The effects of an electromagnetic field on the boundary tissue of the seminiferous tubules of the rat: a light and transmission electron microscope study

Human beings are unavoidably exposed to ambient electromagnetic fields (EMF) generated from various electrical devices and from power transmission lines. Controversy exists about the effects of EMF on various organs. One of the critical issues is that EMF may adversely affect the reproductive system. In order to examine this 30 rat pups were exposed to 50 Hz EMF (non-ionising radiation) during in utero development (approximately 3 weeks) and postnatal life (5 weeks). Groups of exposed rats were subsequently left in an environment free of EMF in order to observe recovery, if any, from the changes induced by EMF on the boundary tissue of the seminiferous tubules. The materials were processed and observed under a light and a transmission electron microscope. In the experimental rats boundary tissue was found disrupted at various layers. This tissue showed infoldings, which were perhaps due to the loss of collagen and reticular fibrils from the inner and outer non-cellular layers. The outer non-cellular layer, which was thinner than that of the control, was stripped away from the myoid cell layer in multiple regions, giving a “blister-like” appearance. The myoid cells showed fewer polyribosomes, pinocytotic vesicles and glycogen granules. Most mitochondria were found to lack cristae. The connections between individual myoid cells were apparently lost. There were signs of recovery in the boundary tissue following withdrawal from EMF exposure. These results suggest that EMF exposure may cause profound changes in the boundary tissue of the seminiferous tubules. Therefore exposure to EMF may result in pathological changes that lead to subfertility and infertility

A study on the dependence of structure of multi-walled carbon nanotubes on acid treatment

In the current research, the role of both concentrated nitric acid and ultrasound waves on oxidation of multi-walled carbon nanotubes (MWNTs) was studied. The functionalized MWCNTs were characterized by transmission electron microscopy (TEM), thermogravimetric analyzer, and Fourier transform infrared spectroscopy (FTIR) techniques. It was found that desirable modifications to MWNTs occurred after acid treatment. Carboxylic acid groups were appeared on the side surfaces of MWNTs. FTIR presented the formation of oxygen-containing groups such as C=O and COOH after modification by concentrated nitric acid. The TEM images showed that the aspect ratio of opened MWCNTs was controlled by both ultrasonic waves and acid treatment time. It was also found that the exposure of about 4 h in nitric acid led to the highest removal of the impurities with the least destructive effect

End-to-End Supervised Multilabel Contrastive Learning

Multilabel representation learning is recognized as a challenging problem that can be associated with either label dependencies between object categories or data-related issues such as the inherent imbalance of positive/negative samples. Recent advances address these challenges from model- and data-centric viewpoints. In model-centric, the label correlation is obtained by an external model designs (e.g., graph CNN) to incorporate an inductive bias for training. However, they fail to design an end-to-end training framework, leading to high computational complexity. On the contrary, in data-centric, the realistic nature of the dataset is considered for improving the classification while ignoring the label dependencies. In this paper, we propose a new end-to-end training framework -- dubbed KMCL (Kernel-based Mutlilabel Contrastive Learning) -- to address the shortcomings of both model- and data-centric designs. The KMCL first transforms the embedded features into a mixture of exponential kernels in Gaussian RKHS. It is then followed by encoding an objective loss that is comprised of (a) reconstruction loss to reconstruct kernel representation, (b) asymmetric classification loss to address the inherent imbalance problem, and (c) contrastive loss to capture label correlation. The KMCL models the uncertainty of the feature encoder while maintaining a low computational footprint. Extensive experiments are conducted on image classification tasks to showcase the consistent improvements of KMCL over the SOTA methods. PyTorch implementation is provided in \url{https://github.com/mahdihosseini/KMCL}

Fabrication of Iron Aluminide Coatings (Fe3Al and FeAl3) on Steel Substrate by Self-Propagating High Temperature Synthesis (SHS) Process

Iron aluminides (Fe3Al and FeAl3) coatings were fabricated on a steel substrate by self-propagating high temperature synthesis (SHS) method. Raw materials, Fe and Al powders, were mixed at two different stoichiometry ratios (3:1 and 1:3). The mixtures and the substrate were placed in a furnace at 950 °C to ignite the SHS process. Coating phases were investigated using X-ray diffraction (XRD) and Energy Dispersive Spectroscopy (EDS). The microstructure of the coatings was analyzed with optical microscopy (OM) and scanning electron microscopy (SEM). The results confirmed that it is possible to produce Fe3Al and FeAl3 coatings on steel substrate using SHS method. In addition, the results show that the coatings were composed of two different phases and their microstructures were non-porous and dense. Wear resistance of the coatings were higher than that of the substrate

A wandering spleen presenting as a pelvic mass: case report and review of the literature

Wandering spleens are rare clinical entities found more commonly in females. We report a young female patient found to harbour a pelvic spleen. The literature regarding this rare ectopia is reviewed. The wandering spleen should be considered in the differential diagnosis of pelvic masses

Recycled cobalt from spent Li-ion batteries as a superhydrophobic coating for corrosion protection of plain carbon steel

A new recycling and film formation scheme is developed for spent Li-ion batteries, which involves the combination of ascorbic-assisted sulfuric leaching and electrodeposition to fabricate a corrosion resistance superhydrophobic coating. The idea behind the simultaneous use of sulfuric and ascorbic is to benefit from the double effect of ascorbic acid, as a leaching reducing agent and as morphological modifier during electrodeposition. Quantum chemical calculations based on the density functional theory are performed to explain the cobalt-ascorbate complexation during the electrocristalization. The optimum parameters for the leaching step are directly utilized in the preparation of an electrolyte for the electrodeposition process, to fabricate a superhydrophobic film with a contact angle of > 150\ub0 on plain carbon steel. The potentiodynamic polarization measurments in 3.5 wt % NaCl showed that boric-pulsed electrodeposited cobalt film has 20-times lower corrosion current density and higher corrosion potential than those on the non-coated substrate

Winter wheat yield prediction using convolutional neural networks from environmental and phenological data

Crop yield forecasting depends on many interactive factors, including crop genotype, weather, soil, and management practices. This study analyzes the performance of machine learning and deep learning methods for winter wheat yield prediction using an extensive dataset of weather, soil, and crop phenology variables in 271 counties across Germany from 1999 to 2019. We proposed a Convolutional Neural Network (CNN) model, which uses a 1-dimensional convolution operation to capture the time dependencies of environmental variables. We used eight supervised machine learning models as baselines and evaluated their predictive performance using RMSE, MAE, and correlation coefficient metrics to benchmark the yield prediction results. Our findings suggested that nonlinear models such as the proposed CNN, Deep Neural Network (DNN), and XGBoost were more effective in understanding the relationship between the crop yield and input data compared to the linear models. Our proposed CNN model outperformed all other baseline models used for winter wheat yield prediction (7 to 14% lower RMSE, 3 to 15% lower MAE, and 4 to 50% higher correlation coefficient than the best performing baseline across test data). We aggregated soil moisture and meteorological features at the weekly resolution to address the seasonality of the data. We also moved beyond prediction and interpreted the outputs of our proposed CNN model using SHAP and force plots which provided key insights in explaining the yield prediction results (importance of variables by time). We found DUL, wind speed at week ten, and radiation amount at week seven as the most critical features in winter wheat yield prediction

Psychometric Properties of the Farsi Version of Posttraumatic Growth Inventory for Children-Revised in Iranian Children with Cancer

Objective: Coping with childhood cancer, as a stressful incident, can lead to a growth in various aspects of the child's life. Therefore, this study aims to validate Posttraumatic Growth Inventory for Children-Revised (PTGI-C-R) in children with cancer. Methods: This methodological research was carried out in referral children hospitals in Tehran. PTGI-C-R was translated and back-translated. Content and face validity were assessed. Confirmatory factor analysis (CFA) was performed on 200 children with inclusion criteria, using LISREL V8.5. Due to the rejection of the model, an exploratory factor analysis (EFA) was done, using SPSS V21. The correlation of posttraumatic growth (PTG) with the variables, i.e., age and gender, was investigated. Results: Some writing changes were made in phrases in the sections concerning face and content validity. CFA rejected the five-factor model due to the undesirable fit indices. Therefore, an EFA was used and the three-factor model was not approved, either despite the statistical appropriateness or due to the lack of similarity between the items loaded on factors. The results also indicated a significant relationship between PTG and age (r = 0.13, P = 0.05). There is no significant relationship between PTG and gender (z = -1.35, P = 0.83). Conclusions: PTGI-C-R does not have desirable psychometric properties in Iranian children with cancer and may not be able to reflect all the aspects of PTG experienced by them. Therefore, it cannot be used as an appropriate scale, and it is necessary to develop and validate a specific tool through a qualitative study. © 2021 Wolters Kluwer Medknow Publications. All rights reserved

Nonequilibrium Steady States of Matrix Product Form: A Solver's Guide

We consider the general problem of determining the steady state of stochastic nonequilibrium systems such as those that have been used to model (among other things) biological transport and traffic flow. We begin with a broad overview of this class of driven diffusive systems - which includes exclusion processes - focusing on interesting physical properties, such as shocks and phase transitions. We then turn our attention specifically to those models for which the exact distribution of microstates in the steady state can be expressed in a matrix product form. In addition to a gentle introduction to this matrix product approach, how it works and how it relates to similar constructions that arise in other physical contexts, we present a unified, pedagogical account of the various means by which the statistical mechanical calculations of macroscopic physical quantities are actually performed. We also review a number of more advanced topics, including nonequilibrium free energy functionals, the classification of exclusion processes involving multiple particle species, existence proofs of a matrix product state for a given model and more complicated variants of the matrix product state that allow various types of parallel dynamics to be handled. We conclude with a brief discussion of open problems for future research.Comment: 127 pages, 31 figures, invited topical review for J. Phys. A (uses IOP class file