bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting the Onset of Diabetes with Machine Learning Methods
Authors: Chou Chun-Yang , Hsu Ding-Yang , Chou Chun-Hung
Published: February 2023

The number of people suffering from diabetes in Taiwan has continued to rise in recent years. According to the statistics of the International Diabetes Federation, about 537 million people worldwide (10.5% of the global population) suffer from diabetes, and it is estimated that 643 million people will develop the condition (11.3% of the total population) by 2030. If this trend continues, the number will jump to 783 million (12.2%) by 2045. At present, the number of people with diabetes in Taiwan has reached 2.18 million, with an average of one in ten people suffering from the disease. In addition, according to the Bureau of National Health Insurance in Taiwan, the prevalence rate of diabetes among adults in Taiwan has reached 5% and is increasing each year. Diabetes can cause acute and chronic complications that can be fatal. Meanwhile, chronic complications can result in a variety of disabilities or organ decline. If holistic treatments and preventions are not provided to diabetic patients, it will lead to the consumption of more medical resources and a rapid decline in the quality of life of society as a whole. In this study, based on the outpatient examination data of a Taipei Municipal medical center, 15,000 women aged between 20 and 80 were selected as the subjects. These women were patients who had gone to the medical center during 2018–2020 and 2021–2022 with or without the diagnosis of diabetes. This study investigated eight different characteristics of the subjects, including the number of pregnancies, plasma glucose level, diastolic blood pressure, sebum thickness, insulin level, body mass index, diabetes pedigree function, and age. After sorting out the complete data of the patients, this study used Microsoft Machine Learning Studio to train the models of various kinds of neural networks, and the prediction results were used to compare the predictive ability of the various parameters for diabetes. Finally, this study found that after comparing the models using two-class logistic regression as well as the two-class neural network, two-class decision jungle, or two-class boosted decision tree for prediction, the best model was the two-class boosted decision tree, as its area under the curve could reach a score of 0.991, which was better than other models.
Age and Sex-Related Effects on Single-Subject Gray Matter Networks in Healthy Participants
Authors: Shigemoto Yoko , Sato Noriko , Maikusa Norihide , Sone Daichi , Ota Miho , Kimura Yukio , Chiba Emiko , Okita Kyoji , Yamao Tensho , Nakaya Moto , Maki Hiroyuki , Arizono Elly , Matsuda Hiroshi
Published: February 2023

Recent developments in image analysis have enabled an individual’s brain network to be evaluated and brain age to be predicted from gray matter images. Our study aimed to investigate the effects of age and sex on single-subject gray matter networks using a large sample of healthy participants. We recruited 812 healthy individuals (59.3 ± 14.0 years, 407 females, and 405 males) who underwent three-dimensional T1-weighted magnetic resonance imaging. Similarity-based gray matter networks were constructed, and the following network properties were calculated: normalized clustering, normalized path length, and small-world coefficients. The predicted brain age was computed using a support-vector regression model. We evaluated the network alterations related to age and sex. Additionally, we examined the correlations between the network properties and predicted brain age and compared them with the correlations between the network properties and chronological age. The brain network retained efficient small-world properties regardless of age; however, reduced small-world properties were observed with advancing age. Although women exhibited higher network properties than men and similar age-related network declines as men in the subjects aged < 70 years, faster age-related network declines were observed in women, leading to no differences in sex among the participants aged ≥ 70 years. Brain age correlated well with network properties compared to chronological age in participants aged ≥ 70 years. Although the brain network retained small-world properties, it moved towards randomized networks with aging. Faster age-related network disruptions in women were observed than in men among the elderly. Our findings provide new insights into network alterations underlying aging.
Safety and Tolerability of Concentrated Intraventricular Nicardipine for Poor-Grade Aneurysmal Subarachnoid Hemorrhage–Related Vasospasm
Authors: Zahra Kaneez , Domingo Ricardo A. , Turnbull Marion T. , Santos Christan D. , Peacock Sarah H. , Jackson Daniel A. , Tawk Rabih G. , Siegel Jason L. , Freeman William David
Published: February 2023

Objective: To report the preliminary safety, tolerability, and cerebral spinal fluid (CSF) sampling utility of serial injections of concentrated intraventricular nicardipine (IVN) in the treatment of aneurysmal subarachnoid hemorrhage (aSAH). Methods: We report the clinical, radiographic, and laboratory safety and tolerability data of a retrospective case series from a single academic medical center. All patients with aSAH developed vasospasm despite enteral nimodipine and received serial injections of concentrated IVN (2.5 mg/mL). CSF injection safety, tolerability, and utility are defined and reported. Results: A total of 59 doses of concentrated IVN were administered to three patients with poor-grade SAH. In Case 1, a 33-year-old man with modified Fisher scale (mFS) grade 4 and Hunt-Hess scale (HH) score 4 received 26 doses; in Case 2, a 36-year-old woman with mFS grade 4 and HH score 5 received 13 doses; and in Case 3, a 70-year-old woman with mFS grade 3 and HH score 4 received 20 doses. No major safety or tolerability events occurred. Two patients were discharged to a rehabilitation facility, and one died after discharge from the hospital. Conclusions: A concentrated 4 mg IVN dose (2.5 mg/mL) in a 1.6 mL injection appears relatively safe and tolerable and potentially offers a second-line strategy for treating refractory vasospasm in poor-grade SAH without compromising intracranial pressure or cerebral perfusion pressure.
Microvascular and Endothelial Dysfunction in Prediabetes
Authors: Lamprou Stamatina , Koletsos Nikolaos , Mintziori Gesthimani , Anyfanti Panagiota , Trakatelli Christina , Kotsis Vasileios , Gkaliagkousi Eugenia , Triantafyllou Areti
Published: February 2023

Prediabetes is a significant metabolic status since there is high potential for future progression of diabetes mellitus (DM). People with prediabetes are at increased risk of cardiovascular disease (CVD) and mortality. Endothelial and microvascular dysfunction is considered a key step towards the development and progression of CVD. Importantly, endothelial and microvascular dysfunction can be detected and monitored using non-invasive procedures in peripheral organs and tissues, including the retina, kidney, skin and skeletal muscle. Structural and functional alterations of the microvasculature have been consistently documented in the above microvascular beds in patients with diabetes mellitus. In contrast, such alterations remain understudied in prediabetes, but are currently receiving attention as markers of subclinical and future CVD. The aim of this review is to summarize available evidence regarding the presence of subclinical microvascular and endothelial dysfunction in prediabetes and their impact on cardiovascular risk.
Bioactive Compounds from Kalanchoe Genus Potentially Useful for the Development of New Drugs
Authors: Nascimento Luana Beatriz dos Santos , Casanova Livia Marques , Costa Sônia Soares
Published: February 2023

The genus Kalanchoe Adans. (Crassulaceae) is native to Madagascar and comprises 145 species, being naturalized in the tropics and cultivated worldwide. In addition to having ornamental value, several Kalanchoe species are commonly used in popular medicine for the treatment of inflammatory conditions, wounds, gastric ulcers, and other diseases. The great importance of the genus is reflected on its acknowledgment by traditional and alternative health systems and organizations, as well as on the growing number of papers reporting pharmacological properties of extracts and isolated compounds from Kalanchoe. Among these properties, we highlight anti-inflammatory, antitumor, wound healing, antiulcer, and muscle relaxing properties. These activities are attributed mostly to flavonoids and bufadienolides, the main secondary metabolites reported in Kalanchoe extracts. While bufadienolides are generally related to cytotoxic and muscle relaxing activities, flavonoids are commonly reported as anti-inflammatory and wound healing agents. This review provides up to date information and perspectives on bioactive compounds from the Kalanchoe genus that are potentially useful for the development of new drugs. It includes not only a discussion on the advantages of the Kalanchoe species as source of bioactive compounds, but also the gaps, opportunities, and challenges to translate the acquired knowledge into innovation for drug development.
Biosynthesis of Novel Ag-Cu Bimetallic Nanoparticles from Leaf Extract of Salvia officinalis and Their Antibacterial Activity
Authors: Malik Maqsood Ahmad , Albeladi Shroog ShdiedRoyji , Al-Maaqar Saleh Mohammed , Alshehri Abdulmohsen Ali , Al-Thabaiti Shaeel Ahmed , Khan Imran , Kamli Majid Rasool
Published: February 2023

Bimetallic nanoparticles exhibit bifunctional or synergistic effects prevailing between two metals with the capabilities of enhanced electronic, catalytic, and optical properties. Green synthetic routes have gained tremendous interest because of the noninvolvement of toxic and harmful chemical reagents in preparation. Therefore, we develop bimetallic Ag-Cu nanoparticles (Ag-Cu NPs) through an eco-friendly and biocompatible preparation method. In this study, Ag-Cu NPs have been synthesized from leaf extracts of the commonly known sage, S. officinalis. The extract has a rich phytochemical composition, including bioreducing polyphenols, flavonoids, and capping/stabilizing agents. An array of well-known spectroscopic and microscopic techniques were used to characterize the as-prepared Ag-Cu bimetallic nanoparticles, including X-ray diffraction (XRD), ultraviolet-visible spectroscopy, Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy, transmission electron microscopy, and energy-dispersive X-ray spectroscopy. The size of the Ag-Cu NPs was found to be 50 nm with a spherical shape and an almost uniform distribution. The antibacterial effect was further evaluated using agar well diffusion and disc diffusion assays. Ag-Cu NPs exhibit antibacterial and antibiofilm properties against Gram-positive and Gram-negative bacteria strains. The minimum inhibitory concentration (MIC) of Ag-Cu NPs was between 5 g/mL and 15 g/mL. The Ag-Cu NPs inhibit biofilm formation at 25 g/mL and 50 g/mL. The results of biogenic Ag-Cu NPs provide novel antibacterial activity against Gram-positive and Gram-negative bacteria, as well as antibiofilm activity. Hence, Ag-Cu NPs might serve as a novel antibacterial agent with potential antibacterial and antibiofilm properties.
Analysis of the Operational Wear of the Combustion Engine Piston Pin
Authors: Kowalski Sławomir , Cieślikowski Bogusław , Barta Dalibor , Dižo Ján , Dittrich Aleš
Published: February 2023

This article presents the results of research into the causes of the wear of the piston pin mounted in piston bosses by means of a hinge joint and in the connecting rod small end by means of the thermocompression bond. Changes in geometry and in the pin-top surface structure, which are caused by the mutual influence of the mating surfaces in variable lubrication conditions, are presented. The progress of scuffing as a result of insufficient lubrication of the mating elements or oil film breaking is demonstrated. The state of destruction was confirmed by the results of surface roughness measurements showing the formation of build-ups. The loss of the thermocompression bond surface, caused by the penetration of sintered engine oil fractions containing biofuel additive components and spent engine oil improver packages, was noted. The progressing forms of wear are the cause of engine failures due to the pin movement towards the cylinder wall, and due to boss breakage in the piston.
Control over Multi-Scale Self-Organization-Based Processes under the Extreme Tribological Conditions of Cutting through the Application of Complex Adaptive Surface-Engineered Systems
Authors: Fox-Rabinovich German , Gershman Iosif , Goel Saurav , Endrino Jose Luis
Published: February 2023

This paper features a comprehensive analysis of various multiscale selforganization processes that occur during cutting. A thorough study of entropy production during friction has uncovered several channels of its reduction that can be achieved by various selforganization processes. These processes are (1) self-organization during physical vapor deposition PVD coating deposition on the cutting tool substrates; (2) tribofilm formation caused by interactions with the environment during operation, which consist of the following compounds: thermal barriers; Magnéli phase tribo-oxides with metallic properties at elevated temperatures, tribo-oxides that transform into a liquid phase at operating temperatures, and mixed action tribo-oxides that serve as thermal barriers/lubricants, and (3) multiscale selforganization processes that occur on the surface of the tool during cutting, which include chip formation, the generation of adhesive layers, and the buildup edge formation. In-depth knowledge of these processes can be used to significantly increase the wear resistance of the coated cutting tools. This can be achieved by the application of the latest generation of complex adaptive surface-engineered systems represented by several state-of-the-art adaptive nano-multilayer PVD coatings, as well as high entropy alloy coatings (HEAC).
An Optimal Family of Block Techniques to Solve Models of Infectious Diseases: Fixed and Adaptive Stepsize Strategies
Authors: Abuasbeh Kinda , Qureshi Sania , Soomro Amanullah , Awadalla Muath
Published: February 2023

The contemporary scientific community is very familiar with implicit block techniques for solving initial value problems in ordinary differential equations. This is due to the fact that these techniques are cost effective, consistent and stable, and they typically converge quickly when applied to solve particularly stiff models. These aspects of block techniques are the key motivations for the one-step optimized block technique with two off-grid points that was developed in the current research project. Based on collocation points, a family of block techniques can be devised, and it is shown that an optimal member of the family can be picked up from the leading term of the local truncation error. The theoretical analysis is taken into consideration, and some of the concepts that are looked at are the order of convergence, consistency, zero-stability, linear stability, order stars, and the local truncation error. Through the use of numerical simulations of models from epidemiology, it was demonstrated that the technique is superior to the numerous existing methodologies that share comparable characteristics. For numerical simulation, a number of models from different areas of medical science were taken into account. These include the SIR model from epidemiology, the ventricular arrhythmia model from the pharmacy, the biomass transfer model from plants, and a few more.
A Novel Computational Procedure for the Waiting-Time Distribution (In the Queue) for Bulk-Service Finite-Buffer Queues with Poisson Input
Authors: Chaudhry Mohan , Datta Banik Abhijit Datta , Barik Sitaram , Goswami Veena
Published: February 2023

In this paper, we discuss the waiting-time distribution for a finite-space, single-server queueing system, in which customers arrive singly following a Poisson process and the server operates under (a,b)-bulk service rule. The queueing system has a finite-buffer capacity ‘N’ excluding the batch in service. The service-time distribution of batches follows a general distribution, which is independent of the arrival process. We first develop an alternative approach of obtaining the probability distribution for the queue length at a post-departure epoch of a batch and, subsequently, the probability distribution for the queue length at a random epoch using an embedded Markov chain, Markov renewal theory and the semi-Markov process. The waiting-time distribution (in the queue) of a random customer is derived using the functional relation between the probability generating function (pgf) for the queue-length distribution and the Laplace–Stieltjes transform (LST) of the queueing-time distribution for a random customer. Using LSTs, we discuss the derivation of the probability density function of a random customer’s waiting time and its numerical implementations.
Door State Recognition Method for Wall Reconstruction from Scanned Scene in Point Clouds
Authors: Ning Xiaojuan , Sun Zeqian , Wang Lanlan , Wang Man , Lv Zhiyong , Zhang Jiguang , Wang Yinghui
Published: February 2023

Doors are important elements of building façades in scanned point clouds. Accurate door detection is a critical step in building reconstruction and indoor navigation. However, recent door detection methods may often obtain incomplete information and can only detect doors with a single state (open or closed). To improve this, a door state recognition method is proposed based on corner detection and straight-line fitting. Firstly, plane segmentation based on local features is introduced to obtain structural division from the raw scanned data to extract the wall. Next, the bounding box of each plane is calculated to obtain the corner points, which is then combined with the feature constraint to classify the elements of door and wall. Then, the boundary of each plane is extracted by normal vector, and the disordered and discontinuous boundary points are straight-line fitted based on projection. Finally, the state of the door is obtained through analysis of the angle between the straight-lines of the wall and the door. The effectiveness of the proposed method is tested and evaluated on the Livingroom of ICL-NUIM and House of Room detection datasets. Furthermore, comparative experimental results indicate that our method can extract corner points and recognize the different states of doors effectively and robustly in different scenes.
Toward Zero-Determinant Strategies for Optimal Decision Making in Crowdsourcing Systems
Authors: Wang Jiali , Tang Changbing , Lu Jianquan , Chen Guanrong
Published: February 2023

The crowdsourcing system is an internet-based distributed problem-solving and production organization model, which has been applied in human–computer interaction, databases, natural language processing, machine learning and other fields. It guides the public to complete some tasks through specific strategies and methods. However, rational and selfish workers in crowdsourcing systems will submit solutions of different qualities in order to maximize their own benefits. Therefore, how to choose optimal strategies for selfish workers to maximize their benefits is important and crucial in such a scenario. In this paper, we propose a decision optimization method with incomplete information in a crowdsourcing system based on zero-determinant (ZD) strategies to help workers make optimal decisions. We first formulate the crowdsourcing problem, where workers have “winner-takes-all” rules as an iterated game with incomplete information. Subsequently, we analyze the optimal decision of workers in crowdsourcing systems in terms of ZD strategies, for which we find conditions to reach the maximum payoff of a focused worker. In addition, the analysis helps understand what solutions selfish workers will submit under the condition of having incomplete information. Finally, numerical simulations illustrate the performances of different strategies and the effects of the parameters on the payoffs of the focused worker.
On Some Inequalities Involving Generalized Distance Functions
Authors: Jleli Mohamed , Samet Bessem
Published: February 2023

In this paper, a new class of generalized distance functions with respect to a pair of mappings is introduced. Next, some inequalities involving such distance functions are established. Our obtained results generalize and cover some recent results from the literature. Moreover, new distance inequalities for self-crossing polygons are obtained.
The Two Stage Moisture Diffusion Model for Non-Fickian Behaviors of 3D Woven Composite Exposed Based on Time Fractional Diffusion Equation
Authors: Yu Hang , Zhu Chenhui , Yao Lu , Ma Yan , Ni Yang , Li Shenkai , Li Huan , Liu Yang , Wang Yuming
Published: February 2023

The moisture diffusion behaviors of 3D woven composites exhibit non-Fickian properties when they are exposed to a hydrothermal environment. Although some experimental works have been undertaken to investigate this phenomenon, very few mathematical works on non-Fickian moisture diffusion predictions of 3D woven composites are available in the literature. To capture the non-Fickian behavior of moisture diffusion in 3D woven composites, this study first utilized a time fractional diffusion equation to derive the percentage of moisture content of a homogeneous material under hydrothermal conditions. A two-stage moisture diffusion model was subsequently developed based on the moisture diffusion mechanics of both neat resin and 3D woven composites, which describes the initial fast diffusion and the long-term slow diffusion stages. Notably, the model incorporated fractional order parameters to account for the nonlinear property of moisture diffusion in composites. Finally, the weight gain curves of neat resin and the 3D woven composite were calculated to verify the fractional diffusion model, and the predicted moisture uptake curves were all in good agreement with the experimental results. It is important to note that when the fractional order parameter α < 1, the initial moisture uptake will become larger with a later slow down process. This phenomenon can better describe non-Fickian behavior caused by initial voids or complicated structures.
MFANet: A Collar Classification Network Based on Multi-Scale Features and an Attention Mechanism
Authors: Qin Xiao , Ya Shanshan , Yuan Changan , Chen Dingjia , Long Long , Liao Huixian
Published: February 2023

The collar is an important part of a garment that reflects its style. The collar classification task is to recognize the collar type in the apparel image. In this paper, we design a novel convolutional module called MFA (multi-scale features attention) to address the problems of high noise, small recognition target and unsatisfactory classification effect in collar feature recognition, which first extracts multi-scale features from the input feature map and then encodes them into an attention weight vector to enhance the representation of important parts, thus improving the ability of the convolutional block to combat noise and extract small target object features. It also reduces the computational overhead of the MFA module by using the depth-separable convolution method. Experiments on the collar dataset Collar6 and the apparel dataset DeepFashion6 (a subset of the DeepFashion database) show that MFANet is able to perform at a relatively small number of collars. MFANet can achieve better classification performance than most current mainstream convolutional neural networks for complex collar images with less computational overhead. Experiments on the standard dataset CIFAR-10 show that MFANet also outperforms current mainstream image classification algorithms.
A Moving Target Detection Model Inspired by Spatio-Temporal Information Accumulation of Avian Tectal Neurons
Authors: Huang Shuman , Niu Xiaoke , Wang Zhizhong , Liu Gang , Shi Li
Published: February 2023

Moving target detection in cluttered backgrounds is always considered a challenging problem for artificial visual systems, but it is an innate instinct of many animal species, especially the avian. It has been reported that spatio-temporal information accumulation computation may contribute to the high efficiency and sensitivity of avian tectal neurons in detecting moving targets. However, its functional roles for moving target detection are not clear. Here we established a novel computational model for detecting moving targets. The proposed model mainly consists of three layers: retina layer, superficial layers of optic tectum, and intermediate-deep layers of optic tectum; in the last of which motion information would be enhanced by the accumulation process. The validity and reliability of this model were tested on synthetic videos and natural scenes. Compared to EMD, without the process of information accumulation, this model satisfactorily reproduces the characteristics of tectal response. Furthermore, experimental results showed the proposed model has significant improvements over existing models (EMD, DSTMD, and STMD plus) on STNS and RIST datasets. These findings do not only contribute to the understanding of the complicated processing of visual motion in avians, but also further provide a potential solution for detecting moving targets against cluttered environments.
Glycoproteins Involved in Sea Urchin Temporary Adhesion
Authors: Ventura Inês , Harman Victoria , Beynon Robert J. , Santos Romana
Published: February 2023

Biomedical adhesives, despite having been used increasingly in recent years, still face a major technological challenge: strong adhesion in wet environments. In this context, biological adhesives secreted by marine invertebrates have appealing characteristics to incorporate into new underwater biomimetic adhesives: water resistance, nontoxicity and biodegradability. Little is still known about temporary adhesion. Recently, a transcriptomic differential analysis of sea urchin Paracentrotus lividus tube feet pinpointed 16 adhesive/cohesive protein candidates. In addition, it has been demonstrated that the adhesive secreted by this species is composed of high molecular weight proteins associated with N-Acetylglucosamine in a specific chitobiose arrangement. As a follow-up, we aimed to investigate which of these adhesive/cohesive protein candidates were glycosylated through lectin pulldowns, protein identification by mass spectroscopy and in silico characterization. We demonstrate that at least five of the previously identified protein adhesive/cohesive candidates are glycoproteins. We also report the involvement of a third Nectin variant, the first adhesion-related protein to be identified in P. lividus. By providing a deeper characterization of these adhesive/cohesive glycoproteins, this work advances our understanding of the key features that should be replicated in future sea urchin-inspired bioadhesives.
Marinobazzanan, a Bazzanane-Type Sesquiterpenoid, Suppresses the Cell Motility and Tumorigenesis in Cancer Cells
Authors: Pulat Sultan , Hillman Prima F. , Kim Sojeong , Asolkar Ratnakar N. , Kim Haerin , Zhou Rui , Taş İsa , Gamage Chathurika D. B. , Varlı Mücahit , Park So-Yeon , Park Sung Chul , Yang Inho , Shin Jongheon , Oh Dong-Chan , Kim Hangun , Nam Sang-Jip , Fenical William
Published: February 2023

Marinobazzanan (1), a new bazzanane-type sesquiterpenoid, was isolated from a marine-derived fungus belonging to the genus Acremonium. The chemical structure of 1 was elucidated using NMR and mass spectroscopic data, while the relative configurations were established through the analysis of NOESY data. The absolute configurations of 1 were determined by the modified Mosher’s method as well as vibrational circular dichroism (VCD) spectra calculation and it was determined as 6R, 7R, 9R, and 10R. It was found that compound 1 was not cytotoxic to human cancer cells, including A549 (lung cancer), AGS (gastric cancer), and Caco-2 (colorectal cancer) below the concentration of 25 μM. However, compound 1 was shown to significantly decrease cancer-cell migration and invasion and soft-agar colony-formation ability at concentrations ranging from 1 to 5 μM by downregulating the expression level of KITENIN and upregulating the expression level of KAI1. Compound 1 suppressed β-catenin-mediated TOPFLASH activity and its downstream targets in AGS, A549, and Caco-2 and slightly suppressed the Notch signal pathway in three cancer cells. Furthermore, 1 also reduced the number of metastatic nodules in an intraperitoneal xenograft mouse model.
Enhanced Antifouling in Flat-Sheet Polyphenylsulfone Membranes Incorporating Graphene Oxide–Tungsten Oxide for Ultrafiltration Applications
Authors: Al-Maliki Raghad M. , Alsalhy Qusay F. , Al-Jubouri Sama , AbdulRazak Adnan A. , Shehab Mohammed Ahmed , Németh Zoltán , Hernadi Klara , Majdi Hasan Sh.
Published: February 2023

In this study tungsten oxide and graphene oxide (GO-WO2.89) were successfully combined using the ultra-sonication method and embedded with polyphenylsulfone (PPSU) to prepare novel low-fouling membranes for ultrafiltration applications. The properties of the modified membranes and performance were investigated using Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), contact angle (CA), water permeation flux, and bovine serum albumin (BSA) rejection. It was found that the modified PPSU membrane fabricated from 0.1 wt.% of GO-WO2.89 possessed the best characteristics, with a 40.82° contact angle and 92.94% porosity. The permeation flux of the best membrane was the highest. The pure water permeation flux of the best membrane showcased 636.01 L·m−2·h−1 with 82.86% BSA rejection. Moreover, the membranes (MR-2 and MR-P2) manifested a higher flux recovery ratio (FRR %) of 92.66 and 87.06%, respectively, and were less prone to BSA solution fouling. The antibacterial performance of the GO-WO2.89 composite was very positive with three different concentrations, observed via the bacteria count method. These results significantly overtake those observed by neat PPSU membranes and offer a promising potential of GO-WO2.89 on activity membrane performance.
High Efficient CO2 Separation at High Pressure by Grain-Boundary-Controlled CHA Zeolite Membrane Investigated by Non-Equilibrium Molecular Dynamics
Authors: Hirosawa Fumiya , Miyagawa Masaya , Takaba Hiromitsu
Published: February 2023

The CO2 permeability and selectivity of CHA-type zeolite membranes in the separation of a CO2/CH4 mixture gas at high pressure were evaluated using non-equilibrium molecular dynamics (NEMD). It was found that in a perfectly crystalline, defect-free CHA membrane, the adsorption of CH4, which diffuses slowly in the pores, hinders CO2 permeation. Therefore, an increase in the amount of CH4 adsorbed at high pressure decreases the CO2 permeability and significantly reduces the CO2 selectivity of the CHA membrane. CHA membranes with grain boundaries parallel to the permeation direction were found to show higher CO2 selectivity than perfectly crystalline CHA membranes at high pressure, as the blocking effect of CH4 on CO2 permeation occurring within the grain boundary is not significant. This paper is the first to show that the CO2 permeability of CHA membranes with controlled grain boundaries can exceed the intrinsic performance of fully crystalline zeolite membranes at high pressure.
Removal of Reactive Black 5 Azo Dye from Aqueous Solutions by a Combination of Reduction and Natural Adsorbents Processes
Authors: Ben Mbarek Wael , Daza Jason , Escoda Lluisa , Fiol Núria , Pineda Eloi , Khitouni Mohamed , Suñol Joan-Josep
Published: February 2023

In this study, a combined process of reduction and adsorption for the degradation of azo dye with nanocrystalline Fe80Si10B10 powder as a reducing agent is analyzed. A mechanical alloying technique produced the powdered alloys needed for the redox process. The synthesized nanocrystalline structure favors the efficiency of the reduction step of Reactive Black 5 (RB5) azo dye. According to the UV-Vis analysis, the reductive process alone allowed for nearly complete color removal after 3 min of reaction. In this regard, the nanocrystallized FeSiB powder has excellent application potential in the first step of the reduction processes for degrading azo dye solutions. Indeed, the nanocrystalline FeSiB powder outperforms commercial Fe powders in terms of degradation efficiency because of the formation of multiple micro-batteries between the α-Fe solid solution and the Fe3Si nanocrystalline phases, favoring the loss of electrons from iron and exhibiting different corrosion resistance. In the second step, the adsorption process, the efficient removal of intermediate undesired compounds from the reduction processes, principally aromatic amines, is analyzed. Different adsorbents, including wood, graphene oxide, activated carbon, and pine particles, were used. The results suggest that graphene oxide and activate carbon performed the best for secondary product adsorption following RB5 degradation. The current study could serve as a guide for environmental applications, such as industrial wastewater treatment, using metallic powders produced by high-energy mechanical alloying.
Effect of WC Content on Microstructure and Element Diffusion of Nano WC-Co-TiC/304 Stainless Steel Composites for Micro Drill
Authors: Zhu Rui , Zhang Hongmei , Wang Jianling , Li Hongnan , Li Jinmeng , Zhang Zhisong , Zhu Yuchuan , Jiang Zhengyi
Published: February 2023

In this study, WC-Co-TiC/304 stainless steel composites were successfully prepared by compression at room temperature and vacuum sintering in a special mold. Through analysis and comparison of the microstructure, density, and particle size of WC-Co-TiC/304 stainless steel composite, the effects of different WC contents on the structure and properties of WC-Co-TiC were studied. The results show that among different WC contents when the WC content is 60%, the distribution of each structure is relatively uniform and fine, and the agglomeration of each structure is not obvious. The bonding effect of WC-Co-TiC cemented carbide and 304 stainless steel composite interface is the best. With the increase of WC content, the side defects of WC-Co-TiC cemented carbide increase gradually. When WC content is 60%, the best ratio is 1:1 of Co/TiC, as the density is 94.45%, the particle size of 0.2–0.3 μm is 38.9%, and the highest hardness of WC-Co-TiC cemented carbide side is 1370 HV0.1, but it is better when the ratio of Co/TiC is 3:2 at the composite interface, as the hardness value is 852 HV0.1 and the diffusion of Cr element is more uniform, while other elements have little difference.
Determination of Decarburization Depth Base on Deep Learning Methods
Authors: Huang Huang-Chu , Hu Ting-Kuang , Lee Jen-Chun , Lin Jao-Chuan , Chen Chung-Hsien , Lin Chiu-Chin
Published: February 2023

In the heat treatment of steel, decarburization is a serious issue that leads to poor wear resistance and low fatigue life. At present, the decarburization depth was determined using a visual estimation by the human eye, and the software estimation was determined through traditional image analysis. Therefore, decarburization depth analysis remains limited in experts and traditional algorithms. Artificial intelligence is a general-purpose technology that has a multitude of applications. This paper uses the concept of deep learning to propose a decarburization layer detector (DLD) that can determine the depth of decarburized layers. This DLD system boasts high performance, real-time, low learning, and computation costs. In addition, we used several kinds of decarburized layers images to compare the proposed method with other deep learning network architectures. The experimental results show that the proposed method yields a detection accuracy of 92.97%, which is higher than existing methods and boasts computational demands which are far lower than other network architectures. Therefore, we propose a novel system for automatic decarburization depth determination as an application for metallographic analysis.
The Influence of Sm Content on the Surface Morphology and Corrosion Behavior of Zn-Co-Sm Composite Coatings
Authors: Bučko Mihael , Stupar Stevan , Bajat Jelena B.
Published: February 2023

The influence of samarium, as an additional alloying element, on the morphology and corrosion performance of the Zn-Co-Sm alloy electrodeposited coatings, was investigated by scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM/EDS) and electrochemical impedance spectroscopy (EIS) measurements. The Zn-Co-Sm coatings were electrodeposited from the aqueous solution containing Sm(NO3)3, ZnCl2, and CoCl2 as the metal ion source. The percentage of Sm in the coating may be very finely tuned by setting electrodeposition parameters, including cathodic current density, glycine concentration in the electroplating solution, and the solution temperature. The coatings with Sm content from 0.5 to 18.5 wt.% were produced. Since low deposition current densities (10–50 mA cm−2) were applied, the samples obtained were of good adhesion and compact. The presence of Sm2O3 inclusion was verified by XRD as the Sm2O3 crystalline phase. Samarium is incorporated in the coatings through the mechanism of oxide/hydroxide formation during the electroreduction of Zn and Co. Corrosion tests in NaCl solution show that the presence of Sm significantly increases the polarization resistance for the corrosion process of Zn-Co-Sm coatings (one order of magnitude, i.e., from ~500 Ω cm2 measured without Sm to 2000–3000 Ω cm2 with 12 wt.% Sm), giving evidence of the self-healing action that is provided by Sm particles in the coatings. This effect is more pronounced in the case when the coatings contain a higher Sm percentage.
Association between Gut Dysbiosis and the Occurrence of SIBO, LIBO, SIFO and IMO
Authors: Banaszak Michalina , Górna Ilona , Woźniak Dagmara , Przysławski Juliusz , Drzymała-Czyż Sławomira
Published: February 2023

Gut microbiota is the aggregate of all microorganisms in the human digestive system. There are 1014 CFU/mL of such microorganisms in the human body, including bacteria, viruses, fungi, archaea and protozoa. The Firmicutes and Bacteroidetes bacteria phyla comprise 90% of the human gut microbiota. The microbiota support the healthy functioning of the human body by helping with digestion (mainly via short-chain fatty acids and amino acids) and producing short-chain fatty acids. In addition, it exhibits many physiological functions, such as forming the intestinal epithelium, intestinal integrity maintenance, the production of vitamins, and protection against pathogens. An altered composition or the number of microorganisms, known as dysbiosis, disrupts the body’s homeostasis and can lead to the development of inflammatory bowel disease, irritable bowel syndrome, and metabolic diseases such as diabetes, obesity and allergies. Several types of disruptions to the gut microbiota have been identified: SIBO (Small Intestinal Bacterial Overgrowth), LIBO (Large Intestinal Bacterial Overgrowth), SIFO (Small Intestinal Fungal Overgrowth), and IMO (Intestinal Methanogen Overgrowth). General gastrointestinal problems such as abdominal pain, bloating, gas, diarrhoea and constipation are the main symptoms of dysbiosis. They lead to malabsorption, nutrient deficiencies, anaemia and hypoproteinaemia. Increased lipopolysaccharide (LPS) permeability, stimulating the inflammatory response and resulting in chronic inflammation, has been identified as the leading cause of microbial overgrowth in the gut. The subject literature is extensive but of limited quality. Despite the recent interest in the gut microbiome and its disorders, more clinical research is needed to determine the pathophysiology, effective treatments, and prevention of small and large intestinal microbiota overgrowth. This review was designed to provide an overview of the available literature on intestinal microbial dysbiosis (SIBO, LIBO, SIFO and IMO) and to determine whether it represents a real threat to human health.
Human Colonization and Infection by Staphylococcus pseudintermedius: An Emerging and Underestimated Zoonotic Pathogen
Authors: Moses Ikechukwu Benjamin , Santos Fernanda Fernandes , Gales Ana Cristina
Published: February 2023

S. pseudintermedius is a known resident of the skin and mucous membranes and a constituent of the normal microbiota of dogs. It has also been recognized as an opportunistic and zoonotic pathogen that is able to colonize humans and cause severe diseases, especially in immunocompromised hosts. Most importantly, methicillin-resistant S. pseudintermedius (MRSP), which is intrinsically multidrug-resistant, has emerged with serious public health consequences. The epidemiological situation is further exacerbated with reports of its zoonotic transmission and human infections which have been mostly attributed to the increasing frequency of dog ownership and close contact between dogs and humans. Evidence on the zoonotic transmission of MRSP from pet dogs to humans (such as dog owners, small-animal veterinarians, and other people in close proximity to dogs) is limited, especially due to the misidentification of S. pseudintermedius as S. aureus. Despite this fact, reports on the increasing emergence and spread of MRSP in humans have been increasing steadily over the years since its first documented report in 2006 in Belgium. The emergence of MRSP strains has further compromised treatment outcomes in both veterinary and human medicine as these strains are resistant to beta-lactam antimicrobials usually prescribed as first line treatment. Frustratingly, the limited awareness and surveillance of the zoonotic transmission of S. pseudintermedius have underestimated their extent of transmission, prevalence, epidemiology, and public health significance. In order to fill this gap of information, this review focused on detailed reports on zoonotic transmission, human colonization, and infections by S. pseudintermedius, their pathogenic features, antimicrobial resistance profiles, epidemiology, risk factors, and treatment. In writing this review, we searched Web of Science, PubMed, and SCOPUS databases using the keyword “Staphylococcus pseudintermedius AND humans”. A phylogenetic tree to determine the genetic relatedness/diversity of publicly available genomes of S. pseudintermedius was also constructed.
Circulating Bacterial DNA as Plasma Biomarkers for Lung Cancer Early Detection
Authors: Zhou Huifen , Liao Jipei , Leng Qixin , Chinthalapally Molangur , Dhilipkannah Pushpa , Jiang Feng
Published: February 2023

Lung cancer is a leading cause of cancer deaths and early diagnosis can significantly improve outcomes. Pathogenic bacteria have been shown to play a role in tumorigenesis and its analysis provides a new approach for cancer diagnosis. To evaluate the potential of bacteria as plasma biomarkers for early lung cancer detection, we analyzed eight lung-cancer-related bacterial genera in 58 lung cancer patients and 58 controls using ddPCR. Our results showed that five genera had higher DNA abundance in lung tumor tissues compared with normal tissues. Three of these genera (Selenomonas, Streptococcus, and Veillonella) displayed consistent changes in plasma, with higher DNA abundance in lung cancer patients compared with controls. When used as a panel, these three bacterial genera had a sensitivity of 75% and specificity of 78% for lung cancer detection, regardless of stage or histology. The performance of this biomarker panel was confirmed in an independent cohort of 93 lung cancer cases and 93 controls. Thus, circulating bacterial DNA has the potential to be used as plasma biomarkers for early lung cancer detection.
Fungal Pathogens Associated with Aerial Symptoms of Avocado (Persea americana Mill.) in Tenerife (Canary Islands, Spain) Focused on Species of the Family Botryosphaeriaceae
Authors: Hernández David , García-Pérez Omar , Perera Santiago , González-Carracedo Mario A. , Rodríguez-Pérez Ana , Siverio Felipe
Published: February 2023

Fungi of the family Botryosphaeriaceae are considered responsible for various symptoms in avocado such as dieback, external necrosis of branches and inflorescences, cankers on branches and trunks, or stem-end rot of fruits. In recent years, these problems are becoming more frequent in avocado orchards in the Canary Islands (Spain). This work includes the characterization of fungal species involved in these diseases, which were isolated from avocado crops in Tenerife Island between 2018 and 2022. A total of 158 vegetal samples were collected, from which 297 fungal isolates were culture-isolated. Fifty-two of them were selected according to their morphological features as representative isolates of Botryosphaeriaceae, and their molecular characterization was carried out, sequencing the ITS1-2 region as well as the β-tubulin and the elongation factor 1-alpha genes. Five species of Botryosphaeriaceae were isolated, including Neofusicoccum australe, N. cryptoaustrale/stellenboschiana, N. luteum, N. parvum, and Lasiodiplodia brasiliensis. This is the first time that L. brasiliensis has been associated with avocado dieback and that N. cryptoaustrale/stellenboschiana has been cited in avocado causing symptoms of dieback and stem-end rot. However, it was not possible to assign our isolates unequivocally to N. cryptoaustrale or N. stellenboschiana even additionally using the rpb2 marker for their molecular characterization. Botryosphaeriaceae family seem to be involved in avocado dieback, in the premature fall of fruits during their development in the field and in post-harvest damage in Tenerife, but further studies are needed to clarify the fungal pathogens associated with symptoms in relation to phenological plant growth stages or less frequently observed.
Isolation of Bioactive Metabolites from Soil Derived Fungus-Aspergillus fumigatus
Authors: Gill Harman , Sykes Ellen M. E. , Kumar Ayush , Sorensen John L.
Published: February 2023

Fungi produce numerous secondary metabolites with intriguing biological properties for the health, industrial, and agricultural sectors. Herein, we report the high-yield isolation of phenolic natural products, N-formyl-4-hydroxyphenyl-acetamide 1 (~117 mg/L) and atraric acid 2 (~18 mg/L), from the ethyl acetate extract of the soil-derived fungus, Aspergillus fumigatus. The structures of compounds 1 and 2 were elucidated through the detailed spectroscopic analysis of NMR and LCMS data. These compounds were assayed for their antimicrobial activities. It was observed that compounds 1 and 2 exhibited strong inhibition against a series of fungal strains but only weak antibacterial properties against multi-drug-resistant strains. More significantly, this is the first known instance of the isolation of atraric acid 2 from a non-lichen fungal strain. We suggest the optimization of this fungal strain may exhibit elevated production of compounds 1 and 2, potentially rendering it a valuable source for the industrial-scale production of these natural antimicrobial compounds. Further investigation is necessary to establish the veracity of this hypothesis.