bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recent Advances on Single‐Atom Catalysts for Photocatalytic CO2 Reduction
Authors: Shang Ziang , Feng Xueting , Chen Guanzhen , Qin Rong , Han Yunhu 
Published: August 2023

AbstractThe present energy crisis and environmental challenges may be efficiently resolved by converting carbon dioxide (CO2) into various useful carbon products. The development of more effective catalysts has been the main focus of current research on photocatalytic CO2 reduction. Due to their high atomic efficiency and superior catalytic activity, single‐atom catalysts (SACs) have attracted considerable interest in catalytic CO2 conversion. This review discusses the current research developments, obstacles, and potential of SACs for photocatalytic CO2 reduction. And further, discusses the principle of photocatalytic carbon dioxide reduction. This work has compared and analyzed the effects of support materials and active site types in SACs on photocatalytic CO2 reduction performance. This work believes that by sharing these developments, some inspiration for the rational design and development of stable and effective photocatalytic CO2 reduction catalysts based on SACs can be provided.
A Sewing Approach to the Fabrication of Eco/bioresorbable Electronics
Authors: Wu Yunyun , Rytkin Eric , Bimrose Miles , Li Shupeng , Choi Yeon Sik , Lee Geumbee , Wang Yue , Tang Lichao , Madrid Micah , Wickerson Grace , Chang Jan‐Kai , Gu Jianyu , Zhang Yamin , Liu Jiaqi , Tawfick Sameh , Huang Yonggang , King William P. , Efimov Igor R. , Rogers John A. 
Published: August 2023

AbstractEco/bioresorbable electronics represent an emerging class of technology defined by an ability to dissolve or otherwise harmlessly disappear in environmental or biological surroundings after a period of stable operation. The resulting devices provide unique capabilities as temporary biomedical implants, environmental sensors, and related systems. Recent publications report schemes to overcome challenges in fabrication that follow from the low thermostability and/or high chemical reactivity of the eco/bioresorbable constituent materials. Here, this work reports the use of high‐speed sewing machines, as the basis for a high‐throughput manufacturing technique that addresses many requirements for these applications, without the need for high temperatures or reactive solvents. Results demonstrate that a range of eco/bioresorbable metal wires and polymer threads can be embroidered into complex, user‐defined conductive patterns on eco/bioresorbable substrates. Functional electronic components, such as stretchable interconnects and antennas are possible, along with fully integrated systems. Examples of the latter include wirelessly powered light‐emitting diodes, radiofrequency identification tags, and temporary cardiac pacemakers. These advances add to a growing range of options in high‐throughput, automated fabrication of eco/bioresorbable electronics.
A comprehensive review of generative adversarial networks: Fundamentals, applications, and challenges
Authors: Megahed Mohammed , Mohammed Ammar 
Published: August 2023

AbstractIn machine learning, a generative model is responsible for generating new samples of data in terms of a probabilistic model. Generative adversarial network (GAN) has been widely used to generate realistic samples in different domains and outperforms its peers in the generative models family. However, producing a robust GAN model is not a trivial task because many challenges face the GAN during the training process and impact its performance, affecting the quality and diversity of the generated samples. In this article, we conduct a comprehensive review of GANs to present the fundamentals of GAN, including its components, types, and objective functions. Also, we present an overview of the evaluation matrices used to evaluate GAN models. Moreover, we list the applications of GANs and research work in various domains. Finally, we present the challenges that face GANs and highlight two significant issues, representing mode collapse and training instability, in addition to those research efforts that tackle these challenges.This article is categorized under:
Statistical Learning and Exploratory Methods of the Data Sciences > Deep Learning
Statistical Learning and Exploratory Methods of the Data Sciences > Neural Networks
Failure Analysis of a Conveyor Belt Rail (Tripper) of Mineral
Authors: Fosca Carlos 
Published: August 2023

AbstractA failure analysis of a fractured rail corresponding to a railway conveyor belt (Tripper) that operated in service for two years has been carried out. A visual inspection, chemical composition analysis, metallographic analysis, hardness and microhardness measurements were carried out on the failed piece. The rail was made of 0.89% C carbon steel and presented a decarburized area on the running surface, with strong plastic deformation due to the operation and work hardened. The metallurgical root cause is associated with the presence of pro-eutectoid ferrite and non-metallic inclusions that have been severely deformed by rolling stresses, generating a weak continuous region that nucleated rolling contact fatigue cracks (RCF) and accelerated the formation of a longitudinal crack that propagated vertically (vertical split head) as a consequence of other possible material defects.
Isolation and Characterization of Crystalline Cellulose Nanofibers (CNF’S) from Guadua Angustifolia Kunth (GAK)
Authors: Seminario Jorge Fajardo , Verdugo Carlos O. , Paltan Cesar A. , Zuluaga Robin 
Published: August 2023

AbstractThis work aims to isolate and characterize crystalline cellulose nanofibers from a tropical bamboo named guadua angustifolia. A nanofiber extraction methodology was developed that includes: i) a thermomechanical pretreatment by steam explosion, ii) an acid hydrolysis phase, and iii) a disintegration phase using a supermasscolloid grinder. The nanofibers were evaluated for their morphology (SEM) and (AFM), functional groups (FTIR), thermal degradation (TGA) and crystallinity index (XRD). The diameters of the nanofibers ranged from 20 to 60 nm. FTIR analysis determined an effective removal of functional groups characteristic of non-cellulosic compounds such as lignin and hemicellulose. The nanofibers showed greater thermal stability in relation to the microfibers. The crystallinity index was 75%, evidencing the effectiveness of the methodology to obtain crystalline nanocellulose.
Research into Novel Coatings on Composites and Technical Polymers, with Tailored Functionalities for the Transport and Biomedical Industries
Authors: Velasco Manrique Jorge , González Manuel Ignacio , Alonso Sastre Carlos , Cañibano Álvarez Esteban , Fernández Peña Maria Teresa 
Published: August 2023

AbstractThis work presents the methodology and results of the research into pre-treatments for thermal spray processes, applied to composites and technical polymers, as preparatory stage for the subsequent coating (ceramic and metallic) deposition via wire arc spray process. The research methodology includes the study of the thermal degradation of substrate materials, as well as the execution and characterization of mechanical (sand blasting), laser (surface texturing) and chemical (acid and base etching) pre-treatments. The quality of the proposed solutions is evaluated through visual inspection of the samples, optical micrography, surface roughness measurements, and mechanical adhesion testing of the coating. Finally, the selection of the most appropriate coating pre-treatment is made, considering technical and scalability criteria.
Study and Optimization of a Numerical Algorithm for Hydrodynamic Lubrication Problems with Cavitation
Authors: Gómez Molina Pedro , Carpio Huertas Jaime , Sanz Lorenzo Luis 
Published: August 2023

AbstractWe present a study of a method to solve numerically stationary problems of hydrodynamic lubrication with cavitation in bearings using the finite element method and the method of characteristics. The problem is based on the Elrod-Adams mathematic model for the lubricant fluid behavior. To achieve realistic pressure solutions, cavitation must be considered. However, this leads to a non-linear system of equations including a multivalued operator. To solve this problem, we use the Bermúdez-Moreno algorithm combining its ideas with a mesh intersection technique, known as supermesh, to compute certain integrals exactly, and with other strategies to improve the performance of the iterative method. We have studied the solutions, the precision in mass conservation and the speed of convergence of the method trying to improve it. Results of the simulations are presented and analyzed.
Electricity and Hydrogen Generation from Food and Vegetable Wastes – Technical and Economic Analysis
Authors: Micena Raul Pereira , de Brito Paulo Sérgio Duque , Tuna Celso Eduardo , Silveira José Luz 
Published: August 2023

AbstractThe city of Guaratinguetá, Brazil, produces 104 tons of MSW daily, 45.3% of which is its organic fraction, and the rest is divided between recyclable material and waste without use. This study proposes the calculation of the biogas production potential from the anaerobic digestion of the Organic Fraction of Municipal Solid Waste (OFMSW). This fraction is mainly composed of food residues, such as fruits and vegetables, as well as paper and cardboard, among others, being a compound able to be processed in a biodigester. A production potential of 3,1 Nm3 of biogas per day, or 3,6 kg/day, was calculated. An electricity generation potential of 6.3 MWh/day was calculated. Considering the use of all this electrical potential in a water electrolysis process, a production potential of 107 kg/day of electrolytic hydrogen was calculated. An economic analysis of electricity generation is carried out, resulting in a cost of electricity between 34.7 and 41.2 USD/MWh, depending on the interest rate applied. The payback of the investment in electricity generation was calculated between 3 and 4 years, considering the local electricity tariff of 74 USD/MWh.
Initial Considerations for a P2P Trading Model for Electricity Generated from Photovoltaic Solar Energy Based on Blockchain Technology
Authors: Veikka Sarkkinen , Renó Alex Alcântara , Khosravi Ali , Pabon Juan J. Garcia 
Published: August 2023

AbstractThe article proposed a list and discussion of the aspects that should be considered before implementing Blockchain technology in the renewable energy trade. In the proposed model, electricity is generated by solar energy and uses consumption and production data, among other things, to price electricity in a double auction, in which sellers present their prices and buyers send their bids at the same time. The use of Blockchain technology allows real-time monitoring of consumption and production, and real-time trading where third parties are not needed. It also has the potential to maximize profits from the perspective of prossumidor and minimize electricity losses. Considering Finland, it is already possible to realize that customer segments are delimited in subgroups within cities and requires the involvement of the electricity company, awareness at the state level and inversion in pilot projects.
Competitive Strategies for Renewable Energies: Brazilian Market
Authors: Corrêa Cynthia Siqueira , Maya Diego Mauricio Yepes 
Published: August 2023

AbstractRenewable energy sources are sustainable alternatives for the electrical and energy development of countries. This paper analyzes the different mechanisms applicable to the Brazilian scenario. Brazil has several fronts and has direct policy instruments, such as subsidies and tax incentives, and indirect mechanisms. We analyze the need to expand existing mechanisms, implement new strategies, and improve the dissemination of existing programs to increase public awareness and pursue of a more efficient renewable energy transition. The participation of renewable sources, such as solar and wind, are gaining more and more space in the energy market in Brazil and much of this is due to incentives, such as tax and tariff rebates and long-term contracts. In 2021, the expansion of the Brazilian electric matrix was almost 1 GW (957.03 MW), according to the National Agency of Electrical Energy (ANEEL). Of this total power, 80% comes from renewable plants, from wind, hydro and solar sources.
Cavitation Analysis in Kaplan Turbines at the Yacyretá Hydropower Plant
Authors: Maldonado Liz Esquivel , Benitez Vivian González , Aguilera Fernando Arenas , Fleitas Elías Espínola , Doerksen Jovan Toews , Ratzlaff Patrik Kehler , Suárez Ferdinand Meixner , Cabañas Herminia Duarte , Duré Marcelo Subeldía , Nagasawa Jorge Kurita 
Published: August 2023

AbstractThe cavitation effect occurred during the operation of hydraulic machinery is a widely known and thoroughly studied phenomenon. This research work presents a case study of cavitation analysis that was conducted on the Kaplan turbines at the Yacyretá hydropower plant. This effect was observed during scheduled maintenance routines of the power generating units. These turbines belonged to the Entidad Nacional Yacyretá (EBY) [1]. The cavitation phenomenon could cause significant damage to blades and other turbine components under certain operating conditions [2].
Determination of Tool Wear in Peripheral Milling Operations Based on Acoustic Emission Signals
Authors: Alzugaray-Franz Ricardo , Diez-Cifuentes Eduardo , Leal-Muñoz Erardo , Villaverde-San José Mónica , Vizán-Idoipe Antonio 
Published: August 2023

AbstractIn this work, an indirect approach based on acoustic emission signals is presented to predict progressive tool wear in peripheral milling operations. Measurements of flank wear and cutting forces are considered in order to assess the performance of the method. The acoustic emission is found to be sensitive to changes of tool condition and the evolution of the wear land. The latter provides experimental evidence to support the current knowledge on tool wear estimation towards the definition of tool-life criteria based on indirect process variables.
CT-Based FEM: Assessment of the Influence of Porosity on the Mechanical Behavior and Failure of AM Components
Authors: Pascual Alejandro , Plaza Soraya , Ortega Naiara , Sendino Sara , Martínez Silvia 
Published: August 2023

AbstractThis work aims to present a digital-twin for prediction of the mechanical behavior and failure of additive manufacturing components, considering the characteristics of heterogeneities, mainly porosities, which appear during the manufacturing process. Therefore, the proposed methodology is based on the development of a CT-based FEM model, as well as the study of different porosity features by CT analysis and FEM modelling. Their influence on predictions is also evaluated. To this end, tensile test specimens were manufactured by means of L-PBF, according to ASTM E8/E8M. Afterwards, the analysis and digitalization of each specimen were carried out using CT, followed by FEM modelling of each one. Finally, the results obtained by the analysis were correlated with experimental tensile tests. Taking advantage of the virtual model proposed, virtual cases and hypothesis were also analyzed. Hence, the promising future of the proposed methodology is highlighted.
5-Axis Machining Center OMM Uncertainty Estimation
Authors: González Guillermo , Medina Brayan Eduwars , Ortega Naiara , Plaza Soraya , Gómez Gaizka 
Published: August 2023

AbstractNowadays, on-machine tool measurement (OMM) and coordinate measuring machine measurement (CMM) are the most common inspection methods. Although the ex-situ CMM measurements usually offers higher accuracy and reliability, OMM can inspect the workpiece without removing it from the machine tool. Therefore, it is possible to perform both in-process and post-process measurements, avoiding possible unclamping errors. However, due to the non-constant conditions in which machine tools usually operate, it is difficult to guarantee the traceability of measurements over time. For example, thermal fluctuations become a potential source of uncertainty.This paper presents a methodology for ensuring the traceability of OMM on shop floor conditions. For this purpose, several features of a prismatic workpiece are measured on a five-axis machining center. The measurement results and its corresponding uncertainty budget are presented. For the uncertainty estimation the substitution method based on ISO 15530-3:2011 standard is used. In order to identify the impact of the different error sources on the results, a breakdown of the relative weights of the factors that may have an influence on the uncertainties is also given,
Using Artificial Intelligence to Predict Lubricated Friction in Microtextured Mechanical Contacts
Authors: Franco-Martínez Francisco , Moltó Jorge Juan García , Otero Javier Echávarri , Tanarro Enrique Chacón , Díaz-Lantada Andrés 
Published: August 2023

AbstractIt has been shown that surface microtexturing is useful for improving lubrication. It offers strong reductions in the friction coefficient under operation conditions which compromise the maintenance of full film lubrication. To study the influence of texturing in the reduction of the friction coefficient, an Artificial Intelligence algorithm will be used. Its performance will be optimized. Afterwards, the algorithm will be applied to a new set of textured surfaces with the objective of finding the optimal one, that is, the one capable of reducing friction under different operating conditions. The selection of the optimal texturing will be based on the Weighted Mean Value of the friction coefficient (WMPT), a metric that was specifically created for this purpose.
Autonomous Navigation for an Intelligent Sailboat - Sensailor
Authors: Fajardo-Pruna Marcelo , Sanchez-Orozco Daniela , Torres-Medina Karen , Lopez-Estrada Luis , Tutiven Christian , Vidal Yolanda 
Published: August 2023

AbstractThis article presents the development of an autonomous navigation system for the intelligent sailboat Sensailor. This vehicle will be equipped with a Lidar and a camera for obstacle recognition. The recollected data will allow the sailboat to register the obstacle coordinates and determine the zones for safe navigation. Based on that, the intelligent system will apply AI algorithms for path planning, in order to get the shortest safe trajectory. This way, it will be guaranteed that the Sensailor can translate from an initial to a target position while optimizing time and resources.
Measuring inflaton couplings via primordial gravitational waves
Authors: Barman Basabendu , Ghoshal Anish , Grzadkowski Bohdan , Socha Anna 
Published: August 2023

Abstract
We investigate the reach of future gravitational wave (GW) detectors in probing inflaton couplings with visible sector particles that can either be bosonic or fermionic in nature. Assuming reheating takes place through perturbative quantum production from vacuum in presence of classical inflaton background field, we find that the spectral energy density of the primordial GW generated during inflation becomes sensitive to inflaton-matter coupling. We conclude, obeying bounds from Big Bang Nucleosysthesis and Cosmic Microwave Background, that, e.g., inflaton-scalar couplings of the order of ~ 𝒪(10−20) GeV fall within the sensitivity range of several proposed GW detector facilities. However, this prediction is sensitive to the size of the inflationary scale, nature of the inflaton-matter interaction and shape of the potential during reheating. Having found the time-dependent effective inflaton decay width, we also discuss its implications for dark matter (DM) production from the thermal plasma via UV freeze-in during reheating. It is shown, that one can reproduce the observed DM abundance for its mass up to several PeVs, depending on the dimension of the operator connecting DM with the thermal bath and the associated scale of the UV physics. Thus we promote primordial GW to observables sensitive to feebly coupled inflaton, which is very challenging if not impossible to test in conventional particle physics laboratories or astrophysical measurements.
Non-perturbative effects for dark sectors with QCD portals
Authors: Biondini Simone , Chowdhury Talal Ahmed , Saad Shaikh 
Published: August 2023

Abstract
In this work, we consider a class of dark matter (DM) models where the DM does not directly interact with the Standard Model (SM) particles at the tree-level. Therefore, the coannihilation mechanism is crucial in achieving the correct DM relic abundance, which in turn requires the coannihilating partner to be close in mass to the actual DM particle. In our systematisation of the models’ class, the mediator and the coannihilation partner are assumed to be charged under QCD interactions. This last feature calls for a scrutiny of non-perturbative effects, namely Sommerfeld factors and bound-state formation, on the annihilations of the colored partner. Such non-perturbative effects are illustrated with an example model comprising a scalar leptoquark mediator, a Dirac vector-like fermion coannihilation partner, and a singlet DM fermion. Phenomenological features of this model, namely DM direct and indirect detection prospects, collider implications, and impact on the muon anomalous magnetic moment, are discussed.
The expanding organelle lipidomes: current knowledge and challenges
Authors: Sarmento Maria J. , Llorente Alicia , Petan Toni , Khnykin Denis , Popa Iuliana , Nikolac Perkovic Matea , Konjevod Marcela , Jaganjac Morana 
Published: August 2023

AbstractLipids in cell membranes and subcellular compartments play essential roles in numerous cellular processes, such as energy production, cell signaling and inflammation. A specific organelle lipidome is characterized by lipid synthesis and metabolism, intracellular trafficking, and lipid homeostasis in the organelle. Over the years, considerable effort has been directed to the identification of the lipid fingerprints of cellular organelles. However, these fingerprints are not fully characterized due to the large variety and structural complexity of lipids and the great variability in the abundance of different lipid species. The process becomes even more challenging when considering that the lipidome differs in health and disease contexts. This review summarizes the information available on the lipid composition of mammalian cell organelles, particularly the lipidome of the nucleus, mitochondrion, endoplasmic reticulum, Golgi apparatus, plasma membrane and organelles in the endocytic pathway. The lipid compositions of extracellular vesicles and lamellar bodies are also described. In addition, several examples of subcellular lipidome dynamics under physiological and pathological conditions are presented. Finally, challenges in mapping organelle lipidomes are discussed.
Knowledge of India as an Instrument of Nazi Politics: Ludwig Alsdorf, German Indology and Indian Anti-Colonialism
Authors: Roy Baijayanti 
Published: August 2023

AbstractLudwig Alsdorf (1904–1978) is primarily remembered as a scholar of ancient and medieval India. This paper examines a little known aspect of Alsdorf’s career: his role as an expert of modern India in Nazi Germany. Alsdorf, who was in India from 1930 to 1932, joined the NSDAP and a few of its subsidiaries after 1933. Political contacts as well as his claims of having “first-hand experience” of India secured Alsdorf writing assignments that aimed to fulfil the regime’s political objectives. In return, he gained professional advancement and the reputation of being an authority on modern India. This paper reviews Alsdorf’s trajectory within the NS state by focussing on the following aspects: the ways in which Alsdorf offered his knowledge of India to the Nazi regime; the material and symbolic resources that he received in return; the relative importance of political affiliations, professional networks and academic accomplishments for Alsdorf’s career; the “politics of the past” practised by Alsdorf and some of peers after 1945; and the (re)presentation of the “uses” of Indology in the “Third Reich” and in the Federal Republic of Germany by Alsdorf and his colleagues.