Search Results (21)

Pulmonary drug delivery is governed by three main categories of forces: interparticle forces in the powder formulation, the dispersion forces during inhalation by the device, and deposition forces in the lungs. The interaction between fine inhalable powder particles of the active ingredient is governed by various types of forces, such as capillary forces, electrostatic forces, and van der Waals forces. The different types of inter-particle interactions influence the balance between powder dispersibility and agglomerate stability. The high level of cohesion forces arising from high surface energy of very fine powder hinders powder flowability, leading to issues of agglomeration. Therefore, there is a critical need for advanced manufacturing techniques to overcome the challenges of handling and manufacture of fine cohesive particles, particularly high-dose powders for inhalation. This review will focus on the challenges facing the formulation process of very fine inhalable powder, the various types of existing particle engineering techniques for high-dose powder inhalers, and the characterization techniques employed to analyse the powder characteristics required to meet the acceptance criteria of inhalable preparations. Full article

Drug discovery is the process by which new drug candidates are discovered and drug development takes place. To enhance the efficiency, accuracy, and speed of the drug discovery process, machine learning (ML) could play a transformative role. For this research study, antidiabetic natural compounds from C. intybus, which is commonly known as chicory, were selected, as they have promising antidiabetic properties that can complement conventional diabetes treatments. A bioactive natural compound dataset was retrieved on the chicory plant using Indian Medicinal Plants, Phytochemistry, and Therapeutics (IMPPAT) public source information. This collected dataset was analyzed for its absorption, distribution, metabolism, and excretion (ADME) properties using the SwissADME online tool. Principal component analysis (PCA) and correlation analysis were performed using trial-version XLSTAT software 2014.5.03 and Python. The obtained dataset from SwissADME was subjected to cleaning, after that, it was used to develop machine learning models, such as support vacuum (SVM) ML, random forest (RF), Naive Bayes (NB), and decision tree (DT). The Lipinski rule of violation was chosen as the target variable. To improve the vitality of the created ADME dataset, PCA, a biplot graph, and correlation analysis were carried out. A large dataset of naturally occurring antidiabetic compounds was used to predict the drug-likeness of ML models that were effectively deployed on heterogeneous ADME datasets. Among all these ML models, DT performed better than the rest of the models. Full article

The intensified concerns related to agrochemicals’ ecological and health risks have encouraged the exploration of microbial agents as eco-friendly alternatives. Some members of Bacillus spp. are potential plant-growth-promoting agents and benefit numerous crop plants globally. This study aimed to explore the beneficial effects of two Bacillus strains (B. subtilis strain IS1 and B. amyloliquificiens strain IS6) capable of alleviating the growth of tomato plants against salinity stress and Fusarium wilt disease. These strains were able to significantly promote the growth of tomato plants and biomass accumulation in pot trials in the absence of any stress. Under salinity stress conditions (150 mM NaCl), B. subtilis strain IS1 demonstrated superior performance and significantly increased shoot length (45.74%), root length (101.39%), fresh biomass (62.17%), and dry biomass (49.69%) contents compared to control plants. Similarly, B. subtilis strain IS1 (63.7%) and B. amyloliquificiens strain IS6 (32.1%) effectively suppressed Fusarium wilt disease and significantly increased plant growth indices compared to the pathogen control. Furthermore, these strains increased the production of chlorophyll, carotenoid, and total phenolic contents. They significantly affected the activities of enzymes involved in antioxidant machinery and the phenylpropanoid pathway. Hence, this study effectively demonstrates that these Bacillus strains can effectively alleviate the growth of tomato plants under multiple stress conditions and can be used to develop bio-based formulations for use in the fields. Full article

To enhance the software implementation process, developers frequently leverage preexisting code snippets by exploring an extensive codebase. Existing code search tools often rely on keyword- or syntactic-based methods and struggle to fully grasp the semantics and intent behind code snippets. In this paper, we propose a novel hybrid C2B model that combines CodeT5 and bidirectional long short-term memory (Bi-LSTM) for source code search and recommendation. Our proposed C2B hybrid model leverages CodeT5’s domain-specific pretraining and Bi-LSTM’s contextual understanding to improve code representation and capture sequential dependencies. As a proof-of-concept application, we implemented the proposed C2B hybrid model as a deep neural code search tool and empirically evaluated the model on the large-scale dataset of CodeSearchNet. The experimental findings showcase that our methodology proficiently retrieves pertinent code snippets and surpasses the performance of prior state-of-the-art techniques. Full article

Herbal products are preferable to synthetic medicines, and the use of traditional medicines is increasing day-by-day. The current study was designed to evaluate the potentials of bioactive compounds from Citrullus colocynthis by performing FTIR, HPLC, and GC-MS analyses, which explore the good concentration of the secondary metabolites, such as gallic acid (74.854 ppm), vanillic acid (122.616 ppm), and ferulic acid (101.045 ppm) with considerable bioactivities. Antimicrobial protein was estimated by performing SDS-PAGE, ranging from 15 to 70 kDa in all protein fractions. The current study also checked the cytotoxicity of the bioactive compounds in the active fraction of C. colocynthis, and to perform this activity, the groups of rats were arranged with 16 rats randomly divided into four groups (three experimental and one control) by administering various dosage of methanolic fractions in dose-dependent manner. Histopathology was conducted on the livers of the rats after 15 days of sacrifice under deep anesthesia. In liver cell slides examined at the maximum dose of 600 mg/kg, minimal morphological changes, such as slight ballooning, nuclear variation, vacuolar degeneration, and hydropic degeneration, were observed. Furthermore, the in silico analysis identified bioactive compounds as potential drug candidates. Full article

The development of robotic applications necessitates the availability of useful, adaptable, and accessible programming frameworks. Robotic, IoT, and sensor-based systems open up new possibilities for the development of innovative applications, taking advantage of existing and new technologies. Despite much progress, the development of these applications remains a complex, time-consuming, and demanding activity. Development of these applications requires wide utilization of software components. In this paper, we propose a platform that efficiently searches and recommends code components for reuse. To locate and rank the source code snippets, our approach uses a machine learning approach to train the schema. Our platform uses trained schema to rank code snippets in the top k results. This platform facilitates the process of reuse by recommending suitable components for a given query. The platform provides a user-friendly interface where developers can enter queries (specifications) for code search. The evaluation shows that our platform effectively ranks the source code snippets and outperforms existing baselines. A survey is also conducted to affirm the viability of the proposed methodology. Full article

Medicinal plants have played an essential role in the treatment of various diseases. Thymus vulgaris, a medicinal plant, has been extensively used for biological and pharmaceutical potential. The current study was performed to check the biopotential of active biological compounds. The GC-MS analysis identified 31 compounds in methanolic crude extract, among which thymol, carvacrol, p-cymene, and eugenol are the main phytoconstituents present in T. vulgaris. The HPLC analysis quantified that flavonoids and phenolic acids are present in a good concentration in the active fraction of ethyl acetate and n-butanol. FTIR confirmed the presence of functional groups such as phenols, a carboxylic group, hydroxy group, alcohols, and a benzene ring. Among both fractions, ethyl acetate showed high antioxidant activity in the DPPH (84.1 0.88) and ABTS (87.1 0.89) assays, respectively. The anti-inflammatory activity of the fractions was done in vitro and in vivo by using a carrageenan-induced paw edema assay, while the hexane-based extract showed high anti-inflammatory activity (57.1 0.54) in a dose-response manner. Furthermore, the lead compound responsible for inhibition in the denaturation of proteins is thymol, which exhibits the highest binding affinity with COX1 (−6.4 KJ/mol) and COX2 (−6.3 KJ/mol) inflammatory proteins. The hepatotoxicity analysis showed that plant-based phytoconstituents are safe to use and have no toxicity, with no necrosis, fibrosis, and vacuolar degeneration, even at a high concentration of 800 mg/kg body weight. Furthermore, the in silico analysis of HPLC phytochemical compounds against gastric cancer genes showed that chlorogenic acid exhibited anticancer activity and showed good drug-designing characteristics. Thrombolysis and hemolysis are the major concerns of individuals suffering from gastric cancer. However, the T. vulgaris fractions showed thrombolysis from 17.6 to 5.4%; similarly, hemolysis ranged from 9.73 to 7.1% at a concentration of 12 mg/mL. The phytoconstituents present in T. vulgaris have the potential for multiple pharmacological applications. This should be further investigated to isolate bioactive compounds that can be used for the treatment of different ailments. Full article

Fall armyworm, Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), is a polyphagous insect pest of many important crops. To evaluate the influence of host plants on the biology and survival of the Pakistani population of S. frugiperda, we examined life table parameters of S. frugiperda raised on maize, sorghum, wheat, and rice. The development rate was significantly higher on the maize crop than on the other three host plants. Different larval diets affected development time and fecundity. S. frugiperda attained the fastest larval development (16 days) on maize and the slowest development (32.74 days) on rice. Adult females from maize-fed larvae laid 1088 eggs/female, those from sorghum-fed larvae laid 591.6 eggs/female, those from wheat-fed larvae laid 435.6 eggs/female, and those from rice-fed larvae laid 49.6 eggs/female. Age stage-specific parameters also indicated the higher fecundity, higher life expectancy, and higher survival of S. frugiperda on maize plants than on the other three hosts. Larval diets had a significant varying effect on the finite and intrinsic increase rates, reflecting that maize was the most suitable diet. The findings of the present study are useful for predicting population dynamics especially in areas cultivating Poaceae crops, except maize, to develop sustainable integrated pest management strategies for this pest. Full article

In this article, we introduce bipolar neutrosophic (BN) aggregation operators (AOs) as a revolutionary notion in aggregation operators (AOs) by applying Einstein operations to bipolar neutrosophic aggregation operators (AOs), with its application related to a real-life problem. The neutrosophic set is able to drawout the incomplete, inconsistent and indeterminate information pretty efficiently. Initially, we present essential definitions along with operations correlated to the neutrosophic set (NS) and its generalization, the bipolar neutrosophic set (BNS). The Einstein aggregation operators are our primary targets, such asthe BN Einstein weighted average (BNEWA), BN Einstein ordered weighted average (BNEOWA), BN Einstein hybrid average (BNEHA), BN Einstein weighted geometric (BNEWG), BN Einstein ordered weighted geometric (BNEOWG) and BN Einstein hybrid geometric (BNEHG), as well as their required properties. The most important benefit of using the suggested approaches is that they provide decision-makers with complete sight of the issue. These techniques, when compared to other methods, provide complete, progressive and precise findings. Lastly, by means of diverse types of newly introduced aggregation operators and a numerical illustration by an example, we suggest an innovative method to be used for multi-criteria community decision-making (DM). This illustrates the utility and applicability of this new strategy when facing real-world problems. Full article

Fall armyworm [Spodoptera frugiperda (J. E. Smith, 1797)] was first reported in the Americas, then spread to all the continents of the world. Chemical insecticides are frequently employed in managing fall armyworms. These insecticides have various modes of actions and target sites to kill the insects. Chlorantraniliprole is a selective insecticide with a novel mode of action and is used against Lepidopteran, Coleopteran, Isopteran, and Dipteran pests. This study determined chlorantraniliprole’s lethal, sub-lethal, and trans-generational effects on two consecutive generations (F₀, F₁, and F₂) of the fall armyworm. Bioassays revealed that chlorantraniliprole exhibited higher toxicity against fall armyworms with a LC₅₀ of 2.781 mg/L after 48 h of exposure. Significant differences were noted in the biological parameters of fall armyworms in all generations. Sub-lethal concentrations of chlorantraniliprole showed prolonged larval and adult durations. The parameters related to the fitness cost in F₀ and F₁ generations showed non-significant differences. In contrast, the F₂ generation showed lower fecundity at lethal (71 eggs/female) and sub-lethal (94 eggs/female) doses of chlorantraniliprole compared to the control (127.5–129.3 eggs/female). Age-stage specific survival rate (S_xj), life expectancy (E_xj) and reproductive rate (V_xj) significantly differed among insecticide-treated groups in all generations compared to the control. A comparison of treated and untreated insects over generations indicated substantial differences in demographic parameters such as net reproduction rate (R₀), intrinsic rate of increase (r), and mean generation time (T). Several biological and demographic parameters were shown to be negatively impacted by chlorantraniliprole. We conclude that chlorantraniliprole may be utilized to manage fall armyworms with lesser risks. Full article

Sucking pests of cotton (Gossypium hirsutum L.), such as thrips, or Thrips tabaci Lindeman, and jassid, or Amrasca biguttula Ishida, are among the most threatening insect pests to young cotton plants in Pakistan. New chemical insecticides have been trialed to control their damage in commercial fields. Formulations that show good suppression of these pest’s populations, while sparing bio-controlling agents, are always preferred for obtaining better crop yield. Six different commercially available insecticides, namely Fountain^® (fipronil and imidacloprid), Movento Energy^® (spirotetramat and imidacloprid), Oshin^® (dinotefuran), Concept Plus^® (pyriproxyfen, fenpyroximate, and acephate), Maximal^® (nitenpyram), and Radiant^® (spinetoram) were evaluated in the present study to shortlist the best available insecticide against targeted pests. Harmful impacts of selected insecticides were also evaluated against naturally occurring predators, such as spiders and green lacewings (Chrysoperla carnea). Radiant^® (spinetoram) and Movento Energy^®, respectively, were best at controlling thrips (with 61% and 56% mortality, respectively) and jassid (62% and 57% mortality, respectively) populations during 2018 and 2019. Radiant^® proved itself as the best option and showed minimal harmful effects on both major arthropod predators of cotton fields i.e., spiders (with 8–9% mortality) and green lacewings (with 12–16% mortality). Movento Energy^® also showed comparatively less harmful effects (with 15–18% mortality) towards natural predatory fauna of cotton crops, as compared to other selective insecticides used in the study. The findings of current study suggest that the judicious use of target-oriented insecticides can be an efficient and predator-friendly management module in cotton fields. However, the impact of these chemicals is also depended on their timely application, keeping in consideration the ETL of pests and the population of beneficial arthropods. Full article

The physiological and biochemical characterization of the “Halloween” genes has fundamental importance in the biosynthesis pathway of ecdysteroids. These genes were found to catalyze the final phases of ecdysteroid biosynthesis from dietary cholesterol to the molting hormone 20-hydroxyecdysone. We report the characterization of the Cs-Phm in a major insect pest in agriculture, the rice striped stem borer, Chilo suppressalis (C. suppressalis). A full-length transcript of Cs-Phm was amplified with an open reading frame (ORF) of 478 amino acids through 5′ and 3′ RACE. Cs-Phm shows five insect-conserved P450 motifs: Helix-C, Helix-I, Helix-K, PERF, and heme-binding motifs. Phylogenetic analysis clearly shows high similarity to Lepidoptera and evolutionary conservation in insects. The relative spatial and temporal transcript profile shows that Cs-Phm is highly expressed in the prothoracic glands and appears throughout the larval development, but with low expression at the start of the larval instar. It seems to peak in 3–4 days and decreases again before the larvae molt. Double-stranded RNA (dsRNA) injection of Cs-Phm at the larval stage efficiently knocked down the target gene and decreased its expression level. The dsRNA-treated group showed significantly decreased ecdysteroid titers, which leads to delayed larval development and higher larval mortality. Negative effects of larval development were rescued by treating 20E in the dsRNA-treated group. Thus, in conclusion, our results suggest that Cs-Phm is functionally conserved in C. suppressalis and encodes functional CYP that contributes to the biogenesis of 20E. Full article

The control of Spodoptera frugiperda, the key invasive pest of maize, is a serious concern due to its biology and the current global restriction on applying synthetic pesticides. Entomopathogenic fungi are considered to be a potential biological control strategy. The pathogenicity of 12 isolates of Beauveria bassiana in the immature stages and feeding efficacy of S. frugiperda were evaluated. The B. bassiana isolates QB-3.45, QB-3.46 and QB-3.428 caused the highest egg mortality rates of 87.3, 82.7 and 79.3%, respectively, when applied at a concentration of 1 × 10⁸ conidia/mL and measured at 7 days post-treatment. Neonate mortality rates of 45.6 to 53.6% were observed with the same isolates. The B. bassiana isolates caused significant cumulative mortality rates ranging from 71.3 to 93.3% at 14 days post-treatment and reduced larval feeding efficacy from 69.4 to 77.8% at 48 h post-treatment. This study supports using the effective B. bassiana isolates as a biological control agent against S. frugiperda. The significant mortality of the eggs and neonatal larvae and the reduction in the feeding efficacy of the second instar larvae of the S. frugiperda that were treated with isolates of B. bassiana supports the application of entomopathogenic fungi as a biocontrol agent for the effective control of the S. frugiperda population. Full article

Fall armyworm, Spodoptera frugiperda (JE Smith) (Lepidoptera: Noctuidae), is a destructive pest of a wide array of agricultural and horticultural crops worldwide. This in vitro research assessed the combined effect of methanolic extracts of indigenous flora of Soone Valley (Khushab, Pakistan) and nine commonly used synthetic insecticides against 3rd instar larvae of S. frugiperda using the leaf-dip bioassay method. Toxicity bioassays with twelve plant extracts revealed that the extracts of Withania somnifera (L.) Dunal, Sophora mollis (Royle) Baker and Rhazya stricta Decne. were the most effective, exhibiting minimum LC₅₀ and LT₅₀ values. Bioassays with synthetic insecticides revealed a significantly higher mortality of S. frugiperda larvae by emamectin benzoate (45%), chlorpyrifos (40%) and chlorantraniliprole (38%). Further bioassays with 10 binary combinations of these most effective botanical and synthetic insecticides showed that seven pesticidal combinations exhibited synergistic toxicity, and three combinations comprising emamectin benzoate exhibited an additive effect on the mortality of S. frugiperda larvae. GC–MS analyses of methanolic extracts of W. somnifera, S. mollis and R. stricta revealed 1,2,4-trimethyl-benzene and 3,5-dimethyl-octane, 1-ethyl-2-methyl-benzene, and 1-monolinoleoylglycerol trimethylsilyl ether, decane, and lupeol as major bioconstituents, respectively. Our results demonstrated that combining botanicals with synthetic insecticides can synergize their toxicity against S. frugiperda larvae, suggesting their potential incorporation into future IPM programs against S. frugiperda and other lepidopterous pests. Full article

In this paper, we propose an agent-based approach for the evaluation of Multiple Unmanned Autonomous Vehicle (MUAV) wildfire monitoring systems for remote and hard-to-reach areas. Emerging environmental factors are causing a higher number of wildfires and keeping these fires in check is becoming a global challenge. MUAV deployment for the monitoring and surveillance of potential fires has already been established. However, most of the scholarly work is still focused on MUAV operations details. In wildfire surveillance and monitoring, evaluations of the system-level performance in terms of the analysis of the effects of individual behavior on system surveillance has yet to be established. Especially in an MUAV system, the individual and cooperative behaviors of the team affect the overall performance of the system. Such systems are dynamic and stochastic because of an ever-changing environment. Quantifying the emergent system behavior and general performance measures of such a system by analytical methods is challenging. In our work, we present an agent-based model for MUAV surveillance missions. This paper focuses on the overall system performance of cooperative UAVs performing forest fire surveillance. The principal theme is to present the effects of three behaviors on overall performance: (1) the area allocation and (2) dynamic coverage, and (3) the effects of forest density on team allocation. For area allocation, three behaviors are simulated: (1) randomized, (2) two-layer barrier sweep coverage, and (3) full sweep coverage. For dynamic coverage, the effects of communication and resource unavailability during the mission are studied by analyzing the agent’s downtime spent on refueling. Last, an extensive simulation is carried out on wildfire models with varying forest density. It is found that cooperative complete sweep coverage strategies perform better than the rest and the performance of the team is greatly affected by the forest density. Full article