bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of the phase composition and mechanical characteristics of laser welded joints of aluminum-lithium alloys
Authors: Malikov A G , Ancharov A.I.
Published: November 2021

A study of laser welding of modern aluminum-lithium alloys has been carried out. Optimization of post heat treatment of laser welded joints has been carried out. The change in the structural-phase composition of welded joints was investigated. The strength of welded joints after heat treatment was equal to the strength of the base alloy.
Application of Random Region Augmentation Algorithm in Deep Learning
Authors: Chen Tao , Lu Hongying , Xiao Sihe
Published: November 2021

In the field of computer vision, the collection and sorting of image data is the core driving force. However, the current data collection work cannot perfectly collect the image data of each actual landing scene. The purpose of the data augmentation algorithm is to increase the diversity of the data set and improve the robustness of the model. Traditional data augmentation methods include geometric augmentation and color augmentation, mainly including flipping, rotating, cropping, translation, stretching, zooming, adding noise, blurring, Dropout, Cutout, color jittering. Traditional data augmentation methods have certain limitations, and the effect is not obvious. Based on the idea of Cutout algorithm, this paper proposes the RRA augmentation algorithm, which divides four quadrant regions in the image, and randomly selects the ROI region in each region, and is different from the Cutout algorithm directly discarding the region, but randomizing the region Enhance the color, and finally do geometric augmentation processing on the overall image. Compared with the original single data augmentation operation, the algorithm improves precision by 7%, and recall improves by 7%.
A Modified Gamma Correction Algorithm Applied to the Medium and Bright Light Problems in AI Image Recognition
Authors: Yu Lu , Wang Yali , Li Jie
Published: November 2021

In this paper, an improved block gamma correction algorithm is proposed for the problem of bright light repair in outdoor scenes in the field of artificial intelligence image recognition, and simulation verification is carried out. Firstly, the strong light area is quickly extracted to meet the high-speed and low-calculation requirements of the artificial intelligence image recognition algorithm. Secondly, the strong light area is divided into sub-blocks, and different gamma values are used according to the standard deviation of each sub-block, which effectively reduces the strong light area. Finally, high image detail information and color confidence are preserved, and at the same time, it meets the requirements of the subsequent image recognition network for the input image.
An Intelligent Path Selection Algorithm Based on Deep Reinforcement Learning
Authors: Sun Mengchen
Published: November 2021

Path selection is the most important algorithm in intelligent devices such as robots. At present, the traditional path-planning algorithm has achieved some results, but it lacks the ability of environmental perception and continuous learning. In order to solve the above problems, this paper proposes an intelligent path selection algorithm based on deep reinforcement learning, which uses the learning ability of deep learning and the decision-making ability of reinforcement learning to realize the autonomous path planning of robots and other equipment. Simulation results show that the proposed algorithm has faster convergence, efficiency and accuracy.
CNN-BiLSTM water level prediction method with attention mechanism
Authors: Nie Qingqing , Wan Dingsheng , Wang Rui
Published: November 2021

Hydrological time series data is stochastic and complex, and the importance of its historical features is different. A single model is difficult to overcome its own limitations when dealing with hydrological time series prediction problems, and the prediction accuracy of a single model can be further improved. According to the characteristics of hydrological time series data, a CNN-BiLSTM water level prediction method with attention mechanism is proposed. In this paper, CNN extracts the spatial characteristics of water level data and BiLSTM learns the time period characteristics by combining the past and future sequence information, attention mechanism is introduced to focus the salient features in the sequence. Taking the hourly water level data of Pinghe basin in China as experimental basis, experimental result shows that this method is more accuracy than Support Vector Machine (SVM), Temporal Convolutional Neural network (TCN), and Bidirectional Long Short-Term Memory network (BiLSTM) model.
Application and Research of Convolution Neural Network in MRI Image Classification and Recognition
Authors: Hou Xuemei , Gao Fei , Wu Jianping , Wu Minghui
Published: November 2021

The traditional hepaticcell carcinoma (HCC) pathological grading depends on biopsy, which will cause damage to the patient's body and is not suitable for everyone's pathological grading diagnosis. The purpose of this paper is to study the pathological grading of liver tumors on MRI images by using deep learning algorithm, so as to further improve the accuracy of HCC pathological grading. An improved network model based on SE-DenseNet is proposed. The nonlinear mapping relationship between feature channels is modeled and recalibrated using attention mechanism, and rich deep-seated features are extracted, so as to improve the feature expression ability of the network. The method proposed in this paper is verified on the data set including 197 patients, including 130 training sets and 67 test sets. The experimental results are evaluated by receiver operating characteristic (ROC) and area under the ROC curve (AUC). The improved SE-Densenet network achieves good results, and AUC 0.802 is obtained on the test set. The experimental results show that the method proposed in this paper can well predict the pathological grade of HCC.
A Skin Cancer Detection Interactive Application Based on CNN and NLP
Authors: Gong Xuping , Xiao Yuting
Published: November 2021

Skin cancer is the most common cancer with several different types. According to current estimations, one in five Americans will develop skin cancer in their lifetime. Therefore, early diagnosis and treatment of it is of crucial significance. Several advanced image processing methods have been applied to predict skin cancer. However, few researchers utilize those methods to build an interactive application. In this work, we implemented an interactive skin cancer diagnosis website, combining the convolutional neural network (CNN) and natural language processing (NLP) technology. The neural network model uses four convolutional layers and dense layers respectively to improve the accuracy. Two max-pooling layers were used to reduce redundant information. To address the severe overfitting problem, we chose to utilize the batch normalization along with dropout layers. Based on our results, 0.9935 in accuracy and 0.0225 loss is realized for training data, and accuracy of 0.8393 and 0.6648 loss for testing data. Natural language processing (NLP) was used to implement a chatbot for interaction with users. We crawled skin cancer related questions and answers from Quora and used them to train our chatbot. Lastly, we combined CNN and NLP to build an interactive skin cancer diagnosis website. VUE.js and Django were used to build the front-end and back-end of our website. These results offer a guideline for combining artificial intelligence with not only medicine but also interactive network, which enables people to get medical care more easily.
Design of a Skin Cancer Diagnosing Web Application Based on Convolutional Neural Network Model and Chatterbot Application Programming Interface
Authors: An Qi
Published: November 2021

Skin cancer has become a great concern for people's wellness. With the popularization of machine learning, a considerable amount of data about skin cancer has been created. However, applications on the market featuring skin cancer diagnosis have barely utilized the data. In this paper, we have designed a web application to diagnose skin cancer with the CNN model and Chatterbot API. First, the application allows the user to upload an image of the user's skin. Next, a CNN model is trained with a huge amount of pre-taken images to make predictions about whether the skin is affected by skin cancer, and if the answer is yes, which kind of skin cancer the uploaded image can be classified. Last, a chatbot using the Chatterbot API is trained with hundreds of answers and questions asked and answered on the internet to interact with and give feedback to the user based on the information provided by the CNN model. The application has achieved significant performance in making classifications and has acquired the ability to interact with users. The CNN model has reached an accuracy of 0.95 in making classifications, and the chatbot can answer more than 100 questions about skin cancer. We have also done a great job on connecting the backend based on the CNN model as well as the Chatterbot API and the frontend based on the VUE Javascript framework.
A Plug-and-play Attention Module for CT-Based COVID-19 Segmentation
Authors: Zhang Zhengqian , Xue Haoqian , Zhou Guanglu
Published: November 2021

At the end of 2019, a new type of coronavirus (COVID-19) rapidly spread globally, even if the penetration of vaccination is getting higher and higher, the emergence of viral variants has increased the number of new coronal pneumonia infections. The deep learning model can help doctors quickly and accurately divide the lesion zone. However, there are many problems in the segmentation of the slice from the CT slice, including the problem of uncertainty of the disease area, low accuracy. At the same time, the semantic segmentation model of the traditional CNN architecture has natural defects, and the sensing field restrictions result in constructing the relationship between pixels and pixels, and the context information is insufficient. In order to solve the above problems, we introduced a Transformer module. Visual Transformer has been proved to effectively improve the accuracy of the model. We have designed a plug-and-play spatial attention module, on the basis of attention, increased positional offset, effective aggregate advanced features, and improve the accuracy of existing models.
Characteristic of Neural Signal Feature for Spike Sorting and Detection
Authors: Wang Tongwei
Published: November 2021

Neural spike plays an important role in understanding brain activities, and in neural spike sorting, the features of signal are of great importance. This paper aims to have a review on features used to discriminate different originated spikes. The features are divided into three categories: features in the time domain, features in the transformation domain, and features of dimensional reduction. For each kind of feature, the basic principle, advantages, and disadvantages are described and discussed. Results showed that features in the time domain are suitable for on-chip or real-time spike sorting, while features in the transformation domain can be used in offline spike sorting aiming at high performance. For features of dimensional reduction, it makes a large number of features available in spike sorting. In conclusion, researchers need to determine features by balancing the minimization of calculation complexity and maximizing sorting performance according to different occasions and demands. Expectations are also made for future directions of spike feature studies. The article may guide both the physiologists who want to determine features in neural spike sorting and researchers who want to work on feature extracting algorithms further to achieve better performance in experimental challenges.
Research on the Application of Uninterrupted 5G Private Network in Smart Grid
Authors: Lu Guosheng , Tian Lin , Liu Hang , Zhu Hailong , Wang Long , Zeng Jielin
Published: November 2021

Based on the demand for smart grid 5G network, this paper studies 5G mobile communication technology and the industry's 5G private network construction mode. Combined with power grid requirements, this paper focuses on analyzing the uninterrupted 5G private network solution, the principal of the solution is also explained. Taking a 5G test network deployed at a converter station as an example, the construction, isolation, operation, and maintenance plans of the uninterrupted 5G private network solution in the power communication network is proposed, the actual tests verify the feasibility of the continuous 5G private network. This paper will provide reference for the promotion and application of 5G private network technology in the power grid.
Indoor Positioning Method Based on Infrared Vision and UWB Fusion
Authors: Zhang Qianrong , Li Yi
Published: November 2021

Ultra-wideband (UWB) has broad application prospects in the field of indoor localization. In order to make up for the shortcomings of ultra-wideband that is easily affected by the environment, a positioning method based on the fusion of infrared vision and ultra-wideband is proposed. Infrared vision assists locating by identifying artificial landmarks attached to the ceiling. UWB uses an adaptive weight positioning algorithm to improve the positioning accuracy of the edge of the UWB positioning coverage area. Extended Kalman filter (EKF) is used to fuse the real-time location information of the two. Finally, the intelligent mobile vehicle-mounted platform is used to collect infrared images and UWB ranging information in the indoor environment to verify the fusion method. Experimental results show that the fusion positioning method is better than any positioning method, has the advantages of low cost, real-time performance, and robustness, and can achieve centimeter-level positioning accuracy.
Research on Intelligent Fire Risk Perception System of High-rise Building Based on Big Data of Internet of Things
Authors: Wu Xiaosha , Tian Shixiang , Wang Wei , Jiang Zebiao , Guo Kai
Published: November 2021

Due to the characteristics of high-rise buildings, such as dense personnel, complex structure and many combustibles, fire safety problems are more prominent. Aiming at the fire problem of high-rise buildings, based on the Internet of Things and big data technology, the intelligent fire risk perception system of high-rise buildings is studied. Through the functional modules of fire water monitoring system, intelligent electricity monitoring system and fire automatic alarm system, the hydraulic and water level of fire water, the current and voltage values of key nodes such as distribution cabinets, and the on-duty personnel in fire control room are mastered in real time, so as to grasp the specific location of fire in time and accurately, so as to realize the intelligent control of fire safety of high-rise buildings.
Research on the Application of 5G Network Slicing in Smart Grid
Authors: Dongwu  , Zhangtao  , Chenxiaojin  , Zhuhailong  , Pengdili
Published: November 2021

With the continuous construction and development of domestic power grids, the state has put forward many effective strategies to achieve the effectiveness and durability of energy supply, in order to ensure the stable operation of the power grid and the construction of smart grids. One of the most important components of the smart grid is various communication technologies. 5G network slicing is a typical application of the smart grid, because the wide-area distributed grid has greater requirements for low latency, high reliability and security. And 5G network slicing has the ability to meet its requirements. This paper analyzes the principle of 5G network slicing, analyzes the end-to-end isolation scheme of network slicing and the current smart grid slicing business model and existing problems, and proposes an effective solution for building a smart 5G slicing network.
Research on Intelligent Position Posture Detection and Control based on Multi-sensor Fusion Method
Authors: He Langning , Liu Shaowei , Guan Jiao
Published: November 2021

Aiming at the problems of low efficiency and high safety risks encountered in grabbing and placing the boxes by manual mode, the multi-sensor fusion method of vision and laser ranging sensor is used for position and posture detection, and the global rough positioning is detected by the global binocular camera. Precise positioning uses four local measurement modules, including a monocular camera and three laser ranging modules, to detect the position and posture of the target, and uses Move it in ROS for trajectory planning, obstacle avoidance detection and object grabbing. The intelligent position posture detection and control technology proposed in this paper can effectively improve the timeliness of the box grabbing operation, ensure the safety of the box grabbing operation, and enhance the adaptability to harsh environments.
The deformation and breakup of a droplet under the combined influence of electric field and shear flow
Authors: Chen Yanyan , Liang Yusheng , Chen Mengyuan
Published: November 2021

A lattice Boltzmann and finite-difference hybrid method is used to simulate the droplet deformation and breakup under the combined action of shear flow and electric field. The hybrid method is first used to validate for the droplet deformation in the combined action of shear flow and electric field. It is then used to simulate the droplet deformation and breakup in two different electric systems. Results of prolate droplets show that the droplet height and deformation both increase with increasing electric capillary number (

C

a
E

). In addition, for the breakup mode of prolate droplets, increasing

C

a
E

makes the long axis of the droplet incline more towards the wall electrodes and droplet breaks up into more daughter droplets. Results of oblate droplets show that the droplet height decreases with increasing

C

a
E

. However, the droplet deformation first decreases and then increases with increasing

C

a
E

, and its minima occurs at

C

a
E

=
0.01

. For the breakup mode of oblate droplets, the droplet deforms into a more oblate shape with a longer neck and finally breakup into more daughter droplets with increasing

C

a
E

.
Se-concentration dependent superstructure transformations of CuSe monolayer on Cu(111) substrate
Authors: Niu Gefei , Lu Jianchen , Wang Xingyue , Ruan Zilin , Zhang Hui , Gao Lei , Cai Jinming , Lin Xiao
Published: November 2021

As one of the most distinctive members of the monolayer transition metal monochalcogenides (TMM) family, the CuSe monolayer with a honeycomb structure has drawn much attention in the past few years. Depending on the Se concentration, the CuSe monolayer has two distinct superstructures on a Cu(111) substrate, a one dimensional (1D) moiré pattern, and two dimensional (2D) periodic nanopores. Here, we devise a strategy for simultaneous fabrication of the two superstructures of the CuSe monolayer on a Cu(111) substrate via artificially creating a density gradient of the Se concentration by an off-centered deposition method. At the boundary of the two superstructures, an intermediate state of the CuSe monolayer with a 2D hexagonal moiré pattern connected by six twisted petal-like stripes is observed. High-resolution scanning tunneling microscopy characterizations of three distinct CuSe monolayer superstructures demonstrate that the Se density can effectively modulate the stress in the CuSe monolayer formed by the lattice mismatch, driving the superstructure transformation from 1D moiré pattern through 2D intermediate states to 2D periodic nanopores. In addition, scanning tunneling spectroscopy measurements show that the intermediate state features a semiconducting behavior with a band gap of ∼2.0 eV. Our findings open up a new route for superstructure transformation control of 2D materials.
Microstructure and properties of ZrO2/Ni3Al-Ni3Al double-layer coating on stainless steel prepared by powder sintering one-step forming process
Authors: Li Xinxing , Yang Zirun , Wang Hongxia , Li Lin , Ren Naifei
Published: November 2021

ZrO2/Ni3Al-Ni3Al double-layer coating on stainless steel was prepared by powder sintering one-step forming process. The surface-interface morphologies, chemical element distribution and phase compositions of the coatings before and after thermal oxidation or hot corrosion were analyzed using scanning electron microscope (SEM), energy dispersive spectrometer (EDS) and X-ray diffractometer (XRD). The microstructure of the coating was Ni3Al matrix with dispersed ZrO2 particles, which was pure and compacted. The Ni3Al intermediate layer compactly formed between stainless steel substrate and ZrO2/Ni3Al composite coating, with good metallurgical bonding interfaces. The ZrO2/Ni3Al-Ni3Al double-layer coating exhibited a relatively high outmost microhardness of about 500 HV, and then gradually decreased from the coating to the substrate. When thermal oxidized or hot corroded at 1050 °C, a mixed oxide layer of NiO, Al2O3 and NiAl2O4 formed on the coating surface, which effectively acted as a diffusion barrier for oxygen and corrosive substances, and thus demonstrated the good protective effect of ZrO2/Ni3Al coating.
Assessing the dose rate delivery of helical TomoTherapy prostate and head & neck treatments
Authors: Kouris P , Moutsatsos A , Pappas E P , Beli I , Pantelakos P , Karaiskos P , Pantelis E
Published: November 2021

The dose rate distributions delivered to 55 prostate and head & neck (H&N) cancer patients treated with a helical TomoTherapy (HT) system were resolved and assessed with regard to pitch and field width defined during treatment planning. Statistical analysis of the studied cases showed that the median treatment delivery time was 4.4 min and 6.3 min for the prostate and H&N cases, respectively. Dose rate volume histogram data for the studied cases showed that the 25% and 12% of the volume of the planning target volumes of the prostate and H&N cases are irradiated with a dose rate of greater or equal to 1 Gy min−1. Quartile dose rate (QDR) data confirmed that in HT, where the target is irradiated in slices, most of the dose is delivered to each voxel of the target when it travels within the beam. Analysis of the planning data from all cases showed that this lasts for 68 s (median value). QDRs results showed that using the 2.5 cm field width, 75% of the prescribed dose is delivered to target voxels with a median dose rate of at least 3.2 Gy min−1 and 4.5 Gy min−1, for the prostate and H&N cases, respectively. Systematically higher dose rates were observed for the H&N cases due to the shallower depths of the lesions in this anatomical site. Delivered dose rates were also found to increase with field width and pitch setting, due to the higher output of the system which, in general, results in accordingly decreased total treatment time. The biological effect of the dose rate findings of this work needs to be further investigated using in-vitro studies and clinical treatment data.
Learning to teleoperate an upper-limb assistive humanoid robot for bimanual daily-living tasks
Authors: Connan Mathilde , Sierotowicz Marek , Henze Bernd , Porges Oliver , Albu-Schäffer Alin , Roa Máximo A , Castellini Claudio
Published: November 2021

Objective. Bimanual humanoid platforms for home assistance are nowadays available, both as academic prototypes and commercially. Although they are usually thought of as daily helpers for non-disabled users, their ability to move around, together with their dexterity, makes them ideal assistive devices for upper-limb disabled persons, too. Indeed, teleoperating a bimanual robotic platform via muscle activation could revolutionize the way stroke survivors, amputees and patients with spinal injuries solve their daily home chores. Moreover, with respect to direct prosthetic control, teleoperation has the advantage of freeing the user from the burden of the prosthesis itself, overpassing several limitations regarding size, weight, or integration, and thus enables a much higher level of functionality. Approach. In this study, nine participants, two of whom suffer from severe upper-limb disabilities, teleoperated a humanoid assistive platform, performing complex bimanual tasks requiring high precision and bilateral arm/hand coordination, simulating home/office chores. A wearable body posture tracker was used for position control of the robotic torso and arms, while interactive machine learning applied to electromyography of the forearms helped the robot to build an increasingly accurate model of the participant’s intent over time. Main results. All participants, irrespective of their disability, were uniformly able to perform the demanded tasks. Completion times, subjective evaluation scores, as well as energy- and time- efficiency show improvement over time on short and long term. Significance. This is the first time a hybrid setup, involving myoeletric and inertial measurements, is used by disabled people to teleoperate a bimanual humanoid robot. The proposed setup, taking advantage of interactive machine learning, is simple, non-invasive, and offers a new assistive solution for disabled people in their home environment. Additionnally, it has the potential of being used in several other applications in which fine humanoid robot control is required.
Pushing the boundaries of lithium battery research with atomistic modelling on different scales
Authors: Morgan Lucy M , Mercer Michael P , Bhandari Arihant , Peng Chao , Islam Mazharul M , Yang Hui , Holland Julian , Coles Samuel W , Sharpe Ryan , Walsh Aron , Morgan Benjamin J , Kramer Denis , Islam M Saiful , Hoster Harry E , Edge Jacqueline Sophie , Skylaris Chris-Kriton
Published: November 2021

Computational modelling is a vital tool in the research of batteries and their component materials. Atomistic models are key to building truly physics-based models of batteries and form the foundation of the multiscale modelling chain, leading to more robust and predictive models. These models can be applied to fundamental research questions with high predictive accuracy. For example, they can be used to predict new behaviour not currently accessible by experiment, for reasons of cost, safety, or throughput. Atomistic models are useful for quantifying and evaluating trends in experimental data, explaining structure-property relationships, and informing materials design strategies and libraries. In this review, we showcase the most prominent atomistic modelling methods and their application to electrode materials, liquid and solid electrolyte materials, and their interfaces, highlighting the diverse range of battery properties that can be investigated. Furthermore, we link atomistic modelling to experimental data and higher scale models such as continuum and control models. We also provide a critical discussion on the outlook of these materials and the main challenges for future battery research.
The simplicial coalgebra of chains determines homotopy types rationally and one prime at a time
Authors: Rivera Manuel , Wierstra Felix , Zeinalian Mahmoud
Published: November 2021

We prove that the simplicial cocommutative coalgebra of singular chains on a connected topological space determines the homotopy type rationally and one prime at a time, without imposing any restriction on the fundamental group. In particular, the fundamental group and the homology groups with coefficients in arbitrary local systems of vector spaces are completely determined by the natural algebraic structure of the chains. The algebraic structure is presented as the class of the simplicial cocommutative coalgebra of chains under a notion of weak equivalence induced by a functor from coalgebras to algebras coined by Adams as the cobar construction. The fundamental group is determined by a quadratic equation on the zeroth homology of the cobar construction of the normalized chains which involves Steenrod’s chain homotopies for cocommutativity of the coproduct. The homology groups with local coefficients are modeled by an algebraic analog of the universal cover which is invariant under our notion of weak equivalence. We conjecture that the integral homotopy type is also determined by the simplicial coalgebra of integral chains, which we prove when the universal cover is of finite type.
Algebra of Borcherds products
Authors: Ma Shouhei
Published: November 2021

Borcherds lift for an even lattice of signature

(
p
,
q
)

(p, q)

is a lifting from weakly holomorphic modular forms of weight

(
p
−
q
)

/

2

(p-q)/2

for the Weil representation. We introduce a new product operation on the space of such modular forms and develop a basic theory. The product makes this space a finitely generated filtered associative algebra, without unit element and noncommutative in general. This is functorial with respect to embedding of lattices by the quasi-pullback. Moreover, the rational space of modular forms with rational principal part is closed under this product. In some examples with

p
=
2

p=2

, the multiplicative group of Borcherds products of integral weight forms a subring.
Child Maltreatment and Mental Health in Middle Childhood: A Longitudinal Study in Japan
Authors: Isumi Aya , Doi Satomi , Ochi Manami , Kato Tsuguhiko , Fujiwara Takeo
Published: November 2021

Toxic stress caused by child maltreatment can lead to adverse mental health outcomes in later life, yet unmeasured confounding has been a major issue in many previous studies. To examine the association between child maltreatment and resilience and behavior problems among early elementary school-age children, we used data from a population-based longitudinal survey targeting all first-grade children in 2015 in Adachi City, a ward in Tokyo, Japan. Children whose caregivers provided valid responses during the 2015 (first grade; ages 6–7 years), 2016 (second grade; ages 7–8 years), and 2018 (fourth grade; ages 9–10 years) waves of the study were included in the analysis (n = 2,920). Fixed-effects regression models revealed that child maltreatment was inversely associated with resilience (β = −0.89, 95% confidence interval (CI): −1.05, −0.72) and prosocial behavior (β = −0.03, 95% CI: −0.05, −0.003) and positively associated with behavior problems (β = 0.32, 95% CI: 0.27, 0.37) over 4 years of follow-up (2015–2018), after controlling for all time-invariant confounders and measured time-varying confounders and survey year. These associations were consistent across sex. Child maltreatment may hamper the development of resilience and prosocial behavior and induce behavior problems in early elementary school children over time. Future researchers should identify modifiable protective factors for better mental health among maltreated children.
Advancing the Social Epidemiology Mission of theAmerican Journal of Epidemiology
Authors: Gilman Stephen E , Aiello Allison , Galea Sandro , Howe Chanelle J , Kawachi Ichiro , Lovasi Gina S , Dean Lorraine T , Oakes J Michael , Siddiqi Arjumand , Glymour M Maria
Published: November 2021

Social epidemiology is concerned with how social forces influence population health. Rather than focusing on a single disease (as in cancer or cardiovascular epidemiology) or a single type of exposure (e.g., nutritional epidemiology), social epidemiology encompasses all the social and economic determinants of health, both historical and contemporary. These include features of social and physical environments, the network of relationships in a society, and the institutions, politics, policies, norms and cultures that shape all of these forces. This commentary presents the perspective of several editors at the Journal with expertise in social epidemiology. We articulate our thinking to encourage submissions to the Journal that: 1) expand knowledge of emerging and underresearched social determinants of population health; 2) advance new empirical evidence on the determinants of health inequities and solutions to advance health equity; 3) generate evidence to inform the translation of research on social determinants of health into public health impact; 4) contribute to innovation in methods to improve the rigor and relevance of social epidemiology; and 5) encourage critical self-reflection on the direction, challenges, successes, and failures of the field.
Tenuazonic acid production is dispensable for virulence, but its biosynthetic gene expression pattern is associated with the infection of Pyricularia oryzae
Authors: Kashiwa Takeshi , Motoyama Takayuki , Yoshida Kazuko , Yun Choong-Soo , Osada Hiroyuki
Published: November 2021

Tenuazonic acid (TeA) is a toxin produced by the rice blast fungus Pyricularia oryzae. Although knockout of the TeA biosynthetic gene TAS1 did not affect the virulence of P. oryzae, constitutive TAS1 expression suppressed its infection. TAS1 expression was induced alongside transition of P. oryzae infection behavior. The results suggested that controlling TeA biosynthesis is important for P. oryzae infection.
Validation of predicted anonymous proteins simply using Fisher’s exact test
Authors: Claverie Jean-Michel , Santini Sébastien
Published: November 2021

Motivation

Genomes sequencing has become the primary (and often the sole) experimental method to characterize newly discovered organisms, in particular from the microbial world (bacteria, archaea, viruses). This generates an ever increasing number of predicted proteins the existence of which is unwarranted, in particular among those without homolog in model organisms. As a last resort, the computation of the selection pressure from pairwise alignments of the corresponding ‘Open Reading Frames’ (ORFs) can be used to validate their existences. However, this approach is error-prone, as not usually associated with a significance test.

Results

We introduce the use of the straightforward Fisher’s exact test as a postprocessing of the results provided by the popular CODEML sequence comparison software. The respective rates of nucleotide changes at the nonsynonymous versus synonymous position (as determined by CODEML) are turned into entries into a 2 × 2 contingency table, the probability of which is computed under the Null hypothesis that they should not behave differently if the ORFs do not encode actual proteins. Using the genome sequences of two recently isolated giant viruses, we show that strong negative selection pressures do not always provide a solid argument in favor of the existence of proteins.
COBREXA.jl: constraint-based reconstruction and exascale analysis
Authors: Kratochvíl Miroslav , Heirendt Laurent , Wilken St Elmo , Pusa Taneli , Arreckx Sylvain , Noronha Alberto , van Aalst Marvin , Satagopam Venkata P , Ebenhöh Oliver , Schneider Reinhard , Trefois Christophe , Gu Wei
Published: November 2021

COBREXA.jl is a Julia package for scalable, high-performance constraint-based reconstruction and analysis of very large-scale biological models. Its primary purpose is to facilitate the integration of modern high performance computing environments with the processing and analysis of large-scale metabolic models of challenging complexity. We report the architecture of the package, and demonstrate how the design promotes analysis scalability on several use-cases with multi-organism community models.

Availability and implementation

https://doi.org/10.17881/ZKCR-BT30.

Supplementary information

Supplementary data are available at Bioinformatics online.
Chromosome numbers and heterochromatin variation in introgressed and non-introgressed populations ofEpidendrum(Orchidaceae: Epidendroideae): interspecific transfers of heterochromatin lead to divergent variable karyotypes in the parental populations
Authors: Nollet Felipe , Medeiros Neto Enoque , Cordeiro Joel M P , Buril Maria Teresa , Chase Mark W , Felix Leonardo P
Published: November 2021

Some groups in Epidendrum have stable chromosome numbers, whereas the species of Epidendrum subgenus Amphiglottium exhibit high levels of chromosome number variability and other genomic alterations. Polyploidy and dysploidy have both been invoked to explain chromosome number variation in the subgenus, but little is known about what is driving the high frequency of chromosome modification within some species in this group. To test whether hybridization and introgression are involved, we use fluorochrome staining to evaluate the chromosome numbers and heterochromatin bands in E. subgenus Amphiglottium, including individual parental genotypes from introgressed and non-introgressed populations. Two main types of heterochromatin were observed forming CMA and DAPI bands in Epidendrum spp. B chromosomes were identified in some individuals. In non-introgressed populations, E. secundum has three cytotypes, 2n = 28, 56 and 84, found in different parts of its geographical range and a small number of DAPI bands. In introgressed populations of E. secundum, there was dysploid variation among individuals that were morphologically typical parental plants, and in one introgressed population a high number of DAPI bands was observed in what appeared on morphological grounds to be pure parental individuals. Our data corroborate the hypothesis that hybridization and introgression play a role in generating chromosome variation (number and form) and heterochromatin diversification in E. subgenus Amphiglottium.
High dream recall frequency is associated with an increase of both bottom-up and top-down attentional processes
Authors: Ruby Perrine , Masson Rémy , Chatard Benoit , Hoyer Roxane , Bottemanne Laure , Vallat Raphael , Bidet-Caulet Aurélie
Published: November 2021

Event-related potentials (ERPs) associated with the involuntary orientation of (bottom-up) attention toward an unexpected sound are of larger amplitude in high dream recallers (HR) than in low dream recallers (LR) during passive listening, suggesting different attentional functioning. We measured bottom-up and top-down attentional performance and their cerebral correlates in 18 HR (11 women, age = 22.7 years, dream recall frequency = 5.3 days with a dream recall per week) and 19 LR (10 women, age = 22.3, DRF = 0.2) using EEG and the Competitive Attention Task. Between-group differences were found in ERPs but not in behavior. The results show that HR present larger ERPs to distracting sounds than LR even during active listening, arguing for enhanced bottom-up processing of irrelevant sounds. HR also presented larger contingent negative variation during target expectancy and P3b to target sounds than LR, speaking for an enhanced recruitment of top-down attention. The attentional balance seems preserved in HR since their performances are not altered, but possibly at a higher resource cost. In HR, increased bottom-up processes would favor dream recall through awakening facilitation during sleep and enhanced top-down processes may foster dream recall through increased awareness and/or short-term memory stability of dream content.
The 30-day readmission rate of same-day discharge protocol following catheter ablation for atrial fibrillation: a propensity score-matched analysis from National Readmission Database
Authors: Sahashi Yuki , Kuno Toshiki , Tanaka Yoshihiro , Passman Rod , Briasoulis Alexandros , Malik Aaqib H
Published: November 2021

Aims

The effectiveness and safety of same-day discharge (SDD) for catheter ablation (CA) for atrial fibrillation (AF) has not been fully elucidated using a large nationwide database. This study aimed to evaluate the all-cause readmission rates within 30-days among patients receiving CA for AF with an SDD protocol compared with a conventional overnight stay (ONS).

Methods and results

We performed a retrospective cohort study using the US Nationwide Readmission Database. The primary outcome was all-cause 30-day readmission following discharge in patients receiving CA and a secondary outcome was requiring total healthcare cost. A 1 : 3 propensity score matching was conducted to compare the safety and efficacy within both SDD and ONS group. Among 30 776 patients [mean 67.2 ± 11.4 years, 12 590 female (41.5%)] who received CA from 2016 through 2018, 440 (1.42%) patients were discharged on the same-day following CA (SDD group), and the remaining 30 336 patients stayed at least one night in the hospital (ONS group). A propensity score analysis generated 1751 matched pairs (440 in the SDD group; 1311 in the ONS group). The 30-day readmission following discharge was not significantly higher in the SDD group than the ONS group (SDD vs. ONS: 12.7% vs. 9.7%; hazard ratio: 1.17, 95% confidence interval: 0.76–1.81, P = 0.47). Healthcare cost was significantly higher in the ONS group ($25 237 ± 14 036 vs. $30 749 ± 16 383; P < 0.01).

Conclusion

In this nationwide database study, there was no significant difference in the all-cause 30-day readmission following SDD for CA compared with ONS.
Recognizing sinonasal cancer in primary care: a matched case–control study using electronic records
Authors: Khan Tuba , El-Sockary Yusera , Hamilton William T , Shephard Elizabeth A
Published: November 2021

Background

Cancers of the nasopharynx, nasal cavity, and accessory sinuses (“sinonasal”) are rare in England, with around 750 patients diagnosed annually. There are no specific National Institute for Health and Care Excellence (NICE) referral guidelines for these cancers and no primary care research published.

Objective

To identify and quantify clinical features of sinonasal cancer in UK primary care patients.

Methods

This matched case–control study used UK Clinical Practice Research Datalink (CPRD) data. Patients were aged ≥40 years with a diagnosis of sinonasal cancer between January 1, 2000 and December 31, 2009 and had consulted their GP in the year before diagnosis. Clinical features of sinonasal cancer were analysed using conditional logistic regression. Positive predictive values (PPVs) for single and combined features were calculated.

Results

In total, 155 cases and 697 controls were studied. Nine symptoms and one abnormal investigation were significantly associated with the cancer: nasal mass; odds ratio, 95 (95% confidence interval 7.0, 1315, P = 0.001); head and neck lumps, 68 (12, 387, P < 0.001); epistaxis, 17 (3.9, 70, P < 0.001); rhinorrhoea, 14 (4.6, 44, P < 0.001); visual disturbance, 12 (2.2, 67, P = 0.004); sinusitis, 7.3 (2.2, 25, P = 0.001); sore throat, 6.0 (2.0, 18, P = 0.001); otalgia, 5.4 (1.6, 18, P = 0.007); headache, 3.6 (1.4, 9.5, P = 0.01); raised white cell count, 8.5 (2.8, 27, P < 0.001). Combined PPVs for epistaxis/rhinorrhoea, epistaxis/sinusitis, and rhinorrhoea/sinusitis were 0.62%.

Conclusion

This is the first primary care study identifying epistaxis, sinusitis, and rhinorrhoea as part of the clinical prodrome of sinonasal cancer. Although no PPVs meet the 3% NICE referral threshold, these results may help clinicians identify who warrants safety-netting and possible specialist referral, potentially reducing the number of advanced-stage diagnoses of sinonasal cancer.
Biosurfactant production by halophilic yeasts isolated from extreme environments in Botswana
Authors: Loeto Daniel , Jongman Mosimanegape , Lekote Lerato , Muzila Mbaki , Mokomane Margaret , Motlhanka Koketso , Ndlovu Thando , Zhou Nerve
Published: November 2021

Nine morphologically distinct halophilic yeasts were isolated from Makgadikgadi and Sua pans, as pristine and extreme environments in Botswana. Screening for biosurfactant production showed that Rhodotorula mucilaginosa SP6 and Debaryomyces hansenii MK9 exhibited the highest biosurfactant activity using Xanthocercis zambesiaca seed powder as a novel and alternative inexpensive carbon substrate. Chemical characterization of the purified biosurfactants by Fourier Transform Infra-Red spectroscopy suggested that the biosurfactant from R. mucilaginosa SP6 was a rhamnolipid-type whereas the biosurfactant from D. hansenii MK9 was a sophorolipid-type. The two biosurfactants exhibited antimicrobial activities against eight pathogenic bacteria and fungal strains (Proteus vulgaris, Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, Micrococcus luteus, Cryptococcus neoformans, Candida albicans and Aspergilus niger). The sophorolopid-type biosurfactant was found to be the most potent among the antimicrobial drug resistant strains tested. The findings open up prospects for the development of environmentally friendly antimicrobial drugs that use an inexpensive source of carbon to reduce the costs associated with the production of biosurfactants.
Detection and modelling of strong topography of mid-mantle structures beneath the North Atlantic
Authors: Saki Morvarid , Thomas Christine , Abreu Rafael
Published: November 2021

There is mounting evidence for the presence of seismic reflectors in the mantle at a depth of around 1000 km, however, the cause for these reflectors is not yet well established and published observations show a range of depth estimates for these structures. Discussion is also still ongoing whether it is one global or several different reflectors. Here, we investigate the presence of seismic reflectors beneath the North Atlantic using a large number of PP and SS underside reflections. We analyse over 2600 earthquakes with Mw ≥ 5.7 and use array seismic methods to improve the visibility of the small-amplitude reflected signals. The measured time lag between PP/SS arrivals and their corresponding precursors on robust stacks are used to estimate the depth of the reflector. Our results reveal the presence of mid-mantle structure beneath the North Atlantic in a depth range of ∼700–1300 km, consistent for both P- and S-wave observations. The reflector depth is shallower than 1000 km beneath the southern part of the investigation area and deepens seemingly abruptly towards the northern part of the North Atlantic. We find polarity variations in a region of strong depth change which we assume to be due to wave interference. Using 3-D waveform modelling, we implement models with strong topography as well as models with two overlapping reflectors and two separated reflectors and show that a large step in reflector depth over a short lateral distance, as imaged with our data set, can be resolved, while the discrimination between strong topography and two overlapping and separated reflectors, respectively, is also possible. The variations in precursor polarity can also be observed in our synthetic data in the region of strong topography confirming our assumption of wave interference for generating apparent precursor polarity and waveform changes. While the opposite polarity can be produced by the two overlapping reflectors as well, the strong topography model is preferred in this region, since we do detect only one reflected signal in our observations.
Environmental Law
Authors: Fisher Elizabeth , Lange Bettina , Scotford Eloise
Published: November 2021

All books in this flagship series contain carefully selected substantial extracts from key cases, legislation, and academic debate, providing able students with a stand-alone resource. Environmental Law: Text, Cases & Materials provides students with a deep understanding of environmental law while also encouraging critical reflection of legal reasoning and pointing out areas of controversy and debate. The authors present a wide range of extracts from UK, EU, and international cases, legislation, and articles to help support learning and demonstrate both how the law works in practice and how it should or could work, clearly guiding students through key areas while providing insightful explanations and analysis. Topics have been carefully selected to support a wide range of environmental law courses, within law school and beyond. These include pollution control, nature conservation, climate change regulation, town planning, and water regulation, all incorporating aspects of law from local, UK, EU and international legal cultures. With its unique combination of extracts and author discussion, this new edition provides a wide-ranging, stimulating, and fresh approach to environmental law, which can be relied upon throughout your course and career. This book is also accompanied by an Online Resource Centre that features updates to the law, further reading suggestions, and useful weblinks.