Presidency University, Kolkata

A metal free oxidative desulfitative C−N coupling reaction through activation of latent thiol group using hypervalent iodine reagent is being reported in eco‐friendly solvent ethanol. Here, the thio‐amide group present in 5‐alkylidene‐rhodanine has been utilized as latent thiol functionality and C−N coupling with amines is realized. The reaction occurs evading the use of metal catalysts, inert atmosphere, high temperature or microwave heating, and strong base which is normally required for metal catalyzed C−N coupling reaction. Pertinently, here poorly nucleophilic aromatic amines react very efficiently. Desulfitative C−N coupling involving free thiol moiety and poorly nucleophilic aromatic amines in metal free condition has never been accomplished in one step, without requiring high temperature microwave heating or strong bases. The reaction occurs at just 50 °C in few hours under ambient atmosphere. Moreover, here no H2S is released in the environment, since solid sulphur is precipitated out as side product, making this protocol environmentally friendly. Metal free condition, low temperature, use of non‐toxic solvent and reagent, prevention of the release of H2S in the environment make this protocol very much environmentally friendly and highly suitable for C−N coupling in a sustainable way.

Laser marking is the operation to mark the surface with minimal heat interaction and time. The heat interaction of laser with PMMA causes the materials to melt and their melting rate are greatly impacted by in-depth radiation absorption. The paper highlighted the comparative studies of laser marking of red and white PMMA with the view to produce good quality laser marked surface for product identification and traceability. A fiber laser beam with a wavelength of 1064 nm with a spot diameter of 21 µm was used for marking of PMMA material. The laser process variables such as laser irradiation, pulse rate and scan rate were varied to analyse its effect on PMMA materials for achieving the better marking characteristics. Experimental studies revealed that for marking white and red PMMA, high power laser was essential for producing desired marking characteristics and it is the most dominant factor as compared to other laser process variables. Better value of marking characteristics were achieved at laser irradiation of 100 % of 50 W, pulse rate of 85 kHz, and scan rate of 35 mm/s, respectively.

The objective of this work is to present the complete design and simulation of a microelectromechanical system (MEMS) based differential capacitive accelerometer developed to detect tremor signals in patients with Multiple Sclerosis (MS). The primary challenge is to address the difficulties of sensing at low frequencies (below 10 Hz) associated with tremors in multiple sclerosis (MS). The design mainly focuses on the 3.5 to 7.5 Hz band of frequencies. The methods used in the design of the accelerometer consider these multiple attributes to provide optimization with regard to resonance frequency, mechanical stability, and sensitivity. The design is validated by performing finite element analysis (FEA) in COMSOL Multiphysics software. The mechanical properties of the accelerometer are characterized by the development of analytical models to compute resonance frequency and effective spring constant. The FEA results show that the system has a resonance frequency of 5.5 Hz, and the maximum displacement is around 1.77 μm under an acceleration of 0.04 g taking into account bias voltage at operation 10 V in air as external condition for this study; hence mechanical sensitivity was found to be about 44.25 μm. The accelerometer exhibits a considerable dynamic range: from static forces up to near resonant frequencies with very high level sensitivities; linearity also outperforms previous research studies. The feasibility of using a MEMS differential capacitive accelerometer in the effective and accurate evaluation/quantification of tremor signals from MS patients is demonstrated as an emerging technology. Specific documentation and analyzed tremors could have a dramatic impact on many areas of disease identification/management especially in the area of multiple sclerosis.

COVID-19, caused by severe acute respiratory syndrome corona virus 2 (SARS-CoV-2), is primarily a respiratory illness but significantly affects the cardiovascular system as well. After entering the body through the respiratory tract, the virus directly and indirectly disrupts the vascular system. Vascular endothelial cells (ECs), which express ACE2 and TMPRSS2, are targets for viral invasion. However, the predominant cause of widespread vascular damage is the “cytokine storm” induced by the immune response. This leads to EC activation, inflammation, neutrophil activation, and neutrophil–platelet aggregation, causing endothelial injury. Additionally, increased expression of plasminogen activator inhibitor-1 disrupts the balance between prothrombotic and fibrinolytic processes, while activation of the renin–angiotensin–aldosterone system adds oxidative stress to the vascular endothelium. In the heart, SARS-CoV-2 invades ECs, leading to apoptosis and pyroptosis, exacerbated by inflammation and elevated catecholamines. These factors contribute to arrhythmias, strokes, and myocardial infarction in severe cases of COVID-19. This narrative review aims to explore the mechanisms by which SARS-CoV-2 affects the cardiovascular system and to highlight the resulting complications. It also identifies research gaps and discusses potential therapeutic strategies to mitigate the cardiovascular impacts of COVID-19.

Bamboos belong to the grass family Poaceae, sub-family Bambusoideae and possess many interesting developmental features including a long vegetative period before flowering. Previously, transcriptome based analyses have identified differentially expressed transcripts in flowering and vegetative tissues to predict gene clusters of functional relevance. In contrast, limited studies were conducted to characterize individual genes to decipher their precise role to induce flowering. This was primarily due to the unavailability of sufficient genomic resources, which has lately been overcome by the release of additional bamboo genomes. In this study, the APETALA1 gene homologs (MADS14, MADS15, MADS18 and MADS20) have been identified from five sequenced bamboo species (Bonia amplexicaulis, Guadua angustifolia, Raddia guianensis, Olyra lati-folia, Phyllostachys edulis). In addition, APETALA1 homologs from a tropical bamboo (Bambusa tulda) have been PCR amplified, sequenced and included in the analyses to widen spectrum of sampling. Assessment of their phylogenetic and syntenic relationship with related Poaceae neighbours revealed closer relationship between MADS14 and MADS15 members than MADS18 and MADS20. Transcriptional expression patterns of B. tulda BtMADS14, BtMADS15, BtMADS18 and BtMADS20 in vegetative and floral tissues indicated a possible role of BtMADS14 and BtMADS15 in flower induction and differentiation, while BtMADS18 might be associated with seed development. Total 24 proteins were predicted to interact with the Phyllostachys edulis homolog of BtMADS14 protein and 8 of them were members of the MADS-box family. The p35S::BtMADS14 overexpressing Arabidopsis plants flowered 8-10 days earlier than the wild type plants suggesting its possible involvement in the floral induction of B. tulda.

The Jiti–Khuji Diana interfluve of the Himalayan piedmont zone has been considered to reanalyse the tectonic character of the Main Boundary Thrust (MBT) and Main Frontal Thrust (MFT), which are two major east–west trending structural units of the Himalayan orogen. The MBT marks a tectonic boundary between the Lesser and sub-Himalayan sequences (Gansser, Geology of Himalayas, Wiley Interscience, New York, 1964), while the MFT is the youngest deforming front that carries the Siwalik Group of rocks over the Quaternary deposits (Yin, Earth Sci Rev 76:1–131, https://doi.org/10.1016/j.earscirev.2005.05.004, 2006). This area is dissected by three main steams of the Jaldhaka system, i.e. rivers Jiti, Khuji Diana, and Thaljhora; amongst which the Thalhjora flows from east to west and the other two rivers flow roughly from NNE to SSW. Thaljhora and Chalsa fault scarps are observed, respectively, at and near the MBT and MFT. The present research focuses on significance of active Thaljhora and Chalsa fault scarps, which represent the monocline faults that deformed the geomorphic landscape. The displacement along these faults have formed a synform that uplifted over time and formed river terraces by incision processes of rivers. The analysis of morphometric indices confirms the recent neotectonic activities going on in the region. The deformed landforms, emerged as terrace and Doon-shaped valley, are observed between the Jiti fault (MBT) and Chalsa scarp (MFT). The doon-shaped valley is developed as a flat-lying surface situated between the Jiti fault and Thaljhora scarp. This study has deciphered the application of morphometric indices to study the active neotectonics.

The changing nature of groundwater resources is commonly associated with the urban development process around the globe. This is also evident in the different parts of NCT Delhi, which is one of the most metropolitan hubs in the Indian subcontinent. This region offers an intriguing groundwater scenario that has been rapidly evolving in recent years. While studies have attributed this groundwater evolution to anthropogenic intrusion and urban development for the entire city in general, the influence of geogenic factors such as the nature of aquifers, the impact of surface–water interactions, etc., at the local (site-specific) level has not been thoroughly investigated. In regard to this, the objective of this study is to identify the changes in groundwater dynamics of south-western parts of NCT Delhi in the last few years and assess the response of its groundwater system to urbanization with respect to other prevailing local geological factors (such as Delhi ridge, Najafgarh drain, etc.). The inferences for this study were drawn from the compilation of pre-existing researches and satellite imageries, primarily represented by LULC maps as well as remote sensing-based techniques such as NDBI and NDWI. This is supplemented by a simple evaluation of salinity enrichment over the years. This study revealed some interesting facts about the regional groundwater dynamics and groundwater quality in the south-western part of NCT Delhi, including that the rise in urban build-up area (48–71% between 2008 and 2021) corresponds to fluctuations in groundwater dynamics in most places, as well as that there is a clear declining influence of geology on groundwater salinity over the years. These observations were further examined and substantiated by the primary field investigation, leading to development of schematics showing local changes along major sites across the region. The major outcome drawn from all of this hint to the fact that while urbanization plays a critical role in shaping the groundwater dynamics, it does not completely dominate regional groundwater scenario. Moreover, the groundwater dynamics in the study also respond to a delicate network of local factors that have evolved along with urban development in this part of the city over the past two decades. Thus, it could be said that while there is a need to check urbanization to maintain the sustainability of existing groundwater resources in the south-western part of NCT Delhi for better utilization of freshwater resources for all, constant vigilance on local factors such as identifying waterlogged areas, maintaining regulated abstraction in shallow aquifers close to Najafgarh drain, proper development planning in peri-urban areas could also help in the endeavour.

The current article unveils the repercussions obtained from analysing the Casson–Williamson nanofluid flow across a curved stretched surface using the Darcy–Forchheimer model. The modelling is contemplated with homogeneous–heterogeneous chemical reactions. The impact of nonlinear thermal radiation, exponential heat source and magnetic field is considered. Further, response surface methodology is a statistical technique used to understand the association of parametric factors under consideration on the response which is the Nusselt number in the present context. The prime aim of this modelling is to give optimal conditions for producing the highest heat transfer rate to build an efficient model with the aid of sensitivity analysis. In addition, entropy propagated in the media is provided to enhance the importance of this investigation. Runge–Kutta–Fehlberg 4–5th order technique has been used to obtain the numerical output. The analysis reveals that the first-order slip component has a negative effect on velocity distribution, whereas the second-order slip factor has the opposite effect. The Nusselt number decreases as the unsteadiness parameter reaches its maximum value and when the sheet is susceptible to intense radiation. Graphical representations of streamlines and isotherms are provided to illustrate the flow and heat distribution. The sensitivity analysis emphasises that the Brownian motion parameter has positive sensitivity, whereas thermophoresis and an exponential heat source have negative sensitivity on the Nusselt number.

We discuss the nonclassical properties of photon-subtracted compass states (PSCS). Nonclassical behavior is studied using various parameters like the Wigner function, squeezing, and photon statistical parameters like Mandel’s Q-function, second-order correlation function, Agarwal-Tara $A_3$ criterion, and photon number distribution. Further analysis is being done to investigate the sub-Planck structures in the Wigner functions of these PSCS. We also show that the photon subtraction doesn’t cause the loss of sensitivity due to displacement of the states in phase space.

Secret Sharing schemes are very much well-developed in classical cryptography. This paper introduces a novel Secret Sharing scheme that leverages entanglement for secure communication. While our protocol initially focuses on a single reconstructor, it offers the flexibility to dynamically change the reconstructor without compromising the reconstruction security of the shared secret. Traditional Secret Sharing schemes often require secure channels for transmitting secret shares to the reconstructor, which can be costly and complex. In contrast, our proposed protocol eliminates the need for secure channels, significantly reducing implementation overhead. Our proposed scheme introduces a secret reconstruction method for $d \ge 2$, expanding upon previous works that primarily focused on $d > 2.$ Our work provides a unified framework that bridges the gap between the cases $d = 2$ and $d > 2.$ We carefully analyze the conditions under which each case achieves its highest level of security, utilizing newly developed concepts, termed Perfectly Symmetric, Almost Symmetric, and queryless or Vacuously Symmetric entanglements. By eliminating the need for Quantum Fourier Transform and Inverse Quantum Fourier Transform, which were commonly used in previous schemes, we simplify the proposed protocol and potentially improve its efficiency. We thoroughly analyze the correctness and security of our proposed scheme, ensuring its reliability and resistance to certain quantum attacks. Finally, we propose a detailed comparison with the previous works.

For $\sigma ,\kappa$ infinite cardinals with $\kappa \ge \sigma$, we introduce the notion of $\sigma$-matroids on $\kappa$. For $\sigma :=\omega$, the first infinite cardinal, the notion of $\sigma$-matroid coincides with the notion of finitary matroid. One method for obtaining $\sigma$-structures is by adding special subsets of $\kappa$ of size ${\ge }\sigma$ to the collection of independent sets of some already existing matroid structure which contains independent sets only of size ${<}\sigma$. We show that under some additional order property our newly obtained structure actually forms a matroid. Also we show that we can get $\sigma$-structures from any arbitrary matroid structure by considering its circuits. We give two characterizations of some matroid to be a $\sigma$-matroid, one in terms of circuit sizes and another by considering certain topology on $2^\kappa$. Finally, we briefly discuss some results about matroid unions.

The healthcare industry is about to undergo an important shift because to generative artificial intelligence (AI). Unlike traditional AI systems that rely on pre-established rules and algorithms, generative AI has the incredible ability to generate fresh data and produce outputs that approximate human ingenuity and reasoning. Deep learning and natural language processing advances are driving this revolutionary technology, which has the potential to completely change many aspects of healthcare and usher in a new era known as Healthcare 5.0. The potential of generative AI to improve diagnosis speed and accuracy in the medical field is one of its most important uses. Generative AI algorithms can help medical personnel uncover trends, abnormalities, and probable disease flags with remarkable precision by evaluating large datasets of genetic information, medical pictures, and patient records. For instance, generative AI-powered systems can assist doctors in forecasting patient outcomes based on intricate clinical data or help radiologists identify early indicators of cancer in medical images. Generative artificial intelligence has the potential to completely transform the drug development process, which now involves costly, time-consuming trial-and-error research. Algorithms for generative artificial intelligence (AI) can mimic molecular structures and predict how they will interact with biological targets. This makes it possible to create novel medication candidates more quickly, potentially with fewer side effects and higher therapeutic efficacy. This expedites the development of new medicines and advances personalized medicine by enabling medications to be tailored for each patient based on their genetic makeup and particular medical characteristics. Generative AI holds great promise for improving healthcare delivery efficacy and efficiency, in addition to diagnosis and medicine discovery. Healthcare staff can focus more on patient care by using virtual assistants with natural language processing capabilities to streamline administrative tasks like scheduling appointments and recording medical information. Furthermore, generative AI-powered predictive analytics can prevent medical errors, improve hospital operations, and anticipate the need for healthcare resources—all of which improve patient outcomes and lower costs for healthcare providers.

In the current scenario, where we can see young people struggling for their careers, they are even fighting a battle with their stress and tension. None of their work is done without stress to complete their task and compete with others. To overcome stress, one should have good emotional intelligence to cope with emotions and any upcoming stress. But at some point, due to lack of guidance, some people don’t know how to analyze the situations and how to handle them without taking the stress and end up with anxiety, depression, disappointment, suicide, heart attack, stroke etc. Due to the advancement of Human–Computer Interaction (HCI), medical science has leveled up to another peak. Machine Learning and Deep Learning played a major role in such interactions and predictions. Many applications have been developed in past years based on machine learning and deep learning. One of those applications is related to psychology and is still in research. These applications can be used for emotion and stress analysis among people, especially youngsters. Research in this field is being conducted using various verbal and non-verbal parameters. This paper addresses the research problem of improving emotion recognition accuracy and robustness to better analyze and manage stress. The primary objective is to develop an advanced Emotion Recognition System (ERS) that leverages deep learning algorithms to analyses both verbal and non-verbal cues—specifically, speech and body posture, including facial expressions. We have further integrated it with the Flask web framework to make an Emotion Recognition System that takes input in the form of video and audio to analyze Emotions and Stress. We have also compared our proposed ERS with existing ones and found that our ERS gives better results.

This paper addresses the challenge of channel estimation for Reconfigurable Intelligent Surfaces assisted Millimeter Wave Multi-User Multiple-Input Multiple-Output Systems. The task is complex because of the large number of antennas at the Base Station and the passive nature of RIS elements, which lack active transmitter/receiver and signal processing capabilities. In this paper, the mmWave channel is generated using the Saleh-Valenzuela channel model dataset. While compressive sensing algorithms like Orthogonal Matching Pursuit and Approximate Message Passing can be used for channel estimation, their performance is limited by fixed shrinkage functions. To overcome this limitation, a Learned Approximate Message passing network is first explored. However, the performance of the Learned Approximate Message passing network degrades for both non-i.i.d. and i.i.d. Gaussian matrices. Hence, a Learned Vector Approximate Message Passing algorithm is proposed to improve channel estimation accuracy for both matrix types. This paper presents the performance of the Learned Vector Approximate Message Passing network-based channel estimation for Reconfigurable Intelligent Surfaces assisted mmWave Multi-User Multiple-Input Multiple-Output Systems Systems, comparing it with the existing algorithms algorithms. Additionally, the impact of different shrinkage functions, such as Gaussian Mixture, Bernoulli-Gaussian, and Soft Threshold, are also analyzed within the proposed network.

Pyridine is one of the significant six‐membered N‐heterocycles that has gained the attention of the scientific community because it is an integral part of various medicinally important natural products. There is a sizable and expanding market for pyridine derivatives due to their many pharmaceutical, medicinal, and agricultural uses. Numerous chemicals are being tested in clinical studies, in which pyridine analogs have occupied the top position. Pyridine scaffolds are also becoming more and more prominent for the use of modern medicine and are anticipated to have several uses in daily life. In this connection, various techniques have been developed to create novel pyridine derivatives, such as multicomponent one‐pot reactions, green catalysts environmentally friendly solvents, solvent‐free synthesizing, ultrasonic production, and microwave‐assisted synthesis. This study unifies the synthesis of various pyridine‐based molecular frameworks using green protocols and the results will support new ideas about creating biologically active compounds.

Based on Newtonian mechanics, in this article, we present a heuristic derivation of the Friedmann equations, providing an intuitive foundation for these fundamental relations in cosmology. Additionally, using the first law of thermodynamics and Euler’s equation, we derive a set of equations that, at linear order, coincide with those obtained from the conservation of the stress-energy tensor in general relativity. This approach not only highlights the consistency between Newtonian and relativistic frameworks in certain limits, but also serves as a pedagogical bridge, offering insights into the physical principles underlying the dynamics of the universe.