bluuebunny/crossref_metadata_2025 huggingface dataset:
According the data analyse to study of the Frost Resistance of Corrugated Metal Pipe Culverts in Permafrost Regions
Authors: Wang Xu , Yu Tianlai
Published: February 2023

In this paper, we mainly studied the stress variation law of corrugated pipe culvert in permafrost regions under the influence of external load and temperature field, and formulated the corresponding experimental arrangement and observation scheme, in order to reveal the mechanical characteristics and action mechanism of corrugated metal pipe culverts.At the same time, we studied the law of the upper limit variation of permafrost foundation under corrugated pipe culvert, established the finite element model of corrugated pipe culverts, and for which we conducted mechanical analysis, frost heave analysis, and solution(thawing) settlement analysis; measured the variation of earth pressure and temperature field around pipe wall during and after filling soil.
Research on the generalization of resident load Identification based on Hybrid Branch Network
Authors: Tan Zhukui , Xu Yutao , Xiao Xiaobing , Zhang Qiuyan , Liu Bin
Published: February 2023

Household energy consumption has become an important part of energy consumption, and improving its utilization plays an important role in solving the global energy crisis. As an effective means, load identification technology promotes energy saving on the user side by providing detailed power consumption information. In this paper, aiming at the generalization of power supply voltage fluctuation in load identification, electrical appliances are classified into four categories: time-varying load, linear load, constant power load, and other nonlinear loads. A load identification model with many kinds of neural network branches is proposed. According to the characteristic differences of different types of loads, different branches are selected for different types of electrical appliances for identification. Finally, compared with the recognition accuracy of other common models in different environments, it is concluded that the method in this paper has higher recognition ability and generalization ability.
Big Data Analysis on Complex Network—with the example of smart city
Authors: Cong Wang , Yang Lin
Published: February 2023

The network of smart cities is a typical complex network with big data in the theoretical level and practical level. How can we analysis the smart cities better under the complexity and uncertainty. It is a question. We try to give a new framework to this question, providing a chance to make the smart city smarter.
Neural Networks with the Correlative Layer for Multi-label Classification
Authors: Liang Lixin , Li Ning , Li Yihong , Lin Lin
Published: February 2023

Multi-label classification is a very significant but challenging task. Correlation between labels often exists, so recent works have paid much attention to using the correlation between labels to improve the classification performance. However, how to effectively learn the correlation is still a problem. In this paper, a general framework, i.e., the neural network with the correlative layer (CLNN), is proposed, where the correlative layer is used to express the dependencies between labels. Different from existing work, CLNN first trains a neural network without the correlative layer to obtain rough classification results and then trains the whole neural network to adaptively adjust all the weights including those of the correlation layer. Thus CLNN could learn both positive/negative and strong/weak relationships between labels. We test CLNN with three typical neural networks, and experimental results show that neural network can achieve better performance by adding the correlative layer, which demonstrates that the CLNN framework is very effective.
Statistical Learning Based Wireless Channel Parameter Estimation for Power Internet of Things
Authors: Tan Chong , Chen Jinshan , Sun Xin , Qi Qi
Published: February 2023

With the rapid increase in the number of sensors in Power Internet of Things (PIOT), the data volume surges and efficient communications are needed. Precise estimation of delay spread is critical to improve the communication performance. In this paper, we propose a statistical learning (SL) based root mean square delay spread (RMSDS) estimation method, which consists of offline training and online estimation. During the offline training process, the instantaneous delay spread (IDS) for each data frame is firstly computed based on the known pilots. The acquired IDS is a random variable and its statistical parameter is related to the actual RMSDS, which is preset and known during offline training. Then, the functional relationship between the statistical parameter and the preset RMSDS is acquired through the SL algorithm. The acquired functional relationship can be used in the online estimation process to accurately estimate the RMSDS. Simulation results indicate that the proposed method can accurately estimate the RMSDS and greatly improve the bit error rate performance.
Research on Intelligent Elevator Based on ZigBee
Authors: Wang Lei
Published: February 2023

With the rapid increase of the number of elevators, the safety of elevators has attracted more and more attention of the public. How to improve the safety of elevators and how to reduce the occurrence of elevator failures has become the focus of attention of all parties.With the development of science and technology and the continuous improvement of the intelligent degree of elevator, intelligent elevator comes into being.This paper proposes a ZigBee-based intelligent elevator and its management method, aiming to help the elevator supervision department, user unit, maintenance unit, insurance company, ect., establish a new elevator use management mode, and reduce the occurrence of accidents such as elevator failure.
Application of terahertz spectroscopy in medical microbiological detection
Authors: Ruan Xiaohu , Ruan Xiaofu , Huang Hai
Published: February 2023

In recent years, pathogenic bacteria and other microorganisms are still a very important aspect of human health. Nowadays, with the rapid development of information science, it has become a new research idea to explore scientific problems from the perspective of interdisciplinary integration. The research on the biomedical application of Terahertz (THz) wave is a hot frontier of the intersection between physical optics and bio-medicine. Based on the background of terahertz spectrum application, this paper introduces the application and progress of terahertz technology in medical microorganism detection, analyzes the characteristics of terahertz and the application technology in medical microorganism detection. Secondly, it tries to comprehensively summarize the application research results of terahertz technology in the field of microbial bio-medicine. Finally, it analyzes and prospects the shortcomings and advantages of the application of terahertz technology in the field of biomedical science.
A time-space coding metasurface and potential applications
Authors: Zhang Zhongzheng , Li Hongwei , Noman Khandaker , Li Yongbo
Published: February 2023

Compared with the deepening development of time-space coding metasurfaces in the electromagnetic and acoustic field, the research on time-space coding metasurface in the field of elastic vibration is still in the infancy. In order to enrich the designed schemes of spatiotemporal coding for elastic vibration, a time-space coding metasurface based on the random modulation strategy of wavefront phase is proposed in this paper. Compared with traditional homogeneous materials with highly correlated vibration transmission, the proposed coding metasurfaces with homogeneous materials realizes extremely low correlated vibration transmission in different vibration directions, which provides a physical realization for the measurement matrix in compression sensing. Furthermore, combined with compressed sensing technology, the potential application value of the proposed time-space coding metasurfaces in single-sensor vibration location and impact identification is verified through simulation.
Research and application of deep learning in image recognition
Authors: Zhao Xingzhi
Published: February 2023

In recent years, deep learning technology has been one of the most important representatives of progress in the field of artificial intelligence technology in China. It has made great achievements in many fields, such as language recognition, natural language processing, image processing and video analysis. This paper further discusses the application research and practice of deep learning technology in modern digital image recognition. Deep learning technology has played a more and more important role in modern digital image recognition.
Research on PMSM control system based on high order sliding mode method
Authors: Wang Zhicheng , Li Zhiyuan
Published: February 2023

A high-order sliding mode viewer using the stator current and rotor magnetic chain as state quantities is designed and implemented, which is based on the fourth-order state equation and can directly output the observed values of the rotor magnetic chain. To avoid the phase change of the magnetic chain due to the introduction of a low-pass filter, a vector equation of state filtering method is proposed to filter the dither signal through the magnetic chain equation by taking the observed deviation of the current as the sliding mode surface and inputting the equivalent control signal directly into the magnetic chain equation. Simulation results show that the designed extended sliding mode observer is able to accurately estimate the rotor position and speed at lower speeds without accurate compensation of the observed values for rotor information collection present in the counter potential and the rotor magnetic chain. The sensorless vector control system is characterized by robustness, wide speed range, and higher feasibility and effectiveness.
Research on non-time-series data filling methods based on feature evaluation
Authors: Yang Fengyu , Fan Yongjian , Xie Lingze , Zhong Yihui
Published: February 2023

With the rapid development of the information age, a large amount of data is used in popular research areas such as data mining. Missing data has a very serious impact on both the process and the result of data mining, and it is important to find out how to fill the missing values accurately and efficiently. In this paper, we propose a method to optimally fill the missing values based on the backpropagation of evaluation functions for non-time-series data. Based on both the target value error and its own error after filling, four classical filling methods, namely mean, interpolation, model prediction, and K-nearest neighbor, are considered for selection. Finally, single-model padding and multi-model weighted padding schemes are compared, and the results show that the padding method with the highest fitness value is selected to work best for data with different degrees of missingness in different datasets.
3D Laser Scanning Acquisition and Modeling of Tunnel Engineering Point Cloud Data
Authors: Shi Fangzhe , Yang Jingxin , Li Qiuyi , He Junjie , Chen Boning
Published: February 2023

For tunnel deformation analysis using traditional measurement methods to obtain tunnel section data, there are problems such as small data coverage and low efficiency. 3D laser scanning technology has the advantages of automatic, high precision and high efficiency in collecting the point cloud data of the target object, and can completely and accurately express the target entity. Based on the tunnel point cloud acquired by 3D laser scanner, the tunnel engineering modeling research is carried out in this paper. Firstly, the engineering survey and 3D reconstruction technology of shield tunnel were carried out based on 3D laser scanning technology. The total station layout control was used to scan the subway platform and tunnel interval, and the high-precision laser point cloud data were obtained. Secondly, a random sampling consistency algorithm is proposed to extract engineering measurement results such as tunnel axis and cross section. Finally, the 3D modeling of the tunnel is established by using the stretching setting out modeling method. Taking Yuzhu Tunnel planning and acceptance project as an example, the experimental results show that the method can effectively visualize the overall deformation of the tunnel, and provide accurate and scientific spatial data for tunnel engineering measurement, operation and maintenance.
Research on the Development and Application of Acoustic Testing Technology
Authors: Liu Feng
Published: February 2023

Taking the commonly used acoustic detection technology as the research object, the working principle of different types of acoustic detection technology and the application of adverse geological forecasting and nondestructive testing in the geotechnical field are described, and the advantages and disadvantages of different types of acoustic detection technology are pointed out through the discussion of the development of acoustic detection technology.
Research on Multi-axis Synchronous Test Technology based on GLINK Bus
Authors: Yu Zikou , Shen Li , Liang Yuchen , Guo Yunqi , Li Zhanye , Zhang Xian , Kang Ping
Published: February 2023

As a rocket engine for thrust vector control system of high reliability and redundancy, high precision, and the requirements of lightweight, servo system for test system can quickly test a certain level and fast data processing of the test location, transient, and frequency characteristic indexes, a rocket motor thrust vector control system using GLINK as control bus. Moreover, the first level servo is an all-in-one machine with four drives and controls, so the test system is required to have the ability to control and test four actuators simultaneously under the GLINK main line. This paper discusses the hardware knowledge of the test system based on the GLINK bus: GLINK bus technology, communication topology of GLINK station card and network card; software function of the test system; multi-axis synchronous test function, and synchronous data processing function developed by LabVIEW.
Ultra-short-term PV prediction based on LSTM with a multi-head attention mechanism
Authors: Zhu Xiaoming , Wang Liang , Gu Jiaru , Wang Peng , Tang Jigang , Hao Jinbao , Xiang Min , Lu Yangwen , Lu Xincheng
Published: February 2023

With the increasing penetration and installation of renewable energy such as photovoltaic (PV) generation, ultra-short-term PV output prediction is necessary to guarantee the stability of the power system. However, the traditional methods cannot capture the important features of PV power data, and prediction accuracy cannot be guaranteed. Focusing on these problems, this paper presents a novel PV prediction method based on LSTM with a multi-head attention mechanism. The mechanism can make the matrix operation run in parallel. At the same time, the model assigns weight to different features of the input data to improve the prediction. To show the effectiveness, this paper constructs four scale types for PV power prediction. Case studies show that the multi-head attention mechanism can improve the prediction performance, and the prediction accuracy decreases following the increase of time scale.
Analysis of Impurities in Sulfur Hexafluoride Gas via Gas Chromatography Based on Enhanced Plasma Detector
Authors: Luo Zongchang , Zhang Longfei , Tang Bin , Liang Qinqin , Pan Jiqi , Hu Mengzhu
Published: February 2023

An analytical method for detecting impurities in high-purity sulfur hexafluoride (SF6) gas is established by using gas chromatography (GC) based on the enhanced plasma detector (EPD). The concentration of impurities (hydrogen, oxygen, nitrogen, methane, carbon monoxide, carbon dioxide, carbon tetrafluoride, hexafluoroethane, and octafluoropropane) can be quantitatively detected through one-time sampling and external standard method, and the minimum detection limit of each component is calculated to be about 0.1ppm, the RSD of the test results is less than 3%. This method can meet the requirements of detecting the purity of SF6 gas used in electrical equipment.
Research on the Automatic Control System of Coolant Circulation in Laboratory
Authors: Li Xin , Tian Xiaodi , Zhai Guifei , Liu Jixu
Published: February 2023

This paper introduces a design method of an automatic control system for coolant circulation in the laboratory, which can use a “pneumatic pump + valve control” manual in place of “manual pressing + manual liquid filling + manual collection”. Then this paper analyzes the system principle and has carried out the application in a practical laboratory, which had solved the problems of low efficiency, environmental pollution, and waste of resources of the existing manual operation mode.
Target Recognition Network Based on Improved Convolutional Regression Network
Authors: Zhang Shuang , Song Jinyu , Li Weiwei
Published: February 2023

For refine the regression precision and speed of convolutional neural recognition network, propose improved detection and identification algorithm on the basis of deep learning algorithms, mainly aiming at improving the accuracy and speed of regression prediction of target recognition. Firstly, the acquired images are preprocessed in batches to obtain image datasets with different sizes of detection objects, that is, the enhancement of small sample images. Secondly, the one-stage target detection network SSD algorithm is improved. ResNet50 network is used to extract features, while FPN is fused with the main algorithm to ameliorate the detection network, which purpose is to improve the target detection accuracy. The test results on remote sensing datasets show that the actual accuracy was elevated to about 0.9% compared to the conventional algorithm. The speed in the actual measurement is also increased by 0.6 frame/s.
Baihetan - Jiangsu engineering soil and water conservation online monitoring data system
Authors: Lei Lei , Song Ji Ming , Wang Jin , Hai Zheng Shu , Yi Li Feng , Wan Hao
Published: February 2023

Baihetan - Jiangsu ± 800kV UHVDC project can improve the power supply stability of the hydropower station, which has very important economic significance. The construction of power transmission projects will affect the water and soil conservation situation along the site. Currently, the commonly used monitoring methods are based on manual data collection with low accuracy and a large workload. Therefore, the government vigorously promotes the development of intelligent water conservancy and strives to improve the digitalization degree of water and soil monitoring systems. In this paper, the traditional chain pin method was improved, using the photosensitive chain pin and ultrasonic chain pin instead of the ordinary chain pin. Then calculated the soil erosion modulus by collecting the soil loss index of the measured point, and uploading it to the cloud for analysis by the radio transmission device, so that the monitor system obtained accurate soil loss data. Finally, the system is applied to the baihetan-Jiangsu soil and water conservation monitoring project, and the monitoring data of soil and water conservation of the two stations are obtained. Combined with the local meteorological conditions, we can analyze the causes of soil and water loss, and give the corresponding prevention measures.
Design of Multi-sensor Fusion Positioning and Navigation Method Based on Federated Kalman Filter for Low-Speed Rotorcraft of Atmospheric Detection
Authors: Yu Binggang , Chen Lei , Fatin Fatihur Rahman Mohammad
Published: February 2023

A rotorcraft needs to accurately sample the predetermined path at a low flight rate when performing atmospheric sounding tasks; thus, it is particularly critical to obtain accurate positioning and navigation information in real-time. Hence, this paper designs a multi-sensor fusion positioning and navigation algorithm for atmospheric detection of low-speed rotorcraft. The multi-sensor fusion positioning and navigation algorithm for velocity and spatial position are presented based on the Federated Kalman Filter combined with the accelerometer, Global Positioning System (GPS), and barometer. The experimental results show that the fusion algorithm result of the velocity and spatial position is closer to the actual position than a single sensor. In conclusion, this paper’s multi-sensor fusion positioning and navigation algorithm overcomes the problems of low positioning accuracy of a single sensor and cumulative errors and effectively improves positioning accuracy, real-time, and stability.
Research on Tip Clearance Measurement Technology of Aero-engine Blade Based on Optical Fiber Sensing System
Authors: Ma Huiping , Wang Xiaoming , Zhang Xiaoguang , Liu Yongmeng
Published: February 2023

A novel non-contact detecting method of aero-engine blade tip clearance based on an optical fiber sensing system is presented. To eliminate the sensor measurement error caused by the slight change of the reflectivity value of the mechanical end face when the light source angle fluctuates and rotates, a three-coil coaxial fiber bundle sensor is proposed. Relevant experimental results show that the system has the advantages of high measurement sensitivity, small sensing probe volume, strong electromagnetic interference resistance, and high reliability. The application of this technology provides an effective method for dynamic radial gap detection of high-speed rotating machinery.
Study on Measurement Method of β Radioactivity in Environmental Water by Liquid Scintillation Spectrometers
Authors: Qi Yelin , Lai Yongfang , Zhang Xuan , Huang Weiqi
Published: February 2023

Compared with other methods for measuring radioactivity in water, liquid scintillation measurement has the outstanding advantages of fast sample pretreatment, simple measurement method and high detection efficiency. Based on liquid scintillation spectrometer (SIM-MAX LSA3000B), 14C and 90Sr-90Y are selected as typical nuclides to study the change of TDCR quenching correction curve under different activity concentrations, and the basic method for measuring radioactive water samples with different activity concentrations is proposed, which is applied to the measurement of lake water, mountain spring water, tap water, mineral water and rainwater. The measurement results show that the total time of this method is less than 60 minutes, and the measurement error is less than 20%, which is obviously superior to the existing water sample radioactivity measurement method under nuclear emergency conditions.
Research on Time Synchronization and Spatial Calibration Algorithms of Radar and Camera
Authors: Song Shiping , Dong Changqing , Qin Kongjian , Hou Xintian , Zhao Xiong , Tian Xiaodi , Wang HuaSen
Published: February 2023

The intelligent connected vehicle can detect 360° full coverage around the vehicle by installing multiple radars and cameras. However, the sampling frequency of each sensor is different and each sensor outputs the target motion state information based on its coordinate system. the accurate and rapid realization of time synchronization and spatial position alignment between sensors is very important for multi-sensor data fusion. This paper presents a method of radar and camera time synchronization based on least squares cubic spline curve fitting. Based on time synchronization, a fast space joint calibration method of radar and camera is proposed based on the longitudinal symmetry plane of the vehicle. The validation data of the target object show that the proposed algorithm is accurate and simple.
The effectiveness of different machine learning algorithms in classifying pulsar stars and the impact of data preparation
Authors: Rong Song Jin
Published: February 2023

With massive improvements in technology, astronomers have been uncovering impressive findings of the mysteries of the universe. At the same time, new technology is able to do more and more of the tasks usually given to people, especially when it comes to handling big pieces of data. As such, more jobs are being replaced by machines in the modern industrial age, which may very well include the jobs of astronomers. To investigate the potential of machine learning in astronomy and its effect on the livelihoods of astronomers, this paper aims to demonstrate the capabilities of machine learning algorithms in completing tasks usually done by astronomers, which in this case the identifying pulsar stars. Astronomers study these stars extensively to learn about extreme states of matter and explore different solar systems. This paper introduces various classification algorithms to perform the task of identifying pulsar stars from data of radio wave emissions in the universe. Two distinct methods of dealing with missing values were also used. Once the algorithms were applied to the dataset, the results were recorded and analyzed, mainly focusing on the accuracy of each model. From the results, all the models yielded accuracies above 90%. In addition, the models performed better on average with data preparation using the drop method compared to the average value method. These results provide extensive evidence that machine learning can perform certain tasks commonly performed by astronomers themselves. At the moment they cannot replace astronomers, but in the future, it has a possibility.
Spectrometer for ultrashort X-ray based on scintillator and optical fiber: proof of principle study
Authors: Song Honghu , Qiu Rui , Yi Hongchang , Zuo Qi , Liu Yining , Wu Zhen , Li Junli
Published: February 2023

An active filter stack spectrometer based on the scintillator and optical fiber is proposed and characterized for measuring the ultrashort X-ray spectrum. The active filter stack spectrometer consists of multiple detection modules, each of which has three components: a scintillator, an optical fiber, and a PMT. After simulation optimization of the detection module for better coupling efficiency, a detection module was fabricated and assembled for subsequent coupling efficiency measurements. Two proof-of-principle experiments using an X-ray source were conducted to validate the feasibility of this active filter stack spectrometer.
Design of a megawatt superradiant terahertz source for FELiChEM
Authors: Xia M. , Yang N. , Xu Y. , Zhao Z. , Li H.
Published: February 2023

FELiChEM is an infrared free electron laser user facility
built at the University of Science and Technology of China
(USTC). It consists of two free electron laser oscillators which
produce mid-infrared and far-infrared lasers covering the spectral
range of 2–200 μm at current stage. In this paper, we
propose a new operation mode of a megawatt (MW) terahertz (THz)
superradiance free electron laser (FEL) for FELiChEM. Start-to-end
(S2E) simulations have been carried out, in which the
three-dimension particle-in-cell (PIC) code PUFFIN is used for the
generation of the THz superradiance. Simulation results demonstrate
that this superradiant FEL can provide 100–1000 μm laser
with MW-class peak power from a 1.2 meter single-pass undulator when
the electron energy is around 15 MeV.
A new method to improve homogeneity and oxidation stability of Cu nanoparticles for lubricant additive in liquid phase reduction process
Authors: Kim Song Chol , Ri Yun Sik , Ju Dae Gun
Published: February 2023

In the preparation of Cu nanoparticles by liquid phase reduction, the traditional reagent mixing mode was changed to improve the homogeneity in Cu nanoparticle size. In addition, Cu nanoparticles were collected by adding the volatile organic solvent (benzine) to the reaction system to prevent the oxidation of them. XRD and SEM analysis confirmed that the reaction products were spherical Cu particles with relatively uniform size of 30–50 nm. EDS analysis showed that the oxygen content in the product was 36.2% for using a centrifuge and 12.6% for using benzine, indicating that the oxidation of Cu nanoparticles was relatively prevented in the preparation process. The lubricant containing Cu nanoparticles of 0.15 wt% exhibited decreased friction coefficient by 60% compared the pure lubricant. Moreover, the decreasing tendency of friction coefficient of the Cu nanoparticles prepared by the proposed method was more stable than that of Cu nanoparticles prepared by the common liquid phase reduction process.
Blow up limits of the fractional Laplacian and their applications to the fractional Nirenberg problem
Authors: Du Xusheng , Jin Tianling , Xiong Jingang , Yang Hui
Published: February 2023

We show a convergence result of the fractional Laplacian for sequences of nonnegative functions without uniform boundedness near infinity. As an application, we construct a sequence of solutions to the fractional Nirenberg problem that blows up in the region where the prescribed functions are negative. This is a different phenomenon from the classical Nirenberg problem.
A Hilbert irreducibility theorem for Enriques surfaces
Authors: Gvirtz-Chen Damián , Mezzedimi Giacomo
Published: February 2023

We define the over-exceptional lattice of a minimal algebraic surface of Kodaira dimension

0
0

. Bounding the rank of this object, we prove that a conjecture by Campana [Ann. Inst. Fourier (Grenoble) 54 (2004), pp. 499–630] and Corvaja–Zannier [Math. Z. 286 (2017), pp. 579–602] holds for Enriques surfaces, as well as K3 surfaces of Picard rank

≥
6

\geq 6

apart from a finite list of geometric Picard lattices.

Concretely, we prove that such surfaces over finitely generated fields of characteristic

0
0

satisfy the weak Hilbert Property after a finite field extension of the base field. The degree of the field extension can be uniformly bounded.
ALKGene Mutation and ALK Protein Expression in Advanced Neuroblastoma and the Potential Value in Risk Stratification in Fine-Needle Aspiration Biopsy Samples
Authors: Bhardwaj Neha , Rohilla Manish , Gautam Upasana , Trehan Amita , Bansal Deepak , Kakkar Nandita , Srinivasan Radhika
Published: February 2023

Objectives

The protein ALK is targeted for therapy in neuroblastoma, and ALK mutation confers a poor prognosis. We evaluated ALK in a cohort of patients with advanced neuroblastoma diagnosed by fine-needle aspiration biopsy (FNAB).

Methods

Fifty-four cases of neuroblastoma were evaluated for ALK protein expression by immunocytochemistry and ALK gene mutation by next-generation sequencing. MYCN amplification by fluorescence in situ hybridization, International Neuroblastoma Risk Group (INRG) staging, and risk assignment was performed, and patients were managed accordingly. All parameters were correlated with overall survival (OS).

Results

ALK protein showed cytoplasmic expression in 65% cases and did not correlate with MYCN amplification (P = .35), INRG groups (P = .52), and OS (P = .2); however, ALK-positive, poorly differentiated neuroblastoma showed better prognosis (P = .02). ALK negativity was associated with poor outcome by Cox proportional hazard model (hazard ratio, 2.36). Two patients showed ALK gene F1174L mutation with 8% and 54% allele frequency and high ALK protein expression; they died of disease 1 and 17 months following diagnosis, respectively. A novel IDH1 exon 4 mutation was also detected.

Conclusions

ALK expression is a promising prognostic and predictive marker in advanced neuroblastoma that can be evaluated in cell blocks from FNAB samples along with traditional prognostic parameters. ALK gene mutation confers a poor prognosis for patients with this disease.
Guselkumab for hidradenitis suppurativa: a phase II, open-label, mode-of-action study
Authors: Dudink Koen , Bouwman Klasiena , Chen Yanqing , DePrimo Samuel E , Munoz-Elias Ernesto J , Aarts Pim , Schappin Renske , Florencia Edwin F , van Heeswijk Bennie , Prens Lisette M , van der Zee Hessel H , Prens Errol P , van Straalen Kelsey R , Horváth Barbara
Published: February 2023

Background

The effectiveness of available biologics for the treatment of hidradenitis suppurativa (HS) is limited. Additional therapeutic options are needed.

Objectives

To investigate the efficacy and mode of action of guselkumab [an anti-interleukin (IL)-23p19 monoclonal antibody] 200 mg subcutaneously every 4 weeks for 16 weeks in patients with HS.

Methods

An open-label, multicentre, phase IIa trial in patients with moderate-to-severe HS was carried out (NCT04061395). The pharmacodynamic response in skin and blood was measured after 16 weeks of treatment. Clinical efficacy was assessed using the Hidradenitis Suppurativa Clinical Response (HiSCR), the International Hidradenitis Suppurativa Severity Score System (IHS4), and the abscess and inflammatory nodule (AN) count. The protocol was reviewed and approved by the local institutional review board (METC 2018/694), and the study was conducted in accordance with good clinical practice guidelines and applicable regulatory requirements.

Results

Thirteen of 20 patients (65%) achieved HiSCR with a statistically significant decrease in median IHS4 score (from 8.5 to 5.0; P = 0.002) and median AN count (from 6.5 to 4.0; P = 0.002). The overall patient-reported outcomes did not show a similar trend. One serious adverse event, likely to be unrelated to guselkumab treatment, was observed. In lesional skin, transcriptomic analysis revealed the upregulation of various genes associated with inflammation, including immunoglobulins, S100, matrix metalloproteinases, keratin, B-cell and complement genes, which decreased in clinical responders after treatment. Immunohistochemistry revealed a marked decrease in inflammatory markers in clinical responders at week 16.

Conclusions

Sixty-five per cent of patients with moderate-to-severe HS achieved HiSCR after 16 weeks of treatment with guselkumab. We could not demonstrate a consistent correlation between gene and protein expression and clinical responses. The main limitations of this study were the small sample size and absence of a placebo arm. The large placebo-controlled phase IIb NOVA trial for guselkumab in patients with HS reported a lower HiSCR response of 45.0–50.8% in the treatment group and 38.7% in the placebo group. Guselkumab seems only to be of benefit in a subgroup of patients with HS, indicating that the IL-23/T helper 17 axis is not central to the pathophysiology of HS.
Meta-analysis reveals between-population differences affect the link between glucocorticoids and population health
Authors: Newediuk Levi , Bath Devon R
Published: February 2023

Glucocorticoids are a popular tool for monitoring health of animal populations because they can increase with environmental stressors and can indicate chronic stress. However, individual responses to stressors create variation in the glucocorticoid–fitness relationship within populations. The inconsistency in this relationship calls into question the widespread use of glucocorticoids in conservation. We investigated the sources of variation in the glucocorticoid–fitness relationship by conducting a meta-analysis across a diverse set of species exposed to conservation-relevant stressors. We first quantified the extent to which studies inferred population health from glucocorticoids without first validating the glucocorticoid–fitness relationship in their own populations. We also tested whether population-level information like life history stage, sex and species longevity influenced the relationship between glucocorticoids and fitness. Finally, we tested for a universally consistent relationship between glucocorticoids and fitness across studies. We found more than half of peer-reviewed studies published between 2008 and 2022 inferred population health solely based on glucocorticoid levels. While life history stage explained some variation in the relationship between glucocorticoids and fitness, we found no consistent relationship between them. Much of the variation in the relationship could be the result of idiosyncratic characteristics of declining populations, such as unstable demographic structure, that coincided with large amounts of variation in glucocorticoid production. We suggest that conservation biologists capitalize on this variation in glucocorticoid production by declining populations by using the variance in glucocorticoid production as an early warning for declines in population health.
Clean Energy Access: Gender Disparity, Health and Labour Supply
Authors: Verma Anjali P , Imelda
Published: February 2023

Women bear a disproportionate share of the health and time burden associated with lack of access to modern energy. We study the impact of clean energy access on adult health and labour supply outcomes by exploiting a nationwide rollout of a clean cooking fuel program in Indonesia. We find that access to clean cooking fuel led to an improvement in women’s health and an increase in their work hours. We also find an increase in men’s work hours and in their propensity to have an additional job, primarily in those households where women accrued the largest program benefits.
Elevated Serum Neurofilament Light Chain Levels Are Associated With All-Cause Mortality: Evidence From National Health and Nutrition Examination Survey
Authors: Chen Xiaotong , Lin Yong , Wei Kai
Published: February 2023

Background

Several studies have reported the association between blood neurofilament light chain (NfL) levels and all-cause mortality. However, the generalizability of these findings in general adults remains unclear. The study aimed to examine the association between serum NfL and all-cause mortality in a nationally representative population.

Methods

Longitudinal data were obtained from 2 071 participants aged 20–75 years in the National Health and Nutrition Examination Survey 2013–14 cycle. Serum NfL levels were measured by using a novel, high-throughput acridinium-ester immunoassay. Kaplan–Meier curves, multivariate Cox regression analysis, and restricted cubic spline regression were employed to investigate the association between serum NfL and all-cause mortality.

Results

Over a median follow-up of 73 (interquartile range = 12) months, 85 (3.50%) participants died. After adjustment for sociodemographic characteristics, lifestyle variables, comorbidity, body mass index, and estimated glomerular filtration rate, elevated serum NfL levels were still significantly associated with a higher risk of all-cause mortality (hazard ratio = 2.45, 95% confidence interval = 1.89–3.18 for per lnNfL increase) in a linear manner.

Conclusions

Our findings suggest that circulating levels of NfL may serve as a biomarker of mortality risk in a nationally representative population.
Assessment of Inflammatory Bowel Disease Training Among Gastroenterology Fellows
Authors: Al-Bawardy Badr , Malter Lisa , Ehrlich Adam C , Rieder Florian , Gaidos Jill K J , Proctor Deborah , Windish Donna M
Published: February 2023

Lay Summary

In this multicenter survey study, we found that many gastroenterology fellows lacked confidence and desired a “moderate to a lot more” training in important inflammatory bowel disease management domains.
How COVID-19 Changed Self-Presentation on Instagram and its Relation to User Well-Being
Authors: Turner Mark , Ordonia Danna
Published: February 2023

Social media use increased during the COVID-19 pandemic with platforms providing an important forum for communication and self-expression. In this study, we explore shifts in online posting behaviors and self-presentation following the onset of lockdown. Content analysis of active Instagram accounts (n = 73) was conducted for the 3-month period before and immediately following the start of lockdown in the UK, and compared to psychological well-being, social media dependency and motives for online self-presentation during lockdown. Changes in the nature of images and captions used by profile owners were found following the start of lockdown, with more selfies and throwback photographs of past events being posted. Images in contexts depicting users as ‘social’, and positive or explanatory message captioning decreased during lockdown. Limited evidence was found to support the hypothesis that images posted were predictive of psychological well-being in lockdown. More followers and the degree to which online portrayals represented ‘real-self’ appeared more critical to well-being during lockdown.
The Clinical Utility of MRSA Nasal Surveillance Swabs in Ruling-Out MRSA Infections in Children
Authors: Diseroad Emily R , Tamma Pranita D , Same Rebecca G , Hsu Alice J
Published: February 2023

The utility of methicillin-resistant Staphylococcus aureus (MRSA) nasal surveillance swabs has not been well-described in children. This retrospective, cohort study yielded a negative predictive value of 99.4% for an initial negative MRSA nasal surveillance swab in 165 hospitalized children with a suspected infection and clinical cultures obtained from a likely site of infection.
Diagnostic nightmare: intra-intestinal bleed masks intra-abdominal bleed after colonoscopy
Authors: Jackson Hillary M , Jones Victoriann M , Jayaratne Sharani U , Fokin Alexander A , Masri Mohammad M
Published: February 2023

Colonoscopy is a widely used method of screening, diagnosis and intervention. Complications are infrequent and generally present as colonic perforation or colonic hemorrhage. A rare and life-threatening complication of colonoscopy is splenic injury or rupture. We present a case report of an 81-year-old female who was admitted with hemodynamic instability and tachycardia due to gastrointestinal (GI) bleeding and developed hemoperitoneum within 24 hours following colonoscopy. The initial computed tomography (CT) scan was misdiagnosed due to the patient history of GI bleed, and the iatrogenic splenic injury was recognized only during a second CT after continued hemodynamic instability. The patient’s initial diagnosis of a GI bleed masked the intraperitoneal bleed and led to a delayed diagnosis of splenic rupture and increased morbidity. This patient required an emergent laparotomy with a total splenectomy with lysis of adhesions.
Internet-based basic body awareness therapy in fibromyalgia syndrome: A report of three cases
Authors: Tahran Özge , Ersöz Hüseyinsinoğlu Burcu , Yolcu Günay , Karadağ Saygı Evrim
Published: February 2023

Previous literature has shown that basic body awareness therapy (BBAT) may be an effective treatment for fibromyalgia syndrome (FMS). This study constitutes the first case study evaluating internet-based BBAT for FMS. The purpose of this case study was to describe the feasibility and preliminary outcomes of an internet-based BBAT training for a total of 8 weeks in three patients with FMS. The patients underwent a synchronous individual internet-based BBAT training. Outcomes were assessed using Fibromyalgia Impact Questionnaire Revised, Awareness-Body-Chart, Short-Form McGill Pain Questionnaire (SF-MPQ), and plasma fibrinogen level. These measures were administered at baseline and after the treatment. Patient satisfaction with the treatment was evaluated using a structured questionnaire. At the post-treatment evaluation, each patient showed improvements in all outcome measures. All patients had clinically significant changes in Fibromyalgia Impact Questionnaire Revised. The SF-MPQ total score in Patients 1 and 3 exceeded the minimal clinically important difference. All patients’ pain severity exceeded the minimal clinically important difference for Visual Analogue Scale (SF-MPQ). Besides, we found some benefits in body awareness and the level of dysautonomia. At the end of the treatment, patient satisfaction with the programme was very high. Based on this case study, the application of internet-based BBAT seems feasible and promising for clinical benefits.
Ecological restoration for sustainable development in China
Authors: Fu Bojie , Liu Yanxu , Meadows Michael E
Published: February 2023

Facing the need for transdisciplinary research to promote ecological restoration that achieves both social and ecological benefits, research on past restoration efforts that have directly or indirectly contributed to regional or national sustainable development warrants reassessment. Using China as an example, in this review, we address three basic research questions that can be summarized as follows: ecological restoration—of what, for whom and to what purpose? Accordingly, a ‘landscape pattern—ecosystem service—sustainable development’ co-evolutionary framework is proposed here to describe landscape-scale ecological restoration and its impact on landscape patterns and ecological processes, ecosystem services for human well-being, sustainable livelihoods and socioeconomic development. From the strategic pattern of national ecological security to the pattern of major projects to protect and restore major national ecosystems, the spatial pattern of China's ecological restoration is more geographically integrative. From major function-oriented zoning to systematic ecological protection and restoration, and for the purpose of achieving the Beautiful China Initiative, there are three stages of ecosystem services management: classification, synergy and integration, respectively. The difference in geographic processes should be considered in the key requirements of ecological restoration for China's five national strategies for regional sustainable-development strategies. Deepening understanding of the relationship between humans and nature in different geographical contexts is a scientific prerequisite to support policymaking related to ecological restoration. To promote greater harmony between humans and nature, we propose four important research directions: (i) understanding coupling processes among key components, (ii) identifying ecosystem service flows, (iii) evaluating social-ecological benefits and (iv) supporting adaptive management for regional sustainable development.
COVID-19 and Outpatient Antibiotic Prescriptions in the United States: A County-Level Analysis
Authors: Hamilton Alisa , Poleon Suprena , Cherian Jerald , Cosgrove Sara , Laxminarayan Ramanan , Klein Eili
Published: February 2023

Background

Declines in outpatient antibiotic prescribing were reported during the beginning of the coronavirus disease 2019 (COVID-19) pandemic in the United States; however, the overall impact of COVID-19 cases on antibiotic prescribing remains unclear.

Methods

This was an ecological study using random-effects panel regression of monthly reported COVID-19 county case and antibiotic prescription data, controlling for seasonality, urbanicity, health care access, nonpharmaceutical interventions (NPIs), and sociodemographic factors.

Results

Antibiotic prescribing fell 26.8% in 2020 compared with prior years. Each 1% increase in county-level monthly COVID-19 cases was associated with a 0.009% (95% CI, 0.007% to 0.012%; P < .01) increase in prescriptions per 100 000 population dispensed to all ages and a 0.012% (95% CI, −0.017% to −0.008%; P < .01) decrease in prescriptions per 100 000 children. Counties with schools open for in-person instruction were associated with a 0.044% (95% CI, 0.024% to 0.065%; P < .01) increase in prescriptions per 100 000 children compared with counties that closed schools. Internal movement restrictions and requiring facemasks were also associated with lower prescribing among children.

Conclusions

The positive association of COVID-19 cases with prescribing for all ages and the negative association for children indicate that increases in prescribing occurred primarily among adults. The rarity of bacterial coinfection in COVID-19 patients suggests that a fraction of these prescriptions may have been inappropriate. Facemasks and school closures were correlated with reductions in prescribing among children, possibly due to the prevention of other upper respiratory infections. The strongest predictors of prescribing were prior years’ prescribing trends, suggesting the possibility that behavioral norms are an important driver of prescribing practices.