Efficacy and safety of cilta-cel in patients with progressive multiple myeloma after exposure to other BCMA-targeting agents.

B-cell maturation antigen (BCMA)-targeting therapies, including bispecific antibodies (BsAbs) and antibody-drug conjugates (ADCs), are promising treatments for multiple myeloma (MM), but disease may progress after their use. CARTITUDE-2 is a phase 2, multicohort study evaluating the safety and efficacy of cilta-cel, an anti-BCMA chimeric antigen receptor T therapy, in various myeloma patient populations. Patients in cohort C progressed despite treatment with a proteasome inhibitor, immunomodulatory drug, anti-CD38 antibody, and noncellular anti-BCMA immunotherapy. A single cilta-cel infusion was given after lymphodepletion. The primary end point was minimal residual disease (MRD) negativity at 10-5. Overall, 20 patients were treated (13 ADC exposed; 7 BsAb exposed; 1 in the ADC group also had prior BsAb exposure). Sixteen (80%) were refractory to prior anti-BCMA therapy. At a median follow-up of 11.3 months (range, 0.6-16.0), 7 of 20 (35%) patients were MRD negative (7 of 10 [70.0%] in the MRD-evaluable subset). Overall response rate (95% confidence interval [CI]) was 60.0% (36.1-80.9). Median duration of response and progression-free survival (95% CI) were 11.5 (7.9-not estimable) and 9.1 (1.5-not estimable) months, respectively. The most common adverse events were hematologic. Cytokine release syndrome occurred in 12 (60%) patients (all grade 1-2); 4 had immune effector cell-associated neurotoxicity syndrome (2 had grade 3-4); none had parkinsonism. Seven (35%) patients died (3 of progressive disease, 4 of adverse events [1 treatment related, 3 unrelated]). Cilta-cel induced favorable responses in patients with relapsed/refractory MM and prior exposure to anti-BCMA treatment who had exhausted other therapies. This trial was registered at www.clinicaltrials.gov as NCT04133636.

Theory of Moiré Magnetism in Twisted Bilayer α-RuCl3.

Motivated by the recent developments in moiré superlattices of van der Waals magnets and the desire to control the magnetic interactions of α-RuCl3, here we present a comprehensive theory of the long-range ordered magnetic phases of twisted bilayer α-RuCl3. Using a combination of first-principles calculations and atomistic simulations, we show that the stacking-dependent interlayer exchange gives rise to an array of magnetic phases that can be realized by controlling the twist angle. In particular, we discover a complex hexagonal domain structure in which multiple zigzag orders coexist. This multidomain order minimizes the interlayer energy while enduring the energy cost due to domain wall formation. Further, we show that quantum fluctuations can be enhanced across the phase transitions. Our results indicate that magnetic frustration due to stacking-dependent interlayer exchange in moiré superlattices can be exploited to tune quantum fluctuations and the magnetic ground state of α-RuCl3.

Biochar enhances the growth and physiological characteristics of Medicago sativa, Amaranthus caudatus and Zea mays in saline soils.

Biochar is a promising solution to alleviate the negative impacts of salinity stress on agricultural production. Biochar derived from food waste effect was investigated on three plant species, Medicago sativa, Amaranthus caudatus, and Zea mays, under saline environments. The results showed that biochar improved significantly the height by 30%, fresh weight of shoot by 35% and root by 45% of all three species compared to control (saline soil without biochar adding), as well as enhanced their photosynthetic pigments and enzyme activities in soil. This positive effect varied significantly between the 3 plants highlighting the importance of the plant-biochar interactions. Thus, the application of biochar is a promising solution to enhance the growth, root morphology, and physiological characteristics of plants under salt-induced stress.

Therapeutic drug monitoring of vancomycin in surgical patients using a validated HPLC method.

BACKGROUND: Vancomycin is being used for the treatment of a variety of infections caused by methicillin resistant Staphylococcus aureus and methicillin susceptible Staphylococcus aureus. Therapeutic drug monitoring (TDM) is highly recommended for ensuring the safe and effective therapy with vancomycin. A reliable and cost-effective bioanalytical method is required for TDM as well as pharmacokinetic studies of vancomycin. MATERIALS AND METHODS: A selective, sensitive, and cost effective HPLC method was developed and validated for quantification of vancomycin concentrations in human plasma. The mobile phase was a mixture of buffer (50 mM ammonium dihydrogen phosphate, pH 2.4) and acetonitrile 88 : 12 v/v. The separation was carried on C18 column (125 × 4.6 mm, particle size 5 µm) with isocratic flow rate of 0.370 mL/min at room temperature with UV detection at 215 nm. The method was validated for sensitivity, accuracy, and precision as well as stability of vancomycin in human plasma by following European Medicine Agency (EMA) guideline. Therapeutic drug monitoring of vancomycin was performed by quantifying the trough concentrations of vancomycin in 65 human plasma samples after administration of therapeutically relevant dose. RESULTS: The developed method was sensitive enough to quantify vancomycin concentrations as low as 0.25 mg/L in human plasma. Moreover, the method was proved accurate and precise in terms of quantifying the unknown concentration of vancomycin. The evaluation of short-term, long-term, and freeze-thaw stability proved the stability of vancomycin in human plasma. The TDM of vancomycin by using this method showed that 39 (60%) samples were within the target trough concentration range (TTCR), i.e. 10 - 20 mg/L, while 23 samples (35.4%) were below the TTCR, and 3 samples (4.6%) were above this range. CONCLUSION: The developed method is sensitive and cost effective for quantification of vancomycin in human plasma. The results of sample analysis shows that the developed method can be used reliably for TDM of vancomycin.

Smart Resource Allocation in Mobile Cloud Next-Generation Network (NGN) Orchestration with Context-Aware Data and Machine Learning for the Cost Optimization of Microservice Applications.

Mobile cloud computing (MCC) provides resources to users to handle smart mobile applications. In MCC, task scheduling is the solution for mobile users' context-aware computation resource-rich applications. Most existing approaches have achieved a moderate service reliability rate due to a lack of instance-centric resource estimations and task offloading, a statistical NP-hard problem. The current intelligent scheduling process cannot address NP-hard problems due to traditional task offloading approaches. To address this problem, the authors design an efficient context-aware service offloading approach based on instance-centric measurements. The revised machine learning model/algorithm employs task adaptation to make decisions regarding task offloading. The proposed MCVS scheduling algorithm predicts the usage rates of individual microservices for a practical task scheduling scheme, considering mobile device time, cost, network, location, and central processing unit (CPU) power to train data. One notable feature of the microservice software architecture is its capacity to facilitate the scalability, flexibility, and independent deployment of individual components. A series of simulation results show the efficiency of the proposed technique based on offloading, CPU usage, and execution time metrics. The experimental results efficiently show the learning rate in training and testing in comparison with existing approaches, showing efficient training and task offloading phases. The proposed system has lower costs and uses less energy to offload microservices in MCC. Graphical results are presented to define the effectiveness of the proposed model. For a service arrival rate of 80%, the proposed model achieves an average 4.5% service offloading rate and 0.18% CPU usage rate compared with state-of-the-art approaches. The proposed method demonstrates efficiency in terms of cost and energy savings for microservice offloading in mobile cloud computing (MCC).

ANN-Based Intelligent Secure Routing Protocol in Vehicular Ad Hoc Networks (VANETs) Using Enhanced AODV.

A vehicular ad hoc network (VANET) is a sophisticated wireless communication infrastructure incorporating centralized and decentralized control mechanisms, orchestrating seamless data exchange among vehicles. This intricate communication system relies on the advanced capabilities of 5G connectivity, employing specialized topological arrangements to enhance data packet transmission. These vehicles communicate amongst themselves and establish connections with roadside units (RSUs). In the dynamic landscape of vehicular communication, disruptions, especially in scenarios involving high-speed vehicles, pose challenges. A notable concern is the emergence of black hole attacks, where a vehicle acts maliciously, obstructing the forwarding of data packets to subsequent vehicles, thereby compromising the secure dissemination of content within the VANET. We present an intelligent cluster-based routing protocol to mitigate these challenges in VANET routing. The system operates through two pivotal phases: first, utilizing an artificial neural network (ANN) model to detect malicious nodes, and second, establishing clusters via enhanced clustering algorithms with appointed cluster heads (CH) for each cluster. Subsequently, an optimal path for data transmission is predicted, aiming to minimize packet transmission delays. Our approach integrates a modified ad hoc on-demand distance vector (AODV) protocol for on-demand route discovery and optimal path selection, enhancing request and reply (RREQ and RREP) protocols. Evaluation of routing performance involves the BHT dataset, leveraging the ANN classifier to compute accuracy, precision, recall, F1 score, and loss. The NS-2.33 simulator facilitates the assessment of end-to-end delay, network throughput, and hop count during the path prediction phase. Remarkably, our methodology achieves 98.97% accuracy in detecting black hole attacks through the ANN classification model, outperforming existing techniques across various network routing parameters.

Internet of Vehicles (IoV)-Based Task Scheduling Approach Using Fuzzy Logic Technique in Fog Computing Enables Vehicular Ad Hoc Network (VANET).

The intelligent transportation system (ITS) relies heavily on the vehicular ad hoc network (VANET) and the internet of vehicles (IoVs), which combine cloud and fog to improve task processing capabilities. As a cloud extension, the fog processes' infrastructure is close to VANET, fostering an environment favorable to smart cars with IT equipment and effective task management oversight. Vehicle processing power, bandwidth, time, and high-speed mobility are all limited in VANET. It is critical to satisfy the vehicles' requirements for minimal latency and fast reaction times while offloading duties to the fog layer. We proposed a fuzzy logic-based task scheduling system in VANET to minimize latency and improve the enhanced response time when offloading tasks in the IoV. The proposed method effectively transfers workloads to the fog computing layer while considering the constrained resources of car nodes. After choosing a suitable processing unit, the algorithm sends the job and its associated resources to the fog layer. The dataset is related to crisp values for fog computing for system utilization, latency, and task deadline time for over 5000 values. The task execution, latency, deadline of task, storage, CPU, and bandwidth utilizations are used for fuzzy set values. We proved the effectiveness of our proposed task scheduling framework via simulation tests, outperforming current algorithms in terms of task ratio by 13%, decreasing average turnaround time by 9%, minimizing makespan time by 15%, and effectively overcoming average latency time within the network parameters. The proposed technique shows better results and responses than previous techniques by scheduling the tasks toward fog layers with less response time and minimizing the overall time from task submission to completion.

Soluble and insoluble expression of recombinant human interleukin-2 protein using pET expression vector in Escherichia coli.

Interleukin-2 has emerged as a potent protein-based drug to treat various cancers, AIDS, and autoimmune diseases. Despite its immense requirement, the production procedures are inefficient to meet the demand. Therefore, efficient production procedures must be adopted to improve protein yield and decrease procedural loss. This study analyzed cytoplasmic and periplasmic IL-2 expression for increased protein yield and significant biological activity. The study is focused on cloning IL-2 into a pET-SUMO and pET-28a vector that expresses IL-2 in soluble form and inclusion bodies, respectively. Both constructs were expressed into different E. coli expression strains, but the periplasmic and cytoplasmic expression of IL-2 was highest in overnight culture in Rosetta 2 (DE3). Therefore, E. coli Rosetta 2 (DE3) was selected for large-scale production and purification. Purified IL-2 was characterized by SDS-PAGE and western blotting, while its biological activity was determined using MTT bioassay. The results depict that the periplasmic and cytoplasmic IL-2 achieved adequate purification, yielding 0.86 and 0.51 mg/mL, respectively, with significant cytotoxic activity of periplasmic and cytoplasmic IL-2. Periplasmic IL-2 has shown better yield and significant biological activity in vitro which describes its attainment of native protein structure and function.

Plant trait networks reveal adaptation strategies in the drylands of China.

BACKGROUND: Plants accomplish multiple functions by the interrelationships between functional traits. Clarifying the complex relationships between plant traits would enable us to better understand how plants employ different strategies to adapt to the environment. Although increasing attention is being paid to plant traits, few studies focused on the adaptation to aridity through the relationship among multiple traits. We established plant trait networks (PTNs) to explore the interdependence of sixteen plant traits across drylands. RESULTS: Our results revealed significant differences in PTNs among different plant life-forms and different levels of aridity. Trait relationships for woody plants were weaker, but were more modularized than for herbs. Woody plants were more connected in economic traits, whereas herbs were more connected in structural traits to reduce damage caused by drought. Furthermore, the correlations between traits were tighter with higher edge density in semi-arid than in arid regions, suggesting that resource sharing and trait coordination are more advantageous under low drought conditions. Importantly, our results demonstrated that stem phosphorus concentration (SPC) was a hub trait correlated with other traits across drylands. CONCLUSIONS: The results demonstrate that plants exhibited adaptations to the arid environment by adjusting trait modules through alternative strategies. PTNs provide a new insight into understanding the adaptation strategies of plants to drought stress based on the interdependence among plant functional traits.

Hierarchical Nanospheres with Polycrystalline Ir&Cu and Amorphous Cu2 O toward Energy-Efficient Nitrate Electrolysis to Ammonia.

Electrochemical reduction reaction of nitrate (NITRR) provides a sustainable route toward the green synthesis of ammonia. Nevertheless, it remains challenging to achieve high-performance electrocatalysts for NITRR especially at low overpotentials. In this work, hierarchical nanospheres consisting of polycrystalline Iridium&copper (Ir&Cu) and amorphous Cu2 O (Cux Iry Oz NS) have been fabricated. The optimal species Cu0.86 Ir0.14 Oz delivers excellent catalytic performance with a desirable NH3 yield rate (YR) up to 0.423 mmol h-1  cm-2 (or 4.8 mg h-1  mgcat -1 ) and a high NH3 Faradaic efficiency (FE) over 90% at a low overpotential of 0.69 V (or 0 VRHE ), where hydrogen evolution reaction (HER) is almost negligible. The electrolyzer toward NITRR and hydrazine oxidation (HzOR) is constructed for the first time with an electrode pair of Cu0.86 Ir0.14 Oz //Cu0.86 Ir0.14 Oz , yielding a high energy efficiency (EE) up to 87%. Density functional theory (DFT) calculations demonstrate that the dispersed Ir atom provides active site that not only promotes the NO3 - adsorption but also modulates the H adsorption/desorption to facilitate the proton supply for the hydrogenation of *N, hence boosting the NITRR. This work thus points to the importance of both morphological/structural and compositional engineering for achieving the highly efficient catalysts toward NITRR.

Solid Dispersion Incorporated into Dissolving Microneedles for Improved Antifungal Activity of Amphotericin B: In Vivo Study in a Fungal Keratitis Model.

Fungal keratitis (FK) is a fungal infection of the cornea, which is part of the eye and causes corneal ulcers and an increased risk of permanent blindness, which is often found in Candida albicans species. Amphotericin B (AMB), which is a group of polyenes as the first-line treatment of FK, is effective in annihilating C. albicans. However, AMB preparations such as eye drops and ointments have major drawbacks, for instance, requiring more frequent administrations, loss of the drug by the drainage process, and rapid elimination in the precornea, which result in low bioavailability of the drug. An ocular dissolving microneedle containing the solid dispersion amphotericin B (DMN-SD-AMB) had been developed using a mixture of poly(vinyl alcohol) (PVA) and poly(vinylpyrrolidone) (PVP) polymers, while the solid dispersion AMB (SD-AMB) was contained in the needle as a drug. This study aims to determine the most optimal and safest DMN-SD-AMB formula for the treatment of FK in the eye as well as a solution to overcome the low bioavailability of AMB eye drops and ointment preparations. SD-AMB had been successfully developed, which was characterized by increased antifungal activity and drug release in vitro compared to other treatments. Furthermore, DMN-SD-AMB studies had also been successfully performed with the best formulation, which exhibited the best ex vivo corneal permeation profile and antifungal activity as well as being safe from eye irritation. In addition, an in vivo antifungal activity using a rabbit infection model shows that the number of fungal colonies was 0.98 ± 0.11 log10 CFU/mL (F3), 5.76 ± 0.32 log10 CFU/mL (AMB eye drops), 4.01 ± 0.28 log10 CFU/mL (AMB ointments), and 9.09 ± 0.65 log10 CFU/mL (control), which differed significantly (p < 0.05). All of these results evidence that DMN-SD-AMB is a new approach to developing intraocular preparations for the treatment of FK.

Impacts of nutritive and bioactive compounds on cancer development and therapy.

For persons who survive with progressive cancer, nutritional therapy and exercise may be significant factors to improve the health condition and life quality of cancer patients. Nutritional therapy and medications are essential to managing progressive cancer. Cancer survivors, as well as cancer patients, are mostly extremely encouraged to search for knowledge about the selection of diet, exercise, and dietary supplements to recover as well as maintain their treatment consequences, living quality, and survival of patients. A healthy diet plays an important role in cancer treatment. Different articles are studied to collect information and knowledge about the use of nutrients in cancer treatment as well as cancer prevention. The report deliberates nutrition and exercise strategies during the range of cancer care, emphasizing significant concerns during treatment of cancer and for patients of advanced cancer, but concentrating mostly on the requirements of the population of persons who are healthy or who have constant disease following their repossession from management. It also deliberates choice nutrition and exercise problems such as dietary supplements, food care, food selections, and weight; problems interrelated to designated cancer sites, and common questions about diet, and cancer survival. Decrease the side effects of medicines both during and after treatment.

Modelling count, bounded and skewed continuous outcomes in physical activity research: beyond linear regression models.

BACKGROUND: Inference using standard linear regression models (LMs) relies on assumptions that are rarely satisfied in practice. Substantial departures, if not addressed, have serious impacts on any inference and conclusions; potentially rendering them invalid and misleading. Count, bounded and skewed outcomes, common in physical activity research, can substantially violate LM assumptions. A common approach to handle these is to transform the outcome and apply a LM. However, a transformation may not suffice. METHODS: In this paper, we introduce the generalized linear model (GLM), a generalization of the LM, as an approach for the appropriate modelling of count and non-normally distributed (i.e., bounded and skewed) outcomes. Using data from a study of physical activity among older adults, we demonstrate appropriate methods to analyse count, bounded and skewed outcomes. RESULTS: We show how fitting an LM when inappropriate, especially for the type of outcomes commonly encountered in physical activity research, substantially impacts the analysis, inference, and conclusions compared to a GLM. CONCLUSIONS: GLMs which more appropriately model non-normally distributed response variables should be considered as more suitable approaches for managing count, bounded and skewed outcomes rather than simply relying on transformations. We recommend that physical activity researchers add the GLM to their statistical toolboxes and become aware of situations when GLMs are a better method than traditional approaches for modeling count, bounded and skewed outcomes.

Associations of home and neighborhood environments with children's physical activity in the U.S.-based Neighborhood Impact on Kids (NIK) longitudinal cohort study.

INTRODUCTION: Physical activity is important for children's health and well-being. Supportiveness for physical activity of home and neighborhood environments may affect children's PA, but most studies are cross-sectional. We examined environmental predictors of change in children's physical activity over two years. METHODS: Data were from the longitudinal, observational cohort study, 'Neighborhood Impact on Kids'. Participants were children (initially aged 6-12 years) and their parent/caregiver (n = 727 dyads) living in neighborhoods throughout San Diego County, California and King County (Seattle area), Washington, USA. Children's moderate-to-vigorous physical activity (MVPA) was measured using accelerometers at T1 (Time 1 or baseline, 2007-2009) and T2, the two-year follow-up. At T1, parents survey-reported on physical activity (PA) equipment at home and demographics. Neighborhood environment was measured using spatial data in Geographic Information Systems (intersection density; park availability) and in-person audits (informal play space near home; park-based PA facilities; land use; support for walking/cycling). Generalized additive mixed models estimated total effects, then direct effects, of environmental attributes on MVPA at T1. Two-way moderating effects of child's sex and age were examined at T1. To examine associations of environmental exposures with changes in MVPA, we estimated interaction effects of environmental attributes on the association between time and MVPA. RESULTS: On average, children accumulated 146 min/day (standard deviation or SD = 53) of MVPA at T1, and 113 (SD = 58) min/day at T2. There were no significant total or direct effects of environmental attributes on MVPA at T1, and no significant two-way interaction effects of child's age and sex for T1 MVPA. Having informal play spaces proximal to home with more amenities was associated with less MVPA decline from T1 to T2. Higher residential density, higher land use mix, and higher number of PA facilities in nearby parks were unexpectedly associated with greater MVPA decline. CONCLUSION: Higher quality informal play spaces close to home may help offset declines in MVPA during middle childhood, as they may promote unstructured active play with opportunities for parental or neighbor surveillance. Unexpectedly, environmental factors consistent with higher walkability were associated with greater declines in children's MVPA. As physical activity differs across the lifespan, so may environmental factors that facilitate it.

Enhanced soluble expression of active recombinant human interleukin-29 using champion pET SUMO system.

Current research focuses on the soluble and high-level expression of biologically active recombinant human IL-29 protein in Escherichia coli. The codon-optimized IL-29 gene was cloned into the Champion™ pET SUMO expression system downstream of the SUMO tag under the influence of the T7 lac promoter. The expression of SUMO-fused IL-29 protein was compared in E. coli Rosetta 2(DE3), Rosetta 2(DE3) pLysS, and Rosetta-gami 2(DE3). The release of the SUMO fusion partner resulted in approximately 98 mg of native rhIL-29 protein with a purity of 99% from 1 l of fermentation culture. Purified rhIL-29 was found to be biologically active, as evaluated by its anti-proliferation assay. It was found that Champion™ pET SUMO expression system can be used to obtained high yield of biologically active soluble recombinant human protein compared to other expression vector.

Honey and Nigella sativa against COVID-19 in Pakistan (HNS-COVID-PK): A multicenter placebo-controlled randomized clinical trial.

Until now, no specific and effective treatment exists for coronavirus disease 2019 (COVID-19). Since honey and Nigella sativa (HNS) have established antiviral, antibacterial, antiinflammatory, antioxidant, and immunomodulatory properties, we tested their efficacy for this disease in a multicenter, placebo-controlled, and randomized clinical trial at four medical care facilities in Pakistan. RT-PCR confirmed COVID-19 adults showing moderate or severe disease were enrolled in the trial. Patients were randomly assigned in a 1:1 ratio to receive either honey (1 g kg-1 day-1 ) and Nigella sativa seeds (80 mg kg-1 day-1 ) or a placebo for up to 13 days along with standard care. The outcomes included symptoms' alleviation, viral clearance, and 30-day mortality in the intention-to-treat population. Three hundred and thirteen patients, 210 with moderate and 103 with severe disease, underwent randomization from April 30 to July 29, 2020. Among the moderate cases, 107 were assigned to HNS, whereas 103 were assigned to the placebo group. Among the severe cases, 50 were given HNS, and 53 were given the placebo. HNS resulted in ~50% reduction in time taken to alleviate symptoms as compared to placebo (moderate cases: 4 vs. 7 days, Hazard Ratio [HR]: 6.11; 95% Confidence Interval [CI]: 4.23-8.84, p < 0.0001 and for severe cases: 6 vs. 13 days, HR: 4.04; 95% CI: 2.46-6.64; p < 0.0001). HNS also cleared the virus earlier than placebo in both moderate cases (6 vs. 10 days, HR: 5.53; 95% CI: 3.76-8.14, p < 0.0001) and severe cases (8.5 vs. 12 days, HR: 4.32; 95% CI: 2.62-7.13, p < 0.0001). HNS further led to a better clinical score on day 6 with normal activity resumption in 63.6% vs. 10.9% among moderate cases (OR: 0.07; 95% CI: 0.03-0.13, p < 0.0001) and hospital discharge in 50% versus 2.8% in severe cases (OR: 0.03; 95% CI: 0.01-0.09, p < 0.0001). In severe cases, the mortality rate was less than 1/4th in the HNS group than in placebo (4% vs. 18.87%, OR: 0.18; 95% CI: 0.02-0.92, p = 0.029). No HNS-related adverse effects were observed. HNS, compared with placebo, significantly improved symptoms, expedited viral load clearance, and reduced mortality in COVID-19 patients. This trial was registered on April 15, 2020 with ClinicalTrials.gov Identifier: NCT04347382.

Response Surface Methodology-Based Optimized Ultrasonic-Assisted Extraction and Characterization of Selected High-Value Components from Gemlik Olive Fruit.

This article presents an optimized ultrasound-assisted ethanolic extraction (UAEE) and characterization of selected high-value components from Gemlik olive fruit (GOF) harvested from Potohar region of Pakistan. Response surface methodology (RSM), involving central composite design (CCD), was applied to optimize the extraction variables i. e., temperature (25-65 °C), extraction time (15-45 min) and aqueous ethanol concentration (60-90 %) for optimal recovery of bioactives extract, total phenolic contents (TPC) and DPPH free radical scavengers. Under the optimized set of conditions such as 43 °C temperature, 32 min extraction time and 80 % aqueous ethanol, the best extract yield (218.82 mg/g), TPC (19.87 mg GAE/g) and DPPH scavenging activity (63.04 %) were recorded. A quadratic polynomial model was found to be reasonably fitted to the observed results for extract yield (p<0.0001 and R2 =0.9941), TPC (p<0.0001 and R2 =0.9891), and DPPH radical scavenging activity (p<0.0001 and R2 =0.9692). Potent phenolic compounds were identified by GC/MS in GOF extract and considerable amount of essential fatty acids were also detected. The current findings support the use of UAEE as an effective green route for optimized recovery of high-value components from GOF and hence its applications can be extended to functional food and nutra-pharmaceutical developments.

Chemical Characterization, Antioxidant, Antimicrobial, Cytotoxicity and in Silico Studies of Hexane Extract and Essential Oils from Citrus limon Leaves.

The present study investigates the chemical composition, antioxidant and antimicrobial bioactivities of essential oil and hexane extract from Citrus limon leaves. The isolation of essential oil was carried out using the Clevenger apparatus. The percentage yield of essential oil and hexane extract from Citrus limon leaves was 0.59 and 0.50 %, respectively. 2,2-Diphenyl-1-picrylhydrazyl (DPPH) scavenging assay highlighted that Citrus limon leaves essential oil (CLEO) and hexane extract exhibited the significant antioxidant potential of 69.64 and 67.55 %, respectively, compared to the BHT standard. Similarly, a significant inhibition in linoleic acid peroxidation was recorded in both CLEO (81.93 %) and hexane extract (50.34 %). Characterization of chemical constituents in CLEO and extract was executed using GC/MS, where Limonene was detected as a major compound in CLEO (60.52 %) and hexane extract (73.62 %). The haemolytic activity ranged from 2.46 to 5.75 % revealing negligible cytotoxicity of CLEO and hexane extract. In silico studies agree with the in vitro antimicrobial studies, where vinimalol, taraxasterol, and moretenol present in CLEO showed strong interactions/inhibition against dihydroorotase and DNA gyrase from E. coli, and the tyrosyl-tRNA synthetase and DNA gyrase from S. aureus. Based on the current data, it may be concluded that both CLEO and hexane extract possessed significant bioactivities, such as antimicrobial and antioxidant activity, with minimal cytotoxicity.

FedBranched: Leveraging Federated Learning for Anomaly-Aware Load Forecasting in Energy Networks.

Increased demand for fast edge computation and privacy concerns have shifted researchers' focus towards a type of distributed learning known as federated learning (FL). Recently, much research has been carried out on FL; however, a major challenge is the need to tackle the high diversity in different clients. Our research shows that using highly diverse data sets in FL can lead to low accuracy of some local models, which can be categorised as anomalous behaviour. In this paper, we present FedBranched, a clustering-based framework that uses probabilistic methods to create branches of clients and assigns their respective global models. Branching is performed using hidden Markov model clustering (HMM), and a round of branching depends on the diversity of the data. Clustering is performed on Euclidean distances of mean absolute percentage errors (MAPE) obtained from each client at the end of pre-defined communication rounds. The proposed framework was implemented on substation-level energy data with nine clients for short-term load forecasting using an artificial neural network (ANN). FedBranched took two clustering rounds and resulted in two different branches having individual global models. The results show a substantial increase in the average MAPE of all clients; the biggest improvement of 11.36% was observed in one client.

Improved Photoluminescence Performance of Eu3+-Doped Y2(MoO4)3 Red-Emitting Phosphor via Orderly Arrangement of the Crystal Lattice.

In this study, we developed a technology for broadening the 465 nm and 535 nm excitation peaks of Eu3+:Y2(MoO4)3 via crystal lattice orderly arrangement. This was achieved by powder particle aggregation and diffusion at a high temperature to form a ceramic structure. The powdered Eu3+:Y2(MoO4)3 was synthesized using the combination of a sol-gel process and the high-temperature solid-state reaction method, and it then became ceramic via a sintering process. Compared with the Eu3+:Y2(MoO4)3 powder, the full width at half maximum (FWHM) of the excitation peak of the ceramic was broadened by two- to three-fold. In addition, the absorption efficiency of the ceramic was increased from 15% to 70%, while the internal quantum efficiency reduced slightly from 95% to 90%, and the external quantum efficiency was enhanced from 20% to 61%. More interestingly, the Eu3+:Y2(MoO4)3 ceramic material showed little thermal quenching below a temperature of 473 K, making it useful for high-lumen output operating at a high temperature.