bluuebunny/crossref_metadata_2025 huggingface dataset:
Computational Statistics and Machine Learning Techniques for Effective Decision Making on Student’s Employment for Real-Time
Authors: Kumar Deepak , Verma Chaman , Singh Pradeep Kumar , Raboaca Maria Simona , Felseghi Raluca-Andreea , Ghafoor Kayhan Zrar
Published: May 2021

The present study accentuated a hybrid approach to evaluate the impact, association and discrepancies of demographic characteristics on a student’s job placement. The present study extracted several significant academic features that determine the Master of Business Administration (MBA) student placement and confirm the placed gender. This paper recommended a novel futuristic roadmap for students, parents, guardians, institutions, and companies to benefit at a certain level. Out of seven experiments, the first five experiments were conducted with deep statistical computations, and the last two experiments were performed with supervised machine learning approaches. On the one hand, the Support Vector Machine (SVM) outperformed others with the uppermost accuracy of 90% to predict the employment status. On the other hand, the Random Forest (RF) attained a maximum accuracy of 88% to recognize the gender of placed students. Further, several significant features are also recommended to identify the placement of gender and placement status. A statistical t-test at 0.05 significance level proved that the student’s gender did not influence their offered salary during job placement and MBA specializations Marketing and Finance (Mkt&Fin) and Marketing and Human Resource (Mkt&HR) (p > 0.05). Additionally, the result of the t-test also showed that gender did not affect student’s placement test percentage scores (p > 0.05) and degree streams such as Science and Technology (Sci&Tech), Commerce and Management (Comm&Mgmt). Others did not affect the offered salary (p > 0.05). Further, the χ2 test revealed a significant association between a student’s course specialization and student’s placement status (p < 0.05). It also proved that there is no significant association between a student’s degree and placement status (p > 0.05). The current study recommended automatic placement prediction with demographic impact identification for the higher educational universities and institutions that will help human communities (students, teachers, parents, institutions) to prepare for the future accordingly.
Navier–Stokes Cauchy Problem with |v0(x)|2 Lying in the Kato Class K3
Authors: Crispo Francesca , Maremonti Paolo
Published: May 2021

We investigate the 3D Navier–Stokes Cauchy problem. We assume the initial datum v0 is weakly divergence free, supR3∫R3|v0(y)|2|x−y|dy<∞ and |v0(y)|2∈K3, where K3 denotes the Kato class. The existence is local for arbitrary data and global if supR3∫R3|v0(y)|2|x−y|dy is small. Regularity and uniqueness also hold.
Circulant Singular Spectrum Analysis to Monitor the State of the Economy in Real Time
Authors: Bógalo Juan , Poncela Pilar , Senra Eva
Published: May 2021

Real-time monitoring of the economy is based on activity indicators that show regular patterns such as trends, seasonality and business cycles. However, parametric and non-parametric methods for signal extraction produce revisions at the end of the sample, and the arrival of new data makes it difficult to assess the state of the economy. In this paper, we compare two signal extraction procedures: Circulant Singular Spectral Analysis, CiSSA, a non-parametric technique in which we can extract components associated with desired frequencies, and a parametric method based on ARIMA modelling. Through a set of simulations, we show that the magnitude of the revisions produced by CiSSA converges to zero quicker, and it is smaller than that of the alternative procedure.
Multiple Capture in a Group Pursuit Problem with Fractional Derivatives and Phase Restrictions
Authors: Petrov Nikolay Nikandrovich
Published: May 2021

The problem of conflict interaction between a group of pursuers and an evader in a finite-dimensional Euclidean space is considered. All participants have equal opportunities. The dynamics of all players are described by a system of differential equations with fractional derivatives in the form D(α)zi=azi+ui−v,ui,v∈V, where D(α)f is a Caputo derivative of order α of the function f. Additionally, it is assumed that in the process of the game the evader does not move out of a convex polyhedral cone. The set of admissible controls V is a strictly convex compact and a is a real number. The goal of the group of pursuers is to capture of the evader by no less than m different pursuers (the instants of capture may or may not coincide). The target sets are the origin. For such a conflict-controlled process, we derive conditions on its parameters and initial state, which are sufficient for the trajectories of the players to meet at a certain instant of time for any counteractions of the evader. The method of resolving functions is used to solve the problem, which is used in differential games of pursuit by a group of pursuers of one evader.
Design Improvement for Complex Systems with Uncertainty
Authors: Chen Yue , Shi Jian , Yi Xiao-Jian
Published: May 2021

The uncertainty of the engineering system increases with its complexity, therefore, the tolerance to the uncertainty becomes important. Even under large variations of design parameters, the system performance should achieve the design goal in the design phase. Therefore, engineers are interested in how to turn a bad design into a good one with the least effort in the presence of uncertainty. To improve a bad design, we classify design parameters into key parameters and non-key parameters based on engineering knowledge, and then seek the maximum solution hyper-box which already includes non-key parameters of this bad design. The solution hyper-box on which all design points are good, that is, they achieve the design goal, provides target intervals for each parameter. The bad design can be turned into a good one by only moving its key parameters into their target intervals. In this paper, the PSO-Divide-Best method is proposed to seek the maximum solution hyper-box which is in compliance with the constraints. This proposed approach has a considerably high possibility to find the globally maximum solution hyper-box that satisfies the constraints and can be used in complex systems with black-box performance functions. Finally, case studies show that the proposed approach outperforms the EPCP and IA-CES methods in the literature.
Personalized Characterization of Emotional States in Patients with Bipolar Disorder
Authors: Llamocca Pavel , López Victoria , Santos Matilde , Čukić Milena
Published: May 2021

There is strong clinical evidence from the current literature that certain psychological and physiological indicators are closely related to mood changes. However, patients with mental illnesses who present similar behavior may be diagnosed differently, which is why a personalized study of each patient is necessary. Following previous promising results in the detection of depression, in this work, supervised machine learning (ML) algorithms were applied to classify the different states of patients diagnosed with bipolar depressive disorder (BDD). The purpose of this study was to provide relevant information to medical staff and patients’ relatives in order to help them make decisions that may lead to a better management of the disease. The information used was collected from BDD patients through wearable devices (smartwatches), daily self-reports, and medical observation at regular appointments. The variables were processed and then statistical techniques of data analysis, normalization, noise reduction, and feature selection were applied. An individual analysis of each patient was carried out. Random Forest, Decision Trees, Logistic Regression, and Support Vector Machine algorithms were applied with different configurations. The results allowed us to draw some conclusions. Random Forest achieved the most accurate classification, but none of the applied models were the best technique for all patients. Besides, the classification using only selected variables produced better results than using all available information, though the amount and source of the relevant variables differed for each patient. Finally, the smartwatch was the most relevant source of information.
A New Algebraic Inequality and Some Applications in Submanifold Theory
Authors: Mihai Ion , Mihai Radu-Ioan
Published: May 2021

We give a simple proof of the Chen inequality involving the Chen invariant δ(k) of submanifolds in Riemannian space forms. We derive Chen’s first inequality and the Chen–Ricci inequality. Additionally, we establish a corresponding inequality for statistical submanifolds.
Thermal Conductivity Estimation Based on Well Logging
Authors: Hu Jie , Jiang Guangzheng , Wang Yibo , Hu Shengbiao
Published: May 2021

The thermal conductivity of a stratum is a key factor to study the deep temperature distribution and the thermal structure of the basin. A huge expense of core sampling from boreholes, especially in offshore areas, makes it expensive to directly test stratum samples. Therefore, the use of well logging (the gamma-ray, the neutron porosity, and the temperature) to estimate the thermal conductivity of the samples obtained from boreholes could be a good alternative. In this study, we measured the thermal conductivity of 72 samples obtained from an offshore area as references. When the stratum is considered to be a shale–sand–fluid model, the thermal conductivity can be calculated based on the mixing models (the geometric mean and the square root mean). The contents of the shale and the sand were derived from the natural gamma-ray logs, and the content of the fluid (porosity) was derived from the neutron porosity logs. The temperature corrections of the thermal conductivity were performed for the solid component and the fluid component separately. By comparing with the measured data, the thermal conductivity predicted based on the square root model showed good consistency. This technique is low-cost and has great potential to be used as an application method to obtain the thermal conductivity for geothermal research.
A Fuzzy Seasonal Long Short-Term Memory Network for Wind Power Forecasting
Authors: Liao Chin-Wen , Wang I-Chi , Lin Kuo-Ping , Lin Yu-Ju
Published: May 2021

To protect the environment and achieve the Sustainable Development Goals (SDGs), reducing greenhouse gas emissions has been actively promoted by global governments. Thus, clean energy, such as wind power, has become a very important topic among global governments. However, accurately forecasting wind power output is not a straightforward task. The present study attempts to develop a fuzzy seasonal long short-term memory network (FSLSTM) that includes the fuzzy decomposition method and long short-term memory network (LSTM) to forecast a monthly wind power output dataset. LSTM technology has been successfully applied to forecasting problems, especially time series problems. This study first adopts the fuzzy seasonal index into the fuzzy LSTM model, which effectively extends the traditional LSTM technology. The FSLSTM, LSTM, autoregressive integrated moving average (ARIMA), generalized regression neural network (GRNN), back propagation neural network (BPNN), least square support vector regression (LSSVR), and seasonal autoregressive integrated moving average (SARIMA) models are then used to forecast monthly wind power output datasets in Taiwan. The empirical results indicate that FSLSTM can obtain better performance in terms of forecasting accuracy than the other methods. Therefore, FSLSTM can efficiently provide credible prediction values for Taiwan’s wind power output datasets.
The Existence and Uniquenes Solution of Nonlinear Integral Equations via Common Fixed Point Theorems
Authors: Mani Gunaseelan , Gnanaprakasam Arul Joseph , Li Yongjin , Gu Zhaohui
Published: May 2021

In this paper, we prove some common fixed-point theorems on complex partial metric space. The presented results generalize and expand some of the well-known results in the literature. We also explore some of the applications of our key results.
Investigation of the Effect of a Flapping Propeller on Its Aerodynamic Performance
Authors: Rimša Vytautas , Kilikevičius Artūras
Published: May 2021

This paper focuses on the dynamic effects of flexible propellers on F2 class aircraft models. An oscillating propeller affects an engine’s mechanical performance, and this combination has a huge influence on the model’s flight dynamic performance. In the first and second sections of this paper, two physical tests that were performed according to the test results obtained using a CFX numerical model are discussed. The studies on flexible propellers for class F2 aircraft models performed in this paper show that, when the first resonant frequencies of the propeller are within the operating range of the aircraft, better flight parameters are achieved. This study helps to explain the effect of a glass composite’s Young’s modulus on the mechanical behavior of a physical propeller in operating conditions and the effect of propeller stiffness on flapping propeller dynamics and unsteady aerodynamics.
A Conservative and Implicit Second-Order Nonlinear Numerical Scheme for the Rosenau-KdV Equation
Authors: Guo Cui , Wang Yinglin , Luo Yuesheng
Published: May 2021

In this paper, for solving the nonlinear Rosenau-KdV equation, a conservative implicit two-level nonlinear scheme is proposed by a new numerical method named the multiple integral finite volume method. According to the order of the original differential equation’s highest derivative, we can confirm the number of integration steps, which is just called multiple integration. By multiple integration, a partial differential equation can be converted into a pure integral equation. This is very important because we can effectively avoid the large errors caused by directly approximating the derivative of the original differential equation using the finite difference method. We use the multiple integral finite volume method in the spatial direction and use finite difference in the time direction to construct the numerical scheme. The precision of this scheme is O(τ2+h3). In addition, we verify that the scheme possesses the conservative property on the original equation. The solvability, uniqueness, convergence, and unconditional stability of this scheme are also demonstrated. The numerical results show that this method can obtain highly accurate solutions. Further, the tendency of the numerical results is consistent with the tendency of the analytical results. This shows that the discrete scheme is effective.
A Hybrid, Data-Driven Causality Exploration Method for Exploring the Key Factors Affecting Mobile Payment Usage Intention
Authors: Fang Ching Ching , Liou James J. H. , Huang Sun-Weng , Wang Ying-Chuan , Huang Hui-Hua , Tzeng Gwo-Hshiung
Published: May 2021

Several methodologies for academically exploring causality have been addressed in recent years. The decision-making trial and evaluation laboratory (DEMATEL), one of the multiple criteria decision-making (MCDM) techniques, relies on expert judgements to construct an influential network relation map (INRM), revealing the mutual causes and effects of the criteria and dimensions for presentation of the results in a visual manner. The interactional impacts may be evaluated without considering the presumed hypotheses. The DEMATEL has been successfully utilized to assist in complex decision-making problems in various contexts. However, there is controversy about the reliance upon expert judgements, which could be subjective. Thus, this study seeks to overcome this dispute by developing a data-driven, concept-based novel hybrid model which the authors call SEM-DEMATEL. The model first constructs the direct effects between indicators based on structural equation modeling (SEM) and then utilizes DEMATEL to confirm the interdependence among the variables and identify their causes and effects. Finally, an empirical study exploring the key factors affecting mobile payment usage intention is further conducted to demonstrate the feasibility, validity, and reliability of the novel SEM-DEMATEL research approach. The results identify that the perceived value is the key influencing indicator of m-payment usage intention, and the objectivity and efficiency of the research results are compared.
Using Markov Models to Characterize and Predict Process Target Compliance
Authors: McClean Sally
Published: May 2021

Processes are everywhere, covering disparate fields such as business, industry, telecommunications, and healthcare. They have previously been analyzed and modelled with the aim of improving understanding and efficiency as well as predicting future events and outcomes. In recent years, process mining has appeared with the aim of uncovering, observing, and improving processes, often based on data obtained from logs. This typically requires task identification, predicting future pathways, or identifying anomalies. We here concentrate on using Markov processes to assess compliance with completion targets or, inversely, we can determine appropriate targets for satisfactory performance. Previous work is extended to processes where there are a number of possible exit options, with potentially different target completion times. In particular, we look at distributions of the number of patients failing to meet targets, through time. The formulae are illustrated using data from a stroke patient unit, where there are multiple discharge destinations for patients, namely death, private nursing home, or the patient’s own home, where different discharge destinations may require disparate targets. Key performance indicators (KPIs) of this sort are commonplace in healthcare, business, and industrial processes. Markov models, or their extensions, have an important role to play in this work where the approach can be extended to include more expressive assumptions, with the aim of assessing compliance in complex scenarios.
Flexible Log-Linear Birnbaum–Saunders Model
Authors: Martínez-Flórez Guillermo , Barranco-Chamorro Inmaculada , Gómez Héctor W.
Published: May 2021

Rieck and Nedelman (1991) introduced the sinh-normal distribution. This model was built as a transformation of a N(0,1) distribution. In this paper, a generalization based on a flexible skew normal distribution is introduced. In this way, a more general model is obtained that can describe a range of asymmetric, unimodal and bimodal situations. The paper is divided into two parts. First, the properties of this new model, called flexible sinh-normal distribution, are obtained. In the second part, the flexible sinh-normal distribution is related to flexible Birnbaum–Saunders, introduced by Martínez-Flórez et al. (2019), to propose a log-linear model for lifetime data. Applications to real datasets are included to illustrate our findings.
Probabilistic Non-Negative Matrix Factorization with Binary Components
Authors: Ma Xindi , Gao Jie , Liu Xiaoyu , Zhang Taiping , Tang Yuanyan
Published: May 2021

Non-negative matrix factorization is used to find a basic matrix and a weight matrix to approximate the non-negative matrix. It has proven to be a powerful low-rank decomposition technique for non-negative multivariate data. However, its performance largely depends on the assumption of a fixed number of features. This work proposes a new probabilistic non-negative matrix factorization which factorizes a non-negative matrix into a low-rank factor matrix with 0,1 constraints and a non-negative weight matrix. In order to automatically learn the potential binary features and feature number, a deterministic Indian buffet process variational inference is introduced to obtain the binary factor matrix. Further, the weight matrix is set to satisfy the exponential prior. To obtain the real posterior distribution of the two factor matrices, a variational Bayesian exponential Gaussian inference model is established. The comparative experiments on the synthetic and real-world datasets show the efficacy of the proposed method.
Spirulina Microalgae and Brain Health: A Scoping Review of Experimental and Clinical Evidence
Authors: Sorrenti Vincenzo , Castagna Davide Augusto , Fortinguerra Stefano , Buriani Alessandro , Scapagnini Giovanni , Willcox Donald Craig
Published: May 2021

Spirulina microalgae contain a plethora of nutrient and non-nutrient molecules providing brain health benefits. Numerous in vivo evidence has provided support for the brain health potential of spirulina, highlighting antioxidant, anti-inflammatory, and neuroprotective mechanisms. Preliminary clinical studies have also suggested that spirulina can help to reduce mental fatigue, protect the vascular wall of brain vessels from endothelial damage and regulate internal pressure, thus contributing to the prevention and/or mitigating of cerebrovascular conditions. Furthermore, the use of spirulina in malnourished children appears to ameliorate motor, language, and cognitive skills, suggesting a reinforcing role in developmental mechanisms. Evidence of the central effect of spirulina on appetite regulation has also been shown. This review aims to understand the applicative potential of spirulina microalgae in the prevention and mitigation of brain disorders, highlighting the nutritional value of this “superfood”, and providing the current knowledge on relevant molecular mechanisms in the brain associated with its dietary introduction.
Ultrasound Elastography—Cornerstone of Non-Invasive Metabolic Dysfunction-Associated Fatty Liver Disease Assessment
Authors: Hari Andrej
Published: May 2021

Metabolic dysfunction-associated fatty liver disease has become the most common chronic liver disease as well as the most common cause for liver transplantation. With its different methods types, elastography of the liver can be used for non-invasive evaluation of the liver fibrosis and steatosis degree. The article focuses on the description, use, advantages, and limitations of the currently known elastographic techniques. It proposes a simple risk assessment algorithm for the liver fibrosis progress evaluation. The following is an overview of the use of liver and spleen elastography in the detection of clinically relevant portal hypertension. It concludes with research and technological possibilities that could be important to the field in the upcoming years.
Early Surgery Does Not Improve Outcomes for Patients with Periprosthetic Femoral Fractures—Results from the Registry for Geriatric Trauma of the German Trauma Society
Authors: Bliemel Christopher , Rascher Katherine , Knauf Tom , Hack Juliana , Eschbach Daphne , Aigner Rene , Oberkircher Ludwig ,   on behalf of the AltersTraumaRegister DGU
Published: May 2021

Background and Objectives: Appropriate timing of surgery for periprosthetic femoral fractures (PFFs) in geriatric patients remains unclear. Data from a large international geriatric trauma register were analyzed to examine the outcome of patients with PFF with respect to the timing of surgical stabilization. Materials and Methods: The Registry for Geriatric Trauma of the German Trauma Society (Deutsche Gesellschaft für Unfallchirurgie (DGU)) (ATR-DGU) was analyzed. Patients treated surgically for PFF were included in this analysis. As outcome parameters, in-house mortality rate and mortality at the 120-day follow-up as well as mobility, the EQ5D index score and reoperation rate were analyzed in relation to early (<48 h) or delayed (≥48 h) surgical stabilization. Results: A total of 1178 datasets met the inclusion criteria; 665 fractures were treated with osteosynthesis (56.4%), and 513 fractures were treated by implant change (43.5%). In contrast to the osteosynthesis group, the group with implant changes underwent delayed surgical treatment more often. Multivariate logistic regression analysis of mortality rate (p = 0.310), walking ability (p = 0.239) and EQ5D index after seven days (p = 0.812) revealed no significant differences between early (<48 h) and delayed (≥48 h) surgical stabilization. These items remained insignificant at the follow-up as well. However, the odds of requiring a reoperation within 120 days were significantly higher for delayed surgical treatment (OR: 1.86; p = 0.003). Conclusions: Early surgical treatment did not lead to decreased mortality rates in the acute phase or in the midterm. Except for the rate of reoperation, all other outcome parameters remained unaffected. Nevertheless, for most patients, early surgical treatment should be the goal, so as to achieve early mobilization and avoid secondary nonsurgical complications. If early stabilization is not possible, it can be assumed that orthogeriatric co-management will help protect these patients from further harm.
Non-Celiac Gluten Sensitivity: An Update
Authors: Cárdenas-Torres Feliznando Isidro , Cabrera-Chávez Francisco , Figueroa-Salcido Oscar Gerardo , Ontiveros Noé
Published: May 2021

Non-celiac gluten sensitivity (NCGS) is a clinical entity characterized by the absence of celiac disease and wheat allergy in patients that trigger reproducible symptomatic responses to gluten-containing foods consumption. Due to the lack of sensitive and reproducible biomarkers for NCGS diagnosis, placebo-controlled gluten challenges must be carried out for its diagnosis. The gluten challenges can be either double- or single-blind, for research or clinical practice purposes, respectively. For improving our understanding about the magnitude and relevance of NCGS in different populations, epidemiological studies based on self-report have been carried out. However, the gluten challenge-based prevalence of NCGS remains to be estimated. Since NCGS was recently recognized as a clinical entity, more studies are needed to delve into NCGS pathogenesis, for instance, the molecular interactions between the suspected cereal grain components that trigger NCGS, such as fermentable oligo-, di-, monosaccharides, and polyols (FODMAPs) and amylase and trypsin inhibitors, and the immune system remains to be elucidated. Although still under debate, NCGS patients can be susceptible to only one or more than one of the NCGS triggers. The treatment of NCGS involves the dietary restriction of the suspected triggers of the disease, but there is controversial data about the effectiveness of different dietary interventions such as the gluten-free diet and low-FODMAP diet. Certainly, our understanding of NCGS is improving quickly due to the constant availability of new scientific information on this topic. Thus, the aim of the present narrative review is to present an up-to-date overview on NCGS from epidemiology to current therapy.
The Mechanisms for the Association of Cancer and Esophageal Dysmotility Disorders
Authors: Tustumi Francisco , de Sousa Jorge Henrique Bento , Dornelas Nicolas Medeiros , Rosa Guilherme Maganha , Steinman Milton , Bianchi Edno Tales
Published: May 2021

Background: Achalasia and other esophageal dysmotility disorders mimicking achalasia can be associated with cancer. This study aimed to review the main mechanisms for which cancer may develop in esophageal dysmotility disorder patients. Methods: A narrative review was performed. Results: The mechanism for developing squamous cell carcinoma and adenocarcinoma are discussed. Besides, achalasia-like syndromes related to familial KIT-gene mutation and pseudoachalasia are discussed. Conclusions: Knowing the main mechanism for which achalasia can be related to cancer is essential for clinicians to conduct the proper investigation, surveillance, and treatment.
Adjuvant Inhaled Corticosteroids in Community-Acquired Pneumonia: A Review Article
Authors: Kukhon Faeq R. , Festic Emir
Published: May 2021

Community-acquired pneumonia is still a major cause of morbidity and mortality worldwide. Since the inflammatory response induced by the immune system is often a major contributor to the lung injury, it becomes reasonable to assess the potential benefit of anti-inflammatory agents in treating community-acquired pneumonia. The role of corticosteroids as adjunct anti-inflammatory agents in treating community-acquired pneumonia is still controversial. Several studies have assessed the benefit of their use in patients with community-acquired pneumonia. In most of those studies, the route of corticosteroids administration was systemic. The aim of this article is to provide a concise review of the role of corticosteroids in treating community-acquired pneumonia when administered via inhalational route, with the potential benefit of avoiding systemic side effects of corticosteroids while exerting the same anti-inflammatory effects on the lungs. Conclusion: the use of inhaled corticosteroids may be of benefit in certain patient subsets with community-acquired pneumonia. Further randomized controlled trials are needed for better determination of such patient subsets.
Recent Advances in the Prediction of Fouling in Membrane Bioreactors
Authors: Shi Yaoke , Wang Zhiwen , Du Xianjun , Gong Bin , Jegatheesan Veeriah , Haq Izaz Ul
Published: May 2021

Compared to the traditional activated sludge process, the membrane bioreactor (MBR) has several advantages such as the production of high-quality effluent, generation of low excess sludge, smaller footprint requirements, and ease of automatic control of processes. The MBR has a broader prospect of its applications in wastewater treatment and reuse. However, membrane fouling is the biggest obstacle for its wider application. This paper reviews the techniques available to predict fouling in MBR, discusses the problems associated with predicting fouling status using artificial neural networks and mathematical models, summarizes the current state of fouling prediction techniques, and looks into the trends in their development.
Kinetic Analysis of the Transformation from 14M Martensite to L21 Austenite in Ni-Fe-Ga Melt Spun Ribbons
Authors: Manchón-Gordón Alejandro F. , López-Martín Raúl , Ipus Jhon J. , Blázquez Javier S. , Svec Peter , Conde Clara F. , Conde Alejandro
Published: May 2021

In this study, the non-isothermal kinetics of the martensitic transition from 14M modulated martensite to austenite phase in Ni55Fe19Ga26 ribbons obtained by melt-spinning has been analyzed. The proximity of the martensitic transition to room temperature makes it very sensitive to pressure and subtle differences for different pieces of the ribbon (ascribed to stresses stored in the ribbon during its rapid solidification process). Despite the dispersion in the characteristic parameters of the transition, a general behavior is observed with a decreasing activation energy as the heating rate increases due to the nucleation driven character of the transition. It has been shown that a first-order autocatalysis can describe the temperature evolution of the austenite fraction using only two experimental temperatures. Predicted curves are in good agreement with experimental data.
Effect of Molybdenum Content on the Corrosion and Microstructure of Low-Ni, Co-Free Maraging Steels
Authors: Seikh Asiful H. , Halfa Hossam , Soliman Mahmoud S.
Published: May 2021

Molybdenum (Mo) is an important alloying element in maraging steels. In this study, we altered the Mo concentration during the production of four cobalt-free maraging steels using an electroslag refining process. The microstructure of the four forged maraging steels was evaluated to examine phase contents by optical microscopy, scanning electron microscopy (SEM), and X-ray diffraction (XRD) analysis. Additionally, we assessed the corrosion resistance of the newly developed alloys in 3.5% NaCl solution and 1 M H2SO4 solution through potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) techniques. Furthermore, we performed SEM and energy-dispersive spectroscopy (EDS) analysis after corrosion to assess changes in microstructure and Raman spectroscopy to identify the presence of phases on the electrode surface. The microstructural analysis shows that the formation of retained austenite increases with increasing Mo concentrations. It is found from corrosion study that increasing Mo concentration up to 4.6% increased the corrosion resistance of the steel. However, further increase in Mo concentration reduces the corrosion resistance.
Rapid Discrimination and Authentication of Korean Farmstead Mozzarella Cheese through MALDI-TOF and Multivariate Statistical Analysis
Authors: Kandasamy Sujatha , Yoo Jayeon , Yun Jeonghee , Kang Han-Byul , Seol Kuk-Hwan , Ham Jun-Sang
Published: May 2021

Geographical origin and authenticity are the two crucial factors that propel overall cheese perception in terms of quality and price; therefore, they are of great importance to consumers and commercial cheese producers. Herein, we demonstrate a rapid, accurate method for discrimination of domestic and import mozzarella cheeses in the Republic of Korea by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The protein profiles’ data aided by multivariate statistical analysis successfully differentiated farmstead and import mozzarella cheeses according to their geographical location of origin. A similar investigation within domestic samples (farmsteads/companies) also showed clear discrimination regarding the producer. Using the biomarker discovery tool, we identified seven distinct proteins, of which two (m/z 7407.8 and 11,416.6) were specific in farmstead cheeses, acting as potential markers to ensure authentication and traceability. The outcome of this study can be a good resource in building a database for Korean domestic cheeses. This study also emphasizes the combined utility of MALDI-TOF MS and multivariate analysis in preventing fraudulent practices, thereby ensuring market protection for Korean farmstead cheeses.
Dynamics of Fat Oxidation from Sitting at Rest to Light Exercise in Inactive Young Humans
Authors: Calonne Julie , Fares Elie-Jacques , Montani Jean-Pierre , Schutz Yves , Dulloo Abdul , Isacco Laurie
Published: May 2021

Societal erosion of daily life low-level physical activity has had a great influence on the obesity epidemic. Given that low fat oxidation is also a risk factor for obesity, we investigated, in a repeated measures design, the dynamics of fat oxidation from a resting state to a light-intensity leg cycling exercise (0–50 watts) in inactive, healthy young adults. Using indirect calorimetry, energy expenditure and the respiratory quotient (RQ) were assessed in a sitting posture at rest and during a cycling exercise in 35 subjects (20 women). The rate of perceived exhaustion (RPE) was assessed using the Borg Scale. During graded leg cycling, the mean RPE did not exceed values corresponding to the exercise being perceived as ‘light’. However, analysis of individual data at 50 watts revealed two distinct subgroups among the subjects: those having RPE values corresponding to the exercise being perceived as ‘very light to light’ and showing no increase in RQ relative to resting levels, as opposed to an increase in RQ in those who perceived the exercise as being ‘somewhat hard to hard’ (p < 0.001). Our study in inactive individuals showing that high fat oxidation was maintained during ‘light-perceived’ physical activity reinforced the potential importance of light physical activity in the prevention of obesity.
Enhancing Metabolic Imaging of Energy Metabolism in Traumatic Brain Injury Using Hyperpolarized [1-13C]Pyruvate and Dichloroacetate
Authors: DeVience Stephen J. , Lu Xin , Proctor Julie L. , Rangghran Parisa , Medina Juliana A. , Melhem Elias R. , Gullapalli Rao P. , Fiskum Gary , Mayer Dirk
Published: May 2021

Hyperpolarized magnetic resonance spectroscopic imaging (MRSI) of [1-13C]pyruvate metabolism has previously been used to assess the effects of traumatic brain injury (TBI) in rats. Here, we show that MRSI can be used in conjunction with dichloroacetate to measure the phosphorylation state of pyruvate dehydrogenase (PDH) following mild-to-moderate TBI, and that measurements can be repeated in a longitudinal study to monitor the course of injury progression and recovery. We found that the level of 13C-bicarbonate and the bicarbonate-to-lactate ratio decreased on the injured side of the brain four hours after injury and continued to decrease through day 7. Levels recovered to normal by day 28. Measurements following dichloroacetate administration showed that PDH was inhibited equally by PDH kinase (PDK) on both sides of the brain. Therefore, the decrease in aerobic metabolism is not due to inhibition by PDK.
General Unified Microbiome Profiling Pipeline (GUMPP) for Large Scale, Streamlined and Reproducible Analysis of Bacterial 16S rRNA Data to Predicted Microbial Metagenomes, Enzymatic Reactions and Metabolic Pathways
Authors: Murovec Boštjan , Deutsch Leon , Stres Blaž
Published: May 2021

General Unified Microbiome Profiling Pipeline (GUMPP) was developed for large scale, streamlined and reproducible analysis of bacterial 16S rRNA data and prediction of microbial metagenomes, enzymatic reactions and metabolic pathways from amplicon data. GUMPP workflow introduces reproducible data analyses at each of the three levels of resolution (genus; operational taxonomic units (OTUs); amplicon sequence variants (ASVs)). The ability to support reproducible analyses enables production of datasets that ultimately identify the biochemical pathways characteristic of disease pathology. These datasets coupled to biostatistics and mathematical approaches of machine learning can play a significant role in extraction of truly significant and meaningful information from a wide set of 16S rRNA datasets. The adoption of GUMPP in the gut-microbiota related research enables focusing on the generation of novel biomarkers that can lead to the development of mechanistic hypotheses applicable to the development of novel therapies in personalized medicine.
The Effects of Plant-Associated Bacterial Exopolysaccharides on Plant Abiotic Stress Tolerance
Authors: Morcillo Rafael , Manzanera Maximino
Published: May 2021

Plant growth-promoting rhizobacteria (PGPR) are beneficial soil microorganisms that can stimulate plant growth and increase tolerance to biotic and abiotic stresses. Some PGPR are capable of secreting exopolysaccharides (EPS) to protect themselves and, consequently, their plant hosts against environmental fluctuations and other abiotic stresses such as drought, salinity, or heavy metal pollution. This review focuses on the enhancement of plant abiotic stress tolerance by bacterial EPS. We provide a comprehensive summary of the mechanisms through EPS to alleviate plant abiotic stress tolerance, including salinity, drought, temperature, and heavy metal toxicity. Finally, we discuss how these abiotic stresses may affect bacterial EPS production and its role during plant-microbe interactions.
Effect of Plasma-Enhanced Atomic Layer Deposition on Oxygen Overabundance and Its Influence on the Morphological, Optical, Structural, and Mechanical Properties of Al-Doped TiO2 Coating
Authors: Chiappim William , Testoni Giorgio , Miranda Felipe , Fraga Mariana , Furlan Humber , Saravia David Ardiles , Sobrinho Argemiro da Silva , Petraconi Gilberto , Maciel Homero , Pessoa Rodrigo
Published: May 2021

The chemical, structural, morphological, and optical properties of Al-doped TiO2 thin films, called TiO2/Al2O3 nanolaminates, grown by plasma-enhanced atomic layer deposition (PEALD) on p-type Si <100> and commercial SLG glass were discussed. High-quality PEALD TiO2/Al2O3 nanolaminates were produced in the amorphous and crystalline phases. All crystalline nanolaminates have an overabundance of oxygen, while amorphous ones lack oxygen. The superabundance of oxygen on the crystalline film surface was illustrated by a schematic representation that described this phenomenon observed for PEALD TiO2/Al2O3 nanolaminates. The transition from crystalline to amorphous phase increased the surface hardness and the optical gap and decreased the refractive index. Therefore, the doping effect of TiO2 by the insertion of Al2O3 monolayers showed that it is possible to adjust different parameters of the thin-film material and to control, for example, the mobility of the hole-electron pair in the metal-insulator-devices semiconductors, corrosion protection, and optical properties, which are crucial for application in a wide range of technological areas, such as those used to manufacture fluorescence biosensors, photodetectors, and solar cells, among other devices.
Fault Detection and Isolation of the Multi-Sensor Inertial System
Authors: Liang Hao , Guo Yu , Zhao Xingfa
Published: May 2021

In order to solve the problem that the generalized likelihood test method cannot isolate the single fault of the four-gyro system and the double faults of the six-gyro system, a fault detection and isolation method combining the generalized likelihood test method with the residual error of the metabolism grey model is presented. The problem of isolating the single fault of the four-gyro system and the double faults of the six-gyro system using the generalized likelihood test method is analyzed. The method and process of fault detection and isolation are designed. The validity of the method presented in this paper is verified by simulation tests of the single fault of the four-gyro system and the double faults of the six-gyro system. By comparing the isolation performance with the generalized likelihood test method, it is proved that the isolation performance of the method proposed in this paper is better than that of the generalized likelihood test method. The method mentioned in this paper can effectively realize fault detection and isolation of the multi-gyro system and improve the inertial system’s reliability.
A Novel Modified Super-Twisting Control Augmented Feedback Linearization for Wearable Robotic Systems Using Time Delay Estimation
Authors: Brahmi Brahim , El Bojairami Ibrahim , Ahmed Tanvir , Swapnil Asif , AssadUzZaman Mohammad , Wang Inga , McGonigle Erin , Rahman Mohammad
Published: May 2021

The research presents a novel controller designed for robotic systems subject to nonlinear uncertain dynamics and external disturbances. The control scheme is based on the modified super-twisting method, input/output feedback linearization, and time delay approach. In addition, to minimize the chattering phenomenon and ensure fast convergence to the selected sliding surface, a new reaching law has been integrated with the control law. The control scheme aims to provide high performance and enhanced accuracy via limiting the effects brought by the presence of uncertain dynamics. Stability analysis of the closed-loop system was conducted using a powerful Lyapunov function, showing finite time convergence of the system’s errors. Lastly, experiments shaping rehabilitation tasks, as performed by healthy subjects, demonstrated the controller’s efficiency given its uncertain nonlinear dynamics and the external disturbances involved.
Recent Progress on Bioresorbable Passive Electronic Devices and Systems
Authors: Wei Zhihuan , Xue Zhongying , Guo Qinglei
Published: May 2021

Bioresorbable electronic devices and/or systems are of great appeal in the field of biomedical engineering due to their unique characteristics that can be dissolved and resorbed after a predefined period, thus eliminating the costs and risks associated with the secondary surgery for retrieval. Among them, passive electronic components or systems are attractive for the clear structure design, simple fabrication process, and ease of data extraction. This work reviews the recent progress on bioresorbable passive electronic devices and systems, with an emphasis on their applications in biomedical engineering. Materials strategies, device architectures, integration approaches, and applications of bioresorbable passive devices are discussed. Furthermore, this work also overviews wireless passive systems fabricated with the combination of various passive components for vital sign monitoring, drug delivering, and nerve regeneration. Finally, we conclude with some perspectives on future fundamental studies, application opportunities, and remaining challenges of bioresorbable passive electronics.
Novel Flexible PVDF-TrFE and PVDF-TrFE/ZnO Pressure Sensor: Fabrication, Characterization and Investigation
Authors: Liu Mingran , Liu Yang , Zhou Limin
Published: May 2021

With the development of human healthcare devices, smart sensors, e-skins, and pressure sensors with outstanding sensitivity, flexibility, durability and biocompatibility have attracted more and more attention. In this paper, to develop a novel flexible pressure sensor with high sensitivity, different poly (vinylidene fluoride-trifluoroethylene) (PVDF-TrFE)-based composite membranes were fabricated, characterized and tested. To improve the β-phase crystallinity and piezoelectricity of the membranes, and for the purpose of comparison, nano ZnO particles with different concentrations (99:1, 9:1 in a weight ratio of PVDF-TrFE to ZnO) were, respectively added into PVDF-TrFE polymer acting as a nucleating agent and dielectric material. To facilitate the formation of β-phase crystal, the membranes were fabricated by electrospinning method. After the electrospinning, an annealing process was conducted to the fabricated membranes to increase the size and content of β-phase crystal. Then, the fabricated PVDF-TrFE membranes, acting as the core sensing layer, were, respectively built into multiple prototype sensors in a sandwich structure. The sensitivity of the prototype sensors was tested by an auto-clicker. The stimulation of the auto-clicker on the prototype sensors generated electrical signals, and the electrical signals were collected by a self-built testing platform powered by LabVIEW. As a result, combining the addition of ZnO nanofillers and the annealing process, a highly sensitive pressure sensor was fabricated. The optimal peak-to-peak voltage response generated from the prototype sensor was 1.788 V which shows a 75% increase compared to that of the pristine PVDF-TrFE sensor. Furthermore, a human pulse waveform was captured by a prototype sensor which exhibits tremendous prospects for application in healthcare devices.
On-Line Compensation for Micromilling of High-Aspect-Ratio Straight Thin Walls
Authors: Li Yang , Cheng Xiang , Ling Siying , Zheng Guangming
Published: May 2021

In order to improve the machining quality and reduce the dimensional errors of micro high-aspect-ratio straight thin walls, the on-line cutting parameter compensation device has been introduced and corresponding micromilling processes have been investigated. Layered milling strategies for the micromilling of thin walls have been modeled and simulated for thin walls with different thicknesses based on the finite element method. The radial cutting parameters compensation method is adopted to compensate the thin wall deformation by raising the radial cutting parameters since the thin wall deformation make the actual radial cutting parameters smaller than nominal ones. The experimental results show that the dimensional errors of the thin wall have been significantly reduced after the radial cutting parameter compensation. The average relative dimensional error is reduced from 6.9% to 2.0%. Moreover, the fabricated thin walls keep good shape formation. The reduction of the thin wall dimensional error shows that the simulation results are reliable, which has important guiding significance for the improvement of thin wall machining quality, especially the improvement of dimensional accuracy. The experimental results show that the developed device and the machining strategy can effectively improve the micromilling quality of thin walls.