bluuebunny/crossref_metadata_2025 huggingface dataset:
RF Sputter-Deposited Nanostructured CuO Films for Micro-Supercapacitors
Authors: Mahendra Goddati , Malathi Reddappagari , Kedhareswara Sairam P. , Lakshmi-Narayana Ambadi , Dhananjaya Merum , Guruprakash Nunna , Hussain Obili M. , Mauger Alain , Julien Christian M.
Published: February 2021

Copper oxide is considered as an alternative electrode material for supercapacitors due to its low cost, chemical stability and high theoretical specific capacitance. In the present work, nanostructured copper oxide (CuO) films are prepared by radio-frequency (RF) magnetron sputtering, and the influence of the substrate temperature on the microstructure and supercapacitive properties was studied. The copper oxide films prepared at 350 °C exhibit a predominant (1¯11) orientation corresponding to the monoclinic Cu(II)O phase with a crystallite size of 24 nm. The surface of the film consists of uniformly distributed oval-like grains providing a high surface roughness of 45 nm. The films exhibit an optical bandgap of 1.68 ± 0.01 eV and an electrical conductivity of 0.4 S cm−1 at room temperature. The as-prepared CuO films deliver a discharge specific capacitance of 387 mF cm−2 (375 F g−1) at a current density of 1 mA cm−2 with excellent cyclic capacitance retention of 95% (367 mF cm−2) even after 1000 cycles. Hence, these films are potential electrodes for micro-supercapacitors.
Assessment and Improvement of Two Low-Cost Particulate Matter Sensor Systems by Using Spatial Interpolation Data from Air Quality Monitoring Stations
Authors: Liang Chen-Jui , Yu Pei-Rong
Published: February 2021

Two low-cost fine particulate matter (PM2.5) sensor systems have been established by the government and community in Taiwan. Each system combines hundreds of PM2.5 sensors through an Internet of Things architecture. Since these sensors have not been calibrated, their performance has been questioned. In this study, the spatial interpolation data from air quality monitoring stations (AQMSs) was used to quantify the performances of the two sensor systems. The linearity, sensitivity, offset, precision, accuracy, and bias of the two sensor systems were estimated. The results indicate that the linearity of the government’s sensor system was higher than that of the community sensor system. However, the sensitivity of the government’s system was lower than that of the community system. The relative standard deviation, relative error, offset, and bias of the community sensor system were higher than those of the government sensor system. However, the government sensor system exhibited superior spatial interpolation results for the AQMS data than the community sensor system did. The precision and accuracy of the two sensor systems were poor during a period of low PM2.5 concentrations. A working platform of improvements consisting of monitoring the operation loop and automatic correction loop is proposed. The monitoring operation loop comprises five modules, namely outlier detection, temporal anomaly analysis, spatial anomaly analysis, spatiotemporal anomaly analysis, and trajectory analysis modules. The automatic correction loop contains spatial interpolation module, a sensor performance detection module, and a correction module. The proposed working platform can enhance the performance of low-cost sensor systems, especially as alert systems for reportable events.
Influence of the Thermal Conductivity and Ambient Temperature Uncertainty on the Heat Losses through the External Wall
Authors: Koniorczyk Marcin , Grymin Witold
Published: February 2021

Numerous parameters assumed in the calculations of the buildings’ energy demand are uncertain. Therefore, calculations should be accompanied by determination of propagation of such uncertainties in the mathematical model. In the article, the influence of uncertainty of thermal conductivity and ambient temperature has been studied by means of the generalized perturbation stochastic finite element method and compared against the Monte Carlo results, indicating good accordance. Expected value and variance of heat flux on the internal side of the wall have been investigated. The perturbation stochastic finite element method is much more efficient than the Monte Carlo method for the analysed problem. The largest variance of temperature is noted in the node between the constructive layer and insulation.
The Prognostic Value of Whole-Blood PSMB5, CXCR4, POMP, and RPL5 mRNA Expression in Patients with Multiple Myeloma Treated with Bortezomib
Authors: Robak Pawel , Jarych Dariusz , Mikulski Damian , Dróżdż Izabela , Węgłowska Edyta , Kotkowska Aleksandra , Misiewicz Małgorzata , Smolewski Piotr , Stawiski Konrad , Fendler Wojciech , Szemraj Janusz , Robak Tadeusz
Published: February 2021

Proteasome inhibitors, like bortezomib, play a key role in the treatment of multiple myeloma (MM); however, most patients eventually relapse and eventually show multiple drug resistance, and the molecular mechanisms of this resistance remain unclear. The aim of our study is to assess the expression of previously described genes that may influence the resistance to bortezomib treatment at the mRNA level (ABCB1, CXCR4, MAF, MARCKS, POMP, PSMB5, RPL5, TXN, and XBP1) and prognosis of MM patients. mRNA expression was determined in 73 MM patients treated with bortezomib-based regimens (30 bortzomib-sensitive and 43 bortezomib-refractory patients) and 11 healthy controls. RPL5 was significantly down-regulated in multiple myeloma patients as compared with healthy controls. Moreover, POMP was significantly up-regulated in MM patients refractory to bortezomib-based treatment. In multivariate analysis, high expression of PSMB5 and CXCR and autologous stem cell transplantation were independent predictors of progression-free survival, and high expression of POMP and RPL5 was associated with shorter overall survival.
Are In Vitro Human Blood–Brain–Tumor-Barriers Suitable Replacements for In Vivo Models of Brain Permeability for Novel Therapeutics?
Authors: Prashanth Archana , Donaghy Heather , Stoner Shihani P. , Hudson Amanda L. , Wheeler Helen R. , Diakos Connie I. , Howell Viive M. , Grau Georges E. , McKelvey Kelly J.
Published: February 2021

Background: High grade gliomas (HGG) are incapacitating and prematurely fatal diseases. To overcome the poor prognosis, novel therapies must overcome the selective and restricted permeability of the blood–brain barrier (BBB). This study critically evaluated whether in vitro human normal BBB and tumor BBB (BBTB) are suitable alternatives to “gold standard” in vivo models to determine brain permeability. Methods: A systematic review utilizing the PRISMA guidelines used English and full-text articles from the past 5 years in the PubMed, Embase, Medline and Scopus databases. Experimental studies employing human cell lines were included. Results: Of 1335 articles, the search identified 24 articles for evaluation after duplicates were removed. Eight in vitro and five in vivo models were identified with the advantages and disadvantages compared within and between models, and against patient clinical data where available. The greatest in vitro barrier integrity and stability, comparable to in vivo and clinical permeability data, were achieved in the presence of all cell types of the neurovascular unit: endothelial cells, astrocytes/glioma cells, pericytes and neurons. Conclusions: In vitro co-culture BBB models utilizing stem cell-derived or primary cells are a suitable proxy for brain permeability studies in order to reduce animal use in medical research.
FOXM1 Inhibition in Ovarian Cancer Tissue Cultures Affects Individual Treatment Susceptibility Ex Vivo
Authors: Brückner Luzie , Reinshagen Annika , Hoang Ngoc Anh , Höhn Anne Kathrin , Lordick Florian , Bechmann Ingo , Aktas Bahriye , Nel Ivonne , Kallendrusch Sonja
Published: February 2021

Diagnosis in an advanced state is a major hallmark of ovarian cancer and recurrence after first line treatment is common. With upcoming novel therapies, tumor markers that support patient stratification are urgently needed to prevent ineffective therapy. Therefore, the transcription factor FOXM1 is a promising target in ovarian cancer as it is frequently overexpressed and associated with poor prognosis. In this study, fresh tissue specimens of 10 ovarian cancers were collected to investigate tissue cultures in their ability to predict individual treatment susceptibility and to identify the benefit of FOXM1 inhibition. FOXM1 inhibition was induced by thiostrepton (3 µM). Carboplatin (0.2, 2 and 20 µM) and olaparib (10 µM) were applied and tumor susceptibility was analyzed by tumor cell proliferation and apoptosis in immunofluorescence microscopy. Resistance mechanisms were investigated by determining the gene expression of FOXM1 and its targets BRCA1/2 and RAD51. Ovarian cancer tissue was successfully maintained for up to 14 days ex vivo, preserving morphological characteristics of the native specimen. Thiostrepton downregulated FOXM1 expression in tissue culture. Individual responses were observed after combined treatment with carboplatin or olaparib. Thus, we successfully implemented a complex tissue culture model to ovarian cancer and showed potential benefit of combined FOXM1 inhibition.
Bifidobacterium Strain-Specific Enhances the Efficacy of Cancer Therapeutics in Tumor-Bearing Mice
Authors: Yoon Youngmin , Kim Gihyeon , Jeon Bu-Nam , Fang Sungsoon , Park Hansoo
Published: February 2021

Colorectal cancer (CRC) is among the leading causes of cancer-related death in the world. The development of CRC is associated with smoking, diet, and microbial exposure. Previous studies have shown that dysbiosis of the gut microbiome affects cancer development, because it leads to inflammation and genotoxicity. Supplementation with specific microbiota induces anti-tumor effects by enhancing of anti-tumor immunity. Here, we observed that supplementation with either of two B. breve strains reduces tumor growth in MC38 colon carcinoma-bearing mice. Interestingly, only one B. breve strain boosted the efficacy of cancer therapeutics, including oxaliplatin and PD-1 blockade. Extensive immune profiling and transcriptomic analysis revealed that the boosting B. breve strain augments lymphocyte-mediated anti-cancer immunity. Our results suggest that supplementation with B. breve strains could potentially be used as a strategy to enhance the efficacy of CRC therapeutics.
Mouse Models of Peritoneal Carcinomatosis to Develop Clinical Applications
Authors: Bella Ángela , Di Trani Claudia Augusta , Fernández-Sendin Myriam , Arrizabalaga Leire , Cirella Assunta , Teijeira Álvaro , Medina-Echeverz José , Melero Ignacio , Berraondo Pedro , Aranda Fernando
Published: February 2021

Peritoneal carcinomatosis of primary tumors originating in gastrointestinal (e.g., colorectal cancer, gastric cancer) or gynecologic (e.g., ovarian cancer) malignancies is a widespread type of tumor dissemination in the peritoneal cavity for which few therapeutic options are available. Therefore, reliable preclinical models are crucial for research and development of efficacious treatments for this condition. To date, a number of animal models have attempted to reproduce as accurately as possible the complexity of the tumor microenvironment of human peritoneal carcinomatosis. These include: Syngeneic tumor cell lines, human xenografts, patient-derived xenografts, genetically induced tumors, and 3D scaffold biomimetics. Each experimental model has its own strengths and limitations, all of which can influence the subsequent translational results concerning anticancer and immunomodulatory drugs under exploration. This review highlights the current status of peritoneal carcinomatosis mouse models for preclinical development of anticancer drugs or immunotherapeutic agents.
Correction: Pavlov, Y.I., et al. DNA Polymerases at the Eukaryotic Replication Fork Thirty Years After: Connection to Cancer. Cancers 2020, 12, 3489
Authors: Pavlov Youri I. , Zhuk Anna S. , Stepchenkova Elena I.
Published: February 2021

The authors wish to make the following corrections to this paper [...]
Addendum: Manabu, K., et al. Prognostic Significance of Aberrant Claudin-6 Expression in Endometrial Cancer. Cancers 2020, 12, 2748
Authors: Kojima Manabu , Sugimoto Kotaro , Tanaka Mizuko , Endo Yuta , Kato Hitomi , Honda Tsuyoshi , Furukawa Shigenori , Nishiyama Hiroshi , Watanabe Takafumi , Soeda Shu , Fujimori Keiya , Chiba Hideki
Published: February 2021

The authors wish to make the following correction to this paper [...]
Radiogenomics in Colorectal Cancer
Authors: Badic Bogdan , Tixier Florent , Cheze Le Rest Catherine , Hatt Mathieu , Visvikis Dimitris
Published: February 2021

The steady improvement of high-throughput technologies greatly facilitates the implementation of personalized precision medicine. Characterization of tumor heterogeneity through image-derived features—radiomics and genetic profile modifications—genomics, is a rapidly evolving field known as radiogenomics. Various radiogenomics studies have been dedicated to colorectal cancer so far, highlighting the potential of these approaches to enhance clinical decision-making. In this review, a general outline of colorectal radiogenomics literature is provided, discussing the current limitations and suggested further developments.
Comparative Analysis of Stk11/Lkb1 versus Pten Deficiency in Lung Adenocarcinoma Induced by CRISPR/Cas9
Authors: Berthelsen Martin F. , Leknes Siv L. , Riedel Maria , Pedersen Mette A. , Joseph Justin V. , Hager Henrik , Vendelbo Mikkel H. , Thomsen Martin K.
Published: February 2021

This study focused on STK11, PTEN, KRAS, and TP53, which are often found to be mutated in lung cancer. We compared Stk11 and Pten implication in lung cancer in combination with loss of Trp53 and gain of function of Kras in a CRISPR/Cas9 mouse model. Mice with loss of Stk11, Trp53, and KrasG12D mutation (SKT) reached human endpoint at around four months post-initiation. In comparison, mice with loss of Pten, Trp53, and KrasG12D mutation (PKT) survived six months or longer post-initiation. Pathological examination revealed an increase in proliferation in SKT deficient lung epithelia compared to PKT. This difference was independent of Pten loss, indicating that loss of Pten is dispensable for cell proliferation in lung adenocarcinoma. Furthermore, tumors with loss of Stk11, Trp53, and KrasG12D mutation had a significantly higher progression rate, monitored by PET/MRI scanning, compared to mice with loss of Pten, Trp53, and KrasG12D mutation, revealing that mutations in Stk11 are essential for adenocarcinoma progression. Overall, by using the CRISPR/Cas9 mouse model of lung adenocarcinoma, we showed that mutations in Stk11 are a key driver, whereas loss of Pten is dispensable for adenocarcinoma progression.
Involvement of Long Non-Coding RNAs in Glucose Metabolism in Cancer
Authors: Balihodzic Amar , Barth Dominik A. , Prinz Felix , Pichler Martin
Published: February 2021

The rapid and uncontrolled proliferation of cancer cells is supported by metabolic reprogramming. Altered glucose metabolism supports cancer growth and progression. Compared with normal cells, cancer cells show increased glucose uptake, aerobic glycolysis and lactate production. Byproducts of adjusted glucose metabolism provide additional benefits supporting hallmark capabilities of cancer cells. Long non-coding RNAs (lncRNAs) are a heterogeneous group of transcripts of more than 200 nucleotides in length. They regulate numerous cellular processes, primarily through physical interaction with other molecules. Dysregulated lncRNAs are involved in all hallmarks of cancer including metabolic alterations. They may upregulate metabolic enzymes, modulate the expression of oncogenic or tumor-suppressive genes and disturb metabolic signaling pathways favoring cancer progression. Thus, lncRNAs are not only potential clinical biomarkers for cancer diagnostics and prediction but also possible therapeutic targets. This review summarizes the lncRNAs involved in cancer glucose metabolism and highlights their underlying molecular mechanisms.
Optimization of the Clinical Setting Using Numerical Simulations of the Electromagnetic Field in an Obese Patient Model for Deep Regional Hyperthermia of an 8 MHz Radiofrequency Capacitively Coupled Device in the Pelvis
Authors: Ohguri Takayuki , Kuroda Kagayaki , Yahara Katsuya , Nakahara Sota , Kakinouchi Sho , Itamura Hirohide , Morisaki Takahiro , Korogi Yukunori
Published: February 2021

Background: The purpose of this study was to evaluate the effectiveness of the clinical setting for deep regional hyperthermia of an 8 MHz radiofrequency (RF) capacitively coupled device in the pelvis by using numerical simulations of the electromagnetic field. Methods: A three-dimensional patient model of cervical cancer of the uterus in an obese patient was reconstructed with computed tomography data. The specific absorption rate (SAR) and temperature distributions among the various heating settings were evaluated using numerical simulations. Results: The averaged SAR value of the deep target tumor was similar between with or without overlay boluses (OBs), and that of the subcutaneous fat (SF) at the edges of cooling boluses with OBs was lower than that of the SF without OBs. The use of OBs reduced the overheating of the SF. The 0.5% salt solution in the OB produced the least overheated areas outside the deep target tumor compared with the other concentrations. The insertion of the intergluteal cleft (IGC) bolus could improve the temperature concentration of the deep target tumor. Conclusions: The use of OBs and the salt solution concentration in the OB were important to optimize the temperature distribution. IGC bolus might contribute to temperature optimization. Further studies with individualized numerical simulations in each patient are expected.
Neoadjuvant Chemoradiotherapy Followed by Esophagectomy with Three-Field Lymph Node Dissection for Thoracic Esophageal Squamous Cell Carcinoma Patients with Clinical Stage III and with Supraclavicular Lymph Node Metastasis
Authors: Sato Yusuke , Motoyama Satoru , Wada Yuki , Wakita Akiyuki , Kawakita Yuta , Nagaki Yushi , Terata Kaori , Imai Kazuhiro , Anbai Akira , Hashimoto Manabu , Minamiya Yoshihiro
Published: February 2021

Background: Neoadjuvant chemoradiotherapy (NACRT) followed by esophagectomy is now the standard treatment for patients with resectable advanced thoracic esophageal squamous cell carcinoma (ESCC) worldwide. However, the efficacy of NACRT followed by esophagectomy with three-field lymph node dissection for clinical Stage III patients and for clinical Stage IVB patients with supraclavicular LN metastasis has not yet been determined. Methods: Between 2008 and 2018, 94 ESCC patients diagnosed as clinical Stage III and 18 patients diagnosed as clinical Stage IVB with supraclavicular LN metastasis as the only distant metastatic factor were treated with NACRT followed by esophagectomy with extended lymph node dissection at Akita University Hospital. Long-term survival and the patterns of recurrence in these 112 patients were analyzed. Results: The median follow-up period of censored cases was 60 months. The five-year OS and DSS rates among the clinical Stage III patients were 57.6% and 66.6%, respectively. The five-year OS and DSS rates among the clinical Stage IVB patients were 41.3% and 51.6%, respectively. The most frequent recurrence pattern was distant metastasis (69.2%) in the Stage III patients and LN metastasis (75.0%) in the Stage IVB patients. Conclusion: NACRT followed by esophagectomy with three-field LN dissection is feasible and offers the potential for long-term survival of clinical Stage III ESCC patients and even clinical Stage IVB patients with supraclavicular LN metastasis as the only distant metastatic factor. At least in patients with upper and middle thoracic ESCC, treating supraclavicular LNs as regional LNs seems to be appropriate.
A Broad Overview of Signaling in Ph-Negative Classic Myeloproliferative Neoplasms
Authors: Guijarro-Hernández Ana , Vizmanos José Luis
Published: February 2021

Ph-negative myeloproliferative neoplasms (polycythemia vera (PV), essential thrombocythemia (ET) and primary myelofibrosis (PMF)) are infrequent blood cancers characterized by signaling aberrations. Shortly after the discovery of the somatic mutations in JAK2, MPL, and CALR that cause these diseases, researchers extensively studied the aberrant functions of their mutant products. In all three cases, the main pathogenic mechanism appears to be the constitutive activation of JAK2/STAT signaling and JAK2-related pathways (MAPK/ERK, PI3K/AKT). However, some other non-canonical aberrant mechanisms derived from mutant JAK2 and CALR have also been described. Moreover, additional somatic mutations have been identified in other genes that affect epigenetic regulation, tumor suppression, transcription regulation, splicing and other signaling pathways, leading to the modification of some disease features and adding a layer of complexity to their molecular pathogenesis. All of these factors have highlighted the wide variety of cellular processes and pathways involved in the pathogenesis of MPNs. This review presents an overview of the complex signaling behind these diseases which could explain, at least in part, their phenotypic heterogeneity.
Morphology Regulation Mechanism and Enhancement of Photocatalytic Performance of BiOX (X = Cl, Br, I) via Mannitol-Assisted Synthesis
Authors: Wilczewska Patrycja , Bielicka-Giełdoń Aleksandra , Szczodrowski Karol , Malankowska Anna , Ryl Jacek , Tabaka Karol , Siedlecka Ewa Maria
Published: February 2021

BiOX (X = Cl, Br, I) photocatalysts with dominant (110) facets were synthesized via a mannitol-assisted solvothermal method. This is the first report on the exposed (110) facets-, size-, and defects-controlled synthesis of BiOX achieved by solvothermal synthesis with mannitol. This polyol alcohol acted simultaneously as a solvent, capping agent, and/or soft template. The mannitol concentration on the new photocatalysts morphology and surface properties was investigated in detail. At the lowest concentration tested, mannitol acted as a structure-directing agent, causing unification of nanoparticles, while at higher concentrations, it functioned as a solvent and soft template. The effect of exposed (110) facet and surface defects (Bi(3−x)+, Bi4+, Bi5+) of BiOX on the photocatalytic activity of nanomaterials under the UV–Vis irradiation were evaluated by oxidation of Rhodamine B (RhB) and 5-fluorouracil (5-FU), an anticancer drug, and by reduction of Cr(VI). Additionally, the influence of crucial factors on the formation of BiOX in the synthesis with mannitol was discussed extensively, and the mechanism of BiOX formation was proposed. These studies presented a new simple method for synthesizing BiOX without any additional surfactants or shape control agents with good photocatalytic activity. The study also provided a better understanding of the effects of solvothermal conditions on the BiOX crystal growth.
Cluster-Based Coordination Polymers of Mn/Fe-Oxo Pivalates and Isobutyrates
Authors: Baca Svetlana , Kögerler Paul
Published: February 2021

Polynuclear coordination clusters can be readily arranged in cluster-based coordination polymers (CCPs) by appropriate bridging linkers. This review provides an overview of our recent developments in exploring structurally well-defined Mn/Fe-oxo pivalate and isobutyrate building blocks in the formation of CCPs assemblies with an emphasis on synthetic strategies and magnetic properties.
Application of Improved Asynchronous Advantage Actor Critic Reinforcement Learning Model on Anomaly Detection
Authors: Zhou Kun , Wang Wenyong , Hu Teng , Deng Kai
Published: February 2021

Anomaly detection research was conducted traditionally using mathematical and statistical methods. This topic has been widely applied in many fields. Recently reinforcement learning has achieved exceptional successes in many areas such as the AlphaGo chess playing and video gaming etc. However, there were scarce researches applying reinforcement learning to the field of anomaly detection. This paper therefore aimed at proposing an adaptable asynchronous advantage actor-critic model of reinforcement learning to this field. The performances were evaluated and compared among classical machine learning and the generative adversarial model with variants. Basic principles of the related models were introduced firstly. Then problem definitions, modelling processes and testing were detailed. The proposed model differentiated the sequence and image from other anomalies by proposing appropriate neural networks of attention mechanism and convolutional network for the two kinds of anomalies, respectively. Finally, performances with classical models using public benchmark datasets (NSL-KDD, AWID and CICIDS-2017, DoHBrw-2020) were evaluated and compared. Experiments confirmed the effectiveness of the proposed model with the results indicating higher rewards and lower loss rates on the datasets during training and testing. The metrics of precision, recall rate and F1 score were higher than or at least comparable to the state-of-the-art models. We concluded the proposed model could outperform or at least achieve comparable results with the existing anomaly detection models.
The Challenges of Machine Learning and Their Economic Implications
Authors: Borrellas Pol , Unceta Irene
Published: February 2021

The deployment of machine learning models is expected to bring several benefits. Nevertheless, as a result of the complexity of the ecosystem in which models are generally trained and deployed, this technology also raises concerns regarding its (1) interpretability, (2) fairness, (3) safety, and (4) privacy. These issues can have substantial economic implications because they may hinder the development and mass adoption of machine learning. In light of this, the purpose of this paper was to determine, from a positive economics point of view, whether the free use of machine learning models maximizes aggregate social welfare or, alternatively, regulations are required. In cases in which restrictions should be enacted, policies are proposed. The adaptation of current tort and anti-discrimination laws is found to guarantee an optimal level of interpretability and fairness. Additionally, existing market solutions appear to incentivize machine learning operators to equip models with a degree of security and privacy that maximizes aggregate social welfare. These findings are expected to be valuable to inform the design of efficient public policies.
The Natural Philosophy of Economic Information: Autonomous Agents and Physiosemiosis
Authors: Herrmann-Pillath Carsten
Published: February 2021

Information is a core concept in modern economics, yet its definition and empirical specification is elusive. One reason is the intellectual grip of the Shannon paradigm which marginalizes semantic information. However, a precise concept of economic information must be based on a theory of semantics, since what counts economically is the meaning, function and use of information. This paper introduces a new principled approach to information that adopts the paradigm of biosemiotics, rooted in the philosophy of Charles S. Peirce and builds on recent developments of the thermodynamics of information. Information processing by autonomous agents, defined as autopoietic heat engines, is conceived as physiosemiosis operating according to fundamental thermodynamic principles of information processing, as elucidated in recent work by Kolchinsky and Wolpert (KW). I plug the KW approach into a basic conceptual model of physiosemiosis and present an evolutionary interpretation. This approach has far-reaching implications for economics, such as suggesting an evolutionary view of the economic agent, choice and behavior, which is informed by applications of statistical thermodynamics on the brain.
Image Defogging Framework Using Segmentation and the Dark Channel Prior
Authors: Anan Sabiha , Khan Mohammad Ibrahim , Kowsar Mir Md Saki , Deb Kaushik , Dhar Pranab Kumar , Koshiba Takeshi
Published: February 2021

Foggy images suffer from low contrast and poor visibility problem along with little color information of the scene. It is imperative to remove fog from images as a pre-processing step in computer vision. The Dark Channel Prior (DCP) technique is a very promising defogging technique due to excellent restoring results for images containing no homogeneous region. However, having a large homogeneous region such as sky region, the restored images suffer from color distortion and block effects. Thus, to overcome the limitation of DCP method, we introduce a framework which is based on sky and non-sky region segmentation and restoring sky and non-sky parts separately. Here, isolation of the sky and non-sky part is done by using a binary mask formulated by floodfill algorithm. The foggy sky part is restored by using Contrast Limited Adaptive Histogram Equalization (CLAHE) and non-sky part by modified DCP. The restored parts are blended together for the resultant image. The proposed method is evaluated using both synthetic and real world foggy images against state of the art techniques. The experimental result shows that our proposed method provides better entropy value than other stated techniques along with have better natural visual effects while consuming much lower processing time.
Conditional Entropy: A Potential Digital Marker for Stress
Authors: Keshmiri Soheil
Published: February 2021

Recent decades have witnessed a substantial progress in the utilization of brain activity for the identification of stress digital markers. In particular, the success of entropic measures for this purpose is very appealing, considering (1) their suitability for capturing both linear and non-linear characteristics of brain activity recordings and (2) their direct association with the brain signal variability. These findings rely on external stimuli to induce the brain stress response. On the other hand, research suggests that the use of different types of experimentally induced psychological and physical stressors could potentially yield differential impacts on the brain response to stress and therefore should be dissociated from more general patterns. The present study takes a step toward addressing this issue by introducing conditional entropy (CE) as a potential electroencephalography (EEG)-based resting-state digital marker of stress. For this purpose, we use the resting-state multi-channel EEG recordings of 20 individuals whose responses to stress-related questionnaires show significantly higher and lower level of stress. Through the application of representational similarity analysis (RSA) and K-nearest-neighbor (KNN) classification, we verify the potential that the use of CE can offer to the solution concept of finding an effective digital marker for stress.
Coupled Feedback Loops Involving PAGE4, EMT and Notch Signaling Can Give Rise to Non-Genetic Heterogeneity in Prostate Cancer Cells
Authors: Singh Divyoj , Bocci Federico , Kulkarni Prakash , Jolly Mohit Kumar
Published: February 2021

Non-genetic heterogeneity is emerging as a crucial factor underlying therapy resistance in multiple cancers. However, the design principles of regulatory networks underlying non-genetic heterogeneity in cancer remain poorly understood. Here, we investigate the coupled dynamics of feedback loops involving (a) oscillations in androgen receptor (AR) signaling mediated through an intrinsically disordered protein PAGE4, (b) multistability in epithelial–mesenchymal transition (EMT), and (c) Notch–Delta–Jagged signaling mediated cell-cell communication, each of which can generate non-genetic heterogeneity through multistability and/or oscillations. Our results show how different coupling strengths between AR and EMT signaling can lead to monostability, bistability, or oscillations in the levels of AR, as well as propagation of oscillations to EMT dynamics. These results reveal the emergent dynamics of coupled oscillatory and multi-stable systems and unravel mechanisms by which non-genetic heterogeneity in AR levels can be generated, which can act as a barrier to most existing therapies for prostate cancer patients.
Localize the Impact of Global Greenhouse Gases Emissions under an Uncertain Future: A Case Study in Western Cape, South Africa
Authors: He Bowen , Ding Ke J.
Published: February 2021

The growing impact of CO2 and other greenhouse-gas (GHG) emissions on the socio-climate system in the Western Cape, South Africa, urgently calls for the need for better climate adaptation and emissions-reduction strategies. While the consensus has been that there is a strong correlation between CO2 emissions and the global climate system, few studies on climate change in the Western Cape have quantified the impact of climate change on local climate metrics such as precipitation and evaporation under different future climate scenarios. The present study investigates three different CO2 emissions scenarios: Representative Concentration Pathway (RCP) 2.6, RCP 4.5, and RCP 8.5, from moderate to severe, respectively. Specifically, we used climate metrics including precipitation, daily mean and maximum near-surface air temperature, and evaporation to evaluate the future climate in Western Cape under each different RCP climate scenario. The projected simulation results reveal that temperature-related metrics are more sensitive to CO2 emissions than water-related metrics. Districts closer to the south coast are more resilient to severer GHG emissions scenarios compared to inland areas regarding temperature and rainfall; however, coastal regions are more likely to suffer from severe droughts such as the “Day-Zero” water crisis. As a result, a robust drying signal across the Western Cape region is likely to be seen in the second half of the 21st century, especially under the scenario of RCP 8.5 (business as usual) without efficient emissions reduction policies.
Adaptive Global Sliding Mode Controller Design for Perturbed DC-DC Buck Converters
Authors: Mobayen Saleh , Bayat Farhad , Lai Chun-Chi , Taheri Asghar , Fekih Afef
Published: February 2021

This paper proposes a novel adaptive intelligent global sliding mode control for the tracking control of a DC-DC buck converter with time-varying uncertainties/disturbances. The proposed control law is formulated using a switching surface that eliminates the reaching phase and ensures the existence of the sliding action from the start. The control law is derived based on the Lyapunov stability theory. The effectiveness of the proposed approach is illustrated via high-fidelity simulations by means of Simscape simulation environment in MATLAB. Satisfactory tracking accuracy, efficient suppression of the chattering phenomenon in the control input, and high robustness against uncertainties/disturbances are among the attributes of the proposed control approach.
Effect of Pore Shape and Spacing on Water Droplet Dynamics in Flow Channels of Proton Exchange Membrane Fuel Cells
Authors: Fan Mengying , Duan Fengyun , Wang Tianqi , Kang Mingming , Zeng Bin , Xu Jian , Anderson Ryan , Du Wei , Zhang Lifeng
Published: February 2021

Effective water management increases the performance of proton exchange membrane fuel cells (PEMFCs). The liquid droplet movement mechanism in the cathode channel, the gas-liquid two-phase flow pattern, and the resulting pressure drop are important to water management in PEMFCs. This work employed computational fluid dynamics (CFD) with a volume of fluid (VOF) to simulate the effects of two operating parameters on the liquid water flow in the cathode flow channel: Gas diffusion layer (GDL) pore shape for water emergence, and distance between GDL pores. From seven pore shapes considered in this work, the longer the windward side of the micropore is, the larger the droplet can grow, and the duration of droplet growth movement will be longer. In the cases of two micropores for water introduction, a critical pore distance is noted for whether two droplets coalesce. When the micropore distance was shorter than this critical value, different droplets coalesce after the droplets grew to a certain extent. These results indicate that the pore shape and the distance between pores should be accounted for in future simulations of PEMFC droplet dynamics and that these parameters need to be optimized when designing novel GDL structures.
Identifying Challenges in Engaging Users to Increase Self-Consumption of Electricity in Microgrids
Authors: El Gohary Fouad , Nyström Sofie , Reitsma Lizette , Bartusch Cajsa
Published: February 2021

A microgrid’s self-consumption rate reflects its ability to retain its own energy and decrease its reliance on the synchronous grid. This paper investigates the empirical case of a microgrid equipped with photovoltaic (PV) panels and identifies challenges in engaging the microgrid’s users to increase their self-consumption. Accordingly, we explored both the physical and social dimensions of the microgrid. The former involved mapping the electricity consumption and production through an exploratory data analysis, and evaluating the associated price signals, while the latter involved the use of design interventions to explore users’ perceptions of the system. We highlight the problem of price signal impedance, the need for cost reflective pricing and the challenge in designing and extending internal price models in settings with various actors. We address the limitations of price signals, alongside alternative unidimensional signals, and emphasize the need for an integrated approach to a user engagement strategy as well as the challenges that this approach entails. Our results shed light on the complexity of energy communities such as microgrids, and why their implementation can introduce multidimensional challenges that demand cross-disciplinary approaches.
Direct Comparison of Immersion and Cold-Plate Based Cooling for Automotive Li-Ion Battery Modules
Authors: Dubey Prahit , Pulugundla Gautam , Srouji A. K.
Published: February 2021

The current paper evaluates the thermal performance of immersion cooling for an Electric Vehicle (EV) battery module comprised of NCA-chemistry based cylindrical 21700 format Lithium-ion cells. Efficacy of immersion cooling in improving maximum cell temperature, cell’s temperature gradient, cell-to-cell temperature differential, and pressure drop in the module are investigated by direct comparison with a cold-plate-cooled battery module. Parametric analyses are performed at different module discharge C-rates and coolant flow rates to understand the sensitivity of each cooling strategy to important system performance parameters. The entire numerical analysis is performed using a validated 3D time-accurate Computational Fluid Dynamics (CFD) methodology in STAR-CCM+. Results demonstrate that immersion cooling due its higher thermal conductance leads to a lower maximum cell temperature and lower temperature gradients within the cells at high discharge rates. However, a higher rate of heat rejection and poor thermal properties of the dielectric liquid results in a much higher temperature non-uniformity across the module. At lower discharge rates, the two cooling methods show similar thermal performance. Additionally, owing to the lower viscosity and density of the considered dielectric liquid, an immersion-cooled battery module performs significantly better than the cold-plate-cooled module in terms of both coolant pressure drop.
Massive Generation of Customer Load Profiles for Large Scale State Estimation Deployment: An Approach to Exploit AMI Limited Data
Authors: Della Giustina Davide , Rinaldi Stefano , Robustelli Stefano , Angioni Andrea
Published: February 2021

The management of the distribution network is becoming increasingly important as the penetration of distributed energy resources is increasing. Reliable knowledge of the real-time status of the network is essential if algorithms are to be used to help distribution system operators define network configurations. State Estimation (SE) algorithms are capable of producing such an accurate snapshot of the network state but, in turn, require a wide range of information, e.g., network topology, real-time measurement and power profiles from customers/productions. Those profiles which may, in principle, be provided by smart meters are not always available due to technical limitations of existing Advanced Metering Infrastructure (AMI) in terms of communication, storage and computing power. That means that power profiles are only available for a subset of customers. The paper proposes an approach that can overcome these limitations: the remaining profiles, required by SE algorithms, are generated on the basis of customer-related information, identifying clusters of customers with similar features, such as the same contract and pattern of energy consumption. For each cluster, a power profile estimator is generated using long-term power profiles of a limited sub-set of customers, randomly selected from the cluster itself. The synthesized full power profile, representing each customer of the distribution network, is then obtained by scaling the power profile estimator of the cluster to which the customer belongs, by the monthly energy exchanged by that customer, data that are easily available. The feasibility of the proposed approach was validated considering the distribution grid of Unareti SpA, an Italian Distribution System Operator (DSO), operating in northern Italy and serving approximately one million customers. The application of the proposed approach to the actual infrastructure shows some limitations in terms of the accuracy of the estimation of the power profile of the customer. In particular, the proposed methodology is not fully able to properly represent clusters composed of customers with a large variability in terms of power exchange with the distribution network. In any case, the root mean square error of the synthesized full power profile with the respect to validation power profiles belonging to the same cluster is, in the worst case, on the order of 6.3%, while in the rest of cases is well below 5%. Thus, the proposed approach represents a good compromise between accuracy in representing the behavior of customers on the network and resources (in terms of computational power, data storage and communication resources) to achieve that results.
Hydroelectric Plants and Dams as Industrial Heritage in the Context of Nature-Culture Interrelation: An Overview of Examples in Turkey
Authors: Kuban Nurdan
Published: February 2021

The article investigates nature–culture interrelation over the case studies of hydroelectric plants of the 20th century. In many cases, construction of these structures has evidently resulted in irreversible changes in natural and cultural environments. However, they have also supplied energy for the industrialization of civilizations. After approximately 100 years of existence, it is crucial to determine the future of these hydroelectric facilities, which are artifacts of industrial heritage approaching the end of their productive life spans. The article proposes an analytical approach aiming to sustain the integrity of nature and culture in the conservation of hydroelectric plants, presenting these energy facilities as cultural properties of industrial heritage, and discussing the impact of hydroelectric dams on natural and cultural environments, along with the effects of nature in the deterioration of these structures in order to pave the way to an optimized and sustainable future for the heritage of energy.
Selection of Parameters for Accumulating Layer of Solar Walls with Transparent Insulation
Authors: Świrska-Perkowska Jadwiga , Perkowski Zbigniew
Published: February 2021

One of the strategies to improve the energy performance of buildings may be the use of passive solar systems with transparent insulation. In the article, a numerical model of solar wall (SW) with transparent insulation (TI) obtained using the method of elementary balances is presented. On this basis, numerical simulations of the behavior of SW with a transparent honeycomb insulation made of modified cellulose acetate were performed for 4 different climatic conditions in Europe (Stockholm, Warsaw, Paris, and Rome). For each location, the calculations were carried out for three different TI thickness values (48, 88, and 128 mm), for thermal diffusivity of the accumulating layer (AL) ranging from 4.32 × 10−7 to 8.43 × 10−7 m2/s, and for its thickness ranging from 0.1 to 0.5 m. The purpose of simulations was to select the appropriate material and thickness of AL and TI for the climatic conditions. The following solutions proved to be the most favorable: Stockholm: TI—thk. 128 mm, AL—sand-lime blocks, thk. 25 cm; Warsaw: TI—thk. 128 mm, AL—sand-lime blocks, thk. 27 cm; Paris: TI—thk. 88 mm, AL—solid ceramic brick, thk. 27 cm; Rome: TI—thk. 48 mm, AL—solid ceramic brick, thk. 29 cm.
Sensitivity and Uncertainty of the FLORIS Model Applied on the Lillgrund Wind Farm
Authors: van Beek Maarten T. , Viré Axelle , Andersen Søren J.
Published: February 2021

Wind farms experience significant efficiency losses due to the aerodynamic interaction between turbines. A possible control technique to minimize these losses is yaw-based wake steering. This paper investigates the potential for improved performance of the Lillgrund wind farm through a detailed calibration of a low-fidelity engineering model aimed specifically at yaw-based wake steering. The importance of each model parameter is assessed through a sensitivity analysis. This work shows that the model is overparameterized as at least one model parameter can be excluded from the calibration. The performance of the calibrated model is tested through an uncertainty analysis, which showed that the model has a significant bias but low uncertainty when comparing the predicted wake losses with measured wake losses. The model is used to optimize the annual energy production of the Lillgrund wind farm by determining yaw angles for specific inflow conditions. A significant energy gain is found when the optimal yaw angles are calculated deterministically. However, the energy gain decreases drastically when uncertainty in input conditions is included. More robust yaw angles can be obtained when the input uncertainty is taken into account during the optimization, which yields an energy gain of approximately 3.4%.
Investigation of Degradation and Upgradation Models for Flexible Unit Systems: A Systematic Literature Review
Authors: Samala Thirupathi , Manupati Vijaya Kumar , Varela Maria Leonilde R. , Putnik Goran
Published: February 2021

Research on flexible unit systems (FUS) with the context of descriptive, predictive, and prescriptive analysis have remarkably progressed in recent times, being now reinforced in the current Industry 4.0 era with the increased focus on integration of distributed and digitalized systems. In the existing literature, most of the work focused on the individual contributions of the above mentioned three analyses. Moreover, the current literature is unclear with respect to the integration of degradation and upgradation models for FUS. In this paper, a systematic literature review on degradation, residual life distribution, workload adjustment strategy, upgradation, and predictive maintenance as major performance measures to investigate the performance of the FUS has been considered. In order to identify the key issues and research gaps in the existing literature, the 59 most relevant papers from 2009 to 2020 have been sorted and analyzed. Finally, we identify promising research opportunities that could expand the scope and depth of FUS.