Digital hologram reconstruction algorithm based on the Fractional Fourier transform in non-telecentric digital holographic microscopy.

A hologram reconstruction algorithm is proposed based on the fractional Fourier transform (FRFT) in non-telecentric digital holographic microscopy. The optimal fractional order representing the recorded hologram is estimated based on an evaluation metric. The FRFT-based hologram reconstruction enables noise robust amplitude and phase imaging with enhanced resolution. The effectiveness of the proposed approach is demonstrated in practical scenarios through both simulation and experimental results.

A first-principles study on the phase stability and physical properties of a B-site ordered Nd2CrFeO6 double perovskite.

Here, the first-principles predictions on the structural stability, magnetic behavior and electronic structure of B-site ordered double perovskite Nd2CrFeO6 have been reported. Initially, the ground state of the parent single perovskites NdCrO3 and NdFeO3 has been studied to determine the relevant Hubbard U parameter to investigate the properties of Nd2CrFeO6. The thermodynamic, mechanical, and dynamic stability analyses suggest the possibility of the synthesis of the Nd2CrFeO6 double perovskite at ambient pressure. The compound shows a ferrimagnetic nature with 2 µB net magnetic moment and the magnetic ordering temperature has been estimated to be ∼265 K. The electronic structure indicates a higher probability of direct photon transition over the indirect transition with a band gap of ∼1.85 eV. Additional effects of Nd (4f) spin and spin-orbit coupling on the band edges have been found to be negligible for this 4f-3d-3d spin system. This first-principles investigation predicts that due to the ferrimagnetic nature and a significantly lower band gap compared to those of its antiferromagnetic parent single perovskites, the B-site ordered Nd2CrFeO6 double perovskite could be a promising material for spintronic and visible-light driven energy applications.

Regulation of ROS Metabolism in Plants under Environmental Stress: A Review of Recent Experimental Evidence.

Various environmental stresses singly or in combination generate excess amounts of reactive oxygen species (ROS), leading to oxidative stress and impaired redox homeostasis. Generation of ROS is the obvious outcome of abiotic stresses and is gaining importance not only for their ubiquitous generation and subsequent damaging effects in plants but also for their diversified roles in signaling cascade, affecting other biomolecules, hormones concerning growth, development, or regulation of stress tolerance. Therefore, a good balance between ROS generation and the antioxidant defense system protects photosynthetic machinery, maintains membrane integrity, and prevents damage to nucleic acids and proteins. Notably, the antioxidant defense system not only scavenges ROS but also regulates the ROS titer for signaling. A glut of studies have been executed over the last few decades to discover the pattern of ROS generation and ROS scavenging. Reports suggested a sharp threshold level of ROS for being beneficial or toxic, depending on the plant species, their growth stages, types of abiotic stresses, stress intensity, and duration. Approaches towards enhancing the antioxidant defense in plants is one of the vital areas of research for plant biologists. Therefore, in this review, we accumulated and discussed the physicochemical basis of ROS production, cellular compartment-specific ROS generation pathways, and their possible distressing effects. Moreover, the function of the antioxidant defense system for detoxification and homeostasis of ROS for maximizing defense is also discussed in light of the latest research endeavors and experimental evidence.

Tebuconazole and trifloxystrobin regulate the physiology, antioxidant defense and methylglyoxal detoxification systems in conferring salt stress tolerance in Triticum aestivum L.

Fungicides are widely used for controlling fungi in crop plants. However, their roles in conferring abiotic stress tolerance are still elusive. In this study, the effect of tebuconazole (TEB) and trifloxystrobin (TRI) on wheat seedlings (Triticum aestivum L. cv. Norin 61) was investigated under salt stress. Seedlings were pre-treated for 48 h with fungicide (1.375 µM TEB + 0.5 µM TRI) and then subjected to salt stress (250 mM NaCl) for 5 days. Salt treatment alone resulted in oxidative damage and increased lipid peroxidation as evident by higher malondialdehyde (MDA) and hydrogen peroxide (H2O2) content. Salt stress also decreased the chlorophyll and relative water content and increased the proline (Pro) content. Furthermore, salt stress increased the dehydroascorbate (DHA) and glutathione disulfide (GSSG) content while ascorbate (AsA), the AsA/DHA ratio, reduced glutathione (GSH) and the GSH/GSSG ratio decreased. However, a combined application of TEB and TRI significantly alleviated growth inhibition, photosynthetic pigments and leaf water status improved under salt stress. Application of TEB and TRI also decreased MDA, electrolyte leakage, and H2O2 content by modulating the contents of AsA and GSH, and enzymatic antioxidant activities. In addition, TEB and TRI regulated K+/Na+ homeostasis by improving the K+/Na+ ratio under salt stress. These results suggested that exogenous application of TEB and TRI rendered the wheat seedling more tolerant to salinity stress by controlling ROS and methylglyoxal (MG) production through the regulation of the antioxidant defense and MG detoxification systems.

Silicon-induced antioxidant defense and methylglyoxal detoxification works coordinately in alleviating nickel toxicity in Oryza sativa L.

Nickel (Ni), an essential nutrient of plant but very toxic to plant at supra-optimal concentration that causes inhibition of seed germination emergence and growth of plants as a consequence of physiological disorders. Hence, the present study investigates the possible mechanisms of Ni tolerance in rice seedlings by exogenous application of silicon (Si). Thirteen-day-old hydroponically grown rice (Oryza sativa L. cv. BRRI dhan54) were treated with Ni (NiSO4.7H2O, 0.25 and 0.5 mM) sole or in combination with 0.50 mM Na2SiO3 for a period of 3 days to investigate the effect of Si supply for revoking the Ni stress. Nickel toxicity gave rise to reactive oxygen species (ROS) and cytotoxic methylglyoxal (MG), accordingly, initiated oxidative stress in rice leaves, and accelerated peroxidation of lipids and consequent damage to membranes. Reduced growth, biomass accumulation, chlorophyll (chl) content, and water balance under Ni-stress were also found. However, free proline (Pro) content increased in Ni-exposed plants. In contrast, the Ni-stressed seedlings fed with supplemental Si reclaimed the seedlings from chlorosis, water retrenchment, growth inhibition, and oxidative stress. Silicon up-regulated most of the antioxidant defense components as well as glyoxalase systems, which helped to improve ROS scavenging and MG detoxification. Hence, these results suggest that the exogenous Si application can improve rice seedlings' tolerance to Ni-toxicity.

Polyamine Action under Metal/Metalloid Stress: Regulation of Biosynthesis, Metabolism, and Molecular Interactions.

Polyamines (PAs) are found in all living organisms and serve many vital physiological processes. In plants, PAs are ubiquitous in plant growth, physiology, reproduction, and yield. In the last decades, PAs have been studied widely for exploring their function in conferring abiotic stresses (salt, drought, and metal/metalloid toxicity) tolerance. The role of PAs in enhancing antioxidant defense mechanism and subsequent oxidative stress tolerance in plants is well-evident. However, the enzymatic regulation in PAs biosynthesis and metabolism is still under research and widely variable under various stresses and plant types. Recently, exogenous use of PAs, such as putrescine, spermidine, and spermine, was found to play a vital role in enhancing stress tolerance traits in plants. Polyamines also interact with other molecules like phytohormones, nitric oxides, trace elements, and other signaling molecules to providing coordinating actions towards stress tolerance. Due to the rapid industrialization metal/metalloid(s) contamination in the soil and subsequent uptake and toxicity in plants causes the most significant yield loss in cultivated plants, which also hamper food security. Finding the ways in enhancing tolerance and remediation mechanism is one of the critical tasks for plant biologists. In this review, we will focus the recent update on the roles of PAs in conferring metal/metalloid(s) tolerance in plants.

Explicating physiological and biochemical responses of wheat cultivars under acidity stress: insight into the antioxidant defense and glyoxalase systems.

Soil acidity causes proton (H+) rhizotoxicity, inhibits plant growth and development, and is a major yield-limiting factor for wheat production worldwide. Therefore, we investigated the physiological and biochemical responses of wheat (Triticum aestivum L.) to acidity stress in vitro. Five popular wheat cultivars developed by Bangladesh Agricultural Research Institute (BARI), namely, BARI Gom-21, BARI Gom-24, BARI Gom-25, BARI Gom-26, and BARI Gom-30, were studied in growing media under four different pH levels (3.5, 4.5, 5.5, and 6.5). We evaluated the cultivars based on their relative water content, proline (Pro) content, growth, biomass accumulation, oxidative damage, membrane stability, and mineral composition, as well as the performance of the antioxidant defense and glyoxalase systems. Although decrements of pH significantly reduced the tested morphophysiological and biochemical attributes in all the cultivars, there was high variability among the cultivars in response to the varying pH of the growing media. Acidity stress reduced growth, biomass, water content, and chlorophyll content in all the cultivars. However, BARI Gom-26 showed the least damage, with the lowest H2O2 generation, lipid peroxidation (MDA), and greater membrane stability, which indicate better tolerance against oxidative damage. In addition, the antioxidant defense components, ascorbate (AsA) and glutathione (GSH), and their redox balance were higher in this cultivar. Maximum H2O2 scavenging due to upregulation of the antioxidant enzymes [AsA peroxidase (APX), monodehydroascorbate reductase (MDHAR), dehydroascorbate reductase (DHAR), GSH reductase (GR), GSH peroxidase (GPX), and GSH-S-transferase (GST)] was observed in BARI Gom-26, which also illustrated significant enhancement of methylglyoxal (MG) detoxification by upregulating glyoxalase I (Gly I) and glyoxalase II (Gly II). This study also showed that balanced essential nutrient content as well as lower toxic micronutrient content was found in BARI Gom-26. Therefore, considering the physiological and biochemical attributes and growth, we conclude that BARI Gom-26 can withstand acidity stress during the early seedling stage, by regulating the coordinated action of the antioxidant defense and glyoxalase systems as well as maintaining nutrient balance.

Acetate-induced modulation of ascorbate: glutathione cycle and restriction of sodium accumulation in shoot confer salt tolerance in Lens culinaris Medik.

Physiological and biochemical changes in six-day-old hydroponically grown lentil seedlings exposed to 100 mM salinity stress with or without 5 and 10 mM Na-acetate were studied. Results showed that salt stress reduced recovery percentage, fresh weight (FW), chlorophyll (chl) content, disturbed water balance, disrupted antioxidant defense pathway by decreasing reduced ascorbate content, and caused ion toxicity resulting from increased Na+ accumulation, severe K+ loss from roots in hydroponic culture. However, exogenous application of Na-acetate improved the seedling growth by maintaining water balance and increasing chl content. Furthermore, Na-acetate application reduced oxidative damage by modulating antioxidant defense pathway, and sustained ion homeostasis by reducing Na+ uptake and K+ loss. In the second experiment in glass house, we investigated the role of Na-acetate on lentil for long-term salinity. Acetate application increased FW and dry weight, reduced oxidative and membrane damage, and lowered the accumulation of Na+ in shoot compared with salt stressed seedlings alone. From the results of both experiments, it is clear that the exogenous application of Na-acetate enhanced salt tolerance in lentil seedlings.

Efficient point-by-point Bragg gratings fabricated in embedded laser-written silica waveguides using ultrafast Bessel beams.

We demonstrate highly efficient Bragg gratings written point-by-point by sequential single-pulse ultrashort Bessel laser beams in laser photoinscribed single-mode waveguides in bulk fused silica. The use of chirped non-diffractive Bessel beams determines a strong Bragg resonance in a weak-to-strong transitional regime, augmenting to a record value of 40 dB/cm at 1550 nm in the third order. The Bessel-induced refractive index modulation is negative and localized to sub-micrometer (200 nm) transverse scales. The strong light confinement in Bessel beams ensuring uniform one-dimensional void conditions thus allows for enhanced precision in the Bragg grating waveguide design. We demonstrate flexible fabrication of multiplexed waveguide gratings for multiple and tunable spectral resonances.

Insights into citric acid-induced cadmium tolerance and phytoremediation in Brassica juncea L.: Coordinated functions of metal chelation, antioxidant defense and glyoxalase systems.

Cadmium (Cd) is a serious environmental threat because it accumulates in plants from soil and is subsequently transported into the food cycle. Increased Cd uptake in plants disrupts plant metabolism and hampers crop growth and development. Therefore, remediation of Cd from soil and enhancing plant tolerance to metal toxicity is vital. In the present study, we investigated the function of different doses of citric acid (CA) on Cd toxicity in terms of metal accumulation and stress tolerance in mustard (Brassica juncea L.). Brassica juncea seedlings (12-day-old) were treated with Cd (0.5mMCd and 1.0mM CdCl2) alone and in combination with CA (0.5mM and 1.0mM) in a semi-hydroponic medium for three days. Cadmium accumulation in the roots and shoots of the mustard seedlings increased in a dose-dependent manner and was higher in the roots. Increasing the Cd concentration led to reduced growth, biomass, water status, and chlorophyll (chl) content resulting from increased oxidative damage (elevated malondialdehyde, MDA content; hydrogen peroxide, H2O2 level; superoxide, O2•- generation; lipoxygenase, LOX activity; and methylglyoxal, MG content) and downregulating of the major enzymes of the antioxidant defense and glyoxalase systems. Under Cd stress, both doses of CA improved the growth of the plants by enhancing leaf relative water content (RWC) and chl content; reducing oxidative damage; enhancing the pool of ascorbate (AsA) and glutathione (GSH) and the activities of the antioxidant enzymes (ascorbate peroxidase, APX; monodehydroascorbate reductase, MDHAR; dehydroascorbate reductase, DHAR; glutathione reductase, GR; glutathione peroxidase, GPX; superoxide dismutase, SOD; catalase, CAT); improving the performance of the glyoxalase system (glyoxalase I, Gly I and glyoxalase II, Gly II activity); and increasing the phytochelatin (PC) content. Exogenous CA also increased the root and shoot Cd content and Cd translocation from the roots to the shoots in a dose-dependent manner. Our findings suggest that CA plays a dual role in mustard seedlings by increasing phytoremediation and enhancing stress tolerance through upregulating the antioxidant defense and glyoxalase systems.

Near infrared spectro-interferometer using femtosecond laser written GLS embedded waveguides and nano-scatterers.

Guided optics spectrometers can be essentially classified into two main families: based on Fourier transform or dispersion. In the first case, an interferogram generated inside an optical waveguide and containing the spectral information is sampled using spatially distributed nanodetectors. These scatter quasi-non-perturbingly light into the detector that is in contact with the waveguide, helping to reconstruct the stationary wave. A dedicated FFT processing is needed in order to recover the spectrum with high resolution but limited spectral range. Another way is to directly disperse the different wavelengths to different pixels, either introducing differential optical path in the same propagation plane (multiple Mach-Zehnder interferometers or Arrayed Waveguides Gratings), or using a periodic structure to perpendicularly extract the optical signal confined in a waveguide (photonic crystals or surface gratings), and by means of a relay optics, generate the spectrum on the Fourier plane of the lens, where the detector is placed. Following this second approach, we present a laser-fabricated high-resolution compact dispersive spectro-interferometer (R>2500, 30nm spectral range at λ = 1560nm), using four parallel waveguides that can provide up to three non-redundant interferometric combinations. The device is based on guided optics technology embedded in bulk optical glass. Ultrafast laser photoinscription with 3D laser index engineering in bulk chalcogenide Gallium Lanthanium Sulfide glass is utilized to fabricate large mode area waveguides in an evanescently-coupled hexagonal multicore array configuration, followed by subsequent realization of nanoscaled scattering centers via one dimensional nanovoids across the waveguide, written in a non-diffractive Bessel configuration. A simple relay optics, with limited optical aberrations, reimages the diffracted signal on the focal plane array, leading to a robust, easy to align instrument.

Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges.

Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps during the live examination can be challenging due to various factors such as variation of skills and experience among the endoscopists, lack of attentiveness, and fatigue leading to a high polyp miss-rate. Therefore, there is a need for an automated system that can flag missed polyps during the examination and improve patient care. Deep learning has emerged as a promising solution to this challenge as it can assist endoscopists in detecting and classifying overlooked polyps and abnormalities in real time, improving the accuracy of diagnosis and enhancing treatment. In addition to the algorithm's accuracy, transparency and interpretability are crucial to explaining the whys and hows of the algorithm's prediction. Further, conclusions based on incorrect decisions may be fatal, especially in medicine. Despite these pitfalls, most algorithms are developed in private data, closed source, or proprietary software, and methods lack reproducibility. Therefore, to promote the development of efficient and transparent methods, we have organized the "Medico automatic polyp segmentation (Medico 2020)" and "MedAI: Transparency in Medical Image Segmentation (MedAI 2021)" competitions. The Medico 2020 challenge received submissions from 17 teams, while the MedAI 2021 challenge also gathered submissions from another 17 distinct teams in the following year. We present a comprehensive summary and analyze each contribution, highlight the strength of the best-performing methods, and discuss the possibility of clinical translations of such methods into the clinic. Our analysis revealed that the participants improved dice coefficient metrics from 0.8607 in 2020 to 0.8993 in 2021 despite adding diverse and challenging frames (containing irregular, smaller, sessile, or flat polyps), which are frequently missed during a routine clinical examination. For the instrument segmentation task, the best team obtained a mean Intersection over union metric of 0.9364. For the transparency task, a multi-disciplinary team, including expert gastroenterologists, accessed each submission and evaluated the team based on open-source practices, failure case analysis, ablation studies, usability and understandability of evaluations to gain a deeper understanding of the models' credibility for clinical deployment. The best team obtained a final transparency score of 21 out of 25. Through the comprehensive analysis of the challenge, we not only highlight the advancements in polyp and surgical instrument segmentation but also encourage subjective evaluation for building more transparent and understandable AI-based colonoscopy systems. Moreover, we discuss the need for multi-center and out-of-distribution testing to address the current limitations of the methods to reduce the cancer burden and improve patient care.

Lymph node detection in CT scans using modified U-Net with residual learning and 3D deep network.

PURPOSE: Lymph node (LN) detection is a crucial step that complements the diagnosis and treatments involved during cancer investigations. However, the low-contrast structures in the CT scan images and the nodes' varied shapes, sizes, and poses, along with their sparsely distributed locations, make the detection step challenging and lead to many false positives. The manual examination of the CT scan slices could be time-consuming, and false positives could divert the clinician's focus. To overcome these issues, our work aims at providing an automated framework for LNs detection in order to obtain more accurate detection results with low false positives. METHODS: The proposed work consists of two stages: candidate generation and false positive reduction. The first stage generates volumes of interest (VOI) of probable LN candidates using a modified U-Net with ResNet architecture to obtain high sensitivity but with the cost of increased false positives. The second-stage processes the obtained candidate LNs for false positive reduction using 3D convolutional neural network (CNN) classifier. We further present an analysis of various deep learning models while decomposing 3D VOI into different representations. RESULTS: The method is evaluated on two publicly available datasets containing CT scans of mediastinal and abdominal LNs. Our proposed approach yields sensitivities of 87% at 2.75 false positives per volume (FP/vol.) and 79% at 1.74 FP/vol. with the mediastinal and abdominal datasets, respectively. Our method presented a competitive performance in terms of sensitivity compared to the state-of-the-art methods and encountered very few false positives. CONCLUSION: We developed an automated framework for LNs detection using a modified U-Net with residual learning and 3D CNNs. The results indicate that our method could achieve high sensitivity with relatively low false positives, which helps avoid ineffective treatments.

Two-stream fusion model using 3D-CNN and 2D-CNN via video-frames and optical flow motion templates for hand gesture recognition.

Hand gestures are useful tools for many applications in the human-computer interaction community. Here, the objective is to track the movement of the hand irrespective of the shape, size and color of the hand. And, for this, a motion template guided by optical flow (OFMT) is proposed. OFMT is a compact representation of the motion information of a gesture encoded into a single image. Recently, deep networks have shown impressive improvements as compared to conventional hand-crafted feature-based techniques. Moreover, it is seen that the use of different streams with informative input data helps to increase the recognition performance. This work basically proposes a two-stream fusion model for hand gesture recognition. The two-stream network consists of two layers-a 3D convolutional neural network (C3D) that takes gesture videos as input and a 2D-CNN that takes OFMT images as input. C3D has shown its efficiency in capturing spatiotemporal information of a video, whereas OFMT helps to eliminate irrelevant gestures providing additional motion information. Though each stream can work independently, they are combined with a fusion scheme to boost the recognition results. We have shown the efficiency of the proposed two-stream network on two databases.

Overview of diagnostics on a small-scale RF source for fusion (ROBIN) and the one planned for the diagnostic beam for ITER.

India is responsible for the supply of diagnostic neutral beam systems for ITER to diagnose its helium ash during the deuterium-tritium plasma phase using the charge exchange recombination spectroscopy technique. Considering the many first of its kind in terms of technologies and beam development aspects, ITER Indian domestic agency has adopted a strategy of developing the technology and beam experimentation in parallel. On the beam development front three test beds, namely, the ROBIN (Rf Operated Beam source in India for Negative ion research), the TWIN (TWo rf driver-based Indigenously built Negative ion source), and the INTF (INdian Test Facility) are presently in their various phases of operation, optimization, and setting up at IPR, respectively. Experiments related to plasma production, beam production, and acceleration up to 30 keV in volume and surface mode have been performed on ROBIN. The maximum negative hydrogen ion current density to a tune of 27 mA/cm2 is obtained in the surface mode with Cs injection. Optimal source performance requires optimal surface conditions, minimum impurities, careful characterization of the plasma, cesium feed and its redistribution, and optimal wall temperatures of the surfaces of the plasma box and the plasma grid. A combination of probe, optical, vacuum, laser based, electrical, and calorimetric diagnostic measurements enables such a control. At ROBIN, the above diagnostics are being used regularly. The operational and diagnostic experiences on ROBIN shall provide the desired experience and database for operations of TWIN and INTF in the coming years. A large number of conventional and advanced diagnostic techniques are used for plasma and beam characterization. These diagnostics are suitable not only to detect and understand the plasma but also for studies related to impurity evolution. The temporal evolution of impurities significantly impacts the plasma and beam properties. The studies help in establishing correlations between physical parameters and operational parameters to optimize the source performance ensuring adequate safety and investment protection. This paper will present a brief overview of various diagnostics implemented, lessons learned, and the results obtained from ROBIN. In addition, an outline of the diagnostics planned for INTF based on the experience and understandings developed during the present experiments on ROBIN and TWIN and considering the requirements of large systems shall be discussed.

Extraction and Calculation of Roadway Area from Satellite Images Using Improved Deep Learning Model and Post-Processing.

Roadway area calculation is a novel problem in remote sensing and urban planning. This paper models this problem as a two-step problem, roadway extraction, and area calculation. Roadway extraction from satellite images is a problem that has been tackled many times before. This paper proposes a method using pixel resolution to calculate the area of the roads covered in satellite images. The proposed approach uses novel U-net and Resnet architectures called U-net++ and ResNeXt. The state-of-the-art model is combined with the proposed efficient post-processing approach to improve the overlap with ground truth labels. The performance of the proposed road extraction algorithm is evaluated on the Massachusetts dataset and it is shown that the proposed approach outperforms the existing solutions which use models from the U-net family.

Methods, Databases and Recent Advancement of Vision-Based Hand Gesture Recognition for HCI Systems: A Review.

Hand gesture recognition is viewed as a significant field of exploration in computer vision with assorted applications in the human-computer communication (HCI) community. The significant utilization of gesture recognition covers spaces like sign language, medical assistance and virtual reality-augmented reality and so on. The underlying undertaking of a hand gesture-based HCI framework is to acquire raw data which can be accomplished fundamentally by two methodologies: sensor based and vision based. The sensor-based methodology requires the utilization of instruments or the sensors to be genuinely joined to the arm/hand of the user to extract information. While vision-based plans require the obtaining of pictures or recordings of the hand gestures through a still/video camera. Here, we will essentially discuss vision-based hand gesture recognition with a little prologue to sensor-based data obtaining strategies. This paper overviews the primary methodologies in vision-based hand gesture recognition for HCI. Major topics include different types of gestures, gesture acquisition systems, major problems of the gesture recognition system, steps in gesture recognition like acquisition, detection and pre-processing, representation and feature extraction, and recognition. Here, we have provided an elaborated list of databases, and also discussed the recent advances and applications of hand gesture-based systems. A detailed discussion is provided on feature extraction and major classifiers in current use including deep learning techniques. Special attention is given to classify the schemes/approaches at various stages of the gesture recognition system for a better understanding of the topic to facilitate further research in this area.

Computational learning of features for automated colonic polyp classification.

Shape, texture, and color are critical features for assessing the degree of dysplasia in colonic polyps. A comprehensive analysis of these features is presented in this paper. Shape features are extracted using generic Fourier descriptor. The nonsubsampled contourlet transform is used as texture and color feature descriptor, with different combinations of filters. Analysis of variance (ANOVA) is applied to measure statistical significance of the contribution of different descriptors between two colonic polyps: non-neoplastic and neoplastic. Final descriptors selected after ANOVA are optimized using the fuzzy entropy-based feature ranking algorithm. Finally, classification is performed using Least Square Support Vector Machine and Multi-layer Perceptron with five-fold cross-validation to avoid overfitting. Evaluation of our analytical approach using two datasets suggested that the feature descriptors could efficiently designate a colonic polyp, which subsequently can help the early detection of colorectal carcinoma. Based on the comparison with four deep learning models, we demonstrate that the proposed approach out-performs the existing feature-based methods of colonic polyp identification.

High aspect ratio taper-free microchannel fabrication using femtosecond Bessel beams.

We present a systematic study of femtosecond laser microchannel machining in glass using nondiffracting Bessel beams. In particular, our results identify a source and focusing parameter working window where high aspect ratio taper-free microchannels can be reproducibly produced without sample translation. With appropriate source parameters, we machine channels of 2 microm diameter and with aspect ratios up to 40. We propose the filamentation stability of the Bessel beam propagation as the critical factor underlying the controlled and reproducible results that have been obtained.

Selenium Toxicity in Plants and Environment: Biogeochemistry and Remediation Possibilities.

Selenium (Se) is a widely distributed trace element with dual (beneficial or toxic) effects for humans, animals, and plants. The availability of Se in the soil is reliant on the structure of the parental material and the procedures succeeding to soil formation. Anthropogenic activities affect the content of Se in the environment. Although plants are the core source of Se in animal and human diet, the role of Se in plants is still debatable. A low concentration of Se can be beneficial for plant growth, development, and ecophysiology both under optimum and unfavorable environmental conditions. However, excess Se results in toxic effects, especially in Se sensitive plants, due to changing structure and function of proteins and induce oxidative/nitrosative stress, which disrupts several metabolic processes. Contrary, Se hyperaccumulators absorb and tolerate exceedingly large amounts of Se, could be potentially used to remediate, i.e., remove, transfer, stabilize, and/or detoxify Se-contaminants in the soil and groundwater. Thereby, Se-hyperaccumulators can play a dynamic role in overcoming global problem Se-inadequacy and toxicity. However, the knowledge of Se uptake and metabolism is essential for the effective phytoremediation to remove this element. Moreover, selecting the most efficient species accumulating Se is crucial for successful phytoremediation of a particular Se-contaminated area. This review emphasizes Se toxicity in plants and the environment with regards to Se biogeochemistry and phytoremediation aspects. This review follows a critical approach and stimulates thought for future research avenues.