bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Chlorophyll-Meter-Index-Based Dynamic Models for Evaluation of High-Yield Japonica Rice Production in Yangtze River Reaches
Authors: Zhang Ke , Liu Xiaojun , Tahir Ata-Ul-Karim Syed , Lu Jingshan , Krienke Brian , Li Songyang , Cao Qiang , Zhu Yan , Cao Weixing , Tian Yongchao
Published: February 2019

Accurate estimation of the nitrogen (N) spatial distribution of rice (Oryza sativa L.) is imperative when it is sought to maintain regional and global carbon balances. We systematically evaluated the normalized differences of the soil and plant analysis development (SPAD) index (the normalized difference SPAD indexes, NDSIs) between the upper (the first and second leaves from the top), and lower (the third and fourth leaves from the top) leaves of Japonica rice. Four multi-location, multi-N rate (0–390 kg ha−1) field experiments were conducted using seven Japonica rice cultivars (9915, 27123, Wuxiangjing14, Wunyunjing19, Wunyunjing24, Liangyou9, and Yongyou8). Growth analyses were performed at different growth stages ranging from tillering (TI) to the ripening period (RP). We measured leaf N concentration (LNC), the N nutrition index (NNI), the NDSI, and rice grain yield at maturity. The relationships among the NDSI, LNC, and NNI at different growth stages showed that the NDSI values of the third and fourth fully expanded leaves more reliably reflected the N nutritional status than those of the first and second fully expanded leaves (LNC: NDSIL3,4, R2 > 0.81; NDSIothers, 0.77 > R2 > 0.06; NNI: NDSIL3,4, R2 > 0.83; NDSIothers, 0.76 > R2 > 0.07; all p < 0.01). Two new diagnostic models based on the NDSIL3,4 (from the tillering to the ripening period) can be used for effective diagnosis of the LNC and NNI, which exhibited reasonable distributions of residuals (LNC: relative root mean square error (RRMSE) = 0.0683; NNI: RRMSE = 0.0688; p < 0.01). The relationship between grain yield, predicted yield, and NDSIL3,4 were established during critical growth stages (from the stem elongation to the heading stages; R2 = 0.53, p < 0.01, RRMSE = 0.106). An NDSIL3,4 high-yield change curve was drawn to describe critical NDSIL3,4 values for a high-yield target (10.28 t ha−1). Furthermore, dynamic-critical curve models based on the NDSIL3,4 allowed a precise description of rice N status, facilitating the timing of fertilization decisions to optimize yields in the intensive rice cropping systems of eastern China.
A Study on the Effects of Rumen Acidity on Rumination Time and Yield, Composition, and Technological Properties of Milk from Early Lactating Holstein Cows
Authors: Saha Sudeb , Gallo Luigi , Bittante Giovanni , Schiavon Stefano , Bergamaschi Matteo , Gianesella Matteo , Fiore Enrico
Published: February 2019

The use of high grain rations in dairy cows is related to an increase in rumen acidity. This study investigated whether the rumen acidity status affects rumination time (RT), and the production, composition, coagulation properties (MCPs) and cheese yield (CY) of milk. One hundred early-lactating Holstein cows with no clinical signs of disease and fed total mixed rations were used. Rumen fluid was collected once from each cow by rumenocentesis to determine pH and volatile fatty acid (VFA) content. The cows were classified according to the quartile of rumen acidity (QRA), a factor defined by multivariate analysis and associated with VFA and pH. Rumen fluid pH averaged 5.61 in the first quartile and 6.42 in the fourth, and total VFA content increased linearly with increasing rumen acidity. In addition, RT increased as rumen acidity increased, but only in the daily time interval from 08:00 to 12:00. Milk yield linearly decreased as rumen acidity increased, whereas QRA did not affect pH, fat or protein contents of milk. Furthermore, the MCPs, assessed by lactodynamograph, and CY were unaffected by QRA. It is suggested that differences in rumen acidity have little influence on the nutrient content, coagulation properties and CY of milk.
Pet Grief: Tools to Assess Owners’ Bereavement and Veterinary Communication Skills
Authors: Testoni Ines , De Cataldo Loriana , Ronconi Lucia , Colombo Elisa Silvia , Stefanini Cinzia , Dal Zotto Barbara , Zamperini Adriano
Published: February 2019

In Italy, there are still very few studies on the psychological impact of losing a pet. The need to fill this gap springs from the fact that pet loss counseling services are increasingly being activated. The aim of this study is the Italian adaptation of instruments for veterinary counseling services. The survey instruments adapted were: Pet Bereavement Questionnaire (PBQ) to describe the individual experience of pet-grief; Regret of Bereaved Family Members (RBFM) to assess the family regret; Shared Decision-Making Questionnaire (SDM-Q-9) for decision making in end of life; Consultation and Relational Empathy Measure (CARE) to assess the veterinarian relational empathy during clinical encounters. All the instruments obtained good internal reliability, and the results of the confirmative factor analysis of all the Italian versions were in accordance with the original ones. The correlational analysis among the variables evidenced the following aspects: the more the owner feels involved by the veterinarian in the decision making process the more the veterinarian is perceived by the owner as empathetic; when the veterinarian is perceived as empathic and the decision making is shared the owners’ pet bereavement distress and regrets are reduced; negative dimensions of bereavement (grief, guilt, anger, intrusive thoughts and decisional regrets) are strictly linked to each other, therefore if one dimension increases or decreases the others do too. The path analysis suggests that developing a veterinary relationship-centered care practice may be beneficial for pet owners facing end-of-life issues and the death of their companion animals since it showed that shared-decision making strategies and empathic communication may reduce negative dimensions of bereavement that may complicate grief. Interestingly, adopting shared decision-making strategies may contribute to be perceived as more empathic. These aspects may be taken into consideration in end-of -life communication training in veterinary medicine.
Generative Oversampling Method for Imbalanced Data on Bearing Fault Detection and Diagnosis
Authors: Suh Sungho , Lee Haebom , Jo Jun , Lukowicz Paul , Lee Yong Oh
Published: February 2019

In this study, we developed a novel data-driven fault detection and diagnosis (FDD) method for bearing faults in induction motors where the fault condition data are imbalanced. First, we propose a bearing fault detector based on convolutional neural networks (CNN), in which the vibration signals from a test bench are used as inputs after an image transformation procedure. Experimental results demonstrate that the proposed classifier for FDD performs well (accuracy of 88% to 99%) even when the volume of normal and fault condition data is imbalanced (imbalance ratio varies from 20:1 to 200:1). Additionally, our generative model reduces the level of data imbalance by oversampling. The results improve the accuracy of FDD (by up to 99%) when a severe imbalance ratio (200:1) is assumed.
Multi-Twin-SSB Modulation with Direct Detection Based on Kramers–Kronig Scheme for Long-Reach PON Downstream
Authors: Gao Xiang , Cai Yuancheng , Xu Bo , Zhang Xiaoling , Qiu Kun
Published: February 2019

As the demand for high data volumes keeps increasing in optical access networks, transmission capacities and distance are becoming bottlenecks for passive optical networks (PONs). To solve this problem, a novel scheme based on multi-twin single sideband (SSB) modulation with direct detection is proposed and investigated in this paper. At the central office, two SSB signals are generated simultaneously with the same digital-to-analog converters (DACs). The twin-SSB signal is not only robust against frequency selected power fading introduced by chromatic dispersion (CD), but also improves the spectral efficiency (SE). By combining a twin-SSB technique with multi-band carrier-less amplitude/phase modulation (multi-CAP), different optical network units (ONUs) can be supported by flexible multi-band allocation based on software-reconfigurable optical transceivers. The Kramers–Kronig (KK) scheme is adopted on the ONU side to effectively mitigate the signal–signal beat interference (SSBI) induced by the square-law detection. The proposed system is extensively studied and validated with four sub-bands using 50 Gbps 16 quadrature amplitude modulation (QAM) modulation for each sub-band using numerical simulations. Digital pre-equalization is introduced at the transmitter-side to balance the performance of different ONUs. After system optimization, a bit error rate (BER) threshold for hard decision forward error correction (HD-FEC) code with 7% redundancy ratio (BER = 3.8 × 10−3) can be reached for all ONUs over 50-km standard single-mode fiber.
Accurate Evaluation of the Average Probability of Error of Pulse Position Modulation in Amplified Optical Wireless Communications under Turbulence
Authors: Boucouvalas Anthony C. , Sagias Nikos C. , Yiannopoulos Konstantinos
Published: February 2019

We present exact and approximate results on the average probability of error (PER) for pulse position modulation (PPM) in pre-amplified optical wireless communication systems with diversity. The approximate results are obtained by combining a new mathematical formula that we derive for binary PPM and an existing formula that associates higher-order PPM PERs with their binary PPM counterpart. The approximate results are compared with the exact in weak, moderate, and strong turbulence, and it is demonstrated that they are in good agreement under all fading conditions. Moreover, the accuracy of the approximation improves with the optical signal-to-noise ratio and the number of diversity branches that are used, which correspond to implementation scenarios that are typically anticipated in practice.
Sparse Envelope Spectra for Feature Extraction of Bearing Faults Based on NMF
Authors: Liang Lin , Shan Lei , Liu Fei , Niu Ben , Xu Guanghua
Published: February 2019

Periodic impulses and the oscillation response signal are the vital feature indicators of rolling bearing faults. However, finding the suitable feature frequency band is usually difficult due to the interferences of other components and multiple resonance regions. According to the characteristics of non-negative matrix factorization (NMF) on a spectrogram, the feature extraction method from a sparse envelope spectrum for rolling bearing faults is proposed in this paper. On the basis of the time–frequency distribution (TFD) of the periodic transient oscillations, the basic matrix can be interpreted as the spectral bases, and the time weight matrix corresponding to spectral bases can be extracted by NMF. Because the bases and the weights have a one-to-one correspondence, the frequency band filtering with the basic component and the time domain envelope of the weight vector are calculated respectively. Then, the sparse envelope spectrum can be derived by the inner product of the above results. The effectiveness of the proposed method is verified by simulations and experiments. Compared with band-pass filtering and spectral kurtosis methods, and considering the time weights and corresponding the spectral bases for the periodic transient oscillations, the weak fault-rated feature can be enhanced in the sparse spectrum, while other components and noise are weakened. Therefore, the proposed method can reduce the requirement of selecting frequency band filtering.
Effects of Configurations of Internal Walls on the Threshold Value of Operation Hours for Intermittent Heating Systems
Authors: Wang Shuhan , Zhong Ke
Published: February 2019

The heating load of intermittent heating is not always lower than that of continuous heating for heat storage and release of internal walls. Therefore, the threshold value of daily operation hours exists, and is affected by the configuration of internal walls. A comparative study is performed between continuous and intermittent heating modes to investigate the threshold value of daily operation hours for different internal wall configurations by employing computational fluid dynamic (CFD) models. Meanwhile, field tests on the temperature distribution within a thermal mass was carried out to validate the simulation. The results show that the heating load index of intermittent heating is larger than that of continuous heating with increased amplitude ranging from 31.58% to 152.63%. The threshold value of daily operation hours is, respectively, 18.04 h, 15.80 h, 14.59 h, and 13.46 h for four internal wall configurations. Moreover, with the increase in the insulation level of internal walls, the threshold value of daily operation hours decreases. In addition, the results indicate that it is more economical to use continuous heating when the daily operation hours are more than the threshold values.
Cavitation Evolution around a NACA0015 Hydrofoil with Different Cavitation Models Based on Level Set Method
Authors: Yu An , Tang Qinghong , Zhou Daqing
Published: February 2019

Cavitation is a complex multiphase flow phenomenon that is usually involved in marine propulsion systems, and can be simulated with a couple of methods. In this study, three widespread cavitation models were compared using experimental data and a new modified simulation method. The accuracy of the three cavitation models was evaluated regarding their steady and unsteady characteristics, such as the flow field, re-entrant jet, vortex-shedding, and so on. Based on the experimental data and numerical results, the applicability of different cavitation models in different conditions was obtained. The Kunz model can accurately capture both the adverse pressure gradient and the action of the re-entrant jet in sheet cavitation, while the full cavitation model (FCM) has an accurate prediction for the flow field structure and the shedding characteristic of cloud cavitation. Through comparing the results, the optimal selection of cavitation models for further study at different conditions was obtained.
Effects of Bogies on the Wake Flow of a High-Speed Train
Authors: Liu Wen , Guo Dilong , Zhang Zijian , Chen Dawei , Yang Guowei
Published: February 2019

The wake region of high-speed trains is an area of complex turbulent flow characterized by the periodic generation and shedding of vortices, which causes discomfort to passengers and affects the stability and safety of the train. In this study, the unsteady characteristics of the wake flows of three 1:1 scale China Railway High-Speed 380A (CRH380A) high-speed train models with different degrees of simplification were numerically investigated using the improved delayed detached eddy simulation (IDDES) method. Analyses of the aerodynamic forces, train-induced slipstream, and turbulent kinetic energy (TKE) were conducted to determine the effects of the bogies on the wake flow of the high-speed train. It was found that the existence of bogies on the bottom of the train, especially the last bogie, not only enhanced the wake flow but also introduced large perturbances into the wake flow. Moreover, the generation and evolution of the vortices in the wake flows were determined by analyzing the instantaneous flow fields and coherent flow structures that were obtained by the dynamic mode decomposition (DMD) method. The results showed that a pair of large, counter-rotating streamwise vortices in the real model of the high-speed train was generated by the cowcatcher and their intensity was significantly enhanced by perturbances that were introduced by the bogies on the bottom of the train.
Experimental and Parametric Study on the Pull-Out Resistance of a Notched Perfobond Shear Connector
Authors: Zheng Shuangjie , Liu Yuqing , Liu Yangqing , Zhao Chen
Published: February 2019

To ease the installation of perforating rebars through multi-holes, an alternative notched perfobond shear connector was proposed by cutting out the hole edge. This paper presents the test results of six pull-out specimens with conventional and notched perfobond shear connectors. The objective was to compare the failure modes and pull-out behaviors of perfobond shear connectors using circular holes and notched holes. Furthermore, the explicit finite element method was introduced and validated to generate parametric results for pull-out tests of notched perfobond shear connectors. A total of 33 parametric simulations were performed to further study the influences of several variables, including the hole diameter, the cut width, the perfobond thickness, the concrete strength, the diameter and strength of the rebar, and the strength of the structural steel. The experimental and numerical results were used to evaluate the previous equations for perfobond shear connectors. Finally, an alternative equation was proposed to estimate the pull-out resistance of notched perfobond shear connectors.
The Role of Powered Surgical Instruments in Ear Surgery: An Acoustical Blessing or a Curse?
Authors: Ito Tsukasa , Kubota Toshinori , Furukawa Takatoshi , Matsui Hirooki , Futai Kazunori , Hull Melinda , Kakehata Seiji
Published: February 2019

Ear surgery in many ways lagged behind other surgical fields because of the delicate anatomical structures within the ear which leave surgeons with little room for error. Thus, while surgical instruments have long been available, their use in the ear would most often do more damage than good. This state of affairs remained the status quo well into the first half of the 20th century. However, the introduction of powered surgical instruments, specifically the electric drill used in conventional microscopic ear surgery (MES) and the ultrasonic aspirator, the Sonopet® Omni, in transcanal endoscopic ear surgery (TEES) marked major turning points. Yet, these breakthroughs have also raised concerns about whether the use of these powered surgical instruments within the confines of the ear generated so much noise and vibrations that patients could suffer sensorineural hearing loss as a result of the surgery itself. This paper reviews the intersection between the noise and vibrations generated during surgery; the history of surgical instruments, particularly powered surgical instruments, used in ear surgeries and the two main types of surgical procedures to determine whether these powered surgical instruments may pose a threat to postoperative hearing.
Cavitation Technology—The Future of Greener Extraction Method: A Review on the Extraction of Natural Products and Process Intensification Mechanism and Perspectives
Authors: Panda Debabrata , Manickam Sivakumar
Published: February 2019

With growing consumer demand for natural products, greener extraction techniques are found to be potential alternatives especially for pharmaceutical, nutraceutical, and cosmetic manufacturing industries. Cavitation-based technology has drawn immense attention as a greener extraction method, following its rapid and effective extraction of numerous natural products compared to conventional techniques. The advantages of cavitation-based extraction (CE) are to eliminate the application of toxic solvents, reduction of extraction time and to achieve better extraction yield, as well as purity. The cavitational phenomena enhance the extraction efficiency via increased mass transfer rate between the substrate and solvent, following the cell wall rupture, due to the intense implosion of bubbles. This review includes a detailed overview of the ultrasound-assisted extraction (UAE), negative pressure cavitation (NPC) extraction, hydrodynamic cavitation extraction (HCE) and combined extractions techniques which have been implemented for the extraction of high-value-added compounds. A list of essential parameters necessary for the maximum possible extraction yield has been discussed. The optimization of parameters, such as ultrasonic power density, frequency, inlet pressure of HC, extraction temperature and the reactor configuration denote their significance for better efficiency. Furthermore, the advantages and drawbacks associated with extraction and future research directions have also been pointed out.
Gear Pitting Fault Diagnosis Using Integrated CNN and GRU Network with Both Vibration and Acoustic Emission Signals
Authors: Li Xueyi , Li Jialin , Qu Yongzhi , He David
Published: February 2019

This paper deals with gear pitting fault diagnosis problem and presents a method by integrating convolutional neural network (CNN) and gated recurrent unit (GRU) networks with vibration and acoustic emission signals to solve the problem. The presented method first trains a one-dimensional CNN with acoustic emission signals and a GRU network with vibration signals. Then the gear pitting fault features obtained by the two networks are concatenated to form a deep learning structure for gear pitting fault diagnosis. Seven different gear pitting conditions are used to test the feasibility of the presented method. The diagnosis result of the gear pitting fault shows that the accuracy of the presented method reaches above 98% with only a relatively small number of training samples. In comparison with the results using CNN or GRU network alone, the presented method gives more accurate diagnosis results. By comparing the results of different loads and learning rates, the robustness of the presented method for gear pitting fault diagnosis is proved. Moreover, the presented deep structure can be easily extended to more other sensor input signals for gear pitting fault diagnosis in the future.
A Time–Frequency Correlation Analysis Method of Time Series Decomposition Derived from Synchrosqueezed S Transform
Authors: Pan Gaoyuan , Li Shunming , Zhu Yanqi
Published: February 2019

Traditional correlation analysis is analyzed separately in the time domain or the frequency domain, which cannot reflect the time-varying and frequency-varying characteristics of non-stationary signals. Therefore, a time–frequency (TF) correlation analysis method of time series decomposition (TD) derived from synchrosqueezed S transform (SSST) is proposed in this paper. First, the two-dimensional time–frequency matrices of the signals is obtained by synchrosqueezed S transform. Second, time series decomposition is used to transform the matrices into the two-dimensional time–time matrices. Third, a correlation analysis of the local time characteristics is carried out, thus attaining the time–frequency correlation between the signals. Finally, the proposed method is validated by stationary and non-stationary signals simulation and is compared with the traditional correlation analysis method. The simulation results show that the traditional method can obtain the overall correlation between the signals but cannot reflect the local time and frequency correlations. In particular, the correlations of non-stationary signals cannot be accurately identified. The proposed method not only obtains the overall correlations between the signals, but can also accurately identifies the correlations between non-stationary signals, thus showing the time-varying and frequency-varying correlation characteristics. The proposed method is applied to the acoustic signal processing of an engine–gearbox test bench. The results show that the proposed method can effectively identify the time–frequency correlation between the signals.
Fully Symmetric Convolutional Network for Effective Image Denoising
Authors: Priyanka Steffi Agino , Wang Yuan-Kai
Published: February 2019

Neural-network-based image denoising is one of the promising approaches to deal with problems in image processing. In this work, a deep fully symmetric convolutional–deconvolutional neural network (FSCN) is proposed for image denoising. The proposed model comprises a novel architecture with a chain of successive symmetric convolutional–deconvolutional layers. This framework learns convolutional–deconvolutional mappings from corrupted images to the clean ones in an end-to-end fashion without using image priors. The convolutional layers act as feature extractor to encode primary components of the image contents while eliminating corruptions, and the deconvolutional layers then decode the image abstractions to recover the image content details. An adaptive moment optimizer is used to minimize the reconstruction loss as it is appropriate for large data and noisy images. Extensive experiments were conducted for image denoising to evaluate the FSCN model against the existing state-of-the-art denoising algorithms. The results show that the proposed model achieves superior denoising, both qualitatively and quantitatively. This work also presents the efficient implementation of the FSCN model by using GPU computing which makes it easy and attractive for practical denoising applications.
Optimization of EPB Shield Performance with Adaptive Neuro-Fuzzy Inference System and Genetic Algorithm
Authors: Elbaz Khalid , Shen Shui-Long , Zhou Annan , Yuan Da-Jun , Xu Ye-Shuang
Published: February 2019

The prediction of earth pressure balance (EPB) shield performance is an essential part of project scheduling and cost estimation of tunneling projects. This paper establishes an efficient multi-objective optimization model to predict the shield performance during the tunneling process. This model integrates the adaptive neuro-fuzzy inference system (ANFIS) with the genetic algorithm (GA). The hybrid model uses shield operational parameters as inputs and computes the advance rate as output. GA enhances the accuracy of ANFIS for runtime parameters tuning by multi-objective fitness function. Prior to modeling, datasets were established, and critical operating parameters were identified through principal component analysis. Then, the tunneling case for Guangzhou metro line number 9 was adopted to verify the applicability of the proposed model. Results were then compared with those of the ANFIS model. The comparison showed that the multi-objective ANFIS-GA model is more successful than the ANFIS model in predicting the advance rate with a high accuracy, which can be used to guide the tunnel performance in the field.
Intelligent Fault Diagnosis Techniques Applied to an Offshore Wind Turbine System
Authors: Simani Silvio , Castaldi Paolo
Published: February 2019

Fault diagnosis of wind turbine systems is a challenging process, especially for offshore plants, and the search for solutions motivates the research discussed in this paper. In fact, these systems must have a high degree of reliability and availability to remain functional in specified operating conditions without needing expensive maintenance works. Especially for offshore plants, a clear conflict exists between ensuring a high degree of availability and reducing costly maintenance. Therefore, this paper presents viable fault detection and isolation techniques applied to a wind turbine system. The design of the so-called fault indicator relies on an estimate of the fault using data-driven methods and effective tools for managing partial knowledge of system dynamics, as well as noise and disturbance effects. In particular, the suggested data-driven strategies exploit fuzzy systems and neural networks that are used to determine nonlinear links between measurements and faults. The selected architectures are based on nonlinear autoregressive with exogenous input prototypes, which approximate dynamic relations with arbitrary accuracy. The designed fault diagnosis schemes were verified and validated using a high-fidelity simulator that describes the normal and faulty behavior of a realistic offshore wind turbine plant. Finally, by accounting for the uncertainty and disturbance in the wind turbine simulator, a hardware-in-the-loop test rig was used to assess the proposed methods for robustness and reliability. These aspects are fundamental when the developed fault diagnosis methods are applied to real offshore wind turbines.
Italian Rationalist Design: Modernity between Tradition and Innovation
Authors: Dal Falco Federica
Published: February 2019

This article is devoted to the Italian modern project of the 1930s, which involved architecture and design. The main theme is the influence that the autarchic economic policy of the Fascist regime had in the choice of materials and technologies, and, above all, the manner in which this choice led to innovative practices and figurative research. Through significant examples, the essay provides some insight into the style of Italian rationalism, whose contradictory aspects—conditioned by the regime’s policy—shaped urban planning, architecture, and design in the 1930s. I show that the Italian rationalist culture is a field of investigation that is of considerable scientific interest because it represents the idea of an integral project comprised of all the elements associated to a building, including those that are still used today. In particular, I present a case study centered on the Physics Institute of Rome’s Sapienza University (1933–1935) designed by the architect Giuseppe Pagano Pogatschnig, analyzing its materials, technologies, and architectural features, as well as its furnishings. Along these lines, the objective of this investigation is the transmission of a specific knowledge, looking at objects as essential parts of the aesthetics of Rationalism in order to protect and enhance the cultural heritage of modernity.
Assessing the Performance of CMIP5 GCMs for Projection of Future Temperature Change over the Lower Mekong Basin
Authors: Ruan Yunfeng , Liu Zhaofei , Wang Rui , Yao Zhijun
Published: February 2019

In this study, we assessed the performance of 34 Coupled Model Intercomparison Project Phase 5 (CMIP5) general climate models (GCMs) for simulating the observed temperature over the Lower Mekong Basin (LMB) in 1961–2004. An improved score-based method was used to rank the performance of the GCMs over the LMB. Two methods of multi-model ensemble (MME), sub-ensemble from the top 25% ranked GCMs and full ensemble from the entire GCMs, were calculated using arithmetic mean (AM) method and downscaled using the Delta method to project future temperature change during two future time periods, the near future (2006–2049) and the far future (2050–2093), under representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5 scenarios) over the LMB. The improved score-based method combining multiple criteria showed a robust assessment of the GCMs performance over the LMB, which can provide good information for projecting future temperature change. The results showed a significant increase in temperature over the LMB under the two ensembles. However, there were differences in the magnitudes of the future temperature increase between the two ensemble methods, with a higher mean annual temperature increase from full ensemble and sub-ensemble at 1.26 °C (1.09 °C), 1.90 °C (1.70 °C), and 2.97 °C (2.78 °C) during 2050–2093 under the RCP2.6, RCP4.5, and RCP8.5 scenarios compared to the values at 0.93 °C (0.87 °C), 0.99 °C (0.95 °C), and 1.09 °C (1.06 °C) during 2006–2049, respectively, relative to the reference time period of 1961–2004. In the future (2006–2093), the temperature is likely to increase at 0.06 °C, 0.18 °C, and 0.39 °C decade−1 under the RCP2.6, RCP4.5, and RCP8.5 scenarios by the sub-ensemble, while a higher temperature increase at 0.08 °C, 0.20 °C, and 0.42 °C was found by the full ensemble over the LMB, relative to the reference time period of 1961–2004. On the whole, the higher warming mainly occurred in the northern and central areas over the LMB, while the lower warming mainly occurred in the southeast and the southwest, especially under the RCP4.5 and RCP8.5 scenarios, with the warming increased with increasing RCP for both ensembles. Moreover, in order to reduce the uncertainty of temperature projection in further studies in the LMB, multiple methods of GCMs ensemble should be considered and compared.
Identification of Drought Events and Correlations with Large-Scale Ocean–Atmospheric Patterns of Variability: A Case Study in Xinjiang, China
Authors: Yao Junqiang , Tuoliewubieke Dilinuer , Chen Jing , Huo Wen , Hu Wenfeng
Published: February 2019

This research analyzed the spatiotemporal patterns of drought in Xinjiang (northwestern China) between 1961 and 2015 using the standardized precipitation evapotranspiration index (SPEI). Furthermore, the correlations between Atlantic Multidecadal Oscillation (AMO)/El Niño–Southern Oscillation (ENSO) events and drought were explored. The results suggested an obvious trend toward aggravated drought, with a significant inflection point in 1997, after which the frequency of drought increased sharply. Spatially, the increase in drought occurred largely in southern and eastern Xinjiang, where occurrences of moderate and extreme drought have become more frequent during the last two decades, whereas northwestern Xinjiang and the Pamir Plateau showed wetting trends. Empirical orthogonal function analysis (EOF) of drought patterns showed a north–south antiphase and an east–west antiphase distribution. The positive (negative) phase of the AMO was related to increased (decreased) drought in Xinjiang, particularly after 1997. During a warm phase (El Niño), major droughts occurred over northern Xinjiang, but they lagged by 12 months. However, not all El Niño and La Niña events were responsible for drought events in northern Xinjiang during this period, and other drivers remain to be identified. This study suggests the possibility of AMO and ENSO links to drought in Xinjiang, but further analysis is needed to better understand such mechanisms.
Spatial and Temporal Variations of Compound Droughts and Hot Extremes in China
Authors: Wu Xinying , Hao Zengchao , Hao Fanghua , Li Chong , Zhang Xuan
Published: February 2019

Droughts and hot extremes may lead to tremendous impacts on the ecosystem and different sectors of the society. A variety of studies have been conducted on the variability of the individual drought or hot extreme in China. However, the evaluation of compound droughts and hot extremes, which may induce even larger impacts than the individual drought or hot extreme, is still lacking. The aim of this study is to investigate changes in the frequency and spatial extent of compound droughts and hot extremes during summer in China using monthly precipitation and daily temperature data from 1953 to 2012. Results show that a high frequency of compound droughts and hot extremes mostly occur in the regions stretching from northeast to southwest of China. There is an overall increase in the frequency of co-occurrence of droughts and hot extremes across most parts of China with distinct regional patterns. In addition, an increasing trend in the areas covered by compound extremes has been observed, especially after the 1990s. At regional scales, the increase of the frequency and spatial extent of compound extremes has been shown to be most profound in North China (NC), South China (SC), and Southwest China (SWC), while the decrease of compound extremes was found in Central China (CC). These results show the variability of compound droughts and hot extremes and could provide useful insights into the mitigation efforts of extreme events in China.
Theory of the Anomalous Magnetic Moment of the Electron
Authors: Aoyama Tatsumi , Kinoshita Toichiro , Nio Makiko
Published: February 2019

The anomalous magnetic moment of the electron a e measured in a Penning trap occupies a unique position among high precision measurements of physical constants in the sense that it can be compared directly with the theoretical calculation based on the renormalized quantum electrodynamics (QED) to high orders of perturbation expansion in the fine structure constant α , with an effective parameter α / π . Both numerical and analytic evaluations of a e up to ( α / π ) 4 are firmly established. The coefficient of ( α / π ) 5 has been obtained recently by an extensive numerical integration. The contributions of hadronic and weak interactions have also been estimated. The sum of all these terms leads to a e ( theory ) = 1 159 652 181.606 ( 11 ) ( 12 ) ( 229 ) × 10 − 12 , where the first two uncertainties are from the tenth-order QED term and the hadronic term, respectively. The third and largest uncertainty comes from the current best value of the fine-structure constant derived from the cesium recoil measurement: α − 1 ( Cs ) = 137.035 999 046 ( 27 ) . The discrepancy between a e ( theory ) and a e ( ( experiment ) ) is 2.4 σ . Assuming that the standard model is valid so that a e (theory) = a e (experiment) holds, we obtain α − 1 ( a e ) = 137.035 999 1496 ( 13 ) ( 14 ) ( 330 ) , which is nearly as accurate as α − 1 ( Cs ) . The uncertainties are from the tenth-order QED term, hadronic term, and the best measurement of a e , in this order.
VizTract: Visualization of Complex Social Networks for Easy User Perception
Authors: Akula Ramya , Garibay Ivan
Published: February 2019

Social networking platforms connect people from all around the world. Because of their user-friendliness and easy accessibility, their traffic is increasing drastically. Such active participation has caught the attention of many research groups that are focusing on understanding human behavior to study the dynamics of these social networks. Oftentimes, perceiving these networks is hard, mainly due to either the large size of the data involved or the ineffective use of visualization strategies. This work introduces VizTract to ease the visual perception of complex social networks. VizTract is a two-level graph abstraction visualization tool that is designed to visualize both hierarchical and adjacency information in a tree structure. We use the Facebook dataset from the Social Network Analysis Project from Stanford University. On this data, social groups are referred as circles, social network users as nodes, and interactions as edges between the nodes. Our approach is to present a visual overview that represents the interactions between circles, then let the user navigate this overview and select the nodes in the circles to obtain more information on demand. VizTract aim to reduce visual clutter without any loss of information during visualization. VizTract enhances the visual perception of complex social networks to help better understand the dynamics of the network structure. VizTract within a single frame not only reduces the complexity but also avoids redundancy of the nodes and the rendering time. The visualization techniques used in VizTract are the force-directed layout, circle packing, cluster dendrogram, and hierarchical edge bundling. Furthermore, to enhance the visual information perception, VizTract provides interaction techniques such as selection, path highlight, mouse-hover, and bundling strength. This method helps social network researchers to display large networks in a visually effective way that is conducive to ease interpretation and analysis. We conduct a study to evaluate the user experience of the system and then collect information about their perception via a survey. The goal of the study is to know how humans can interpret the network when visualized using different visualization methods. Our results indicate that users heavily prefer those visualization techniques that aggregate the information and the connectivity within a given space, such as hierarchical edge bundling.
Thermal Performance of Hollow-Core Slab Ventilation System with Macro-Encapsulated Phase-Change Materials in Supply Air Duct
Authors: Jamil Hasnat , Alam Morshed , Sanjayan Jay
Published: February 2019

The aim of this research was to evaluate the effectiveness of phase-change materials (PCMs) incorporated into the supply air duct of a hollow-core slab ventilation system. Both experimental and numerical approaches were adopted in this investigation. In the experimental work, the air was passed through a PCM-incorporated aluminum air duct, and the temperature at various points of the duct was recorded. Computational fluid dynamics models of the PCM-incorporated supply air duct and the hollow-core slab were developed and validated with the respective experimental data. The validated models were used to simulate the performance of PCM-incorporated hollow-core slabs during summer in Melbourne, Australia. The results showed that the reduction in temperature fluctuation varied with the way the PCM was incorporated inside the supply air duct. The temperature difference was maximum and was maintained for a longer period when the PCM was spread to all four internal surfaces of the supply air duct. The results also showed that the effectiveness of the combined PCM–air duct–hollow-core slab system in reducing the temperature fluctuation was lower than the individual performance of the PCM–air duct and hollow-core concrete slab for a given inlet temperature condition during the simulated period. This was because the integration of PCMs in the supply air duct resulted in a precooling effect which reduced the difference between the amplitude of slab inlet temperature swing and average slab temperature. As a result, the reduction in temperature fluctuation due to the thermal mass of the hollow-core slab was 21% lower in the presence of PCMs compared to the no-PCM case.
Metaphors as Discourse Interaction Devices in Architectural Design
Authors: Casakin Hernan
Published: February 2019

Metaphor is a fundamental heuristic supporting cognitive and communicative requirements in design problem solving. This reasoning mechanism helps structure how architects reason about problems, and how they approach design situations from novel perspectives. This paper investigated empirically the use of metaphors during the conceptual front edge design, known as the most creative stage of the process. Figurative phenomena were analyzed in their original context of occurrence. Emerging metaphorical expressions generated during communication interactions maintained by sixty architects were identified and examined based on protocol analysis approach. Metaphors were further categorized according to main experiential domains at different levels of detail, as well as in terms of image and conceptual descriptions. The study contributed to gain a deeper insight into the rhetorical potential of metaphor during design problem solving, and to strengthen its centrality in architecture.
Exosome Analysis in Tumor-Draining Pulmonary Vein Identifies NSCLC Patients with Higher Risk of Relapse after Curative Surgery
Authors: Navarro Alfons , Molins Laureano , Marrades Ramon M. , Moises Jorge , Viñolas Nuria , Morales Sara , Canals Jordi , Castellano Joan J. , Ramírez José , Monzo Mariano
Published: February 2019

Since tumor-draining pulmonary vein blood (PV) is enriched in tumor-secreted products, we hypothesized that it would also be enriched in tumor-derived exosomes, which would be important in the metastasis process. We characterized exosomes from PV of 61 resected non-small cell lung cancer (NSCLC) patients to evaluate its potential as relapse biomarkers. Exosomes were characterized using transmission electron microscopy, western blot and nanoparticle tracking analysis and we examined time to relapse (TTR) and overall survival (OS). Differences between PV and peripheral vein were found. PV was enriched in smaller exosomes than the paired peripheral vein (p = 0.01). Moreover, PV exosome size mode was able to identify relapsed patients (Area under the curve [AUC] = 0.781; 95%CI: 0.6641–0.8978), in whom exosome size was smaller (<112 nm; p < 0.001). The combination of PV exosome size and N (lymph node involvement) showed an AUC of 0.89 (95%CI: 0.80–0.97). Moreover, smaller PV exosome size was associated with shorter TTR (28.3 months vs. not reached, p < 0.001) and OS (43.9 months vs. not reached, p = 0.009). Multivariate analyses identified PV exosome size and stage as independent prognostic markers for TTR and OS. PV exosome size is a promising relapse biomarker after surgery that can add valuable information to clinical variables.
The OncoAge Consortium: Linking Aging and Oncology from Bench to Bedside and Back Again
Authors: Hofman Paul , Ayache Nicholas , Barbry Pascal , Barlaud Michel , Bel Audrey , Blancou Philippe , Checler Frédéric , Chevillard Sylvie , Cristofari Gael , Demory Mathilde , Esnault Vincent , Falandry Claire , Gilson Eric , Guérin Olivier , Glaichenhaus Nicolas , Guigay Joel , Ilié Marius , Mari Bernard , Marquette Charles-Hugo , Paquis-Flucklinger Véronique , Prate Frédéric , Saintigny Pierre , Seitz-Polsky Barbara , Skhiri Taycir , Van Obberghen-Schilling Ellen , Van Obberghen Emmanuel , Yvan-Charvet Laurent
Published: February 2019

It is generally accepted that carcinogenesis and aging are two biological processes, which are known to be associated. Notably, the frequency of certain cancers (including lung cancer), increases significantly with the age of patients and there is now a wealth of data showing that multiple mechanisms leading to malignant transformation and to aging are interconnected, defining the so-called common biology of aging and cancer. OncoAge, a consortium launched in 2015, brings together the multidisciplinary expertise of leading public hospital services and academic laboratories to foster the transfer of scientific knowledge rapidly acquired in the fields of cancer biology and aging into innovative medical practice and silver economy development. This is achieved through the development of shared technical platforms (for research on genome stability, (epi)genetics, biobanking, immunology, metabolism, and artificial intelligence), clinical research projects, clinical trials, and education. OncoAge focuses mainly on two pilot pathologies, which benefit from the expertise of several members, namely lung and head and neck cancers. This review outlines the broad strategic directions and key advances of OncoAge and summarizes some of the issues faced by this consortium, as well as the short- and long-term perspectives.
Pan-Cancer Analyses Reveal Genomic Features of FOXM1 Overexpression in Cancer
Authors: Barger Carter J , Branick Connor , Chee Linda , Karpf Adam R.
Published: February 2019

FOXM1 is frequently overexpressed in cancer, but this has not been studied in a comprehensive manner. We utilized genotype-tissue expression (GTEx) normal and The Cancer Genome Atlas (TCGA) tumor data to define FOXM1 expression, including its isoforms, and to determine the genetic alterations that promote FOXM1 expression in cancer. Additionally, we used human fallopian tube epithelial (FTE) cells to dissect the role of Retinoblastoma (Rb)-E2F and Cyclin E1 in FOXM1 regulation, and a novel human embryonic kidney cell (HEK293T) CRISPR FOXM1 knockout model to define isoform-specific transcriptional programs. FOXM1 expression, at the mRNA and protein level, was significantly elevated in tumors with FOXM1 amplification, p53 inactivation, and Rb-E2F deregulation. FOXM1 expression was remarkably high in testicular germ cell tumors (TGCT), high-grade serous ovarian cancer (HGSC), and basal breast cancer (BBC). FOXM1 expression in cancer was associated with genomic instability, as measured using aneuploidy signatures. FTE models confirmed a role for Rb-E2F signaling in FOXM1 regulation and in particular identified Cyclin E1 as a novel inducer of FOXM1 expression. Among the three FOXM1 isoforms, FOXM1c showed the highest expression in normal and tumor tissues and cancer cell lines. The CRISPR knockout model demonstrated that FOXM1b and FOXM1c are transcriptionally active, while FOXM1a is not. Finally, we were unable to confirm the existence of a FOXM1 auto-regulatory loop. This study provides significant and novel information regarding the frequency, causes, and consequences of elevated FOXM1 expression in human cancer.