bluuebunny/crossref_metadata_2025 huggingface dataset:
Reducing workload in malignant melanoma sentinel node examination: a national study of pathology reports from 507 melanoma patients
Authors: Mellemgaard Carina , Christensen Ib Jarle , Salkus Giedrius , Wirenfeldt Staun Pia , Korsgaard Niels , Hein Lindahl Kim , Skaarup Larsen Mathilde , Klausen Siri , Lade-Keller Johanne
Published: February 2023

Aims

Even though extensive melanoma sentinel node (SN) pathology protocols increase metastasis detection, there is a need for balancing high detection rates with reasonable workload. A newly tested Danish protocol recommended examining nodes at six levels 150 µm apart (six-level model) and using SOX10 and Melan-A immunohistochemistry (IHC). We explored if a protocol examining 3 levels 300 µm apart (three-level model) combined with IHC would compromise metastasis detection. The study aim was to optimise the protocol to reduce workload without compromising detection rate.

Methods

8 months after protocol implementation, we reviewed the pathology reports of SNs from 507 melanoma patients nationwide, including 117 SN-positive patients. Each report was reviewed to determine histopathological features, including detection of metastasis, exact levels with metastasis, exact levels with metastasis >1 mm in diameter and IHC results.

Results

The six-level model detected metastases in 23% of patients, whereas the three-level model would have detected metastases in 22% of patients. The three-level model would have missed a few small metastases (n=4), measuring <0.1 mm, 0.1 mm, 0.4 mm and 0.1 mm, respectively. The six-level model detected metastases >1 mm in 7% of patients. One of these metastases (measuring 1.1 mm) would have been detected by the three-level model, but not as >1 mm. SOX10 and Melan-A had equal sensitivity.

Conclusions

Reducing the number of levels examined to three levels 300 µm apart combined with IHC does not have significant impact on metastasis detection rate, and we will therefore recommend that the future melanoma SN guideline takes this into consideration to reduce overall workload.
Healthy, happy, rational: reflections on genetic counselling in the GDR
Authors: Doetz Susanne
Published: February 2023

The development of genetic counselling in the German Democratic Republic (GDR) was closely connected to a well-established system of prenatal care and a process that placed reproductive decisions in the hands of women. It was embedded in the pronatalist reproductive policy of the GDR and a narrative of medical and (socialist) humanistic progress. As in other countries at that time, it promoted the goal of avoiding the birth of children with disabilities and was hence based on ableist premises. In this paper, I focus on communicative aspects of genetic counselling, as it was established in the 1970s and 1980s in university and district clinics. Thus, on the one hand I explore the communication of genetic counselling to the public; and on the other, I study the communication processes in genetic counselling centres themselves. In contrast to the USA, where the ‘genetic counsellor’ became established as a professional identity in the 1970s, there was no distinct profession of ‘genetic counsellor’ in the GDR. Instead, counselling was practised by physicians or biologists with a special interest in human genetics. This resulted in a strong emphasis in these clinical encounters on diagnosis and technical solutions, as well as an educational impetus. I propose that an important goal of genetic counselling in the GDR was to generate a sense of ‘rationality’ in prospective parents. To achieve this, those advocating and giving counselling explicitly sought to distance this practice from the eugenic ideas of the past, and to dispel superstitious ideas of heredity and religious ideas of fate. In addition, they attempted to alleviate emotions such as fear and guilt. It was in that context that counselling physicians and biologists provided interpretations of genetic findings, risk figures and disease values. I show how different interests and experiences shaped these and how risk evaluations structured counsellor-counsellee communication.
Electrical Stimulation Induced Current Distribution in Peripheral Nerves Varies Significantly with the Extent of Nerve Damage: A Computational Study Utilizing Convolutional Neural Network and Realistic Nerve Models
Authors: Du Jinze , Morales Andres , Kosta Pragya , Bouteiller Jean-Marie C. , Martinez-Navarrete Gema , Warren David J. , Fernandez Eduardo , Lazzi Gianluca
Published: February 2023

Electrical stimulation of the peripheral nervous system is a promising therapeutic option for several conditions; however, its effects on tissue and the safety of the stimulation remain poorly understood. In order to devise stimulation protocols that enhance therapeutic efficacy without the risk of causing tissue damage, we constructed computational models of peripheral nerve and stimulation cuffs based on extremely high-resolution cross-sectional images of the nerves using the most recent advances in computing power and machine learning techniques. We developed nerve models using nonstimulated (healthy) and over-stimulated (damaged) rat sciatic nerves to explore how nerve damage affects the induced current density distribution. Using our in-house computational, quasi-static, platform, and the Admittance Method (AM), we estimated the induced current distribution within the nerves and compared it for healthy and damaged nerves. We also estimated the extent of localized cell damage in both healthy and damaged nerve samples. When the nerve is damaged, as demonstrated principally by the decreased nerve fiber packing, the current penetrates deeper into the over-stimulated nerve than in the healthy sample. As safety limits for electrical stimulation of peripheral nerves still refer to the Shannon criterion to distinguish between safe and unsafe stimulation, the capability this work demonstrated is an important step toward the development of safety criteria that are specific to peripheral nerve and make use of the latest advances in computational bioelectromagnetics and machine learning, such as Python-based AM and CNN-based nerve image segmentation.
An improved local efficient routing strategy on scale-free networks
Authors: Ma Jinlong , Wei Jindong , Ma Jiaxin , Lu Zhijia
Published: February 2023

To improve the traffic capacity of scale-free networks, we propose an improved local efficient routing (ILER) strategy based on node degree and network constraint index (NCI). NCI describes how closely a node is maintained directly or indirectly with other nodes, and it only considers the relationship between nodes and their neighbors, not the topology of the network. Both the node degree and NCI are a parameter to describe the importance of nodes, and the combination of the two can make up for their own shortcomings, making it particularly important. Under the ILER strategy, packets can bypass some central nodes in the network for transmission, so that the central nodes in the network are not prone to congestion, thereby increasing the network traffic capacity. Through simulation comparison, the network traffic capacity under ILER strategy is significantly higher than that under probability routing (PR) strategy and efficient routing (ER) strategy. Under the ILER strategy, the average path length (APL) of the network is also shorter than that under the PR and ER strategies. In addition, whether target attack or random attack, the network has strong robustness under ILER strategy.
ENVIRONMENTAL EXTERNALITIES OF URBAN AGGLOMERATION IN CHINA: NEW EVIDENCE FROM THE PERSPECTIVE OF ECONOMIC DENSITY
Authors: LIANG CHANGYI , LIU XIUYAN , TAVERA CHRISTOPHE
Published: February 2023

In order to capture the environmental externalities of urban agglomeration, we use an agglomeration indicator referred to as economic density, which can be decomposed into the average population density and the concentration of population distribution. Our benchmark regressions use the ordinary least squares method and grid-level panel data for China and for the period 2000–2016. We find that economic density is positively correlated with PM2.5 concentration, and the effects of the two components of economic density are opposite. To address the endogeneity issues, the causal effect of economic density on PM2.5 concentration is estimated with an instrumental variable method. Empirical results show that the PM2.5 concentration increases with economic density, and the associated elasticity is between 0.045 and 0.079. The findings of our benchmark regressions are also supported by a variety of robustness checks. Moreover, while economic growth, the development of secondary industry, and the presence of coal-driven power plants explain why cities with more dense population are more polluted, residential energy use is an opposite channel through which cities with higher economic density can reduce air pollution. Overall, the total effect is a trade-off, and the negative environmental externalities of agglomeration are larger than positive environmental externalities.
NONLINEAR AND TIME-VARYING HETEROGENEITY OF THE SPATIAL EFFECT OF G20 COUNTRIES’ MONETARY POLICIES
Authors: GAO SONGYAO , CUI BAISHENG
Published: February 2023

This study examines how nonlinear and time-varying heterogeneity of the spatial spillover effects of price-based and quantitative monetary policy instruments affect G20 countries’ economic growth by building spatial panel smooth transition models with a trade geography weight matrix. We find spatial dependence between economic growth and monetary policy in G20 countries. Then, we use G7+Spain and BRICS to represent developed and emerging economies, respectively, and re-estimate the spatial fixed effect. G7 countries’ quantitative monetary policy is not significant, and reduced interest rates do not improve GDP; however, both increased money supply and reduced interest rates improve BRICS countries’ GDP. Furthermore, lower interest rates in G7 countries cannot improve GDP during bad times, but during good times, price-based monetary policy effectiveness is improved. Although economic conditions do not affect BRICS countries’ quantitative regulation, they do influence price-based monetary policy’s effects. Neighboring countries’ price-based regulation brings different degrees of spillovers to domestic GDP using both linear and nonlinear models.
WHY DOES A RULER TOLERATE CORRUPTION AND HOW CAN CORRUPTION POSSIBLY BE ELIMINATED?
Authors: LU YUANZHU , XU MINBO , YIN XUNDONG , ZHONG HAI
Published: February 2023

There is a fundamental conflict of interests between the ruler and most citizens in non-democracies. When the ruler maximizes his benefit from taxation, the major constraint is that citizens might make attempts to overthrow the existing regime. The continuity and stability of regime are crucially related to the degree of support to the existing political regime by the bureaucracy. In this paper, we use a simple model to argue that, when the ruler maximizes his benefit and faces exogenous restriction on wage setting, toleration of corruption is necessary to induce the required support and effort from the bureaucracy. We then relax the exogenous restriction on wages and study the case in which the ruler may eliminate corruption by setting efficiency wage. We also explore the possibility that the ruler may use an audit device to check corruption.
Looking for the signals of the missing baryons in the extragalactic background light
Authors: Zhu Wei , Wang Rong
Published: February 2023

The missing baryons in the universe are assumed to be hidden in the whole space as a warm–hot intergalactic medium (WHIM). Finding them is one of the important subjects in modern cosmology. In this paper, we point out that the very high-energy electron–positron rays may light up the WHIM due to the anomalous bremsstrahlung according to an improved Bethe–Heitler formula. The resulting excess of the extragalactic background light (EBL) can be observed by the direct measurement method. A possible explanation on the difference between the direct and indirect measurements of EBL is also proposed. Thus, we find a new window to probe the WHIM properties via the EBL.
Topological edge states and harmonic generation from one-dimensional photonic crystal
Authors: Zhu Yuguang , Hou Lu , Zhou Zhenhua
Published: February 2023

In this paper, in order to achieve certain one-dimensional (1D) topological edge states, we provide a method to construct an edge configuration from the two-periodic structures. Those two-periodic structures have different Zak phases that lead to some topological edge states found in the transmission spectrum. A field distribution shows the intense field localization effect around the interface. When the structure includes nonlinear material, the intense field localization field at the interface will result in nonlinear effect. The simulation based on a finite-difference time-domain (FDTD) method demonstrates that the topological edge states can result in the third-order harmonic (TH) generation.
Coarse-graining modeling of primitive chains in entangled polymer melts
Authors: Hou Ji-Xuan
Published: February 2023

In this paper, we provide a coarse-graining method to obtain the primitive chain from a polymer chain configuration in the entangled polymer melt by knocking out its high-frequency Rouse modes. Adopting this coarse-graining procedure, we theoretically demonstrate that the tube step length is twice the tube diameter. Moreover, a simple method to visualize the tube by adding high-frequency modes to the primitive chain is also provided.
Modified GAN with Proposed Feature Set for Text-to-Image Synthesis
Authors: Talasila Vamsidhar , Narasingarao M. R. , Mohan V. Murali
Published: February 2023

Automated synthesis of practical images from the text could be useful and interesting; however, present AI systems are yet far from this objective. Nevertheless, in current years, powerful and generic Recurrent Neural Network (RNN) structures were introduced to train discriminative text feature representation. In the meantime, Deep Convolutional GANs have started producing highly convincing images of specified categories, like room interiors, album covers, and faces. In this research work, we plan to develop a new model for text-to-image synthesis, which contains three important phases: (i) feature extraction, (ii) text encoding, and (iii) optimal image synthesis. Initially, the text features such as improved TF–IDF, bag of words, and N-gram are extracted from the text and they are trained by Bi-LSTM. During the encoding of an image from text, cross-modal feature grouping is performed. Further, the image is synthesized using modified GAN (MGAN) with a new loss function. Here, for precise synthesis of images, the weights of GAN are optimized using Self-improved Social Ski-Driver (SI-SSD) optimization algorithm. Eventually, the superiority of the suggested model is examined via an assessment over existing schemes.
A Method for 3D Human Pose Estimation and Similarity Calculation in Tai Chi Videos
Authors: Cai Xingquan , Lu Rui , Zhang Haoyu , Huo Yuqing , Sun Haiyan , Ji Jiaqi
Published: February 2023

Human pose estimation from video sequences has become a hot research topic in the domain of robotics and computer vision. However, existing three-dimensional (3D) pose estimation methods usually analyze individual frames, which have a low accuracy due to various human movement speed, limiting its practical application. In this paper, we propose a method for estimating 3D pose and calculating similarity from Tai Chi video sequences based on Seq2Seq network. Specifically, using 2D joint point coordinate sequence of the original image as input, our method constructs an encoder and a decoder to build a Seq2Seq network. Our method introduces an attention mechanism for weighing the input data to obtain an intermediate vector and decode it to estimate the 3D joint point sequence. Afterwards, using a template video and a target video as input, our method calculates the cost of passing through each point within the constraints to construct a cost matrix for video similarity. With the cost matrix, our method can determine the optimal path and use the correspondence of the video sequence to calculate the image similarity of the corresponding frame. The experimental data show that the proposed method can effectively improve the accuracy of 3D pose estimation, and increase the speed for video similarity calculation.
Intelligent Positioning Algorithm Based on CSI Channel Mode
Authors: Wang Wenjie , Huang Zhenzhen , Gao Zongqian
Published: February 2023

Using wearable devices to realize the mining and application of human behavior patterns has become a hotspot in the field of intelligent positioning. Wearable devices provide an analyzable data foundation for indoor spatial distribution and human behavior pattern prediction. The development of the intelligent positioning system based on RSSI has encountered a bottleneck that it is difficult to improve the positioning accuracy. Therefore, some research works started emphasizing location technology based on channel state information (CSI). In this paper, the principle used by Wi-Fi channel state information to realize intelligent positioning is described, the characteristics of CSI are analyzed, and an intelligent positioning algorithm based on CSI is proposed. Specifically, the algorithm first estimates the angle of arrival (AoA) based on the MUSIC algorithm, separates the reflected paths in the multipath components, and accurately estimates the AoA of each path. Second, phase estimation with channel state information is achieved by forming different antenna subarray measurements under the consideration of a subset of antennas and subcarriers. Then, the phase response linear fitting of the data packet CSI is eliminated using the ToF purification algorithm to obtain the corrected phase response and realize the elimination of the STO noise of the channel state information. Finally, the target position is calculated by effectively filtering the reflection path through the likelihood value, and the accurate target positioning function is achieved. The experimental results demonstrate that the intelligent positioning algorithm proposed in this paper can achieve decimeter-level positioning accuracy under the condition of a fixed number of APs, and the average error is better than that of deep learning-based and SVM-based positioning algorithms. In other words, the accuracy of intelligent positioning is improved.
A Novel High Gain Non-Isolated Three-Port DC–DC Converter for DC Microgrid Applications
Authors: Bheemraj T. S. , Prajapathi Dandu , Karthikeyan V. , Kumaravel S.
Published: February 2023

In this paper, a high gain nonisolated three-port bidirectional DC–DC converter is proposed to interface solar photovoltaic and battery energy storage system to DC bus with a reduced number of components. Four modes of operation based on the power flow and load demand are identified. The operating principle of the proposed converter and its operational waveform for all four modes of operation is described in this paper. The steady-state analysis of the proposed converter is performed to determine the voltage gain of the converter in all four modes of operation. The steady-state analysis is done for both continuous conduction mode and discontinuous conduction mode; and the boundary condition. The reduced number of components to achieve high-voltage gain ensures the lowering of the cost and weight of the converter. The analytical results are validated utilizing the simulation results from PSCAD and hardware results. Also, the results indicate that the ripple in the current and voltage is reduced significantly.
Drive-By Fleet Monitoring to Detect Bearing Damage in Bridges Using a Moving Reference Influence Function
Authors: OBrien Eugene J. , McCrum Daniel P. , Wang Shuo
Published: February 2023

This paper introduces a new bridge damage indicator, the moving reference influence function (MRIF), to detect bridge bearing damage using deflections inferred from vehicle accelerations. Recently, vehicle acceleration has been used to find the apparent profile (AP) of a bridge when a vehicle passes. This AP consists of bridge profile elevations and bridge deflection components. To describe the relationship between these deflection components and load, a MRIF is proposed for the first time in this paper. An error minimization process is used to find the MRIF and the road surface profile on the bridge. The vehicle acceleration signals used in the paper are assumed to be collected from a partially instrumented vehicle fleet. In the fleet, only the first axle acceleration is collected from each vehicle. To simplify the minimization process, both the MRIF and the bridge profile are represented by kernel density functions. The results show that the bridge profile can be accurately obtained and that bridge bearing damage can be identified from the MRIF. Both area and skewness of the MRIF are damage sensitive and can be used together to find the location and severity of bridge bearing damage.
Reconsidering Photonic Quantum Heat Engine Efficiency
Authors: Kirk Alexander P.
Published: February 2023

A device — referred to as a photonic quantum heat engine — was reported in Nature Photonics [J. Kim, S. Oh, D. Yang, J. Kim, M. Lee and K. An, A photonic quantum engine driven by superradiance, Nat. Photon. 16 (2022) 707–711] with an efficiency of [Formula: see text]%. Moreover, in a related News & Views contribution in the same issue [M. Kim, M. Scully and A. Svidzinsky, A supercharged photonic quantum heat engine, Nat. Photon. 16 (2022) 669–670], this device was reported to exceed the Carnot limit, an extraordinary claim. As Carl Sagan once remarked, “Extraordinary claims require extraordinary evidence.” Here, we outline the fundamental lack of empirical evidence that would be required to support such a claim, show that the actual efficiency of the device is [Formula: see text] 0% and bring to attention critical aspects of the operating physics of the device.
Finite solvable groups with two imprimitive monolithic characters
Authors: Çınarcı Burcu
Published: February 2023

Let [Formula: see text] be a finite group and let [Formula: see text] be an irreducible character of [Formula: see text]. If [Formula: see text] has a unique minimal normal subgroup, then [Formula: see text] is called monolithic. The character [Formula: see text] is said to be imprimitive if [Formula: see text] is induced from a character of a proper subgroup of [Formula: see text]. In this paper, we classify the finite solvable groups having exactly two imprimitive monolithic characters whose kernels intersect trivially.
Lemon-Juice-Based Microwave Synthesis and Optical Characterization of Anisotropic Gold Nanoparticles
Authors: Baez-Cruz Ricardo , Sekar Ramkumar , Manidurai Paulraj
Published: February 2023

Anisotropic gold nanoparticles (AuNPs) were synthesized using microwave (MW)-assisted route. Lemon extract was used as both reducing and stabilizing agent. Subsequent UV treatment was carried out to modify the particle size and shape. Distribution of triangular and pentagonal-shaped particles were found to increase in number. Moreover, up to 60% increase in particle size was also observed. Change in optical property and appearance of plasmon modes were clear indication of the modification caused. Local density of photonic states (LDOS) and electric field distribution were obtained through computational simulation using MATLAB toolbox. Experimental results were used as the input values for the simulation. Dipolar distribution was observed along the boundaries of the spherical NPs, while for triangular and pentagonal-shaped NPs, they were found to be concentrated along their edges and corners. The results presented here encourage us to choose an alternative eco-friendly, quick and simple route to synthesize gold NPs of various shapes for various application such as in viral detection, nanobiomaterials, biomedical images, detection-therapy, etc.
On distributive lattices of simple ordered semirings
Authors: Mondal T. K. , Chowdhury J. , Bhuniya A. K.
Published: February 2023

In this paper, we study principal ordered ideals of ordered semirings, and give their descriptions with some properties. The characterization of simple ordered semirings is studied, and a relation between a prime ordered ideal and filter has been developed. Finally, we characterize the ordered semirings which are distributive lattices of simple ordered semirings. Here, we find that the equivalence relations [Formula: see text] and [Formula: see text] induced, respectively, from principal filters and principal ordered ideals coincide as distributive lattice congruence in an ordered semiring [Formula: see text] whenever [Formula: see text] is a distributive lattice of simple ordered semirings.
Weakly J-submodules of modules over commutative rings
Authors: Khashan Hani A. , Yetkin Celikel Ece
Published: February 2023

Let [Formula: see text] be a commutative ring with identity and [Formula: see text] be a unitary [Formula: see text]-module. By [Formula: see text] we denote the Jacobson radical of [Formula: see text]. The purpose of this paper is to introduce the concept of weakly [Formula: see text]-submodules generalizing [Formula: see text]-submodules. We call a proper submodule [Formula: see text] of [Formula: see text] a weakly [Formula: see text]-submodule if whenever [Formula: see text] for [Formula: see text] and [Formula: see text], then [Formula: see text] or [Formula: see text] Various properties and characterizations of weakly [Formula: see text]-submodules are investigated especially in the case of multiplication modules.
TOO HOT FOR SUSTAINABLE DEVELOPMENT: CLIMATE CHANGE AND ENERGY EFFICIENCY
Authors: JIN GANG , SUN YUTING
Published: February 2023

Previous studies have focused on the benefits of adaptation in mitigating the negative effect of climate change on economic production, neglecting that adaptive energy input cannot be directly translated into output, which may be a barrier to sustainable development. Based on panel data from 280 cities in China from 2003 to 2016, we first calculate the energy efficiency as a proxy for sustainable development by using the nonradial directional distance function (NDDF) method. Second, we estimate energy efficiency as a function of temperature shocks, and we use these estimates to predict future potential impacts from climate change. We find three primary results: First, higher temperatures substantially reduce energy efficiency. Second, the heat effect on energy efficiency is homogenous across regions with different climates, suggesting that while adaptations in hot regions can mitigate the harmful effects of heat on output, this mitigation is completely offset by the concomitant increase in energy costs. Third, the energy efficiency would decrease by 2.82% in the medium term (2041–2060) and by 12.02% in the long term (2061–2080), under the assumption that carbon dioxide emissions continue to increase throughout the 21st century. These findings suggest that moderate adaptations to climate change are crucial for sustainable development.
NATURAL DISASTERS AND DEBT FINANCING COSTS
Authors: FISERA BORIS , HORVATH ROMAN , MELECKY MARTIN
Published: February 2023

Using a comprehensive dataset of 272 large-scale natural disasters in 83 countries from 1986 to 2018, we find that disasters increase government debt financing costs (T-bill rates and 10-year government bond yields) but only in the middle- and low-income countries. This distinct response relative to high-income countries is due to lower levels of credit market depth, of private insurance penetration, and of central bank independence. The results for all natural disasters are driven by biological (epidemic) and climatological disasters — two types of hazards, the frequency and severity of which have been rising.
Does Hiring M&A Advisers Matter for Private Sellers?
Authors: Agrawal Anup , Cooper Tommy , Lian Qin , Wang Qiming
Published: February 2023

M&A advisers can find and negotiate better deals for sellers, but hiring them entails fees and potential agency costs. Using a novel, hand-collected dataset on the hiring of seller advisers for a large sample of M&A deals, we find that private sellers use advisers or top-tier advisers when it makes economic sense. After accounting for this selection effect, advisers and top-tier advisers positively affect deal valuations. We find some evidence that acquirers’ announcement returns are lower in deals where private sellers use advisers. Our findings suggest that M&A advisers can find and negotiate better deals for private sellers.
Review—Flow Batteries from 1879 to 2022 and Beyond
Authors: Tolmachev Yuriy V.
Published: February 2023

We present a quantitative bibliometric study of flow battery technology from the first zinc-bromine cells in the 1870’s to megawatt vanadium RFB installations in the 2020’s. We emphasize, that the cost advantage of RFBs in multi-hour charge-discharge cycles is compromised by an inferior energy efficiency of these systems, and that there are limits on the efficiency improvement due to internal cross-over and the cost of power (at low current densities) and due to an acceptable pressure drop (at high current densities). Differences between lithium-ion and vanadium redox flow batteries (VRFBs) are discussed from the end-user perspective. We conclude, that the area-specific resistance, cross-over current and durability of contemporaneous VRFBs are appropriate for commercialization in multi-hour stationary energy storage markets, and the most import direction in the VRFB development today is the reduction of stack materials and manufacturing costs. Chromium-iron RFBs should be given a renewed attention, since it seems to be the most promising durable low-energy-cost chemistry.
Value of Humanized Nursing under Emergency Green Channel on Gastrointestinal Function Recovery in Patients with Acute Intestinal Obstruction after Operation
Authors: Luo Siqi , Wang Yan
Published: February 2023

Acute intestinal obstruction (AIO) is one of the most common surgical acute abdomens. Emergency green channel refers to a fast and efficient service system provided by hospitals for critically ill patients. It is the key to ensure that emergency patients receive timely, standardized, efficient and thoughtful medical services, improve the success rate of rescue, and reduce medical risks. Acute intestinal obstruction is mainly treated by surgery in the clinic. Previous reports have shown that the application of different nursing methods in the operation of acute intestinal obstruction has different effects on the results of surgical treatment. In this study, the clinical data of 80 patients with AIO were retrospectively analyzed to explore the value of humanistic care under the emergency green channel in promoting the recovery of gastrointestinal function after AIO surgery.
Chemical Composition and Biological Activities of Lavandula coronopifolia Poir Extracts: A Comparison between Callus Culture and Native Plant
Authors: Sharifzadeh Shady , Karimi Safoora , Abbasi Habib , Assari Mohammadreza
Published: February 2023

Nowadays, according to the development and high functions of in vitro cultivation, one of the questions that researchers are looking for is whether the characteristics and compositions of the obtained product meet the needs of the society or not. Therefore, this research was done aimed to compare the bioactive characteristics of callus and native plant aqueous extracts of Lavandula coronopifolia Poir. Thus, two different culture media were utilized for calluses’ growth. Extracts from these calluses and native plants were obtained using the sequential ultrasound-microwave assisted extraction (SUMAE) method. The extraction conditions were a constant temperature of 70°C ultrasound in 20 min at 250 W and 8 minutes at 800 W for microwave at 85°C. At first, results revealed that callus cultures were not able to produce any significant amounts of essential oil. Therefore, aqueous extracts obtained from calluses as well as the natural plant were examined in terms of antioxidant activity, total phenolic content, total flavonoid content, and antimicrobial activity. Moreover, their volatile components were detected with GC-MS. Both DPPH and FRAP techniques demonstrated that the callus on MS + Auxin had stronger antioxidant activity than the other callus and native plant. It also had the greatest total phenolic content. In terms of total flavonoid content, the native plant has the highest value. Generally, it can be concluded that the extract of callus on MS + Auxin has shown significant activity against the tested microorganisms than the other samples.
Kriging-Based Space Exploration Global Optimization Method in Aerodynamic Design
Authors: Zhang Wei , Gao Zhenghong , Wang Chao , Xia Lu
Published: February 2023

For complicated aerodynamic design problems, the efficient global optimization method suffered from the defect of the incorrect portrayal of the design space, resulting in bad global convergence and efficiency performance. To this end, a Kriging-based global optimization method, named the Kriging-based space exploration method (KSE), was proposed in this paper. It selected multiple promising local minima and classified them into partially and fully explored minima in terms of the fitting quality of the surrogate model. Then, the partially explored minima would be furtherly exploited. During the local search, an enhanced trust-region method was adopted to make deep exploitation. By combining local and global searches, the proposed method could improve the fitting quality of the surrogate model and the optimization efficiency. The KSE was compared to other global surrogate-based optimization methods on 12 bound-constrained testing functions with 2 to 16 design variables and 2 aerodynamic optimization problems with 24 to 77 design variables. The results indicated that the KSE generally took fewer function evaluations to find the global optima or reach the target value in most test problems, holding better efficiency and robustness.
The Nine RNA Methylation Regulatory Gene Signature Is Associated with the Pathogenesis of Atrial Fibrillation by Modulating the Immune Microenvironment in the Atrial Tissues
Authors: Wang Qiuyu , Zhang Shuaipeng , Xu Xiruo , Liu Jianguo , Tan Pengjin , Wang Chunbo , Wang Jing , Li Xin , Shang Lihua
Published: February 2023

Background. Atrial fibrillation (AF) is the most common type of cardiac arrhythmias and a major cause of cardiovascular disease (CVD)-related deaths globally. RNA methylation is the most frequent posttranscriptional modification in the eukaryotic RNAs. Previous studies have demonstrated close associations between the status of RNA methylation and CVD. Methods. We comprehensively evaluated the relationship between RNA methylation and AF. Least absolute shrinkage and selection operator (LASSO) logistic regression analysis was used to establish a risk score model in AF. Biological functional analysis was used to explore the relationship between RNA methylation related signatures and immune microenvironment characteristics. Machine learning was used to recognize the outstanding RNA methylation regulators in AF. Results. There was a significant variant of the mRNA expression of RNA methylation regulators in AF. RNA methylation related risk score could predict the onset of AF and closely associated with immune microenvironment features. XG-Boost algorithm and SHAP recognized that NSUN3 and DCPS might play a key role in the development of AF. Meanwhile, NSUN3 and DCPS had potential diagnostic value in AF. Conclusion. RNA methylation regulatory genes are associated with the onset of AF by modulating the immune microenvironment. The nine AF risk-related RNA methylation regulatory gene signature is a potential diagnostic biomarker and therapeutic target for AF.
Impact of Lipoprotein(a) on Macrovascular Complications of Diabetes in a Multiethnic Population in the French Amazon
Authors: Dordonne Sabrina , Mergeayfabre Mayka , Hafsi Nezha , Ntoutoum Andre , Salazar-Cardozo Clara , Casse Olivier , Hounnou Marianne , Adenis Antoine , Aurelus Jean-Markens , Misslin-Tristch Caroline , Carod Jean-François , De Toffol Bertrand , Lienne Jean François , Demar Magalie , Nacher Mathieu , Sabbah Nadia
Published: February 2023

Background and Aims. In French Guiana, the prevalence of diabetes is around 10%, and cardio and neurovascular pathologies are the first medical cause of early mortality. Lipoprotein(a) (Lp(a)) is described in the literature as a risk factor independent of other cardiovascular risk factors, but there are important interindividual differences, especially according to ethnicity. The objective of this study was to investigate the association of Lp(a) and macrovascular complications in a multiethnic population of patients with diabetes in the French Amazon. Materials and Methods. Since May 2019, 1243 patients were screened 806 of whom had Lp(a) determination. We compared the prevalence of macrovascular complications in three groups according to Lp(a) concentration: between 0 and 75 mg/mL, between 76 and 300 mg/mL, and >300 mg/mL. Results. 712 patients in the study had type 2 diabetes (88.34% of the sample). A history of hypertension was significantly associated with greater Lp(a) levels. Lp(a) concentration was greater among Creole ethnic groups. No association was found between Lp(a) levels and macrovascular complications in the

Lp

a

>
300

 mg/mL group. Conclusions. These results do not replicate findings in mostly Caucasian populations suggesting that the Lp(a) threshold for, or the link with, cardiovascular risk may be different given the predominantly African origin of the French Guianese population. Further studies should study genetic polymorphisms in our population.
Synergistic Agglomeration of Manufacturing and Logistics Industries and Urban Green Economy Efficiency: Influence and Upgrading
Authors: Zhang Qian , Tao Ye
Published: February 2023

Synergistic industrial agglomeration has an impact on green economy. In this research, the evaluation index system of urban green economic efficiency (GEE) is constructed; the superefficiency SBM model, Malmquist index method, location entropy method, and Tobit regression analysis are used to analyse the static and dynamic GEE, the industrial agglomeration level of manufacturing and logistics industries, the synergistic agglomeration level of the two, and the influencing factors of GEE of 41 cities and four provinces in the Yangtze River Delta (YRD) region from 2010 to 2019. The results show that the urban GEE in the YRD region is generally not high, and the annual change trend of efficiency is U‐shaped. In the YRD region as a whole and in each province, the relationship between the synergistic agglomeration level of the two industries and the GEE presents regional heterogeneity and GEE is influenced by various factors. Synergistic alignment and integrated development of the two industries are good ways to optimize and upgrade industrial structure transformation. The government can improve urban GEE by adjusting the horizontal and vertical intergovernmental relations as well as adjusting the talent support mechanism to promote integration of technologies with industry and optimizing the upgrading and transformation of industrial structure to achieve sustainable industry development.
Determination Rule for α, β Directions and φ in Teaching of Slip-Line Theory
Authors: Mei Ruibin , Bao Li , Gao Han , Zhang Xin
Published: February 2023

In the teaching of plastic mechanics and applications of slip-line theory using conventional methods, multivalued results are usually caused by the uncertain direction of the slip line and dip angles. Determination rules for the α and β directions and φ values are proposed to improve slip-line theory according to the particle flow law under the effect of principal stress, and slip lines and dip angles suitable for a typical stress boundary problem are described. The α and β slip lines should simultaneously point to or away from the intersection, and the synthetic direction of the slip lines should point to the first principal stress σ1 or away from the direction of the third principal stress σ3. When the Hencky stress equation of the α line is applied, two points on the α line should maintain the same direction, and the absolute value of the φ difference should be less than or equal to π. Moreover, the α line of two points should simultaneously point to the inner and outer normal direction of the β line when the Hencky stress equation of the β line is used. The average stress and critical load of plastic deformation in the plane lath V-notch tension are solved using slip-line theory. Both the calculated critical stress and the load maintain uniformity using different slip lines and dip angles, and the proposed determination rule reliably avoids multivalued solutions. This is important for students and researchers in correctly understanding and applying slip-line theory.
A Smart Contract Vulnerability Detection Model Based on Syntactic and Semantic Fusion Learning
Authors: Han Daojun , Li Qiuyue , Zhang Lei , Xu Tao
Published: February 2023

As a trusted decentralized application, smart contracts manage a large number of digital assets on the blockchain. Vulnerability detection of smart contracts is an important part of ensuring the security of digital assets. At present, many researchers extract features of smart contract source code for vulnerability detection based on deep learning methods. However, the current research mainly focuses on the single representation form of the source code, which cannot fully obtain the rich semantic and structural information contained in the source code, so it is not conducive to the detection of various and complex smart contract vulnerabilities. Aiming at this problem, this paper proposes a vulnerability detection model based on the fusion of syntax and semantic features. The syntactic and semantic representation of the source code is obtained from the abstract syntax tree and control flow graph of the smart contract through TextCNN and Graph Neural Network. The syntactic and semantic features are fused, and the fused features are used to detect vulnerabilities. Experiments show that the detection accuracy and recall rate of this model have been improved on the detection tasks of five types of vulnerabilities, with an average precision of 96% and a recall rate of 90%, which can effectively identify smart contract vulnerabilities.
Predicting Spacecraft Telemetry Data by Using Grey–Markov Model with Sliding Window and Particle Swarm Optimization
Authors: Ren Liang , Yang Feng , Gao Yuanhe , He Yongcong
Published: February 2023

Predicting telemetry data is vital for the proper operation of orbiting spacecraft. The Grey–Markov model with sliding window (GMSW) combines Grey model (GM (1, 1)) and Markov chain forecast model, which allows it to describe the fluctuation of telemetry data. However, the Grey–Markov model with sliding window does not provide better predictions of telemetry series with the pseudo-periodic phenomenon. To overcome this drawback, we improved the GMSW model by applying particle swarm optimization (PSO) algorithm a sliding window for better prediction of spacecraft telemetry data (denoted as PGMSW model). In order to produce more accurate predictions, background-value optimization is specially carried out using the particle swarm optimization technique in conventional GM (1, 1). For verifying PGMSW, it is utilized in the prediction of the cyclic fluctuation of telemetry series data and exponential variations therein. The simulation results indicate that the PGMSW model provides accurate solutions for prediction problems similar to the pseudo-periodic telemetry series.
Interpretability of Clinical Decision Support Systems Based on Artificial Intelligence from Technological and Medical Perspective: A Systematic Review
Authors: Xu Qian , Xie Wenzhao , Liao Bolin , Hu Chao , Qin Lu , Yang Zhengzijin , Xiong Huan , Lyu Yi , Zhou Yue , Luo Aijing
Published: February 2023

Background. Artificial intelligence (AI) has developed rapidly, and its application extends to clinical decision support system (CDSS) for improving healthcare quality. However, the interpretability of AI‐driven CDSS poses significant challenges to widespread application. Objective. This study is a review of the knowledge‐based and data‐based CDSS literature regarding interpretability in health care. It highlights the relevance of interpretability for CDSS and the area for improvement from technological and medical perspectives. Methods. A systematic search was conducted on the interpretability‐related literature published from 2011 to 2020 and indexed in the five databases: Web of Science, PubMed, ScienceDirect, Cochrane, and Scopus. Journal articles that focus on the interpretability of CDSS were included for analysis. Experienced researchers also participated in manually reviewing the selected articles for inclusion/exclusion and categorization. Results. Based on the inclusion and exclusion criteria, 20 articles from 16 journals were finally selected for this review. Interpretability, which means a transparent structure of the model, a clear relationship between input and output, and explainability of artificial intelligence algorithms, is essential for CDSS application in the healthcare setting. Methods for improving the interpretability of CDSS include ante‐hoc methods such as fuzzy logic, decision rules, logistic regression, decision trees for knowledge‐based AI, and white box models, post hoc methods such as feature importance, sensitivity analysis, visualization, and activation maximization for black box models. A number of factors, such as data type, biomarkers, human‐AI interaction, needs of clinicians, and patients, can affect the interpretability of CDSS. Conclusions. The review explores the meaning of the interpretability of CDSS and summarizes the current methods for improving interpretability from technological and medical perspectives. The results contribute to the understanding of the interpretability of CDSS based on AI in health care. Future studies should focus on establishing formalism for defining interpretability, identifying the properties of interpretability, and developing an appropriate and objective metric for interpretability; in addition, the user′s demand for interpretability and how to express and provide explanations are also the directions for future research.
Cancer Cells Employ the Most Prolific RNA Editors: A Closer Look at the Single-Cell Level
Authors: Luo Yikai , Liang Han
Published: February 2023

Adenosine-to-inosine (A-to-I) RNA editing is a major source of nucleotide diversification that has significant mechanistic implications in cancer progression and treatment response. However, its activity and prevalence have not yet been systematically determined at a single-cell resolution. Chan and colleagues revealed widespread A-to-I RNA editing events in single cancer cells through an in-depth analysis of a public lung adenocarcinoma single-cell transcriptome dataset. Edits significantly enriched in cancer cells compared to other cell types have the potential to inhibit innate immune response and to predict poor therapeutic response and prognosis in patients treated with targeted therapies.

See related article by Chan et al., p. 374