bluuebunny/crossref_metadata_2025 huggingface dataset:
Psychological and pedagogical conditions for the formation of an intellectual and creative personality
Authors: Pekhota G.V.
Published: February 2019

The article presents the system of formation of intellectual and creative individual at the different stages of age development: the prenatal period, pre-school and general secondary education stages.

The article emphasizes the importance of the prenatal period in the formation of intellectual and creative individual, as the intellectual and creative potential, as well as many features of the character of the future person, level of physical health are laid from the moment of his birth.

At the stage of pre-school education it is necessary to create psychological and pedagogical conditions for formation of a child’s subjective position in the game activity, which consists in the manifestation of the search initiative, self-regulation of their actions, immediacy of self-expression. The fundamental psychological innovation of preschool age is creative imagination which is in the basis of the theoretical thinking development in the subsequent stages of age development.

At the I stage of general secondary education the learning activity is of crucial importance. It is precisely in the learning activity it is formed the primary component of the intellectual and creative potential of an individual ¬– theoretical thinking: the ability to analyze, plan, reflect. Developing the theoretical thinking of pupils and forming their achievement motivation, we develop giftedness.

At the II and III stages of general secondary education it should be provided conditions for high personal activity aimed at achieving the goals in broad cognitive, educational, socially useful and other kinds of activity. In the middle school age communication with peers in communicative, collective-distributed activity is of fundamental importance, and at the senior school age an individual subject of learning activity is already being formed. And precisely this age is a final period in the formation of the whole complex of parameters and characteristics which are necessary for the development of creativity as a personal new formation.
General psychological theories of development, study and education
Authors: Maksymenko S.D.
Published: February 2019

Presentation of the chapter from the book by Maksymenko, S.D. (2018).  Psychology of human learning: genetically-modeling approach. Kyiv.

The monograph considers the personality, its sources, structural components and its inward world in terms of genetic psychology. The principles for construction of experimental genetic and genetically-modeling methods as the most adequate for explanation of laws and mechanisms of appropriation, formation and development of human abilities and genesis of personality development are presented for the first time. Genetically-original units of various abilities and “needs” as sources for stimulating activity of individual (Latin: Vis vitalis - vital power), its deepness and initial unity (synthetic character) (Latin: Vis vitae - vital force) that constitutes the personality are presented.

The following fundamental analysis is made:

-       theory of learning as a way for development and self-realization of personality;

-       study as a public form for management of learning and personality development;

-       learning as a direct and by-product of study.

The following specific peculiarities for needs (in vital force or vital power) were found:

-       energy informative virtues of human in onto- and phylogenesis;

-       genetic psychological problems, as well as personality structure were fixed;

-       sources and driving forces of personality activity were proved (presented);

-        fundamentally new personality structure, its forecast for development and life way; life (existence) of human; realization of love and needs and motivational regulators for life way of personality inward space
Peculiarities of insight of the European charter on the status of judges in the context of protecting their labor rights
Authors: Dei M. , Kochkova A.
Published: February 2019

The paper is devoted to questions of legal regulation of the peculiarities of insight the principles of the European Charter on the Status of Judges in the context of their labor rights in accordance with the legislation of Ukraine. It is clear that the development of the rule-of-law state, the protection of human rights and the rule of law are impossible without the effective functioning of the legal system, where one of the components of the judicial system . That is why the relevant legal system must realize the decree where a person is of the highest social value, despite the fact that those who administer justice also need proper protection. That is, it should be noted that the rights of judges as employees, taking into account the specifics of their work and status, should also be protected by the state. In joining the European community of international law, special attention should be paid to certain international standards concerning regulating relevant issues, where the European Charter on the Status of Judges of 1998, adopted within the Council of Europe, which in its turn is declarative, places particular emphasis. This document concerns, for example, issues such as appointment, status of judges, career development, responsibility, termination of judge's powers, etc. The characteristic of this document in the context of the subject under study is that most of the decree is devoted precisely to the labor rights of judges. Obviously, such decrees have become a progressive push for appropriate changes to the laws of the member states of the Council of Europe, where Ukraine did not become an exception, especially in the context of reforming the judicial system.
Projects management in the formation of a new model of education management of the combined territorial communities under the conditions of decentralization of power in Ukraine: definitions and aptness of implementation
Authors: Lіubchenko N.
Published: February 2019

The article reveals the relevance of the problem of education management under the conditions of decentralization of power in Ukraine,there we analyzed and compared the system of concepts on projects management, project cycle management, project portfolio management, cluster approach, and event management. The ways of implementation of the project cycle management technologies built on the basis of integrated and logical-structural approaches, in the management of the education of the united territorial community are proposed. The author's position is to apply the cluster approach in the system of management of education and methodical service and proposals for determining the role of public council in the local executive body of the united community.
Efficiency of using air transport during cargo transportation
Authors: Sokolova O. , Soloviova O.
Published: February 2019

In the article, the author’s vision on forming of multimodal cargo transportation systems is suggested. It is proposed to develop conceptual considerations on formation and practical recommendations regarding the choice of the optimal cargo delivery schemewhich includes air transport.
The system of medical and psychological support of adolescents with obesity
Authors: Belyaeva O. , Markova M.
Published: February 2019

The thesis is devoted to improving the system of psychological support to adolescents with obesity by definition of psychoemotional, cognitive, behavioral, and family components and their relationships in the genesis of psychological maladjustment formation in young patients. Some features of psychoemotional, cognitive, behavioral, and family components of  psychological maladjustment have been established in adolescents with obesity, psychographic markers of difficulties in self-perception of our patients have been singled out, and correlations of stylistic peculiarities in their eating behavior with parameters of quality of life have also been identified. Relationships between pronounced disorders in eating behavior, as well as desadaptive psychoemotional characteristics of patients, and some peculiarities in the emotional state of their mothers have been established. The model and the technology of the psychological support of adolescents with obesity have been substantiated, and the system of measures for their employment has been introduced. Age and gender-related characteristics of personality in adolescents with obesity were depicted, and some peculiarities in the attitude to their children of mothers both of boys and girls with different body weight were defined. Due to the analysis and generalization of our study results, the model of medical and psychological support of adolescents with obesity has been scientifically substantiated, developed and introduced into the clinical practice. The proposed model, aimed at correcting psychological maladjustment of adolescent patients and providing involvement of their parents at the diagnostic, consultative, and corrective stages, has demonstrated its effectiveness.
Combination Therapy With Fingolimod and Neural Stem Cells Promotes Functional Myelination in vivo Through a Non-immunomodulatory Mechanism
Authors: Zhang Yuan , Lu Xin-Yu , Ye Ze-Qin , Ciric Bogoljub , Ma Cun-Gen , Rostami Abdolmohamad , Li Xing , Zhang Guang-Xian
Published: February 2019

Myelination, which occurs predominantly postnatally and continues throughout life, is important for proper neurologic function of the mammalian central nervous system (CNS). We have previously demonstrated that the combination therapy of fingolimod (FTY720) and transplanted neural stem cells (NSCs) had a significantly enhanced therapeutic effect on the chronic stage of experimental autoimmune encephalomyelitis, an animal model of CNS autoimmunity, compared to using either one of them alone. However, reduced disease severity may be secondary to the immunomodulatory effects of FTY720 and NSCs, while whether this therapy directly affects myelinogenesis remains unknown. To investigate this important question, we used three myelination models under minimal or non-inflammatory microenvironments. Our results showed that FTY720 drives NSCs to differentiate into oligodendrocytes and promotes myelination in an ex vivo brain slice culture model, and in the developing CNS of healthy postnatal mice in vivo. Elevated levels of neurotrophic factors, e.g., brain-derived neurotrophic factor and glial cell line-derived neurotrophic factor, were observed in the CNS of the treated infant mice. Further, FTY720 and NSCs efficiently prolonged the survival and improved sensorimotor function of shiverer mice. Together, these data demonstrate a direct effect of FTY720, beyond its known immunomodulatory capacity, in NSC differentiation and myelin development as a novel mechanism underlying its therapeutic effect in demyelinating diseases.
Fog-Computing-Based Heartbeat Detection and Arrhythmia Classification Using Machine Learning
Authors: Scirè Alessandro , Tropeano Fabrizio , Anagnostopoulos Aris , Chatzigiannakis Ioannis
Published: February 2019

Designing advanced health monitoring systems is still an active research topic. Wearable and remote monitoring devices enable monitoring of physiological and clinical parameters (heart rate, respiration rate, temperature, etc.) and analysis using cloud-centric machine-learning applications and decision-support systems to predict critical clinical states. This paper moves from a totally cloud-centric concept to a more distributed one, by transferring sensor data processing and analysis tasks to the edges of the network. The resulting solution enables the analysis and interpretation of sensor-data traces within the wearable device to provide actionable alerts without any dependence on cloud services. In this paper, we use a supervised-learning approach to detect heartbeats and classify arrhythmias. The system uses a window-based feature definition that is suitable for execution within an asymmetric multicore embedded processor that provides a dedicated core for hardware assisted pattern matching. We evaluate the performance of the system in comparison with various existing approaches, in terms of achieved accuracy in the detection of abnormal events. The results show that the proposed embedded system achieves a high detection rate that in some cases matches the accuracy of the state-of-the-art algorithms executed in standard processors.
Blurred Boundaries: Ethnofiction and Its Impact on Postwar Japanese Cinema
Authors: Coates Jennifer
Published: February 2019

This article explores the use of ethnofiction, a technique emerging from the field of visual anthropology, which blends documentary and fiction filmmaking for ethnographic purposes. From Imamura Shōhei’s A Man Vanishes (Ningen jōhatsu, 1967) to Hou Hsiao Hsien’s Cafe Lumieré (Kōhi jikō, 2003), Japanese cinema, including Japan-set and Japan-associated cinema, has employed ethnofiction filmmaking techniques to alternately exploit and circumvent the structural barriers to filmmaking found in everyday life. Yet the dominant understanding in Japanese visual ethnography positions ethnofiction as an imported genre, reaching Japan through Jean Rouch and French cinema-verité. Blending visual analysis of Imamura and Hou’s ethnofiction films with an auto-ethnographic account of my own experience of four years of visual anthropology in Kansai, I interrogate the organizational barriers constructed around geographical perception and genre definition to argue for ethnofiction as a filmmaking technique that simultaneously emerged in French cinema-verité and Japanese feature filmmaking of the 1960s. Blurring the boundaries between Japanese, French, and East Asian co-production films, and between documentary and fiction genres, allows us to understand ethnofiction as a truly global innovation, with certain regional specificities.
The Application of Adeno-Associated Viral Vector Gene Therapy to the Treatment of Fragile X Syndrome
Authors: Hampson David R. , Hooper Alexander W. M. , Niibori Yosuke
Published: February 2019

Viral vector-mediated gene therapy has grown by leaps and bounds over the past several years. Although the reasons for this progress are varied, a deeper understanding of the basic biology of the viruses, the identification of new and improved versions of viral vectors, and simply the vast experience gained by extensive testing in both animal models of disease and in clinical trials, have been key factors. Several studies have investigated the efficacy of adeno-associated viral (AAV) vectors in the mouse model of fragile X syndrome where AAVs have been used to express fragile X mental retardation protein (FMRP), which is missing or highly reduced in the disorder. These studies have demonstrated a range of efficacies in different tests from full correction, to partial rescue, to no effect. Here we provide a backdrop of recent advances in AAV gene therapy as applied to central nervous system disorders, outline the salient features of the fragile X studies, and discuss several key issues for moving forward. Collectively, the findings to date from the mouse studies on fragile X syndrome, and data from clinical trials testing AAVs in other neurological conditions, indicate that AAV-mediated gene therapy could be a viable strategy for treating fragile X syndrome.
Treatment of Glioblastoma (GBM) with the Addition of Tumor-Treating Fields (TTF): A Review
Authors: Fabian Denise , Guillermo Prieto Eibl Maria del Pilar , Alnahhas Iyad , Sebastian Nikhil , Giglio Pierre , Puduvalli Vinay , Gonzalez Javier , Palmer Joshua D.
Published: February 2019

Glioblastoma (GBM) is the most common primary brain tumor. Despite aggressive treatment, GBM almost always recurs. The current standard-of-care for treatment of newly diagnosed GBM has remained relatively unchanged since 2005: maximal safe resection followed by concomitant chemoradiation (CRT) with temozolomide (TMZ), and subsequent adjuvant TMZ. In 2011, the first-generation tumor treating fields (TTF) device, known at the time as the NovoTTF-100A System (renamed Optune), was approved by the Food and Drug Administration (FDA) for treatment of recurrent GBM. The TTF device was subsequently approved as an adjuvant therapy for newly-diagnosed GBM in 2015. The following is a review of the TTF device, including evidence supporting its use and limitations.
Connexin43 Suppresses Lung Cancer Stem Cells
Authors: Ruch Randall J.
Published: February 2019

Alterations in gap junctions and their protein components, connexins, have been associated with neoplastic transformation and drug resistance, and more recently have been shown to play important roles in cancer stem cells (CSCs). However, there is less knowledge of connexins and gap junctions in lung CSCs. To address this, Connexin43 (Cx43), the major human lung epithelial gap junction protein, was expressed ectopically in poorly expressing National Cancer Institute-125 (NCI-H125) metastatic human lung adenocarcinoma cells, and phenotypic characteristics of malignant cells and abundance of CSCs were evaluated. The ectopic expression of Cx43 resulted in the formation of functional gap junctions; a more epithelial morphology; reduced proliferation, invasion, colony formation, tumorsphere formation, pluripotency marker expression, and percentage of aldehyde dehydrogenase (ALDH)-positive cells; and increased cisplatin sensitivity. Similarly, in NCI-H522 (human lung adenocarcinoma) and NCI-H661 (human lung large cell carcinoma) cell lines, which express Cx43 and functional gap junctions endogenously, the Cx43 content was lower in tumorspheres and ALDH-positive cells than in bulk cells. These results demonstrate that Cx43 can reverse several neoplastic characteristics and reduce the abundance of human lung CSCs.
Mining-Guided Machine Learning Analyses Revealed the Latest Trends in Neuro-Oncology
Authors: Hana Taijun , Tanaka Shota , Nejo Takahide , Takahashi Satoshi , Kitagawa Yosuke , Koike Tsukasa , Nomura Masashi , Takayanagi Shunsaku , Saito Nobuhito
Published: February 2019

In conducting medical research, a system which can objectively predict the future trends of the given research field is awaited. This study aims to establish a novel and versatile algorithm that predicts the latest trends in neuro-oncology. Seventy-nine neuro-oncological research fields were selected with computational sorting methods such as text-mining analyses. Thirty journals that represent the recent trends in neuro-oncology were also selected. As a novel concept, the annual impact (AI) of each year was calculated for each journal and field (number of articles published in the journal × impact factor of the journal). The AI index (AII) for the year was defined as the sum of the AIs of the 30 journals. The AII trends of the 79 fields from 2008 to 2017 were subjected to machine learning predicting analyses. The accuracy of the predictions was validated using actual past data. With this algorithm, the latest trends in neuro-oncology were predicted. As a result, the linear prediction model achieved relatively good accuracy. The predicted hottest fields in recent neuro-oncology included some interesting emerging fields such as microenvironment and anti-mitosis. This algorithm may be an effective and versatile tool for prediction of future trends in a particular medical field.
Targeting the Tetraspanins with Monoclonal Antibodies in Oncology: Focus on Tspan8/Co-029
Authors: Bonnet Mathilde , Maisonial-Besset Aurélie , Zhu Yingying , Witkowski Tiffany , Roche Gwenaëlle , Boucheix Claude , Greco Céline , Degoul Françoise
Published: February 2019

Tetraspanins are exposed at the surface of cellular membranes, which allows for the fixation of cognate antibodies. Developing specific antibodies in conjunction with genetic data would largely contribute to deciphering their biological behavior. In this short review, we summarize the main functions of Tspan8/Co-029 and its role in the biology of tumor cells. Based on data collected from recently reported studies, the possibilities of using antibodies to target Tspan8 in immunotherapy or radioimmunotherapy approaches are also discussed.
A Survey of the Concept of Disturbance in Quantum Mechanics
Authors: Benítez Rodríguez Ernesto , Arévalo Aguilar Luis Manuel
Published: February 2019

The concept of disturbance is of transcendental importance in Quantum Mechanics (QM). This key concept has been described in two different ways, the first one considering that the disturbance affects observables like x and p, as in the Heisenberg’s analysis of the measurement process and the other one takes into consideration that disturbance affects the state of the system instead. Entropic information measures have provided a path for studying disturbance in these both approaches; in fact, we found that initially it was studied by employing these entropic measures. In addition, in the last decade, there was an extensive amount of analyses and several new definitions of the disturbance concept emerged. Many crucial factors like this have inspired this concise paper which gathers the different concepts and definitions that have emerged through time for the better understanding of this topic.
Joint Deep Model with Multi-Level Attention and Hybrid-Prediction for Recommendation
Authors: Lin Zhipeng , Tang Yuhua , Zhang Yongjun
Published: February 2019

The Recommender System (RS) has obtained a pivotal role in e-commerce. To improve the performance of RS, review text information has been extensively utilized. However, it is still a challenge for RS to extract the most informative feature from a tremendous amount of reviews. Another significant issue is the modeling of user–item interaction, which is rarely considered to capture high- and low-order interactions simultaneously. In this paper, we design a multi-level attention mechanism to learn the usefulness of reviews and the significance of words by Deep Neural Networks (DNN). In addition, we develop a hybrid prediction structure that integrates Factorization Machine (FM) and DNN to model low-order user–item interactions as in FM and capture the high-order interactions as in DNN. Based on these two designs, we build a Multi-level Attentional and Hybrid-prediction-based Recommender (MAHR) model for recommendation. Extensive experiments on Amazon and Yelp datasets showed that our approach provides more accurate recommendations than the state-of-the-art recommendation approaches. Furthermore, the verification experiments and explainability study, including the visualization of attention modules and the review-usefulness prediction test, also validated the reasonability of our multi-level attention mechanism and hybrid prediction.
Improving the Performance of Storage Tank Fault Diagnosis by Removing Unwanted Components and Utilizing Wavelet-Based Features
Authors: Tra Viet , Duong Bach-Phi , Kim Jae-Young , Sohaib Muhammad , Kim Jong-Myon
Published: February 2019

This paper proposes a reliable fault diagnosis model for a spherical storage tank. The proposed method first used a blind source separation (BSS) technique to de-noise the input signals so that the signals acquired from a spherical tank under two types of conditions (i.e., normal and crack conditions) were easily distinguishable. BSS split the signals into different sources that provided information about the noise and useful components of the signals. Therefore, an unimpaired signal could be restored from the useful components. From the de-noised signals, wavelet-based fault features, i.e., the relative energy (REWPN) and entropy (EWPN) of a wavelet packet node, were extracted. Finally, these features were used to train one-against-all multiclass support vector machines (OAA MCSVMs), which classified the instances of normal and faulty states of the tank. The efficiency of the proposed fault diagnosis model was examined by visualizing the de-noised signals obtained from the BSS method and its classification performance. The proposed fault diagnostic model was also compared to existing techniques. Experimental results showed that the proposed method outperformed conventional techniques, yielding average classification accuracies of 97.25% and 98.48% for the two datasets used in this study.
Heat Recovery for a Textile Stenter: CFD Analysis of Air Curtain Benefits
Authors: Ciappi Lorenzo , Fiaschi Daniele , Manfrida Giampaolo , Salvadori Simone , Smolka Jacek , Talluri Lorenzo
Published: February 2019

Modern textile stenters are designed to reduce the inefficiency of the process and to recover the flow stream, which still contains a relatively high energetic value. In recent years, research has focused on the recovery of the energy content of the low-temperature exhaust flow; nonetheless, another important aspect that may increase the efficiency of the process is the reduction of the ambient air suction. In the present research, an innovative way to improve both machine insulation and energy savings, by using preheated air, was numerically evaluated. The proposed solution utilizes an air stream transverse to the fabric (generally called air curtain), either preheated or not, to create soft gates both at the inlet and at the outlet section of the drying machine. Several valuable advantages can be listed when using this solution: reduction of the dispersion of heat and humid polluted air to the work environment, limitation of air ingestion from outside, and effective heat recovery coupled to a uniform temperature profile around the textile fabric. To analyze the insulation capability of the air curtains in terms of mass and energy transfer, a two-dimensional CFD model of the machine was realized. A test matrix including three possible fabric speeds (20, 40 and 60 m/min), three tilt angles (−15°, 0° and 15°), four mass flow rates (0% with no air curtains and 3%, 5% and 7% of the total flow rate through the machine, where the 5% case is equivalent to the flow rate ingested from the ambient) and two temperatures (15 °C and 70 °C) of the plane jets exiting from the air curtains was considered, thus covering a wide range of possible practical applications. The obtained results demonstrate that warm air curtains at both the inlet and outlet are very effective in a fabric speed range up to 40 m/min; at higher fabric speed, entrainment of warm gases from inside the machine at the fabric outlet becomes relevant, and the adoption of a cold air curtain (capable of better insulation) can be recommended in this position.
A Cross-Entropy-Based Hybrid Membrane Computing Method for Power System Unit Commitment Problems
Authors: Xie Min , Du Yuxin , Cheng Peijun , Wei Wei , Liu Mingbo
Published: February 2019

The cross-entropy based hybrid membrane computing method is proposed in this paper to solve the power system unit commitment problem. The traditional unit commitment problem can be usually decomposed into a bi-level optimization problem including unit start-stop scheduling problem and dynamic economic dispatch problem. In this paper, the genetic algorithm-based P system is proposed to schedule the unit start-stop plan, and the biomimetic membrane computing method combined with the cross-entropy is proposed to solve the dynamic economic dispatch problem with a unit start-stop plan given. The simulation results of 10–100 unit systems for 24 h day-ahead dispatching show that the unit commitment problem can be solved effectively by the proposed cross-entropy based hybrid membrane computing method and obtain a good and stable solution.
Velocity-Controlled Particle Swarm Optimization (PSO) and Its Application to the Optimization of Transverse Flux Induction Heating Apparatus
Authors: Wang Youhua , Li Bin , Yin Liuxia , Wu Jiancheng , Wu Shipu , Liu Chengcheng
Published: February 2019

The main disadvantage of transverse flux induction heating (TFIH) is its resulting non-uniform temperature distribution on the surface of the strip at the inductor outlet. For obtaining a uniform temperature distribution, an improved particle swarm optimization (PSO) named velocity-controlled PSO (VCPSO) is proposed and applied to optimize this problem. Support vector machine (SVM) is adopted to establish a regression model to replace the complex and time-consuming coupling calculation process involved in TFIH problem. Simulation results of several test functions show that VCPSO performs much better than standard PSO (SPSO). Moreover, based on the existing research and experiments, the application of VCPSO combined with SVM to the TFIH problem achieves satisfactory results.
Preventing Internal Congestion in an Integrated European Balancing Activation Optimization
Authors: Håberg Martin , Bood Hanna , Doorman Gerard
Published: February 2019

New common platforms for optimization of balancing energy activation will facilitate cross-border exchange and integrate the fragmented European balancing markets. Having a zonal market structure, these platforms will optimize balancing actions as if intra-zonal transmission constraints did not exists, leaving it to each Transmission System Operator (TSO) to manage internal congestion caused by balancing energy activations. This paper describes a new method to pre-filter balancing bids likely to cause internal congestion due to their location. Furthermore, the complementary concept of exchange domains has been developed to prevent congested and infeasible balancing situations. A numerical example illustrates both the effectiveness and limitations of each method.
The Next-Generation Retail Electricity Market in the Context of Distributed Energy Resources: Vision and Integrating Framework
Authors: do Prado Josue Campos , Qiao Wei , Qu Liyan , Agüero Julio Romero
Published: February 2019

The increasing adoption of distributed energy resources (DERs) and smart grid technologies (SGTs) by end-user retail customers is changing significantly both technical and economic operations in the distribution grid. The next-generation retail electricity market will promote decentralization, efficiency, and competitiveness by accommodating existing and new agents through new business models and transactive approaches in an advanced metering infrastructure (AMI). However, these changes will bring several technical challenges to be addressed in transmission and distribution systems. Considerable activities have been carried out worldwide to study the impacts of integrating DERs into the grid and in the wholesale electricity market. However, the big vision and framework of the next-generation retail market in the context of DERs is still unclear. This paper aims to present a brief review of the present retail electricity market, some recent developments, and a comprehensive vision of the next-generation retail electricity market by describing its expected characteristics, challenges, needs, and future research topics to be addressed. A framework of integrating retail and wholesale electricity markets is also presented and discussed. The proposed vision and framework particularly highlight the necessity of new business models and regulatory initiatives to establish decentralized markets for DERs at the retail level as well as advances in technology and infrastructure necessary to allow the widespread use of DERs in active and effective ways.
Techno-Economic Analysis of a Small-Scale Biomass-to-Energy BFB Gasification-Based System
Authors: Porcu Andrea , Sollai Stefano , Marotto Davide , Mureddu Mauro , Ferrara Francesca , Pettinau Alberto
Published: February 2019

In order to limit global warming to around 1.5–2.0 °C by the end of the 21st century, there is the need to drastically limit the emissions of CO2. This goal can be pursued by promoting the diffusion of advanced technologies for power generation from renewable energy sources. In this field, biomass can play a very important role since, differently from solar and wind, it can be considered a programmable source. This paper reports a techno-economic analysis on the possible commercial application of gasification technologies for small-scale (2 MWe) power generation from biomass. The analysis is based on the preliminary experimental performance of a 500 kWth pilot-scale air-blown bubbling fluidized-bed (BFB) gasification plant, recently installed at the Sotacarbo Research Centre (Italy) and commissioned in December 2017. The analysis confirms that air-blown BFB biomass gasification can be profitable for the applications with low-cost biomass, such as agricultural waste, with a net present value up to about 6 M€ as long as the biomass is provided for free; on the contrary, the technology is not competitive for high-quality biomass (wood chips, as those used for the preliminary experimental tests). In parallel, an analysis of the financial risk was carried out, in order to estimate the probability of a profitable investment if a variation of the key financial parameters occurs. In particular, the analysis shows a probability of 90% of a NPV at 15 years between 1.4 and 5.1 M€ and an IRR between 11.6% and 23.7%.
Development of Complex Energy Systems with Absorption Technology by Combining Elementary Processes
Authors: Seki Kosuke , Takeshita Keisuke , Amano Yoshiharu
Published: February 2019

Optimal design of energy systems ultimately aims to develop a methodology to realize an energy system that utilizes available resources to generate maximum product with minimum components. For this aim, several researches attempt to decide the optimal system configuration as a problem of decomposing each energy system into primitive process elements. Then, they search the optimal combination sequentially from the minimum number of constituent elements. This paper proposes a bottom-up procedure to define and explore configurations by combining elementary processes for energy systems with absorption technology, which is widely applied as a heat driven technology and important for improving system’s energy efficiency and utilizing alternative energy resources. Two examples of application are presented to show the capability of the proposed methodology to find basic configurations that can generate the maximum product. The demonstration shows that the existing absorption systems, which would be calculated based on the experience of designers, could be derived by performing optimization with the synthesis methodology automatically under the simplified/idealized operating conditions. The proposed bottom-up methodology is significant for realizing an optimized absorption system. With this methodology, engineers will be able to predict all possible configurations and identify a simple yet feasible optimal system configuration.
Transmission Channel Analysis for Broadband Communication over Multiconductor UIC Cables Onboard Regional Trains
Authors: Barmada Sami , Tucci Mauro , Romano Francesco
Published: February 2019

In this contribution, the authors perform a detailed analysis relating to the use of the multiconductor UIC (Union Internationale des Chemins de fer) cables as a broadband data transmission channel onboard regional trains. The analysis is performed evaluating the channel frequency response and the channel capacity as a function of the distance between communication devices, in the 2–30 MHz frequency range of broadband powerline communications. The per unit length (p.u.l.) parameters are measured and simulated in a finite element method (FEM) code, allowing accurate full multiconductor simulations to evaluate the attenuations of the selected channel for communication and the cross-talk between cables. This study has been conducted considering that there are other signals carried by the cable, during regular train operation, and their integrity needs to be taken into account. The results show that, as a matter of fact, UIC cables can be used to transmit high-speed data; this can be exploited for introducing additional facilities (i.e., infotainment, safety features and so on) onboard regional trains, at a reasonably low cost, since no new cabling harnesses need be installed.
The Long-Term Effects of Wind Disturbance on a Sitka Spruce-Western Hemlock Forest
Authors: Harmon Mark E. , Pabst Robert J.
Published: February 2019

Wind is an important disturbance in many forested regions, but research has largely focused on immediate to short-term (<10 years) effects on species composition and structure of stands and landscapes. We used a set of ten, 0.4-ha plots established in 1935 and measured every 5–13 years to examine the cumulative effects of multiple wind disturbance events in the coastal forests of Oregon. Since 1935 there have been ten documented wind events in coastal Oregon with hurricane-force winds. Most of the eight windstorms since 1962 noticeably influenced at least one plot; however, no individual storm clearly influenced all plots. Net rate of biomass accumulation of plots was negative when biomass mortality exceeded 29–41 Mg/ha per 5-year period (or 3.4%–5.8% per 5 years). In contrast, wind disturbance did not clearly reduce NPP (Net Primary Production) in any plot until biomass mortality exceeded 50%. Major wind-related mortality episodes in individual plots did not necessarily strongly influence the average loss of biomass across all plots. For example, a biomass loss of 88% in one plot resulted in an average loss of only 3.4% across all plots. In contrast, the cumulative effect of multiple plots with repeated wind-related mortality did decrease biomass at the multi-plot level. Depending on the plot, wind caused 16%–59% of the total mortality over time, and the proportion of wind-related mortality has increased 5- to 8-fold since 1940. The majority (80%) of wind-related mortality was “immediate”, but some trees survived up to 35 years after being significantly wind damaged. Despite western hemlock having a wind-related mortality rate that was at least twice that of Sitka spruce, the number of stems of the former species increased over time. This trend may be related to the predominant recovery mechanism which was the release of existing small trees and the fact that the majority of ingrowth was western hemlock. This study suggests that wind disturbance is a heterogeneous, gradual process and that while individual events have a detectable impact on structure and function, the largest impacts, at least in systems where it reoccurs each decade, are cumulative.
Physiological and Transcriptome Analysis of a Yellow-Green Leaf Mutant in Birch (Betula platyphylla × B. Pendula)
Authors: Gang Huixin , Liu Guifeng , Chen Su , Jiang Jing
Published: February 2019

Chlorophyll (Chl)-deficient mutants are ideal materials for the study of Chl biosynthesis, chloroplast development, and photosynthesis. Although the genes encoding key enzymes related to Chl biosynthesis have been well-characterized in herbaceous plants, rice (Oryza sativa L.), Arabidopsis (Arabidopsis thaliana), and maize (Zea mays L.), yellow-green leaf mutants have not yet been fully studied in tree species. In this work, we explored the molecular mechanism of the leaf color formation in a yellow-green leaf mutant (yl). We investigated the differentially expressed genes (DEGs) between yl and control plants (wild type birch (WT) and BpCCR1 overexpression line 11, (C11)) by transcriptome sequencing. Approximately 1163 genes (874 down-regulated and 289 up-regulated) and 930 genes (755 down-regulated and 175 up-regulated) were found to be differentially expressed in yl compared with WT and C11, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs revealed that photosynthesis antenna proteins represent the most significant enriched pathway. The expressions of photosynthesis antenna proteins are crucial to the leaf color formation in yl. We also found that Chl accumulate, leaf anatomical structure, photosynthesis, and growth were affected in yl. Taken together, our results not only provide the difference of phenomenal, physiological, and gene expression characteristics in leaves between yl mutant and control plants, but also provide a new insight into the mutation underlying the chlorotic leaf phenotype in birch.
Prediction of Diameter Distributions with Multimodal Models Using LiDAR Data in Subtropical Planted Forests
Authors: Zhang Zhengnan , Cao Lin , Mulverhill Christopher , Liu Hao , Pang Yong , Li Zengyuan
Published: February 2019

Tree diameter distributions are essential for the calculation of stem volume and biomass, as well as simulation of growth and yield and to understand timber assortments. Accurate and reliable prediction of tree diameter distributions is critical for optimizing forest structure compositions, scheduling silvicultural operations and promoting sustainable management. In this study, we investigated the potential of airborne Light Detection and Ranging (LiDAR) data for predicting tree diameter distributions using a bimodal finite mixture model (FMM) and a multimodal k-nearest neighbor (KNN) model (compared to the unimodal Weibull model (UWM)) over a subtropical planted forest in southern China. To do so, we first evaluated the capability of various LiDAR predictions (i.e., the bimodality coefficient (BC) and Lorenz-based indicators) to stratify forest structural types into unimodal and multimodal stands. Once the best LiDAR prediction for the differentiation was determined, the parameters of UWM (in non-specific and species-specific models) and FMM (in structure-specific models) were estimated by LiDAR-derived metrics and the tree diameter distributions of stands were generated by the estimated LiDAR parameters. When KNN was applied for constructing diameter distributions, optimal KNN strategies, including number of neighbors k, response configurations and imputation methods (i.e., Most Similar Neighbor (MSN) and Random Forest (RF)) for different species were heuristically determined. Finally, the predictive performance of estimated LiDAR the parameters of UWM, FMM and KNN for predicting diameter distributions were assessed. The results showed that LiDAR-predicted Lorenz-based indicators performed best for differentiation. Parameters of UWM and FMM were predicted well and the species-specific models had higher accuracies than the non-specific models. Overall, RF imputation from KNN with an optimal response set (i.e., DBH) were was stable than MSN imputation when k = 5 neighbors. In addition, the inclusion of bimodal FMM for differentiated all plots generally produced a more accurate result (Mean eR = 40.85, Mean eP = 0.20) than multimodal KNN (Mean eR = 52.19, Mean eP = 0.26), whereas the UWM produced the lowest performance (Mean eR = 52.31, Mean eP = 0.26). This study demonstrated the benefits of multimodal models with LiDAR for estimating diameter distributions for supporting forest inventory and sustainable forest management in subtropical planted forests.
Percolation and Internet Science
Authors: Bagnoli Franco , Bellini Emanuele , Massaro Emanuele , Rechtman Raúl
Published: February 2019

Percolation, in its most general interpretation, refers to the “flow” of something (a physical agent, data or information) in a network, possibly accompanied by some nonlinear dynamical processes on the network nodes (sometimes denoted reaction–diffusion systems, voter or opinion formation models, etc.). Originated in the domain of theoretical and matter physics, it has many applications in epidemiology, sociology and, of course, computer and Internet sciences. In this review, we illustrate some aspects of percolation theory and its generalization, cellular automata and briefly discuss their relationship with equilibrium systems (Ising and Potts models). We present a model of opinion spreading, the role of the topology of the network to induce coherent oscillations and the influence (and advantages) of risk perception for stopping epidemics. The models and computational tools that are briefly presented here have an application to the filtering of tainted information in automatic trading. Finally, we introduce the open problem of controlling percolation and other processes on distributed systems.
Autonomic Network Management and Cross-Layer Optimization in Software Defined Radio Environments
Authors: Stamou Adamantia , Kakkavas Grigorios , Tsitseklis Konstantinos , Karyotis Vasileios , Papavassiliou Symeon
Published: February 2019

The demand for Autonomic Network Management (ANM) and optimization is as intense as ever, even though significant research has been devoted towards this direction. This paper addresses such need in Software Defined (SDR) based Cognitive Radio Networks (CRNs). We propose a new framework for ANM and network reconfiguration combining Software Defined Networks (SDN) with SDR via Network Function Virtualization (NFV) enabled Virtual Utility Functions (VUFs). This is the first approach combining ANM with SDR and SDN via NFV, demonstrating how these state-of-the-art technologies can be effectively combined to achieve reconfiguration flexibility, improved performance and efficient use of available resources. In order to show the feasibility of the proposed framework, we implemented its main functionalities in a cross-layer resource allocation mechanism for CRNs over real SDR testbeds provided by the Orchestration and Reconfiguration Control Architecture (ORCA) EU project. We demonstrate the efficacy of our framework, and based on the obtained results, we identify aspects that can be further investigated for improving the applicability and increasing performance of our broader framework.
Steady Two-Dimensional Free-Surface Flow Past Disturbances in an Open Channel: Solutions of the Korteweg–De Vries Equation and Analysis of the Weakly Nonlinear Phase Space
Authors: Binder Benjamin J.
Published: February 2019

Two-dimensional free-surface flow past disturbances in an open channel is a classical problem in hydrodynamics—a problem that has received considerable attention over the last two centuries (e.g., see Lamb’s Treatise, 1879). With traces back to Russell’s experimental observations of the Great Wave of Translation in 1834, Korteweg and de Vries (1895), and others, derived an unforced equation to describe the balance between nonlinearity and dispersion required to model the solitary wave. More recently, Akylas (1984) derived a forced KdV equation to model a pressure distribution on the free-surface (e.g., a ship). Since then, the forced KdV equation has been shown to be a useful model approximation for two-dimensional flow past disturbances in an open channel. In this paper, we review the stationary solutions of the forced KdV equation for four types of localised disturbances: (i) a flat plate separating two free surfaces; (ii) a compact bump, or dip in the channel bottom topography; (iii) a compact distribution of pressure on the free surface and (iv) a step-wise change in the otherwise constant horizontal level of the channel bottom topography. Moreover, Dias and Vanden-Broeck (2002) developed a phase plane method to analyse flow over a bump, and this general approach has also been applied to the three other types of forcing (see Binder et al., 2005–2015, and others). In this study, we use eleven basic flow types to classify the steady solutions of the forced KdV equation using the phase plane method. Additionally, considering solutions that are wave-free both far upstream and far downstream, we compare KdV model approximations of the uniform flow conditions in the far-field with exact solutions of the full problem. In particular, we derive a new KdV model approximation for the upstream dimensionless flow-rate which is conveniently given in terms of the known downstream dimensionless flow-rate.