bluuebunny/crossref_metadata_2025 huggingface dataset:
Brown adipose tissue activity is reduced in women with polycystic ovary syndrome
Authors: Flávia R Oliveira , Mamede Marcelo , Bizzi Mariana F , Ana Luiza L Rocha , Ferreira Cláudia N , Gomes Karina B , Cândido Ana L , Reis Fernando M
Published: September 2019

Objective

To evaluate whether brown adipose tissue (BAT) activity is altered in women with polycystic ovary syndrome (PCOS), and whether BAT activity correlates with plasma levels of irisin, a myokine that can induce BAT formation.

Design

We performed a cross-sectional study including women with PCOS (n = 45) and a healthy control group (n = 25) matched by age and body mass index (BMI).

Methods

BAT activity was measured using 18F-FDG positron emission tomography-computed tomography (PET-CT) and plasma irisin levels were measured by a validated enzyme immunoassay.

Results

Total BAT activity was significantly reduced in women with PCOS (maximal standardized uptake value (SUVmax): median 7.4 g/mL, interquartile range 0.9–15.4) compared to controls (median 13.0 g/mL, interquartile range 4.7–18.4, P = 0.047). However, this difference was no longer significant after adjustment for waist circumference, a surrogate marker of central adiposity. In the PCOS group, BAT activity correlated negatively with BMI (Spearman’s r = −0.630, P = 0.000) and waist circumference (r = −0.592, P = 0.000) but not with plasma irisin levels.

Conclusions

BAT activity was reduced in women with PCOS possibly due to increased central adiposity. In PCOS women, BAT activity did not correlate with plasma irisin levels.
Ghrelin and vascular protection
Authors: Pearson James T , Shirai Mikiyasu , Sukumaran Vijayakumar , Du Cheng-Kun , Tsuchimochi Hirotsugu , Sonobe Takashi , Waddingham Mark T , Katare Rajesh , Schwenke Daryl O
Published: September 2019

Ghrelin is a small peptide with important roles in the regulation of appetite, gut motility, glucose homeostasis as well as cardiovascular protection. This review highlights the role that acyl ghrelin plays in maintaining normal endothelial function by maintaining the balance of vasodilator-vasoconstrictor factors, inhibiting inflammatory cytokine production and immune cell recruitment to sites of vascular injury and by promoting angiogenesis.
Wettbewerb und Privatautonomie: Gegenseitige Gefährdungen im digitalen Zeitalter
Authors: Guski Roman
Published: September 2019

Die Aufgabe des Kartellrechts ist es, eine Selbstsabotage der Privatautonomie zu verhindern. Diese systemimmanente Antinomie nimmt unter Bedingungen digitalisierter Kommunikation neue Formen an. So steuern Intermediäre wie Suchmaschinen und Plattformen den Zugriff auf Informationen und die Bedingungen des Wettbewerbs, und durch datenbezogene Geschäftsbedingungen lassen sich Wirkungen erzielen, die aus Sicht der Privatautonomie problematisch sind. Das Kartellrecht reagiert hierauf durch Erweiterung des Marktbegriffs und Anpassung der Missbrauchstatbestände. Inwiefern das Kartellrecht über den Schutz der Wettbewerbsordnung hinaus eine gesamtgesellschaftliche Ordnungsfunktion hat, ist fraglich. Dies hängt unter anderem davon ab, inwiefern sich systemexterne Voraussetzungen für unternehmerischen Wettbewerb in die kartellrechtliche Bewertung einbeziehen lassen.
Collaboration Based Multi-Label Learning
Authors: Feng Lei , An Bo , He Shuo
Published: September 2019

It is well-known that exploiting label correlations is crucially important to multi-label learning. Most of the existing approaches take label correlations as prior knowledge, which may not correctly characterize the real relationships among labels. Besides, label correlations are normally used to regularize the hypothesis space, while the final predictions are not explicitly correlated. In this paper, we suggest that for each individual label, the final prediction involves the collaboration between its own prediction and the predictions of other labels. Based on this assumption, we first propose a novel method to learn the label correlations via sparse reconstruction in the label space. Then, by seamlessly integrating the learned label correlations into model training, we propose a novel multi-label learning approach that aims to explicitly account for the correlated predictions of labels while training the desired model simultaneously. Extensive experimental results show that our approach outperforms the state-of-the-art counterparts.
Explainable Recommendation through Attentive Multi-View Learning
Authors: Gao Jingyue , Wang Xiting , Wang Yasha , Xie Xing
Published: September 2019

Recommender systems have been playing an increasingly important role in our daily life due to the explosive growth of information. Accuracy and explainability are two core aspects when we evaluate a recommendation model and have become one of the fundamental trade-offs in machine learning. In this paper, we propose to alleviate the trade-off between accuracy and explainability by developing an explainable deep model that combines the advantages of deep learning-based models and existing explainable methods. The basic idea is to build an initial network based on an explainable deep hierarchy (e.g., Microsoft Concept Graph) and improve the model accuracy by optimizing key variables in the hierarchy (e.g., node importance and relevance). To ensure accurate rating prediction, we propose an attentive multi-view learning framework. The framework enables us to handle sparse and noisy data by co-regularizing among different feature levels and combining predictions attentively. To mine readable explanations from the hierarchy, we formulate personalized explanation generation as a constrained tree node selection problem and propose a dynamic programming algorithm to solve it. Experimental results show that our model outperforms state-of-the-art methods in terms of both accuracy and explainability.
Incomplete Label Multi-Task Deep Learning for Spatio-Temporal Event Subtype Forecasting
Authors: Gao Yuyang , Zhao Liang , Wu Lingfei , Ye Yanfang , Xiong Hui , Yang Chaowei
Published: September 2019

Due to the potentially significant benefits for society, forecasting spatio-temporal societal events is currently attracting considerable attention from researchers. Beyond merely predicting the occurrence of future events, practitioners are now looking for information about specific subtypes of future events in order to allocate appropriate amounts and types of resources to manage such events and any associated social risks. However, forecasting event subtypes is far more complex than merely extending binary prediction to cover multiple classes, as 1) different locations require different models to handle their characteristic event subtype patterns due to spatial heterogeneity; 2) historically, many locations have only experienced a incomplete set of event subtypes, thus limiting the local model’s ability to predict previously “unseen” subtypes; and 3) the subtle discrepancy among different event subtypes requires more discriminative and profound representations of societal events. In order to address all these challenges concurrently, we propose a Spatial Incomplete Multi-task Deep leArning (SIMDA) framework that is capable of effectively forecasting the subtypes of future events. The new framework formulates spatial locations into tasks to handle spatial heterogeneity in event subtypes, and learns a joint deep representation of subtypes across tasks. Furthermore, based on the “first law of geography”, spatiallyclosed tasks share similar event subtype patterns such that adjacent tasks can share knowledge with each other effectively. Optimizing the proposed model amounts to a new nonconvex and strongly-coupled problem, we propose a new algorithm based on Alternating Direction Method of Multipliers (ADMM) that can decompose the complex problem into subproblems that can be solved efficiently. Extensive experiments on six real-world datasets demonstrate the effectiveness and efficiency of the proposed model.
Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift
Authors: Gelada Carles , Bellemare Marc G.
Published: September 2019

In this paper we revisit the method of off-policy corrections for reinforcement learning (COP-TD) pioneered by Hallak et al. (2017). Under this method, online updates to the value function are reweighted to avoid divergence issues typical of off-policy learning. While Hallak et al.’s solution is appealing, it cannot easily be transferred to nonlinear function approximation. First, it requires a projection step onto the probability simplex; second, even though the operator describing the expected behavior of the off-policy learning algorithm is convergent, it is not known to be a contraction mapping, and hence, may be more unstable in practice. We address these two issues by introducing a discount factor into COP-TD. We analyze the behavior of discounted COP-TD and find it better behaved from a theoretical perspective. We also propose an alternative soft normalization penalty that can be minimized online and obviates the need for an explicit projection step. We complement our analysis with an empirical evaluation of the two techniques in an off-policy setting on the game Pong from the Atari domain where we find discounted COP-TD to be better behaved in practice than the soft normalization penalty. Finally, we perform a more extensive evaluation of discounted COP-TD in 5 games of the Atari domain, where we find performance gains for our approach.
Interpretation of Neural Networks Is Fragile
Authors: Ghorbani Amirata , Abid Abubakar , Zou James
Published: September 2019

In order for machine learning to be trusted in many applications, it is critical to be able to reliably explain why the machine learning algorithm makes certain predictions. For this reason, a variety of methods have been developed recently to interpret neural network predictions by providing, for example, feature importance maps. For both scientific robustness and security reasons, it is important to know to what extent can the interpretations be altered by small systematic perturbations to the input data, which might be generated by adversaries or by measurement biases. In this paper, we demonstrate how to generate adversarial perturbations that produce perceptively indistinguishable inputs that are assigned the same predicted label, yet have very different interpretations. We systematically characterize the robustness of interpretations generated by several widely-used feature importance interpretation methods (feature importance maps, integrated gradients, and DeepLIFT) on ImageNet and CIFAR-10. In all cases, our experiments show that systematic perturbations can lead to dramatically different interpretations without changing the label. We extend these results to show that interpretations based on exemplars (e.g. influence functions) are similarly susceptible to adversarial attack. Our analysis of the geometry of the Hessian matrix gives insight on why robustness is a general challenge to current interpretation approaches.
Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input
Authors: Guo Junliang , Tan Xu , He Di , Qin Tao , Xu Linli , Liu Tie-Yan
Published: September 2019

Non-autoregressive translation (NAT) models, which remove the dependence on previous target tokens from the inputs of the decoder, achieve significantly inference speedup but at the cost of inferior accuracy compared to autoregressive translation (AT) models. Previous work shows that the quality of the inputs of the decoder is important and largely impacts the model accuracy. In this paper, we propose two methods to enhance the decoder inputs so as to improve NAT models. The first one directly leverages a phrase table generated by conventional SMT approaches to translate source tokens to target tokens, which are then fed into the decoder as inputs. The second one transforms source-side word embeddings to target-side word embeddings through sentence-level alignment and word-level adversary learning, and then feeds the transformed word embeddings into the decoder as inputs. Experimental results show our method largely outperforms the NAT baseline (Gu et al. 2017) by 5.11 BLEU scores on WMT14 English-German task and 4.72 BLEU scores on WMT16 English-Romanian task.
Distributional Semantics Meets Multi-Label Learning
Authors: Gupta Vivek , Wadbude Rahul , Natarajan Nagarajan , Karnick Harish , Jain Prateek , Rai Piyush
Published: September 2019

We present a label embedding based approach to large-scale multi-label learning, drawing inspiration from ideas rooted in distributional semantics, specifically the Skip Gram Negative Sampling (SGNS) approach, widely used to learn word embeddings. Besides leading to a highly scalable model for multi-label learning, our approach highlights interesting connections between label embedding methods commonly used for multi-label learning and paragraph embedding methods commonly used for learning representations of text data. The framework easily extends to incorporating auxiliary information such as label-label correlations; this is crucial especially when many training instances are only partially annotated. To facilitate end-to-end learning, we develop a joint learning algorithm that can learn the embeddings as well as a regression model that predicts these embeddings for the new input to be annotated, via efficient gradient based methods. We demonstrate the effectiveness of our approach through an extensive set of experiments on a variety of benchmark datasets, and show that the proposed models perform favorably as compared to state-of-the-art methods for large-scale multi-label learning.
Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons
Authors: Heo Byeongho , Lee Minsik , Yun Sangdoo , Choi Jin Young
Published: September 2019

An activation boundary for a neuron refers to a separating hyperplane that determines whether the neuron is activated or deactivated. It has been long considered in neural networks that the activations of neurons, rather than their exact output values, play the most important role in forming classificationfriendly partitions of the hidden feature space. However, as far as we know, this aspect of neural networks has not been considered in the literature of knowledge transfer. In this paper, we propose a knowledge transfer method via distillation of activation boundaries formed by hidden neurons. For the distillation, we propose an activation transfer loss that has the minimum value when the boundaries generated by the student coincide with those by the teacher. Since the activation transfer loss is not differentiable, we design a piecewise differentiable loss approximating the activation transfer loss. By the proposed method, the student learns a separating boundary between activation region and deactivation region formed by each neuron in the teacher. Through the experiments in various aspects of knowledge transfer, it is verified that the proposed method outperforms the current state-of-the-art.
Shear strength of cement-treated marine clay under triaxial and plane strain conditions
Authors: Azneb A. S. , Banerjee Subhadeep , Robinson Retnamony G.
Published: September 2019

Conventional triaxial compression and unconfined compressive strength tests are the most common testing methods used in the laboratory to determine the shear strength of soil. These tests employ the axisymmetric condition for testing. However, several geotechnical problems in the field can be approximated as plane strain (PS) problems. Hence, testing under PS condition would better represent such field conditions. PS testing has been widely performed on natural soils in the past. However, PS testing on cement-treated clays has not been reported in the literature. This paper attempts to explore the PS behaviour of cement-treated marine clays. A comparison of the strength behaviour of cement-treated clays under PS and triaxial tests has also been presented in this paper.
Pull-out behaviour of simulated tree roots embedded in compacted soil
Authors: Galpathage Shiran G. , Indraratna Buddhima , Heitor Ana , Rujikiatkamjorn Cholachat
Published: September 2019

Vegetated ground is strengthened by the suction generated during evapotranspiration as well as physically and mechanically by the reinforcement effect induced by tree roots. When suction suddenly decreases during flooding or intense rainfall, the shear strength of the soil–plant system relies mainly on the physical root reinforcement. In this paper, the pull-out behaviour of simulated roots embedded in a compacted soil is investigated to assess how the soil–plant system is mechanically strengthened. An analytical framework is developed to estimate the pull-out force and it is validated using a series of pull-out tests. The tests are carried out on simulated roots embedded in a box of compacted soil having different water contents and equivalent dry unit weights. The results show that the pull-out capacity of this root system is mainly influenced by the initial (as-compacted) suction, and the length and diameter of the roots. The model predictions agree reasonably well with the experimental observations.
The efficiency of confinement reinforcement in post-tensioning anchorage zones
Authors: Rebelo Jorge , Marchão Carla , Lúcio Válter
Published: September 2019

In this paper, a parametric study based on the load transfer test specified in ETAG 013 was performed with the aim of investigating the efficiency of the confining reinforcement in the local anchorage zone of post-tensioning tendons, in particular when there are two types of confining reinforcement, spiral and stirrups. The parametric study was conducted using the finite element software ATENA 3D and included 45 specimens of ordinary concrete reinforced with a combination of spirals and stirrups. The models were calibrated using the experimental results obtained in tests of similar specimens. The influence of concrete strength, cross-section dimensions, reinforcement ratio and type of anchorage device were investigated. The reinforcement strains were monitored to assess the relation between the strains of the inner and outer levels of reinforcement and the uniformity of the confinement forces along the confined length. A comparison between the bearing strength obtained by the numerical simulation and that obtained by models found in the literature is also presented. From the analysis of the strain values, it can be concluded that the spiral reinforcement is more effective. However, the results show that stirrups make an important contribution to the control of concrete cracking.
Adsorption of water and fatty acids at magnesium hydroxide surface from an MDS perspective
Authors: Liu Weiping , Xu Hui , Wang Zhixing , Wang Xuming
Published: September 2019

The adsorption characteristics of fatty acids at the magnesium hydroxide (Mg(OH)2) surface are crucial in the wet surface modification process for the preparation of apyrous high-polymer materials and the concentration of brucite by flotation. In this regard, the interfacial water structures at the magnesium hydroxide (001), (101), (102) and (110) surfaces were examined and compared. The adsorption of fatty acids – namely, undecylenic acid (C11H20O2), lauric acid (C12H24O2), oleic acid (C18H34O2) and stearic acid (C18H36O2) – and their hydrophobicity at the magnesium hydroxide (001) surface were investigated by molecular dynamics simulation (MDS). The results indicate that the magnesium hydroxide (101) and (001) surfaces have the greatest and least effect on the interfacial water structure, respectively. The fatty acids overall have similar adsorption affinity at the magnesium hydroxide (001) cleavage surface, while the chemical reaction mainly contributes to the fatty acid adsorption at the magnesium hydroxide (001) surface. The hydrophobicity of the magnesium hydroxide surface increases as a function of the carbon (C) chain length with the adsorption of fatty acids. The presented results improve the fundamental understanding of fatty acid adsorption at the magnesium hydroxide surface, which will help enhance and/or support the robust performance of magnesium hydroxide wet surface modification and brucite flotation.
A Toolbox to Characterize Human Induced Pluripotent Stem Cell–Derived Kidney Cell Types and Organoids
Authors: Vanslambrouck Jessica M. , Wilson Sean B. , Tan Ker Sin , Soo Joanne Y.-C. , Scurr Michelle , Spijker H. Siebe , Starks Lakshi T. , Neilson Amber , Cui Xiaoxia , Jain Sanjay , Little Melissa Helen , Howden Sara E.
Published: September 2019

Significance Statement

Kidney organoids generated from human induced pluripotent stem cells (iPSCs) show great potential for modeling kidney diseases and studying disease pathogenesis. However, the relative accuracy with which kidney organoids model normal morphogenesis, as well as the maturity and identity of the renal cell types they comprise, remain to be fully investigated. The authors describe the generation and validation of ten fluorescent CRISPR/Cas9 gene-edited iPSC reporter lines specifically designed for the visualization, isolation, and characterization of cell types and states within kidney organoids, and demonstrate the use of these lines for cellular isolation, time-lapse imaging, protocol optimization, and lineage-tracing applications. These tools offer promise for better understanding this model system and its congruence with human kidney morphogenesis.

Background

The generation of reporter lines for cell identity, lineage, and physiologic state has provided a powerful tool in advancing the dissection of mouse kidney morphogenesis at a molecular level. Although use of this approach is not an option for studying human development in vivo, its application in human induced pluripotent stem cells (iPSCs) is now feasible.

Methods

We used CRISPR/Cas9 gene editing to generate ten fluorescence reporter iPSC lines designed to identify nephron progenitors, podocytes, proximal and distal nephron, and ureteric epithelium. Directed differentiation to kidney organoids was performed according to published protocols. Using immunofluorescence and live confocal microscopy, flow cytometry, and cell sorting techniques, we investigated organoid patterning and reporter expression characteristics.

Results

Each iPSC reporter line formed well patterned kidney organoids. All reporter lines showed congruence of endogenous gene and protein expression, enabling isolation and characterization of kidney cell types of interest. We also demonstrated successful application of reporter lines for time-lapse imaging and mouse transplantation experiments.

Conclusions

We generated, validated, and applied a suite of fluorescence iPSC reporter lines for the study of morphogenesis within human kidney organoids. This fluorescent iPSC reporter toolbox enables the visualization and isolation of key populations in forming kidney organoids, facilitating a range of applications, including cellular isolation, time-lapse imaging, protocol optimization, and lineage-tracing approaches. These tools offer promise for enhancing our understanding of this model system and its correspondence with human kidney morphogenesis.
Does Trade Policy Uncertainty Affect Global Economic Activity?
Authors: Caldara Dario , Raffo Andrea , Iacoviello Matteo , Molligo Patrick , Prestipino Andrea
Published: September 2019

In this note, we first document the recent rise in trade policy uncertainty, henceforth TPU, by using two complementary measures based on text-search analysis: one focusing on newspapers articles, and another constructed from transcripts of firms' earning calls. We then use econometric evidence on the joint movements in aggregate TPU, industrial production, and other macroeconomic variables in order to provide an estimate of the effects of the recent spikes in TPU on U.S. GDP, as well as GDP in advanced foreign economies (AFEs) and emerging market economies (EMEs).
Biological rationale for a patient-specific approach in the treatment of breast cancer. Clinical value of novel biomarkers of breast cancer
Authors: Paltuev R. M.
Published: September 2019

Breast cancer, being the most common type of malignant diseases, remains a significant challenge for both clinicians and fundamental researchers. The implementation of screening mammography, as well as adjuvant and neoadjuvant systemic therapy has made a significant progress in tackling the disease. The studies aimed at the assessment of novel biomarkers of breast cancer, alternative to standard ones, are becoming increasingly relevant. A number of new markers, such as p53, CK5/6, SMA, p63, PHH3, E-cadherin, EGFR, FOXA1, androgen receptors, TILs etc., have demonstrated their high predictive and/or prognostic value in multiple studies. New findings suggest that evaluation of novel biomarkers in breast cancer requires further thorough analysis.

Recent studies have identified the role of biomarkers in choosing an optimal treatment strategy for breast cancer, estimated the prognostic value of biomarkers associated with tumor proliferative activity (including cyclin D1, G1-cyclin-dependent kinases 4 and 6, and cyclin-dependent kinases 8/19), specified the role of phospho-histone H3 (which is a proliferation marker that can be used to determine tumor grade), and evaluated the prognostic value of androgen receptors and other biomarkers. Multiple studies have also analyzed the expression of various biomarkers and their impact on overall and relapse-free survival.
Estrategias de mediación para fortalecer la comunicación oral en el Nivel Medio Superior
Authors: Valero Rivero Dámaris , Gallues Leiva Ida Lys
Published: September 2019

La comunicación en el preuniversitario es de gran importancia porque se pretende que los egresados de este nivel sean personas críticas, participativas, activas, para exponer opiniones y argumentaciones. En este contexto el presente artículo se orienta a proponer estrategias de mediación didáctica para fortalecer procesos de comunicación oral desde la clase de Español Literatura en los estudiantes del Nivel Medio Superior. Se trabaja un diseño documental y de campo que incluye un componente teórico y otro empírico, donde se aplican técnicas como encuestas, observación participante y entrevista semiestructurada aplicada a un grupo de estudiantes que cursan el preuniversitario. Entre los resultados destacan logros en una dimensión cuantitativa y otra cualitativa; con base en la información acumulada en la indagación final y tomando como referente el desarrollo de habilidades para la expresión oral, en los siguientes rangos: bajo 2 (8.0%); medio 2 (8.0%); alto 21(84%). Entre las principales conclusiones se validan las estrategias propuestas puesto que apuntan a fortalecer procesos de mediación en torno a habilidades comunicacionales formándolos desde los criterios de asertividad, eficacia y eficiencia.
Internal youth migration in Uganda: Analyzing associates and employment outcomes
Authors: Mirembe Sandra , Nzabona Abel , Mushomi John A.
Published: September 2019

Youth internal migration is seen as a solution to youth unemployment, and this has resulted in over urbanization and its associated negative effects such as congestion, pollution, unemployment, underemployment, and increased crime rates. The study aimed at examining the employment status of youth migrants, assessing the relationship between demographic factors and youth internal migration, investigating the association between socio-economic factors and youth internal migration, and evaluating the association between reasons for migration and migrant employment status. The study used secondary data collected in the youth employment and migration in Eastern and Southern Africa project. In Uganda, the project was carried out in nine districts. The study focused on both men and women aged 18-35 years and a total number of 1524 respondents were interviewed. Results of the study revealed that age, residence, and region had a significant association with migration status (p≤0.05). Age, sex, number of children, region, and reasons for migration had a significant association with self-employment status of the migrant (p<0.05). Marital status, sex, and reasons for migration had an association with the possibility of a migrant youth being employed (p≤0.05). The study recommends that local governments should provide the required infrastructures, social services, and amenities to encourage youths to carry out economic activities so as to develop their places of origin.
Design and Performance Analysis of B15 Engine Intake System
Authors: Wen Shirong , Wei Baolei , Tong Huabei
Published: September 2019

In recent years, with the development of the economy, the automobile industry has also undergone ever-changing changes. At present, the design of the engine in addition to the car to achieve the dynamic, economic indicators but also need to meet their emissions and noise requirements, it is necessary for the engine into the exhaust system for in-depth study. The intake system mainly comprises two parts of the pipeline and the intake manifold before the intake manifold, in which the pipeline in front of the manifold acts to reduce the intake noise. How to design the components of the intake system reasonably and analyze its comprehensive performance is the most important topic in the project.

Firstly, this article introduces the principle of variable valve timing and variable intake manifold technology, establishes B15 engine model in GT-Power software and uses the test data to complete the calibration of the model so that the error is not more than 5% for subsequent simulation calculations. In order to design the silencer element of the intake system, the sensitivity of the parameters of the Helmholtz resonator, 1/4 wavelength tube and air ﬁlter is calculated and analyzed, and the inﬂuence of the parameter change on the muﬄer performance is summarized. The design ﬂow and method of the intake muﬄer element are described in detail, and the concrete design scheme is put forward. The noise of the muﬄer element is optimized according to the problem that the noise of the individual order is higher than the target value. After the optimization of the intake system air intake noise improved significantly, the pressure loss is no higher than 2.5 kPa, in line with the target value requirements, the optimization effect is good.

Secondly, in order to analyze the performance of the intake manifold, three methods are proposed: the zero-dimensional or one-dimensional model is used to simplify the processing, and the CFD software is used to calculate the steady-state or isolated transients and the coupling analysis using one-dimensional and three-dimensional software. By comparing the advantages and disadvantages of the three methods, it is found that the coupling of software can obtain real-time boundary condition in the calculation process and have high accuracy. This paper focuses on the key issues that need to be solved by coupling with GT-Power and STAR-CCM + software and completes the calculation of the model.

Finally, in order to evaluate the advantages and disadvantages of the intake muﬄer element better, the maximum noise of the intake system is calculated by using the model of the vehicle acceleration in the GT-Power software, and the maximum noise of the intake system is 61.8 dB (A) which satisfies the target requirement for the individual contribution rate through noise.
A Comparative Study of Iranian Smell Identification Test (Iran-SIT) and Single-photon Emission Computed Tomography (SPECT) Results in Discrimination of Anosmia and Malingering in Forensic Cases
Authors: Pouraghaei S. , Samadirad B. , Baybordi E. , Seyffarshad AA. , Seraj J.Mehdizadeh , Kolahi F. , Taherkhani S.
Published: September 2019

Purpose: Olfactory dysfunction is a common complaint following head trauma. Few subjective and objective tests had been proposed for purposes of litigation. Currently, the two most common methodologies for separating malingerers from genuine anosmics are single-photon emission computed tomography (SPECT) and smell identification tests as objective and subjective tests, respectively. The objective of the present study was to compare the efficacy of the SPECT and Iranian Smell Identification Test (Iran-SIT) in discrimination of anosmia and malingering in forensic cases. Method: All of the 16 subjects that fulfilled the requirements completely, underwent both SPECT imaging and Iran-SIT assessment. Results: The sensitivity of SPECT in diagnosing malingering and anosmia was estimated to be 66.6% and 87.5%, respectively. That of Iran-SIT was estimated to be 90% and 75%, respectively. In addition, the sensitivity and specificity of Iran-SIT in diagnosing hyposmia were 100%. Conclusion: Because of the higher sensitivity of Iran-SIT in diagnosing anosmia and higher specificity in diagnosing malingering, it is recommended for directly ruling out the suspicious cases.
Research and Verification of Blackbody Radiation Law
Authors: Lu Xiaoming , Tang Qishan , Kang Wendong
Published: September 2019

Blackbody radiation theory is one of the important origins of light quantum theory in the twentieth century. It is not only an important basis for quantum mechanics and photonics theory, but also an important conclusion of blackbody radiation, and an important foundation of modern measurement. In the early nineteenth century, the study of thermal radiation was supported by thermodynamics and spectroscopy, and the rapid development of electromagnetism and optics was used. By the end of the 19th century, it was recognized that both the thermal radiation and the optical radiation were electromagnetic waves, and began to study the distribution of radiant energy in different frequency ranges, especially the study of blackbody radiation in theory and practice. Blackbody radiation experiment is one of the contents of modern physics experiment in colleges and universities. This paper mainly studies and validates the law of blackbody radiation by the WGH-10 blackbody experimental device. There is already a calibrated bromine tungsten lamp energy curve at 2940k. At the beginning of the experiment, we should scan at 2940k color temperature to get the baseline, and then calculate the transfer function. Again, the energy curve obtained by scanning at different color temperatures is divided by the transfer function to obtain the correct energy radiation curve. The experimental study of blackbody radiation by computer scanning grating spectrometer and bromine tungsten lamp was carried out. By means of scrolling grating and sine mechanism, the data were recorded by computer scanning to verify the three laws of blackbody radiation directly, and the radiation, transmission and reception of blackbody were analyzed Error correction. 
Fitting of decomposition of sewage sludge and oat straw by nonlinear models
Authors: Silva Edilson Marcelino , Silveira Silvio de Castro , Ribeiro Furtado Thais Destefani , Muniz Joel Augusto
Published: September 2019

An economic and environmentally feasible way to recycle sewage sludge is its use in agriculture.Information on carbon mineralization curves allows us to seek improvements in soil quality andcrop productivity. The objective of this work was to evaluate the nonlinear models that describecarbon mineralization in the soil. The experiment was conducted in laboratory and the design wascompletely randomized, with four replicates and three treatments. The following treatments wereevaluated: sewage sludge, black oat straw and sewage sludge + oat straw, incorporated into the soil.Pots with soil and the applied treatment were incubated for 110 days. The Stanford and Smith andCabrera models were used, considering structure of autoregressive errors AR (1) when necessary.The fittings were compared using the Akaike Information Criterion (AIC). The evaluated nonlinearmodels described the carbon decomposition dynamics of the treatments satisfactorily. The Stanfordand Smith model is suitable for describing the carbon decomposition in the soil + sludge and soil +oat straw treatments. The Cabrera model is suitable to describe the carbon decomposition of the soil+ sludge + straw treatment.Keywords: Mineralization. Stanford and Smith model. Cabrera model. Half-life.
Description of the carbon mineralization of swine manure and oat straw in the soil through nonlinear models
Authors: Silva Edilson Marcelino , Ribeiro Thais Destefani , Fernandes Jaqueline Gonçalves , Muniz Joel Augusto
Published: September 2019

Agricultural management is a viable way for recycling animal residues in feedlots. Thesubstances that make up organic residues change the dynamics of the organic matter decompositionin the soil. Information on carbon mineralization curves allows seeking improvements in soil qualityand, consequently, in crop productivity. The Stanford & Smith Nonlinear Model is the most usedto describe C mineralization of organic residues in the soil. This model considers organic residuesare composed of substances that are mineralized exponentially. The Cabrera Model considers twofractions, one composed of substances that are mineralized exponentially and other composed ofmore resistant substances with constant mineralization. The objective of this work was to comparenonlinear models that describe carbon mineralization, considering residues on surface or incorporatedinto the soil. The data evaluated were from an experiment with oat straw, liquid swine manure, andswine litter bedding. The Stanford & Smith and Cabrera Models were used considering structure offirst order autoregressive errors - AR(1), when necessary. The fittings were compared using the AkaikeInformation Criterion (AIC). The Cabrera Model was more adequate to describe C mineralization infour treatments (soil + incorporated liquid swine manure; soil + oat straw on surface + liquid swinemanure on surface; soil + incorporated straw; and soil + straw on surface). The Stanford & SmithModel was better in three treatments (soil + incorporated straw + incorporated liquid swine manure;swine litter bedding on surface; and incorporated swine litter bedding). None of the models describedthe treatment soil + liquid swine manure on surface.Keywords: Decomposition. Half-life. Stanford & Smith Model. Cabrera Model.
A Modified Subformula Property for the Modal Logic S4.2
Authors: Takano Mitio
Published: September 2019

The modal logic S4.2 is S4 with the additional axiom ◊□A ⊃ □◊A. In this article, the sequent calculus GS4.2 for this logic is presented, and by imposing an appropriate restriction on the application of the cut-rule, it is shown that, every GS4.2-provable sequent S has a GS4.2-proof such that every formula occurring in it is either a subformula of some formula in S, or the formula □¬□B or ¬□B, where □B occurs in the scope of some occurrence of □ in some formula of S. These are just the K5-subformulas of some formula in S which were introduced by us to show the modied subformula property for the modal logics K5 and K5D (Bull Sect Logic 30(2): 115–122, 2001). Some corollaries including the interpolation property for S4.2 follow from this. By slightly modifying the proof, the finite model property also follows.
Gradualizm etyczny – poza antropocentryzmem i biocentryzmem?
Authors: Skirbekk Gunnar
Published: September 2019

Obszar etyki jest najczęściej ograniczany do człowieka i świata ludzkiego: tylko ludzie mogą działać moralnie lub niemoralnie, tylko ludzie mogą być z moralnego punktu widzenia godni pochwały lub nagany; tylko ludziom przypisuje się status podmiotów moralnego działania i podmiotów moralnych praw. W jakim stopniu ten antropocentryzm etyczny daje się utrzymać? Czy współczesna wiedza biologiczna, uwydatniająca ciągłość i stopniowalność cech właściwych dla istot żywych, nie podważa takiego mocnego rozgraniczenia i założenia o uprzywilejowanej pozycji człowieka? Czy nie powinniśmy wyjść poza gatunkowy egoizm, a przynajmniej go ograniczyć? W niniejszym artykule rozważę argumenty na rzecz stanowiącej osobny paradygmat, wyjątkowej pozycji etycznej człowieka oraz zbadam argumenty na rzecz etycznego gradualizmu [czyli stopniowalnych różnic] między istotami ludzkimi (humans) a pozostałymi ssakami oraz między człowiekiem a przyrodą.
Pokazać niedające się pokazać. Wieloznaczność i wytwarzanie (obrazów) wspólnoty
Authors: Sikorska Karolina
Published: September 2019

W artykule przyglądam się strategiom wizualizowania wspólnoty zawartym w wideo Anny Okrasko Next to you I remember I am (2016). Elementy konstrukcji wyobrażeń wspólnot oparte są na przemówieniu polityka i scenach z procesji religijnych. Analizując wartości, organizujące te opowieści, zastanawiam się nie tylko nad rzeczywistością, do której się odnoszą, ale próbuję również zdać sprawę z roli, jaką w konstruowaniu lub/i demontowaniu wywołanych wspólnot odgrywa wieloznaczność (traktowana za Zygmuntem Baumanem jako praktyka specyficznie nowoczesna i ujawniająca się w nieustannym starciu z potrzebą ładu).
Nasḫī – an Efficient Tool for the OCR-Aided Transcription of Printed Texts
Authors: Büttner Andreas
Published: September 2019

This paper presents a simple yet effective solution for the transcrip- tion of printed texts. Our tool consists of a web-based user interface that provides an easy-to-use and ergonomic workflow and a col- laborative environment for the philologists while allowing them to profit from machine learning OCR technology. As the targeted use case is not mass digitisation but the creation of accurate citable digital editions, the user interface for ground truth production and post correction is built to provide the means for rapid proofread- ing while minimising the amount of errors. The productivity of the setup is further improved by enabling progressive OCR train- ing and recognition in the background to constantly increase the accuracy of the predictions. The advantages of the application are showcased in the second part of the paper by documenting our experiences utilising it for di- gitising Arabic and Latin texts. Over the course of several months the tool has been used to create transcriptions of a wide range of sources, among them challenging early modern editions and Ar- abic scripts, producing a large amount of reusable OCR training data as a positive side effect. Finally, there will be a discussion of possible future extensions of the tool and of how it could be adapted to fit the needs of other digitisation projects.
Analisis Pengembangan Ekspor Pala, Lawang, dan Kapulaga Indonesia
Authors: Nurhayati Ely , Hartoyo Sri , Mulatsih Sri
Published: September 2019

Export is an important component in the economy. The higher export performance, the greater positive impact. From 2012 to 2016, Indonesia’s exports continued to decline, so Indonesia needs to boost its exports. One of the potential commodities to be developed is nutmeg, mace, and cardamoms. This study analyzed the competitiveness of nutmeg, mace, and cardamoms, as well as the factors aecting its exports. The methods used are RCA, EPD, X-Model, and Gravity. The competitiveness analysis showed that the optimistic export markets were Pakistan, Germany, Italy, and USA. The potential export markets were Malaysia, Vietnam, Thailand, France, and Netherlands. Factors that affecting exports were GDP per capita, price, economic distance, and tariff. -------------------------------- Ekspor merupakan komponen penting dalam perekonomian. Semakin tinggi kinerja ekspor, semakin besar pula dampak positifnya. Sejak 2012 hingga 2016, ekspor Indonesia terus menurun sehingga Indonesia perlu meningkatkan kembali ekspornya. Salah satu komoditas yang potensial dikembangkan adalah pala, lawang, dan kapulaga. Penelitian ini menganalisis daya saing pala, lawang, dan kapulaga, serta faktor yang memengaruhi ekspornya. Metode yang digunakan adalah RCA, EPD, X-Model, dan Gravity. Hasil analisis daya saing menunjukkan bahwa pasar ekspor yang optimis adalah Pakistan, Jerman, Italia, dan Amerika Serikat. Pasar ekspor yang potensial adalah Malaysia, Vietnam, Thailand, Prancis, dan Belanda. Faktor yang memengaruhi ekspor adalah PDB per kapita, harga, jarak ekonomi, dan tarif.
Bootstrap LM Tests for Spatial Dependence in Panel Data Models with Fixed Effects
Authors: Ou Bianling , Long Zhihe , Li Wenqian
Published: September 2019

This paper applies bootstrap methods to LM tests (including LM-lag test and LM-error test) for spatial dependence in panel data models with fixed effects, and removes fixed effects based on orthogonal transformation method proposed by Lee and Yu (2010). The consistencies of LM tests and their bootstrap versions are proved, and then some asymptotic refinements of bootstrap LM tests are obtained. It shows that the convergence rate of bootstrap LM tests isO((NT)−2) and that of fast double bootstrap LM tests isO((NT)−5/2). Extensive Monte Carlo experiments suggest that, compared to aysmptotic LM tests, the size of bootstrap LM tests gets closer to the nominal level of signifiance, and the power of bootstrap LM tests is higher, especially in the cases with small spatial correlation. Moreover, when the error is not normal or with heteroskedastic, asymptotic LM tests suffer from severe size distortion, but the size of bootstrap LM tests is close to the nominal significance level. Bootstrap LM tests are superior to aysmptotic LM tests in terms of size and power.
Taxation, exchange rate and foreign direct investment in Nigeria
Authors: Ranti Uwuigbe Olubukola , Omoyiola Ayomide , Uwuigbe Uwalomwa , Lanre Nassar , Ajetunmobi Opeyemi
Published: September 2019

This paper investigates factors that may impact foreign direct investment in Nigeria. It seeks to establish the role of taxation (corporate tax) for foreign direct investment in Nigeria. Annual time series data derived from the Central Bank of Nigeria statistical bulletin and the United Nations Conference on Trade and Development covering a period of 31 years (1985–2015) were used for this study. The variables considered in the study include FDI, corporate tax, exchange rate, inflation rate, real gross domestic product (RGDP). They were analyzed using Ordinary Least Squares (OLS), Johansen Co-Integration model and Unit Root Test. Findings from this research observed that a negative relationship exists between corporate taxation and FDI. Also, the study observed that corporate tax have a significant impact on FDI and there exists a long-run relationship between the two variables.
Analysis of the stability factors of Ukrainian banks during the 2014–2017 systemic crisis using the Kohonen self-organizing neural networks
Authors: Mints Oleksii , Marhasova Viktoriya , Hlukha Hanna , Kurok Roman , Kolodizieva Tetiana
Published: September 2019

The article proposes an approach to analyzing reliability factors of commercial banks during the 2014–2017 systemic crisis in the Ukrainian banking system, using the Kohonen self-organizing neural networks and maps. As a result of an experimental study, data were obtained on financial factors affecting the stability of a commercial bank in a crisis period.
It has been concluded that during the banking crisis in Ukraine in 2014–2017, the resource base of a bank was the main factor of this bank stability. The most preferred sources of resources were funds from other banks (bankruptcy rate of 5.7%) and legal entities (bankruptcy rate of 8%), and the least stable were funds from individuals (bankruptcy rate of 28.5%).
The relationship between financial stability and the amount of capital and the structure of bank loans is less pronounced. However, one can say that banks that focused on lending to individuals experienced a worse crisis than banks whose main borrowers were legal entities.
The tools considered in the article (the Kohonen self-organizing neural networks and maps) allow for efficiently segmenting data samples according to various criteria, including bank solvency. The “hazardous” zones with a high bankruptcy rate (up to 49.2%) and the “safe” zone with a low rate of bankruptcy (6.3%) were highlighted on the map constructed. These results are of practical value and can be used in analyzing and selecting counterparties in the banking system during a downturn.