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AbstractBrands’ positions on sociopolitical issues have a digital impact on their social media presence. While previous studies concentrated on text-based platforms to unravel the digital impact, less attention was given to video-based platforms. This research explores whether brand-activistic videos are more popular than nonactivistic videos on YouTube. Furthermore, this research examines which facial emotions increase a video’s popularity, a topic limitedly addressed in the prior literature. Compiling two data sets of YouTube videos (NStudy1= 174 videos; NStudy2= 666 videos), this research finds that activistic video ads are more popular than nonactivistic video ads on YouTube. Activistic video ads with higher amounts of sadness, anger, and fear expressed as facial emotions have greater popularity. This finding may be because activistic videos are created around social issues, and when actors convey these issues empathically these videos stimulate actionable behaviors. Moreover, the results show that videos focused on lesbian, gay, bisexual, transgender, and queer (LGBTQ) issues are more popular than non-LGBTQ video ads. The implications of these findings are discussed in detail.

Time series forecasting is a vital component of data science, giving essential insights that help decision-makers to predict future trends across a number of sectors. This paper focuses on projecting complicated stock market price dynamics, weather data variations, and hourly traffic occupancy rates. The Informer-Based Time Series Forecasting (IBTSF) model, which employs a transformer-based architecture to capture long-term relationships and give probabilistic predictions, is proposed.This model is assessed against Long Short-Term Memory (LSTM), Temporal Convolutional Network (TCN) and Gated Recurrent Unit (GRU) model to benchmark its performance. Simulation findings demonstrate that the IBTSF model considerably outperforms other models across all datasets. For traffic data, the IBTSF model achieves a Mean Squared Error (MSE) of 10.1 and a Mean Absolute Scaled Error (MASE) of 1.69, compared to other model's larger mistakes. In stock data forecasting, the IBTSF model reports an MSE of 8.04 and a MASE of 1.53, again outperforming other models. Similarly, using meteorological data, the IBTSF model obtains an MSE of 86.12 and a MASE of 0.7, whereas other models fall short. These results underline the IBTSF model's resilience and accuracy in capturing subtle patterns and relationships within time series data, giving precise insights that benefit decision-making processes.

Background and Aims: This study aims to investigate the clinicopathological profile of cervical lymphadenopathy in a tertiary referral centre. The findings will contribute to a deeper understanding of the disease spectrum, aid in accurate diagnosis, and help in improving patient treatment and outcomes.Methodology: This is a prospective study conducted in the Department of ENT, Head and Neck Surgery, Apollo Hospital, Chennai, between June 2022 and May 2023. The clinicopathological profile of all patients was analysed. The final histological diagnosis and the preoperative Fine Needle Aspiration Cytology (FNAC) were correlated. The primary tumour was identified in cases with metastatic secondary tumours in the neck.Results: Among the 80 patients in our study, 67% had a benign aetiology (most common was tuberculosis), and 33% had a malignant aetiology (most common was Hodgkin’s Lymphoma). Gender distribution was equal, with those between the ages of 35 and 60 more frequently affected. The nasopharynx (30%) was the most likely location of the occult primary, followed by the thyroid (20%) and larynx (20%). In detecting TB, FNAC had a sensitivity of 75.5% and a specificity of 98%; in detecting lymphomas, it was 64% and 100%; in detecting metastatic secondaries, it was 80% and 100%; and in detecting reactive lymphadenitis, it was 79% and 86%.Conclusion: Cervical lymphadenopathy is a common entity requiring careful evaluation and treatment. PET scans prove invaluable in detecting occult primary tumours. FNAC is an initial, cost-effective diagnostic tool. However, biopsy is indicated in specific conditions to obtain accurate diagnosis to enable prompt treatment.

Smart windows using thermochromic materials provide an excellent thermal management system over broad temperature ranges, leading to significant energy savings. Existing thermochromic materials face challenges, including difficulty in application, degradation during use, and limited durability. Here, we report a simple salted polymer blend system, consisting of poly(dimethylsiloxane), poly(ethylene oxide), and lithium perchlorate, that shows excellent thermochromic properties across an accessible temperature window and remarkable durability. The reversible temperature dependence of optical transmittance of the films arises due to the miscibility of the constituent polymers at room temperature, leading to high transparency, and the gradual phase separation and opaqueness with temperature rise. The easy-to-fabricate, stable polymer system can be a viable and cost-effective alternative to inorganic thermochromic materials such as vanadium dioxide for many applications.

Meat consumption could increase the risk of type 2 diabetes. However, evidence is largely based on studies of European and North American populations, with heterogeneous analysis strategies and a greater focus on red meat than on poultry. We aimed to investigate the associations of unprocessed red meat, processed meat, and poultry consumption with type 2 diabetes using data from worldwide cohorts and harmonised analytical approaches.

This paper presents the numerical analysis of a convergent-divergent circular nozzle with the exit Mach number of 1.69 with and without passive control at the exit. The passive control method opted for this analysis was inward and outward ascending triangular protrusion. This paper explores the influence of the passive control geometry and its blockage area concerning the nozzle exit. The nozzle pressure ratio (NPR) used for carrying out the flow analysis were 3, 4.932, and 6. Two different inward and outward protrusions were used with a height of 1.5 mm and 3 mm. From the results, the potential core length of the protrusion 1.5 mm height was not much changed in the both outward and inward cases. But when the height of the protrusion was increased to 3 mm, there was a noticeable core length reduction at all NPR but with different cases. At the NPR of 6, the potential core length of the inward protrusions 3 mm was reduced by 44 % compared to the plain CD nozzle.

Legislative agendas aimed at regulating nurse staffing in US hospitals have intensified after acute workforce disruptions triggered by COVID-19. Emerging evidence consistently demonstrates the benefits of higher nurse staffing levels, although uncertainty remains regarding whether and which legislative approaches can achieve this outcome. The purpose of this study was to provide a comprehensive updated review of hospital nurse staffing requirements across all fifty states. As of January 2024, seven states had laws pertaining to staffing ratios for at least one hospital unit, including California and Oregon, which had ratios pertaining to multiple units. Eight states required nurse staffing committees, of which six specified a percentage of committee members who must be registered nurses. Eleven states required nurse staffing plans. Five states had pending legislation, and one state, Idaho, had passed legislation banning minimum nurse staffing requirements. The variety of state regulations provides an opportunity for comparative evaluations of efficacy and feasibility to inform new legislation on the horizon.

More than 90% of gestational diabetes cases are estimated to occur in low-income and middle-income countries (LMICs). Most current guidelines recommend an oral glucose tolerance test (OGTT) at 24–28 weeks of gestation. The OGTT is burdensome, especially in LMICs, resulting in a high proportion of women not being screened. We aimed to develop a simple and effective screening strategy for gestational diabetes.

ABSTRACTExotropic-Duane Syndrome (XT-DRS) is a congenital cranial nerve dysinnervation disorder characterized by exotropia, anomalous head posture (contralateral face turn), limited adduction, globe retraction, palpebral fissure narrowing, upshoot and downshoot in adduction, and varying levels of limitation of abduction. Patients with XT-DRS often have poor convergence because attempted convergence induces co-contraction of the lateral rectus muscle (LR) due to anomalous LR innervation. We describe two patients with XT-DRS who underwent simultaneous lateral rectus muscle (LR) disinsertion and periosteal fixation (LRDAPF) and modified Nishida procedure (MNP) and discuss their outcome. In one patient, we combined this procedure with a contralateral LR recession. Anomalous head posture, exotropia, globe retraction, and palpebral fissure narrowing were reduced. Upshoot and downshoot were also reduced. Convergence improved in both patients.

The article focuses on logging and the Loki Operator within Kubernetes environments, emphasizing their roles in managing and analyzing log data for troubleshooting, performance monitoring, and security analysis. Topics include deploying the Loki Operator on s390x architecture, configuring log aggregation with Loki and Prometheus, and utilizing OpenShift Container Platform for centralized logging, with insights into application, infrastructure, and audit logs.

The removal of organic particulates from septic tank waste waters is the most crucial part of biological treatment processes. In this regard, the present study explores the potential applications of septic tank waste water treatment (STWW) system in the removal of organic matter and energy generation using Microbial fuel cells. The effect of acrylic varnish coating over the clay cup along with stirring (ACS- SMFC) has produced 70% more electricity than the uncoated clay cups without stirring, with the OCV of 984 ± 2 mV, current and power density of 706 ± 5.78 mA/m3and 61.17 ± 0.29 mW/m3. The fabrication of the clay cup proves the presence of Niobium and chlorine functional groups in EDAX analysis, which affirms its high electron flow and superconductivity for better electricity production. SEM and confocal laser scanning microscopy affirmed the catabolic conversion of organic substrates of STWW through microbial communities of biofilm on bioelectricity production. Thus the higher COD removal value of 60.3 ± 0.09% was achieved in the ACS –SMFC module by utilizing STWW as substrate. Acrylic varnishing's efficacy on clay cups was confirmed via Fourier transform infrared spectroscopy with prominent peaks between 700 cm−1to 3612 cm−1.

Aluminum (Al) holds a pivotal role in augmenting the energetic potential of solid fuel formulations. Its incorporation can notably amplify the energy yield upon combustion. Nevertheless, challenges such as ignition delay and incomplete combustion have hindered its optimal utilization. In the context of hybrid rocket propulsion, where reignition and high regression rates are sought, a promising solution lies in harnessing the potential of metal-fluoropolymer combinations. This paper explores the influence of polytetrafluoroethylene (PTFE) and Viton fluoropolymer additives on the combustion and regression rates of hydroxyl‑terminated polybutadiene (HTPB)-based solid fuels loaded with nano-aluminum (nAl). To comprehensively address these objectives, binary composites of nAl-PTFE and nAl-Viton were prepared using high-energy ball-milling, and the resulting mixtures were incorporated into hydroxyl‑terminated polybutadiene (HTPB)-based fuel through a vacuum-casting technique. The ignition and combustion characteristics of the solid fuels, as well as the post-combustion products, were examined using an opposed flow burner setup to gain insights into their oxidation and combustion mechanisms. The findings demonstrate that the inclusion of PTFE and Viton in nAl has a positive impact on the ignition delay time, combustion behavior, and regression rates of the solid fuels. The HTPB-nAl-PTFE(S3) sample exhibited the shortest ignition delay time of 108 ms, outperforming the other tested samples (S1: 227 ms, S2: 182 ms, S4: 122 ms). Furthermore, the addition of nAl to pure HTPB resulted in an average regression rate of 0.3–0.6 mm/s for HTPB-nAl (S2), representing a two fold improvement compared to pure HTPB-based samples. Compared to the baseline HTPB fuel, HTPB-nAl-PTFE(S3) demonstrated a significant increase in regression rate by approximately 178%, while HTPB-nAl-Viton(S4) exhibited an increased regression rate of 122%. These results highlight the positive influence of fluoropolymers on combustion behavior, ultimately enhancing the overall performance of the fuel. Additionally, the study observed gas-phase reactions during the combustion process, including the reaction between nano-aluminum (nAl) and fluoride, the intermediate product of Al oxidation, and the decomposition products of fluoride. These reactions resulted in the faster fracture of the alumina (Al2O3) shell, leading to improved heat release and regression rate performance.

Purpose: The purpose of the designed MEMS dual axis accelerometer is to act as a seismic sensor by measuring low-level vibration at low frequencies, usually including those below 1 Hz. Piezoelectric materials have demonstrated broad applicability in numerous devices and electronic applications. Since piezoelectric energy harvesting devices create their highest power at the resonance frequency, there is a strong relationship between frequency and power density, where ω is the fundamental vibration mode frequency, the potential output power is proportional to 1/ω. Methods: A dual-axis MEMS piezoelectric accelerometer for low-frequency seismic sensing was modelled and simulated with different suspension systems. For a bandwidth range of 1 KHz, COMSOL Multiphysics has been used to simulate the accelerometer supported by a U beam, Parallel beam, folded beam, and Swastik structures. The dual detection of acceleration in the X–Y direction and the ability to produce voltage was detected in all four variations of MEMS accelerometers. Results: The dual detection of acceleration in the X–Y direction and the ability to produce voltage was detected in all four variations of MEMS accelerometers. Based on the investigation, it has been found that the Swastik design produces the highest stress overall, with a value of 0.4 × 105N/m2and has a maximum sensitivity of 0.8 × 10-3Volts/g, making it more suited for seismic sensing applications. Conclusion: The proposed dual-axis MEMS piezoelectric accelerometer with the Swastik suspension system can be used as a seismic sensor to detect low-frequency seismic signals, particularly P-waves. The findings of this paper can be applied in the development of new and improved MEMS accelerometers for various applications, such as vibration sensing, structural health monitoring, and seismic sensing.

Prolonged inflammation leads to the genesis of various inflammatory diseases such as atherosclerosis, cancer, inflammatory bowel disease, Alzheimer’s, etc. The uncontrolled inflammatory response is characterized by the excessive release of pro-inflammatory mediators such as nitric oxide (NO), tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-1alpha (IL-1α), and inflammatory enzymes such as cyclooxygenase-2 (COX-2). Hence, the downregulation of these inflammatory mediators is an active therapy to control aberrant inflammation and tissue damage. To address this, herein, we present the rational design and synthesis of novel phytochemical entities (NPCEs) through strategic linker-based molecular hybridization of aromatic/heteroaromatic fragments with the labdane dialdehyde, isolated from the medicinally and nutritionally significant rhizomes of the plant Curcuma amada. To validate the anti-inflammatory potential, we employed a comprehensive in vitrostudy assessing its inhibitory effect on the COX-2 enzyme and other inflammatory mediators, viz., NO, TNF-α, IL-6, and IL-1α, in bacterial lipopolysaccharide-stimulated macrophages, as well as in-silicomolecular modeling studies targeting the inflammation regulator COX-2 enzyme. Among the synthesized novel compounds, 5fexhibited the highest anti-inflammatory potential by inhibiting the COX-2 enzyme (IC50= 17.67 ± 0.89 μM), with a 4-fold increased activity relative to the standard drug indomethacin (IC50= 67.16 ± 0.17 μM). 5falso significantly reduced the levels of LPS-induced NO, TNF-α, IL-6, and IL-1α, much better than the positive control. Molecular mechanistic studies revealed that 5fsuppressed the expression of COX-2 and pro-inflammatory cytokine release dose-dependently, which was associated with the inhibition of the NF-κB signaling pathway. This infers that the labdane derivative 5fis a promising lead candidate as an anti-inflammatory agent to further explore its therapeutic landscape.

In this study, density was measured for hydrophilic deep eutectic solvents based on tetrabutylammonium bromide (as hydrogen bond acceptor) and glycerol (as hydrogen bond donor) in a 1:3 mol ratio with an aqueous heavy metal (Cu/Hg) solution at various concentrations in the temperature range of 298.15–348.15 K at atmospheric pressure. The excess molar volume, partial molar volume, excess partial molar volume, apparent molar volume, excess partial molar volume at infinite dilution, and isobaric expansivity were calculated to study the nonideal behavior of these pseudobinary systems. The obtained excess molar volumes (VmE) of 72 systems were then fitted to Redlich–Kister-type polynomial expressions. In addition, the performance of the predictive conductor-like screening model for real solvents (COSMO-RS) model is capable of quantitatively observing the sigma surface, sigma profile, and sigma potential of the individual chemical species and six prepared deep eutectic solvents. The existence of bands was analyzed for hydrogen bond acceptors (HBAs), hydrogen bond donors (HBDs), and used metal salts using Fourier transform infrared (FTIR) spectroscopy. Hydrophobic deep eutectic solvents (DESs) removed heavy metal (HM) ions from the synthetic contaminated water stream. At lower concentrations of Hg2+ions, extraction efficiency showed a higher value of 98.85% with capric acid-based DESs. Similarly, the extraction efficiency for Cu2+ions reached a maximum of 54.25% in this study. Before and after extraction, the concentrations of divalent copper and mercury were analyzed using inductively coupled plasma optical emission spectroscopy (ICP-OES).

In flying ad hoc networks (FANET), medium access layer (MAC) protocols play an essential role in ensuring better network performance. The effective utilization of network resources and providing access fairness are key research issues in this area, and the contention window size directly influences these factors. This paper mainly focuses on addressing the upper and lower boundaries of the contention window in Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) with a binary exponential back-off algorithm. Existing solutions include static and dynamic window adjustment techniques only to update the upper boundary of the contention window size. However, the static window adjustment technique is unsuitable for changing network conditions, while the dynamic window adjustment technique may need to be more efficient in dense network environments. The proposed solution uses a Deep Q-learning algorithm(DQN) framework to adjust the contention window adaptively based on the reward function, resulting in efficient and dynamic adaptation to changing network conditions among unmanned aerial vehicles (UAV). The proposed methodology is evaluated through simulations, and performance is measured using channel utilization, efficiency, delay, and collision rate. The simulation findings show that, in comparison to generic MAC protocols, the proposed algorithm is 5% more efficient in throughput and incurs a four-fold reduction in delay.

Caveolin-1 (Cav-1) is a critical lipid raft protein playing dual roles as both a tumor suppressor and promoter. While its role in tumorigenesis, progression, and metastasis has been recognized, the explicit contribution of Cav-1 to the onset of lung metastasis from primary breast malignancies remains unclear. Here, we present the first evidence that Cav-1 knockout in mammary epithelial cells significantly reduces lung metastasis in syngeneic breast cancer mouse models. In vitro, Cav-1 knockout in 4T1 cells suppressed extracellular vesicle secretion, cellular motility, and MMP secretion compared to controls. Complementing this, in vivo analyses demonstrated a marked reduction in lung metastatic foci in mice injected with Cav-1 knockout 4T1 cells as compared to wild-type cells, which was further corroborated by mRNA profiling of the primary tumor. We identified 21 epithelial cell migration genes exhibiting varied expression in tumors derived from Cav-1 knockout and wild-type 4T1 cells. Correlation analysis and immunoblotting further revealed that Cav-1 might regulate metastasis via integrin α3 (ITGα3). In silico protein docking predicted an interaction between Cav-1 and ITGα3, which was confirmed by co-immunoprecipitation. Furthermore, Cav-1 and ITGα3 knockdown corroborated its role in metastasis in the cell migration assay.

In this study, we construct a single server retrial queueing system with two types of breakdowns, delayed repair, Bernoulli feedback, balking and working vacation. Two different categories of customers like priority and ordinary are to be considered. This model proposes non-pre-emptive priority discipline. Ordinary and priority customers arrive as per Poisson processes. For both ordinary and priority customers, the server consistently affords a single service that follows to general distribution. During certain periods, an arriving ordinary customer may balk the system. When the orbit and priority queue are empty after the service is ended, the server takes a single working vacation. In this study, we used probability generating function and supplementary variable technique to solve the Laplace transforms of time-dependent probabilities of system states. In order to accelerate the sensitivity analysis of system descriptions, numerical data are obtained and also examined.

Asciminib targets the BCR::ABL1myristoyl pocket, maintaining activity against BCR::ABL1T315I, which is resistant to most approved adenosine triphosphate–competitive tyrosine kinase inhibitors. We report updated phase I results (NCT02081378) assessing safety/tolerability and antileukemic activity of asciminib monotherapy 200 mg twice daily in 48 heavily pretreated patients with T315I-mutated chronic-phase chronic myeloid leukemia (CML-CP; data cutoff: January 6, 2021). With 2 years’ median exposure, 56.3% of patients continued receiving asciminib. Overall, 62.2% of evaluable patients achieved BCR::ABL1≤1% on the International Scale (IS); 47.6% and 81.3% of ponatinib-pretreated and -naive patients, respectively, achieved BCR::ABL1IS≤1%. Of 45 evaluable patients, 48.9% achieved a major molecular response (MMR, BCR::ABL1IS≤0.1%), including 34.6% and 68.4% of ponatinib-pretreated and -naive patients, respectively. MMR was maintained until data cutoff in 19 of 22 patients who achieved it. The most common grade ≥3 adverse events (AEs) included increased lipase level (18.8%) and thrombocytopenia (14.6%). Five (10.4%) patients experienced AEs leading to discontinuation, including 2 who discontinued asciminib and died due to COVID-19; these were the only deaths reported. These results show asciminib’s effectiveness, including in almost 50% of ponatinib pretreated patients, and confirm its risk-benefit profile, supporting its use as a treatment option for T315I-mutated CML-CP.

This article explores a two-commodity stochastic queueing-inventory system (TCSQIS) along with a multi-server and a classical retrial facility. In this two-commodity, the first one is called a primary product (PP) and the second one is called a complimentary product (CP). The TCSQIS provides a multi-server service facility to an arriving customer in order to reduce the loss of arrival and increase more sales and profit. Suppose the arriving customer sees that all the servers are engaged or there are no sufficient products in the system, they go to an infinite orbit compulsorily. The customers in orbit can approach the system under classical retrial policy, whenever they confirm that the system must consist of at least one server that is free and positive stock. The stationary probability vector is obtained by the matix-geometric approach (MGA). Further, adequate examples are provided to explore the proposed model.

Ontology based information extraction and summarization process in news content retrieved the news based on the user query. The user query should be of any context about the news content. So that, users need not be aware of the information that they search. This type of ontology based multi-document summarization system mainly focused on abstract document found in the news content. So, we proposed a work to combine information extraction, Abstraction based summarization and natural language generation to generate efficient multi-document summarization from multiple news articles. In this paper, we proposed an IE-supported summarization system that automatically extracts keyword for text summarization in Tamil e-newspaper datasets. The system first requires that the user need to select the particular domain. A set of news articles related to the domain is searched by search engine. One or more scenario templates (likes extraction domains such as Science, and technology, sports and natural disasters) are used to activate the system. The user optionally provides filters and preferences on the scenario template slots, specifying what information he/she wants to be reported in the summary. Then the system invokes the Summarizer to generate a natural language summary of the extracted information subject to the user’s constraints.

Background: The readability of online bariatric surgery patient education materials (PEMs) often surpasses the recommended 6th grade level. Large language models (LLMs), like ChatGPT and Bard, have the potential to revolutionize PEM delivery. We aimed to evaluate the readability of PEMs produced by U.S. medical institutions compared to LLMs, as well as the ability of LLMs to simplify their responses. Methods: Responses to frequently asked questions (FAQs) related to bariatric surgery were gathered from top-ranked health institutions. FAQ responses were also generated from GPT-3.5, GPT-4, and Bard. LLMs were then prompted to improve the readability of their initial responses. The readability of institutional responses, initial LLM responses, and simplified LLM responses were graded using validated readability formulas. Accuracy and comprehensiveness of initial and simplified LLM responses were also compared. Results: Responses to 66 FAQs were included. All institutional and initial LLM responses had poor readability, with average reading levels ranging from 9th grade to college graduate. Simplified responses from LLMs had significantly improved readability, with reading levels ranging from 6th grade to college freshman. When comparing simplified LLM responses, GPT-4 responses demonstrated the highest readability, with reading levels ranging from 6th to 9th grade. Accuracy was similar between initial and simplified responses from all LLMs. Comprehensiveness was similar between initial and simplified responses from GPT-3.5 and GPT-4. However, 34.8% of Bard's simplified responses were graded as less comprehensive compared to initial. Conclusion: Our study highlights the efficacy of LLMs in enhancing the readability of bariatric surgery PEMs. GPT-4 outperformed other models, generating simplified PEMs from 6th to 9th grade reading levels. Unlike GPT-3.5 and GPT-4, Bard’s simplified responses were graded as less comprehensive. We advocate for future studies examining the potential role of LLMs as dynamic and personalized sources of PEMs for diverse patient populations of all literacy levels.

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Objective: The present study proposed Dabigatran Etexilate loaded solid supersaturated self-nanoemulsifying drug delivery system (solid S-SNEDDS) for enhancement of payload, drug solubility, dissolution rate as well as minimization of drug precipitation.Methods: The study involved formulation optimization using the Box-Behnken design. The optimal SNEDDS consisting of Caprylic acid (32.9% w/w), Cremophor EL (50.2% w/w) and Transcutol HP (18.8% w/w) as Oil, Surfactant and Co-surfactant, respectively were formulated and evaluated for particle size, PDI, Zeta potential and saturation solubility. The SNEDDS was further incorporated with PPIs for the preparation of supersaturated SNEDDS (S-SNEDDS) to increase the drug payload in the formulation. S-SNEDDS was converted to solid S-SNEDDS by adsorption onto the porous carrier i.e., Aerosil®200. The in-vitro drug release study was also conducted for solid S-SNEDDS.Results: SNEDDS had size, PDI, and Zeta potential of 82 nm, 0.347, -10.50 mV, respectively. SNEDDS enhanced the saturation solubility of the drug by 93.65-fold. Among PPIs, HPMC K4M showed the most effective response for the formulation of S-SNEDDS. The S-SNEDDS had a more substantial drug payload, which further increased the solubility by 150 times of pure drugs and 16 times of SNEDDS. Solid S-SNEDDS exhibited free-flowing properties. Reconstituted solid S-SNEDDS had acceptable size, PDI, and Zeta potential of 131.3 nm, 0.457, and -11.3 mV, respectively. In-vitro drug release study revealed higher drug dissolution and minimized drug precipitation by SNEDDS compared to marketed products and pure drugs.Conclusion: Proposed nano-formulation was found to efficiently improve the aqueous solubility of the drug and avoid the drug precipitation, thereby avoiding drug loss and improving drug bioavailability.

To develop electrochemical sensor for detecting ppm level CO, pure and Ni2+doped α-Fe2O3nanopowder was synthesized by solution combustion technique. The basic properties of the synthesized materials were studied. XRD and Raman studies showed that at ≥ 10 mol% doping, NiO phase appear due to segregation. Band gap decreased with doping concentration. In the amperometric mode a constant bias voltage of + 1 V was applied at α-Fe2O3based electrode with respect to a fixed lanthanum strontium cobaltite (LSC55) electrode with 15 mol% Gd doped CeO2(GDC) as solid electrolyte in the sensor structure 3–40 ppm CO tested in base gas (5% O2+ N2) from 350 ºC to 650 ºC with the aim of exhaust gas like application. With pure α-Fe2O3electrode highest sensitivity of 324 μA/decade was obtained at 500 ºC. The response and recovery times were found to vary from 40 to 125 s and 42 s to 260 s respectively in the concentration range 3 ppm to 40 ppm. Sensor with 10 mol% Ni2+doped α-Fe2O3showed inferior performance. In short term repeatability test sensor showed consistently ~ 60 μA change upon 3 ppm CO sensing for several consecutive cycles at 500 ºC. High selectivity to CO with respect to sensing of other coexisting gases makes such sensor promising for application.

Sugarcane mosaic virus(SCMV) and Sugarcane streak mosaic virus(SCSMV) belonging to the family Potyviridaeare the causal agents of mosaic disease complex of sugarcane reported from different Asian countries which causes significant economic losses to sugarcane production. In the present study, a sensitive RT-LAMP based assay was developed for rapid diagnosis of SCMV and SCSMV causing mosaic disease of sugarcane. Primers were designed to amplify the six different regions of the coat protein genes of SCMV and SCSMV and both the viruses were successfully detected by this technique. Comparative analysis of RT-LAMP with the conventional reverse transcription polymerase chain reaction (RT-PCR) and quantitative real time PCR (RT-qPCR) showed that RT-LAMP was more sensitive than the other methods due to its rapid visual detection of the viruses. The sensitivity of RT-LAMP assay developed in the present study was tenfold more than that of conventional RT-PCR and RT-qPCR techniques. This is the first report of RT-LAMP based diagnosis of SCMV and SCSMV from India.

Nanoparticles play a major role in the field of biomedical science, agriculture, engineering, and environment. Plant-based nanoparticles provide biocompatibility, antimicrobial activity, and antioxidant properties. Flowers of Tagetes erecta(marigold flower) have medicinal properties. The novelty of the present study is the synthesis of magnesium oxide nanoparticles (MgO NPs) using the flower extract of Tagetes erecta(marigold flower). The obtained T. erecta–mediated MgO NPs (M-MgO NPs) were examined by UV–Vis spectroscopy, FTIR, XRD, FESEM, EDAX, and TGA. The absorbance spectra of UV–Vis analysis shows the peak at 280 nm which indicates the presence of M-MgO NPs. FTIR spectral analysis confirmed the presence of functional groups such as O–H stretch, C-H stretch, C–O–C bond, and Mg-O-Mg bond. XRD analysis determined the crystalline phase–mediated face-centered cubic M-MgO NPs. Field emission scanning electron microscopic analysis confirmed the spherical shape of M-MgO NPs. The occurrence of Mg, O, and C was identified by EDX analysis. The persistence of thermal stability and mass reduction was observed by TGA. The 67% free radical scavenging activity was observed in M-MgO NPs and proves that M-MgO NPs possess the antioxidant activity. Through the process of green synthesis, M-MgO NPs have biocompatible property and it can be utilized in various fields.

Inventory models with integrated price and stock-dependent demands for deteriorative items are considered in this study. The demand models found in the literature include constant, linear, quadratic, exponential, price dependent, and stock dependent among others. To wit, no study exists that uses price dependent integrated with stock dependent demand. Three models are developed: the first model uses price-dependent demand integrated with stock-dependent demands. The second model uses stock-dependent demand which is given in Appendix A and the third model uses price-dependent demand which is given in Appendix B. Mathematical models are delineated for each model and relevant examples are provided to elucidate the proposed procedure. The objective herein is to obtain optimum cycle time with respect to the overall minimum cost. Sensitivity analysis is provided. The necessary data was generated using visual basic 6.0.

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Fortified rice kernels (FRK) are novel extruded products that are rice-shaped and fortified with folic acid, cyanocobalamin, and iron to manage the prevalence of anemia in developing countries like India. Analysis of micronutrient content in FRK is necessary to ensure its compliance with the legal limits requirement of the added micronutrients. The present study aims to develop an easy, simple, and quick extraction method for analyzing the folic acid content of FRK using HPLC equipped with a variable wavelength detector. Ultrasonic-assisted extraction with probe-type and water-bath-type ultrasonication units was compared, and the extraction conditions were optimized. The time and temperature combinations were 30, 40, and 50°C for 1 to 15 min. Ultrasonic-assisted direct probe extraction at 30°C for 5 min gave the best recovery (98%) with good repeatability. The method showed good linearity with R2= 0.999, 91 to 107% recovery, and repeatability with relative standard deviation (RSD) ≤ 4%. The method’s limit of detection (LoD) and quantification (LoQ) were 0.35 and 1.17 mg/kg, respectively. A control chart was used to determine the reliability of the method over the course of ten months, and values of folic acids were found not to exceed the upper and lower control limits. The stability of folic acid in FRK after extrusion and during rinsing and different cooking methods (open vessel, microwave, and pressure cooker) were analyzed. The retention of folic acid in cooked FRK ranged from 71.64 to 95.15%.

The agricultural sector holds significant importance in the socio-economic structure of India. The inability of farmers to make informed decisions regarding the optimal crop selection for their land, based on non-scientific and traditional methods, poses a significant challenge for a nation where farming constitutes the livelihood of nearly 58% of the population. At times, farmers have experienced challenges in selecting appropriate crops that align with the soil conditions, sowing season, and geographical location. By collecting data from sensors in the fields, ranchers can easily ascertain the extent of the crops, which helps preserve scarce resources and lessens the negative effects of weeds on the environment. The majority of Indian farmers choose conventional farming methods when deciding how their crops should be grown. Regardless, ranchers do not jeopardize agricultural yields, which are sensitive to abiotic factors such as soil type. In this proposed method, two types of datasets have been collected from the southern and northern parts of the country through IoT-based sensors. The crop recommendation system has been processed with various machine learning algorithms like logistic regression, KNN, decision tree, and support vector machine through the collected dataset. The accuracy of 97% and 96% has been achieved for processed datasets in the southern and northern parts of India.

Background: Locoregionally advanced esophageal cancer is typically treated with neoadjuvant chemoradiation followed by surgery 4 to 8 weeks later. Occasionally surgery is delayed >12 weeks; outcomes of this approach are not well studied. We hypothesized that delayed esophagectomy after chemoradiation would have inferior long-term overall survival relative to planned trimodality esophagectomy.Methods: Adult patients with locally advanced esophageal cancer (T2−4aN0M0, T0−4aN+M0) who received multi-agent chemotherapy, radiation, and esophagectomy were identified in the 2018 National Cancer Database. Esophagectomy performed within 90 days from end of chemoradiation were categorized as “trimodality” and those ≥90 days were categorized as “delayed.” Primary outcome was overall survival measured using Kaplan-Meier estimates and Cox proportional hazard models. Secondary outcomes included surgical margin status, hospital length of stay, and readmission.Results: Included were 19 698 patients, 3905 (19.8%) “delayed.” Median time to surgery for trimodality patients was 51 days (IQR 41-63) versus 110 days (IQR 98-131) for delayed patients. Delayed patients tended to be older, non-white, have non-private insurance, and have more comorbidities. Overall survival was shorter for delayed patients (34.8 months) versus trimodality patients (43.1 months, P≤ .001). In multivariable analysis, delay was associated with inferior overall survival (HR 1.15, 95% CI 1.08-1.23). Length of stay and readmission rate were similar between cohorts, but delay was associated with a higher rate of positive surgical margins (6.7% vs 4.6%, P≤ .001).Conclusions: In the National Cancer Database, delayed esophagectomy is associated with inferior long-term survival. Nonetheless, delayed esophagectomy may be appropriate for select patients; further research is needed to identify the optimal approach.

Rapid changes in the environment and geographical conditions can cause major disasters. Monitoring these changes to save lives is a major challenge. In addition to monitoring, timely action is also important. Achieving this goal requires timely preventative information. In this article, a novel Internet of Things (IoT)-based IDISense app has been proposed to monitor and broadcast real-time parameters related to dams and weather conditions. Initially, rainfall sensors, waterfall sensors, flow sensors, and ultrasonic sensors are used to sense the water quantity, dam vacant level, and flow of water in the dam. Data collected by sensors placed at various points on the dam are sent to an Internet-connected Arduino. And, the spiking neural network (SNN) for predicting rainfall using previous year data from the meteorology dataset. Data collected from sensor nodes are used for monitoring and emission sensors are used to control gate opening to specified limits. All decisions are made from the central control room, which observes the situation in all areas and then issues orders to the various local control rooms. Finally, the proposed IDISense app is used to give alerts to neighboring people. The experimental result shows the proposed IDISense app compared with CNN, Resnet, Alexnet, and SNN. In one day, the SNN achieves an overall accuracy is 93.4% and in four days the SNN achieves an overall accuracy is 95.9%.

As companies struggle with chronic skills shortages and changing labor demographics, a new generation of talent platforms, offering on-demand access to highly trained workers, has begun to help. These platforms include marketplaces for premium expertise (such as Toptal and Catalant), for freelance workers (Upwork and 99designs), and for crowdsourcing innovation (Kaggle and InnoCentive). Almost all Fortune 500 firms use such platforms. But most do so in an ad hoc, inefficient way, according to a Harvard Business School/BCG study. Companies need to get much more strategic about their engagement with talent platforms and fully embrace their ability to increase labor force flexibility, speed time to market, and facilitate business model innovation. That will require rewiring policies and processes and redefining working norms. Most important, leaders must inspire the cultural shift needed to realize the platforms’ transformative potential. [ABSTRACT FROM AUTHOR]