bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Theory and Practice of Data Quality Management
Authors: Liang Yundan , Xu Yinghui , Xie Hongbin , Huang Yi , Yang Zhi , Li Chuang , Ge Lianzhu , Jiang Tianying
Published: March 2024

Data quality management includes both theory and technology, as well as practice and management. Through data quality management, enterprises can obtain high-quality data, which is an important prerequisite for developing data products, providing data services, and realizing the value of data. It is also the core goal of enterprise data governance. This article first reviews and compares the relevant theories of data quality management; Then summarize the data quality practices carried out by typical case enterprises; Finally, based on the theory and practical cases of data quality management, valuable experiences for data quality management are proposed, and prospects for data quality management are presented.
Applications and Challenges of Artificial Intelligence in Life Sciences
Authors: Liu Tianyao , Li Wenbo
Published: March 2024

With the continuous development of science and technology, exploration in the field of life sciences has become increasingly profound, encompassing the understanding of human beings themselves and the exploration of disease etiology and treatment methods.Artificial intelligence is defined as the intelligence exhibited by artificially created systems. The application of artificial intelligence is quite extensive and can replace humans in various aspects of work, significantly enhancing efficiency in daily life and work. Artificial intelligence has a dual nature, as it could provide convenience to human society but could also bring about various adverse effects.This paper summarizes the current applications of artificial intelligence in the field of life sciences. By analyzing the applications of artificial intelligence in areas such as gene editing, drug development, and bioinformatics, it demonstrates the potential of artificial intelligence in the field of life sciences. At the same time, this paper also points out the ethical, technical, social, and various challenges that the application of artificial intelligence technology in the field of life sciences faces, with the aim of providing reference for research in related fields.
Research on the impact of commercial health education and promotion activities on consumer health behavior
Authors: Wang Yuzhuo
Published: March 2024

The Chinese government emphasizes the importance of public health and disease prevention under the Healthy China strategy. According to data, cardiovascular diseases, cancer, and chronic respiratory diseases are the leading causes of death among both urban and rural residents in China, and the number of patients with chronic diseases and medical expenses continues to rise. The Healthy China strategy advocates a shift from treatment to prevention, emphasizing the importance of health education and promotion. However, the development of China’s health industry is relatively late, and academic research related to health lags behind. Currently, research in the field of health education in China is mainly focused on school health education, prevention and control of chronic diseases, and intervention in major diseases. There is relatively limited research on the impact of commercial health education and promotional activities on the daily health behaviors and health consumption behaviors of the general population. This study aims to investigate the impact of commercial health education and promotional activities on Chinese consumers.
The Market Strategy of the International Education Industry: A differentiation perspective in research
Authors: Hu Yang
Published: March 2024

The outbreak of COVID-19 in 2019 has had a profound impact on the overseas education industry, resulting in widespread enterprise self-protection measures such as layoffs, institutional restructuring, marketing strategy adjustments, downsizing and even bankruptcy. Numerous enterprises have proactively adjusted their marketing strategies through rapid and differentiated management methods to navigate and thrive during the epidemic. This paper primarily investigates the differentiated market strategy of the overseas study industry, analyzes the significance of differentiated management for overseas study enterprises, discusses the perspective of differentiation in formulating market strategies within the overseas study industry, and proposes specific countermeasures with an aim to provide impetus for the development of large, medium-sized, small, and micro-scale overseas study enterprises in this sector.
Research on the Application and Future Trend of Artificial Intelligence in Education and Teaching
Authors: Zhu Xueling , Li Chunmei , Bao Min
Published: March 2024

With the rapid development of information technology, artificial intelligence technology has had a revolutionary impact on all walks of life. In the education industry, the deep integration of artificial intelligence and education has provided new ideas and directions for education and teaching reform, triggered changes in the educational pattern, At the same time, it spawned some new products, such as smart teaching and smart classroom and so on. This paper makes a visual analysis of relevant literatures on CNKI, studies the hot issues and development trends of “education + artificial intelligence”, explores future research directions in this field, and provides useful references for subsequent research.
The Design and Development of Intangible Cultural Heritage Products Based on Internet Education Technology
Authors: Huang Zhenbin , Pan Chao
Published: March 2024

This paper explores innovative development and pathway innovation in the inheritance of intangible cultural heritage (ICH) through the utilization of modern internet education technologies. Taking Tujia brocade weaving as a case study, we establish a resource repository and develop virtual reality (VR) scenes to propose a conceptual framework where virtual reality technology serves the “vision” of intangible cultural heritage inheritance. This framework aims to construct a digital innovation “model” for the preservation of intangible cultural heritage. The paper deliberates on the feasibility, effectiveness, and innovativeness of combining virtual interactive technology with intangible cultural heritage protection.
Research on the popularization of Wuqiang New Year’s Paintings Cultural App from the Perspective of Intangible Cultural Heritage Protection
Authors: Liu Kun , He Jiali
Published: March 2024

The celebration of the “New Year” holds profound significance for the Chinese people, symbolizing both reflection on the past and anticipation of a fresh start. Wuqiang New Year paintings, characterized by vibrant colors and a diverse range of themes, not only depict the lives of ancient farmers but also adapt to the evolving times, bearing witness to the relentless flow of time.With the rapid development of mobile Internet, there is a growing demand for diverse information and entertainment. As a kind of application with the theme of spreading non-heritage culture, non-heritage culture App is gradually becoming an important way for people to acquire non-heritage cultural knowledge, enjoy cultural entertainment and cultural innovation. Based on the inheritance and innovation of Wuqiang New Year’s Paintings, this paper improves the protection and inheritance mode of Wuqiang New Year’s Paintings as well as the dissemination mode through the interactive design of the interface of the “Ji New Year’s Paintings” App and explores how to give new vitality to the intangible cultural heritage in the era of new media.
Research on the Construction of a New Business Talent Training System in Private Colleges in the Context of the Digital Economy
Authors: Jiang Yaping
Published: March 2024

In the context of the digital economy, this paper explores how private higher education institutions can construct a contemporary business education talent development system. The analysis delves into the present challenges confronting business education in private colleges, proposing a set of strategies including reforms in the curriculum, innovation in teaching methodologies, and the integration of industry and education. A significant emphasis is placed on the necessity of digital technology and data analysis skills, as well as cross-cultural communication and collaborative abilities for business professionals. The objective of this research is to enhance the adaptability and practical effectiveness of business education, in order to fulfill the societal demand for highly qualified business professionals.
Dirac points and flat bands in two-dimensional magnonic crystals with honeycomb–kagome structure
Authors: Liang Yu , Yun Guohong , Yang Hui , Bai Narsu , Cao Yongjun
Published: March 2024

Based on the model of magnonic crystals (MCs) with honeycomb structure, we propose another model of two-dimensional MCs with honeycomb–kagome structure that is a periodic magnetic composite system composed of Fe, Co, or Py ferromagnetic cylindrical scatterers arranged in the EuO matrix as the honeycomb–kagome structure. The band structures of magnons in these systems are studied numerically by using the plane-wave expansion method. The results show that the Dirac points of magnons will be generated at the Brillouin region points if the scatterers are close-packed, that is to say, the edges of cylindrical scatterers are in contact with each other. The frequency of Dirac points can be indirectly adjusted by changing the radius ratio of close-packed cylinders. In addition, in the case of a large difference in the radius between the close-packed cylindrical scatterers, there will be a magnonic flat band in the band structure, which is a phenomenon of so-called compact localized states different from the impurity state in the crystal, and it is formed by the highly interference superposition of spin waves in the honeycomb–kagome structure. The research on the generation and modulation of magnonic Dirac points and flat bands not only expands the research content of condensed matter topological physics but also provides a promising platform for the application of artificial MCs in the fabrication of spin-wave topological devices.
MBE-grown tetragonal FeTe consisting of c-axis-aligned nanocrystals
Authors: He Zhihao , To Yick On , Ma Chen , Wang Jiannong , Sou Iam Keong
Published: March 2024

Tetragonal FeTe grown on c-plane sapphire by the molecular beam epitaxy technique is found to result in a new structural phase consisting of c-axis-aligned nanocrystals. Their reflection high-energy electron diffraction patterns display two sets of streaks simultaneously at all rotation angles of the sample. High-resolution x-ray diffraction studies confirm that the nanocrystals are tetragonal FeTe with their c-axes aligned to the growth direction. Atomic force microscopy imaging reveals that further growth of these nanocrystals involves a cannibalism process resulting in nanocrystal pillars with sizes of about 0.5–1 µm. The temperature-dependent resistance of these thin films displays an overall semiconducting behavior, however, with a non-measurable state or jumps and falls depending on their nominal thickness, which can be attributed to the thermal responses of the nanocrystals during cooling and heating processes. This discovery provides an approach to form inhomogeneous heterostructures with all possible twisted angles.
Study of microstructure evolution and strengthening mechanisms in Mox(Nb3TaTi3Zr)100−x high-entropy alloys
Authors: Chen Sishuo , Bao Li , Yang Hongtao , Si Xudong
Published: March 2024

A new series of high-entropy alloys denoted as Mox(Nb3TaTi3Zr)100−x, has been designed for aero-engine applications. The study focused on investigating the microstructural evolution and strengthening mechanisms of the alloys in response to varying Mo content. Results indicate that the alloys primarily display a BCC crystal structure. Notably, an FCC phase precipitates in the alloy when the Mo content reaches 30%. Furthermore, as the Mo content increases, the strength of the alloys significantly increases while their plasticity diminishes. The room-temperature yield strength of the alloys shows a substantial increase from 729 MPa (x = 0) to 1202 MPa (x = 25), while the yield strength at 1200 °C rises from 62 MPa (x = 0) to 498 MPa (x = 30). Concurrently, the microhardness of the alloys also increases from 247 HV (x = 0) to 471 HV (x = 30). The observed strengthening mechanisms include solid solution strengthening, fine grain strengthening, and precipitated phase strengthening.
Influence of machining process of MoS2/B4C/Az31 Mg alloy composite and its tribological characteristics
Authors: Arunachalam Jothi , R Saravanan , Sathish T. , Makki Emad , Giri Jayant
Published: March 2024

The automotive, biomedical, and aerospace industries are among those with a rising need for lightweight materials with enhanced mechanical and tribological qualities. Composites based on magnesium alloys have attracted interest because of their excellent strength-to-weight ratio and promise to improve component performance. Magnesium (Mg) alloy-based composites find applications in sports and leisure equipment, aerospace, biomedical implants, and more. The research outlined here serves a critical need in the field of materials science and engineering, particularly regarding the development of advanced magnesium (Mg) alloy-based composites. In this study, we have created a new aluminum composite using the AZ31 alloy mixed with 5% boron carbide (B4C) and 5% molybdenum disulfide (MoS2) as reinforcement through a powder metallurgical technique. The magnesium alloy contains 3% aluminum and 1% zinc. Our research aims to understand the mechanical and tribological behaviors and the impact of Electrical Discharge Machining (EDM) process parameters on AZ31 magnesium alloy. We need to modify these properties for various applications. Many industrial researchers have studied the machinability of magnesium alloys using EDM. We conducted wear tests on AZ31 alloy reinforced with both B4C and MoS2 in altered quantities using a pin-on-disc setup. The outcome displays that the wear resistance of these composites is considerably better matched to other magnesium matrix composites (MMCs). We also measured various densities of the hybrid composite, including apparent density, green density, and sintered density, which were found to be 0.839, 1.495, and 1.504 g/cm3, respectively—better than other composites. In addition, the hybrid composite exhibited a substantial increase in micro hardness, reaching 22.012 HV, indicating improved wear resistance of the material. Comparatively, low density, minimum wear profile, and maximum hardness were recorded for the sample of AZ31 + 5%MoS2 + 5%B4C. The influence of EDM parameters was discussed.
Calculations of the mechanical, optoelectronic, and magnetic properties of FrGeX3 (X = Cl, Br, I) under hydrostatic pressures based on first-principles theories
Authors: Hasan M. D. Ratul , Apon Imtiaz Ahamed , Ovi Istiak Ahmed , Haque Mohammad Salman
Published: March 2024

Using first-principles calculations based on density functional theory, this work investigated the mechanical, magnetic, elastic, electrical, and optical characteristics of the halide-based perovskite FrGeX3 (X = Cl, Br, I) at different hydrostatic pressures ranging from 0 to 9 GPa. It was determined that the compound FrGeX3 (X = Cl, Br, I) is stable and ductile in nature by calculating its thermodynamic and mechanical stability using the parameters of its formation enthalpy and elastic constant. When no hydrostatic pressure is applied, the band computations reveal that FrGeCl3, FrGeBr3, and FrGeI3 all remain in the semiconductor region with bandgaps of 1.14, 0.8, and 0.645 eV, respectively. The study examined how increasing induced pressure affects the bandgap and density of states of the structure for all three halides. The bandgap of FrGeCl3, FrGeBr3, and FrGeI3 fell to 0 eV at 9, 6, and 5 GPa, respectively. In addition, the optical absorption, reflectivity, refractive index, and imaginary and real components of dielectric functions were all studied in detail for cubic perovskites FrGeX3 (X = Cl, Br, I) under varying hydrostatic pressures, from 0 to 9 GPa. Due to increased pressure, the compound transitioned into a conductor and improved its absorption capabilities for all compounds within the 8–14 eV range, making it suitable for use in the UV spectrum. Cl has the largest absorption among all compounds, whereas I displays the lowest. Reflectivity ranges from around 14% to 18% for all compounds and increases w%ith pressure. The actual component of the refractive index ranges from around 2.25 to 2.7 at 0 eV and increases with pressure. Chlorine has a low refractive index, whereas iodine demonstrates the greatest. The highest fluctuation is shown for Br. The dielectric characteristics vary from around 5 to 7.5 F/m. Chlorine (Cl) has the least charge storage capacity, while iodine (I) demonstrates the most, of which both increase with pressure in all compounds. Structure FrGeX3 (X = Cl, Br, I) is hardened and made more ductile by applying hydrostatic pressure, as seen by the increasing bulk, Young’s, and shear modulus values, as well as the elastic constants (C11 and C12). While the electrons were in a co-linear position, the magnetic property was also studied by optimizing the band structure and density of states. The diamagnetic property of the combination FrGeX3 (where X = Cl, Br, I) remained unchanged even when subjected to increased pressure. According to the findings, this perovskite material has remarkable absorption properties, which point to a change in its behavior from semiconductor to metal. Their potential uses in solar cells, UV absorbers, and optoelectronic devices are highlighted by these computational results.
Electromagnetic analysis of a wound rotor synchronous machine using an improved subdomain technique considering finite permeability of the core
Authors: Yu Kyeong-Tae , Ban Hwi-Rang , Lee Ju-Hyeong , Choi Jang-Young , Sung Soyoung , Park Jung-Hyung , Shin Kyung-Hun
Published: March 2024

This study proposed an improved analytical method for electromagnetic field analysis of a wound rotor synchronous machine (WRSM) considering the permeability of soft magnetic materials. A simplified analytical model considering the magnetic permeability of each region is presented. The governing equations of each region are derived from Maxwell’s equations and the electromagnetic field theory, and a general solution is derived by using mathematical techniques. The analytical solutions of all domains are derived by calculating the boundary conditions. To validate the proposed analytical method, the radial and circumferential magnetic flux densities are compared with finite element analysis (FEA) results. In addition, electromagnetic performance parameters such as flux linkage, back-electromotive force, and torque are determined using electromagnetic theories. In particular, the magnetic saturation of the soft magnetic material is due to field and armature current, and the superiority of the proposed method is demonstrated by comparing the improved analytical method considering the global saturation of each region with the nonlinear FEA result considering local saturation. The proposed analytical method can be widely used in the initial and optimal design of WRSM because it can consider saturation of the core due to changes in field and armature current.
Single-sequence protein structure prediction by integrating protein language models
Authors: Jing Xiaoyang , Wu Fandi , Luo Xiao , Xu Jinbo
Published: March 2024

Protein structure prediction has been greatly improved by deep learning in the past few years. However, the most successful methods rely on multiple sequence alignment (MSA) of the sequence homologs of the protein under prediction. In nature, a protein folds in the absence of its sequence homologs and thus, a MSA-free structure prediction method is desired. Here, we develop a single-sequence-based protein structure prediction method RaptorX-Single by integrating several protein language models and a structure generation module and then study its advantage over MSA-based methods. Our experimental results indicate that in addition to running much faster than MSA-based methods such as AlphaFold2, RaptorX-Single outperforms AlphaFold2 and other MSA-free methods in predicting the structure of antibodies (after fine-tuning on antibody data), proteins of very few sequence homologs, and single mutation effects. By comparing different protein language models, our results show that not only the scale but also the training data of protein language models will impact the performance. RaptorX-Single also compares favorably to MSA-based AlphaFold2 when the protein under prediction has a large number of sequence homologs.
Exitron splicing of odor receptor genes in
Drosophila
Authors: Shang Xueying , Talross Gaëlle J. S. , Carlson John R.
Published: March 2024

Proper expression of odor receptor genes is critical for the function of olfactory systems. In this study, we identified exitrons (exonic introns) in four of the 39
Odorant receptor
(
Or
) genes expressed in the
Drosophila
antenna. Exitrons are sequences that can be spliced out from within a protein-coding exon, thereby altering the encoded protein. We focused on
Or88a
, which encodes a pheromone receptor, and found that exitron splicing of
Or88a
is conserved across five
Drosophila
species over 20 My of evolution. The exitron was spliced out in 15% of
Or88a
transcripts. Removal of this exitron creates a non-coding RNA rather than an RNA that encodes a stable protein. Our results suggest the hypothesis that in the case of
Or88a
, exitron splicing could act in neuronal modulation by decreasing the level of functional
Or
transcripts. Activation of
Or88a
-expressing olfactory receptor neurons via either optogenetics or pheromone stimulation increased the level of exitron-spliced transcripts, with optogenetic activation leading to a 14-fold increase. A fifth
Or
can also undergo an alternative splicing event that eliminates most of the canonical open reading frame. Besides these cases of alternative splicing, we found alternative polyadenylation of four
Ors
, and exposure of Or67c to its ligand ethyl lactate in the antenna downregulated all of its 3′ isoforms. Our study reveals mechanisms by which neuronal activity could be modulated via regulation of the levels of
Or
isoforms.
Spatially structured optical effects via composite vortex light in a dielectric medium
Authors: Ibrahim Ahmed Ahmed , Hussein Shaymaa Abed , Mahmud Sanaa Fathy , Ward Zahraa Hassan , Mohammed Bahira Abdulrazzaq , Batoo Khalid Mujasam , Hussain Sajjad , Alwaily Enas R , Al-Shaikhli Taha Raad , Abbas Hussein Abdullah , Alawadi Ahmed , Ihsan Ali
Published: March 2024

In this letter, we have proposed a model for spatially structured transmitted and reflected lights from dielectric medium consists of four-level coherent system. An elliptically polarized probe field and a composite vortex light in the presence of external magnetic field are interacted by this medium. We have shown that by controlling the external magnetic field, ellipticity of the probe light and orbital angular momentum (OAM) of the composite vortex light, the transmitted and reflected lights can be controlled. We have also found that due to the spatial pattern of the composite vortex light, the spatially pattern light amplification can be obtained by adjusting the spatial control of the transmitted and reflected lights. In other word, by tuning the OAM number of the composite vortex light and external magnetic field, the spatial controlling of the transmitted and reflected lights are possible and this leads to controlling the high-gain spatially pattern regions.
Effect of trace oxygen on plasma nitriding of titanium foil
Authors: Zhou 周 Hai-Tao 海涛 , Xiong 熊 Xi-Ya 希雅 , Ma 马 Ke-Xin 可欣 , Luo 罗 Bing-Wei 炳威 , Luo 罗 Fei 飞 , Shen 申 Cheng-Min 承民
Published: March 2024

Titanium nitride films are prepared by plasma enhanced chemical vapor deposition method on titanium foil using N2 as precursor. In order to evaluate the effect of oxygen on the growth of titanium nitride films, a small amount of O2 is introduced into the preparation process. The study indicates that trace O2 addition into the reaction chamber gives rise to significant changes on the color and micro-morphology of the foil, featuring dense and long nano-wires. The as-synthesized nanostructures are characterized by various methods and identified as TiN, Ti2N, and TiO2 respectively. Moreover, the experiment results show that oxide nanowire has a high degree of crystallinity and the nitrides present specific orientation relationships with the titanium matrix.
Multiwavelength Observations of the Infrared Dust Bubble N75 and its Surroundings
Authors: Cui Quan-Ling , Zhang Chuan-Peng , Wang Jun-Jie
Published: March 2024

Infrared dust bubbles play an important role in the study of star formation and the evolution of the interstellar medium. In this work, we study the infrared dust bubble N75 and the infrared dark cloud G38.93 mainly using the tracers C18O, HCO+, HNC and N2H+ observed by the 30 m IRAM telescope. We also study the targets using data from large-scale surveys: GLIMPSE, MIPSGAL, GRS, NRAO VLA Sky Survey and Bolocam Galactic Plane Survey. We found that the C18O emission is morphologically similar to the Spitzer IRAC 8.0 μm emission. The 1.1 mm cold dust emission of G38.93 shows an elongated structure from southwest to northeast. The ionized gas from G38.93 is surrounded by polycyclic aromatic hydrocarbon emission, which may be excited by radiation from G38.93. We found that the identified young stellar objects tend to cluster around G38.93 and are mostly in class II, with several class I cases distributed around N75, but no class II examples. We also found evidence of expanding feedback, which could have triggered star formation.
Financial incentive programs and farm diversification with cover crops: assessing opportunities and challenges
Authors: Surdoval Alison , Jain Meha , Blair Erica , Wang Haoyu , Blesh Jennifer
Published: March 2024

Farmers in the Great Lakes region of the U.S. face tremendous pressure to reduce nutrient losses from agriculture. Increasing crop rotation diversity with overwintering cover crops can support ecological processes that maintain productivity while improving multiple ecosystem functions, including nutrient retention. We conducted a mixed-methods study to understand how financial incentive programs impact transitions to cover cropping in Michigan. Michigan farms span a wide range of soil types, climate conditions, and cropping systems that create opportunities for cover crop adoption in the state. We tested the relationship between Environmental Quality Incentives Program (EQIP) payments for cover crops and cover crop adoption between 2008–2019, as measured by remote sensing. We coupled this quantitative analysis with interviews with 21 farmers in the Lake Erie watershed to understand farmers’ perspectives on how incentive programs could support greater cover crop adoption. Panel fixed effects regressions showed that EQIP increased winter cover crop presence. Every EQIP dollar for cover crops was associated with a 0.01 hectare increase in winter cover, while each hectare enrolled in an EQIP contract for cover crops was associated with a 0.86–0.93 hectare increase in winter cover. In semi-structured interviews, farmers reported that financial incentives were instrumental to cover crop adoption, but that program outcomes fall short of intended goals due to policy design problems that may limit widespread participation and effectiveness. Thus, strengthening EQIP and related conservation programs could support broader transitions to diversified farming systems that are more sustainable and resilient.
Assessing the probability of extremely low wind energy production in Europe at sub-seasonal to seasonal time scales
Authors: Cozian Bastien , Herbert Corentin , Bouchet Freddy
Published: March 2024

The European energy system will undergo major transformations in the coming decades to implement mitigation measures and comply with the Paris Agreement. In particular, the share of weather-dependent wind generation will increase significantly in the European energy mix. The most extreme fluctuations of the production at all time scales need to be taken into account in the design of the power system. In particular, extreme long-lasting low wind energy production events constitute a specific challenge, as most flexibility solutions do not apply at time scales beyond a few days. However, the probability and amplitude of such events has to a large extent eluded quantitative study so far due to lack of sufficiently long data. In this letter, using a 1000-year climate simulation, we study rare events of wind energy production that last from a few weeks to a few months over the January–February period, at the scale of a continent (Europe) and a country (France). The results show that the fluctuations of the capacity factor over Europe exhibit nearly Gaussian statistics at all time scales. A similar result holds over France for events longer than about two weeks and return times up to a few decades. In that case, the return time curves follow a universal curve. Furthermore, a simple Gaussian process with the same covariance structure as the data gives good estimates of the amplitude of the most extreme events. This method allows to estimate return times for rare events from shorter but more accurate data sources. We demonstrate this possibility with reanalysis data.
Reply to Comment on ‘Anomalous diffusion originated by two Markovian hopping-trap mechanisms’
Authors: Vitali S , Paradisi P , Pagnini G
Published: March 2024

Reply to V P Shkilev.
Fabrication of a tailor-made conductive polyaniline/ascorbic acid-coated nanofibrous mat as a conductive and antioxidant cell-free cardiac patch
Authors: Moradikhah Farzad , Shabani Iman , Tafazzoli Shadpour Mohammad
Published: March 2024

Polyaniline (PANI) was in-situ polymerized on nanofibrous polycaprolactone mats as cell-free antioxidant cardiac patches (CPs), providing electrical conductivity and antioxidant properties. The fabricated CPs took advantage of intrinsic and additive antioxidant properties in the presence of PANI backbone and ascorbic acid as a biocompatible dopant of PANI. The antioxidant nature of CPs may reduce the serious repercussions of oxidative stress, produced during the ischemia-reperfusion (I/R) process following myocardial infarction. The polymerization parameters were considered as aniline (60 mM, 90 mM, and 120 mM), ascorbic acid concentrations ([aniline]:[ascorbic acid] = 3:0, 3:0.5, 3:1, 3:3), and polymerization time (1 h and 3 h). Mainly, the more aniline concentrations and polymerization time, the less sheet resistance was obtained. 1,1 diphenyl-2-picrylhydrazyl (DPPH) assay confirmed the dual antioxidant properties of prepared samples. The advantage of the employed in-situ polymerization was confirmed by the de-doping/re-doping process. Non-desirable groups were excluded based on their electrical conductivity, antioxidant properties, and biocompatibility. The remained groups protected H9c2 cells against oxidative stress and hypoxia conditions. Selected CPs reduced the intracellular reactive oxygen species content and mRNA level of caspase-3 while the Bcl-2 mRNA level was improved. Also, the selected cardiac patch could attenuate the hypertrophic impact of hydrogen peroxide on H9c2 cells. The in vivo results of the skin flap model confirmed the CP potency to attenuate the harmful impact of I/R.
Unbalanced penalization: a new approach to encode inequality constraints of combinatorial problems for quantum optimization algorithms
Authors: Montañez-Barrera J A , Willsch Dennis , Maldonado-Romo A , Michielsen Kristel
Published: March 2024

Solving combinatorial optimization problems of the kind that can be codified by quadratic unconstrained binary optimization (QUBO) is a promising application of quantum computation. Some problems of this class suitable for practical applications such as the traveling salesman problem (TSP), the bin packing problem (BPP), or the knapsack problem (KP) have inequality constraints that require a particular cost function encoding. The common approach is the use of slack variables to represent the inequality constraints in the cost function. However, the use of slack variables considerably increases the number of qubits and operations required to solve these problems using quantum devices. In this work, we present an alternative method that does not require extra slack variables and consists of using an unbalanced penalization function to represent the inequality constraints in the QUBO. This function is characterized by larger penalization when the inequality constraint is not achieved than when it is. We evaluate our approach on the TSP, BPP, and KP, successfully encoding the optimal solution of the original optimization problem near the ground state cost Hamiltonian. Additionally, we employ D-Wave Advantage and D-Wave hybrid solvers to solve the BPP, surpassing the performance of the slack variables approach by achieving solutions for up to 29 items, whereas the slack variables approach only handles up to 11 items. This new approach can be used to solve combinatorial problems with inequality constraints with a reduced number of resources compared to the slack variables approach using quantum annealing or variational quantum algorithms.
Effect of solution treatment on the microstructure, phase transformation behavior and functional properties of NiTiNb ternary shape memory alloys fabricated via laser powder bed fusion in-situ alloying
Authors: Xi Rui , Jiang Hao , Li Guichuan , Zhang Zhihui , Wei Huiliang , Zhao Guoqun , Humbeeck Jan Van , Wang Xiebin
Published: March 2024

Highlights

The feasibility of developing NiTi-X alloys by laser powder bed fusion is exemplified.

Solution treatment was used to enhance the mechanical and functional properties.

Ternary NiTiNb alloys show good tensile properties and wide hysteresis.

The relationship between microstructure and performance was established.
Qudit machine learning
Authors: Roca-Jerat Sebastián , Román-Roche Juan , Zueco David
Published: March 2024

We present a comprehensive investigation into the learning capabilities of a simple d-level system (qudit). Our study is specialized for classification tasks using real-world databases, specifically the Iris, breast cancer, and MNIST datasets. We explore various learning models in the metric learning framework, along with different encoding strategies. In particular, we employ data re-uploading techniques and maximally orthogonal states to accommodate input data within low-dimensional systems. Our findings reveal optimal strategies, indicating that when the dimension of input feature data and the number of classes are not significantly larger than the qudit’s dimension, our results show favorable comparisons against the best classical models. This trend holds true even for small quantum systems, with dimensions d < 5 and utilizing algorithms with a few layers (

L
=
1
,
2

). However, for high-dimensional data such as MNIST, we adopt a hybrid approach involving dimensional reduction through a convolutional neural network. In this context, we observe that small quantum systems often act as bottlenecks, resulting in lower accuracy compared to their classical counterparts.
Efficient interpolation of molecular properties across chemical compound space with low-dimensional descriptors
Authors: Mao Yun-Wen , Krems Roman V
Published: March 2024

We demonstrate accurate data-starved models of molecular properties for interpolation in chemical compound spaces with low-dimensional descriptors. Our starting point is based on three-dimensional, universal, physical descriptors derived from the properties of the distributions of the eigenvalues of Coulomb matrices. To account for the shape and composition of molecules, we combine these descriptors with six-dimensional features informed by the Gershgorin circle theorem. We use the nine-dimensional descriptors thus obtained for Gaussian process regression based on kernels with variable functional form, leading to extremely efficient, low-dimensional interpolation models. The resulting models trained with 100 molecules are able to predict the product of entropy and temperature (S × T) and zero point vibrational energy (ZPVE) with the absolute error under 1 kcal mol−1 for

>

78

% and under 1.3 kcal mol−1 for

>

92

% of molecules in the test data. The test data comprises 20 000 molecules with complexity varying from three atoms to 29 atoms and the ranges of S × T and ZPVE covering 36 kcal mol−1 and 161 kcal mol−1, respectively. We also illustrate that the descriptors based on the Gershgorin circle theorem yield more accurate models of molecular entropy than those based on graph neural networks that explicitly account for the atomic connectivity of molecules.
A case report of recurrent primary posterior mediastinal perivascular epithelioid cell tumour compressing the right inferior pulmonary vein, atria, and inferior vena cava
Authors: Kumar Preetham , Maloney Nolan S , Razzouk Anees , Pai Ramdas G , Varadarajan Padmini
Published: March 2024

Background

Perivascular epithelioid cell tumours (PEComas) are rare soft tissue neoplasms that commonly occur in the uterus, skin, and liver and less commonly in the retroperitoneum, colon, and mediastinum.

Case summary

A 36-year-old male patient with a history of mediastinal PEComa status post resection, essential hypertension, and atrial fibrillation status post appendage ligation currently not on anticoagulation presented with a 1-week history of fevers, chills, productive cough, chest pain, dyspnoea on exertion, loss of appetite, and general weakness. Vital signs, physical exam, laboratory data, electrocardiogram, and chest radiograph were grossly unremarkable. A multimodality imaging approach utilizing transthoracic echocardiogram, transoesophageal echocardiogram (TEE), cardiac magnetic resonance imaging (cMRI), and computed tomography angiography of the chest, abdomen, and pelvis revealed a local 40 mm × 53 mm globular bilobed vascularized scar-free posterior mediastinal mass arising from the roof of the left and right atria and extending superiorly to the main pulmonary artery and inferiorly to the inferior vena cava. Based on the mass’ size and proximity to vital structures and tumour recurrence, the case was presented during tumour board rounds, and the outcome was to surgically resect the mass and then have the patient follow up with medical oncology and radiation oncology for possible chemotherapy and radiation, respectively.

Discussion

Perivascular epithelioid cell tumours are rare, and mediastinal PEComas are even rarer, warranting a multimodality imaging approach involving TEE and cMRI and a multidisciplinary approach involving anaesthesiologists, cardiologists, cardiothoracic surgeons, medical oncologists, pathologists, radiologists, and radiation oncologists.
Is Imitation Really Flattery? The UK’s Trade Continuity Agreements: A Reply to Joris Larik
Authors: Castellarin Emanuel
Published: March 2024

The assessment of the United Kingdom’s (UK) trade continuity programme is open to debate. Joris Larik argues that this programme should be seen as a success both for the UK (although a ‘modest’ one) and for the European Union (EU). However, the significance of the UK’s trade continuity agreements should not be overstated, as the replication of the EU’s trade agreements seems to result above all from pragmatic considerations. It is submitted that this programme cannot be described as a success for the UK and only allows limited conclusions to be drawn about the external influence of the EU’s trade policy.
Strain-specific evolution and host-specific regulation of transposable elements in the model plant symbiont Rhizophagus irregularis
Authors: Oliveira Jordana Inácio Nascimento , Corradi Nicolas
Published: March 2024

Transposable elements (TEs) are repetitive DNA that can create genome structure and regulation variability. The genome of Rhizophagus irregularis, a widely studied arbuscular mycorrhizal fungus (AMF), comprises ∼50% repetitive sequences that include TEs. Despite their abundance, two-thirds of TEs remain unclassified, and their regulation among AMF life stages remains unknown. Here, we aimed to improve our understanding of TE diversity and regulation in this model species by curating repeat datasets obtained from chromosome-level assemblies and by investigating their expression across multiple conditions. Our analyses uncovered new TE superfamilies and families in this model symbiont and revealed significant differences in how these sequences evolve both within and between R. irregularis strains. With this curated TE annotation, we also found that the number of upregulated TE families in colonized roots is 4 times higher than in the extraradical mycelium, and their overall expression differs depending on the plant host. This work provides a fine-scale view of TE diversity and evolution in model plant symbionts and highlights their transcriptional dynamism and specificity during host–microbe interactions. We also provide Hidden Markov Model profiles of TE domains for future manual curation of uncharacterized sequences (https://github.com/jordana-olive/TE-manual-curation/tree/main).
Fibrosis signature of anastomotic margins for predicting anastomotic stenosis in rectal cancer with neoadjuvant chemoradiotherapy and sphincter-preserving surgery
Authors: Liu Zhun , Xu Meifang , Yu Qian , Song Jianyuan , Lin Qili , Huang Shenghui , Chen Zhifen , Huang Ying , Chi Pan
Published: March 2024

Background

Radiation-induced colorectal fibrosis (RICF) is a common pathological alteration among patients with rectal cancer undergoing neoadjuvant chemoradiotherapy (nCRT). Anastomotic stenosis (AS) causes symptoms and negatively impacts patients’ quality of life and long-term survival. In this study, we aimed to evaluate the fibrosis signature of RICF and develop a nomogram to predict the risk of AS in patients with rectal cancer undergoing nCRT.

Methods

Overall, 335 pairs of proximal and distal margins were collected and randomly assigned at a 7:3 ratio to the training and testing cohorts. The RICF score was established to evaluate the fibrosis signature in the anastomotic margins. A nomogram based on the RICF score for AS was developed and evaluated by using the area under the curve, decision curve analysis, and the DeLong test.

Results

The training cohort included 235 patients (161 males [68.51%]; mean age, 59.61 years) with an occurrence rate of AS of 17.4%, whereas the testing cohort included 100 patients (72 males [72.00%]; mean age, 57.17 years) with an occurrence rate of AS of 11%. The RICF total score of proximal and distal margins was significantly associated with AS (odds ratio, 3.064; 95% confidence interval [CI], 2.200–4.268; P < 0.001). Multivariable analysis revealed that the RICF total score, neoadjuvant radiotherapy, and surgical approach were independent predictors for AS. The nomogram demonstrated good discrimination in the training cohort (area under the receiver-operating characteristic curve, 0.876; 95% CI, 0.816–0.937), with a sensitivity of 68.3% (95% CI, 51.9%–81.9%) and a specificity of 85.5% (95% CI, 78.7%–89.3%). Similar results were observed in the testing cohort.

Conclusions

This study results suggest that the RICF total score of anastomotic margins is an independent predictor for AS. The prediction model developed based on the RICF total score may be useful for individualized AS risk prediction in patients with rectal cancer undergoing nCRT and sphincter-preserving surgery.
Commodified State Feminism: The Entanglements of Feminist Commodity Activism and Feminist Politics in a Nordic Welfare State
Authors: Ylöstalo Hanna , Lamberg Emma
Published: March 2024

This article analyzes the entanglements of feminist commodity activism and state feminism. Feminist commodity activism refers to consumption and commodified communication as modes of feminist political participation. Earlier research on these topics has focused on the business sector and on media and popular culture, largely sidelining the state as a site of feminism. This article addresses the increasingly close relations between consumerism and state politics and asks how feminist commodity activism interacts with state feminism. It draws on two empirical cases in the Nordic welfare state of Finland. The first is Uhana Design, a small-scale fashion business, and its Girl Gang campaign that leans on state feminism. The second is Finland's former leading female politicians’ engagements with feminist fashion. By analyzing these cases via three theoretical lenses, business, popular, and state feminism, this article develops the notion of commodified state feminism, paying attention to economic, cultural, and political dimensions of feminist commodity activism and state feminism. It also argues that commodified state feminism is emblematic of the current political context, in which the boundaries between market and politics have become blurred.
Newborn Screening: Current Practice and Our Journey over the Last 60 Years
Authors: Cao Jing , Pasquali Marzia , Jones Patricia M
Published: March 2024

Background

Inborn errors of metabolism comprise a set of more than 2000 known disorders which can result in significant morbidity and may be rapidly fatal. Diagnosing these disorders at birth and treating immediately, however, may often result in a normal to near-normal life for the affected infant. Thus, newborn screening (NBS) has saved or improved the lives of countless individuals since its inception in the 1960s.

Content

This review covers NBS, from its early beginnings up to the current day practice. We follow the evolution of NBS, as well as describe the need and how disorders are added to NBS programs, the testing and how its performance is monitored, and the follow-up to the testing. We also briefly touch on NBS outside the United States.

Newborn screening in the United States is a major public health success story and it continues to grow and evolve to cover more disorders and utilize new technological advances.
Beta-Hebbian Learning to enhance unsupervised exploratory visualizations of Android malware families
Authors: Basurto Nuño , García-Prieto Diego , Quintián Héctor , Urda Daniel , Calvo-Rolle José Luis , Corchado Emilio
Published: March 2024

As it is well known, mobile phones have become a basic gadget for any individual that usually stores sensitive information. This mainly motivates the increase in the number of attacks aimed at jeopardizing smartphones, being an extreme concern above all on Android OS, which is the most popular platform in the market. Consequently, a strong effort has been devoted for mitigating mentioned incidents in recent years, even though few researchers have addressed the application of visualization techniques for the analysis of malware. Within this field, the present work proposes the extension of a new technique called Hybrid Unsupervised Exploratory Plots to visualize Android malware datasets. More precisely, the novel Beta-Hebbian Learning (BHL) method is applied for the first time and validated under the frame of Hybrid Unsupervised Exploratory Plots, in conjunction with clustering methods. The informative visualization achieved provides a picture of the structure of the malware families, allowing subsequent analysis of their organization. To validate the Hybrid Unsupervised Exploratory Plot extension and its tuning, the popular Android Malware Genome dataset has been used in the experimental setting. Promising results have been obtained, suggesting that BHL applied in combination with clustering techniques in Hybrid Unsupervised Exploratory Plots are a viable resource for the visualization of malware families.