bluuebunny/crossref_metadata_2025 huggingface dataset:
RNA Sequencing of Collecting Duct Renal Cell Carcinoma Suggests an Interaction between miRNA and Target Genes and a Predominance of Deregulated Solute Carrier Genes
Authors: Wach Sven , Taubert Helge , Weigelt Katrin , Hase Nora , Köhn Marcel , Misiak Danny , Hüttelmaier Stefan , Stöhr Christine G. , Kahlmeyer Andreas , Haller Florian , Vera Julio , Hartmann Arndt , Wullich Bernd , Lai Xin
Published: December 2019

Collecting duct carcinoma (CDC) is a rare renal cell carcinoma subtype with a very poor prognosis. There have been only a few studies on gene expression analysis in CDCs. We compared the gene expression profiles of two CDC cases with those of eight normal tissues of renal cell carcinoma patients. At a threshold of |log2fold-change| ≥1, 3349 genes were upregulated and 1947 genes were downregulated in CDCs compared to the normal samples. Pathway analysis of the deregulated genes revealed that cancer pathways and cell cycle pathways were most prominent in CDCs. The most upregulated gene was keratin 17, and the most downregulated gene was cubilin. Among the most downregulated genes were four solute carrier genes (SLC3A1, SLC9A3, SLC26A7, and SLC47A1). The strongest negative correlations between miRNAs and mRNAs were found between the downregulated miR-374b-5p and its upregulated target genes HIST1H3B, HK2, and SLC7A11 and between upregulated miR-26b-5p and its downregulated target genes PPARGC1A, ALDH6A1, and MARC2. An upregulation of HK2 and a downregulation of PPARGC1A, ALDH6A1, and MARC2 were observed at the protein level. Survival analysis of the cancer genome atlas (TCGA) dataset showed for the first time that low gene expression of MARC2, cubilin, and SLC47A1 and high gene expression of KRT17 are associated with poor overall survival in clear cell renal cell carcinoma patients. Altogether, we identified dysregulated protein-coding genes, potential miRNA-target interactions, and prognostic markers that could be associated with CDC.
Current Strategies to Target Tumor-Associated-Macrophages to Improve Anti-Tumor Immune Responses
Authors: Anfray Clément , Ummarino Aldo , Andón Fernando Torres , Allavena Paola
Published: December 2019

: Established evidence demonstrates that tumor-infiltrating myeloid cells promote rather than stop-cancer progression. Tumor-associated macrophages (TAMs) are abundantly present at tumor sites, and here they support cancer proliferation and distant spreading, as well as contribute to an immune-suppressive milieu. Their pro-tumor activities hamper the response of cancer patients to conventional therapies, such as chemotherapy or radiotherapy, and also to immunotherapies based on checkpoint inhibition. Active research frontlines of the last years have investigated novel therapeutic strategies aimed at depleting TAMs and/or at reprogramming their tumor-promoting effects, with the goal of re-establishing a favorable immunological anti-tumor response within the tumor tissue. In recent years, numerous clinical trials have included pharmacological strategies to target TAMs alone or in combination with other therapies. This review summarizes the past and current knowledge available on experimental tumor models and human clinical studies targeting TAMs for cancer treatment.
Specific Upregulation of TRPC1 and TRPC5 Channels by Mineralocorticoid Pathway in Adult Rat Ventricular Cardiomyocytes
Authors: Bartoli Fiona , Moradi Bachiller Soraya , Antigny Fabrice , Bedouet Kaveen , Gerbaud Pascale , Sabourin Jessica , Benitah Jean-Pierre
Published: December 2019

Whereas cardiac TRPC (transient receptor potential canonical) channels and the associated store-operated Ca2+ entry (SOCE) are abnormally elevated during cardiac hypertrophy and heart failure, the mechanism of this upregulation is not fully elucidated but might be related to the activation of the mineralocorticoid pathway. Using a combination of biochemical, Ca2+ imaging, and electrophysiological techniques, we determined the effect of 24-h aldosterone treatment on the TRPCs/Orai-dependent SOCE in adult rat ventricular cardiomyocytes (ARVMs). The 24-h aldosterone treatment (from 100 nM to 1 µM) enhanced depletion-induced Ca2+ entry in ARVMs, as assessed by a faster reduction of Fura-2 fluorescence decay upon the addition of Mn2+ and increased Fluo-4/AM fluorescence following Ca2+ store depletion. These effects were prevented by co-treatment with a specific mineralocorticoid receptor (MR) antagonist, RU-28318, and they are associated with the enhanced depletion-induced N-[4-[3,5-Bis(trifluoromethyl)-1H-pyrazol-1-yl]phenyl]-4-methyl-1,2,3-thiadiazole-5-carboxamide (BTP2)-sensitive macroscopic current recorded by patch-clamp experiments. Molecular screening by qRT-PCR and Western blot showed a specific upregulation of TRPC1, TRPC5, and STIM1 expression at the messenger RNA (mRNA) and protein levels upon 24-h aldosterone treatment of ARVMs, corroborated by immunostaining. Our study provides evidence that the mineralocorticoid pathway specifically promotes TRPC1/TRPC5-mediated SOCE in adult rat cardiomyocytes.
The Mitotic Apparatus and Kinetochores in Microcephaly and Neurodevelopmental Diseases
Authors: Degrassi Francesca , Damizia Michela , Lavia Patrizia
Published: December 2019

Regulators of mitotic division, when dysfunctional or expressed in a deregulated manner (over- or underexpressed) in somatic cells, cause chromosome instability, which is a predisposing condition to cancer that is associated with unrestricted proliferation. Genes encoding mitotic regulators are growingly implicated in neurodevelopmental diseases. Here, we briefly summarize existing knowledge on how microcephaly-related mitotic genes operate in the control of chromosome segregation during mitosis in somatic cells, with a special focus on the role of kinetochore factors. Then, we review evidence implicating mitotic apparatus- and kinetochore-resident factors in the origin of congenital microcephaly. We discuss data emerging from these works, which suggest a critical role of correct mitotic division in controlling neuronal cell proliferation and shaping the architecture of the central nervous system.
Atherosclerosis and the Capillary Network; Pathophysiology and Potential Therapeutic Strategies
Authors: Ziegler Tilman , Abdel Rahman Farah , Jurisch Victoria , Kupatt Christian
Published: December 2019

Atherosclerosis and associated ischemic organ dysfunction represent the number one cause of mortality worldwide. While the key drivers of atherosclerosis, arterial hypertension, hypercholesterolemia and diabetes mellitus, are well known disease entities and their contribution to the formation of atherosclerotic plaques are intensively studied and well understood, less effort is put on the effect of these disease states on microvascular structure an integrity. In this review we summarize the pathological changes occurring in the vascular system in response to prolonged exposure to these major risk factors, with a particular focus on the differences between these pathological alterations of the vessel wall in larger arteries as compared to the microcirculation. Furthermore, we intend to highlight potential therapeutic strategies to improve microvascular function during atherosclerotic vessel disease.
Dampened Slow Oscillation Connectivity Anticipates Amyloid Deposition in the PS2APP Mouse Model of Alzheimer’s Disease
Authors: Leparulo Alessandro , Mahmud Mufti , Scremin Elena , Pozzan Tullio , Vassanelli Stefano , Fasolato Cristina
Published: December 2019

To fight Alzheimer’s disease (AD), we should know when, where, and how brain network dysfunctions initiate. In AD mouse models, relevant information can be derived from brain electrical activity. With a multi-site linear probe, we recorded local field potentials simultaneously at the posterior-parietal cortex and hippocampus of wild-type and double transgenic AD mice, under anesthesia. We focused on PS2APP (B6.152H) mice carrying both presenilin-2 (PS2) and amyloid precursor protein (APP) mutations, at three and six months of age, before and after plaque deposition respectively. To highlight defects linked to either the PS2 or APP mutation, we included in the analysis age-matched PS2.30H and APP-Swedish mice, carrying each of the mutations individually. Our study also included PSEN2−/− mice. At three months, only predeposition B6.152H mice show a reduction in the functional connectivity of slow oscillations (SO) and in the power ratio between SO and delta waves. At six months, plaque-seeding B6.152H mice undergo a worsening of the low/high frequency power imbalance and show a massive loss of cortico-hippocampal phase-amplitude coupling (PAC) between SO and higher frequencies, a feature shared with amyloid-free PS2.30H mice. We conclude that the PS2 mutation is sufficient to impair SO PAC and accelerate network dysfunctions in amyloid-accumulating mice.
Ca2+ Channels Mediate Bidirectional Signaling between Sarcolemma and Sarcoplasmic Reticulum in Muscle Cells
Authors: Avila Guillermo , de la Rosa Juan A. , Monsalvo-Villegas Adrián , Montiel-Jaen María G.
Published: December 2019

The skeletal muscle and myocardial cells present highly specialized structures; for example, the close interaction between the sarcoplasmic reticulum (SR) and mitochondria—responsible for excitation-metabolism coupling—and the junction that connects the SR with T-tubules, critical for excitation-contraction (EC) coupling. The mechanisms that underlie EC coupling in these two cell types, however, are fundamentally distinct. They involve the differential expression of Ca2+ channel subtypes: CaV1.1 and RyR1 (skeletal), vs. CaV1.2 and RyR2 (cardiac). The CaV channels transform action potentials into elevations of cytosolic Ca2+, by activating RyRs and thus promoting SR Ca2+ release. The high levels of Ca2+, in turn, stimulate not only the contractile machinery but also the generation of mitochondrial reactive oxygen species (ROS). This forward signaling is reciprocally regulated by the following feedback mechanisms: Ca2+-dependent inactivation (of Ca2+ channels), the recruitment of Na+/Ca2+ exchanger activity, and oxidative changes in ion channels and transporters. Here, we summarize both well-established concepts and recent advances that have contributed to a better understanding of the molecular mechanisms involved in this bidirectional signaling.
CXCL5 Modified Nanoparticle Surface Improves CXCR2+ Cell Selective Internalization
Authors: Cagliani Roberta , Gatto Francesca , Cibecchini Giulia , Marotta Roberto , Catalano Federico , Sanchez-Moreno Paola , Pompa Pier Paolo , Bardi Giuseppe
Published: December 2019

Driving nanomaterials to specific cell populations is still a major challenge for different biomedical applications. Several strategies to improve cell binding and uptake have been tried thus far by intrinsic material modifications or decoration with active molecules onto their surface. In the present work, we covalently bound the chemokine CXCL5 on fluorescently labeled amino-functionalized SiO2 nanoparticles to precisely targeting CXCR2+ immune cells. We synthesized and precisely characterized the physicochemical features of the modified particles. The presence of CXCL5 on the surface was detected by z-potential variation and CXCL5-specific electron microscopy immunogold labeling. CXCL5-amino SiO2 nanoparticle cell binding and internalization performances were analyzed in CXCR2+ THP-1 cells by flow cytometry and confocal microscopy. We showed improved internalization of the chemokine modified particles in the absence or the presence of serum. This internalization was reduced by cell pre-treatment with free CXCL5. Furthermore, we demonstrated CXCR2+ cell preferential targeting by comparing particle uptake in THP-1 vs. low-CXCR2 expressing HeLa cells. Our results provide the proof of principle that chemokine decorated nanomaterials enhance uptake and allow precise cell subset localization. The possibility to aim at selective chemokine receptor-expressing cells can be beneficial for the diverse pathological conditions involving immune reactions.
Dislocation Reaction Mechanism for Enhanced Strain Hardening in Crystal Nano-Indentations
Authors: Armstrong Ronald W. , Elban Wayne L.
Published: December 2019

Stress–strain calculations are presented for nano-indentations made in: (1) an ammonium perchlorate (AP), NH4ClO4, {210} crystal surface; (2) an α-iron (111) crystal surface; (3) a simulated test on an α-iron (100) crystal surface. In each case, the calculation of an exceptionally-enhanced plastic strain hardening, beyond that coming from the significant effect of small dislocation separations in the indentation deformation zone, is attributed to the formation of dislocation reaction obstacles hindering further dislocation movement. For the AP crystal, the exceptionally-high dislocation reaction-based strain hardening, relative to the elastic shear modulus, leads to (001) cleavage cracking in nano-, micro- and macro-indentations. For α-iron, the reaction of (a/2) <111> dislocations to form a [010] Burgers vector dislocation obstacles at designated {110} slip system intersections accounts for a higher strain hardening in both experimental and simulated nano-indentation test results. The α-iron stress–strain calculations are compared, both for the elastic deformation and plastic strain hardening of nano-indented (100) versus (111) crystal surfaces and include important observations derived from internally-tracked (a/2) <010> Burgers vector dislocation structures obtained in simulation studies. Additional comparisons are made between the α-iron calculations and other related strength properties reported either for bulk, micro-pillar, or additional simulated nano-crystal or heavily-drawn polycrystalline wire materials.
Disentangling the Effects of Disturbance from Those of Dominant Tall Grass Features in Driving the Functional Variation of Restored Grassland in a Sub-Mediterranean Context
Authors: Bricca Alessandro , Tardella Federico Maria , Tolu Fabio , Goia Irina , Ferrara Arianna , Catorci Andrea
Published: December 2019

Land abandonment in sub-Mediterranean grasslands causes the spread of tall-grasses, affecting biodiversity and ecosystem functioning. Mowing allows the recovery of the coenological composition after invasion, but the mechanisms acting at the fine-scale are poorly investigated. Since 2010 in the Central Apennines, we fenced a grassland invaded by Brachypodium rupestre, divided it into two areas, half of each was mowed biyearly and half remained unmown. In 2017 we selected ten 20 × 20 cm experimental units per half-area, collecting data on species occurrences, plant traits, B. rupestre height and phytomass. We used generalized linear mixed-effect modelling to disentangle the role of mowing from the impact of B. rupestre features in driving the community functional variations. Mowing was the main driver in the recovery process, acting as an abiotic filter (enhancement of tolerance-avoidance strategies). Furthermore, the reduction of weaker competitor exclusion processes fostered the increase of functional variation between coexisting species. Both drivers acted on different plant traits (e.g., mowing on life span, vegetative propagation types and plant height, mowing and B. rupestre features on space occupation types, seed mass and leaf anatomy), generally enhancing the extent of functional strategies related to resource acquisition and storage, reproduction, space occupation and temporal niche exploitation.
Flavivirus Cross-Reactivity to Dengue Nonstructural Protein 1 Antigen Detection Assays
Authors: Tan Li Kiang , Wong Wing Yan , Yang Hui Ting , Huber Roland G. , Bond Peter J. , Ng Lee Ching , Maurer-Stroh Sebastian , Hapuarachchi Hapuarachchige Chanditha
Published: December 2019

Dengue virus (DENV) and Zika virus (ZIKV) are flaviviruses of public health relevance. Both viruses circulate in the same endemic settings and acute infections generally manifest similar symptoms. This highlights the importance of accurate diagnosis for clinical management and outbreak control. One of the commonly used acute diagnostic markers for flaviviruses is nonstructural protein 1 (NS1). However, false positives due to antigenic cross-reactivity have been reported between DENV and ZIKV infections when using DENV NS1 antigen (NS1 Ag) detection assays in acute cases. Therefore, we investigated the lowest detectable virus titres and cross-reactivity of three commercial dengue NS1 Ag rapid assays and two ELISAs for different flaviviruses. Our results showed that substantially high viral titres of ZIKV, Kunjin virus (KUNV) and yellow fever virus (YFV) are required to give false-positive results when using DENV NS1 rapid detection assays. Commercial DENV NS1 ELISAs did not react with ZIKV and YFV. In comparison, tested assays detected DENV at a significantly low virus titre. Given the relatively low viral loads reported in clinical samples, our findings suggest that commercially available dengue NS1 Ag detection assays are less likely to generate false-positive results among clinical samples in areas where multiple flaviviruses cocirculate.
The Capacity of Periodontal Gel to Occupy the Spaces Inside the Periodontal Pockets Using Computational Fluid Dynamic
Authors: Levrini Luca , Paracchini Luigi , Nosotti Maria Giulia
Published: December 2019

The aim of the current work is to demonstrate the capacity of a new periodontal gel to occupy the spaces inside the periodontal pockets through Computational Fluid Dynamic (CFD). The test gel consists of two resorbable medical grade polymers (PEO, Poly Ethylen Oxide and HPMC, Hydroxy Propyl Metyl Cellulose), Type I Collagen, SAP (Vitamin C), and PBS (Saline Solution), while the control gel is 14% doxyclin controlled release gel, which is used for treating periodontal pockets with probing ≥5 mm after scaling and root plaining. The study examined the fluid dynamic analysis (Computational Fluid Dynamic—CFD) of two different gels, used in dentistry to treat periodontitis, in relation to both the geometry of the periodontal pocket and the function of two different types of needles that are used to distribute the preparation. The periodontal pocket was determined by reading DICOM images taken from the patient’s CAT scan. The results show that the H42® gel comes out uniformly compared to the other gel. Moreover, it is possible to observe how the rheological properties of the gel allow the fluid to spread evenly within the periodontal pocket in relation to the geometry of the needle. In particular, H42® gel exits in a constant way both from the first and the second exit. In fact, it was observed that by changing the geometry of the needle or the type of periodontal gel, the distribution of the gel inside the pocket was no longer homogeneous. Thus, having the correct rheological properties and correct needle geometries both speeds up the gel and optimizes the pressure distribution. Currently, the literature is still lacking, therefore further studies will be needed to confirm these results.
Quantum Information and Foundations
Authors: D’Ariano Giacomo Mauro , Perinotti Paolo
Published: December 2019

The new era of quantum foundations, fed by the quantum information theory experience and opened in the early 2000s by a series of memorable papers [...]
Continuous Variables Graph States Shaped as Complex Networks: Optimization and Manipulation
Authors: Sansavini Francesca , Parigi Valentina
Published: December 2019

Complex networks structures have been extensively used for describing complex natural and technological systems, like the Internet or social networks. More recently, complex network theory has been applied to quantum systems, where complex network topologies may emerge in multiparty quantum states and quantum algorithms have been studied in complex graph structures. In this work, we study multimode Continuous Variables entangled states, named cluster states, where the entanglement structure is arranged in typical real-world complex networks shapes. Cluster states are a resource for measurement-based quantum information protocols, where the quality of a cluster is assessed in terms of the minimal amount of noise it introduces in the computation. We study optimal graph states that can be obtained with experimentally realistic quantum resources, when optimized via analytical procedure. We show that denser and regular graphs allow for better optimization. In the spirit of quantum routing, we also show the reshaping of entanglement connections in small networks via linear optics operations based on numerical optimization.
A New Fuzzy Logic Classifier Based on Multiscale Permutation Entropy and Its Application in Bearing Fault Diagnosis
Authors: Du Wenhua , Guo Xiaoming , Wang Zhijian , Wang Junyuan , Yu Mingrang , Li Chuanjiang , Wang Guanjun , Wang Longjuan , Guo Huaichao , Zhou Jinjie , Shao Yanjun , Xue Huiling , Yao Xingyan
Published: December 2019

The self-organizing fuzzy (SOF) logic classifier is an efficient and non-parametric classifier. Its classification process is divided into an offline training stage, an online training stage, and a testing stage. Representative samples of different categories are obtained through the first two stages, and these representative samples are called prototypes. However, in the testing stage, the classification of testing samples is completely dependent on the prototype with the maximum similarity, without considering the influence of other prototypes on the classification decision of testing samples. Aiming at the testing stage, this paper proposed a new SOF classifier based on the harmonic mean difference (HMDSOF). In the testing stage of HMDSOF, firstly, each prototype was sorted in descending order according to the similarity between each prototype in the same category and the testing sample. Secondly, multiple local mean vectors of the prototypes after sorting were calculated. Finally, the testing sample was classified into the category with the smallest harmonic mean difference. Based on the above new method, in this paper, the multiscale permutation entropy (MPE) was used to extract fault features, linear discriminant analysis (LDA) was used to reduce the dimension of fault features, and the proposed HMDSOF was further used to classify the features. At the end of this paper, the proposed fault diagnosis method was applied to the diagnosis examples of two groups of different rolling bearings. The results verify the superiority and generalization of the proposed fault diagnosis method.
Adapted or Adaptable: How to Manage Entropy Production?
Authors: Goupil Christophe , Herbert Eric
Published: December 2019

Adaptable or adapted? Whether it is a question of physical, biological, or even economic systems, this problem arises when all these systems are the location of matter and energy conversion. To this interdisciplinary question, we propose a theoretical framework based on the two principles of thermodynamics. Considering a finite time linear thermodynamic approach, we show that non-equilibrium systems operating in a quasi-static regime are quite deterministic as long as boundary conditions are correctly defined. The Novikov–Curzon–Ahlborn derivation applied to non-endoreversible systems then makes it possible to precisely determine the conditions for obtaining characteristic operating points. As a result, power maximization principle (MPP), entropy minimization principle (mEP), efficiency maximization, or waste minimization states are only specific modalities of system operation. We show that boundary conditions play a major role in defining operating points because they define the intensity of the feedback that ultimately characterizes the operation. Armed with these thermodynamic foundations, we show that the intrinsically most efficient systems are also the most constrained in terms of controlling the entropy and dissipation production. In particular, we show that the best figure of merit necessarily leads to a vanishing production of power. On the other hand, a class of systems emerges, which, although they do not offer extreme efficiency or power, have a wide range of use and therefore marked robustness. It therefore appears that the number of degrees of freedom of the system leads to an optimization of the allocation of entropy production.
Machine Learning-Based Driving Style Identification of Truck Drivers in Open-Pit Mines
Authors: Wang Qun , Zhang Ruixin , Wang Yangting , Lv Shuaikang
Published: December 2019

The significance in constructing a driving style identification model for open-pit mine truck drivers is to reduce diesel consumption and improve training. First, we developed a driving behavior and mining truck condition monitoring system for an open-pit mine. Under heavy-load and no-load conditions of a mining truck, based on the same experimental truck and haulage road, the data of driving behavior and truck status of different drivers were collected. The driving style characteristic parameters of mining trucks under heavy-load and no-load conditions were constructed through Pearson correlation analysis. Using a k-means clustering algorithm, driving style can be divided into three types: normal type, soft type, and aggressive type, and we verified the validity of this driving style classification with a box plot. On this basis, the parameters of random forest, k-nearest neighbor, support vector machine, and neural network models were optimized and the accuracy was compared through a cross-validation grid search, and then a driving style identification model based on the random forest method was finally proposed. Driving style parameter weight values were obtained based on the Gini coefficient. Last, the fuel consumption characteristics of different driving styles were calculated. The results show that the driving style identification models based on random forest can effectively identify different driving styles when the mining truck is operating under heavy load and no load, and the overall accuracy of the model is 95.39% and 90.74% respectively. The fuel consumption of the aggressive driving style was the largest and was 10% higher than the average fuel consumption. The research results provide data support and new ideas for operation training and fuel-saving driving of mining trucks in open-pit mines.
Experimental and Numerical Study on the Cooling Performance of Fins and Metal Mesh Attached on a Photovoltaic Module
Authors: Kim Jaemin , Bae Sangmu , Yu Yongdong , Nam Yujin
Published: December 2019

The electrical efficiency and durability of a photovoltaic (PV) cell degrades as its temperature increases. Accordingly, there have been continued efforts to control the cell temperature by cooling the PV module. Generally, passive PV cooling using heat sinks attached on the back of the PV module can improve the electrical efficiency. However, few experimental studies have evaluated the effect of the heat sink shape on PV cooling. Therefore, this study proposed a passive cooling technology using meshes made of iron and aluminum, and performed indoor tests using a solar simulator to analyze the cooling performance. The experimental results demonstrated that iron and aluminum meshes reduced the PV module temperature by approximately 4.35 °C and 6.56 °C, respectively. Additionally, numerical studies were performed using a computational fluid dynamics (CFD) simulation to compare the cooling fins and meshes. The numerical results showed that the cooling fins exhibited a better cooling performance than the metal mesh. However, meshes can be mass-produced and have a high structural stability against wind loads. Meshes are more likely be applied to PV systems than cooling fins if adhesion were improved.
A New Hybrid Short-Term Interval Forecasting of PV Output Power Based on EEMD-SE-RVM
Authors: Wang Sen , Sun Yonghui , Zhou Yan , Jamil Mahfoud Rabea , Hou Dongchen
Published: December 2019

The main characteristics of the photovoltaic (PV) output power are the randomness and uncertainty, such features make it not easy to establish an accurate forecasting method. The accurate short-term forecasting of PV output power has great significance for the stability, safe operation and economic dispatch of the power grid. The deterministic point forecast method ignores the randomness and volatility of PV output power. Aiming at overcoming those defects, this paper proposes a novel hybrid model for short-term PV output power interval forecasting based on ensemble empirical mode decomposition (EEMD) as well as relevance vector machine (RVM). Firstly, the EEMD is used to decompose the PV output power sequences into several intrinsic mode functions (IMFs) and residual (RES) components. After that, based on the decomposed components, the sample entropy (SE) algorithm is utilized to reconstruct those components where three new components with typical characteristics are obtained. Then, by implementing RVM, the forecasting model for every component is developed. Finally, the forecasting results of every new component are superimposed in order to achieve the overall forecasting results with certain confidence level. Simulation results demonstrate, by comparing them with some previous methods, that the hybrid method based on EEMD-SE-RVM has relatively higher forecasting accuracy, more reliable forecasting interval and high engineering application value.
Technology Development of Electric Vehicles: A Review
Authors: Sun Xiaoli , Li Zhengguo , Wang Xiaolin , Li Chengjiang
Published: December 2019

To reduce the dependence on oil and environmental pollution, the development of electric vehicles has been accelerated in many countries. The implementation of EVs, especially battery electric vehicles, is considered a solution to the energy crisis and environmental issues. This paper provides a comprehensive review of the technical development of EVs and emerging technologies for their future application. Key technologies regarding batteries, charging technology, electric motors and control, and charging infrastructure of EVs are summarized. This paper also highlights the technical challenges and emerging technologies for the improvement of efficiency, reliability, and safety of EVs in the coming stages as another contribution.
Characteristics of Roof Ground Subsidence While Applying a Continuous Excavation Continuous Backfill Method in Longwall Mining
Authors: Yu Yihe , Ma Liqiang , Zhang Dongsheng
Published: December 2019

Activities of traditional longwall mining will result in ground subsidence and therefore cause issues such as damages to buildings and farmlands, water pollution and loss, and potential ecological and environmental problems in the mining region. With advantages of the longwall backfill mining method, as well as the room and pillar mining method, a continuous excavation and continuous backfill (CECB) method in longwall mining is recommended to effectively control the ground subsidence. In this method, mining roadways (MRs) are initially planned in a panel, and then they are excavated and backfilled in several stages until the whole panel is mined out and backfilled. According to the geologic conditions of an underground coal mine, and the elastic foundation beam theory, a mechanical model was built to study the subsidence of the roof while using this new mining method. In addition, methods to calculate roof subsidence in various stages in CECB were also provided. The mechanical parameters of backfilling materials, which were used in the theoretical calculation and the numerical analysis for mutual check, were defined through analyzing the stability conditions of the coal pillars and the filling bodies. The control effect for the ground subsidence of using the newly proposed mining method was analyzed based on both simulation results and site monitoring results, including the ground subsidence, horizontal displacement, tilt, curvature and horizontal strain. This research could provide suggestions to effectively control ground subsidence for a mine site with similar geologic conditions.
Long-Term Temperature Evaluation of a Ground-Coupled Heat Pump System Subject to Groundwater Flow
Authors: Jaziri Nehed , Raymond Jasmin , Giordano Nicoló , Molson John
Published: December 2019

The performance of ground-coupled heat pump systems (GCHPs) operating under significant groundwater flow can be difficult to predict due to advective heat transfer in the subsurface. This is the case of the Carignan-Salières elementary school located on the south shore of the St. Lawrence River near Montréal, Canada. The building is heated and cooled with a GCHP system including 31 boreholes subject to varying groundwater flow conditions due to the proximity of an active quarry being irregularly dewatered. A study with the objective of predicting the borehole temperatures in order to anticipate potential operational problems was conducted, which provided an opportunity to evaluate the impact of groundwater flow. For this purpose, a numerical model was calibrated using a full-scale heat injection test and then run under different scenarios for a period of twenty years. The heat exchange capacity of the GCHP system is clearly enhanced by advection when the Darcy flux changes from 6 × 10−8 m s−1 (no dewatering) to 8 × 10−7 m s−1 (high dewatering). This study further suggests that even the lowest groundwater flow condition can be beneficial to avoid a progressive cooling of the subsurface due to the unbalanced building loads, which can have important impacts for design of new systems.
Capacitated Multicommodity Flow Problem for Heterogeneous Smart Electricity Metering Communications Using Column Generation
Authors: Inga Esteban , Hincapié Roberto , Céspedes Sandra
Published: December 2019

This paper addresses the planning and deployment of wireless heterogeneous networks (WHNs) for smart metering, based on a cross-layer solution. We combine the constraints of the network layer that considers routing and flow demands at each link in the WHN, while at the same time, we account for the restrictions of the physical layer referred to the capacity of a short range technology when used in a multi-hop fashion. We propose a model based on a column generation approach to solve the capacitated multicommodity flow problem (CMCF); the model includes wireless links capacities, coverage, and cost. The work integrates the multi-hop routing of packets in a mesh network formed by smart meters and concentrators connected to a cellular network via base stations. The traffic of each link is represented in a multigraph with the occupation percentage, and we build a scalable routing tree on a georeferenced map to represent a real deployment. The results describe the behavior of the proposed model in terms of the traffic load per concentrator, the network coverage, and the reduction of energy consumption. We demonstrate that an infrastructure cost reduction is achieved with the inclusion of multi-hop short range technology, which reduces the number of smart meters that require a direct connection to cellular technology. The model guarantees 100% coverage of the smart meters analyzed in each scenario. The calculation time of the CMCF for advanced metering infrastructure (CMCF-AMI) based on the column generation algorithm as the population increases is reduced by 10%, and this is the expected return when the population is considerable.
Optimal Management of Combined-Cycle Gas Units with Gas Storage under Uncertainty
Authors: Gómez-Villarreal Hernán , Carrión Miguel , Domínguez Ruth
Published: December 2019

We formulated a problem faced by a power producer who owns a combined-cycle gas turbine (CCGT) and desires to maximize its expected profit in a medium-term planning horizon. We assumed that this producer can participate in the spot and over-the-counter markets to buy and sell natural gas and electricity. We also considered that the power producer has gas storage available that can be used for handling the availability of gas and the uncertainty of gas prices. A stochastic programming model was used to formulate this problem, where the electricity and gas prices were characterized as stochastic processes using a set of scenarios. The proposed model includes the technical constraints resulting from the operation of the combined cycle power plant and the gas storage and a detailed description of the different markets in which the power producer can participate. Finally, the performance of the proposed model is tested in a realistic case study. The numerical results show that the usage of the gas storage unit allows the power producer to increase its expected profit. Additionally, it is observed that bilateral contracting decisions are not influenced by the presence of the gas storage unit.
Research in Forest Biology in the Era of Climate Change and Rapid Urbanization
Authors: Pei Nancai , Kress W. John
Published: December 2019

Green plants provide the foundation for the structure, function, and interactions among organisms in both tropical and temperate zones. To date, many investigations have revealed patterns and mechanisms that generate plant diversity at various scales and from diverse ecological perspectives. However, in the era of climate change, anthropogenic disturbance, and rapid urbanization, new insights are needed to understand how plant species in these forest habitats are changing and adapting. Here, we recognize four themes that link studies from Asia and Europe presented in this Special Issue: (1) genetic analyses of diverse plant species; (2) above- and below-ground forest biodiversity; (3) trait expression and biological mechanisms; and (4) interactions of woody plants within a changing environment. These investigations enlarge our understanding of the origins of diversity, trait variation and heritability, and plant–environment interactions from diverse perspectives.
Scientific Forest Management Practice in Nepal: Critical Reflections from Stakeholders’ Perspectives
Authors: Poudyal Bishnu Hari , Maraseni Tek , Cockfield Geoff
Published: December 2019

Design and application of context-specific forest management practices with the participation of key stakeholders plays a significant role in sustainable forest management outcomes. However, key forestry stakeholders often hold different, and sometimes conflicting, expectations in relation to forest management policies and management objectives. Applying the triple-perspective typology of stakeholder theory, this paper assessed the evolution of “Scientific Forest Management” (SciFM), a signature programme of the Nepalese Government, as well as its policy processes and explored compatibility, complexity, cost and relative advantages of the adoption of SciFM. The government believes that without this programme, Nepal is losing 91 Million US Dollar (USD) per year. This study revealed that participation of key stakeholders remained contested from the beginning of its implementation, primarily due to differences they held in understanding and interpretation of SciFM. Although stakeholders’ views converged on the potential role of SciFM to increase forest product supply and the domination of timber-centric management, their perspectives differed in nomenclature and implementation modality of SciFM. Primarily, the community forest users and their networks did not own the concept from the beginning, as they were suspicious of recentralization and bureaucratic dominance in forest governance through SciFM. Since historically ingrained skepticism in both government officials and community forest users’ networks towards each other has negatively influenced the trust-building environment, the management of stakeholders’ relations through frequent and meaningful deliberations, and the simplification of bureaucratic procedures in implementation and capacity development of key actors could be instrumental in achieving SciFM objectives.
Developing a Scene-Based Triangulated Irregular Network (TIN) Technique for Individual Tree Crown Reconstruction with LiDAR Data
Authors: Liu Haijian , Wu Changshan
Published: December 2019

LiDAR (Light Detection and Ranging)-based individual tree crown reconstruction is a challenge task due to the variable canopy morphologies and the penetrating properties of LiDAR to tree crown surfaces. Traditional methods, including LiDAR-derived rasterization, low-pass filtering smooth algorithm, and original triangular irregular network (TIN) model, have difficulties in balancing morphological accuracy and model smoothness. To address this issue, a scene-based TIN was generated with three steps based on the local scene principle. First, local Delaunay triangles were formed through connecting neighboring point sets. Second, key control points within each local Delaunay triangle, including steeple, inverted tip, ridge, saddle, and horseshoe shape control points, were extracted by analyzing multiple local scenes. These key points were derived to determine the fluctuations of forest canopies. Third, the scene-based TIN model was generated using the control points as nodes. Visual analysis indicates the new model can accurately reconstruct different canopy shapes with a relatively smooth surface, and statistical analysis of individual trees confirms that the overall error of the new model is smaller than others. Especially, the scene-based TIN derived raster reduced the average error to 0.18 m, with a standard deviation of 0.41, while the average errors of LiDAR-derived raster, low-pass filtered smooth raster, and original TIN derived raster have average errors of 0.96, 2.05, and 1.00 m, respectively. The local scene-based control point extraction also reduces data storage due to the elimination of redundant points, and furthermore the different point densities on different objects are beneficial for canopy segmentation.
Object-Based Tree Species Classification Using Airborne Hyperspectral Images and LiDAR Data
Authors: Wu Yanshuang , Zhang Xiaoli
Published: December 2019

The identification of tree species is one of the most basic and key indicators in forest resource monitoring with great significance in the actual forest resource survey and it can comprehensively improve the efficiency of forest resource monitoring. The related research has mainly focused on single tree species without considering multiple tree species, and therefore the ability to classify forest tree species in complex stand is not clear, especially in the subtropical monsoon climate region of southern China. This study combined airborne hyperspectral data with simultaneously acquired LiDAR data, to evaluate the capability of feature combinations and k-nearest neighbor (KNN) and support vector machine (SVM) classifiers to identify tree species, in southern China. First, the stratified classification method was used to remove non-forest land. Second, the feature variables were extracted from airborne hyperspectral image and LiDAR data, including independent component analysis (ICA) transformation images, spectral indices, texture features, and canopy height model (CHM). Third, random forest and recursion feature elimination methods were adopted for feature selection. Finally, we selected different feature combinations and used KNN and SVM classifiers to classify tree species. The results showed that the SVM classifier has a higher classification accuracy as compared with KNN classifier, with the highest classification accuracy of 94.68% and a Kappa coefficient of 0.937. Through feature elimination, the classification accuracy and performance of SVM classifier was further improved. Recursive feature elimination method based on SVM is better than random forest. In the spectral indices, the new constructed slope spectral index, SL2, has a certain effect on improving the classification accuracy of tree species. Texture features and CHM height information can effectively distinguish tree species with similar spectral features. The height information plays an important role in improving the classification accuracy of other broad-leaved species. In general, the combination of different features can improve the classification accuracy, and the proposed strategies and methods are effective for the identification of tree species at complex forest type in southern China.
Overexpression of a Novel LcKNOX Transcription Factor from Liriodendron chinense Induces Lobed Leaves in Arabidopsis thaliana
Authors: Ma Jikai , Mei Guoguo , Liu Huanhuan , Li Huogen
Published: December 2019

Liriodendron chinense is a common ornamental tree that has attractive leaves, which is a valuable trait for use in landscape architecture. In this work, we aimed to identify the potential genes that control and regulate the development of L. chinense leaf lobes. Based on the transcriptome data for the leaf developmental stages we previously generated, two candidate genes were identified in this study. KNOTTED-LIKE HOMEOBOX(KNOX), encoding homeobox family proteins, play a large role in leaf lobe and leaf complexity regulation. Here, two full length KNOX genes from L. chinense were amplified and named LcKNOX1 and LcKNOX6 according to their sequence similarities with the respective Arabidopsis thaliana KNOX family genes. Overexpression vectors were constructed and subsequently transformed into wild type (WT) A. thaliana. Additionally, LcKNOX6 was expressed in tobacco leaves to examine its subcellular localization, and the 35S::LcKNOX6 transgenic A. thaliana leaf cells were imaged with the use of SEM. The expression of several genes that participate in KNOX gene regulation were validated by quantitative real-time PCR. The results show that LcKNOX1 produces almost the same phenotype as that found in WT A. thaliana. Notably, the LcKNOX6-1 lines presented deep leaf lobes that were similar to L. chinense leaf lobes. Two 35S::LcKNOX6 lines induced an abnormal growth phenotype whose seeds were abortive. In short, these results indicate that the LcKNOX6 gene might affect leaf development in A. thaliana and provide insights into the regulation of L. chinense leaf shaping.
5G Cross-Border Operation for Connected and Automated Mobility: Challenges and Solutions
Authors: Kousaridas Apostolos , Schimpe Andreas , Euler Sebastian , Vilajosana Xavier , Fallgren Mikael , Landi Giada , Moscatelli Francesca , Barmpounakis Sokratis , Vázquez-Gallego Francisco , Sedar Roshan , Silva Rodrigo , Dizambourg Laurent , Wendt Stefan , Muehleisen Maciej , Eckert Kurt , Härri Jérôme , Alonso-Zarate Jesus
Published: December 2019

The vision of cooperative, connected and automated mobility (CCAM) across Europe can only be realized when harmonized solutions that support cross-border traffic exist. The possibility of providing CCAM services along different countries when vehicles drive across various national borders has a huge innovative business potential. However, the seamless provision of connectivity and the uninterrupted delivery of services along borders also poses interesting technical challenges. The situation is particularly innovative given the multi-country, multi-operator, multi-telco-vendor, and multi-car-manufacturer scenario of any cross-border layout. This paper introduces the challenges associated to a cross-border deployment of communication technologies through the analysis of three use cases: tele-operated driving, high-definition map generation and distribution for autonomous vehicles, and anticipated cooperative collision avoidance. Furthermore, a set of 5G solutions have been identified to ensure that CCAM services can be supported efficiently in cross-border scenarios. Faster handover of a data connection from one operator to another, generalized inter-mobile edge computing (MEC) coordination, and quality of service (QoS) prediction are some of the solutions that have been introduced to reduce the uncertainties of a real 5G cross-border deployment.