Efficient and Visual Detention of Ammonia and TNP Vapors by a Sustainable Highly Luminescent 1D Zn(II) Coordination Polymer.

To realize the aim of easy and accurate detection of ammonia and picric acid (PA) in both aqueous and vapor phases based on function-oriented investigation principles, in the present study, we include a luminescent performance with recognition performance, taking into account the application conditions. Zn(II) ions with luminescence qualities and an amine-substituted imidazole moiety with selective recognition properties towards picric acid and ammonia are coupled to generate a novel 1D luminous Zn(II) coordination polymer, Zn-CP [{Zn(II)( 2-ABZ)2(2-BDC)}].MeOH]∞, where 2-ABZ and 2-BDC stand for terephthalic acid and protonated 2 aminobenzimidazole, respectively.

Ru(III)-PhI(OAc)─A Combination for Generation of Isocyanate Intermediate from Benzimidate through a Rearrangement: Synthesis of Unsymmetrical Urea, Carbamate, and Chiral Analogues.

Ru(III)-PhI(OAc), an unprecedented combination, is a highly efficient reagent system for the in situ generation of a valuable isocyanate intermediate from benzimidate synthons through a rearrangement. It unlocks a powerful platform for forming diverse C-N bonds, enabling the one-pot synthesis of an expansive array of valuable unsymmetrical ureas, carbamates, and their chiral analogues toward complex molecular structures with high selectivity and excellent yields. This new strategy not only exemplifies efficiency but also serves as a versatile tool for the construction of valuable molecular architectures, enhancing the scope and impact of modern synthetic chemistry.

New routes towards azomethine ylide generation from prolines to synthesize diverse -heterocycles: a DFT supported -selective mechanism.

Azomethine ylides are generated using either organocatalysts or metal catalysts a ballet of decarboxylative C-N coupling choreographed by prolines. These strategies enable diastereoselective [3 + 2] cycloaddition, C-C coupling, and ring annulation, providing sustainable routes. The synthesized pyrrolizines and other heterocycles have potential applications in the development of crucial biomolecules and pharmaceuticals.

Synergistic Improvement of Antibacterial and Osteogenic Differentiation of Thermomechanically Processed Mg-Zr-Sr-Ce Alloy: Insights into the Role of Precipitate Evolution Supported by AIMD Simulation Study.

In the present study, we have discussed the influence of forging temperature (623 K (FT623), 723 K (FT723) and 823 K (FT823)) on microstructure and texture evolution and its implication on mechanical behavior, - biocorrosion, antibacterial response, and cytocompatibility of microalloyed Mg-Zr-Sr-Ce alloy. Phase analysis, SEM, and TEM characterization confirm the presence of MgCe precipitate, and its stability was further validated by performing molecular dynamic simulation study. FT723 exhibits strengthened basal texture, higher fraction of second phases, and particle-stimulated nucleation-assisted DRX grains compared to other two specimens, resulting in superior strength with comparable ductility.

Cu-Catalyzed Radical Reaction of Benzimidates to Form Valuable 4,5-Dihydrooxazoles through Regioselective Aerobic Oxidative Cross-Coupling.

A straightforward Cu(I)-catalyzed oxidative cross-coupled organic transformation has been developed under mild conditions for the construction of functionalized 4,5-dihydrooxazoles through a four-bond-forming regiocontrolled C-C/C-N/C-O coupling strategy emerging benzimidates, paraformaldehyde, and 1,3-diketo analogues using eco-friendly O as the sole oxidant. The fundamental features of these designed approaches involve operational simplicity, selectivity, generality, and a broad substrate scope with high yields under the same reaction conditions.

Role of pinch in Argon impurity transport in ohmic discharges of Aditya-U Tokamak.

We present experimental results of the trace argon impurity puffing in the ohmic plasmas of Aditya-U tokamak performed to study the argon transport behaviour. Argon line emissions in visible and Vacuum Ultra Violet (VUV) spectral ranges arising from the plasma edge and core respectively are measured simultaneously. During the experiments, space resolved brightness profile of Ar line emissions at 472.

Evaluation of Sagittal Curving Osteotomy vs Conventional Advancement Genioplasty in Retrogenia Patients: a Randomized Control Trial.

Background And Objectives: With increasing aesthetic awareness, in addition to the forehead, nose, and cheekbone prominence, the chin nowadays is seen as one of the most important parts of the facial skeleton. Position of the chin has a strong influence on the assessment of the facial harmony; its different types and forms dominate the appearance. Furthermore, the expression of the chin is equated with character traits, and thus, it is an important component of the profile forms.

Catalytic I-moist DMSO-mediated synthesis of valuable α-amidohydroxyketones and unsymmetrical -bisamides from benzimidates.

We developed an efficient and straightforward I-catalyzed strategy for the synthesis of functionalized α-amidohydroxyketones and symmetrical and unsymmetrical bisamides using incipient benzimidate scaffolds as starting materials and moist-DMSO as a reagent and solvent. The developed method proceeds through chemoselective intermolecular N-C-bond formation of benzimidates and the α-C(sp)-H bond of acetophenone moieties. The key advantages of these design approaches include broad substrate scope and moderate yields.

First results of fast visible imaging diagnostic in Aditya-U tokamak.

A Fast Visible Imaging Diagnostic (FVID) system, measuring the visible light emission spectrum (400-1000 nm) from tokamak plasma, has been installed on the Aditya-U tokamak to monitor the two-dimensional dynamics of the poloidal cross section of the plasma. In this work, we present the design and installation of the FVID system on the Aditya-U tokamak. The evolution of plasma and plasma-wall interactions is described.

Initial results from near-infrared spectroscopy on ADITYA-U tokamak.

Spectroscopy in vacuum ultraviolet (VUV) and visible ranges plays an important role in the investigation and diagnosis of tokamak plasmas. However, under harsh environmental conditions of fusion grade devices, such as ITER, VUV-visible systems encounter many issues due to the degradation of optical components used in such systems. Here, near-infrared (NIR) spectroscopy has become an effective tool in understanding the edge plasma dynamics.

A Family of 2D-MXenes: Synthesis, Properties, and Gas Sensing Applications.

Gas sensors, capable of detecting and monitoring trace amounts of gas molecules or volatile organic compounds (VOCs), are in great demand for numerous applications including diagnosing diseases through breath analysis, environmental and personal safety, food and agriculture, and other fields. The continuous emergence of new materials is one of the driving forces for the development of gas sensors. Recently, 2D materials have been gaining huge attention for gas sensing applications, owing to their superior electrical, optical, and mechanical characteristics.

A processive GH9 family endoglucanase of Bacillus licheniformis and the role of its carbohydrate-binding domain.

One of the critical steps in lignocellulosic deconstruction is the hydrolysis of crystalline cellulose by cellulases. Endoglucanases initially facilitate the breakdown of cellulose in lignocellulosic biomass and are further aided by other cellulases to produce fermentable sugars. Furthermore, if the endoglucanase is processive, it can adsorb to the smooth surface of crystalline cellulose and release soluble sugars during repeated cycles of catalysis before dissociating.

Antiviral potential of nanoparticles for the treatment of Coronavirus infections.

Background: On 31st December 2019 in Wuhan, China, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was acknowledged. This virus spread quickly throughout the world causing a global pandemic. The World Health Organization declared COVID-19 a pandemic disease on 11th March 2020.

COVID-19: morphology and mechanism of the SARS-CoV-2, global outbreak, medication, vaccines and future of the virus.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is a lethal virus that was detected back on 31st December 2019 in Wuhan, Hubei province in China, and since then this virus has been spreading across the globe causing a global outbreak and has left the world fighting against the virus. The disease caused by the SARS-CoV-2 was named COVID-19 and this was declared a pandemic disease by the World Health Organization on 11th March 2020. Several nations are trying to develop a vaccine that can save millions of lives.

A Soft Voting Ensemble-Based Model for the Early Prediction of Idiopathic Pulmonary Fibrosis (IPF) Disease Severity in Lungs Disease Patients.

Idiopathic pulmonary fibrosis, which is one of the lung diseases, is quite rare but fatal in nature. The disease is progressive, and detection of severity takes a long time as well as being quite tedious. With the advent of intelligent machine learning techniques, and also the effectiveness of these techniques, it was possible to detect many lung diseases.

Artificial Intelligence Is Reshaping Healthcare amid COVID-19: A Review in the Context of Diagnosis & Prognosis.

Preventing respiratory failure is crucial in a large proportion of COVID-19 patients infected with SARS-CoV-2 virus pneumonia termed as Novel Coronavirus Pneumonia (NCP). Rapid diagnosis and detection of high-risk patients for effective interventions have been shown to be troublesome. Using a large, computed tomography (CT) database, we developed an artificial intelligence (AI) parameter to diagnose NCP and distinguish it from other kinds of pneumonia and traditional controls.

Development of a System for Storing and Executing Bio-Signal Analysis Algorithms Developed in Different Languages.

With the development of mobile and wearable devices with biosensors, various healthcare services in our life have been recently introduced. A significant issue that arises supports the smart interface among bio-signals developed by different vendors and different languages. Despite its importance for convenient and effective development, however, it has been nearly unexplored.

Forecast the Exacerbation in Patients of Chronic Obstructive Pulmonary Disease with Clinical Indicators Using Machine Learning Techniques.

Preventing exacerbation and seeking to determine the severity of the disease during the hospitalization of chronic obstructive pulmonary disease (COPD) patients is a crucial global initiative for chronic obstructive lung disease (GOLD); this option is available only for stable-phase patients. Recently, the assessment and prediction techniques that are used have been determined to be inadequate for acute exacerbation of chronic obstructive pulmonary disease patients. To magnify the monitoring and treatment of acute exacerbation COPD patients, we need to rely on the AI system, because traditional methods take a long time for the prognosis of the disease.

High-efficacy subcellular micropatterning of proteins using fibrinogen anchors.

Protein micropatterning allows proteins to be precisely deposited onto a substrate of choice and is now routinely used in cell biology and in vitro reconstitution. However, drawbacks of current technology are that micropatterning efficiency can be variable between proteins and that proteins may lose activity on the micropatterns. Here, we describe a general method to enable micropatterning of virtually any protein at high specificity and homogeneity while maintaining its activity.

A Supervised Machine Learning Approach to Detect the On/Off State in Parkinson's Disease Using Wearable Based Gait Signals.

Fluctuations in motor symptoms are mostly observed in Parkinson's disease (PD) patients. This characteristic is inevitable, and can affect the quality of life of the patients. However, it is difficult to collect precise data on the fluctuation characteristics using self-reported data from PD patients.

Detection of Parkinson's Disease from 3T T1 Weighted MRI Scans Using 3D Convolutional Neural Network.

Parkinson's Disease is a neurodegenerative disease that affects the aging population and is caused by a progressive loss of dopaminergic neurons in the substantia nigra pars compacta (SNc). With the onset of the disease, the patients suffer from mobility disorders such as tremors, bradykinesia, impairment of posture and balance, etc., and it progressively worsens in the due course of time.

Engineering of a highly thermostable endoglucanase from the GH7 family of Bipolaris sorokiniana for higher catalytic efficiency.

In a previous study, we reported an alkaliphilic and thermostable endoglucanase (BsGH7-3) of glycoside hydrolase family 7 (GH7) from the hemibiotrophic plant pathogen Bipolaris sorokiniana. However, the catalytic efficiency of the enzyme was lower than for some other endoglucanases of the GH7 family reported in the literature. To engineer a more active enzyme, we identified conserved residues in the substrate-binding tunnel and on the surface of the protein that could play a role in charge-charge interaction and stabilize the structure.

Design of a Machine Learning-Assisted Wearable Accelerometer-Based Automated System for Studying the Effect of Dopaminergic Medicine on Gait Characteristics of Parkinson's Patients.

In the last few years, the importance of measuring gait characteristics has increased tenfold due to their direct relationship with various neurological diseases. As patients suffering from Parkinson's disease (PD) are more prone to a movement disorder, the quantification of gait characteristics helps in personalizing the treatment. The wearable sensors make the measurement process more convenient as well as feasible in a practical environment.