bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of national savings on economic development: a focused study on the ten poorest countries in Sub-Saharan Africa
Authors: Ibe Ndukwe 
Published: July 2024

AbstractThe purpose of this study is to examine the impact of national savings on economic development, as measured by the Human Development Index (HDI), Inequality-adjusted HDI (iHDI), and Multidimensional Poverty Index (MPI), in ten of the poorest countries in Sub-Saharan Africa. The study employs a sequential Generalized Method of Moments (GMM) analysis to address potential endogeneity issues and account for the dynamic nature of the relationships, covering the period from 2009 to 2019. The findings reveal a complex relationship between national savings and the selected development indicators. While national savings exhibit positive impacts on HDI and iHDI, the results are not consistently statistically significant across all the sequential models. However, the analysis suggests that national savings have a positive influence on reducing multidimensional poverty, as measured by MPI, particularly when effectively channeled into productive investments. The study also highlights the significant positive impact of government expenditure and foreign direct investment (FDI) on human development, underscoring the importance of strategic public investments and foreign capital. The results suggest that while national savings are crucial, their effective utilization is essential for enhancing human development indices. Strategic investments in public goods and foreign capital are also important. The mixed effects of inflation and official development assistance (ODA) emphasize the need for stable economic policies and effective utilization of foreign aid. The modest positive impact of institutional quality suggests that improvements in governance and institutional frameworks can contribute to human development. The findings underscore the need for policies promoting financial inclusion, efficient public expenditure, foreign direct investment, and stable macroeconomic conditions to leverage national savings for economic development. The study’s findings provide valuable insights for policymakers in Sub-Saharan Africa, highlighting the need for comprehensive strategies that leverage national savings, public expenditure, and foreign investment to drive sustainable economic development and poverty reduction.
Deubiquitinating enzyme mutagenesis screens identify a USP43-dependent HIF-1 transcriptional response
Authors: Pauzaite Tekle , Wit Niek , Seear Rachel V , Nathan James A 
Published: July 2024

AbstractThe ubiquitination and proteasome-mediated degradation of Hypoxia Inducible Factors (HIFs) is central to metazoan oxygen-sensing, but the involvement of deubiquitinating enzymes (DUBs) in HIF signalling is less clear. Here, using a bespoke DUBs sgRNA library we conduct CRISPR/Cas9 mutagenesis screens to determine how DUBs are involved in HIF signalling. Alongside defining DUBs involved in HIF activation or suppression, we identify USP43 as a DUB required for efficient activation of a HIF response. USP43 is hypoxia regulated and selectively associates with the HIF-1α isoform, and while USP43 does not alter HIF-1α stability, it facilitates HIF-1 nuclear accumulation and binding to its target genes. Mechanistically, USP43 associates with 14-3-3 proteins in a hypoxia and phosphorylation dependent manner to increase the nuclear pool of HIF-1. Together, our results highlight the multifunctionality of DUBs, illustrating that they can provide important signalling functions alongside their catalytic roles.
Cytokinetic abscission in Toxoplasma gondii is governed by protein phosphatase 2A and the daughter cell scaffold complex
Authors: Marq Jean-Baptiste , Gosetto Margaux , Altenried Aline , Vadas Oscar , Maco Bohumil , Dos Santos Pacheco Nicolas , Tosetti Nicolò , Soldati-Favre Dominique , Lentini Gaëlle 
Published: July 2024

AbstractCytokinetic abscission marks the final stage of cell division, during which the daughter cells physically separate through the generation of new barriers, such as the plasma membrane or cell wall. While the contractile ring plays a central role during cytokinesis in bacteria, fungi and animal cells, the process diverges in Apicomplexa. In Toxoplasma gondii, two daughter cells are formed within the mother cell by endodyogeny. The mechanism by which the progeny cells acquire their plasma membrane during the disassembly of the mother cell, allowing daughter cells to emerge, remains unknown. Here we identify and characterize five T. gondii proteins, including three protein phosphatase 2A subunits, which exhibit a distinct and dynamic localization pattern during parasite division. Individual downregulation of these proteins prevents the accumulation of plasma membrane at the division plane, preventing the completion of cellular abscission. Remarkably, the absence of cytokinetic abscission does not hinder the completion of subsequent division cycles. The resulting progeny are able to egress from the infected cells but fail to glide and invade, except in cases of conjoined twin parasites.
DiPRO1 distinctly reprograms muscle and mesenchymal cancer cells
Authors: Rich Jeremy , Bennaroch Melanie , Notel Laura , Patalakh Polina , Alberola Julien , Issa Fayez , Opolon Paule , Bawa Olivia , Rondof Windy , Marchais Antonin , Dessen Philippe , Meurice Guillaume , Le-Gall Morgane , Polrot Melanie , Ser-Le Roux Karine , Mamchaoui Kamel , Droin Nathalie , Raslova Hana , Maire Pascal , Geoerger Birgit , Pirozhkova Iryna 
Published: July 2024

AbstractWe have recently identified the uncharacterized ZNF555 protein as a component of a productive complex involved in the morbid function of the 4qA locus in facioscapulohumeral dystrophy. Subsequently named DiPRO1 (Death, Differentiation, and PROliferation related PROtein 1), our study provides substantial evidence of its role in the differentiation and proliferation of human myoblasts. DiPRO1 operates through the regulatory binding regions of SIX1, a master regulator of myogenesis. Its relevance extends to mesenchymal tumors, such as rhabdomyosarcoma (RMS) and Ewing sarcoma, where DiPRO1 acts as a repressor via the epigenetic regulators TIF1B and UHRF1, maintaining methylation of cis-regulatory elements and gene promoters. Loss of DiPRO1 mimics the host defense response to virus, awakening retrotransposable repeats and the ZNF/KZFP gene family. This enables the eradication of cancer cells, reprogramming the cellular decision balance towards inflammation and/or apoptosis by controlling TNF-α via NF-kappaB signaling. Finally, our results highlight the vulnerability of mesenchymal cancer tumors to si/shDiPRO1-based nanomedicines, positioning DiPRO1 as a potential therapeutic target.
2D human skeleton action recognition with spatial constraints
Authors: Wang Lei , Zhang Jianwei , Yang Wenbing , Gu Song , Yang Shanmin 
Published: July 2024

AbstractHuman actions are predominantly presented in 2D format in video surveillance scenarios, which hinders the accurate determination of action details not apparent in 2D data. Depth estimation can aid human action recognition tasks, enhancing accuracy with neural networks. However, reliance on images for depth estimation requires extensive computational resources and cannot utilise the connectivity between human body structures. Besides, the depth information may not accurately reflect actual depth ranges, necessitating improved reliability. Therefore, a 2D human skeleton action recognition method with spatial constraints (2D‐SCHAR) is introduced. 2D‐SCHAR employs graph convolution networks to process graph‐structured human action skeleton data comprising three parts: depth estimation, spatial transformation, and action recognition. The initial two components, which infer 3D information from 2D human skeleton actions and generate spatial transformation parameters to correct abnormal deviations in action data, support the latter in the model to enhance the accuracy of action recognition. The model is designed in an end‐to‐end, multitasking manner, allowing parameter sharing among these three components to boost performance. The experimental results validate the model's effectiveness and superiority in human skeleton action recognition.
Induction de proximité et dégradation de cibles thérapeutiques par les nouveaux dégradeurs : quels concepts, quels développements, quel futur ?
Authors: Reboud-Ravaux Michèle 
Published: July 2024

La recherche dans le domaine de la dégradation ciblée des protéines s’est considérablement développée conduisant à l’élaboration de nouveaux outils chimiques à visée thérapeutique, les dégradeurs, potentiellement utiles dans diverses pathologies. Une grande variété d’objets à dégrader appartenant à divers compartiments intra- ou extracellulaires (protéines, complexes ou agrégats, organelles, acides nucléiques, gouttelettes lipidiques) a été ciblée à l’aide de ligands déjà existants, d’autres restent à découvrir. Les molécules de première génération, PROTAC et colles moléculaires, utilisent le système ubiquitine-protéasome pour détruire spécifiquement des protéines pathogéniques, certaines considérées jusqu’à présent comme inaccessibles en tant que cibles thérapeutiques. Au cours des cinq dernières années, ont été développés de nouveaux types de PROTAC hétéro-bifonctionnels comme les homo-PROTAC, pro-PROTAC, CLIPTAC, HaloPROTAC, PHOTOTAC, Bac-PROTAC, mais aussi des PROTAC macromoléculaires comme les AbTAC et ARN-PROTAC. Du fait de la grande diversité des substrats dégradés par les lysosomes, de nouveaux dégradeurs impliquant deux voies distinctes ont été ensuite produits : les chimères LYTAC pour la voie endosome-lysosome et les chimères ATTEC, AUTAC et AUTOTAC pour la voie autophagie-lysosome, augmentant ainsi considérablement le champ d’action des dégradeurs. Ces nouvelles molécules reconnaissent spécifiquement des protéines et/ou des organelles et permettent leur transport dans les lysosomes où ils sont dégradés. Les succès obtenus, que ce soit par dégradation protéasomale ou lysosomale pour plusieurs dizaines de dégradeurs (preuves de concepts et études cliniques en cours), expliquent l’intérêt quasi mondial des industries pharmaceutiques pour ces nouvelles molécules. Les challenges posés par leur développement et leur utilisation en clinique sont discutés.
Antithrombotic Therapy in Cancer Patients with Cardiovascular Diseases: Daily Practice Recommendations by the Hemostasis Working Party of the German Society of Hematology and Medical Oncology (DGHO) and the Society for Thrombosis and Hemostasis Research (GTH e.V.)
Authors: Parmentier Stefani , Koschmieder Steffen , Henze Larissa , Griesshammer Martin , Matzdorff Axel , Bakchoul Tamam , Langer Florian , Alesci Rosa Sonja , Duerschmied Daniel , Thomalla Goetz , Riess Hanno 
Published: July 2024

AbstractActive cancer by itself but also chemotherapy is associated with an increased risk of cardiovascular disease (CVD) and especially coronary artery disease (CAD) and atrial fibrillation (AF). The frequency of CVD, CAD, and AF varies depending on comorbidities (particularly in older patients), cancer type, and stage, as well as the anticancer therapeutic being taken. Many reports exist for anticancer drugs being associated with CVD, CAD, and AF, but robust data are often lacking. Because of this, each patient needs an individual structured approach concerning thromboembolic and bleeding risk, drug–drug interactions, as well as patient preferences to evaluate the need for anticoagulation therapy and targeting optimal symptom control. Interruption of specific cancer therapy should be avoided to reduce the potential risk of cancer progression. Nevertheless, additional factors like thrombocytopenia and anticoagulation in the elderly and frail patient with cancer cause additional challenges which need to be addressed in daily clinical management. Therefore, the aim of these recommendations is to summarize the available scientific data on antithrombotic therapy (both antiplatelet and anticoagulant therapy) in cancer patients with CVD and in cases of missing data providing guidance for optimal careful decision-making in daily routine.
Graphene Schottky barrier diode acting as a semi-transparent contact to n-GaN
Authors: Kruszewski P. , Sai P. , Krajewska A. , Sakowski K. , Ivonyak Y. , Jakiela R. , Plesiewicz J. , Prystawko P. 
Published: July 2024

In this letter, we demonstrate the successful development of graphene Schottky barrier diodes (Gr SBDs), which act as an efficient semi-transparent contact to n-GaN. We show that Gr SBDs can be used for deep trap investigations in n-GaN by capacitance-based spectroscopic techniques. To demonstrate its functionality, Gr Schottky barrier diodes on an n-GaN sample grown by the metal organic vapor phase technique were fabricated and then used in the measurements of steady-state photo-capacitance (SSPC) and deep level optical spectroscopy (DLOS). It is shown that the SSPC and DLOS spectra obtained for Gr SBDs are in excellent agreement with Ni-based semi-transparent contacts to n-GaN used in this study for comparison. Deep trap levels located at Ec-3.3 eV, Ec-2.6 eV, and Ec-1.84 eV for Ni SBD and Ec-3.3 eV and Ec-2.6 eV for Gr SBD were found, respectively. The presence of a trap level with Ec-1.84 eV observed only in the Ni SBD samples suggests that this trap originates from different sample treatments prior to Schottky contact deposition. Additionally, the optical capture cross-section data (σ0) derived from DLOS were fitted using the Lucovsky model under the assumption of no lattice relaxation for all deep traps observed in this study. Discrepancies in trap concentration derived from SSPC measurements among different diodes for a trap with EC-3.3 eV were attributed to reduced light transmission through the Gr contact in the UV spectral range and the presence of some macroscopic defects related to Gr transfer to the n-GaN film.
Research on thermomechanical effects and influencing factors in high voltage cable under multiphysics field coupling
Authors: Yang Fan , Zhao Jian , Xia Rong , Wang Shaohua , Cao Junping 
Published: July 2024

The interior of a high-voltage cable causes a state of extrusion due to thermomechanical effects; the resulting stress and deformation can easily lead to the destruction of the cable structure. Aiming at the problem, we establish an electromagnetic–thermal–force field model of a high voltage cable. By considering the influence of temperature on the material properties, a bidirectional couple simulation of electromagnetic and thermal fields is established. The thermal load excitation is introduced into the structural field, and the simulation calculation of thermal strain and thermal stress of the axial and radial layers is realized. The influence of ambient temperature, load current, and circulating current defect factors on the thermal–force characteristics of each layer of the cable is studied. The results show that the response of the insulating layer to the thermomechanical effect is the most significant, and its characteristic change law shows the nonlinear trend. In addition, the thermal strain of the cable has an approximate axial symmetry; the axial thermomechanical effect is significantly higher than the radial direction. The maximum axial and radial deformations of the cable when running at full load are 1.21 and 0.16 mm respectively. Among the three influencing factors, the impact of circulating current defects on the thermomechanical effect of cables is the most obvious. The thermomechanical effect of the cable approximately is positively related to the square of the circulating current defect factors, the load current, and the ambient temperature.
Tool wear prediction based on kernel principal component analysis and least square support vector machine
Authors: Gao Kangping , Xu Xinxin , Jiao Shengjie 
Published: July 2024

Abstract
To accurately predict the amount of tool wear in the machining process, a monitoring model of tool wear based on multi-sensor information feature fusion is proposed. First, by collecting the cutting force, vibration, and acoustic emission signals of the tool during the whole life cycle, the multi-domain characteristics of the signal are extracted; then, kernel principal component analysis is used to reduce the dimensionality of the extracted data, and the principal components whose cumulative contribution ratio exceeds 85% are obtained. The redundant features with little correlation with tool wear were removed from the feature vectors to generate the fusion features. Finally, the fusion features are input into the least squares support vector machine model optimized by particle swarm algorithm for regression prediction of tool wear. The non-linear mapping relationship between the physical signal and the tool wear is discovered, which effectively realizes the prediction of the tool wear. Compared with the existing tool wear prediction methods, the method proposed has higher prediction accuracy.
Remaining useful life prediction method based on stacked autoencoder and generalized wiener process for degrading bearing
Authors: Chen Zhe , Li Yonghua , Gong Qi , Wang Denglong , Yin Xuejiao 
Published: July 2024

Abstract
Remaining useful life (RUL) prediction using deep learning networks primarily produces point estimates of RUL, but capturing the inherent uncertainty in RUL prediction is difficult. The use of the stochastic process approach can reflect the uncertainty in RUL predictions. However, the amount of data generated during equipment operation cannot be effectively utilized. This paper aims to propose an adaptive RUL prediction method tailored for extensive datasets and prediction uncertainty, effectively harnessing the strengths of deep learning methods in managing massive data and stochastic process techniques in quantifying uncertainties. RUL prediction method, based on stacked autoencoder (SAE) combined with Generalized Wiener Process, employs SAE to extract profound underlying features from the monitoring signals. Principal component analysis (PCA) is then used to select highly trending features as inputs. The output of PCA accurately reflects health status. A Generalized Wiener Process is used to construct a model for the evolution of the health indicators. The estimation values for the model parameters are determined using the Maximum Likelihood Estimation method. Furthermore, an adaptive update is performed based on Bayesian theory. Utilizing the sense of the first hitting time concept, the Probability Density Function for RUL prediction is derived accurately. Finally, the effectiveness and superiority of the proposed method is verified using numerical simulations and experimental studies of bearing degradation data. The method improves the life prediction accuracy while reducing the prediction uncertainty.
Unsupervised method for detecting surface defects in steel based on joint optimization of pseudo-labeling and clustering
Authors: Bai Dongxu , Li Gongfa , Jiang Du , Jiang Guozhang , Hao Zhiqiang , Zhou Dalin , Ju Zhaojie 
Published: July 2024

Abstract
Advances in the field of measurement science and technology have improved the detection of defects in industrial production. One of the key challenges in steel plate surface defect detection is the need to quickly detect a small number of defects in an overwhelmingly defect-free sample. Unlike supervised learning, which relies heavily on precise sample labeling, unsupervised learning leverages its inherent learning capabilities for detection. This paper introduces an innovative method for smart steel diagnosis, integrating joint optimization of feature extraction and clustering. The proposed approach merges mini-batch K-means clustering with a feature extraction network to acquire pseudo-label information for current images. It employs a multi-view transformation strategy, enabling classification through the optimized feedback from pseudo-labels. This method allows the network to self-optimize the distinction of image features through backpropagation. The method exhibits a mere 4% classification failure rate for steel surface images. This significant reduction in additional data processing requirements enhances the inspection system’s efficiency and accuracy. Furthermore, the versatility of this method extends beyond steel defect diagnosis. It holds potential for application in various engineering domains, particularly in scenarios characterized by data imbalance.
Three-dimensional surface temperature measurement using lifetime-based phosphor thermometry
Authors: Cai Tao , Fu Ruiyu , Luan Di , Liu Yingzheng , Peng Di 
Published: July 2024

Abstract
In this study, we propose a three-dimensional (3D) surface temperature measurement method based on the principle of stereoscopic 3D reconstruction and the dependence of phosphorescence lifetime on temperature. A 385 nm UV light was used as the excitation light, and two high-speed cameras were used as the detectors. The phosphor MFG (Mg4FGeO6: Mn4+) was mixed with the binder HPC and sprayed onto the tested 3D surface. The natural texture generated by the surface roughness of the phosphor coating was used as a feature for cross-correlation calculations. The digital image correlation algorithm was used to match these feature positions in the phosphorescent images from the two cameras. The effects of the excitation angle and detecting angle were analyzed. The results indicate that the temperature measurement based on phosphorescent lifetime was not affected by the excitation and detecting angle. The method was validated on a turbine blade as an example of a 3D surface to demonstrate the capability. A comparison of the measurement results with the thermocouples proves that the current method can successfully measure the temperature on 3D surfaces with a maximum difference of 1.63 °C. The spatial accuracy of the method was obtained by comparing with the measurement results of a 3D scanner, which shows that the maximum absolute error of the 3D reconstruction was 0.350 mm. The current study proposes a promising 3D surface temperature measurement method, which is expected to be widely used in gas turbine blades, Internal Combustion engine cylinders, complex curved heat exchangers, and other fields due to its non-contact measurement, low susceptibility to infrared radiation interference, high measurement accuracy, and ability to withstand harsh environments.
Construction of GSH-responsive polyethyleneimine-based delivery vector for effective gene transfection
Authors: Kou Fang , Wang Wei , Zhu Xiaohong , Han Tian-Yan , Shi Yajun , Zhang Bang-Le 
Published: July 2024

Abstract
The rise of gene therapy has solved many diseases that cannot be effectively treated by conventional methods. Gene vectors is very important to protect and deliver the therapeutic genes to the target site. Polyethyleneimine (PEI) modified with mannitol could enhance the gene transfection efficiency reported by our group previously. In order to further control and improve the effective gene release to action site, disulfide bonds were introduced into mannitol-modified PEI to construct new non-viral gene vectors PeiSM. The degrees of mannitol linking with disulfide bonds were screened. Among them, moderate mannitol-modified PEI with disulfide bonds showed the best transfection efficiency, and significantly enhanced long-term systemic transgene expression for 72 h in vivo even at a single dose administration, and could promote caveolae-mediated uptake through up-regulating the phosphorylation of caveolin-1 and increase the loaded gene release from the nanocomplexes in high glutathione intracellular environment. This functionalized gene delivery system can be used as an potential and safe non-viral nanovector for further gene therapy.