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We consider the effect of non-cylindrical axonal shape on axonal diameter mapping with diffusion MRI. Practical sensitivity to axon diameter is attained at strong diffusion weightingsb, where the deviation from thescaling yields the finite transverse diffusivity, which is then translated into axon diameter. While axons are usually modeled as perfectly straight, impermeable cylinders, the local variations in diameter (caliber variation or beading) and direction (undulation) have been observed in microscopy data of human axons. Here we quantify the influence of cellular-level features such as caliber variation and undulation on axon diameter estimation. For that, we simulate the diffusion MRI signal in realistic axons segmented from 3-dimensional electron microscopy of a human brain sample. We then create artificial fibers with the same features and tune the amplitude of their caliber variations and undulations. Numerical simulations of diffusion in fibers with such tunable features show that caliber variations and undulations result in under- and over-estimation of axon diameters, correspondingly; this bias can be as large as 100%. Given that increased axonal beading and undulations have been observed in pathological tissues, such as traumatic brain injury and ischemia, the interpretation of axon diameter alterations in pathology may be significantly confounded.

Differential expression of myelin-related genes and changes in myelin thickness have been demonstrated in mice after chronic psychosocial stress, a risk factor for anxiety disorders. To determine whether and how stress affects structural remodeling of nodes of Ranvier, another form of myelin plasticity, we developed a 3D reconstruction analysis of node morphology in C57BL/6NCrl and DBA/2NCrl mice. We identified strain-dependent effects of chronic social defeat stress on node morphology in the medial prefrontal cortex (mPFC) gray matter, including shortening of paranodes in C57BL/6NCrl stress-resilient and shortening of node gaps in DBA/2NCrl stress-susceptible mice compared to controls. Neuronal activity has been associated with changes in myelin thickness. To investigate whether neuronal activation is a mechanism influencing also node of Ranvier morphology, we used DREADDs to repeatedly activate the ventral hippocampus-to-mPFC pathway. We found reduced anxiety-like behavior and shortened paranodes specifically in stimulated, but not in the nearby non-stimulated axons. Altogether, our data demonstrate (1) nodal remodeling of the mPFC gray matter axons after chronic stress and (2) axon-specific regulation of paranodes in response to repeated neuronal activity in an anxiety-associated pathway. Nodal remodeling may thus contribute to aberrant circuit function associated with anxiety disorders.

Cyclic voltammetry and potentiodynamic polarization analyses were utilized to investigate the mechanism and kinetics of glycine leaching reactions for chalcopyrite. The effects of pH (9–12), temperature (30–90 °C) and glycine concentration (0–2 mol/L) on corrosion current density, corrosion potential and cyclic voltammograms were investigated using chalcopyrite concentrate–carbon paste electrodes. Results showed that an increase in the glycine concentration from 0 to 2 mol/L led to an increased oxidation peak current density. Under the same conditions, corrosion current density was found to change from approximately 28 to 89 μA/cm whereas corrosion potential was decreased from –80 to –130 mV. Elevated temperatures enhanced the measured current densities up to 60 °C; however, above this level, current density was observed to decrease. A similar current density behavior was determined with pH. A pH change from 9 to 10.5 resulted in an increase in current density and pH higher than 10.5 gave rise to a reduced current density. In addition, the thermodynamic stability of copper and iron oxides was found to increase at higher temperatures.

In this research, flotation of copper, lead and zinc minerals from a copper oxide–sulfide ore was studied. The identification tests showed that the sample is a mixture of quartz, chalcopyrite, galena, cerussite, hemimorphite and iron oxide minerals with 5.04% CuO, 1.61% PbO, 2.07% ZnO and 56.40% SiO2. The experimental design methodology (RSM) was conducted to investigate the effect of parameters such as pH, collector, depressant, dispersant, preparation time and size of particles on Cu–Pb–Zn minerals flotation in three steps: sulfide bulk flotation, oxide bulk flotation and sulfide differential flotation. The experiments showed that the pH, potassium amyl xanthate and sodium silicate variation influence copper, lead and zinc recoveries. In the first step, recovery of Cu–Pb sulfide reached 45.49% with grade of 15.96% for Cu and 61.65% with grade of 7.4% for Pb. In the third step, the recovery and grade of Cu enhanced to 88% and 18.3%, respectively. The optimization of parameters was conducted by software, and the supplementary tests were done by considering the optimal conditions. Under optimal conditions, the recovery of copper and lead was, respectively, 88% with grade of 24.5% in Cu concentrate and 81% with grade of 13.8% in Pb concentrate.

Background and Objective: Advances in electron microscopy (EM) now allow three-dimensional (3D) imaging of hundreds of micrometers of tissue with nanometer-scale resolution, providing new opportunities to study the ultrastructure of the brain. In this work, we introduce a freely available Matlab-based gACSON software for visualization, segmentation, assessment, and morphology analysis of myelinated axons in 3D-EM volumes of brain tissue samples. Methods: The software is equipped with a graphical user interface (GUI). It automatically segments the intra-axonal space of myelinated axons and their corresponding myelin sheaths and allows manual segmentation, proofreading, and interactive correction of the segmented components. gACSON analyzes the morphology of myelinated axons, such as axonal diameter, axonal eccentricity, myelin thickness, or gratio. Results: We illustrate the use of the software by segmenting and analyzing myelinated axons in six 3DEM volumes of rat somatosensory cortex after sham surgery or traumatic brain injury (TBI). Our results suggest that the equivalent diameter of myelinated axons in somatosensory cortex was decreased in TBI animals five months after the injury. Conclusion: Our results indicate that gACSON is a valuable tool for visualization, segmentation, assessment, and morphology analysis of myelinated axons in 3D-EM volumes. It is freely available at https://github.com/AndreaBehan/g-ACSON under the MIT license. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

Dynamic simulation approach can be used for understanding the nonlinear behavior in mineral processing circuits. In this study, the gel point, the main parameters of batch flux density function and the main parameters of effective solid stress were determined at different conditions (pH, flocculant dosage and particle size). Therefore, the main parameters of phenomenological model of sedimentation and thickening were determined as a function of particle size, pH and flocculant dosages using the result of experimental tests and Curve expert professional software. Then, the dynamic simulation was carried out for the industrial thickener of coal washing plant and the time-dependent variation of response variables was investigated by time-dependent variation of pH of input feed to thickener using the obtained equations. It was observed that it is possible to predict the thickener behavior as a function of time for time dependent variation of pH of input feed to the thickener of coal washing plant using obtained equations that it was not possible using phenomenological model of thickener alone.

Transfer learning refers to machine learning techniques that focus on acquiring knowledge from related tasks to improve generalization in the tasks of interest. In MRI, transfer learning is important for developing strategies that address the variation in MR images. Additionally, transfer learning is beneficial to re-utilize machine learning models that were trained to solve related tasks to the task of interest. Our goal is to identify research directions, gaps of knowledge, applications, and widely used strategies among the transfer learning approaches applied in MR brain imaging. We performed a systematic literature search for articles that applied transfer learning to MR brain imaging. We screened 433 studies and we categorized and extracted relevant information, including task type, application, and machine learning methods. Furthermore, we closely examined brain MRI-specific transfer learning approaches and other methods that tackled privacy, unseen target domains, and unlabeled data. We found 129 articles that applied transfer learning to brain MRI tasks. The most frequent applications were dementia related classification tasks and brain tumor segmentation. A majority of articles utilized transfer learning on convolutional neural networks (CNNs). Only few approaches were clearly brain MRI specific, considered privacy issues, unseen target domains or unlabeled data. We proposed a new categorization to group specific, widely-used approaches. There is an increasing interest in transfer learning within brain MRI. Public datasets have contributed to the popularity of Alzheimer's diagnostics/prognostics and tumor segmentation. Likewise, the availability of pretrained CNNs has promoted their utilization. Finally, the majority of the surveyed studies did not examine in detail the interpretation of their strategies after applying transfer learning, and did not compare to other approaches., Comment: Accepted in Journal of Imaging

Purpose Image processing plays a fundamental role in the study of central nervous system, for example in the analysis of the vascular network in neurodegenerative diseases. Synchrotron X-ray Phase-contrast micro-Tomography (SXPCT) is a very attractive method to study weakly absorbing samples and features, such as the vascular network in the spinal cord (SC). However, the identification and segmentation of vascular structures in SXPCT images is seriously hampered by the presence of image noise and strong contrast inhomogeneities, due to the sensitivity of the technique to small electronic density variations. In order to help with these tasks, we implemented a user-friendly ImageJ plugin based on a 3D Gaussian steerable filter, tuned up for the enhancement of tubular structures in SXPCT images. Methods The developed 3D Gaussian steerable filter plugin for ImageJ is based on the steerability properties of Gaussian derivatives. We applied it to SXPCT images of ex-vivo mouse SCs acquired at different experimental conditions. Results The filter response shows a strong amplification of the source image contrast-to-background ratio (CBR), independently of structures orientation. We found that after the filter application, the CBR ratio increases by a factor ranging from ~6 to ~60. In addition, we also observed an increase of 35% of the contrast to noise ratio in the case of injured mouse SC. Conclusion The developed tool can generally facilitate the detection/segmentation of capillaries, veins and arteries that were not clearly observable in non-filtered SXPCT images. Its systematic application could allow obtaining quantitative information from pre-clinical and clinical images.

The simplest amino acid, glycine has recently been reported as a safe and environmentally benign reagent for the extraction of copper from both oxide and sulfide minerals. In the current study, leaching of a chalcopyrite concentrate from the Sarcheshmeh Copper Mine (Kerman, Iran) was conducted in stirred tank reactors in the presence of a glycine medium. The effect of some critical leaching parameters including glycine concentration (0.4–2 M), temperature (30–90 °C), stirring rate (250–750 rpm), pH (9–12), oxygen flowrate (0.5–2 L/min) and pulp density (1–20%) was investigated on copper recovery from the chalcopyrite concentrate. Results show that an increase in temperature from 30 to 60 ˚C enhanced the copper extraction, whereas at conditions > 60 ˚C a decrease in copper extraction was observed, probably as a result of the conversion of glycine to glycinate and decrease in oxygen solubility. Moreover, prolonged leaching times at higher pH levels (10.5 and 12) led to a decrease in the extraction of copper, primarily due to the chemical precipitation of copper sulfide and crystallization of copper glycinate. By increasing the pulp density from 1 to 20%, copper extraction declined significantly primarily as a consequence of the partial dissolved copper precipitation at higher copper concentrations. SEM/WDX analyses were subsequently used in order to evaluate the leach residues. Further investigation determined that the activation energy of the glycine leaching of concentrate was 37.4 KJ/mol, thus the kinetics were controlled by diffusion of the reagents through the product layer. From these results, it is evident that due to the high initial rate of glycine leaching and the precipitation of copper-bearing phases (i.e. copper glycinate and covellite) at high pulp densities, glycine leaching processes are recommended for the treatment of low grade chalcopyrite concentrates, ores or tailings.

BackgroundA system of lymphatic vessels has been recently characterized in the meninges, with a postulated role in ‘cleaning’ the brain via cerebral fluid drainage. As meninges are the origin site of migraine pain, we hypothesized that malfunctioning of the lymphatic system should affect the local trigeminal nociception. To test this hypothesis, we studied nociceptive and inflammatory mechanisms in the meninges of K14-VEGFR3-Ig mice lacking the meningeal lymphatic system.MethodsWe recorded the spiking activity of meningeal afferents and estimated the local mast cells infiltration, calcitonin gene-related peptide (CGRP) and cytokine levels (basal and stimulated), as well as the dural trigeminal innervation in freshly-isolated hemiskull preparations from K14-VEGFR3-Ig (K14) or wild type C57BL/6 mice (WT).ResultsWe found that the meningeal level of CGRP and of the pro-inflammatory cytokines IL12-p70 and TNFα (implicated in migraine) were reduced in the meninges of K14 mice. On the contrary, in the meninges of K14 mice, we found an increased level of the mast cell activator MCP-1 and, consistently, a larger number of dural mast cells. The other migraine-related pro-inflammatory cytokines did not differ between the two genotypes. The patterns of trigeminal innervation in meninges remained unchanged and we did not observe alterations in basal or ATP-induced nociceptive firing in the meningeal afferents.ConclusionsIn summary, the lack of meningeal lymphatic system does not induce migraine-like nociceptive state per se, but leads to a new balance between pro- and antiinflammatory factors implicated in migraine mechanisms.

The feasibility and kinetics of lead recovery from the slag of traditional lead melting furnace using chloride leaching were investigated. The effects of operating parameters such as leaching time, NaCl concentration, FeCl3 concentration, liquid/solid ratio, stirring rate, temperature, and particle size on recovery of lead were studied and the optimization was done through the response surface methodology (RSM) based on central composite design (CCD) model. The optimum conditions were achieved as follows: leaching time 60 min, 80 °C, stirring rate 800 r/min, NaCl concentration 200 g/L, FeCl3 concentration 80 g/L, liquid/solid ratio 16, and particle size less than 106 μm. More than 96% of lead was effectively recovered in optimum condition. Based on analysis of variance, the reaction temperature, liquid/solid ratio, and NaCl concentration were determined as the most effective parameters on leaching process, respectively. Kinetics study revealed that chloride leaching of galena is a first-order reaction and the diffusion through solid reaction product and chemical reaction control the mechanism. The activation energy of chloride leaching of galena was determined using Arrhenius model as 27.9 kJ/mol.

The effect of mechanical activation on the leaching and electrochemistry of chalcopyrite was investigated in a glycine medium. Leaching experiments were conducted to evaluate the effect of particle size (with re-ground sample in ball mill) and mechanical activation (with re-ground sample in planetary mill for 4 h) on chalcopyrite dissolution in a stirred tank reactor. Results show that a maximum copper extraction (95.1%) was obtained for mechanically activated chalcopyrite after 12 h leaching in a 0.4 M glycine solution at 60 °C, 2% (w/v) pulp density and an initial solution pH of 10.5. Under these same leaching conditions, a decrease in particle size for conventionally ground chalcopyrite from 106 to 125 μm to

Real time dynamic simulation provides a powerful tool to control the mineral processing plants with the minimum cost. In this study, the dynamic simulation was carried out for the thickener at coal washing plant. Therefore, the parameters of the phenomenological model for the sedimentation and thickening were determined at different conditions. Dynamic simulation was carried out for each condition and the effect of feed flow rate variations on solid volume fraction of the thickener underflow and bed height was investigated. For all conditions, it was observed that when feed flow rate increases, the solid volume fraction of discharge and bed height increase. It was also observed that, in the case of the flocculated suspension, the maximum solid volume fraction of the thickener underflow decreases and the bed height increases with pH reduction, for two size fractions. Also, the maximum solid volume fraction of the thickener underflow for d 80 = 275 μm is higher than that of d 80 = 125 μm and the height of compression zone for d 80 = 125 μm is higher than that of d 80 = 275 μm at the certain pH and flocculant dosages.

Solutions containing copper ions are produced at copper mines due to its dissolution from ores and dumps. It is important to recover these ions to prevent this toxic element from entering the environment and because it could be economical. We investigated the use of ion flotation for extracting Cu ions from diluted mine water from the Veshnaveh Mine in Qom, Iran. Experiments were conducted using floatation cells at pH 6, 9, and 12 with diluted solutions containing 10 mg L−1 of Cu. Sodium dodecyl sulfate and hexadecyl trimethyl ammonium bromide (HTAB) were used as collectors and methyl isobutyl carbinol (MIBC) and ethanol were used as frothers. The best result was achieved by maximizing Cu ion recovery and minimizing water recovery at pH 12, using 100 mg L−1 of HTAB and 0.1 % (v/v) of MIBC. Copper and water recovery were 79 and 24 %, respectively.

Axonal structure underlies white matter functionality and plays a major role in brain connectivity. The current literature on the axonal structure is based on the analysis of two-dimensional (2D) cross-sections, which, as we demonstrate, is precarious. To be able to quantify three-dimensional (3D) axonal morphology, we developed a novel pipeline, called ACSON (AutomatiC 3D Segmentation and morphometry Of axoNs), for automated 3D segmentation and morphometric analysis of the white matter ultrastructure. The automated pipeline eliminates the need for time-consuming manual segmentation of 3D datasets. ACSON segments myelin, myelinated and unmyelinated axons, mitochondria, cells and vacuoles, and analyzes the morphology of myelinated axons. We applied the pipeline to serial block-face scanning electron microscopy images of the corpus callosum of sham-operated (n = 2) and brain injured (n = 3) rats 5 months after the injury. The 3D morphometry showed that cross-sections of myelinated axons were elliptic rather than circular, and their diameter varied substantially along their longitudinal axis. It also showed a significant reduction in the myelinated axon diameter of the ipsilateral corpus callosum of rats 5 months after brain injury, indicating ongoing axonal alterations even at this chronic time-point.

Dynamic simulation approach can be used for understanding the nonlinear behavior in mineral processing circuits. In this study, the dynamic simulation was carried out for the thickener of the Tabas coal-washing plant at different conditions and the effect of discharge rate variations on the solid volume fraction of the thickener under flow and mudline height was investigated. It was observed that for the conditions that the solid volume fraction of the thickener underflow is higher and the midline height is lower, the time to reach the steady state condition is higher. It was also observed that the maximum solid volume fraction of the thickener underflow decreases and the mudline height increases with pH reduction. Also, the maximum solid volume fraction of the thickener underflow decreases and the mudline height increases with particle size reduction at certain pH and flocculant dosage values.

This study was conducted to establish the possible application of bioleaching to recover valuable metals from the sulfidic tailing of Golgohar Iron Mine (Kerman, Iran). Shake flask leaching experiments were carried out in the presence of a mixed culture of moderately thermopilic microorganisms at a stirring rate of 150 rpm and a temperature of 45 °C, with the addition of yeast extract (%0.02 (w/w). The influence of bacterial inoculation, pH, nutrient medium type and pulp density on the recovery of copper, nickel and cobalt from the tailing was investigated. The results showed that 55.0% of copper, 98.2% of nickel and 59.5% of cobalt could be extracted from the tailing through the bioleaching process after 30 days at 5% (w/v) pulp density. The recovery of valuable metals from the tailing in the presence of microorganisms was approximately three times higher than that in the un-inoculated leaching experiment under similar conditions. It was also found that the recovery of copper at the initial pH of 1.2 was 17% higher than that at the pH of 1.8, while nickel and cobalt recoveries were 37% and 23% more at the pH of 1.8, respectively. It was also revealed that the recoveries of valuable metals were approximately similar in both 9 K and Norris nutrient media. Moreover, the results showed that in both nutrient media, copper recovery at the higher pulp density was significantly higher than that at the lower pulp density; this was mainly attributed to the lower redox potential. On the other hand, nickel and cobalt recoveries were higher at the lower pulp density, probably due to the higher redox potential values. A two-stage bioleaching process in which the redox potential is controlled at a low level in the primary reactors, followed by the secondary reactors with a high redox potential is supposed to achieve the maximum recovery of valuable metals.

In cryo-electron microscopy (cryo-EM), the Wiener filter is the optimal operation – in the least-squares sense – of merging a set of aligned low signal-to-noise ratio (SNR) micrographs to obtain a class average image with higher SNR. However, the condition for the optimal behavior of the Wiener filter is that the signal of interest shows stationary characteristic thoroughly, which cannot always be satisfied. In this paper, we propose substituting the conventional Wiener filter, which encompasses the whole image for denoising, with its local adaptive implementation, which denoises the signal locally. We compare our proposed local adaptive Wiener filter (LA-Wiener filter) with the conventional class averaging method using a simulated dataset and an experimental cryo-EM dataset. The visual and numerical analyses of the results indicate that LA-Wiener filter is superior to the conventional approach in single particle reconstruction (SPR) applications.

To carry out metallurgical and economic calculations as well as plant control, mass balance for mineral processing circuits is a very important and fundamental issue. For this purpose, sufficient and correct data from mineral processing circuits are necessary. On the other hand, due to economic or technical reasons, measurement or sampling from all of circuits is not possible. In this paper, regarding the measurement or sampling system that has been installed in the mineral processing circuit, a basic cycle matrix method was used for the determination of observable and unobservable variables in the mineral processing circuit. Also, two new methods including linear and bilinear methods were used for calculation of observable variables. These methods have been used in the case study related to dry tailing processing of the Golegohar iron processing plant.

In this paper it is assumed n observation decisions units with m inputs and s outputs are exist. Sensitivity analysis is for the case when the index added to the collection. Adding a new index to indexes and we find the range for this index in a way that performance of efficient unit and performance of inefficient units to be maintained. To create this area and avoid resolve problem use sensitivities of linear programming techniques.

Botnets have been detected as the most important internet threat in recent years which are developing and spreading constantly. Botnets detection is a new and challenging research domain in security section of computer nets. Because detection of an attack isn’t considered as a normal situation or a definite Botnet attack and we can’t decide definitely, therefore this article intends to count each intrusion with one degree of attack and give the action initiative to the organization for regulating the sensitiveness measure for the attack of intrusions perception. Also in this research a combined approach based on evolutional algorithm of colonial competition and fuzzy clustering (fuzzy C-Mean) has been presented in order to detect Botnet. For all simulations, programming in MATLAB 2013 B environment has been used. The used Botnet data collection in this article was MCFP. The results indicate the superiority of suggested method over similar basic methods.

International audience; A new technique of data reconciliation, applied to validation of measures collected on a system, is suggested in this paper. This approach is based on the inequality constraints describing the hyper space in which the state of the considered system is probably located. We also use the model of the system in which the residuals must, in the same way, be constrained in an hyper space. Finally, the complete problem of reconciliation appears in the form of LMI (linear matrix inequality) and thus can be solved with the software tools that are appropriate to this technique. Some examples show that classical problems of balance equilibration can be solved: total flow balances, partial flow balances, balances with partial measures, consideration of biased measures.