BRCA1 could lead to drug resistance whereas demethylation of MLH1 could sensitise cells to chemotherapy. Patient selection based on a solid understanding of the disease pathway will be one means to tackle these challenges. The role of epigenetic modification of DDR genes during tumour development, such as causing a mutator phenotype, has different selective pressures and outcomes compared to epigenetic adaptation during treatment. The prevention of epigenetic adaptation during the acquisition of drug resistance will be a potential strategy to improve the treatment of patients using epigenetic therapies.
Who Knows? Information Received, and Knowledge about, Cancer, Treatment and Late Effects in a National Cohort of Long-Term Childhood, Adolescent and Young Adult Cancer Survivors
Authors: Gianinazzi Micol E. , Kiserud Cecilie E. , Ruud Ellen , Lie Hanne C.
Published: March 2022

Background: Knowledge of medical history and late effects is central in modern survivorship management, especially for long-term childhood, adolescent and young adult cancer survivors’ (CAYACS) with long life expectancy rates and high risks of late effects. Identifying information and knowledge gaps is, therefore, important. As part of the population-based NOR-CAYACS study, we investigated the following: (1) written information received about their disease and treatment, and any information about late effects; (2) satisfaction with this information and associated factors; (3) knowledge about late effects and factors associated with low knowledge of specific late effects. Material and methods: A questionnaire-based survey (Nor-CAYACS) was mailed to 5361 CAYACS (childhood cancers, breast and colorectal cancer, acute lymphatic leukemia, non-Hodgkin lymphoma and malignant melanoma) identified by the Cancer Registry of Norway (CRN). Of these, 2018 answered questions about disease and late effects information and knowledge. Exposure variables were extracted from the questionnaire and CRN. Unfortunately, it was not possible to stratify by treatment in the analyses. We ran descriptive statistics for comparisons and logistic regressions to identify factors associated with outcomes of interest. Results: Overall, 50% to 60% of survivors reported not having received written information about their disease and treatment, or any information about late effects. There was a large variation in reported knowledge across 17 late effects. Lower levels of knowledge were associated with male sex, lower education and poorer health literacy in multivariable regression models. Conclusions: Knowledge of cancer history and risks of late effects is essential for effective self-management, yet significant information and knowledge gaps were reported in this population-based sample of long-term CAYACS. Systematic approaches to making (up-to-date) information available to long-term survivors are needed to ensure that information does not get lost in medical and life transitions.
Assessing the Association of Sodium, Potassium Intake and Sodium/Potassium Ratio on Blood Pressure and Central Adiposity Measurements amongst Ellisras Undernourished, Rural Children Aged 5–13 Years: South Africa
Authors: Raphadu Thato Tshepo , Matshipi Moloko , Mphekgwana Peter Modupi , Monyeki Kotsedi Daniel
Published: March 2022

Background: Numerous studies have shown how diet, such as sodium (Na) and potassium (K) intake, is an important risk factor for non-communicable diseases (NCDs). This study aimed to assess the relationship between sodium intake, potassium intake; and sodium/potassium ratio with blood pressure (BP) and abdominal obesity amongst Ellisras rural children. Method: In this cross-sectional study, data on dietary intake of sodium and potassium were collected using a 24-h recall questionnaire from a total of 765 participants, aged 5–13 years. Blood pressure and anthropometric measurements were also collected. Generalised linear models and Pearson correlation were conducted to assess the association of sodium intake, potassium intake; and their ratio with BP, waist circumference (WC), and waist-to-height ratio (WHtR). Results: In both age groups, less than 14.9% of males and 19.8% of females consumed above the recommended adequate intake (AI) of sodium. In addition, both age groups had more than 90% of males and females who consumed below the recommended AI of potassium. Moreover, the sodium/potassium ratio was above the WHO recommended level in more than 30% of males and females. The study found a significant, weak positive correlation of sodium intake with systolic BP (SBP), diastolic BP (DBP), and with WHtR. A significant, weak positive correlation was also found between sodium/potassium ratio and WHtR. In addition, a significant association was found between potassium intake and systolic BP. Conclusion: Although our study found a notable low average intake of sodium and potassium as compared to the recommended values. There was positive correlation found between sodium intake and BP. Furthermore, a positive correlation of sodium intake and sodium/potassium ratio with WHtR was also found.
Surface Plasmon Resonance Imaging (SPRi) and Photonic Integrated Circuits (PIC) for COVID-19 Severity Monitoring
Authors: Steglich Patrick , Schasfoort Richard
Published: March 2022

Direct optical detection methods such as surface plasmon resonance imaging (SPRi) and photonic-integrated-circuits (PIC)-based biosensors provide a fast label-free detection of COVID-19 antibodies in real-time. Each technology, i.e., SPRi and PIC, has advantages and disadvantages in terms of throughput, miniaturization, multiplexing, system integration, and cost-effective mass production. However, both technologies share similarities in terms of sensing mechanism and both can be used as high-content diagnostics at or near to point of care, where the analyte is not just quantified but comprehensively characterized. This is significant because recent results suggest that not only the antibody concentration of the three isotypes IgM, IgG, and IgA but also the strength of binding (affinity) gives an indication of potential COVID-19 severity. COVID-19 patients with high titers of low affinity antibodies are associated with disease severity. In this perspective, we provide some insights into how SPR and PIC technologies can be effectively combined and complementarily used for a comprehensive COVID-19 severity monitoring. This opens a route toward an immediate therapy decision to provide patients a treatment in an early stage of the infection, which could drastically lowers the risk of a severe disease course.
Red-Backed Shrike Lanius collurio Whole-Genome Sequencing Reveals Population Genetic Admixture
Authors: Pârâu Liviu G. , Wang Erjia , Wink Michael
Published: March 2022

The Red-backed Shrike (Lanius collurio) is a medium-sized, carnivorous passerine, occurring throughout the western Palearctic. As with numerous other bird species, its numbers are declining, mainly due to anthropogenic factors. Therefore, revealing the population structure and genetic diversity is paramount in ensuring the survival of the species. However, until present, only mitochondrial DNA has been targeted to reveal the genetic structure of the species. These studies suggested a panmictic population structure. In this study, we employed next-generation sequencing of 88 Red-backed Shrikes from 11 countries and used single nucleotide polymorphisms (SNPs)) to investigate the population structure. Even with such high-resolution DNA data, we found considerable genetic variability, but our results indicate no genetic structure in the Red-backed Shrike, suggesting a panmictic population. Migrant birds from Israel and Kuwait could not be attributed to breeding populations. Panmixia is the genetic legacy of the widespread and continuous distribution of the species, high locomotion capacities, and, most importantly, the numerous ice ages from the past few million years, which forced various populations to retract to refugia and expand their ranges several times, and to interbreed both in the glacial refugia and during warm periods in Eurasia.
The Ecological Role of Salamanders as Prey and Predators
Authors: Salvidio Sebastiano
Published: March 2022

Salamanders comprise more than 700 living species, mainly found in the Northern hemisphere (i [...]
A Non-Invasive Interpretable Diagnosis of Melanoma Skin Cancer Using Deep Learning and Ensemble Stacking of Machine Learning Models
Authors: Alfi Iftiaz A. , Rahman Md. Mahfuzur , Shorfuzzaman Mohammad , Nazir Amril
Published: March 2022

A skin lesion is a portion of skin that observes abnormal growth compared to other areas of the skin. The ISIC 2018 lesion dataset has seven classes. A miniature dataset version of it is also available with only two classes: malignant and benign. Malignant tumors are tumors that are cancerous, and benign tumors are non-cancerous. Malignant tumors have the ability to multiply and spread throughout the body at a much faster rate. The early detection of the cancerous skin lesion is crucial for the survival of the patient. Deep learning models and machine learning models play an essential role in the detection of skin lesions. Still, due to image occlusions and imbalanced datasets, the accuracies have been compromised so far. In this paper, we introduce an interpretable method for the non-invasive diagnosis of melanoma skin cancer using deep learning and ensemble stacking of machine learning models. The dataset used to train the classifier models contains balanced images of benign and malignant skin moles. Hand-crafted features are used to train the base models (logistic regression, SVM, random forest, KNN, and gradient boosting machine) of machine learning. The prediction of these base models was used to train level one model stacking using cross-validation on the training set. Deep learning models (MobileNet, Xception, ResNet50, ResNet50V2, and DenseNet121) were used for transfer learning, and were already pre-trained on ImageNet data. The classifier was evaluated for each model. The deep learning models were then ensembled with different combinations of models and assessed. Furthermore, shapely adaptive explanations are used to construct an interpretability approach that generates heatmaps to identify the parts of an image that are most suggestive of the illness. This allows dermatologists to understand the results of our model in a way that makes sense to them. For evaluation, we calculated the accuracy, F1-score, Cohen’s kappa, confusion matrix, and ROC curves and identified the best model for classifying skin lesions.
Cooperative Multi-UAV Task Assignment in Cross-Regional Joint Operations Considering Ammunition Inventory
Authors: Yu Xinyong , Gao Xiaohua , Wang Lei , Wang Xinwei , Ding Yu , Lu Chen , Zhang Sheng
Published: March 2022

As combat missions become increasingly complex in both space and time, cross-regional joint operations (CRJO) is becoming an overwhelming trend in modern air warfare. How to allocate resources and missions prior to the operation becomes a central issue to improve the combat efficiency. In this paper, we focus on the cooperative mission planning of multiple heterogeneous unmanned aerial vehicles (UAVs) in a CRJO. A multi-objective optimization problem is presented with the aim of minimizing the makespan while maximizing the value expectation obtained. Moreover, it is not mandatory for each UAV to return exactly to the base which it takes off. Furthermore, in addition to the constraints commonly found in UAV mission assignment problems, the ammunition inventory at each base is also taken into account. To solve such a problem, we developed an improved genetic algorithm (IGA) with a novel chromosome encoding format. It can determine the number of attacks on a given target based on the expectations obtained, rather than being predetermined. Specifically, an efficient logic-based unlocking mechanism is designed for the crossover and mutation operations in the algorithm. Simulation results show that the developed IGA can efficiently solve the considered problem. Through numerical experimental comparisons, the algorithm proposed in this work is superior to other existing IGA-like algorithms in terms of computational efficiency.
Speaker Recognition Using Constrained Convolutional Neural Networks in Emotional Speech
Authors: Simić Nikola , Suzić Siniša , Nosek Tijana , Vujović Mia , Perić Zoran , Savić Milan , Delić Vlado
Published: March 2022

Speaker recognition is an important classification task, which can be solved using several approaches. Although building a speaker recognition model on a closed set of speakers under neutral speaking conditions is a well-researched task and there are solutions that provide excellent performance, the classification accuracy of developed models significantly decreases when applying them to emotional speech or in the presence of interference. Furthermore, deep models may require a large number of parameters, so constrained solutions are desirable in order to implement them on edge devices in the Internet of Things systems for real-time detection. The aim of this paper is to propose a simple and constrained convolutional neural network for speaker recognition tasks and to examine its robustness for recognition in emotional speech conditions. We examine three quantization methods for developing a constrained network: floating-point eight format, ternary scalar quantization, and binary scalar quantization. The results are demonstrated on the recently recorded SEAC dataset.
Access to Baccalaureate School in Switzerland: Regional Variance of Institutional Conditions and Its Consequences for Educational Inequalities
Authors: Leemann Regula Julia , Pfeifer Brändli Andrea , Imdorf Christian
Published: March 2022

In Switzerland, baccalaureate school is still considered to be the royal road to a university education and the elite path for the social reproduction of the upper class. However, cantonal enrollment to baccalaureate school varies widely due to Swiss federalism. There is a recurring debate on whether access to baccalaureate school is fair and equal among pupils who live in different cantons and who are of different social origin. This paper aims to analyze how the institutional conditions of cantons and municipalities impact a pupil’s probability of entering baccalaureate school and how the cantonal provisioning of places in baccalaureate school affects social inequality of access. For our theoretical foundation, we combine concepts of neo-institutionalism with mechanisms of social reproduction in education. Empirically, we analyze national longitudinal register data to model educational transitions from compulsory to baccalaureate school by using logistic regression models. Our results show that institutional structures at the cantonal and municipal levels influence the probability of transition beyond individual pupils’ characteristics. The degree of inequality varies between cantons, depending on the supply of baccalaureate school places. Inequality first increases with an increasing number of places (the scissors effect) and decreases only after the demand of more privileged families for places at baccalaureate school is saturated.
Marine SINS Self-Alignment Method in Complex Interference Environment Based on MEEMD Algorithm
Authors: Xing Jinlong , Yang Gongliu , Cai Tijing
Published: March 2022

It is difficult to rapidly and accurately achieve alignment under complicated interferential environmental conditions with a marine strapdown inertial navigation system (SINS) subject to angular swaying interference and linear motion interference. To solve this problem, an SINS self-alignment algorithm in a complex interference environment is presented in this article. For the angular motion disturbance problem, we used the attitude-updating algorithm in the coagulation inertial coordinate system to reflect the carrier’s attitude change in real time under the swaying interference so as to eliminate the influence of angular motion disturbance. To solve the problem of linear motion interference, we first use Fourier transform analysis (FFT) to analyze the frequency characteristics of linear motion interference signals. We then adaptively decompose the original signal into a series of signal components with different time scales and local characteristics according to the amplitude and frequency using the modified ensemble empirical mode decomposition (MEEMD) algorithm. Finally, we remove and reconstruct the disturbing signal components according to the frequency characteristics of the disturbing signal to filter the line motion disturbing signal. We use the MEEMD algorithm to conduct a ship alignment test. After pre-filtering by MEEMD, high accuracy can be achieved after 100 s of alignment, and the mean square error of the heading angle is 2.85′. The test results show that the MEEMD method has a good noise removal effect. The anti-jamming initial alignment algorithm based on the MEEMD algorithm has the ability to suppress the interference of angular motion and linear motion and achieve high-precision anti-jamming initial alignment under the complicated interferential environmental conditions with angular swaying interference and linear motion interference.
Controller Design of Tracking WMR System Based on Deep Reinforcement Learning
Authors: Lee Chin-Tan , Sung Wen-Tsai
Published: March 2022

Traditional PID controllers are widely used in industrial applications due to their simple computational architecture. However, the gain parameters of this simple computing architecture are fixed, and in response to environmental changes, the PID parameters must be continuously adjusted until the system is optimized. This research proposes to use the most important deep reinforcement learning (DRL) algorithm in deep learning as the basis and to modulate the gain parameters of the PID controller with fuzzy control. The research has the ability and advantages of reinforcement learning and fuzzy control and constructs a tracking unmanned wheel system. The mobile robotic platform uses a normalization system during computation to reduce the effects of reading errors caused by the wheeled mobile robot (WMR) of environment and sensor processes. The DRL-Fuzzy-PID controller architecture proposed in this paper utilizes degree operation to avoid the data error of negative input in the absolute value judgment, thereby reducing the amount of calculation. In addition to improving the accuracy of fuzzy control, it also uses reinforcement learning to quickly respond and minimize steady-state error to achieve accurate calculation performance. The experimental results of this study show that in complex trajectory sites, the tracking stability of the system using DRL-fuzzy PID is improved by 15.2% compared with conventional PID control, the maximum overshoot is reduced by 35.6%, and the tracking time ratio is shortened by 6.78%. If reinforcement learning is added, the convergence time of the WMR system will be about 0.5 s, and the accuracy rate will reach 95%. This study combines the computation of deep reinforcement learning to enhance the experimentally superior performance of the WMR system. In the future, intelligent unmanned vehicles with automatic tracking functions can be developed, and the combination of IoT and cloud computing can enhance the innovation of this research.
Graphene-Based Plasmonic Metamaterial Perfect Absorber for Biosensing Applications
Authors: Koondhar Masood Ali , Jamali Abdul Aleem , Ren Xin-Cheng , Laghari Mujeeb ur Rehman , Qureshi Fatima , Anjum Muhammad Rizwan , Khan Yousuf , Zhai Yongzhi , Zhu Yanmin
Published: March 2022

Graphene as a mono-atomic sheet has recently grabbed attention as a material with enormous properties. It has also been examined for enhancing absorbance in the current plasmonic structure. This has led to an increment in the sensitivity of the plasmonic sensors. In this paper, we present theoretical investigation of the novel graphene-based plasmonic metamaterial perfect absorber for biosensing applications. The simulation study performs the analysis of the novel plasmonic metamaterial absorber structure by adding coatings of graphene sheets. Each sheet of graphene enhances absorbance of the structure. In this study, we demonstrate three layers of graphene sheets lead to perfect absorbance (100%) for multiple bands in the visible and near-infrared regions. Furthermore, we also computed the sensitivity of the graphene-based proposed structure by varying the refractive index (RI) of the sensing region from 1.33–1.36 with RI change of 0.01. Proposed fabrication steps for realization of the device are also discussed.
A Lab on a Chip Experiment for Upscaling Diffusivity of Evolving Porous Media
Authors: Poonoosamy Jenna , Lu Renchao , Lönartz Mara Iris , Deissmann Guido , Bosbach Dirk , Yang Yuankai
Published: March 2022

Reactive transport modelling is a powerful tool to assess subsurface evolution in various energy-related applications. Upscaling, i.e., accounting for pore scale heterogeneities into larger scale analyses, remains one of the biggest challenges of reactive transport modelling. Pore scale simulations capturing the evolutions of the porous media over a wide range of Peclet and Damköhler number in combination with machine learning are foreseen as an efficient methodology for upscaling. However, the accuracy of these pore scale models needs to be tested against experiments. In this work, we developed a lab on a chip experiment with a novel micromodel design combined with operando confocal Raman spectroscopy, to monitor the evolution of porous media undergoing coupled mineral dissolution and precipitation processes due to diffusive reactive fluxes. The 3D-imaging of the porous media combined with pore scale modelling enabled the derivation of upscaled transport parameters. The chemical reaction tested involved the replacement of celestine by strontianite, whereby a net porosity increase is expected because of the smaller molar volume of strontianite. However, under our experimental conditions, the accessible porosity and consequently diffusivity decreased. We propose a transferability of the concepts behind the Verma and Pruess relationship to be applied to also describe changes of diffusivity for evolving porous media. Our results highlight the importance of calibrating pore scale models with quantitative experiments prior to simulations over a wide range of Peclet and Damköhler numbers of which results can be further used for the derivation of upscaled parameters.
Thermochromic Materials as Passive Roof Technology: Their Impact on Building Energy Performance
Authors: Crespo Sánchez Eva , Masip Vilà David
Published: March 2022

Over the last few years, new materials have been developed which a priori, appear to improve passive energy efficiency in buildings. This article focuses on chromogenic devices that allow changing their optical properties in a reversible manner through some external stimulus. The covering of the envelopes may have different textures or colors, which determine the amount of solar radiation absorbed by the material compared to the incident radiation. In buildings with a high percentage of roof relative to façade, the surface finish plays an interesting role in the energy demand. In the present work, the influence of the application of thermochromic materials to the roofs of commercial buildings is analyzed. It has been demonstrated that the application of a thermochromic surface finish can produce savings of annual energy demand between 1% and 12% in kilowatt-hours and kilograms of CO2 and they become more significant for construction solutions with higher transmittances values. Then, the impact of applying a thermochromic finish per day is analyzed and which transition temperature range will be the most optimal to the highest energy performance is discussed. At the same time, an assessment is made of the optimal cost; although economic investment is not currently amortized, it is a good resource for reducing energy demand in buildings.
Analysis and Design of a High-Efficiency SiC MOSFET 6-Phase Boost Rectifier
Authors: Di Nezio Giulia , di Benedetto Marco , Lidozzi Alessandro , Solero Luca
Published: March 2022

In this paper, the analysis and the design of a high-efficiency power electronic conversion system for offshore wind applications are presented. This system is composed of a 6-phase AC–DC converter based on the SiC power semiconductors, to be used to control the achievable power from the wind turbine electrical generator. Thanks to the phase redundancy, the proposed boost rectifier is suitable for applications where reliability and fault tolerance capability are the main targets. To select the appropriate power semiconductor devices, voltage and current ratings have to be determined. After that, the power loss equations are derived in order to evaluate the conversion efficiency. To design the appropriate DC-bus capacitor configuration, an analytical investigation is carried out by estimating the DC-bus RMS current and the voltage ripple. Finally, the thermal sizing of the system is calculated to identify a suitable heatsink. To validate the proposed analysis, the analytical results are compared to simulation ones using the Plexim/PLECS tool in the MATLAB/Simulink environment. For further validation, a prototype of the converter is built and the experimental results are carried out. The results demonstrate that the peak efficiency of the 6-phase boost rectifier can reach 98% at 100 kHz switching frequency.
In-Situ Synthesis of Sm0.5Sr0.5Co0.5O3-δ@Sm0.2Ce0.8O1.9 Composite Oxygen Electrode for Electrolyte-Supported Reversible Solid Oxide Cells (RSOC)
Authors: Yang Xiaoxing , Miao He , Pan Baowei , Chen Ming , Yuan Jinliang
Published: March 2022

Oxygen electrode has a crucial impact on the performance of reversible solid oxide cells (RSOC), especially in solid oxide electrolysis cell (SOEC) mode. Herein, Sm0.5Sr0.5Co0.5O3-δ@Sm0.2Ce0.8O1.9 (5SSC@5SDC) composite material has been fabricated by the in-situ synthesis method and applied as the oxygen electrode for RSOCs with scandium stabilized zirconia (SSZ) electrolyte. The phase structures, thermal expansion coefficients, and micromorphologies of 5SSC@5SDC have all been further analyzed and discussed. 5SSC@5SDC is composed of a skeleton with large SDC particles in the diameter range of 200~300 nm and many fine SSC nanoparticles coated on the skeleton. Thanks to the special microstructure of 5SSC@5SDC, the electrolyte-supported RSOC with SSC@SDC oxygen electrode shows a polarization resistance of only 0.69 Ω·cm2 and a peak power density of 0.49 W·cm−2 at 800 °C with hydrogen as the fuel in solid oxide fuel cell (SOFC) mode. In addition, the electrolysis current density of RSOC with SSC@SDC can reach 0.40 A·cm−2 at 1.30 V in SOEC model, being much higher than that with the SSC-SDC (SSC and SDC composite prepared by physical mixing). RSOC with 5SSC@5SDC shows an improved stability in SOEC model comparing with that with SSC-SDC. The improved performance indicates that 5SSC@5SDC prepared by the in-situ synthesis may be a promising candidate for RSOC oxygen electrode.
Best Practice in Government Use and Development of Long-Term Energy Transition Scenarios
Authors: Carvajal Pablo E. , Miketa Asami , Goussous Nadeem , Fulcheri Pauline
Published: March 2022

Long-term energy scenarios (LTES) have been serving as an important planning tool by a wide range of institutions. This article focuses on how LTES have been used (and also devised in some cases) in the government sector, and specifically how the new challenges and opportunities brought by the aspiration for the clean energy transition change the way that governments use LTES. The information tends to remain tacit, and a gap exists in understanding the way to enhance LTES use and development at the government level. To address this gap, we draw on the experience from national institutions that are leading the improvement in official energy scenario planning to articulate a set of overarching best practices to (i) strengthen LTES development, (ii) effectively use LTES for strategic energy planning and (iii) enhance institutional capacity for LTES-based energy planning, all in the context of new challenges associated with the clean energy transition. We present implementation experience collected through the International Renewable Agency’s LTES Network activities to exemplify these best practices. We highlight that in the context of the broad and complex challenges of a clean energy transition driven by ambitious climate targets, the LTES-based energy planning methodologies need to evolve, reflecting the changing landscapes, and that more effective and extensive use of LTES in government needs to be further encouraged.
Optimized Configuration of Diesel Engine-Fuel Cell-Battery Hybrid Power Systems in a Platform Supply Vessel to Reduce CO2 Emissions
Authors: Vieira Giovani T. T. , Pereira Derick Furquim , Taheri Seyed Iman , Khan Khalid S. , Salles Mauricio B. C. , Guerrero Josep M. , Carmo Bruno S.
Published: March 2022

The main objective of this paper is to select the optimal configuration of a ship’s power system, considering the use of fuel cells and batteries, that would achieve the lowest CO2 emissions also taking into consideration the number of battery cycles. The ship analyzed in this work is a Platform Supply Vessel (PSV) used to support oil and gas offshore platforms transporting goods, equipment, and personnel. The proposed scheme considers the ship’s retrofitting. The ship’s original main generators are maintained, and the fuel cell and batteries are installed as complementary sources. Moreover, a sensitivity analysis is pursued on the ship’s demand curve. The simulations used to calculate the CO2 emissions for each of the new hybrid configurations were developed using HOMER software. The proposed solutions are auxiliary generators, three types of batteries, and a proton-exchange membrane fuel cell (PEMFC) with different sizes of hydrogen tanks. The PEMFC and batteries were sized as containerized solutions, and the sizing of the auxiliary engines was based on previous works. Each configuration consists of a combination of these solutions. The selection of the best configuration is one contribution of this paper. The new configurations are classified according to the reduction of CO2 emitted in comparison to the original system. For different demand levels, the results indicate that the configuration classification may vary. Another valuable contribution of this work is the sizing of the battery and hydrogen storage systems. They were installed in 20 ft containers, since the installation of batteries, fuel cells and hydrogen tanks in containers is widely used for ship retrofit. As a result, the most significant reduction of CO2 emissions is 10.69%. This is achieved when the configuration includes main generators, auxiliary generators, a 3,119 kW lithium nickel manganese cobalt (LNMC) battery, a 250 kW PEMFC, and 581 kg of stored hydrogen.
Analysis of Factors Affecting Termite Damage to Wooden Architectural Heritage Buildings in Korea
Authors: Kim Si-Hyun , Chung Yong-Jae
Published: March 2022

Many wooden architectural heritage buildings exist in Korea, and the authenticity and structural stability of these cultural assets are being affected by termites. This study aimed to identify the degree of termite damage and related factors in these buildings. The degree of termite damage to 182 nationally designated wooden architectural heritage buildings (national treasures and treasures) in Korea was quantified, and data were collected for 11 factors affecting termite damage, such as the surrounding environment and architectural features. Based on the results of a general linear model analysis, the following three factors were identified to have a significant effect on termite damage: the type of contact between the ground and wooden structural items, the number of days of termite activity, and the proportion of forests in the land surrounding the property. This study is the first attempt to statistically analyze factors affecting termite damage to wooden heritage buildings, and our results provide initial data for the preservation and management of these properties.
Sustainable and Eco-Friendly Conversions of Olive Mill Wastewater-Based Media by Pleurotus pulmonarius Cultures
Authors: Diamantis Ilias , Melanouri Eirini-Maria , Dedousi Marianna , Panagopoulou Ioanna , Papanikolaou Seraphim , Stoforos Nikolaos G. , Diamantopoulou Panagiota
Published: March 2022

Pleurotus pulmonarius mushroom was cultivated on liquid cultures with olive mill wastewaters (OMWs) of initial phenolic compound concentrations of 0 (control), 1, 2 and 3 g/L and glucose at initial concentrations of 40 and 60 g/L. The ability of the fungus to grow on media containing toxic compounds enriched with glucose was assessed through biomass production, glucose consumption, polysaccharide (IPS) accumulation and total cellular lipids biosynthesis, while the total phenolic compounds (TPC) and antioxidant component monitoring were also assessed during a 43-day fermentation. An analysis of the total simple sugar composition of IPS and the total fatty acid composition of lipids was performed. The phenolic reduction and media decolorization were also monitored. Results showed that the addition of glucose in OMW-based media had a positive effect on biomass, IPS and lipid production and increased the unsaturated fatty acids and TPC concentration. The maximum recorded values were the following: biomass 32.76 g/L, IPS 4.38 g/L (14.70%, w/w in dry weight), lipids 2.85 g/L (11.69%, w/w in dry weight). The mycelial lipids were unsaturated and dominated by linoleic acid, whereas IPS were composed mainly of glucose. Significant phenolic compound reduction (87–95%) and color removal (70–85%) occurred. Results strongly suggest the potentiality of P. pulmonarius utilization in the OMW treatment.
Correction: Silva et al. Chemical Profile and Bioactivities of Extracts from Edible Plants Readily Available in Portugal. Foods 2021, 10, 673
Authors: Silva Beatriz Nunes , Cadavez Vasco , Ferreira-Santos Pedro , Alves Maria José , Ferreira Isabel C. F. R. , Barros Lillian , Teixeira José António , Gonzales-Barron Ursula
Published: March 2022

The authors found a mistake in the original paper [...]