bluuebunny/crossref_metadata_2025 huggingface dataset:
Valorization of Rice Husk and Straw Agriculture Wastes of Eastern Saudi Arabia: Production of Bio-Based Silica, Lignocellulose, and Activated Carbon
Authors: Abd-Rabboh Hisham S. M. , Fawy Khaled F. , Hamdy Mohamed S. , Elbehairi SeragEldin I. , Shati Ali A. , Alfaifi Mohammad Y. , Ibrahium Hala A. , Alamri Saad , Awwad Nasser S.
Published: May 2022

Bio-based silica, lignocellulose, and activated carbon were simply produced via the recycling of Hassawi rice biomass waste of Al-Ahsa governorate in the eastern Saudi Arabia region using a fast chemical treatment procedure. Rice husk and rice straw wastes were collected, ground, and chemically treated with sodium hydroxide to extract silica/silicate from the dried plant tissues. The liquid extract is then treated with acid solutions in order to precipitate silica/silicate at neutral medium. Lowering the pH of the supernatant to 2 resulted in the precipitation of lignocellulose. Thermal treatment of the biomass residue under N2 gas stream resulted in activated carbon production. Separated products were dried/treated and characterized using several physical examination techniques, such as FT-IR, SEM/EDX, XRD, and Raman spectroscopy in order to study their structure and morphology. Silica and lignocelluloses products were then preliminarily used in the treatment of wastewaters and water-desalination processes.
3D Printed Customized Facemask for Maxillary Protraction in the Early Treatment of a Class III Malocclusion: Proof-of-Concept Clinical Case
Authors: Franchi Lorenzo , Vichi Alessandro , Marti Patrizia , Lampus Flavio , Guercio Simone , Recupero Annamaria , Giuntini Veronica , Goracci Cecilia
Published: May 2022

In order to improve fit and comfort, a maxillary protraction facemask customized to the patient’s anatomy was produced by means of 3D face scanning, digital design and additive manufacturing. An 8-year-old patient in need of early treatment for the Class III malocclusion received a rapid palatal expander and a Petit-type facemask, whose components were digitally designed on a 3D scan of the patient’s face. For face scanning, the iPad Pro 2018 tablet (Apple, Cupertino, CA, USA) with the Bellus3D DentalPro application (Bellus3D, Campbell, CA, USA) was used. Facemask components were modelled with 3D Blender software. The rests were 3D printed in BioMed Clear biocompatible resin (Formlabs, Somerville, MA, USA), and the bar in stainless steel. For greater comfort, the internal surface of the rests was lined with a polymer gel pad (Silipos, Niagara Falls, NY, USA). The manufacturing procedure of the customized facemask is patented. The patient wore the facemask at night for a period of 9 months. The patient’s experience was evaluated with a questionnaire at 1 week, 3, 6, and 10 months of treatment. The customized facemask was well accepted by the patient and obtained the expected treatment outcome. Furthermore, 3D face scanning, 3D modelling and 3D printing allow for the manufacturing of customized facemasks with improved fit and comfort, favoring patient compliance and treatment success.
Surface Kinetic Mechanisms of Epitaxial Chemical Vapour Deposition of 4H Silicon Carbide Growth by Methyltrichlorosilane-H2 Gaseous System
Authors: Song Botao , Gao Bing , Han Pengfei , Yu Yue
Published: May 2022

The chemical vapour deposition (CVD) technique could be used to fabricate a silicon carbide (SiC) epitaxial layer. Methyltrichlorosilane (CH3SiCl3, MTS) is widely used as a precursor for CVD of SiC with a wide range of allowable deposition temperatures. Typically, an appropriate model for the CVD process involves kinetic mechanisms of both gas-phase reactions and surface reactions. Here, we proposed the surface kinetic mechanisms of epitaxial SiC growth for MTS-H2 gaseous system where the MTS employed as the single precursor diluted in H2. The deposition face is assumed to be the Si face with a surface site terminated by an open site or H atom. The kinetic mechanisms for surface reactions proposed in this work for MTS-H2 gaseous system of epitaxial growth of SiC by CVD technique from mechanisms proposed for H-Si-C-Cl system are discussed in detail. Predicted components of surface species and growth rates at different mechanisms are discussed in detail.
Genipin-Crosslinked Gelatin/Chitosan-Based Functional Films Incorporated with Rosemary Essential Oil and Quercetin
Authors: Roy Swarup , Rhim Jong-Whan
Published: May 2022

Functional food packaging films were prepared using a binary mixture of chitosan and gelatin through crosslinking with genipin and hybridization with rosemary essential oil and quercetin. The mixture of chitosan and gelatin produced the compatible film, and the added fillers also showed good compatibility. The physical properties of the chitosan/gelatin film were not greatly affected by crosslinking with genipin, and the functionality of the composite film was increased by the addition of rosemary essential oil and quercetin. The bioactive additives did not significantly affect the hydrophobicity and water vapor barrier properties of the chitosan/gelatin film but significantly changed the color, while the mechanical and thermal properties were slightly affected. The addition of these functional fillers significantly improved the UV protection, antioxidant, and antibacterial properties of the chitosan/gelatin film. Therefore, the novel chitosan/gelatin film with genipin crosslinking and the integration of rosemary essential oil and quercetin is considered to have high potential for applications in active food packaging.
Liquid Silicone Rubber Foamed with Thermoplastic Expandable Microspheres
Authors: Marl Svenja , Giesen Ralf-Urs , Heim Hans-Peter
Published: May 2022

To reduce the material costs as well as the density of Liquid Silicone Rubber (LSR), LSR foams can be produced in an injection molding process. Expandable thermoplastic microspheres can be used as blowing agents. This publication deals with the analysis of the cell structure of these LSR foams. For this purpose, cylindrical disks are injection molded and examined for their cell structure as a function of different proportions of microspheres using a scanning electron spectroscope. In addition, the density of the samples is determined. It was found that a very homogeneous cell structure is produced in this process, that heat transport has a significant influence on the expansion of the microspheres, and that the formation of a filler network limits the expansion at higher proportions of blowing agent.
Open-Source 3D Printing in the Prosthetic Field—The Case of Upper Limb Prostheses: A Review
Authors: Wendo Kevin , Barbier Olivier , Bollen Xavier , Schubert Thomas , Lejeune Thierry , Raucent Benoit , Olszewski Raphael
Published: May 2022

Upper limb loss alters individuals’ private and professional life. Prosthetic devices are thus a solution to supply the missing upper limb segments. Nevertheless, commercial prostheses are often unaffordable, or inaccessible, to underprivileged individuals (e.g., no health insurance, low incomes, warzone). Among potential affordable alternatives, additive manufacturing, commonly “3D printing”, has been increasingly employed. This technology offers higher availability and accessibility, and can produce complex geometrical and highly customized products, which are essential features for prostheses manufacturing. Therefore, this study aims to portray an overview of reliable open-source upper limb 3D-printed prostheses currently available. We thus searched the scientific literature and online repositories hosting 3D-printable designs. We extracted data relative to mechanical and kinematic properties, 3D printing process and efficacy for each device. We found six studies implementing open-source 3DP upper limb prostheses and twenty-five open-source designs from online databases meeting selection criteria. Devices’ technical specifications were not systematically reported. In conclusion, though open-source 3D-printed upper limb prostheses can perform some functional tasks and grasps, and are widely employed to supply limb differences, further research is mandatory to validate their usage and to prove their clinical efficacy. More guidelines are required to unify contributions from private makers and non-governmental organizations with scientific groups.
Adaptively Promoting Diversity in a Novel Ensemble Method for Imbalanced Credit-Risk Evaluation
Authors: Guo Yitong , Mei Jie , Pan Zhiting , Liu Haonan , Li Weiwei
Published: May 2022

Ensemble learning techniques are widely applied to classification tasks such as credit-risk evaluation. As for most credit-risk evaluation scenarios in the real world, only imbalanced data are available for model construction, and the performance of ensemble models still needs to be improved. An ideal ensemble algorithm is supposed to improve diversity in an effective manner. Therefore, we provide an insight in considering an ensemble diversity-promotion method for imbalanced learning tasks. A novel ensemble structure is proposed, which combines self-adaptive optimization techniques and a diversity-promotion method (SA-DP Forest). Additional artificially constructed samples, generated by a fuzzy sampling method at each iteration, directly create diverse hypotheses and address the imbalanced classification problem while training the proposed model. Meanwhile, the self-adaptive optimization mechanism within the ensemble simultaneously balances the individual accuracy as the diversity increases. The results using the decision tree as a base classifier indicate that SA-DP Forest outperforms the comparative algorithms, as reflected by most evaluation metrics on three credit data sets and seven other imbalanced data sets. Our method is also more suitable for experimental data that are properly constructed with a series of artificial imbalance ratios on the original credit data set.
Prediction of Whole Social Electricity Consumption in Jiangsu Province Based on Metabolic FGM (1, 1) Model
Authors: Zhang Siyu , Wu Liusan , Cheng Ming , Zhang Dongqing
Published: May 2022

The achievement of the carbon peaking and carbon neutrality targets requires the adjustment of the energy structure, in which the dual-carbon progress of the power industry will directly affect the realization process of the goal. In such terms, an accurate demand forecast is imperative for the government and enterprises’ decision makers to develop an optimal strategy for electric energy planning work in advance. According to the data of the whole social electricity consumption in Jiangsu Province of China from 2015 to 2019, this paper uses the improved particle swarm optimization algorithm to calculate the fractional-order r of the FGM (1, 1) model and establishes a metabolic FGM (1, 1) model to predict the whole social electricity consumption in Jiangsu Province of China from 2020 to 2023. The results show that in the next few years the whole social electricity consumption in Jiangsu Province will show a growth trend, but the growth rate will slow down generally. It can be seen that the prediction accuracy of the metabolic FGM (1, 1) model is higher than that of the GM (1, 1) and FGM (1, 1) models. In addition, the paper analyzes the reasons for the changes in the whole society electricity consumption in Jiangsu Province of China and provides support for government decision making.
On Predictive Modeling Using a New Flexible Weibull Distribution and Machine Learning Approach: Analyzing the COVID-19 Data
Authors: Ahmad Zubair , Almaspoor Zahra , Khan Faridoon , El-Morshedy Mahmoud
Published: May 2022

Predicting and modeling time-to-events data is a crucial and interesting research area. For modeling and predicting such types of data, numerous statistical models have been suggested and implemented. This study introduces a new statistical model, namely, a new modified flexible Weibull extension (NMFWE) distribution for modeling the mortality rate of COVID-19 patients. The introduced model is obtained by modifying the flexible Weibull extension model. The maximum likelihood estimators of the NMFWE model are obtained. The evaluation of the estimators of the NMFWE model is assessed in a simulation study. The flexibility and applicability of the NMFWE model are established by taking two datasets representing the mortality rates of COVID-19-infected persons in Mexico and Canada. For predictive modeling, we consider two pure statistical models and two machine learning (ML) algorithms. The pure statistical models include the autoregressive moving average (ARMA) and non-parametric autoregressive moving average (NP-ARMA), and the ML algorithms include neural network autoregression (NNAR) and support vector regression (SVR). To evaluate their forecasting performance, three standard measures of accuracy, namely, root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) are calculated. The findings demonstrate that ML algorithms are very effective at predicting the mortality rate data.
Multi-View Cosine Similarity Learning with Application to Face Verification
Authors: Wang Zining , Chen Jiawei , Hu Junlin
Published: May 2022

An instance can be easily depicted from different views in pattern recognition, and it is desirable to exploit the information of these views to complement each other. However, most of the metric learning or similarity learning methods are developed for single-view feature representation over the past two decades, which is not suitable for dealing with multi-view data directly. In this paper, we propose a multi-view cosine similarity learning (MVCSL) approach to efficiently utilize multi-view data and apply it for face verification. The proposed MVCSL method is able to leverage both the common information of multi-view data and the private information of each view, which jointly learns a cosine similarity for each view in the transformed subspace and integrates the cosine similarities of all the views in a unified framework. Specifically, MVCSL employs the constraints that the joint cosine similarity of positive pairs is greater than that of negative pairs. Experiments on fine-grained face verification and kinship verification tasks demonstrate the superiority of our MVCSL approach.
Queueing-Inventory System for Two Commodities with Optional Demands of Customers and MAP Arrivals
Authors: Anbazhagan N. , Joshi Gyanendra Prasad , Suganya R. , Amutha S. , Vinitha V. , Shrestha Bhanu
Published: May 2022

This research analyses the performance of a perishable queueing-inventory system for two commodities with optional customers demands. We assume in the article that all customers who come to the system can only purchase the first item or the second item or service (they do not purchase both items). This is the original aspect of the paper. We show the significance of the impact of optional demands on the system’s performance, which is the purpose of the paper. In this system, customers arrive, using the Markovian arrival process (MAP), to a demand for a single unit. The system is composed of a waiting hall with a limited capacity of F. The arriving customer observes the waiting hall is filled to capacity or the stock stage is zero, and they decide to leave the system. In the steady-state case, the joint probability distribution for the first commodity, the second commodity, and the number of customers in the system are computed using matrix geometric methods. We evaluate diverse system performance measures. Finally, we provide a numerical illustration of the optimal value for diverse parameters of the system, which highlights the results and implications of the article.
Multi-Objective Model and Variable Neighborhood Search Algorithms for the Joint Maintenance Scheduling and Workforce Routing Problem
Authors: Dahite Lamiaa , Kadrani Abdeslam , Benmansour Rachid , Guibadj Rym Nesrine , Fonlupt Cyril
Published: May 2022

This paper addresses a problem faced by maintenance service providers: performing maintenance activities at the right time on geographically distributed machines subjected to random failures. This problem requires determining for each technician the sequence of maintenance operations to perform to minimize the total expected costs while ensuring a high level of machine availability. To date, research in this area has dealt with routing and maintenance schedules separately. This study aims to determine the optimal maintenance and routing plan simultaneously. A new bi-objective mathematical model that integrates both routing and maintenance considerations is proposed for time-based preventive maintenance. The first objective is to minimize the travel cost related to technicians’ routing. The second objective can either minimize the total preventive and corrective maintenance cost or the failure cost. New general variable neighborhood search (GVNS) and variable neighborhood descent (VND) algorithms based on the Pareto dominance concept are proposed and performed over newly generated instances. The efficiency of our approach is demonstrated through several experiments. Compared to the commercial solver and existing multi-objective VND and GVNS, these new algorithms obtain highly competitive results on both mono-objective and bi-objective variants.
Metacognitive Strategies Related with Logical–Mathematical Thinking for Adolescents with ADHD
Authors: Tsampouris Georgios , Sampedro Requena Begoña Esther
Published: May 2022

This article focuses on the contributions of the still-scarce corroborations available on the social nature of the metacognitive regulation of joint attempts in order to offer systematic means to operationalize and analyze shared regulation. The mathematical knowledge aims to achieve the metacognitive needs of students and, in particular, those with learning difficulties. The present research process aims to explain the relationship between the logical and mathematical thinking of students with ADHD in secondary education schools in Heraklion (Crete) and metacognitive awareness and academic motivation, including questions about pupils’ logical–mathematical skills and logical decisions of life and problem solving. Appropriate psychometric tools are used to evaluate their performance as well as their short and medium-term and consequently their long-term goals. The results of the current study imply that, when students realize that teachers and their parents emphasize the essential process of learning, appropriate strategies can be shown to them to allow them to learn how to solve problems on their own. As a result, it is of great significance to point out the relationship between students’ academic achievement and academic motivation.
Remote Geotechnical Monitoring of a Buried Oil Pipeline
Authors: Vladova Alla Yu.
Published: May 2022

Extensive but remote oil and gas fields in Canada and Russia require extremely long pipelines. Global warming and local anthropogenic effects drive the deepening of seasonal thawing of cryolithozone soils and enhance pathological processes such as frost heave, thermokarst, and thermal erosion. These processes lead to a reduction in the subgrade capacity of the soils, causing changes in the spatial position of the pipelines, consequently increasing the number of accidents. Oil operators are compelled to monitor the daily temperatures of unevenly heated soils along pipeline routes. However, they are confronted with the problem of separating anthropogenic heat losses from seasonal temperature fluctuations. To highlight heat losses, we propose a short-term prediction approach to a transformed multidimensional dataset. First, we define the temperature intervals according to the classification of permafrost to generate additional features that sharpen seasonal and permafrost conditions, as well as the timing of temperature measurement. Furthermore, linear and nonlinear uncorrelated features are extracted and scaled. The second step consists of selecting a training sample, learning, and adjusting the additive regression model. Forecasts are then made from the test sample to assess the accuracy of the model. The forecasting procedure is provided by the three-component model named Prophet. Prophet fits linear and nonlinear functions to define the trend component and Fourier series to define the seasonal component; the third component, responsible for the abnormal days (when the heating regime is changed for some reason), could be defined by an analyst. Preliminary statistical analysis shows that the subsurface frozen soils containing the oil pipeline are mostly unstable, especially in the autumn season. Based upon the values of the error metrics, it is determined that the most accurate forecast is obtained on a three-month uniform time grid.
New Result for the Analysis of Katugampola Fractional-Order Systems—Application to Identification Problems
Authors: Kahouli Omar , Jmal Assaad , Naifar Omar , Nagy Abdelhameed M. , Ben Makhlouf Abdellatif
Published: May 2022

In the last few years, a new class of fractional-order (FO) systems, known as Katugampola FO systems, has been introduced. This class is noteworthy to investigate, as it presents a generalization of the well-known Caputo fractional-order systems. In this paper, a novel lemma for the analysis of a function with a bounded Katugampola fractional integral is presented and proven. The Caputo–Katugampola fractional derivative concept, which involves two parameters 0 < α < 1 and ρ > 0, was used. Then, using the demonstrated barbalat-like lemma, two identification problems, namely, the “Fractional Error Model 1” and the “Fractional Error Model 1 with parameter constraints”, were studied and solved. Numerical simulations were carried out to validate our theoretical results.
On Resolvability- and Domination-Related Parameters of Complete Multipartite Graphs
Authors: Hayat Sakander , Khan Asad , Zhong Yubin
Published: May 2022

Graphs of order n with fault-tolerant metric dimension n have recently been characterized.This paper points out an error in the proof of this characterization. We show that the complete multipartite graphs also have the fault-tolerant metric dimension n, which provides an infinite family of counterexamples to the characterization. Furthermore, we find exact values of the metric, edge metric, mixed-metric dimensions, the domination number, locating-dominating number, and metric-locating-dominating number for the complete multipartite graphs. These results generalize various results in the literature from complete bipartite to complete multipartite graphs.
Contagion Effect of Financial Markets in Crisis: An Analysis Based on the DCC–MGARCH Model
Authors: Ji Xiuping , Wang Sujuan , Xiao Honggen , Bu Naipeng , Lin Xiaonan
Published: May 2022

Global crises have created unprecedented challenges for communities and economies across the world, triggering turmoil in global finance and economy. This study adopts the dynamic conditional correlation multiple generalized autoregressive conditional heteroskedasticity (DCC–MGARCH) model to explore contagion effects across financial markets in crisis. The main findings are as follows: (1) the financial crisis and COVID-19 pandemic intensified the connection between the Chinese and US stock markets in the short term; (2) the dynamic conditional correlations (DCCs) during the COVID-19 pandemic are higher than those during the 2008 financial crisis owing to the further opening of the Chinese capital market, and financial institutions’ investments in the European market are higher than those in the American markets; (3) a stepwise increase is observed in the dynamic conditional correlation between the returns on the S&P 500 Index and SSEC during and after the onset of a destructive crisis; and (4) a unidirectional contagion effect exists between the Chinese market and US market, and the Hong Kong stock market contributes to the risk spillover. Effective transmission channels of external negative shocks may be investors’ sentiments, financial institutions, and the RMB exchange rate in the stock markets. This study provides useful suggestions to authorities formulating financial regulations and investors diversifying risk investments.
Deep Neural Networks for Form-Finding of Tensegrity Structures
Authors: Lee Seunghye , Lieu Qui X. , Vo Thuc P. , Lee Jaehong
Published: May 2022

Analytical paradigms have limited conventional form-finding methods of tensegrities; therefore, an innovative approach is urgently needed. This paper proposes a new form-finding method based on state-of-the-art deep learning techniques. One of the statical paradigms, a force density method, is substituted for trained deep neural networks to obtain necessary information of tensegrities. It is based on the differential evolution algorithm, where the eigenvalue decomposition process of the force density matrix and the process of the equilibrium matrix are not needed to find the feasible sets of nodal coordinates. Three well-known tensegrity examples including a 2D two-strut, a 3D-truncated tetrahedron and an icosahedron tensegrity are presented for numerical verifications. The cases of the ReLU and Leaky ReLU activation functions show better results than those of the ELU and SELU. Moreover, the results of the proposed method are in good agreement with the analytical super-stable lines. Three examples show that the proposed method exhibits more uniform final shapes of tensegrity, and much faster convergence history than those of the conventional one.
A 3D-Printed Polycaprolactone/Marine Collagen Scaffold Reinforced with Carbonated Hydroxyapatite from Fish Bones for Bone Regeneration
Authors: Kim Se-Chang , Heo Seong-Yeong , Oh Gun-Woo , Yi Myunggi , Jung Won-Kyo
Published: May 2022

In bone tissue regeneration, extracellular matrix (ECM) and bioceramics are important factors, because of their osteogenic potential and cell–matrix interactions. Surface modifications with hydrophilic material including proteins show significant potential in tissue engineering applications, because scaffolds are generally fabricated using synthetic polymers and bioceramics. In the present study, carbonated hydroxyapatite (CHA) and marine atelocollagen (MC) were extracted from the bones and skins, respectively, of Paralichthys olivaceus. The extracted CHA was characterized using Fourier transform infrared (FTIR) spectroscopy and X-ray diffraction (XRD) analysis, while MC was characterized using FTIR spectroscopy and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). The scaffolds consisting of polycaprolactone (PCL), and different compositions of CHA (2.5%, 5%, and 10%) were fabricated using a three-axis plotting system and coated with 2% MC. Then, the MC3T3-E1 cells were seeded on the scaffolds to evaluate the osteogenic differentiation in vitro, and in vivo calvarial implantation of the scaffolds was performed to study bone tissue regeneration. The results of mineralization confirmed that the MC/PCL, 2.5% CHA/MC/PCL, 5% CHA/MC/PCL, and 10% CHA/MC/PCL scaffolds increased osteogenic differentiation by 302%, 858%, 970%, and 1044%, respectively, compared with pure PCL scaffolds. Consequently, these results suggest that CHA and MC obtained from byproducts of P. olivaceus are superior alternatives for land animal-derived substances.
Marine-Derived Xanthone from 2010 to 2021: Isolation, Bioactivities and Total Synthesis
Authors: Veríssimo Ana C. S. , Pinto Diana C. G. A. , Silva Artur M. S.
Published: May 2022

Marine life has proved to be an invaluable source of new compounds with significant bioactivities, such as xanthones. This review summarizes the advances made in the study of marine-derived xanthones from 2010 to 2021, from isolation towards synthesis, highlighting their biological activities. Most of these compounds were isolated from marine-derived fungi, found in marine sediments, and associated with other aquatic organisms (sponge and jellyfish). Once isolated, xanthones have been assessed for different bioactivities, such as antibacterial, antifungal, and cytotoxic properties. In the latter case, promising results have been demonstrated. Considering the significant bioactivities showed by xanthones, efforts have been made to synthesize these compounds, like yicathins B and C and the secalonic acid D, through total synthesis.
Comparative Study on the Performance of Three Detection Methods for the Quantification of Pacific Ciguatoxins in French Polynesian Strains of Gambierdiscus polynesiensis
Authors: Darius Hélène , Revel Taina , Viallon Jérôme , Sibat Manoëlla , Cruchet Philippe , Longo Sébastien , Hardison Donnie , Holland William , Tester Patricia , Litaker R. , McCall Jennifer , Hess Philipp , Chinain Mireille
Published: May 2022

Gambierdiscus and Fukuyoa dinoflagellates produce a suite of secondary metabolites, including ciguatoxins (CTXs), which bioaccumulate and are further biotransformed in fish and marine invertebrates, causing ciguatera poisoning when consumed by humans. This study is the first to compare the performance of the fluorescent receptor binding assay (fRBA), neuroblastoma cell-based assay (CBA-N2a), and liquid chromatography tandem mass spectrometry (LC-MS/MS) for the quantitative estimation of CTX contents in 30 samples, obtained from four French Polynesian strains of Gambierdiscus polynesiensis. fRBA was applied to Gambierdiscus matrix for the first time, and several parameters of the fRBA protocol were refined. Following liquid/liquid partitioning to separate CTXs from other algal compounds, the variability of CTX contents was estimated using these three methods in three independent experiments. All three assays were significantly correlated with each other, with the highest correlation coefficient (r2 = 0.841) found between fRBA and LC-MS/MS. The CBA-N2a was more sensitive than LC-MS/MS and fRBA, with all assays showing good repeatability. The combined use of fRBA and/or CBA-N2a for screening purposes and LC-MS/MS for confirmation purposes allows for efficient CTX evaluation in Gambierdiscus. These findings, which support future collaborative studies for the inter-laboratory validation of CTX detection methods, will help improve ciguatera risk assessment and management.
Schizophrenia and Alarmins
Authors: Ma Huan , Cheng Ning , Zhang Caiyi
Published: May 2022

Schizophrenia, consisting of a group of severe psychiatric disorders with a complex etiology, is a leading cause of disability globally. Due to the lack of objective indicators, accurate diagnosis and selection of effective treatments for schizophrenia remain challenging. The association between schizophrenia and alarmins levels has been proposed for many years, but without solid evidence. Alarmins are prestored molecules that do not require processing and can be released upon cell death or damage, making them an ideal candidate for an early initiator of inflammation. Immunological biomarkers seem to be related to disease progression and treatment effectiveness. Several studies suggest strong associations among the high-mobility group box 1 protein (HMGB1), interleukin-1α, interleukin-33, S100B, heat-shock proteins, and uric acid with schizophrenic disorders. The purpose of this review is to discuss the evidence of central and peripheral immune findings in schizophrenia, their potential causes, and the effects of immunomodulatory therapies on symptoms and outline potential applications of these markers in managing the illness. Although there are currently no effective markers for diagnosing or predicting treatment effects in patients with schizophrenia, we believe that screening immune-inflammatory biomarkers that are closely related to the pathological mechanism of schizophrenia can be used for early clinical identification, diagnosis, and treatment of schizophrenia, which may lead to more effective treatment options for people with schizophrenia.
A Rare Case of Effusive-Constrictive Pericarditis Caused by Streptococcus agalactiae: Emergency Surgical Treatment
Authors: Iavazzo Annarita , Pinna Giovanni Battista , Romeo Maria Grazia , Mileo Emilio , Pilato Emanuele , Di Tommaso Luigi
Published: May 2022

A 70-year-old male patient was admitted to the emergency room in cardiac arrest. The patient was resuscitated and then referred to our cardiac surgery department, where he was diagnosed with suspected effusive constrictive pericarditis. A failed trial of TEE-guided pericardiocentesis led to the decision of surgical intervention. Sternotomy was performed and revealed pericardial thickening and very dense adhesions involving the pericardium and both pleurae, suggesting a neoplastic disease. An extensive pericardiectomy and bilateral pleural decortication were performed. After surgery, the patient improved significantly and was discharged from the intensive care unit 24 h later. Pericardial thickening, dense adhesions, the amount and color of pericardial fluid and the aspect of epicardial tissue increased our suspicion of neoplastic disease. Histological samples were sent to be analyzed immediately; a few days later, they were unexpectedly negative for any neoplastic disease but showed a group-B-hemolytic Streptococcus agalactiae infection, which causes pericarditis in extremely rare cases. Postoperatively, the patient, under intravenous antibiotic and anti-inflammatory therapy, remained asymptomatic and was discharged ten days after the surgery. At the three-month follow-up, transthoracic echocardiography showed a normal right and left ventricular function with no pericardial effusion.
Histopathological Analysis of the Effect of Photodynamic Action on Post-Chemotherapy Excised Breast Cancer Tissue
Authors: Ostańska Elżbieta , Barnaś Edyta , Bartusik-Aebisher Dorota , Dynarowicz Klaudia , Szpunar Magdalena , Skręt-Magierło Joanna , Aebisher David
Published: May 2022

Background and objectives: Breast cancer is the most commonly diagnosed cancer in women and its mortality is increasing. Therefore, research to improve treatment is of paramount importance. One method of treatment is photodynamic therapy. Photodynamic therapy selectively stimulates apoptosis in photosensitizer-treated neoplastic breast cells as a result of cytotoxic singlet oxygen generation via collisions between triplet excited state photosensitizer and triplet ground state oxygen upon tissue irradiation. The aim of this study was to evaluate the effects of photodynamic action on cancerous breast tissue samples as a model of photodynamic therapy. Materials and Methods: Breast cancer tissue samples were obtained from post-operative material and the patterns of histopathological changes in breast cancer tissue before and after photodynamic action on post-chemotherapy tissue were evaluated. Excised tissue samples were obtained from 48 female breast cancer patients who had previously undergone chemotherapy. Breast cancer tissues for this study were taken from macroscopically visible tumors larger than 10 mm. Histopathological analysis was performed to evaluate any morphological changes prior to and after photodynamic action on the post-chemotherapy tissue samples. Eighteen breast cancer tissue samples were analyzed before chemotherapy, fifteen after chemotherapy, and fifteen samples were analyzed after chemotherapy and application of photodynamic action. The photosensitizer Rose Bengal was applied to the samples subjected to photodynamic action. Results: Photodynamic action on post-chemotherapy neoplastic tissue showed histological changes under a light microscope. The results showed that morphological changes in breast cancer tissues after chemotherapy and photodynamic action were dependent on the concentration of Rose Bengal. In all cases, follow-up imaging showed tumor shrinkage of an average of 35% from baseline size. Conclusions: Histopathological examination revealed photosensitizer-concentration-dependent changes after photodynamic action in excised post-chemotherapy tissue. The effects of photodynamic action observed in this study suggest that the application of photodynamic therapy after chemotherapy can aid in breast cancer cell eradication.
Modeling and Structural Optimization of MSF-RO Desalination System
Authors: He Lu , Jiang Aipeng , Huang Qiuyun , Zhao Yan , Li Chuang , Wang Jian , Xia Yudong
Published: May 2022

Based on the mathematical modeling and operational optimization studies of reverse osmosis (RO) and multistage flash (MSF) desalination, the structural optimization of the hybrid process was specially studied in this work with the consideration of reducing comprehensive expenses under given operational conditions. Firstly, according to the process mechanism and flowchart of the RO and MSF seawater desalination technologies, seven hybrid structures with different feed conditions were designed, and their connection equations were established for numerical calculation. Then, in order to evaluate the economic performance of the hybrid systems with different structures, the hourly average operational cost equations of RO and MSF processes were established and formulated as the comprehensive evaluation indicators. Next, with a given water production requirement, simulation calculations of the hybrid system with seven different structures were performed. The results show that the hybrid system with the fourth structure has the lowest operational cost of 4.6834 CNY/m3, and at the same time it has the lowest blowdown. However, if we take GOR or production water temperature as the target, the optimal structure of the hybrid system is the fifth or the seventh option. The obtained results are helpful in structural optimization of the hybrid system with aspects of operational cost reduction, maximum GOR, or minimizing the wastewater discharge.
Correction: Boruah, D.; Zhang, X. Effect of Post-Deposition Solution Treatment and Ageing on Improving Interfacial Adhesion Strength of Cold Sprayed Ti6Al4V Coatings. Metals 2021, 11, 2038
Authors: Boruah Dibakor , Zhang Xiang
Published: May 2022

The authors wish to make the following corrections to this paper [...]
Effect of Solution Treatment and Aging Treatment on Mechanical Properties of 2060 Al-Li Alloy and Process Multi-Objective Optimization
Authors: Zhou Jing , Miao Jihang , Wang Baoyu , Wang Jiapeng
Published: May 2022

Solution and aging heat treatment are effective means to improve the mechanical properties of Al-Li alloys. The solution treatment and aging treatment tests of 2060 Al-Li alloy were carried out. The yield strength, tensile strength, elongation, Vickers hardness, and microstructure of specimens after heat treatment were obtained by the tensile test at room temperature, Vickers hardness test, SEM analysis, TEM analysis, and EDS analysis. The effects of solution and aging heat treatment parameters on mechanical properties of 2060 Al-Li alloy were analyzed by response surface model and test results. The results show that sufficient solution can make the Cu-rich second phase of the alloy continuously dissolves into the aluminum matrix, and consequently obtain the supersaturated solid solution, the insoluble second phase is mainly θ’ (Al2Cu) phase, T(Al2Cu2Mg3) phase, and S’ (Al2CuMg) phase. The strength and hardness of the alloy are improved, but the ductility worsens with the degree of solution treatment enhances. With the increase of aging temperature and aging time, the strength and hardness of the alloy increase, but the elongation decreases. Taking tensile strength, elongation, and Vickers hardness of the alloy as the optimization objectives, the NSGA-II multi-objective optimization algorithm was used to optimize the process parameters of solution and aging heat treatment, and the heat treatment experiment was carried out. The optimization results show that the best mechanical properties of the alloy with matching strength and toughness can be obtained under the solution treatment at 466 °C/60 min and aging treatment at 185 °C/13 h.
Analysis of Fatigue Strength of L-PBF AlSi10Mg with Different Surface Post-Processes: Effect of Residual Stresses
Authors: Sausto Francesco , Tezzele Christian , Beretta Stefano
Published: May 2022

Space and aerospace industries has been starting in the recent years the replacement process of parts and components obtained by traditional manufacturing processes with those produced by Additive Manufacturing (AM). The complexity of the obtainable parts makes, in general, challenging the superficial post processing of some zones, making a stringent requirement the investigation of the fatigue performances of components with rough superficial state or machined. The aim of this work is then to analyse and compare the fatigue performances of an additively manufactured (AMed) AlSi10Mg material considering both the effects of the manufacturing defects and residual stresses related to three different superficial states, namely machined, net-shape and sandblasted. The residual stress profiles of the three superficial states were found to play a key role in determining the fatigue properties of the analysed material, while the manufacturing defects at the failure origin were found to be comparable among the three series. To take into account the combined effect of residual stresses and manufacturing defects a fracture mechanics approach was considered for the estimation of the fatigue performances in both infinite and finite life regimes. It was found that by considering the nominal measured residual stress profiles in the fracture mechanics model the estimations were satisfactory compared to the experimental data-point. To increase the accuracy of the fatigue life estimations a series of numerical analyses were performed aimed to investigate the residual stresses relaxation during the cyclic loading. The adoption of the relaxed residual stress profiles in the fracture mechanics model resulted in good estimations respect to the experimental data-points, highlighting the necessity in adopting such developed approaches during the design phase of AM parts and components.
Occurrence and Identification of Yeasts in Production of White-Brined Cheese
Authors: Geronikou Athina , Larsen Nadja , Lillevang Søren K. , Jespersen Lene
Published: May 2022

The aim of this study was to reveal the sites of yeast contamination in dairy production and perform taxonomic characterization of potential yeast spoilers in cheese making. Occurrence of spoilage yeasts was followed throughout the manufacture of white-brined cheese at a Danish dairy, including the areas of milk pasteurization, curd processing, and packaging (26 sites in total). Spoilage yeasts were isolated from whey, old cheese curd, and air samples in viable counts of 1.48–6.27 log CFU/mL, 5.44 log CFU/g, and 1.02 log CFU/m3, respectively. Yeast isolates were genotypically classified using (GTG)5-PCR fingerprinting and identified by sequencing of the D1/D2 region of the 26S rRNA gene. The largest yeast heterogeneity was found in old curd collected under the turning machine of molds, where 11 different yeast species were identified. The most frequently isolated yeast species were Candida intermedia, Kluyveromyces marxianus, and Pichia kudriavzevii. The less abundant yeast species included Candida auris, Candida parapsilosis, Candida pseudoglaebosa, Candida sojae, Cutaneotrichosporon curvatus, Cutaneotrichosporon moniliiforme, Papiliotrema flavescens, Rhodotorula mucilaginosa, Vanrija humicola, and Wickerhamiella sorbophila. The awareness on occurrence and taxonomy of spoilage yeasts in cheese production will contribute to a knowledge-based control of contaminating yeasts and quality management of cheese at the dairies.
Inhibition of In Vitro Clostridioides difficile Biofilm Formation by the Probiotic Yeast Saccharomyces boulardii CNCM I-745 through Modification of the Extracellular Matrix Composition
Authors: Lacotte Pierre-Alexandre , Simons Alexis , Bouttier Sylvie , Malet-Villemagne Jeanne , Nicolas Valérie , Janoir Claire
Published: May 2022

Clostridioides difficile is responsible for post-antibiotic diarrhea and most of the pseudomembranous colitis cases. Multiple recurrences, one of the major challenges faced in C. difficile infection (CDI) management, can be considered as chronic infections, and the role of biofilm formation in CDI recurrences is now widely considered. Therefore, we explored if the probiotic yeast Saccharomyces boulardii CNCM I-745 could impact the in vitro formation of C. difficile biofilm. Biomass staining and viable bacterial cell quantification showed that live S. boulardii exerts an antagonistic effect on the biofilm formation for the three C. difficile strains tested. Confocal laser scanning microscopy observation revealed a weakening and an average thickness reduction of the biofilm structure when C. difficile is co-incubated with S. boulardii, compared to the single-species bacterial biofilm structure. These effects, that were not detected with another genetically close yeast, S. cerevisiae, seemed to require direct contact between the probiotic yeast and the bacterium. Quantification of the extrapolymeric matrix components, as well as results obtained after DNase treatment, revealed a significant decrease of eDNA, an essential structural component of the C. difficile biofilm matrix, in the dual-species biofilm. This modification could explain the reduced cohesion and robustness of C. difficile biofilms formed in the presence of S. boulardii CNCM I-745 and be involved in S. boulardii clinical preventive effect against CDI recurrences.
Vivax Malaria and the Potential Role of the Subtelomeric Multigene vir Superfamily
Authors: Goo Youn-Kyoung
Published: May 2022

Vivax malaria, caused by Plasmodium vivax, remains a public health concern in Central and Southeast Asia and South America, with more than two billion people at risk of infection. Compared to Plasmodium falciparum, P. vivax is considered a benign infection. However, in recent decades, incidences of severe vivax malaria have been confirmed. The P. falciparum erythrocyte membrane protein 1 family encoded by var genes is known as a mediator of severe falciparum malaria by cytoadherence property. Correspondingly, the vir multigene superfamily has been identified as the largest multigene family in P. vivax and is implicated in cytoadherence to endothelial cells and immune response activation. In this review, the functions of vir genes are reviewed in the context of their potential roles in severe vivax malaria.
Evaluation of the Pathogenic Potential of Escherichia coli Strains Isolated from Eye Infections
Authors: Nunes Pedro Henrique Soares , Valiatti Tiago Barcelos , Santos Ana Carolina de Mello , Nascimento Júllia Assis da Silva , Santos-Neto José Francisco , Rocchetti Talita Trevizani , Yu Maria Cecilia Zorat , Hofling-Lima Ana Luisa , Gomes Tânia Aparecida Tardelli
Published: May 2022

While primarily Gram-positive bacteria cause bacterial eye infections, several Gram-negative species also pose eye health risks. Currently, few studies have tried to understand the pathogenic mechanisms involved in E. coli eye infections. Therefore, this study aimed to establish the pathogenic potential of E. coli strains isolated from eye infections. Twenty-two strains isolated between 2005 and 2019 from patients with keratitis or conjunctivitis were included and submitted to traditional polymerase chain reactions (PCR) to define their virulence profile, phylogeny, clonal relationship, and sequence type (ST). Phenotypic assays were employed to determine hemolytic activity, antimicrobial susceptibility, and adhesion to human primary corneal epithelial cells (PCS-700-010). The phylogenetic results indicated that groups B2 and ST131 were the most frequent. Twenty-five virulence genes were found among our strains, with ecp, sitA, fimA, and fyuA being the most prevalent. Two strains presented a hemolytic phenotype, and resistance to ciprofloxacin and ertapenem was found in six strains and one strain, respectively. Regarding adherence, all but one strains adhered in vitro to corneal cells. Our results indicate significant genetic and virulence variation among ocular strains and point to an ocular pathogenic potential related to multiple virulence mechanisms.