Search

Introduction: Human teeth serve many crucial functions, and aesthetics is one of these. Aesthetics and beauty are often correlated with the Golden Divine Ratio (GDR), a unique proportion hypothesised to exist in individuals or things with a harmonious appearance. Aim: To estimate the crown length, root length, and GDR in extracted human permanent maxillary and mandibular Central Incisors (CI) in the population of Tamil ethnicity from South India. Materials and Methods: This in-vitro cross-sectional study was conducted in the Department of Oral Pathology and Microbiology at Saveetha Dental College and Hospitals, Chennai, Tamil Nadu, India, from January 2023 to October 2023. The study included a total of 90 extracted human teeth from the Institutional tooth repository, out of which 27 were upper permanent CIs and the remaining 63 were mandibular CIs. Crown length and root length were measured using digital vernier calipers, and golden ratios were derived. Statistical Package for Social Sciences (SPSS) software version 26.0. was used for descriptive analysis and deriving means and standard deviation. Results: The average crown length, root length, and total length of upper CIs were 8.06±0.09 mm, 13.01±1.47 mm, and 21.06±2.36 mm, respectively. For the remaining 63 extracted permanent mandibular CIs, the mean crown length, root length, and total length were 7.85±0.66 mm, 12.6±0.97 mm, and 20.45±1.49 mm, respectively. The Root-to-Crown (R/C) ratio and Total Length to Root Length (T/R) ratio approximated 1.618 for both sets of teeth. Conclusion: The crown length of maxillary and mandibular CIs from the Tamil population followed the golden ratio in the present study.

Background Antimicrobial resistance is a growing concern globally, leading to more difficult-to-treat infections and higher mortality rates. Urinary tract infections (UTI) are one of the major indications for prescribing antibiotics, with multidrug resistant Gram-negative bacilli being responsible for a growing proportion of community-acquired uncomplicated UTIs. Our goal is to determine nitrofurantoin, a less costly effective substitute in treating uncomplicated UTI caused by multidrug resistant gram negative bacilli.

As the power generation sector moving towards the sustainability to achieve clean and renewable energy source, the wind power generation plays a vital role due to its abundance in nature. A big chunk of the decrease in carbon emission is a major attribute to the growth of the wind energy sector. Wind turbine production, structural development, logistics, maintenance and R&D are just some of the areas that could benefit from the growth of the wind energy industry. This brought out the attention of researchers of the electrical engineering to focus on wind power generation. It can be more efficient and cost-effective to operate wind turbines as a wind farm rather than individually. This has led to a surge in the construction of wind farms, both onshore and offshore wind farms. Therefore, in this paper, the study and analyse of single Induction generator with wind turbines and 33MW windfarm performance is presented. The simulation result demonstrates the efficiency of DFIG in producing energy at a constant wind speed, as well as its ability to regulate both active and reactive power at steady-state.

Paediatric population is very vulnerable to toxicities resulting from exposure to many traditional medicines, which are often used in our culture as treatments for various ailments. People are unaware of the untoward complications arising from the toxicity of these native medicines, especially camphor. Adding to the problem, parents often believe that native medicines, particularly when applied topically, are safe for children. Here, the author reported a previously healthy 2-year-old child who had multiple episodes of seizures after the mother applied topical camphor oil for five days to relieve the child’s symptoms of nasal congestion. While there is no clear data on the concentration and duration of topical camphor exposure that causes toxicity in children, the case report highlighted the possibility that younger children may develop toxicity in a relatively short period of exposure. In this modern era of evidence-based medicine, it is important to raise awareness among the public, especially parents, that not everything applied to the skin is safe for children, as their anatomy differs from that of adults.

The solar radiation is a critical metric for design and optimal operation of the solar energy system. Most of the locations available solar radiation records are not available due to high cost for buying and maintaining the measuring instruments. Aim of this paper is building an efficient neural network model that can reliably estimate solar radiation. In this work, different ANN models with three popular algorithms admired from the literature are investigated. The models were trained using meteorological data collected over a year from six different places from the hot area locations of Tamil Nadu, India. Based on minimal Mean Absolute Deviation (MAD), Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE), the optimum ANN algorithm and model are determined (R). Furthermore, the research illustrates that the ANN model’s prediction performance is dependent on the entire set of data utilised to train the network. Also, this article aims at finding out the accurate number of hidden layer neurons for the developed model. The proposed ANN model offers improved accuracy and applicability for estimating hourly average global radiation for the purpose of designing or evaluating photovoltaic (PV) installations in areas without meteorological data collection facilities.

An all including control strategy for massive extension decided power foundations in which the stored singular edges are exhausting and the system components don't swing convincingly inside a short period of time stretch is readied. It is suggested to use a two-stage energy management system (EMS) for power networks with massive electric vehicle (EV) consolidation and safe for the biome energy resources. For EVs, the module and battery exchanging modes are the only ones used to determine the best functioning reasons for charging stations and battery exchanging stations (BSS). A chance-grateful upgrade plan that can reasonably obtain the system and the gauge faintness serves to illustrate the proposed stochastic model judicious control (SMPC) issue at this level. The substituting bearing approach for multipliers (ADMM), a spread guess, is used to breathe the progression count when speaking similarly. The causing stage is focused on organising the EV charging tools to continuously follow the primary stage plans, i.e., the goal working centres, and addressing the accusing strains experienced by EV customers via devices for the Advanced Metering Infrastructure (AMI).

Periodontitis is a multifactorial chronic inflammatory disease associated with increased secretion of several proinflammatory mediators such as Interleukin-1β (IL-1β), Interleukin-6 (IL-6), Interleukin-17 (IL-17), Tumour Necrosis Factor-α (TNF-α), Prostaglandins (PGs) in response to increased bacterial load on the tooth surface and within the gingival sulcus leading to the destruction of both hard and soft tissue of the periodontium. The Receptor for Advanced Glycation End products (RAGE) binds multiple ligands, has a transmembrane configuration and is a part of the immunoglobulin receptor family. In healthy individuals RAGE is expressed at lower levels when compared to those with periodontitis and diabetes mellitus. Binding of RAGE to its ligands plays a key role in the inflammatory reactions that lead to disruption of a multitude of cellular processes. One such RAGE ligand involved in inducing hyperinflammatory phenotype is High Mobility Group Box 1 (HMGB1). HMGB1 is a chromatin binding protein predominantly localised in the nucleus and is associated with multiple functions such as Deoxyribonucleic Acid (DNA) repair, nuclear homeostasis, genome stability. In the presence of stressors, it migrates extracellularly and behaves like a Damage Associated Molecular Pattern (DAMP), has chemokine and cytokine activity. Extracellular HMGB1 binds to Toll Like Receptors (TLR)- 2,4 and RAGE, the HMGB1-RAGE interaction in particular has been associated with hyper inflammatory responses and currently hypothesised to be a bigger player in the pathogenesis of periodontitis as well as diabetes associated periodontitis. Therefore, understanding thoroughly the molecular mechanisms driving the tissue destruction in periodontal disease will effectively enable novel therapeutic drug based interventions based on interrupting the HMGB1-RAGE axis which in turn could mitigate the inflammation mediated tissue destruction.

A five-month-old infant presented with fever and cough for 3 weeks. She was diagnosed with multiple tuberculomas and cavitating pulmonary tuberculosis. She was a household contact of an open case of tuberculosis (TB) and developed severe disease, although she had received the Bacillus Calmette–Guérin (BCG) vaccine and had no primary or secondary immunodeficiency. In infants, due to low levels of cell mediated immunity, tuberculosis can be severe and dissemination of tuberculosis to the central nervous system (CNS) can occur very early without following the usual time frame. CNS TB may not have symptoms in the early stages in infants and may require neuroimaging for diagnosis. This is the youngest child that has been reported with multiple CNS tuberculomas.

Oxygen is a prominent element in the well-being of humans, but also responsible for causing tissue damage. The oxygen molecule gets reduced to form a highly reactive oxygen species due to various metabolic events happening in the host. The generated free radicals could react with other biomolecules like protein, lipid, carbohydrate and nucleic acid to impart severe diseases and disorders. Antioxidants could effectively block the oxidation process by neutralizing the produced free radicals. Hence, the present study aims to validate the potent antioxidant activities of Couroupita guianensis Aubl. using goat liver slices that could serve as an in vivo simulated in vitro model. The methanolic extract and the alkaloid fraction of both leaves and flowers of C. guianensis Aubl. were prepared and their enzymatic and non-enzymatic antioxidant activities were evaluated. Hydrogen peroxide was used as a standard free radical throughout the experiments in all the treatment groups. The results have envisaged that the plant has enormous antioxidant activities in oxidatively stressed goat liver slices to combat various oxidative stress-related diseases and disorders. Conclusively, the in vitro model system to explore the antioxidant profiles will eventually mitigate the sacrifice of animals by exactly mimicking the in vivo conditions for research endeavors. [ABSTRACT FROM AUTHOR]

The genus Lathyrus consists of more than 184 herbaceous annual and perennial species suitable for multifaceted sustainable food and feed production system in the arid and semi-arid regions of the world. The grasspea is a promising source of protein nutrition. However, its potential is not being utilized fully due to the presence of neurotoxin content (β-N-oxalyl-l-α, β diaminopropionic acid, β-ODAP), a causal agent of non-reversible lower limbs paralysis. The high protein contents in seeds and leaves with ~90% digestibility make it sustainable super food to beat protein malnutrition in future. Therefore, it is desired to breed new grasspea cultivars with low β-ODAP contents. Limited research has been carried out to date about this feature. A draft genome sequence of grasspea has been recently published that is expected to play a vital role in breeding and identifying the genes responsible for biosynthesis pathway of β-ODAP contents in grasspea. Efforts to increase awareness about the importance of genus Lathyrus and detoxify β-ODAP in grasspea are desired and are in progress. Presently, in South Asia, systematic and dedicated efforts to support the farmers in the grasspea growing regions by disseminating low β-ODAP varieties has resulted in a considerable improvement in reducing the incidence of neurolathyrism. It is expected that the situation will improve further by mainstreaming grasspea cultivation by implementing different approaches such as the development and use of low β-ODAP varieties, strengthening government policies and improved detox methods. The present review provides insight into the multifaceted characteristics of sustainable nutritious grasspea in the global and Indian perspective.

Coronaviruses are positive-sense RNA viruses with crown-like morphology. This family of virus is known to cause outbreak in many species including humans. The pandemic caused by novel coronavirus COVID-19 is reported to have been spread from bats to human. These groups of emerging zoonotic pathogens bind to the host cell through receptor-mediated mechanism. As the viruses lack proper machinery for self-replication, they depend on the host cell for replication. The resulting viremia causes most common clinical symptoms such as fever, cough progressing to shortness of breath. The number of cases reported from COVID-19 is on the rise since diagnosis. The development of drugs and vaccines is under trial for the management of the novel viral infection.

Deep learning and machine learning are cutting-edge methods for analysing images that have considerable potential. Artificial Neural Networks (A-NNs), one of the most well-known methods of computer intelligence, are now used in machine learning (ML) and deep transfer learning (DL) to raise plant production and quality. Identification and primary prevention of plant diseases at the appropriate time are essential for boosting productivity. Due to the phenomenon of minimally intense data in the background and foreground areas of the image, the extensive colour similarity between regions of unhealthy and normal leaves, the presence of noise in the sampling data, and changes in the location, size, and shape of plant leaf, it is difficult to correctly identify and classify plant diseases. In an effort to address these issues, a reliable technique for classifying plant diseases was developed by using a deep AlexNet CNN architecture as the main network with batch normalisation. In the three-step process, the first annotation is made to obtain the RoI (region of interest). The AlexNet CNN is therefore suggested for deep primary feature extraction in a constructed efficient network. The research demonstrates that the existing strategy is superior to more recent ones in terms of accuracy and dependability in recognising diseases in plants. Based on a deep transfer AlexNet CNN model, this research work developed a model for diseases identification and classification in plant leaves. It is trained using additional datasets that include a variety of plant leaf classifications and background images. From Plant Village and Kaggle, we gathered data on healthy and diseased tomato plant leaves. We are obtaining a near-balanced dataset containing ten different leaf disease kinds, such as bacterial, fungal, viral, and nutrient insufficiency. Ten classes have been considered for this research by gathering a dataset with associated images of the typical and abnormal tomato plant leaves. Considered in this work were the various labels for healthy and diseased tomato leaves, such as early blight, Bacterial spot, late bright mold, healthy, etc. Since deep CNN models have shown notable machine vision results, they are used in this case to diagnose and categorise plant illnesses from their leaves. As a result, the proposed CNN models can thus now be evaluated from confusion matrix using data analysis criteria, primarily focusing on metrics for evaluation like training and validation accuracy, loss, Recall, Precision, F1 score, processing speed, and performance.

A social media is rapidly expanding, and its anonymity feature completely supports free speech. Hate speech directed at anyone or any group because of their ethnicity, clan, religion, national or cultural their heritage, sex, disability, gender orientation, or other characteristics is a violation of their authority. Seriously encourages violence or hate crimes and causes social unrest by undermining peace, trustworthiness, and human rights, among other things. Identifying toxic remarks in social media conversation is a critical but difficult job. There are several difficulties in detecting toxic text remarks using a suitable and particular social media dataset and its high-performance, selected classifier. People nowadays share messages not only in person, but also in online settings such as social networking sites and online groups. As a result, all social media sites and apps, as well as all current communities in the digital world, require an identification and prevention system. Finding toxic social media remarks has proven critical for content screening. The identifying blocker in such a system would need to notice any bad online behavior and alert the prophylactic blocker to take appropriate action. The purpose of this research was to assess each text and find various kinds of toxicities such as profanity, threats, name-calling, and identity-based hatred. Jigsaw's designed Wikipedia remark collection is used for this.

CONTEXT: Dengue fever (DF) has been steadily increasing in India with outbreaks in certain areas taking the proportion of epidemics. Along with secondary dengue, several risk factors predispose to dengue hemorrhagic fever and dengue shock syndrome. Very few studies associating the relationship between dengue and its severity with ABO blood group have been documented. AIMS: The aim of this study was to determine the association between distribution of ABO Rh blood groups and DF and DF with thrombocytopenia. SETTINGS AND DESIGN: This was a retrospective descriptive study conducted at the clinical laboratory of the department of microbiology. MATERIALS AND METHODS: Dengue patients whose case record contained information on blood group were screened for details of blood group and confirmed dengue diagnosis. Randomly 384 case records were selected. These were divided into two groups; Group 1 included DF cases (platelet count >20,000) and Group 2 included DF cases with thrombocytopenia (platelet count