bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced third-harmonic generation via gold nanospheres localized surface plasmonic resonance
Authors: Wei Haiyuan , Tang Ziying , Shen Yan , Zheng Huying , Wang Yaqi , Wang Runchen , Zhu Hai , Su Shichen , Zhu Yunliang , Zhou Jie , Qiu Zhi Ren
Published: April 2022

In the progress of nanoengineering of noble metals, the extreme nonlinear optics within nanometric volumes is of great research interest in recent years. In particular, plasmonic nanostructures offer unique route for enhancing high-order harmonic generation and other nonlinear optical progress. Here, we report that strong third harmonic emission in zinc oxide (ZnO) microbelts (MBs) via a strong localization of electromagnetic field caused by localized surface plasmon resonances. In MB/Au-nanoparticles composite, it was demonstrated that the intensity of third-harmonic generation (THG) was enhanced by a factor of five compared to bare MB. Additionally, the polarization characteristics of THG in the same system were illustrated in detail. With respect to the bare MB, the polarization degree of THG was improved significantly. The nonlinear polarization features can be attributed to the crystal structure and the ensemble of anisotropic plasmonic hot spots on the surface of Au nanoparticles. Finally, intrinsic enhancement process of THG was explored comprehensively by finite difference time domain method. The simulation results are consistent with our experimental observation.
Kinetic theory of sech2
x electron holes and applications to Kappa-distributed plasmas
Authors: Guo Ran
Published: April 2022

The kinetic theory of sech2
x-type electron holes (EHs) is studied. The potential of the EHs is solved in the weak amplitude limit by the pseudo-potential method. We investigate the existence condition of the sech2
x EHs. It indicates that the derivatives of trapped and untrapped distributions at the separatrix play significant roles in determining the potential profile. The theory is then applied to the Kappa-distributed plasmas. The amplitude and width of the sech2
x EHs are analyzed. Finally, the theoretical results are verified by numerical calculations.
Temperature-dependent asymmetric Prandtl-Ishlinskii hysteresis model for piezoelectric actuators
Authors: Savoie Marc , Shan Jinjun
Published: April 2022

A temperature-dependent asymmetric Prandtl-Ishlinskii (TAPI) model is developed to describe changes in hysteresis curves with respect to temperature found in the displacement curves vs. input voltage of a piezoelectric actuator (PEA). The proposed modeling scheme considers nonlinearities in an idealized capacitor term in the electromechanical model of the PEA to introduce both asymmetry and temperature dependence in the model. The developed model has the advantage of incorporating asymmetric and thermal effects in a hysteresis-free region of the model which simplifies inversion of the model as well as parameter determination. A parameter identification scheme is described to simplify model identification, even for a large number of thresholds, based on the advantages of the classical Prandtl-Ishlinskii model. The TAPI model is verified experimentally and a compensator is designed to demonstrate that the PEA output is effectively linearized throughout the temperature range.
Thermodynamic selection: mechanisms and scenarios
Authors: Babajanyan S G , Koonin E V , Allahverdyan A E
Published: April 2022

Thermodynamic selection is an indirect competition between agents feeding on the same energy resource and obeying the laws of thermodynamics. We examine scenarios of this selection, where the agent is modeled as a heat-engine coupled to two thermal baths and extracting work from the high-temperature bath. The agents can apply different work-extracting, game-theoretical strategies, e.g. the maximum power or the maximum efficiency. They can also have a fixed structure or be adaptive. Depending on whether the resource (i.e. the high-temperature bath) is infinite or finite, the fitness of the agent relates to the work-power or the total extracted work. These two selection scenarios lead to increasing or decreasing efficiencies of the work-extraction, respectively. The scenarios are illustrated via plant competition for sunlight, and the competition between different ATP production pathways. We also show that certain general concepts of game-theory and ecology—the prisoner’s dilemma and the maximal power principle—emerge from the thermodynamics of competing agents. We emphasize the role of adaptation in developing efficient work-extraction mechanisms.
Design and Implementation of Intelligent Security Robot Based on Lidar and Vision Fusion*
Authors: Zhou Bo , Du Minglin , Chen Zhenguo , Liu Yajun , Zhang Yan , Wang Yan
Published: April 2022

Nowadays, the mainstream security robot is expensive and the single 2D Lidar SLAM robot has large pose error and large matching calculation in navigation. To solve these problems, this paper designs an intelligent security robot based on the ROS system and STM32 microcontroller. Through the fusion of camera, IMU, lidar multi-sensor data, completing its own positioning, surrounding environment mapping and autonomous navigation functions; Binocular camera for face recognition, lock suspicious persons; Combined with temperature and humidity, smoke and other sensors for environmental monitoring, real-time alarm; Security personnel remote control, according to the data uploaded by the robot to complete the patrol. After a lot of experiments, the functions of the robot are better completed, which has a certain practical value.
UAV dynamic obstacle avoidance based on improved reciprocal velocity obstacle
Authors: Gao Jing , Zhang Hongtao , Tan Li , Ren Xueping
Published: April 2022

This paper aims to solve the problem that when the UAV flies from the starting point to the target point in the velocity space, the obstacle avoidance speed provided by the mutual velocity obstacle method will appear too large turning angle in order to avoid dynamic obstacles. In order to better meet the flight performance of UAV, an improved mutual velocity obstacle method is proposed in this paper. This method can not only solve the problem of path jitter caused by the speed obstacle method, but also solve the problem of excessive turning angle when the velocity direction selected by the mutual velocity obstacle method is flying towards the target point. In addition, the UAV will not return to the original path after the obstacle avoidance, but fly along the target point according to the updated best speed direction, so as to reduce the number of turns. The simulation results show that the improved mutual velocity obstacle method can effectively reduce the turning angle of UAV in dynamic environment and meet the flight performance of UAV.
An Active Suspension System Design for a Racing Car
Authors: Shi Kailai
Published: April 2022

This paper investigated the PID controller for an active suspension system for a racing car. A two-wheel half-car model is used and simulated in the Simulink environment. This model allows us to have two outputs and separately change the demand ride height of the front axle and the rear axle. Considering it is a racing car, downforce plays an important part in the suspension system and makes it a bit different from a private car that can only produce little downforce that can be ignored. To improve the control quality, a feedforward controller is added to compensate for the downforce.
Optimal Strategy for Pick-and-Place System with two Robots
Authors: Zhou Min , Jiang Renjie
Published: April 2022

In many situations in industry, a sorting process must be performed to separate different or unnecessary items from those on a moving conveyor belt. In this paper we focus on the problem of how to obtain the optimal pick-and-place (PNP) sequence in a conveyor with two robots. Traditional methods are analyzed and their disadvantages are illustrated, and the algorithm we have developed is presented and accelerated using dynamic planning methods. Furthermore, by building PNPTIME tables, our algorithm considers the complex dynamics and geometry of the different robot models in practice. Our algorithm has sufficient computational speed to be suitable for practical PNP applications requiring high throughput, and extensive testing of the algorithm has shown a 10-20% improvement over traditional methods based on greedy methods.
Synchronous control of the robot for repairing broken strands of overhead ground wires
Authors: Peng Jiaying , Tao Hongfei , Ni Hongyu , Yan Wenxu
Published: April 2022

Abstarct. Overhead ground wire broken strand repair robot is a new type of electric robot, a complex multi-motor system. Therefore, the problem of synchronous control of each mechanism in the robot needs to be solved. A dual-layer sliding mode control strategy based on a cross-coupled synchronous control structure is proposed from the perspectives of mechanical structure synchronization and algorithm synchronization in this paper.

Firstly, a global fast terminal sliding mode controller with single motor is designed for permanent magnet synchronous motor;

Secondly, for the dual-motor system in the pre-twisted wire winding mechanism, a cross-coupling control structure is introduced. And a dual-motor synchronous compensation controller is designed in view of the fast non-singular terminal sliding mode combined with the new approximation law;

Finally, the simulation verification in MATLAB, the results show that it has a certain improvement on the tracking error and synchronization error of the system. The anti-disturbance ability of the pre-twisted wire winding mechanism against uncertain loads is improved.
An improved object detection algorithm based on YOLO*
Authors: Guo Hao , Yang Jiahua
Published: April 2022

Accuracy and speed have always been a measure of the performance of object detection algorithms. The current algorithms have reduced the detection speed on the basis of increasing a certain accuracy due to their complex structure. In response to this problem, this paper uses the RepVGG network to improve the original YOLOv3 structure, which uses a diversified branch structure to enhance the network feature extraction ability during training and transforms the training model into an equivalent VGG-like topology network model during inference. In addition, we use ASFF to deal with the problem of mutually restricted scales. Experiments show that compared with the original algorithm, the improved algorithm increases mAP by 0.51 on the VOC data set, and at the same time the speed increases by 10%.
Target tracking algorithm of intermittently updated template based on reliability evaluation
Authors: Xie Qingsong , Shen Jingwei , An Zhiyong
Published: April 2022

In the siamese network tracking method based on the target matching idea, the tracking performance is closely related to the similarity between the tracking template and the tracking target. The UpdateNet algorithm updates the tracking results of each frame prediction into the template during tracking, which undoubtedly guarantees the real-time correlation between the template and the tracking target. However, tracking targets will encounter tracking challenges such as occlusion and short-term severe deformation. The tracking results predicted under this tracking challenge will be mixed with messy information that has nothing to do with the tracking target. If the UpdateNet algorithm updates the tracking results that are rich in messy information into the template, the purity of the template will decrease. This paper proposes a method of intermittently updating templates by proposing template update constraints, so that the UpdateNet algorithm discards the low-confidence tracking results. This guarantees the purity of the tracking template to a certain extent, which improves the relevance of the tracking template and the tracking target. In addition, this article also conducts optimal training on the UpdateNet algorithm.
SPI-CGAN: Single-pixel imaging based on conditional generative adversarial network
Authors: Lu Yongyun , Tan Benying , Ding Shuxue , Li Yujie
Published: April 2022

Imaging quality at extremely sampling ratios is a key research topic in the field of single-pixel imaging (SPI). Although conventional methods can be used to reconstruct the object images at low sampling ratios, the reconstructed image is still visually unclear. To solve this problem, an SPI model based on a conditional generative adversarial network (SPI-CGAN) is proposed to achieve an end-to-end reconstruction of the object images and improve the image quality of the reconstruction at extremely low sampling ratios. To improve the stability of the training model, the objective function is composed of multiple loss functions. The validity of the model is verified through simulation data, which do not require a long time to collect. The optimized SPI-CGAN can reconstruct a sharp image edge at extremely low sampling ratios. Compared with a linear iterative method and a nonlinear iterative method, the proposed method performs better in terms of the quantitative indicators used.
SETAR Model Research Based on Support Vector Regression Parameter Estimation Method and Empirical Analysis
Authors: Li Yun , Yin Xiangfeng , Wen Xueting
Published: April 2022

In this paper, we use support vector regression (SVR) to estimate the parameters of the SETAR model for predicting the log-return of stock price data. SETAR model is usually estimated using maximum likelihood (ML) and minimize conditional sum-of-squares (CSS), assuming that the data are normal distribution. SVR is a powerful tool for regression estimation. Therefore, this paper proposes to use SVR instead of maximum likelihood and conditional least squares to estimate the parameters of the SETAR model. Empirical analysis on the two stock price data of China Unicom and ICBC, the results show that on the data of China Unicom, the prediction error of the Gaussian kernel SVR-SETAR model is 8% lower than that of the ML-SETAR model and the CSS-SETAR model. And on ICBC data, the prediction error of the Gaussian kernel SVR-SETAR model is 26.32% and 20% lower than that of the ML-SETAR model and CSS-SETAR model, respectively. This suggests that SVR can be used to estimate the parameters of the SESAT model and the SVR-SETAR model has higher predictive power.
Improve the spot-like coding detection of U-net auto-encoder
Authors: Liu Beibei , Hu Weiping , Li Fan
Published: April 2022

The dot-like spray code on the product packaging has always been a difficult problem in industrial inspection due to its complicated background in the printing area, diverse characters in the code, and changeable fonts. With the powerful capabilities of deep learning in the field of computer vision, related algorithms have become popular solutions in the field of computer vision in recent years. The method based on convolutional autoencoders to achieve inkjet detection on food packaging boxes has become a feasible solution. This method takes the mask of the coding character area on the food packaging box as the final goal of network learning. The network inputs the picture with the coding area, and reconstructs the original background of the coding area. At the same time the network uses the residual channel attention mechanism to restore the details of the image, and at the same time introduces the gaussian operator to calculate the loss of network reconstruction. Since the convolutional auto-encoder is an unsupervised learning method, the training data does not require a large amount of manual labeling, and a good solution is proposed for scenarios such as small data sets in industrial production and difficulty in labeling. Through real-time testing of the coding data of the pipeline, it is verified that the method can effectively detect the coding area.
Glass Defect Detection via Multi-Scale Feature Fusion
Authors: Huang Haiying , Zhan Qiugang , Xie Xiurui , Ye Dongsheng , Liu Guisong
Published: April 2022

Glass defect detection is significant in glass industry. However, most of the existing methods for glass defect detection currently still rely on manual screening with high-cost and poor-efficiency. To address this issue, we propose a glass defect detection method using multi-scale feature fusion strategy. Specifically, we first propose an algorithm based on pix2pix to realize the edge extraction. Then, we propose a glass defect detector based on both local and global features. Comprehensive experiments are conducted on collected glass dataset from factories. The experimental results demonstrate that our method outperforms conventional methods including the traditional image processing and Holistically-Nested Edge Detection (HED), with the precision rate (PR) up to 97%, the false precision rate (FP) below 2% and the total accuracy rate (ACC) of glass defect detection up to 98%.
Joint Measurement of Multi-channel Sound Event Detection and Localization Using Deep Neural Network
Authors: Zhou Yuting , Wan Hongjie
Published: April 2022

For joint sound event localization and detection (SELD), a multi-channel sound event method based on deep learning is proposed. This paper uses CRNN model training with datasets of maximum two overlapping sound events. The difficulty of the polyphonic SELD is the combination of SED and DOA estimation in the same network. Using multi-channel audio can better identify these overlapping sound events. The input of the proposed model is a series of continuous spectrograms, which are then output to two branches respectively. As the first branch, SED performs multi-label classification in each time segment. As the second branch, 3-D Cartesian coordinates are used to represent the DOA estimate of each sound event. This paper extracts the phase feature and amplitude feature of the sound spectrum from each audio channel, avoiding feature extraction limited by other microphone arrays.
X-ray security check image recognition based on attention mechanism
Authors: Wu Xiru , Liu Chao
Published: April 2022

In order to improve the detection efficiency and accuracy of the security check process, a detection algorithm that can accurately detect dangerous goods is constructed based on the attention mechanism and combined with the DETR algorithm. Combining the X-ray image data samples collected by the actual security inspection, the image data is trained through the deep learning network and analyzed on the verification data. The results show that the algorithm has higher verification accuracy, and the accuracy is higher than that of traditional detection algorithms, and it can locate dangerous goods more accurately. The method given in this article provides theoretical support and reference for the actual security inspection process.
Remote Sensing Image Retrieval Based on Key Region Detection
Authors: ye Famao , Zhang Rengao , Xing Yuchi , Xin Junwei , Li Dajun
Published: April 2022

Remote sensing (RS) images usually describe large-scale natural geographical scenes with complex and rich background information, which will affect the retrieval performance of image features. How to reduce the background interference and improve the reliability of remote sensing image retrieval (RSIR) features is a problem that needs to be solved. In this paper, a RSIR method based on key region detection was proposed. Firstly, the ground objects of the image are extracted by a famous deep learning object detection model, a YOLO v5 model. Next, we extract the key region of the image according to these ground objects. Then, the image content in the key region is used to extract the retrieval feature by the convolutional neural networks (CNN) model, Resnet. Moreover, the weighted distance based on class probability is used to further improve retrieval performance. Our method utilizes the object detection capability of the YOLO model and the feature extraction capability of RESNET. Our method uses the target detection ability of the YOLO model and the feature extraction ability of RESNET to extract the retrieval feature of RS images. The experimental results on UCMD show that this method can improve the performance of RSIR.
FPGA-based real-time data processing for accelerating reconstruction at LHCb
Authors: Lazzari F. , Baldini W. , Bassi G. , Contu A. , Dorigo M. , Fantechi R. , Giambastiani L. , Morello M.J. , Punzi G. , Sticchi M. , Tuci G.
Published: April 2022

In run-3, beginning in 2022, the LHCb software trigger will start reconstructing events at the LHC average crossing rate of 30 MHz. Within the upgraded DAQ system, LHCb established a testbed for new heterogeneous computing solutions for real-time event reconstruction, in view of future runs at even higher luminosities. One such solution is a highly-parallelized custom tracking processor (“Artificial Retina”), implemented in state of the art FPGA devices connected by fast serial links. We describe the status of a realistic prototype for the reconstruction of pixel tracking detectors that will run on real data during run-3.
Diffusion processes with Gamma-distributed resetting and non-instantaneous returns
Authors: Radice Mattia
Published: April 2022

We consider the dynamical evolution of a Brownian particle undergoing stochastic resetting, meaning that after random periods of time it is forced to return to the starting position. The intervals after which the random motion is stopped are drawn from a Gamma distribution of shape parameter α and scale parameter r, while the return motion is performed at constant velocity v, so that the time cost for a reset is correlated to the last position occupied during the stochastic phase. We show that for any value of α the process reaches a non-equilibrium steady state and unveil the dependence of the stationary distribution on v. Interestingly, there is a single value of α for which the steady state is unaffected by the return velocity. Furthermore, we consider the efficiency of the search process by computing explicitly the mean first passage time. All our findings are corroborated by numerical simulations.
The Effect of Growing Media on the Vitamin C and Chlorophyll Content of Gelinggang Microgreen
Authors: Rohmanna N. A , Mulyawan R.
Published: April 2022

Cassia alata L. (called Gelinggang) was a type of herbal plant used as a skin and diarrhea medicine. However, there has been no further research related to gelinggang microgreens. Therefore, this study utilizes gelinggang as a microgreen. This study aimed to determine the growth media’s effect on chlorophyll and ascorbic acid in gelinggang microgreens. In this study, gelinggang seed was grown in organic soil and rockwool for about 14 days at room temperature (27±1°C). The chlorophyll of acetone extract and ascorbic acid of sodium oxalate extract of this microgreen were determined using UV-Vis spectrophotometric methods. There was a difference between organic soil and rockwool as growing media on the vitamin C and chlorophyll gelinggang microgreen. The study showed that microgreens on organic soil had the highest chlorophyll content, while microgreens on rockwool had the highest vitamin C content. Thus gelinggang microgreens high in phytochemicals compounds could be used as health-promoting food ingredients.
The quality of vermicompost from various sources composted with earthworm Perionyx excavates
Authors: Riwandi  , Muktamar Zainal , Hasanudin  , Anandyawati  , Allsari Vira
Published: April 2022

The quality of vermicompost depends on the source of earthworms feed such as animal waste (cows, buffaloes, chickens, and goats). The aim of the study was to obtain high quality vermicompost and to determine the parameters of vermicompost in accordance with the compost quality standard from SNI 19-7030-2004. The experimental design was Completely Randomized Design (CRD) with the treatment of types animal manures: consisted of cow, buffalo, chicken, and goat manures with 6 replications, so there were 24 experimental units. The results showed that the 9 parameters of vermicompost tested complied to the quality criteria of compost from SNI 19-7030-2004. The significant finding of this study was the weight of the remaining earthworms decreased from 12 g at initial weight to 2.42 g for cow dung, 2.38 g for buffalo dung, 1.62 g for chicken manure and 0,63 g for goat dung after harvesting the vermicompost. The highest quality of vermicompost according to the criteria of SNI 19-7030-2004 was cow dung, followed by buffalo dung, goat dung, and chicken manure. According statistical analysis showed that pH (H2O,1:5 w/v) is 8.90 (highest) for chicken manure, 8.60 (medium) for cow dung as well as 8.46 (medium) for goat dung, and 7.90 (low) for buffalo dung. Water content are not significant for all sources of vermicompost which is 50% more. Temperatures of vermicompost from goat dung (28.70°C) and chicken manure (28.29°C) are significant significantly higher than cow dung (27.68°C), and buffalo dung (27.89°C). Organic C content, total N content, and C/N ratio of vermicompost used descriptive analysis. Organic C content was highest in vermicompost derived from buffalo dung, followed by cow dung, chicken manure, and goat dung as well as total N content from goat dung, chicken manure, buffalo dung, and cow dung. Also C/N ratio from low to high are goat dung, chicken manure, cow dung, and buffalo dung.
Germination of dormant onion bulbs in different growing media
Authors: Sopiana R , Suwignyo R A , Harun M U , Susilawati
Published: April 2022

The aim of the study was to examine the planting media as a stimulant for onion germination. This study used onion bulbs of the Batu ijo variety with one week after harvest sizes ranging from 20 to 25 g/tuber, bulbs lengths were from 4 cm to 5 cm. The research used a completely randomized design with three factors that repeated 10 replications. Onion bulbs were planted in pots with a volume of 2 L which were only filled with 80% of the pot volume. In each pot was planted one onion bulb that had been cut off the top 1/3 with a planting depth. The number of sample plant pots for each media were 15 pots so that the total were 45 pots. Watering was done as much as 1 L/pot/day so that the growing media was always wet. Every two days They were observed for variables number of sprouts, shoots, roots, and leaves. All variables were analysed by analysis of variance. The results showed that the onion bulbs sown for one month in growing media have not been able to stimulate germination, and cocopeat media produced 20% germination compared with more sawdust and husk media. On cocopeat media, dormant onion bulbs germinated in 14 days after planting (DAP), followed by sawdust and husk media in 16 DAP. Roots of dormant onion bulbs appeared between 7 to 14 DAP, and then shoots appeared in 14 to 16 DAP.
The Underlying Causes of Poverty Among Rice Farmers in Indonesia
Authors: Novira Nina , Pulungan Nur Ainun J , Maxriz Jian , Lubis Darwin P. , Pinem Mbina
Published: April 2022

Despite huge amount of support in the form of subsidy, infrastructure development such as irrigation system, and agricultural advisor, Indonesian rice farmers are still in general not doing so well. This raises the question of why could that be. Conservative views put education to the blame without further explanations. However, we argue that the problem is not just as simple as that. This paper therefore explores the underlying causes of rice farmers’ poverty in Indonesia with case studies from North Sumatera. Applying qualitative research using in-depth interview as the data collection tool, we seek to interview officials from the agricultural office as well as rice farmers and the head of farmer union in the case study areas. Results show that rice farmers, as of generally all farmers in Indonesia, do not possess adequate facility to process their commodity and to add value to it. They also do not have access to market with no control over the price. Thus they are merely rice growers, similar to labors in industry.
Field Crop Residue burning Induced Particulate Pollution in NW India – Policy Challenges & Way Forward
Authors: Kaushal Leena Ajit
Published: April 2022

The study aims to provide insights into the effectiveness of numerous policy interventions to curb FCRB-induced air pollution in NW India. The problem is addressed by examining the trend and co-existence of VIIRS retrieved thermal anomalies in NW states and PM2.5 concentrations in New Delhi during the two harvesting seasons (April-May & Oct-Nov) over the period 2014-2020. The findings reveal that various governmental measures that primarily revolve around sustainable residue management practices cannot holistically curb the stubble burning practice in NW India and the related air pollution in neighboring states. The study suggests that besides the short-term residue management measures, crop diversification or discontinuing dual rice-wheat cultivation is the only long term measure to regulate widespread stubble burning and the deteriorating air quality.
Image-based plasma morphology determination and LIBS spectra correction in combustion environments
Authors: CHAI Shu , PENG Haimeng , ZHAO Ziqing , WU Wendong
Published: April 2022

Spectra correction is essential for the quantification of laser-induced breakdown spectroscopy (LIBS) due to the uncertainties in plasma morphology. In this work, we determined the plasma morphology using a charge-coupled device camera and introduced the spectral correction method based on plasma images to a combustion environment. The plasma length, width, volume, and location were extracted from the plasma images. Using a back-scattering setup, the contribution of plasma location fluctuation to the total spectral fluctuation was mitigated. The integral intensity of the plasma image was used as a proxy of the total number density to correct the spectra. Linear relationships were established between the integral intensities of the plasma images and the spectral intensities, under different laser energy levels and gas temperatures. The image-based correction method could significantly reduce the fluctuation of raw spectral intensities when the laser energy was below 240 mJ. Compared with the correction method based on total spectral areas, the proposed method offered significant improvements in the low energy region, which promises to reduce the signal fluctuations in combustion environments while preserving the spatial resolution and mitigating the flow disturbance.
Distinct proteostasis states drive pharmacologic chaperone susceptibility for cystic fibrosis transmembrane conductance regulator misfolding mutants
Authors: McDonald Eli Fritz , Sabusap Carleen Mae P. , Kim Minsoo , Plate Lars
Published: April 2022

FDA-approved corrector drugs treat cystic fibrosis by stabilizing the mutated cystic fibrosis transmembrane conductance regulator (CFTR) protein, but responsiveness varies for mutations. By profiling CFTR protein interactions, we show that corrector VX-809 reduces interactions between highly responsive CFTR mutants and proteasomal degradation factors, uncovering their critical role in the mechanisms of VX-809.
Load adaptation by endocytic actin networks
Authors: Kaplan Charlotte , Kenny Sam J. , Chen Xuyan , Schöneberg Johannes , Sitarska Ewa , Diz-Muñoz Alba , Akamatsu Matthew , Xu Ke , Drubin David G.
Published: April 2022

Elevated load in endocytosis causes the actin network to increase its size and coverage around clathrin-coated pits in a manner conducive to additional force production. Hereby, the network grows from the base of the clathrin-coated pit.
Targeting the androgen receptor signaling pathway in advanced prostate cancer
Authors: Chung Clement , Abboud Karen
Published: April 2022

Purpose

This article summarizes current androgen receptor (AR)–directed therapies that have received regulatory approval for the treatment of advanced prostate adenocarcinoma (herein referred to as prostate cancer, PC).

PC is an androgen-dependent malignancy in which ligands including testosterone and dihydrotestosterone bind to AR, initiating androgen-AR complex translocation to the nucleus followed by AR-mediated transcription of target genes. Androgen deprivation therapy (ADT), including gonadotropin hormone–releasing hormone (GnRH) agonists with or without AR antagonists (antiandrogens), GnRH antagonists, or bilateral orchiectomy, forms the backbone of treatment for patients with metastatic castration-naive PC and/or castration-resistant PC (CRPC). ADT is also an option for high-risk, early-stage PC after prostatectomy and/or radiation. While ADT is often very effective as initial therapy, resistance ultimately develops despite suppression of gonadal and/or adrenal androgens, leading to CRPC, which is characterized by mechanisms such as reactivation of the AR signaling pathway, AR gene overexpression, and mutations in the ligand-binding domain of AR that lead to disease progression, resulting in increased symptom burden and ultimately death. However, disease in patients with CRPC is still dependent on androgen signaling, and these patients continue on ADT to maintain a castrate level of serum testosterone. Novel hormonal therapies including agents that target AR directly (eg, AR antagonists) are often added to ADT in this setting. Targeting the AR signaling pathway led to the development of second-generation AR antagonists, examples of which include enzalutamide, apalutamide, and darolutamide. These agents do not exhibit partial agonism, possess a higher affinity for AR, and are postulated to improve survival outcomes relative to their first-generation counterparts for patients with CRPC. Lastly, the emergence of ADT, including second-generation AR antagonists, has led to the development of supportive care for treatment-related adverse effects.

Conclusion

Major advances have been made in targeting the AR signaling pathway in patients with advanced PC. Further studies are warranted to identify the optimal sequencing of therapies to maximize treatment benefit. Mitigation of treatment-related adverse effects presents new opportunities to advance clinical pharmacy practice.
Maize dispersal patterns associated with different types of endosperm and migration of indigenous groups in lowland South America
Authors: Costa Flaviane Malaquias , Silva Natalia Carolina de Almeida , Vidal Rafael , Clement Charles Roland , Freitas Fabio de Oliveira , Alves-Pereira Alessandro , Petroli César Daniel , Zucchi Maria Imaculada , Veasey Elizabeth Ann
Published: April 2022

Background and Aims

The lowlands of South America appear to be remarkably important in the evolutionary history of maize, due to new evidence that suggests that maize dispersed from Mexico and arrived in this region in a state of partial domestication. This study aimed to identify dispersal patterns of maize genetic diversity in this part of the continent.

Methods

A total of 170 maize accessions were characterized with 4398 single nucleotide polymorphisms (SNPs) and analysed to determine if maize dispersal was associated with types of endosperm and indigenous language families.

Key Results

Four genetic groups were identified in the discriminant analysis of principal components and five groups in the cluster analysis (neighbour-joining method). The groups were structured according to the predominance of endosperm types (popcorn, floury, flint/semi-flint). Spatial principal component analysis of genetic variation suggests different dispersal patterns for each endosperm type and can be associated with hypotheses of expansions of different indigenous groups.

Conclusions

From a possible origin in Southwestern Amazonia, different maize dispersal routes emerged: (1) towards Northern Amazonia, which continued towards the Caatinga and south-eastern Atlantic Forest (Floury); (2) towards Southern Brazil, passing through the Cerrado and Southern Atlantic Forest reaching the Pampa region (Floury); and (3) along the Atlantic Coast, following Tupi movements originating from two separate expansions: one (Tupinamba) from north to south, and the other (Guarani) in the opposite direction, from south to north (flint, floury and popcorn).
Longitudinal assessment of network reorganizations and language recovery in postoperative patients with glioma
Authors: Yuan Binke , Zhang Nan , Gong Fangyuan , Wang Xindi , Yan Jing , Lu Junfeng , Wu Jinsong
Published: April 2022

For patients with glioma located in or adjacent to the linguistic eloquent cortex, awake surgery with an emphasis on the preservation of language function is preferred. However, the brain network basis of postoperative linguistic functional outcomes remains largely unknown. In this work, 34 patients with left cerebral gliomas who underwent awake surgery were assessed for language function and resting-state network properties before and after surgery. We found that there were 28 patients whose language function returned to at least 80% of the baseline scores within 3 months after surgery or to 85% within 6 months after surgery. For these patients, the spontaneous recovery of language function synchronized with changes within the language and cognitive control networks, but not with other networks. Specifically, compared with baseline values, language functions and global network properties were the worst within 1 month after surgery and gradually recovered within 6 months after surgery. The recovery of connections was tumour location dependent and was attributed to both ipsihemispheric and interhemispheric connections. In contrast, for six patients whose language function did not recover well, severe network disruptions were observed before surgery and persisted into the chronic phase. This study suggests the synchronization of functional network normalization and spontaneous language recovery in postoperative patients with glioma.
Psychological Characteristics of Leaders (PsyCL): A New Data Set
Authors: Schafer Mark , Lambert Joshua E
Published: April 2022

This article introduces the Psychological Characteristics of Leaders (PsyCL) data set. Foreign policy decisions are made by humans, and human psychology affects those decisions. While structural factors likely shape policy challenges and opportunities, excluding humans from our models is certain to miss important factors. Psychology has been excluded in the past in part because of the lack of data; PsyCL begins to address this problem. We discuss the importance of psychology in decision-making, describe the structure and scope of the data and its flexible units of analysis, present some simple empirical examples, and conclude with thoughts on future research.
Cas9-mediated maternal effect and derived resistance alleles in a gene-drive strain of the African malaria vector mosquito, Anopheles gambiae
Authors: Carballar-Lejarazú Rebeca , Tushar Taylor , Pham Thai Binh , James Anthony A
Published: April 2022

CRISPR/Cas9 technologies are important tools for the development of gene-drive systems to modify mosquito vector populations to control the transmission of pathogens that cause diseases such as malaria. However, one of the challenges for current Cas9-based drive systems is their ability to produce drive-resistant alleles resulting from insertions and deletions (indels) caused principally by nonhomologous end-joining following chromosome cleavage. Rapid increases in the frequency of such alleles may impair gene-drive dynamics. We explored the generation of indels in the germline and somatic cells in female gene-drive lineages using a series of selective crosses between a gene-drive line, AgNosCd-1, and wild-type mosquitoes. We find that potential drive-resistant mutant alleles are generated largely during embryonic development, most likely caused by deposition of the Cas9 endonuclease and guide RNAs in oocytes and resulting embryos by homozygous and hemizygous gene-drive mothers.
A risk-oriented evaluation of biofilm and other influencing factors on biological quality of drinking water for dairy cows
Authors: Hayer Jason J , Heinemann Céline , Schulze-Dieckhoff Benedikt G , Steinhoff-Wagner Julia
Published: April 2022

Despite the importance of livestock drinking water quality on animal physiology, welfare, and performance, influences such as biofilm formation on trough surfaces on microbial water quality are rarely researched. The objective of this study was to assess the microbial quality of water offered to lactating dairy cows and identify risk factors for poor water quality. We further aimed to determine the impact of biofilm formation on water quality and evaluate rapid test systems to score the hygiene status of dairy troughs on the farm. A total of 105 troughs located on 24 typical Western German dairy farms were sampled. Samples of livestock drinking water and biofilm were analyzed for aerobic total viable count (TVC), coliform count (CC), Escherichia coli, methicillin-resistant Staphylococcus aureus (MRSA), and other bacteria resistant to 3rd generation cephalosporins (CRB). Surface protein- and adenosine triphosphate (ATP)-rapid tests were evaluated to detect biofilm formation. The influence of 22 selected fixed and variable trough characteristics on impaired livestock drinking water quality was evaluated by calculating odds ratios. The average TVC, CC, and E. coli counts were 4.4 ± 0.06 (mean ± SD), 1.7 ± 0.1, and 0.6 ± 0.1 log10 cfu per mL, respectively. CC was detectable in 94.3% of all water samples and E. coli in 48.6%. MRSA was found in pooled livestock drinking water samples of a single farm and CRB on three farms, suggesting that troughs might function as a reservoir of antibiotic-resistant bacteria, thereby contributing to an exchange of antibiotic-resistant bacteria between animals. Risk factors for the impairment of at least one microbial quality criteria (TVC, CC, or E. coli) increased significantly (P < 0.05) when using high-volume troughs, other trough materials than stainless steel, a lower distance to the milking parlor, heavy visible soiling, biofilm formation, and high ambient and high water temperatures. CC (r = 0.46; P < 0.001) and E. coli (r = 0.31; P < 0.01) of water samples correlated with their equivalent in biofilm and with the results of rapid tests on trough surfaces (0.31 > r > 0.19; P < 0.05). Addressing the identified risk factors could be an approach to ensure sufficient biological quality of livestock drinking water.
HPLC–ESI–HRMS2 Determination ofN-(2-Hydroxyethyl)-l-valyl-l-leucine in Human Urine: Method Validation
Authors: Hanzlíková Iveta , Mráz Jaroslav , Tvrdíková Monika , Chrástecká Hana , Moulisová Alena , Linhart Igor
Published: April 2022

Biomonitoring of human exposure to reactive electrophilic chemicals such as ethylene oxide (EO) has been commonly based on the determination of adducts with N-terminal valine in blood protein globin, but a systematic search has also been undertaken to find surrogate markers enabling non-invasive sampling. Recently, N-(2-hydroxyethyl)-L-valyl-L-leucine (HEVL) has been identified as an ultimate cleavage product of EO-adducted globin in the urine of occupationally exposed workers. Herein, full validation of the analytical procedure consisting of solid-phase extraction of HEVL from urine samples (2 mL) followed by high-performance liquid chromatography–electrospray ionization–high-resolution mass spectrometry determination using deuterium-labeled HEVL as an internal standard (IS) is described. Method limit of quantitation is 0.25 ng/mL, and its selectivity is excellent as demonstrated by the invariable ratio of the qualifier and quantifier ion intensities across diverse urine samples and synthetic standard. The linear calibration model was applicable over the whole concentration range tested (0.25–10 ng/mL). The method accuracy assessed as a recovery of HEVL using a spiking experiment was 98–100%. Within-day precision of the method ranged from 1.8% to 3.0%, while the results from consecutive analytical runs conducted within 1 week or within 10–150 weeks differed in the range of 2.2–9.7%. The stability study on urine samples (−20°C up to 3 years, freeze-and-thaw up to 10 cycles) as well as on aqueous solutions (5°C up to 4 months) indicated no relevant changes in HEVL concentration (≤4%) over the time tested. Analytical responses of both HEVL and IS correlated with urinary creatinine as an index of matrix composition, but this matrix effect was mostly eliminated using the HEVL/IS peak area ratio, attaining the IS-normalized relative matrix effect <3%. In conclusion, the method complied successfully with the bioanalytical method validation criteria, making it a reliable tool for HEVL determination in human biomonitoring.
Wage Flexibility under Sectoral Bargaining
Authors: Card David , Cardoso Ana Rute
Published: April 2022

Sectoral contracts in many European countries set wage floors for different occupation groups. In addition, employers often pay a wage premium (or wage cushion) to individual workers. We use administrative data from Portugal, linked to collective bargaining agreements, to study the interactions between wage floors and wage cushions and quantify the impact of sectoral wage floors. Although wages exhibit a “spike” at the wage floor, a typical worker receives a 20% premium over the floor, with larger cushions for older- and better-educated workers and at higher-productivity firms. Cushions also allow wages to covary with firm-specific productivity, even within sectoral agreements. Contract negotiations tend to raise all wage floors proportionally, with increases that reflect average productivity growth among covered firms. As floors rise, however, cushions are compressed, leading to an average passthrough rate of about 50%. Finally, we use a series of counterfactual simulations to show that real wage reductions during the recent financial crisis arose through reductions in real wage floors, reductions in real cushions, and a re-allocation of workers to lower wage floors. Offsetting these effects was a rapid rise in education of new cohorts, which in the absence of other factors would have led to rising real wages.
First Detection of the Invasive Mosquito Vector Aedes albopictus (Diptera: Culicidae) in Benin, West Africa, 2021
Authors: Yadouleton Anges , Hounkanrin Gildas , Tchibozo Carine , Bialonski Alexandra , Schmidt-Chanasit Jonas , Jöst Hanna
Published: April 2022

Aedes albopictus (Skuse) is native to Southeast Asia and has colonized tropical and temperate regions worldwide in the last three to four decades. In Africa, data on its distribution is incomplete. Most studies having focused on the abundance, competition to other species, and phylogenetics of this vector are from the central African region. Here, we report the first detection of Ae. albopictus in Benin, West Africa. A total of 13 specimens were collected during the study period in 2021. The phylogenetic analysis of a cytochrome oxidase c subunit I gene fragment revealed a close relationship to populations from tropical India. Because of its close geographical proximity to areas where it has been found, it is assumed that the species was introduced several years before and is currently widely distributed in Benin. Additional studies are needed to explore its distribution, expansion range, and competitive effects on native species.