Influence of Melissa officinalis essential oil and its formulation on Typhlodromips swirskii and Neoseiulus barkeri (Acari: Phytoseiidae)

The toxicity of Melissa officinalis L. essential oil and its formulation (Melissacide) were evaluated against eggs and females of two predatory phytoseiid mites, Typhlodromips swirskii (Athias Henriot) and Neoseiulus barkeri (Hughes), using direct spray. Results indicate that both tested materials were potent on predatory females than egg stage. Typhlodromips swirskii was proved to be more sensitive to the oil and formulation than N. barkeri. Females mortality were (62-100%) in T. swirskii, and (46-69%) in N. barkeri, when both predatory mites were sprayed with LC50 and LC90 of the oil and Melissacide reported on Tetranychus urticae Koch. Females of both predators were suffered from reduction in food consumption when sprayed with two sublethal concentrations of Melissacide, while insignificant differences reported in daily number of eggs deposited by females of T. swirskii, when sprayed with its LC25 value of Melissacide and control

Spoken language identification based on the enhanced self-adjusting extreme learning machine approach

Spoken Language Identification (LID) is the process of determining and classifying natural language from a given content and dataset. Typically, data must be processed to extract useful features to perform LID. The extracting features for LID, based on literature, is a mature process where the standard features for LID have already been developed using Mel-Frequency Cepstral Coefficients (MFCC), Shifted Delta Cepstral (SDC), the Gaussian Mixture Model (GMM) and ending with the i-vector based framework. However, the process of learning based on extract features remains to be improved (i.e. optimised) to capture all embedded knowledge on the extracted features. The Extreme Learning Machine (ELM) is an effective learning model used to perform classification and regression analysis and is extremely useful to train a single hidden layer neural network. Nevertheless, the learning process of this model is not entirely effective (i.e. optimised) due to the random selection of weights within the input hidden layer. In this study, the ELM is selected as a learning model for LID based on standard feature extraction. One of the optimisation approaches of ELM, the Self-Adjusting Extreme Learning Machine (SA-ELM) is selected as the benchmark and improved by altering the selection phase of the optimisation process. The selection process is performed incorporating both the Split-Ratio and K-Tournament methods, the improved SA-ELM is named Enhanced Self-Adjusting Extreme Learning Machine (ESA-ELM). The results are generated based on LID with the datasets created from eight different languages. The results of the study showed excellent superiority relating to the performance of the Enhanced Self-Adjusting Extreme Learning Machine LID (ESA-ELM LID) compared with the SA-ELM LID, with ESA-ELM LID achieving an accuracy of 96.25%, as compared to the accuracy of SA-ELM LID of only 95.00%

Modified technique for sacrospinous-sacrotuberous ligament complex colpopexy in apical prolapse: preliminary results of a pilot randomized study

Background: Apical prolapse is frequently encountered following vaginal hysterectomy either or as a primary finding in patients with pelvic organ prolapse. This pilot comparative study introduces a modified sacrospinous sacrotuberous ligament fixation with biologic mesh augmentation which necessitates no special kits to be performed.Methods: This study was conducted at Department of Obstetrics and gynecology, Ain Shams University, Cairo, Egypt, and Department of Women Health of Bethanien Hospital, Iserlöhn, Germany from March 2018 to May 2020. 40 women with either utero-vaginal or vaginal vault prolapse were randomized to either; group (A): 20 women scheduled for modified sacrospinous-sacrotuberous fixation procedure, or group (B): 20 women scheduled for conventional sacrospinous-sacrotuberous fixation procedure.Results: Improvement of the Pelvic organ prolapse quantification system (POP-Q) stage from the base line pre-operative stage was 1 stage higher in the modified SS/ST-F group compared to the conventional SSF group (3 stage improvement from baseline in SS/ST-F group versus 2 stage improvement only in conventional SSF group).Conclusions: This pilot study provides a modified sacrospinous sacrotuberous ligament colpopexy technique which is easier to be performed and mastered, does not need the use of special devices, provides better improvement of grade of prolapse and less complications compared to the conventional technique.

Further Studies on Spectrophotometric Determination of Mg(II) with Eriochrome Black T

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Humanizing GenAI at work: bridging the gap between technological innovation and employee engagement

Purpose: This paper seeks to explore the influence of generative artificial intelligence (GenAI) on employee performance in the workplace, viewed from a managerial perspective. It concentrates on key elements such as employee engagement, trust in GenAI and attitudes toward its implementation. This exploration is motivated by the ongoing evolution of GenAI, which presents managers with the crucial task of understanding and integrating this technology into their strategic frameworks. Design/methodology/approach: We collected 251 responses from managers and senior managers representing companies that have embraced GenAI in Spain. A hierarchical regression analysis was employed to examine the hypotheses. Subsequently, mediating effects and moderated mediation effects were scrutinized using the bias-corrected bootstrapping method. Findings: The data analysis suggests a significant enhancement in employee engagement and performance from a managerial perspective, attributed to improved attitudes and trust toward the adoption of GenAI. This conclusion is drawn from our research conducted with samples collected in Spain. Notably, our findings indicate that while positive attitudes toward GenAI correlate with enhanced engagement and performance, there exists a weakening effect on the significant positive impact of GenAI adoption in the workplace. This suggests that GenAI is still in its early stages of adoption within these companies, necessitating additional time for managers to develop greater confidence in its efficacy. Originality/value: This study represents one of the pioneering investigations centered on the implementation of GenAI within the workplace context. It contributes significantly to the existing body of literature concerning the stimulus-organism-response (S-O-R) model in technology innovation adoption within work environments

Investigation of the Influence of Ambient Conditions on the Thermodynamic Characteristics of Air as a Working Fluid for Gas Turbines

The study focuses on estimating thermodynamic characteristics at constant pressure for ambient air as a working fluid for gas turbines. The objective of this paper is to carry out a thermodynamic analysis of the properties of air as a working gas for a power plant. Various values of relative humidity, as well as temperatures, were examined in this study. Code was written using EES (Engineering Equations Solver) to conduct the simulation. This code contains the necessary equation to compute the thermodynamic characteristics of the working fluid. According to the results, both temperature and relative humidity remarkably influence the specific heat capacity (C_p), isentropic exponent (γ_h) as well as the gas constant of air (R_h). According to the results, when the ambient air temperature is increased from 0 to 45 ℃ with constant relative humidity values of either 10% or 90%, the specific heat capacity increases by 5.01% and 17.6%, respectively. Furthermore, the isentropic exponent decreases by 1.07% and 4.5%, respectively. The results show that the gas constant of air increases with ambient air temperature and relative humidity. One can conclude that the ambient conditions have considerable influence on the thermodynamic characteristics of a gas turbine working fluid. © 2023, Semarak Ilmu Publishing. All rights reserved.This research was not funded by any grant

Influence of Surrounding Air Temperature and Humidity upon the Performance of a Gas Turbine Power Plant

Nowadays, energy demand continuously rises while energy stocks are dwindling. Using current resources more effectively is crucial for the world. A wide method to effectively utilize energy is to generate electricity using thermal gas turbines (GT). One of the most important problems that gas turbines suffer from is high ambient air temperature especially in summer. The current paper details the effects of ambient conditions on the performance of a gas turbine through energy audits taking into account the influence of ambient conditions on the specific heat capacity (Cp), isentropic exponent (γh) as well as the gas constant of air (Rh). A computer program was developed to examine the operation of a power plant at various ambient temperatures and relative humidities. The ambient temperatures ranged from 0 to 45 ºC, with relative humidities from 10 to 90%. The obtained results show that a GT operated at increased inlet air temperatures is characterized by lower net power and thermal efficiency. At higher inlet air temperatures, increased relative humidity has a slight positive impact on the GT cycle net power and its thermal efficiency. Net output power of the GT decreased from 93.3 MW at 15 °C to 70 MW at 45 °C. Its efficiency decreased from 32.32% at 5 °C to 28.3% at 30 °C. Although fuel consumption is reduced, the heat rate as well and the specific fuel consumption (SFC) are enhanced. SFC increased by 5.36% with a 10 °C temperature rise in temperature at a constant relative humidity. Therefore, use of a gas turbine with inlet air cooling and humidification is appropriate for improved GT efficiency. © 2023, Semarak Ilmu Publishing. All rights reserved.This research was not funded by any grant

Design of a multi-level inverter for solar power systems with a variable number of levels technique

Overall harmonic distortion and losses will grow during an energy conversion process, while power stability will be reduced. Multilevel inverter technologies have recently become very popular as low-cost alternatives for a variety of industrial purposes. The design's minimal benefits include reduced component losses, decreased switching and conduction losses, along with enhanced output voltage and current waveforms. Also, a reduction of the harmonic components of the current and output voltage of the inverter are the most important requirements in multilevel inverters. A seven-level inverter design is presented in this paper that is simulated using MATLAB/Simulink. The inverter converts the DC voltage from three photovoltaic (PV) systems into AC voltage at seven levels. During an outage of one of the PV systems, the inverter will make a switching reduction and supply the AC voltage as a five-level inverter. The inverter’s total harmonic distortion (THD) when it performs as a five-level or seven-level inverter is 4.19% or 1.13% respectively. The modulation technique used is phase disposition via six carriers and a single reference signal at the fundamental frequency. © 2023, Institute of Advanced Engineering and Science. All rights reserved.Ministry of Education and Science of the Russian Federation, Minobrnauka: FEUZ-2022-0031Funding from the Ministry of Science and Higher Education of the Russian Federation (Ural Federal University Program of Development within the Priority-2030 Program) is gratefully acknowledged: Grant Number FEUZ-2022-0031

Role of oesophageal cooling in the prevention of oesophageal injury in atrial fibrillation catheter ablation: a systematic review and meta-analysis of randomized controlled trials.

AIMS: To evaluate the efficacy of oesophageal cooling in the prevention of oesophageal injury in patients undergoing atrial fibrillation (AF) catheter ablation. METHODS AND RESULTS: Comprehensive search of MEDLINE, EMBASE, and Cochrane databases through April 2022 for randomized controlled trials (RCTs) evaluating the role of oesophageal cooling compared with control in the prevention of oesophageal injury during AF catheter ablation. The study primary outcome was the incidence of any oesophageal injury. The meta-analysis included 4 RCTs with a total of 294 patients. There was no difference in the incidence of any oesophageal injury between oesophageal cooling and control [15% vs. 19%; relative risk (RR) 0.86; 95% confidence interval (CI) 0.31-2.41]. Compared with control, oesophageal cooling showed lower risk of severe oesophageal injury (1.5% vs. 9%; RR 0.21; 95% CI 0.05-0.80). There were no significant differences among the two groups in mild to moderate oesophageal injury (13.6% vs. 12.1%; RR 1.09; 95% CI 0.28-4.23), procedure duration [standardized mean difference (SMD) -0.03; 95% CI -0.36-0.30], posterior wall radiofrequency (RF) time (SMD 0.27; 95% CI -0.04-0.58), total RF time (SMD -0.50; 95% CI -1.15-0.16), acute reconnection incidence (RR 0.93; 95% CI 0.02-36.34), and ablation index (SMD 0.16; 95% CI -0.33-0.66). CONCLUSION: Among patients undergoing AF catheter ablation, oesophageal cooling did not reduce the overall risk of any oesophageal injury compared with control. Oesophageal cooling might shift the severity of oesophageal injuries to less severe injuries. Further studies should evaluate the long-term effects after oesophageal cooling during AF catheter ablation