bluuebunny/crossref_metadata_2025 huggingface dataset:
Cross-sectional study of education and knowledge of unintentional injury prevention and postinjury response given by the parents or caregivers of children in Malvani slum area of Mumbai Suburban District, India
Authors: Sawant Dattaprasad Avinash , Kamble Neha Vishwas
Published: April 2024

Background

Child injuries significantly impact health and development, shaping the nation’s future. With proper knowledge, parents or primary caregivers can effectively prevent, address, and treat these predictable injuries.

Methods

Face-to-face interviews were conducted with 373 parents or primary caregivers of children under 14 years old in four randomly selected urban slum areas in Malwani, Mumbai Suburban District.

Results

Only 30% of respondents had basic first aid knowledge, and merely 10% were aware of unintentional injuries, correlating significantly with parental literacy levels. However, most respondents demonstrated appropriate responses.

Conclusions

Parental or primary caregiver knowledge and response play a critical role in mitigating unintentional child injuries. Increasing awareness among parents and primary caregivers about injuries, their impact on child development and first aid is imperative.
Genetic evidence for splicing-dependent structural and functional plasticity in CASK protein
Authors: Patel Paras A , LaConte Leslie E W , Liang Chen , Cecere Thomas , Rajan Deepa , Srivastava Sarika , Mukherjee Konark
Published: April 2024

Background

Pontocerebellar hypoplasia (PCH) may present with supratentorial phenotypes and is often accompanied by microcephaly. Damaging mutations in the X-linked geneCASKproduce self-limiting microcephaly with PCH in females but are often lethal in males. CASK deficiency leads to early degeneration of cerebellar granule cells but its role in other regions of the brain remains uncertain.

Method

We generated a conditionalCaskknockout mice and deletedCaskubiquitously after birth at different times. We examined the clinical features in several subjects with damaging mutations clustered in the central part of the CASK protein. We have performed phylogenetic analysis and RT-PCR to assess the splicing pattern within the same protein region and performed in silico structural analysis to examine the effect of splicing on the CASK’s structure.

Result

We demonstrate that deletion of murineCaskafter adulthood does not affect survival but leads to cerebellar degeneration and ataxia over time. Intriguingly, damaging hemizygousCASKmutations in boys who display microcephaly and cerebral dysfunction but without PCH are known. These mutations are present in two vertebrate-specificCASKexons. These exons are subject to alternative splicing both in forebrain and hindbrain. Inclusion of these exons differentially affects the molecular structure and hence possibly the function/s of the CASK C-terminus.

Conclusion

Loss of CASK function disproportionately affects the cerebellum. Clinical data, however, suggest that CASK may have additional vertebrate-specific function/s that play a role in the mammalian forebrain. Thus, CASK has an ancient function shared between invertebrates and vertebrates as well as novel vertebrate-specific function/s.
2020 design and methods of the Population Assessment of Tobacco and Health (PATH) study during the COVID-19 pandemic
Authors: DiGaetano Ralph , Dohrmann Sylvia , Taylor Ethel V , Everard Colm D , Castleman Victoria , Yan Ting , Kimmel Heather L , Zandberg Izabella , Piesse Andrea , Opsomer Jean D , Borek Nicolette , Silveira Marushka L , Hubbard Frost , Taylor Kristie , Creamer MeLisa R , Salim Anikah H , Sharma Eva , Cheng Yu-Ching , Vignare Victoria , Cook Tammy , Szeszel-Fedorowicz Wioletta , Siegfried Yumiko , Carusi Charles , Stark Debra , Skara Silvana , Hyland Andrew
Published: April 2024

The Population Assessment of Tobacco and Health (PATH) Study is a nationally representative, longitudinal study of the US population on tobacco use and its effects on health, collecting data annually since 2013. The COVID-19 pandemic interrupted in-person survey data collections around the world. In the USA, this included a PATH Study data collection focused on youth (13–17) and young adults (18–19) as well as other US surveys on tobacco use. Given that it was necessary to pause data collection and considering that tobacco-use behaviours could be expected to change along with pandemic-related changes in the social environment, the original design for the 2020 PATH Study data collection for youth and young adults was modified. Also, the PATH Study Adult Telephone Survey was developed to address the need for adult tobacco use monitoring in this unprecedented time. This article describes the modifications made to the 2020 PATH Study design and protocol to provide nationally representative data for youth and adults after the onset of the COVID-19 pandemic as well as the implications of these modifications for researchers.
A combined short- and medium-term traffic flow prediction method for proactive traffic control at expressway toll stations
Authors: Xue Bingbing , Wang Xu , Han Zishuang
Published: April 2024

Traffic flow prediction can support proactive control strategies to alleviate queues and delays at expressway toll stations. The prediction should be enough accurate and advanced that leaves sufficient preparation time to implement control measures for upcoming congestions. The accuracy of prediction and the lead time for accurate prediction are contradictory. To balance both aspects, a control-oriented combined prediction method was proposed in this study. This method automatically tuned prediction horizons based on predicted level of congestion. It used long short-term memory (LSTM) neural networks to learn the spatial–temporal characteristics of historical traffic flow and predict short-term and medium-term traffic flow at toll stations. Then, the level of congestion was determined for graded congestion warning and dynamic tuning of prediction horizons. To validate the proposed method, the Ganggou toll station was selected as the study site. The proposed integrated model can facilitate reliable proactive control measures at expressway toll stations.
Identification of quantitative trait loci associated with seed quality traits in two early-maturing soybean populations
Authors: Bélanger Jérôme Gélinas , Copley Tanya Rose , Hoyos-Villegas Valerio , O'Donoughue Louise
Published: April 2024

In Canada, soybean ( Glycine max (L.) Merr.) is primarily cultivated in three provinces (Ontario, Quebec, and Manitoba). Canadian breeders want to expand the current cultivation range to more northern agro-environments by developing early-maturing elite lines while maintaining good seed quality traits. To examine quantitative trait loci involved in 100-seed weight and seed protein, oil, and fatty acid (oleic, linolenic, and linoleic acids) contents, we generated an early-maturing recombinant inbred line population (QS15544RIL) and an F2:F3 (QS15524F2:F3) population adapted to cultivation zones MGs 00 and 000, and phenotyped them for 3 years and 1 year, respectively. Using two mapping algorithms (Inclusive composite interval mapping and Genome-wide composite interval mapping), we identified a total of 12 major regions that were either associated with QS15544RIL (five loci), QS15524F2:F3 (four loci), or both (three loci) populations. Of the 12 identified regions, three (RIL_GM12, RIL_GM16, and F2_GM04.2) were not previously identified and might, respectively, serve as novel sources of regulation for oil content, seed weight, and oleic acid. For the RIL_GM05 locus, we identified two novel variants in Glyma.05G244100/ MOTHER OF FT AND TFL1, a gene with a confirmed role in the regulation of oleic and linoleic acid contents. Two of the major loci (RIL_GM04 and RIL_GM16) associated with the 100-seed weight trait and one locus (F2_GM04.2) associated with oleic acid were found to be overlapping three loci ( E8-r1, GM16:5,680,173–5,730,237, and E8-r2) involved in early-maturity and/or shorter pod-filling that were previously identified by our group, suggesting possible breeding bottlenecks due to linkage drag or pleiotropic effects.
Isomers in superheavy nuclei
Authors: Ackermann D. , Antalic S. , Heßberger F. P.
Published: April 2024

Isomeric states in atomic nuclei are a well-known phenomenon all over the complete chart of nuclei. Their properties deliver valuable information on the structure of the nuclei. A region of specific interest are the very heavy and superheavy nuclei, where the occurrence and properties of isomeric states will have an impact on the prediction of localization and strength of the spherical superheavy proton and neutron shells. In this review, an overview of the present situation is given. Some specific features are discussed for selected examples.
The effect of theme on the number of celebrity active fans under China Weibo data
Authors: Dong Gaogao , Shi Wenqi , Sun Zhipeng , Wang Fan , Liu Jianguo
Published: April 2024

Online social media platforms have emerged as integral channels for facilitating social interactions, with celebrities utilizing these platforms to engage with their fan base and cultivate a substantial following. The group of engaged fans, commonly referred to as “active fans”, represents individuals who actively communicate with celebrities and actively participate in discussions pertaining to the celebrities’ endeavors. For celebrities, the task of retaining and augmenting the count of active fans holds immense significance, as it significantly amplifies their social impact and commercial value. Here, we construct dynamic weighted active fan networks by leveraging data from 2021 on Sina Weibo, which stands as China’s largest social media platform. Through a comparative analysis encompassing the network’s structure, the growth rate and the duration of active fans, we delve into the influence wielded by six distinct thematic categories, endorsement, variety, public welfare, sports, music and national affairs. This analysis covers a cohort of nine celebrities spanning five diverse domains, including actors, singers, online influencers, anchors and athletes. The growth trajectory and life cycle exhibited by celebrity fans exhibit notable variations, both within and across the aforementioned themes. These dynamics are further influenced by the inherent structural attributes of the personal fan network belonging to each celebrity. Employing the K-Shape time series clustering algorithm, we have undertaken an in-depth exploration of outburst growth patterns observed in active fans and determined the optimal value of the number of clusters to be [Formula: see text] through comparative analysis. Our findings underscore that the themes of endorsement and public welfare exhibit all four growth patterns, namely Double-Peak, Oscillatory, Single-Peak and Continuous Growth Patterns. In contrast, when considering all themes collectively, they collectively demonstrate a single-peaked decaying growth pattern the insights gleaned from this study not only serve as a valuable reference and guide for celebrities across diverse domains who aspire to bolster and augment their social influence but also contribute to the burgeoning fan economy. Moreover, this research introduces novel perspectives and insights for scrutinizing patterns of fan growth and their corresponding dynamics.
Inter- and sub-harmonics estimation: Treatise on raptor-inspired Harris Hawks collective wisdom
Authors: Malik Naveed Ahmed , Chang Ching-Lung , Chaudhary Naveed Ishtiaq , Raja Muhammad Asif Zahoor , Shu Chi-Min
Published: April 2024

In contemporary power systems, harmonics as undesired electrical phenomena, have drawn considerable attention of the research community investigating in design and development of optimal electrical networks. Harmonics affect the power electronics devices with a number of negative impacts, including higher power losses, worse power quality, and interference with other delicate grid connected equipment. An objective function of inter- and sub-harmonics is constructed for joint estimation of amplitude and phase with known frequency. Accurate estimation of the harmonics model is carried out with stupendous knacks of raptor-inspired Harris Hawks optimization algorithm (HHOA), a revolutionary population-based, nature-motivated optimization approach. The primary sources of inspiration for HHOA are Harris Hawks cooperative demeanor and surprise pounce chasing style in nature. The HHOA’s performance is assessed for harmonics parameter estimation with several noise conditions, differing particle sizes and iterations. The proposed HHOA-based estimation technique provides accurate, convergent and robust performance for harmonics estimation. The reliable level of fitness is achieved consistently in the range of 10−3 to 10−10, an evidence of valuable precision, stability and robustness of the proposed algorithm.
MAINTAINING THE BALANCE BETWEEN PRODUCTION ACTIVITIES AND ENVIRONMENTAL CONSERVATION IN ECOLOGICAL EFFICIENCY ASSESSMENT: EVIDENCE FROM OECD COUNTRIES
Authors: LIANG XIAOXING , ZHOU ZHIXIANG , WU YUMENG
Published: April 2024

Enhancing ecological efficiency stands out as a crucial avenue to realize carbon emission reduction without compromising economic and social development. This study introduces a fairness-concern ecological efficiency evaluation model to address the overestimation of efficiency values in traditional models with maintaining the balance between production activities and environmental conservation during the process of ecological efficiency measurement. The theoretical model is applied to 28 OECD countries, and reveals a general ecological efficiency for them during 2013 to 2017. The efficiency value assessments presented herein offer policymakers valuable insights for enhancing efficiency based on diverse preferences.
Structural and decay properties of even–even trans-lead nuclei
Authors: Adel A. , Qandil Omnia S. A.
Published: April 2024

A systematic study of the ground-state properties of even–even Po, Rn, Ra and Th isotopes is conducted using the self-consistent Skyrme-Hartree–Fock–Bogoliubov (HFB) theory. Different Skyrme interactions are employed in the study. The bulk properties such as binding energy, two-neutron separation energies, two-proton separation energies and neutron skin thickness are investigated. The obtained results from the Skyrme-HFB formalism are compared with the calculated results from the Finite Range Droplet Model (FRDM) and the available experimental data. Our theoretical values were found to be consistent with their counterparts. In addition, the density-dependent cluster model is utilized to estimate [Formula: see text]-decay half-lives. A good agreement is achieved between the calculated results and the recent experimental data.
Assessing Available Care Time and Nursing Shortage in a Hospital
Authors: Biard Romain , Deschamps Marc , Diss Mostapha , Roussel Alexis
Published: April 2024

This paper develops a model to assess the number of nurses needed to ensure both healthy patients and caregivers. We propose a model with random arrivals and exits of patients who may be of a single type (or several), and calculate the average care time they can receive. We show that the mean care time does not depend only on the mean number of patients in the unit. Actually, the probability distribution of the new patients per time step plays a central role. In the Poissonian case, we obtain totally explicit results, prove that the mean care time converges to a constant and give numerical examples. We also propose an analysis of the impact of working conditions on the average time that can be devoted to a patient. Four scenarios are proposed with numerical applications. Our analysis provides insights into current discussions on the introduction of caregiver ratios in hospitals to improve both the quality of care and caregivers’ working conditions.
Parameter Tuning and Positioning Strategy of VD and TMD Joint Control System for Multi-Modal Vibration of Stay Cables
Authors: Li Shengli , Gou Wei , Gao Wudi , Zhang Jiaxiang , Wang Xidong
Published: April 2024

Stay cables are becoming slender and their fundamental frequencies are becoming lower with the span of bridges increasing, thus leading to the occurrence of multi-modal vibration under various excitations. As a simple and effective strategy for cable vibration mitigation, the external damper is widely used in practice. However, one damper normally can target only fewer modes and poses limited effects on the control of multi-modal vibration. This paper proposed the use of a joint control system combining a viscous damper and a tuned mass damper for mitigating the multi-modal vibration of stay cables, followed by the optimization methodology of tuning and positioning. The control performance of the joint system was evaluated by numerical simulations. The feasibility of the joint control system was validated by analyzing the results of the comparative study, therefore providing a possible solution to multi-modal and high-modal vibration of stay cables.
Application of Deep Convolutional Generative Adversarial Network to Identification of Bridge Structural Damage
Authors: Zhu Siyu , Xiang Tianyu , Yang Mengxue , Li Yongle
Published: April 2024

In recent years, the increase in the number of vehicles on the road has impacted the service life of bridges, and thus, their performance. In China, bridge inspections must be performed and documented at least once per year using labor-intensive and subjective approaches. In this study, a computationally efficient damage identification methodology for bridges was developed based on a deep convolutional generative adversarial network (DCGAN). To predict the damage to bridges, the vibration data of the structural damage are extracted from sensor measurements on the bridges and applied to the DCGAN model. The proposed damage identification method was validated on a simple supported beam bridge and a continuous girder bridge. The effects of sample size and noise on the identification accuracy were also evaluated. The performance of the DCGAN in the damage identification process is robust and reliable. This method for structural health monitoring offers a more objective evaluation of the overall performance and condition of a bridge, thus enabling bridge owners to efficiently allocate finite maintenance resources.
Shaking Table Test Study of Dynamic Response and Failure Mode of Liquefiable Layer Slope Under Earthquake
Authors: Yang Bo , Dong Jianhua , Tian Wentong , He Pengfei , Guo Dingnan , Zhao Lvhua
Published: April 2024

As a kind of special terrain, the landslide disaster generated by liquefiable layer slopes under earthquake has become a major engineering challenge due to its large scale and long slip distance. In order to study the seismic response and damage mode of liquefiable layer slope, this paper follows the research line of “geological generalization, physical modeling, and result analysis”, and takes the liquefiable layer slope in the upper reaches of the Yellow River Class secondary terrace as the object of study, generalizes the physical model of the slope, and carries out shaking table test. Based on the PGA amplification coefficient, Fourier analysis and HHT time–frequency characterization of the model slope, it was found that the PGA amplification coefficient increases gradually along the slope height, reaches the maximum value at the top of the liquefiable layer and then decreases gradually, which indicates that the liquefiable sand layer has an obvious energy dissipation effect, and on the horizontal direction of model slope is a tendency to the surface effect; the seismic waves at the discontinuous interface change drastically, and the Hilbert time–frequency spectrum transforms from multiple peaks to a single peak; with the increase of the intensity, the intrinsic frequency of the overall model decreases, and the high-frequency component within the liquefiable sand layer decreases from 5–15[Formula: see text]Hz to 0–5[Formula: see text]Hz, indicating that the liquefiable layer has a filtering effect; the damage process of the liquefiable layer slope is the tensile crack at the top of the slope — seismic subsidence at the top of the slope — the shear yielding at the angle of the slope — shear surface penetration at the slope face — overall slope instability and flow-slip damage. The research results will provide a reference for the study of the disaster mechanism of the liquefiable layer slope.
Semirings generated by idempotents
Authors: Dolžan David
Published: April 2024

We prove that a semiring multiplicatively generated by its idempotents is commutative and Boolean, if every idempotent in the semiring has an orthogonal complement. We prove that a semiring additively generated by its idempotents is commutative, if every idempotent in the semiring has an orthogonal complement and all the nilpotents in the semirings are central. We also provide examples that the assumptions on the existence of orthogonal complements of idempotents and the centrality of nilpotents cannot be omitted.
On finite groups whose power graphs are line graphs
Authors: Parveen  , Kumar Jitender
Published: April 2024

Bera [Line graph characterization of power graphs of finite nilpotent groups, Comm. Algebra 50(11) (2022) 4652–4668] characterized finite nilpotent groups whose power graphs and proper power graphs are line graphs. In this paper, we extend the results of above-mentioned paper to arbitrary finite groups. Also, we correct the corresponding result of the proper power graphs of dihedral groups. Moreover, we classify all the finite groups whose enhanced power graphs are line graphs. We classify all the finite nilpotent groups (except non-abelian [Formula: see text]-groups) whose proper enhanced power graphs are line graphs of some graphs. Finally, we determine all the finite groups whose (proper) power graphs and (proper) enhanced power graphs are the complement of line graphs, respectively.
Development and Implementation of a Multilayer Deep Learning-Based Bank Credit Risk Forecasting System
Authors: Long Xiaohui
Published: April 2024

The complexity of the financial environment and the international community makes the capital flow face various challenges, and it is difficult to obtain accurate credit prediction results in the actual application environment. Considering the complex non-linear characteristics of customer information, the Analytic Hierarchy Process is studied to meet the needs of bank credit risk assessment. On this basis, a depth neural network with different complexities was selected for the three indicators built to classify the features. The composition of the neural network module and the number of neurons were determined by experiment, and Dropout was used to prevent overfitting of the test dataset. Stability and ablation experiments showed that the model can control the error between datasets to 0.021. The ablation experiment showed that the numbers of hidden layers and neurons were the best. Simulation tests showed that the sensitivity and accuracy of this method were 85.25% and 92.55%, respectively, which were superior to other classification methods. The real data of banks in the past four years were tested. The results could accurately classify the risks of enterprises and individual customers, and the results of stress test showed that the model is stable. It is found that traditional credit risk assessment models rely on statistical means and rule decisions, and these methods may not fully reveal the complex non-linear relationship and the internal relationship of financial indicators in high-dimensional data. The combination of deep learning technology and hierarchical analysis can better deal with and explain the complex non-linear problems in bank risk assessment.
Gtie-Rt: A comprehensive graph learning model for predicting drugs targeting metabolic pathways in human
Authors: Shah Hayat Ali , Liu Juan , Yang Zhihui
Published: April 2024

Drugs often target specific metabolic pathways to produce a therapeutic effect. However, these pathways are complex and interconnected, making it challenging to predict a drug’s potential effects on an organism’s overall metabolism. The mapping of drugs with targeting metabolic pathways in the organisms can provide a more complete understanding of the metabolic effects of a drug and help to identify potential drug–drug interactions. In this study, we proposed a machine learning hybrid model Graph Transformer Integrated Encoder (GTIE-RT) for mapping drugs to target metabolic pathways in human. The proposed model is a composite of a Graph Convolution Network (GCN) and transformer encoder for graph embedding and attention mechanism. The output of the transformer encoder is then fed into the Extremely Randomized Trees Classifier to predict target metabolic pathways. The evaluation of the GTIE-RT on drugs dataset demonstrates excellent performance metrics, including accuracy (>95%), recall (>92%), precision (>93%) and F1-score (>92%). Compared to other variants and machine learning methods, GTIE-RT consistently shows more reliable results.
Deep Learning Accelerated Design of Bézier Curve-Based Cellular Metamaterials with Target Properties
Authors: Liu Chuang , Wu Heng-An
Published: April 2024

Machine learning has sparked significant interest in the realm of designing mechanical metamaterials. These metamaterials derive their unique properties from microstructures rather than the constituent materials themselves. In this context, we introduce a novel data-driven approach for the design of an orthotropic cellular metamaterials with specific target properties. Our methodology leverages a Bézier curve framework with strategically placed control points. A machine learning model harnesses the positions of these control points to achieve the desired material properties. This process consists of two main steps. Initially, we establish a forward model capable of predicting material properties based on given designs. Then, we construct an inverse model that takes material properties as inputs and produces corresponding design parameters as outputs. Our results demonstrate that the dataset generated using the Bézier curve-based strategy shows a wide range of elastic distributions. Describing the geometry in terms of design parameters, rather than pixel-based figures, enhances the training efficiency of the networks. The dual-network training approach helps avoid contradictions where specific elastic properties may correspond to various geometric designs. We verify the prediction accuracy of the inverse model concerning elastic properties and relative density. The presented approach holds promise for accelerating the design of cellular metamaterials with desired properties.
An upper bound on the number of classes of perfect unary forms in totally real number fields
Authors: Porter Christian , Mendelsohn Andrew
Published: April 2024

Let K be a totally real number field of degree n over [Formula: see text], with discriminant and regulator [Formula: see text], respectively. In this paper, using a similar method to van Woerden, we prove that the number of classes of perfect unary forms, up to equivalence and scaling, can be bounded above by [Formula: see text], where [Formula: see text] is the discriminant of the field K, [Formula: see text] is the additive Hermite–Humbert constant over positive-definite unary forms for K and [Formula: see text] is the covering radius of the log-unit lattice. In particular, when K is Galois over [Formula: see text] and n is a prime number, the number of homothety classes of unary forms is upper bounded by [Formula: see text], where [Formula: see text] is the regulator of K. Moreover, if K is a maximal totally real subfield of a cyclotomic field, the number of homothety classes of perfect unary forms is upper bounded by [Formula: see text].
A Sampling-Based Approach to Solve Difficult Path Planning Queries Efficiently in Narrow Environments for Autonomous Ground Vehicles
Authors: Kiss Domokos
Published: April 2024

Path planning is an essential subproblem of autonomous robots’ navigation. Reaching a given goal pose or covering the available space are typical navigation missions, that require different planning approaches. We focus on such problems in this paper, where a goal pose must be reached by a wheeled autonomous ground vehicle in challenging situations, i.e. in complex environments with limited free space. Many path-planning methods are available, from which the sampling-based approaches gained the highest interest due to their computational efficiency. However, the performance of such methods degrades if the free space is limited and narrow passages have to be crossed on the way to the goal. Finding real-time planning methods to deliver high-quality paths in such situations is challenging. This paper aims to take steps toward solving this problem. On the one hand, an approach is presented to characterize free space narrowness and the difficulty of planning tasks. This can be used as a tool to compare planning queries and evaluate the performance of planning methods from the perspective of their sensitivity to environmental narrowness. On the other hand, an improved variant of our previously proposed RTR planner, an incremental sampling-based path-planning method, is introduced that exhibits good performance even in narrow and difficult planning situations. It is shown by simulations that it outperforms the popular RRT and RRT* planners in terms of running time and path quality, and that it is less sensitive to the narrowness of the environment where the planning task has to be solved.
SPH Simulation of Cnoidal Wave Generation by Cylinder-Shaped Plunger
Authors: Sui Yu-Cheng , Meng Yu-Jie , Zhang Xu-Feng , Qu Heng-Liang , Li Xue-Yan , He Ming
Published: April 2024

Plunger-type wavemakers have been installed in many ocean laboratories around the world, yet there still lacks the wavemaker theory for cnoidal waves, mainly due to the complexity of the cnoidal wave theory and plunger geometry. In this paper, motion equations for a cylinder-shaped plunger generating cnoidal waves, along with constraints on wave parameters, are derived. Afterwards, the generation of cnoidal waves is simulated in a Smooth Particle Hydrodynamic (SPH) wave flume, the accuracy of which is pre-examined by reproducing a laboratory experiment in the literature. Computational results are in satisfactory agreement with analytical solutions in terms of wave height, wave period, pressure and flow velocity. Moreover, pressure fields remain stable during both wave generation and propagation. It can be anticipated that the derived wavemaker theory will extend the functionalities of existing cylinder-shaped plungers and benefit plunger design in the future.
The Dynamics of Reports on the Belt and Road Initiative (BRI) in Cambodian Mainstream Media Before and After the COVID-19
Authors: Qiang Anni
Published: April 2024

The outbreak of the pandemic in early 2020 greatly slowed down the economic and trade exchanges as well as the cultural exchanges among countries. The Chinese government and media are facing challenges communicating internationally the “Belt and Road Initiative” (BRI). This paper selects the reports of mainstream media in Cambodia related to the “Belt and Road” Initiative before and after the epidemic, and comprehensively analyzes the research samples with the help of content analysis methods. By studying the law of “other shaping” of the image of the BRI reported by the Agence Kampuchea Presse (AKP) and the Phnom Penh Post, the two major mainstream media representing Cambodia’s official and private perspectives, respectively, it is helpful to analyze internal laws and explore the logic behind the discourse of the two Cambodia’s mainstream media; by excavating the attitude and value orientation hidden behind the Cambodian media towards the BRI, the paper comes up with the objective conclusion that the national interests and economic benefits brought by “the Belt and Road” projects are the key internal factors influencing the position of Cambodia’s mainstream media. The paper also notices that the spillover effect of China-US competition has an important impact on the Cambodian mainstream media’s coverage of the “Belt and Road” Initiative, and it also has significance for China to look at external communications and seek a breakthrough in vision by studying the international communication of the United States to Southeast Asia in history and learning from its successful experiences.
Interrogating Neoliberalist Approach to Global Climate Governance
Authors: Wang Sidan
Published: April 2024

While global climate governance has been identified across a wide range of international political events, it has been deeply rooted in the liberal international order which encounters various political challenges. This work employs the ecological modernization approach as a way to observe how the neoliberal elements of the global climate governance have been interrogated by different and emerging critical discourses. This work identifies that the populism, green movements and (radical) left-wing concepts have been emerging to challenge the existing global climate governance by holding critical stances on the key elements of the ecological modernization approach.
Toward Robust ASR System against Audio Adversarial Examples using Agitated Logit
Authors: Park Namgyu , Kim Jong
Published: April 2024

Automatic speech recognition (ASR) systems are vulnerable to audio adversarial examples, which aim at deceiving ASR systems by adding perturbations to benign speech signals. These audio adversarial examples appear indistinguishable from benign audio waves, but the ASR system decodes them as intentional malicious commands. Previous studies have demonstrated the feasibility of such attacks in simulated environments (over-line) and have further showcased the creation of robust physical audio adversarial examples (over-air). Various defense techniques have been proposed to counter these attacks. However, most of them have either failed to handle various types of attacks effectively or have resulted in significant time overhead.

In this article, we propose a novel method for detecting audio adversarial examples. Our approach involves feeding both smoothed audio and original audio inputs into the ASR system. Subsequently, we introduce noise to the logits before providing them to the decoder of the ASR. We demonstrate that carefully selected noise can considerably influence the transcription results of audio adversarial examples while having minimal impact on the transcription of benign audio waves. Leveraging this characteristic, we detect audio adversarial examples by comparing the altered transcription, resulting from logit noising, with the original transcription. The proposed method can be easily applied to ASR systems without requiring any structural modifications or additional training. Experimental results indicate that the proposed method exhibits robustness against both over-line and over-air audio adversarial examples, outperforming state-of-the-art detection methods.
Reading and Writing the Human Glycocode
Authors: de Haan Noortje , Nielsen Mathias I. , Wandall Hans H.
Published: April 2024

The complex carbohydrate structures decorating human proteins and lipids, also called glycans, are abundantly present at cell surfaces and in the secretome. Glycosylation is vital for biological processes including cell–cell recognition, immune responses, and signaling pathways. Therefore, the structural and functional characterization of the human glycome is gaining more and more interest in basic biochemistry research and in the context of developing new therapies, diagnostic tools, and biotechnology applications. For glycomics to reach its full potential in these fields, it is critical to appreciate the specific factors defining the function of the human glycome. Here, we review the glycosyltransferases (the writers) that form the glycome and the glycan-binding proteins (the readers) with an essential role in decoding glycan functions. While abundantly present throughout different cells and tissues, the function of specific glycosylation features is highly dependent on their context. In this review, we highlight the relevance of studying the glycome in the context of specific carrier proteins, cell types, and subcellular locations. With this, we hope to contribute to a richer understanding of the glycome and a more systematic approach to identifying the roles of glycosylation in human physiology.
The Evolutionary Interplay of Somatic and Germline Mutation Rates
Authors: Beichman Annabel C. , Zhu Luke , Harris Kelley
Published: April 2024

Novel sequencing technologies are making it increasingly possible to measure the mutation rates of somatic cell lineages. Accurate germline mutation rate measurement technologies have also been available for a decade, making it possible to assess how this fundamental evolutionary parameter varies across the tree of life. Here, we review some classical theories about germline and somatic mutation rate evolution that were formulated using principles of population genetics and the biology of aging and cancer. We find that somatic mutation rate measurements, while still limited in phylogenetic diversity, seem consistent with the theory that selection to preserve the soma is proportional to life span. However, germline and somatic theories make conflicting predictions regarding which species should have the most accurate DNA repair. Resolving this conflict will require carefully measuring how mutation rates scale with time and cell division and achieving a better understanding of mutation rate pleiotropy among cell types.
The Genetics of Human Sleep and Sleep Disorders
Authors: Zou Xianlin , Ptáček Louis J. , Fu Ying-Hui
Published: April 2024

Healthy sleep is vital for humans to achieve optimal health and longevity. Poor sleep and sleep disorders are strongly associated with increased morbidity and mortality. However, the importance of good sleep continues to be underrecognized. Mechanisms regulating sleep and its functions in humans remain mostly unclear even after decades of dedicated research. Advancements in gene sequencing techniques and computational methodologies have paved the way for various genetic analysis approaches, which have provided some insights into human sleep genetics. This review summarizes our current knowledge of the genetic basis underlying human sleep traits and sleep disorders. We also highlight the use of animal models to validate genetic findings from human sleep studies and discuss potential molecular mechanisms and signaling pathways involved in the regulation of human sleep.
Effect of Asymmetric InAlGaN/GaN Superlattice Barrier Structure on the Optoelectronic Performance of GaN-Based Green Laser Diode
Authors: Mu Yue Wei , Dong Hai Liang , Jia Zhi Gang , Jia Wei , Liang Jian , Wang Zhi Yong , Xu Bing She
Published: April 2024

An asymmetric InAlGaN/GaN superlattice barrier structure without the first quantum barrier layer (FQB) is designed, and its effect on the optoelectronic performance of GaN-based green laser diode (LD) has been investigated based on simulation experiment and analytical results. It is found that, compared with conventional GaN barrier LD, device performance is significantly improved by using FQB-free asymmetric InAlGaN/GaN superlattice barrier structure, including low threshold current, high output power, and high photoelectric conversion efficiency. The threshold current of LD with novel structure is 16.19 mA, which is 22.46% less than GaN barrier LD. Meanwhile, the output power is 110.69 mW at an injection current of 120 mA, which is 16.20% higher compared to conventional LD, and the wall-plug efficiency has an enhancement of 9.5%, reaching 20.27%. FQB-free asymmetric InAlGaN/GaN superlattice barrier layer can reduce optical loss, suppress the polarization effect, and improve the carrier injection efficiency, which is beneficial to improve output power and photoelectric conversion efficiency. The novel epitaxial structure provides theoretical guidance and data support for improving the optoelectronic performance of GaN-based green LD.
Electrochemical Sensing of Phenylbutazone using Multi-Walled Carbon Nanotube Paste Electrode in Pharmaceutical and Biological Fluids
Authors: Patil Yuvarajgouda , Megalamani Manjunath , Abbar Jyothi , Nandibewoor Sharanappa
Published: April 2024

The electrochemical performance of phenylbutazone (PBZ) was studied using a multi-walled carbon-nanotube-modified paste electrode (MWCNT/CPE) using a variety of voltammetric tools like cyclic voltammetry (CV), linear sweep voltammetry (LSV), and square wave voltammetry (SWV). The results showed that the MWCNT/CPE exhibited remarkable electro-catalytic action towards the electrochemical oxidation of PBZ in a phosphate buffer solution of physiological pH 7 compared to a bare carbon paste electrode. The electro-kinetic parameters like heterogeneous rate constant, transfer coefficient, scan rate, pH, and involvement of electrons in electro-oxidation of PBZ was investigated. For bare CPE, the peak current was noted to be 19.53 μA with peak potential of 0.6871 V. For MWCNT/CPE, the peak current was 30.53 μA with peak potential of 0.6792 V. The anodic peak was analyzed, and the process was diffusion controlled. For the estimation of PBZ, a SWV technique was developed with great precision and accuracy, with a detection limit of 5.2 nM and a limit of quantification of 17 nM, in the concentration range 1 × 10−7 to 10 × 10−6 M. The MWCNT/CPE has been used successfully for PBZ detection in injection, blood, and urine samples, with recovery rates of 98.9% to 101.5%, 96.3% to101.7% and 98.3% to 102.8%, respectively.
Understanding changes in echocardiographic parameters at different ages following fetal growth restriction: a systematic review and meta-analysis
Authors: van de Meent Mette , Nijholt Kirsten T. , Joemmanbaks Shary C. A. , Kooiman Judith , Schipper Henk S. , Wever Kimberley E. , Lely A. Titia , Terstappen Fieke
Published: April 2024

Fetal growth restriction (FGR) increases cardiovascular risk by cardiac remodeling and programming. This systematic review and meta-analysis across species examines the use of echocardiography in FGR offspring at different ages. PubMed and Embase.com were searched for animal and human studies reporting on echocardiographic parameters in placental insufficiency-induced FGR offspring. We included six animal and 49 human studies. Although unable to perform a meta-analysis of animal studies because of insufficient number of studies per individual outcome, all studies showed left ventricular dysfunction. Our meta-analyses of human studies revealed a reduced left ventricular mass, interventricular septum thickness, mitral annular peak velocity, and mitral lateral early diastolic velocity at neonatal age. No echocardiographic differences during childhood were observed, although the small age range and number of studies limited these analyses. Only two studies at adult age were performed. Meta-regression on other influential factors was not possible due to underreporting. The few studies on myocardial strain analysis showed small changes in global longitudinal strain in FGR offspring. The quality of the human studies was considered low and the risk of bias in animal studies was mostly unclear. Echocardiography may offer a noninvasive tool to detect early signs of cardiovascular predisposition following FGR. Clinical implementation yet faces multiple challenges including identification of the most optimal timing and the exact relation to long-term cardiovascular function in which echocardiography alone might be limited to reflect a child’s vascular status. Future research should focus on myocardial strain analysis and the combination of other (non)imaging techniques for an improved risk estimation.
Enhancing Electric Vehicle Performance with a Hybrid PI‐Sliding Mode Controller for Battery Supercapacitor Integration
Authors: Suthar Monika , Manthati Udaya Bhasker , Arunkumar C. R. , Srinivas Punna , Alsaif Faisal , Zaitsev Ievgen
Published: April 2024

Nowadays, most of the works are based on electric vehicle usage for sustainable transportation using traditional energy storage device, such as battery. Usage of batteries in electric vehicles is having several disadvantages, for example, life span, temperature, and charge estimation. In this paper, a novel control scheme for battery and supercapacitor‐ (SC‐) based hybrid energy storage system (HESS) using hybrid proportional and integral‐ (PI‐) sliding mode control (SMC) for electric vehicle (EV) applications is introduced and implemented. This HESS with hybrid controller proves the usage of batteries in EVs to its fullest potential. The conventional control strategy for HESS follows two‐loop voltage and current PI controllers with low‐pass filter (LPF) and involves tuning of multiple control parameters with variations of source and load disturbances. Performance of the system is affected by tuning PI controller constants. A slow response time with linear PI controllers is long which is not advisable for starting and sudden jerk conditions of EVs. Moreover, the PI controller performance is affected by the system parameter variations during load changes. And these parameters are dynamic in nature due to nonideal conditions. In this paper, a hybrid PI‐sliding mode controller (SMC) scheme is designed to control the bidirectional DC‐DC converters to overcome the drawbacks of aforementioned issues. The combined PI‐SMC controller reduces the tuning effort and reduces the effect of shift in operating point in controller performance. Linear modeling is done using small signal analysis for each subsystems. Permanent magnet synchronous machine (PMSM) is used as electric vehicle. The entire system and its controllers are simulated using MATLAB‐Simulink, and detailed comparison is carried between conventional PI and proposed hybrid PI‐SMC scheme to regulate the DC link voltage. The results are tabulated and show that the hybrid PI‐SMC scheme outperforms in transient and steady‐state conditions than the traditional PI controller. A scaled hardware prototype of 48 W set‐up is developed using dSPACE‐1104, and the experimental results have been carried out to verify the proposed system’s feasibility.
Calculation of Temperature Action of Flat Steel Box Girder of Long‐Span Bridges Using a Joint Model of ARMA Mean and GARCH Variance
Authors: Yang Jun , Zhao Dacheng , Chen Bin , Wang Gaoxin
Published: April 2024

Using the monitoring temperature field data from the flat steel box girder, the time histories of temperature data and temperature difference data are investigated using the extreme value analysis method. Because the calculation of standard values of temperature action needs massive temperature field data, the simulation of daily extreme values of temperature data and temperature difference data is carried out by virtual of Probability Statistical Method. The seasonal and nonstationary trend terms are described using the weighted sum of a series of basic elementary functions. The random fluctuation term is represented by a joint model of ARMA mean and GARCH variance. Moreover, the yearly extreme values of temperature data and temperature difference data are considered as statistical variables, and their standard values of temperature action with 50‐year return period are calculated by means of the general extreme value (GEV) distributive function. The research results can supply references for temperature action of flat steel box girder.