bluuebunny/crossref_metadata_2025 huggingface dataset:
Characteristics of Eukaryotic Plankton Communities in the Cold Water Masses and Nearshore Waters of the South Yellow Sea
Authors: Sun Yanfeng , Liu Yang , Wu Chao , Fu Xiaoting , Guo Congcong , Li Liuyang , Sun Jun
Published: January 2021

Eukaryotic plankton are important parts of the marine biome and play an important role in maintaining the stability of marine ecosystems. In order to characterize the eukaryotic plankton communities in the South Yellow Sea Cold Water Mass (CWM) and the South Yellow Sea nearshore waters (NW) in October 2019, Illumina high–throughput sequencing was performed using the 18S rDNA V9 region as the target gene. Environmental factors (depth, pH, salinity, temperature, Chl a, nitrate, nitrite, ammonium, silicate, phosphate) in two sea areas were measured, and their correlations with abundance and diversity of eukaryotic plankton were analyzed. A total of 807 species of plankton were identified, of which 663 species in 24 categories were from the CWM area, and 614 species in 26 categories were from NW. The total phytoplankton abundance in CWM waters was higher than that in NW. Dinophyta and Bacillariophyta were the most abundant phyla of phytoplankton in the two areas. Arthropoda and Cnidaria were the major zooplankton taxa. The dominant fungal population was mainly Basidiomycota. Both the CWM and NW have effects on dissolved inorganic nutrient concentrations and plankton abundance. Environmental factor correlation analysis showed that the concentration of dissolved inorganic nutrients within the CWM increased with water depth and the abundance of plankton gradually increased. Ammonium salts, nitrates, phosphates, silicates and water depth were important factors affecting phytoplankton growth. Phytoplankton abundance increased with increasing concentrations of inorganic nutrients. Bacillariophyta showed a strong positive correlation with silicates and depth. Depth and microscopic phytoplankton abundance were important factors influencing the structure of the zooplankton community.
Drugs, Active Ingredients and Diseases Database in Spanish. Augmenting the Resources for Analyses on Drug–Illness Interactions
Authors: López-Rodríguez Irene , Reyes-Manzano César F. , Reyes-Ramírez Israel , Contreras-Uribe Tania J. , Guzmán-Vargas Lev
Published: January 2021

Quantitative and qualitative data on active-ingredient drug composition are essential information for characterizing near-field exposure of consumers to product-related chemicals, among other things. Equally as important is the characterization of the relationship between one or many active ingredients in terms of the diseases they are prescribed for. Such evaluations, however, require quantitative information at different anatomical levels. To complement the available sources of information on active substances and diseases, we have designed a database with enough versatility to potentially be used in a variety of analyzes. By using information provided by a well-established online pharmacological dictionary, we present a database with 11 tables which are easy to access and manipulate. Specifically, we present datasets containing the details of 12,827 marketed drug products, 40,164 diseases, 6231 active pharmaceutical ingredients and 4093 side effects. We exemplify the usefulness of our database with three simple visualizations, which confirm the importance of the data for quantifying the complexity in the associations among active substances, diseases and side effects. Although there are databases with detailed information on active substances and diseases, none of them can be found in Spanish. Our work presents an option that contributes substantially to obtaining well classified information in order to evaluate the roles of active pharmaceutical ingredients, diseases and side effects. These datasets also provide information about clinical and pharmacological groupings which may be useful for clinical and academic researchers. The database will be regularly updated and extended with the newly available Virtual Medicinal Products.
Type I Neurofibromatosis: Case Report and Review of the Literature Focused on Oral and Cutaneous Lesions
Authors: Buchholzer Samanta , Verdeja Raùl , Lombardi Tommaso
Published: January 2021

Neurofibromatosis type 1 (NF1) is a common genetic disease whose dermatological lesions are at the forefront of its development. Cutaneous manifestations include café au lait spots, intertriginous freckling, and neurofibromas which appear during childhood and adolescence and are part of the clinical criteria to diagnose NF1. However, it is only recently that oral manifestations have been highlighted in many studies as frequently associated to NF1. This article aims to review oral and cutaneous manifestations related to NF1 and to report a case of a 51-year-old male with skin and oral neurofibromas related to NF1. Our patient presented with lesions on the gingiva, a rare localization that takes a hypertrophic form mimicking other various pathological conditions. Although not frequent, malignant transformation in NF1, especially regarding plexiform neurofibromas, is well established. Patients with NF1 therefore have regular follow-ups based on clinical examination, as sarcomatous transformation brings an extremely poor prognosis, recurrences and distant metastasis being common.
The Effects of COVID-19 on Placenta and Pregnancy: What Do We Know So Far?
Authors: Wong Yin Ping , Khong Teck Yee , Tan Geok Chin
Published: January 2021

The current coronavirus disease 2019 (COVID-19) pandemic, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has inflicted a serious health crisis globally. This virus is associated with a spectrum of respiratory illness ranging from asymptomatic, mild to severe pneumonia, and acute respiratory distress syndrome. Accumulating evidence supports that COVID-19 is not merely a respiratory illness per se, but potentially affects other organ systems including the placenta. SARS-CoV-2 gains access to human cells via angiotensin-converting enzyme 2 (ACE-2). The abundance of ACE-2 on the placental cell surface, especially the syncytiotrophoblasts, could potentially contribute to vertical transplacental transmission to the fetus following maternal COVID-19 infection. Intriguingly, despite the placentas being tested positive for SARS-CoV-2, there are very few newborns that manifest virus-induced diseases. The protective effects of the placental barrier to viral infection, limiting the spread of the virus to newborn infants, remain a mystery. The detrimental role of COVID-19 in pregnancies is largely debatable, although COVID-19 maternal infection has been implicated in unfavorable pregnancy outcomes. In this review, we summarize the pathological features manifested in placenta due to COVID-19 maternal infection that have been previously reported, and relate them to the possible disease manifestation. The potential mechanistic pathways associated with transplacental viral transmission and adverse pregnancy outcomes are also discussed.
A Rare Entity–Percutaneous Lead Extraction in a Very Late Onset Pacemaker Endocarditis: Case Report and Review of Literature
Authors: Ursaru Andreea Maria , Haba Cristian Mihai , Popescu Ștefan Eduard , Crișu Daniela , Petriș Antoniu Octavian , Tesloianu Nicolae Dan
Published: January 2021

The number of infections related to cardiac implantable electronic devices (CIEDs) has increased as the number of devices implanted around the world has grown exponentially in recent years. CIED complications can sometimes be difficult to diagnose and manage, as in the case of lead-related infective endocarditis. We present the case of a 48-year-old male diagnosed with Staphylococcus aureus device-related infective endocarditis, 12 years after the implant of a single chamber pacemaker. A recent history of the patient includes two urinary catheterizations due to obstructive uropathy in the context of a prostatic adenoma, 2 months previously, both without antibiotic prophylaxis; no other possible entry sites were found and no history of other invasive procedures. After initiation of antibiotic therapy according to antibiotic susceptibility testing, we decided to remove the right ventricular passive fixation lead along with the vegetation and pacemaker generator; because of severe lead adhesions in the costoclavicular region, and especially in the right ventricle, we needed mechanical sheaths to remove the abundant fibrous tissue that encompassed the lead. After a difficult, but successful, lead extraction along with a large vegetation and 6 weeks’ antibiotic therapy, the clinical and biological evolution was favorable, without reappearance of symptoms. While very late lead endocarditis is a rarity, late lead-related infective endocarditis (more than 12 months elapsed since implant) is not an exception; this is why we find that endocarditis prophylaxis should be reconsidered in certain patient categories, our patient being proof that procedures with neglectable endocarditis risk according to the guidelines can lead to bacterial endocarditis.
Transvaginal Strain Elastosonography May Help in the Differential Diagnosis of Endometriosis?
Authors: Szabó Gábor , Madár István , Bokor Attila , Rigó János
Published: January 2021

Dear Editor, [...]
From Nutcracker Phenomenon to Nutcracker Syndrome: A Pictorial Review
Authors: Granata Antonio , Distefano Giulio , Sturiale Alessio , Figuera Michele , Foti Pietro Valerio , Palmucci Stefano , Basile Antonio
Published: January 2021

Left renal vein (LRV) entrapment, also known as nutcracker phenomenon if it is asymptomatic, is characterized by abnormality of outflow from the LRV into the inferior vena cava (IVC) due to extrinsic LRV compression, often accompanied by demonstrable lateral (hilar) dilatation and medial (mesoaortic) stenosis. Nutcracker syndrome, on the other hand, includes a well-defined set of symptoms, and the severity of these clinical manifestations is related to the severity of anatomic and hemodynamic findings. With the aim of providing practical guidance for nephrologists and radiologists, we performed a review of the literature through the PubMed database, and we commented on the definition, the main clinical features, and imaging pattern of this syndrome; we also researched the main therapeutic approaches validated in the literature. Finally, from the electronic database of our institute, we have selected some characteristic cases and we have commented on the imaging pattern of this disease.
Dual-Antigen System Allows Elimination of False Positive Results in COVID-19 Serological Testing
Authors: Komarov Andrei , Kaznadzey Anna , Li Yue , Kireeva Maria , Mazo Ilya
Published: January 2021

Determining the presence of antibodies in serum is important for epidemiological studies, to be able to confirm whether a person has been infected, predicting risks of them getting sick and spreading the disease. During the ongoing pandemic of COVID-19, a positive serological test result can suggest if it is safe to return to work and re-engage in social activities. Despite a multitude of emerging tests, the quality of respective data often remains ambiguous, yielding a significant fraction of false positive results. The human organism produces polyclonal antibodies specific to multiple viral proteins, so testing simultaneously for multiple antibodies appeared a practical approach for increasing test specificity. We analyzed immune response and testing potential for a spectrum of antigens derived from the spike and nucleocapsid proteins of SARS-CoV-2, developed a dual-antigen testing system in the ELISA format and designed a robust algorithm for data processing. Combining nucleocapsid protein and receptor-binding domain for analysis allowed us to completely eliminate false positive results in the tested cohort (achieving specificity within a 95% confidence interval of 97.2–100%). We also tested samples collected from different households, and demonstrated differences in the immune response of COVID-19 patients and their family members; identifying, in particular, asymptomatic cases showing strong presence of studied antibodies, and cases showing none despite confirmed close contacts with the infected individuals.
Towards Routine Implementation of Liquid Biopsies in Cancer Management: It Is Always Too Early, until Suddenly It Is Too Late
Authors: IJzerman Maarten J. , de Boer Jasper , Azad Arun , Degeling Koen , Geoghegan Joel , Hewitt Chelsee , Hollande Frédéric , Lee Belinda , To Yat Ho , Tothill Richard W. , Wright Gavin , Tie Jeanne , Dawson Sarah-Jane
Published: January 2021

Blood-based liquid biopsies are considered a new and promising diagnostic and monitoring tool for cancer. As liquid biopsies only require a blood draw, they are non-invasive, potentially more rapid and assumed to be a less costly alternative to genomic analysis of tissue biopsies. A multi-disciplinary workshop (n = 98 registrations) was organized to discuss routine implementation of liquid biopsies in cancer management. Real-time polls were used to engage with experts’ about the current evidence of clinical utility and the barriers to implementation of liquid biopsies. Clinical, laboratory and health economics presentations were given to illustrate the opportunities and current levels of evidence, followed by three moderated break-out sessions to discuss applications. The workshop concluded that tumor-informed assays using next-generation sequencing (NGS) or PCR-based genotyping assays will most likely provide better clinical utility than tumor-agnostic assays, yet at a higher cost. For routine application, it will be essential to determine clinical utility, to define the minimum quality standards and performance of testing platforms and to ensure their use is integrated into current clinical workflows including how they complement tissue biopsies and imaging. Early health economic models may help identifying the most viable application of liquid biopsies. Alternative funding models for the translation of complex molecular diagnostics, such as liquid biopsies, may also be explored if clinical utility has been demonstrated and when their use is recommended in multi-disciplinary consensus guidelines.
Electrochemical Aptasensors: Current Status and Future Perspectives
Authors: Radi Abd-Elgawad , Abd-Ellatief Maha Ragaa
Published: January 2021

This article reviews the progress of diversity of electrochemical aptasensor for target analytes detection. The immobilization strategies of aptamers on an electrode surface are addressed. The aptasensors are also introduced in compliance with the assay platforms. Many electrochemical aptasensors are nearly identical to conventional immunochemical approaches, sandwich and competition assays using electroactive signaling moieties. Others are “signal-on” and “sign-off” aptasensors credited to the target binding-induced conformational change of aptamers. Label-free aptasensors are also highlighted. Furthermore, the aptasensors applied for clinically important biomarkers are emphasized.
Efficient Detection of Knee Anterior Cruciate Ligament from Magnetic Resonance Imaging Using Deep Learning Approach
Authors: Javed Awan Mazhar , Mohd Rahim Mohd , Salim Naomie , Mohammed Mazin , Garcia-Zapirain Begonya , Abdulkareem Karrar
Published: January 2021

The most commonly injured ligament in the human body is an anterior cruciate ligament (ACL). ACL injury is standard among the football, basketball and soccer players. The study aims to detect anterior cruciate ligament injury in an early stage via efficient and thorough automatic magnetic resonance imaging without involving radiologists, through a deep learning method. The proposed approach in this paper used a customized 14 layers ResNet-14 architecture of convolutional neural network (CNN) with six different directions by using class balancing and data augmentation. The performance was evaluated using accuracy, sensitivity, specificity, precision and F1 score of our customized ResNet-14 deep learning architecture with hybrid class balancing and real-time data augmentation after 5-fold cross-validation, with results of 0.920%, 0.916%, 0.946%, 0.916% and 0.923%, respectively. For our proposed ResNet-14 CNN the average area under curves (AUCs) for healthy tear, partial tear and fully ruptured tear had results of 0.980%, 0.970%, and 0.999%, respectively. The proposing diagnostic results indicated that our model could be used to detect automatically and evaluate ACL injuries in athletes using the proposed deep-learning approach.
The Route to Autism Spectrum Diagnosis in Pediatric Practice in Bulgaria
Authors: Ivanov Ivan , Pacheva Iliyana , Timova Elena , Iordanova Ralitsa , Galabova Fani , Gaberova Katerina , Petkova Aneliya , Kotetarov Vasil , Panova Margarita , Tonchev Nikolay , Franz Lauren
Published: January 2021

Diagnosis of autism spectrum disorder (ASD) before the age of three years is a challenge. Analyzing the present practice may help reaching that goal. Aim: To investigate developmental abnormalities and diagnostic pathway of ASD patients in pediatric practice. Methods: Retrospective cross-sectional study of 192 children aged 13 months to 17 years 11 months (average 4 years 9 months), investigated in an outpatient and hospital setting from January 2015 to June 2018 by a semi-structured history and clinical examination, and diagnosed with ASD by Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria. Results: Behavioral peculiarities were detected in the history of the first two years of life in 74.8% of the subjects. The first developmental abnormalities were noticed by the parents at ages from 8 to 36 months (mean 15.6 months) and were predominantly in speech (in 94.6%) and non-verbal communication (11.3%). Developmental regression was reported in 42.1% of the patients occurring between the ages of 6 and 50 months (mean 17.9 months), affecting most commonly speech (88.4% of cases), non-verbal communication (29.2%), and behavior (12.8%). By history, the first manifestations of ASD were noticed at ages from 8 months to 84 months (mean 18.5 months), and were disorders of expressive speech (in 66.7% of cases), receptive speech (in 45.8%), non-verbal communication (35.4%), behavior (27.6%), play (8.9%), socialization (5.7%), and joint attention (2.1%). The most common motive for specialized consultation was delay in language development—in 84.6% of children. The age of ASD diagnosis varied between 12 and 132 months (mean 39.7 months), and the time period between first ASD manifestations and diagnosis was in the range of 0 to 79 months (mean 23.3 months). Many symptoms of abnormal social communication, unnoticed by parents, were detected objectively in more than 95% of the cases—absent or rare spontaneous or reciprocal smile; lack of sharing of interest or affect; abnormal eye contact; lack of finger pointing; lack of gaze to a pointed object; poor facial expressions; lack of imaginary play, etc. Conclusions: Almost two years are needed for diagnosing abnormal development in other domains besides speech in ASD patients. Diagnosis before the age of three years can be achieved by focusing parents’ and pediatricians’ attention on social communication and behavior in patients with speech delay or developmental regression.
Signal Fluctuations and the Information Transmission Rates in Binary Communication Channels
Authors: Pregowska Agnieszka
Published: January 2021

In the nervous system, information is conveyed by sequence of action potentials, called spikes-trains. As MacKay and McCulloch suggested, spike-trains can be represented as bits sequences coming from Information Sources (IS). Previously, we studied relations between spikes’ Information Transmission Rates (ITR) and their correlations, and frequencies. Now, I concentrate on the problem of how spikes fluctuations affect ITR. The IS are typically modeled as stationary stochastic processes, which I consider here as two-state Markov processes. As a spike-trains’ fluctuation measure, I assume the standard deviation σ, which measures the average fluctuation of spikes around the average spike frequency. I found that the character of ITR and signal fluctuations relation strongly depends on the parameter s being a sum of transitions probabilities from a no spike state to spike state. The estimate of the Information Transmission Rate was found by expressions depending on the values of signal fluctuations and parameter s. It turned out that for smaller s<1, the quotient ITRσ has a maximum and can tend to zero depending on transition probabilities, while for 1<s, the ITRσ is separated from 0. Additionally, it was also shown that ITR quotient by variance behaves in a completely different way. Similar behavior was observed when classical Shannon entropy terms in the Markov entropy formula are replaced by their approximation with polynomials. My results suggest that in a noisier environment (1<s), to get appropriate reliability and efficiency of transmission, IS with higher tendency of transition from the no spike to spike state should be applied. Such selection of appropriate parameters plays an important role in designing learning mechanisms to obtain networks with higher performance.
Calibration Invariance of the MaxEnt Distribution in the Maximum Entropy Principle
Authors: Korbel Jan
Published: January 2021

The maximum entropy principle consists of two steps: The first step is to find the distribution which maximizes entropy under given constraints. The second step is to calculate the corresponding thermodynamic quantities. The second part is determined by Lagrange multipliers’ relation to the measurable physical quantities as temperature or Helmholtz free energy/free entropy. We show that for a given MaxEnt distribution, the whole class of entropies and constraints leads to the same distribution but generally different thermodynamics. Two simple classes of transformations that preserve the MaxEnt distributions are studied: The first case is a transform of the entropy to an arbitrary increasing function of that entropy. The second case is the transform of the energetic constraint to a combination of the normalization and energetic constraints. We derive group transformations of the Lagrange multipliers corresponding to these transformations and determine their connections to thermodynamic quantities. For each case, we provide a simple example of this transformation.
Long-Term Lateral Semicircular Canal Function in Children with Cochlear Implants: Results of Video Head Impulse Test
Authors: Nassif Nader , Balzanelli Cristiano , Redaelli de Zinis Luca Oscar
Published: January 2021

In children with profound deafness, bilateral cochlear implant (CI) is an effective, established procedure. However, its safety on vestibular function has recently been debated. The goal of this study is to evaluate the long-term lateral semicircular canal high-frequency vestibulo-oculomotor reflex (LSC HF VOR) in children with CI by video head impulse testing (vHIT). This is a cross-sectional study assessing a cohort of children who received either a unilateral (12) or a bilateral (12) cochlear implant (CI), compared with a control group of 12 normal-hearing children. No significant LSC HF VOR gain difference was found between CI users and controls. In the unilaterally implanted group, the LSC HF VOR gain measured in the “CI-ON” condition was significantly higher than in the “CI-OFF” condition, both in the implanted and in the non-implanted ear. In the bilaterally implanted group, the difference between the two conditions was not significant. Our results do not show any impairment of LSC HF VOR function in children with CI compared to normal-hearing children in the long-term period. This suggests that both unilateral and simultaneous/sequential bilateral CI are procedures that do not impair HF LSC long-term function when analyzed by vHIT.
Multivariate Analysis of Attitudes, Knowledge and Use of ICT in Students Involved in Virtual Research Seedbeds
Authors: Martinez-Daza Magda Alejandra , Guzmán Rincón Alfredo , Castaño Rico Jader Alexis , Segovia-García Nuria , Montilla Buitrago Harvey Yesid
Published: January 2021

The incorporation of information and communication technologies (ICTs) in higher education has been carried out in a transversal manner within the curriculum, and the processes of formative research in both face-to-face and virtual programmes are not an exception to this process. In this context, it is recognised that students’ perceptions of the inclusion of technologies in the classroom can influence their teaching and learning process; however, they have not been widely addressed in multiple settings including research seedbeds. Thus, this paper aims to identify such perceptions represented in the attitudes, knowledge and uses of ICTs in students ascribed to the research seedbed in a virtual business administration programme of an Institution of Higher Education located in Colombia. For its fulfillment, the ACUTIC scale was applied to a sample of 65 students in order to identify these perceptions through a hierarchical cluster analysis, a single factor analysis of variance (ANOVA) test, a post hoc Tukey method and a factor analysis. The main result is that attitudes, knowledge and use of ICTs are varied and they can be represented in three clusters. In general, the attitude towards the incorporation of technologies in the research seedbed is positive; however, there is a gap in terms of knowledge and use, especially of those tools oriented to the disciplinary field and research.
Microstructure and Thermoelectric Properties of (Bi0.48Sb1.52)Te3 Thick Films Prepared with Tape Casting Method
Authors: Liu Lichen , Cao Ziping , Chen Min , Jiang Jun
Published: January 2021

This paper reports the fabrication and characterization of (Bi0.48Sb1.52)Te3 thick films using a tape casting process on glass substrates. A slurry of thermoelectric (Bi0.48Sb1.52)Te3 was developed and cured thick films were annealed in a vacuum chamber at 500–600 °C. The microstructure of these films was analyzed, and the Seebeck coefficient and electric conductivity were tested. It was found that the subsequent annealing process must be carefully designed to achieve good thermoelectric properties of these samples. Conductive films were obtained after annealing and led to acceptable thermoelectric performance. While the properties of these initial materials are not at the level of bulk materials, this work demonstrates that the low-cost tape casting technology is promising for fabricating thermoelectric modules for energy conversion.
Modeling Energy Communities with Collective Photovoltaic Self-Consumption: Synergies between a Small City and a Winery in Portugal
Authors: Pontes Luz Guilherme , Amaro e Silva Rodrigo
Published: January 2021

The recently approved regulation on Energy Communities in Europe is paving the way for new collective forms of energy consumption and production, mainly based on photovoltaics. However, energy modeling approaches that can adequately evaluate the impact of these new regulations on energy community configurations are still lacking, particularly with regards to the grid tariffs imposed on collective systems. Thus, the present work models three different energy community configurations sustained on collective photovoltaics self-consumption for a small city in southern Portugal. This energy community, which integrates the city consumers and a local winery, was modeled using the Python-based Calliope framework. Using real electricity demand data from power transformers and an actual winery, the techno-economic feasibility of each configuration was assessed. Results show that all collective arrangements can promote a higher penetration of photovoltaic capacity (up to 23%) and a modest reduction in the overall cost of electricity (up to 8%). However, there are clear trade-offs between the different pathways: more centralized configurations have 53% lower installation costs but are more sensitive to grid use costs (which can represent up to 74% of the total system costs). Moreover, key actor’s individual self-consumption rate may decrease by 10% in order to benefit the energy community as a whole.
Examining the Journey of a Pay-as-You-Go Solar Home System Customer: A Case Study of Rwanda
Authors: Kizilcec Vivien , Parikh Priti , Bisaga Iwona
Published: January 2021

Solar home systems (SHSs) are successfully addressing energy access deficits across the globe, particularly when combined with pay-as-you-go (PAYG) payment models, allowing households to pay for energy services in small instalments. To increase energy access, it is vital to understand the PAYG SHS customer journey in depth. To aid this, the paper presents unique data from active customers, consisting of structured interviews (n = 100) and two focus groups (n = 24) across two districts in Rwanda. These results are presented under a novel customer journey framework, which describes all the individual stages a customer might experience, including awareness and understanding, purchase, usage, upgrade, recommendation and retaining or switching energy source. The paper reveals that the customer journey is non-linear and cyclical in nature, acknowledging that a household operates in a social network within which they could influence or be influenced by others. It also highlights the growing importance of SHS recommendations in raising awareness of SHSs, pointing to the shifts in the off-grid energy market environment where customer awareness no longer appears to be a main adoption barrier.
Maximum Power Point Tracking Based on Reinforcement Learning Using Evolutionary Optimization Algorithms
Authors: Bavarinos Kostas , Dounis Anastasios , Kofinas Panagiotis
Published: January 2021

In this paper, two universal reinforcement learning methods are considered to solve the problem of maximum power point tracking for photovoltaics. Both methods exhibit fast achievement of the MPP under varying environmental conditions and are applicable in different PV systems. The only required knowledge of the PV system are the open-circuit voltage, the short-circuit current and the maximum power, all under STC, which are always provided by the manufacturer. Both methods are compared to a Fuzzy Logic Controller and the universality of the proposed methods is highlighted. After the implementation and the validation of proper performance of both methods, two evolutionary optimization algorithms (Big Bang—Big Crunch and Genetic Algorithm) are applied. The results demonstrate that both methods achieve higher energy production and in both methods the time for tracking the MPP is reduced, after the application of both evolutionary algorithms.
Cloud Energy Storage System Operation with Capacity P2P Transaction
Authors: Sim Jungsub , Kim Minsoo , Kim Dongjoo , Kim Hongseok
Published: January 2021

Research on energy storage systems (ESS) is actively aiming to mitigate against the unreliability of renewable energy sources (RES), and ESS operation and management has become one of the most important research topics. Since installing ESS for each user requires high investment cost, a study on cloud ESS gains attention recently. Cloud ESS refers to an ESS that is logically shared by multiple users as if they have their own ESS in their premises. In this paper, we propose a new cloud ESS sharing technique that allows capacity P2P transactions among users. Since cloud ESS is a virtual facility that is linked to an actual ESS, it is easy for users to sell the unused storage capacity to other users or to buy additional capacity from other users during operation. We also propose a system that encourages users to completely entrust the cloud ESS operator and share the extra benefit with the operator and other users. To verify the proposed method, we demonstrate the benefit of capacity P2P transaction based on real year-round data of users.
Study on Outlet Temperature Control of External Receiver for Solar Power Tower
Authors: Zhang Qiang , Jiang Kaijun , Kong Yanqiang , Wu Jiangbo , Du Xiaoze
Published: January 2021

Due to the change of direct normal irradiance (DNI) and the change of output power load, the receiver of the solar tower is in an unstable state in the actual operation. In this paper, a 100 MW external cylindric receiver is designed and modelled. The dynamic and comprehensive model is established for the receiver, including the thermal and mechanical equations. The temperature control strategy is applied to the receiver model. The validity of the control strategy is verified by disturbance experiments, including DNI, the inlet temperature of the heat transfer fluid (HTF), and the weather data on a cloudy day. The response characteristics of the receiver are demonstrated. Its thermal lag characteristics and restraining effect on the fluctuating environment are revealed. The dangerous occasion of the receiver during operation are detected, including the overheat of the local panel, and the dissociation point of the molten salt. Both the robustness and the deficiency of the control strategy of the receiver are pointed out. The research results will contribute to the control strategy formulation of the SPT (solar power tower) station.
Amphiphilic Block Copolymers with Vinyl Caprolactam as Kinetic Gas Hydrate Inhibitors
Authors: Rajput Faraz , Maric Milan , Servio Phillip
Published: January 2021

Macrosurfactants consisting of water-soluble poly(vinylcaprolactam) (PVCap) or poly(vinylpyrrolidone) (PVP) segments with comparatively shorter hydrophobic poly(styrene) (PS) or poly(2,3,4,5,6-pentafluorostyrene) (PPFS) segments were used as kinetic hydrate inhibitors (KHIs). These were synthesized with 2-cyanopropan-2-yl N-methyl-N-(pyridin-4-yl)dithiocarbamate switchable reversible addition–fragmentation chain transfer (RAFT) agent at 60 °C or 90 °C for 1-P(S/PFS) or 1-PVCap, respectively, followed by chain extension at 90 °C or 70 °C with PVCap or PVP, respectively. The addition of PVCap to the pure methane-water system resulted in a 53% reduction of methane consumption (comparable to PVP with 51% inhibition) during the initial growth phase. A PS-PVCap block copolymer comprised of 10 mol% PS and 90 mol% PVCap improved inhibition to 56% compared to the pure methane-water system with no KHIs. Substituting PS with a more hydrophobic PPFS segment further improved inhibition to 73%. By increasing the ratio of the hydrophobic PS- to PVCap- groups in the polymer, an increase of its inhibition potential was measured. For PPFS-PVCap, an increase of PPFS ratio from 5% to 10% decreased the methane formation rate by 6%. However, PPFS-PVCap block copolymers with more than 20 mol% PPFS were unable to dissolve in water due to increase in hydrophobicity and the attendant low critical micelle concentration (CMC).
Evaluation of Tooth Space Pressure and Incomplete Filling in External Gear Pumps by Means of Three-Dimensional CFD Simulations
Authors: Corvaglia Alessandro , Rundo Massimo , Casoli Paolo , Lettini Antonio
Published: January 2021

The paper presents the computational fluid dynamics simulation of an external gear pump for fluid power applications. The aim of the study is to test the capability of the model to evaluate the pressure in a tooth space for the entire shaft revolution and the minimum inlet pressure for the complete filling. The model takes into account the internal fluid leakages and two different configurations of the thrust plates have been considered. The simulations in different operating conditions have been validated with proper high dynamics transducers measuring the internal pressure in a tooth space for the entire shaft revolution. Steady-state simulations have been also performed in order to detect the fall of the flow rate due to the incomplete filling of the tooth spaces when the inlet pressure is reduced. It has been demonstrated that, despite the need of a compromise for overcoming the limitation of considering fixed positions of the gears’ axes and of the thrust plates, significant results can be obtained, making the CFD approach very suitable for such analyses.
Engineering Parameters of Rice Straw Concrete with Granulated Blast Furnace Slag
Authors: Ashour Taha , Morsy Mohamad , Korjenic Azra , Fischer Henriette , Khalil Mervat , Sesto Eldira , Orabi Mohammed , Yehia Ibrahim
Published: January 2021

The construction industry is responsible for a large amount of both embodied carbon and emissions. Especially with concrete, there is still a lot of potential for designing recipes in a more ecological way. Approaches to reduce the environmental impact of concrete include the use of industrial and agricultural by-products. This study combines the approaches of replacing cement with granulated blast furnace slag and the use of NaOH-treated rice straw fibers. The research objective comprises the design of an ecologically optimized concrete as well as the question of whether a pretreatment of rice straw fibers with NaOH improves the performance of the designed concrete. The method includes mechanical and physical testing of the of the designed concrete as well as an optical analysis with a scanning electron microscope. The results indicated that treating rice straw with 1% NaOH indicates a better bond between fibers and the surrounding matrix. The tests in which the rice straw was treated with NaOH achieved a higher density, splitting strength, tensile strength and compressive strength. The study contributes an ecologically optimized concrete with granulated blast furnace slag and NaOH-treated rice straw concrete, which shows a great potential as an environmentally friendly, low-cost construction material.
Numerical Investigation of a Phase Change Material Including Natural Convection Effects
Authors: Andreozzi Assunta , Iasiello Marcello , Tucci Claudio
Published: January 2021

Nowadays, Organic Rankine Cycle (ORC) is one of the most promising technologies analyzed for electrical power generation from low-temperature heat such as renewable energy sources (RES), especially solar energy. Because of the solar source variation throughout the day, additional Thermal Energy Storage (TES) systems can be employed to store the energy surplus saved during the daytime, in order to use it at nighttime or when meteorological conditions are adverse. In this context, latent heat stored in phase-change transition by Phase Change Materials (PCM) allows them to stock larger amounts of energy because of the larger latent energy values as compared to the specific heat capacity. In this study, a thermal analysis of a square PCM for a solar ORC is carried out, considering four different boundary conditions that refer to different situations. Furthermore, differences in including or not natural convection effects in the model are shown. Governing equations for the PCM are written with references to the heat capacity method and solved with a finite element scheme. Experimental data from literature are employed to simulate the solar source using a time-variable temperature boundary condition. Results are presented in terms of temperature profiles, stored energy, velocity fields and melting fraction, showing that natural convection effects are remarkable on the temperature values and consequently on the stored energy achieved.
Compensation Method for Estimating the State of Charge of Li-Polymer Batteries Using Multiple Long Short-Term Memory Networks Based on the Extended Kalman Filter
Authors: Shin Donghoon , Yoon Beomjin , Yoo Seungryeol
Published: January 2021

Many battery state of charge (SOC) estimation methods have been studied for decades; however, it is still difficult to precisely estimate SOC because it is nonlinear and affected by many factors, including the battery state and charge–discharge conditions. The extended Kalman filter (EKF) is generally used for SOC estimation, however its accuracy can decrease owing to the uncertain and inaccurate parameters of battery models and various factors with different time scales affecting the SOC. Herein, a SOC estimation method based on the EKF is proposed to obtain robust accuracy, in which the errors are compensated by a long short-term memory (LSTM) network. The proposed approach trains the errors of the EKF results, and the accurate SOC is estimated by applying calibration values corresponding to the condition of the battery and its load profiles with the help of LSTM. Furthermore, a multi-LSTM structure is implemented, and it adopts the ensemble average to guarantee estimation accuracy. SOC estimation with a root mean square error of less than 1% was found to be close to the actual SOC calculated by coulomb counting. Moreover, once the EKF model was established and the network trained, it was possible to predict the SOC online.
A Study of UVER in Santiago, Chile Based on Long-Term In Situ Measurements (Five Years) and Empirical Modelling
Authors: González-Rodríguez Lisdelys , de Oliveira Amauri Pereira , Rodríguez-López Lien , Rosas Jorge , Contreras David , Baeza Ana Carolina
Published: January 2021

Ultraviolet radiation is a highly energetic component of the solar spectrum that needs to be monitored because is harmful to life on Earth, especially in areas where the ozone layer has been depleted, like Chile. This work is the first to address the long-term (five-year) behaviour of ultraviolet erythemal radiation (UVER) in Santiago, Chile (33.5° S, 70.7° W, 500 m) using in situ measurements and empirical modelling. Observations indicate that to alert the people on the risks of UVER overexposure, it is necessary to use, in addition to the currently available UV index (UVI), three more erythema indices: standard erythemal doses (SEDs), minimum erythemal doses (MEDs), and sun exposure time (tery). The combination of UVI, SEDs, MEDs, and tery shows that in Santiago, individuals with skin types III and IV are exposed to harmfully high UVER doses for 46% of the time that UVI indicates is safe. Empirical models predicted hourly and daily values UVER in Santiago with great accuracy and can be applied to other Chilean urban areas with similar climate. This research inspires future advances in reconstructing large datasets to analyse the UVER in Central Chile, its trends, and its changes.
Ovarian Rejuvenation Using Autologous Platelet-Rich Plasma
Authors: Vo Tuyen Kim Cat , Tanaka Yuka , Kawamura Kazuhiro
Published: January 2021

Advanced maternal age is associated with the natural oocyte depletion, leading to low oocyte yield, high infertility treatment cancellation rates, and eventual decreases in pregnancy rates. Various innovative interventions have been introduced to improve the outcome of infertility treatment for aging patients. Numerous published data demonstrated that early follicle development was regulated by intraovarian growth factors through autocrine or paracrine mechanisms. Platelet-rich plasma (PRP), a plasma fraction of peripheral blood with a high concentration of platelets, has been implemented in regenerative medicine in the last decade. The plasma contains a variety of growth factors that were suggested to be able to enhance angiogenesis regeneration and the cell proliferation process. The initial report showed that an intraovarian injection of PRP improved the hormonal profile and increased the number of retrieved oocytes in patients with diminished ovarian reserve. Subsequently, several studies with larger sample sizes have reported that this approach resulted in several healthy live births with no apparent complications. However, the use of ovarian PRP treatment needs to be fully investigated, because no randomized controlled trial has yet been performed to confirm its efficacy.
Traditional Villages in Forest Areas: Exploring the Spatiotemporal Dynamics of Land Use and Landscape Patterns in Enshi Prefecture, China
Authors: Wang Luqi , Wen Chen
Published: January 2021

In the context of the implementation of rural revitalization strategies in China, limited attention has been paid to the landscape patterns of traditional villages that are located in vulnerable environments. This study explores the land-use dynamics and landscape patterns of traditional villages in Enshi Prefecture, China. Based on a spatiotemporal analysis of land use and landscape metrics, we analyzed the prefecture and the environment surrounding 73 traditional villages. The results show that, from 2000 to 2020, most villages have had an increased share of forest, a decreased share of cultivated land and grassland, and a decreased level of landscape diversity and fragmentation. Additionally, villages at a higher elevation or with a steeper slope are associated with a lower level of landscape diversity, a lower proportion of cultivated land and grassland, and a higher proportion of forest. Overall, although the environment around the villages does not show dramatic changes in landscape patterns, land-use change at the prefecture level shows an increasing rate of urban growth from 2010 to 2020. For remote traditional villages in ecologically vulnerable and less-developed areas, caution is needed in the tradeoff between environmental conservation and economic development.
Using U-Net-Like Deep Convolutional Neural Networks for Precise Tree Recognition in Very High Resolution RGB (Red, Green, Blue) Satellite Images
Authors: Korznikov Kirill A. , Kislov Dmitry E. , Altman Jan , Doležal Jiří , Vozmishcheva Anna S. , Krestov Pavel V.
Published: January 2021

Very high resolution satellite imageries provide an excellent foundation for precise mapping of plant communities and even single plants. We aim to perform individual tree recognition on the basis of very high resolution RGB (red, green, blue) satellite images using deep learning approaches for northern temperate mixed forests in the Primorsky Region of the Russian Far East. We used a pansharpened satellite RGB image by GeoEye-1 with a spatial resolution of 0.46 m/pixel, obtained in late April 2019. We parametrized the standard U-Net convolutional neural network (CNN) and trained it in manually delineated satellite images to solve the satellite image segmentation problem. For comparison purposes, we also applied standard pixel-based classification algorithms, such as random forest, k-nearest neighbor classifier, naive Bayes classifier, and quadratic discrimination. Pattern-specific features based on grey level co-occurrence matrices (GLCM) were computed to improve the recognition ability of standard machine learning methods. The U-Net-like CNN allowed us to obtain precise recognition of Mongolian poplar (Populus suaveolens Fisch. ex Loudon s.l.) and evergreen coniferous trees (Abies holophylla Maxim., Pinus koraiensis Siebold & Zucc.). We were able to distinguish species belonging to either poplar or coniferous groups but were unable to separate species within the same group (i.e. A. holophylla and P. koraiensis were not distinguishable). The accuracy of recognition was estimated by several metrics and exceeded values obtained for standard machine learning approaches. In contrast to pixel-based recognition algorithms, the U-Net-like CNN does not lead to an increase in false-positive decisions when facing green-colored objects that are similar to trees. By means of U-Net-like CNN, we obtained a mean accuracy score of up to 0.96 in our computational experiments. The U-Net-like CNN recognizes tree crowns not as a set of pixels with known RGB intensities but as spatial objects with a specific geometry and pattern. This CNN’s specific feature excludes misclassifications related to objects of similar colors as objects of interest. We highlight that utilization of satellite images obtained within the suitable phenological season is of high importance for successful tree recognition. The suitability of the phenological season is conceptualized as a group of conditions providing highlighting objects of interest over other components of vegetation cover. In our case, the use of satellite images captured in mid-spring allowed us to recognize evergreen fir and pine trees as the first class of objects (“conifers”) and poplars as the second class, which were in a leafless state among other deciduous tree species.