bluuebunny/crossref_metadata_2025_split huggingface dataset:
A patient-independent classification system for onset detection of seizures
Authors: Ansari Abdul Quaiyum , Sharma Priyanka , Tripathi Manjari 
Published: February 2021

AbstractSeizures are the most common brain dysfunction. Electroencephalography (EEG) is required for their detection and treatment initially. Studies show that if seizures are detected at their early stage, instant and effective treatment can be given to the patients. In this paper, an automated system for seizure onset detection is proposed. As the power spectrum of normal person’s EEG and EEG of someone with epilepsy is plotted, powers present at different frequencies are found to be different for both. The proposed algorithm utilizes this frequency discrimination property of EEG with some statistical features to detect the seizure onset using simple linear classifier. The tests conducted on EEG data of 30 patients, obtained from the two different datasets, show the presence of all 183 seizures with mean latency of 0.9 s and 1.02 false detections per hour. The main contribution of this study is the use of simple features and classifier in the field of seizures onset detection that reduces the computational complexity of the algorithm. Also, the classifier used is patient independent. This patient independency in the classification system would be helpful in the implementation of the proposed algorithm to develop an online detection system.
Qualitative and semi-quantitative assessment of anthocyanins in Tibetan hulless barley from different geographical locations by UPLC-QTOF-MS and their antioxidant capacities
Authors: Zhang Tangwei , Ma Jialin , Wu Xuelian , Hao Zhihua , Dun Ci , Chen Chen 
Published: February 2021

Abstract
Tibetan hulless barley (“qingke” in Chinese) is a valuable food in Tibet. Purple qingke (PQK) and black qingke (BQK), two special pigmented types of hulless barley, have traditionally been widely cultivated and consumed in Tibet for thousands of years. The composition and contents of anthocyanins of two cultivars are unknown. This study aimed to explore the composition and contents of anthocyanins of two cultivars and their antioxidant capacities. Six anthocyanins were identified by ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry from barley, most of the anthocyanins were acylated by malonyl group. The total anthocyanin contents ranged from 141 to 2,304 μg/g in PQK and from 248.7 to 2902.9 μg/g in BQK. Furthermore, qingke has strong antioxidant activity against DPPH, ABTS˙+, and FRAP. Qingke may be useful for treating or preventing diseases caused by the overproduction of radicals.
Overview of the major classes of new psychoactive substances, psychoactive effects, analytical determination and conformational analysis of selected illegal drugs
Authors: Lukić Vera , Micić Ružica , Arsić Biljana , Nedović Bojan , Radosavljević Živana 
Published: February 2021

Abstract
The misuse of psychoactive substances is attracting a great deal of attention from the general public. An increase use of psychoactive substances is observed among young people who do not have enough awareness of the harmful effects of these substances. Easy access to illicit drugs at low cost and lack of effective means of routine screening for new psychoactive substances (NPS) have contributed to the rapid increase in their use. New research and evidence suggest that drug use can cause a variety of adverse psychological and physiological effects on human health (anxiety, panic, paranoia, psychosis, and seizures). We describe different classes of these NPS drugs with emphasis on the methods used to identify them and the identification of their metabolites in biological specimens. This is the first review that thoroughly gives the literature on both natural and synthetic illegal drugs with old known data and very hot new topics and investigations, which enables the researcher to use it as a starting point in the literature exploration and planning of the own research. For the first time, the conformational analysis was done for selected illegal drugs, giving rise to the search of the biologically active conformations both theoretically and using lab experiments.
Influence of nanoscale-modified apatite-type calcium phosphates on the biofilm formation by pathogenic microorganisms
Authors: Grynyuk Iryna I. , Vasyliuk Olga M. , Prylutska Svitlana V. , Strutynska Nataliia Yu. , Livitska Oksana V. , Slobodyanik Mykola S. 
Published: February 2021

Abstract
Nanoparticles (25–50 nm) of chemically modified calcium phosphates Ca10−x−y
M
ii

x
Na
y
(PO4)6−z
(CO3)
z
(OH)2 (M
ii
– Cu2+, Zn2+) were synthesized via a wet precipitation method at room temperature. The Fourier-transform infrared spectroscopy data confirmed the partial substitution of

PO

4

3
−

{\text{PO}}_{4}^{3-}

→

CO

3

2
−

{\text{CO}}_{3}^{2-}

(B-type) in apatite-type structure. The influence of prepared phosphates on biofilm formation by pathogenic microorganisms was investigated. It was found that the samples Na+,

CO

3

2
−

{\text{CO}}_{3}^{2-}

-hydroxyapatite (HAP) and Na+, Zn2+,

CO

3

2
−

{\text{CO}}_{3}^{2-}

-HAP (5–20 mM) had the highest inhibitory effect on biofilm formation by Staphylococcus aureus strains. The sample Na+,

CO

3

2
−

{\text{CO}}_{3}^{2-}

-HAP had the slight influence on the formation of the biofilm by Pseudomonas aeruginosa, while for the samples Na+, Cu2+,

CO

3

2
−

{\text{CO}}_{3}^{2-}

-HAP and Na+, Zn2+,

CO

3

2
−

{\text{CO}}_{3}^{2-}

-HAP such an effect was not detected. According to transmission electron microscopy data, a correlation between the activity of synthesized apatite-related modified calcium phosphates in the processes of biofilm formation and their ability to adhere to the surface of bacterial cells was established. The prepared samples can be used for the design of effective materials with antibacterial activity for medicine.
Defects in Active Nematics – Algorithms for Identification and Tracking
Authors: Wenzel Dennis , Nestler Michael , Reuther Sebastian , Simon Maximilian , Voigt Axel 
Published: February 2021

Abstract
The growing interest in active nematics and the emerging evidence of the relevance of topological defects in biology asks for reliable data analysis tools to identify, classify and track such defects in simulation and microscopy data. We here provide such tools and demonstrate on two examples, on an active turbulent state in an active nematodynamic model and on emerging nematic order in a multi-phase field model, the possibility to compare statistical data on defect velocities with experimental results. The considered tools, which are physics based and data driven, are compared with each other.
Contractive Local Adaptive Smoothing Based on Dörfler’s Marking in A-Posteriori-Steeredp-Robust Multigrid Solvers
Authors: Miraçi Ani , Papež Jan , Vohralík Martin 
Published: February 2021

AbstractIn this work, we study a local adaptive smoothing algorithm for a-posteriori-steeredp-robust multigrid methods. The solver tackles a linear system which is generated by the discretization of a second-order elliptic diffusion problem using conforming finite elements of polynomial orderp≥1{p\geq 1}. After one V-cycle (“full-smoothing” substep) of the solver of [A. Miraçi, J. Papež, and M. Vohralík, A-posteriori-steeredp-robust multigrid with optimal step-sizes and adaptive number of smoothing steps, SIAM J. Sci. Comput. 2021, 10.1137/20M1349503], we dispose of a reliable, efficient, and localized estimation of the algebraic error. We use this existing result to develop our new adaptive algorithm: thanks to the information of the estimator and based on a bulk-chasing criterion, cf. [W. Dörfler, A convergent adaptive algorithm for Poisson’s equation, SIAM J. Numer. Anal. 33 1996, 3, 1106–1124], we mark patches of elements with increased estimated error on all levels. Then, we proceed by a modified and cheaper V-cycle (“adaptive-smoothing” substep), which only applies smoothing in the marked regions. The proposed adaptive multigrid solver picks autonomously and adaptively the optimal step-size per level as in our previous work but also the type of smoothing per level (weighted restricted additive or additive Schwarz) and concentrates smoothing to marked regions with high error. We prove that, under a numerical condition that we verify in the algorithm, each substep (full and adaptive) contracts the errorp-robustly, which is confirmed by numerical experiments. Moreover, the proposed algorithm behaves numerically robustly with respect to the number of levels as well as to the diffusion coefficient jump for a uniformly-refined hierarchy of meshes.
Sensor Number Optimization Using Neural Network for Ankle Foot Orthosis Equipped with Magnetorheological Brake
Authors: Adiputra Dimas , Azizi Abdul Rahman Mohd , Bahiuddin Irfan , Ubaidillah  , Imaduddin Fitrian , Nazmi Nurhazimah 
Published: February 2021

Abstract
A passive controlled ankle foot orthosis (PICAFO) used a passive actuator such as Magnetorheological (MR) brake to control the ankle stiffness. The PICAFO used two kinds of sensors, such as Electromyography (EMG) signal and ankle position (two inputs) to determine the amount of stiffness (one output) to be generated by the MR brake. As the overall weight and design of an orthotic device must be optimized, the sensor numbers on PICAFO wanted to be reduced. To do that, a machine learning approach was implemented to simplify the previous stiffness function. In this paper, Non-linear Autoregressive Exogeneous (NARX) neural network were used to generate the simplified function. A total of 2060 data were used to build the network with detail such as 1309 training data, 281 validation data, 281 testing data 1, and 189 testing data 2. Three training algorithms were used such as Levenberg-Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient. The result shows that the function can be simplified into one input (ankle position) – one output (stiffness). Optimized result was shown by the NARX neural network with 15 hidden layers and trained using Bayesian Regularization with delay 2. In this case, the testing data shows R-value of 0.992 and MSE of 19.16.
Selection of a workpiece clamping system for computer-aided subtractive manufacturing of geometrically complex medical models
Authors: Wojnarowska Wiktoria , Kwolek Maciej , Miechowicz Sławomir 
Published: February 2021

Abstract
Physical models of anatomical structures can be made using Additive Manufacturing (AM) or Subtractive Manufacturing (SM). The advantage of subtractive techniques over additive ones is the possibility of maintaining the homogeneity and consistency of the processed material, which is extremely important in the case of medical devices. Currently, a geometrically complex medical model can be made even on a simple, 3-axis CNC machine tool. However, often the semi-finished product must be machined in at least two clamping configurations. The aim of the work is to present the method of fixing a workpiece in the process of subtractive production of geometrically complex medical objects on the example of skull bone prostheses. The paper discusses the use of two clamping systems for machining such models. It presents the process of subtractive production of bone prostheses models fitted to the defect of the skull bone with the use of the proposed methods of fixing the workpiece. The result of the work are two models of the skull bone prosthesis. A more complex model was analysed in terms of the accuracy of geometry reproduction. The research confirmed the usefulness of the proposed clamping systems for the preparation of medical models of geometrically complex anatomical structures.
Vocational Student's Attitude and Response Towards Experiential Learning in Mechanical Engineering
Authors: Fajar Pamungkas Stephanus , Widiastuti Indah , Suharno  
Published: February 2021

Abstract
This study evaluated the use of an experiential learning design for vocational education in mechanical engineering. The research objective is to analyze students’ attitudes and responses after participating in learning activities using a worksheet designed according to Kolb's stages by considering Felder-Silverman's student learning styles. This research was conducted using a case study research employing qualitative data analysis. The data were collected using a purposive random sampling technique with 28 respondents in a 10th grade. The datawere analyzed using descriptive qualitative analysis. The experiential learning activities were carried out concrete experience, reflective observations, abstract conceptualization, and active experimentation. It is shown that students have a positive attitude and response. Experiential activities help students in learning Basic of Mechanical Engineering and they enjoy participating in the learning activities. Experiential learning activities are considered to be fun, interesting, and easy to be understood. The students could relate the course material to real-life situations, which may benefit the students to enhance learning and connect the knowledge they learned to their own experiences. It is suggested that the experiential design is effectively used and could explore the relationship between learning theory and practice in Vocational High School.
Plastic forming processes of transverse non-homogeneous composite metallic sheets
Authors: Davidi Gal 
Published: February 2021

Abstract
In this work an analysis of the radial stress and velocity fields is performed according to the J
2 flow theory for a rigid/perfectly plastic material. The flow field is used to simulate the forming processes of sheets. The significant achievement of this paper is the generalization of the work by Nadai & Hill for homogenous material in the sense of its yield stress, to a material with general transverse non-homogeneity. In Addition, a special un-coupled form of the system of equations is obtained where the task of solving it reduces to the solution of a single non-linear algebraic differential equation for the shear stress. A semi-analytical solution is attained solving numerically this equation and the rest of the stresses term together with the velocity field is calculated analytically. As a case study a tri-layered symmetrical sheet is chosen for two configurations: soft inner core and hard coating, hard inner core and soft coating.
The main practical outcome of this work is the derivation of the validity limit for radial solution by mapping the “state space” that encompasses all possible configurations of the forming process. This configuration mapping defines the “safe” range of configurations parameters in which flawless processes can be achieved. Several aspects are researched: the ratio of material's properties of two adjacent layers, the location of layers interface and friction coefficient with the walls of the dies.
Forced convection heat transfer study of a blunt-headed cylinder in non-Newtonian power-law fluids
Authors: Kaur Jaspinder , Melnik Roderick , Tiwari Anurag Kumar 
Published: February 2021

AbstractIn this present work, forced convection heat transfer from a heated blunt-headed cylinder in power-law fluids has been investigated numerically over the range of parameters, namely, Reynolds number (Re): 1–40, Prandtl number (Pr): 10–100 and power-law index (n): 0.3–1.8. The results are expressed in terms of local parameters, like streamline, isotherm, pressure coefficient, and local Nusselt number and global parameters, like wake length, drag coefficient, and average Nusselt number. The length of the recirculation zone on the rear side of the cylinder increases with the increasing value of Re andn. The effect of the total drag coefficient acting on the cylinder is seen to be higher at the low value of Re and its effect significant in shear-thinning fluids (n < 1). On the heat transfer aspect, the rate of heat transfer in fluids is increased by increasing the value of Re and Pr. The effect of heat transfer is enhanced in shear-thinning fluids up to ∼ 40% and it impedes it’s to ∼20% shear-thickening fluids. In the end, the numerical results of the total drag coefficient and average Nusselt number (in terms ofJH−factor) have been correlated by simple expression to estimate the intermediate value for the new application.
Predictive model development and simulation of photobioreactors for algal biomass growth estimation
Authors: Banerjee Nilanjana 
Published: February 2021

Abstract
In the current scenario of energy requirement and the commercialization aspect of algal biofuel and biomass, it is important that means of predicting the production be available. In this paper, the mathematical models are developed for the tubular, bubble column and airlift photobioreactors to predict the productivity of the algal biomass. A modified Monod kinetic equation, incorporating the effect of nutrient and CO2 concentrations, light availability and oxygen built-up, is used to the estimate specific growth rate of the biomass. The light availability inside the reactor is defined in terms of the modified Beer–Lambert’s law as a function of distance from the surface where light is incident and the cell mass concentration. This allows a more accurate measurement of the shading effect. The equations are solved for different reactor types and their estimated productivities are successfully validated against values available in published literature. The model predicts comparatively better productivity for the tubular reactor (1.5 g/L day) than the bubble column and airlift reactor (1.42 and 1.35 g/L day respectively) because tubular reactor has shorter light/dark cycles and better light availability. The analysis is also done to identify the effect of nutrient, carbon dioxide, light and hydrodynamics on the overall productivity.
Hepatoprotective effects of Quassia amara stem bark against cadmium-induced toxicity in male Wistar rats
Authors: Obembe Olawale O. , Usman Taofeek O. , Raji Yinusa 
Published: February 2021

Abstract

Objectives
The liver is one of the primary biorepositories of cadmium (Cd) and it has been implicated in the pathogenesis of hepatic diseases. Quassia amara stem bark has been reputed to have strong antimalarial, antimicrobial, antiulcerative and amoebicidal properties. This study aims to determine the effects of Q. amara on Cd-induced hepatotoxicity and lipid profile in male Wistar rats.

Methods
The animals were divided into three groups of five animals each. Group 1 served as control while group 2 received Cd (5 mg/kg) for 4 weeks. Prior to Cd treatment, group 3 was treated with Q. amara extract (200 mg/kg) for 2 weeks and received the Q. amara and Cd simultaneously for 4 weeks.

Results
Cadmium caused significant increase in serum total cholesterol and low-density lipoprotein (LDL) as well as increased hepatic malondialdehyde (MDA) when compared with the control group. On the other hand, Cd caused a decrease in serum high-density lipoprotein (HDL) and hepatic superoxide dismutase (SOD) when compared with control. However, treatment with Q. amara prevented Cd-induced changes in the lipid profile, augmented Cd-induced decline in SOD and also ameliorated the Cd-induced increase in MDA. Catalase level was however comparable across the groups.

Conclusions

Q. amara ameliorated the Cd-induced damage to liver by preventing dyslipidemia and oxidative damage in the hepatic tissue.
Recognition of facial expression of fetuses by artificial intelligence (AI)
Authors: Miyagi Yasunari , Hata Toshiyuki , Bouno Saori , Koyanagi Aya , Miyake Takahito 
Published: February 2021

Abstract

Objectives
The development of the artificial intelligence (AI) classifier to recognize fetal facial expressions that are considered as being related to the brain development of fetuses as a retrospective, non-interventional pilot study.

Methods
Images of fetal faces with sonography obtained from outpatient pregnant women with a singleton fetus were enrolled in routine conventional practice from 19 to 38 weeks of gestation from January 1, 2020, to September 30, 2020, with completely de-identified data. The images were classified into seven categories, such as eye blinking, mouthing, face without any expression, scowling, smiling, tongue expulsion, and yawning. The category in which the number of fetuses was less than 10 was eliminated before preparation. Next, we created a deep learning AI classifier with the data. Statistical values such as accuracy for the test dataset and the AI confidence score profiles for each category per image for all data were obtained.

Results
The number of fetuses/images in the rated categories were 14/147, 23/302, 33/320, 8/55, and 10/72 for eye blinking, mouthing, face without any expression, scowling, and yawning, respectively. The accuracy of the AI fetal facial expression for the entire test data set was 0.985. The accuracy/sensitivity/specificity values were 0.996/0.993/1.000, 0.992/0.986/1.000, 0.985/1.000/0.979, 0.996/0.888/1.000, and 1.000/1.000/1.000 for the eye blinking, mouthing, face without any expression, scowling categories, and yawning, respectively.

Conclusions
The AI classifier has the potential to objectively classify fetal facial expressions. AI can advance fetal brain development research using ultrasound.
The impact of transfers from neonatal intensive care to paediatric intensive care
Authors: Williams Emma E. , Lee Rebecca , Williams Nia , Deep Akash , Subramaniam Nadisha , Dwarakanathan Buvana , Dassios Theodore , Greenough Anne 
Published: February 2021

Abstract

Objectives
Infants receiving care from neonatal intensive care unit (NICU) can develop chronic problems and be transferred to a paediatric intensive care unit (PICU) for on-going care. There is concern that such infants may take up a large amount of PICU resource, but this is not evidence based. We determined the impact of such transfers.

Methods
We reviewed 10 years of NICU admissions to two tertiary PICUs, which had approximately 12,000 admissions during that period.

Results
Sixty-seven infants, gestational age at birth 34.7 (IQR 27.1–38.8) weeks and postnatal age on transfer 81 (IQR 9–144) days were admitted from NICUs. The median (IQR) length of stay was 12 (4–41) days. The 19 infants born <28 weeks of gestation had a greater median length of stay (32, range IQR 10–93 days) than more mature born infants (7.5, IQR 4–26 days) (p=0.003). The median cost of PICU stay for NICU transfers was £23,800 (range 1,205–1,034,000) per baby. The total cost of care for infants transferred from NICUs was £6,457,955.

Conclusions
Infants transferred from NICUs were a small proportion of PICU admissions but, particularly those born <28 weeks of gestation, had prolonged stays which needs to be considered when determining bed capacity.