bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of Wear Rate in Al/SiC Metal Matrix Composites Using a Neurosymbolic Artificial Intelligence (NSAI)-Based Algorithm
Authors: Mishra Akshansh , Jatti Vijaykumar S.
Published: June 2023

This research paper delves into an innovative utilization of neurosymbolic programming for forecasting wear rates in aluminum-silicon carbide (Al/SiC) metal matrix composites (MMCs). The study scrutinizes compositional transformations in MMCs with various weight percentages of SiC (0%, 3%, and 5%), employing comprehensive spectroscopic analysis. The effect of SiC integration on the compositional distribution and ratio of elements within the composite is meticulously examined. In a novel move for this field of research, the study introduces and applies neurosymbolic programming as a novel computational modeling approach. The performance of this cutting-edge methodology is compared to a traditional simple artificial neural network (ANN). The neurosymbolic algorithm exhibits superior performance, providing lower mean squared error (MSE) values and higher R-squared (R2) values across both training and validation datasets. This highlights its potential for delivering more precise and resilient predictions, marking a significant development in the field. Despite the promising results, the study recognizes that the performance of the model might vary based on specific characteristics of the composite material and operational conditions. Thus, it encourages future studies to authenticate and expand these innovative findings across a wider spectrum of materials and conditions. This research represents a substantial advancement towards a more profound understanding of wear rates in Al/SiC MMCs and emphasizes the potential of the novel neurosymbolic programming in predictive modeling of complex material systems.
High-Temperature Liquid–Liquid Phase Transition in Glass-Forming Liquid Pd43Ni20Cu27P10
Authors: Zhou Huanyi , Yu Pengfei , Miao Xiaoyu , Peng Cunjin , Fu Lulu , Si Conghui , Lu Qifang , Chen Shunwei , Han Xiujun
Published: June 2023

Liquid–liquid phase transition (LLPT) is a transition from one liquid state to another with the same composition but distinct structural change, which provides an opportunity to explore the relationships between structural transformation and thermodynamic/kinetic anomalies. Herein the abnormal endothermic LLPT in Pd43Ni20Cu27P10 glass-forming liquid was verified and studied by flash differential scanning calorimetry (FDSC) and ab initio molecular dynamics (AIMD) simulations. The results show that the change of the atomic local structure of the atoms around the Cu-P bond leads to the change in the number of specific clusters <0 2 8 0> and <1 2 5 3>, which leads to the change in the liquid structure. Our findings reveal the structural mechanisms that induce unusual heat-trapping phenomena in liquids and advance the understanding of LLPT.
Mesoporous Silica Modified with Polydopamine and Zinc Ions as a Potential Carrier in the Controlled Release of Mercaptopurine
Authors: Sandomierski Mariusz , Chojnacka Martyna , Długosz Maria , Pokora Monika , Zwolińska Joanna , Majchrzycki Łukasz , Voelkel Adam
Published: June 2023

Mercaptopurine is one of the drugs used in the treatment of acute lymphoblastic leukemia. A problem with mercaptopurine therapy is its low bioavailability. This problem can be solved by preparing the carrier that releases the drug in lower doses but over a longer period of time. In this work, polydopamine-modified mesoporous silica with adsorbed zinc ions was used as a drug carrier. SEM images confirm the synthesis of spherical carrier particles. The particle size is close to 200 nm, allowing for its use in intravenous delivery. The zeta potential values for the drug carrier indicate that it is not prone to agglomeration. The effectiveness of drug sorption is indicated by a decrease in the zeta potential and new bands in the FT-IR spectra. The drug was released from the carrier for 15 h, so all of the drug can be released during circulation in the bloodstream. The release of the drug from the carrier was sustained, and no ‘burst release’ was observed. The material also released small amounts of zinc, which are important in the treatment of the disease because these ions can prevent some of the adverse effects of chemotherapy. The results obtained are promising and have great application potential.
Challenges and Solutions for Low-Temperature Lithium–Sulfur Batteries: A Review
Authors: Liu Yiming , Qin Tian , Wang Pengxian , Yuan Menglei , Li Qiongguang , Feng Shaojie
Published: June 2023

The lithium–sulfur (Li-S) battery is considered to be one of the attractive candidates for breaking the limit of specific energy of lithium-ion batteries and has the potential to conquer the related energy storage market due to its advantages of low-cost, high-energy density, high theoretical specific energy, and environmental friendliness issues. However, the substantial decrease in the performance of Li-S batteries at low temperatures has presented a major barrier to extensive application. To this end, we have introduced the underlying mechanism of Li-S batteries in detail, and further concentrated on the challenges and progress of Li-S batteries working at low temperatures in this review. Additionally, the strategies to improve the low-temperature performance of Li-S batteries have also been summarized from the four perspectives, such as electrolyte, cathode, anode, and diaphragm. This review will provide a critical insight into enhancing the feasibility of Li-S batteries in low-temperature environments and facilitating their commercialization.
On the Symmetry, Electronic Properties, and Possible Metallic States in NASICON-Structured A4V2(PO4)3 (A = Li, Na, K) Phosphates
Authors: Gryaznov Denis , Vilčiauskas Linas
Published: June 2023

In this work, the electronic structure and properties of NASICON-structured A4V2(PO4)3, where A = Li, Na, K were studied using hybrid density functional theory calculations. The symmetries were analyzed using a group theoretical approach, and the band structures were examined by the atom and orbital projected density of states analyses. Li4V2(PO4)3 and Na4V2(PO4)3 adopted monoclinic structures with the C2 space group and averaged vanadium oxidation states of V+2.5 in the ground state, whereas K4V2(PO4)3 adopted a monoclinic structure with the C2 space group and mixed vanadium oxidation states V+2/V+3 in the ground state. The mixed oxidation state is the least stable state in Na4V2(PO4)3 and Li4V2(PO4)3. Symmetry increases in Li4V2(PO4)3 and Na4V2(PO4)3 led to the appearance of a metallic state that was independent of the vanadium oxidation states (except for the averaged oxidation state R32 Na4V2(PO4)3). On the other hand, K4V2(PO4)3 retained a small band gap in all studied configurations. These results might provide valuable guidance for crystallography and electronic structure investigations for this important class of materials.
Study on Acoustic Emission Characteristics of Fatigue Damage of A7N01 Aluminum Alloy for High-Speed Trains
Authors: Zhu Ronghua , Fang Song , Sun Weibing , Chi Dazhao
Published: June 2023

Online monitoring of the fatigue damage process of A7N01 aluminum alloy base metal and weld seam was conducted based on acoustic emission (AE) and digital microscopic imaging technology. The AE signals were recorded during the fatigue tests and analyzed using the AE characteristic parameter method. Fatigue fracture was observed using scanning electron microscopy (SEM) to analyze the source mechanism of AE. The AE results show that the AE count and rise time can effectively predict the initiation of fatigue microcracks in A7N01 aluminum alloy. The digital image monitoring results of a notch tip verified the prediction of fatigue microcracks using the AE characteristic parameters. In addition, the AE characteristics of the A7N01 aluminum alloy under different fatigue parameters were studied, and the relationships between the AE characteristic values of the base metal and weld seam and the crack propagation rate were calculated using the seven-point recurrence polynomial method. These provide a basis for predicting the remaining fatigue damage in the A7N01 aluminum alloy. The present work indicates that AE technology can be used to monitor the fatigue damage evolution of welded aluminum alloy structures.
Comprehensive Analysis of Different Coating Materials on the POM Substrate
Authors: Bončina Tonica , Glodež Srečko , Polanec Brigita , Hočuršćak Lara , Zupanič Franc
Published: June 2023

This study presents a comprehensive analysis of different coating materials on the POM substrate. Specifically, it investigated physical vapour deposition (PVD) coatings of aluminium (Al), chromium (Cr), and chromium nitride (CrN) of three various thicknesses. The deposition of Al was accomplished through a three-step process, particularly plasma activation, metallisation of Al by magnetron sputtering, and plasma polymerisation. The deposition of Cr was attained using the magnetron sputtering technique in a single step. For the deposition of CrN, a two-step process was employed. The first step involved the metallisation of Cr using magnetron sputtering, while the second step involved the vapour deposition of CrN, obtained through the reactive metallisation of Cr and nitrogen using magnetron sputtering. The focus of the research was to conduct comprehensive indentation tests to obtain the surface hardness of the analysed multilayer coatings, SEM analyses to examine surface morphology, and thorough adhesion analyses between the POM substrate and the appropriate PVD coating.
Permeability Coefficient of Concrete under Complex Stress States
Authors: Gu Jiafeng , Ren Qingwen , Tao Mei , Han Yan , Zhang Linfei
Published: June 2023

Hydraulic structures are typically subjected to long-term hydraulic loading, and concrete—the main material of structures—may suffer from cracking damage and seepage failure, which can threaten the safety of hydraulic structures. In order to assess the safety of hydraulic concrete structures and realize the accurate analysis of the whole failure process of hydraulic concrete structures under the coupling effect of seepage and stress, it is vital to comprehend the variation law of concrete permeability coefficients under complex stress states. In this paper, several concrete samples were prepared, designed for loading conditions of confining pressures and seepage pressures in the first stage, and axial pressures in the later stage, to carry out the permeability experiment of concrete materials under multi-axial loading, followed by the relationships between the permeability coefficients and axial strain, and the confining and seepage pressures were revealed accordingly. In addition, during the application of axial pressure, the whole process of seepage–stress coupling was divided into four stages, describing the permeability variation law of each stage and analyzing the causes of its formation. The exponential relationship between the permeability coefficient and volume strain was established, which can serve as a scientific basis for the determination of permeability coefficients in the analysis of the whole failure process of concrete seepage–stress coupling. Finally, this relationship formula was applied to numerical simulation to verify the applicability of the above experimental results in the numerical simulation analysis of concrete seepage–stress coupling.
Computational Analysis of Sandwich Panels with Graded Foam Cores Subjected to Combined Blast and Fragment Impact Loading
Authors: Li Lang , Zhang Fan , Li Jiahui , Jia Fusen , Han Bin
Published: June 2023

This study aimed to evaluate the performance of sandwich panels with graded foam cores of layered densities against combined blast and fragment impact loading, and to ascertain the optimal gradient of core configuration that would maximize the performance of sandwich panels against combined loading. First, based on a recently developed composite projectile, impact tests of the sandwich panels against simulated combined loading were conducted to provide a benchmark for the computational model. Second, a computational model, based on three-dimensional finite element simulation, was constructed and verified by means of a comparison of the numerically calculated and experimentally measured peak deflections of the back facesheet and the residual velocity of the penetrated fragment. Third, the structural response and energy absorption characteristics were examined, based on numerical simulations. Finally, the optimal gradient of core configuration was explored and numerically examined. The results indicated that the sandwich panel responded in a combined manner involving global deflection, local perforation and perforation hole enlargement. As the impact velocity increased, both the peak deflection of the back facesheet and the residual velocity of the penetrated fragment increased. The front facesheet was found to be the most important sandwich component in consuming the kinetic energy of the combined loading. Thus, the compaction of the foam core would be facilitated by placing the low-density foam at the front side. This would further provide a larger deflecting space for the front facesheet, thus reducing the deflection of the back facesheet. The gradient of core configuration was found to have limited influence on the anti-perforation ability of the sandwich panel. Parametric study indicated that the optimal gradient of foam core configuration was not sensitive to time delay between blast loading and fragment impact loading, but was sensitive to the asymmetrical facesheet of the sandwich panel.
Mechanical Properties and Crack Resistance of Basalt Fiber Self-Compacting High Strength Concrete: An Experimental Study
Authors: Xue Zhicheng , Qi Pengfei , Yan Ziran , Pei Qiang , Zhong Jintu , Zhan Qinjian
Published: June 2023

Pure self-compacting concrete has many disadvantages, such as early shrinkage and cracking. The addition of fibers can effectively improve the properties of resistance to tension and cracking of self-compacting concrete, thereby the effect of improving its strength and toughness can be achieved. Basalt fiber is a “new green industrial material” that has unique advantages, such as high crack resistance and being lightweight compared with other fiber materials. In order to study the mechanical properties and crack resistance of basalt fiber self-compacting high-strength concrete intensively, the self-compacting high-strength concrete of C50 was designed and obtained using the absolute volume method with multiple proportions. Orthogonal experimental methods were used to study the influence of the water binder ratio, fiber volume fraction, fiber length, and fly ash content on the mechanical properties of the basalt fiber self-compacting high-strength concrete. Meanwhile, the efficiency coefficient method was used to determine the best experiment plan (water binder ratio 0.3, fiber volume ratio 0.2%, fiber length 12 mm, fly ash content 30%), and the effect of fiber volume fraction and fiber length on the crack resistance of the self-compacting high-performance concrete was investigated using improved plate confinement experiments. The results show that (1) the water binder ratio had the greatest impact on the compressive strength of basalt fiber self-compacting high-strength concrete, and as the fiber volume fraction increased, the splitting tensile strength and flexural strength both increased; (2) there was an optimal value for the effect of the fiber length on the mechanical properties; (3) with the increase in fiber volume fraction, the total crack area of the fiber self-compacting high-strength concrete significantly decreased. When the fiber length increased, the maximum crack width first decreased and then slowly increased. The best crack resistance effect was achieved when the fiber volume fraction was 0.3% and the fiber length was 12 mm. Therefore, basalt fiber self-compacting high-strength concrete can be widely used in engineering fields, such as national defense construction, transportation, and building structure reinforcement and repair, due to its excellent mechanical and crack resistance properties.
Turning Chatter Detection Using a Multi-Input Convolutional Neural Network via Image and Sound Signal
Authors: The Ho Quang Ngoc , Do Thanh Trung , Minh Pham Son , Nguyen Van-Thuc , Nguyen Van Thanh Tien
Published: June 2023

In mechanical cutting and machining, self-excited vibration known as “Chatter” often occurs, adversely affecting a product’s quality and tool life. This article proposes a method to identify chatter by applying a machine learning model to classify data, determining whether the machining process is stable or vibrational. Previously, research studies have used detailed surface image data and sound generated during the machining process. To increase the specificity of the research data, we constructed a two-input model that enables the inclusion of both acoustic and visual data into the model. Data for training, testing, and calibration were collected from machining flanges SS400 in the form of thin steel sheets, using electron microscopes for imaging and microphones for sound recording. The study also compares the accuracy of the two-input model with popular models such as a visual geometry group network (VGG16), residual network (Restnet50), dense convolutional network (DenseNet), and Inception network (InceptionNet). The results show that the DenseNet model has the highest accuracy of 98.8%, while the two-input model has a 98% higher accuracy than other models; however, the two-input model is more appreciated due to the generality of the input data of the model. Experimental results show that the recommended model has good results in this work.
Gearbox Fault Diagnosis Based on Multi-Sensor Deep Spatiotemporal Feature Representation
Authors: Xie Fengyun , Wang Gan , Shang Jiandong , Sun Enguang , Xie Sanmao
Published: June 2023

The vibration signal acquired by a single sensor contains limited information and is easily interfered by noise signals, resulting in the inability to fully express the operating characteristics and state of a gearbox. To address this problem, our study proposes a gearbox fault diagnosis method based on multi-sensor deep spatiotemporal feature representation. This method utilizes two vibration sensors to obtain the vibration information of the gearbox. A fault diagnosis model (PCNN–GRU) combined with a parallel convolutional neural network (PCNN) and gated recurrent unit (GRU) was used to fuse the gearbox vibration information. The parallel convolutional neural network was used to extract the spatial information of the vibration signals collected by different position sensors, and the timing information was mined through the gated recurrent unit. The deep spatiotemporal features that fuse the multi-sensor spatial and temporal information were composed. The collected multi-sensor vibration signals were directly input into the PCNN–GRU model, and an end-to-end intelligent diagnosis of the gearbox faults was realized. Finally, through experimental verification, the accuracy rate of this model can reach up to 99.92%. Compared with other models, this model has a higher diagnostic accuracy and stability.
An Archive-Guided Equilibrium Optimizer Based on Epsilon Dominance for Multi-Objective Optimization Problems
Authors: Chalabi Nour Elhouda , Attia Abdelouahab , Bouziane Abderraouf , Hassaballah Mahmoud , Alanazi Abed , Binbusayyis Adel
Published: June 2023

In real-world applications, many problems involve two or more conflicting objectives that need to be optimized at the same time. These are called multi-objective optimization problems (MOPs). To solve these problems, we introduced a guided multi-objective equilibrium optimizer (GMOEO) algorithm based on the equilibrium optimizer (EO), which was inspired by control–volume–mass balance models that use particles (solutions) and their respective concentrations (positions) as search agents in the search space. The GMOEO algorithm involves the integration of an external archive that acts as a guide and stores the optimal Pareto set during the exploration and exploitation of the search space. The key candidate population also acted as a guide, and Pareto dominance was employed to obtain the non-dominated solutions. The principal of ϵ-dominance was employed to update the archive solutions, such that they could then guide the particles to ensure better exploration and diversity during the optimization process. Furthermore, we utilized the fast non-dominated sort (FNS) and crowding distance methods for updating the position of the particles efficiently in order to guarantee fast convergence in the direction of the Pareto optimal set and to maintain diversity. The GMOEO algorithm obtained a set of solutions that achieved the best compromise among the competing objectives. GMOEO was tested and validated against various benchmarks, namely the ZDT and DTLZ test functions. Furthermore, a benchmarking study was conducted using cone-ϵ-dominance as an update strategy for the archive solutions. In addition, several well-known multi-objective algorithms, such as the multi-objective particle-swarm optimization (MOPSO) and the multi-objective grey-wolf optimization (MOGWO), were compared to the proposed algorithm. The experimental results proved definitively that the proposed GMOEO algorithm is a powerful tool for solving MOPs.
An Adaptive Frequency Sampling Algorithm for Dynamic Condensation-Based Frequency Response Analysis
Authors: Lee Jaehun , Park Younggeun , Lee Yeji , Chang Seongmin
Published: June 2023

This paper proposed an efficient and adaptive frequency sampling algorithm for frequency response analysis using dynamic condensation-based reduced-order modeling. For the degree of freedom-based model reduction method, the reduced-order basis becomes a frequency-dependent matrix since the relationship between master and slave degrees of freedom stems from partial equations of a second-order dynamical system. Such frequency-dependency makes the analysis inefficient for investigating the frequency response of the system. Considering that the coverage of a local reduced-order basis at a single frequency varies depending on the frequency, a new frequency sampling algorithm was proposed with a strategy of constructing multiple local reduced-order models (ROMs) at sample frequencies. For adaptive sampling, the frequency range of a local ROM was evaluated, and a new sample was added if there was a gap between two adjacent ROMs. As a result, the accuracy of the local ROM can be estimated, and the efficiency in the online stage was greatly enhanced. The proposed method was verified by performing frequency response analysis with several numerical examples, including a large-scale structural and dynamic system.
Second-Order Robust Numerical Method for a Partially Singularly Perturbed Time-Dependent Reaction–Diffusion System
Authors: Mariappan Manikandan , Muthusamy Chandru , Ramos Higinio
Published: June 2023

This article aims at the development and analysis of a numerical scheme for solving a singularly perturbed parabolic system of n reaction–diffusion equations where m of the equations (with m<n) contain a perturbation parameter while the rest do not contain it. The scheme is based on a uniform mesh in the temporal variable and a piecewise uniform Shishkin mesh in the spatial variable, together with classical finite difference approximations. Some analytical properties and error analyses are derived. Furthermore, a bound of the error is provided. Under certain assumptions, it is proved that the proposed scheme has almost second-order convergence in the space direction and almost first-order convergence in the time variable. Errors do not increase when the perturbation parameter ε→0, proving the uniform convergence. Some numerical experiments are presented, which support the theoretical results.
Investigating Symmetric Soliton Solutions for the Fractional Coupled Konno–Onno System Using Improved Versions of a Novel Analytical Technique
Authors: Yasmin Humaira , Aljahdaly Noufe H. , Saeed Abdulkafi Mohammed , Shah Rasool
Published: June 2023

The present research investigates symmetric soliton solutions for the Fractional Coupled Konno–Onno System (FCKOS) by using two improved versions of an Extended Direct Algebraic Method (EDAM) i.e., modified EDAM (mEDAM) and r+mEDAM. By obtaining precise analytical solutions, this research explores the characteristics and behaviours of symmetric solitons in FCKOS. Further, the amplitude, shape and propagation behaviour of some solitons are visualized by means of a 3D graph. This investigation fosters a more thorough comprehension of non-linear wave phenomena in considered systems and offers helpful insights towards soliton behavior in it. The outcomes reveal that the recommended techniques are successful in constructing symmetric soliton solutions for complex models like the FCKOS.
On Recovering Sturm–Liouville-Type Operators with Global Delay on Graphs from Two Spectra
Authors: Buterin Sergey
Published: June 2023

We suggest a new formulation of the inverse spectral problem for second-order functional-differential operators on star-shaped graphs with global delay. The latter means that the delay, which is measured in the direction of a specific boundary vertex, called the root, propagates through the internal vertex to other edges. Now, we intend to recover the potentials from the spectra of two boundary value problems on the graph with a common set of boundary conditions at all boundary vertices except the root. For simplicity, we focus on star graphs with equal edges when the delay parameter is not less than their length. Under the assumption that the common boundary conditions are of the Robin type and they are known and pairwise linearly independent, the uniqueness theorem is proven and a constructive procedure for solving the proposed inverse problem is obtained.
Multi-Aspect SAR Target Recognition Based on Non-Local and Contrastive Learning
Authors: Zhou Xiao , Li Siyuan , Pan Zongxu , Zhou Guangyao , Hu Yuxin
Published: June 2023

Synthetic aperture radar (SAR) automatic target recognition (ATR) has been widely applied in multiple fields. However, the special imaging mechanism of SAR results in different visual features of the same target at different azimuth angles, so single-aspect SAR target recognition has the limitation of observing the target from a single perspective. Multi-aspect SAR target recognition technology can overcome this limitation by utilizing information from different azimuths and effectively improve target recognition performance. Considering the order dependency and data limitation of existing methods, this paper proposes a multi-aspect SAR recognition method based on Non-Local, which applies a self-attention calculation to feature maps to learn the correlation between multi-aspect SAR images. Meanwhile, in order to improve the generalization ability of the proposed method under limited data, a network based on contrastive learning was designed to pre-train the feature extraction part of the whole network. The experimental results using the MSTAR dataset show that the proposed method has excellent recognition accuracy and good robustness.
A New Estimator: Median of the Distribution of the Mean in Robustness
Authors: García-Pérez Alfonso
Published: June 2023

In some statistical methods, the statistical information is provided in terms of the values used by classical estimators, such as the sample mean and sample variance. These estimations are used in a second stage, usually in a classical manner, to be combined into a single value, as a weighted mean. Moreover, in many applied studies, the results are given in these terms, i.e., as summary data. In all of these cases, the individual observations are unknown; therefore, computing the usual robustness estimators with them to replace classical non-robust estimations by robust ones is not possible. In this paper, the use of the median of the distribution Fx¯ of the sample mean is proposed, assuming a location-scale contaminated normal model, where the parameters of Fx¯ are estimated with the classical estimations provided in the first stage. The estimator so defined is called median of the distribution of the mean, MdM. This new estimator is applied in Mendelian randomization, defining the new robust inverse weighted estimator, RIVW.
Genetic Insights into the Molecular Pathophysiology of Depression in Parkinson’s Disease
Authors: Angelopoulou Efthalia , Bougea Anastasia , Paudel Yam Nath , Georgakopoulou Vasiliki Epameinondas , Papageorgiou Sokratis G. , Piperi Christina
Published: June 2023

Background and Objectives: Parkinson’s disease (PD) is a clinically heterogeneous disorder with poorly understood pathological contributing factors. Depression presents one of the most frequent non-motor PD manifestations, and several genetic polymorphisms have been suggested that could affect the depression risk in PD. Therefore, in this review we have collected recent studies addressing the role of genetic factors in the development of depression in PD, aiming to gain insights into its molecular pathobiology and enable the future development of targeted and effective treatment strategies. Materials and Methods: we have searched PubMed and Scopus databases for peer-reviewed research articles published in English (pre-clinical and clinical studies as well as relevant reviews and meta-analyses) investigating the genetic architecture and pathophysiology of PD depression. Results: in particular, polymorphisms in genes related to the serotoninergic pathway (sodium-dependent serotonin transporter gene, SLC6A4, tryptophan hydrolase-2 gene, TPH2), dopamine metabolism and neurotransmission (dopamine receptor D3 gene, DRD3, aldehyde dehydrogenase 2 gene, ALDH2), neurotrophic factors (brain-derived neurotrophic factor gene, BDNF), endocannabinoid system (cannabinoid receptor gene, CNR1), circadian rhythm (thyrotroph embryonic factor gene, TEF), the sodium-dependent neutral amino acid transporter B(0)AT2 gene, SLC6A15), and PARK16 genetic locus were detected as altering susceptibility to depression among PD patients. However, polymorphisms in the dopamine transporter gene (SLC6A3), monoamine oxidase A (MAOA) and B (MAOB) genes, catechol-O-methyltransferase gene (COMT), CRY1, and CRY2 have not been related to PD depression. Conclusions: the specific mechanisms underlying the potential role of genetic diversity in PD depression are still under investigation, however, there is evidence that they may involve neurotransmitter imbalance, mitochondrial impairment, oxidative stress, and neuroinflammation, as well as the dysregulation of neurotrophic factors and their downstream signaling pathways.
Subglottotracheal Adenoid Cystic Carcinoma in a 16-Year-Old Female—A Case Report
Authors: Dumitru Cristina , Balica Nicolae
Published: June 2023

Cystic adenoid carcinoma (ACC) is a rare malignant epithelial tumor arising from exocrine glands and accounts for only 1% of head and neck cancers. ACCs are common in the fifth and sixth decades of life, predominantly in women, and characterized by slow progression, local aggression, recurrence, and high metastasis. Subglottotracheal ACC is a rare tumor in the pediatric population, with only a few cases reported in the literature. We present a case of a 16-year-old female who was diagnosed with ACC in the subglottic and tracheal region. The patient presented with respiratory failure but without a history of dysphonia, dyspnea, stridor, or dysphagia. The diagnosis was confirmed by a biopsy, and subsequent imaging studies showed a large tumor involving the subglottic and tracheal region. The therapeutic management of this patient has been challenging due to the rarity of this tumor in the pediatric population and the potential long-term complications associated with tumor recurrence and psychological impact. This case highlights the diagnostic and therapeutic challenges in the management of subglottotracheal ACC in children and the importance of a multidisciplinary approach to optimize patient outcomes.
Autonomic and Vascular Responses during Reactive Hyperemia in Healthy Individuals and Patients with Sickle Cell Anemia
Authors: López-Galán Erislandis , Vitón-Castillo Adrián Alejandro , Carrazana-Escalona Ramón , Planas-Rodriguez Maylet , Fernández-García Adolfo Arsenio , Cutiño-Clavel Ileana , Pascau-Simon Alexander , Connes Philippe , Sánchez-Hechavarría Miguel Enrique , Muñoz-Bustos Gustavo Alejandro
Published: June 2023

Background and Objectives: To compare autonomic and vascular responses during reactive hyperemia (RH) between healthy individuals and patients with sickle cell anemia (SCA). Materials and Methods: Eighteen healthy subjects and 24 SCA patients were subjected to arterial occlusion for 3 min at the lower right limb level. The pulse rate variability (PRV) and pulse wave amplitude were measured through photoplethysmography using the Angiodin® PD 3000 device, which was placed on the first finger of the lower right limb 2 min before (Basal) and 2 min after the occlusion. Pulse peak intervals were analyzed using time–frequency (wavelet transform) methods for high-frequency (HF: 0.15–0.4) and low-frequency (LF: 0.04–0.15) bands, and the LF/HF ratio was calculated. Results: The pulse wave amplitude was higher in healthy subjects compared to SCA patients, at both baseline and post-occlusion (p < 0.05). Time–frequency analysis showed that the LF/HF peak in response to the post-occlusion RH test was reached earlier in healthy subjects compared to SCA patients. Conclusions: Vasodilatory function, as measured by PPG, was lower in SCA patients compared to healthy subjects. Moreover, a cardiovascular autonomic imbalance was present in SCA patients with high sympathetic and low parasympathetic activity in the basal state and a poor response of the sympathetic nervous system to RH. Early cardiovascular sympathetic activation (10 s) and vasodilatory function in response to RH were impaired in SCA patients.
Etiology and Multi-Drug Resistant Profile of Bacterial Infections in Severe Burn Patients, Romania 2018–2022
Authors: Nițescu Bogdan , Pițigoi Daniela , Tălăpan Daniela , Nițescu Maria , Aramă Sorin Ștefan , Pavel Bogdan , Streinu-Cercel Adrian , Rafila Alexandru , Aramă Victoria
Published: June 2023

Infections in severe burns and their etiology are and will remain a big concern for the medical field. The multi-drug resistant strains of bacteria are a challenge of today’s medicine. The aim of our study was to identify the etiological spectrum of bacterial infections in severe burn patients in Romania and their multi-drug resistant patterns. We performed a prospective study that included 202 adult patients admitted to the intensive care unit (ICU) of the Clinical Emergency Hospital of Plastic, Reconstructive Surgery and Burns, Bucharest, Romania (CEHPRSB), from 1 October 2018 to 1 April 2022, a period which includes the first 2 years of the outbreak of COVID-19. From each patient, wound swabs, endotracheal aspirates, blood for blood culture, and urine were collected. The most frequently isolated bacterium was Pseudomonas aeruginosa (39%), followed by Staphylococcus aureus (12%), Klebsiella spp. (11%), and Acinetobacter baumannii (9%). More than 90% of Pseudomonas aeruginosa and Acinetobacter baumannii were MDR, regardless of the clinical specimen from which they were isolated.
Bittersweet Sugars: How Unusual Glycan Structures May Connect Epithelial-to-Mesenchymal Transition and Multidrug Resistance in Cancer
Authors: Fonseca Leonardo Marques da , Diniz-Lima Israel , da Costa Santos Marcos André Rodrigues , Franklim Tatiany Nunes , da Costa Kelli Monteiro , Santos Ariely Costa dos , Morrot Alexandre , Decote-Ricardo Debora , Valente Raphael do Carmo , Freire-de-Lima Celio Geraldo , dos Reis Jhenifer Santos , Freire-de-Lima Leonardo
Published: June 2023

Glycobiology is an exponentially growing field focused on the function, structure, evolution and biology of carbohydrates across all living organisms, being relevant to basic research, clinical medicine and biotechnology [...]
In Vitro and In Silico Anti-Picornavirus Triterpene Alkanoic Acid Ester from Saudi Collection of Rhazya stricta Decne
Authors: Abdel-Kader Maged S. , Almutib Fahad S. , Aldosari Abdullah F. , Soliman Gamal A. , Elzorba Hisham Y. , Alqarni Mohammed H. , Ibrahim Reham S. , Zaatout Hala H.
Published: June 2023

The total alcohol extract obtained from the aerial parts of R. stricta and fractions of the liquid–liquid fractionation process were tested against picornavirus-causing foot-and-mouth disease (FMD) based on the traditional use of the plant in Saudi Arabia. The most active petroleum ether soluble fraction was subjected to chromatographic purification, and nine compounds were isolated, identified using various chemical and spectroscopic methods, and tested for their anti-viral potential. The new ester identified as α-Amyrin 3-(3′R-hydroxy)-hexadecanoate (1) was the most active compound with 51% inhibition of the viral growth and was given the name Rhazyin A. Compounds with ursane skeleton were more active than those with lupane skeleton except in the case of the acid derivatives where betulenic acid showed 26.1% inhibition against the viral growth, while ursolic acid showed only 16.6% inhibition. Moreover, molecular docking analysis using a glide extra-precision module was utilized for investigating the possible molecular interactions accounting for anti-viral activity against picornavirus of the nine isolated compounds. Molecular docking studies revealed a strong binding of the discovered hits within the active site of FMDV 3Cpro. Compound 1 showed the lowest docking score within the nine isolated compounds comparable to the two known anti-viral drugs; glycyrrhizic acid and ribavirin. The results of this research will provide lead candidates from natural origin with potential safety and efficacy compared to the synthetic ones with lower production costs for managing FMVD.
The FilZ Protein Contains a Single PilZ Domain and Facilitates the Swarming Motility of Pseudoalteromonas sp. SM9913
Authors: Sheng Qi , Liu Ang , Yang Peiling , Chen Zhuowei , Wang Peng , Sun Haining , Li Chunyang , McMinn Andrew , Chen Yin , Zhang Yuzhong , Su Hainan , Chen Xiulan , Zhang Yuqiang
Published: June 2023

Swarming regulation is complicated in flagellated bacteria, especially those possessing dual flagellar systems. It remains unclear whether and how the movement of the constitutive polar flagellum is regulated during swarming motility of these bacteria. Here, we report the downregulation of polar flagellar motility by the c-di-GMP effector FilZ in the marine sedimentary bacterium Pseudoalteromonas sp. SM9913. Strain SM9913 possesses two flagellar systems, and filZ is located in the lateral flagellar gene cluster. The function of FilZ is negatively controlled by intracellular c-di-GMP. Swarming in strain SM9913 consists of three periods. Deletion and overexpression of filZ revealed that, during the period when strain SM9913 expands quickly, FilZ facilitates swarming. In vitro pull-down and bacterial two-hybrid assays suggested that, in the absence of c-di-GMP, FilZ interacts with the CheW homolog A2230, which may be involved in the chemotactic signal transduction pathway to the polar flagellar motor protein FliMp, to interfere with polar flagellar motility. When bound to c-di-GMP, FilZ loses its ability to interact with A2230. Bioinformatic investigation indicated that filZ-like genes are present in many bacteria with dual flagellar systems. Our findings demonstrate a novel mode of regulation of bacterial swarming motility.
Maternal Nutritional Status and the Microbiome across the Pregnancy and the Post-Partum Period
Authors: Strobel Katie M. , Juul Sandra E. , Hendrixson David Taylor
Published: June 2023

Appropriate nutrition during pregnancy and the post-partum period is vital for both the mothers and their offspring. Both under- and over-nourished status may have important microbial implications on the maternal and infant gut microbiomes. Alterations in the microbiome can have implications for a person’s risk of obesity and metabolic diseases. In this review, we examine alterations in the maternal gut, vaginal, placental, and milk microbiomes in the context of pre-pregnancy BMI, gestational weight gain, body composition, gestational diabetes, and maternal diet. We also investigate how the infant gut microbiome may be altered by these different parameters. Many of the microbial changes seen in under- and over-nourished states in birthing parents may result in long-term implications for the health of offspring. Differences in diet appear to be a major driver of the maternal and subsequently milk and offspring microbiomes. Further prospective longitudinal cohort studies are needed to examine nutrition and the microbiome to better understand its implications. Additionally, trials involving dietary interventions in child-bearing age adults should be explored to improve the mother and child’s risks for metabolic diseases.
TGF Beta as a Prognostic Biomarker of COVID-19 Severity in Patients with NAFLD—A Prospective Case–Control Study
Authors: Susak Frano , Vrsaljko Nina , Vince Adriana , Papic Neven
Published: June 2023

Non-alcoholic fatty liver disease (NAFLD), the leading cause of chronic liver disease in Western countries, has been identified as a possible risk factor for COVID-19 severity. However, the immunological mechanisms by which NAFLD exacerbates COVID-19 remain unknown. Transforming growth factor-beta 1 (TGF-β1) has an important immunomodulatory and pro-fibrotic role, which has already been described in NAFLD. However, the role of TGF-β1 in COVID-19 remains unclear, and could also be the pathophysiology link between these two conditions. The aim of this case–control study was to analyze the expression of TGF-β1 in COVID-19 patients depending on the presence of NAFLD and COVID-19 severity. Serum TGF-β1 concentrations were measured in 60 hospitalized COVID-19 patients (30 with NAFLD). NAFLD was associated with higher serum TGF-β1 concentrations that increased with disease severity. Admission TGF-β1 concentrations showed good discriminative accuracy in predicting the development of critical disease and COVID-19 complications (need for advanced respiratory support, ICU admission, time to recovery, development of nosocomial infections and mortality). In conclusion, TGF-β1 could be an efficient biomarker for predicting COVID-19 severity and adverse outcomes in patients with NAFLD.
The Impact of Sea Ice Cover on Microbial Communities in Antarctic Shelf Sediments
Authors: Baloza Marwa , Henkel Susann , Kasten Sabine , Holtappels Moritz , Molari Massimiliano
Published: June 2023

The area around the Antarctic Peninsula (AP) is facing rapid climatic and environmental changes, with so far unknown impacts on the benthic microbial communities of the continental shelves. In this study, we investigated the impact of contrasting sea ice cover on microbial community compositions in surface sediments from five stations along the eastern shelf of the AP using 16S ribosomal RNA (rRNA) gene sequencing. Redox conditions in sediments with long ice-free periods are characterized by a prevailing ferruginous zone, whereas a comparatively broad upper oxic zone is present at the heavily ice-covered station. Low ice cover stations were highly dominated by microbial communities of Desulfobacterota (mostly Sva1033, Desulfobacteria, and Desulfobulbia), Myxococcota, and Sva0485, whereas Gammaproteobacteria, Alphaproteobacteria, Bacteroidota, and NB1-j prevail at the heavy ice cover station. In the ferruginous zone, Sva1033 was the dominant member of Desulfuromonadales for all stations and, along with eleven other taxa, showed significant positive correlations with dissolved Fe concentrations, suggesting a significant role in iron reduction or an ecological relationship with iron reducers. Our results indicate that sea ice cover and its effect on organic carbon fluxes are the major drivers for changes in benthic microbial communities, favoring potential iron reducers at stations with increased organic matter fluxes.
Incorporating Domain Knowledge and Structure-Based Descriptors for Machine Learning: A Case Study of Pd-Catalyzed Sonogashira Reactions
Authors: Chan Kalok , Ta Long Thanh , Huang Yong , Su Haibin , Lin Zhenyang
Published: June 2023

Machine learning has revolutionized information processing for large datasets across various fields. However, its limited interpretability poses a significant challenge when applied to chemistry. In this study, we developed a set of simple molecular representations to capture the structural information of ligands in palladium-catalyzed Sonogashira coupling reactions of aryl bromides. Drawing inspiration from human understanding of catalytic cycles, we used a graph neural network to extract structural details of the phosphine ligand, a major contributor to the overall activation energy. We combined these simple molecular representations with an electronic descriptor of aryl bromide as inputs for a fully connected neural network unit. The results allowed us to predict rate constants and gain mechanistic insights into the rate-limiting oxidative addition process using a relatively small dataset. This study highlights the importance of incorporating domain knowledge in machine learning and presents an alternative approach to data analysis.
Nitrogen-Rich Porous Organic Polymers from an Irreversible Amine–Epoxy Reaction for Pd Nanocatalyst Carrier
Authors: Li Ailing , Dong Fuping , Xiong Yuzhu
Published: June 2023

Nitrogen-rich porous organic polymers were fabricated through a nonreversible ring-opening reaction from polyamines and polyepoxides (PAEs). The epoxide groups reacted with both primary and secondary amines provided by the polyamines at different epoxide/amine ratios with polyethylene glycol as the solvent to form the porous materials. Fourier-transform infrared spectroscopy confirmed the occurrence of ring opening between the polyamines and polyepoxides. The porous structure of the materials was confirmed through N2 adsorption–desorption data and scanning electron microscopy images. The polymers were found to possess both crystalline and noncrystalline structures, as evidenced by X-ray diffraction and high-resolution transmission electron microscopy (HR-TEM) results. The HR-TEM images revealed a thin, sheet-like layered structure with ordered orientations, and the lattice fringe spacing measured from these images was consistent with the interlayer of the PAEs. Additionally, the selected area electron diffraction pattern indicated that the PAEs contained a hexagonal crystal structure. The Pd catalyst was fabricated in situ onto the PAEs support by the NaBH₄ reduction of the Au precursor, and the size of the nano-Pd was about 6.9 nm. The high nitrogen content of the polymer backbone combined with Pd noble nanometals resulted in excellent catalytic performance in the reduction of 4-nitrophenol to 4-aminophenol.