bluuebunny/crossref_metadata_2025 huggingface dataset:
Robot Static Path Planning Method Based on Deterministic Annealing
Authors: Dai Jinyu , Qiu Jin , Yu Haocheng , Zhang Chunyang , Wu Zhengtian , Gao Qing
Published: July 2022

Heuristic calculation is an essential method to solve optimisation problems. However, its vast computing requirements limit its real-time and online applications, especially in embedded systems with limited computing resources, such as mobile robots. This paper presents a robot path planning algorithm called DA-APF based on deterministic annealing. It is derived from the artificial potential field and can effectively solve the local minimum problem of the model established by the potential field method. The calculation performance of DA-APF is considerably improved by introducing temperature parameters to enhance the potential field function and by using annealing and tempering methods. Moreover, an optimal or near-optimal robot path planning scheme is given. A comprehensive case study is performed using heuristic methods, such as genetic algorithm and simulated annealing. Simulation results show that DA-APF performs well in various static path planning environments.
A Novel Ensemble of Arithmetic Optimization Algorithm and Harris Hawks Optimization for Solving Industrial Engineering Optimization Problems
Authors: Yao Jinyan , Sha Yongbai , Chen Yanli , Zhao Xiaoying
Published: July 2022

Recently, numerous new meta-heuristic algorithms have been proposed for solving optimization problems. According to the Non-Free Lunch theorem, we learn that no single algorithm can solve all optimization problems. In order to solve industrial engineering design problems more efficiently, we, inspired by the algorithm framework of the Arithmetic Optimization Algorithm (AOA) and the Harris Hawks Optimization (HHO), propose a novel hybrid algorithm based on these two algorithms, named EAOAHHO in this paper. The pinhole imaging opposition-based learning is introduced into the proposed algorithm to increase the original population diversity and the capability to escape from local optima. Furthermore, the introduction of composite mutation strategy enhances the proposed EAOAHHO exploitation and exploration to obtain better convergence accuracy. The performance of EAOAHHO is verified on 23 benchmark functions and the IEEE CEC2017 test suite. Finally, we verify the superiority of the proposed EAOAHHO over the other advanced meta-heuristic algorithms for solving four industrial engineering design problems.
EEG-Based Empathic Safe Cobot
Authors: Borboni Alberto , Elamvazuthi Irraivan , Cusano Nicoletta
Published: July 2022

An empathic collaborative robot (cobot) was realized through the transmission of fear from a human agent to a robot agent. Such empathy was induced through an electroencephalographic (EEG) sensor worn by the human agent, thus realizing an empathic safe brain-computer interface (BCI). The empathic safe cobot reacts to the fear and in turn transmits it to the human agent, forming a social circle of empathy and safety. A first randomized, controlled experiment involved two groups of 50 healthy subjects (100 total subjects) to measure the EEG signal in the presence or absence of a frightening event. The second randomized, controlled experiment on two groups of 50 different healthy subjects (100 total subjects) exposed the subjects to comfortable and uncomfortable movements of a collaborative robot (cobot) while the subjects’ EEG signal was acquired. The result was that a spike in the subject’s EEG signal was observed in the presence of uncomfortable movement. The questionnaires were distributed to the subjects, and confirmed the results of the EEG signal measurement. In a controlled laboratory setting, all experiments were found to be statistically significant. In the first experiment, the peak EEG signal measured just after the activating event was greater than the resting EEG signal (p < 10−3). In the second experiment, the peak EEG signal measured just after the uncomfortable movement of the cobot was greater than the EEG signal measured under conditions of comfortable movement of the cobot (p < 10−3). In conclusion, within the isolated and constrained experimental environment, the results were satisfactory.
Fractional Order KDHD Impedance Control of the Stewart Platform
Authors: Bruzzone Luca , Polloni Alessio
Published: July 2022

In classical impedance control, KD, the steady-state end-effector forces are imposed to be proportional to the end-effector position errors through the stiffness matrix, K, and a proper damping term is added, proportional to the first-order derivatives of the end-effector position errors according to the damping matrix, D. This paper presents a fractional-order impedance control scheme, named KDHD, in which an additional damping is added, proportional to the half-order derivatives of the end-effector position errors according to the half-derivative damping matrix, HD. Since the finite-order digital filters which implement in real-time the half-order derivatives modify the steady-state stiffness of the end-effector—which should be defined exclusively by the stiffness matrix—a compensation method is proposed (KDHDc). The effectiveness of this approach is validated by multibody simulation on a Stewart platform. The proposed impedance controller represents the extension to multi-input multi-output robotic systems of the PDD1/2 controller for single-input single-output systems, which overperforms the PD scheme in the transient behavior.
A Multi-Part Production Planning System for a Distributed Network of 3D Printers under the Context of Social Manufacturing
Authors: Makanda Inno Lorren Désir , Yang Maolin , Shi Haoliang , Guo Wei , Jiang Pingyu
Published: July 2022

Additive manufacturing (AM) systems are currently evolving into network-based models, where the distributed manufacturing resources from multiple enterprises are coordinated to complete product orders. The layer-by-layer approach of AM technologies gives manufacturers unprecedented freedom to create complex parts tailored to customer needs, but this comes at slow build rates. Consequently, for AM to become mainstream in the industry, challenges in production planning remain to be addressed to increase AM system productivity. This paper considers two practical problems encountered in AM systems, namely, production planning and part-to-printer assignment, and a series of heuristic algorithms are proposed to solve these problems. In particular, an approach for automatically determining part orientation, part-to-printer allocation, and nesting of multiple parts for a distributed network of fused filament fabrication three-dimensional printers is described to reduce the total production cost and time regarding the context of social manufacturing. The proposed method is implemented through a web application. The case study, using real-world parts and comparative analysis findings, indicated that the proposed method produces high-performance results.
A Qubit Represented by the Oscillator’s Quantum States in Magnetic Resonance Force Microscopy
Authors: Christou Panayiotis , Tsifrinovich Vladimir I.
Published: July 2022

We consider magnetic resonance force microscopy (MRFM) in the situation when the frequency of the electron spin resonance matches the fundamental frequency of the cantilever with a ferromagnetic particle attached to its tip. We suggest that in this situation, the quantum states of the oscillating cantilever may represent a qubit. We develop a scheme for manipulation with the qubit state and derive the expression describing the Rabi oscillations of the qubit.
Visualizing a Cubic Linkage through the Use of CAS and DGS
Authors: Recio Tomás , Losada-Liste Rafael , Tabera Luis Felipe , Ueno Carlos
Published: July 2022

Our goal is to discuss the different issues that arise when attempting to visualize a joints-and-bars cube through GeoGebra, a widespread program that combines dynamic geometry (DGS) and computer algebra systems (CAS). As is standard in the DGS framework, the performance of the graphic model (i.e., the positions of the other vertices when dragging a given one) must correspond to a mathematically rigorous, symbolic computation-driven output. This requirement poses both computational algebraic geometry and dynamic geometry programming challenges that will be described, together with the corresponding proposed solutions. Among these, we include a complete determination of the dimension of the cubic linkage from an algebraic perspective, and introduce advanced 3D visualizations of this structure by using the GeoGebra software.
Game Theory and an Improved Maximum Entropy-Attribute Measure Interval Model for Predicting Rockburst Intensity
Authors: Zhao Yakun , Chen Jianhong , Yang Shan , Liu Zhe
Published: July 2022

To improve the accuracy of predicting rockburst intensity, game theory and an improved maximum entropy-attribute measure interval model were established. First, by studying the mechanism of rockburst and typical cases, rock uniaxial compressive strength σc, rock compression-tension ratio σc/σt, rock shear compression ratio σθ/σc, rock elastic deformation coefficient Wet, and rock integrity coefficient Kv were selected as indexes for predicting rockburst intensity. Second, by combining the maximum entropy principle with the attribute measure interval and using the minimum distance Di−k between sample and class as the guide, the entropy solution of the attribute measure was obtained, which eliminates the greyness and ambiguity of the rockburst indexes to the maximum extent. Third, using the compromise coefficient to integrate the comprehensive attribute measure, which avoids the ambiguity about the number of attribute measure intervals. Fourth, from the essence of measurement theory, the Euclidean distance formula was used to improve the attribute identification mode, which overcomes the effect of the confidence coefficient taking on the results. Moreover, in order to balance the shortcomings of the subjective weights of the Analytic Hierarchy Process and the objective weights of the CRITIC method, game theory was used for the combined weights, which balances experts’ experience and the amount of data information. Finally, 20 sets of typical cases for rockburst in the world were selected as samples. On the one hand, the reasonableness of the combined weights of indexes was analyzed; on the other hand, the results of this paper’s model were compared with the three analytical models for predicting rockburst, and this paper’s model had the lowest number of misjudged samples and an accuracy rate of 80%, which was better than other models, verifying the accuracy and applicability.
Review of Artificial Intelligence and Machine Learning Technologies: Classification, Restrictions, Opportunities and Challenges
Authors: Mukhamediev Ravil I. , Popova Yelena , Kuchin Yan , Zaitseva Elena , Kalimoldayev Almas , Symagulov Adilkhan , Levashenko Vitaly , Abdoldina Farida , Gopejenko Viktors , Yakunin Kirill , Muhamedijeva Elena , Yelis Marina
Published: July 2022

Artificial intelligence (AI) is an evolving set of technologies used for solving a wide range of applied issues. The core of AI is machine learning (ML)—a complex of algorithms and methods that address the problems of classification, clustering, and forecasting. The practical application of AI&ML holds promising prospects. Therefore, the researches in this area are intensive. However, the industrial applications of AI and its more intensive use in society are not widespread at the present time. The challenges of widespread AI applications need to be considered from both the AI (internal problems) and the societal (external problems) perspective. This consideration will identify the priority steps for more intensive practical application of AI technologies, their introduction, and involvement in industry and society. The article presents the identification and discussion of the challenges of the employment of AI technologies in the economy and society of resource-based countries. The systematization of AI&ML technologies is implemented based on publications in these areas. This systematization allows for the specification of the organizational, personnel, social and technological limitations. This paper outlines the directions of studies in AI and ML, which will allow us to overcome some of the limitations and achieve expansion of the scope of AI&ML applications.
Research on Path Planning Algorithm for Driverless Vehicles
Authors: Ma Hao , Pei Wenhui , Zhang Qi
Published: July 2022

In a complex environment, although the artificial potential field (APF) method of improving the repulsion function solves the defect of local minimum, the planned path has an oscillation phenomenon which cannot meet the vehicle motion. In order to improve the efficiency of path planning and solve the oscillation phenomenon existing in the improved artificial potential field method planning path. This paper proposes to combine the improved artificial potential field method with the rapidly exploring random tree (RRT) algorithm to plan the path. First, the improved artificial potential field method is combined with the RRT algorithm, and the obstacle avoidance method of the RRT algorithm is used to solve the path oscillation; The vehicle kinematics model is then established, and under the premise of ensuring the safety of the vehicle, a model predictive control (MPC) trajectory tracking controller with constraints is designed to verify whether the path planned by the combination of the two algorithms is optimal and conforms to the vehicle motion. Finally, the feasibility of the method is verified in simulation. The simulation results show that the method can effectively solve the problem of path oscillation and can plan the optimal path according to different environments and vehicle motion.
New Solitary-Wave Solutions of the Van der Waals Normal Form for Granular Materials via New Auxiliary Equation Method
Authors: Zhu Xiaomeng , Cheng Jinkang , Chen Zhuokai , Wu Guojiang
Published: July 2022

In this paper, we use general Riccati equation to construct new solitary wave solutions of the Van der Waals normal form, which is one of the most famous models for natural and industrial granular materials. It is very important to understand the static and dynamic characteristics of this models in many application fields. We solve the general Riccati equation through different function transformation, and many new hyperbolic function solutions are obtained. Then, it is substituted into the Van der Waals normal form as an auxiliary equation. Abundant types of solitary-wave solutions are obtained by choosing different coefficient in the general Riccati equation, and some of them have not been found in other documents. The results show that the analysis method we used is very simple and effective for dealing with nonlinear models.
An Entity-Matching System Based on Multimodal Data for Two Major E-Commerce Stores in Mexico
Authors: Estrada-Valenciano Raúl , Muñiz-Sánchez Víctor , De-la-Torre-Gutiérrez Héctor
Published: July 2022

E-commerce has grown considerably in Latin America in recent years due to the COVID-19 pandemic. E-commerce users in English-speaking and Chinese-speaking countries have web-based tools to compare the prices of products offered by various retailers. The task of product comparison is known as entity matching in the data-science domain. This paper proposes the first entity-matching system for product comparison in Spanish-speaking e-commerce. Given the lack of uniformity of e-commerce sites in Mexico, we opted for a bimodal entity-matching system that uses the image and textual description of products from two of the largest e-commerce stores in Mexico. State-of-the-art techniques in natural language processing and machine learning were used to develop this research. The resulting system achieves F1 values of approximately 80%, representing a significant step towards consolidating a product-matching system in Spanish-speaking e-commerce.
Mathematical Problem Solving through the Lens of Ethics and Aristotelian Attitude: A Case Study
Authors: Marbán José M. , Fernández-Gago Joaquín
Published: July 2022

Attitudes are central to the affective domain in mathematics. However, we still have a long way to go to reach a clear consensus on the characterization of such construct and its operationalization, as there are a wide variety of intertwined approaches depending on the theoretical framework that accompanies each of them. In this article, we explore the idea of incorporating ethics as part of a new characterization of attitude in problem solving contexts by means of an instrumental case study consisting of a key informant 10th grade student. Data were collected via classroom observations, questionnaires, semi-structured interviews and written productions. Results were analyzed using the lens of Aristotelian Ethics and the Theory of Creative Intelligence and show how happiness, responsibility and strength are key concepts that help to describe and understand the way the student behaves when solving mathematical problems. We conclude that besides the traditional attention paid to attitudes towards math, it is worth directing our attention towards attitudes influenced by ethics and personal affect as a whole.
A New Software-Based Optimization Technique for Embedded Latency Improvement of a Constrained MIMO MPC
Authors: Sotelo David , Favela-Contreras Antonio , Avila Alfonso , Pinto Arturo , Beltran-Carbajal Francisco , Sotelo Carlos
Published: July 2022

Embedded controllers for multivariable processes have become a powerful tool in industrial implementations. Here, the Model Predictive Control offers higher performances than standard control methods. However, they face low computational resources, which reduces their processing capabilities. Based on pipelining concept, this paper presents a new embedded software-based implementation for a constrained Multi-Input-Multi-Output predictive control algorithm. The main goal of this work focuses on improving the timing performance and the resource usage of the control algorithm. Therefore, a profiling study of the baseline algorithm is developed, and the performance bottlenecks are identified. The functionality and effectiveness of the proposed implementation are validated in the NI myRIO 1900 platform using the simulation of a jet transport aircraft during cruise flight and a tape transport system. Numerical results for the study cases show that the latency and the processor usage are substantially reduced compared with the baseline algorithm, 4.6× and 3.17× respectively. Thus, efficient program execution is obtained which makes the proposed software-based implementation mainly suitable for embedded control systems.
Deep Machine Learning Model-Based Cyber-Attacks Detection in Smart Power Systems
Authors: Almalaq Abdulaziz , Albadran Saleh , Mohamed Mohamed
Published: July 2022

In this study, a deep learning-based attack detection model is proposed to address the problem of system disturbances in energy systems caused by natural events like storms and tornadoes or human-made events such as cyber-attacks. The proposed model is trained using the long time recorded data through accurate phasor measurement units (PMUs). The data is then sent to various machine learning methods based on the effective features extracted out using advanced principal component analysis (PCA) model. The performance of the proposed model is examined and compared with some other benchmarks using various indices such as confusion matrix. The results show that incorporating PCA as the feature selection model could effectively decrease feature redundancy and learning time while minimizing data information loss. Furthermore, the proposed model investigates the potential of deep learning-based and Decision Tree (DT) classifiers to detect cyber-attacks for improving the security and efficiency of modern intelligent energy grids. By utilizing the big data recorded by PMUs and identifying relevant properties or characteristics using PCA, the proposed deep model can effectively detect attacks or disturbances in the system, allowing operators to take appropriate action and prevent any further damage.
Supplementation with Spirulina platensis Prevents Damage to Rat Erections in a Model of Erectile Dysfunction Promoted by Hypercaloric Diet-Induced Obesity
Authors: Souza Iara Leão Luna de , Barros Bárbara Cavalcanti , Ferreira Elba dos Santos , Queiroga Fernando Ramos , Vasconcelos Luiz Henrique César , Toscano Lydiane de Lima Tavares , Silva Alexandre Sérgio , Silva Patrícia Mirella da , Cavalcante Fabiana de Andrade , Silva Bagnólia Araújo da
Published: July 2022

Erectile dysfunction (ED) is the inability to achieve and/or maintain a penile erection sufficient for sexual satisfaction. Currently, many patients do not respond to the pharmacotherapy. The effects of a supplementation with Spirulina platensis, were evaluated in a model of ED induced by hypercaloric diet consumption. Wistar rats were divided into groups fed with standard diet (SD) or hypercaloric diet (HD) and supplemented with this alga at doses of 25, 50 or 100 mg/kg. Experimental adiposity parameters and erectile function were analyzed. In SD groups, Spirulina platensis reduced food intake, final body mass and adiposity index, and increased the total antioxidant capacity (TAC) of adipose tissue. However, no change was observed in erectile function. In the HD group, without Spirulina supplementation, a decrease in food intake was observed, in addition to an increase of final body mass, weight gain, adipose reserves, and adiposity index. Additionally, reduction in the number and increase in the latency of penile erection and adipose malondialdehyde levels, as well as a reduction in TCA was noted. Furthermore, cavernous contractility was increased, and the relaxing response was decreased. Interestingly, these deleterious effects were prevented by the algae at doses of 25, 50 and/or 100 mg/kg. Therefore, the supplementation with S. platensis prevents damages associated to a hypercaloric diet consumption and emerges as an adjuvant the prevention of ED.
Expression Plasticity of Peroxisomal Acyl-Coenzyme A Oxidase Genes Implies Their Involvement in Redox Regulation in Scallops Exposed to PST-Producing Alexandrium
Authors: Li Moli , Wang Yangrui , Tang Zhihong , Wang Huizhen , Hu Jingjie , Bao Zhenmin , Hu Xiaoli
Published: July 2022

Filter-feeding bivalves can accumulate paralytic shellfish toxins (PST) produced by toxic microalgae, which may induce oxidative stress and lipid peroxidation. Peroxisomal acyl-coenzyme A oxidases (ACOXs) are key enzymes functioning in maintaining redox and lipid homeostasis, but their roles in PST response in bivalves are less understood. Herein, a total of six and six ACOXs were identified in the Chlamys farreri and Patinopecten yessoensis genome, respectively, and the expansion of ACOX1s was observed. Gene expression analysis revealed an organ/tissue-specific expression pattern in both scallops, with all ACOXs being predominantly expressed in the two most toxic organs, digestive glands and kidneys. The regulation patterns of scallop ACOXs after exposure to different PST-producing algaes Alexandrium catenella (ACDH) and A. minutum (AM-1) were revealed. After ACDH exposure, more differentially expressed genes (DEGs) were identified in C. farreri digestive glands (three) and kidneys (five) than that in P. yessoensis (two), but the up-regulated DEGs showed similar expression patterns in both species. In C. farreri, three DEGs were found in both digestive glands and kidneys after AM-1 exposure, with two same CfACOX1s being acutely and chronically induced, respectively. Notably, these two CfACOX1s also showed different expression patterns in kidneys between ACDH (acute response) and AM-1 (chronic response) exposure. Moreover, inductive expression of CfACOXs after AM-1 exposure was observed in gills and mantles, and all DEGs in both tissues were up-regulated and their common DEGs exhibited both acute and chronic induction. These results indicate the involvement of scallop ACOXs in PST response, and their plasticity expression patterns between scallop species, among tissues, and between the exposure of different PST analogs.
Assessment of Instability in Thoracolumbar Burst Fractures Using a New Bone Scan Scoring System
Authors: Choi Hyung Jin , Park Seol Hoon , Choi Jun Ik , Kim Jae Young , Seo Minjung
Published: July 2022

Background and Objectives: Unstable thoracolumbar burst fractures require surgical management as they can result in neurological deficits if left untreated. This study aimed to evaluate whether a new bone scan scoring system could accurately assess instability in thoracolumbar burst fractures. Materials and Methods: Fifty-two patients with thoracolumbar burst fractures who underwent bone scans and magnetic resonance imaging prior to surgery between January 2015 and August 2017 at Ulsan University Hospital were selected for inclusion. Instability was determined by clinical assessment and imaging, and the Thoracolumbar Injury Classification and Severity score was determined. Bone scans were visually evaluated using a new bone scan scoring system. Bone scan findings of vertebral body (BB) and posterior column (BP) were scored separately and were summed to produce BTS {BTS (total score) = BB (body score, 5 points) + BP (posterior score, 2 points)}. The diagnostic performance of the scoring system for identifying unstable then thoracolumbar burst fractures were assessed. Results: Of the 52 thoracolumbar burst fractures, 34 (65.4%) were unstable and 31 (59.6%) had a Thoracolumbar Injury Classification and Severity score ≥ 5. The diagnostic performance of using BTS ≥ 4 to identify unstable thoracolumbar burst fractures and those with a Thoracolumbar Injury Classification and Severity score ≥ 5 was as follows: sensitivity, 61.8% and 58.1%; specificity, 94.4% and 81.0%; positive predictive value, 95.5% and 81.8%; and negative predictive value, 56.7% and 56.7%, respectively. Conclusions: The proposed bone scan scoring system has a high specificity and positive predictive value for identifying thoracolumbar burst fractures that are unstable or have a Thoracolumbar Injury Classification and Severity score ≥ 5. This scoring system may help to inform decisions regarding surgical management.
The Characteristics of Benzodiazepine Prescribing in the Republic of Srpska, Bosnia and Herzegovina
Authors: Maksimović Žana M. , Stajić Mladen , Stojiljković Miloš P. , Stoisavljević Šatara Svjetlana , Stojaković Nataša , Škrbić Ranko
Published: July 2022

Background and Objectives: Benzodiazepines (BZDs) are among the most prescribed psychotropic drugs and significant number of patients use these drugs for longer periods than recommended. The objective of this study was to determine the factors associated with prescribing of BZDs at the primary healthcare level. Materials and Methods: A retrospective analysis of family physicians’ prescriptions from the databases of family medicine teams of the Republic of Srpska was performed. The number of BZDs users, as well as the total number of prescriptions, were determined. Thereafter, it was determined which specific BZD had been prescribed, in which dose, for how long, as well as the specific social and demographic characteristics of patients to whom the drugs were prescribed. Results: The results showed that 38.47% of patients used the BZDs for a period longer than six months. The most frequent BZDs prescribed were the intermediate-acting BZDs, primarily bromazepam (58.69%). Two thirds of patients were women. The average age of the patients was 60, 60.46% of patients were single, and 69.68% lived in urban areas. The longer uses of BZDs were recorded in women, the elderly, single people and those who lived in urban areas, while higher doses of BZDs were prescribed to men, as well as younger and married people. The highest positive correlation was found between the dose and length of use of BZD. Conclusions: A significant percentage of patients used BZDs for a time period longer than recommended. Caution is necessary when prescribing BZDs to women, the elderly, patients that live in urban areas and patients who are single. When prescribing BZDs, family physicians should be aware of their potential interactions and addictive potentials.
Teriparatide as an Effective Nonsurgical Treatment for a Patient with Basicervical Peritrochanteric Fracture Nonunion—A Case Report
Authors: Ho Cheng-Han , Tzeng Shi-Chien , Farn Chui-Jia , Lee Chia-Che
Published: July 2022

The nonunion rate of surgically treated basicervical peritrochanteric fractures has been reported to be as high as 9%. Due to the high 1-year mortality rate following revision surgery, finding an effective nonsurgical treatment option is of interest. Over the last decade, numerous reports have been published that have suggested teriparatide as an effective treatment for certain types of fracture nonunion. However, the literature focused on teriparatide treatment for proximal femoral fracture nonunion is scanty. A 70-year-old man suffering from a left hip basicervical peritrochanteric fracture received cephalomedullary nail fixation. Nine months after the surgery, the patient still complained of left hip pain referring to the medial thigh with an antalgic limping gait. No sign of healing was noted for more than a consecutive 3 months of follow-up. Fracture nonunion was diagnosed and further confirmed by the computed tomography (CT). The patient preferred nonsurgical treatment after thorough discussion. He then received 4 months of subcutaneous teriparatide injections, 20 mcg daily. After less than 4 months of teriparatide treatment, a follow-up CT confirmed fracture union and the patient’s pain subsided. The patient also tolerated independent ambulation afterward. Teriparatide has been reported to be an effective treatment for certain types of fracture nonunion. Our case goes a step further to expand its possible application for basicervical peritrochanteric fracture nonunion. However, further larger scale studies are needed to confirm its efficacy.
Pulmonary Alveolar Proteinosis and Pregnancy: A Review of the Literature and Case Presentation
Authors: Cimpoca Raptis Brindusa Ana , Panaitescu Anca Maria , Peltecu Gheorghe , Gica Nicolae , Botezatu Radu , Popescu Mihaela Roxana , Macri Anca , Constantin Ana , Pavel Bogdan
Published: July 2022

Pulmonary Alveolar Proteinosis (PAP) is a rare, usually autoimmune, disease, where surfactant accumulates within alveoli due to decreased clearance, causing dyspnea and hypoxemia. The disease is even more rare in pregnancy; nevertheless, it has been reported in pregnant women and can even appear for the first time during pregnancy as an asthma-like illness. Therefore, awareness is important. Similarly to many autoimmune diseases, it can worsen during pregnancy and postpartum, causing maternal and fetal/neonatal complications. This paper offers a narrative literature review of PAP and pregnancy, while illustrating a case of a pregnant patient with known PAP who developed preeclampsia in the third trimester but had an overall fortunate maternal and neonatal outcome.
Level of Knowledge and Awareness of Female Undergraduate Students and Determinants of Knowledge of Folic Acid and Supplementation
Authors: Sabi Essa M. , Mujamammi Ahmed H. , Alturki Norah , Alzaid Taibah , Almutairi Ateen , Algarni Reem , Almaziad Deema , Alhumaidhi Nouf , Kurdee Zeyad , Sumaily Khalid M.
Published: July 2022

Background and Objectives: Folic acid (FA) is a necessary ingredient for numerous bodily activities including pregnancy. Because of this, women should have knowledge and awareness of the health benefits of FA supplementation. Thus, we aimed to investigate the level of knowledge on the importance of FA and determine associated factors for knowledge among female college students at King Saud University in Riyadh, Saudi Arabia. Material and Methods: We conducted a cross-sectional study using a questionnaire between January 2020 and February 2021 among female college students aged 17 to 26 years old. The questionnaire adapted with permission from Alnaami et al. included questions on the demographic profile of the participants as well as questions related to their knowledge and awareness of FA, FA supplementation, the importance of supplementation and their sources of knowledge of FA. Results: A total of 437 female undergraduate students participated in the study, 285 (65.2%) of whom were from the non-health colleges and 152 (34.8%) from the health colleges. The majority of participants were between ages 17 and 21 years old (n = 361, 82.6%). Half of the respondents were in their 3rd and 4th year of study (n = 122, 50.8%), 138 respondents (31.6%) were married, and 111 of these married women (80.4%) had children. There were 266 respondents (61.0%) who had heard and had knowledge of FA, 241 (55.3%) knew of FA timing of intake, 243 (55.7%) of FA duration of intake and 362 (83.0%) knew of the diseases prevented by FA supplementation. Linear regression analysis showed that being in the health college (B = 1.464, t = 11.37, p < 0.001, 95% CI = 1.211, 1.717) and a higher educational year level (B = 0.139, t = 2.442, p = 0.015, 95% CI = 0.027, 0.251) were the significant predictors of knowledge of FA. Conclusions: Knowledge of FA and FA supplementation was low at 61% considering that our study population were college students. Being enrolled in a health college and in a higher educational year level were significant positive correlates of higher knowledge of FA and FA supplementation. Despite this, there exists a gap of information regarding FA and FA supplementation particularly among single women and college educated women in the early years of their college life as well as those in non-health colleges.
Biomarkers of Endothelial Damage in Distinct Phases of Multisystem Inflammatory Syndrome in Children
Authors: Gelzo Monica , Giannattasio Antonietta , Maglione Marco , Muzzica Stefania , D’Anna Carolina , Scialò Filippo , Gagliardo Thaililja , Grieco Michela , Tipo Vincenzo , Castaldo Giuseppe
Published: July 2022

Endothelial hyperinflammation and vasculitis are known hallmarks of acute COVID-19 and multisystem inflammatory syndrome in children (MIS-C). They are due to the direct effect of the virus on endothelial cells enhanced by pro-inflammatory modulators and may cause venous/arterial thrombosis. Therefore, it is essential to identify patients with endothelial damage early in order to establish specific therapies. We studied the monocyte chemoattractant protein 1 (MCP-1), the perinuclear anti-neutrophil cytoplasmic antibodies (pANCA), and the vascular endothelial growth factor A (VEGF-A) in serum from 45 MIS-C patients at hospital admission and 24 healthy controls (HC). For 13/45 MIS-C patients, we measured the three serum biomarkers also after one week from hospitalization. At admission, MIS-C patients had significantly higher levels of MCP-1 and VEGF-A than the HC, but no significant differences were observed for pANCA. While after one week, MCP-1 was significantly lower, pANCA was higher and VEGF-A levels were not significantly different from the admission values. These findings suggest an involvement of epithelium in MIS-C with an acute phase, showing high MCP-1 and VEGF-A, followed by an increase in pANCA that suggests a vasculitis development. The serum biomarker levels may help to drive personalized therapies in these phases with anticoagulant prophylaxis, immunomodulators, and/or anti-angiogenic drugs.
An RBF Meshless Approach to Evaluate Strain Due to Large Displacements in Flexible Printed Circuit Boards
Authors: Groth Corrado , Chiappa Andrea , Porziani Stefano , Salvini Pietro , Biancolini Marco Evangelos
Published: July 2022

Thin plates are very often employed in a context of large displacements and rotations, for example, whenever the extreme flexibility of a body can replace the use of complicated kinematic pairs. This is the case of the flexible Printed Circuit Boards (PCBs) used, for example, within last-generation foldable laptops and consumer electronics products. In these applications, the range of motion is generally known in advance, and a simple strategy of stress assessment leaving out nonlinear numerical calculations appears feasible other than desirable. In this paper, Radial Basis Functions (RBFs) are used to represent a generic transformation of a bi-dimensional plate, with all the derivate fields being analytically achieved without the need for a numerical grid for large-displacement applications. Strains due to bending are easily retrieved with this method and satisfactorily compared to analytical and shell-based Finite Element Method (FEM) benchmarks. On the other hand, the computational costs of the juxtaposed methods appear far different; with the machine being equal, the orders of magnitude of the time elapsed in computation are seconds for the RBF-based strategy versus minutes for the FEM approach.
Facile Fabrication of a Highly Sensitive and Robust Flexible Pressure Sensor with Batten Microstructures
Authors: Zhang Xuefeng , Chang Sheng , Tong Zhixue
Published: July 2022

As the foremost component of wearable devices, flexible pressure sensors require high sensitivity, wide operating ranges, and great stability. In this paper, a pressure sensor comprising a regular batten microstructure active layer is presented. First, the influences of the dimensional parameters of the microstructures on the performances of the sensors were investigated by the mechanical finite element method (FEM). Then, parameters were optimized and determined based on the results of this investigation. Next, active layers were prepared by molding multiwalled carbon nanotube/polyurethane (MWCNT/PU) conductive composite using a printed circuit board template. Finally, a resistive flexible pressure sensor was fabricated by combining an active layer and an interdigital electrode. With advantages in terms of the structure and materials, the sensor exhibited a sensitivity of up to 46.66 kPa−1 in the range of 0–1.5 kPa and up to 6.67 kPa−1 in the range of 1.5–7.5 kPa. The results of the experiments show that the designed flexible pressure sensor can accurately measure small pressures and realize real-time human physiological monitoring. Furthermore, the preparation method has the advantages of a low cost, simple design, and high consistency. Thus, it has potential to promote the development of flexible sensors, wearable devices, and other related devices.
Mechanical Force Acting on Ferrogel in a Non-Uniform Magnetic Field: Measurements and Modeling
Authors: Blyakhman Felix A. , Safronov Alexander P. , Zubarev Andrey Yu. , Melnikov Grigory Yu. , Sokolov Sergey Yu. , Larrañaga Varga Aitor , Kurlyandskaya Galina V.
Published: July 2022

The development of magnetoactive microsystems for targeted drug delivery, magnetic biodetection, and replacement therapy is an important task of present day biomedical research. In this work, we experimentally studied the mechanical force acting in cylindrical ferrogel samples due to the application of a non-uniform magnetic field. A commercial microsystem is not available for this type of experimental study. Therefore, the original experimental setup for measuring the mechanical force on ferrogel in a non-uniform magnetic field was designed, calibrated, and tested. An external magnetic field was provided by an electromagnet. The maximum intensity at the surface of the electromagnet was 39.8 kA/m and it linearly decreased within 10 mm distance from the magnet. The Ferrogel samples were based on a double networking polymeric structure which included a chemical network of polyacrylamide and a physical network of natural polysaccharide guar. Magnetite particles, 0.25 micron in diameter, were embedded in the hydrogel structure, up to 24% by weight. The forces of attraction between an electromagnet and cylindrical ferrogel samples, 9 mm in height and 13 mm in diameter, increased with field intensity and the concentration of magnetic particles, and varied within 0.1–30 mN. The model provided a fair evaluation of the mechanical forces that emerged in ferrogel samples placed in a non-uniform magnetic field and proved to be useful for predicting the deformation of ferrogels in practical bioengineering applications.
An Electrochemical Electrode to Detect Theophylline Based on Copper Oxide Nanoparticles Composited with Graphene Oxide
Authors: Patil Vinoda B. , Malode Shweta J. , Mangasuli Sumitra N. , Tuwar Suresh M. , Mondal Kunal , Shetti Nagaraj P.
Published: July 2022

The electrochemical analysis of theophylline (THP) was investigated by fabricating a carbon paste electrode (CPE) modified with graphene oxide (GO) along with copper oxide (CuO) nanoparticles (CuO-GO/CPE). The impact of electro-kinetic parameters such as the heterogeneous rate constant, the scan rate, the accumulation time, the pH, the transfer coefficient, and the number of electrons and protons transferred into the electro-oxidation mechanism of THP has been studied utilizing electrochemical methods such as cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The differential pulse voltammetry technique was employed to investigate THP in pharmaceutical and biological samples, confirming the limit of detection (LOD) and quantification (LOQ) of the THP. X-ray diffraction (XRD) and scanning electron microscopy (SEM) analysis were performed to characterize the CuO nanoparticles. The CuO-GO/CPE was more sensitive in THP detection because its electrocatalytic characteristics displayed an enhanced peak current in the 0.2 M supporting electrolyte of pH 6.0, proving the excellent sensing functioning of the modified electrode.
Antimicrobial Resistance and Antimicrobial Activity of Staphylococcus lugdunensis Obtained from Two Spanish Hospitals
Authors: Fernández-Fernández Rosa , Lozano Carmen , Ruiz-Ripa Laura , Robredo Beatriz , Azcona-Gutiérrez José Manuel , Alonso Carla Andrea , Aspiroz Carmen , Zarazaga Myriam , Torres Carmen
Published: July 2022

Staphylococcus lugdunensis is a coagulase-negative-staphylococci (CoNS) that lately has gained special attention in public health as a human pathogen and also as a bacteriocin-producer bacteria. In this study, we characterized 56 S. lugdunensis isolates recovered from human samples in two Spanish hospitals. Antimicrobial susceptibility testing was performed and antimicrobial resistance and virulence genotypes were determined. Antimicrobial activity (AA) production was evaluated by the spot-on-lawn method against 37 indicator bacteria, including multidrug-resistant (MDR) isolates, and the presence of the lugD gene coding for lugdunin bacteriocin was analyzed by PCR. The antibiotic resistance detected was as follows (% resistance/genes detected): penicillin (44.6%/blaZ), oxacillin (1.8%/mecA on SCCmec-V), erythromycin-clindamycin inducible (7.1%/erm(C), msrA), tetracycline (5.3%/tetK), gentamicin and/or tobramycin (3.6%/ant(4′)-Ia, acc(6′)-aph(2″)), and fosfomycin (21.4%). A MDR phenotype was detected in 5% of isolates. Twenty-one of the S. lugdunensis isolates showed susceptibility to all 20 antibiotics tested (37.5%). The screening for AA revealed 23 antimicrobial producer (AP) isolates with relevant inhibition against coagulase-positive-staphylococci (CoPS), including both methicillin-susceptible and –resistant S. aureus. The lugD gene was detected in 84% of the 56 S. lugdunensis isolates. All of the AP S. lugdunensis isolates (n = 23) carried the lugD gene and it was also detected in 24 of the non-AP isolates, suggesting different gene expression levels. One of the AP isolates stood out due to its high antimicrobial activity against more than 70% of the indicator bacteria tested, so it will be further characterized at genomic and proteomic level.
Microalgae: A Promising Future
Authors: Caroppo Carmela , Pagliara Patrizia
Published: July 2022

Microalgae are photosynthetic unicellular microorganisms that represent an extremely important component of the aquatic ecosystem productivity, diversity, and functioning [...]
Microbial Communities of Seawater and Coastal Soil of Russian Arctic Region and Their Potential for Bioremediation from Hydrocarbon Pollutants
Authors: Semenova Ekaterina M. , Babich Tamara L. , Sokolova Diyana S. , Ershov Alexey P. , Raievska Yeva I. , Bidzhieva Salimat K. , Stepanov Alexey L. , Korneykova Maria V. , Myazin Vladimir A. , Nazina Tamara N.
Published: July 2022

The development of Arctic regions leads to pollution of marine and coastal environments with oil and petroleum products. The purpose of this work was to determine the diversity of microbial communities in seawater, as well as in littoral and coastal soil, and the potential ability of their members to degrade hydrocarbons degradation and to isolate oil-degrading bacteria. Using high-throughput sequencing of the V4 region of the 16S rRNA gene, the dominance of bacteria in polar communities was shown, the proportion of archaea did not exceed 2% (of the total number of sequences in the libraries). Archaea inhabiting the seawater belonged to the genera Nitrosopumilus and Nitrosoarchaeum and to the Nitrososphaeraceae family. In the polluted samples, members of the Gammaproteobacteria, Alphaproteobacteria, and Actinomycetes classes predominated; bacteria of the classes Bacteroidia, Clostridia, Acidimicrobiia, Planctomycetia, and Deltaproteobacteria were less represented. Using the iVikodak program and KEGG database, the potential functional characteristics of the studied prokaryotic communities were predicted. Bacteria were potentially involved in nitrogen and sulfur cycles, in degradation of benzoate, terephthalate, fatty acids, and alkanes. A total of 19 strains of bacteria of the genera Pseudomonas, Aeromonas, Oceanisphaera, Shewanella, Paeniglutamicibacter, and Rhodococcus were isolated from the studied samples. Among them were psychrotolerant and psychrophilic bacteria growing in seawater and utilizing crude oil, diesel fuel, and motor oils. The data obtained suggest that the studied microbial communities could participate in the removal of hydrocarbons from arctic seawater and coastal soils and suggested the possibility of the application of the isolates for the bioaugmentation of oil-contaminated polar environments.
Editorial for Special Issue “Microorganisms and Organic Waste Valorisation”
Authors: Braguglia Camilla M. , Rossetti Simona
Published: July 2022

Increasing amounts of organic waste are produced globally from a wide range of industrial activities, wastewater treatment plants, agricultural processing, and human food consumption [...]
Valorisation of Broccoli By-Products: Technological, Sensory and Flavour Properties of Durum Pasta Fortified with Broccoli Leaf Powder
Authors: Drabińska Natalia , Nogueira Mariana , Szmatowicz Beata
Published: July 2022

The aim of this study was to evaluate the effect of broccoli leaf powder (BLP) incorporation on the technological properties, sensory quality and volatile organic compounds (VOCs) of durum wheat pasta. Incorporation of BLP increased cooking loss; however, all pasta samples were found to be in the acceptable range of 8 g/100 g. The addition of BLP decreased optimal cooking time and water absorption but increased the swelling index. Firmness and total shearing force decreased with increased BLP content. The obtained pasta was greener than the control, with a higher content of minerals, and an increasing tendency with respect to protein was observed. The VOC profile of enriched pasta was richer and contained compounds typical of broccoli (e.g., dimethyl sulphide), affecting its aroma. The sensory evaluation results indicate that the addition of BLP did not affect the overall acceptance of pasta. Up to 5% BLP content afforded an interesting, more nutritious pasta without compromising its technological and sensory quality.