bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Effect of Electrode Angle on the Backward Directional Longitudinal Against Penetration Percentage
Authors: Hafni Hafni , Rifqi  
Published: August 2023

Shielded Metal Arc Welding (SMAW) is one of the liquid welding processes (fusion welding) that produces a homogeneous fusion of the electrode with the base metal (base metal), which is caused by an electric arc that generates high heat to melt the electrode and base metal (base metal). simultaneously and protected by a shielding gas from the chemical reaction of the electrode flux. The depth of fusion formed is determined by the heat input, the electrode angle and the welding direction. The research was conducted at the Mechanical Engineering Laboratory of the Padang Institute of Technology. The base metal used is low carbon steel ST 37 with a thickness of 10 mm and a length of 100 mm. width 100 mm. Welding is carried out on the surface of the base metal in the flat position, the type of connection (weld type) is a surfacing weld with 4 welding lines, each strip having a distance of 20 mm. Weld length 100 mm. AWS E6013 electrode specifications with a diameter of 3.2 mm. SMAW welding machine AC current with a voltage of 30 V. current 85 A. The measured electrode angle between the electrode and the welding line is 75o, 85o, 90o. The backward welding direction where the electrode draws the welding fluid into the welding path and the normal arc height where the distance between the electrode and the base metal is equal to the diameter of the electrode. From the welding results, a penetration presentation will be obtained, namely the ratio of the depth of fusion to the width. The research results obtained welding speed: 2.48 mm/s for electrode angle 75o, 2.49 mm/s for electrode angle 85o and 2.51 mm/s for electrode angle 90o. Heat input for electrode angle 750 is 1015.93 J/ mm , the heat input for the electrode angle 85o is 1024.20 J/mm and the heat input for the electrode angle 90o is 1015.93 J/mm. From the comparison of the width with the depth of fusion, it is obtained; The electrode angle 85o has a penetration presentation of 9.85%, which is better in height than the electrode angle 75o, which has a penetration presentation of 8.43%, and the electrode angle 90o has a penetration presentation of 8.35%..
Measuring income inequality via percentile relativities
Authors: Greselin Francesca , Brazauskas Vytaras , Zitikis Ricardas 
Published: August 2023

Abstract
"The rich are getting richer" implies that the population income distributions are getting more right skewed and heavily tailed. For such distributions, the mean is not the best measure of the center, but the classical indices of income inequality, including the celebrated Gini index, are all mean-based. In view of this, Professor Gastwirth sounded an alarm back in 2014 by suggesting to incorporate the median into the definition of the Gini index, although noted a few shortcomings of his proposed index. In the present paper we make a further step in the modification of classical indices and, to acknowledge the possibility of differing viewpoints, arrive at three median-based indices of inequality. They avoid the shortcomings of the previous indices and can be used even when populations are ultra heavily tailed, that is, when their first moments are infinite. The new indices are illustrated both analytically and numerically using parametric families of income distributions, and further illustrated using capital incomes coming from 2001 and 2018 surveys of fifteen European countries. We also discuss the performance of the indices from the perspective of income transfers.
Twin primes as a consequence of Goldbach's conjecture
Authors: Nunez Hector 
Published: August 2023

Abstract
The binary Goldbach conjecture asserts that every even integer greater than 2 can be expressed as the sum of two primes. In addition, the ternary Goldbach conjecture states that every odd integer greater than 5 is the sum of three primes. Both conjectures originated in an exchange of letters between Leonhard Euler and Christian Goldbach in 1742. We claim that both Goldbach problems are valid and have multiple partitions for every integer greater than 12. We approach the binary Goldbach problem by the Second Principle of Mathematical Induction. Based on the inductive hypothesis, we prove that every even integer within a finite interval can be expressed as the difference between two primes. This fact allows us to tackle the inductive step advantageously. Using the binary and ternary Goldbach problems, we prove that every even integer can be written infinitely many ways as the difference between two primes, where the twin-prime problem is a particular case.
MSC Classification: 11P32 , 11N05
Long-term sustainable development prospects of EU decarbonisation pathways: a multi-model study
Authors: Moreno Jorge , Campagnolo Lorenza , Boitier Baptiste , Nikas Alexandros , Koasidis Konstantinos , Gambhir Ajay , González-Eguino Mikel , Perdana Sigit , de Ven Dirk-Jan van , Chiodi Alessandro , Delpiazzo Elisa , Doukas Haris , Gargiulo Maurizio , Herbst Andrea , Mouël Pierre Le , Vielle Marc 
Published: August 2023

Abstract
Climate action to achieve the Paris Agreement ambitions should also respect the broader UN Sustainable Development Goals. Using an integrated assessment modelling framework with 9 harmonised models, we quantify the impacts of decarbonisation pathways on SDGs in Europe, at continental and national levels. Current climate policies would improve energy- and carbon-related aspects of sustainability (represented by metrics within SDGs 7, 9, 11, 12, and 13), inequalities (metrics within SDGs 1 and 10), and education levels (metrics within SDG 4). More ambitious net-zero emissions pathways would further improve health and agricultural productivity (metrics within SDGs 2 and 3). Furthermore, countries currently lagging in SDG performance would see the greatest benefits from ambitious climate action. Negative socioeconomic impacts from climate action (represented by metrics within SDGs 1, 2, and 8) require remedial policies, notwithstanding that our analysis does not quantify the damages that less ambitious climate policy could do to societies and the SDG Agenda.
Dynamics of growing carbon nanotube interfaces probed by machine learning-enabled molecular simulations
Authors: Hedman Daniel , McLean Ben , Bichara Christophe , Maruyama Shigeo , Larsson J. Andreas , Ding Feng 
Published: August 2023

Abstract

Carbon nanotubes (CNTs), hollow cylinders of carbon1 with diameters in the nanometer range, hold great promise for advanced technologies2–5, provided their structure is controlled and remains uniform throughout their length6–9. Their growth, facilitated by a metal catalyst, takes place at high temperatures across a tube-catalyst interface comprising a few tens of carbon atoms. During growth, the structure, and properties of CNTs are defined but defects can alter them10. These defects are believed to form and heal at the tube-catalyst interface although an understanding of these mechanisms at the atomic-level is still lacking11, 12. Here, using molecular dynamics simulations driven by a machine learning force field13 (MLFF) we developed, DeepCNT-22, we unveil the mechanisms of CNT formation from nucleation to growth including defect formation and healing. We find the tube-catalyst interface to be highly dynamic during growth, with large fluctuations in the chiral structure of the CNT-edge. This contradicts the previous notion of a continuous spiral growth mode14, but confirms that the growing tube edge exhibits significant configurational entropy15. We demonstrate that defects form stochastically at the tube-catalyst interface, however, under low growth rates and high temperatures, healing becomes more efficient than formation, allowing CNTs to grow defect-free to seemingly unlimited lengths. These insights, not readily available via experiments, demonstrate the remarkable power of MLFF-driven simulations and fill long-standing gaps in our understanding of CNT growth mechanisms.
Advances in the use of lignocellulosic biomass aimed at sustainable methyl levulinate production
Authors: Silva Leonete Cristina de Araújo Ferreira Medeiros , Silva Poliana Pinheiro da , Neto Eduardo Lins de Barros , Nascimento Paula Fabiane Pinheiro do , Melo Ricardo Paulo Fonseca , Wendell Francisco , Duarte Lindemberg de Jesus Nogueira 
Published: August 2023

Abstract
Methyl levulinate is a promising chemical in the biofuel industry, as a product with high added value obtained from lignocellulosic biomass valorization. The aim of this review was to present a comprehensive view of the processing of carbohydrates and their derivatives, highlighting recent progress in methyl levulinate production from lignocellulosic biomass. In this respect, scientific production analysis focuses on understanding the synthetic routes of methyl levulinate, identifying the factors that affect operations and types of catalysts being used. In addition, we sought to identify the research trends and advances, as well as the technological development of the processes. Also reported were routes including direct biomass use without pretreatment and levulinic acid esterification. Technological development has sought direct conversions using methanol as cosolvent. Laboratory-scale studies are advanced, but several factors have not been fully elucidated. In addition, broader and more robust large-scale studies are needed. Nevertheless, simulations and research indicate the real possibility of methyl levulinate production in the context of integrated biorefineries.
Can we achieve successful outcome with sirolimus treatment for complicated lymphatic malformations?: A multicenter analysis
Authors: Cho Yu Jeong , Kwon Hyunhee , Ha Suhyeon , Kim Seong Chul , Kim Dae Yeon , Namgoong Jung-Man , Cho Minjeng , Lee Ju Yeon , Jung Eunyoung , Nam So Hyun 
Published: August 2023

Abstract
Background: Sirolimus has emerged as a safe and effective treatment for complicated lymphatic malformations (LMs). We aim to prove the effectiveness and safety of sirolimus as therapeutic option for patients with complicated LMs.
Methods: 58 patients with complicated LMs treated with sirolimus for at least six months in multicenter between July 2018 and January 2023 were enrolled. We reviewed medical records and radiological images. All patients were administered oral sirolimus starting at 0.8mg/m2 every twelve hours, with target serum concentration levels of 8 to 15 ng/mL Evaluation for clinical symptoms and LMs volume on magnetic resonance imaging (MRI) were reviewed to assess treatment response and toxicities. Evaluation of disease response was divided into three values: complete response (CR), partial response (PR-significant, moderate, modest), and progressive disease (PD).
Results: The median age at the initiation of sirolimus treatment was 6.0 years (range, 1 months - 26.7 years). The median duration of treatment was 2.0 years (range, 6 months - 4.4 years). The most common lesions were head and neck (27/58, 46.6%). Two out of five patients weaned tracheostomy after sirolimus treatment. 51 patients (87.9%) demonstrated a reduction in LMs volume on MRI or improvement of clinical symptoms including two of CR. Seven patients (12.1%) showed no response to sirolimus administration. Young age group and the patients who underwent few prior therapies showed better response. Ten patients (17.2%) were taken off the medication secondary to adverse effects, gastrointestinal at nine (15.5%), respiratory at three (5.2%), and skin/appendages at three (5.2%). None of the patients had Grade 3 and higher toxicities attributable to sirolimus.
Conclusions: Oral sirolimus treatment brought successful outcome without severe adverse effects. It could be the first line therapy especially for young age group of complicated LMs, and additional option for refractory lesions which did not respond to conventional treatment.
Where top-down meets bottom-up: Cell-type specific connectivity map of the whisker system
Authors: Rault Nicolas , Bergmans Tido , Delfstra Natasja , Kleijnen Bisley , Zeldenrust Fleur , Celikel Tansu 
Published: August 2023

Abstract
Sensorimotor computation is a closed-loop process where bottom-up information collected about the current state of the world is integrated with top-down, internally generated knowledge, task- and goal-related affordances to create an action plan. In the rodent whisker system, a canonical model of sensorimotor computation in the context of active sensing, emerging evidence suggests that neuromodulatory neurotransmitters help shape sensorimotor control of the whisker position, and contribute to context-dependent changes of whisking frequency and amplitude. Given that neuromodulatory neurotransmitters are primarily released from subcortical nuclei whose long-range projections target the rest of the central nervous system, the circuit mapping of top-down neuromodulatory control of sensorimotor nuclei in the rodent brain will help to address the mechanisms of active sensing systematically. Therefore, taking advantage of the Allen Institute's Mouse Connectivity database, we provide an updated, cell-type specific map of the sensorimotor circuits in the mouse brain. The map includes 180 projections (68 of which were not previously reported in the literature) across 18 principal and neuromodulatory neurotransmitter-releasing nuclei of the whisker system. Performing a graph network analysis of this connectome, we identify cell-type specific hubs, sources, and sinks, provide anatomical evidence for monosynaptic inhibitory projections into all stages of the ascending pathway, and show that neuromodulatory projections improve network-wide connectivity. These results argue that beyond the modulatory chemical contributions to information processing and transfer in the whisker system, the circuit connectivity features of the neuromodulatory networks position them as nodes of sensory and motor integration.
DynamicBind: Predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model
Authors: Lu Wei , Zhang Ji-Xian , Huang Weifeng , Zhang Ziqiao , Jia Xiangyu , Wang Zhenyu , Shi Leilei , Li Chengtao , Wolynes Peter , Zheng Shuangjia 
Published: August 2023

Abstract
While significant advances have been made in predicting static protein structures, the inherent dynamics of proteins, modulated by ligands, are crucial for understanding protein function and facilitating drug discovery. Traditional docking methods, frequently used in studying protein-ligand interactions, typically treat proteins as rigid. While molecular dynamics simulations can propose appropriate protein conformations, they’re computationally demanding due to rare transitions between biologically relevant equilibrium states. In this study, we present DynamicBind, a novel method that employs equivariant geometric diffusion networks to construct a smooth energy landscape, promoting efficient transitions between different equilibrium states. DynamicBind accurately recovers ligand-specific conformations from unbound protein structures without the need for holo-structures or extensive sampling. Remarkably, it demonstrates state-of-the-art performance in docking and virtual screening benchmarks. Our experiments reveal that DynamicBind can accommodate a wide range of large protein conformational changes and identify novel cryptic pockets in unseen protein targets. As a result, DynamicBind shows potential in accelerating the development of small molecules for previously undruggable targets and expanding the horizons of computational drug discovery.
Genetic Predictors of Neurocognitive Outcomes in Survivors of Pediatric Brain Tumors
Authors: Grob Sydney T. , Miller Kristen R. , Sanford Bridget , Donson Andrew M. , Jones Kenneth , Griesinger Andrea M. , Amani Vladimir , Foreman Nicholas K. , Liu Arthur , Handler Michael , Hankinson Todd C. , Milgrom Sarah , Levy Jean Mulcahy 
Published: August 2023

Abstract
Purpose: Neurocognitive deficits are common in pediatric brain tumor survivors. The use of single nucleotide polymorphism (SNP) analysis in DNA repair genes may identify children treated with radiation therapy for brain tumors at increased risk for treatment toxicity and adverse neurocognitive outcomes.
Methods: The Human 660W-Quad v1.0 DNA BeadChip analysis (Illumina) was used to evaluate 1048 SNPs from 59 DNA repair genes in 46 subjects. IQ testing was measured by the Wechsler Intelligence Scale for Children. Linear regression was used to identify the 10 SNPs with the strongest association with IQ scores while adjusting for radiation type.
Results: The low vs high IQ patient cohorts were well matched for time from first treatment to most recent IQ, first treatment age, gender, and treatments received. 5 SNPs on 3 different genes (CYP29, XRCC1, and BRCA1) and on 3 different chromosomes (10, 19, and 17) had the strongest association with most recent IQ score that was not modified by radiation type. Furthermore, 5 SNPs on 4 different genes (WRN, NR3C1, ERCC4, RAD51L1) on 4 different chromosomes (8, 5, 16, 14) had the strongest association with change in IQ independent of radiation type, first IQ, and years between IQ measures.
Conclusions: SNP polymorphisms offer potential to predict adverse neurocognitive outcomes in pediatric brain tumor survivors. Our results require validation in a larger patient cohort. Improving the ability to identify children at risk of treatment related neurocognitive deficits could allow for better treatment stratification and early cognitive interventions.
A Bibliometric Analysis of Trends on Organizational Learning and Organizational Innovation: Future Research and Agenda
Authors: Mohammed  
Published: August 2023

Abstract
Organizational learning and innovation research has received increasing attention from researchers in recent years because it is important for improving performance and increasing competitive advantage, in addition to playing a vital role in helping organizations embrace change, respond to emerging challenges, and seize new opportunities. However, the research subject's development as well as directions in this study field are limited and unclear. Therefore, we conducted a bibliometric analysis of a sample of 773 research articles published over the past 41 years, from March 1982 to March 2023, to explore research directions about organizational learning and innovation through the top contributing and productive Sources, institutions, and countries, the analysis of collaboration networks between authors, and keywords' co-occurrence analysis in three specified periods. Publication output data was determined based on research articles in the Scopus database. The results of the analysis of this study showed that the number of publications related to organizational learning and innovation has witnessed a continuous increase, around 18.85% per year. The United States ranked first in the field of organizational learning and innovation, contributing 21.86% of the total publications. In addition, the " "Universidad de Granada" has been ranked first in terms of overall publication output (16 publications, 2.07%). The focus of researchers in this field expanded during the three phases to include different and new topics. The obtained results of this paper may help academics and practitioners better understand research development trends, and research hotspots in the field of organizational learning and innovation, and provide a comprehensive view of future research.
Assessing flash flood inundation from an extreme rainfall event: case study: Wadi Al Jizzi Oman
Authors: Abushandi Eyad , Al Sarihi Moza , Ibrahim Osama 
Published: August 2023

Abstract
Flash floods present a significant risk to urbanized arid regions, and assessing their inundation patterns is crucial for effective disaster management. Extreme hydrologic events due to aridity and climate change are shaping human lives and major activities in numerous countries at an unprecedented pace. This study aims to assess flash floods from extreme storm events in an arid catchment using high-resolution data. The study applied two models on the event of a single storm, namely the IHACRES and AHP models. The observed flow was used for models' validation. The average flow output determined with the IHACRES model was approximately 0.47 m3/s while the flow output resulting from the AHP model was 0.45 m3/s. The efficiency showed that the IHACRES performed better in evaluating extreme events with an average of 0.88 while the AHP model showed an efficiency of 0.68. The quantitative simulation of both models is likely to have good applicability for simulating single storm events in arid catchments. The validated IHACRES and AHP models offer valuable tools for simulating flash flood. The study's outcomes have implications for flood management policy and infrastructure planning, ensuring a more resilient response to extreme flood events in arid regions globally.
Recent advancement in NiFe2O4-based nanocomposites for the photocatalytic degradation of pollutants in aqueous solutions: a comprehensive systematic review
Authors: Derakhshani Elham , Naghizadeh Ali 
Published: August 2023

AbstractNanocomposites with diameters of 1 to 100 nm have modified properties such as uniform size distribution, small size, high surface-to-volume ratio, high absorbability, porosity, and various potential roles, including in catalytic and biological activities. The purpose of this research study was to systematically review all research studies on the photocatalytic decomposition of pollutants by NiFe2O4-based nanocomposites and evaluate the optimal laboratory conditions and the results of these studies. The present systematic review was conducted by searching Scopus, PubMed and Web of Science databases until March 2022. The parameters of nano catalyst type and size, synthesis methods, pollutant type, optimal pH, optimal initial pollutant concentration, optimal catalyst concentration, optimal time, radiation and removal efficiency were investigated. 454 studies were screened and using the inclusion and exclusion criteria, in total, 31 studies met our inclusion criteria and provided the information necessary to photocatalytic degradation of pollutants by NiFe2O4-based nanocomposites. In the investigated studies, the percentage of photocatalytic degradation of pollutants by NiFe2O4-based nanocomposites was reported to be above 70%, and in some studies, the removal efficiency had reached 100%. From the results of this systematic review, it was concluded that the photocatalytic process using NiFe2O4-based nanocomposites has a high effect on the degradation of aqueous solution pollutants.
How do material characteristics and antimicrobial mechanisms affect microbial control and water disinfection performance of metal nanoparticles?
Authors: Zhao Jinghan , Yan Peihua , Qureshi Aizaz , Chiang Yi Wai 
Published: August 2023

AbstractNanotechnology has been rapidly developing in the past decade, and metal nanomaterials have shown promising improvement in microbial control. Metal nanoparticles have been applied in medical settings for adequate disease spread control and to overcome the challenges of multidrug-resistant microorganisms. Recently, the demand for safe water supply has increased, requiring higher sanitation of the water treatment technology as well as being environmentally sustainable. However, the employed water disinfection technologies cannot meet the elevated demand due to limitations including chemical byproducts, immobility, energy consumption, etc. Metal nanomaterials are considered to be an alternative disinfection technology considering their high efficiency, mobility, and stability. A significant amount of research has been carried out on enhancing the antimicrobial efficiency of metal nanomaterials and determining the underlying antimicrobial mechanisms. This paper provides an overview of emerging metal nanomaterials development, including the synthesis method, material characteristics, disinfection performance, environmental factors, potential mechanism, limitations, and future opportunities in the water disinfection process.