bluuebunny/crossref_metadata_2025 huggingface dataset:
Granular Computing Based on Graph Theory
Authors: Guan Sujie , Li Min , Deng Shaobo
Published: September 2020

The rough set theory begins with the concepts of the equivalence relations and equivalence classes. Then, we will use the equivalence relation to research granulation and granulation computing. In current paper, we present the concepts of elementary granulation and granulation, and describe how to convert a decision table into a granular network which has the characteristics of simple and intuitive for describe a decision table. We also define a granular network for a decision table. On this basis, we present a concrete method for converting a decision table into a granular network and give an example for illustrate purpose. Further, we describe a type of data reduction algorithm based on granular network. Lastly, we prove that the data reduction based on data analysis method is equivalent to the data reduction based on granular network. The data reduction based on granular network has the characteristics of simple and intuitive. Theoretical analysis and experimental results indicate that the proposed approach for the data reduction is efficient and feasible.
A CNN Based Method for Quantitatively Evaluating 3D Face Reconstruction Algorithms
Authors: Sun Miao , Singh Gurjeet , Yin Chiang Patrick
Published: September 2020

3D face reconstruction is an attractive topic in computer vision. We have seen dramatic rise in its development recently. Now the state-of-the-art method can reconstruct a face from a single 2D face image. Since the work conditions and cost of a 3D scanner is limited, these 3D reconstruction algorithms are tough to evaluate. Some researchers had proposed different algorithms by measuring the distances between reconstructed images and true depth face previously. Inspired by CNN’s powerful representative ability, here we investigate the issue from CNN’s perspective by comparing the performances of various 3D face reconstruction algorithms on two classification tasks. One is an identity classification task for evaluating the intra-dataset discrimination and another is a binary classification for reconstructed faces and 3D ground truth faces for evaluating the inter-dataset discrimination. To accomplish this, we adopt hourglass neural network as backbone to perform comparisons for three 3D reconstructed algorithms on two datasets. In the end, we show the pros and cons of various algorithms and explicit the mechanisms of the results.
An Accelerated U-Shapelet Time Series Clustering Method with LSH
Authors: Luo Linghao , Lv Shu
Published: September 2020

The clustering method of time series is based on the measurement of the whole time series, and the traditional clustering method is used for direct clustering. It was only recently that Keough came up with the concept of Shapelet. He later applied this concept to unsupervised time series clustering. This is a time series clustering method based on the feature of sub-series. This method has good clustering accuracy and stability. However, due to the fact that traversal sequences are all sub-sequences, the original violent search algorithm is very complex and difficult to be applied to a large number of time series data sets. In this paper, on the basis of the original method, you introduce the idea of data retrieval in the data preprocessing stage to quickly screen candidate subsequences. Then we introduce a position-aware hashing algorithm -LSH. The method is used to match the sub-sequences of the pre-processed time series data, and the wide representativeness of the high-quality u-Shapelet is used for selection. Therefore, LSH-us is proposed in this paper to speed up the extraction process of feature sub-sequences. Experimental results show that this algorithm can improve the speed of u-Shapelet time series clustering algorithm and ensure the accuracy of clustering.
Research on Iron Surface Crack Detection Algorithm Based on Improved YOLOv4 Network
Authors: Deng Huafu , Cheng Jianghua , Liu Tong , Cheng Bang , Sun Zhenhua
Published: September 2020

Metal surface defect detection has always been an important branch of target detection. In certain places, if the cracks on the metal surface can be found in time, the existing safety hazards can be eliminated. In this paper, a polarized imaging camera with strong environmental applicability is used for sampling, and the degree of polarization image is applied to the detection of iron material cracks. The iron material polarization image crack data set (PICD-iron) is established, and the Cascade-YOLOv4 (C-YOLOv4) network model is used for crack detection. Then it solves the problems of target detection in the dark environment, complex and variable crack detection, small target detection. Experimental tests verify that the detection accuracy of the C-YOLOv4 net-work has improved while comparing with the YOLOv4 network, the detection speed has also increased by 28%.
Risk Analysis of Enterprise Management Accounting Based on Big Data Association Rule Algorithm
Authors: Wang Zhenkun , Qiong Makai , Wang Hanjie
Published: September 2020

With the popularization of the development and applications of information technology, enterprise’s management in making decisions is paying more attention to “data driven” and depend on the objective data rather than subjective judgement, in addition to the basic financial data, enterprises in daily operation will produce a very large number of data, despite big data itself is a special kind of enterprise assets, but in order to get valuable information from these data, we must filter out the useless data based on the analysis method of big data, mine and sort out the comparable information, and provide reference for decision makers. The combination of big data and management accounting is the inevitable development trend in future, this article adopted the method Empirical Analysis to establish enterprise management accounting risk analysis model and simulated enterprise using big data analysis method, determined ten key financial indicators the enterprise needed to pay attention to in enterprise risk control, to show the application of big data analysis method in the process of enterprise management accounting, and looked forward to the future of interdisciplinary integration of big data and management accounting.
Containment Control for Lipschitz Nonlinear Multi-agent Systems with Semi-Markov Switching Topologies
Authors: Huang Hui , Zou Yuanyuan , Hu Peng , Cai Qingrong , Jiang Li , Liang Yanyang , Wang Hongmin , Tang Jianhua
Published: September 2020

This letter studies containment control and the communicate topologies are driven by a semi-Markov chain. The Lipschitz nonlinear stochastic systems are investigated in this paper. The error system is established by model transformation, and the containment control is transformed into error stability between followers and multiple leaders. Then, a control protocol is employed and a Lyapunov-Krasovskii method is established to analyze the protocol. Moreover, we prove the specific point that followers ultimately will converge to. Finally, we give the conditions that followers converge leader’s convex hull in mean square sense.
Dynamic Multi-view Combination for Image Classification
Authors: Li Chenghua , Wang Wanguo , Liu Fengyuan , Guo Zhenyu
Published: September 2020

Multi-view learning is widely used in image classification tasks to better explore the discriminative information of different views. However, existing multi-view methods commonly rely on some pre-defined assumptions or fail to fully take advantage of the combination commonality between individual images. This paper presents an efficient dynamic multi-view combination approach to dynamically combine the discriminative power of different views. Specially, we firstly utilize a group of pre-trained CNNs to extract different views of an image. Secondly, we apply a dynamic gating module to the image, which will generate a weight vector of these views to model the image-level information for the multi-view learning. Finally, the weight vector and the views are combined for the classification. Experimental results and analysis on CIFAR-10 and ImageNet show the effectiveness of the proposed dynamic multi-view combination method (DMVC) for visual classification.
Data Expansion Method Based on Wavelet Transform
Authors: Li Xiaochun , Li Wen , Liu Zhe
Published: September 2020

For small sample data, data expansion is an effective means to improve the accuracy of target recognition. To image magnification to enhance image resolution as a starting point, the author puts forward two kinds of image magnification method based on wavelet transform. Qualitative analysis on the experimental data and quantitative analysis using average gradient, cross entropy as performance index, show that the proposed image magnification method has obvious advantages in terms of image definition, maintaining image gray scale information. Finally, the author proposes the method of image expansion based on the image magnification data of the four methods, which greatly enriches the diversification of the training set on resolution, clarity, contrast, integrity and so on, and theoretically analyzes the feasibility of improving the recognition accuracy of the data with few samples and small targets.
Application of BP Dual Network Model Considering Internal and External Factors in Short-Term Load Forecasting
Authors: Yang Xiaoliang , Ren Hongyuan , Zhao Honggang
Published: September 2020

In the reform of electricity sales, the accuracy of short-term load forecasting is very important for power grid operation scheduling, user demand response and pricing mechanism. Based on the theory of internal and external factors, the paper accurately extracted temperature, humidity, entropy of peak load and load volatility as the main influencing factors. Based on the artificial intelligence learning method, it introduced experts’ experience to build a dual neural network short-term load prediction model, simulated load characteristics from multiple angles, and accurately predicted the trend. The simulation results show that the improved short-term load prediction model is more suitable to deal with dynamic problems due to its fast convergence speed and high prediction accuracy.
Exploiting Node Similarity Based on Graphical Markov Models for Link Prediction
Authors: Sun Jing , Lin Zhijie
Published: September 2020

Link prediction has been attached more attention in recent years. In this paper, we develop a link prediction method which has a unique perspective on using network structures. The key idea is to exploit the relationship information based on Graphical Markov models (GMM) for designing similarity indices. Specifically, networks with GMM were modeled to capture the relational influence of nodes by taking multi-hop neighbors into consideration. Then, link ties are measured for supporting relationship prediction based on the theory of weak and strong ties. Moreover, the proposed method can be used to predict the emergence of future relationships between the nodes. Finally, empirical studies on real-world dataset demonstrate that the benchmark of the proposed method improves with a significant margin compared with other methods.
Research on Observer-Based Bidirectional DC-DC Converter Current Prediction Strategy
Authors: Zhu Jiaxiong , Jing Cao , Feng Chang , Yao Jiang
Published: September 2020

In a DC microgrid system containing distributed power, factors such as output fluctuations and load switching of distributed power can cause DC bus voltage fluctuations. In order to increase the capacity and improve the stability of hybrid photovoltaic energy storage system, taking into account the nonlinear characteristics of bi-directional set DC-DC converter, this paper proposes an observer-based bi-directional set DC-DC converter current prediction strategy. Without additional sensors, a feedforward control channel based on a non-linear disturbance observer is added to the DC bus voltage control outer loop to compute system interference through using the disturbance observer, the disturbance feed-forward is compensated into the expected value, thereby improving the inductance The fast following performance of current expectation. MATLAB/Simulink simulation, the results show that the observer-based Bi-directional set DC-DC converter predictive current control processes and policies can restrain the voltage jump of DC bus effectively and improve the system’s rapidity and anti-interference ability under disturbances.
Research on Product Design Efficiency Improvement Based on Computer Information Technology
Authors: Yang Shuai , Yao Meijing
Published: September 2020

With the progress of society, computer technology has gradually penetrated into all aspects of life. The product design industry is an industry that emphasizes innovation and efficiency. In the process of new product design, the product details and existing problems need to be fully considered. This requires further optimization and innovative design. Among them, computer-aided technology can smoothly apply information technology to the forefront of product design life cycle and provide intellectual innovative solutions for the design and application of new products. The intervention of computer technology will greatly improve the efficiency of product design and help promote the development of product development companies.
Data-Driven Sensor Fault Diagnosis for Fighter under Harsh Conditions
Authors: Wang Qi , Chen Fuyang , Wang Li
Published: September 2020

This paper presents a multi-classification fault diagnosis scheme for the sensor of fighter. It is difficult to diagnose sensor faults for fighter under harsh conditions like hyper maneuver because the states change rapidly and the data of fault-free and faulty sensor are similar to each other. The rapidly changing states means that values of sensor faults may be small compared with states variation. Similar data may raise the difficulty to find the separating plane. Wavelet packet decomposition can transform the raw dataset to fault features by computing the energy values of each frequency band. And principal component analysis (PCA) can grasp the main features and reduce computational complexity by transform a group of dependent parameters into a group of independent parameters via orthogonal transformation. A support vector machine (SVM) trains fault features to achieve a multi-classifier via one-versus-rest method. The classifier can obtain fault diagnosis results by inputting features of new data. Numerical simulation results illustrate the effectiveness and accuracy of the proposed fault diagnosis scheme.
A Broadband Filter Transmitarray Based on Quasi-Yagi Antenna Element
Authors: Sun Fugang , Li Chuanqing , Liu Yi , Wan Lulan , Qin Fan , Liu Yi
Published: September 2020

A transmitarray (TA) antenna operating at X-band with band-pass filtering performance is presented. The proposed antenna is composed of a wideband TA and a filter feed antenna. Two quasi-Yagi antennas are connected as the unit cell of the proposed TA, leading to high transmission efficiency over a broadband range. By simply changing the length of the transmission lines, 360° phase shift is obtained. To verify this idea, a design with 16×26-unit cells is simulated and optimized, showing that approximately 14.5% 1-dB and 24.6% 3-dB gain bandwidths are achieved, respectively, with the peak gain of 23.1 dBi. Moreover, by employing the bandpass filter feed antenna, good bandpass filtering property is achieved, showing that the upper and lower out-of-band suppression in the 0.3GHz range can reach 27.3dB and 24.2dB, respectively, with the passband range from 9.6GHz to 11.9GHz.
Trident SSD: A Trident Single-Shot Multibox Object Detector with Deconvolution
Authors: Li Xinlong , Li Xingwei , Guan Shaojie , Jin Jiating , Ge Yizhi
Published: September 2020

Scale variation is one of the key challenges in the object detection area, which limits the precision of detection methods like Single shot multibox detector (SSD). This paper proposes a detection method based on SSD, which focuses on handling scale variation and better detection performance of small objects. Our method, called TridentSSD, have an architecture with three branches, which are respectively responsible for detecting different scales of objects, solving the problem of scale variation while training. Then we augment small object branch with deconvolution module and feature fusion methods to improve precision, especially for small object detection. During training, we modify the original matching rules to generate training samples. Consequently, we can use objects of different scales to train the corresponding branches respectively. Finally, Experiments have done on both PASCAL VOC2007 and VOC2012 datasets. Results show that, with an input size of 300×300, our TridentSSD achieves better performance compared to the benchmark method SSD.
An Online Intelligent Method to Calibrate Radar and Camera Sensors for Data Fusing
Authors: Liu Ming , Li Dongdong , Li Qiankun , Lu Wei , Yin Jun
Published: September 2020

This paper introduces an intelligent method to calibrate radar and camera sensors for data fusing. Camera can recognize pedestrians, non-motor vehicles, motor vehicles high accuracy by advanced deep learning neural networks. But it’s hard to acquire the target’s spatial position and speed information simply relying on image. For the radar sensor, it’s easy to acquire the target’s spatial position and speed information by itself, but it cannot recognize target. In other words, the advantage of radar is the disadvantage of camera, and the advantage of camera is the disadvantage of radar. So combining these two complementary sensors is valid and necessary for solving the problem: Who is doing what. Then the first and foremost thing is to calibrate the radar and camera sensors. Calibration includes time synchronization and space calibration, which will seriously affect the sensors data fusing performance. This paper emphasizes on spatial calibration. Traditional methods (based on the principle of geometric projection or four-point calibration method) cannot acquire enough high calibration accuracy in the general scenarios with low time cost or easy operation. So this paper introduces an online intelligent method to calibrate radar and camera sensor without human assistance operation in the general scenarios. Firstly, we introduce what is spatial calibration. Secondly, we introduce two conventional methods and their defects. And then we introduce the online intelligent calibration method. At last we compare three calibration methods with the actual data to further explain the advance of our new method.
Structural Fuzzy Multi-class Support Vector Machine
Authors: Li Kai , Li Jie
Published: September 2020

Support vector machine is a kind of generalized linear classifier that classifies data in a supervised learning manner, and its decision boundary is the maximum margin hyperplane for solving learning samples. It is used to solve the problem of binary classification. For multi-classification problems, a combination method of multiple binary classifiers is usually used to solve, but such methods are prone to generate inseparable regions of data. Therefore, on the basis of constructing a multi-class problem directly, using the pinball loss function, and introducing the structural information of different classes in the data and the role of different samples, a new support vector machine algorithm Pin-SFSimMSVM for solving multi-classification problems is proposed. It not only retains the advantages of avoiding the existence of inseparable regions and fast calculation speed of multiple types of data, but also is insensitive to noise and resampling data, and has greatly improved the accuracy. The effectiveness of the proposed algorithm is verified by experimenting on UCI standard data sets and comparing with some multi-classification algorithms.
Dynamic genesis potential index for diagnosing present-day and future global tropical cyclone genesis
Authors: Wang Bin , Murakami Hiroyuki
Published: September 2020

Tropical cyclone (TC) genesis potential index (GPI) has been extensively used to understand the processes governing climate variability and future change of TC genesis (TCG). However, the relative roles of the thermodynamic versus dynamic environmental factors in TC genesis remain elusive, especially under a warming world. Here we show that four leading dynamic factors, the 850 hPa absolute vorticity, 500 hPa vertical motion, tropospheric vertical wind shear, and 500 hPa shear vorticity of zonal winds, are objectively identified by the logarithmic stepwise regression analysis from 11 dynamic and thermodynamic candidate factors. We further demonstrate that the model results from a TC-permitting global model ascertain the four leading dynamical factors as the most influential in both the present-day simulation and future projection under global warming. A dynamic GPI, consisting of the four dynamic parameters, provides a diagnostic tool for understanding future change of TC genesis. Meanwhile, it improves skills in representing interannual variations of TCG frequency in the western Pacific and Southern Hemisphere oceans.
Boosting the eco-friendly sharing economy: the effect of gasoline prices on bikeshare ridership in three U.S. metropolises
Authors: He Pan , Zou Zhenpeng , Zhang Yongping , Baiocchi Giovanni
Published: September 2020

Transportation has become the largest CO2 emitter in the United States in recent years with low gasoline prices standing out from many contributors. As demand side changes are called for reducing car use, the fast-growing sharing economy shows great potential to shift travel demand away from single-occupancy vehicles. Although previous inter-disciplinary research on shared mobility has explored its multitudes of benefits, it is yet to be investigated how the uptake of this eco-friendly sharing scheme is affected by gasoline prices. In this study, we examine the impact of gasoline prices on the use of bikeshare programs in three U.S. metropolises: New York City, Boston, and Chicago. Using bikeshare trip data, we estimate the impact of citywide gasoline prices on both bikeshare trip duration and trip frequency in a generalized linear regression setting. The results suggest that gasoline prices significantly affect bikeshare trip frequency and duration, with a noticeable surge in short trips. Doubling gasoline prices could help save an average of 1933 gallons of gasoline per day in the three cities, approximately 0.04% of the U.S. daily per capita gasoline consumption. Our findings indicate that fuel pricing could be an effective policy tool to support technology driven eco-friendly sharing mobility and boost sustainable transportation.
A semi-analytical model for the scale-dependent friction of nanosized asperity
Authors: Wang Jian , Yuan Weike , Bian Jianjun , Wang Gangfeng
Published: September 2020

The friction of a nanosized spherical asperity in commensurate contact with a flat substrate is investigated by performing molecular dynamics simulations. Particular focus is on the distribution of shear stress within the contact region. It is noticed that within the slip zone, the local friction coefficient defined by the ratio of shear stress to normal pressure declines monotonically as the distance to the contact center increases. With the lateral force increasing, the slip zone expands inwards from the contact edge. At the same time, the local friction coefficient at the contact edge decreases continuously, while that at the dividing between the slip and stick zones keeps nearly invariant. These characteristics are distinctly different from the prediction of the conventional Cattaneo-Mindlin model assuming a constant local friction coefficient within the entire slip zone. An analytical model is advanced in view of such new features and generalized based on numerous atomic simulation results. This model not only accurately characterizes the interfacial shear stress, but also explains the size-dependence of static friction of single nanosized asperity.
From colony to empire to republic
Authors: Pereira Anthony W.
Published: September 2020

‘From colony to empire to republic’ details Brazil’s unique path to statehood and nationhood. Brazil is a relatively recent creation. For more than three centuries, it was a colony of Portugal, and for the first sixty-seven years of its independent history, it was a monarchy and an empire rather than a republic. It is only in the 20th century that Brazil had all three essential components of a modern nation-state. The chapter then considers the role of indigenous groups, the Portuguese, African slaves, and other immigrants—as well as the events of the gold rush in the 1690s and the Paraguay War in the 19th century—in Brazil’s history.
Dictatorship and repression
Authors: Pereira Anthony W.
Published: September 2020

‘Dictatorship and repression’ assesses the twenty-one-year dictatorship in Brazil from 1964 to 1985. A result of tensions in the second republic of 1945–64, the coup that created the Brazilian dictatorship occurred in 1964. The subsequent authoritarian regime in Brazil was also distinctive; in the first four years, the regime oversaw a process of conservative modernization of the economy. However, the repression of the military regime reached its peak from 1969 to 1974, when disappearances, executions, and torture took place amidst the clamp-down engendered by the passage of Institutional Act Number 5 (AI-5). The chapter then looks at the legacy of the Brazilian dictatorship.
Exile poetry
Authors: Morgan Llewelyn
Published: September 2020

In 8/9 CE Ovid was sent by the emperor Augustus to the town of Tomi in modern Romania, at the time at the far edge of the Roman Empire. 'Exile poetry' focuses on the Tristia (Sad Songs) and the Epistulae ex Ponto (Letters from the Black Sea), in total nine books of laments in which Ovid begs to be restored to Rome, or at least to be moved to a more congenial location. The main development between Tristia and ExPonto is Ovid's formal adoption in the later series of a letter format natural to poems sent over a long distance. The circumstances of this poetry, and particularly the identification of the addressee in the Ex Ponto, allows a degree of poignancy rare elsewhere is his poetry. Certainly, for all his claims to the contrary, Ovid’s poetic powers do not abandon him on the Black Sea, and what has made Ovid's exile poetry one of the most influential parts of his oeuvre is the rarity of a classical poet offering an intimately personal account of estrangement and alienation. In turn, these poems provided perhaps unexpected inspiration for modern writers exercised by themes of separation.
2. ‘Unpleasant’
Authors: Wixson Christopher
Published: September 2020

‘Unpleasant’ studies George Bernard Shaw’s first three plays, which he published together in a volume titled Plays Unpleasant in 1898. Inspired by Norwegian playwright Henrik Ibsen, these plays show his understanding of writing for the stage as a unique opportunity for Fabian activism. Widowers’ Houses (1892) focuses on the shameful living conditions of the working poor in urban slums. The Philanderer (1893) and Mrs Warren’s Profession (1893) tackle the constrictions for women in relation to money and marriage. For Shaw, playwriting was another outlet to confront a culture with its own moral hypocrisy and provoke discussion of ‘unmentionable’ topics tied to discrimination, injustice, and social oppression.
Nuclear Weapons: A Very Short Introduction
Authors: Siracusa Joseph M.
Published: September 2020

Nuclear Weapons: A Very Short Introduction covers the scientific, historical, and political development of nuclear weapons, and how they transformed the very nature of war and peace. Nuclear weapons have not been used in anger since Hiroshima and Nagasaki, seventy-five years ago. However, nuclear threats remain fundamental to relations between many states, complicating issues of global security. Their potential use by terrorists is an increasing concern. This book looks at the race to acquire the hydrogen bomb; Ronald Reagan’s Strategic Defence Initiative (‘Star Wars’); contemporary defences against possible ballistic missile launches; and the policies nuclear weapons have generated since the end of the Cold War.
4. Race for the H-bomb
Authors: Siracusa Joseph M.
Published: September 2020

America’s monopoly on atomic weapons was shorter than expected. ‘Race for the H-bomb’ details the development of the hydrogen bomb and the political developments surrounding it. The Soviet Union developed an atomic weapon faster than worst-case scenarios had predicted. Stalin appeared at first to dismiss the bomb, but it is likely that his understanding was more nuanced. What else could America have done with their short window of opportunity? Some argued for preventive war, but this went against the national character. The development of the hydrogen bomb took war out of the realms of logic and human control altogether, and anti-nuclear movements began to gather force in the 1950s.
Philosophy
Authors: Craig Edward
Published: September 2020

If philosophy is so close to us, why do many people regard it as something outlandish? ‘Philosophy: a very short introduction’ summarizes some key questions. What is philosophy for? What should we do? Philosophy is seen as a field of study, but also means simply being reflective. Our level of comfort with a school of philosophy is often related to how closely it resembles our world-view. As civilization developed and humans became more sophisticated, philosophy has become more relevant. People have often come up with compelling philosophical arguments under duress, and these arguments and solutions have changed the course of civilization.
What’s in it for whom?
Authors: Craig Edward
Published: September 2020

Most philosophy attempts to do something for somebody. ‘What’s in it for whom?’ looks again at Plato’s dialogues, unpacking early philosophical problems involving the individual, the state, and contract theory. Philosophy needs a large constituency to transform lives. We can see this in the example of the working classes (via Karl Marx, who was influenced by Hegel) and women (via the writings of Simone de Beauvoir). Even animals’ lives may have been affected for the better by a philosophy that promotes vegetarianism. Professional philosophers should avoid the temptation to write only puzzles for other thinkers and prioritize the issues of our time.
Clinical Characteristics and Mortality of Health-Care Workers With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection in Mexico City
Authors: Guerrero-Torres Lorena , Caro-Vega Yanink , Crabtree-Ramírez Brenda , Sierra-Madero Juan G
Published: September 2020

Background

We evaluated the risk of death for health-care workers (HCW) with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Mexico City during the coronavirus disease 2019 (COVID-19) pandemic, and describe the associated factors in hospitalized HCW, compared with non-HCW.

Methods

We analyzed data from laboratory-confirmed SARS-CoV-2 cases registered from 27 February–31 August 2020 in Mexico City’s public database. Individuals were classified as non-HCW or HCW (subcategorized as physicians, nurses, and other HCW). In hospitalized individuals, a multivariate logistic regression model was used to analyze the potential factors associated with death and compare mortality risks among groups.

Results

A total of 125 665 patients were included. Of these, 13.1% were HCW (28% physicians, 38% nurses, and 34% other HCW). Compared with non-HCW, HCW were more frequently female, were younger, and had fewer comorbidities. Overall, 25 771 (20.5%) were treated as inpatients and 11 182 (8.9%) deaths were reported. Deaths in the total population (9.9% vs 1.9%, respectively; P < .001) and in hospitalized patients (39.6% vs 19.3%, respectively; P < .001) were significantly higher in non-HCW than in HCW. In hospitalized patients, using a multivariate model, the risk of death was lower in HCW in general (odds ratio [OR], 0.53) than in non-HCW, and the risks were also lower by specific occupation (OR for physicians, 0.60; OR for nurses, 0.29; OR for other HCW 0.61).

Conclusions

HCW represent an important proportion of individuals with SARS-CoV-2 infection in Mexico City. While the mortality risk is lower in HCW compared to non-HCW, a high mortality rate in hospitalized patients was observed in this study. Among HCW, nurses had a lower risk of death compared to physicians and other HCW.
Impact of Coronavirus Disease 2019 Public Health Measures on Detections of Influenza and Respiratory Syncytial Virus in Children During the 2020 Australian Winter
Authors: Yeoh Daniel K , Foley David A , Minney-Smith Cara A , Martin Andrew C , Mace Ariel O , Sikazwe Chisha T , Le Huong , Levy Avram , Blyth Christopher C , Moore Hannah C
Published: September 2020

Public health measures targeting coronavirus disease 2019 have potential to impact transmission of other respiratory viruses. We found 98.0% and 99.4% reductions in respiratory syncytial virus and influenza detections, respectively, in Western Australian children through winter 2020 despite schools reopening. Border closures have likely been important in limiting external introductions.
The Role of Evidence in the US Response to the Opioid Crisis
Authors: Sharfstein Joshua M , Olsen Yngvild
Published: September 2020

The National Institutes of Health is investing hundreds of millions of dollars into new research on opioids. As these studies yield insights and results, their results will have to change policy and practice before they can bend the curve of the epidemic. However, the United States does not have a strong track record of translating evidence on drug policy into action. Three reasons for the translation gap are the historical legacy of drugs in the United States, vested interests, and politics. Researchers can become engaged in policy and political processes to strengthen the US response.
Association Between Estimated Glomerular Filtration Rate Based on Cystatin C and Grip Strength in Community-Dwelling Japanese Older Adults
Authors: Kabasawa Keiko , Nakamura Kazutoshi , Ito Yumi , Tanaka Junta , Narita Ichiei
Published: September 2020

Background

Kidney dysfunction is associated with sarcopenia. Estimated glomerular filtration rate based on cystatin C (eGFRcys), an alternative to creatinine-based measures of kidney function eGFR, is not affected by muscle mass. Given that the association of eGFRcys with muscle weakness would be limited, we examined the association in older adults with normal or compromised kidney function.

Methods

This cross-sectional study involved 594 community-dwelling Japanese adults aged ≥40 years living in Yuzawa, Japan. Serum creatinine, cystatin C, and handgrip strength were concurrently measured at a health-check examination in 2015. eGFR was calculated according to the equation developed for the Japanese population using creatinine and cystatin C. Associations of eGFRcys and eGFRcreat with low grip strength (men, <26 kg and women, <18 kg) were analyzed using logistic regression models adjusted to control for potential confounders.

Results

Participants (mean age, 74.9 years) included 319 women and 109 individuals with low grip strength. Mean eGFRcys was 75.2 (SD 18.6) mL/min/1.73 m2. Pearson’s correlation coefficients of handgrip strength for eGFRcys and eGFRcreat were 0.19 (p < .001) and −0.04 (p = .281), respectively. Multivariate logistic regression analysis showed the adjusted odds ratio (OR) of low grip strength for the highest versus lowest quartile of eGFRcys value was 2.46 (95% confidence interval, 1.03–5.86; p-trend = .026); whereas the comparative adjusted OR for eGFRcreat was 0.67 (95% confidence interval, 0.34–1.32).

Conclusions

Low kidney function as assessed by eGFRcys was associated with muscle weakness in community-dwelling Japanese older adults.
Fentanyl Quality Assurance Project Prompted Change in Clinical Workflow and Test Configurations
Authors: Tacker Danyel Hermes , Adelanwa Ayodele , Pearson Nathan , Marshalek Patrick , Berry James H
Published: September 2020

Background

Deaths attributable to fentanyl (FEN, a synthetic opioid) are high in Appalachia and highest in West Virginia. The goal of the study was to determine FEN prevalence among specimens submitted for definitive opioid testing and monitor responses to provider notifications of unexpected FEN findings during Q1 2020.

Methods

All definitive opioid test data were reviewed daily for FEN signatures in Q1 2020. Unexpected FEN results were communicated to providers and monitored for 10 days to record actions taken. Prevalence data were categorized. Behavioral Medicine (BMED) leaders analyzed January data and implemented FEN screening in the clinic. BMED Q1 clinic visits and order volumes for drug screens were reviewed after Q1.

Results

FEN positivity was 11% in Q1; >60% of findings were unexpected. Actions were taken for 54% of notifications in January but only 18% in March. Notifications required 70 hours of combined laboratory effort each month. BMED providers ordered 44% of definitive opioid tests and 69% of definitive FEN tests. Data prompted the addition of FEN to routine drug screen panels in the laboratory, and a 10% random FEN screening rate in the BMED opioid use disorder clinics (COAT).

Conclusions

Prevalence of FEN positivity was higher than initially expected, even for this region in Appalachia. Expanded presence of FEN screening should assist BMED providers with clinical efforts and help identify patients in need of intervention/therapy.
Comparison of Two Automated Immunoassays for the Detection of SARS-CoV-2 Nucleocapsid Antibodies
Authors: Hubbard Jacqueline A , Geno K Aaron , Khan Jenna , Szczepiorkowski Zbigniew M , de Gijsel David , Ovalle Anais A , AlSalman Ahmad S , Gallagher Torrey L , Johnston Abigail A , Tibbetts Amanda R , Vital Sarah E , Cervinski Mark A , Nerenz Robert D
Published: September 2020

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel member of the coronavirus family that caused the global coronavirus 2019 (COVID-19) pandemic. The prevalence remains largely unknown because of early testing supply shortages. Although it cannot currently be used to determine level of immunity, antibody testing can contribute to epidemiological studies, identify convalescent plasma donors, or satisfy curiosity about previous exposure to the virus.

Methods

407 samples collected from hospitalized inpatients with and without a confirmed SARS-CoV-2 infection, 170 remnant clinical specimens collected and frozen prior to the COVID-19 outbreak, and paired serum and plasma samples from 23 convalescent plasma donors were used to determine performance characteristics of the Abbott SARS-CoV-2 IgG and Roche Elecsys Anti–SARS-CoV-2 assays. The sensitivity, specificity, imprecision, interferences, and sample stability were determined. These assays were then used to characterize the antibody response in serial samples from 20 SARS-CoV-2 positive inpatients.

Results

Both assays exhibited 100% specificity (95% CI; 99.05–100.00), giving no positive results in 170 specimens collected before July 2019 and 215 specimens from patients without a confirmed SARS-CoV-2 infection. Differences between platforms were most notable in SARS-CoV-2 positive samples. Roche offered higher sensitivity in convalescent plasma donors at 95.7% (95% CI; 78.1–99.9) versus 91.3% (95% CI; 72.0–98.9) but Abbott detected antibodies in 2 immunocompromised patients whereas Roche did not. The Roche and Abbott platforms also exhibited different trends in antibody signal for a subset of patients.

Conclusions

Both the Abbott and Roche platforms offer excellent specificity but different trends in antibody signal may reflect qualitative differences in the types of antibodies recognized by the 2 assays. Negative serologic results do not exclude previous SARS-CoV-2 infection.
Electrophysiological Responses to Cuelure of Raspberry Ketone-Fed Queensland Fruit Flies
Authors: Biswas Md Jamil Hossain , Mainali Bishwo , Park Soo Jean , Taylor Phillip , Rempoulakis Polychronis
Published: September 2020

The sterile insect technique (SIT) and male annihilation technique (MAT) are important tools for the control of Queensland fruit fly (Q-fly), Bactrocera tryoni (Froggatt) (Diptera: Tephritidae), a major insect pest of horticultural crops in Australia. In MAT, mature Q-fly males are attracted to a toxic bait using Cuelure, a synthetic analog of raspberry ketone (RK). Substantial improvements in control could be achieved by simultaneous use of SIT and MAT, but this requires suppression of the Cuelure response in released sterile flies. Recent studies report that prerelease feeding with RK during the first 48 h after emergence can reduce the response of mature Q-fly males to Cuelure, but the mechanism underpinning this is unknown. Here, to test whether reduced sensory sensitivity to Cuelure is involved, we evaluated the effects of RK supplements, adult diet (yeast-supplemented diet throughout adult stage vs yeast-supplemented diet only for 48 h), and age on electroantennogram (EAG) and electropalpogram (EPG) responses of Q-flies to Cuelure stimuli. EAG responses did not vary with RK supplements, sex, or age of Q-flies fed yeast-supplemented diet throughout the adult stage, but the responses of Q-flies fed other diet regime decreased with age. EPG responses of both sexes of Q-flies were affected by RK supplements, age, and their interaction, but without patterns that might indicate reduced maxillary palp response of RK supplemented flies to Cuelure. Our findings do not support the hypothesis that reduced Cuelure response of male Q-flies fed RK supplements is explained by reduced electrophysiological response in antennae or maxillary palps.
Population Genomics Reveals Incipient Speciation, Introgression, and Adaptation in the African Mona Monkey (Cercopithecus mona)
Authors: Ayoola Adeola Oluwakemi , Zhang Bao-Lin , Meisel Richard P , Nneji Lotanna M , Shao Yong , Morenikeji Olanrewaju B , Adeola Adeniyi C , Ng’ang’a Said I , Ogunjemite Babafemi G , Okeyoyin Agboola O , Roos Christian , Wu Dong-Dong
Published: September 2020

Guenons (tribe Cercopithecini) are the most widely distributed nonhuman primate in the tropical forest belt of Africa and show considerable phenotypic, taxonomic, and ecological diversity. However, genomic information for most species within this group is still lacking. Here, we present a high-quality de novo genome (total 2.90 Gb, contig N50 equal to 22.7 Mb) of the mona monkey (Cercopithecus mona), together with genome resequencing data of 13 individuals sampled across Nigeria. Our results showed differentiation between populations from East and West of the Niger River ∼84 ka and potential ancient introgression in the East population from other mona group species. The PTPRK, FRAS1, BNC2, and EDN3 genes related to pigmentation displayed signals of introgression in the East population. Genomic scans suggest that immunity genes such as AKT3 and IL13 (possibly involved in simian immunodeficiency virus defense), and G6PD, a gene involved in malaria resistance, are under positive natural selection. Our study gives insights into differentiation, natural selection, and introgression in guenons.
Dose escalation of osimertinib for intracranial progression in EGFR mutated non-small-cell lung cancer with brain metastases
Authors: Goldstein Iris M , Roisman Laila C , Keren-Rosenberg Shoshana , Dudnik Julia , Nechushtan Hovav , Shelef Ilan , Fuchs Vered , Kian Waleed , Peled Nir
Published: September 2020

Background

Osimertinib is a selective irreversible epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) with increased penetration across the blood–brain barrier compared with previous EGFR-TKIs, and thus, a 52% reduction in the risk of intracranial disease progression is seen when it is used as a first line of therapy compared with gefitinib and erlotinib. It is also efficient as second-line therapy for patients who developed the T790M resistance mutation following treatment with previous generation TKIs. Here, we report 11 patients who were treated by an increasing dose of osimertinib from 80 mg to 160 mg QD orally following intracranial progression in either first- or second-line setting.

Methods

This is a subcohort analysis from a larger nonrandomized, phase 2, open-label trial, evaluating the efficacy of osimertinib dose escalation from 80 mg to 160 mg in EGFR-mutated advanced non-small-cell lung cancer (NSCLC) patients with intracranial progression in either first- (arm A) or second-line setting (arm B for T790M+ and C for T790M−).

Results

Eleven patients, 5 in arm A, 4 in arm B, and 2 in arm C were reported in this study. The mPFS of osimertinib before dose escalation was 11.4 ± 8.9 (6.6–30.7) months for arm A, 8.7 ± 1.8 (6.3–11.2) for arm B, and 14.5 ± 7.8 (6.7–22.3) for arm C. Intracranial response rate to dose escalation was 54% (6 of 11) with 2 of 11 having intracranial stability. Median iPFS was 4.3 ± 7.4 (0.7–25.5) months; 3.8 ± 6.4 (1.8–18.9), 5.6 ± 9.7 (0.7–25.5), and 7.0 ± 2.7 (4.3–9.6) for arms A/B/C, respectively. Dose escalation was well tolerated with diarrhea and paronychia as the main dose-limiting symptoms.

Conclusions

Osimertinib 160 mg is feasible and may offer a therapeutic alternative for patients with isolated intracranial progression on osimertinib standard (80 mg) dose. Further studies on CNS osimertinib pharmacokinetics are needed to test this hypothesis.
Gender Differences in Reasons for Using Electronic Cigarettes and Product Characteristics: Findings From the 2018 ITC Four Country Smoking and Vaping Survey
Authors: Yimsaard Pongkwan , McNeill Ann , Yong Hua-Hie , Cummings K Michael , Chung-Hall Janet , Hawkins Summer Sherburne , Quah Ann C K , Fong Geoffrey T , O’Connor Richard J , Hitchman Sara C
Published: September 2020

Introduction

Little is known about why males are more likely to use electronic cigarettes (ECs) compared with females. This study examined gender differences in reasons for vaping and characteristics of EC used (device type, device capacity, e-liquid nicotine strength, and flavor).

Methods

Data were obtained from 3938 current (≥18 years) at-least-weekly EC users who participated in Wave 2 (2018) ITC Four Country Smoking and Vaping Survey in Canada, the United States, England, and Australia.

Results

Of the sample, 54% were male. The most commonly cited reasons for vaping in females were “less harmful to others” (85.8%) and in males were “less harmful than cigarettes” (85.5%), with females being more likely to cite “less harmful to others” (adjusted odds ratio [aOR] = 1.64, p = .001) and “help cut down on cigarettes” (aOR = 1.60, p = .001) than males. Significant gender differences were found in EC device type used (χ  2 = 35.05, p = .043). Females were less likely to report using e-liquids containing >20 mg/mL of nicotine, and tank devices with >2 mL capacity (aOR = 0.41, p < .001 and aOR = 0.65, p = .026, respectively) than males. There was no significant gender difference in use of flavored e-liquids, with fruit being the most common flavor for both males (54.5%) and females (50.2%).

Conclusion

There were some gender differences in reasons for vaping and characteristics of the product used. Monitoring of gender differences in patterns of EC use would be useful to inform outreach activities and interventions for EC use.

Implications

Our findings provide some evidence of gender differences in reasons for vaping and characteristics of EC used. The most common reason for vaping reported by females was “less harmful to others,” which may reflect greater concern by female vapers about the adverse effects of secondhand smoke compared with male vapers. Gender differences might be considered when designing gender-sensitive smoking cessation policies. Regarding characteristics of EC products used, we found gender differences in preferences for e-liquid nicotine strength and device capacity. Further studies should examine whether the observed gender differences in EC use reasons and product characteristics are predictive of smoking cessation. Furthermore, studies monitoring gender-based marketing of ECs may be considered.