DFT and TDDFT exploration on electronic transitions and bonding aspect of DPA and PTDC ligated transition metal complexes.

CONTEXT: In this study, we have investigated the structure, reactivity, bonding, and electronic transitions of DPA and PDTC along with their Ni-Zn complexes using DFT/TD-DFT methods. The energy gap between the frontier orbitals was computed to understand the reactivity pattern of the ligands and metal complexes. From the energies of FMO's, the global reactivity descriptors such as electron affinity, ionization potential, hardness (η), softness (S), chemical potential (µ), electronegativity (χ), and electrophilicity index (ω) have been calculated. The complexes show a strong NLO properties due to easily polarization as indicated by the narrow HOMO-LUMO gap. The polarizability and hyperpolarizabilities of the complexes indicate that they are good candidates for NLO materials. Molecular electrostatic potential (MEP) maps identified electrophilic and nucleophilic sites on the surfaces of the complexes. TDDFT and NBO analyses provided insights into electronic transitions, bonding, and stabilizing interactions within the studied complexes. DPA and PDTC exhibited larger HOMO-LUMO gaps and more negative electrostatic potentials compared to their metal complexes suggesting the higher reactivity. Ligands (DPA and PDTC) had absorption spectra in the range of 250 nm to 285 nm while their complexes spanned 250 nm to 870 nm. These bands offer valuable information on electronic transitions, charge transfer and optical behavior. This work enhances our understanding of the electronic structure and optical properties of these complexes. METHODS: Gaussian16 program was used for the optimization of all the compounds. B3LYP functional in combination with basis sets, such as LanL2DZ for Zn, Ni and Cu while 6-311G** for other atoms like C, H, O, N, and S was used. Natural bond orbital (NBO) analysis is carried out to find out how the filled orbital of one sub-system interacts with the empty orbital of another sub-system. The ORCA software is used for computing spectral features along with the zeroth order regular approximation method (ZORA) to observe its relativistic effects. TD-DFT study is carried out to calculate the excitation energy by using B3LYP functional.

COVID-19 Vaccination in a Patient With Gluten Enteropathy: A Case Report.

In India, the COVID-19 vaccination for adolescents aged 15-17 years has been started since January 2022. Gluten enteropathy, also known as celiac or nontropical sprue, can arise as an autoimmune disease of the small intestines. We report a 15-year-old female with a history of allergy to gluten-containing products who came for the first dose of the COVID-19 vaccination to adult vaccination OPD at All India Institute of Medical Sciences, Jodhpur. After taking a detailed history, she had an allergy to gluten-containing products for five years. She had no previous history of allergic reactions to injections or medicines. The first dose of Covaxin was given to this female under proper supervision, and she was followed up for any adverse events. We did not find any evidence of adverse events following the COVID-19 vaccination in people with gluten enteropathy. The patient was discharged after one hour of observation. To date, no cases of Covaxin vaccination have been reported among gluten enteropathy patients. We discuss the current evidence relating to Covaxin vaccinations, highlighting that administering the vaccine to gluten-sensitive individuals did not cause any adverse reactions. However, proper history taking and other standard procedures should be followed while administering Covaxin to any known allergies.

Extranodal follicular dendritic cell sarcoma presenting as colonic mass: A diagnostic and therapeutic challenge.

Folliclular dendritic cell sarcoma (FDCS) is an extremely rare neoplasm originating from folliclular dendritic cells, both nodally and extranodally. Its primary presentation as a large colonic mass is rare and can be misdiagnosed as epithelial tumor/soft tissue tumor both clinically and through histomorphology. Due to its rarity and limited consensus guidelines about its management, it presents as a diagnostic and therapeutic challenge for pathologists and oncologists. However, accurate diagnosis is imperative due to its distinct prognostic and therapeutic implications. Herein we report, two cases of extranodal FDCS of colon with the aim of contributing to the management of this uncommon entity.

Numerical Investigation on Precipitation Hardening of Mg-Gd Alloys.

The second-phase particles in magnesium alloys could affect the mechanical properties of the material significantly. In this work, 3D finite element models with explicit incorporation of second-phase particles are established. The simulations are calibrated with the experimental results of the Mg-1Gd alloy. The influences of factors, such as the particle distribution, size, and orientation of cylindrical particles, on precipitation hardening are investigated in detail. Three interface conditions between particles and the matrix-perfect bonding and high- and low-strength bonding-are studied at the same time. The interface conditions are shown to exert a stronger influence on precipitation hardening compared to the factors of particle distribution and size. In contrast, the influence of the orientation of cylindrical particles at grain boundaries outweighs the effect of interface property. When second-phase particles are relatively large and all located at grain boundaries, the hardening effect can be improved, and the magnesium alloy shows relatively high flow stress. However, the high hardening effect from the second-phase particles could result in high local stress concentration and possible early failure or low ductility of Mg alloys.

Primary Oropharyngeal SMARCA4-Deficient Carcinoma: Expanding the Diagnostic Spectrum in Head and Neck Cancer.

With the advent of molecular immunohistochemistry and next generation sequencing, Switch/sucrose non-fermentable (SWI/SNF) chromatin remodeling complex altered tumors have gained recognition recently. SWI/SNF related, matrix associated, actin dependent regulator of chromatin subfamily B member 1 (SMARCB1) and SMARCA4 are the primary SWI/SNF components altered in several recently described undifferentiated malignancies in head and neck region with predilection for paranasal sinuses in SMARCB1-deficient tumors and nasal cavity in SMARCA4-deficient tumors. However, to the best of our knowledge, SMARCA4-deficient tumors of the oropharynx have not been described. We present an unusual case of SMARCA4-deficient carcinoma of the oropharynx (palatine tonsil) which is the first case in the literature, expanding the topographic distribution of SMARCA4-deficient tumors in the head and neck region and emphasizing the importance of BRG1 as an essential immunohistochemical marker for the diagnosis of this distinct entity.

Groundwater quality assessment using water quality index and principal component analysis in the Achnera block, Agra district, Uttar Pradesh, Northern India.

The qualitative and quantitative assessment of groundwater is one of the important aspects for determining the suitability of potable water. Therefore, the present study has been performed to evaluate the groundwater quality for Achhnera block in the city of Taj, Agra, India, where groundwater is an important water resource. The groundwater samples, 50 in number were collected and analyzed for major ions along with some important trace element. This study has further investigated for the applicability of groundwater quality index (GWQI), and the principal component analysis (PCA) to mark out the major geochemical solutes responsible for origin and release of geochemical solutes into the groundwater. The results confirm that, majority of the collected groundwater samples were alkaline in nature. The variation of concentration of anions in collected groundwater samples were varied in the sequence as, HCO3- > Cl- > SO42- > F- while in contrast the sequence of cations in the groundwater as Na > Ca > Mg > K. The Piper diagram demonstrated the major hydro chemical facies which were found in groundwater (sodium bicarbonate or calcium chloride type). The plot of Schoellar diagram reconfirmed that the major cations were Na+ and Ca2+ ions, while in contrast; major anions were bicarbonates and chloride. The results showed water quality index mostly ranged between 105 and 185, hence, the study area fell in the category of unsuitable for drinking purpose category. The PCA showed pH, Na+, Ca2+, HCO3- and fluoride with strong loading, which pointed out geogenic source of fluoride contamination. Therefore, it was inferred that the groundwater of the contaminated areas must be treated and made potable before consumption. The outcomes of the present study will be helpful for the regulatory boards and policymaker for defining the actual impact and remediation goal.

Weekly assessment of volumetric and dosimetric changes during volumetric modulated arc therapy of locally advanced head and neck carcinoma: Implications for adaptive radiation therapy-A prospective study.

BACKGROUND: Chemoradiation in head and neck carcinoma (HNC) shows significant anatomical resulting in erroneous dose deposition in the target or the organ at risk (OAR). Adaptive radiotherapy (ART) can overcome this. Timing of significant target and OAR changes with dosimetric impact; thus, most suitable time and frequency of ART is unclear. METHODS: This dosimetric study used prospective weekly non-contrast CT scans in 12 HNC patients (78 scans). OARs and TVs were manually contoured after registration with simulation scan. Dose overlay done on each scan without reoptimization. Dosimetric and volumetric variations assessed. RESULTS: Commonest site was oropharynx. Gross Tumor Volume (GTV) reduced from 47.5 ± 19.2 to 17.8 ± 10.7 cc. Nodal GTV reduced from 15.7 ± 18.8 to 4.7 ± 7.1 cc. Parotid showed mean volume loss of 35%. T stage moderately correlated with GTV regression. CONCLUSION: Maximum GTV changes occurred after 3 weeks. Best time to do single fixed interval ART would be by the end of 3 weeks.

LSTMCNN: A hybrid machine learning model to unmask fake news.

The widespread dissemination of false information across various online platforms has emerged as a matter of paramount concern due to the potential harm it poses to individuals, communities, and entire nations. Substantial efforts are currently underway in the research community to combat this issue. A burgeoning area of study gaining significant traction is the development of fake news identification techniques. However, this field faces formidable challenges primarily stemming from limited resources, including access to comprehensive datasets, computational resources, and evaluation tools. To overcome these challenges, researchers are exploring various methodologies. One promising approach involves the use of feature abstraction and vectorization techniques. In this context, we highly recommend utilizing the Python sci-kit-learn module, which offers many invaluable tools such as the Count Vectorizer and Tiff Vectorizer. These tools enable the efficient handling of text data by converting it into numerical representations, thereby facilitating subsequent analysis. Once the text data is appropriately transformed, the next crucial step involves feature selection. To achieve optimal results, researchers often employ feature selection methods based on misperception matrices. These methods allow for the exploration and selection of the most suitable features, which are essential for achieving the highest accuracy in fake news identification.

Implementation of the deep learning method for signal detection in massive-MIMO-NOMA systems.

The deep learning method (DLM) is one way to fix issues in optical nonorthogonal multiple access (O-NOMA) systems that are caused by signals that overlap and interfere with each other. NOMA increases the optical framework's spectrum efficiency, allowing several users to share the same time-frequency resources. However, NOMA-DLM-based detection's complicated interference patterns and variable channel conditions are challenging for conventional detection methods to manage. By utilizing deep neural networks' advantages, these methods are able to overcome these challenges and improve detection performance. An overview of the main features and advantages of DLM detection in massive multiple input and output (M-MIMO) O-NOMA systems is given in this article. It describes the essential elements, such as the training procedure and the network design. In order to process the sent symbols or decode data streams, DLM networks are built to process the incoming signal, power allocation coefficients, and extra information. Gradient descent optimization is used to update the network parameters iteratively while training the network, and a diverse and representative dataset is created. Additionally, the challenges of detecting deep learning in O-NOMA systems are examined. It recognizes that in order to get the best results, significant computational resources, a large amount of training data, and careful model design are required. It looks at and compares the 16 × 16, 32 × 32, and 64 × 64 M-MIMO-NOMA models in terms of bit error rate (BER), complexity, and power spectral density (PSD). The suggested DLM algorithms have been demonstrated to perform better than traditional methods by achieving an excellent BER of 10-3 at 4.1 dB and PSD (-2500) performance with low complexity.

A Comprehensive Review of the Diverse Spectrum Activity of 1,2,3-Triazole-linked Isatin Hybrids.

Heterocyclic compounds containing 1,2,3-triazole and isatin as core structures have emerged as promising drug candidates due to their diverse biological activities such as anti-cancer, antifungal, antimicrobial, antitumor, anti-epileptic, antiviral, and more. The presence of 1,2,3-triazoles and isatin heterocycles in these hybrids, both individually known for their medicinal significance, has increasingly piqued the interest of drug discovery researchers, as they seek to delve deeper into their extensive pharmacological potential for enhancing therapeutic efficacy. Moreover, these hybrid compounds are synthetically accessible using readily available materials. Therefore, there is a pressing need to provide a comprehensive overview of the existing knowledge in this field, offering valuable insights to readers and paving the way for the discovery of novel 1,2,3-triazole-linked isatin hybrids with therapeutic potential.

150 Gbps THz Chipscale Topological Photonic Diplexer.

Photonic diplexers are being widely investigated for high data transfer rates in on-chip communication. However, dividing the available spectrum into nonoverlapping multicarrier frequency sub-bands has remained a challenge in designing frequency-selective time-invariant channels. Here, an on-chip topological diplexer is reported exhibiting terahertz frequency band filtering through Klein tunneling of topological edge modes. The silicon topological diplexer chip facilitates two high-speed channels with quadrature amplitude modulation (QAM) over a broad bandwidth of 12.5 GHz each. These channels operate at carrier frequencies of 305 and 321.6 GHz, achieving a combined diplexer capacity of 150 Gbit s-1 . To ensure minimal interference between adjacent channels, a guard band is implemented. Topologically protected edge modes suppress the frequency selective fading of the broadband signals and hold promise for diverse integrated photonic applications spanning terahertz and telecommunication realms, including the design of lossless topological multiplexers, interconnects, antennas, and modulators for the sixth to X generation (6G to XG) wireless.

Birth Asphyxia among Neonates Admitted to the Neonatal Intensive Care Unit of a Tertiary Care Hospital.

Introduction: Birth asphyxia causes significant morbidity and mortality among neonates, especially in low-income and middle-income countries like Nepal. However, there is a paucity of data regarding its burden. This study aimed to find the prevalence of birth asphyxia among neonates admitted to the neonatal intensive care unit of a tertiary care hospital. Methods: This descriptive cross-sectional study was conducted among neonates at a tertiary care hospital between 15 January 2022 to 14 January 2023 after obtaining ethical approval from the Institutional Review Committee. Neonates with gestational age ≥35 weeks were included and those with major congenital anomalies were excluded. A convenience sampling method was used. A point estimate was calculated at a 95% Confidence Interval. Results: Among 902 neonates, 120 (13.30%) (11.08-15.52, 95% Confidence Interval) had birth asphyxia. A total of 108 (90%) were outborn, and 84 (70%) were males. HIE stage-I, II and III were seen in 47 (39.17%), 64 (53.33%) and 9 (7.50%) of the asphyxiated neonates respectively. Poor suck 92 (76.67%), seizures 73 (60.83%) and lethargy 70 (58.33%) were common abnormal neurological findings. Death occurred in 15 (12.50%) neonates in the hospital. Conclusions: The prevalence of birth asphyxia was found to be similar to other studies done in similar settings. The high burden underscores an urgent need to implement better perinatal care and delivery room management practices. Keywords: hypoxic-ischemic encephalopathy; neonates; prevalence.

Unveiling a robust and high-temperature-stable two-dimensional ZnAl layered double hydroxide nanosheet based flexible triboelectric nanogenerator.

Triboelectric nanogenerators have the ability to harvest low- and mid-frequency vibrational energy from the environment; however, achieving stable performance of the nanogenerator device in high-temperature conditions remains challenging. In this work, a flexible and temperature-stable polyvinyl alcohol (PVA)/layered double hydroxides (LDH) nanocomposite-based triboelectric nanogenerator was developed to harvest unexploited vibrational energy for the first time. Crystalline ZnAl LDH nanosheets grown by a hydrothermal route are used to fabricate the high-performance flexible nanogenerator. The ZnAl LDH exhibits fire-retardancy and high-temperature stability (∼500 °C). A triboelectric nanogenerator based on the ZnAl LDH-PVA nanocomposite generated a very high output voltage of 60 V even under a low vertical pressure of 1 kgf. Surprisingly, the developed device shows ultra-stable output performance even up to a temperature of 200 °C. In addition, a ZnAl LDH-nanosheet-reinforced PVA nanocomposite film shows very high dielectric constant of about 5 × 105 at the low-frequency side. The tremendous increase in the output voltage and stable performance are discussed in terms of the high dielectric constant and synergistic effect of the LDH nanosheets and PVA. Furthermore, the device was also used to monitor human body movements such as finger and wrist bending to develop self-powered sensors.

National and regional prevalence of gestational diabetes mellitus in India: a systematic review and Meta-analysis.

BACKGROUND: Gestational diabetes mellitus (GDM) is frequently misdiagnosed during pregnancy. There is an abundance of evidence, but little is known regarding the regional prevalence estimates of GDM in India. This systematic review and meta-analysis aims to provide valuable insights into the national and regional prevalence of GDM among pregnant women in India. METHODS: We conducted an initial article search on PubMed, Scopus, Google Scholar, and ShodhGanga searches to identify quantitative research papers (database inception till 15th June,2022). This review included prevalence studies that estimated the occurrence of GDM across different states in India. RESULTS: Two independent reviewers completed the screening of 2393 articles, resulting in the identification of 110 articles that met the inclusion criteria, which collectively provided 117 prevalence estimates. Using a pooled estimate calculation (with an Inverse square heterogeneity model), the pooled prevalence of GDM in pregnant women was estimated to be 13%, with a 95% confidence interval (CI) ranging from 9 to 16%.. In India, Diabetes in Pregnancy Study of India (DIPSI) was the most common diagnostic criteria used, followed by International Association of Diabetes and Pregnancy Study Groups (IADPSG) and World Health Organization (WHO) 1999. It was observed that the rural population has slightly less prevalence of GDM at 10.0% [6.0-13.0%, I2=96%] when compared to the urban population where the prevalence of GDM was 12.0% [9.0-16.0%, I2 = 99%]. CONCLUSIONS: This review emphasizes the lack of consensus in screening and diagnosing gestational diabetes mellitus (GDM), leading to varied prevalence rates across Indian states. It thoroughly examines the controversies regarding GDM screening by analyzing population characteristics, geographic variations, diagnostic criteria agreement, screening timing, fasting vs. non-fasting approaches, cost-effectiveness, and feasibility, offering valuable recommendations for policy makers. By fostering the implementation of state-wise screening programs, it can contribute to improving maternal and neonatal outcomes and promoting healthier pregnancies across the country.

Microbiology proficiency testing in fish and fishery products: detection of Listeria monocytogenes and Salmonella spp.

This paper presents the results of two proficiency testing (PT) rounds conducted by the Export Inspection Agency (EIA) Chennai laboratory in 2021 for food testing laboratories in India. The PT program was designed in accordance with ISO/TS 22117, a standard for proficiency testing in food microbiology, and targeted Listeria monocytogenes and Salmonella spp as the organisms of focus. The samples were found to be stable and recoverable during the analysis, and all PT sample packages were delivered to participant laboratories in good condition. The participant laboratories reported high sensitivity rates of 100% for PT round 061021 M and 96.49% for PT round 050721 M. The accuracy rate in PT round 061021 M was 91.89% and 92.10% in case of PT round 050721 M. However, there were some false positive and false negative results reported by some participant laboratories in both PT rounds, which may have been caused by operational errors or inconsistencies in analysis. During the PT round 061021 M, out of a total of 38 participant laboratories, five laboratories reported false positive results and one laboratory reported a false negative result. Similarly, during the PT round 050721 M, six laboratories reported false positive results which resulted in their results being deemed unsatisfactory.

Stochastic intelligent computing solvers for the SIR dynamical prototype epidemic model using the impacts of the hospital bed.

The present investigations are related to design a stochastic intelligent solver using the infrastructure of artificial neural networks (ANNs) and scaled conjugate gradient (SCG), i.e. ANNs-SCG for the numerical simulations of SIR dynamical prototype system based impacts of hospital bed. The SIR dynamical model is defined into three classes, susceptible patients in the hospital, infected population and recovered people. The proposed results are obtained through the sample statics of verification, testing and training of the dataset. The selection of the statics for training, testing and validation is chosen as 80%, 8% and 12%. A dataset is proposed based on the Adams scheme for the comparison of dynamical SIR prototype using the impacts of hospital bed. The numerical solutions are presented through the ANNs-SCG in order to reduce the values of the mean square error. To achieve the reliability, capability, accuracy, and competence of ANNs-SCG, the mathematical solutions are presented in the form of error histograms (EHs), regression, state transitions (STs) and correlation.

A Complex Adult Congenital Heart Disease Case in Pregnancy: A Multidisciplinary Approach.

Multidisciplinary teams decrease the likelihood of adverse pregnancy outcomes in high-risk pregnant cardiac patients. We present the case of a patient with complex congenital heart disease and a mechanical mitral valve, whose treatment included warfarin until delivery despite the discovery of placental hematomas. A multidisciplinary approach mitigated both maternal and fetal adverse pregnancy outcomes.

C-H bond activation by high-valent iron/cobalt-oxo complexes: a quantum chemical modeling approach.

High-valent metal-oxo species serve as key intermediates in the activation of inert C-H bonds. Here, we present a comprehensive DFT analysis of the parameters that have been proposed as influencing factors in modeled high-valent metal-oxo mediated C-H activation reactions. Our approach involves utilizing DFT calculations to explore the electronic structures of modeled FeIVO (species 1) and CoIVO ↔ CoIII-O˙ (species 2), scrutinizing their capacity to predict improved catalytic activity. DFT and DLPNO-CCSD(T) calculations predict that the iron-oxo species possesses a triplet as the ground state, while the cobalt-oxo has a doublet as the ground state. Furthermore, we have investigated the mechanistic pathways for the first C-H bond activation, as well as the desaturation of the alkanes. The mechanism was determined to be a two-step process, wherein the first hydrogen atom abstraction (HAA) represents the rate-limiting step, involving the proton-coupled electron transfer (PCET) process. However, we found that the second HAA step is highly exothermic for both species. Our calculations suggest that the iron-oxo species (Fe-O = 1.672 Å) exhibit relatively sluggish behavior compared to the cobalt-oxo species (Co-O = 1.854 Å) in C-H bond activation, attributed to a weak metal-oxygen bond. MO, NBO, and deformation energy analysis reveal the importance of weakening the M-O bond in the cobalt species, thereby reducing the overall barrier to the reaction. This catalyst was found to have a C-H activation barrier relatively smaller than that previously reported in the literature.

Slow light topological photonics with counter-propagating waves and its active control on a chip.

Topological slow light exhibits potential to achieve stopped light by virtue of its widely known robust and non-reciprocal behaviours. Conventional approach for achieving topological slow light often involves flat-band engineering without disentangling the underlying physical mechanism. Here, we unveil the presence of counter-propagating waves within valley kink states as the distinctive hallmark of the slow light topological photonic waveguides. These counter-propagating waves, supported by topological vortices along glide-symmetric interface, provide significant flexibility for controlling the slowness of light. We tune the group velocity of light by changing the spatial separation between vortices adjacent to the glide-symmetric interface. We also dynamically control the group delay by introducing a non-Hermitian defect using photoexcitation to adjust the relative strength of the counter-propagating waves. This study introduces active slow light topological photonic device on a silicon chip, opening new horizons for topological photon transport through defects, topological light-matter interactions, nonlinear topological photonics, and topological quantum photonics.