Highly Stereoselective Diels-Alder-Based Strategy for the Synthesis of 3-epi-Formicin A and 1-epi-Formicin B.

The first enantioselective approach based on a highly stereoselective Diels-Alder reaction for the synthesis of 3-epi-formicin A and 1-epi-formicin B with rare N-acetylcysteamine-containing indenone thioesters is reported. The strategy utilizes a key Diels-Alder reaction to form the core hydrindane system with three contiguous stereocenters in very high levels of diastereo- and regioselectivity and one-pot oxidation/isomerization/dehydrogenation. The scope of this method was tested with different substrates to give cycloadducts in a highly diastereoselective manner.

A 17.8-20.2 GHz Compact Vector-Sum Phase Shifter in 130 nm SiGe BiCMOS Technology for LEO Gateways Receivers.

This paper presents a novel and compact vector modulator (VM) architecture implemented in 130 nm SiGe BiCMOS technology. The design is suitable for use in receive phased arrays for the gateways of major low Earth orbit (LEO) constellations that operate in the 17.8 to 20.2 GHz frequency range. The proposed architecture uses four variable gain amplifiers (VGA) that are active at any given time and are switched to generate the four quadrants. Compared to conventional architectures, this structure is more compact and produces double the output amplitude. The design offers 6-bit phase control for 360°, and the total root mean square (RMS) phase and gain errors are 2.36° and 1.46 dB, respectively. The design occupies an area of 1309.4 µm × 1783.8 µm (including pads).

PEG-mediated synthesis, antibacterial, antifungal and antioxidant studies of some new 1,3,5-trisubstituted 2-pyrazolines.

A new series of 1,3,5-trisubstituted 2-pyrazoline derivatives (3a-l) are synthesized in good to excellent yields from the corresponding chalcones (1a-h) and acid hydrazides (2a-e) in polyethylene glycol-400 (PEG-400) as a green reaction medium. The newly synthesized 2-pyrazoline derivatives are screened for their antibacterial and antifungal activity. The synthesized trisubstituted pyrazolines displayed moderate to good antibacterial and antifungal properties as compared with the standard reference penicillin and fluconazole drugs. Additionally, the antioxidant potential of the 1,3,5-trisubstituted 2-pyrazolines is evaluated by OH and DPPH assay. The 1,3,5-trisubstituted 2-pyrazolines showed good radical scavenger activity and were found as good antioxidant agents.

Phased Array Antenna Analysis Workflow Applied to Gateways for LEO Satellite Communications.

Nowadays, mega-constellations of Low Earth Orbit (LEO) satellites have become increasingly important to provide high-performance Internet access with global coverage. This paper provides an updated comparison of four of the largest LEO mega-constellations: Telesat, SpaceX, OneWeb and Amazon. It describes the gateway design workflow from the patch antenna to phased array analysis. Patch antennas are developed for both transmission and reception after a thorough examination of the four systems. The results of electromagnetic simulation using Advanced Design Software (ADS) Momentum are shown, including their radiation pattern. Finally, a model of the gateway phased array using SystemVue is obtained using hexagonal, circular, and square arrays. According to the required effective isotropic radiated power (EIRP) and gain, the antenna sizes for the four constellations are estimated. As an example, for SpaceX constellation, a reception antenna with 8910 radiating elements using a hexagonal distribution with a gain of 46.9 dB and a sensitivity of -113.1 dBm was obtained.

Deep Neural Network-Based Novel Mathematical Model for 3D Brain Tumor Segmentation.

The use of multimodal magnetic resonance imaging (MRI) to autonomously segment brain tumors and subregions is critical for accurate and consistent tumor measurement, which can help with detection, care planning, and evaluation. This research is a contribution to the neuroscience research. In the present work, we provide a completely automated brain tumor segmentation method based on a mathematical model and deep neural networks (DNNs). Each slice of the 3D picture is enhanced by the suggested mathematical model, which is then sent through the 3D attention U-Net to provide a tumor segmented output. The study includes a detailed mathematical model for tumor pixel enhancement as well as a 3D attention U-Net to appropriately separate the pixels. On the BraTS 2019 dataset, the suggested system is tested and verified. This proposed work will definitely help for the treatment of the brain tumor patient. The pixel level accuracy for tumor pixel segmentation is 98.90%. The suggested system architecture's outcomes are compared to those of current system designs. This study also examines the suggested system architecture's time complexity on various processing units with neuroscience approach.

Image Processing and Machine Learning-Based Classification and Detection of Liver Tumor.

The liver is in charge of a plethora of tasks that are critical to healthy health. One of these roles is the conversion of food into protein and bile, which are both needed for digestion. Inhaled and possibly harmful chemicals are flushed from the body. It destroys numerous nutrients acquired through the gastrointestinal system and limits the release of cholesterol by utilizing vitamins, carbohydrates, and minerals stored in the liver. The body's tissues are made up of tiny structures known as cells. Cells proliferate and divide in order to create new ones in the normal sequence of events. When an old or damaged cell has to be replaced, a new cell must be synthesized. In other circumstances, the procedure is a total and utter failure. If the tissues of dead or damaged cells that have been cleared from the body are not removed, they may give birth to nodules and tumors. The liver can produce two types of tumors: benign and malignant. Malignant tumors are more dangerous to one's health than benign tumors. This article presents a technique for the classification and identification of liver cancers that is based on image processing and machine learning. The approach may be found here. During the preprocessing stage of picture creation, the fuzzy histogram equalization method is applied in order to bring about a reduction in image noise. After that, the photographs are divided into many parts in order to zero down on the area of interest. For this particular classification task, the RBF-SVM approach, the ANN method, and the random forest method are all applied.

Homogeneous Decision Community Extraction Based on End-User Mental Behavior on Social Media.

Aiming at the inadequacy of the group decision-making method with the current attribute value as interval language information, an interval binary semantic decision-making method is proposed, which considers the decision maker's psychological behavior. The scope of this research is that this paper is based on localized amplification method. The localized amplification method used in this research may amplify physiological movement after removing unwanted noise, allowing the movement trend to be seen with the naked eye, improving the CNN network's mental identification accuracy. These two algorithms analyze the input picture from various perspectives, allowing the CNN network to extract more information and enhance identification accuracy. A new distance formula with interval binary semantics closer to decision-makers thinking habits is defined; time degree is introduced. An optimization model is established to solve the time series weights by considering the comprehensive consistency of expert evaluation. Based on prospect theory, a prospect deviation value is constructed and minimized weight optimization model, using the interactive multiple attribute decision community making (TODIM) method based on the new distance measure to calculate the total overall dominance of the schemes to rank the schemes. Taking the selection and evaluation of supply chain collaboration partners as an example, the effectiveness and rationality of the proposed method are verified.

Biosynthesis and regulation of anthocyanin pathway genes.

Anthocyanins are the phenolic compounds responsible for coloring pigments in fruits and vegetables. Anthocyanins offer a wide range of health benefits to human health. Their scope has expanded dramatically in the past decade, making anthocyanin control, influx, and outflow regulation fascinating for many researchers. The main culprit is anthocyanin stability and concentration form, which demands novel ways because these are critical in the food industry. This review aims to examine anthocyanin synthesis via triggering transcription genes that code for anthocyanin-producing enzymes. The balance between production and breakdown determines anthocyanin accumulation. Thus, increasing the anthocyanin content in food requires the stability of molecules in the vacuolar lumen, the pigment fading process, and a better understanding of the mechanism. The promising option is biosynthesis by metabolically engineered microorganisms with a lot of success. This study aims to look into and evaluate the existing literature on anthocyanin production, namely the biosynthesis of anthocyanin pathway genes, production by microbial cell factories, and the regulatory factors that can modulate the production of anthocyanins. Understanding these mechanisms will provide new biotechnological approaches.Key points• Factors affecting the regulation of anthocyanins• Focus on degradation, biosynthesis pathway genes, and alternative systems for the production of anthocyanins• Microbial cell factories can be used to produce large amounts of anthocyanins.

Physicochemical Characterization and In Vitro Digestibility Study of an In Silico Designed Recombinant Protein Enriched with Large Neutral Amino Acids and Lacking Phenylalanine for Phenylketonuria.

In our previous study, a 3D structure of LNAA66 model protein containing 4-5 α-helices, high large neutral amino acids (LNAA) and lacking phenylalanine was designed, refined, expressed in Pichia pastoris and confirmed by Western blotting. Here the study is focused on the characterization of the expressed and purified recombinant LNAA66 protein. The results revealed that the expressed protein had 68.59% of LNAA enrichment, containing 41.6% of α-helix, 50.4% turns and 8% ß-sheet, which are as per the in silico designed protein. The LC-ESI-MS/MS results confirmed the recombinant protein by identifying the first 30 N-terminal amino acids with a sequence coverage of ~ 29%. The protein was digested entirely into smaller molecular weight fragments when treated with digestive enzymes mimicking the human GI tract digestion, which indicated complete digestibility of the protein. These results suggest that the protein can be utilized for the envisioned application of dietary treatment for phenylketonuria.

Tuberculosis Pathways to Care and Transmission of Multidrug Resistance in India.

Rationale: India is experiencing a regional increase in cases of multidrug-resistant tuberculosis (MDR-TB). Objectives: Given the complexity of MDR-TB diagnosis and care, we sought to address key knowledge gaps in MDR risk factors, care delays, and drivers of delay to help guide disease control. Methods: From January 2018 to September 2019, we conducted interviews with adults registered with the National TB Elimination Program for MDR (n = 128) and non-MDR-TB (n = 269) treatment to quantitatively and qualitatively study care pathways. We collected treatment records and GeneXpert-TB/RIF diagnostic reports. Measurements and Main Results: MDR-TB was associated with young age and crowded residence. GeneXpert rifampicin resistance diversity was measured at 72.5% Probe E. Median time from symptom onset to diagnosis of MDR was 90 days versus 60 days for non-MDR, Wilcoxon P < 0.01. Delay decreased by a median of 30 days among non-MDR patients with wider access to GeneXpert, Wilcoxon P = 0.02. Pathways to care were complex, with a median (interquartile range) of 4 (3-5) and 3 (2-4) encounters for MDR and non-MDR, respectively. Of patients with MDR-TB, 68% had their first encounter in the private sector, and this was associated with a larger number of subsequent healthcare encounters and catastrophic expenditure. Conclusions: The association of MDR with young age, crowding, and low genotypic diversity raises concerns of ongoing MDR transmission fueled by long delays in care. Delays are decreasing with GeneXpert use, suggesting the need for routine use in presumptive TB. Qualitatively, we identify the need to improve patient retention in the National TB Elimination Program and highlight patients' trust relationship with private providers.

Microwave prompted solvent-free synthesis of new series of heterocyclic tagged 7-arylidene indanone hybrids and their computational, antifungal, antioxidant, and cytotoxicity study.

In this study, we report the expeditious synthesis of ten new antifungal and antioxidant agents containing heterocyclic linked 7-arylidene indanone moiety. The solvent-free microwave technique, ample substrate scope, superfast synthesis, and very simple operation are noteworthy features of this protocol. Antifungal activities of the newly synthesized compounds were evaluated against four fungal strains namely Rhizophus oryzae, Mucor mucido, Aspergillus niger, and Candida albicans. Most of the compounds were shown strong inhibition of the investigated fungal agents. In vitro, antioxidant potential against DPPH and OH radicals affirmed that the synthesized compounds are good to excellent radicals scavenging agents. The cytotoxicity data of the synthesized compounds towards HL-60 cells uncovered that the synthesized compounds display very low to negligible cytotoxicity. The structural and quantum chemical parameters of the synthesized compounds were explored by employing density functional theory (DFT) at B3LYP functional using 6-311G(d,p) basis set. The compound 3a is discussed in detail for the theoretical and experimental correlation. Time-dependent density functional theory (TD-DFT) at CAM-B3LYP functional with 6-311G(d,p) basis set was used for the electronic absorption study in the gas phase and indichloromethane and benzene solvents. The UV-Visible absorption peaks and fundamental vibrational wavenumbers were computed and a good agreement between observed and theoretical results has been achieved. From the DFT and antifungal activity correlation, it has been found that the 7-heteroarylidene indanones with more stabilized LUMO energy levels display good antifungal potential.

Characterization of in silico modeled synthetic protein enriched with branched-chain amino acids expressed in Pichia pastoris.

We have designed earlier the 3-dimensional structure of protein enriched with 56% branched-chain amino acids (BCAA) based on an α-helical coiled-coil structure. The chemically synthesized DNA (BCAA51 gene) was expressed in Pichia pastoris and confirmed by SDS-PAGE and western blot analysis. In the present study, the purified recombinant protein was characterized using circular dichroism and data revealed that the secondary structure contained 53.5% α-helix, 3.2% ß-strand, and 43.3% turns, which is in concurrence with the overall structure predicted by in silico modeling. The LC-ESI-MS/MS spectra revealed that three peptide masses showed similarity to peptides like EQLTK, LEIVIR, and ILDK, of the modeled BCAA51 protein with the sequence coverage of ~16% from N-terminal region. The N-terminal sequence of the first seven amino acid residues (EQLTKLE) was exactly matching with the in silico designed protein. In vitro digestibility of the protein using SGF and SIF showed the disappearance of ~11 kDa band and appearance of low molecular weight peptides, which indicated that the protein was easily digestible and non-allergenic, which is the overall objective of this study. Further in vivo digestibility and toxicology studies are required to conclusively utilize this protein as a supplement for the treatment of chronic liver diseases.

In silico modelling and characterization of eight blast resistance proteins in resistant and susceptible rice cultivars.

BACKGROUND: Nucleotide-binding site-leucine-rich repeat (NBS-LRR) resistance genes are the largest class of plant resistance genes which play an important role in the plant defense response. These genes are better conserved than others and function as a recognition-based immune system in plants through their encoded proteins. RESULTS: Here, we report the effect of Magnaporthe oryzae, the rice blast pathogen inoculation in resistant BR2655 and susceptible HR12 rice cultivars. Transcriptomic profiling was carried out to analyze differential gene expression in these two cultivars. A total of eight NBS-LRR uncharacterized resistance proteins (RP1, RP2, RP3, RP4, RP5, RP6, RP7, and RP8) were selected in these two cultivars for in silico modeling. Modeller 9.22 and SWISS-MODEL servers were used for the homology modeling of eight RPs. ProFunc server was utilized for the prediction of secondary structure and function. The CDvist Web server and Interpro scan server detected the motif and domains in eight RPs. Ramachandran plot of eight RPs confirmed that the modeled structures occupied favorable positions. CONCLUSIONS: From the present study, computational analysis of these eight RPs may afford insights into their role, function, and valuable resource for studying the intricate details of the plant defense mechanism. Furthermore, the identification of resistance proteins is useful for the development of molecular markers linked to resistance genes.

Effect of Conformance Control Patterns and Size of the Slug of In Situ Supercritical CO2 Emulsion on Tertiary Oil Recovery by Supercritical CO2 Miscible Injection for Carbonate Reservoirs.

The reservoir heterogeneity is the major cause of poor volumetric sweep efficiency in sandstone and carbonate reservoirs. Displacing fluids (water, chemical solution, gas, and supercritical CO2 (sc-CO2)) flow toward the high permeable zone. A significant fraction of oil remains in the low permeable zone due to the permeability contrast. This study used in situ sc-CO2 emulsion as a conformance control agent to plug the high permeable zone and improve the low permeable zone's volumetric sweep efficiency in carbonate formation. We investigated the effect of two types of conformance control patterns and the size of sc-CO2 emulsion on tertiary oil recovery performance by sc-CO2 miscible injection for carbonate reservoirs at reservoir conditions. The conformance control patterns are achieved using two different approaches. In the first approach, the low permeable zone was isolated, and the diverting gel system, a 0.4 pore volume slug, was injected into a high permeable zone. In the second approach, the simultaneous injection of the diverting gel system, a 0.2 pore volume slug, was done on both the low and high permeable zones. The first sc-CO2 injection was conducted as a tertiary oil recovery mode to recover the remaining oil after water flooding. The diverting gel system was injected after the first sc-CO2 flood for the conformance control. The second or post sc-CO2 injection was conducted after the diverting gel system injection. The diverting gel system used in this study consisted of a polymer and a surfactant. An in situ emulsion was generated when the injected diverting gel system interacts with the sc-CO2 in the core plug. Results obtained from dual-core core flooding experiments suggested that the in situ sc-CO2 emulsion was generated successfully in the formation based on the different pressure increases and observation of the dual-core core flooding experiments. The volumetric sweep efficiency and oil recovery in both conformance control patterns were improved. The production performances were also compared for both conformance control models before and after the diverting gel system injection. The conformance control model 2 (simultaneous injection of the diverting gel system into low and high permeability cores) has a better choice to be applied in field application due to high recovery with a small sc-CO2 emulsion easy operation in the field.

An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim to develop a neuromorphic system for tactile pattern recognition. We particularly target texture recognition as it is one of the most necessary and challenging tasks for artificial sensory systems. Our system consists of a piezoresistive fabric material as the sensor to emulate skin, an interface that produces spike patterns to mimic neural signals from mechanoreceptors, and an extreme learning machine (ELM) chip to analyze spiking activity. Benefiting from intrinsic advantages of biologically inspired event-driven systems and massively parallel and energy-efficient processing capabilities of the ELM chip, the proposed architecture offers a fast and energy-efficient alternative for processing tactile information. Moreover, it provides the opportunity for the development of low-cost tactile modules for large-area applications by integration of sensors and processing circuits. We demonstrate the recognition capability of our system in a texture discrimination task, where it achieves a classification accuracy of 92% for categorization of ten graded textures. Our results confirm that there exists a tradeoff between response time and classification accuracy (and information transfer rate). A faster decision can be achieved at early time steps or by using a shorter time window. This, however, results in deterioration of the classification accuracy and information transfer rate. We further observe that there exists a tradeoff between the classification accuracy and the input spike rate (and thus energy consumption). Our work substantiates the importance of development of efficient sparse codes for encoding sensory data to improve the energy efficiency. These results have a significance for a wide range of wearable, robotic, prosthetic, and industrial applications.

A Saccade Based Framework for Real-Time Motion Segmentation Using Event Based Vision Sensors.

Motion segmentation is a critical pre-processing step for autonomous robotic systems to facilitate tracking of moving objects in cluttered environments. Event based sensors are low power analog devices that represent a scene by means of asynchronous information updates of only the dynamic details at high temporal resolution and, hence, require significantly less calculations. However, motion segmentation using spatiotemporal data is a challenging task due to data asynchrony. Prior approaches for object tracking using neuromorphic sensors perform well while the sensor is static or a known model of the object to be followed is available. To address these limitations, in this paper we develop a technique for generalized motion segmentation based on spatial statistics across time frames. First, we create micromotion on the platform to facilitate the separation of static and dynamic elements of a scene, inspired by human saccadic eye movements. Second, we introduce the concept of spike-groups as a methodology to partition spatio-temporal event groups, which facilitates computation of scene statistics and characterize objects in it. Experimental results show that our algorithm is able to classify dynamic objects with a moving camera with maximum accuracy of 92%.

Discrimination of Dynamic Tactile Contact by Temporally Precise Event Sensing in Spiking Neuromorphic Networks.

This paper presents a neuromorphic tactile encoding methodology that utilizes a temporally precise event-based representation of sensory signals. We introduce a novel concept where touch signals are characterized as patterns of millisecond precise binary events to denote pressure changes. This approach is amenable to a sparse signal representation and enables the extraction of relevant features from thousands of sensing elements with sub-millisecond temporal precision. We also proposed measures adopted from computational neuroscience to study the information content within the spiking representations of artificial tactile signals. Implemented on a state-of-the-art 4096 element tactile sensor array with 5.2 kHz sampling frequency, we demonstrate the classification of transient impact events while utilizing 20 times less communication bandwidth compared to frame based representations. Spiking sensor responses to a large library of contact conditions were also synthesized using finite element simulations, illustrating an 8-fold improvement in information content and a 4-fold reduction in classification latency when millisecond-precise temporal structures are available. Our research represents a significant advance, demonstrating that a neuromorphic spatiotemporal representation of touch is well suited to rapid identification of critical contact events, making it suitable for dynamic tactile sensing in robotic and prosthetic applications.

Encapsulation of Piezoelectric Transducers for Sensory Augmentation and Substitution with Wearable Haptic Devices.

The integration of polymeric actuators in haptic displays is widespread nowadays, especially in virtual reality and rehabilitation applications. However, we are still far from optimizing the transducer ability in conveying sensory information. Here, we present a vibrotactile actuator characterized by a piezoelectric disk embedded in a polydimethylsiloxane (PDMS) shell. An original encapsulation technique was performed to provide the stiff active element with a compliant cover as an interface towards the soft human skin. The interface stiffness, together with the new geometry, generated an effective transmission of vibrotactile stimulation and made the encapsulated transducer a performant component for the development of wearable tactile displays. The mechanical behavior of the developed transducer was numerically modeled as a function of the driving voltage and frequency, and the exerted normal forces were experimentally measured with a load cell. The actuator was then tested for the integration in a haptic glove in single-finger and bi-finger condition, in a 2-AFC tactile stimulus recognition test. Psychophysical results across all the tested sensory conditions confirmed that the developed integrated haptic system was effective in delivering vibrotactile information when the frequency applied to the skin is within the 200⁻700 Hz range and the stimulus variation is larger than 100 Hz.

CONE: Convex-Optimized-Synaptic Efficacies for Temporally Precise Spike Mapping.

Spiking neural networks are well suited to perform time-dependent pattern recognition problems by encoding the temporal dimension in precise spike times. With an appropriate set of weights, a spiking neuron can emit precisely timed action potentials in response to spatiotemporal input spikes. However, deriving supervised learning rules for spike mapping is nontrivial due to the increased complexity. Existing methods rely on heuristic approaches that do not guarantee a convex objective function and, therefore, may not converge to a global minimum. In this paper, we present a novel technique to obtain the weights of spiking neurons by formulating the problem in a convex optimization framework, rendering it be compatible with the established methods. We introduce techniques to influence the weight distribution and membrane trajectory, and then study how these factors affect robustness in the presence of noise. In addition, we show how the existence of a solution can be determined and assess memory capacity limits of a neuron model using synthetic examples. The practical utility of our technique is further assessed by its application to gait-event detection using the experimental data.

Gasification: An alternative solution for energy recovery and utilization of vegetable market waste.

Vegetables waste is generally utilized through a bioconversion process or disposed of at municipal landfills, dumping sites or dumped on open land, emitting a foul odor and causing health hazards. The presents study deals with an alternative way to utilize solid vegetable waste through a thermochemical route such as briquetting and gasification for its energy recovery and subsequent power generation. Briquettes of 50 mm diameter were produced from four different types of vegetable waste. The bulk density of briquettes produced was increased 10 to 15 times higher than the density of the dried vegetable waste in loose form. The lower heating value (LHV) of the briquettes ranged from 10.26 MJ kg-1 to 16.60 MJ kg-1 depending on the type of vegetable waste. The gasification of the briquettes was carried out in an open core downdraft gasifier, which resulted in syngas with a calorific value of 4.71 MJ Nm-3 at the gasification temperature between 889°C and 1011°C. A spark ignition, internal combustion engine was run on syngas and could generate a maximum load up to 10 kWe. The cold gas efficiency and the hot gas efficiency of the gasifier were measured at 74.11% and 79.87%, respectively. Energy recovery from the organic vegetable waste was possible through a thermochemical conversion route such as briquetting and subsequent gasification and recovery of the fuel for small-scale power generation.