bluuebunny/crossref_metadata_2025 huggingface dataset:
Clinical and Radiological Outcome of Disc Arthroplasty for the Treatment of Cervical Spondylotic Myelopathy
Authors: Obid Peter , Rakow Anastasia , Lang Gernot Michael , Marx Wolfgang , Niemeyer Thomas , Rahim Tamim
Published: March 2023

Introduction: The aim of this study is to evaluate the clinical and radiological results of cervical disc arthroplasty (CDA) in patients with cervical spondylotic myelopathy (CSM) using the CP ESP® disc prosthesis. Materials and Methods: Prospectively collected data of 56 patients with CSM have been analyzed. The mean age at surgery was 35.6 years (range: 25–43 years). The mean follow-up was 28.2 months (range: 13–42 months). The range of motion (ROM) of the index segments, as well as upper and lower adjacent segments, was measured before surgery and at final follow-up. The C2-C7 sagittal vertical axis (SVA), C2-C7 cervical lordosis (CL), and T1 slope minus cervical lordosis (T1s-CL) were analyzed as well. Pain intensity was measured preoperatively and during follow-up using an 11-point numeric rating scale (NRS). Modified Japanese Orthopaedic Association (mJOA) score was assessed preoperatively and during follow-up for the clinical assessment of myelopathy. Surgical and implant-associated complications were analyzed as well. Results: The NRS pain score improved from a mean of 7.4 (±1.1) preoperatively to a mean of 1.5 (±0.7) at last follow-up (p < 0.001). The mJOA score improved from a mean of 13.1 (±2.8) preoperatively to a mean of 14.8 (±2.3) at last follow-up (p < 0.001). The mean ROM of the index levels increased from 5.2° (±3.0) preoperatively to 7.3° (±3.2) at last follow-up (p < 0.05). Four patients developed heterotopic ossifications during follow-up. One patient developed permanent dysphonia. Conclusions: CDA showed good clinical and radiological outcome in this cohort of young patients. The motion of index segments could be preserved. CDA may be a viable treatment option in selected patients with CSM.
Patient Self-Inflicted Lung Injury—A Narrative Review of Pathophysiology, Early Recognition, and Management Options
Authors: Sklienka Peter , Frelich Michal , Burša Filip
Published: March 2023

Patient self-inflicted lung injury (P-SILI) is a life-threatening condition arising from excessive respiratory effort and work of breathing in patients with lung injury. The pathophysiology of P-SILI involves factors related to the underlying lung pathology and vigorous respiratory effort. P-SILI might develop both during spontaneous breathing and mechanical ventilation with preserved spontaneous respiratory activity. In spontaneously breathing patients, clinical signs of increased work of breathing and scales developed for early detection of potentially harmful effort might help clinicians prevent unnecessary intubation, while, on the contrary, identifying patients who would benefit from early intubation. In mechanically ventilated patients, several simple non-invasive methods for assessing the inspiratory effort exerted by the respiratory muscles were correlated with respiratory muscle pressure. In patients with signs of injurious respiratory effort, therapy aimed to minimize this problem has been demonstrated to prevent aggravation of lung injury and, therefore, improve the outcome of such patients. In this narrative review, we accumulated the current information on pathophysiology and early detection of vigorous respiratory effort. In addition, we proposed a simple algorithm for prevention and treatment of P-SILI that is easily applicable in clinical practice.
Intrusion Detection System Using Feature Extraction with Machine Learning Algorithms in IoT
Authors: Musleh Dhiaa , Alotaibi Meera , Alhaidari Fahd , Rahman Atta , Mohammad Rami M.
Published: March 2023

With the continuous increase in Internet of Things (IoT) device usage, more interest has been shown in internet security, specifically focusing on protecting these vulnerable devices from malicious traffic. Such threats are difficult to distinguish, so an advanced intrusion detection system (IDS) is becoming necessary. Machine learning (ML) is one of the promising techniques as a smart IDS in different areas, including IoT. However, the input to ML models should be extracted from the IoT environment by feature extraction models, which play a significant role in the detection rate and accuracy. Therefore, this research aims to introduce a study on ML-based IDS in IoT, considering different feature extraction algorithms with several ML models. This study evaluated several feature extractors, including image filters and transfer learning models, such as VGG-16 and DenseNet. Additionally, several machine learning algorithms, including random forest, K-nearest neighbors, SVM, and different stacked models were assessed considering all the explored feature extraction algorithms. The study presented a detailed evaluation of all combined models using the IEEE Dataport dataset. Results showed that VGG-16 combined with stacking resulted in the highest accuracy of 98.3%.
Exploring the Dynamics of Occupation between Resilience and Abandonment in Two Post-Classic Rural Landscapes on the Iberian Peninsula
Authors: Sarabia-Bautista Julia
Published: March 2023

In this paper, we present a comparison of two rural landscapes in the southeast of the Iberian Peninsula, where the dynamics of occupation have differed since the end of the ancient world in terms of both the degree of resilience of settlements and the land use. Our purpose was to explore the social, political, economic, and environmental factors that could explain why there has been a long-term cross-cultural occupation of some resilient sites and landscapes for almost a millennium, while there have been only very specific temporary occupations in other areas. The first part of this paper describes the archaeological investigations carried out by means of intensive survey methods, geophysics, and some excavations in peripheral and peri-urban spaces. In the second part, we reflect on whether the use of the same methodology in all cases allows us to compare and understand what makes societies sustainable (or not) over time through their archaeological record.
Mapping Groundwater Prospective Areas Using Remote Sensing and GIS-Based Data Driven Frequency Ratio Techniques and Detecting Land Cover Changes in the Yellow River Basin, China
Authors: Li Shuhang , Abdelkareem Mohamed , Al-Arifi Nassir
Published: March 2023

Groundwater is an essential resource that meets all of humanity’s daily water demands, supports industrial development, influences agricultural output, and maintains ecological equilibrium. Remote sensing data can predict the location of potential water resources. The current study was conducted in China’s Yellow River region, Ningxia Hui Autonomous Region (NHAR). Through the use of a GIS-based frequency ratio machine learning technique, nine layers of evidence influenced by remote sensing data were generated and integrated. The layers used are soil characteristics, aspect, and roughness index of the terrain, drainage density, elevation, lineament density, depressions, rainfall, and distance to the river from the location. Six groundwater prospective zones (GWPZs) were found to have very low (13%), low (30%), moderate (25%), high (16%), very high (11%), and extreme potentiality (5.26%) values. According to well data used to validate the GWPZs map, approximately 40% of the wells are consistent to very high to excellent zones. Information about groundwater productivity was gathered from 150 well locations. Using well data that had not been used for model training, the resulting GWPZs maps were validated using area-under-the-curve (AUC) analysis. FR models have an accuracy rating of 0.759. Landsat data were used to characterize the study area’s changes in land cover. The spatiotemporal differences in land cover are detected and quantified using multi-temporal images which revealed changes in water, agricultural, and anthropogenic activities. Overall, combining different data sets through a GIS can reveal the promising areas of water resources that aid planners and managers.
Covariants of Gemination in Eastern Andalusian Spanish: /t/ following Underlying /s/, /k/, /p/ and /ks/
Authors: Herrero de Haro Alfredo , Hajek John
Published: March 2023

In Eastern Andalusian Spanish, consonants are deleted in syllable-final position, triggering regular gemination of a following consonant, even across word boundaries. This paper investigates five underlying phonemic contexts involving /t/, including singleton /t/ and four different underlying /C+t/ sequences that typically surface as [t:], by analyzing how durational and formant differences vary depending on the presence and identity of the preceding underlying consonant. Following the acoustic and statistical analyses of 444 instances of /ˈeta/, /ˈesta/, /ˈekta/, /ˈepta/ and /ˈeksta/, a Discriminant Function Analysis shows that differences in the total duration of /t/ and in the duration of the closure of /t/ are the strongest cues to distinguishing singletons from geminated consonants, with 91.9% and 90.6% accurate classifications, respectively. Cues indicating which specific consonants have been deleted before /t/ are much less robust and more varied in nature. It is unclear, however, whether this outcome is due to different compensation strategies in each case or whether they are affected by some kind of underlying coarticulatory effect. Given that gemination in this language variety is the result of regular /C1C2/ to [Cː] assimilation, and that its underlying phonemic status has not been demonstrated, Eastern Andalusian Spanish is unusual amongst languages studied with respect to gemination, making this study typologically interesting.
Surface Treatment of Mongolian Scots Pine Using Phosphate Precipitation for Better Performance of Compressive Strength and Fire Resistance
Authors: Ge Yan , Wang Liang , Wang Xuepeng , Wang Hao
Published: March 2023

Wood, as a naturally green and environmentally friendly material, has been widely used in the construction and decoration industries. However, the flammability of wood poses serious safety problems. To improve the fire resistance of wood, In this study, it is proposed to use calcium chloride (CaCl2) and disodium hydrogen phosphate (Na2HPO4, DSP) to impregnate wood for multiple cycles. The experimental results show that phosphate mineral precipitation can be deposited on the surface of the wood. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) are used to analyze the micromorphology of mineral precipitation and use the MIP test to analyze the treated wood pore structure. The results show that with the increase in the number of cycles, the phosphate deposited on the surface of the wood increases, and the cumulative pore volume and water absorption rate of the wood after 10 cycles are 54.3% and 13.75% lower than that of untreated wood respectively. In addition, the cone calorimeter (CONE) confirmed that the total heat release (THR) and total smoke production (TSP) of wood treated in 10 cycles have decreased by 48.7% and 54.2% respectively compared with the untreated wood. Hence, this treatment method not only improves the mechanical properties of wood. It also improves fire resistance.
Multidimensional Study on the Wear of High-Speed, High-Temperature, Heavy-Load Bearings
Authors: Wang Dongfeng , Yuan Julong , Hu Lai , Lyu Binghai
Published: March 2023

The friction and wear performance of high-performance bearings directly affects the accuracy and maneuverability of weapons and equipment. In this study, high-speed, high-temperature, and heavy-load durability experiments of weapon bearings were carried out, and their wear properties (i.e., surface wear, metamorphic layer, scanning electron microscopy/energy-dispersive spectroscopy (SEM/EDS), residual stress, and retained austenite) were analyzed in multiple dimensions. The results showed the following: (1) The experimental temperature of the serviced front-end bearing is always lower than that of the rear bearing. (2) The metamorphic layer of the serviced rear bearing (i.e., inner ring, outer ring, rolling body, and cage) > the metamorphic layer of the serviced front-end bearing > the metamorphic layer of the unserviced bearing. (3) The rolling body of the rear bearing at high experimental temperatures contains not only elemental O, but also elemental P and Sr. (4) In the EDS analysis of the rolling elements, with the migration from the “ball edge” to the “ball center”, the elemental C in the rolling elements of serviced or unserviced bearings decreases slowly, while the elemental Fe content increases slowly.
Single-Camera Three-Dimensional Digital Image Correlation with Enhanced Accuracy Based on Four-View Imaging
Authors: Shao Xinxing , Qu Jingye , Chen Wenwu
Published: March 2023

Owing to the advantages of cost-effectiveness, compactness, and the avoidance of complicated camera synchronization, single-camera three-dimensional (3D) digital image correlation (DIC) techniques have gained increasing attention for deformation measurement of materials and structures. In the traditional single-camera 3D-DIC system, the left and right view images can be recorded by a single camera using diffraction grating, a bi-prism, or a set of planar mirrors. To further improve the measurement accuracy of single-camera 3D-DIC, this paper introduces a single-camera four-view imaging technique by installing a pyramidal prism in front of the camera. The 3D reconstruction of the measured points before and after deformation is realized with eight governing equations induced by four views, and the strong geometric constraints of four views can help to improve the measurement accuracy. A static experiment, a rigid body translation experiment, and a four-point bending experiment show that the proposed single-camera 3D-DIC method can achieve higher measurement accuracy than the dual-view single-camera 3D-DIC techniques and that the single-camera 3D-DIC method has advantages in reducing both random error and systematic error.
Kidney Transplant: Survival Analysis and Prognostic Factors after 10 Years of Follow-Up
Authors: Beviá-Romero Álvaro , Quereda-Flores Francisco , Díaz-Carnicero Javier , Gómez-Palomo Francisco , Ramos-Cebrián María , Espinosa-Vañó Joaquín , Castillo-Antón Dario J. , Broseta-Rico Enrique , Vivas-Consuelo David , Budía-Alba Alberto
Published: March 2023

The aim of this work is to analyse recipient and graft survival after kidney transplant in a three-year cohort and to identify predictive factors with up to 10 years of follow-up. Methods: retrospective consecutive cohort study of 250 kidney transplant recipients operated between 2010 and 2012. Multiorganic transplants and both dead-donor and living-donor transplants were included. Data were collected from electronic health records. A survival analysis was conducted using the Kaplan-Meier method and a Cox proportional-hazards multivariate model. Results: mean follow-up was 8.1 ± 3.2 years. Graft survival at 2, 5 and 10 years was 89.0%, 85.1% and 78.4% respectively. The multivariate model identified the following risk factors for graft loss: diabetic nephropathy (HR 3.2 CI95% [1.1–9.4]), delayed graft function (3.8 [2.0–7.4]), chronic kidney rejection (3.7 [1.2–11.4]), and early surgical complications (2.6 [1.4–5.1]). Conversely, combined transplant was found to be a protective factor for graft loss (0.1 [0.0–0.5]). Recipient patient survival was 94.3%, 90.0% and 76.6% at 2, 5 and 10 years respectively. The model identified the following mortality risk factors: older recipient age (1.1 [1.1–1.2]), combined transplant (7.6 [1.7–34.5]) and opportunistic infections (2.6 [1.3–5.0]). Conclusions: 10-year recipient and graft survival were 76.6% and 78.4% respectively. Main mortality risk factors were older recipient age, opportunistic infections and multiorganic transplant. Main graft loss risk factors were diabetic nephropathy, delayed graft function, chronic kidney rejection and early surgical complications.
Applying Neural Networks on Biometric Datasets for Screening Speech and Language Deficiencies in Child Communication
Authors: Toki Eugenia I. , Tatsis Giorgos , Tatsis Vasileios A. , Plachouras Konstantinos , Pange Jenny , Tsoulos Ioannis G.
Published: March 2023

Screening and evaluation of developmental disorders include complex and challenging procedures, exhibit uncertainties in the diagnostic fit, and require high clinical expertise. Although typically, clinicians’ evaluations rely on diagnostic instrumentation, child observations, and parents’ reports, these may occasionally result in subjective evaluation outcomes. Current advances in artificial intelligence offer new opportunities for decision making, classification, and clinical assessment. This study explores the performance of different neural network optimizers in biometric datasets for screening typically and non-typically developed children for speech and language communication deficiencies. The primary motivation was to give clinicians a robust tool to help them identify speech disorders automatically using artificial intelligence methodologies. For this reason, in this study, we use a new dataset from an innovative, recently developed serious game collecting various data on children’s speech and language responses. Specifically, we employed different neural network approaches such as Artificial Neural Networks (ANNs), K-Nearest Neighbor (KNN), Support Vector Machines (SVM), along with state-of-the-art Optimizers, namely the Adam, the Broyden–Fletcher–Goldfarb–Shanno (BFGS), Genetic algorithm (GAs), and Particle Swarm Optimization algorithm (PSO). The results were promising, while Integer-bounded Neural Network proved to be the best competitor, opening new inquiries for future work towards automated classification supporting clinicians’ decisions on neurodevelopmental disorders.
Novel Creation Method of Feature Graphics for Image Generation Based on Deep Learning Algorithms
Authors: Li Ying , Tang Ye
Published: March 2023

In this paper, we propose a novel creation method of feature graphics by deep learning algorithms based on a channel attention module consisting of a separable deep convolutional neural network and an SENet network. The main innovation of this method is that the image feature of sample images is extracted by convolution operation and the key point matrix is obtained by channel weighting calculation to create feature graphics within the channel attention module. The main problem of existing image generation methods is that the complex network training and calculation process affects the accuracy and efficiency of image generation. It greatly reduced the complexity of image generation and improved the efficiency when we trained the image generation network with the feature graphic maps. To verify the superiority of this method, we conducted a comparative experiment with the existing method. Additionally, we explored the influence on the accuracy and efficiency of image generation of the channel number of the weighting matrix based on the test experiment. The experimental results demonstrate that this method highlights the image features of geometric lines, simplifies the complexity of image generation and improves the efficiency. Based on this method, images with more prominent line features are generated from the description text and dynamic graphics are created for the display of the images generated, which can be applied in the construction of smart museums.
Diagnosing Vascular Aging Based on Macro and Micronutrients Using Ensemble Machine Learning
Authors: Patino-Alonso Carmen , Gómez-Sánchez Marta , Gómez-Sánchez Leticia , Rodríguez-Sánchez Emiliano , Agudo-Conde Cristina , García-Ortiz Luis , Gómez-Marcos Manuel A
Published: March 2023

The influence of dietary components on vascular dysfunction and aging is unclear. This study therefore aims to propose a model to predict the influence of macro and micronutrients on accelerated vascular aging in a Spanish population without previous cardiovascular disease. This cross-sectional study involved a total of 501 individuals aged between 35 and 75 years. Carotid-femoral pulse wave velocity (cfPWV) was measured using a Sphygmo Cor® device. Carotid intima-media thickness (IMTc) was measured using a Sonosite Micromax® ultrasound machine. The Vascular Aging Index (VAI) was estimated according to VAI = (LN (1.09) × 10 cIMT + LN (1.14) × cfPWV) 39.1 + 4.76. Vascular aging was defined considering the presence of a vascular lesion and the p75 by age and sex of VAI following two steps: Step 1: subjects were labelled as early vascular aging (EVA) if they had a peripheral arterial disease or carotid artery lesion. Step 2: they were classified as EVA if the VAI value was >p75 and as normal vascular aging (NVA) if it was ≤p75. To predict the model, we used machine learning algorithms to analyse the association between macro and micronutrients and vascular aging. In this article, we proposed the AdXGRA model, a stacked ensemble learning model for diagnosing vascular aging from macro and micronutrients. The proposed model uses four classifiers, AdaBoost (ADB), extreme gradient boosting (XGB), generalized linear model (GLM), and random forest (RF) at the first level, and then combines their predictions by using a second-level multilayer perceptron (MLP) classifier to achieve better performance. The model obtained an accuracy of 68.75% in prediction, with a sensitivity of 66.67% and a specificity of 68.79%. The seven main variables related to EVA in the proposed model were sodium, waist circumference, polyunsaturated fatty acids (PUFA), monounsaturated fatty acids (MUFA), total protein, calcium, and potassium. These results suggest that total protein, PUFA, and MUFA are the macronutrients, and calcium and potassium are the micronutrients related to EVA.
The Approach of Artificial Intelligence in Neuroendocrine Carcinomas of the Breast: A Next Step towards Precision Pathology?—A Case Report and Review of the Literature
Authors: Chiorean Diana Maria , Mitranovici Melinda-Ildiko , Mureșan Maria Cezara , Buicu Corneliu-Florin , Moraru Raluca , Moraru Liviu , Cotoi Titiana Cornelia , Cotoi Ovidiu Simion , Apostol Adrian , Turdean Sabin Gligore , Mărginean Claudiu , Petre Ion , Oală Ioan Emilian , Simon-Szabo Zsuzsanna , Ivan Viviana , Roșca Ancuța Noela , Toru Havva Serap
Published: March 2023

Primary neuroendocrine tumors (NETs) of the breast are considered a rare and undervalued subtype of breast carcinoma that occur mainly in postmenopausal women and are graded as G1 or G2 NETs or an invasive neuroendocrine carcinoma (NEC) (small cell or large cell). To establish a final diagnosis of breast carcinoma with neuroendocrine differentiation, it is essential to perform an immunohistochemical profile of the tumor, using antibodies against synaptophysin or chromogranin, as well as the MIB-1 proliferation index, one of the most controversial markers in breast pathology regarding its methodology in current clinical practice. A standardization error between institutions and pathologists regarding the evaluation of the MIB-1 proliferation index is present. Another challenge refers to the counting process of MIB-1′s expressiveness, which is known as a time-consuming process. The involvement of AI (artificial intelligence) automated systems could be a solution for diagnosing early stages, as well. We present the case of a post-menopausal 79-year-old woman diagnosed with primary neuroendocrine carcinoma of the breast (NECB). The purpose of this paper is to expose the interpretation of MIB-1 expression in our patient’ s case of breast neuroendocrine carcinoma, assisted by artificial intelligence (AI) software (HALO—IndicaLabs), and to analyze the associations between MIB-1 and common histopathological parameters.
Gingival Orofacial Granulomatosis Clinical and 2D/3D Microscopy Features after Orthodontic Therapy: A Pediatric Case Report
Authors: Cecchin-Albertoni Chiara , Pieruccioni Laetitia , Canceill Thibault , Benetah Robin , Chaumont Jade , Guissard Christophe , Monsarrat Paul , Kémoun Philippe , Marty Mathieu
Published: March 2023

Orofacial granulomatosis (OFG) represents a heterogeneous group of rare orofacial diseases. When affecting gingiva, it appears as a chronic soft tissue inflammation, sometimes combined with the enlargement and swelling of other intraoral sites, including the lips. Gingival biopsy highlights noncaseating granulomatous inflammation, similar to that observed in Crohn’s disease and sarcoidosis. At present, the etiology of OFG remains uncertain, although the involvement of the genetic background and environmental triggers, such as oral conditions or therapies (including orthodontic treatment), has been suggested. The present study reports the results of a detailed clinical and 2D/3D microscopy investigation of a case of gingival orofacial granulomatosis in an 8-year-old male patient after orthodontic therapy. Intraoral examination showed an erythematous hyperplasia of the whole gingiva with a granular appearance occurring a few weeks after the installation of a quad-helix. Peri-oral inspection revealed upper labial swelling and angular cheilitis. General investigations did not report ongoing extra-oral disturbances with the exception of a weakly positive anti-Saccharomyces cerevicae IgG auto-antibody. Two- and three-dimensional microscopic investigations confirmed the presence of gingival orofacial granulomatosis. Daily corticoid mouthwashes over a period of 3 months resulted in a slight improvement in clinical signs, despite an intermittent inflammation recurrence. This study brings new insights into the microscopic features of gingival orofacial granulomatosis, thus providing key elements to oral practitioners to ensure accurate and timely OFG diagnosis. The accurate diagnosis of OFG allows targeted management of symptoms and patient monitoring over time, along with early detection and treatment of extra-oral manifestations, such as Crohn’s disease.
Editorial for the Special Issue “Chronic Neuropathic Pain Therapy and Anaesthesia”
Authors: Miękisiak Grzegorz
Published: March 2023

Chronic neuropathic pain (CNP), a complex and debilitating condition arising from damage or dysfunction of the somatosensory nervous system, affects millions of people worldwide [...]
Histologic Evidence of Oral and Periodontal Regeneration Using Recombinant Human Platelet-Derived Growth Factor
Authors: Meghil Mohamed M. , Mandil Obada , Nevins Myron , Saleh Muhammad H. A. , Wang Hom-Lay
Published: March 2023

Human histology provides critical information on the biological potential of various regenerative protocols and biomaterials, which is vital to advancing the field of periodontal regeneration, both in research and clinical practice. Outcomes of histologic studies are particularly valuable when interpreted considering additional evidence available from pre-clinical and clinical studies. One of the best-documented growth factors areproven to have positive effects on a myriad of oral regenerative procedures is recombinant human platelet-derived growth factor—BB (rhPDGF-BB). While a systematic review of clinical studies evaluating rhPDGF in oral regenerative procedures has been recently completed, a review article that focuses on the histologic outcomes is needed. Hence, this communication discusses the histologic effects of rhPDGF-BB on oral and periodontal regenerative procedures, including root coverage and soft tissue augmentation, intrabony defects, furcation defects, peri-implant bone augmentation, and guided bone regeneration. Studies from 1989 to 2022 have been included in this review.
Advanced Oxidation Processes Coupled to Nanofiltration Membranes with Catalytic Fe0 Nanoparticles in Symmetric and Asymmetric Polyelectrolyte Multilayers
Authors: Wang Tao , Bachs Enrique Serra , de Grooth Joris , de Vos Wiebe M.
Published: March 2023

The in situ synthesis of Fe0 particles using poly-(acrylic acid) (PAA) is an effective tool for fabricating catalytic membranes relevant to advanced oxidation processes (AOPs). Through their synthesis in polyelectrolyte multilayer-based nanofiltration membranes, it becomes possible to reject and degrade organic micropollutants simultaneously. In this work, we compare two approaches, where Fe0 nanoparticles are synthesized in or on symmetric multilayers and asymmetric multilayers. For the membrane with symmetric multilayers (4.0 bilayers of poly (diallyldimethylammonium chloride) (PDADMAC)/PAA), the in situ synthesized Fe0 increased its permeability from 1.77 L/m2/h/bar to 17.67 L/m2/h/bar when three Fe2+ binding/reducing cycles were conducted. Likely, the low chemical stability of this polyelectrolyte multilayer allows it to become damaged through the relatively harsh synthesis. However, when the in situ synthesis of Fe0 was performed on top of asymmetric multilayers, which consist of 7.0 bilayers of the very chemically stable combination of PDADMAC and poly(styrene sulfonate) (PSS), coated with PDADMAC/PAA multilayers, the negative effect of the Fe0 in situ synthesized can be mitigated, and the permeability only increased from 1.96 L/m2/h/bar to 2.38 L/m2/h/bar with three Fe2+ binding/reducing cycles. The obtained membranes with asymmetric polyelectrolyte multilayers exhibited an excellent naproxen treatment efficiency, with over 80% naproxen rejection on the permeate side and 25% naproxen removal on the feed solution side after 1 h. This work demonstrates the potential of especially asymmetric polyelectrolyte multilayers to be effectively combined with AOPs for the treatment of micropollutants (MPs).
Study on the Bath Smelting Reduction Reaction and Mechanism of Iron Ore: A Review
Authors: Wang Guilin , Zhang Jianliang , Wang Yaozu , Tan Yubo , Li Zhen , Zhang Bo , Liu Zhengjian
Published: March 2023

Against the background of low global carbonization, blast furnace ironmaking technology with coking puts huge amounts of pressure on the global steel industry to save energy and reduce emissions due to its high pollution levels and high energy consumption. Bath smelting reduction technology is globally favored and studied by metallurgists as a non-blast furnace ironmaking technology that directly reduces iron ore into liquid metal without using coke as the raw material. The smelting reduction reaction of iron ore, which is the core reaction of the process, is greatly significant to its productivity and energy saving. Therefore, this paper focuses on the behavior and mechanism of iron ore’s smelting reduction. This work focuses on three key aspects of smelting reduction, namely, the thermal decomposition characteristics of iron ore during the smelting reduction, the smelting reduction mechanism of iron-ore particles, and the smelting reduction mechanism of FeO-bearing slag. The experimental study methods, reaction mechanisms, influencing factors, and kinetic behavior of the three are highlighted. In this work, the reaction mechanism of thermal iron-ore decomposition, iron-ore particle smelting reduction, and FeO-bearing slag smelting reduction on the three reactions were observed, providing a theoretical basis for how to select and optimize raw materials for the bath smelting reduction process. Moreover, the kinetic study clarifies the limiting steps of the reactions and provides guidance for an improvement in the reaction rate. However, certain blank points in previous studies need to be further explored, such as the differences in the research results of same factor, the large variation in reaction activation energy, and the coupling mechanism and inter-relatedness of the three key aspects’ reactions with each other.
Study of the Metabolite Changes in Ganoderma lucidum under Pineapple Leaf Residue Stress via LC-MS/MS Coupled with a Non-Targeted Metabolomics Approach
Authors: Liu Yijun , Qian Yangyang , Wang Chunyu , He Yingying , Zhu Chuxing , Chen Gang , Lin Lijing , Chen Yuliang
Published: March 2023

The effects of fermentation metabolites of G. lucidum under different pineapple leaf residue additions were separated and identified using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). The mass spectra showed that the metabolites had good response values only in the positive ion mode, and 3019 metabolites with significant differences, mainly distributed in 95 metabolic pathways, were identified. The multivariate analyses, including the principal component analysis (PCA), orthogonal least squares discriminant analysis (OPLS-DA), and volcano plots (VP), revealed that the G. lucidum metabolites exhibited significant differences (p < 0.05) and were well clustered under various pineapple leaf residue additions, featuring 494–545 upregulated and 998–1043 downregulated metabolites. The differential metabolic pathway analysis proved that two metabolic pathways related to the biosynthesis of amino acids and ABC transporters were particularly significant under the addition of pineapple leaf residue, where amino acids such as histidine and lysine were upregulated in contrast to downregulated tyrosine, valine, L-alanine, and L-asparagine. These study results are considered instrumental in substantiating the application of pineapple leaf residue in the cultivation of G. lucidum and improving its utilization rate and added value.
Techno-Economic Assessment of On-Site Production of Biomethane, Bioenergy, and Fertilizer from Small-Scale Anaerobic Digestion of Jabuticaba By-Product
Authors: Sganzerla William Gustavo , da Rosa Rafael Gabriel , Barroso Tiago Linhares Cruz Tabosa , Castro Luiz Eduardo Nochi , Forster-Carneiro Tânia
Published: March 2023

Bioenergy recovery from biomass by-products is a promising approach for the circular bioeconomy transition. However, the management of agri-food by-products in stand-alone treatment facilities is a challenge for the low-capacity food processing industry. In this study, the techno-economic assessment of a small-scale anaerobic digestion process was evaluated for the management of jabuticaba by-product and the production of biomethane, electricity, heat, and fertilizer. The process was simulated for a treatment capacity of 782.2 m3 y−1 jabuticaba peel, considering the experimental methane production of 42.31 L CH4 kg−1 TVS. The results of the scaled-up simulated process demonstrated the production of biomethane (13,960.17 m3 y−1), electricity (61.76 MWh y−1), heat (197.62 GJ y−1), and fertilizer (211.47 t y−1). Economic analysis revealed that the process for biomethane recovery from biogas is not profitable, with a net margin of −19.58% and an internal rate of return of −1.77%. However, biogas application in a heat and power unit can improve project feasibility, with a net margin of 33.03%, an internal rate of return of 13.14%, and a payback of 5.03 years. In conclusion, the application of small-scale anaerobic digestion can prevent the wrongful open-air disposal of jabuticaba by-products, with the generation of renewable energy and biofertilizer supporting the green economy toward the transition to a circular economy.
Enhancement of Molecular Transport into Film Stacked Structures for Micro-Immunoassay by Unsteady Rotation
Authors: Maeno Hinata , Ogata Satoshi , Shimizu Tetsuhide , Yang Ming
Published: March 2023

A film-stacked structure consisting of polyethylene terephthalate (PET) films stacked in a gap of 20 µm that can be combined with 96-well microplates used in biochemical analysis has been developed by the authors. When this structure is inserted into a well and rotated, convection flow is generated in the narrow gaps between the films to enhance the chemical/bio reaction between the molecules. However, since the main component of the flow is a swirling flow, only a part of the solution circulates into the gaps, and reaction efficiency is not achieved as designed. In this study, an unsteady rotation is applied to promote the analyte transport into the gaps using the secondary flow generated on the surface of the rotating disk. Finite element analysis is used to evaluate the changes in flow and concentration distribution for each rotation operation and to optimize the rotation conditions. In addition, the molecular binding ratio for each rotation condition is evaluated. It is shown that the unsteady rotation accelerates the binding reaction of proteins in an ELISA (Enzyme Linked Immunosorbent Assay), a type of immunoassay.
Reduced Graphene Oxide as a Platform for the Immobilization of Amino-Cyclodextrins
Authors: Villalobos Elias , Marco José F. , Yáñez Claudia
Published: March 2023

In the present work, we reported on a method to combine amino β-cyclodextrins (CD1) with reduced graphene oxide (obtained by the electrochemical reduction of graphene oxide, erGO) to produce a glassy carbon electrode (GCE) modified with both CD1 and erGO (CD1-erGO/GCE). This procedure avoids the use of organic solvents such as hydrazine or long reaction times and high temperatures. The material combining both CD1 and erGO (CD1-erGO/GCE) was characterized by SEM, ATR-FTIR, Raman, XPS, and electrochemical techniques. As proof-of-concept, the determination of the pesticide carbendazim was carried out. The spectroscopic measurements, especially XPS, proved that CD1 was covalently attached to the surface of the erGO/GCE electrode. The attachment of cyclodextrin at the reduced graphene oxide produced an increase in the electrochemical behavior of the electrode. The cyclodextrin-functionalized reduced graphene oxide, CD1-erGO/GCE, showed a larger sensitivity (1.01 μA/μM) and a lower limit of detection for carbendazim (LOD = 0.50 μM) compared with the non-functionalized material, erGO/GCE, (sensitivity = 0.63 μA/μM and LOD = 4.32 μM, respectively). Overall, the results of the present work show that this simple method is suitable to attach cyclodextrins to graphene oxide, maintaining their inclusion abilities.
Integrated Intelligent Method Based on Fuzzy Logic for Optimizing Laser Microfabrication Processing of GnPs-Improved Alumina Nanocomposites
Authors: Alqahtani Khaled N. , Nasr Mustafa M. , Anwar Saqib , Al-Samhan Ali M. , Alhaag Mohammed H. , Kaid Husam
Published: March 2023

Studies on using multifunctional graphene nanostructures to enhance the microfabrication processing of monolithic alumina are still rare and too limited to meet the requirements of green manufacturing criteria. Therefore, this study aims to increase the ablation depth and material removal rate and minimize the roughness of the fabricated microchannel of alumina-based nanocomposites. To achieve this, high-density alumina nanocomposites with different graphene nanoplatelet (GnP) contents (0.5 wt.%, 1 wt.%, 1.5 wt.%, and 2.5 wt.%) were fabricated. Afterward, statistical analysis based on the full factorial design was performed to study the influence of the graphene reinforcement ratio, scanning speed, and frequency on material removal rate (MRR), surface roughness, and ablation depth during low-power laser micromachining. After that, an integrated intelligent multi-objective optimization approach based on the adaptive neuro-fuzzy inference system (ANIFS) and multi-objective particle swarm optimization approach was developed to monitor and find the optimal GnP ratio and microlaser parameters. The results reveal that the GnP reinforcement ratio significantly affects the laser micromachining performance of Al2O3 nanocomposites. This study also revealed that the developed ANFIS models could obtain an accurate estimation model for monitoring the surface roughness, MRR, and ablation depth with fewer errors than 52.07%, 100.15%, and 76% for surface roughness, MRR, and ablation depth, respectively, in comparison with the mathematical models. The integrated intelligent optimization approach indicated that a GnP reinforcement ratio of 2.16, scanning speed of 342 mm/s, and frequency of 20 kHz led to the fabrication of microchannels with high quality and accuracy of Al2O3 nanocomposites. In contrast, the unreinforced alumina could not be machined using the same optimized parameters with low-power laser technology. Henceforth, an integrated intelligence method is a powerful tool for monitoring and optimizing the micromachining processes of ceramic nanocomposites, as demonstrated by the obtained results.
Fabrication of Large-Area Micro-Hexagonal Cube Corner Retroreflectors on Three-Linear-Axis Ultraprecision Lathes
Authors: Xia Senbin , Yin Ziqiang , Huang Cheng , Meng Songtao
Published: March 2023

Hexagonal cube corner retroreflectors (HCCRs) are the micro-optics arrays with the highest reflectivity. However, these are composed of prismatic micro-cavities with sharp edges, and conventional diamond cutting is considered unmachinable. Besides, 3-linear-axis ultraprecision lathes were considered unfeasible to fabricate HCCRs due to the lack of a rotation axis. Therefore, a new machining method is proposed as a viable option to manufacture HCCRs on the 3-linear-axis ultraprecision lathes in this paper. For the mass production of HCCRs, the dedicated diamond tool is designed and optimized. The toolpaths are proposed and optimized to further increase tool life and machining efficiency. The Diamond Shifting Cutting (DSC) method is analyzed in-depth both theoretically and experimentally. By using the optimized methods, the large-area HCCRs with a structure size of 300 µm covering an area of 10 × 12 mm2 are successfully machined on 3-linear-axis ultraprecision lathes. The experimental results show that the whole array is highly uniform, and the surface roughness Sa of three cube corner facets is all less than 10 nm. More importantly, the machining time is reduced to 19 h, which is far less than the previous processing methods (95 h). This work will significantly reduce the production threshold and costs, which is important to promote the industrial application of HCCRs.
A Predictive Model of Capillary Forces and Contact Diameters between Two Plates Based on Artificial Neural Network
Authors: Huang Congcong , Fan Zenghua , Fan Ming , Xu Zhi , Gao Jun
Published: March 2023

Many efforts have been devoted to the forecasting of the capillary force generated by capillary adsorption between solids, which is fundamental and essential in the fields of micro-object manipulation and particle wetting. In this paper, an artificial neural network (ANN) model optimized by a genetic algorithm (GA-ANN) was proposed to predict the capillary force and contact diameter of the liquid bridge between two plates. The mean square error (MSE) and correlation coefficient (R2) were employed to evaluate the prediction accuracy of the GA-ANN model, theoretical solution method of the Young–Laplace equation and simulation approach based on the minimum energy method. The results showed that the values of MSE of capillary force and contact diameter using GA-ANN were 10.3 and 0.0001, respectively. The values of R2 were 0.9989 and 0.9977 for capillary force and contact diameter in regression analysis, respectively, demonstrating the accuracy of the proposed predictive model. The sensitivity analysis was conducted to investigate the influence of input parameters, including liquid volume and separation distance, on the capillary force and contact diameter. The liquid volume and separation distance played dominant roles in affecting the capillary force and contact diameter.
Predatory Strategies of Myxococcus xanthus: Prey Susceptibility to OMVs and Moonlighting Enzymes
Authors: Zwarycz Allison S. , Page Thomas , Nikolova Gabriela , Radford Emily J. , Whitworth David E.
Published: March 2023

Predatory outer membrane vesicles (OMVs) secreted by myxobacteria fuse readily with the outer membranes of Gram-negative bacteria, introducing toxic cargo into their prey. Here we used a strain of the myxobacterium Myxococcus xanthus that produces fluorescent OMVs to assay the uptake of OMVs by a panel of Gram-negative bacteria. M. xanthus strains took up significantly less OMV material than the tested prey strains, suggesting that re-fusion of OMVs with producing organisms is somehow inhibited. The OMV killing activity against different prey correlated strongly with the predatory activity of myxobacterial cells, however, there was no correlation between OMV killing activity and their propensity to fuse with different prey. It has previously been proposed that M. xanthus GAPDH stimulates the predatory activity of OMVs by enhancing OMV fusion with prey cells. Therefore, we expressed and purified active fusion proteins of M. xanthus glyceraldehyde-3-phosphate dehydrogenase and phosphoglycerate kinase (GAPDH and PGK; moonlighting enzymes with additional activities beyond their roles in glycolysis/gluconeogenesis) to investigate any involvement in OMV-mediated predation. Neither GAPDH nor PGK caused lysis of prey cells or enhanced OMV-mediated lysis of prey cells. However, both enzymes were found to inhibit the growth of Escherichia coli, even in the absence of OMVs. Our results suggest that fusion efficiency is not a determinant of prey killing, but instead resistance to the cargo of OMVs and co-secreted enzymes dictates whether organisms can be preyed upon by myxobacteria.
Effects of Inbreeding on Microbial Community Diversity of Zea mays
Authors: Schultz Corey R. , Johnson Matthew , Wallace Jason G.
Published: March 2023

Heterosis, also known as hybrid vigor, is the basis of modern maize production. The effect of heterosis on maize phenotypes has been studied for decades, but its effect on the maize-associated microbiome is much less characterized. To determine the effect of heterosis on the maize microbiome, we sequenced and compared the bacterial communities of inbred, open pollinated, and hybrid maize. Samples covered three tissue types (stalk, root, and rhizosphere) in two field experiments and one greenhouse experiment. Bacterial diversity was more affected by location and tissue type than genetic background for both within-sample (alpha) and between-sample (beta) diversity. PERMANOVA analysis similarly showed that tissue type and location had significant effects on the overall community structure, whereas the intraspecies genetic background and individual plant genotypes did not. Differential abundance analysis identified only 25 bacterial ASVs that significantly differed between inbred and hybrid maize. Predicted metagenome content was inferred with Picrust2, and it also showed a significantly larger effect of tissue and location than genetic background. Overall, these results indicate that the bacterial communities of inbred and hybrid maize are often more similar than they are different and that non-genetic effects are generally the largest influences on the maize microbiome.
Computational Approaches for Identification of Potential Plant Bioactives as Novel G6PD Inhibitors Using Advanced Tools and Databases
Authors: Aldossari Rana M. , Ali Aarif , Rehman Muneeb U. , Rashid Summya , Ahmad Sheikh Bilal
Published: March 2023

In glucose metabolism, the pentose phosphate pathway (PPP) is the major metabolic pathway that plays a crucial role in cancer growth and metastasis. Although it has been pointed out that blockade of the PPP is a promising approach against cancer, in the clinical setting, effective anti-PPP agents are still not available. Dysfunction of the G6PD enzyme in this pathway leads to cancer development as this enzyme possesses oncogenic activity. In the present study, an attempt was made to identify bioactive compounds that can be developed as potential G6PD inhibitors. In the present study, 11 natural compounds and a controlled drug were taken. The physicochemical and toxicity properties of the compounds were determined via ADMET and ProTox-II analysis. In the present study, the findings of docking studies revealed that staurosporine was the most effective compound with the highest binding energy of −9.2 kcal/mol when docked against G6PD. Homology modeling revealed that 97.56% of the residues were occupied in the Ramachandran-favored region. The modeled protein gave a quality Z-score of −10.13 by ProSA tool. iMODS server provided significant insights into the mobility, stability and flexibility of the G6PD protein that described the collective functional protein motion. In the present study, the physical and functional interactions between proteins were determined by STRING. CASTp server determined the topological and geometric properties of the G6PD protein. The findings of the present study revealed that staurosporine could be developed as a potential G6PD inhibitor; however, further in vivo and in vitro studies are needed for further validation of these results.