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This study systematically reviewed literature regarding the effect of different concentrations of sodium hypochlorite (NaOCl) used during root canal treatment (RCT) on postendodontic pain (PEP) and rescue analgesia. Following registration with PROSPERO (CRD42023388916), a search was conducted using PubMed, Scopus, Web of Science, and Embase databases. Randomized controlled trials of patients receiving RCT which assessed PEP at different time intervals were included. Following data extraction and Cochrane risk of bias assessment 2, meta-analyses were performed to evaluate PEP during the first 48 hours along with rescue analgesic intake. The certainty of the evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation approach. Five randomized controlled trials with 674 patients were included. One study exhibited a low risk of bias, while 4 raised some concerns. Patients treated with low concentrations of NaOCl (≤3%) were significantly less likely to report PEP at 24 hours (OR = 2.32; [95% CI, 1.63–3.31]; P <.05) and 48 hours (OR = 2.49; [95% CI, 1.73–3.59]; P <.05) as compared with high concentrations of NaOCl (≥5%). Furthermore, with low concentrations of NaOCl, significantly lesser moderate-severe PEP was reported at 24 hours (OR = 2.32; [95% CI, 1.47–3.62]; P <.05) and 48 hours (OR = 2.35; [95% CI, 1.32–4.16]; P <.05) and lesser analgesia was needed (OR = 2.43; [95% CI, 1.48–4.00]; P <.05). While PEP can be influenced by several factors, low certainty evidence suggests that when NaOCl is used as an irrigant during RCT, PEP may be less likely with lower concentrations of NaOCl. Moderate certainty evidence indicates that lesser analgesia may be required with lower concentrations of NaOCl. These results should be cautiously interpreted. [ABSTRACT FROM AUTHOR]

Narrow band imaging (NBI) is an emerging modality that enhances the accuracy of detection of head and neck malignancies by visualisation of aberrant neoangiogenesis in malignant tissue using narrow bandwidth light in blue and green spectrum. The purpose of this study was to assess the role of NBI in detecting recurrence in patients with Squamous cell carcinoma larynx and hypopharynx who have undergone Radiotherapy/Chemoradiotherapy (RT/CTRT). The aim of the study was to (a) determine the role of NBI in follow-up of patients with carcinoma of larynx and hypopharynx previously treated with radiotherapy or chemotherapy, (b) determine the role of NBI as the initial investigatory tool of choice in detecting local recurrence and compare with other modalities like fibreoptic laryngoscopy (FOL), Magnetic Resonance Imaging (MRI) and Positron Emission Tomography- Computed Tomography (PETCT). Prospective multicentric study at ENT departments of tertiary care centres in Delhi, Bangalore and Pune in India was conducted from Jan 2019 to Sep 2022. Thirty-four consecutive patients diagnosed as squamous cell carcinoma (SCC) larynx/hypopharynx who underwent chemo/radiotherapy were scheduled for NBI 12 weeks after completion of therapy with FOL and PETCT/MRI and followed up 03 monthly for 02 years. NBI/FOL/PETCT or MRI and Histopathological Examination (HPE) were compared. NBI was found to be 100% sensitive and 96% specific with a positive predictive value of 85% and negative predictive value of 100% respectively with a diagnostic accuracy of 97%. NBI along with FOL increases the sensitivity of detection of recurrence in patients of laryngeal/hypopharyngeal cancer post-chemo/radiotherapy. [ABSTRACT FROM AUTHOR]

Smart grid represents an advanced and interconnected system that incorporates modern technologies to enhance efficiency, reliability and sustainability. In comparison to the conventional grid, the smart grid (SG) uses many cutting-edge technologies. This research introduces a fog computing encryption-based model for privacy preservation in the smart grid model. By using different advanced technologies, our model addresses the balance between privacy, security, effectiveness and functionality. The model facilitates efficient communication and function inquiry while mitigating challenges posed by massive Internet of Things (IoT) systems in the smart grid environment. Specifically, it tackles the secure data consolidation challenge by employing encryption-based techniques for transmitting private data from smart meters to fog devices. These devices consolidate the data before updating to cloud. Conventional data consolidation approaches for SGs have high computation and communication costs and suffer from high storage requirement. The proposed model resolves these issues; algorithms for data consolidation and extraction of data at fog device and cloud respectively to obtain the secure communication has also been included. The performance of the developed mechanism has been computed against existing data consolidation mechanisms GCEDA (Grouping of Clusters for Efficient Data Aggregation), SPPDA (Secure Privacy-Preserving Data Aggregation) and LPDA (Lightweight Privacy-preserving Data Aggregation) for numerous performance parameters. And the results proves that the performance of developed mechanism with respect to bytes of storage, communication cost and ratio of transmission is better than the existing ones. [Display omitted] • Encryption-based data consolidation strategy for 5G in fog computing is presented. • Data consolidation and data extraction algorithm at fog devices and cloud servers. • A comparative analysis based on storage, communication and transmission cost is done. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) sensor networks are connected systems of physical devices set with actuators, sensors, and communication abilities, allowing them to gather, spread, and exchange information with centralized methods. These networks are essential in numerous businesses, such as healthcare, manufacturing, agriculture, and smart cities, as they deliver real-time observation, data-driven insights, and automation. Threat recognition in IoT sensor networks is a vital feature of safeguarding the protection and consistency of interconnected systems in the IoT. As IoT sensor networks endure to increase across various industries, the vulnerability to malicious actions and cyber-attacks increases. Threat recognition utilizing deep learning (DL) leverages neural networks to examine complex patterns and anomalies in data, permitting the identification of potential safety threats. DL techniques like convolutional neural networks (CNNs) or recurrent neural networks (RNNs) excel at learning complex representations of data and feature extraction, making them suitable for identifying sophisticated attacks in different fields, including cybersecurity. This research develops a Hybrid Sine-Cosine Chimp Optimization Feature Selection with a Deep Learning (HSCCOFS-DL) approach for Threat Recognition in IoT Sensor Networks. The foremost aim of the HSCCOFS-DL system lies in the automated detection of threats using DL models. To accomplish this, the HSCCOFS-DL approach undergoes a data normalization process. Besides, the selection of features can be performed using the HSCCO algorithm. Meanwhile, the symmetrical autoencoder (SAE) technique effectively classifies threats. Finally, the sparrow search algorithm (SSA) can be applied to the selection of the hyperparameter of the SAE system. The experimental assessment of the HSCCOFS-DL technique takes place on a benchmark dataset. The simulation results indicated that the HSCCOFS-DL approach attains enhanced performance over other methods. [ABSTRACT FROM AUTHOR]

The Humeral retroversion angle (HRA) has been described in the literature as the orientation of the humeral head compared with the epicondylar axis of the distal humerus. HRA is a crucial measurement for designing shoulder prostheses and surgical technique, and is often noted to range from 25° to 35° in healthy adults. However, a wide range of individual variability has been reported in literature, with reported values ranging from −6° to 74°. Various imaging modalities including X-rays, computed tomography scans, and magnetic resonance imaging have historically been used to measure this angle, but conventional 2-dimensional technologies may result in inaccuracy and variability in angular measurements. Therefore, recent studies have focused on using 3-dimensional (3D) modalities to measure HRA. These studies have shown promising results regarding accuracy and clinical significance, although most have only included a small number of subjects and have not procured conclusive findings. This study aims to measure the HRA in a large sample of subjects using 3D imaging to establish measurements for the general population. We examined the right and left cadaveric humerus from 559 individuals (146 females and 413 males). All of the humeri underwent computed tomography scan and surface models generated. 3D landmarks were automatically calculated on each 3D bone using custom-written software in C++. Those landmarks were used to calculate (1) HRA as the angle between the epicondylar axis and the humeral neck axis and (2) humeral proximal neck angle (HPNA) as the angle between the humeral neck axis and the anatomical axis. Descriptive statistics of both HRA and HPNA was analyzed using JMP Pro statistical software version 15.2.0. The HPNA was found to be 137.7° ± 1.04° for males and 136.34° ± 1.4° for females with a 95% confidence interval. HRA was found to be 39.89° ± 12.77° for males and 38.89° ± 3.15° for females with a 95% confidence interval. Results of analysis of variance revealed that males had a statistically significant larger HRA than females (P <.001). Our study suggests using a standardized measurement for the HRA, which we believe may improve operative outcomes. However, future prospective trials are required to validate our results in a clinical setting. [ABSTRACT FROM AUTHOR]

Traffic management is a critical activity, the population is increasing day by day and so the traffic on the road is also increasing. Traffic jams and long waiting queues of vehicles at the road crossing are now part of everyone's life. The traffic lights used at the crossing to regulate the traffic play a vital role in the smooth functioning of traffic movement. At a crossing of four roads, it has been observed that giving an equal amount of green light to all roads is meaningless since the arrival of traffic on different paths is different. Importantly, the arrival rate is responsible for all traffic jams, long queues, and increased waiting time. Therefore, this paper suggests a green light allocation scheme for all paths i depending on the arrival rate of the vehicles. Thus, the allocation of green light will be dynamic. Further, weight is also computed, where more arrival rate means more weight, thereby assigning more time to the green signal. This will help in reducing the long queue length, residual traffic, and long waiting times. On simulating the traffic with the traffic data, the proposed optimized green light allocation scheme to path i reduces the residue traffic to negligible, allowing smooth traffic flow even during peak hours. The work also provides a proficient optimization of the waiting time of vehicles accumulated during the red light. According to the simulation, the maximum time assigned for the green signal during the peak hour of 9:30 AM to 10:00 AM for paths i , where 1 ≤ i ≤ 4 is 39.96, 33.36, 26.64, and 20.04 seconds respectively. Similarly, during the second rush hour of 5:00 PM to 6:00 PM, the simulation assigns a green signal time of 41.4, 37.2, 24.84, and 16.56 seconds for corresponding paths 1–4. Thus, the proposed work suggests an effective traffic management scheme at the four-road crossing. [ABSTRACT FROM AUTHOR]

Ventricular arrhythmia (VA) is the primary mechanism of sudden death in patients with structural heart disease. Cardiac stereotactic body radiation therapy (SBRT) delivered to the scar in the left ventricle significantly reduces the burden of VA. The goal of this study was to investigate the impact of SBRT on scar morphology and VA inducibility in a porcine infarct model. Myocardial infarction (MI) was created in 10 Yorkshire pigs involving the left anterior descending artery territory. Cardiac positron emission tomography and computed tomography were performed for targeted SBRT. Alternative pigs received SBRT at 25 Gy in a single fraction. The terminal experiment included endocardial mapping, programmed ventricular stimulation, and tissue harvesting. Of the 10 pigs infarcted, 2 died prematurely after MI and 8 (4 MI and 4 MI+SBRT) survived. Mean time from MI to SBRT was 48 ± 12 days, and mean time from SBRT to harvest was 32 ± 12 days. Scar was localized on intracardiac mapping in all pigs, and the scar was denser in the MI+SBRT compared with the MI-only group (33% ± 20% vs 14% ± 11%; P =.07). All 4 MI pigs had inducible VA during programmed stimulation, whereas only 1 of 4 pigs had inducible VA in the MI+SBRT arm (100% vs 25%; P =.07). No myocardial fibrosis was seen in the remote areas in either group. SBRT reduced VA inducibility in pigs with scarring after MI. Endocardial mapping revealed denser scar in pigs receiving SBRT compared with those that did not, suggesting that SBRT suppresses VA inducibility through better scar homogenization. [Display omitted] [ABSTRACT FROM AUTHOR]

We meta-analyzed the diagnostic accuracy of rapid diagnostic tests (dipsticks) and loop-mediated isothermal amplification (LAMP) method to detect Shigella species. We searched MEDLINE, Embase, Web of Science and Google Scholar from inception to 2023 for studies reporting on the performance of Shigella dipstick and LAMP tests compared with culture or polymerase chain reaction (PCR). Our search identified 2618 studies, of which fourteen met the inclusion criteria for the systematic review. Ten studies covering 4056 tests (from twelve countries) were included in the meta-analysis. The overall pooled sensitivity and specificity were 98 % (95 % CI: 94–100) and 97 % (95 % CI: 92–99), respectively. Pooled sensitivity and specificity of dipsticks were 95 % and 98 %, respectively. In contrast, LAMP showed higher pooled sensitivity (100 %) and diagnostic odds ratio (431752), but similar specificity (97 %). LAMP and dipstick tests exhibited promising performance, suggesting that they could be useful for assisting in the diagnosis of shigellosis. • Shigella infection can result in growth deficits among children. • We investigated the diagnostic accuracy of Shigella dipsticks tests and LAMP. • Ten studies were included in the meta-analysis. • Dipsticks pooled sensitivity and specificity: 95 % and 98 %, respectively. • LAMP pooled sensitivity and specificity: 100 % and 97 %, respectively. [ABSTRACT FROM AUTHOR]

This work aimed to investigate the validity of wearable activity monitors (WAMs) as an objective tool to measure the return toward normal functional mobility following abdominal wall surgery. This was achieved by quantifying and comparing pre- and postoperative physical activity (PA). A multicenter, prospective, observational cohort study was designed. Patients undergoing abdominal wall surgery were assessed for eligibility and consent for study participation was obtained. Participants were asked to wear a WAM (AX3, Axivity) on the wrist of their dominant hand at least 48 hours pre-operatively, for up to 2 weeks postop, and again after 6 months postop for 48 hours. A cohort of 20 patients were recruited in this validation study with a mean age of 47.3 ± 13.0 years. Postoperation, the percentage median PA (±IQR) dropped to 32.6% (20.1), whereas on day 14, PA had reached 64.6% (22.7) of the preoperative value providing construct validity. Activity levels at >6 months postop increased by 16.4% on an average when compared to baseline preoperative PA (p = 0.046). This study demonstrates that WAMs are valid markers of postoperative recovery following abdominal wall surgery. This was achieved by quantifying the reduction in PA postoperation, which has not been previously shown. In addition, this study suggests that abdominal wall surgery may improve the patient's quality of life via increased functional mobility at 6 months postop. In the future, this technology could be used to identify the patient and surgical factors that are predictors of outcome following abdominal wall surgery. [ABSTRACT FROM AUTHOR]

The pandemic of COVID-19 has created an unprecedented burden on the healthcare system and medical communities resulting in new public health challenges. On the other hand, in tropical countries, another concern arises due to the similar spectrum of clinical manifestations between COVID-19 and dengue fever. Thus, the neglected tropical disease 'Dengue' writhed with more inattention. This study aims to find the effect of the COVID-19 pandemic on dengue infections in endemic areas of West Bengal, India, and their combined impact on public health. The alterations in circulating dengue serotype and their genomic diversity in different COVID-19 waves were also monitored. A total of 1782 patients were included in this study. Dengue NS1 ELISA, molecular serotyping, genotyping and their phylogenetic analysis were performed. GISaided analysis of various dengue serotypes and hotspot identification for risk maps of severe dengue in endemic zones were done. The burden of dengue fever and the sustainability of their viral strains with changing meteorological parameters in parallel to COVID-19 waves were analyzed. Co-circulation of all the four dengue serotypes with rapid change in the pattern of prevalent serotype DENV4 (Genotype-I) in the year 2020 and DENV3 (Genotype-III) in 2021 were observed, in parallel to different circulating strains of COVID-19. Spatiotemporal distribution of DENV using Geographic Information System (GIS) applications observed a serotypic shift and hotspot mapping for risk analysis detected Kolkata as a dengue hotspot, which has also reported the maximum number of COVID-19 cases. This study indicates the increased fitness of circulating dengue virus strains with optimal virulence as per changing environmental conditions and the inhabitant's immunity. The high infectivity rate of both the RNA viruses and considering.the consequences of severe dengue and COVID-19 in the population of the same geographical settings is an alarming risk. [ABSTRACT FROM AUTHOR]

[Display omitted] • The free energy landscape for silicon and arsenic permeation was traced. • The transport cycle reveals novel energy constraints on silicon and arsenic permeation. • Predicted functionally important residues were validated in yeast. • Altering conserved amino acids in loop C and loop D directly influenced metalloid uptake of OsNIP2;1. • Protein variants with lower arsenic uptake were identified to reduce arsenic levels with minimum counterproductive effects. Nodulin-26-like intrinsic proteins (NIPs) are integral membrane proteins belonging to the aquaporin family, that facilitate the transport of neutral solutes across the bilayer. The OsNIP2;1 a member of NIP-III class of aquaporins is permeable to beneficial elements like silicon and hazardous arsenic. However, the atomistic cross-talk of these molecules traversing the OsNIP2;1 channel is not well understood. Due to the lack of genomic variation but the availability of high confidence crystal structure, this study aims to highlight structural determinants of metalloid permeation through OsNIP2;1. The molecular simulations, combined with site-directed mutagenesis were used to probe the role of specific residues in the metalloid transport activity of OsNIP2;1. We drew energetic landscape of OsNIP2;1, for silicic and arsenous acid transport. Potential Mean Force (PMF) construction illuminate three prominent energetic barriers for metalloid passage through the pore. One corresponds to the extracellular molecular entry in the channel, the second located on ar/R filter, and the third size constriction in the cytoplasmic half. Comparative PMF for silicic acid and arsenous acid elucidate a higher barrier for silicic acid at the cytoplasmic constrict resulting in longer residence time for silicon. Furthermore, our simulation studies explained the importance of conserved residues in loop-C and loop-D with a direct effect on pore dynamics and metalloid transport. Next we assessed contribution of predicted key residues for arsenic uptake, by functional complementation in yeast. With the aim of reducing arsenic uptake while maintaining beneficial elements uptake, we identified novel OsNIP2;1 mutants with substantial reduction in arsenic uptake in yeast. We provide a comprehensive assessment of pore lining residues of OsNIP2;1 with respect to metalloid uptake. The findings will expand mechanistic understanding of aquaporin's metalloid selectivity and facilitate variant interpretation to develop novel alleles with preference for beneficial metalloid species and reducing hazardous ones. [ABSTRACT FROM AUTHOR]

Acanthosis nigricans (AN) is a skin condition characterized by hyperpigmentation and thickening, often found in individuals with insulin resistance. Despite this well-established association, the potential link between AN and hepatic fibrosis in people with type 2 diabetes (T2D) has yet to be thoroughly explored. We recruited a total of 300 people with T2D, half of whom had AN (n, 150), and the other half without AN (n, 150). We evaluated body composition, biochemistry, and hepatic fat analysis (using the controlled attenuation parameter, CAP), as well as assessments of hepatic stiffness (using the kilopascal, kPa) using Fibroscan. We used multivariable regression analysis to find independent predictors of AN and their relationship to hepatic fibrosis. Furthermore, we developed a prediction equation and AUC for hepatic fibrosis. Upon comparison between AN vs. NAN group, following were significatly higher; weight, BMI, hepatic transaminases, liver span, CAP, and kPa. After adjusting for age, weight, body mass index, diabetes duration, and specific anti-hyperglycaemic drugs (gliclazide, DPP-4 inhibitors, pioglitazone, and Glucagon-like peptide-1 receptor agonists), adjusted OR for AN were, liver span, 1.78 (95% CI: 0.91–3.49, p = 0.09), CAP, 7.55 (95% CI: 0.93–61.1, p = 0.05), and kPa, 2.47 (95% CI: 1.50–4.06, p = 0.001). A ROC analysis of predictive score for hepatic fibrosis showed optimal sensitivity and specificity at a score cut-off of 25.2 (sensitivity 62%, specificity 63%), with an AUC of 0.6452 (95% CI: 0.61235–0.76420). Acanthosis nigricans has the potential to be used as an easy-to-identify clinical marker for risk of hepatic fat and fibrosis in Asian Indians with T2D, allowing for early detection and management strategies. • T2D and AN showed higher values for weight, BMI, CAP, kPa, and liver span. • AN in people with T2D was independently associated with liver span, CAP and kPa. • AN as potential hepatic fibrosis risk marker in T2D Asian Indians. [ABSTRACT FROM AUTHOR]

• A transfer learning model is designed to predict critical temperatures. • Critical temperatures for ∼19k magnesium based compounds are predicted. • DFT calculations are performed to validate the predicted results. • Virtual compounds are designed to show the ability to predict new superconductors. This study presents a transfer learning approach for discovering potential Mg-based superconductors utilizing a comprehensive target dataset. Initially, a large source dataset (Bandgap dataset) comprising approximately ∼75k compounds is utilized for pretraining, followed by fine-tuning with a smaller Critical Temperature (T c) dataset containing ∼300 compounds. Comparatively, there is a significant improvement in the performance of the transfer learning model over the traditional deep learning (DL) model in predicting T c. Subsequently, the transfer learning model is applied to predict the properties of approximately 150k compounds. Predictions are validated computationally using density functional theory (DFT) calculations based on lattice dynamics-related theory. Moreover, to demonstrate the extended predictive capability of the transfer learning model for new materials, a pool of virtual compounds derived from prototype crystal structures from the Materials Project (MP) database is generated. T c predictions are obtained for ∼3600 virtual compounds, which underwent screening for electroneutrality and thermodynamic stability. An Extra Trees-based model is trained to utilize E hull values to obtain thermodynamically stable materials, employing a dataset containing E hull values for approximately 150k materials for training. Materials with E hull values exceeding 5 meV/atom were filtered out, resulting in a refined list of potential Mg-based superconductors. This study showcases the effectiveness of transfer learning in predicting superconducting properties and highlights its potential for accelerating the discovery of Mg-based materials in the field of superconductivity. [ABSTRACT FROM AUTHOR]

Classifying unbalanced datasets is a challenging task, and traditional Support Vector Machine (SVM) algorithms often struggle to achieve accurate results. In this paper, we propose an Ant Colony Optimization based Support Vector Machine (SVM-ACO) algorithm that outperforms SVM on unbalanced datasets. Traditional SVM algorithms tend to be biased towards the majority class, leading to suboptimal performance for the minority class. However, SVM-ACO addresses this issue by incorporating the ant colony optimization approach, which assigns different weights to samples based on their class membership, giving higher importance to the minority class. This enables SVM-ACO to achieve a more balanced classification performance and improved accuracy. We compare the accuracy achieved by SVM-ACO and SVM on various imbalanced datasets from the literature. The experimental results support the effectiveness of SVM-ACO in addressing the challenges of unbalanced datasets. By incorporating ant colony optimization, SVM-ACO achieves improved accuracy and provides a promising alternative for handling unbalanced classification problems. [ABSTRACT FROM AUTHOR]

Clustering methods have become widely popular in the field of data analysis, as they enable the grouping of similar data points. However, the challenge of clustering high-dimensional data remains a significant obstacle due to the "curse of dimensionality." Traditional methods like Principal Component Analysis (PCA) and hierarchy-based feature agglomeration have been used to overcome this challenge by reducing the dimensionality of the dataset. However, there is currently no efficient method for clustering features of a high-dimensional dataset. To address this issue, we present a non-parametric clustering method in this paper, specifically designed for identifying features in a high-dimensional dataset. Our proposed feature clustering algorithm utilizes a partitioning algorithm that creates clusters of features. Through experimental results using publicly available datasets, we demonstrate the effectiveness of our method. Our approach offers a valuable tool for researchers and practitioners to better understand and analyze high-dimensional data. [ABSTRACT FROM AUTHOR]

The economic crisis in Sri Lanka began in 2019 and reached a crisis point in 2022 when protesters stormed the presidential palace in Colombo. Acute food, fuel, and other item shortages, soaring inflation, prolonged power outages, and a collapsing economy with few job opportunities all contribute to the populace's unrest. Sri Lanka still faces severe economic difficulties, and no one can say when they will be resolved. This country has seen the most prominent financial collapse since its independence in 1948. Unexpected inflation levels, a close to complete exhaustion of foreign currency reserves, a shortage of medical aid, and a rising price of essential commodities are the results. Numerous compounding reasons, including tax cuts, printing money, a countrywide regulation to move to natural or biological agriculture, the 2019 Sri Lanka Easter bombings, and the repercussions of the COVID-19 epidemic, have been cited as the root cause of the disaster. As early as 2022, these protests in Sri Lanka might be traced back to the country's economic woes. The primary driver of the current financial crisis in Sri Lanka is inflation. This article will look into Sri Lanka's inflation rates beginning in 2021. The inflation Rate of Sri Lanka has been forecasted for the next 6 months (through September 2023) using time series data. We used numerous Time Series Forecasting Algorithms for this multi-step ahead forecast. The results generated by these time series forecasters were in accordion with each other. Thus, we put forward the normalized results from each of these forecasting paradigms to get a better prediction on the inflation Rates, that Sri Lanka is supposed to face shortly (6 months), keeping in consideration of the current scenario being unaltered. The authors hope the Sri Lankan Administration will use the paper's predictions to take charge, which could lead to positive changes. [ABSTRACT FROM AUTHOR]

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Stress and illness connection is complex and involves multiple physiological systems. Panax ginsengs, reputed for their broad-spectrum "cure-all" effect, are widely prescribed to treat stress and related illnesses. However, the identity of ginseng's "cure-all" medicinal compounds that relieve stress remains unresolved. Here, we identify ginsentides as the principal bioactives that coordinate multiple systems to restore homeostasis in response to stress. Ginsentides are disulfide-rich, cell-penetrating and proteolytic-stable microproteins. Using affinity-enrichment mass spectrometry target identification together with in vitro , ex vivo and in vivo validations, we show that highly purified or synthetic ginsentides promote vasorelaxation by producing nitric oxide through endothelial cells via intracellular PI3K/Akt signaling pathway, alleviate α 1-adrenergic receptor overactivity by reversing phenylephrine-induced constriction of aorta, decrease monocyte adhesion to endothelial cells via CD166/ESAM/CD40 and inhibit P2Y12 receptors to reduce platelet aggregation. Orally administered ginsentides were effective in animal models to reduce ADP-induced platelet aggregation, to prevent collagen and adrenaline-induced pulmonary thrombosis as well as anti-stress behavior of tail suspension and forced swimming tests in mice. Together, these results strongly suggest that ginsentides are the principal panacea compounds of ginsengs because of their ability to target multiple extra- and intra-cellular proteins to reverse stress-induced damages. This study shows ginsentides are "first-in-class" bioactive peptides from ginseng with a variety of functions that answers part of the "cure-all" functions of ginseng, particularly for cardiovascular health and stress. [Display omitted] [ABSTRACT FROM AUTHOR]

While digital technologies provide the backbone for digital twins of product, process, and performance, early adopters of digitalization recommend that technologies need to be supported by reengineered processes to unlock capacities and empower people. While the existing research literature provides insights into digital technologies, holistic consideration of product development processes and their responses to interventions is found lacking. This study focuses on the experiential inputs of manufacturing professionals to build a perspective of a customer-centric digitalized value chain enriched with digital twins of product, process, and performance. Authors interacted with SME stakeholders, through brainstorming workshops organized under the aegis of a premier Indian industry association. Based on the insights drawn from the expert interactions, monitoring, optimization, integration, and customer satisfaction have been established as the strategic steps of digitalization. This study adds to the digital twin-based engineering knowledge by introducing a versatile process-technology-performance matrix. SMEs can adopt this matrix to tailor solutions to their unique business needs, enabling flexible creation of digital twins. This aspect makes this study relevant and novel for manufacturing SMEs preparing for implementing transformative digital technologies. [ABSTRACT FROM AUTHOR]

In this paper, a method to analyse load features utilising sample shifting technique (SST) for non-intrusive load identification (NILI) is presented and discussed. Fuzzy rules are used as the foundation for the identification logic. Voltage and current signals for electrical home appliances are acquired in order to develop their respective features. Two features like reactive power and total harmonic distortion for current (THD I), are created with the necessary computations of the samples using SST. A method based on fuzzy rules is created in order to identify different electrical equipment both for their individual as well as simultaneous running. Again, the performance of the proposed system is tested under the noisy environment while the accuracy of the system is found satisfactory. By utilising SST, the burden of computation is reduced in comparison to the other methods which are justified with the experimental results. • Only voltage and current information are used for load identification. • Sample Shifting Technique is used to extract load features. • Reactive power and THD for current are used as load features. • Fuzzy logic-based rules are applied for non-intrusive load identification. • The use of of SST assists in the extraction of load features and reduces the complexity of the hardware by eliminating the need for filters or ZCDs. • Individual load can be identified during practical multiple loads are working parallelly. • System shows robustness under noisy environment. [ABSTRACT FROM AUTHOR]

Septic arthritis of the shoulder is distinctly challenging to diagnose and treat. Guidelines for appropriate workup and management are limited and do not account for the variations in clinical presentation. The purpose of this study was to present a comprehensive and anatomically based classification system and treatment algorithm for septic arthritis of the native shoulder joint. A multicenter, retrospective analysis of all patients treated surgically for septic arthritis of the native shoulder joint was performed at 2 tertiary care academic institutions. Preoperative magnetic resonance imaging and operative reports were used to classify patients as having 1 of 3 infection subtypes: type I, confined to the glenohumeral joint; type II, extra-articular extension; or type III, concomitant osteomyelitis. On the basis of these clinical groupings of patients, the comorbidities, types of surgical management, and outcomes were analyzed. Sixty-five shoulders in 64 patients met the inclusion criteria for the study. Of these infected shoulders, 9.2% had type I infections, 47.7% had type II, and 43.1% had type III. Age and the time between symptom onset and diagnosis were the only significant risk factors for the development of a more severe infection. Fifty-seven percent of shoulder aspirates revealed cell counts below the standard surgical cutoff of 50,000 cells/mL. On average, each patient required 2.2 surgical débridements to eradicate the infection. Infections recurred in 8 shoulders (12.3%). Body mass index was the only risk factor for recurrence of infection. Of the 64 patients, 1 (1.6%) died acutely of sepsis and multiorgan system failure. We propose a comprehensive system for the classification and management of spontaneous shoulder sepsis based on stage and anatomy. Preoperative magnetic resonance imaging can help determine the severity of disease and aid in surgical decision making. A systematic approach to septic arthritis of the shoulder as a unique entity from septic arthritis of other large peripheral joints may lead to more timely diagnosis and treatment and improve the overall prognosis. [ABSTRACT FROM AUTHOR]

The risk of tuberculosis (TB) disease is higher in individuals with TB infection. In a TB endemic country like India, it is essential to understand the current burden of TB infection at the population level. The objective of the present analysis is to estimate the prevalence of TB infection in India and to explore the factors associated with TB infection. Individuals aged > 15 years in the recently completed National TB prevalence survey in India who were tested for TB infection by QuantiFERON-TB Gold Plus (QFT-Plus) assay were considered for this sub-analysis. TB infection was defined as positive by QFT-Plus (value >0.35 IU/ml). The estimates for prevalence, prevalence ratio (PR) and adjusted risk ratio (aRR) estimates with 95% confidence intervals (CIs) were calculated. Of the 16864 individuals analysed, the prevalence of TB infection was 22.6% (95% CI:19.4 −25.8). Factors more likely to be associated with TB infection include age > 30 years (aRR:1.49;95% CI:1.29–1.73), being male (aRR:1.26; 95%CI: 1.18–1.34), residing in urban location (aRR:1.58; 95%CI: 1.03–2.43) and past history of TB (aRR:1.49; 95%CI: 1.26–1.76). About one fourth (22.6%) of the individuals were infected with TB in India. Individuals aged > 30 years, males, residing in urban location, and those with past history of TB were more likely to have TB infection. Targeted interventions for prevention of TB and close monitoring are essential to reduce the burden of TB in India. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) technology involves a network of interconnected devices and sensors that gather and exchange information. In smart cities, IoT devices were utilized in several fields including energy, transportation, waste management, healthcare, etc., to improve the overall quality of life and sustainability of the populace. But, as the usage of IoT increases, the cybersecurity and data privacy become a concern of safety. An anomaly detection system helps to identify possible data breaches or cyber-attacks by identifying abnormal data patterns. Deep learning (DL) driven anomaly detection has emerged as an effective and powerful method for identifying abnormal behaviours or patterns in the data domain. This technique leverages the abilities of a deep neural network for automated learning of complex patterns and representations from data, which make it better for anomaly detection task where irregularities cannot be easily defined by handcrafted rules. This paper establishes a new Billiard Based Optimization with Deep Learning Driven Anomaly Detection and Classification (BBODL-ADC) technique in IoT-assisted Sustainable Smart Cities. The goal of the BBODL-ADC technique lies in the proper recognition and classification of anomalies in the IoT-assisted smart city. To obtain that, the BBODL-ADC system applies a binary pigeon optimization algorithm (BPEO) algorithm for the effectual selection of features. Besides, the BBODL-ADC technique utilizes Elman recurrent neural network (ERNN) approach for the recognition and classification of anomalies. Moreover, the BBO system can be used for better parameters chosen by the ERNN algorithm. The stimulation value of the BBODL-ADC algorithm can be executed benchmark database. The achieved outcomes demonstrate the remarkable outcome of the BBODL-ADC methodology of 95.69% and 99.21% compared to existing models under dataset-1 and dataset-2. [ABSTRACT FROM AUTHOR]

The exponential increase in the dependence on electrical power by rapid industrialization and increasing population has given rise to the need of supplying electric power efficiently and with good power quality (PQ). The evolution of renewable energy sources and their increased penetration into traditional grid systems has increased the complexity of electric power transmission and distribution. The significant increase in the use of complex converters, Flexible AC Transmission System devices and complex nonlinear loads in modern power systems have amplified the issues associated with the production and distribution of electricity having proper PQ. The proper functioning of the power system network requires healthy quality of power, maintained both at the load and source end. The Dynamic Voltage Restorer is a prospective D-FACTS (Distribution Flexible AC Transmission System) device that has been widely incorporated for addressing the PQ issues caused by irregularities in the distribution grid's voltage, current, or frequency. This research article attempts to enhance PQ indices of Photovoltaic, Fuel Cell, DVR and energy storage (battery) based Microgrid systems through a proposed Scaled Conjugate based Artificial Neural Network (SC-ANN) in the Matlab/Simulink architecture. The suggested technique's effectiveness is verified by introducing severe PQ faults such as sag and swell and numerous power system responses have been comprehensively studied by comparing them with traditional Fuzzy Logic Controller and Proportional Integral controllers. The results obtained validates the efficiency of the proposed controller over FLC and PI methods in maintaining the system power indices constant during the onset of PQ faults by reducing harmonics and oscillations thereby enhancing the overall system reliability, efficiency and stability paving its way for real-time implementation in the areas of MG system. [ABSTRACT FROM AUTHOR]

• Chenodeoxycholic acid (CDCA) is the standard of care for treatment of CTX. • Treatment with CDCA in women with CTX during pregnancy is not widely accepted. • Cessation of CDCA treatment for CTX during pregnancy may harm the mother and fetus. • Most CTX experts recommend continuation of treatment with CDCA during pregnancy. • Our report highlights the experience of two women with CTX treated during pregnancy. • Neither woman experienced complications related to CDCA treatment during pregnancy. Cerebrotendinous xanthomatosis (CTX) is a rare, autosomal recessive disorder of bile acid synthesis that presents with varied and progressive symptomology. Early treatment with chenodeoxycholic acid (CDCA) improves symptoms and slows degeneration. Patients with CTX are commonly recommended to discontinue CDCA treatment during pregnancy because of theoretical risks to the fetus, but patient and clinician concerns about the risks of stopping treatment cause uncertainty. Herein, we report the experiences and perspectives of two women with CTX from the time of diagnosis through pregnancy, as well as decisions regarding CDCA treatment during pregnancy. Before becoming pregnant, both women were concerned about potential risks to their newborns if they continued or stopped CDCA treatment during pregnancy. Reassurance from their CTX specialist was the primary factor in their decision to continue treatment during pregnancy. After pregnancies complicated by preeclampsia, one gave birth to a healthy infant and the other gave birth to an infant later diagnosed with periventricular leukomalacia. Neither experienced CDCA-related complications. [ABSTRACT FROM AUTHOR]

Environmental Sound classification (ESC) is crucial in various fields such as audio surveillance, wildlife conservation, and acoustic monitoring. However, traditional methods often struggle to handle the curse of dimensionality and the limitations of classical machine learning algorithms. In the paper, a novel approach is proposed for ESC using a Quantized Hybrid Quantum-Classical Neural Network (QQNN), which leverages the potential advantages of quantum computing. The Hybrid QQNN architecture aims to reduce the required parameters and achieve performance comparable to traditional methods. It uses a set of pre-trained layers to reduce the number of features for the parameterized quantum circuit (PQC). This approach was evaluated using the ESC-10 dataset in Pennylane's environment to train the hybrid quantum model. The results demonstrate that the proposed Hybrid QQNN approach achieves comparable accuracy with the classical machine learning methods. This opens up the possibility of performing additional transfer learning in the future. [ABSTRACT FROM AUTHOR]

Cerebrotendinous xanthomatosis (CTX) is a rare, autosomal recessive bile acid synthesis disorder caused by pathologic variants in CYP27A1 , a gene involved in bile acid synthesis. Impaired function in this gene leads to accumulation of plasma cholestanol (PC) in various tissues, often in early childhood, resulting in such clinical signs as infantile diarrhea, early-onset bilateral cataracts, and neurological deterioration. The current study aimed to identify cases of CTX in a population of patients with a greater CTX prevalence than the general population, to facilitate early diagnosis. Patients diagnosed with early-onset, apparently idiopathic, bilateral cataracts between the ages of 2 and 21 years were enrolled. Genetic testing of patients with elevated PC and urinary bile alcohol (UBA) levels was used to confirm CTX diagnosis and determine CTX prevalence. Of 426 patients who completed the study, 26 met genetic testing criteria (PC ≥ 0.4 mg/dL and positive UBA test), and 4 were confirmed to have CTX. Prevalence was found to be 0.9% in enrolled patients, and 15.4% in patients who met the criteria for genetic testing.▪ [ABSTRACT FROM AUTHOR]

OBJECTIVE: To assess changes in screening completion in a diverse, 7-clinic network after making annual screening for social/emotional/behavioral (SEB) problems the standard of care for all infant through late adolescent-aged patients and rolling out a fully automated screening system tied to the electronic medical record and patient portal. METHODS: In 2017, the Massachusetts General Hospital made SEB screening using the age-appropriate version of the Pediatric Symptom Checklist the standard of care in its pediatric clinics for all patients aged 2.0 months to 17.9 years. Billing records identified all well-child visits between January 1, 2016 and December 31, 2019. For each visit, claims were searched for billing for an SEB screen and the electronic data warehouse was queried for an electronically administered screen. A random sample of charts was reviewed for other evidence of screening. Chi-square analyses and generalized estimating equations assessed differences in screening over time and across demographic groups. RESULTS: Screening completion (billing and/or electronic) significantly increased from 2016 (37.2%) through 2019 (2017 [46.2%] vs 2018 [66.8%] vs 2019 [70.9%]; χ² (3) =112652.33, P < .001), with an even higher prevalence found after chart reviews. Most clinics achieved screening levels above 90% by the end of 2019. Differences among demographic groups were small and dependent on whether data were aggregated at the clinic or system level. CONCLUSIONS: Following adoption of a best-practice policy and implementation of an electronic system, SEB screening increased in all age groups and clinics. Findings demonstrate that the AAP recommendation for routine psychosocial assessment is feasible and sustainable. [ABSTRACT FROM AUTHOR]

[Display omitted] • Sendra Formation sediments deposited in a passive margin setting at < 1065 Ma. • Detritus source: Neoarchean-Paleoproterozoic basement and juvenile terrane. • Post-collisional A- and I-type magmatism at 1000–970 Ma. • I-type Source - mantle wedge formed during previous subduction. • A-type sources: juvenile arc, depleted mantle and ancient crust. The Meso- to Neoproterozoic tectonic evolution of the Aravalli orogen in northwestern India is poorly understood because of limited combined isotopic-geochemical constraints on magmatic and sedimentary rocks. In this study, we present new zircon U-Pb-Hf isotope and whole-rock geochemical data for the Sendra Granitoid Suite and associated host quartzite of the Sendra Formation (Kumbhalgarh Group of the South Delhi Supergroup). Detrital zircon grains reveal a maximum age of deposition during the Stenian at 1065 Ma, and two major sources in the hinterland: (1) a Neoarchean to Paleoproterozoic basement (HfT DM = 2.7 – 2.0 Ga) affected by crustal reworking at 1.8–1.6 Ga, and (2) a juvenile terrain derived from the depleted mantle at ca. 1.6 Ga, and periodically reworked until 1.06 Ga in the Aravalli hinterland. Sediment deposition occurred in a passive margin setting. The post-collisional Sendra granitoids intruded during the Tonian between 1000 and 970 Ma from multiple sources. The highly superchondritic I-type granitoids (εHf t = +10.8 to +12.1; HfT DM = 1.22 Ga) were formed from the fractional crystallisation of calc-alkaline mafic magma generated from partial melting of a mantle wedge. In contrast, the A-type granitoids originated either from melting of (1) relatively young, arc-related juvenile basaltic crust (εHf 1.0 Ga = +10.3 to +15.3), (2) ancient felsic crust of the Aravalli continental margin (εHf 1.0 Ga = -4.4 to −6.4; T DM = 2.08 Ga), and/or (3) by mixing of melts derived from different crust and mantle sources (εHf 0.98 Ga = +0.8 to +3.1). All together, the new results provide evidence that NW India underwent transformation from a passive margin to an accretionary orogenic terrane between 1065 and 1000 Ma, followed by post-collisional magmatism and extension until 970 Ma. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic impacted healthcare delivery worldwide. Resource limitations prompted a multicenter quality initiative to enhance outpatient sleeve gastrectomy workflow and reduce the inpatient hospital burden. This study aimed to determine the efficacy of this initiative, as well as the safety of outpatient sleeve gastrectomy and potential risk factors for inpatient admission. A retrospective analysis of sleeve gastrectomy patients was conducted from February 2020 to August 2021. Inclusion criteria were adult patients discharged on postoperative day 0, 1, or 2. Exclusion criteria were body mass index ≥60 kg/m2 and age ≥65 years. Patients were divided into outpatient and inpatient cohorts. Demographic, operative, and postoperative variables were compared, as well as monthly trends in outpatient versus inpatient admission. Potential risk factors for inpatient admission were assessed, as well as early Clavien-Dindo complications. Analysis included 638 sleeve gastrectomy surgeries (427 outpatient, 211 inpatient). Significant differences between cohorts were age, co-morbidities, surgery date, facility, operative duration, and 30-day emergency department (ED) readmission. Monthly frequency of outpatient sleeve gastrectomy rose as high as 71% regionally. An increased number of 30-day ED readmissions was found for the inpatient cohort (P =.022). Potential risk factors for inpatient admission included age, diabetes, hypertension, obstructive sleep apnea, pre–COVID-19 surgery date, and operative duration. Outpatient sleeve gastrectomy is safe and efficacious. Administrative support for extended postanesthesia care unit recovery was critical to successful protocol implementation for outpatient sleeve gastrectomy within this large multicenter healthcare system, demonstrating potential applicability nationwide. • Outpatient sleeve gastrectomy is safe and effective. • Extended PACU recovery increases success for outpatient sleeve gastrectomy. • There is no increase in 30-day ED visits, hospital readmission, or reoperation. [ABSTRACT FROM AUTHOR]

The population of adult patients with both Down syndrome and congenital heart disease is increasing due to better medical and surgical care. This cohort presents with multiple unique comorbidities, secondary to both progressions of health conditions associated with the aging of patients with Down syndrome, as well as due to pathophysiologic effects of uncorrected, corrected, or palliated congenital heart disease. These patients need frequent medical care and interventions requiring multiple anesthetics. This review focuses on the various factors relevant to the perioperative medical care of adult patients with both Down syndrome and congenital heart disease, founded on existing literature. Various anesthetic considerations for the different patterns of noncardiac and cardiac comorbidities are reviewed, and a systematic approach for the perioperative anesthetic management of these patients is presented. [ABSTRACT FROM AUTHOR]

• A 3-months, randomized, placebo-controlled trial of individualized homeopathic medicines was conducted on 60 participants with post-stroke hemiparesis at National Institute of Homoeopathy, West Bengal, India. • There was a small, but non-significant direction of effect favoring homeopathy against placebos in treatment of post-stroke hemiparesis. • Causticum, Lachesis mutus , and Nux vomica were the most frequently prescribed medicines. : Hemiparesis is a serious motor impairment following stroke and affecting around 65% of stroke patients. This trial attempts to study the efficacy of individualized homeopathic medicines (IHMs) in comparison with identical-looking placebos in treatment of post-stroke hemiparesis (PSH) in the mutual context of standard physiotherapy (SP). : A 3-months, open-label, randomized, placebo-controlled trial (n = 60) was conducted at the Organon of Medicine outpatient departments of National Institute of Homoeopathy, West Bengal, India. Patients were randomized to receive IHMs plus SP (n = 30) or identical-looking placebos plus SP (n = 30). Primary outcome measure was Medical Research Council (MRC) muscle strength grading scale; secondary outcomes were Stroke Impact Scale (SIS) version 2.0, Modified Ashworth Scale (MAS), and stroke recovery 0–100 visual analogue scale (VAS) scores; all measured at baseline and 3 months after intervention. Group differences and effect sizes (Cohen's d) were calculated on intention-to-treat sample. : Although overall improvements were higher in the IHMs group than placebos with small to medium effect sizes, the group differences were statistically non-significant (all P >0.05, unpaired t -tests). Improvement in SIS physical problems was significantly higher in IHMs than placebos (mean difference 2.0, 95% confidence interval 0.3 to 3.8, P = 0.025, unpaired t -test). Causticum, Lachesis mutus , and Nux vomica were the most frequently prescribed medicines. No harms, unintended effects, homeopathic aggravations or any serious adverse events were reported from either group. : There was a small, but non-significant direction of effect favoring homeopathy against placebos in treatment of post-stroke hemiparesis. : CTRI/2018/10/016196; UTN: U1111–1221–7664 [Display omitted] [ABSTRACT FROM AUTHOR]