bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effectiveness of Ecklonia Cava Kjellman Extract in Improving Menopausal Syndrome in Osteoporosis and Depression
Authors: Yang Hyun , Kim Hye Jin , Lee Hye Won
Published: June 2021

Ecklonia cava (EC) is a natural material commonly used to decrease swelling, allergy, cancer, and sleep issues. Using EC has been reported to regulate hormones during ovarian failure in an aromatase inhibition rodent model. The aim of this study was to investigate EC’s benefits on ovariectomized female mice. Hormone replacement therapy is beneficial in menopause, but the risk of side effects increases. In the present study, alkaline phosphatase (ALP) activity and tryptophan hydroxylases (TPHs) expression were studied after the EC extracts were incorporated as elemental, phloroglucinol, eckol, dieckol, 6,6′-biekcol, and 8,8′-bieckol. In this in vivo study, the following seven groups of 10-week-old Balb/c female mice were evaluated over 8 weeks: normal mice (Sham), ovariectomized mice (OVX), ovariectomized and restraint stressed mice (OVX + R), ovariectomized and 17β-estradiol-treated mice (OVX + R + E2), ovariectomized and fluoxetine-treated mice (OVX + R + E2), and ovariectomized and EC-extract-treated mice (OVX + R + EC150 or OVX + R + EC300). The serum lipid profile, bone loss, and depressive symptoms were investigated in an ovariectomized and restraint-stressed mice model. In the in vitro models, ALP activity was dose-dependently upregulated by EC, including phloroglucinol, eckol, dieckol, 6,6′-biekcol, and 8,8′-bieckol, in RBL-2H3 cells. The transcripts of TPH1 and TPH2 were induced by EC and/or its elements (phloroglucinol, eckol, dieckol, 6,6′-biekcol, and 8,8′-bieckol) in RBL-2H3 cells. The re-uptake activity of serotonin (5-HT) was also decreased by EC and its ingredients such as phloroglucinol, eckol, dieckol, 6,6′-biekcol, and 8,8′-bieckol. In the models, the serum cholesterol and triglyceride levels were downregulated in OVX + R mice by EC treatment. The bone mineral density (BMD) was determined in EC-treated groups, and the bone metabolism markers, CTX and osteocalcin, were also reduced to normal levels. The depression experiments revealed that the immobility time was shortened in the forced-swimming test in OVX + R mice. Moreover, the serum serotonin level was promoted by EC treatment in OVX + R mice. These results showed that EC extract inhibits bone loss and depressive symptoms in a menopausal mouse model by modulating bone metabolism markers (CTX and osteocalcin) and serotonin level in OVX + R mice.
Experimental Study and Simulation Calculation of the Chloride Resistance of Concrete under Multiple Factors
Authors: Ding Yang , Yang Tong-Lin , Liu Hui , Han Zhen , Zhou Shuang-Xi , Wang Zhong-Ping , She An-Ming , Wei Yong-Qi , Dong Jing-Liang
Published: June 2021

Cement is widely used in marine concrete, and its resistance to chloride ion corrosion has been widely considered. In this paper, based on a laboratory test, the influence of different hydrostatic pressures, coarse aggregate contents and w/c ratios on the chloride resistance performance is analyzed. Based on COMSOL finite element software, a two-dimensional cementitious materials model is established, and the simulation results are compared with the experimental results. The results show that the penetration depth of chloride ions in cement increases with the increase of the w/c ratio. Under the hydrostatic pressure of 0 MPa, when the w/c ratio is 0.35, the penetration depth of chloride ions is 7.4 mm, and the simulation result is 8.0 mm. When the w/c ratio is 0.45, the penetration depth of chloride ions is 9.3 mm, and the simulation result is 9.9 mm. When the w/c ratio is 0.55, the penetration depth of chloride ions is 12.9 mm, and the simulation result is 12.1 mm. Under different hydrostatic pressures, the penetration depth of chloride ions obviously changes, and with the increase in hydrostatic pressure, the penetration depth of chloride ions deepens. Under the w/c ratio of 0.35, when the hydrostatic pressure is 0.5 MPa, the penetration depth of chloride ions is 11.3 mm, and the simulation result is 12.1 mm. When the hydrostatic pressure is 1.0 MPa, the penetration depth of chloride ions is 16.2 mm, and the simulation result is 17.5 mm.
Exploring the Impact of Driver Adherence to Speed Limits and the Interdependence of Roadside Collisions in an Urban Environment: An Agent-Based Modelling Approach
Authors: Olmez Sedar , Douglas-Mann Liam , Manley Ed , Suchak Keiran , Heppenstall Alison , Birks Dan , Whipp Annabel
Published: June 2021

Roadside collisions are a significant problem faced by all countries. Urbanisation has led to an increase in traffic congestion and roadside vehicle collisions. According to the UK Government’s Department for Transport, most vehicle collisions occur on urban roads, with empirical evidence showing drivers are more likely to break local and fixed speed limits in urban environments. Analysis conducted by the Department for Transport found that the UK’s accident prevention measure’s cost is estimated to be £33bn per year. Therefore, there is a strong motivation to investigate the causes of roadside collisions in urban environments to better prepare traffic management, support local council policies, and ultimately reduce collision rates. This study utilises agent-based modelling as a tool to plan, experiment and investigate the relationship between speeding and vehicle density with collisions. The study found that higher traffic density results in more vehicles travelling at a slower speed, regardless of the degree to which drivers comply with speed restrictions. Secondly, collisions increase linearly as speed compliance is reduced for all densities. Collisions are lowest when all vehicles comply with speed limits for all densities. Lastly, higher global traffic densities result in higher local traffic densities near-collision sites across all adherence levels, increasing the likelihood of congestion around these sites. This work, when extended to real-world applications using empirical data, can support effective road safety policies.
Scaling Properties and Persistence of Long-Term Solar Activity
Authors: Lepreti Fabio , Carbone Vincenzo , Vecchio Antonio
Published: June 2021

The long-range correlations associated with the presence of persistence are investigated by applying the detrended fluctuation analysis (DFA) on three different proxies of long-term solar activity. The considered datasets are a sunspot number reconstruction (SNR04) obtained from the atmospheric activity of the cosmogenic isotope 14C derived from tree rings, a total solar irradiance reconstruction (TSIR12) obtained from several 10Be ice core records from Greenland and Antarctica in combination with the global record of 14C in tree rings and a new multi-proxy sunspot number reconstruction (SNR18), also derived from 10Be datasets and the global 14C production series. The DFA scaling exponents found for the three time series are similar (lying in the range between 0.70 and 0.77) and the scaling ranges are comparable. These results indicate the presence of long-range correlations with persistence, in substantial agreement with the findings of previous studies carried out on other solar activity indices and proxies.
Integrin Adhesion Complex Organization in Sheep Myometrium Reflects Changing Mechanical Forces during Pregnancy and Postpartum
Authors: McLendon Bryan A. , Kramer Avery C. , Seo Heewon , Bazer Fuller W. , Burghardt Robert C. , Johnson Gregory A.
Published: June 2021

Cells respond to extracellular mechanical forces through the assembly of integrin adhesion complexes (IACs) that provide a scaffold through which cells sense and transduce responses to those forces. IACs are composed of transmembrane integrin receptors that bind to extracellular matrix (ECM) proteins externally and connect with the actomyosin cytoskeleton internally. Myometrial smooth muscle cells respond to forces that arise due to increases in fetal growth/weight, placental fluid volumes, and blood flow. As a result, the uterus transforms into an organ that can forcefully expel the fetus and placental membranes during parturition. While earlier studies focused on IAC expression in the myometrial compartment of rodents and humans to explore pregnancy-associated responses, the present study examines IAC assembly in ovine myometrium where mechanical forces are expected to be amplified in a manner similar to humans. Results indicate that the ITGA5 and ITGB1 heterodimers associate with the ECM protein FN1 externally, and with VCL and TLN1 internally, to form IACs in myometrial cells during the first trimester of pregnancy. These IACs become increasingly ordered until parturition. This ordered structure is lost by one day postpartum; however, the abundance of the integrin proteins remains elevated for at least two weeks postpartum. Implications of the present study are that sheep are similar to humans regarding the assembly of IACs in the pregnant myometrium and suggest that IACs may form much earlier in human gestation than was previously implied by the rat model. Results highlight the continued value of the sheep model as a flagship gynecological model for understanding parturition in humans.
Reducing Lung ATP Levels and Alleviating Asthmatic Airway Inflammation through Adeno-Associated Viral Vector-Mediated CD39 Expression
Authors: Huang Yung-An , Chen Jeng-Chang , Wu Chih-Ching , Hsu Chia-Wei , Ko Albert Min-Shan , Chen Li-Chen , Kuo Ming-Ling
Published: June 2021

Asthma is a chronic respiratory inflammatory disease. Patients usually suffer long-term symptoms and high medical expenses. Extracellular ATP (eATP) has been identified as a danger signal in innate immunity and serves as a potent inflammatory mediator for asthma. Hydrolyzing eATP in lungs might be a potential approach to alleviate asthmatic inflammation. Recombinant adeno-associated virus (rAAV) vectors that contain tissue-specific cap protein have been demonstrated to efficiently transfer exogenous genes into the lung tissues. To test anti-inflammation efficacy of rAAV-mediated CD39 gene transfer, rAAV-CD39 was generated and applied to OVA-mediated asthmatic mice. BALB/c mice were sensitized intraperitoneally and challenged intratracheally with OVA and treated with rAAV-CD39. At the end of procedure, some inflammatory features were examined. rAAV-CD39 treatment downregulated the levels of pulmonary eATP by the rescued expression of CD39. Several asthmatic features, such as airway hyperresponsiveness, eosinophilia, mucin deposition, and IL-5/IL-13 production in the lungs were decreased in the rAAV-CD39-treated mice. Reduced IL-5/IL-13 production and increased frequency of CD4+FoxP3+ regulatory T cells were detected in draining lymph nodes of rAAV-CD39 treated mice. This evidence suggested that rAAV-mediated CD39 gene transfer attenuated the asthmatic airway inflammation locally. The results suggest that rAAV-CD39 might have therapeutic potential for asthma.
Brain-Specific Gene Expression and Quantitative Traits Association Analysis for Mild Cognitive Impairment
Authors: Yuan Shao-Xun , Li Hai-Tao , Gu Yu , Sun Xiao
Published: June 2021

Transcriptome–wide association studies (TWAS) have identified several genes that are associated with qualitative traits. In this work, we performed TWAS using quantitative traits and predicted gene expressions in six brain subcortical structures in 286 mild cognitive impairment (MCI) samples from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. The six brain subcortical structures were in the limbic region, basal ganglia region, and cerebellum region. We identified 9, 15, and 6 genes that were stably correlated longitudinally with quantitative traits in these three regions, of which 3, 8, and 6 genes have not been reported in previous Alzheimer’s disease (AD) or MCI studies. These genes are potential drug targets for the treatment of early–stage AD. Single–Nucleotide Polymorphism (SNP) analysis results indicated that cis–expression Quantitative Trait Loci (cis–eQTL) SNPs with gene expression predictive abilities may affect the expression of their corresponding genes by specific binding to transcription factors or by modulating promoter and enhancer activities. Further, baseline structure volumes and cis–eQTL SNPs from correlated genes in each region were used to predict the conversion risk of MCI patients. Our results showed that limbic volumes and cis–eQTL SNPs of correlated genes in the limbic region have effective predictive abilities.
A Validation Study of a Commercial Wearable Device to Automatically Detect and Estimate Sleep
Authors: Miller Dean J. , Roach Gregory D. , Lastella Michele , Scanlan Aaron T. , Bellenger Clint R. , Halson Shona L. , Sargent Charli
Published: June 2021

The aims of this study were to: (1) compare actigraphy (ACTICAL) and a commercially available sleep wearable (i.e., WHOOP) under two functionalities (i.e., sleep auto-detection (WHOOP-AUTO) and manual adjustment of sleep (WHOOP-MANUAL)) for two-stage categorisation of sleep (sleep or wake) against polysomnography, and; (2) compare WHOOP-AUTO and WHOOP-MANUAL for four-stage categorisation of sleep (wake, light sleep, slow wave sleep (SWS), or rapid eye movement sleep (REM)) against polysomnography. Six healthy adults (male: n = 3; female: n = 3; age: 23.0 ± 2.2 yr) participated in the nine-night protocol. Fifty-four sleeps assessed by ACTICAL, WHOOP-AUTO and WHOOP-MANUAL were compared to polysomnography using difference testing, Bland–Altman comparisons, and 30-s epoch-by-epoch comparisons. Compared to polysomnography, ACTICAL overestimated total sleep time (37.6 min) and underestimated wake (−37.6 min); WHOOP-AUTO underestimated SWS (−15.5 min); and WHOOP-MANUAL underestimated wake (−16.7 min). For ACTICAL, sensitivity for sleep, specificity for wake and overall agreement were 98%, 60% and 89%, respectively. For WHOOP-AUTO, sensitivity for sleep, wake, and agreement for two-stage and four-stage categorisation of sleep were 90%, 60%, 86% and 63%, respectively. For WHOOP-MANUAL, sensitivity for sleep, wake, and agreement for two-stage and four-stage categorisation of sleep were 97%, 45%, 90% and 62%, respectively. WHOOP-AUTO and WHOOP-MANUAL have a similar sensitivity and specificity to actigraphy for two-stage categorisation of sleep and can be used as a practical alternative to polysomnography for two-stage categorisation of sleep and four-stage categorisation of sleep.
Post-Acute COVID-19 Symptoms, a Potential Link with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A 6-Month Survey in a Mexican Cohort
Authors: González-Hermosillo J Antonio , Martínez-López Jhanea Patricia , Carrillo-Lampón Sofía Antonieta , Ruiz-Ojeda Dayanara , Herrera-Ramírez Sharon , Amezcua-Guerra Luis M. , Martínez-Alvarado María del Rocío
Published: June 2021

The aim of this study was to describe the clinical evolution during 6 months of follow-up of adults recovered from COVID-19. We tried to determine how many met the definition of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). A total of 130 patients (51.0 ± 14 years, 34.6% female) were enrolled. Symptoms were common, participants reported a median number of 9 (IQR 5–14) symptoms. Fatigue was the most common symptom (61/130; 46.9%). Patients with fatigue were older 53.9 ± 13.5 years compared with 48.5 ± 13.3 years in those without fatigue (p = 0.02) and had a longer length of hospital stay, 17 ± 14 days vs. 13 ± 10 days (p = 0.04). There was no difference in other comorbidities between patients with fatigue and those without it, and no association between COVID-19 severity and fatigue. After multivariate adjustment of all baseline clinical features, only age 40 to 50 years old was positively associated with fatigue, OR 2.5 (95% CI 1.05–6.05) p = 0.03. In our survey, only 17 (13%) patients met the Institute of Medicine’s criteria for “systemic exertion intolerance disease,” the new name of ME/CFS. In conclusion, in some patients, the features of post-acute COVID-19 syndrome overlap with the clinical features of ME/CFS.
Stereotypies in the Autism Spectrum Disorder: Can We Rely on an Ethological Model?
Authors: Keller Roberto , Costa Tatiana , Imperiale Daniele , Bianco Annamaria , Rondini Elisa , Hassiotis Angela , Bertelli Marco O.
Published: June 2021

Background: Stereotypic behaviour can be defined as a clear behavioural pattern where a specific function or target cannot be identified, although it delays on time. Nonetheless, repetitive and stereotypical behaviours play a key role in both animal and human behaviour. Similar behaviours are observed across species, in typical human developmental phases, and in some neuropsychiatric conditions, such as Autism Spectrum Disorder (ASD) and Intellectual Disability. This evidence led to the spread of animal models of repetitive behaviours to better understand the neurobiological mechanisms underlying these dysfunctional behaviours and to gain better insight into their role and origin within ASD and other disorders. This, in turn, could lead to new treatments of those disorders in humans. Method: This paper maps the literature on repetitive behaviours in animal models of ASD, in order to improve understanding of stereotypies in persons with ASD in terms of characterization, pathophysiology, genomic and anatomical factors. Results: Literature mapping confirmed that phylogenic approach and animal models may help to improve understanding and differentiation of stereotypies in ASD. Some repetitive behaviours appear to be interconnected and mediated by common genomic and anatomical factors across species, mainly by alterations of basal ganglia circuitry. A new distinction between stereotypies and autotypies should be considered. Conclusions: Phylogenic approach and studies on animal models may support clinical issues related to stereotypies in persons with ASD and provide new insights in classification, pathogenesis, and management.
The Potential of Using an Eye Tracker in Architectural Education: Three Perspectives for Ordinary Users, Students and Lecturers
Authors: Rusnak Marta Alina , Rabiega Mateusz
Published: June 2021

The aim of this paper is to discuss the potential of eye trackers as tools providing diversified support for the architectural education of future designers. The possibility to track eye movement guaranteed by this group of devices enables an extension of knowledge on the non-professional perception of architectural creations. It also allows people to monitor progress while learning and verify a project’s assumptions as well as provide lecturers with an opportunity to optimize didactic methods. The paper includes authors’ ideas for modifications of teaching methods applied at technical universities. It is a result of an analysis of research related to the perception of urban designs and architectural objects—research during which noticeable differences were observed between how experts and non-professionals perceive these structures. What also contributed to the contents of this paper was a comprehension of the wide range of eye tracking studies examining the level of acquisition of specialist professional skills. The presented ideas are also based on the analysis and adaptation of eye-tracking research conducted by scientists within other areas of life.
PBRM1 Cooperates with YTHDF2 to Control HIF-1α Protein Translation
Authors: Shmakova Alena , Frost Mark , Batie Michael , Kenneth Niall S. , Rocha Sonia
Published: June 2021

PBRM1, a component of the chromatin remodeller SWI/SNF, is often deleted or mutated in human cancers, most prominently in renal cancers. Core components of the SWI/SNF complex have been shown to be important for the cellular response to hypoxia. Here, we investigated how PBRM1 controls HIF-1α activity. We found that PBRM1 is required for HIF-1α transcriptional activity and protein levels. Mechanistically, PBRM1 is important for HIF-1α mRNA translation, as absence of PBRM1 results in reduced actively translating HIF-1α mRNA. Interestingly, we found that PBRM1, but not BRG1, interacts with the m6A reader protein YTHDF2. HIF-1α mRNA is m6A-modified, bound by PBRM1 and YTHDF2. PBRM1 is necessary for YTHDF2 binding to HIF-1α mRNA and reduction of YTHDF2 results in reduced HIF-1α protein expression in cells. Our results identify a SWI/SNF-independent function for PBRM1, interacting with HIF-1α mRNA and the epitranscriptome machinery. Furthermore, our results suggest that the epitranscriptome-associated proteins play a role in the control of hypoxia signalling pathways.
Sarcoma Metabolomics: Current Horizons and Future Perspectives
Authors: Esperança-Martins Miguel , Fernandes Isabel , Soares do Brito Joaquim , Macedo Daniela , Vasques Hugo , Serafim Teresa , Costa Luís , Dias Sérgio
Published: June 2021

The vast array of metabolic adaptations that cancer cells are capable of assuming, not only support their biosynthetic activity, but also fulfill their bioenergetic demands and keep their intracellular reduction–oxidation (redox) balance. Spotlight has recently been placed on the energy metabolism reprogramming strategies employed by cancer cells to proliferate. Knowledge regarding soft tissue and bone sarcomas metabolome is relatively sparse. Further characterization of sarcoma metabolic landscape may pave the way for diagnostic refinement and new therapeutic target identification, with benefit to sarcoma patients. This review covers the state-of-the-art knowledge on cancer metabolomics and explores in detail the most recent evidence on soft tissue and bone sarcoma metabolomics.
SARS-CoV-2 Entry: At the Crossroads of CD147 and ACE2
Authors: Fenizia Claudio , Galbiati Silvia , Vanetti Claudia , Vago Riccardo , Clerici Mario , Tacchetti Carlo , Daniele Tiziana
Published: June 2021

In late 2019, the betacoronavirus SARS-CoV-2 was identified as the viral agent responsible for the coronavirus disease 2019 (COVID-19) pandemic. Coronaviruses Spike proteins are responsible for their ability to interact with host membrane receptors and different proteins have been identified as SARS-CoV-2 interactors, among which Angiotensin-converting enzyme 2 (ACE2), and Basigin2/EMMPRIN/CD147 (CD147). CD147 plays an important role in human immunodeficiency virus type 1, hepatitis C virus, hepatitis B virus, Kaposi’s sarcoma-associated herpesvirus, and severe acute respiratory syndrome coronavirus infections. In particular, SARS-CoV recognizes the CD147 receptor expressed on the surface of host cells by its nucleocapsid protein binding to cyclophilin A (CyPA), a ligand for CD147. However, the involvement of CD147 in SARS-CoV-2 infection is still debated. Interference with both the function (blocking antibody) and the expression (knock down) of CD147 showed that this receptor partakes in SARS-CoV-2 infection and provided additional clues on the underlying mechanism: CD147 binding to CyPA does not play a role; CD147 regulates ACE2 levels and both receptors are affected by virus infection. Altogether, these findings suggest that CD147 is involved in SARS-CoV-2 tropism and represents a possible therapeutic target to challenge COVID-19.
Human Keratinocytes Inhibit CD4+ T-Cell Proliferation through TGFB1 Secretion and Surface Expression of HLA-G1 and PD-L1 Immune Checkpoints
Authors: Mestrallet Guillaume , Auvré Frédéric , Schenowitz Chantal , Carosella Edgardo D. , LeMaoult Joel , Martin Michèle T. , Rouas-Freiss Nathalie , Fortunel Nicolas O.
Published: June 2021

Human skin protects the body against infection and injury. This protection involves immune and epithelial cells, but their interactions remain largely unknown. Here, we show that cultured epidermal keratinocytes inhibit allogenic CD4+ T-cell proliferation under both normal and inflammatory conditions. Inhibition occurs through the secretion of soluble factors, including TGFB1 and the cell-surface expression of HLA-G1 and PD-L1 immune checkpoints. For the first time, we here describe the expression of the HLA-G1 protein in healthy human skin and its role in keratinocyte-driven tissue immunomodulation. The overexpression of HLA-G1 with an inducible vector increased the immunosuppressive properties of keratinocytes, opening up perspectives for their use in allogeneic settings for cell therapy.
Red Seaweeds as a Source of Nutrients and Bioactive Compounds: Optimization of the Extraction
Authors: Carpena Maria , Caleja Cristina , Pereira Eliana , Pereira Carla , Ćirić Ana , Soković Marina , Soria-Lopez Anton , Fraga-Corral Maria , Simal-Gandara Jesus , Ferreira Isabel C. F. R. , Barros Lillian , Prieto Miguel A.
Published: June 2021

The present work aimed to determine the nutritional composition (ash, protein, fat, carbohydrate content and energy value), phenolic compounds, pigments and organic acids content of three typical red algae from the Northwest of Spain: Chondrus crispus, Mastocarpus stellatus, and Gigartina pistillata; as well as their antioxidant and antimicrobial activities. Furthermore, the present work compared two extraction techniques: conventional heat assisted extraction (HAE) and high pressure assisted extraction (HPAE) to maximize the yield and the concentration of target compounds. Different independent variables were considered for the response study. Time (t) and percentage of ethanol of the solvent (S) were chosen for both techniques and temperature (T) and pressure (P) were used for HAE and HPAE, respectively. The experiments were designed following a response surface methodology (RSM) approach. The obtained results showed a similar nutritional composition between algae samples: low-fat content and high content of proteins, carbohydrates and energy. All tested algae showed good antioxidant and antimicrobial properties. Finally, HEA demonstrated to be the most efficient extraction technique. This study confirms the potential of red algae to be part of the human diet as a source of non-animal protein, due to its nutritional content, phenolic profile, pigments concentration and bioactive properties, which proves that HAE is the optimum technique for the extraction maximization.
Measuring Complex Refractive Indices of a Nanometer-Thick Superconducting Film Using Terahertz Time-Domain Spectroscopy with a 10 Femtoseconds Pulse Laser
Authors: Lee Hyoung-Taek , Ji Gang-Seon , Oh Jun-Yung , Seo Choong-Won , Kang Byeong-Won , Kim Kyung-Wan , Park Hyeong-Ryeol
Published: June 2021

Superconducting thin films are widely applied in various fields, including switching devices, because of their phase transition behaviors in relation to temperature changes. Therefore, it is important to quantitatively determine the optical constant of a superconducting material in the thin-film state. We performed a terahertz time-domain spectroscopy, based on a 10 femtoseconds pulse laser, to measure the optical constant of a superconducting GdBa2Cu3O7−x (GdBCO) thin film in the terahertz region. We then estimated the terahertz refractive indices of the 70 nm-thick GdBCO film using a numerical extraction process, even though the film thickness was approximately 1/10,000 times smaller than the terahertz wavelength range of 200 μm to 1 mm. The resulting refractive indices of the GdBCO thin film were consistent with the theoretical results using the two-fluid model. Our work will help to further understand the terahertz optical properties of superconducting thin films with thicknesses under 100 nm, as well as provide a standard platform for characterizing the optical properties of thin films without the need of Kramers–Kronig transformation at the terahertz frequencies.
Deep Learning-Based Differentiation between Mucinous Cystic Neoplasm and Serous Cystic Neoplasm in the Pancreas Using Endoscopic Ultrasonography
Authors: Nguon Leang Sim , Seo Kangwon , Lim Jung-Hyun , Song Tae-Jun , Cho Sung-Hyun , Park Jin-Seok , Park Suhyun
Published: June 2021

Mucinous cystic neoplasms (MCN) and serous cystic neoplasms (SCN) account for a large portion of solitary pancreatic cystic neoplasms (PCN). In this study we implemented a convolutional neural network (CNN) model using ResNet50 to differentiate between MCN and SCN. The training data were collected retrospectively from 59 MCN and 49 SCN patients from two different hospitals. Data augmentation was used to enhance the size and quality of training datasets. Fine-tuning training approaches were utilized by adopting the pre-trained model from transfer learning while training selected layers. Testing of the network was conducted by varying the endoscopic ultrasonography (EUS) image sizes and positions to evaluate the network performance for differentiation. The proposed network model achieved up to 82.75% accuracy and a 0.88 (95% CI: 0.817–0.930) area under curve (AUC) score. The performance of the implemented deep learning networks in decision-making using only EUS images is comparable to that of traditional manual decision-making using EUS images along with supporting clinical information. Gradient-weighted class activation mapping (Grad-CAM) confirmed that the network model learned the features from the cyst region accurately. This study proves the feasibility of diagnosing MCN and SCN using a deep learning network model. Further improvement using more datasets is needed.
Serum Levels of Cytokine-Induced Apoptosis Inhibitor 1 (CIAPIN1) as a Potential Prognostic Biomarker of Cholangiocarcinoma
Authors: Truong Son Dinh An , Tummanatsakun Doungdean , Proungvitaya Tanakorn , Limpaiboon Temduang , Wongwattanakul Molin , Chua-on Daraporn , Roytrakul Sittiruk , Proungvitaya Siriporn
Published: June 2021

The mortality rate of cholangiocarcinoma (CCA) is high since there is a lack of a non-invasive technique to accurately detect tumors at the early stage. CCA biomarkers are consistently needed for various purposes including screening, early diagnosis, prognosis and follow-up. Herein, using bioinformatic analysis of our mitochondrial proteome database of CCA tissues, we identified cytokine-induced apoptosis inhibitor 1 (CIAPIN1) as a potential prognostic biomarker for CCA. CIAPIN1 levels in the sera of 159 CCA patients and 93 healthy controls (HC) were measured using a dot blot assay. The median level ± quartile deviation of CIAPIN1 level in the sera of CCA patient group was 0.5144 ± 0.34 µg/µL, which was significantly higher than 0.2427 ± 0.09 µg/µL of the HC group (p < 0.0001). In CCA patients, higher serum CIAPIN1 level was significantly associated with lymph node metastasis (p = 0.024) and shorter overall survival time (p = 0.001, Kaplan–Meier test). Cox regression analysis showed that the serum CIAPIN1 level can be an independent prognostic indicator for the survival of CCA patients. Moreover, for the prediction of CCA prognosis, CIAPIN1 is superior to CEA, CA19-9 and ALP. In conclusion, CIAPIN1 can be a serum biomarker candidate for the poor prognosis of CCA.
Genetic Basis of Dual Diagnosis: A Review of Genome-Wide Association Studies (GWAS) Focusing on Patients with Mood or Anxiety Disorders and Co-Occurring Alcohol-Use Disorders
Authors: Stoychev Kaloyan , Dilkov Dancho , Naghavi Elahe , Kamburova Zornitsa
Published: June 2021

(1) Background: Comorbidity between Alcohol Use Disorders (AUD), mood, and anxiety disorders represents a significant health burden, yet its neurobiological underpinnings are elusive. The current paper reviews all genome-wide association studies conducted in the past ten years, sampling patients with AUD and co-occurring mood or anxiety disorder(s). (2) Methods: In keeping with PRISMA guidelines, we searched EMBASE, Medline/PUBMED, and PsycINFO databases (January 2010 to December 2020), including references of enrolled studies. Study selection was based on predefined criteria and data underwent a multistep revision process. (3) Results: 15 studies were included. Some of them explored dual diagnoses phenotypes directly while others employed correlational analysis based on polygenic risk score approach. Their results support the significant overlap of genetic factors involved in AUDs and mood and anxiety disorders. Comorbidity risk seems to be conveyed by genes engaged in neuronal development, connectivity, and signaling although the precise neuronal pathways and mechanisms remain unclear. (4) Conclusion: given that genes associated with complex traits including comorbid clinical presentations are of small effect, and individually responsible for a very low proportion of the total variance, larger samples consisting of multiple refined comorbid combinations and confirmed by re-sequencing approaches will be necessary to disentangle the genetic architecture of dual diagnosis.
Role of Contrast-Enhanced Ultrasound (CEUS) in Native Kidney Pathology: Limits and Fields of Action
Authors: Granata Antonio , Campo Irene , Lentini Paolo , Pesce Francesco , Gesualdo Loreto , Basile Antonio , Cantisani Vito , Zeiler Matthias , Bertolotto Michele
Published: June 2021

Gray scale ultrasound has an important diagnostic role in native kidney disease. Low cost, absence of ionizing radiation and nephrotoxicity, short performance time, and repeatability even at the bedside, are the major advantages of this technique. The introduction of contrast enhancement ultrasound (CEUS) in daily clinical practice has significantly reduced the use of contrast enhancement computed tomography (CECT) and contrast enhancement magnetic resonance (CEMR), especially in patients with renal disease. Although there are many situations in which CECT and CEMRI are primarily indicated, their use may be limited by the administration of the contrast medium, which may involve a risk of renal function impairment, especially in the elderly, and in patients with acute kidney injury (AKI) and moderate to severe chronic kidney disease (CKD). In these cases, CEUS can be a valid diagnostic choice. To date, numerous publications have highlighted the role of CEUS in the study of parenchymal micro-vascularization and renal pathology by full integration with second level imaging methods (CECT and CEMRI) both in patients with normal renal function and with diseased kidneys. The aim of this review is to offer an updated overview of the limitations and potential applications of CEUS in native kidney disease.
Principled Decision-Making Workflow with Hierarchical Bayesian Models of High-Throughput Dose-Response Measurements
Authors: Ma Eric J. , Kummer Arkadij
Published: June 2021

We present a case study applying hierarchical Bayesian estimation on high-throughput protein melting-point data measured across the tree of life. We show that the model is able to impute reasonable melting temperatures even in the face of unreasonably noisy data. Additionally, we demonstrate how to use the variance in melting-temperature posterior-distribution estimates to enable principled decision-making in common high-throughput measurement tasks, and contrast the decision-making workflow against simple maximum-likelihood curve-fitting. We conclude with a discussion of the relative merits of each workflow.
The Financial Integration in the European Capital Market Using a Clustering Approach on Financial Data
Authors: Danko Jakub , Suchý Erik
Published: June 2021

In 2009, when the effects of the economic crisis were fully felt, countries around the world experienced negative impacts, starting from the USA, where the crisis began, through Europe to Asia. Economic cycles, fluctuations, and crises are a common part of the financial market, for example, the crisis in 1929 and the crisis in 2000. The recovery of the economy is a key factor in this process. Due to the increasingly powerful process of globalization and the growth of the interconnectedness of individual economies to each other, not to mention an increasing pressure on the formation of integration clusters, the creation and emergence of new financial crises with supranational and transnational character are highly likely in the future. It is possible that a one-day crisis reaches and expands with global reach, but it is important for us to be prepared through effective tools. In this article, we will be dealing with financial indicators within the European Union that define and create the capital market. Based on cluster analysis, we create groups of countries that are similar to each other. We determine which countries are the leaders and which, on the contrary, lag behind the rest of Europe.
Generation of Cross-Lingual Word Vectors for Low-Resourced Languages Using Deep Learning and Topological Metrics in a Data-Efficient Way
Authors: JP Sanjanasri , Menon Vijay Krishna , KP Soman , S Rajendran , Wolk Agnieszka
Published: June 2021

Linguists have been focused on a qualitative comparison of the semantics from different languages. Evaluation of the semantic interpretation among disparate language pairs like English and Tamil is an even more formidable task than for Slavic languages. The concept of word embedding in Natural Language Processing (NLP) has enabled a felicitous opportunity to quantify linguistic semantics. Multi-lingual tasks can be performed by projecting the word embeddings of one language onto the semantic space of the other. This research presents a suite of data-efficient deep learning approaches to deduce the transfer function from the embedding space of English to that of Tamil, deploying three popular embedding algorithms: Word2Vec, GloVe and FastText. A novel evaluation paradigm was devised for the generation of embeddings to assess their effectiveness, using the original embeddings as ground truths. Transferability across other target languages of the proposed model was assessed via pre-trained Word2Vec embeddings from Hindi and Chinese languages. We empirically prove that with a bilingual dictionary of a thousand words and a corresponding small monolingual target (Tamil) corpus, useful embeddings can be generated by transfer learning from a well-trained source (English) embedding. Furthermore, we demonstrate the usability of generated target embeddings in a few NLP use-case tasks, such as text summarization, part-of-speech (POS) tagging, and bilingual dictionary induction (BDI), bearing in mind that those are not the only possible applications.
Research on QoS Classification of Network Encrypted Traffic Behavior Based on Machine Learning
Authors: Huang Yung-Fa , Lin Chuan-Bi , Chung Chien-Min , Chen Ching-Mu
Published: June 2021

In recent years, privacy awareness is concerned due to many Internet services have chosen to use encrypted agreements. In order to improve the quality of service (QoS), the network encrypted traffic behaviors are classified based on machine learning discussed in this paper. However, the traditional traffic classification methods, such as IP/ASN (Autonomous System Number) analysis, Port-based and deep packet inspection, etc., can classify traffic behavior, but cannot effectively handle encrypted traffic. Thus, this paper proposed a hybrid traffic classification (HTC) method based on machine learning and combined with IP/ASN analysis with deep packet inspection. Moreover, the majority voting method was also used to quickly classify different QoS traffic accurately. Experimental results show that the proposed HTC method can effectively classify different encrypted traffic. The classification accuracy can be further improved by 10% with majority voting as K = 13. Especially when the networking data are using the same protocol, the proposed HTC can effectively classify the traffic data with different behaviors with the differentiated services code point (DSCP) mark.
Comparison of Advanced Charge Strategies for Modular Cascaded Battery Chargers
Authors: Fernandes Nicolas T. D. , Rocha Anderson , Brandao Danilo , Filho Braz C.
Published: June 2021

Although the literature extensively covers the development of battery chargers control strategies, a comparison of these strategies remains a literary gap. The inherent conditions (i.e., State of Health and State of Charge) of each unit in the Battery Energy Storage Systems directly influence the charger control techniques for extending battery lifetime, which makes modular battery chargers an appealing topology for this analysis. This work groups charger control strategies presented in the literature into two: Adapted SoC strategies, directly linked to the field of overstress management, and SoH strategies, which are directly linked to the field of wear-out management. The methodology for comparing the control strategies encompasses battery lifetime, charger, and photovoltaic plant models. Three distinct cases were simulated using real measure data from a solar power plant and a battery model provided by MathWorks®. The results evidence that the Capacity Fade and Energy Throughput strongly depend on the strategy. The controller action evidences the previous statement, as the strategies have different goals that are related to each field. Furthermore, this work analyses the effect of the estimation process in the action of the controller.
Electrical Infrastructure Design Methodology of Dynamic and Static Charging for Heavy and Light Duty Electric Vehicles
Authors: Danese Alberto , Garau Michele , Sumper Andreas , Torsæter Bendik Nybakk
Published: June 2021

Full electrification of the transport sector is a necessity to combat climate change and a pressing societal issue: climate agreements require a fuel shift of all the modes of transport, but while uptake of passenger electric vehicles is increasing, long haul trucks rely almost completely on fossil fuels. Providing highways with proper charging infrastructure for future electric mobility demand is a problem that is not fully investigated in literature: in fact, previous work has not addressed grid planning and infrastructure design for both passenger vehicles and trucks on highways. In this work, the authors develop a methodology to design the electrical infrastructure that supplies static and dynamic charging for both modes of transport. An algorithm is developed that selects substations for the partial electrification of a highway and, finally, the design of the electrical infrastructure to be implemented is produced and described, assessing conductors and substations sizing, in order to respect voltage regulations. The system topology of a real highway (E18 in Norway) and its traffic demand is analyzed, together with medium-voltage substations present in the area.
The Price of Wind: An Empirical Analysis of the Relationship between Wind Energy and Electricity Price across the Residential, Commercial, and Industrial Sectors
Authors: Dorrell John , Lee Keunjae
Published: June 2021

This paper quantifies the long-term impact of wind energy development on electricity prices across the residential, commercial, and industrial sectors in the United States. Our data set is made up of state level panel data from 2000 through 2018. This time period covers the vast majority of total wind energy capacity installed in the history of the USA. Our econometric model accounts for the primary factors that influence electricity prices, incorporating both fixed effects and general method of moments in order to more precisely isolate the effect of wind energy. The empirical results conclude that wind energy is positively and significantly related to electricity prices across all sectors, as indicated by the higher average electricity prices in states with higher percentages of wind energy. The price increase is largest in the industrial sector, followed by commercial, then residential. Wind turbine technology has become significantly more efficient, but the technical gains have been offset by the increased indirect costs of incorporating wind energy into the grid. Transmission and balancing costs have increased the final price to consumers. Our results highlight the need to view wind energy development from a more holistic perspective that accounts for structural and systemic costs. This will ensure the continued growth of wind energy. These results provide relevant insight to help wind energy developers, policy makers, and utility companies build a more sustainable energy future.
What Solutions for Waste Management? Issues of Flows and Governance Exemplified by the Łódź Agglomeration (Poland)
Authors: Mazurek Damian , Czapiewski Konrad
Published: June 2021

This article seeks to propose a waste-management model based on qualitative and quantitative research. Specifically, an analysis of the flow of municipal waste was carried out, with the case involved being that of the biodegradable waste generated in households of Poland’s Łódź Metropolitan Area, which is heterogeneous from the points of view of both settlement structure and land use. The analysis of flows of waste then served an evaluation of the system of waste management in the study area, while also representing an important input into a process of identification of problems and possible solutions via so-called PULL (“Peri-Urban Living Lab”) workshop methodology. Indeed, the research detailed here was participatory throughout (from the stages of problem identification through to conclusion-drawing). All of these stages to the work were kept cohesive through the use of an advanced tool allowing for both analysis of the given area and the devising of strategies by which circular economy could be developed. Specifically, GDSE (GeoDesign Decision Support Environment) programming—devised within the framework of the REPAiR Project—offered opportunities for flows of different kinds of materials and raw materials across space to be identified. It also served in the implementation of Eco-innovative solutions (EIS), as were developed jointly in cooperation with participants of the PULL workshops. The article offers a synthetic presentation of the results of different stages to the research, along with a synthesis relating to the waste-management context, with particular account taken of the development of the circular economy.
Model Predictive Control for the Energy Management in a District of Buildings Equipped with Building Integrated Photovoltaic Systems and Batteries
Authors: Fotopoulou Maria C. , Drosatos Panagiotis , Petridis Stefanos , Rakopoulos Dimitrios , Stergiopoulos Fotis , Nikolopoulos Nikolaos
Published: June 2021

This paper introduces a Model Predictive Control (MPC) strategy for the optimal energy management of a district whose buildings are equipped with vertically placed Building Integrated Photovoltaic (BIPV) systems and Battery Energy Storage Systems (BESS). The vertically placed BIPV systems are able to cover larger areas of buildings’ surfaces, as compared with conventional rooftop PV systems, and reach their peak of production during winter and spring, which renders them suitable for energy harvesting especially in urban areas. Driven by both these relative advantages, the proposed strategy aims to maximize the district’s autonomy from the external grid, which is achieved through the cooperation of interactive buildings. Therefore, the major contribution of this study is the management and optimal cooperation of a group of buildings, each of which is equipped with its own system of vertical BIPV panels and BESS, carried out by an MPC strategy. The proposed control scheme consists of three main components, i.e., the forecaster, the optimizer and the district, which interact periodically with each other. In order to quantitatively evaluate the benefits of the proposed MPC strategy and the implementation of vertical BIPV and BESS, a hypothetical five-node distribution network located in Greece for four representative days of the year was examined, followed by a sensitivity analysis to examine the effect of the system configuration on its performance.