bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection and Tracking of Moving Pedestrians with a Small Unmanned Aerial Vehicle
Authors: Yeom Seokwon , Cho In-Jun
Published: August 2019

Small unmanned aircraft vehicles (SUAVs) or drones are very useful for visual detection and tracking due to their efficiency in capturing scenes. This paper addresses the detection and tracking of moving pedestrians with an SUAV. The detection step consists of frame subtraction, followed by thresholding, morphological filter, and false alarm reduction, taking into consideration the true size of targets. The center of the detected area is input to the next tracking stage. Interacting multiple model (IMM) filtering estimates the state of vectors and covariance matrices, using multiple modes of Kalman filtering. In the experiments, a dozen people and one car are captured by a stationary drone above the road. The Kalman filter and the IMM filter with two or three modes are compared in the accuracy of the state estimation. The root-mean squared errors (RMSE) of position and velocity are obtained for each target and show the good accuracy in detecting and tracking the target position—the average detection rate is 96.5%. When the two-mode IMM filter is used, the minimum average position and velocity RMSE obtained are around 0.8 m and 0.59 m/s, respectively.
Research on an Output Power Model of a Doubly-Fed Variable-Speed Pumped Storage Unit with Switching Process
Authors: Zhao Guopeng , Ren Jiyun
Published: August 2019

The doubly-fed variable-speed pumped storage (DFVSPS) is an effective method to balance the fluctuation of renewable energy generation and is an important means of frequency and voltage regulation of a power grid. Firstly, this paper introduces the structure and mathematical model of the DFVSPS unit. Secondly, the control methods of each switching stage in generating mode and pump mode are proposed, and the simulation study of each stage of DFVSPS switching process is carried out by MATLAB/Simulink. Thirdly, when studying the regulating effect of DFVSPS unit in the power system, due to the high switching frequency of converter in the electromagnetic transient model, the simulation speed is very slow and the data volume is large, so the model of DFVSPS unit needs to be simplified. By analyzing the dynamic behavior of the pumped storage power station, the mathematical model of output power of the DFVSPS unit is established, which includes start-up stage, load ramping stage, stable operation stage, load rejection stage and shutdown stage of generating mode and pump mode. Finally, the simplified model of DFVSPS unit is applied to a simple power system to verify its regulating effect on grid power.
Evidence for Rayleigh-Taylor Plasma Instability at the Front of Solar Coronal Mass Ejections
Authors: Telloni Daniele , Carbone Francesco , Bemporad Alessandro , Antonucci Ester
Published: August 2019

This work focuses on the interaction of a Coronal Mass Ejection (CME) with the ambient solar corona, by studying the spatial and temporal evolution of the density fluctuations observed by the SOHO/UV Coronagraph Spectrometer (UVCS) during the CME. The investigation is performed by applying a wavelet analysis to the HI Ly α 1216 Å line intensity fluctuations observed with UVCS during the CME occurred on 24 December 2006. Strong and coherent fluctuations, with a significant spatial periodicity of about 84 Mm ≃ 0.12 R ⊙ , are shown to develop in about an hour along the front of the CME. The results seem to indicate the Rayleigh-Taylor (RT) instability, susceptible to the deceleration of the heavier fluid of the CME front into the lighter surrounding coronal plasma, as the likely mechanism underlying the generation of the observed plasma fluctuations. This could be the first inference of the RT instability in the outer solar corona in UV, due to the transit of a CME front in the quiet coronal plasma; this interpretation is also supported by a linear magnetohydrodynamic analysis of the RT instability.
Noncoding RNAs in Extracellular Fluids as Cancer Biomarkers: The New Frontier of Liquid Biopsies
Authors: Pardini Barbara , Sabo Alexandru Anton , Birolo Giovanni , Calin George Adrian
Published: August 2019

The last two decades of cancer research have been devoted in two directions: (1) understanding the mechanism of carcinogenesis for an effective treatment, and (2) improving cancer prevention and screening for early detection of the disease. This last aspect has been developed, especially for certain types of cancers, thanks also to the introduction of new concepts such as liquid biopsies and precision medicine. In this context, there is a growing interest in the application of alternative and noninvasive methodologies to search for cancer biomarkers. The new frontiers of the research lead to a search for RNA molecules circulating in body fluids. Searching for biomarkers in extracellular body fluids represents a better option for patients because they are easier to access, less painful, and potentially more economical. Moreover, the possibility for these types of samples to be taken repeatedly, allows a better monitoring of the disease progression or treatment efficacy for a better intervention and dynamic treatment of the patient, which is the fundamental basis of personalized medicine. RNA molecules, freely circulating in body fluids or packed in microvesicles, have all the characteristics of the ideal biomarkers owing to their high stability under storage and handling conditions and being able to be sampled several times for monitoring. Moreover, as demonstrated for many cancers, their plasma/serum levels mirror those in the primary tumor. There are a large variety of RNA species noncoding for proteins that could be used as cancer biomarkers in liquid biopsies. Among them, the most studied are microRNAs, but recently the attention of the researcher has been also directed towards Piwi-interacting RNAs, circular RNAs, and other small noncoding RNAs. Another class of RNA species, the long noncoding RNAs, is larger than microRNAs and represents a very versatile and promising group of molecules which, apart from their use as biomarkers, have also a possible therapeutic role. In this review, we will give an overview of the most common noncoding RNA species detectable in extracellular fluids and will provide an update concerning the situation of the research on these molecules as cancer biomarkers.
Untargeted Assessment of Tumor Fractions in Plasma for Monitoring and Prognostication from Metastatic Breast Cancer Patients Undergoing Systemic Treatment
Authors: Suppan Christoph , Brcic Iva , Tiran Verena , Mueller Hannah D , Posch Florian , Auer Martina , Ercan Erkan , Ulz Peter , Cote Richard J , Datar Ram H , Dandachi Nadia , Heitzer Ellen , Balic Marija
Published: August 2019

The aim of this study was to assess the prognostic and predictive value of an untargeted assessment of tumor fractions in the plasma of metastatic breast cancer patients and to compare circulating tumor DNA (ctDNA) with circulating tumor cells (CTC) and conventional tumor markers. In metastatic breast cancer patients (n = 29), tumor fractions in plasma were assessed using the untargeted mFAST-SeqS method from 127 serial blood samples. Resulting z-scores for the ctDNA were compared to tumor fractions established with the recently published ichorCNA algorithm and associated with the clinical outcome. We observed a close correlation between mFAST-SeqS z-scores and ichorCNA ctDNA quantifications. Patients with mFAST-SeqS z-scores above three (34.5%) showed significantly worse overall survival (p = 0.014) and progression-free survival (p = 0.018) compared to patients with lower values. Elevated z-score values were clearly associated with radiologically proven progression. The baseline CTC count, carcinoembryonic antigen (CEA), and cancer antigen (CA)15-5 had no prognostic impact on the outcome of patients in the analyzed cohort. This proof of principle study demonstrates the prognostic impact of ctDNA levels detected with mFAST-SeqS as a very fast and cost-effective means to assess the ctDNA fraction without prior knowledge of the genetic landscape of the tumor. Furthermore, mFAST-SeqS-based ctDNA levels provided an early means of measuring treatment response.
The Tumor Microenvironment in Colorectal Cancer Therapy
Authors: Pedrosa Leire , Esposito Francis , Thomson Timothy M. , Maurel Joan
Published: August 2019

The current standard-of-care for metastatic colorectal cancer (mCRC) includes chemotherapy and anti-angiogenic or anti-epidermal growth factor receptor (EGFR) monoclonal antibodies, even though the addition of anti-angiogenic agents to backbone chemotherapy provides little benefit for overall survival. Since the approval of anti-angiogenic monoclonal antibodies bevacizumab and aflibercept, for the management of mCRC over a decade ago, extensive efforts have been devoted to discovering predictive factors of the anti-angiogenic response, unsuccessfully. Recent evidence has suggested a potential correlation between angiogenesis and immune phenotypes associated with colorectal cancer. Here, we review evidence of interactions between tumor angiogenesis, the immune microenvironment, and metabolic reprogramming. More specifically, we will highlight such interactions as inferred from our novel immune-metabolic (IM) signature, which groups mCRC into three distinct clusters, namely inflamed-stromal-dependent (IM Cluster 1), inflamed-non stromal-dependent (IM Cluster 2), and non-inflamed or cold (IM Cluster 3), and discuss the merits of the IM classification as a guide to new immune-metabolic combinatorial therapeutic strategies in mCRC.
NF-κB Signaling in Ovarian Cancer
Authors: Harrington Brittney S. , Annunziata Christina M.
Published: August 2019

The NF-κB signaling pathway is a master and commander in ovarian cancer (OC) that promotes chemoresistance, cancer stem cell maintenance, metastasis and immune evasion. Many signaling pathways are dysregulated in OC and can activate NF-κB signaling through canonical or non-canonical pathways which have both overlapping and distinct roles in tumor progression. The activation of canonical NF-κB signaling has been well established for anti-apoptotic and immunomodulatory functions in response to the tumor microenvironment and the non-canonical pathway in cancer stem cell maintenance and tumor re-initiation. NF-κB activity in OC cells helps to create an immune-evasive environment and to attract infiltrating immune cells with tumor-promoting phenotypes, which in turn, drive constitutive NF-κB activation in OC cells to promote cell survival and metastasis. For these reasons, NF-κB is an attractive target in OC, but current strategies are limited and broad inhibition of this major signaling pathway in normal physiological and immunological functions may produce unwanted side effects. There are some promising pre-clinical outcomes from developing research to target and inhibit NF-κB only in the tumor-reinitiating cancer cell population of OC and concurrently activate canonical NF-κB signaling in immune cells to promote anti-tumor immunity.
PML Bodies in Mitosis
Authors: Lång Anna , Lång Emma , Bøe Stig Ove
Published: August 2019

Promyelocytic leukemia (PML) bodies are dynamic intracellular structures that recruit and release a variety of different proteins in response to stress, virus infection, DNA damage and cell cycle progression. While PML bodies primarily are regarded as nuclear compartments, they are forced to travel to the cytoplasm each time a cell divides, due to breakdown of the nuclear membrane at entry into mitosis and subsequent nuclear exclusion of nuclear material at exit from mitosis. Here we review the biochemical and biophysical transitions that occur in PML bodies during mitosis and discuss this in light of post-mitotic nuclear import, cell fate decision and acute promyelocytic leukemia therapy.
Clinical and Genetic Analysis of Children with Kartagener Syndrome
Authors: Pereira Rute , Barbosa Telma , Gales Luís , Oliveira Elsa , Santos Rosário , Oliveira Jorge , Sousa Mário
Published: August 2019

Primary ciliary dyskinesia (PCD) is a rare autosomal recessive disorder characterized by dysfunction of motile cilia causing ineffective mucus clearance and organ laterality defects. In this study, two unrelated Portuguese children with strong PCD suspicion underwent extensive clinical and genetic assessments by whole-exome sequencing (WES), as well as ultrastructural analysis of cilia by transmission electron microscopy (TEM) to identify their genetic etiology. These analyses confirmed the diagnostic of Kartagener syndrome (KS) (PCD with situs inversus). Patient-1 showed a predominance of the absence of the inner dynein arms with two disease-causing variants in the CCDC40 gene. Patient-2 showed the absence of both dynein arms and WES disclosed two novel high impact variants in the DNAH5 gene and two missense variants in the DNAH7 gene, all possibly deleterious. Moreover, in Patient-2, functional data revealed a reduction of gene expression and protein mislocalization in both genes’ products. Our work calls the researcher’s attention to the complexity of the PCD and to the possibility of gene interactions modelling the PCD phenotype. Further, it is demonstrated that even for well-known PCD genes, novel pathogenic variants could have importance for a PCD/KS diagnosis, reinforcing the difficulty of providing genetic counselling and prenatal diagnosis to families.
PeTaL (Periodic Table of Life) and Physiomimetics
Authors: Shyam Vikram , Friend Lauren , Whiteaker Brian , Bense Nicholas , Dowdall Jonathan , Boktor Bishoy , Johny Manju , Reyes Isaias , Naser Angeera , Sakhamuri Nikhitha , Kravets Victoria , Calvin Alexandra , Gabus Kaylee , Goodman Delonte , Schilling Herbert , Robinson Calvin , Reid II Robert Omar , Unsworth Colleen
Published: August 2019

The Periodic Table of Life (PeTaL) is a system design tool and open source framework that uses artificial intelligence (AI) to aid in the systematic inquiry of nature for its application to human systems. This paper defines PeTaL’s architecture and workflow. Biomimicry, biophysics, biomimetics, bionics and numerous other terms refer to the use of biology and biological principles to inform practices in other disciplines. For the most part, the domain of inquiry in these fields has been confined to extant biological models with the proponents of biomimicry often citing the evolutionary success of extant organisms relative to extinct ones. An objective of this paper is to expand the domain of inquiry for human processes that seek to model those that are, were or could be found in nature with examples that relate to the field of aerospace and to spur development of tools that can work together to accelerate the use of artificial intelligence, topology optimization and conventional modeling in problem solving. Specifically, specialized fields such as paleomimesis, anthropomimesis and physioteleology are proposed in conjunction with artificial evolution. The overarching philosophy outlined here can be thought of as physiomimetics, a holistic and systematic way of learning from natural history. The backbone of PeTaL integrates an unstructured database with an ontological model consisting of function, morphology, environment, state of matter and ecosystem. Tools that support PeTaL include machine learning, natural language processing and computer vision. Applications of PeTaL include guiding human space exploration, understanding human and geological history, and discovering new or extinct life. Also discussed is the formation of V.I.N.E. (Virtual Interchange for Nature-inspired Exploration), a virtual collaborative aimed at generating data, research and applications centered on nature. Details of implementation will be presented in subsequent publications. Recommendations for future work are also presented.
Spectral Embedded Deep Clustering
Authors: Wada Yuichiro , Miyamoto Shugo , Nakagama Takumi , Andéol Léo , Kumagai Wataru , Kanamori Takafumi
Published: August 2019

We propose a new clustering method based on a deep neural network. Given an unlabeled dataset and the number of clusters, our method directly groups the dataset into the given number of clusters in the original space. We use a conditional discrete probability distribution defined by a deep neural network as a statistical model. Our strategy is first to estimate the cluster labels of unlabeled data points selected from a high-density region, and then to conduct semi-supervised learning to train the model by using the estimated cluster labels and the remaining unlabeled data points. Lastly, by using the trained model, we obtain the estimated cluster labels of all given unlabeled data points. The advantage of our method is that it does not require key conditions. Existing clustering methods with deep neural networks assume that the cluster balance of a given dataset is uniform. Moreover, it also can be applied to various data domains as long as the data is expressed by a feature vector. In addition, it is observed that our method is robust against outliers. Therefore, the proposed method is expected to perform, on average, better than previous methods. We conducted numerical experiments on five commonly used datasets to confirm the effectiveness of the proposed method.
Distinguishing between Clausius, Boltzmann and Pauling Entropies of Frozen Non-Equilibrium States
Authors: Feistel Rainer
Published: August 2019

In conventional textbook thermodynamics, entropy is a quantity that may be calculated by different methods, for example experimentally from heat capacities (following Clausius) or statistically from numbers of microscopic quantum states (following Boltzmann and Planck). It had turned out that these methods do not necessarily provide mutually consistent results, and for equilibrium systems their difference was explained by introducing a residual zero-point entropy (following Pauling), apparently violating the Nernst theorem. At finite temperatures, associated statistical entropies which count microstates that do not contribute to a body’s heat capacity, differ systematically from Clausius entropy, and are of particular relevance as measures for metastable, frozen-in non-equilibrium structures and for symbolic information processing (following Shannon). In this paper, it is suggested to consider Clausius, Boltzmann, Pauling and Shannon entropies as distinct, though related, physical quantities with different key properties, in order to avoid confusion by loosely speaking about just “entropy” while actually referring to different kinds of it. For instance, zero-point entropy exclusively belongs to Boltzmann rather than Clausius entropy, while the Nernst theorem holds rigorously for Clausius rather than Boltzmann entropy. The discussion of those terms is underpinned by a brief historical review of the emergence of corresponding fundamental thermodynamic concepts.
Road Accidents Detection, Data Collection and Data Analysis Using V2X Communication and Edge/Cloud Computing
Authors: Khaliq Kishwer Abdul , Chughtai Omer , Shahwani Abdullah , Qayyum Amir , Pannek Jürgen
Published: August 2019

With the improvement in transportation infrastructure and in-vehicle technology in addition to a meteoric increase in the total number of commercial and non-commercial vehicles on the road, traffic accidents may occur, which usually cause a high death toll. More than half of these deaths occur due to a delayed response by medical care providers and rescue authorities. The chances of survival of an accident victim could increase drastically if immediate medical assistance is provided at an accident location. This work proposes a low-cost accident detection and notification system, which utilizes a multi-tier IoT-based vehicular environment; principally, it uses V2X Communication and Edge/Cloud computing. In this work, vehicles are equipped with an On-Board Unit (OBU) in addition to mechanical sensors (accelerometer, gyroscope) for reliable accident detection along with a Global Positioning System (GPS) module for identification of accident location. In addition to this, a camera module is implanted on the vehicle to capture the moment when an accident takes place. In order to facilitate inter-vehicle communication (IVC), OBU in each vehicle incorporates a wireless networking interface. Once an accident occurs, a vehicle detects it and generates an alert message. It then sends the message along with the accident location to an intermediate device, placed at the edge of the vehicular network, and therefore called an edge device. Upon receiving the notification, this edge device finds the nearest hospital and makes a request for an ambulance to be dispatched immediately. It also performs some preprocessing of data and effectively acts as a bridge between the sensors installed inside the vehicle and the distant server deployed in the cloud. A significant issue that the traffic authorities are currently facing is the real-time visualization of data obtained through such environments. Wireless interfaces are usually capable of forwarding real-time sensor data; however, this feature is not yet commercially available in the OBU of the vehicle; therefore, practical implementation is carried out using the Internet of things (IoT) in order to create a network among the vehicles, the edge node, and the central server. By performing analysis on the adequate acquired data of road accidents, the constructive plans of action can be devised that may limit the death toll. In order to assist the relevant authorities in performing wholesome analysis of refined and reliable data, a dynamic front-end visualization is proposed, which is hosted in the cloud. The generated charts and graphs help the personnel at relevant organizations to make appropriate decisions based on the conclusive analysis of processed and stored data.
Second Harmonic Beam Shaping and Sensing in Dielectric Bow-Tie Antenna via Convex Optimization Array Synthesis Approach
Authors: Rocco Davide , Di Donato Loreto , Sorbello Gino , De Angelis Costantino
Published: August 2019

We propose a convex optimization approach for an array synthesis pattern to enhance the electromagnetic field in the gap region of a dielectric bow-tie antenna. This method allows the induction of the desired antenna modes by exploiting the concurrent excitation of the structure with plane waves with different propagation directions and complex amplitudes. By engineering the excitation coefficients of the array, different modes are excited in the bow-tie antenna and the radiation pattern of the generated second harmonic (SH) field is modified accordingly. Using our approach, we demonstrate both the feasibility of performing synthesis of the SH radiation pattern in dielectric antennas and the possibility of developing innovative sensing applications in photonics.
A New Predictive Control Strategy for Multilevel Current-Source Inverter Grid-Connected
Authors: Estévez-Bén Adyr A. , López Tapia Héctor Juan Carlos , Carrillo-Serrano Roberto Valentín , Rodríguez-Reséndiz Juvenal , Vázquez Nava Nimrod
Published: August 2019

The DC/AC converters—commonly called inverters—transform the DC into AC and are classified as Voltage-Source Inverters (VSIs) or Current-Source Inverters (CSIs). A variant of the CSIs are the Multilevel Current-Source Inverters (MCSIs). In this paper, a new predictive control strategy for an MCSI with multiple inputs and grid-connected is proposed. The control technique uses the advantages of the Sliding Mode Control (SMC) for the balance of current in the input and Predictive Control (PC) to obtain a suitable grid current, since it separates both functions. The calculations are based on conventional Kirchhoff’s Voltage Law (KVL) and knowledge of the mathematical model of the system is not required. Generally, traditional MCSIs use large input inductors (100–1000 mH). In this paper, it is achieved a reduction in size of the input inductors. Simulation results are shown to validate the proposed control.
Performance Analysis of a Grid-Connected Rooftop Solar Photovoltaic System
Authors: Akpolat Alper Nabi , Dursun Erkan , Kuzucuoğlu Ahmet Emin , Yang Yongheng , Blaabjerg Frede , Baba Ahmet Fevzi
Published: August 2019

Turkey is among the countries largely dependent on energy import. This dependency has increased interest in new and alternative energy sources. Installation of rooftop solar photovoltaic systems (RSPSs) in Turkey is increasing continuously regarding geographical and meteorological conditions. This paper presents an insight into the potential situation for Turkey and a simulation study for the RSPS designing and calculation for the faculty building at Marmara University in Istanbul. This simulation study demonstrates that 84.75-kWp grid-connected RSPS can produce remarkable power. The system is performed in detail with the PV*SOL software (Premium 2017 R8-Test Version, Valentin Software GmbH, Berlin, Germany). Detailed financial and performance analysis of the grid-connected RSPS for faculty building with various parameters is also carried out in this study. According to the simulation results, the system supplies 13.2% of the faculty buildings’ annual electrical energy consumption. The annual savings value of faculty buildings’ electrical consumption is approximately 90,298 kWh energy which costs roughly $7296. A photovoltaic (PV) system installation for the faculty building, which has considerable potential for solar energy and sunshine duration, is indispensable for clean energy requirements and was supported by the simulation results. This paper can be considered to be a basic feasibility study prior to moving on to the implementation project.
Analytical Description of Overhead Transmission Lines Loadability
Authors: Lauria Davide , Mottola Fabio , Quaia Stefano
Published: August 2019

The loadability characteristics of overhead transmission lines (OHLs) is certainly not a new topic. However, driven by sustainability issues, the increasing need to exploit existing electrical infrastructures as much as possible, has given OHL loadability a renowned central role and, recently, new investigations on this subject have been carried out. OHL loadability is generally investigated by means of numerical methods. Even though this approach allows deducing useful information in both planning and operation stage, it does not permit to capture all the insights obtainable by an analytical approach. The goal of this paper is to tailor a general analytical formulation for the loadability of OHLs. The first part of the paper is devoted to the base-case of uncompensated OHLs. Later, aiming to demonstrate the inherent feasibility and flexibility of the novel approach proposed, the less frequent case of shunt compensated radial OHLs is investigated as well. The analytical formulation is combined with the use of circular diagrams. Such diagrams allow a geometrical interpretation of the analytical relationships and are very useful to catch the physical insights of the problem. Finally, in order to show the applicability of the new analytical approach, a practical example is provided. The example concerns calculation of the loadability characteristics of typical 400 kV single-circuit OHLs.
SOC and SOH Joint Estimation of the Power Batteries Based on Fuzzy Unscented Kalman Filtering Algorithm
Authors: Zeng Miaomiao , Zhang Peng , Yang Yang , Xie Changjun , Shi Ying
Published: August 2019

In order to improve the convergence time and stabilization accuracy of the real-time state estimation of the power batteries for electric vehicles, a fuzzy unscented Kalman filtering algorithm (F-UKF) of a new type is proposed in this paper, with an improved second-order resistor-capacitor (RC) equivalent circuit model established and an online parameter identification used by Bayes. Ohmic resistance is treated as a battery state of health (SOH) characteristic parameter, F-UKF algorithms are used for the joint estimation of battery state of charge (SOC) and SOH. The experimental data obtained from the ITS5300-based battery test platform are adopted for the simulation verification under discharge conditions with constant-current pulses and urban dynamometer driving schedule (UDDS) conditions in the MATLAB environment. The experimental results show that the F-UKF algorithm is insensitive to the initial value of the SOC under discharge conditions with constant-current pulses, and the SOC and SOH estimation accuracy under UDDS conditions reaches 1.76% and 1.61%, respectively, with the corresponding convergence time of 120 and 140 s, which proves the superiority of the joint estimation algorithm.
Investigations on the Unsteady Aerodynamic Characteristics of a Horizontal-Axis Wind Turbine during Dynamic Yaw Processes
Authors: Wang Xiaodong , Ye Zhaoliang , Kang Shun , Hu Hui
Published: August 2019

Wind turbines inevitably experience yawed flows, resulting in fluctuations of the angle of attack (AOA) of airfoils, which can considerably impact the aerodynamic characteristics of the turbine blades. In this paper, a horizontal-axis wind turbine (HAWT) was modeled using a structured grid with multiple blocks. Then, the aerodynamic characteristics of the wind turbine were investigated under static and dynamic yawed conditions using the Unsteady Reynolds Averaged Navier-Stokes (URANS) method. In addition, start-stop yawing rotations at two different velocities were studied. The results suggest that AOA fluctuation under yawing conditions is caused by two separate effects: blade advancing & retreating and upwind & downwind yawing. At a positive yaw angle, the blade advancing & retreating effect causes a maximum AOA at an azimuth angle of 0°. Moreover, the effect is more dominant in inboard airfoils compared to outboard airfoils. The upwind & downwind yawing effect occurs when the wind turbine experiences dynamic yawing motion. The effect increases the AOA when the blade is yawing upwind and vice versa. The phenomena become more dominant with the increase of yawing rate. The torque of the blade in the forward yawing condition is much higher than in backward yawing, owing to the reversal of the yaw velocity.
How Hybridization of Energy Storage Technologies Can Provide Additional Flexibility and Competitiveness to Microgrids in the Context of Developing Countries
Authors: Barelli Linda , Bidini Gianni , Cherubini Paolo , Micangeli Andrea , Pelosi Dario , Tacconelli Carlo
Published: August 2019

Hybrid microgrids, integrating renewable energy sources and energy storage, are key in extending energy access in the remote areas of developing countries, in a sustainably way and in providing a good quality of service. Their extensive development faces a financing gap, having a high capital expenditure (CAPEX) also due to high storage costs. In the present work, a case study of a Ugandan microgrid was used to compare various battery technologies employed on their own and in a combination with a flywheel, in terms of their durability and the overall levelized cost of energy (LCOE) of the plant. Simulations show how hybrid storage configurations result in a lower LCOE for the current load profile of the microgrid and even more so for two reference residential and industrial load scenarios, suggesting this would remain the best solution even accounting for future socio-economic development. The resulting LCOE for hybrid storage configurations is lower than the average values reported for microgrid projects and represents a promising solution to speed up the development of such electrification initiatives.
Analytical Study of Tri-Generation System Integrated with Thermal Management Using HT-PEMFC Stack
Authors: Kang Hyun Sung , Shin Yoon Hyuk
Published: August 2019

Recently, extensive studies on power generation using clean energy have been conducted to reduce air pollution and global warming. In particular, as existing internal combustion engines lose favor to power generation through hydrogen fuel cells, the development of tri-generation technology using efficient and reliable fuel cells is gaining importance. This study proposes a tri-generation thermal management model that enables thermal control and waste heat utilization control of a high-temperature PEMFC stack that simultaneously satisfies combined cooling, heating, and power (CCHP) load. As the high-temperature PEMFC stack operates at 150 °C or more, a tri-generative system using such a stack requires a thermal management system that can maintain the operating temperature of the stack and utilize the stack waste heat. Thus, to apply the waste heat produced through the stack to heating (hot water) and absorption cooling, proper distribution control of the thermal management fluid (cooling fluid) of the stack is essential. For the thermal management fluid control design, system analysis modeling was performed to selectively design the heat exchange amount of each part utilizing the stack waste heat. In addition, a thermal management system based on thermal storage was constructed for complementary waste heat utilization and active stack cooling control. Through a coupled analysis of the stack thermal management model and the absorption cooling system model, this study compared changes in system performance by cooling cycle operation conditions. This study investigated into the appropriate operating conditions for cooling operation in a tri-generative system using a high-temperature PEMFC stack.
A Geospatial Decision Support System Tool for Supporting Integrated Forest Knowledge at the Landscape Scale
Authors: Marano Gina , Langella Giuliano , Basile Angelo , Cona Francesco , De Michele Carlo , Manna Piero , Teobaldelli Maurizio , Saracino Antonio , Terribile Fabio
Published: August 2019

Forests are part of a complex landscape mosaic and play a crucial role for people living both in rural and urbanized spaces. Recent progresses in modelling and Decision Support System (DSS) applied to the forestry sector promise to improve public participative forest management and decision-making in planning and conservation issues. However, most DSS are not open-source systems, being in many cases software designed for site-specific applications in forest ecosystems. Furthermore, some of these systems often miss challenging the integration of other land uses within the landscape matrix, which is a key issue in modern forestry planning aiming at linking recent developments in open-source Spatial-DSS systems to sectorial forest knowledge. This paper aims at demonstrating that a new type of S-DSS, developed within the Life+ project SOILCONSWEB over an open-source Geospatial Cyber-Infrastructure (GCI) platform, can provide a strategic web-based operational tool for forest resources management and multi-purpose planning. In order to perform simulation modelling, all accessible via the Web, the GCI platform supports acquisition and processing of both static and dynamic data (e.g., spatial distribution of soil and forest types, growing stock and yield), data visualization and computer on-the-fly applications. The DSS forestry tool has been applied to a forest area of 5,574 ha in the southern Apennines of Peninsular Italy, and it has been designed to address forest knowledge and management providing operational support to private forest owners and decision-makers involved in management of forest landscape at different levels. Such a geospatial S-DSS tool for supporting integrated forest knowledge at landscape represents a promising tool to implement sustainable forest management and planning. Results and output of the platform will be shown through a short selection of practical case studies.
Implications of Selective Harvesting of Natural Forests for Forest Product Recovery and Forest Carbon Emissions: Cases from Tarai Nepal and Queensland Australia
Authors: Poudyal Bishnu Hari , Maraseni Tek Narayan , Cockfield Geoff
Published: August 2019

Selective logging is one of the main natural forest harvesting approaches worldwide and contributes nearly 15% of global timber needs. However, there are increasing concerns that ongoing selective logging practices have led to decreased forest product supply, increased forest degradation, and contributed to forest based carbon emissions. Taking cases of natural forest harvesting practices from the Tarai region of Nepal and Queensland Australia, this study assesses forest product recovery and associated carbon emissions along the timber production chain. Field measurements and product flow analysis of 127 commercially harvested trees up to the exit gate of sawmills and interaction with sawmill owners and forest managers reveal that: (1) Queensland selective logging has less volume recovery (52.8%) compared to Nepal (94.5%) leaving significant utilizable volume in the forest, (2) Stump volume represents 5.5% of total timber volume in Nepal and 3.9% in Queensland with an average stump height of 43.3 cm and 40.1 cm in Nepal and Queensland respectively, (3) Average sawn timber output from the harvested logs is 36.3% in Queensland against 61% in Nepal, (4) Nepal and Queensland leave 0.186 Mg C m−3 and 0.718 Mg C m−3 on the forest floor respectively, (5) Each harvested tree damages an average of five plant species in Nepal and four in Queensland predominantly seedlings in both sites, and (6) Overall logging related total emissions in Queensland are more than double (1.099 Mg C m−3) those in Nepal (0.488 Mg C m−3). We compared these results with past studies and speculated on possible reasons for and potential implications of these results for sustainable forest management and reducing emissions from deforestation and forest degradation.
Mineral Elements in the Raw Milk of Several Dairy Farms in the Province of Alberta
Authors: Zwierzchowski Grzegorz , Ametaj Burim N.
Published: August 2019

The objective of this study was to determine the concentrations of 20 minerals in the whole raw milk from Holstein dairy cows in the province of Alberta, Canada. A total of 156 milk samples were collected from 26 dairy farms (n = 6 per farm) and analyzed with inductively coupled plasma mass spectrometry (ICP-MS) for five macrominerals (Ca, Mg, P, K, and Na), ten microminerals (Bo, Co, Cu, Fe, Mn, Mo, Ru, Se, St, and Zn), and five heavy metals (Al, As, Cd, Cr, and Pb). Calculated means were compared with their recommended daily intakes (RDIs) or minimal risk levels (MRLs) obtained from several food safety agencies and with data obtained from a world meta-analytical study we conducted previously. Results of the present study showed differences in the concentrations of multiple minerals between the Alberta farms involved and world averages (WA) and within Alberta farms. Concentrations of macrominerals, including Ca, Mg, P, K, and Na, in the raw milk were greater in Alberta dairy farms than the WA (p < 00.5; except Ca). Of note, concentrations of Ca showed the highest variability among Alberta farms, with 11 farms having lower milk Ca than WA. The other macrominerals were higher than WA in more than 88% of Alberta farms. Data demonstrated that concentrations of microminerals, including Co, Cu, Fe, Mn, and Mo, in Alberta raw milk were lower compared with WA (p < 0.05). Selenium was the only element in raw milk that was found to have higher concentrations in all farms in Alberta vs. WA. High variability was observed for B, Sr, and Zn, which were lower in multiple locations around the province. Concentrations of heavy metals in the Alberta raw milk, including Al, As, Cd, and Pb, were lower than WA, whereas concentrations of Cr were higher. Most importantly, all heavy metals were below their respective MRLs in all analyzed samples. Overall, data from this study showed that raw milk from Holstein dairy cows in Alberta has concentrations of most mineral elements below their MRLs and some of them different from WA. Of note, although concentrations of Se and Zn in the raw milk were higher in Alberta compared with WA, their concentrations were still below their respective MRLs.
Investigation of Relationship Between Spatial Distribution of Medical Equipment and Preventable Mortality
Authors: Gavurova Beata , Tucek David , Kovac Viliam
Published: August 2019

The aim of the study is to investigate the relationship between the spatial distribution of the selected medical equipment and the preventable mortality rate in the regions of the Slovak Republic. The main analytical approach is carried out through the cluster analysis based on a Euclidean distance technique in order to get similarity of the administrative divisions in form of a district and a pseudot2 approach aimed at the determination of a number of the districts in a cluster. A number of medical equipment had a rising tendency from the year 2008. The most extreme position according to a localisation distribution of the computed tomographs and the magnetic resonance imaging scanners is held by the Košice IV District at the level of 7.50630. From an angle of view of the preventable mortality, the Piešťany District holds the most extreme position peaking at the level of 10.97969 for the female sex and the Kežmarok District with the value of 9.44088. The study has the significant dissemination outputs for health policy interventions, especially to draw up regional health plans for computed tomography and magnetic resonance imaging deployment, mainly in locations with a high preventable mortality rate for both sexes.
Associations between School Food Environments, Body Mass Index and Dietary Intakes among Regional School Students in Victoria, Australia: A Cross-Sectional Study
Authors: Alston Laura , Crooks Nicholas , Strugnell Claudia , Orellana Liliana , Allender Steven , Rennie Claire , Nichols Melanie
Published: August 2019

(1) Background: Childhood overweight and obesity is a significant and preventable problem worldwide. School environments have been suggested to be plausible targets for interventions seeking to improve the quality of children’s dietary intake. The objective of this study was to determine the extent to which the current characteristics of the school food environment were associated with primary school students’ dietary intake and Body Mass Index (BMI) z scores in a representative sample in regional Victoria. (2) Methods: This study included 53 schools, comprising a sample of 3,496 students in year levels two (aged 7–8 years), four (9–10 years) and six (11–12 years). Year four and six students completed dietary questionnaires. Principals from each school completed a survey on school food environment characteristics. Mixed-effects logistic regression was used to assess the relationship between students’ dietary intake and school food environment scores, controlling for confounders such as socio-economic status, school size and sex. Food environment scores were also analysed against the odds of being healthy weight (defined as normal BMI z score). (3) Results: Mixed associations were found for the relationship between students’ dietary intake and food environment scores. Meeting the guidelines for vegetable intake was not associated with food environment scores, but students were more likely (OR: 1.68 95% CI 1.26, 2.24) to meet the guidelines if they attended a large school (>300 enrolments) and were female (OR: 1.28 95% CI: 1.02, 1.59). Healthy weight was not associated with school food environment scores, but being a healthy weight was significantly associated with less disadvantage (OR: 1.24 95% CI 1.05, 1.45). Conclusion: In this study, the measured characteristics of school food environments did not have strong associations with dietary intakes or BMI among students.
Did E-Cigarette Users Notice the New European Union’s E-Cigarette Legislation? Findings from the 2015–2017 International Tobacco Control (ITC) Netherlands Survey
Authors: van Mourik Dirk-Jan A. , Nagelhout Gera E. , van den Putte Bas , Hummel Karin , Willemsen Marc C. , de Vries Hein
Published: August 2019

This study examined to what extent e-cigarette users noticed the European Union’s new legislation regarding e-cigarettes, and whether this may have influenced perceptions regarding addictiveness and toxicity. Data were obtained from yearly surveys (2015–2017) of the International Tobacco Control (ITC) Netherlands Survey. Descriptive statistics and Generalized Estimating Equations were applied. About a third of the e-cigarette users noticed the text warning (28%) and the leaflet (32%). When compared to tobacco-only smokers, e-cigarette users showed greater increases in perceptions regarding addictiveness (β = 0.457, p = 0.045 vs. β = 0.135, p < 0.001) and toxicity (β = 0.246, p = 0.055 vs. β = 0.071, p = 0.010). In conclusion, the new legislation’s noticeability should be increased.
How Do Coworkers Aid in Coping with Emotional Exhaustion? An Experience Sampling Method Approach
Authors: Xiu Jing , Zhang Zhenduo , Li Zhigang , Zheng Junwei
Published: August 2019

The present study emphasizes the indirect influences of coworker helping behavior on emotional exhaustion through psychological availability and the moderating role of perceived task demands on a daily basis. Using a two-wave experience sampling method with data collected via mobile phones, we collected 345 matched data from 69 samples over five consecutive days in mainland China. We developed a moderated mediation model to test our conceptual model, with the following significant results: (1) Daily coworker helping behavior decreased employee emotional exhaustion; (2) daily psychological availability mediated the influence of coworker helping behavior on employee emotional exhaustion; (3) through psychological availability, perceived task demands moderated the indirect influence of daily coworker helping behavior on emotional exhaustion. The indirect influence of daily coworker helping behavior only emerged with a low perception of job demands. This research explores the mechanism and boundary conditions of the relationship between daily coworker helping behavior and employee emotional exhaustion with the job demands-resources model framework. In practice, leaders should adopt beneficial interventions to enhance team cohesion, to facilitate team members’ helping behavior, and to manage task demands.
Residential Wood Combustion in Finland: PM2.5 Emissions and Health Impacts with and without Abatement Measures
Authors: Savolahti Mikko , Lehtomäki Heli , Karvosenoja Niko , Paunu Ville-Veikko , Korhonen Antti , Kukkonen Jaakko , Kupiainen Kaarle , Kangas Leena , Karppinen Ari , Hänninen Otto
Published: August 2019

Exposure to fine particles in ambient air has been estimated to be one of the leading environmental health risks in Finland. Residential wood combustion is the largest domestic source of fine particles, and there is increasing political interest in finding feasible measures to reduce those emissions. In this paper, we present the PM2.5 emissions from residential wood combustion in Finland, as well as the resulting concentrations. We used population-weighed concentrations in a 250 × 250 m grid as population exposure estimates, with which we calculated the disease burden of the emissions. Compared to a projected baseline scenario, we studied the effect of chosen reduction measures in several abatement scenarios. In 2015, the resulting annual average concentrations were between 0.5 and 2 µg/m3 in the proximity of most cities, and disease burden attributable to residential wood combustion was estimated to be 3400 disability-adjusted life years (DALY) and 200 deaths. Disease burden decreased by 8% in the 2030 baseline scenario and by an additional 63% in the maximum feasible reduction scenario. Informational campaigns and improvement of the sauna stove stock were assessed to be the most feasible abatement measures to be implemented in national air quality policies.