bluuebunny/crossref_metadata_2025 huggingface dataset:
Rethinking Incarcerated Women's Leisure as Subjected to Coercive and Normative Prison Missions
Authors: Marcoux Rouleau Alexis
Published: November 2020

Leisure is commonly understood as contributing to well-being; this is especially appealing when considering multiply marginalized populations such as incarcerated women. However, leisure is not impervious to cooptation by less benevolent social processes. In this conceptual analysis, I argue that incarcerated women's leisure must be rethought as a component of its environment and by extension, as subjected to coercive and normative prison missions. After broadly delineating incarcerated women's leisure, I determine that some characteristics of leisure can be compatible with these prison missions. I then examine individual, organizational, and social benefits and issues with leisure in women's prisons. I link these practices to reduced coerciveness and increased normativity. I conclude by suggesting that ensuring incarcerated people's well-being through leisure is not in itself an end, but a means to achieve prison's coercive and normative ends. I discuss implications for scholars, practitioners, and advocates.
Antimicrobial Activity of Encapsulated Mexican Oregano (Lippia berlandieri Schauer) Essential Oil Applied on Bagels
Authors: Salgado-Nava Aída Araceli , Hernández-Nava Ruth , López-Malo Aurelio , Jiménez-Munguía María Teresa
Published: November 2020

Several in vitro studies of Mexican oregano essential oil (MOEO) have demonstrated its effectiveness as an antimicrobial. On the other hand, the encapsulation technique of emulsification could be used to mask the intense flavor of MOEO, protect it from physicochemical degradation, and release gradually its antimicrobial components. In the present study, emulsions were elaborated with two encapsulating agents, pectin or Arabic gum, with five concentrations of MOEO (0%, 5%, 7.5%, 10%, or 15% w/w). Emulsions were characterized by density, viscosity, particle size distribution, creaming index, and peroxide index. Emulsions were applied, in a 3:1 ratio, on the surface of two formulations of bagel, one with wheat flour (BW) and another with wheat flour and oats (BWO). Bagels were characterized by water activity, moisture content, and hardness. The antimicrobial activity of MOEO encapsulated by emulsification on Penicillium expansum on the surface of the bagels was determined. In addition, a sensory analysis of the bagels was carried out using a hedonic scale. All physicochemical properties of the emulsions had a significant difference (p < 0.05) because of the encapsulating agent used (pectin or Arabic gum). Emulsions stabilized with Arabic gum were more stable over time than the ones with pectin. The application of the emulsions on the surface of the bagels did not show a statistical difference (p > 0.05) in the physicochemical properties of the breads. The growth of P. expansum was delayed for up to 5 or 6 days in bagels with wheat flour and Arabic gum as encapsulating agent. Both systems, BW and BWO, atomized with MOEO emulsions at high concentrations (MOEO 15% w/w) were well accepted by the panel of judges when these were evaluated on day 0 (freshly baked bread) but not after 6 days of their elaboration.
Pseudo Random Number Generation through Reinforcement Learning and Recurrent Neural Networks
Authors: Pasqualini Luca , Parton Maurizio
Published: November 2020

A Pseudo-Random Number Generator (PRNG) is any algorithm generating a sequence of numbers approximating properties of random numbers. These numbers are widely employed in mid-level cryptography and in software applications. Test suites are used to evaluate the quality of PRNGs by checking statistical properties of the generated sequences. These sequences are commonly represented bit by bit. This paper proposes a Reinforcement Learning (RL) approach to the task of generating PRNGs from scratch by learning a policy to solve a partially observable Markov Decision Process (MDP), where the full state is the period of the generated sequence, and the observation at each time-step is the last sequence of bits appended to such states. We use Long-Short Term Memory (LSTM) architecture to model the temporal relationship between observations at different time-steps by tasking the LSTM memory with the extraction of significant features of the hidden portion of the MDP’s states. We show that modeling a PRNG with a partially observable MDP and an LSTM architecture largely improves the results of the fully observable feedforward RL approach introduced in previous work.
Crystal Structure and Characterization of Human Heavy-Chain Only Antibodies Reveals a Novel, Stable Dimeric Structure Similar to Monoclonal Antibodies
Authors: Mieczkowski Carl , Bahmanjah Soheila , Yu Yao , Baker Jeanne , Raghunathan Gopalan , Tomazela Daniela , Hsieh Mark , McCoy Mark , Strickland Corey , Fayadat-Dilman Laurence
Published: November 2020

We report the novel crystal structure and characterization of symmetrical, homodimeric humanized heavy-chain-only antibodies or dimers (HC2s). HC2s were found to be significantly coexpressed and secreted along with mAbs from transient CHO HC/LC cotransfection, resulting in an unacceptable mAb developability attribute. Expression of full-length HC2s in the absence of LC followed by purification resulted in HC2s with high purity and thermal stability similar to conventional mAbs. The VH and CH1 portion of the heavy chain (or Fd) was also efficiently expressed and yielded a stable, covalent, and reducible dimer (Fd2). Mutagenesis of all heavy chain cysteines involved in disulfide bond formation revealed that Fd2 intermolecular disulfide formation was similar to Fabs and elucidated requirements for Fd2 folding and expression. For one HC2, we solved the crystal structure of the Fd2 domain to 2.9 Å, revealing a highly symmetrical homodimer that is structurally similar to Fabs and is mediated by conserved (CH1) and variable (VH) contacts with all CDRs positioned outward for target binding. Interfacial dimer contacts revealed by the crystal structure were mutated for two HC2s and were found to dramatically affect HC2 formation while maintaining mAb bioactivity, offering a potential means to modulate novel HC2 formation through engineering. These findings indicate that human heavy-chain dimers can be secreted efficiently in the absence of light chains, may show good physicochemical properties and stability, are structurally similar to Fabs, offer insights into their mechanism of formation, and may be amenable as a novel therapeutic modality.
Experimental Implications of Negative Quantum Conditional Entropy—H2 Mobility in Nanoporous Materials
Authors: Chatzidimitriou-Dreismann C. Aris
Published: November 2020

During the last few decades, considerable advances in quantum information theory have shown deep existing connections between quantum correlation effects (like entanglement and quantum discord) and thermodynamics. Here the concept of conditional entropy plays a considerable role. In contrast to the classical case, quantum conditional entropy can take negative values. This counter-intuitive feature, already well understood in the context of information theory, was recently shown theoretically to also have a physical meaning in quantum thermodynamics [del Rio et al. Nature 2011, 474, 61]. Extending this existing work, here we provide evidence of the significance of negative conditional entropy in a concrete experimental context: Incoherent Neutron Scattering (INS) from protons of H2 in nano-scale environments; e.g., in INS from H2 in C-nanotubes, the data of the H2 translational motion along the nanotube axis seems to show that the neutron apparently scatters from a fictitious particle with mass of 0.64 atomic mass units (a.m.u.)—instead of the value of 2 a.m.u. as conventionally expected. An independent second experiment confirms this finding. However, taking into account the possible negativity of conditional entropy, we explain that this effect has a natural interpretation in terms of quantum thermodynamics. Moreover, it is intrinsically related to the number of qubits capturing the interaction of the two quantum systems H2 and C-nanotube. The considered effect may have technological applications (e.g., in H-storage materials and fuel cells).
Sequence-to-Sequence Video Prediction by Learning Hierarchical Representations
Authors: Fan Kun , Joung Chungin , Baek Seungjun
Published: November 2020

Video prediction which maps a sequence of past video frames into realistic future video frames is a challenging task because it is difficult to generate realistic frames and model the coherent relationship between consecutive video frames. In this paper, we propose a hierarchical sequence-to-sequence prediction approach to address this challenge. We present an end-to-end trainable architecture in which the frame generator automatically encodes input frames into different levels of latent Convolutional Neural Network (CNN) features, and then recursively generates future frames conditioned on the estimated hierarchical CNN features and previous prediction. Our design is intended to automatically learn hierarchical representations of video and their temporal dynamics. Convolutional Long Short-Term Memory (ConvLSTM) is used in combination with skip connections so as to separately capture the sequential structures of multiple levels of hierarchy of features. We adopt Scheduled Sampling for training our recurrent network in order to facilitate convergence and to produce high-quality sequence predictions. We evaluate our method on the Bouncing Balls, Moving MNIST, and KTH human action dataset, and report favorable results as compared to existing methods.
Effect of Particle Size on Mechanical Property of Bio-Treated Sand Foundation
Authors: Yang Defeng , Xu Guobin , Duan Yu
Published: November 2020

In the field of geotechnical engineering, microbially induced calcium precipitation technology is feasible and sustainable alternative to improve the engineering characteristics of sand foundation under different geological conditions for a long time. However, it is unclear how the effects of different sand particle sizes on the engineering characteristics of bio-treated sand column. The method of intermittent injection in batches was used to develop a series of bio-treated sand columns. The results showed that the mechanical properties of the bio-treated column improved by increasing the particle size. Low concentration of bacterial suspension and cementation reagent leads to the increase of calcium carbonate and unconfined compressive strength. Additionally, the total injection times increased, thus risking time cost. Furthermore, the increase of sand particle size was beneficial to the uniformity of the spatial distribution of calcium carbonate in the bio-treated column. The coefficient of variation was reduced by up to 52.0%. Scanning electron microscopy results confirmed that the size and uniformity of calcite crystals on the surface of sand particles were related to the concentration of cementation solution.
An Adaptable Big Data Value Chain Framework for End-to-End Big Data Monetization
Authors: Faroukhi Abou Zakaria , El Alaoui Imane , Gahi Youssef , Amine Aouatif
Published: November 2020

Today, almost all active organizations manage a large amount of data from their business operations with partners, customers, and even competitors. They rely on Data Value Chain (DVC) models to handle data processes and extract hidden values to obtain reliable insights. With the advent of Big Data, operations have become increasingly more data-driven, facing new challenges related to volume, variety, and velocity, and giving birth to another type of value chain called Big Data Value Chain (BDVC). Organizations have become increasingly interested in this kind of value chain to extract confined knowledge and monetize their data assets efficiently. However, few contributions to this field have addressed the BDVC in a synoptic way by considering Big Data monetization. This paper aims to provide an exhaustive and expanded BDVC framework. This end-to-end framework allows us to handle Big Data monetization to make organizations’ processes entirely data-driven, support decision-making, and facilitate value co-creation. For this, we present a comprehensive review of existing BDVC models relying on some definitions and theoretical foundations of data monetization. Next, we expose research carried out on data monetization strategies and business models. Then, we offer a global and generic BDVC framework that supports most of the required phases to achieve data valorization. Furthermore, we present both a reduced and full monetization model to support many co-creation contexts along the BDVC.
Three-Dimensional Biofabrication Models of Endometriosis and the Endometriotic Microenvironment
Authors: Wendel Jillian R. H. , Wang Xiyin , Smith Lester J. , Hawkins Shannon M.
Published: November 2020

Endometriosis occurs when endometrial-like tissue grows outside the uterine cavity, leading to pelvic pain, infertility, and increased risk of ovarian cancer. The present study describes the optimization and characterization of cellular spheroids as building blocks for Kenzan scaffold-free method biofabrication and proof-of-concept models of endometriosis and the endometriotic microenvironment. The spheroid building blocks must be of a specific diameter (~500 μm), compact, round, and smooth to withstand Kenzan biofabrication. Under optimized spheroid conditions for biofabrication, the endometriotic epithelial-like cell line, 12Z, expressed high levels of estrogen-related genes and secreted high amounts of endometriotic inflammatory factors that were independent of TNFα stimulation. Heterotypic spheroids, composed of 12Z and T-HESC, an immortalized endometrial stromal cell line, self-assembled into a biologically relevant pattern, consisting of epithelial cells on the outside of the spheroids and stromal cells in the core. 12Z spheroids were biofabricated into large three-dimensional constructs alone, with HEYA8 spheroids, or as heterotypic spheroids with T-HESC. These three-dimensional biofabricated constructs containing multiple monotypic or heterotypic spheroids represent the first scaffold-free biofabricated in vitro models of endometriosis and the endometriotic microenvironment. These efficient and innovative models will allow us to study the complex interactions of multiple cell types within a biologically relevant microenvironment.
Adenosine A2A and A3 Receptors as Targets for the Treatment of Hypertensive-Diabetic Nephropathy
Authors: Patinha Daniela , Abreu Carla , Carvalho Carla , Cunha Olga Mariana , Mota Mariana , Afonso Joana , Sousa Teresa , Albino-Teixeira António , Diniz Carmen , Morato Manuela
Published: November 2020

Diabetic nephropathy (DN) and hypertension are prime causes for end-stage renal disease (ESRD) that often coexist in patients, but are seldom studied in combination. Kidney adenosine levels are markedly increased in diabetes, and the expression and function of renal adenosine receptors are altered in experimental diabetes. The aim of this work is to explore the impact of endogenous and exogenous adenosine on the expression/distribution profile of its receptors along the nephron of hypertensive rats with experimentally-induced diabetes. Using spontaneously hypertensive (SHR) rats rendered diabetic with streptozotocin (STZ), we show that treatment of SHR-STZ rats with an agonist of adenosine receptors increases A2A immunoreactivity in superficial glomeruli (SG), proximal tubule (PCT), and distal tubule (DCT). Differently, treatment of SHR-STZ rats with a xanthinic antagonist of adenosine receptors decreases adenosine A3 immunoreactivity in SG, PCT, DCT, and collecting duct. There is no difference in the immunoreactivity against the adenosine A1 and A2B receptors between the experimental groups. The agonist of adenosine receptors ameliorates renal fibrosis, probably via A2A receptors, while the antagonist exacerbates it, most likely due to tonic activation of A3 receptors. The reduction in adenosine A3 immunoreactivity might be due to receptor downregulation in response to prolonged activation. Altogether, these results suggest an opposite regulation exerted by endogenous and exogenous adenosine upon the expression of its A2A and A3 receptors along the nephron of hypertensive diabetic rats, which has a functional impact and should be taken into account when considering novel therapeutic targets for hypertensive-diabetic nephropathy.
Exercise Reduces the Resumption of Tumor Growth and Proteolytic Pathways in the Skeletal Muscle of Mice Following Chemotherapy
Authors: Alves de Lima Edson , Teixeira Alexandre Abilio de Souza , Biondo Luana Amorim , Diniz Tiego Aparecido , Silveira Loreana Sanches , Coletti Dario , Busquets Rius Silvia , Rosa Neto José Cesar
Published: November 2020

The pathogenesis of muscle atrophy plays a central role in cancer cachexia, and chemotherapy contributes to this condition. Therefore, the present study aimed to evaluate the effects of endurance exercise on time-dependent muscle atrophy caused by doxorubicin. For this, C57 BL/6 mice were subcutaneously inoculated with Lewis lung carcinoma cells (LLC group). One week after the tumor establishment, a group of these animals initiated the doxorubicin chemotherapy alone (LLC + DOX group) or combined with endurance exercise (LLC + DOX + EXER group). One group of animals was euthanized after the chemotherapy cycle, whereas the remaining animals were euthanized one week after the last administration of doxorubicin. The practice of exercise combined with chemotherapy showed beneficial effects such as a decrease in tumor growth rate after chemotherapy interruption and amelioration of premature death due to doxorubicin toxicity. Moreover, the protein degradation levels in mice undergoing exercise returned to basal levels after chemotherapy; in contrast, the mice treated with doxorubicin alone experienced an increase in the mRNA expression levels of the proteolytic pathways in gastrocnemius muscle (Trim63, Fbxo32, Myostatin, FoxO). Collectively, our results suggest that endurance exercise could be utilized during and after chemotherapy for mitigating muscle atrophy promoted by doxorubicin and avoid the resumption of tumor growth.
The Small GTPase RAC1B: A Potent Negative Regulator of-and Useful Tool to Study-TGFβ Signaling
Authors: Ungefroren Hendrik , Wellner Ulrich F. , Keck Tobias , Lehnert Hendrik , Marquardt Jens-Uwe
Published: November 2020

RAC1 and its alternatively spliced isoform, RAC1B, are members of the Rho family of GTPases. Both isoforms are involved in the regulation of actin cytoskeleton remodeling, cell motility, cell proliferation, and epithelial–mesenchymal transition (EMT). Compared to RAC1, RAC1B exhibits a number of distinctive features with respect to tissue distribution, downstream signaling and a role in disease conditions like inflammation and cancer. The subcellular locations and interaction partners of RAC1 and RAC1B vary depending on their activation state, which makes RAC1 and RAC1B ideal candidates to establish cross-talk with cancer-associated signaling pathways—for instance, interactions with signaling by transforming growth factor β (TGFβ), a known tumor promoter. Although RAC1 has been found to promote TGFβ-driven tumor progression, recent observations in pancreatic carcinoma cells surprisingly revealed that RAC1B confers anti-oncogenic properties, i.e., through inhibiting TGFβ-induced EMT. Since then, an unexpected array of mechanisms through which RAC1B cross-talks with TGFβ signaling has been demonstrated. However, rather than being uniformly inhibitory, RAC1B interacts with TGFβ signaling in a way that results in the selective blockade of tumor-promoting pathways, while concomitantly allowing tumor-suppressive pathways to proceed. In this review article, we are going to discuss the specific interactions between RAC1B and TGFβ signaling, which occur at multiple levels and include various components such as ligands, receptors, cytosolic mediators, transcription factors, and extracellular inhibitors of TGFβ ligands.
Pre-Existing Cardiovascular Conditions as Clinical Predictors of Myocarditis Reporting with Immune Checkpoint Inhibitors: A VigiBase Study
Authors: Noseda Roberta , Ruinelli Lorenzo , van der Gaag Linda C. , Ceschi Alessandro
Published: November 2020

Although rare, immune checkpoint inhibitor (ICI)-related myocarditis can be life-threatening, even fatal. In view of increased ICI prescription, identification of clinical risk factors for ICI-related myocarditis is of primary importance. This study aimed to assess whether pre-existing cardiovascular (CV) patient conditions are associated with the reporting of ICI-related myocarditis in VigiBase, the WHO global database of suspected adverse drug reactions (ADRs). In a (retrospective) matched case-control study, 108 cases of ICI-related myocarditis and 108 controls of ICI-related ADRs other than myocarditis were selected from VigiBase. Drugs labeled as treatment for CV conditions (used as a proxy for concomitant CV risk factors and/or CV diseases) were found to be associated more strongly with the reporting of ICI-related myocarditis than with other ICI-related ADRs (McNemar’s chi-square test of marginal homogeneity: p = 0.026, Cramer’s coefficient of effect size: Φ = 0.214). No significant association was found between pre-existing diabetes and ICI-related myocarditis reporting (McNemar’s test of marginal homogeneity: p = 0.752). These findings offer an invitation for future prospective pharmacoepidemiological studies to assess the causal relationship between pre-existing CV conditions and myocarditis onset in a cohort of cancer patients followed during ICI treatment.
Clinicopathological and Molecular Profiles of Sporadic Microsatellite Unstable Colorectal Cancer with or without the CpG Island Methylator Phenotype (CIMP)
Authors: Chang Shih-Ching , Li Anna Fen-Yau , Lin Pei-Ching , Lin Chun-Chi , Lin Hung-Hsin , Huang Shen-Chieh , Lin Chien-Hsing , Liang Wen-Yi , Chen Wei-Shone , Jiang Jeng-Kai , Lin Jen-Kou , Yang Shung-Haur , Lan Yuan-Tzu
Published: November 2020

Background: The 5’-C-phosphate-G-3’ island methylator phenotype (CIMP) is a specific phenotype of colorectal cancer (CRC) associated with microsatellite instability-high (MSI-high) tumors. Methods: In this study, we determined the CIMP status using eight methylation markers in 92 MSI-high CRC patients after excluding five germline mismatch repair (MMR) gene mutations analyzed by next-generation sequencing (NGS) and confirmed by Sanger sequencing. The mutation spectra of 22 common CRC-associated genes were analyzed by NGS. Results: Of the 92 sporadic MSI-high tumors, 23 (25%) were considered CIMP-high (expressed more than 5 of 8 markers). CIMP-high tumors showed proximal colon preponderance and female predominance. The mutation profiles of CIMP-high tumors were significantly different from those of CIMP-low or CIMP-0 tumors (i.e., higher frequencies of BRAF, POLD1, MSH3, and SMAD4 mutations but lower frequencies of APC, TP53, and KRAS mutations). Multivariate analysis demonstrated that tumor, node, metastasis (TNM) stage was the independent prognostic factor affecting overall survival (OS). Among the MSI-high cases, the CIMP status did not impact the outcome of patients with MSI-high tumors. Conclusions: Only TNM stage was a statistically significant predictor of outcomes independent of CIMP profiles in MSI-high CRC patients. Sporadic MSI-high CRCs with different mechanisms of carcinogenesis have specific mutation profiles and clinicopathological features.
Role of Selective Autophagy in Spermatogenesis and Male Fertility
Authors: Lv Chunyu , Wang Xiaoli , Guo Ying , Yuan Shuiqiao
Published: November 2020

Autophagy is a “self-eating” process that engulfs cellular contents for their subsequent digestion in lysosomes to engage the metabolic need in response to starvation or environmental insults. According to the contents of degradation, autophagy can be divided into bulk autophagy (non-selective autophagy) and selective autophagy. Bulk autophagy degrades non-specific cytoplasmic materials in response to nutrient starvation while selective autophagy targets specific cargoes, such as damaged organelles, protein aggregates, and intracellular pathogens. Selective autophagy has been documented to relate to the reproductive processes, especially for the spermatogenesis, fertilization, and biosynthesis of testosterone. Although selective autophagy is vital in the field of reproduction, its role and the underlying mechanism have remained unclear. In this review, we focus on selective autophagy to discuss the recent advances in our understanding of the mechanism and role of selective autophagy on spermatogenesis and male fertility in mammals. Understanding the role of selective autophagy during spermatogenesis will promote the recognition of genetic regulation in male infertility, and shed light on therapies of infertile patients.
The Intergenerational Transmission of Chronic Pain from Parents to Survivors of Childhood Cancer
Authors: Patton Michaela , Stokoe Mehak , Forbes Caitlin , Nwaroh Chidera , Noel Melanie , Reynolds Kathleen , Schulte Fiona
Published: November 2020

Background: Among youth with chronic non-cancer pain, 50% have parents with chronic pain. These youth report significantly more pain interference and posttraumatic stress symptoms (PTSS), and worse health-related quality of life (HRQL) than youth whose parents do not have chronic pain. Additionally, parent chronic pain is linked to increased child anxiety and depressive symptoms. Survivors of childhood cancer (SCCs) are at risk of pain and negative psychosocial outcomes and therefore may be especially vulnerable if their parents have chronic pain. Thus, the aims of the current study were to (1) identify rates of chronic pain among parents of SCCs, (2) test group differences in psychological symptoms in parents with chronic pain versus without, and (3) test group differences in pain interference, HRQL, anxiety, depression, and PTSS in SCCs with parents with chronic pain versus without. Methods: 122 SCCs (Mean age = 15.8, SD = 4.8, 45.7% male, Mean age at diagnosis = 5.9, SD = 4.7) and their parents were recruited from across Canada to complete online questionnaires. Parents were asked if they have had pain for at least three consecutive months and completed the brief symptom inventory (BSI) as a measure of psychological symptomatology. Survivors completed the pain questionnaire, patient reported outcomes measurement information system (PROMIS)—pain interference, anxiety, and depression measures, child posttraumatic stress scale, posttraumatic stress disorder checklist for the Diagnostic and Statistical Manual of Mental Disorders, and the pediatric quality of life inventory. Results: Forty-three (39%) parents of SCCs reported having chronic pain. Of the 29 survivors who had chronic pain, 14 (48%) also had parents with chronic pain. Parents with chronic pain reported significantly higher scores on the BSI than parents without chronic pain, F(1, 116) = 5.07, p = 0.026. SCCs with parents with versus without chronic pain reported significantly higher PTSS F(1, 105) = 10.53, p = 0.002 and depressive symptoms F(1, 102) = 6.68, p = 0.011. No significant differences were found across the other variables tested. Conclusions: Findings suggest that survivors’ parents’ own pain is prevalent and is related to survivors’ increased depressive symptoms and PTSS, but not anxiety, pain interference, or HRQL. Future research should explore whether parents may benefit from psychological intervention after their child has been diagnosed with cancer and how this could improve outcomes for their child.
Combined Heat and Power Dynamic Economic Emissions Dispatch with Valve Point Effects and Incentive Based Demand Response Programs
Authors: Nwulu Nnamdi
Published: November 2020

In this paper, the Combined Heat and Power Dynamic Economic Emissions Dispatch (CHPDEED) problem formulation is considered. This problem is a complicated nonlinear mathematical formulation with multiple, conflicting objective functions. The aim of this mathematical problem is to obtain the optimal quantities of heat and power output for the committed generating units which includes power and heat only units. Heat and load demand are expected to be satisfied throughout the total dispatch interval. In this paper, Valve Point effects are considered in the fuel cost function of the units which lead to a non-convex cost function. Furthermore, an Incentive Based Demand Response Program formulation is also simultaneously considered with the CHPDEED problem further complicating the mathematical problem. The decision variables are thus the optimal power and heat output of the generating units and the optimal power curbed and monetary incentive for the participating demand response consumers. The resulting mathematical formulations are tested on four practical scenarios depicting different system operating conditions and obtained results show the efficacy of the developed mathematical optimization model. Obtained results indicate that, when the Incentive-Based Demand Response (IBDR) program’s operational hours is unrestricted with a residential load profile, the energy curtailed is highest (2680 MWh), the energy produced by the generators is lowest (38,008.53 MWh), power losses are lowest (840.5291 MW) and both fuel costs and emissions are lowest.
Strongly Convex Divergences
Authors: Melbourne James
Published: November 2020

We consider a sub-class of the f-divergences satisfying a stronger convexity property, which we refer to as strongly convex, or κ-convex divergences. We derive new and old relationships, based on convexity arguments, between popular f-divergences.
Information Network Modeling for U.S. Banking Systemic Risk
Authors: Nicola Giancarlo , Cerchiello Paola , Aste Tomaso
Published: November 2020

In this work we investigate whether information theory measures like mutual information and transfer entropy, extracted from a bank network, Granger cause financial stress indexes like LIBOR-OIS (London Interbank Offered Rate-Overnight Index Swap) spread, STLFSI (St. Louis Fed Financial Stress Index) and USD/CHF (USA Dollar/Swiss Franc) exchange rate. The information theory measures are extracted from a Gaussian Graphical Model constructed from daily stock time series of the top 74 listed US banks. The graphical model is calculated with a recently developed algorithm (LoGo) which provides very fast inference model that allows us to update the graphical model each market day. We therefore can generate daily time series of mutual information and transfer entropy for each bank of the network. The Granger causality between the bank related measures and the financial stress indexes is investigated with both standard Granger-causality and Partial Granger-causality conditioned on control measures representative of the general economy conditions.
Differential Geometric Aspects of Parametric Estimation Theory for States on Finite-Dimensional C∗-Algebras
Authors: Ciaglia Florio M. , Jost Jürgen , Schwachhöfer Lorenz
Published: November 2020

A geometrical formulation of estimation theory for finite-dimensional C∗-algebras is presented. This formulation allows to deal with the classical and quantum case in a single, unifying mathematical framework. The derivation of the Cramer–Rao and Helstrom bounds for parametric statistical models with discrete and finite outcome spaces is presented.
Analysis of Energy Transition Impact on the Low-Voltage Network Using Stochastic Load and Generation Models
Authors: Bernards Raoul , van Westering Werner , Morren Johan , Slootweg Han
Published: November 2020

The energy transition poses a challenge for the electricity distribution network design as new energy technologies cause increasing and uncertain network loads. Traditional static load models cannot cope with the stochastic nature of this new technology adoption. Furthermore, traditional nonlinear power methods have difficulty evaluating very large networks with millions of cables, because they are computationally expensive. This paper proposes a method which uses copulas for modeling the uncertainty of technology adoption and load profiles, and combines it with a fast linear load flow model. The copulas are able to accurately model the stochastic behavior of solar irradiance, load measurements, and mobility data, converting them into electricity load profiles. The linear load flow model has better scalability and stability compared to traditional load flow models. The models are applied to a case study which uses a real-world dataset consisting of a realistic technology adoption scenario and a low-voltage network with millions of cables, which considers both voltage and current problems. Results show that risk profiles can be generated for all cables in the network, resulting in a valuable map for the district network operator as to where to focus their efforts.
The Liberalization of the Internal Energy Market in the European Union: Evidence of Its Influence on Reducing Environmental Pollution
Authors: Ponce Pablo , Oliveira Cristiana , Álvarez Viviana , del Río-Rama María de la Cruz
Published: November 2020

From an empirical point of view, the liberalization of the internal energy market reduces carbon dioxide emissions, promoting a wider range of renewable energy sources. The aim of this paper is to examine the effect of the liberalization of the internal energy market on CO2 emissions, which was implemented in the European Union in 2011. The research data cover 27 countries of the European Union during the period 2004–2017 and was processed by estimating a two-way effects econometric model. The results suggest that the liberalization of the internal energy market is negatively related to CO2 emissions; the policy was effective in reducing CO2 emissions and, therefore, slowing down climate change. This result is significant at the level of the European Union, and in high-income countries since the year the policy was implemented, being different in the upper-middle-income countries, which begins to be effective after two years, which is due to the economic characteristics of the countries. The public policies to be implemented to reduce carbon dioxide emissions should focus on reducing the barriers imposed on foreign trade, which prevent efficient use of resources and providing financial and operating facilities to renewable energy providers in order to stimulate their production and consumption.
Influence of an Integral Heave Plate on the Dynamic Response of Floating Offshore Wind Turbine Under Operational and Storm Conditions
Authors: Jiang Yichen , Hu Guanqing , Zong Zhi , Zou Li , Jin Guoqing
Published: November 2020

The hydrodynamic performance of the floating foundation for offshore wind turbines is essential to its stability and energy harvesting. A semi-submersible platform with an integral heave plate is proposed in order to reduce the vertical motion responses. In this study, we compare the heave, pitch, and roll free decay motions of the new platform with a WindFloat-type platform based on Reynolds-Averaged Navier-Stokes simulations. The differences of the linear and quadratic damping properties between these platforms are revealed. Then, a FAST (Fatigue, Aerodynamics, Structures, and Turbulence) model with the consideration of fluid viscosity effects is set up to investigate the performance of the new platform under storm and operational conditions. The time-domain responses, motion spectra, and the mooring-tension statistics of these two platforms are evaluated. It is found that the integral heave plate can increase the viscous hydrodynamic damping, significantly decrease the heave and pitch motion responses, and increase the safety of the mooring cables, especially for the storm condition.
Robust Optimal Operation Strategy for a Hybrid Energy System Based on Gas-Fired Unit, Power-to-Gas Facility and Wind Power in Energy Markets
Authors: Agabalaye-Rahvar Masoud , Mansour-Saatloo Amin , Mirzaei Mohammad Amin , Mohammadi-Ivatloo Behnam , Zare Kazem , Anvari-Moghaddam Amjad
Published: November 2020

Gas-fired power units (GFUs) are the best technology in recent years due to lower natural gas prices, higher energy transformation performance, and lower CO2 emission, as compared to the conventional power units (CPUs). A permanent storage facility called power-to-gas (P2G) technology can provide adaptation of ever-increasing renewable energy sources (RESs) fluctuations in power system operations, as well as reduce dependency to buy natural gas from the gas network. High investment and utilization expenditures of state-of-the-art P2G technology do not lead to economically effective operation individually. Therefore, in the present paper, an integrated GFUs-P2G-wind power unit (WPU) system is proposed to determine its optimal bidding strategy in the day-ahead energy market. A robust optimization approach is also taken into account to accommodate the proposed bidding strategy within the electricity price uncertainty environment. This problem was studied by using a case study that included a P2G facility, GFU, and WPUs to investigate the effectiveness and capability of the proposed robust bidding strategy in the day-ahead energy market. Simulation results indicate that the obtained profit increase by introducing the integrated energy system, and the P2G facility has a significant effect on participating GFUs, which have gas-consumption limitations in order to achieve maximum profit. Moreover, as it can be said, the amount of purchased natural gas is decreased in the situations, which do not have any gas-consumption limitations. Furthermore, the proposed system’s operation in the robust environment provides more robustness against electricity price deviations, although it leads to lower profit. In addition, deploying P2G technology causes about 1% incrementation in the introduced system profit.
Operational Costs of He3 Separation Using the Superfluidity of He4
Authors: Niechciał Jakub , Banat Piotr , Kempiński Wojciech , Trybuła Zbigniew , Chorowski Maciej , Poliński Jarosław , Chołast Katarzyna , Kociemba Andrzej
Published: November 2020

Helium is the second most abundant element in the Universe after hydrogen. Considerable resources of helium-3 isotope (He3) are located mostly outside the Earth. He3 is very important for science and industry, especially for airport neutron detectors, lung tomography and helium dilution refrigerators. Besides, global warming is forcing the industry and governments to search for alternative energy sources, and He3 has the potential to be used as fuel in future nuclear fusion power plants. Unfortunately, the price of gaseous He3 has recently increased from $200 per liter to over $2750. The expected further increase in price and demands led us to present an analysis of the economic profitability for He3 separation process, which utilizes the properties of superfluid helium. This paper shows the arguments supporting the idea that extraction from natural sources is the only economically viable way of obtaining He3 isotope nowadays. The method could be relatively easily implemented into the production cycles of the low temperature natural gas purification plant.
Fog Forecast Using WRF Model Output for Solar Energy Applications
Authors: Nilo Saverio Teodosio , Cimini Domenico , Di Paola Francesco , Gallucci Donatello , Gentile Sabrina , Geraldi Edoardo , Larosa Salvatore , Ricciardelli Elisabetta , Ripepi Ermann , Viggiano Mariassunta , Romano Filomena
Published: November 2020

The occurrence of fog often causes errors in the prediction of the incident solar radiation and the power produced by photovoltaic cells. An accurate fog forecast would benefit solar energy producers and grid operators, who could take coordinated actions to reduce the impact of discontinuity, the main drawback of renewable energy sources. Considering that information on discontinuity is crucial to optimize power production estimation and plant management efficiency, in this work, a fog forecast method based on the output of the Weather Research and Forecasting (WRF) numerical model is presented. The areal extension and temporal duration of a fog event are not easy to predict. In fact, there are many physical processes and boundary conditions that cause fog development, such as the synoptic situation, air stability, wind speed, season, aerosol load, orographic influence, humidity and temperature. These make fog formation a complex and rather localized event. Thus, the results of a fog forecast method based on the output variables of the high spatial resolution WRF model strongly depend on the specific site under investigation. In this work, the thresholds are site-specifically designed so that the implemented method can be generalized to other sites after a preliminary meteorological and climatological study. The proposed method is able to predict fog in the 6–30 h interval after the model run start time; it has been evaluated against METeorological Aerodrome Report data relative to seven selected sites, obtaining an average accuracy of 0.96, probability of detection of 0.83, probability of false detection equal to 0.03 and probability of false alarm of 0.18. The output of the proposed fog forecast method can activate (or not) a specific fog postprocessing layer designed to correct the global horizontal irradiance forecasted by the WRF model in order to optimize the forecast of the irradiance reaching the photovoltaic panels surface.
Deep Learning Approach to Power Demand Forecasting in Polish Power System
Authors: Ciechulski Tomasz , Osowski Stanisław
Published: November 2020

The paper presents a new approach to predicting the 24-h electricity power demand in the Polish Power System (PPS, or Krajowy System Elektroenergetyczny—KSE) using the deep learning approach. The prediction system uses a deep multilayer autoencoder to generate diagnostic features and an ensemble of two neural networks: multilayer perceptron and radial basis function network and support vector machine in regression model, for final 24-h forecast one-week advance. The period of the data that is the subject of the experiments is 2014–2019, which has been divided into two parts: Learning data (2014–2018), and test data (2019). The numerical experiments have shown the advantage of deep learning over classical approaches of neural networks for the problem of power demand prediction.
The Genetic Basis of Obesity and Related Metabolic Diseases in Humans and Companion Animals
Authors: Wallis Natalie , Raffan Eleanor
Published: November 2020

Obesity is one of the most prevalent health conditions in humans and companion animals globally. It is associated with premature mortality, metabolic dysfunction, and multiple health conditions across species. Obesity is, therefore, of importance in the fields of medicine and veterinary medicine. The regulation of adiposity is a homeostatic process vulnerable to disruption by a multitude of genetic and environmental factors. It is well established that the heritability of obesity is high in humans and laboratory animals, with ample evidence that the same is true in companion animals. In this review, we provide an overview of how genes link to obesity in humans, drawing on a wealth of information from laboratory animal models, and summarise the mechanisms by which obesity causes related disease. Throughout, we focus on how large-scale human studies and niche investigations of rare mutations in severely affected patients have improved our understanding of obesity biology and can inform our ability to interpret results of animal studies. For dogs, cats, and horses, we compare the similarities in obesity pathophysiology to humans and review the genetic studies that have been previously reported in those species. Finally, we discuss how veterinary genetics may learn from humans about studying precise, nuanced phenotypes and implementing large-scale studies, but also how veterinary studies may be able to look past clinical findings to mechanistic ones and demonstrate translational benefits to human research.
Transcriptome-Wide Identification of WRKY Transcription Factors and Their Expression Profiles under Different Types of Biological and Abiotic Stress in Pinus massoniana Lamb
Authors: Yao Sheng , Wu Fan , Hao Qingqing , Ji Kongshu
Published: November 2020

Pinus massoniana Lamb, an economically important conifer tree, is widely distributed in China. WRKY transcription factors (TFs) play important roles in plant growth and development, biological and abiotic stress. Nevertheless, there is little information about the WRKY genes in P. massoniana. By searching for conserved WRKY motifs in transcriptomic RNA sequencing data for P. massoniana, 31 sequences were identified as WRKY TFs. Then, phylogenetic and conserved motif analyses of the WRKY family in P. massoniana, Pinus taeda and Arabidopsis thaliana were used to classify WRKY genes. The expression patterns of six PmWRKY genes from different groups were determined using real-time quantitative PCR for 2-year-old P. massoniana seedings grown in their natural environment and challenged by phytohormones (salicylic acid, methyl jasmonate, or ethephon), abiotic stress (H2O2) and mechanical damage stress. As a result, the 31 PmWRKY genes identified were divided into three major groups and several subgroups based on structural and phylogenetic features. PmWRKY genes are regulated in response to abiotic stress and phytohormone treatment and may participate in signaling to improve plant stress resistance. Some PmWRKY genes behaved as predicted based on their homology with A. thaliana WRKY genes, but others showed divergent behavior. This systematic analysis lays the foundation for further identification of WRKY gene functions to aid further exploration of the functions and regulatory mechanisms of PmWRKY genes in biological and abiotic stress in P. massoniana.
GWAS Based on RNA-Seq SNPs and High-Throughput Phenotyping Combined with Climatic Data Highlights the Reservoir of Valuable Genetic Diversity in Regional Tomato Landraces
Authors: Rodriguez Monica , Scintu Alessandro , Posadinu Chiara M. , Xu Yimin , Nguyen Cuong V. , Sun Honghe , Bitocchi Elena , Bellucci Elisa , Papa Roberto , Fei Zhangjun , Giovannoni James J. , Rau Domenico , Attene Giovanna
Published: November 2020

Tomato (Solanum lycopersicum L.) is a widely used model plant species for dissecting out the genomic bases of complex traits to thus provide an optimal platform for modern “-omics” studies and genome-guided breeding. Genome-wide association studies (GWAS) have become a preferred approach for screening large diverse populations and many traits. Here, we present GWAS analysis of a collection of 115 landraces and 11 vintage and modern cultivars. A total of 26 conventional descriptors, 40 traits obtained by digital phenotyping, the fruit content of six carotenoids recorded at the early ripening (breaker) and red-ripe stages and 21 climate-related variables were analyzed in the context of genetic diversity monitored in the 126 accessions. The data obtained from thorough phenotyping and the SNP diversity revealed by sequencing of ripe fruit transcripts of 120 of the tomato accessions were jointly analyzed to determine which genomic regions are implicated in the expressed phenotypic variation. This study reveals that the use of fruit RNA-Seq SNP diversity is effective not only for identification of genomic regions that underlie variation in fruit traits, but also of variation related to additional plant traits and adaptive responses to climate variation. These results allowed validation of our approach because different marker-trait associations mapped on chromosomal regions where other candidate genes for the same traits were previously reported. In addition, previously uncharacterized chromosomal regions were targeted as potentially involved in the expression of variable phenotypes, thus demonstrating that our tomato collection is a precious reservoir of diversity and an excellent tool for gene discovery.