bluuebunny/crossref_metadata_2025 huggingface dataset:
The Do-Not-Resuscitate Order: Incidence of Documentation in the Medical Records of Cancer Patients Referred for Palliative Radiotherapy
Authors: Bradley N.M.E. , Sinclair E. , Danjoux C. , Barnes E.A. , Tsao M.N. , Farhadian M. , Yee A. , Chow E.
Published: February 2021

Patients with symptomatic metastases referred for outpatient palliative radiotherapy for symptom control at the Rapid Response Radiotherapy Program (rrrp) and the Bone Metastases Clinic (bmc) at the Toronto–Sunnybrook Regional Cancer Centre have a limited life expectancy. Relevant medical information is missing from the files of many referred patients when they arrive at the clinics, potentially causing delayed treatment and ambiguity in the best management of their needs in situations of worsening condition. Clear documentation of the do-not-resuscitate (dnr) order is imperative to avoid panic and the taking of unnecessarily aggressive measures in situations in which cardiopulmonary resuscitation (cpr) has no benefit or is not desired. Here, we report the current practices of cpr code status documentation for patients referred to the rrrp and the bmc for outpatient palliative radiotherapy. We reviewed referral notes and accompanying medical records for 209 consecutive patients seen in the rrrp and the bmc during May–August 2004 for documentation of cpr-related advance directives. Patient demographics and cancer history were also recorded. Only 13 (6.2%) of the 209 patients had any documented reference to cpr code status. Of these 13 patients, 8 were dnr-coded, and 5 were full code. As compared with patients having no documented cpr code status, patients with documented status were significantly older (median age: 77 years; p = 0.0347), had poorer performance status (median Karnofsky performance status score: 40; p = 0.0001), and were more likely to be referred hospital inpatients (69%, p = 0.0004). Only a small proportion of symptomatic advanced cancer patients had any documentation of cpr code status upon referral for outpatient palliative radiotherapy. In future, our clinics plan to request information about cpr code status on our referral form.
Promoting Best Gynecologic Oncology Practice: A Role For The Society of Gynecologic Oncologists of Canada
Authors: Elit L. M. , Johnston M. , Brouwers M. , Fung- Kee-Fung M. , Browman G. , Graham I. D.
Published: February 2021

During March 30–April 1, 2005, the Society of Gynecologic Oncologists of Canada (GOC) and the Canadian Strategy for Cancer Control (CSCC) Clinical Practice Guidelines Action Group (CPG-AG) met to • determine how GOC would like to influence practice in the care of women with gynecologic cancer. • explore a collaborative model for developing and implementing evidence-based practice guidelines. • investigate the utility of the CPG evaluation and adaptation cycle as a tool for selecting, adapting, and adopting guidelines. At the workshop meeting, 21 members of the GOC and the CPG-AG heard presentations from various Canadian guideline initiatives. As an example of adaptation and adoption processes, the AGREE (Appraisal of Guidelines for Research and Evaluation) tool was applied to guidelines in recurrent ovarian cancer, and the group explored their opportunity to use knowledge translation to influence the care of women with gynecologic cancer. The themes influencing practice are consistent with GOC’s mandate. The future is expected to involve partnering with other groups to maximize scarce resources. Resources should be directed to facilitating implementation of existing guidelines rather than to developing new documents. The full spectrum of cancer care includes prevention, screening, diagnosis, primary treatment, follow-up, treatment of recurrent disease, and palliation. High-quality evidence is available in some areas, but gaps exist where guideline panels could provide guidance. Development of a pan-Canadian gynecologic oncology process could provide an opportunity to influence access to care at the political and policy levels. The GOC will develop linkages such that the toolbox available through CSCC-CPG-AG can be incorporated into future collaboration.
In This Issue of Current Oncology
Authors: McLean M.
Published: February 2021

Many of the newer clinical studies proposed for the management of high-risk prostate cancer include the use of chemotherapy in addition to androgen deprivation. [...]
Cross-Border Referral for Early Breast Cancer: An Analysis of Radiation Fractionation Patterns
Authors: Dayes Ian , Whelan T. , Julian J. , Kuettel M. , Regmi D. , Okawara G. , Patel M. , Reiter H. , Dubois S.
Published: February 2021

Because of increasing waiting times for adjuvant radiation in the province of Ontario, patients from one Canadian centre were referred to two centres in the United States. This situation provided an opportunity to compare radiation practices. We performed a retrospective review of radiation prescribed to patients following breast-conserving surgery for invasive breast cancer. Patients with positive margins, 4 or more positive lymph nodes, recurrent disease, or large tumours (>5 cm) were excluded. For comparison, we reviewed a random sample of similar patients treated at the Canadian centre during the same period. A total of 120 referred and 217 non-referred patients were eligible for comparison. The analysis included 98 pairs of patients (N = 196), fully matched on age, nodal status, T stage, grade, and estrogen receptor (ER) status. Mean patient age was 60.7 years. The median total dose and number of fractions differed between centres [6040 cGy in 32 fractions (United States) vs. 4250 cGy in 16 fractions (Canadian), both p < 0.001). Boost was used more often in the United States (97% vs. 9%, p < 0.001). Variation in prescribing patterns was seen. In the United States, seven different schedules for whole-breast irradiation were used; at the Canadian centre, two schedules were prescribed. Predicted radiobiologic effects of these schedules were calculated to be similar. Differences in fractionation patterns were observed between and within U.S. and Canadian centres. Such variability is likely to affect patient convenience and resource utilization. Although patient selection, referring surgeon, and change in policies may account for some of the observed differences, further research is necessary to better understand the causes.
Targeting Transforming Growth Factor β to Enhance Cancer Immunotherapy
Authors: Hahn T. , Akporiaye Emmanuel
Published: February 2021

Human tumours have evolved intricate mechanisms to evade the immune system, either by avoiding recognition or by inhibiting and eliminating immune cells. [...]
In this issue of Current Oncology
Authors: McLean M.
Published: February 2021

The year 2008 will see the continued expansion of Current Oncology, Canada’s only multidisciplinary journal devoted to cancer. [...]
The Integrative Oncology Supplement—A Paradigm for Both Patient Care and Communication
Authors: Sagar S.M.
Published: February 2021

Integrative oncology is both a science and a philosophy that focuses on the complexity of[...]
Managing Opioids and Mitigating Risk: A Survey of Attitudes, Confidence and Practices of Oncology Health Care Professionals
Authors: Tedesco Alissa , Brown Jocelyn , Hannon Breffni , Hutton Lauren , Lau Jenny
Published: February 2021

In response to Canada’s opioid crisis, national strategies and guidelines have been developed but primarily focus on opioid use for chronic noncancer pain. Despite the well-established utility of opioids in cancer care, and the growing emphasis on early palliative care, little attention has been paid to opioid risk in this population, where evidence increasingly shows a higher risk of opioid-related harms than was previously thought. The primary objective of this study was to assess oncology clinicians’ attitudes, confidence, and practices in managing opioids in outpatients with cancer. This was explored using pilot-tested, profession-specific surveys for physicians/nurse practitioners, nurses and pharmacists. Descriptive analyses were conducted in aggregate and separately based on discipline. Univariate and multiple linear regression analyses were performed to explore relationships between confidence and practices within and across disciplines. The survey was distributed to approximately 400 clinicians in January 2019. Sixty-five responses (27 physicians/nurse practitioners, 31 nurses, 7 pharmacists) were received. Participants endorsed low confidence, differing attitudes, and limited and varied practice in managing and mitigating opioid risks in the cancer population. This study provides valuable insights into knowledge gaps and clinical practices of oncology healthcare professionals in managing opioids and mitigating associated risks for patients with cancer.
18S rRNA Analysis Reveals High Diversity of Phytoplankton with Emphasis on a Naked Dinoflagellate Gymnodinium sp. at the Han River (Korea)
Authors: Muhammad Buhari Lawan , Kim Taehee , Ki Jang-Seu
Published: February 2021

Biomonitoring of phytoplankton communities in freshwater ecosystems is imperative for efficient water quality management. In the present study, we present the seasonal diversity of phytoplankton from the non-reservoir area of the Han River (Korea), assessed using the 18S rRNA amplicon sequencing. Our results uncovered a considerably high eukaryotic diversity, which was predominantly represented by phytoplankton in all the seasons (38–63%). Of these, the diatoms, Cyclostephanos tholiformis, Stephanodiscus hantzschii, and Stephanodiscus sp., were frequently detected in spring and winter. Interestingly, for the first time in the Han River, we detected a large number of operational taxonomic unit (OTU) reads belonging to the naked dinoflagellate Gymnodinium sp., which dominated in autumn (15.8%) and was observed only in that season. Molecular cloning and quantitative real-time polymerase chain reaction (PCR) confirmed the presence of Gymnodinium sp. in the samples collected in 2012 and 2019. Moreover, a comparison of the present data with our previous data from a reservoir area (Paldang Dam) revealed similar patterns of phytoplankton communities. This molecular approach revealed a prospective toxic species that was not detected through microscopy. Collectively, resolving phytoplankton communities at a level relevant for water quality management will provide a valuable reference for future studies on phytoplankton for environmental monitoring.
The Current State of Eunicida (Annelida) Systematics and Biodiversity
Authors: Zanol Joana , Carrera-Parra Luis F. , Steiner Tatiana Menchini , Amaral Antonia Cecilia Z. , Wiklund Helena , Ravara Ascensão , Budaeva Nataliya
Published: February 2021

In this study, we analyze the current state of knowledge on extant Eunicida systematics, morphology, feeding, life history, habitat, ecology, distribution patterns, local diversity and exploitation. Eunicida is an order of Errantia annelids characterized by the presence of ventral mandibles and dorsal maxillae in a ventral muscularized pharynx. The origin of Eunicida dates back to the late Cambrian, and the peaks of jaw morphology diversity and number of families are in the Ordovician. Species richness is heterogeneous among the seven recent families, with more than half of the valid species belonging to the Eunicidae + Onuphidae clade, one of the latest clades to diverge. Eunicidans inhabit soft and hard substrates from intertidal to deep waters in all oceans. The few freshwater species are restricted to Histriobdellidae, a family exclusively commensal/parasite of crustaceans. The reproductive biology, development and ecology of most families are poorly known and the information available suggests low dispersal ability. However, all families have records of widely distributed species. Scrutiny of these wide distributions has often revealed the presence of exotic species or more than one species. The exploration of the deep-sea and of new habitats has led to recent descriptions of new species. Furthermore, the revision of type specimens, the examination of new morphological features and the use of molecular data have revealed hidden biodiversity under unjustified synonyms, poor understanding of morphological features and incomplete descriptions. Molecular studies are still very few or nonexistent for the families Histriobdellidae, Hartmaniellidae, Lumbrineridae and Oenonidae. The integration of new methodologies for morphological and molecular study, along with information on biological and ecological traits appears to be the path to improve the knowledge on the diversity of Eunicida.
Do Weeds Hinder the Establishment of Native Plants on a Reclaimed North American Boreal Mine Site?
Authors: Trepanier Kaitlyn E. , Burton Brea , Pinno Bradley D.
Published: February 2021

The majority of plant diversity in the boreal forest of northern Alberta, Canada is comprised of native understory plant species that are continuously facing competition from other species, including both undesirable native and weedy species. In oil sands mine reclamation, cover soils rich in organic matter are used to cap overburden materials. The aim of this study is to understand the role of weeds on different reclamation cover soils (forest floor-mineral mix and peat-mineral mix) and determine if they hinder the establishment of the native plant community. This study was conducted four growing seasons after site establishment in June 2019. At that time, both soil types had approximately 45% total cover, had 21 species per plot, and were composed of mainly native vegetation. Competition from non-native forbs (11% average cover, mainly Sonchus arvensis and Melilotus alba) did not seem to impact the development of the native vegetation community on either soil type given the high cover and richness of native forbs. However, native graminoids (predominantly Calamagrostis canadensis) were associated with reduced native forb cover and richness at graminoid cover greater than 17%. Overall, non-native forbs appeared to have little impact on the native forb community on either soil type while native graminoids had a negative influence. We suggest that the classification of what is considered an undesirable weedy species should be evaluated in the context of ecosystem management goals rather than simply the presence of non-native species.
Cardiac Exosomes in Ischemic Heart Disease—A Narrative Review
Authors: Røsand Øystein , Høydal Morten Andre
Published: February 2021

Ischemic heart disease (IHD) is the primary cause of death globally. IHD is associated with the disruption of blood supply to the heart muscles, which often results in myocardial infarction (MI) that further may progress to heart failure (HF). Exosomes are a subgroup of extracellular vesicles that can be secreted by virtually all types of cells, including cardiomyocytes, cardiac fibroblasts, endothelial cells, and stem and progenitor cells. Exosomes represent an important means of cell–cell communication through the transport of proteins, coding and non-coding RNA, and other bioactive molecules. Several studies show that exosomes play an important role in the progression of IHD, including endothelial dysfunction, the development of arterial atherosclerosis, ischemic reperfusion injury, and HF development. Recently, promising data have been shown that designates exosomes as carriers of cardioprotective molecules that enhance the survival of recipient cells undergoing ischemia. In this review, we summarize the functional involvement of exosomes regarding IHD. We also highlight the cardioprotective effects of native and bioengineered exosomes to IHD, as well as the possibility of using exosomes as natural biomarkers of cardiovascular diseases. Lastly, we discuss the opportunities and challenges that need to be addressed before exosomes can be used in clinical applications.
Serological Test to Determine Exposure to SARS-CoV-2: ELISA Based on the Receptor-Binding Domain of the Spike Protein (S-RBDN318-V510) Expressed in Escherichia coli
Authors: Márquez-Ipiña Alan Roberto , González-González Everardo , Rodríguez-Sánchez Iram Pablo , Lara-Mayorga Itzel Montserrat , Mejía-Manzano Luis Alberto , Sánchez-Salazar Mónica Gabriela , González-Valdez José Guillermo , Ortiz-López Rocio , Rojas-Martínez Augusto , Trujillo-de Santiago Grissel , Alvarez Mario Moisés
Published: February 2021

Massive worldwide serological testing for SARS-CoV-2 is needed to determine the extent of virus exposure in a particular region, the ratio of symptomatic to asymptomatic infected persons, and the duration and extent of immunity after infection. To achieve this, the development and production of reliable and cost-effective SARS-CoV-2 antigens is critical. We report the bacterial production of the peptide S-RBDN318-V510, which contains the receptor-binding domain of the SARS-CoV-2 spike protein (region of 193 amino acid residues from asparagine-318 to valine-510) of the SARS-CoV-2 spike protein. We purified this peptide using a straightforward approach involving bacterial lysis, his-tag-mediated affinity chromatography, and imidazole-assisted refolding. The antigen performances of S-RBDN318-V510 and a commercial full-length spike protein were compared in ELISAs. In direct ELISAs, where the antigen was directly bound to the ELISA surface, both antigens discriminated sera from non-exposed and exposed individuals. However, the discriminating resolution was better in ELISAs that used the full-spike antigen than the S-RBDN318-V510. Attachment of the antigens to the ELISA surface using a layer of anti-histidine antibodies gave equivalent resolution for both S-RBDN318-V510 and the full-length spike protein. Results demonstrate that ELISA-functional SARS-CoV-2 antigens can be produced in bacterial cultures, and that S-RBDN318-V510 may represent a cost-effective alternative to the use of structurally more complex antigens in serological COVID-19 testing.
Clinical Implications of (Pro)renin Receptor (PRR) Expression in Renal Tumours
Authors: Solano-Iturri Jon Danel , Echevarría Enrique , Unda Miguel , Loizaga-Iriarte Ana , Pérez-Fernández Amparo , Angulo Javier C. , López José I. , Larrinaga Gorka
Published: February 2021

(1) Background: Renal cancer is one of the most frequent malignancies in Western countries, with an unpredictable clinical outcome, partly due to its high heterogeneity and the scarcity of reliable biomarkers of tumour progression. (Pro)renin receptor (PRR) is a novel receptor of the renin–angiotensin system (RAS) that has been associated with the development and progression of some solid tumours by RAS-dependent and -independent mechanisms. (2) Methods: In this study, we analysed the immunohistochemical expression of PRR at the centre and border in a series of 83 clear-cell renal cell (CCRCCs), 19 papillary (PRCC) and 7 chromophobe (ChRCC) renal cell carcinomas, and the benign tumour renal oncocytoma (RO, n = 11). (3) Results: PRR is expressed in all the tumour subtypes, with higher mean staining intensity in ChRCCs and ROs. A high expression of PRR at the tumour centre and at the infiltrative front of CCRCC tissues is significantly associated with high grade, tumour diameter, local invasion and stage, and with high mortality risk by UCLA integrated staging system (UISS) scale. (4) Conclusions: These findings indicate that PRR is associated with the development and progression of renal tumours. Its potential as a novel biomarker for RCC diagnosis/prognosis and as a promising therapeutic target should be taken into account in the future.
Impact of [18F]FDG-PET and [18F]FLT-PET-Parameters in Patients with Suspected Relapse of Irradiated Lung Cancer
Authors: Christensen Tine , Langer Seppo , Persson Gitte , Larsen Klaus , Amtoft Annemarie , Keller Sune , Kjaer Andreas , Fischer Barbara
Published: February 2021

Radiation-induced changes may cause a non-malignant high 2-deoxy-2-[18F]fluoro-d-glucose (FDG)-uptake. The 3′-deoxy-3′-[18F]fluorothymidine (FLT)-PET/CT performs better in the differential diagnosis of inflammatory changes and lung lesions with a higher specificity than FDG-PET/CT. We investigated the association between post-radiotherapy FDG-PET-parameters, FLT-PET-parameters, and outcome. Sixty-one patients suspected for having a relapse after definitive radiotherapy for lung cancer were included. All the patients had FDG-PET/CT and FLT-PET/CT. FDG-PET- and FLT-PET-parameters were collected from within the irradiated high-dose volume (HDV) and from recurrent pulmonary lesions. For associations between PET-parameters and relapse status, respectively, the overall survival was analyzed. Thirty patients had a relapse, of these, 16 patients had a relapse within the HDV. FDG-SUVmax and FLT-SUVmax were higher in relapsed HDVs compared with non-relapsed HDVs (median FDG-SUVmax: 12.8 vs. 4.2; p < 0.001; median FLT-SUVmax 3.9 vs. 2.2; p < 0.001). A relapse within HDV had higher FDG-SUVpeak (median FDG-SUVpeak: 7.1 vs. 3.5; p = 0.014) and was larger (median metabolic tumor volume (MTV50%): 2.5 vs. 0.7; 0.014) than the relapsed lesions outside of HDV. The proliferative tumor volume (PTV50%) was prognostic for the overall survival (hazard ratio: 1.07 pr cm3 [1.01–1.13]; p = 0.014) in the univariate analysis, but not in the multivariate analysis. FDG-SUVmax and FLT-SUVmax may be helpful tools for differentiating the relapse from radiation-induced changes, however, they should not be used definitively for relapse detection.
Pharmacological Modulation of Rate-Dependent Depression of the Spinal H-Reflex Predicts Therapeutic Efficacy against Painful Diabetic Neuropathy
Authors: Lee-Kubli Corinne A. , Zhou XiaJun , Jolivalt Corinne G. , Calcutt Nigel A.
Published: February 2021

Impaired rate-dependent depression (RDD) of the spinal H-reflex occurs in diabetic rodents and a sub-set of patients with painful diabetic neuropathy. RDD is unaffected in animal models of painful neuropathy associated with peripheral pain mechanisms and diabetic patients with painless neuropathy, suggesting RDD could serve as a biomarker for individuals in whom spinal disinhibition contributes to painful neuropathy and help identify therapies that target impaired spinal inhibitory function. The spinal pharmacology of RDD was investigated in normal rats and rats after 4 and 8 weeks of streptozotocin-induced diabetes. In normal rats, dependence of RDD on spinal GABAergic inhibitory function encompassed both GABAA and GABAB receptor sub-types. The time-dependent emergence of impaired RDD in diabetic rats was preceded by depletion of potassium-chloride co-transporter 2 (KCC2) protein in the dorsal, but not ventral, spinal cord and by dysfunction of GABAA receptor-mediated inhibition. GABAB receptor-mediated spinal inhibition remained functional and initially compensated for loss of GABAA receptor-mediated inhibition. Administration of the GABAB receptor agonist baclofen restored RDD and alleviated indices of neuropathic pain in diabetic rats, as did spinal delivery of the carbonic anhydrase inhibitor acetazolamide. Pharmacological manipulation of RDD can be used to identify potential therapies that act against neuropathic pain arising from spinal disinhibition.
Clinical Analysis of Early-Stage Pancreatic Cancer and Proposal for a New Diagnostic Algorithm: A Multicenter Observational Study
Authors: Ikemoto Juri , Serikawa Masahiro , Hanada Keiji , Eguchi Noriaki , Sasaki Tamito , Fujimoto Yoshifumi , Sugiyama Shinichiro , Yamaguchi Atsushi , Noma Bunjiro , Kamigaki Michihiro , Minami Tomoyuki , Okazaki Akihito , Yukutake Masanobu , Ishii Yasutaka , Mouri Teruo , Shimizu Akinori , Tsuboi Tomofumi , Arihiro Koji , Chayama Kazuaki
Published: February 2021

Early diagnosis of pancreatic ductal adenocarcinoma (PDAC) is challenging but essential for improving its poor prognosis. We established a multicenter study to clarify the clinicopathological features, and to propose new algorithm for early diagnosis of PDAC. Ninety-six patients with stage 0 and IA PDAC were enrolled from 13 high-volume centers. Overall, 70% of the patients were asymptomatic. The serum pancreatic enzyme levels were abnormal in half of the patients. The sensitivity of endoscopic ultrasonography (EUS) for detecting small PDAC was superior to computed tomography and magnetic resonance imaging (MRI) (82%, 58%, and 38%, respectively). Indirect imaging findings were useful to detect early-stage PDAC; especially, main pancreatic duct stenosis on MRI had the highest positive rate of 86% in stage 0 patients. For preoperative pathological diagnosis, the sensitivity of endoscopic retrograde cholangiopancreatography (ERCP)-associated pancreatic juice cytology was 84%. Among the stage IA patients, EUS-guided fine-needle aspiration revealed adenocarcinoma in 93% patients. For early diagnosis of PDAC, it is essential to identify asymptomatic patients and ensure close examinations of indirect imaging findings and standardization of preoperative pathological diagnosis. Therefore, a new diagnostic algorithm based on tumor size and imaging findings should be developed.
The Dissipative Photochemical Origin of Life: UVC Abiogenesis of Adenine
Authors: Michaelian Karo
Published: February 2021

The non-equilibrium thermodynamics and the photochemical reaction mechanisms are described which may have been involved in the dissipative structuring, proliferation and complexation of the fundamental molecules of life from simpler and more common precursors under the UVC photon flux prevalent at the Earth’s surface at the origin of life. Dissipative structuring of the fundamental molecules is evidenced by their strong and broad wavelength absorption bands in the UVC and rapid radiationless deexcitation. Proliferation arises from the auto- and cross-catalytic nature of the intermediate products. Inherent non-linearity gives rise to numerous stationary states permitting the system to evolve, on amplification of a fluctuation, towards concentration profiles providing generally greater photon dissipation through a thermodynamic selection of dissipative efficacy. An example is given of photochemical dissipative abiogenesis of adenine from the precursor HCN in water solvent within a fatty acid vesicle floating on a hot ocean surface and driven far from equilibrium by the incident UVC light. The kinetic equations for the photochemical reactions with diffusion are resolved under different environmental conditions and the results analyzed within the framework of non-linear Classical Irreversible Thermodynamic theory.
Signature of Generalized Gibbs Ensemble Deviation from Equilibrium: Negative Absorption Induced by a Local Quench
Authors: Rossi Lorenzo , Dolcini Fabrizio , Cavaliere Fabio , Traverso Ziani Niccolò , Sassetti Maura , Rossi Fausto
Published: February 2021

When a parameter quench is performed in an isolated quantum system with a complete set of constants of motion, its out of equilibrium dynamics is considered to be well captured by the Generalized Gibbs Ensemble (GGE), characterized by a set {λα} of coefficients related to the constants of motion. We determine the most elementary GGE deviation from the equilibrium distribution that leads to detectable effects. By quenching a suitable local attractive potential in a one-dimensional electron system, the resulting GGE differs from equilibrium by only one single λα, corresponding to the emergence of an only partially occupied bound state lying below a fully occupied continuum of states. The effect is shown to induce optical gain, i.e., a negative peak in the absorption spectrum, indicating the stimulated emission of radiation, enabling one to identify GGE signatures in fermionic systems through optical measurements. We discuss the implementation in realistic setups.
Numerical Evaluation on Parametric Choices Influencing Segmentation Results in Radiology Images—A Multi-Dataset Study
Authors: Prasad Pravda Jith Ray , Survarachakan Shanmugapriya , Khan Zohaib Amjad , Lindseth Frank , Elle Ole Jakob , Albregtsen Fritz , Kumar Rahul Prasanna
Published: February 2021

Medical image segmentation has gained greater attention over the past decade, especially in the field of image-guided surgery. Here, robust, accurate and fast segmentation tools are important for planning and navigation. In this work, we explore the Convolutional Neural Network (CNN) based approaches for multi-dataset segmentation from CT examinations. We hypothesize that selection of certain parameters in the network architecture design critically influence the segmentation results. We have employed two different CNN architectures, 3D-UNet and VGG-16, given that both networks are well accepted in the medical domain for segmentation tasks. In order to understand the efficiency of different parameter choices, we have adopted two different approaches. The first one combines different weight initialization schemes with different activation functions, whereas the second approach combines different weight initialization methods with a set of loss functions and optimizers. For evaluation, the 3D-UNet was trained with the Medical Segmentation Decathlon dataset and VGG-16 using LiTS data. The quality assessment done using eight quantitative metrics enhances the probability of using our proposed strategies for enhancing the segmentation results. Following a systematic approach in the evaluation of the results, we propose a few strategies that can be adopted for obtaining good segmentation results. Both of the architectures used in this work were selected on the basis of general acceptance in segmentation tasks for medical images based on their promising results compared to other state-of-the art networks. The highest Dice score obtained in 3D-UNet for the liver, pancreas and cardiac data was 0.897, 0.691 and 0.892. In the case of VGG-16, it was solely developed to work with liver data and delivered a Dice score of 0.921. From all the experiments conducted, we observed that two of the combinations with Xavier weight initialization (also known as Glorot), Adam optimiser, Cross Entropy loss (GloCEAdam) and LeCun weight initialization, cross entropy loss and Adam optimiser LecCEAdam worked best for most of the metrics in a 3D-UNet setting, while Xavier together with cross entropy loss and Tanh activation function (GloCEtanh) worked best for the VGG-16 network. Here, the parameter combinations are proposed on the basis of their contributions in obtaining optimal outcomes in segmentation evaluations. Moreover, we discuss that the preliminary evaluation results show that these parameters could later on be used for gaining more insights into model convergence and optimal solutions.The results from the quality assessment metrics and the statistical analysis validate our conclusions and we propose that the presented work can be used as a guide in choosing parameters for the best possible segmentation results for future works.
Interleaved High Step-Up Current Sharing Converter with Coupled Inductors
Authors: He Liangzong , Lin Zhile , Tan Qingyang , Lu Fengwang , Zeng Tao
Published: February 2021

An interleaved high-step-up current sharing DC–DC converter with coupled inductors is proposed in this paper. The operation principle and property of this converter are analyzed. The ripple of the input current in the proposed converter is decreased significantly by using the two-phase parallel interleaved input. The voltage gain is extended and the switch voltage stress is reduced by the coupled inductors. The leakage inductance of the coupled inductors reduces the reverse-recovery problem of the output diode, resulting in the reduction of reverse-recovery losses. As there are two interleaved phases in the proposed converter, the third winding of each coupled inductor is embedded in another phase. With this design, when the leakage inductance or duty cycle is asymmetrical, the current sharing performance is still positive. Consequently, the new topology is very suitable for applications to occasions with low voltage input and high voltage output, such as the fuel cell power system. Finally, the performance of this topological circuit is verified by a prototype with 500 W output.
A Cost-Efficient MFCC-Based Fault Detection and Isolation Technology for Electromagnetic Pumps
Authors: Akpudo Ugochukwu Ejike , Hur Jang-Wook
Published: February 2021

Fluid pumps serve critical purposes in hydraulic systems so their failure affects productivity, profitability, safety, etc. The need for proper condition monitoring and health assessment of these pumps cannot be overemphasized and this has resulted in extensive research studies on standard techniques for ensuring optimum fault detection and isolation (FDI) results for these pumps. Interestingly, mechanical vibrational signals reflect operating conditions and by exploring the robust time–frequency-domain feature extraction techniques, the underlying nonlinear characteristics can be captured for reliable fault diagnosis/condition assessment. This study is based on the use of vibrational signals for fault isolation of electromagnetic pumps. From the vibrational signals, Mel frequency cepstral coefficients (MFCCs), the first-order and the second-order differentials were extracted and the salient features selected by a rank-based recursive feature elimination (RFE) of uncorrelated features. The proposed framework was tested and validated on five VSC63A5 electromagnetic pumps at various fault conditions and isolated/classified using the Gaussian kernel SVM (SVM-RBF-RFE). Results show that the proposed feature selection approach is computationally cheaper and significantly improves diagnostics performance. In addition, the proposed framework yields a comparatively better diagnostics results on electromagnetic pumps in comparison with other diagnostics methods, hence a more reliable diagnostics tool for electromagnetic pumps.
Creating Customized CGRAs for Scientific Applications
Authors: Charitopoulos George , Papaefstathiou Ioannis , Pnevmatikatos Dionisios N.
Published: February 2021

Executing complex scientific applications on Coarse Grain Reconfigurable Arrays (CGRAs) offers improvements in the execution time and/or energy consumption when compared to optimized software implementations or even fully customized hardware solutions. In this work, we explore the potential of application analysis methods in such customized hardware solutions. We offer analysis metrics from various scientific applications and tailor the results that are to be used by MC-Def, a novel Mixed-CGRA Definition Framework targeting a Mixed-CGRA architecture that leverages the advantages of CGRAs and those of FPGAs by utilizing a customized cell-array along, with a separate LUT array being used for adaptability. Additionally, we present the implementation results regarding the VHDL-created hardware implementations of our CGRA cell concerning various scientific applications.
Profitability of Energy Supply Contracting and Energy Sharing Concepts in a Neighborhood Energy Community: Business Cases for Austria
Authors: Monsberger Carolin , Fina Bernadette , Auer Hans
Published: February 2021

To ensure broad application of renewable and energy-efficient energy systems in buildings and neighborhoods, profitable business models are vital. Energy supply contracting helps building residents to overcome the barrier of high upfront investment costs while additionally reducing risks related to energy-saving mechanisms. This study examines profitability for energy contractors in a variety of business cases that simultaneously ensure energy cost savings for the residents. A mixed-integer linear optimization model is developed for a neighborhood energy community, consisting of three buildings with diverse usages. In the process, the optimum capacities of building-attached and building-integrated photovoltaics, a heat pump and a gas-fired mini combined heat and power unit are determined to cover the energy community’s electricity and heat load. Results show that cross-domain contracting within energy communities is highly profitable for both, the contractor and the residents, while the extent depends on the accounting method, assumed interest rate and depreciation time. The additional application of energy-efficiency measures in/on the buildings, constituting a combination of energy supply and energy performance contracting, further increases profitability. The investigation of several sensitivities shows that high grid energy costs for electricity and gas enhance profitability of local energy technologies, leading to an increase in optimal technology capacities.
Enhanced Contingency Analysis—A Power System Operator Tool
Authors: Bulat Hrvoje , Franković Dubravko , Vlahinić Saša
Published: February 2021

Contingency analysis (CA) is a well-known function in power system planning and operation. In accordance with CA results, the system operator dispenses information regarding static security of the power system (overloads and/or voltage outside tolerable limits). However, classic CA with remedial action schemes cannot distinguish safe operating regimes from potentially dangerous ones in terms of voltage (in)stability. In fact, voltage instability is considered as one of the major threats leading to power system insecurity. Therefore, in this study an enhanced contingency analysis (ECA) is presented where the classical CA is extended with static voltage analysis based on the modal analysis. The article presents a dedicated methodology for the proposed ECA tool, with special emphasis on the analysis of corrective measures provided by the system operator, intended for enhancing power system security (regulation transformer action, distributed generation and energy storage). Also the influence of the load model was analyzed by simulation and the main conclusions are presented. The study demonstrated the advantages that distributed generation resources and energy storage can provide in the context of voltage stability. Also, the simulations acknowledged the importance of correct load modeling, since over or under estimation of a certain load-type component can result in too optimistic or too pessimistic power system operation limits.
Acceleration Feature Extraction of Human Body Based on Wearable Devices
Authors: Huang Zhenzhen , Niu Qiang , You Ilsun , Pau Giovanni
Published: February 2021

Wearable devices used for human body monitoring has broad applications in smart home, sports, security and other fields. Wearable devices provide an extremely convenient way to collect a large amount of human motion data. In this paper, the human body acceleration feature extraction method based on wearable devices is studied. Firstly, Butterworth filter is used to filter the data. Then, in order to ensure the extracted feature value more accurately, it is necessary to remove the abnormal data in the source. This paper combines Kalman filter algorithm with a genetic algorithm and use the genetic algorithm to code the parameters of the Kalman filter algorithm. We use Standard Deviation (SD), Interval of Peaks (IoP) and Difference between Adjacent Peaks and Troughs (DAPT) to analyze seven kinds of acceleration. At last, SisFall data set, which is a globally available data set for study and experiments, is used for experiments to verify the effectiveness of our method. Based on simulation results, we can conclude that our method can distinguish different activity clearly.
Prediction of Dead Oil Viscosity: Machine Learning vs. Classical Correlations
Authors: Hadavimoghaddam Fahimeh , Ostadhassan Mehdi , Heidaryan Ehsan , Sadri Mohammad Ali , Chapanova Inna , Popov Evgeny , Cheremisin Alexey , Rafieepour Saeed
Published: February 2021

Dead oil viscosity is a critical parameter to solve numerous reservoir engineering problems and one of the most unreliable properties to predict with classical black oil correlations. Determination of dead oil viscosity by experiments is expensive and time-consuming, which means developing an accurate and quick prediction model is required. This paper implements six machine learning models: random forest (RF), lightgbm, XGBoost, multilayer perceptron (MLP) neural network, stochastic real-valued (SRV) and SuperLearner to predict dead oil viscosity. More than 2000 pressure–volume–temperature (PVT) data were used for developing and testing these models. A huge range of viscosity data were used, from light intermediate to heavy oil. In this study, we give insight into the performance of different functional forms that have been used in the literature to formulate dead oil viscosity. The results show that the functional form f(γAPI,T), has the best performance, and additional correlating parameters might be unnecessary. Furthermore, SuperLearner outperformed other machine learning (ML) algorithms as well as common correlations that are based on the metric analysis. The SuperLearner model can potentially replace the empirical models for viscosity predictions on a wide range of viscosities (any oil type). Ultimately, the proposed model is capable of simulating the true physical trend of the dead oil viscosity with variations of oil API gravity, temperature and shear rate.
Using Isopropanol as a Capping Agent in the Hydrothermal Liquefaction of Kraft Lignin in Near-Critical Water
Authors: Ahlbom Anders , Maschietti Marco , Nielsen Rudi , Lyckeskog Huyen , Hasani Merima , Theliander Hans
Published: February 2021

In this study, Kraft lignin was depolymerised by hydrothermal liquefaction in near-critical water (290–335 °C, 250 bar) using Na2CO3 as an alkaline catalyst. Isopropanol was used as a co-solvent with the objective of investigating its capping effect and capability of reducing char formation. The resulting product, which was a mixture of an aqueous liquid, containing water-soluble organic compounds, and char, had a lower sulphur content than the Kraft lignin. Two-dimensional nuclear magnetic resonance studies of the organic precipitates of the aqueous phase and the char indicated that the major lignin bonds were broken. The high molar masses of the char and the water-soluble organics, nevertheless, indicate extensive repolymerisation of the organic constituents once they have been depolymerised from the lignin. With increasing temperature, the yield of char increased, although its molar mass decreased. The addition of isopropanol increased the yield of the water-soluble organic products and decreased the yield of the char as well as the molar masses of the products, which is indicative of a capping effect.
Energy Pathways for Future Norwegian Residential Building Areas
Authors: Nord Natasa , Ding Yiyu , Skrautvol Ola , Eliassen Stian Fossmo
Published: February 2021

Owing to stricter building energy requirements, future buildings will be characterized by low base loads and occasional high peaks. However, future building areas will still contain existing and historical buildings with high energy demand. Meanwhile, there is a requirement that future building areas should obtain energy from renewable energy sources, while existing buildings need to be transited to renewables. Therefore, the aim of this study was to develop an approach for modelling energy pathways for future Norwegian residential building areas by analyzing different energy supply systems. Several calculation methods were combined: building simulation, energy supply technology simulation, heat demand aggregation, and data post-processing. The results showed that the energy pathways would be very dependent on CO2-factors for energy sources, and it is hard to predict accurate CO2-factors. An increasing housing stock development would slightly increase the CO2 emissions towards 2050, although the new buildings used much less energy and the existing buildings underwent renovation. A constant housing stock would yield a 22–27% reduction of CO2 emissions by 2050. This showed that implementing stricter building codes had a lower impact on the total CO2 emissions than CO2-factors and energy technologies. The focus should lie on energy supply systems.
Optimal Pitch Angle Strategy for Energy Maximization in Offshore Wind Farms Considering Gaussian Wake Model
Authors: Serrano González Javier , López Bruno , Draper Martín
Published: February 2021

This paper presents a new approach based on the optimization of the blade pitching strategy of offshore wind turbines in order to maximize the global energy output considering the Gaussian wake model and including the effect of added turbulence. A genetic algorithm is proposed as an optimization tool in the process of finding the optimal setting of the wind turbines, which aims to determine the individual pitch of each turbine so that the overall losses due to the wake effect are minimised. The integration of the Gaussian model, including the added turbulence effect, for the evaluation of the wakes provides a step forward in the development of strategies for optimal operation of offshore wind farms, as it is one of the state-of-the-art analytical wake models that allow the evaluation of the energy output of the project in a more reliable way. The proposed methodology has been tested through the execution of a set of test cases that show the ability of the proposed tool to maximize the energy production of offshore wind farms, as well as highlights the importance of considering the effect of added turbulence in the evaluation of the wake.
An Improved Cuckoo Search Algorithm for Maximum Power Point Tracking of Photovoltaic Systems under Partial Shading Conditions
Authors: Eltamaly Ali M.
Published: February 2021

The problem of partial shading has serious effects on the performance of photovoltaic (PV) systems. Adding a bypass diode in shunt to each PV module avoids hot-spot phenomena, but causes multi-peaks in the power–voltage (P–V) characteristics of the PV array, which cause traditional maximum power point tracking (MPPT) techniques to become trapped in local peaks. This problem has forced researchers to search for smart techniques to track global peaks and prevent the possibility of convergence at local peaks. Swarm optimization techniques have been used to fill this shortcoming; unfortunately, however, these techniques suffer from unacceptably long convergence time. Cuckoo search (CS) is one of the fastest and most reliable optimization techniques, making it an ideal option to be used as an MPPT of PV systems under dynamic partial shading conditions. The standard CS algorithm has a long conversion time, high failure rate, and high oscillations at steady state; this paper aims to overcome these problems and to fill this research gap by improving the performance of the CS. The results obtained from this technique are compared to five swarm optimization techniques. The comparison study shows the superiority of the improved CS strategy introduced in this paper over the other swarm optimization techniques.
A New Model for the Stochastic Point Reactor: Development and Comparison with Available Models
Authors: Elsayed Alamir , El-Beltagy Mohamed , Al-Juhani Amnah , Al-Qahtani Shorooq
Published: February 2021

The point kinetic model is a system of differential equations that enables analysis of reactor dynamics without the need to solve coupled space-time system of partial differential equations (PDEs). The random variations, especially during the startup and shutdown, may become severe and hence should be accounted for in the reactor model. There are two well-known stochastic models for the point reactor that can be used to estimate the mean and variance of the neutron and precursor populations. In this paper, we reintroduce a new stochastic model for the point reactor, which we named the Langevin point kinetic model (LPK). The new LPK model combines the advantages, accuracy, and efficiency of the available models. The derivation of the LPK model is outlined in detail, and many test cases are analyzed to investigate the new model compared with the results in the literature.