bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning Composite-Nanoparticle-Enriched Lubricant Oil Development for Improved Frictional Performance—An Experiment
Authors: Usman Ali , Arif Saad , Raja Ahmed Hassan , Kouhia Reijo , Almqvist Andreas , Liwicki Marcus
Published: June 2023

Improving the frictional response of a functional surface interface has been a significant research concern. During the last couple of decades, lubricant oils have been enriched with several additives to obtain formulations that can meet the requirements of different lubricating regimes from boundary to full-film hydrodynamic lubrication. The possibility to improve the tribological performance of lubricating oils using various types of nanoparticles has been investigated. In this study, we proposed a data-driven approach that utilizes machine learning (ML) techniques to optimize the composition of a hybrid oil by adding ceramic and carbon-based nanoparticles in varying concentrations to the base oil. Supervised-learning-based regression methods including support vector machines, random forest trees, and artificial neural network (ANN) models are developed to capture the inherent non-linear behavior of the nano lubricants. The ANN hyperparameters were fine-tuned with Bayesian optimization. The regression performance is evaluated with multiple assessment metrics such as the root mean square error (RMSE), mean squared error (MSE), mean absolute error (MAE), and coefficient of determination (R2). The ANN showed the best prediction performance among all ML models, with 2.22 × 10−3 RMSE, 4.92 × 10−6 MSE, 2.1 × 10−3 MAE, and 0.99 R2. The computational models’ performance curves for the different nanoparticles and how the composition affects the interface were investigated. The results show that the composition of the optimized hybrid oil was highly dependent on the lubrication regime and that the coefficient of friction was significantly reduced when optimal concentrations of ceramic and carbon-based nanoparticles are added to the base oil. The proposed research work has potential applications in designing hybrid nano lubricants to achieve optimized tribological performance in changing lubrication regimes.
Research on the Effect of Load and Rotation Speed on Resistance to Combined Wear of Stainless Steels Using ANOVA Analysis
Authors: Rozing Goran , Duspara Miroslav , Dudic Branislav , Savkovic Borislav
Published: June 2023

This research was carried out with the aim of obtaining appropriate principles for describing the influence of working parameters and the aggressive action of an acidic medium on the wear and corrosion resistance of martensitic stainless steels. Tribological tests were performed on induction-hardened surfaces of stainless steels X20Cr13 and X17CrNi16-2 under combined wear conditions at a load of 100 to 300 N and a rotation speed of 382 to 754 min−1. The wear test was carried out on a tribometer with the use of an aggressive medium in the chamber. After each wear cycle on the tribometer, the samples were exposed to corrosion action in a corrosion test bath. Analysis of variance revealed a significant influence of rotation speed and load due to wear on the tribometer. Testing the difference in the mass loss values of the samples due to corrosion using the Mann–Whitney U test did not show a significant effect of corrosion. Steel X20Cr13 showed greater resistance to combined wear, which had a 27% lower wear intensity compared to steel X17CrNi16-2. The increase in wear resistance of X20Cr13 steel can be attributed to the higher surface hardness achieved and the effective depth of hardening. The mentioned resistance is the result of the creation of a martensitic surface layer with dispersed carbides, which increases the resistance to abrasion, dynamic durability, and fatigue of the surface of the protective layer.
Statistical Evaluation of the Impacts Detection Methodology (IDM) to Detect Critical Damage Occurrences during Quay Cranes Handling Operations
Authors: Jakovlev Sergej , Eglynas Tomas , Jankunas Valdas , Voznak Miroslav , Jusis Mindaugas , Partila Pavol , Tovarek Jaromir
Published: June 2023

During various marine container handling operations, performed mainly in larger-scale container terminals, containers get damaged regularly. Our previous studies showed that each physical impact results in some form of physical deformation of the backbone structure. Even at low accelerations, the spreaders of the quay cranes impact the containers with enough force to substantially bend the metal parts of the corners of the containers, when additional hooking procedures are required. This means that the first time resulted in the metal rods hitting the metal frame with an average 15-ton mass at the average speed of 1.7 m/s. The metal rods of the hooking mechanisms’ impact areas of the containers are structurally important, and each impact surely damages the containers, diminishing their total operational time. We have already proposed the Impacts Detection Methodology (IDM) and its application system, tested in Klaipeda City port, and it proved to be efficient in real-time operations, detecting concurrent impacts with each new handling cycle. In this paper, we provide a summarisation of a larger number of detections using the IDM, and as a result of this analysis, we have detected that more impact events happen when containers are taken from the upper parts of the ship, in comparison to the ones taken from the shafts. Results suggest that more critical events occur due to operator actions and experiences working with the machinery, yet the same operators tend to make fewer impact mistakes taking the containers from the shafts as the vertical cell guides tend to direct the movements and lower the levels of the natural sway of the spreader inside closed environments. This surely damages the metal infrastructure of the shafts, as seen in our previous study, but minimizes the chances of secondary impacts occurring during hooking.
Vibration Resonance Spectrometry (VRS) for the Advanced Streaming Detection of Rotor Unbalance
Authors: Gerdes Matthew T. , Wang Yawen , Wei Xinqi , Wang Guang C. , Liu Ruixian , Gross Kenny C.
Published: June 2023

Determination of the diagnosis thresholds is crucial for the fault diagnosis of industry assets. Rotor machines under different working conditions are especially challenging because of the dynamic torque and speed. In this paper, an advanced machine learning based signal-processing innovation termed the multivariate state estimation technique is proposed to improve the accuracy of the diagnosis thresholds. A novel preprocessing technique called vibration resonance spectrometry is also applied to achieve a low computation cost capability for real-time condition monitoring. The monitoring system that utilizes the above methods is then applied for prognostics of a fan model as an example. Different levels of radial unbalance were added on the fan and tested, and then compared with the health state. The results show that the proposed methodology can detect the unbalance with a good accuracy and low computation cost. The proposed methodology can be applied for complex engineering assets for better predictive monitoring that could be processed with on-premise edge devices, or eventually a cloud platform due to its capacity for loss-less dimension reduction.
Distributed Finite-Time Coverage Control of Multi-Quadrotor Systems with Switching Topology
Authors: Tnunay Hilton , Moussa Kaouther , Hably Ahmad , Marchand Nicolas
Published: June 2023

This paper studies the distributed coverage control problem of multi-quadcopter systems connected with fixed and switching network topologies to guarantee the finite-time convergence. The proposed method modifies the objective function originating from the locational optimization problem to accommodate the consensus constraint and solves the problem within a given time limit. The coverage problem is solved by sending angular-rate and thrust commands to the quadcopters. By exploiting the finite-time stability theory, we ensure that the rotation and translation controllers of the quadcopters are finite-time stable both in fixed and switching communication topologies, able to be implemented distributively, and able to collaboratively drive the quadcopters towards the desired position and velocity of the Voronoi centroid independent of their initial states. After carefully designing and analyzing the performance, numerical simulations using a Robot Operating System (ROS) and Gazebo simulator are presented to validate the effectiveness of the proposed control protocols.
An Optimization Method of Large-Scale Video Stream Concurrent Transmission for Edge Computing
Authors: Liu Haitao , Chen Qingkui , Liu Puchen
Published: June 2023

Concurrent access to large-scale video data streams in edge computing is an important application scenario that currently faces a high cost of network access equipment and high data packet loss rate. To solve this problem, a low-cost link aggregation video stream data concurrent transmission method is proposed. Data Plane Development Kit (DPDK) technology supports the concurrent receiving and forwarding function of multiple Network Interface Cards (NICs). The Q-learning data stream scheduling model is proposed to solve the load scheduling of multiple queues of multiple NICs. The Central Processing Unit (CPU) transmission processing unit was dynamically selected by data stream classification, as well as a reward function, to achieve the dynamic load balancing of data stream transmission. The experiments conducted demonstrate that this method expands the bandwidth by 3.6 times over the benchmark scheme for a single network port, and reduces the average CPU load ratio by 18%. Compared to the UDP and DPDK schemes, it lowers the average system latency by 21%, reduces the data transmission packet loss rate by 0.48%, and improves the overall system transmission throughput. This transmission optimization scheme can be applied in data centers and edge computing clusters to improve the communication performance of big data processing.
Swarm Robots Search for Multiple Targets Based on Historical Optimal Weighting Grey Wolf Optimization
Authors: Zhu Qian , Li Yongqing , Zhang Zhen
Published: June 2023

This study investigates the problem of swarm robots searching for multiple targets in an unknown environment. We propose the Historical Optimal Weighting Grey Wolf Optimization (HOWGWO) algorithm based on an improved grouping strategy. In the HOWGWO algorithm, we gather and update every individual grey wolf’s historical optimal position and rank grey wolves based on the merit of their historical optimal position. The position of the prey is dynamically estimated by the leader wolf, and all grey wolves move towards the prey’s estimated position. To solve the multi-target problem of swarm robots search, we integrate the HOWGWO algorithm with an improved grouping strategy and divide the algorithm into two stages: the random walk stage and the dynamic grouping stage. During the random walk stage, grey wolves move randomly and update their historical optimal positions. During the dynamic grouping stage, the HOWGWO algorithm generates search auxiliary points (SAPs) by adopting an improved grouping strategy based on individual grey wolves’ historical optimal positions. These SAPs are then utilized for grouping grey wolves to search for different prey. The SAPs are re-generated using the optimum historical positions of every single grey wolf after positions have been updated, rather than just those belonging to a specific group. The effectiveness of the proposed HOWGWO algorithm is extensively assessed in 30 dimensions using the CEC 2017 test suite, which simulates unimodal, multimodal, hybrid, and composition problems. Then, the obtained results are compared with competitors, including GWO, PSO and EGWO, and the results are statistically analyzed through Friedman’s test. Ultimately, simulations are performed to simulate the problem of searching multiple targets by swarm robots in a real environment. The experimental results and statistical analysis confirm that the proposed HOWGWO algorithm has a fast convergence speed and solution quality for solving global optimization problems and swarm robots searching multiple targets problems.
A Robust Distributed Deep Learning Approach to Detect Alzheimer’s Disease from MRI Images
Authors: Ghosh Tapotosh , Palash Md Istakiak Adnan , Yousuf Mohammad Abu , Hamid Md. Abdul , Monowar Muhammad Mostafa , Alassafi Madini O.
Published: June 2023

Alzheimer’s disease has become a major concern in the healthcare domain as it is growing rapidly. Much research has been conducted to detect it from MRI images through various deep learning approaches.However, the problems of the availability of medical data and preserving the privacy of patients still exists. To mitigate this issue in Alzheimer’s disease detection, we implement the federated approach, which is found to be more efficient, robust, and consistent compared with the conventional approach. For this, we need deep excavation on various orientations of MRI images and transfer learning architectures. Then, we utilize two publicly available datasets (OASIS and ADNI) and design various cases to evaluate the performance of the federated approach. The federated approach achieves better accuracy and sensitivity compared with the conventional approaches in most of the cases. Moreover, the robustness of the proposed approach is also found to be better than the conventional approach. In our federated approach, MobileNet, a low-cost transfer learning architecture, achieves the highest 95.24%, 81.94%, and 83.97% accuracy in the OASIS, ADNI, and merged (ADNI + OASIS) test sets, which is much higher than the achieved performance in the conventional approach. Furthermore, in the proposed approach, only the weights of the model are shared, which keeps the original MRI images in their respective hospital or institutions, preserving privacy in the healthcare domain.
A Note on Nearly Sasakian Manifolds
Authors: Massamba Fortuné , Nzunogera Arthur
Published: June 2023

A class of nearly Sasakian manifolds is considered in this paper. We discuss the geometric effects of some symmetries on such manifolds and show, under a certain condition, that the class of Ricci semi-symmetric nearly Sasakian manifolds is a subclass of Einstein manifolds. We prove that a Codazzi-type Ricci nearly Sasakian space form is either a Sasakian manifold with a constant ϕ-holomorphic sectional curvature H=1 or a 5-dimensional proper nearly Sasakian manifold with a constant ϕ-holomorphic sectional curvature H>1. We also prove that the spectrum of the operator H2 generated by the nearly Sasakian space form is a set of a simple eigenvalue of 0 and an eigenvalue of multiplicity 4, and we induce that the underlying space form carries a Sasaki–Einstein structure. We show that there exist integrable distributions with totally geodesic leaves on the same manifolds, and we prove that there are no proper nearly Sasakian space forms with constant sectional curvature.
Balanced-DRL: A DQN-Based Job Allocation Algorithm in BaaS
Authors: Guo Chaopeng , Xu Ming , Hu Shengqiang , Song Jie
Published: June 2023

Blockchain as a Service (BaaS) combines features of cloud computing and blockchain, making blockchain applications more convenient and promising. Although current BaaS platforms have been widely adopted by both industry and academia, concerns arise regarding their performance, especially in job allocation. Existing BaaS job allocation strategies are simple and do not guarantee load balancing due to the dynamic nature and complexity of BaaS job execution. In this paper, we propose a deep reinforcement learning-based algorithm, Balanced-DRL, to learn an optimized allocation strategy in BaaS based on analyzing the execution process of BaaS jobs and a set of job scale characteristics. Following extensive experiments with generated job request workloads, the results show that Balanced-DRL significantly improves BaaS performance, achieving a 5% to 8% increase in job throughput and a 5% to 20% decrease in job latency.
Investigation of Higher Order Localized Approximations for a Fractional Pricing Model in Finance
Authors: Ullah Malik Zaka , Alzahrani Abdullah Khamis , Alshehri Hashim Mohammed , Shateyi Stanford
Published: June 2023

In this work, by considering spatial uniform meshes and stencils having five adjacent discretization nodes, we furnish a numerical scheme to solve the time-fractional Black–Scholes (partial differential equation) PDE to price financial options under the generalized multiquadric radial basis function (RBF). The time-fractional derivative is estimated by an L1-scheme but the spatial variable is discretized using fourth-order RBF-FD methodology. As a matter of fact, the PDE problem is transformed in the form of a linear set of algebraic equations. To support analytical discussions, numerical tests are furnished and reveal the efficacy of the presented solver.
On Nearly Sasakian and Nearly Kähler Statistical Manifolds
Authors: Uddin Siraj , Peyghan Esmaeil , Nourmohammadifar Leila , Bossly Rawan
Published: June 2023

In this paper, we introduce the notions of nearly Sasakian and nearly Kähler statistical structures with a non-trivial example. The conditions for a real hypersurface in a nearly Kähler statistical manifold to admit a nearly Sasakian statistical structure are given. We also study invariant and anti-invariant statistical submanifolds of nearly Sasakian statistical manifolds. Finally, some conditions under which such a submanifold of a nearly Sasakian statistical manifold is itself a nearly Sasakian statistical manifold are given.
From Ion Fluxes in Living Cells to Metabolic Power Considerations
Authors: Lucia Umberto , Grisolia Giulia
Published: June 2023

Recently, the role of thermal resonance has been highlighted in living cells. As a consequence of this approach, the electrochemical potential was obtained in a partial differential equation concerning the cell membrane depth and its external temperature surface. In this paper, this last equation is studied and its solution’s consequences are discussed concerning the cells’ ion fluxes and their related entropy variation and power generation. Moreover, the metabolic power of the whole body is evaluated by using these previous numerical results.
Effects of Eccentric-Oriented Strength Training on Return to Sport Criteria in Late-Stage Anterior Cruciate Ligament (ACL)-Reconstructed Professional Team Sport Players
Authors: Stojanović Marko D. M. , Andrić Nikola , Mikić Mladen , Vukosav Nikola , Vukosav Borko , Zolog-Șchiopea Dan-Nicolae , Tăbăcar Mircea , Melinte Răzvan Marian
Published: June 2023

Background and Objectives: An effective post-injury training program is essential to regain performance and fulfill criteria for return to sport for team sport athletes following anterior cruciate ligament (ACL) reconstruction. The aim of this study was to compare the effects of 6 weeks of eccentric-oriented strength training vs. traditional strength training during the late-stage ACL-rehab phase on leg strength and vertical and horizontal jumping performance in professional team sport athletes. Materials and Methods: Twenty-two subjects (14 males, 8 females, age 19.9 ± 4.4 years, mass 77.4 ± 15.6 kg, height 182.4 ± 11.7 cm) (mean ± SD) with a unilateral reconstructed ACL (BTB graft) were included in the study. All participants enrolled in the same rehabilitation protocol prior to the training study. Players were randomly assigned to an experimental (ECC: n = 11, age 21.8 ± 4.6 years, mass 82.7 ± 16.6 kg, height 185.4 ± 12.2 cm), and a control group (CON: n = 11, age 19.1 ± 2.1 years, mass 76.6 ± 16.5 kg, height 182.5 ± 10.2 cm). Both groups underwent an equivolumed rehabilitation program, with the only difference being in strength training, which consisted of flywheel training vs. traditional strength training for the experimental and control groups, respectively. Testing was organized before and after the 6-week training programs and included isometric semi-squat tests (ISOSI-injured and ISOSU-uninjured legs), vertical jump tests (CMJ), single-leg vertical jump tests (SLJI-injured and SLJU-uninjured legs), single-leg hop tests (SLHI-injured and SLHU-uninjured legs), and triple hop tests (TLHI-injured and TLHU-uninjured legs). In addition, limb symmetry indexes were calculated for the isometric semi-squat (ISOSLSI) test, the single-leg vertical jump (SLJLSI), and the hop (SLHLSI) tests, as well as the triple-leg hop (THLLSI) test. Results: Main effects of time across training were observed for all dependent variables (posttest > pretest, p < 0.05). Significant group-by-time interactions were found for ISOSU (p < 0.05, ES = 2.51, very large), ISOSI (p < 0.05, ES = 1.78, large), CMJ (p < 0.05, ES = 2.23, very large), SLJI (p < 0.05, ES = 1.48, large), SLHI (p < 0.05, ES = 1.83, large), and TLHI (p < 0.05, ES = 1.83, large). Conclusions: This study suggests that eccentric-oriented strength training in late-stage ACL recovery, undertaken twice or three times weekly for 6 weeks, results in better outcomes than traditional strength training in leg strength, vertical jump ability, and single and triple hop tests with injured legs in professional team sport athletes. It seems that flywheel strength training can be recommended in late-stage ACL recovery for professional team sport athletes in order to regain recommended performance outcome levels faster.
Adult-Onset Linear Morphea (en coupe de sabre) of the Face Successfully Treated with Photoactivated Low-Temperature Platelet-Rich Plasma: A Valid Therapeutic Option
Authors: Mercuri Santo Raffaele , Di Nicola Matteo Riccardo , Bianchi Vittoria Giulia , Paolino Giovanni
Published: June 2023

Localized scleroderma (also known as morphea) is a chronic autoimmune disorder characterized by depressed, fibrotic, and dyschromic cutaneous lesions. It has a significant impact on the patient’s daily life due to the unaesthetic evolution of the cutaneous lesions. Morphea is clinically divided into linear, circumscribed (plaque), generalized, pansclerotic, and mixed forms. Linear morphea en coupe de sabre (LM) usually arises in childhood. However, in about 32% of cases, it may arise in adulthood, showing a more aggressive course with also an increased risk of systemic involvement. Methotrexate is the first-line treatment for LM, although systemic steroids, topical agents (corticosteroids and calcineurin inhibitors), hyaluronic acid injections, and hydroxychloroquine or mycophenolate mofetil are valid therapeutic options. In any case, these treatments are not always effective and sometimes can be associated with important side effects and/or not tolerated by the patients. In this spectrum, platelet-rich plasma (PRP) injection can be considered a valid and safe alternative since PRP injections in the skin induce the release of anti-inflammatory cytokines and growth factors, thus reducing inflammation and increasing collagen remodeling. Herein, we describe a successful treatment of an adult-onset LM en coupe de sabre with photoactivated low-temperature PRP (Meta Cell Technology Plasma) sessions, showing an important local improvement of the lesion and patient satisfaction.
Detection of Nonsynonymous Single Variants in Human HLA-DRB1 Exon 2 Associated with Renal Transplant Rejection
Authors: Hassan Mohamed M. , Hussain Mohamed A. , Ali Sababil S. , Mahdi Mohammed A. , Mohamed Nouh Saad , AbdElbagi Hanadi , Mohamed Osama , Sherif Asmaa E. , Osman Wadah , Ibrahim Sabrin R. M. , Ghazawi Kholoud F. , Miski Samar F. , Mohamed Gamal A. , Ashour Ahmed
Published: June 2023

Background: HLA-DRB1 is the most polymorphic gene in the human leukocyte antigen (HLA) class II, and exon 2 is critical because it encodes antigen-binding sites. This study aimed to detect functional or marker genetic variants of HLA-DRB1 exon 2 in renal transplant recipients (acceptance and rejection) using Sanger sequencing. Methods: This hospital-based case-control study collected samples from two hospitals over seven months. The 60 participants were equally divided into three groups: rejection, acceptance, and control. The target regions were amplified and sequenced by PCR and Sanger sequencing. Several bioinformatics tools have been used to assess the impact of non-synonymous single-nucleotide variants (nsSNVs) on protein function and structure. The sequences data that support the findings of this study with accession numbers (OQ747803-OQ747862) are available in National Center for Biotechnology Information (GenBank database). Results: Seven SNVs were identified, two of which were novel (chr6(GRCh38.p12): 32584356C>A (K41N) and 32584113C>A (R122R)). Three of the seven SNVs were non-synonymous and found in the rejection group (chr6(GRCh38.p12): 32584356C>A (K41N), 32584304A>G (Y59H), and 32584152T>A (R109S)). The nsSNVs had varying effects on protein function, structure, and physicochemical parameters and could play a role in renal transplant rejection. The chr6(GRCh38.p12):32584152T>A variant showed the greatest impact. This is because of its conserved nature, main domain location, and pathogenic effects on protein structure, function, and stability. Finally, no significant markers were identified in the acceptance samples. Conclusion: Pathogenic variants can affect intramolecular/intermolecular interactions of amino acid residues, protein function/structure, and disease risk. HLA typing based on functional SNVs could be a comprehensive, accurate, and low-cost method for covering all HLA genes while shedding light on previously unknown causes in many graft rejection cases.
Different Aspects of Machinability in Turning of AISI 304 Stainless Steel: A Sustainable Approach with MQL Technology
Authors: Binali Rüstem , Demirpolat Havva , Kuntoğlu Mustafa , Salur Emin
Published: June 2023

Machining of AISI 304 austenitic stainless steel is considered to be difficult due to its structural aspects and low thermal conductivity, which leads to increased temperatures during machining. To overcome the challenges of machining AISI 304 stainless steel, several cooling and lubricating techniques have been developed. The main objective of this experimental study is to evaluate the different turning conditions of AISI304 stainless steel under dry and minimum quantity lubrication (MQL) environment conditions. The machining experiments were conducted using a two-level full factorial design method and utilized a TiC-coated cutting tool. The tool-tip temperature, cutting force and surface roughness were analyzed regarding three cutting parameters namely, cutting speed, feed rate and cutting depth. Also, chip macro-morphology was investigated to define the interaction at the tool-chip-workpiece region. The cutting medium affects the surface roughness significantly (more than 100%) for all cutting parameter values. In some environmental cutting conditions, high cutting speed provides 10% lesser surface roughness than low cutting speed parameters. Also, the cutting force decreases by 20% in low feed rate machining conditions. However, the effect of this parameter disappeared for cutting forces in high feed rates and low cutting depth conditions in both MQL and dry environments. Cutting speed was observed as the most influential factor on surface roughness, followed by feed rate. The depth of cut was the main parameter that caused the temperature to increase in the dry machining environment.
Numerical Simulations to Predict the Melt Pool Dynamics and Heat Transfer during Single-Track Laser Melting of Ni-Based Superalloy (CMSX-4)
Authors: Azadi Tinat Mohammad Reza , Uddagiri Murali , Steinbach Ingo , López-Galilea Inmaculada
Published: June 2023

Computational Fluid Dynamics (CFD) simulations are used in this work to study the dynamic behavior of the melt pool and heat transfer during the single-track laser melting process of a nickel-based superalloy (CMSX-4). To include the effects of powder inhomogeneities and obtain a realistic distribution of the powder layer on the bed chamber, the CFD model is coupled with a Discrete Element Method (DEM) solver. The coupled model is implemented in the open-source software package OpenFOAM. In the CFD model’s governing equations, some key physical mechanisms, such as the Marangoni effect and recoil pressure, are considered. With the help of the coupled CFD-DEM model, we have investigated the effect of key process parameters, such as laser power, scanning speed of the laser, powder size, and powder shape, on the size and homogeneity of the melt pool. From the simulation results, it was discovered that high laser power and slow scanning speed create a deep and narrow keyhole that leads to porosity. In contrast, balling defects are found to be caused by a small melt pool obtained from fast scanning speeds and inadequate laser power.
Environmental and Economic Analyses of TIG, MIG, MAG and SMAW Welding Processes
Authors: González-González Carlos , Los Santos-Ortega Jorge , Fraile-García Esteban , Ferreiro-Cabello Javier
Published: June 2023

Metal welding processes, and electric arc welding in particular, constitute a key link in a production chain comprising a large number of companies. This fact, in addition to a growing trend in favour of more in-depth environmental analysis and control of industry, and the need to continue affording due consideration to the economic aspect set the stage for this study. Herein, an environmental and economic analysis is conducted of four types of electric arc welding: TIG welding with and without filler, MIG, MAG, and SMAW welding. Different types of materials are examined such as carbon steel, stainless steel, and aluminium, thus the results generate relevant comparative information on the economic and environmental impacts of choosing one type of welding over another. To this end, an experimental study was carried out: 480 test specimens were welded using different welding technologies. A series of data was collected during the welding process to inform an environmental analysis based on a Life Cycle Analysis and an economic study. The most salient results include that the TIG welding process with filler generated the greatest environmental impact due to its higher consumption of shielding gas. On the other hand, the SMAW process demonstrated the best environmental performance as categories such as Global Warming Potential; CO2 emissions dropped by 93.29%. A key factor is the final indicator of human health, where, once again, TIG technology had the worst results, in contrast to SMAW technology, wherein impact decreased by 93.08%. On the other hand, the use of TIG technology implies a higher economic cost due to a 61.36% increase in welding time compared to the average welding technology.
A Comparison of Experimental and Ab Initio Structural Data on Fe under Extreme Conditions
Authors: Belonoshko Anatoly B. , Smirnov Grigory S.
Published: June 2023

Iron is the major element of the Earth’s core and the cores of Earth-like exoplanets. The crystal structure of iron, the major component of the Earth’s solid inner core (IC), is unknown under the high pressures (P) (3.3–3.6 Mbar) and temperatures (T) (5000–7000 K) and conditions of the IC and exoplanetary cores. Experimental and theoretical data on the phase diagram of iron at these extreme PT conditions are contradictory. Though some of the large-scale ab initio molecular dynamics (AIMD) simulations point to the stability of the body-centered cubic (bcc) phase, the latest experimental data are often interpreted as evidence for the stability of the hexagonal close-packed (hcp) phase. Applying large-scale AIMD, we computed the properties of iron phases at the experimental pressures and temperatures reported in the experimental papers. The use of large-scale AIMD is critical since the use of small bcc computational cells (less than approximately 1000 atoms) leads to the collapse of the bcc structure. Large-scale AIMD allowed us to compare the measured and computed coordination numbers as well as the measured and computed structural factors. This comparison, in turn, allowed us to suggest that the computed density, coordination number, and structural factors of the bcc phase are in agreement with those observed in experiments, which were previously assigned either to the liquid or hcp phase.
Sonochemistry of Liquid-Metal Galinstan toward the Synthesis of Two-Dimensional and Multilayered Gallium-Based Metal–Oxide Photonic Semiconductors
Authors: Karbalaei Akbari Mohammad , Siraj Lopa Nasrin , Zhuiykov Serge
Published: June 2023

The scientific field of two-dimensional (2D) nanostructures has witnessed tremendous development during the last decade. To date, different synthesis approaches have been developed; therefore, various exceptional properties of this family of advanced materials have been discovered. It has recently been found that the natural surface oxide films of room-temperature liquid metals is an emerging platform for the synthesis of novel types of 2D nanostructures with numerous functional applications. However, most of the developed synthesis techniques for these materials are based on the direct mechanical exfoliation of 2D materials as research targets. This paper reports a facile and functional sonochemical-assisted approach for the synthesis of 2D hybrid and complex multilayered nanostructures with tunable characteristics. In this method, the intense interaction of acoustic waves with microfluidic gallium-based room-temperature liquid galinstan alloy provides the activation energy for synthesis of hybrid 2D nanostructures. The microstructural characterizations reveal the impact of sonochemical synthesis parameters, including the processing time and composition of the ionic synthesis environment, on the growth of GaxOy/Se 2D hybrid structures and InGaxOy/Se multilayered crystalline structures with tunable photonic characteristics. This technique shows promising potential for synthesis of various types of 2D and layered semiconductor nanostructures with tunable photonic characteristics.
Transmissive Mode Laser Micro-Ablation Performance of Ammonium Dinitramide-Based Liquid Propellant for Laser Micro-Thruster
Authors: Du Baosheng , Zheng Yongzan , Mao Chentao , Cui Haichao , Han Jianhui , Jiang Luyun , Ye Jifei , Hong Yanji
Published: June 2023

The transmissive mode laser micro-ablation performance of near-infrared (NIR) dye-optimized ammonium dinitramide (ADN)-based liquid propellant was investigated in laser plasma propulsion using a pulse YAG laser with 5 ns pulse width and 1064 nm wavelength. Miniature fiber optic near-infrared spectrometer, differential scanning calorimeter (DSC) and high-speed camera were used to study laser energy deposition, thermal analysis of ADN-based liquid propellants and the flow field evolution process, respectively. Experimental results indicate that two important factors, laser energy deposition efficiency and heat release from energetic liquid propellants, obviously affect the ablation performance. The results showed that the best ablation effect of 0.4 mL ADN solution dissolved in 0.6 mL dye solution (40%-AAD) liquid propellant was obtained with the ADN liquid propellant content increasing in the combustion chamber. Furthermore, adding 2% ammonium perchlorate (AP) solid powder gave rise to variations in the ablation volume and energetic properties of propellants, which enhanced the propellant enthalpy variable and burn rate. Based on the AP optimized laser ablation, the optimal single-pulse impulse (I)~9.8 μN·s, specific impulse (Isp)~234.9 s, impulse coupling coefficient (Cm)~62.43 dyne/W and energy factor (η)~71.2% were obtained in 200 µm scale combustion chamber. This work would enable further improvements in the small volume and high integration of liquid propellant laser micro-thruster.
Comparative Analysis of the Silver Nanoparticle’s Yield for Pico-Femto-Nanosecond Laser Generation
Authors: Nastulyavichus Alena , Kudryashov Sergey , Ionin Andrey
Published: June 2023

Comparative analysis of different laser regimes of silver nanoparticle generation in water was performed for laser pulsewidth in the range of 300 fs–100 ns. Optical spectroscopy, scanning electron microscopy, energy-dispersive X-ray spectroscopy and method of dynamic light scattering were used for nanoparticle characterization. Different laser regimes of generation were used with varying pulse duration, pulse energy and scanning velocity. The proposed universal quantitative criteria as productivity and ergonomicity of the obtained colloidal solutions of nanoparticles were investigated to compare different laser regimes of production. The efficiency per unit energy for picosecond generation of nanoparticles, free from the influence of nonlinear effects, turns out to be higher by 1–2 orders of magnitude than for nanosecond generation.
Design and Optimization of Planar Spiral Coils for Powering Implantable Neural Recording Microsystem
Authors: Luo Jie , Xue Ruifeng , Cheong Jiahao , Zhang Xuan , Yao Lei
Published: June 2023

This paper presents a design and optimization method utilizing inductive coupling coils for wireless power transfer in implantable neural recording microsystems, aiming at maximizing power transfer efficiency, which is essential for reducing externally transmitted power and ensuring biological tissue safety. The modeling of inductive coupling is simplified by combining semi-empirical formulations with theoretical models. By introducing the optimal resonant load transformation, the coil optimization is decoupled from an actual load impedance. The complete design optimization process of the coil parameters is given, which takes the maximum theoretical power transfer efficiency as the objective function. When the actual load changes, only the load transformation network needs to be updated instead of rerunning the entire optimization process. Planar spiral coils are designed to power neural recording implants given the challenges of limited implantable space, stringent low-profile restrictions, high-power transmission requirements and biocompatibility. The modeling calculation, electromagnetic simulation and measurement results are compared. The operating frequency of the designed inductive coupling is 13.56 MHz, the outer diameter of the implanted coil is 10 mm and the working distance between the external coil and the implanted coil is 10 mm. The measured power transfer efficiency is 70%, which is close to the maximum theoretical transfer efficiency of 71.9%, confirming the effectiveness of this method.
Lichens from the Roosevelt River Area in the Brazilian Amazon
Authors: Aptroot André
Published: June 2023

Lichens were investigated in Brazil in a small area along the Roosevelt River in Amazonas; 25 species are first reports for Brazil, and 190 additional species are first records for Amazonas state. As many as 24 species are described that are new to science: Allographa lineatipruinosa, Allographa variopruinata, Arthonia xanthopycnidiata, Astrothelium aurantioseptemseptatum, Astrothelium bulbosum, Astrothelium coloratum, Astrothelium inspersonovemseptatum, Astrothelium insulare, Astrothelium laureroides, Astrothelium marjoleinae, Astrothelium meandratum, Astrothelium multireflexum, Astrothelium myopicum, Astrothelium parabathelium, Astrothelium stellare (also known from Mato Grosso state), Astrothelium suprainspersum, Astrothelium xanthocavatum, Ocellularia fuscolichexanthonica, Ocellularia lichexanthocavata, Pertusaria amazonica, Phaeographis xantholirellinata, Porina ramiisidiata, Pseudopyrenula connexa, and Sprucidea squamulosa.
Amelioration of Murine Colitis by Attenuated Salmonella choleraesuis Encoding Interleukin-19
Authors: Chen Shih-Yao , Chu Chun-Ting , Yang Mei-Lin , Lin Jian-Da , Wang Chung-Teng , Lee Che-Hsin , Lin I-Chen , Shiau Ai-Li , Ling Pin , Wu Chao-Liang
Published: June 2023

The imbalance of mucosal immunity in the lower gastrointestinal tract can lead to chronic inflammatory bowel diseases (IBDs), including Crohn’s disease and ulcerative colitis. IBD is a chronic inflammatory disorder that causes small and/or large intestines ulceration. According to previous studies, recombinant interleukin (IL)-10 protein and genetically modified bacteria secreting IL-10 ameliorate dextran sulfate sodium (DSS)-induced colitis in mice. IL-19 is a transcriptional activator of IL-10 and can alter the balance of T helper 1 (Th)1/Th2 cells in favor of Th2. In this study, we aimed to investigate whether the expression of the murine IL-19 gene carried by Salmonella choleraesuis (S. choleraesuis) could ameliorate murine IBD. Our results showed that the attenuated S. choleraesuis could carry and express the IL-19 gene-containing plasmid for IBD gene therapy by reducing the mortality and clinical signs in DSS-induced acute colitis mice as compared to the untreated ones. We also found that IL-10 expression was induced in IL-19-treated colitis mice and prevented inflammatory infiltrates and proinflammatory cytokine expression in these mice. We suggest that S. choleraesuis encoding IL-19 provides a new strategy for treating IBD in the future.
Culture-Dependent and Metabarcoding Characterization of the Sugar Beet (Beta vulgaris L.) Microbiome for High-Yield Isolation of Bacteria with Plant Growth-Promoting Traits
Authors: Krstić Tomić Tamara , Atanasković Iva , Nikolić Ivan , Joković Nataša , Stević Tatjana , Stanković Slaviša , Berić Tanja , Lozo Jelena
Published: June 2023

The diversity of plant-associated bacteria is vast and can be determined by 16S rRNA gene metabarcoding. Fewer of them have plant-beneficial properties. To harness their benefits for plants, we must isolate them. This study aimed to check whether 16S rRNA gene metabarcoding has predictive power in identifying the majority of known bacteria with plant-beneficial traits that can be isolated from the sugar beet (Beta vulgaris L.) microbiome. Rhizosphere and phyllosphere samples collected during one season at different stages of plant development were analyzed. Bacteria were isolated on rich unselective media and plant-based media enriched with sugar beet leaves or rhizosphere extracts. The isolates were identified by sequencing the 16S rRNA gene and tested in vitro for their plant-beneficial properties (stimulation of germination; exopolysaccharide, siderophore, and HCN production; phosphate solubilization; and activity against sugar beet pathogens). The highest number of co-occurring beneficial traits was eight, found in isolates of five species: Acinetobacter calcoaceticus, Bacillus australimaris, B. pumilus, Enterobacter ludwiigi, and Pantoea ananatis. These species were not detected by metabarcoding and have not previously been described as plant-beneficial inhabitants of sugar beets. Thus, our findings point out the necessity of a culture-dependent microbiome analysis and advocate for low-nutrient plant-based media for high-yield isolation of plant-beneficial taxa with multiple beneficial traits. A culture-dependent and -independent approach is required for community diversity assessment. Still, isolation on plant-based media is the best approach to select isolates for potential use as biofertilizers and biopesticides in sugar beet cultivation.
Faecal Microbiota Characterisation of Potamochoerus porcus Living in a Controlled Environment
Authors: Scarafile Donatella , Luise Diana , Motta Vincenzo , Spiezio Caterina , Modesto Monica , Porcu Marzia Mattia , Yitzhak Yadid , Correa Federico , Sandri Camillo , Trevisi Paolo , Mattarelli Paola
Published: June 2023

Intestinal bacteria establish a specific relationship with the host animal, which causes the acquisition of gut microbiota with a unique composition classified as the enterotype. As the name suggests, the Red River Hog is a wild member of the pig family living in Africa, in particular through the West and Central African rainforest. To date, very few studies have analysed the gut microbiota of Red River Hogs (RRHs) both housed under controlled conditions and in wild habitats. This study analysed the intestinal microbiota and the distribution of Bifidobacterium species in five Red River Hog (RRH) individuals (four adults and one juvenile), hosted in two different modern zoological gardens (Parco Natura Viva, Verona, and Bioparco, Rome) with the aim of disentangling the possible effects of captive different lifestyle and host genetics. Faecal samples were collected and studied both for bifidobacterial counts and isolation by means of culture-dependent method and for total microbiota analysis through the high-quality sequences of the V3–V4 region of bacterial 16S rRNA. Results showed a host-specific bifidobacterial species distribution. Indeed, B. boum and B. thermoacidophilum were found only in Verona RRHs, whereas B. porcinum species were isolated only in Rome RRHs. These bifidobacterial species are also typical of pigs. Bifidobacterial counts were about 106 CFU/g in faecal samples of all the individuals, with the only exception for the juvenile subject, showing 107 CFU/g. As in human beings, in RRHs a higher count of bifidobacteria was also found in the young subject compared with adults. Furthermore, the microbiota of RRHs showed qualitative differences. Indeed, Firmicutes was found to be the dominant phylum in Verona RRHs whereas Bacteroidetes was the most represented in Roma RRHs. At order level, Oscillospirales and Spirochaetales were the most represented in Verona RRHs compared with Rome RRHs, where Bacteroidales dominated over the other taxa. Finally, at the family level, RRHs from the two sites showed the presence of the same families, but with different levels of abundance. Our results highlight that the intestinal microbiota seems to reflect the lifestyle (i.e., the diet), whereas age and host genetics are the driving factors for the bifidobacterial population.
Infrared Spectroscopic Investigations of Calcium Oxalate Monohydrate (Whewellite) Dehydration/Rehydration
Authors: White Robert L.
Published: June 2023

Variable-temperature infrared spectroscopy is employed to monitor molecular vibrations during dehydration of calcium oxalate monohydrate (COM) and hydration of anhydrous calcium oxalate (COA). A unique variable-temperature infrared spectroscopy approach combines precise sample temperature control and rapid (2 °C s−1) heating/cooling with high-sensitivity infrared analysis. Infrared spectra are obtained at specific isothermal sample temperatures, while applying linear temperature versus time heating and cooling ramps, and in coordination with programmed temperature steps. Spectrum vibration bands provide information regarding the symmetry and local environments of solid-state water molecules and oxalate anions. When COM is heated, water molecules liberated from different crystallographic sites are selectively detected. Subtle oxalate anion configuration changes associated with water losses are detected based on infrared vibration band shapes and wavenumber trends. Dehydration and rehydration processes occur at lower temperatures and over narrower temperature ranges than conventional thermal analysis methods because samples consist of thin layers of small particles. Reversible and irreversible sample changes are distinguished by using a step heating/cooling temperature program and spectral subtractions. COA temperature-dependent structure variations that occur while heating and cooling samples in an atmosphere with a low water vapor concentration are characterized.