bluuebunny/crossref_metadata_2025 huggingface dataset:
Climate Change Discourse of Spanish-Speaking Airlines in Corporate Reports
Authors: Pérez Cañizares Pilar
Published: September 2023

The airline industry is currently responsible for more than 2% of greenhouse gas emissions, making it a major contributor to climate change and global warming. The aim of this paper is to investigate how airlines in Spanish-speaking countries communicate their position on climate change in their corporate reports and whether this has changed over the last few years. To this end, a corpus of 51 corporate reports produced by 5 different airlines between 2003 and 2020 was designed. The reports were subjected to linguistic analysis using computer processing and corpus linguistic methods. The results show large differences between the airlines in the way they communicate their relationship with climate change and suggest the existence of two phases in terms of attention paid to the issue, with a turning point in 2015/2016. In general, climate change tends to be addressed through the reporting of specific data, with limited mention of possible consequences. References to climate change tend to appear in indexes, titles, headings or literal reproductions of reporting standards. This helps to give some prominence to the issue, although there is most frequently no positioning or appraisal of the issue.
Infinitive vs. Gerund Use and Interpretation in Heritage Spanish
Authors: Solano-Escobar Laura , Cuza Alejandro
Published: September 2023

The present study examines the production and interpretation of infinitives among 26 Spanish heritage speakers born and raised in the US and 25 Spanish-dominant speakers from Mexico and Colombia. We tested participants’ knowledge of infinitives as subjects of the clause and as objects of a preposition via an elicited production task and a contextualized preference task. The results of both tasks showed less infinitive use by the HSs and overextension of the gerund in contexts where it is not required. The results showed that the gerund overextension was modulated by the syntactic context. There was significantly more use of the gerund as the subject of the clause in both production and interpretation and less use as the object of a preposition. Furthermore, the results showed a significant role for proficiency and language experience in the extent of grammatical reconfiguration. The higher the level of Spanish proficiency and the more exposure and use of Spanish, the more likely the participants were to produce and choose infinitives. Results are discussed along the lines of the activation approach.
The Death Taboo: Euphemism and Metaphor in Epitaphs from the English Cemetery of Malaga, Spain
Authors: Crespo-Fernández Eliecer
Published: September 2023

In spite of the fact that taboos change over time, death is still a delicate and sensitive subject in today’s Western societies. Our unwillingness to talk openly about death and dying makes people resort to euphemism as a safe way to talk about human mortality and related matters. Following Steen’s Deliberate Metaphor Theory, this study discusses the role that euphemistic metaphors play on a sample of 174 gravestone inscriptions from the English Cemetery of Malaga, the oldest Protestant cemetery in Spain, and, at the same time, examines the social and cognitive aspects of metaphor in epitaph writing. The analysis carried out reveals that most of the 96 metaphorical items observed in the gravestone inscriptions present positive connotations. Indeed, the source domains of rest, peace, new life and journey offer an optimistic and comforting approach to death and dying, whereas the domains of loss and separation refer to the target domain of death in negative terms. All in all, the metaphors encountered in the epitaphs are deliberately used both to help the bereaved confront the loss of a loved one and pay tribute to the deceased.
Transformative Procurement Trends: Integrating Industry 4.0 Technologies for Enhanced Procurement Processes
Authors: Althabatah Areej , Yaqot Mohammed , Menezes Brenno , Kerbache Laoucine
Published: September 2023

Background: the advent of Industry 4.0 (I4.0) innovations has revolutionized supply chain management through technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) integrated into procurement processes. Methods: this study addresses a critical knowledge gap by conducting a comprehensive review of 111 papers sourced from the Scopus database. These papers are classified into seven sub-themes encompassing I4.0 or procurement 4.0 (P4.0), big data, IoT, additive manufacturing, blockchain, e-procurement, and AI. Results: the investigation reveals that I4.0 technologies, particularly e-procurement and blockchain, have garnered substantial attention. Such technologies offer diverse value propositions, encompassing streamlined supplier evaluation, lead time reduction, cost optimization, and enhanced data security. Conclusion: the paper underscores pivotal trends and insights for the evolution of Procurement 4.0, illuminating a path toward more efficient supply chain management.
Determination of the Friction Coefficient in the Ring Test for Selected Lubricants Dedicated to the Hot Forging Process of Precision Steel Products
Authors: Dudkiewicz Łukasz , Hawryluk Marek , Ziemba Jacek , Miżejewski Adrian , Polak Sławomir , Marzec Jan , Szymańska Tatiana
Published: September 2023

This paper concerns an analysis of the tribological conditions and the effect of the use of seven lubricating agents dedicated to a process of precision forging on a hammer in multiple systems. In particular, it performs a review of the most popular methods of determining the friction coefficient in the aspect of the obtained results. On this basis, the selected method of friction coefficient determination was a hot ring upsetting test for two forging materials: carbon steel (16MnCrS5) and stainless steel (316Ti). The test samples were prepared in the shape of a ring with precisely defined dimensions, and, next, they were subjected to an upsetting process on a hydraulic hammer under conditions similar to those present in an industrial forging process, and the characteristic geometrical features and friction coefficients were determined. Additionally, measurements of the geometrical changes were made with the use of 3D scanning for the extreme friction coefficient values in order to perform their comparison. The obtained results showed that for carbon steel the lowest achieved value was in the case of Lubrodal F185 (µ = 0.24) A and the highest for Lubr_hot_press 123HD (µ = 0.32); in turn, for stainless steel the lowest value µ = 0.19 was achieved for Graphitex CR 7 and the highest for Graphitex CR720K (µ = 0.29). Moreover, for these conditions, numerical modeling was conducted in the Forge 3.0 NxT program, in order to analyze the obtained results and verify the correctness and agreement of the friction coefficients determined in the ring test, on the basis of the geometrical changes. The data obtained in the computer simulation confirmed the possibility of obtaining a good agreement between the FEM (Finite Elements Method) and experimental trials, as the modeling provides reliable information on the plastic deformations and can be used as an alternative method of examining the friction conditions in industrial forging processes.
On the Stability of a Convective Flow with Nonlinear Heat Sources
Authors: Gritsans Armands , Kolyshkin Andrei , Sadyrbaev Felix , Yermachenko Inara
Published: September 2023

The linear stability of a convective flow in a vertical fluid layer caused by nonlinear heat sources in the presence of cross-flow through the walls of the channel is investigated in this paper. This study is relevant to the analysis of factors that affect the effectiveness of biomass thermal conversion. The nonlinear problem for the base flow temperature is investigated in detail using the Krasnosel’skiĭ–Guo cone expansion/contraction theorem. It is shown that a different number of solutions can exist depending on the values of the parameters. Estimates for the norm of the solutions are obtained. The linear stability problem is solved numerically by a collocation method based on Chebyshev polynomials. It is shown that the increase in the cross-flow intensity stabilizes the flow, but there is also a small region of the radial Reynolds numbers where the flow is destabilized.
Enhanced Non-Maximum Suppression for the Detection of Steel Surface Defects
Authors: Kang Seong-Hwan , Palakonda Vikas , Kim Il-Min , Kang Jae-Mo , Yun Sangseok
Published: September 2023

Quality control in manufacturing equipment relies heavily on the detection of steel surface defects. Recently, there have been an increasing number of efforts in which object detection techniques have been utilized to achieve promising results in the detection of steel surface defects since the defect patterns can be considered objects. To enhance the detection performance in the object detection problem, the non-maximum suppression (NMS) step, which eliminates redundant boxes overlapped with a box having the greatest detection score, is essential. In this work, we propose a novel NMS to improve the detection method of steel surface defects. The proposed NMS approach is composed of three novel techniques: IoU regularization, threshold adjustment, and comparison rule modification to enhance the detection performance. To evaluate the performance of the proposed NMS, we carry out extensive numerical experiments using the YOLOv7 and EfficientDet models on the steel surface defect datasets, NEU-DET and GC10-DET. The experimental results demonstrate that the proposed NMS outperforms the conventional NMS methods in both quantitative and qualitative manners.
Robust Design Problem for Multi-Source Multi-Sink Flow Networks Based on Genetic Algorithm Approach
Authors: Boubaker Sahbi , Radwan Noha Hamdy , Refaat Hassan Moatamad , Alsubaei Faisal S. , Younes Ahmed , Sennary Hameda A.
Published: September 2023

Robust design problems in flow networks involve determining the optimal capacity assignments that enable the network to operate effectively even in the case of events’ occurrence such as arcs or nodes’ failures. Multi-source multi-sink flow networks (MMSFNs) are frequent in many real-life systems such as computer and telecommunication, logistics and supply-chain, and urban traffic. Although numerous studies on the design of MMSFNs have been conducted, the robust design problem for multi-source multi-sink stochastic-flow networks (MMSFNs) remains unexplored. To contribute to this field, this study addresses the robust design problem for MMSFNs using an approach of two steps. First, the problem is mathematically formulated as an optimization problem and second, a sub-optimal solution is proposed based on a genetic algorithm (GA) involving two components. The first component, an outer genetic algorithm, is employed to search the optimal capacity assigned to the network components with minimum sum. The second component, an inner genetic algorithm, is used to find the optimal flow vectors that maximize the system’s reliability. Through extensive experimentation on three different networks with different topologies, the proposed solution has been found to be efficient.
A Study on the Effects of Digital Finance on Green Low-Carbon Circular Development Based on Machine Learning Models
Authors: Zhang Xuewei , Ai Xiaoqing , Wang Xiaoxiang , Zong Gang , Zhang Jinghao
Published: September 2023

With technological transformations such as big data, blockchain, artificial intelligence, and cloud computing, digital techniques are infiltrating the field of finance. Digital finance (DF) is a resource-saving and environmentally friendly innovative financial service. It shows great green attributes and can drive the flow of financial resources towards environmentally-friendly enterprises, thereby promoting green low-carbon circular development (GLCD). However, few studies have explored the coupling mechanism between DF and GLCD. To fill this gap, this paper explores the effect of DF on GLCD, and established a mediating effect model to investigate the mechanism of DF in promoting GLCD. Additionally, this paper established a random forest model and a CatBoost model based on machine learning to examine the relative importance of DF and the factors affecting GLCD. The results show that DF has significant positive effects on GLCD, and technological innovation plays a key role in the effect of DF on GLCD; meanwhile, the effect of DF on GLCD shows nonlinear features with an increasing “marginal effect”; moreover, both DF and conventional factors have significant impacts on GLCD. Our study highlights the effect of DF on GLCD and underscores the importance of developing policies for DF and GLCD. This study provides an empirical basis and path reference for DF to achieve “carbon peak, carbon neutralization” in China.
Prevalence of Malocclusions in Down Syndrome Population: A Cross-Sectional Study
Authors: Alessandri-Bonetti Anna , Guglielmi Federica , Mollo Antongiulia , Sangalli Linda , Gallenzi Patrizia
Published: September 2023

Background and Objectives: A higher prevalence of dental malocclusion has been suggested among individuals with Down Syndrome (DS) compared to controls, although no studies to date have investigated such a difference according to age group. Therefore, the aim of this study was to compare the prevalence of dental malocclusion and other orthodontic measures between DS and non-syndromic (non-DS) individuals across three age groups of children, adolescents, and adults. Materials and Methods: This cross-sectional study was conducted on a total of 147 patients. Of those, 72 were diagnosed with DS and were divided into N = 15 children (<10 years), N = 23 adolescents (10–18 years) and N = 34 adults (>18 years). The remaining 75 patients were sex- and age-matched controls. The two groups were compared according to age group in terms of the prevalence of dental malocclusion, measures of sagittal, vertical, and transverse discrepancy, facial profile, and probable sleep bruxism with chi-square tests for proportion. Results: The DS patients consistently exhibited a higher prevalence of Class 3 malocclusion, concave profile and anterior crossbite compared to the non-DS patients, regardless of age group. The non-DS adolescents presented with a significantly higher prevalence of convex profile than the DS adolescents. The adolescent and adult DS patients most commonly presented with a maxillary transverse discrepancy and posterior crossbite compared to the non-DS controls. The DS adults had a higher prevalence of probable sleep bruxism. Conclusions: Patients with DS showed a higher prevalence of Class 3 malocclusion, concave profile and anterior crossbite compared to non-DS controls, regardless of age group. Other orthodontic measures showed a fluctuation according to the age group considered.
Effect of Al2O3 on Inclusion Removal in H13 Steels Using High-Basicity LF (Ladle Furnace) Refining Slags
Authors: Liang Ting , Qin Zhuo , Wang Linzhu
Published: September 2023

In this experiment, a quaternary fluorine-free refining slag system of CaO-SiO2-Al2O3-MgO was selected, with basicity ratios of 2, 4, and 6 and calcium-aluminum ratios of 1.5, 2.1, and 3. High-temperature “slag-steel equilibrium” experiments were conducted to investigate the influence of different basicity ratios and calcium–aluminum ratios on the morphologies, compositions, sizes, and quantities of the inclusions in H13 steel, aiming to improve the cleanliness of H13 steel to meet practical industrial requirements. The experimental results showed that with the increase in the basicity ratio and the calcium–aluminum ratio, the morphologies of the inclusions changed from elliptical to regular circular, with more regular edges. As the basicity ratio increased from 2 to 6, the densities of the inclusions showed a decreasing trend, with values of 40, 35, 30, 25, 32, and 30 inclusions/mm2. When the basicity ratio remained the same, the average size of the inclusions in the steel decreased first and then increased with the increases in the calcium–aluminum ratios, with sizes of 1.59 μm, 1.23 μm, and 1.38 μm, respectively. Among these, when the basicity ratio was 6 and the calcium–aluminum ratio was 2.1, the control effect on the densities and sizes of the inclusions was the best, yielding an inclusion density of 25 inclusions/mm2 and a size of 1.15 μm. Additionally, reducing the Al2O3 content in the slag could reduce the Al2O3 contents in the inclusions, which also promoted improvements in the elastic deformation capacities of the inclusions. With increases in the calcium–aluminum ratios in the slag system, the masses of the inclusions decreased due to the reduced Al contents in the steel. The Al contents in the steel also had an impact on the compositions of the inclusions.
Microbial Detection and Quantification of Low-Biomass Water Samples Using an International Space Station Smart Sample Concentrator
Authors: Blachowicz Adriana , Urbaniak Camilla , Adolphson Alec , Isenhouer Gwyn , Page Andy , Venkateswaran Kasthuri
Published: September 2023

The pressing need to safeguard the health of astronauts aboard the International Space Station (ISS) necessitates constant and rigorous microbial monitoring. Recognizing the shortcomings of traditional culture-based methods, NASA is deliberating the incorporation of molecular-based techniques. The challenge, however, lies in developing and validating effective methods for concentrating samples to facilitate this transition. This study is dedicated to investigating the potential of an ISS Smart Sample Concentrator (iSSC) as an innovative concentration method. First, the iSSC system and its components were tested and optimized for microgravity, including various testing environments: a drop tower, parabolic flight, and the ISS itself. Upon confirming the system’s compatibility with microgravity, we further evaluated its proficiency and reliability in concentrating large volumes (i.e., 1 L) of water samples inoculated with different microbes. The samples carried 102 to 105 colony-forming units (CFUs) of Sphingomonas paucimobilis, Ralstonia pickettii, or Cupriavidus basilensis per liter, aligning with NASA’s acceptable limit of 5 × 104 CFU/L. The average retrieved volume post-concentration was ≈450 µL, yielding samples that were ≈2200 times more concentrated for subsequent quantitative PCR (qPCR) and CFU analysis. The average microbial percent recovery, as assessed with CFU counts, demonstrated consistency for C. basilensis and R. pickettii at around 50% and 45%, respectively. For S. paucimobilis, the efficiency oscillated between 40% and 80%. Interestingly, when we examined microbial recovery using qPCR, the results showed more variability across all tested species. The significance of these findings lies not merely in the successful validation of the iSSC but also in the system’s proven consistency, as evidenced by its alignment with previous validation-phase results. In conclusion, conducted research underscored the potential of the iSSC in monitoring microbial contamination in potable water aboard the ISS, heralding a paradigm shift from culture-based to molecular-based monitoring methods.
Genome Analysis and Potential Ecological Functions of Members of the Genus Ensifer from Subsurface Environments and Description of Ensifer oleiphilus sp. nov.
Authors: Ershov Alexey P. , Babich Tamara L. , Grouzdev Denis S. , Sokolova Diyana S. , Semenova Ekaterina M. , Avtukh Alexander N. , Poltaraus Andrey B. , Ianutsevich Elena A. , Nazina Tamara N.
Published: September 2023

The current work deals with genomic analysis, possible ecological functions, and biotechnological potential of two bacterial strains, HO-A22T and SHC 2-14, isolated from unique subsurface environments, the Cheremukhovskoe oil field (Tatarstan, Russia) and nitrate- and radionuclide-contaminated groundwater (Tomsk region, Russia), respectively. New isolates were characterized using polyphasic taxonomy approaches and genomic analysis. The genomes of the strains HO-A22T and SHC 2-14 contain the genes involved in nitrate reduction, hydrocarbon degradation, extracellular polysaccharide synthesis, and heavy metal detoxification, confirming the potential for their application in various environmental biotechnologies. Genomic data were confirmed by cultivation studies. Both strains were found to be neutrophilic, chemoorganotrophic, facultatively anaerobic bacteria, growing at 15–33 °C and 0–1.6% NaCl (w/v). The 16S rRNA gene sequences of the strains were similar to those of the type strains of the genus Ensifer (99.0–100.0%). Nevertheless, genomic characteristics of strain HO-A22T were below the thresholds for species delineation: the calculated average nucleotide identity (ANI) values were 83.7–92.4% (<95%), and digital DNA–DNA hybridization (dDDH) values were within the range of 25.4–45.9% (<70%), which supported our conclusion that HO-A22T (=VKM B-3646T = KCTC 92427T) represented a novel species of the genus Ensifer, with the proposed name Ensifer oleiphilus sp. nov. Strain SHC 2-14 was assigned to the species ‘Ensifer canadensis’, which has not been validly published. This study expanded the knowledge about the phenotypic diversity among members of the genus Ensifer and its potential for the biotechnologies of oil recovery and radionuclide pollution treatment.
Feed Regime Slightly Modifies the Bacterial but Not the Fungal Communities in the Intestinal Mucosal Microbiota of Cobia Fish (Rachycentron canadum)
Authors: Reinoso Samira , Gutiérrez María Soledad , Reyes-Jara Angélica , Toro Magaly , García Katherine , Reyes Guillermo , Argüello-Guevara Wilfrido , Bohórquez-Cruz Milton , Sonnenholzner Stanislaus , Navarrete Paola
Published: September 2023

The bacterial community of the intestinal microbiota influences many host functions, and similar effects have been recently reported for the fungal community (mycobiota). Cobia is a tropical fish that has been studied for its potential in marine aquaculture. However, the study of its bacterial community has been underreported and the mycobiota has not been investigated. We analyzed the gut bacterial and fungal profile present in the intestinal mucosa of reared adult cobias fed two diets (frozen fish pieces (FFPs) and formulated feed (FF)) for 4 months by sequencing the 16S rRNA (V3-V4) and internal transcribed spacer-2 (ITS2) regions using Illumina NovaSeq 6000. No significant differences in the alpha diversity of the bacterial community were observed, which was dominated by the phyla Proteobacteria (~96%) and Firmicutes (~1%). Cobia fed FF showed higher abundance of 10 genera, mainly UCG-002 (Family Oscillospiraceae) and Faecalibacterium, compared to cobia fed FFPs, which showed higher abundance of 7 genera, mainly Methylobacterium-Methylorubrum and Cutibacterium. The inferred bacterial functions were related to metabolism, environmental information processing and cellular processes; and no differences were found between diets. In mycobiota, no differences were observed in the diversity and composition of cobia fed the two diets. The mycobiota was dominated by the phyla Ascomycota (~88%) and Basidiomycota (~11%). This is the first study to describe the gut bacterial and fungal communities in cobia reared under captive conditions and fed on different diets and to identify the genus Ascobulus as a new member of the core fish mycobiota.
Effects of Different Irrigation Regimes, Nitrogen Levels and Storage Conditions on Volatiles of ‘Gala’ Apple
Authors: Tavares Cláudia , Rodrigues Carolina Ferro , Gonçalves Elsa , Machado Alexandra M. , Pedro Luís , Barroso José , Maurício Anabela , Franco Nuno , Raimundo Délio , Pita Valério , Sánchez Claudia , Figueiredo Ana Cristina
Published: September 2023

With a characteristic flavour and aroma, “Maçã de Alcobaça” are apples produced in the western region of the mainland of Portugal. Given the known influence of pre-harvest cultural techniques and post-harvest conservation methods on fruit quality, this work evaluated the effect of cultural factors and conservation methods on the volatile profile of ‘Gala’ apples. Tests were carried out during four seasons (2018 to 2021) in two ‘Gala’ apple orchards (F and S) maintained with different irrigation rates and nitrogen fertilisation [normal irrigation and normal nitrogen (Control, NINN), normal irrigation and excess nitrogen (NIEN), excess irrigation and normal nitrogen (EINN), excess irrigation and excess nitrogen (EIEN)], and under three storage conditions [Controlled Atmosphere + 1-methylcyclopropene (CA+1-MCP), Dynamic Controlled Atmosphere (DCA) and DCA+1-MCP]. The intact fruit volatiles were isolated by headspace solid–phase microextraction (HS–SPME) and analysed by Gas Chromatography with Flame Ionisation Detection and Gas Chromatography-Mass Spectrometry at harvest (T0) and after 8 months of storage (T8). HS–SPME volatiles from ‘Gala’ apples, obtained at T0 in control conditions, were characterised by trans,trans-α-farnesene dominance (36–69%), followed by hexyl acetate (5–23%) and hexyl hexanoate (3–9%). The four irrigation and nitrogen treatments did not evidence main changes in the apple volatile profile. Instead, storage conditions changed the ratio between compounds; previously undetected compounds attained high percentages and decreased the intensity of the dominant compounds in the control conditions. Although all storage conditions tested changed the volatile profile and emanation intensity, the effect was more accentuated in storage for 8 months with DCA+1-MCP.
Management Considerations for Pulmonary Arterial Hypertension Pharmacotherapy in the Intensive Care Unit
Authors: Foster Elizabeth M. , Sullinger Danine , Coons James C.
Published: September 2023

Pulmonary arterial hypertension is a rare and progressive disease with significant morbidity and mortality risk. Several medications targeting three major disease pathways are approved for treatment. However, the management of pulmonary arterial hypertension pharmacotherapies in a patient admitted to an intensive care unit poses unique challenges. Factors such as intubation and altered mental status may prevent the continuation of home oral and/or inhaled therapy, and the progression of the disease may require escalation of therapy. This review will focus on practical management strategies for the continuation of home pulmonary arterial hypertension pharmacotherapy and escalation of therapy.
A Low-Carbon Scheduling Method of Flexible Manufacturing and Crane Transportation Considering Multi-State Collaborative Configuration Based on Hybrid Differential Evolution
Authors: Liu Zhengchao , Xu Liuyang , Pan Chunrong , Gao Xiangdong , Xiong Wenqing , Tang Hongtao , Lei Deming
Published: September 2023

With increasingly stringent carbon policies, the development of traditional heavy industries with high carbon emissions has been greatly restricted. Manufacturing companies surveyed use multifunctional machining machines and variable speed cranes, as the lack of rational planning results in high energy wastage and low productivity. Reasonable scheduling optimization is an effective way to reduce carbon emissions, which motivates us to work on this research. To reduce the comprehensive energy consumption of the machining process and transportation process in an actual manufacturing environment, this paper addresses a new low-carbon scheduling problem of flexible manufacturing and crane transportation considering multi-state collaborative configuration (LSP-FM&CT-MCC). First, an integrated energy consumption model based on multi-state machining machines and cranes is established to optimize the overall energy efficiency of the production process. Then, a new hybrid differential evolution algorithm and firefly algorithm with collaborative state optimization strategy (DE-FA-CSOS) is proposed to solve the proposed MIP model. In DE-FA-CSOS, the differential evolution algorithm (DE) is used for global search, and the firefly algorithm (FA) is used for local search. The collaborative state optimization strategy (CSOS) is proposed to guide the search direction of the DE-FA algorithm, which greatly improves the performance of the hybrid algorithm. Finally, the practicality and superiority of the solution method are verified by examples. The results show that machining and transportation energy consumption is reduced by 25.17% and 34.52%, respectively. In the context of traditional optimization methods and manual scheduling modes facing failure, the method has a broad application background for manufacturing process optimization in such workshops, which is of guiding significance for promoting the low-carbon development of traditional heavy industry manufacturing.
Comparison of Glass–Glass versus Glass–Backsheet Encapsulation Applied to Carbon-Based Perovskite Solar Cells
Authors: Kyranaki Nikoleta , Perrin Lara , Flandin Lionel , Planès Emilie , Farha Cynthia , Wagner Lukas , Saddedine Karima , Martineau David , Cros Stéphane
Published: September 2023

The record photovoltaic performance of perovskite solar cells is constantly increasing, reaching 26% currently. However, there is a crucial need for the development of simple architectures that are compatible with large-scale industrialization and possess adequate stability. The aim of the work presented here is to compare the efficiency of glass–glass and glass–backsheet encapsulations for carbon-based perovskite solar cell application, which possesses a great potential for industrialization. This was conducted by first separating the relative effects of humidity and heat. A time evolution of the macroscopic power conversion efficiency (PCE) was performed, together with specific characterizations in order to scout the origin of flaws and degradations. A significant contribution of the paper is the identification of both TiO2 and carbon layers as barriers against moisture permeation, which inhibit moisture paths through the interfaces. This is the origin of the equivalent durability of both studied systems, even if the glass–backsheet encapsulation was found to be less efficient than the glass–glass encapsulation at protecting perovskite from damp-heat aging when TiO2 or carbon layers are not used.
Oxidation-Induced Changes in the Lattice Structure of YSZ Deposited by EB-PVD in High-Vacuum Conditions
Authors: Lee Gye-Won , Lee In-Hwan , Oh Yoon-Suk
Published: September 2023

Yttria-stabilized zirconia (YSZ), a thermal barrier coating material characterized by low thermal conductivity, is typically deposited via electron beam-physical vapor deposition. Notably, oxygen depletion occurs during this process, causing color changes in YSZ. Therefore, YSZ is speculated to undergo phase transformation during this process, which demands careful consideration owing to its effect on the life of thermal coatings. To study this phenomenon, bulk samples were prepared, subjected to vacuum heat treatment to induce oxygen depletion, and followed by oxidative heat treatment. Experimental results showed that the color of the samples changed to black after the vacuum heat treatment and to a lighter color after the oxidative heat treatment. In addition, X-ray diffraction and Raman analyses were performed. The monoclinic phase formation was confirmed during the vacuum heat treatment; however, it disappeared after the oxidation heat treatment. The coating obtained in a high vacuum atmosphere exhibited a black color and cubic phase, which changed to a bright color and tetragonal phase after the oxidation heat treatment.
Renewed Interest in Spectroscopy of the Lightest Doubly-Odd N = Z Nuclei
Authors: Kuşoğlu Aslı , Balabanski Dimiter Loukanov
Published: September 2023

The existing experimental data for the γ decay of the stable N=Z doubly-odd nuclei and the β decay of the corresponding isospin multiplets is reviewed. The structure of the lightest nuclei with masses A≤14 is used to test and constrain ab initio nuclear theories. Most of the data were obtained in the second half of the last century and, in some cases, lack the needed precision for comparison with theoretical calculations. Recent spectroscopic studies in the lightest doubly-odd N = Z nuclei are discussed, as well as open problems related to the understanding of their structures and ideas for future experiments.
Full Factorial Design Synthesis of Silver Nanoparticles Using Origanum vulgare
Authors: Rigopoulos Nickolas , Gkaliouri Christina Megetho , Sakavitsi Viktoria , Gournis Dimitrios
Published: September 2023

Green synthesis of silver nanoparticles (AgNPs) involves a reduction reaction of a metal salt solution mixed with a plant extract. The reaction yield can be controlled using several independent factors, such as extract and metal concentration, temperature, and incubation time. AgNPs from Origanum vulgare (oregano) were synthesized in the past. However, no investigations were performed on the combined effects of independent factors that affect the synthesis. In this work, silver nitrate, oregano extract, and sodium hydroxide (NaOH) concentrations were chosen as the independent factors, and full factorial design under Response Surface Methodology was employed. UV–Vis absorbance spectroscopy, X-ray Powder Diffraction (XRD), and Fourier Transform Infrared Spectroscopy (FTIR) were used to characterize the nanoparticles. A Voigt function was fitted on the measured UV–Vis spectra. The fitting parameters of the Voigt function, peak wavelength, area, and Full Width at Half Maximum, were used as the responses. A quadratic model was fitted for the peak wavelength and area. The NaOH concentration proved to be the dominant factor in nanoparticle synthesis. UV–Vis absorbance showed a characteristic plasmon resonance of AgNPs at 409 nm. XRD verified the crystallinity of the nanoparticles and FTIR identified the ligands involved.
Implementation of an Electrosurgical Checklist in a Podiatry Unit in Relation to a Case of Inadvertent Burns during Hallux Valgus Surgery
Authors: Córdoba-Fernández Antonio , Jiménez-Cristino María Dolores , Mármol-García Francisco Javier , Córdoba-Jiménez Victoria Eugenia
Published: September 2023

Iatrogenic burns are unpleasant and sometimes difficult to explain to patients. Podiatric surgeons routinely use electrosurgical devices to cut and coagulate tissue during surgical procedures. Although advances in technology have made electrosurgery increasingly safer for patients and personnel, its use is still poorly understood by the surgical community, and the hazards associated with its use still exist presently. Human error, direct or indirect transfer of electricity to a conductive device, or device malfunction can cause serious adverse events, including burns, electrical shocks, and or fires. Here, we report a rare case of a 43-year-old man who suffered severe burns during hallux valgus surgery. The surgeon and the nursing staff did not notice any injuries during the surgical intervention. This unusual clinical case serves to highlight the importance of implementing protocols to prevent injuries related to the use of electrosurgery. Based on this report, a specific checklist was implemented to prevent adverse events related to electrosurgery in our podiatric surgery unit to reduce the risk of electrosurgical complications. The implementation of the checklist can be useful to help health professionals improve patient safety during surgery and avoid potential medico–legal liability claims.
Piezotronic Antimony Sulphoiodide/Polyvinylidene Composite for Strain-Sensing and Energy-Harvesting Applications
Authors: Jała Jakub , Nowacki Bartłomiej , Toroń Bartłomiej
Published: September 2023

This study investigates the piezoelectric and piezotronic properties of a novel composite material comprising polyvinylidene fluoride (PVDF) and antimony sulphoiodide (SbSI) nanowires. The material preparation method is detailed, showcasing its simplicity and reproducibility. The material’s electrical resistivity, piezoelectric response, and energy-harvesting capabilities are systematically analyzed under various deflection conditions and excitation frequencies. The piezoelectric response is characterized by the generation of charge carriers in the material due to mechanical strain, resulting in voltage output. The fundamental phenomena of charge generation, along with their influence on the material’s resistivity, are proposed. Dynamic strain testing reveals the composite’s potential as a piezoelectric nanogenerator (PENG), converting mechanical energy into electrical energy. Comparative analyses highlight the composite’s power density advantages, thereby demonstrating its potential for energy-harvesting applications. This research provides insights into the interplay between piezoelectric and piezotronic phenomena in nanocomposites and their applicability in energy-harvesting devices.
HIDM: Hybrid Intrusion Detection Model for Industry 4.0 Networks Using an Optimized CNN-LSTM with Transfer Learning
Authors: Lilhore Umesh Kumar , Manoharan Poongodi , Simaiya Sarita , Alroobaea Roobaea , Alsafyani Majed , Baqasah Abdullah M. , Dalal Surjeet , Sharma Ashish , Raahemifar Kaamran
Published: September 2023

Industrial automation systems are undergoing a revolutionary change with the use of Internet-connected operating equipment and the adoption of cutting-edge advanced technology such as AI, IoT, cloud computing, and deep learning within business organizations. These innovative and additional solutions are facilitating Industry 4.0. However, the emergence of these technological advances and the quality solutions that they enable will also introduce unique security challenges whose consequence needs to be identified. This research presents a hybrid intrusion detection model (HIDM) that uses OCNN-LSTM and transfer learning (TL) for Industry 4.0. The proposed model utilizes an optimized CNN by using enhanced parameters of the CNN via the grey wolf optimizer (GWO) method, which fine-tunes the CNN parameters and helps to improve the model’s prediction accuracy. The transfer learning model helps to train the model, and it transfers the knowledge to the OCNN-LSTM model. The TL method enhances the training process, acquiring the necessary knowledge from the OCNN-LSTM model and utilizing it in each next cycle, which helps to improve detection accuracy. To measure the performance of the proposed model, we conducted a multi-class classification analysis on various online industrial IDS datasets, i.e., ToN-IoT and UNW-NB15. We have conducted two experiments for these two datasets, and various performance-measuring parameters, i.e., precision, F-measure, recall, accuracy, and detection rate, were calculated for the OCNN-LSTM model with and without TL and also for the CNN and LSTM models. For the ToN-IoT dataset, the OCNN-LSTM with TL model achieved a precision of 92.7%; for the UNW-NB15 dataset, the precision was 94.25%, which is higher than OCNN-LSTM without TL.
Soot Monitoring of Gasoline Particulate Filters Using a Radio-Frequency-Based Sensor
Authors: Walter Stefanie , Schwanzer Peter , Hagen Gunter , Rabl Hans-Peter , Dietrich Markus , Moos Ralf
Published: September 2023

Owing to increasingly stringent emission limits, particulate filters have become mandatory for gasoline-engine vehicles. Monitoring their soot loading is necessary for error-free operation. The state-of-the-art differential pressure sensors suffer from inaccuracies due to small amounts of stored soot combined with exhaust gas conditions that lead to partial regeneration. As an alternative approach, radio-frequency-based (RF) sensors can accurately measure the soot loading, even under these conditions, by detecting soot through its dielectric properties. However, they face a different challenge as their sensitivity may depend on the engine operation conditions during soot formation. In this article, this influence is evaluated in more detail. Various soot samples were generated on an engine test bench. Their dielectric properties were measured using the microwave cavity perturbation (MCP) method and compared with the corresponding sensitivity of the RF sensor determined on a lab test bench. Both showed similar behavior. The values for the soot samples themselves, however, differed significantly from each other. A way to correct for this cross-sensitivity was found in the influence of exhaust gas humidity on the RF sensor, which can be correlated with the engine load. By evaluating this influence during significant humidity changes, such as fuel cuts, it could be used to correct the influence of the engineon the RF sensor.
Smarter Evolution: Enhancing Evolutionary Black Box Fuzzing with Adaptive Models
Authors: Borcherding Anne , Morawetz Martin , Pfrang Steffen
Published: September 2023

Smart production ecosystems are a valuable target for attackers. In particular, due to the high level of connectivity introduced by Industry 4.0, attackers can potentially attack individual components of production systems from the outside. One approach to strengthening the security of industrial control systems is to perform black box security tests such as network fuzzing. These are applicable, even if no information on the internals of the control system is available. However, most security testing strategies assume a gray box setting, in which some information on the internals are available. We propose a new approach to bridge the gap between these gray box strategies and the real-world black box setting in the domain of industrial control systems. This approach involves training an adaptive machine learning model that approximates the information that is missing in a black box setting. We propose three different approaches for the model, combine them with an evolutionary testing approach, and perform an evaluation using a System under Test with known vulnerabilities. Our evaluation shows that the model is indeed able to learn valuable information about a previously unknown system, and that more vulnerabilities can be uncovered with our approach. The model-based approach using a Decision Tree was able to find a significantly higher number of vulnerabilities than the two baseline fuzzers.
Research on the Cooperative Target State Estimation and Tracking Optimization Method of Multi-UUV
Authors: Chen Tao , Qi Qi
Published: September 2023

This work studied two sub-problems of the cooperative state estimation and cooperative optimization of tracking paths in multiple unmanned underwater vehicle (multi-UUV) cooperative target tracking. The mathematical model of each component of the multi-UUV cooperative target tracking system was established. According to the target bearing-only information obtained by each unmanned underwater vehicle’s (UUV) detection, the extended Kalman filter algorithm based on interacting with multiple model bearing-only data was used to estimate the target state in a distributed way, and the federal fusion algorithm was used to fuse the estimated results of each UUV. The fused target state was predicted, and, based on the predicted target state, to achieve the persistent tracking of the target, the particle swarm optimization algorithm was used for the online collaborative optimization of the UUV tracking path. The simulation results showed that the multi-UUV distributed fusion filtering algorithm could obtain a better target state estimation effect, and the online path collaborative optimization method based on the prediction of the target state could achieve persistent target tracking.
Exploiting Big Data for Experiment Reporting: The Hi-Drive Collaborative Research Project Case
Authors: Capello Alessio , Fresta Matteo , Bellotti Francesco , Haghighi Hamed , Hiller Johannes , Mozaffari Sajjad , Berta Riccardo
Published: September 2023

As timely information about a project’s state is key for management, we developed a data toolchain to support the monitoring of a project’s progress. By extending the Measurify framework, which is dedicated to efficiently building measurement-rich applications on MongoDB, we were able to make the process of setting up the reporting tool just a matter of editing a couple of .json configuration files that specify the names and data format of the project’s progress/performance indicators. Since the quantity of data to be provided at each reporting period is potentially overwhelming, some level of automation in the extraction of the indicator values is essential. To this end, it is important to make sure that most, if not all, of the quantities to be reported can be automatically extracted from the experiment data files actually used in the project. The originating use case for the toolchain is a collaborative research project on driving automation. As data representing the project’s state, 330+ numerical indicators were identified. According to the project’s pre-test experience, the tool is effective in supporting the preparation of periodic progress reports that extensively exploit the actual project data (i.e., obtained from the sensors—real or virtual—deployed for the project). While the presented use case concerns the automotive industry, we have taken care that the design choices (particularly, the definition of the resources exposed by the Application Programming Interfaces, APIs) abstract the requirements, with an aim to guarantee effectiveness in virtually any application context.
A Neural Network Approach to Estimate the Frequency of a Cantilever Beam with Random Multiple Damages
Authors: Saha Prattasha , Yang Mijia
Published: September 2023

Natural frequency is an important parameter in the structural health monitoring (SHM) system. Any changes in this parameter indicate structural alteration due to damage. This study provides a neural network (NN) solution as an alternative to the finite element (FE) method to measure the natural frequencies of a cantilever beam with random multiple damage. It is based on a statistical dataset of a free vibration test obtained from the APDL (Ansys parametric design language) simulation using a MATLAB (matrix laboratory) script. The script can generate an unlimited number of possible damage combinations for any given parameters with the help of the Monte Carlo (MC) technique. MC helps to generate a random number of damages in random locations at each simulation. Damage conditions are controlled by three parameters including damage severity and damage size (in terms of the mean and standard deviation of damage). Moreover, the method proposes a curve-fitting equation to validate the predicted natural frequency for the first three modes obtained from the neural network model. Both methods are in good agreement with each other, having minimal errors in the range of 0.2–3% for each mode. The frequency result shows that the beam frequency is 8.6486 Hz if the area reduction is 10%, whereas it comes down to 7.2338 Hz if there is a 30% area reduction. A two-level factorial test shows that damage severity is the most impactful factor compared to the damage sizes on the frequency shift event. This indicates that damage alters the composition of the beam and has an impact on its frequency change with the assumed damage parameters. Therefore, the proposed NN model can estimate the frequency shift for various damage scenarios. It can be utilized in the vibration-based damage identification process to predict the frequency changes of the damaged beam without any computational burden.