Light microscopy of Pakistani Berberis leaf cuticles and its taxonomic implications

Taxonomy of the genus Berberis is quite complex, due to overlapping morphological characters, making it very difficult to differentiate the species within the genus. In order to resolve this taxonomic complexity, the foliar anatomy of 10 Berberis L. species was carried out, for the first time from Pakistan, using light microscopy (LM). Significant variation in terms of epidermal cells shape, size, cell wall pattern, and stomata type was observed. B. baluchistanica has the largest epidermal cells, Adaxial: length = 45–(53.9 ± 3.6)–62.5 μm; and width = 22.5–(26.3 ± 1.3)–30 μm; Abaxial: length = 37.5–(43.25 ± 2.5)–50 μm; and width = 20–(22.6 ± 0.8)–25. The highest number of stomata was observed in B. glaucocarpa as 62 on the abaxial surface while the lowest number of stomata was recorded in B. baluchistanica as 8 on the adaxial surface. Of 10 investigated species, 6 possess anomocytic type stomata, while 2 species that is, B. aitchisonii and B. parkeriana have both anomocytic and anisocytic stomata while B. baluchistanica and B. calliobotrys have only paracytic type stomata. The highest number of cells per unit area was present on the adaxial surface of B. calliobotrys ranging from 245–(252.4)–260 followed by B. parkeriana with 209–(227.8)–250 on the abaxial surface. Stomatal index (SI) also varied considerably and was the lowest (2.6) percentage in B. baluchistanica and highest (31.9) percentage in B. kunawurensis. A taxonomic key based on micro‐morphological characters is provided for species identification.     

Performance comparison of differential evolution techniques on optimization of feeding profile for an industrial scale baker’s yeast fermentation process

Differential evolution (DE) is one of the novel evolutionary optimization methods used for solving the problems that consist of nondifferentiable, nonlinear and multi-objective functions. In this presented work, the classical DE technique and its various versions, such as opposition based on differential evolution (ODE), adaptive differential evolution (ADE), adaptive opposition based on differential evolution (AODE) which is an advanced version of ODE, are presented to determine the optimal feeding flow profile of an industrial scale fed-batch baker’s yeast fermentation process. The main objective in any fed-batch fermentation process optimization is both to maximize the amount of the biomass at the end of the process and to minimize the ethanol formation during the process. Four different cases regarding the initial condition of the fermentation process were considered so as to evaluate the performances of proposed algorithms. Besides, two strategies of mutation and crossover operators, which are the most popular in DE’s applications, were utilized for performance comparison tests. The influence of initial seed value, initial condition of the process, and both of the mutation and crossover strategies have been investigated for all the different classic, opposition-based, self-adaptive and adaptive opposition-based mechanisms. To demonstrate the performance comparison of the of DE’s techniques, the experimental data collected from the fermentor with volume of 100 m³ are presented with the optimization results obtained by using all the interested DE techniques for the same initial conditions.     

Effect of Reciproc blue,XP‐endo shaper,and WaveOne gold instruments on dentinal microcrack formation: A micro‐computed tomographic evaluation

The purpose of this study was to evaluate and compare the effect of Reciproc Blue (RPCB), XP‐endo Shaper (XPS), and WaveOne Gold (WOG) single‐files on dentinal microcrack formation using micro‐computed tomography (micro‐CT). Twenty‐four mesial roots (24 mesio‐buccal and 24 mesio‐lingual canals) of mandibular molar teeth were prepared using RPCB, XPS, and WOG files (n = 8/each group). The samples were scanned with micro‐CT in the pre‐ and post‐preparation. Then, before preparation and after preparation cross‐sectional images of the teeth were evaluated to detect the presence of microcracks. For each group, the number of microcracks was calculated as a percentage rate. The data were statistically analyzed using McNemar at 5% significance level (p < .05). Dentinal microcracks were observed in 25.99% (2,103 of 7,813), 31.99% (2,482 of 7,758), and 36.66% (2,836 of 7,731) of cross‐sectional images of the XPS, WOG, and RPCB groups, respectively. In all the groups, all the dentinal microcracks seen in the post‐treatment cross‐sectional images were present in the corresponding pre‐treatment images. Within the limitations of this study, the XPS, WOG, and RPCB files did not cause new dentinal microcrack formation or propagation of existing dentinal microcracks.     

Plasmodium species aware based quantification of malaria parasitemia in light microscopy thin blood smear

Malaria is a serious worldwide disease, caused by a bite of a female Anopheles mosquito. The parasite transferred into complex life round in which it is grown and reproduces into the human body. The detection and recognition of Plasmodium species are possible and efficient through a process called staining (Giemsa). The staining process slightly colorizes the red blood cells (RBCs) but highlights Plasmodium parasites, white blood cells and artifacts. Giemsa stains nuclei, chromatin in blue tone and RBCs in pink color. It has been reported in numerous studies that manual microscopy is not a trustworthy screening technique when performed by nonexperts. Malaria parasites host in RBCs when it enters the bloodstream. This paper presents segmentation of Plasmodium parasite from the thin blood smear points on region growing and dynamic convolution based filtering algorithm. After segmentation, malaria parasite classified into four Plasmodium species: Plasmodium falciparum, Plasmodium ovale, Plasmodium vivax, and Plasmodium malaria. The random forest and K‐nearest neighbor are used for classification base on local binary pattern and hue saturation value features. The sensitivity for malaria parasitemia (MP) is 96.75% on training and testing of the proposed approach while specificity is 94.59%. Beside these, the comparisons of the two features are added to the proposed work for classification having sensitivity is 83.60% while having specificity is 94.90% through random forest classifier based on local binary pattern feature.     

Mesh stiffness analysis of beveloid gears for the rotating vector transmission

Journal of Mechanical Science and Technology - This paper investigates the meshing stiffness of beveloid gears in the beveloid rotate vector (BRV) transmission. It is a new kind of transmission...     

Machine learning for post-traumatic stress disorder identification utilizing resting-state functional magnetic resonance imaging

Early detection of post-traumatic stress disorder (PTSD) is essential for proper treatment of the patients to recover from this disorder. The aligned purpose of this study was to investigate the performance deviations in regions of interest (ROI) of PTSD than the healthy brain regions, to assess interregional functional connectivity and applications of machine learning techniques to identify PTSD and healthy control using resting-state functional magnetic resonance imaging (rs-fMRI). The rs-fMRI data of 10 ROI was extracted from 14 approved PTSD subjects and 14 healthy controls. The rs-fMRI data of the selected ROI were used in ANOVA to measure performance level and Pearson's correlation to investigate the interregional functional connectivity in PTSD brains. In machine learning approaches, the logistic regression, K-nearest neighbor (KNN), support vector machine (SVM) with linear, radial basis function, and polynomial kernels were used to classify the PTSD and control subjects. The performance level in brain regions of PTSD deviated as compared to the regions in the healthy brain. In addition, significant positive or negative functional connectivity was observed among ROI in PTSD brains. The rs-fMRI data have been distributed in training, validation, and testing group for maturity, implementation of machine learning techniques. The KNN and SVM with radial basis function kernel were outperformed for classification among other methods with high accuracies (96.6%, 94.8%, 98.5%) and (93.7%, 95.2%, 99.2%) to train, validate, and test datasets, respectively. The study's findings may provide a guideline to observe performance and functional connectivity of the brain regions in PTSD and to discriminate PTSD subject using only the suggested algorithms.     

A High-Resolution Cellular Automata Traffic Simulation Model with Application in a Freeway Traffic Information System

Abstract: In this article, we describe a novel traffic information system for the freeway traffic in North Rhine‐Westphalia (NRW), the most populous German state. It consists of more than 4,000 loop detectors, a simulator, and a microscopic and macroscopic graphical interface. These should be considered as “data input,”“data processing,” and “data output,” respectively. First, we discuss the loop detectors: Their mode of operation, how and where they are located, and the quality of their measurements. Next, we describe the simulator, especially its high‐resolution cellular automaton model of traffic flows, the abstraction of the road network into tracks and nodes, how the data from the loop detectors is integrated, and we give some details on an efficient implementation of the dynamics. Finally, we discuss the graphical interfaces, which display the simulated traffic states, and we give some concluding remarks. In particular, we present the traffic information web page http://www.autobahn.nrw.de , where the simulated actual traffic state on the freeway network in NRW can be sighted.     

Determination of rock type and moisture content in flysch using TLS intensity in the Elerji quarry (south-west Slovenia)

Bulletin of Engineering Geology and the Environment - Terrestrial laser scanning (TLS) was performed in tectonically undisturbed flysch in the Elerji quarry (south-west Slovenia), which represents...     

An interpretation of the changes in demographic behaviour at a sub-national level using spatial measures in post-socialist countries: A case study of the Czech Republic and Slovakia

The transformation of fertility and family behaviour in post-socialist countries was quick and the changes were striking. An account of the changes is the subject of dispute and the mechanisms have still not been explained in a fully satisfying manner. Relatively little attention has been paid to the changes in spatial aspects concerning the broadening of changes in family behaviour. The aim of this paper is to answer the question as to whether changes spread stochastically in post-socialist countries or if there are obvious spatial patterns. The study tries to answer the questions whether there are any cores of changes which may be understood as innovations, if there is any spatial clustering and if the extent is hierarchically arranged.     

Optical,DC and AC electrical investigations of 4-hydroxy coumarin molecule as an organic Schottky diode

The current–voltage (I–V) and optical characteristics of 4-hydroxy coumarin Schottky diode were investigated. The conventional methods related with device were used to extract the various diode parameters. From dielectric study low dielectric constant and loss was observed. From its optical study, an indirect allowed transition is shown by this compound. The optical band gap (E _g ) was found to be around 3.78 eV. The observed properties shown by this molecule give a bright opportunity to explore its application for different organic devices.