bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanistic Model of Fatigue in Ultrasonic Assisted Machining
Authors: Teimouri Reza , Grabowski Marcin
Published: October 2024

Anti-fatigue design in the machining process of aviation material requires advanced processes to enhance the surface integrity and a holistic model which can optimize the process aiming at maximum fatigue life. In the present study, the axial ultrasonic assisted milling process was utilized to machine the Inconel 718 while the process executes the thermomechanical cutting and peening action simultaneously. To optimize the process factors, a hybrid model using a combination of regression analysis and an analytical model was developed to correlate the machining factors, i.e., vibration amplitude, cutting velocity and feed rate to fatigue life. Herein, the former was used to map the process inputs to surface integrity aspects (SIAs), viz. roughness, hardness and residual stress; then, the SIA was mapped to fatigue life through a stress-based approach. The obtained results revealed that there is close agreement between the measured and predicted values of fatigue life where the prediction error is less than two times the dispersion. On the other hand, applying ultrasonic vibration at the highest amplitude together with the maximum feed rate and cutting velocity yield significant improvement in fatigue life, i.e., three times the same condition without ultrasonic vibration in light of the enhancement of compressive residual stress and work hardening of the surface layers.
Electrochemical Properties and Jet Electrochemical Micromilling of (TiB+TiC)/Ti6Al4V Composites in NaCl+NaNO3 Mixed Electrolyte
Authors: Niu Shen , Wang Hao , Ming Pingmei , Qin Ge , Ren Lei , Liu Huan , Li Xinchao
Published: October 2024

Difficult-to-cut titanium matrix composites (TiB+TiC)/Ti6Al4V have extensive application prospects in the fields of biomedical and aerospace metal microcomponents due to their excellent mechanical properties. Jet electrochemical micromilling (JEMM) technology is an ideal method for machining microstructures that leverages the principle of electrochemical anodic dissolution. However, the matrix Ti6Al4V is susceptible to passivation during electrochemical milling, and the inclusion of high-strength TiB whiskers and TiC particles as reinforcing phases further increases the machining difficulty of (TiB+TiC)/Ti6Al4V. In this study, a novel approach using NaCl+NaNO3 mixed electrolyte for the JEMM of (TiB+TiC)/Ti6Al4V was adopted. Electrochemical behaviors were measured in NaCl and NaCl+NaNO3 electrolytes. In the mixed electrolyte, a higher transpassive potential was required to break down the passive film, which led to better corrosion resistance of (TiB+TiC)/Ti6Al4V, and the exposed reinforcing phases on the dissolved surface were significantly reduced. The results of the JEMM machining indicate that, compared to NaCl electrolyte, using mixed electrolyte effectively mitigates stray corrosion at the edges of micro-grooves and markedly improves the uniformity of both groove depth and width dimensions. Additionally, the surface quality was noticeably improved, with a reduction in Ra from 2.84 μm to 1.03 μm and in Rq from 3.41 μm to 1.40 μm.
Nanochannels in Fused Silica through NaOH Etching Assisted by Femtosecond Laser Irradiation
Authors: Barbato Pasquale , Osellame Roberto , Martínez Vázquez Rebeca
Published: October 2024

Sodium hydroxide (NaOH) is increasingly drawing attention as a highly selective etchant for femtosecond laser-modified fused silica. Unprecedented etching contrasts between the irradiated and pristine areas have enabled the fabrication of hollow, high-aspect-ratio structures in the bulk of the material, overcoming the micrometer threshold as the minimum feature size. In this work, we systematically study the effect of NaOH solutions under different etching conditions (etchant concentration, temperature, and etching time) on the tracks created by tightly focused femtosecond laser pulses to assess the best practices for the fabrication of hollow nanostructures in bulk fused silica.
Processing and Characterization of Spent Nickel–Metal Hydride Type AA Batteries to Recover Valuable Materials (Cobalt, Nickel and Rare Earth Elements)
Authors: Iacob Gheorghe , Ghica Valeriu-Gabriel , Niculescu Florentina , Petrescu Mircea-Ionuţ , Vasile Ana
Published: October 2024

The experimental research was focused on the investigation of valuable material from spent Ni-MH type AA batteries, namely the metal grid anodes and the black mass material (anode and cathode powder). The materials of interest were analyzed by X-ray fluorescence spectroscopy (XRF), ICP-OES (inductively coupled plasma optical emission spectrometry), optical microscopy, scanning electron microscopy (SEM), energy-dispersive X-ray analysis (EDX), electron backscatter diffraction (EBSD), and X-ray diffraction (XRD). The analyzed grids have a high Fe content, but some of them correspond to the Invar alloy with approx. 40% Ni. In the black mass material, round particles and large aggregations were observed by SEM analysis, showing a high degree of degradation. The XRD analysis reveals the presence of only three compounds or phases that crystallize in the hexagonal system: La0.52Ce0.33Pr0.04Nd0.11Co0.6Ni4.4, Ni(OH)2, and La5Ni19. The obtained results provide useful and interesting information that can be used for further research in the recycling and economic assessment of metals from spent Ni-MH batteries.
Dual Fractions Proteomic Analysis of Silica Nanoparticle Interactions with Protein Extracts
Authors: Schvartz Marion , Saudrais Florent , Boulard Yves , Renault Jean-Philippe , Henry Céline , Chédin Stéphane , Pin Serge , Aude Jean-Christophe
Published: October 2024

Dual-fraction proteomics reveals a novel class of proteins impacted by nanoparticle exposure. Background: Nanoparticles (NPs) interact with cellular proteomes, altering biological processes. Understanding these interactions requires comprehensive analyses beyond solely characterizing the NP corona. Methods: We utilized a dual-fraction mass spectrometry (MS) approach to analyze both NP-bound and unbound proteins in Saccharomyces cerevisiae sp. protein extracts exposed to silica nanoparticles (SiNPs). We identified unique protein signatures for each fraction and quantified protein abundance changes using spectral counts. Results: Strong correlations were observed between protein profiles in each fraction and non-exposed controls, while minimal correlation existed between the fractions themselves. Linear models demonstrated equal contributions from both fractions in predicting control sample abundance. Combining both fractions revealed a larger proteomic response to SiNP exposure compared to single-fraction analysis. We identified 302/56 proteins bound/unbound to SiNPs and an additional 196 “impacted” proteins demonstrably affected by SiNPs. Conclusion: This dual-fraction MS approach provides a more comprehensive understanding of nanoparticle interactions with cellular proteomes. It reveals a novel class of “impacted” proteins, potentially undergoing conformational changes or aggregation due to NP exposure. Further research is needed to elucidate their biological functions and the mechanisms underlying their impact.
Bayesian Optimization Using Simulation-Based Multiple Information Sources over Combinatorial Structures
Authors: Sabbatella Antonio , Ponti Andrea , Candelieri Antonio , Archetti Francesco
Published: October 2024

Bayesian optimization due to its flexibility and sample efficiency has become a standard approach for simulation optimization. To reduce this problem, one can resort to cheaper surrogates of the objective function. Examples are ubiquitous, from protein engineering or material science to tuning machine learning algorithms, where one could use a subset of the full training set or even a smaller related dataset. Cheap information sources in the optimization scheme have been studied in the literature as the multi-fidelity optimization problem. Of course, cheaper sources may hold some promise toward tractability, but cheaper models offer an incomplete model inducing unknown bias and epistemic uncertainty. In this manuscript, we are concerned with the discrete case, where fx,wi is the value of the performance measure associated with the environmental condition wi and p(wi) represents the relevance of the condition wi (i.e., the probability of occurrence or the fraction of time this condition occurs). The main contribution of this paper is the proposal of a Gaussian-based framework, called augmented Gaussian process (AGP), based on sparsification, originally proposed for continuous functions and its generalization in this paper to stochastic optimization using different risk profiles for combinatorial optimization. The AGP leverages sample and cost-efficient Bayesian optimization (BO) of multiple information sources and supports a new acquisition function to select the new source–location pair considering the cost of the source and the (location-dependent) model discrepancy. An extensive set of computational results supports risk-aware optimization based on CVaR (conditional value-at-risk). Computational experiments confirm the actual performance of the MISO-AGP method and the hyperparameter optimization on benchmark functions and real-world problems.
A Study on the Production-Inventory Problem with Omni-Channel and Advance Sales Based on the Brand Owner’s Perspective
Authors: Pan Jialiang , Lu Chi-Jie , Chen Wei-Jen , Wu Kun-Shan , Yang Chih-Te
Published: October 2024

This study explores a supply chain product-inventory problem with advance sales under the omni-channel strategies (physical and online sales channels) based on the brand owner’s business model and develops corresponding models that have not been proposed in previous studies. In addition, because the brand owner is a member of the supply chain, and has different handling methods for defective products or products returned by customers in various retail channels, defective products or returned products are included in the supply chain models to comply with actual operating conditions and fill the research gap in the handling of defective/returned products. Regarding the mathematical model’s development, we first clarify the definition of model parameters and relevant data collection, and then establish the production-inventory models with omni-channel strategies and advance sales. The primary objective is to determine the optimal production, delivery, and replenishment decisions of the manufacturer, physical agent, and online e-commerce company in order to maximize the joint total profits of the entire supply chain system. Further, this study takes the supply chain system of mobile game steering wheel products as an example, uses data consistent with the actual situation to demonstrate the optimal solutions of the models, and conducts sensitivity analysis for the proposed model. The findings reveal that increased demand shortens the replenishment cycle and raises order quantity and shipment frequency in the physical channel, similar to the online channel during normal sales. However, during the online pre-order period, higher demand reduces order quantity and cycle length but still increases shipment frequency. Rising ordering or fixed shipping costs lead to higher order quantity and cycle length in both channels, but variable shipping costs in the online channel reduce them. Market price increases boost order quantity and frequency in the online channel, while customer return rates significantly impact inventory decisions.
Development of a Digital Twin Driven by a Deep Learning Model for Fault Diagnosis of Electro-Hydrostatic Actuators
Authors: Rodriguez-Aguilar Roman , Marmolejo-Saucedo Jose-Antonio , Köse Utku
Published: October 2024

The first quarter of the 21st century has witnessed many technological innovations in various sectors. Likewise, the COVID-19 pandemic triggered the acceleration of digital transformation in organizations driven by artificial intelligence and communication technologies in Industry 4.0 and Industry 5.0. Aiming at the construction of digital twins, virtual representations of a physical system allow real-time bidirectional communication. This will allow the monitoring of operations, identification of possible failures, and decision making based on technical evidence. In this study, a fault diagnosis solution is proposed, based on the construction of a digital twin, for a cloud-based Industrial Internet of Things (IIoT) system contemplating the control of electro-hydrostatic actuators (EHAs). The system was supported by a deep learning model using Long Short-Term Memory (LSTM) networks for an effective diagnostic approach. The implemented study considers data preparation and integration and system development and application to evaluate the performance against the fault diagnosis problem. According to the results obtained, positive results are shown in the construction of the digital twin using a deep learning model for the fault diagnosis problem of an active EHA-IIoT configuration.
LLE-STD: Traffic Sign Detection Method Based on Low-Light Image Enhancement and Small Target Detection
Authors: Wang Tianqi , Qu Hongquan , Liu Chang’an , Zheng Tong , Lyu Zhuoyang
Published: October 2024

With the continuous development of autonomous driving, traffic sign detection, as an essential subtask, has witnessed constant updates in corresponding technologies. Currently, traffic sign detection primarily confronts challenges such as the small size of detection targets and the complexity of detection scenarios. This paper focuses on detecting small traffic signs in low-light scenarios. To address these issues, this paper proposes a traffic sign detection method that integrates low-light image enhancement with small target detection, namely, LLE-STD. This method comprises two stages: low-light image enhancement and small target detection. Based on classic baseline models, we tailor the model structures by considering the requirements of lightweight traffic sign detection models and their adaptability to varying image qualities. The two stages are then coupled to form an end-to-end processing procedure. During experiments, we validate the performance of low-light image enhancement small target detection, and adaptability to images of different qualities using the public datasets GTSDB, TT-100K, and GLARE. Compared to classic models, LLE-STD demonstrates significant advantages. For example, the mAP results tested on the GLARE dataset show that LLE-STD outperforms RetinaNet by approximately 15%. This research can facilitate the practical application of deep learning-based intelligent methods in the field of autonomous driving.
A Certificate-Less Distributed Key Management Scheme for Space Networks
Authors: Luo Changyuan , Sun Ling
Published: October 2024

The specificity and complexity of space networks render the traditional key management mechanism no longer applicable. The certificate-less-based distributed spatial network key management scheme proposed in this paper combines the characteristics of space networks, solving the problems regarding the difficulty of implementing centralized key management in space networks and the excessive overhead required for maintaining public key certificates by constructing a distributed key generation center and establishing strategies such as private key updates, master key component updates, and session key negotiation. This method also avoids the key escrow problem inherent in existing identity-based key management schemes. This scheme provides the DPKG construction method for space networks; designs the update strategy for the DPKG node’s master key sharing, providing a specific update algorithm; introduces the batch private key update mechanism; and uses the mapping function to evenly distribute the node’s update requests throughout the update time period, avoiding the problem of overly concentrated update requests. After analysis and simulation verification, it was proven that the scheme can meet the necessary security requirements, offering good stability and scalability.
A New Class of Braided Block Codes Constructed by Convolutional Interleavers
Authors: Vafi Sina
Published: October 2024

Parallel Concatenated Block (PCB) codes are conventionally represented as high-rate codes with low error correcting capability. To form a reliable and outstanding code, this paper presents a modification on the structure of PCB codes, which is accomplished by encoding some parity bits of one of their component codes. For the newly proposed code, named as the braided code, non-stuff bit-based convolutional interleavers are applied, aiming to minimize the design complexity while ensuring the proper permutations of the original message and selected parity bits. To precisely determine the error correcting capability, a tight bound for the minimum weight of braided code is presented. Additionally, further analyses are provided, which verify iterative decoding performance and the complexity of the constructed code. It is concluded that an outstanding braided code is formed by utilizing a reasonable number of iterations applied at its decoding processes, while maintaining its design complexity at a level similar to other well-known codes. The significant performance of short and long-length-based braided codes is evident in both waterfall and error floor regions.
Characterization of Bach and Cotton Tensors on a Class of Lorentzian Manifolds
Authors: Li Yanlin , Siddesha M. S. , Kumara H. Aruna , Praveena M. M.
Published: October 2024

In this work, we aim to investigate the characteristics of the Bach and Cotton tensors on Lorentzian manifolds, particularly those admitting a semi-symmetric metric ω-connection. First, we prove that a Lorentzian manifold admitting a semi-symmetric metric ω-connection with a parallel Cotton tensor is quasi-Einstein and Bach flat. Next, we show that any quasi-Einstein Lorentzian manifold admitting a semi-symmetric metric ω-connection is Bach flat.
Continuity Equation of Transverse Kähler Metrics on Sasakian Manifolds
Authors: Fan Yushuang , Zheng Tao
Published: October 2024

We introduce the continuity equation of transverse Kähler metrics on Sasakian manifolds and establish its interval of maximal existence. When the first basic Chern class is null (resp. negative), we prove that the solution of the (resp. normalized) continuity equation converges smoothly to the unique η-Einstein metric in the basic Bott–Chern cohomological class of the initial transverse Kähler metric (resp. first basic Chern class). These results are the transverse version of the continuity equation of the Kähler metrics studied by La Nave and Tian, and also counterparts of the Sasaki–Ricci flow studied by Smoczyk, Wang, and Zhang.
Navier–Stokes Equation in a Cone with Cross-Sections in the Form of 3D Spheres, Depending on Time, and the Corresponding Basis
Authors: Jenaliyev Muvasharkhan , Serik Akerke , Yergaliyev Madi
Published: October 2024

The work establishes the unique solvability of a boundary value problem for a 3D linearized system of Navier–Stokes equations in a degenerate domain represented by a cone. The domain degenerates at the vertex of the cone at the initial moment of time, and, as a consequence of this fact, there are no initial conditions in the problem under consideration. First, the unique solvability of the initial-boundary value problem for the 3D linearized Navier–Stokes equations system in a truncated cone is established. Then, the original problem for the cone is approximated by a countable family of initial-boundary value problems in domains represented by truncated cones, which are constructed in a specially chosen manner. In the limit, the truncated cones will tend toward the original cone. The Faedo–Galerkin method is used to prove the unique solvability of initial-boundary value problems in each of the truncated cones. By carrying out the passage to the limit, we obtain the main result regarding the solvability of the boundary value problem in a cone.
Double Tseng’s Algorithm with Inertial Terms for Inclusion Problems and Applications in Image Deblurring
Authors: Thammasiri Purit , Berinde Vasile , Petrot Narin , Ungchittrakool Kasamsuk
Published: October 2024

In this research paper, we present a novel theoretical technique, referred to as the double Tseng’s algorithm with inertial terms, for finding a common solution to two monotone inclusion problems. Developing the double Tseng’s algorithm in this manner not only comprehensively expands theoretical knowledge in this field but also provides advantages in terms of step-size parameters, which are beneficial for tuning applications and positively impact the numerical results. This new technique can be effectively applied to solve the problem of image deblurring and offers numerical advantages compared to some previously related results. By utilizing certain properties of a Lipschitz monotone operator and a maximally monotone operator, along with the identity associated with the convexity of the quadratic norm in the framework of Hilbert spaces, and by imposing some constraints on the scalar control conditions, we can achieve weak convergence to a common zero point of the sum of two monotone operators. To demonstrate the benefits and advantages of this newly proposed algorithm, we performed numerical experiments to measure the improvement in the signal–to–noise ratio (ISNR) and the structural similarity index measure (SSIM). The results of both numerical experiments (ISNR and SSIM) demonstrate that our new algorithm is more efficient and has a significant advantage over the relevant preceding algorithms.
Modified Liu Parameters for Scaling Options of the Multiple Regression Model with Multicollinearity Problem
Authors: Araveeporn Autcha
Published: October 2024

The multiple regression model statistical technique is employed to analyze the relationship between the dependent variable and several independent variables. The multicollinearity problem is one of the issues affecting the multiple regression model, occurring in regard to the relationship among independent variables. The ordinal least square is the standard method to evaluate parameters in the regression model, but the multicollinearity problem affects the unstable estimator. Liu regression is proposed to approximate the Liu estimators based on the Liu parameter, to overcome multicollinearity. In this paper, we propose a modified Liu parameter to estimate the biasing parameter in scaling options, comparing the ordinal least square estimator with two modified Liu parameters and six standard Liu parameters. The performance of the modified Liu parameter is considered, generating independent variables from the multivariate normal distribution in the Toeplitz correlation pattern as the multicollinearity data, where the dependent variable is obtained from the independent variable multiplied by a coefficient of regression and the error from the normal distribution. The mean absolute percentage error is computed as an evaluation criterion of the estimation. For application, a real Hepatitis C patients dataset was used, in order to investigate the benefit of the modified Liu parameter. Through simulation and real dataset analysis, the results indicate that the modified Liu parameter outperformed the other Liu parameters and the ordinal least square estimator. It can be recommended to the user for estimating parameters via the modified Liu parameter when the independent variable exhibits the multicollinearity problem.
Relation between Urine Cytological Findings and Renal Function in Patients with Kidney Stones in Taif, Saudi Arabia
Authors: Qahtani Sahar Ali , Ismail Khadiga A. , Hagag Howaida M. , Hulbah Maram Jamel , Bakhuraysah Maha M. , Johari Nidaa Mahmoud , Alotaibi Salman Mohammed , Alajmani Seham , Alseyali Hani Diafallah , Ayoub Manal Ali , Althagafi Khalid Abdullah , Alnofaie Ali Awad , Abdulaziz Abdulbadea Dawod , Samman Abdulhadi , Noorwali Hussain , Abdelwahed Mohammed S. , Hasan Abdulkarim
Published: October 2024

Background and Objectives: Urine serves as a vital diagnostic fluid, and urine cytology analysis plays a crucial role in identifying urinary system illnesses such as bladder cancer and kidney stones. The Paris System for Reporting Urinary Cytology establishes a uniform method for diagnosing urinary tract cancer. This study aimed to provide valuable insights that can inform diagnostic strategies related to kidney stones and ultimately improve patient outcomes via the early detection of the cellular changes associated with kidney stones and their relation to kidney function tests. Materials and Methods: A comparative study was conducted and comprised two groups: group 1, consisting of 50 patients diagnosed with kidney stones, and group 2, comprising 50 patients diagnosed with other kidney diseases. Renal function tests and urinalysis (via the PAP staining of urine cellular deposits to detect nuclear changes) were performed, and the results were analyzed. Results: There was a statistically significant increase in urinary red blood cells, white blood cells, and nuclear reactive atypical changes in urinary sediments of kidney stone patients compared to the patients without stones, while there was a decrease in the estimated glomerular filtration rate (eGFR). eGFR showed a 96.7% specificity in detecting cases with nuclear reactive atypia. Conclusions: eGFR emerges as a reliable diagnostic marker for the comprehensive assessment of kidney stones, particularly when associated with nuclear atypia. The significant correlation between the indicators of chronic kidney disease, such as decreased eGFR, and the presence of kidney stones emphasizes the urgent need for efficient diagnostic practices.
Association between Polypharmacy and Adverse Events in Patients with Alzheimer’s Disease: An Analysis of the Japanese Adverse Drug Event Report Database (JADER)
Authors: Otani Nobuhiro , Kanda Kanae , Ngatu Nlandu Roger , Murakami Akitsu , Yamadori Yusuke , Hirao Tomohiro
Published: October 2024

Background and Objectives: Alzheimer’s disease is a global health concern, with a rising prevalence among the elderly. Current pharmacological treatments, including acetylcholinesterase inhibitors (AChEIs) and N-Methyl D-Aspartate (NMDA) receptor antagonists, are associated with adverse events (AEs), particularly in the context of polypharmacy. This study aimed to investigate the relationship between Alzheimer’s disease treatment combinations, the number of concomitant medications, and the occurrence of AEs. Materials and Methods: Data from the Japanese Adverse Drug Event Report database, spanning from April 2004 to June 2020, were analyzed. Patients aged 60 and older with Alzheimer’s disease treated with AChEIs (donepezil, galantamine, and rivastigmine) or the NMDA receptor antagonist memantine were included. Logistic regression models were employed to assess the association between AEs and Alzheimer’s disease drug combinations, as well as the number of concomitant medications. Results: Among 2653 patients, 47.7% were prescribed five or more drugs. The frequency of AEs was 6.4% for bradycardia, 4.6% for pneumonia, 3.6% for altered state of consciousness, 3.5% for seizures, 3.5% for decreased appetite, 3.5% for vomiting, 3.4% for loss of consciousness, 3.4% for fracture, 3.2% for cardiac failure, and 3.0% for falls. The combination of memantine with AChEIs was associated with a higher risk of bradycardia, whereas donepezil alone was linked to a reduced risk of fractures and falls. Polypharmacy was significantly correlated with an increased incidence of AEs, particularly altered state of consciousness, decreased appetite, vomiting, and falls. The adjusted odds ratios for using five or more drugs compared to no drugs was 10.45 for altered state of consciousness, 7.92 for decreased appetite, 4.74 for vomiting, and 5.95 for falls. Conclusions: In the treatment of Alzheimer’s disease, the occurrence of AEs is associated with the number of concurrent medications, independently of the known AEs of Alzheimer’s disease drugs and their combination patterns.
Arthroscopic Debridement Enhanced by Intra-Articular Antibiotic-Loaded Calcium Sulphate Beads for Septic Arthritis of a Native Knee Following Iatrogenic Joint Injection: A Case Report
Authors: Alongi Simone , Troiano Elisa , Latino Cristina , Colasanti Giovanni Battista , Greco Tommaso , Perisano Carlo , Mosca Massimiliano , Giannotti Stefano , Mondanelli Nicola
Published: October 2024

Septic arthritis (SA) represents an orthopedics urgency and mainly affects the knee joint. Due to its devastating effects on cartilage, immediate management is crucial. SA is characterized by an annual incidence of 2 to 10 cases per 100,000 individuals, with mortality rates fluctuating between 0.5% and 15%, with a substantially higher mortality rate observed in older people (15%) in contrast to younger cohorts (4%). The etiology of septic arthritis is multifactorial: a spectrum of Gram-positive and Gram-negative bacteria can contribute to the development of this condition, especially Staphylococcus aureus. The treatment involves urgent (arthroscopic or arthrotomic) debridement associated with adequate antibiotic therapy. Intra-articular antibiotic carriers can also be used to increase their local concentration and effectiveness. The case of a 67-year-old woman affected by knee SA from methicillin-susceptible S. aureus is presented. She was treated with an arthroscopic debridement enhanced by intra-articular antibiotic-loaded calcium sulphate beads, together with antibiotic therapy. At 2-year follow up, the infection had been eradicated and the patient fully recovered. This is the first description, to our knowledge, in the English literature, of the use of antibiotic-loaded calcium sulphate beads as an adjuvant in the surgical treatment of SA of a native knee joint.
Serum Glial Fibrillary Acidic Protein Can Predict Cross-Sectional Vasculitis Activity by Reflecting Renal Involvement in Patients with Antineutrophil Cytoplasmic Antibody-Associated Vasculitis
Authors: Lee Lucy Eunju , Yoon Taejun , Chung Jihye , Ha Jang Woo , Park Yong-Beom , Lee Sang-Won
Published: October 2024

Background and Objectives: Glial fibrillary acidic protein (GFAP) is a type III intermediate filament protein primarily produced by cells in the central nervous system (CNS) and other major organs such as the kidneys. This study investigated whether serum GFAP could be used to estimate cross-sectional vasculitis activity presented via the Birmingham vasculitis activity score (BVAS) in patients with antineutrophil cytoplasmic antibody-associated vasculitis (AAV). Materials and Methods: This study included 74 patients with AAV. Clinical and laboratory data at diagnosis including BVAS and C-reactive protein (CRP) were reviewed. During follow-up, all-cause mortality and end-stage kidney disease (ESKD) were considered poor outcomes. Serum GFAP was measured from sera collected and stored at diagnosis. Results: The median age of the 74 patients was 63.5 years. Serum GFAP was inversely correlated with the cross-sectional BVAS (r = −0.373) and CRP (r = −0.320). It was also significantly correlated with general (r = −0.237) and renal (r = −0.335) manifestations among BVAS systemic items, and furthermore, among minor items of renal manifestation, correlating with sum scores for proteinuria (r = −0.409) and haematuria (r = −0.305). Additionally, compared with patients with serum GFAP > 194.9 pg/mL, those with serum GFAP ≤ 194.9 pg/mL showed a higher risk for progression to ESKD (relative risk 3.150) and a significantly lower cumulative ESKD-free survival rate. Conclusions: This study demonstrated the clinical potential of serum GFAP at diagnosis for predicting not only cross-sectional vasculitis activity through the anticipation of the extent of renal involvement but also future progression to ESKD in patients with AAV.
Gerstmann Syndrome in an Elderly Patient: A Case Report Presented with a Complete Tetrad of Symptoms
Authors: Toader Corneliu , Covache-Busuioc Razvan-Adrian , Rădoi Petrinel Mugurel , Covlea Christian-Adelin , Popa Andrei Adrian , Dumitrascu David-Ioan , Ciurea Alexandru Vlad
Published: October 2024

Gerstmann syndrome, alternatively recognized as angular gyrus syndrome, epitomizes a complex cognitive impairment that has ignited substantial scholarly discourse within the realms of neurology and neuropsychology. The syndrome’s original portrayal was, however, changed. It was demonstrated that the manifestation of its symptomatic tetrad, consisting of four main neurological impairments, is not invariably complete and frequently occurs alongside additional cognitive deficits. Furthermore, the precise cerebral localization of Gerstmann syndrome was traditionally posited to be the left angular gyrus; however, studies mention the possible involvement of other eloquent cerebral areas being pathognomonic. This case report delves into the case of an 86-year-old subject who exhibited the quintessential quartet of symptoms initially delineated by Josef Gerstmann, proposing that elderly patients may manifest a predisposition towards presenting the fully characterized symptomatology initially outlined by Gerstmann.
Mutations of the Cx43 Gene in Non-Small Cell Lung Cancer: Association with Aberrant Localization of Cx43 Protein Expression and Tumor Progression
Authors: Chen Jung-Chien , Yeh Kun-Tu , Lin Yueh-Min , Cheng Ya-Wen
Published: October 2024

Background and Objectives: The Connexin43 (Cx43) gene is a suspected tumor suppressor gene, as re-expressed wild-type Cx43 genes reduce the malignancy potential of tumor cells. However, the role of Cx43 gene expression in human lung tumorigenesis remains unclear. Materials and Methods: Tumor tissues from 165 primary lung cancer patients were collected to study Cx43 protein expression and gene mutations using immunohistochemistry and direct DNA sequencing. In addition, Cx43 genes with or without mutations were transfected to CL-3 human lung cancer cells to confirm the function of these mutant forms of the Cx43 gene. Results: Aberrant localization of Cx43 protein in the nucleus and cytoplasm of tumor cells was detected in 14 out of 165 non-small cell lung cancer (NSCLC) patients. Mutations in the Cx43 gene were also found in patients with aberrant Cx43 localization, and transfection of these mutant genes into lung cancer cells enhanced their proliferation. Conclusions: To our knowledge, this is the first study to demonstrate Cx43 gene mutations in human lung neoplasm, supporting the hypothesis that Cx43 may function as a tumor suppressor in some lung cancer patients. Additionally, the findings suggest an association between aberrant localization of Cx43 protein expression and tumor progression.
The Efficiency of Polyester-Polysulfone Membranes, Coated with Crosslinked PVA Layers, in the Water Desalination by Pervaporation
Authors: Gortat Izabela , Chruściel Jerzy J. , Marszałek Joanna , Żyłła Renata , Wawrzyniak Paweł
Published: October 2024

Composite polymer membranes were obtained using the so-called dry phase inversion and were used for desalination of diluted saline water solutions by pervaporation (PV) method. The tests used a two-layer backing, porous, ultrafiltration commercial membrane (PS20), which consisted of a supporting polyester layer and an active polysulfone layer. The active layer of PV membranes was obtained in an aqueous environment, in the presence of a surfactant, by cross-linking a 5 wt.% aqueous solution of polyvinyl alcohol (PVA)—using various amounts of cross-linking substances: 50 wt.% aqueous solutions of glutaraldehyde (GA) or citric acid (CA) or a 40 wt.% aqueous solution of glyoxal. An ethylene glycol oligomer (PEG 200) was also used to prepare active layers on PV membranes. Witch its help a chemically cross-linked hydrogel with PVA and cross-linking reagents (CA or GA) was formed and used as an active layer. The manufactured PV membranes (PVA/PSf/PES) were used in the desalination of water with a salinity of 35‰, which corresponds to the average salinity of oceans. The pervaporation method was used to examine the efficiency (productivity and selectivity) of the desalination process. The PV was carried at a temperature of 60 °C and a feed flow rate of 60 dm3/h while the membrane area was 0.005 m2. The following characteristic parameters of the membranes were determined: thickness, hydrophilicity (based on contact angle measurements), density, degree of swelling and cross-linking density and compared with the analogous properties of the initial PS20 backing membrane. The physical microstructure of the cross-section of the membranes was analyzed using scanning electron microscopy (SEM) method.
Effects of Solidification Thermal Variables on the Microstructure and Hardness of the Silicon Aluminum Bronze Alloy CuAl6Si2
Authors: Nascimento Paulo Henrique Tedardi do , Santos Vinicius Torres dos , Luca Ricardo de , Silva Marcio Rodrigues da , Lobo Flavia Goncalves , Teram Rogerio , Nascimento Mauricio Silva , Cozza Ronaldo Camara , Couto Antonio Augusto , Santos Givanildo Alves dos , Filho Anibal de Andrade Mendes
Published: October 2024

The properties of the final product obtained by solidification directly result from the thermal variables during solidification. This study aims to analyze the influence of thermal solidification variables on the hardness, microstructure, and phases of the CuAl6Si2 alloy. The material was solidified using unidirectional solidification equipment under non-stationary heat flow conditions, where heat extraction is conducted through a water-cooled graphite base. The thermal solidification variables were extracted using a data acquisition system, and temperature was monitored at six different positions, with cooling rates ranging from 217 to 3 °C/min from the nearest to the farthest position from the heat extraction point. An optical microscope, scanning electron microscope (SEM), and X-ray diffraction (XRD) were used to verify the fusion structure and determine the volumetric fraction of the formed phases. The XRD results showed the presence of β phases, α phases, and possible Fe3Si2 and Fe5Si3 intermetallics with different morphologies and volumetric fractions. Positions with lower cooling rates showed an increased volume fraction of the α phase and possible intermetallics compared to positions with faster cooling. High cooling rates increased the Brinell hardness of the alloy due to the refined and equiaxed β metastable phase, varying from 143 HB to 126 HB for the highest and lowest rates, respectively.
Microstructure and Wear Resistance of FeCrV15 Coatings by Laser Cladding
Authors: Bi Zhiwei , Li Tianqing
Published: October 2024

Improving the surface performance and service life of 60Si2Mn steel is an important issue in agricultural machinery. A FeCrV15 coating layer may exhibit excellent performance in wear resistance. This research focuses on studying the microstructure and wear resistance of the FeCrV15 coating layer at various scanning speeds through laser cladding. Microstructure, phase distribution, surface hardness, and wear resistance of the coating layers are analyzed using X-ray diffraction (XRD), scanning electron microscopy (SEM), a microhardness tester, and laser confocal microscopy. The results indicate that the FeCrV15 alloy coating consists of γ-Fe, V8C7, and Cr7C3. The microhardness of the FeCrV15 coatings increases with the increase in the scanning speed. At a scanning speed of 8 mm/s, the highest microhardness reaches 727.5 ± 27 HV, approximately 2.5 times higher than the substrate. The friction and wear test of the coating is conducted using a 4 mm diameter Si3N4 ball grinding pair. The coatings prepared at different scanning speeds exhibit lower average coefficients of friction and wear rates compared to the substrate. Both the average coefficient of friction and wear rate decrease with increasing scanning speed. At a scanning speed of 8 mm/s, the lowest average coefficient of friction and the lowest wear rate were observed. The main wear mechanisms of the coating are oxidative wear and adhesive wear, with a small amount of abrasive wear.
Accelerating Laser Powder Bed Fusion: The Influence of Roller-Spreading Speed on Powder Spreading Performance
Authors: Salim Mohamed Awad , Tullis Stephen , Elbestawi Mohamed
Published: October 2024

The powder spreading process is a fundamental element within the laser powder bed fusion (PBF-LP) framework given its pivotal role in configuring the powder bed. This configuration significantly influences subsequent processing steps and ultimately determines the quality of the final manufactured part. This research paper presents a comprehensive analysis of the impacts of varying spreading speeds, which are enabled by different roller configurations, on powder distribution in PBF-LP. By utilizing extensive Discrete Element Method (DEM) modelling, we systematically examine how spreading speed affects vital parameters within the spreading process, including packing density, mass fraction, and actual layer thickness. Our exploration of various roller configurations has revealed that increasing spreading speed generally decreases packing density and layer thickness for non-rotating, counter-rotating, and forward-rotating rollers with low clockwise rotational speeds (sub-rolling) due to powder dragging. However, a forward-rotating roller with a high clockwise rotational speed (super-rolling) balances momentum transfer, enhancing packing density and layer thickness while increasing surface roughness. This configuration significantly improves the uniformity and density of the powder bed, providing a technique to accelerate the spreading process while maintaining and not reducing packing density. Furthermore, this configuration offers crucial insights into optimizing additive manufacturing processes by considering the complex relationships between spreading speed, roller configuration, and powder spreading quality.
Reliability Simulation of IGBT Module with Different Solders Based on the Finite Element Method
Authors: Ma Haoran , Gou Min , Tian Xingjian , Tan Wei , Liang Hongwei
Published: October 2024

The interconnecting solder is a key control factor for the reliability of electronic power packaging because it highly affects the junction temperature of insulated-gate bipolar transistor (IGBT) modules and is prone to plasticity, creep, and other failure behaviors under temperature-change environments. In this paper, the interconnecting performance and fatigue life of five different kinds of solders such as SAC305, sintered silver, Au80Sn20, sintered copper, and pure In under direct current (DC), power cycle, and electro-thermal coupling complex environments were studied based on electro-thermal multi-physical field coupling finite element simulation method, respectively. Results show that the sintered silver owns the most outstanding thermal reliability and the DC operating junction temperature of the IGBT module after utilizing sintered silver solder is only 90.2 °C, which is nearly 15 °C lower than that of the IGBT module utilizing SAC305 solder. Furthermore, in the power cycle reliability test, the fatigue life of Au80Sn20 solder reaches a maximum of 3.26 × 107 cycles while the life of indium presents only 5.85 × 103 cycles, a difference of nearly four orders of magnitude. Finally, under the complex environment of electro-thermal coupling, the fatigue life of Au80Sn20 solder is also the largest at 1.9 × 106 cycles, while the smallest life of solder becomes SAC305 solder at 4.44 × 102 cycles. The results of this paper can provide a theoretical basis for solder selection and life prediction of the IGBT module, which is of great significance in improving the reliability of power electronic packaging.
Development of a Triplex qPCR Assay Based on the TaqMan Probe for the Detection of Haemophilus parasuis, Streptococcus suis Serotype 2 and Pasteurella multocida
Authors: Li Kaili , Zhang Yu , Luo Tingyu , Li Changwen , Yu Haibo , Wang Wei , Zhang He , Chen Hongyan , Xia Changyou , Gao Caixia
Published: October 2024

Porcine respiratory disease is a significant economic problem for the global swine industry. Haemophilus parasuis (H. parasuis), Streptococcus suis (S. suis), and Pasteurella multocida (P. multocida) are three important pathogenic bacteria of the swine respiratory tract. Notably, the three pathogens not only frequently manifest as mixed infections, but their striking clinical similarities also present difficulties for pig populations in terms of disease prevention and treatment. Thus, we developed a triplex real-time quantitative polymerase chain reaction (qPCR) assay based on a TaqMan probe for the detection of H. parasuis, S. suis serotype 2, and P. multocida. Primers and probes were designed to target the conserved regions of the H. parasuis OmpP2 gene, the S. suis serotype 2 gdh gene, and the P. multocida Kmt1 gene. By optimizing the reaction system and conditions, a triplex qPCR method for simultaneous detection of H. parasuis, S. suis serotype 2, and P. multocida was successfully established. The amplification efficiencies of the standard curves for all three pathogens were found to be highly similar, with values of 102.105% for H. parasuis, 105.297% for S. suis serotype 2, and 104.829% for P. multocida, and all R2 values achieving 0.999. The specificity analysis results showed that the triplex qPCR method had a strong specificity. The sensitivity test results indicated that the limit of detection can reach 50 copies/μL for all three pathogens. Both intra- and inter-assay coefficients of variation for repeatability were below 1%. This triplex qPCR method was shown to have good specificity, sensitivity, and reproducibility. Finally, the triplex qPCR method established in this study was compared with the nested PCR as recommended by the Chinese national standard (GB/T34750-2017) for H. parasuis, the PCR as recommended by the Chinese national standard (GB/T 19915.9-2005) for S. suis serotype 2, and the PCR as recommended by the Chinese agricultural industry standard (NY/T 564-2016) for P. multocida by detecting the same clinical samples. Both methods are reasonably consistent, while the triplex qPCR assay was more sensitive. In summary, triplex qPCR serves not only as a rapid and accurate detection and early prevention method for these pathogens but also constitutes a robust tool for microbial quality control in specific pathogen-free pigs.
New Insights into the Epidemiological Characteristics of Mycoplasma pneumoniae Infection before and after the COVID-19 Pandemic
Authors: Wu Qianyue , Pan Xiaozhou , Han Dingding , Ma Zhan , Zhang Hong
Published: October 2024

Mycoplasma pneumoniae (M. pneumoniae), a prevalent respiratory pathogen affecting children and adolescents, is known to trigger periodic global epidemics. The most recent significant outbreak commenced in the first half of 2023 and reached its peak globally during the autumn and winter months. Considering the worldwide repercussions of the COVID-19 pandemic, it has become increasingly essential to delve into the epidemiological characteristics of M. pneumoniae both before and after the pandemic. This review aims to provide a comprehensive analysis of the key features of M. pneumoniae epidemics in the pre-and post-COVID-19 contexts, including but not limited to shifts in the susceptible population, the molecular genotypes of the pathogen, the clinical manifestations, and potential new trends in drug resistance. Additionally, we will introduce the latest advancements in the diagnosis of M. pneumoniae.