bluuebunny/crossref_metadata_2025_split huggingface dataset:
Field-assisted machining of difficult-to-machine materials
Authors: Zhang Jianguo , Zheng Zhengding , Huang Kai , Lin Chuangting , Huang Weiqi , Chen Xiao , Xiao Junfeng , Xu Jianfeng 
Published: February 2024

Abstract
Difficult-to-machine materials (DMMs) are extensively applied in critical fields such as aviation, semiconductor, biomedicine, and other key fields due to their excellent material properties. However, traditional machining technologies often struggle to achieve ultra-precision with DMMs resulting from poor surface quality and low processing efficiency. In recent years, field-assisted machining (FAM) technology has emerged as a new generation of machining technology based on innovative principles such as laser heating, tool vibration, magnetic magnetization, and plasma modification, providing a new solution for improving the machinability of DMMs. This technology not only addresses these limitations of traditional machining methods, but also has become a hot topic of research in the domain of ultra-precision machining of DMMs. Many new methods and principles have been introduced and investigated one after another, yet few studies have presented a comprehensive analysis and summarization. To fill this gap and understand the development trend of FAM, this study provides an important overview of FAM, covering different assisted machining methods, application effects, mechanism analysis, and equipment design. The current deficiencies and future challenges of FAM are summarized to lay the foundation for the further development of multi-field hybrid assisted and intelligent FAM technologies.
Functional microfluidics: theory, microfabrication, and applications
Authors: Xie Mingzhu , Zhan Ziheng , Li Yinfeng , Zhao Junkai , Zhang Ce , Wang Zhaolong , Wang Zuankai 
Published: February 2024

Abstract
Microfluidic devices are composed of microchannels with a diameter ranging from ten to a few hundred micrometers. Thus, quite a small (10−9–10−18 l) amount of liquid can be manipulated by such a precise system. In the past three decades, significant progress in materials science, microfabrication, and various applications has boosted the development of promising functional microfluidic devices. In this review, the recent progress on novel microfluidic devices with various functions and applications is presented. First, the theory and numerical methods for studying the performance of microfluidic devices are briefly introduced. Then, materials and fabrication methods of functional microfluidic devices are summarized. Next, the recent significant advances in applications of microfluidic devices are highlighted, including heat sinks, clean water production, chemical reactions, sensors, biomedicine, capillaric circuits, wearable electronic devices, and microrobotics. Finally, perspectives on the challenges and future developments of functional microfluidic devices are presented. This review aims to inspire researchers from various fields—engineering, materials, chemistry, mathematics, physics, and more—to collaborate and drive forward the development and applications of functional microfluidic devices, specifically for achieving carbon neutrality.
A walking soft robot driven by electromagnetism inside the body
Authors: Zhu Yongqiang , Guo Qiang , Zhang Yuhan , Zhu Junru , Zhang Pingxia , Gao Mingming , Li Donglin , Liu Hao 
Published: February 2024

Abstract
Existing magnetically driven soft robots mainly rely on external electromagnetic, leading to a substantial energy consumption due to the requirement of a large external magnetic field. Moreover, the precise control of these soft robots relies on electric current, making them highly susceptible to disturbances and deviations induced by minute variations in the current. To overcome these challenges, we propose and evaluate a novel approach employing a miniature walking soft robot empowered by its internal electromagnets. The overall robot size is 18 mm × 6 mm × 12 mm (length × height× width). This design enables the robot to achieve precise and stable motion using a 240-mA current with a 6 V low voltage. In addition, the incorporation of specially designed sheet-leg mechanism with varying degrees of friction facilitates the transformation of linear motion into an effective forward gait. This paper outlines the principles and control strategies of the robot, illustrates the robot fabrication process, at the same time verifies the structural integrity through experimental validation. Further evaluations include comprehensive analysis of the robot’s gait and speed. The results show that the robot attains a speed of 2.86 mm s–1. This study marks a stride towards the realization of a fully autonomous, unrestrained, cost-effective, and energy-conserving magnetic soft robot.
Equivalent linearization of hyperelastic rubber rings in dynamic vibration absorber boring bar and simulation of its dynamic properties
Authors: Shi Haizhao , Ma Chicheng , Li Xinye , Wang Gang 
Published: February 2024

Abstract
A slight perturbation in high-speed precision cutting could cause violent vibration of boring bars, resulting in unexpected wear and failure of the structures. In this paper, the dynamical characteristic of a boring bar with a dynamic vibration absorber (DVA) is investigated. Considering that the nonlinear characteristics of the rubber ring play a significant role in improving the capacity of DVA, we proposed an equivalent linearization method for modeling hyperelastic rubber rings based on the experimental data of uniaxial tensile test. The relationship between the stiffness of rubber rings and the precompression parameter δ is established for two types of rubber. The equivalent linearization model shows good accuracy and calculation efficiency while the mass of the DVA is confined to a narrow space and the assumption of small strain is inherently satisfied. Numerical results show that the time cost of the equivalent linearization model is only 5% of the full hyperelastic model. Furthermore, the effect of different spring stiffnesses and damping on the dynamic characteristics of the boring bar is compared by using the equivalent linearization model, and the vibration peak of the DVA boring bar is found to be reduced about 45%. Our findings establish a simplified modeling scheme for choosing rubber rings in design of dynamic vibration absorbers with acceptable accuracy and little time cost, which could also give some reference for modeling of metal rubber and gel-like materials.
Changes in Northern Hemisphere extra-tropical cyclone frequency following volcanic eruptions
Authors: Andreasen L S , Cornér J , Abbott P M , Sinclair V A , Riede F , Timmreck C 
Published: February 2024

Abstract
Explosive volcanic eruptions are well known to influence Earth’s temperature. Changes in Earth’s temperature can affect temperature gradients which in turn could affect the isentropic slope and hence Northern Hemisphere high and mid-latitude weather. Yet, the possible influence of volcanic eruptions on these atmospheric circulation patterns and the potential spatial extent are not well understood. To address this issue, we pursue two independent lines of evidence. Firstly, we simulate volcanic eruptions with the MPI-ESM1.2 Earth System Model and use the TRACK algorithm to explore how extra-tropical cyclone (ETC) frequency is affected in the model experiments. Secondly, we query the Greenland ice core NEEM-2011-S1 for indications of increased Northern Hemisphere ETC frequency correlating with evidence for explosive volcanism by comparing the storm proxies sodium and calcium; with the eruption proxy sulphur. Both the model and proxy evidence suggest that large explosive volcanic eruptions increase storminess around the location of the ice core. Furthermore, the simulations indicate that the number of ETCs increases in the subtropics and at high latitudes, while they decrease in the mid-latitudes. A detailed interrogation of the simulated eruptions reveals that increases in cyclone frequency are linked to steepening of the isentropic slope due to a larger meridional temperature gradient and to a lower tropopause. The steepening is driven by a combination of warming of the tropical stratosphere from absorption of longwave radiation by volcanic aerosols and surface cooling due to the scattering of sunlight by the same aerosols, whereas the lower tropopause may be attributed to a warmer stratosphere.
Algebraic cobordism and a Conner–Floyd isomorphism for algebraic K-theory
Authors: Annala Toni , Hoyois Marc , Iwasa Ryomei 
Published: February 2024

We formulate and prove a Conner–Floyd isomorphism for the algebraic K-theory of arbitrary qcqs derived schemes. To that end, we study a stable

∞
\infty

-category of non-

A

1

\mathbb {A}^1

-invariant motivic spectra, which turns out to be equivalent to the

∞
\infty

-category of fundamental motivic spectra satisfying elementary blowup excision, previously introduced by the first and third authors. We prove that this

∞
\infty

-category satisfies

P

1

\mathbb {P}^1

-homotopy invariance and weighted

A

1

\mathbb {A}^1

-homotopy invariance, which we use in place of

A

1

\mathbb {A}^1

-homotopy invariance to obtain analogues of several key results from

A

1

\mathbb {A}^1

-homotopy theory. These allow us in particular to define a universal oriented motivic

E

∞

\mathbb {E}_\infty

-ring spectrum

M
G
L

\mathrm {MGL}

. We then prove that the algebraic K-theory of a qcqs derived scheme

X
X

can be recovered from its

M
G
L

\mathrm {MGL}

-cohomology via a Conner–Floyd isomorphism
\[

M
G
L

∗
∗

(
X
)

⊗

L

Z

[

β

±
1

]
≃

K

∗
∗

(
X
)
,

\mathrm {MGL}^{**}(X)\otimes _{\mathrm {L}{}}\mathbb {Z}[\beta ^{\pm 1}]\simeq \mathrm {K}{}^{**}(X),

\]
where

L

\mathrm {L}{}

is the Lazard ring and

K

p
,
q

(
X
)
=

K

2
q
−
p

(
X
)

\mathrm {K}{}^{p,q}(X)=\mathrm {K}{}_{2q-p}(X)

. Finally, we prove a Snaith theorem for the periodized version of

M
G
L

\mathrm {MGL}

.
Fermented botanical fertilizer controls bacterial wilt of tomatoes caused by Ralstonia pseudosolanacearum
Authors: Hida Akiko , Okano Nanako , Tadokoro Chika , Fukunishi Myuji , Ahmed Asmaa Ali , Takenaka Kohei , Tateuchi Yusuke , Fujioka Kotaro , Torii Hideto , Tajima Takahisa , Kato Junichi 
Published: February 2024

ABSTRACT
This study demonstrates the effect of fermented botanical product (FBP) on Ralstonia pseudosolanacearum-induced bacterial wilt disease and unravels its action mechanism. Soaking with diluted FBP solutions (0.1%-0.5%) significantly suppressed bacterial wilt in tomato plants, and FBP-treated tomato plants grew well against R. pseudosolanacearum infection. Growth assays showed that FBP had no antibacterial effect but promoted R. pseudosolanacearum growth. In contrast, few or no R. pseudosolanacearum cells were detected in aerial parts of tomato plants grown in FBP-soaked soil. Subsequent infection assays using the chemotaxis-deficient mutant (ΔcheA) or the root-dip inoculation method revealed that FBP does not affect pathogen migration to plant roots during infection. Moreover, FBP-pretreated tomato plants exhibited reduced bacterial wilt in the absence of FBP. These findings suggest that the plant, but not the pathogen, could be affected by FBP, resulting in an induced resistance against R. pseudosolanacearum, leading to a suppressive effect on bacterial wilt.
ChemMORT: an automatic ADMET optimization platform using deep learning and multi-objective particle swarm optimization
Authors: Yi Jia-Cai , Yang Zi-Yi , Zhao Wen-Tao , Yang Zhi-Jiang , Zhang Xiao-Chen , Wu Cheng-Kun , Lu Ai-Ping , Cao Dong-Sheng 
Published: February 2024

Abstract
Drug discovery and development constitute a laborious and costly undertaking. The success of a drug hinges not only good efficacy but also acceptable absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties. Overall, up to 50% of drug development failures have been contributed from undesirable ADMET profiles. As a multiple parameter objective, the optimization of the ADMET properties is extremely challenging owing to the vast chemical space and limited human expert knowledge. In this study, a freely available platform called Chemical Molecular Optimization, Representation and Translation (ChemMORT) is developed for the optimization of multiple ADMET endpoints without the loss of potency (https://cadd.nscc-tj.cn/deploy/chemmort/). ChemMORT contains three modules: Simplified Molecular Input Line Entry System (SMILES) Encoder, Descriptor Decoder and Molecular Optimizer. The SMILES Encoder can generate the molecular representation with a 512-dimensional vector, and the Descriptor Decoder is able to translate the above representation to the corresponding molecular structure with high accuracy. Based on reversible molecular representation and particle swarm optimization strategy, the Molecular Optimizer can be used to effectively optimize undesirable ADMET properties without the loss of bioactivity, which essentially accomplishes the design of inverse QSAR. The constrained multi-objective optimization of the poly (ADP-ribose) polymerase-1 inhibitor is provided as the case to explore the utility of ChemMORT.
BiGATAE: a bipartite graph attention auto-encoder enhancing spatial domain identification from single-slice to multi-slices
Authors: Tao Yuhao , Sun Xiaoang , Wang Fei 
Published: February 2024

Abstract
Recent advancements in spatial transcriptomics technology have revolutionized our ability to comprehensively characterize gene expression patterns within the tissue microenvironment, enabling us to grasp their functional significance in a spatial context. One key field of research in spatial transcriptomics is the identification of spatial domains, which refers to distinct regions within the tissue where specific gene expression patterns are observed. Diverse methodologies have been proposed, each with its unique characteristics. As the availability of spatial transcriptomics data continues to expand, there is a growing need for methods that can integrate information from multiple slices to discover spatial domains. To extend the applicability of existing single-slice analysis methods to multi-slice clustering, we introduce BiGATAE (Bipartite Graph Attention Auto Encoder) that leverages gene expression information from adjacent tissue slices to enhance spatial transcriptomics data. BiGATAE comprises two steps: aligning slices to generate an adjacency matrix for different spots in consecutive slices and constructing a bipartite graph. Subsequently, it utilizes a graph attention network to integrate information across different slices. Then it can seamlessly integrate with pre-existing techniques. To evaluate the performance of BiGATAE, we conducted benchmarking analyses on three different datasets. The experimental results demonstrate that for existing single-slice clustering methods, the integration of BiGATAE significantly enhances their performance. Moreover, single-slice clustering methods integrated with BiGATAE outperform methods specifically designed for multi-slice integration. These results underscore the proficiency of BiGATAE in facilitating information transfer across multiple slices and its capacity to broaden the applicability and sustainability of pre-existing methods.
preon: Fast and accurate entity normalization for drug names and cancer types in precision oncology
Authors: Ermshaus Arik , Piechotta Michael , Rüter Gina , Keilholz Ulrich , Leser Ulf , Benary Manuela 
Published: February 2024

Abstract

Motivation
In precision oncology (PO), clinicians aim to find the best treatment for any patient based on their molecular characterization. A major bottleneck is the manual annotation and evaluation of individual variants, for which usually a range of knowledge bases are screened. To incorporate and integrate the vast information of different databases, fast and accurate methods for harmonizing databases with different types of information are necessary. An essential step for harmonization in PO includes the normalization of tumor entities as well as therapy options for patients.

Summary
preon is a fast and accurate library for the normalization of drug names and cancer types in large-scale data integration.

Availability and implementation
preon is implemented in Python and freely available via the PyPI repository. Source code and the data underlying this article are available in GitHub at https://github.com/ermshaua/preon/.
Bioframe: operations on genomic intervals in Pandas dataframes
Authors:   Open2C, Abdennur Nezar , Fudenberg Geoffrey , Flyamer Ilya M , Galitsyna Aleksandra A , Goloborodko Anton , Imakaev Maxim , Venev Sergey 
Published: February 2024

Abstract

Motivation
Genomic intervals are one of the most prevalent data structures in computational genome biology, and used to represent features ranging from genes, to DNA binding sites, to disease variants. Operations on genomic intervals provide a language for asking questions about relationships between features. While there are excellent interval arithmetic tools for the command line, they are not smoothly integrated into Python, one of the most popular general-purpose computational and visualization environments.

Results
Bioframe is a library to enable flexible and performant operations on genomic interval dataframes in Python. Bioframe extends the Python data science stack to use cases for computational genome biology by building directly on top of two of the most commonly-used Python libraries, NumPy and Pandas. The bioframe API enables flexible name and column orders, and decouples operations from data formats to avoid unnecessary conversions, a common scourge for bioinformaticians. Bioframe achieves these goals while maintaining high performance and a rich set of features.

Availability and implementation
Bioframe is open-source under MIT license, cross-platform, and can be installed from the Python Package Index. The source code is maintained by Open2C on GitHub at https://github.com/open2c/bioframe.
The pathogenesis of endometriosis and adenomyosis: insights from single-cell RNA sequencing
Authors: Li Qiutong , Shi Jinghua , Yi Dai , Li Xiaoyan , Gu Zhiyue , Yan Hailan , Leng Jinhua 
Published: February 2024

Abstract
Endometriosis and adenomyosis are two similar gynecological diseases that are characterized by ectopic implantation and the growth of the endometrial tissue. Previous studies have reported that they share a common pathophysiology in some respects, such as a similar cellular composition and resistance to the progestogen of lesions, but their underlying mechanisms remain elusive. Emerging single-cell ribonucleic acid sequencing (scRNA-seq) technologies allow for the dissection of single-cell transcriptome mapping to reveal the etiology of diseases at the level of the individual cell. In this review, we summarized the published findings in research on scRNA-seq regarding the cellular components and molecular profiles of diverse lesions. They show that epithelial cell clusters may be the vital progenitors of endometriosis and adenomyosis. Subclusters of stromal cells, such as endometrial mesenchymal stem cells and fibroblasts, are also involved in the occurrence of endometriosis and adenomyosis, respectively. Moreover, CD8+ T cells, natural killer cells, and macrophages exhibit a deficiency in clearing the ectopic endometrial cells in the immune microenvironment of endometriosis. It seems that the immune responses are activated in adenomyosis. Understanding the immune characteristics of adenomyosis still needs further exploration. Finally, we discuss the application of findings from scRNA-seq for clinical diagnosis and treatment. This review provides fresh insights into the pathogenesis of endometriosis and adenomyosis as well as the therapeutic targets at the cellular level.
Limitation of life sustaining therapy in disorders of consciousness: ethics and practice
Authors: Lissak India A , Young Michael J 
Published: February 2024

Abstract
Clinical conversations surrounding the continuation or limitation of life-sustaining therapies (LLST) are both challenging and tragically necessary for patients with disorders of consciousness (DoC) following severe brain injury. Divergent cultural, philosophical and religious perspectives contribute to vast heterogeneity in clinical approaches to LLST—as reflected in regional differences and inter-clinician variability. Here we provide an ethical analysis of factors that inform LLST decisions among patients with DoC.
We begin by introducing the clinical and ethical challenge and clarifying the distinction between withdrawing and withholding life-sustaining therapy. We then describe relevant factors that influence LLST decision-making including diagnostic and prognostic uncertainty, perception of pain, defining a ‘good’ outcome, and the role of clinicians. In concluding sections, we explore global variation in LLST practices as they pertain to patients with DoC and examine the impact of cultural and religious perspectives on approaches to LLST.
Understanding and respecting the cultural and religious perspectives of patients and surrogates is essential to protecting patient autonomy and advancing goal-concordant care during critical moments of medical decision-making involving patients with DoC.