bluuebunny/crossref_metadata_2025 huggingface dataset:
Pediatric Paroxysmal Exercise-Induced Neurological Symptoms: Clinical Spectrum and Diagnostic Algorithm
Authors: Danti Federica Rachele , Invernizzi Federica , Moroni Isabella , Garavaglia Barbara , Nardocci Nardo , Zorzi Giovanna
Published: June 2021

Paroxysmal exercise-induced neurological symptoms (PENS) encompass a wide spectrum of clinical phenomena commonly presenting during childhood and characteristically elicited by physical exercise. Interestingly, few shared pathogenetic mechanisms have been identified beyond the well-known entity of paroxysmal exercise-induced dyskinesia, PENS could be part of more complex phenotypes including neuromuscular, neurodegenerative, and neurometabolic disease, epilepsies, and psychogenetic disorders. The wide and partially overlapping phenotypes and the genetic heterogeneity make the differential diagnosis frequently difficult and delayed; however, since some of these disorders may be treatable, a prompt diagnosis is mandatory. Therefore, an accurate characterization of these symptoms is pivotal for orienting more targeted biochemical, radiological, neurophysiological, and genetic investigations and finally treatment. In this article, we review the clinical, genetic, pathophysiologic, and therapeutic landscape of paroxysmal exercise induced neurological symptoms, focusing on phenomenology and differential diagnosis.
Radiation Resistance: A Matter of Transcription Factors
Authors: Galeaz Chiara , Totis Cristina , Bisio Alessandra
Published: June 2021

Currently, radiation therapy is one of the standard therapies for cancer treatment. Since the first applications, the field of radiotherapy has constantly improved, both in imaging technologies and from a dose-painting point of view. Despite this, the mechanisms of resistance are still a great problem to overcome. Therefore, a more detailed understanding of these molecular mechanisms will allow researchers to develop new therapeutic strategies to eradicate cancer effectively. This review focuses on different transcription factors activated in response to radiotherapy and, unfortunately, involved in cancer cells’ survival. In particular, ionizing radiations trigger the activation of the immune modulators STAT3 and NF-κB, which contribute to the development of radiation resistance through the up-regulation of anti-apoptotic genes, the promotion of proliferation, the alteration of the cell cycle, and the induction of genes responsible for the Epithelial to Mesenchymal Transition (EMT). Moreover, the ROS-dependent damaging effects of radiation therapy are hampered by the induction of antioxidant enzymes by NF-κB, NRF2, and HIF-1. This protective process results in a reduced effectiveness of the treatment, whose mechanism of action relies mainly on the generation of free oxygen radicals. Furthermore, the previously mentioned transcription factors are also involved in the maintenance of stemness in Cancer Stem Cells (CSCs), a subset of tumor cells that are intrinsically resistant to anti-cancer therapies. Therefore, combining standard treatments with new therapeutic strategies targeted against these transcription factors may be a promising opportunity to avoid resistance and thus tumor relapse.
Therapy-Induced Tumor Cell Death: Friend or Foe of Immunotherapy?
Authors: van Schaik Thijs A. , Chen Kok-Siong , Shah Khalid
Published: June 2021

Combinatory treatments using surgery, radiotherapy and/or chemotherapy together with immunotherapy have shown encouraging results for specific subsets of tumors, but a significant proportion of tumors remains unsusceptible. Some of these inconsistencies are thought to be the consequence of an immunosuppressive tumor microenvironment (TME) caused by therapy-induced tumor cell death (TCD). An increased understanding of the molecular mechanisms governing TCD has provided valuable insights in specific signaling cascades activated by treatment and the subsequent effects on the TME. Depending on the treatment variables of conventional chemo-, radio- and immunotherapy and the genetic composition of the tumor cells, particular cell death pathways are activated. Consequently, TCD can either have tolerogenic or immunogenic effects on the local environment and thereby affect the post-treatment anti-tumor response of immune cells. Thus, identification of these events can provide new rationales to increase the efficacy of conventional therapies combined with immunotherapies. In this review, we sought to provide an overview of the molecular mechanisms initiated by conventional therapies and the impact of treatment-induced TCD on the TME. We also provide some perspectives on how we can circumvent tolerogenic effects by adequate treatment selection and manipulation of key signaling cascades.
Phosphatase and Tensin Homolog in Non-neoplastic Digestive Disease: More Than Just Tumor Suppressor
Authors: He Tianyu , Zhang Xiaoyun , Hao Jianyu , Ding Shigang
Published: June 2021

The Phosphatase and tensin homolog (PTEN) gene is one of the most important tumor suppressor genes, which acts through its unique protein phosphatase and lipid phosphatase activity. PTEN protein is widely distributed and exhibits complex biological functions and regulatory modes. It is involved in the regulation of cell morphology, proliferation, differentiation, adhesion, and migration through a variety of signaling pathways. The role of PTEN in malignant tumors of the digestive system is well documented. Recent studies have indicated that PTEN may be closely related to many other benign processes in digestive organs. Emerging evidence suggests that PTEN is a potential therapeutic target in the context of several non-neoplastic diseases of the digestive tract. The recent discovery of PTEN isoforms is expected to help unravel more biological effects of PTEN in non-neoplastic digestive diseases.
Sorghum Pan-Genome Explores the Functional Utility for Genomic-Assisted Breeding to Accelerate the Genetic Gain
Authors: Ruperao Pradeep , Thirunavukkarasu Nepolean , Gandham Prasad , Selvanayagam Sivasubramani , Govindaraj Mahalingam , Nebie Baloua , Manyasa Eric , Gupta Rajeev , Das Roma Rani , Odeny Damaris A. , Gandhi Harish , Edwards David , Deshpande Santosh P. , Rathore Abhishek
Published: June 2021

Sorghum (Sorghum bicolor L.) is a staple food crops in the arid and rainfed production ecologies. Sorghum plays a critical role in resilient farming and is projected as a smart crop to overcome the food and nutritional insecurity in the developing world. The development and characterisation of the sorghum pan-genome will provide insight into genome diversity and functionality, supporting sorghum improvement. We built a sorghum pan-genome using reference genomes as well as 354 genetically diverse sorghum accessions belonging to different races. We explored the structural and functional characteristics of the pan-genome and explain its utility in supporting genetic gain. The newly-developed pan-genome has a total of 35,719 genes, a core genome of 16,821 genes and an average of 32,795 genes in each cultivar. The variable genes are enriched with environment responsive genes and classify the sorghum accessions according to their race. We show that 53% of genes display presence-absence variation, and some of these variable genes are predicted to be functionally associated with drought adaptation traits. Using more than two million SNPs from the pan-genome, association analysis identified 398 SNPs significantly associated with important agronomic traits, of which, 92 were in genes. Drought gene expression analysis identified 1,788 genes that are functionally linked to different conditions, of which 79 were absent from the reference genome assembly. This study provides comprehensive genomic diversity resources in sorghum which can be used in genome assisted crop improvement.
Improving Autonomous Robotic Navigation Using Imitation Learning
Authors: Cèsar-Tondreau Brian , Warnell Garrett , Stump Ethan , Kochersberger Kevin , Waytowich Nicholas R.
Published: June 2021

Autonomous navigation to a specified waypoint is traditionally accomplished with a layered stack of global path planning and local motion planning modules that generate feasible and obstacle-free trajectories. While these modules can be modified to meet task-specific constraints and user preferences, current modification procedures require substantial effort on the part of an expert roboticist with a great deal of technical training. In this paper, we simplify this process by inserting a Machine Learning module between the global path planning and local motion planning modules of an off-the shelf navigation stack. This model can be trained with human demonstrations of the preferred navigation behavior, using a training procedure based on Behavioral Cloning, allowing for an intuitive modification of the navigation policy by non-technical users to suit task-specific constraints. We find that our approach can successfully adapt a robot’s navigation behavior to become more like that of a demonstrator. Moreover, for a fixed amount of demonstration data, we find that the proposed technique compares favorably to recent baselines with respect to both navigation success rate and trajectory similarity to the demonstrator.
Designing Function-Specific Plant Systems for Sustainable Urban Development
Authors: French Katherine E.
Published: June 2021

Increasingly, architects are embracing “biomorphic urbanism,” a design ideology that takes inspiration from nature to develop more sustainable cities that reduce the environmental impact of urban life. At the moment, plants are incorporated into biomorphic urban designs for conservation or aesthetic reasons. Here, I argue the role of plants in building more sustainable cities can be augmented by integrating plant sciences, ecology, and urban design. I propose that we can develop synthetic Function-Specific Plant Systems (FSPSs) which harness the genetic and metabolic diversity of plants to perform specific services that benefit society and the environment as a whole. FSPSs can contribute to three broad categories of urban life: Urban Landscape and Infrastructure; Biodiversity and the Environment; and Human Health. Across the three categories, FSPSs can be designed to provide nine key services: flood control, soil stabilization, fire control, climate control, water treatment, habitat for endangered flora and fauna, pest control, air purification, and modulation of human immune systems. The plants included in each FSPS are based on several considerations, including (1) functional traits, (2) biogeography, and (3) cultural concerns. In the future, synthetic biology could improve, expand and diversify these services. This approach harnesses plant biodiversity to transform urban spaces while meeting key UN Sustainable Development Goals.
Humanising the Energy Transition: Towards a National Policy on Energy Poverty in the Netherlands
Authors: Feenstra Mariëlle , Middlemiss Lucie , Hesselman Marlies , Straver Koen , Tirado Herrero Sergio
Published: June 2021

Energy poverty is emerging as a national agenda in the Netherlands. Local authority leadership and action on this agenda, and European Union reporting requirements around the energy transition have aligned to create an opportunity to establish a national agenda on this issue. Early action on energy poverty by local authorities stemmed from their recognition of the value of addressing environmental, health, social welfare and poverty goals through measures to address the problem. In contrast, the experiences of vulnerable energy consumers have limited recognition in national policy. Meanwhile EU requirements for climate reporting include a specification for measuring and monitoring energy poverty. This growing momentum has resulted in an emerging interest in energy poverty as a means to achieve a just transition at a national level, as reflected in the Dutch National Climate and Energy Plan. In this paper, we profile the case of the Netherlands, and outline the opportunity we see for the development of an energy poverty agenda in national energy transition policy, as part of a multi-level energy governance effort. We report on a national stakeholder workshop that we led, linking the lived experience of energy poverty in the Netherlands with policy solutions. Following the clear call for a national policy in this workshop, we also outline a strategy for engagement with energy poverty in the Netherlands, published recently in a white paper on this topic.
The Impact of Age Stereotypes and Age Norms on Employees’ Retirement Choices: A Neglected Aspect of Research on Extended Working Lives
Authors: Vickerstaff Sarah , Van der Horst Mariska
Published: June 2021

This article examines how older workers employ internalized age norms and perceptions when thinking about extending their working lives or retirement timing. It draws on semi-structured interviews with employees (n = 104) and line managers, human resource managers and occupational health specialists (n = 52) from four organisations in the United Kingdom. Previous research has demonstrated discrimination against older workers but this is a limiting view of the impact that ageism may have in the work setting. Individuals are likely to internalize age norms as older people have lived in social contexts in which negative images of what it means to be “old” are prevalent. These age perceptions are frequently normalized (taken for granted) in organisations and condition how people are managed and crucially how they manage themselves. How older workers and managers think and talk about age is another dynamic feature of decision making about retirement with implications for extending working lives. Amongst our respondents it was widely assumed that older age would come with worse health—what is more generally called the decline narrative - which served both as a motivation for individuals to leave employment to maximize enjoyment of their remaining years in good health as well as a motivation for some other individuals to stay employed in order to prevent health problems that might occur from an inactive retirement. Age norms also told some employees they were now “too old” for their job, to change job, for training and/or promotion and that they should leave that “to the younger ones”—what we call a sense of intergenerational disentitlement. The implications of these processes for the extending working lives agenda are discussed.
A PID Parameter Tuning Method Based on the Improved QUATRE Algorithm
Authors: Zhao Zhuo-Qiang , Liu Shi-Jian , Pan Jeng-Shyang
Published: June 2021

The PID (proportional–integral–derivative) controller is the most widely used control method in modern engineering control because it has the characteristics of a simple algorithm structure and easy implementation. The traditional PID controller, in the face of complex control objects, has been unable to meet the expected requirements. The emergence of the intelligent algorithm makes intelligent control widely usable. The Quasi-Affine Transformation Evolutionary (QUATRE) algorithm is a new evolutionary algorithm. Compared with other intelligent algorithms, the QUATRE algorithm has a strong global search ability. To improve the accuracy of the algorithm, the adaptive mechanism of online adjusting control parameters was introduced and the linear population reduction strategy was adopted to improve the performance of the algorithm. The standard QUATRE algorithm, particle swarm optimization algorithm and improved QUATRE algorithm were tested by the test function. The experimental results verify the advantages of the improved QUATRE algorithm. The improved QUATRE algorithm was combined with PID parameters, and the simulation results were compared with the PID parameter tuning method based on the particle swarm optimization algorithm and standard QUATRE algorithm. From the experimental results, the control effect of the improved QUATRE algorithm is more effective.
Immunological Aspects of X-Linked Chronic Granulomatous Disease Female Carriers
Authors: Chiriaco Maria , Salfa Irene , Ursu Giorgiana Madalina , Cifaldi Cristina , Di Cesare Silvia , Rossi Paolo , Di Matteo Gigliola , Finocchi Andrea
Published: June 2021

X-linked Granulomatous Disease (XL-CGD) carriers were previously thought to be clinically healthy because random X-chromosome inactivation (XCI) allows approximately half of their phagocytes/monocytes to express functional gp91phox protein. This supports the NADPH oxidase activity necessary for the killing of engulfed pathogens. Some XL-CGD carriers suffer from inflammatory and autoimmune manifestations as well as infections, although the skewed-XCI of a mutated allele is reported to be exclusively determinant for infection susceptibility. Indeed, immune dysregulation could be determined by dysfunctional non-phagocytic leukocytes rather than the percentage of functioning neutrophils. Here we investigated in a cohort of 12 X-CGD female carriers at a particular time of their life the gp91phox protein expression/function and how this affects immune cell function. We showed that 50% of carriers have an age-independent skewed-XCI and 65% of them have a misrepresented expression of the wild-type gene. The majority of carriers manifested immune dysregulation and GI manifestations regardless of age and XCI. Immunological investigations revealed an increase in CD19+ B cells, CD56bright-NK cell percentage, a slightly altered CD107a upregulation on CD4+ T cells, and reduced INFγ-production by CD4+ and CD8+ cells. Notably, we demonstrated that the residual level of ROS robustly correlates with INFγ-expressing T cells, suggesting a role in promoting immune dysregulation in carriers.
Determination of the Distribution of Relaxation Times by Means of Pulse Evaluation for Offline and Online Diagnosis of Lithium-Ion Batteries
Authors: Goldammer Erik , Kowal Julia
Published: June 2021

The distribution of relaxation times (DRT) analysis of impedance spectra is a proven method to determine the number of occurring polarization processes in lithium-ion batteries (LIBs), their polarization contributions and characteristic time constants. Direct measurement of a spectrum by means of electrochemical impedance spectroscopy (EIS), however, suffers from a high expenditure of time for low-frequency impedances and a lack of general availability in most online applications. In this study, a method is presented to derive the DRT by evaluating the relaxation voltage after a current pulse. The method was experimentally validated using both EIS and the proposed pulse evaluation to determine the DRT of automotive pouch-cells and an aging study was carried out. The DRT derived from time domain data provided improved resolution of processes with large time constants and therefore enabled changes in low-frequency impedance and the correlated degradation mechanisms to be identified. One of the polarization contributions identified could be determined as an indicator for the potential risk of plating. The novel, general approach for batteries was tested with a sampling rate of 10 Hz and only requires relaxation periods. Therefore, the method is applicable in battery management systems and contributes to improving the reliability and safety of LIBs.
Molecular Tumor Subtypes of HPV-Positive Head and Neck Cancers: Biological Characteristics and Implications for Clinical Outcomes
Authors: Qin Tingting , Li Shiting , Henry Leanne E. , Liu Siyu , Sartor Maureen A.
Published: June 2021

Until recently, research on the molecular signatures of Human papillomavirus (HPV)-associated head and neck cancers mainly focused on their differences with respect to HPV-negative head and neck squamous cell carcinomas (HNSCCs). However, given the continuing high incidence level of HPV-related HNSCC, the time is ripe to characterize the heterogeneity that exists within these cancers. Here, we review research thus far on HPV-positive HNSCC molecular subtypes, and their relationship with clinical characteristics and HPV integration into the host genome. Different omics data including host transcriptomics and epigenomics, as well as HPV characteristics, can provide complementary viewpoints. Keratinization, mesenchymal differentiation, immune signatures, stromal cells and oxidoreductive processes all play important roles.
Robust Superhydrophobic and Repellent Coatings Based on Micro/Nano SiO2 and Fluorinated Epoxy
Authors: Huang Xiaoye , Yu Ruobing
Published: June 2021

Superhydrophobic surfaces possess low mechanical strength, and can be easily contaminated by fluids with low surface tension, such as oil; this hinders their practical applications. In this study, fluorinated epoxy was prepared through the thiol-ene click reaction at first. The superhydrophobic surface with high oil-repellency was prepared by the addition of unmodified nano-SiO2 and micron-SiO2 to the fluorinated epoxy. The effect of the ratio of micro- and nano-silica particles on the morphology and wettability of the coating was investigated. It was shown that a re-entrant structure appears and FEP-S coating has good liquid repellency when the amounts of nano-SiO2 and micro-SiO2 are equal. The contact angles of the FEP-S coating (coating with the best liquid repellent performance) for water, glycerol, ethylene glycol, and diiodomethane were 158.6° ± 1.1°, 152.4° ± 0.9°, 153.4° ± 1.3°, and 140.7° ± 0.9°, respectively. In addition, the superhydrophobic coatings possess excellent mechanical and chemical durability, excellent performance in self-cleaning, corrosion resistance, and anti-icing properties. The preparation method of superhydrophobic coating is relatively simple; therefore, it has a wide range of applications and can also be applied to various substrates.
Significant Improvement of Strength in Wrought 945A Ni-Based Superalloy by Aging Treatment
Authors: Liu Haiding , Wang Dongzhe , Zhou Linping , She Jia , Wu Wei
Published: June 2021

Ni-based superalloys have attracted much attention due to their good resistance to high-temperature and -pressure environments. Compared with the traditional 718 Ni-based superalloy, 945A Ni-based superalloy with a lower Ni content showed better performance in terms of precipitated hardening and corrosion resistance. In this study, the aging behavior and the evolution of mechanical properties of the wrought 945A Ni-based superalloy were investigated. Microstructures were analyzed by scanning electron microscopy (SEM), bright field transmission electron microscopy (TEM), high-resolution TEM and high-angle annular dark field scanning TEM. Mechanical properties were measured by tensile and compressive tests. The results illustrated that the compressive yield stress was significantly improved by increasing aging time from 229 to 809 MPa. The increase was greater than 220%. This improvement was mainly attributed to the precipitates of the  γ′ phase and carbides during the aging treatment. The residual dislocations generated by the plastic processes stimulated the formation of these precipitates. The precipitation behavior and the strengthening mechanism are discussed in detail.
Misalignment Fault Prediction of Wind Turbines Based on Improved Artificial Fish Swarm Algorithm
Authors: Hua Zhe , Xiao Yancai , Cao Jiadong
Published: June 2021

A misalignment fault is a kind of potential fault in double-fed wind turbines. The reasonable and effective fault prediction models are used to predict its development trend before serious faults occur, which can take measures to repair in advance and reduce human and material losses. In this paper, the Least Squares Support Vector Machine optimized by the Improved Artificial Fish Swarm Algorithm is used to predict the misalignment index of the experiment platform. The mixed features of time domain, frequency domain, and time-frequency domain indexes of vibration or stator current signals are the inputs of the Least Squares Support Vector Machine. The kurtosis of the same signals is the output of the model, and the 3σ principle of the normal distribution is adopted to set the warning line of misalignment fault. Compared with other optimization algorithms, the experimental results show that the proposed prediction model can predict the development trend of the misalignment index with the least prediction error.
Bayesian Reasoning with Trained Neural Networks
Authors: Knollmüller Jakob , Enßlin Torsten A.
Published: June 2021

We showed how to use trained neural networks to perform Bayesian reasoning in order to solve tasks outside their initial scope. Deep generative models provide prior knowledge, and classification/regression networks impose constraints. The tasks at hand were formulated as Bayesian inference problems, which we approximately solved through variational or sampling techniques. The approach built on top of already trained networks, and the addressable questions grew super-exponentially with the number of available networks. In its simplest form, the approach yielded conditional generative models. However, multiple simultaneous constraints constitute elaborate questions. We compared the approach to specifically trained generators, showed how to solve riddles, and demonstrated its compatibility with state-of-the-art architectures.
Medium Entropy Reduction and Instability in Stochastic Systems with Distributed Delay
Authors: Loos Sarah A. M. , Hermann Simon , Klapp Sabine H. L.
Published: June 2021

Many natural and artificial systems are subject to some sort of delay, which can be in the form of a single discrete delay or distributed over a range of times. Here, we discuss the impact of this distribution on (thermo-)dynamical properties of time-delayed stochastic systems. To this end, we study a simple classical model with white and colored noise, and focus on the class of Gamma-distributed delays which includes a variety of distinct delay distributions typical for feedback experiments and biological systems. A physical application is a colloid subject to time-delayed feedback control, which is, in principle, experimentally realizable by co-moving optical traps. We uncover several unexpected phenomena in regard to the system’s linear stability and its thermodynamic properties. First, increasing the mean delay time can destabilize or stabilize the process, depending on the distribution of the delay. Second, for all considered distributions, the heat dissipated by the controlled system (e.g., the colloidal particle) can become negative, which implies that the delay force extracts energy and entropy of the bath. As we show here, this refrigerating effect is particularly pronounced for exponential delay. For a specific non-reciprocal realization of a control device, we find that the entropic costs, measured by the total entropy production of the system plus controller, are the lowest for exponential delay. The exponential delay further yields the largest stable parameter regions. In this sense, exponential delay represents the most effective and robust type of delayed feedback.
Gearbox Failure Diagnosis Using a Multisensor Data-Fusion Machine-Learning-Based Approach
Authors: Habbouche Houssem , Benkedjouh Tarak , Amirat Yassine , Benbouzid Mohamed
Published: June 2021

Failure detection and diagnosis are of crucial importance for the reliable and safe operation of industrial equipment and systems, while gearbox failures are one of the main factors leading to long-term downtime. Condition-based maintenance addresses this issue using several expert systems for early failure diagnosis to avoid unplanned shutdowns. In this context, this paper provides a comparative study of two machine-learning-based approaches for gearbox failure diagnosis. The first uses linear predictive coefficients for signal processing and long short-term memory for learning, while the second is based on mel-frequency cepstral coefficients for signal processing, a convolutional neural network for feature extraction, and long short-term memory for classification. This comparative study proposes an improved predictive method using the early fusion technique of multisource sensing data. Using an experimental dataset, the proposals were tested, and their effectiveness was evaluated considering predictions based on statistical metrics.
Assessment of Cardiorespiratory Interactions during Apneic Events in Sleep via Fuzzy Kernel Measures of Information Dynamics
Authors: Lazic Ivan , Pernice Riccardo , Loncar-Turukalo Tatjana , Mijatovic Gorana , Faes Luca
Published: June 2021

Apnea and other breathing-related disorders have been linked to the development of hypertension or impairments of the cardiovascular, cognitive or metabolic systems. The combined assessment of multiple physiological signals acquired during sleep is of fundamental importance for providing additional insights about breathing disorder events and the associated impairments. In this work, we apply information-theoretic measures to describe the joint dynamics of cardiorespiratory physiological processes in a large group of patients reporting repeated episodes of hypopneas, apneas (central, obstructive, mixed) and respiratory effort related arousals (RERAs). We analyze the heart period as the target process and the airflow amplitude as the driver, computing the predictive information, the information storage, the information transfer, the internal information and the cross information, using a fuzzy kernel entropy estimator. The analyses were performed comparing the information measures among segments during, immediately before and after the respiratory event and with control segments. Results highlight a general tendency to decrease of predictive information and information storage of heart period, as well as of cross information and information transfer from respiration to heart period, during the breathing disordered events. The information-theoretic measures also vary according to the breathing disorder, and significant changes of information transfer can be detected during RERAs, suggesting that the latter could represent a risk factor for developing cardiovascular diseases. These findings reflect the impact of different sleep breathing disorders on respiratory sinus arrhythmia, suggesting overall higher complexity of the cardiac dynamics and weaker cardiorespiratory interactions which may have physiological and clinical relevance.
Foveal Pit Morphology Characterization: A Quantitative Analysis of the Key Methodological Steps
Authors: Romero-Bascones David , Barrenechea Maitane , Murueta-Goyena Ane , Galdós Marta , Gómez-Esteban Juan Carlos , Gabilondo Iñigo , Ayala Unai
Published: June 2021

Disentangling the cellular anatomy that gives rise to human visual perception is one of the main challenges of ophthalmology. Of particular interest is the foveal pit, a concave depression located at the center of the retina that captures light from the gaze center. In recent years, there has been a growing interest in studying the morphology of the foveal pit by extracting geometrical features from optical coherence tomography (OCT) images. Despite this, research has devoted little attention to comparing existing approaches for two key methodological steps: the location of the foveal center and the mathematical modelling of the foveal pit. Building upon a dataset of 185 healthy subjects imaged twice, in the present paper the image alignment accuracy of four different foveal center location methods is studied in the first place. Secondly, state-of-the-art foveal pit mathematical models are compared in terms of fitting error, repeatability, and bias. The results indicate the importance of using a robust foveal center location method to align images. Moreover, we show that foveal pit models can improve the agreement between different acquisition protocols. Nevertheless, they can also introduce important biases in the parameter estimates that should be considered.
Statistical Inference for Ergodic Algorithmic Model (EAM), Applied to Hydrophobic Hydration Processes
Authors: Fisicaro Emilia , Compari Carlotta , Braibanti Antonio
Published: June 2021

The thermodynamic properties of hydrophobic hydration processes can be represented in probability space by a Dual-Structure Partition Function {DS-PF} = {M-PF} · {T-PF}, which is the product of a Motive Partition Function {M-PF} multiplied by a Thermal Partition Function {T-PF}. By development of {DS-PF}, parabolic binding potential functions α) RlnKdual = (−ΔG°dual/T) ={f(1/T)*g(T)} and β) RTlnKdual = (−ΔG°dual) = {f(T)*g(lnT)} have been calculated. The resulting binding functions are “convoluted” functions dependent on the reciprocal interactions between the primary function f(1/T) or f(T) with the secondary function g(T) or g(lnT), respectively. The binding potential functions carry the essential thermodynamic information elements of each system. The analysis of the binding potential functions experimentally determined at different temperatures by means of the Thermal Equivalent Dilution (TED) principle has made possible the evaluation, for each compound, of the pseudo-stoichiometric coefficient ±ξw, from the curvature of the binding potential functions. The positive value indicates convex binding functions (Class A), whereas the negative value indicates concave binding function (Class B). All the information elements concern sets of compounds that are very different from one set to another, in molecular dimension, in chemical function, and in aggregation state. Notwithstanding the differences between, surprising equal unitary values of niche (cavity) formation in Class A <Δhfor>A = −22.7 ± 0.7 kJ·mol−1·ξw−1 sets with standard deviation σ = ±3.1% and <Δsfor>A = −445 ± 3J·K−1·mol−1·ξw−1J·K−1·mol−1·ξw−1 with standard deviation σ = ±0.7%. Other surprising similarities have been found, demonstrating that all the data analyzed belong to the same normal statistical population. The Ergodic Algorithmic Model (EAM) has been applied to the analysis of important classes of reactions, such as thermal and chemical denaturation, denaturation of proteins, iceberg formation or reduction, hydrophobic bonding, and null thermal free energy. The statistical analysis of errors has shown that EAM has a general validity, well beyond the limits of our experiments. Specifically, the properties of hydrophobic hydration processes as biphasic systems generating convoluted binding potential functions, with water as the implicit solvent, hold for all biochemical and biological solutions, on the ground that they also are necessarily diluted solutions, statistically validated.
Quantum Foundations of Classical Reversible Computing
Authors: Frank Michael P. , Shukla Karpur
Published: June 2021

The reversible computation paradigm aims to provide a new foundation for general classical digital computing that is capable of circumventing the thermodynamic limits to the energy efficiency of the conventional, non-reversible digital paradigm. However, to date, the essential rationale for, and analysis of, classical reversible computing (RC) has not yet been expressed in terms that leverage the modern formal methods of non-equilibrium quantum thermodynamics (NEQT). In this paper, we begin developing an NEQT-based foundation for the physics of reversible computing. We use the framework of Gorini-Kossakowski-Sudarshan-Lindblad dynamics (a.k.a. Lindbladians) with multiple asymptotic states, incorporating recent results from resource theory, full counting statistics and stochastic thermodynamics. Important conclusions include that, as expected: (1) Landauer’s Principle indeed sets a strict lower bound on entropy generation in traditional non-reversible architectures for deterministic computing machines when we account for the loss of correlations; and (2) implementations of the alternative reversible computation paradigm can potentially avoid such losses, and thereby circumvent the Landauer limit, potentially allowing the efficiency of future digital computing technologies to continue improving indefinitely. We also outline a research plan for identifying the fundamental minimum energy dissipation of reversible computing machines as a function of speed.
Progress in the Use of Biobutanol Blends in Diesel Engines
Authors: Fernández-Rodríguez David , Lapuerta Magín , German Lizzie
Published: June 2021

Nowadays, the transport sector is trying to face climate change and to contribute to a sustainable world by introducing modern after-treatment systems or by using biofuels. In sectors such as road freight transportation, agricultural or cogeneration in which the electrification is not considered feasible with the current infrastructure, renewable options for diesel engines such as alcohols produced from waste or lignocellulosic materials with advanced production techniques show a significant potential to reduce the life-cycle greenhouse emissions with respect to diesel fuel. This study concludes that lignocellulosic biobutanol can achieve 60% lower greenhouse gas emissions than diesel fuel. Butanol-diesel blends, with up to 40% butanol content, could be successfully used in a diesel engine calibrated for 100% diesel fuel without any additional engine modification nor electronic control unit recalibration at a warm ambient temperature. When n-butanol is introduced, particulate matter emissions are sharply reduced for butanol contents up to 16% (by volume), whereas NOX emissions are not negatively affected. Butanol-diesel blends could be introduced without startability problems up to 13% (by volume) butanol content at a cold ambient temperature. Therefore, biobutanol can be considered as an interesting option to be blended with diesel fuel, contributing to the decarbonization of these sectors.
BASS Model Analysis in “Crossing the Chasm” in E-Cars Innovation Diffusion Scenarios
Authors: Brdulak Anna , Chaberek Grażyna , Jagodziński Jacek
Published: June 2021

In the face of contemporary ecological problems, including the influence of transport and mobility on the greenhouse effect, policy makers see a solution in the technology of electric vehicles (EVs). This innovation has appeared in the automotive market around the world. In this article, Rogers’ innovation diffusion concept was used to determine if and when EVs could replace combustion engine vehicles. The aim of the article is to analyze the current situation of innovative electric vehicle (EV) technology on the European Union (EU) market and the potential and possible directions of its market diffusion. As a result of the analysis of the current situation of the EU automotive markets, three groups of countries with different market conditions regarding the development of EV technology were distinguished. The classification was carried out using the K-means clustering algorithm, based on the current level of innovation and the level of development of the LPG-(Liquefied Petroleum Gas) powered car market. Then, a group of countries with the greatest advancement in EV technology was selected for further research and market diffusion scenarios were created for this innovation using the Bass model, assuming the target market size of 70–100% of all passenger cars.
Thermal Analysis of Energy Storage Capacity According to Thickness of Nickel/Chromium Alloy Layer
Authors: Kim Yonghyeon , Choi Hyeokjoo , Kwon Seokhun , Lee Seokwon , Kang Hyunil , Choi Wonseok
Published: June 2021

This paper examines a microconstruction consisting of nickel (Ni)/chromium (Cr) alloy thin-film. The total length of the microconstruction was 28 mm, the width was 0.2 mm, and the height was designed to be 1 μm. A thin-film of Ni/Cr alloy was co-sputtered on a silicon dioxide wafer patterned with photoresist via a RF magnetron sputtering system. The RF power ratios applied to the 4 inch target of Ni and Cr were 300 W:100 W (3:1), 300 W:150 W (2:1), and 150 W:150 W (1:1). The electrical resistance of the manufactured microconstruction was calculated and measured through Hall measurements. The temperature generated by applying 1–10 V to the microconstruction electrode was observed by using an infrared camera, and was summarized using a linear equation according to the power applied to each sample.
Technology Pathways and Economic Analysis for Transforming High Temperature to Low Temperature District Heating Systems
Authors: Durán Pedro , Torio Herena , Schönfeldt Patrik , Klement Peter , Hanke Benedikt , von Maydell Karsten , Agert Carsten
Published: June 2021

There are 1454 district heating systems in Germany. Most of them are fossil based and with high temperature levels, which is neither efficient nor sustainable and needs to be changed for reaching the 2050 climate goals. In this paper, we present a case study for transforming a high to low temperature district heating system which is more suitable for renewable energy supply. With the Carnot Toolbox, a dynamic model of a potential district heating system is simulated and then transformed to a low temperature supply. A sensitivity analysis is carried out to see the system performance in case space constrains restrict the transformation. Finally, an economic comparison is performed. Results show that it is technically possible to perform the transformation until a very low temperature system. The use of decentralized renewable sources, decentralized heat storage tanks and the placement of a heat pump on each building are the key points to achieve the transformation. Regarding the sensitivity analysis, the transformation is worth doing until the seasonal storage and solar collector field sizes are reduced to 60% and 80% of their values in the reference case, respectively. The economic analysis shows, however, that it is hard for highly efficient low temperature renewable based heat networks to compete with district heating systems based on a centralized fossile CHP solution. Thus, though the presented transformation is technically possible, there is a strong need to change existing economic schemes and policies for fostering a stronger promotion of renewable energy policies in the heat sector.
Optimal Scheduling Strategy of AC/DC Hybrid Distribution Network Based on Power Electronic Transformer
Authors: Peng Qingwen , Qu Lu , Yuan Zhichang , Wang Xiaorui , Chen Yukun , Tian Baoye
Published: June 2021

The AC/DC hybrid distribution network is composed of a medium-voltage DC bus, a low-voltage DC bus, and a power electronic transformer, and has the characteristics of multi-voltage level, multi-DC bus, and multi-converter, so its operation mode and optimal scheduling strategy are more complex. Firstly, this paper constructs the AC/DC hybrid distribution network using an power electronic transformer. Then, a two-layer control structure including a scheduling management layer and a bus control layer is proposed, which simplifies the control structure and gives full play to the role of “energy routing” function of the power electronic transformer. Moreover, the minimum operation cost of the AC/DC hybrid distribution network in the whole scheduling cycle is taken as the optimization objective, considering the characteristics of various distributed generations, the structure of AC/DC hybrid distribution network, and the interaction of “source–load–storage”. Finally, the optimal scheduling model of the AC/DC hybrid distribution network based on power electronic transformer is established, and the feasibility of the optimal scheduling strategy is verified by the open-source solver, which can realize the complete absorption of renewable energy and the optimal coordinated control of “source–load–storage”.
Instantaneous Electromagnetic Torque Components in Synchronous Motors Fed by Load-Commutated Inverters
Authors: Ekemb Gabriel , Slaoui-Hasnaoui Fouad , Song-Manguelle Joseph , Lingom P. M. , Fofana Issouf
Published: June 2021

This paper proposes time-domain analytical expressions of the instantaneous pulsating torque components in a synchronous machine air gap when supplied by a load-commutated-inverter (LCI) system. The LCI technology is one of the most used variable frequency drives when very high power and low speed are required in applications such as pipeline recompression and decompression, as well as liquefied natural gas compression. In such applications, synchronous motors are used because of their high efficiency resulting from a separated supply of the current to their rotor through the excitation circuit. These applications usually have long and flexible shafts, which are very sensitive to torsional vibration excitation when their natural frequencies interact with any external torque applied to the shaft. A torsional analysis is required by international standards to assess the survivability of the shaft through the overall speed range of the motor. Therefore, the magnitude and frequencies of the motor air-gap torque are needed for such evaluation. The proposed developments are supported by numerical simulations of LCI systems in a large range of operation range. From the simulation results, torque harmonic families are derived and expressed in a parametric form, which confirm the accuracy of the proposed relationships.
Short-Term Load Forecasting Using Neural Networks with Pattern Similarity-Based Error Weights
Authors: Dudek Grzegorz
Published: June 2021

Forecasting time series with multiple seasonal cycles such as short-term load forecasting is a challenging problem due to the complicated relationship between input and output data. In this work, we use a pattern representation of the time series to simplify this relationship. A neural network trained on patterns is an easier task to solve. Thus, its architecture does not have to be either complex and deep or equipped with mechanisms to deal with various time-series components. To improve the learning performance, we propose weighting individual errors of training samples in the loss function. The error weights correspond to the similarity between the training pattern and the test query pattern. This approach makes the learning process more sensitive to the neighborhood of the test pattern. This means that more distant patterns have less impact on the learned function around the test pattern and lead to improved forecasting accuracy. The proposed framework is useful for a wide range of complex time-series forecasting problems. Its performance is illustrated in several short-term load-forecasting empirical studies in this work. In most cases, error weighting leads to a significant improvement in accuracy.
Reliability Evaluation of Renewable Power Systems through Distribution Network Power Outage Modelling
Authors: Kebede Fitsum Salehu , Olivier Jean-Christophe , Bourguet Salvy , Machmoum Mohamed
Published: June 2021

Intermittent power interruptions and blackouts with long outage durations are very common, especially on weak distribution grids such as in developing countries. This paper proposes a hybrid photovoltaic (PV)-battery-system sizing optimization through a genetic algorithm to address the reliability in fragile grids measured by the loss of power supply probability (LPSP) index. Recorded historical outage data from a real stochastic grid in Ethiopia and measured customer load is used. The resulting hybrid-system Pareto solutions give the flexibility for customers/power utilities to choose appropriate sizes based on the required reliability level. To evaluate the sizing solutions’ robustness, this work considers and compares grid outage modeling through two different approaches. The first is a Markov model, developed to be minimally implemented with limited outage data available. The second is a Weibull model, commonly used to describe extreme phenomena and failure analysis. It is more faithful in reproducing the dispersion of outage events. Using these models, the effectiveness and performance of the PV-battery system is verified on a large number of simulated outage scenarios, to estimate the real performance of the optimized design. It leads to a more accurate evaluation of the behavior of a renewable power system to a weak and unreliable electrical grid.