High-strength anti-bacterial composite cryogel for lethal noncompressible hemorrhage hemostasis: Synergistic physical hemostasis and chemical hemostasis

This paper presents a compact and simple reconfigurable antenna with wide-band, dual-band, and single-band operating modes. Initially, a co-planar waveguide-fed triangular monopole antenna is obtained with a wide operational frequency band ranging from 4.0 GHz to 7.8 GHz. Then, two additional stubs are connected to the triangular monopole through two p-i-n diodes. By electrically switching these p-i-n diodes ON and OFF, different operating frequency bands can be attained. When turning ON only one diode, the antenna offers dual-band operations of 3.3–4.2 GHz and 5.8–7.2 GHz. Meanwhile, the antenna with single-band operation from 3.3 GHz to 4.2 GHz can be realized when both of the p-i-n diodes are switched to ON states. The proposed compact size antenna with dimensions of 0.27λ0 × 0.16λ0 × 0.017λ0 at the lower operating frequency (3.3 GHz) can be used for several wireless applications such as worldwide interoperability for microwave access (WiMAX), wireless access in the vehicular environment (WAVE), and wireless local area network (WLAN). A comparative analysis with state-of-the-art works exhibits that the presented design possesses advantages of compact size and multiple operating modes.

Design and Realization of a Frequency Reconfigurable Antenna with Wide, Dual, and Single-Band Operations for Compact Sized Wireless Applications

Bowling alone or distancing together? The role of social capital in excess death rates from COVID19.

Aspergillus niger MH078571.1 and A. niger MH079049.1 were identified previously as the two highest Aspergillus niger strains producing lipase. Biochemical characterizations of lipase activity and stability for these two strains were examined and revealed that the optimal temperature is 45 °C at pH 8for A. niger MH078571.1 and 55 °C for MH079049.1. The lipase production of both strains was studied on medium contains waste oil, as a cheap source to reduce the industrial cost, showed that the optimal incubation period for the enzyme production is 3 days. Moreover, an experiment on lipase activates in organic solvents demonstrated that 50% of acetone is the best solvent for the two strains. In the presence of surfactants, 0.1% of tween 80 surfactant showed the best lipase activities. Furthermore, Mg2+ and Zn2+ ions enhanced the lipase activity of A. niger MH078571.1, while Na2+ and Cu2+ enhanced the enzyme activity of A. niger MH079049.1. Lipase activity was also tested for industrial applications such as integrating it with different detergents. Maximum lipase activity was obtained with 1% of Omo as a powder detergent for both strains. In liquid detergent, 0.1% of Fairy showed maximum lipase activity in A. niger MH078571.1, while the lipase in A. niger MH079049.1 was more effective in 1% of Lux. Moreover, the degradation of natural animal fat with crude enzyme was tested using chicken and sheep fats. The results showed that more than 90% of fats degraded after 5 days of the incubation period.

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Application and characterization of crude fungal lipases used to degrade fat and oil wastes.

Evaporation is a key element for water resource management, hydrological modelling, and irrigation system designing. Monthly evaporation (Ep) was projected by deploying three machine learning (ML) models included Extreme Gradient Boosting, ElasticNet Linear Regression, and Long Short-Term Memory; and two empirical techniques namely Stephens-Stewart and Thornthwaite. The aim of this study is to develop a reliable generalised model to predict evaporation throughout Malaysia. In this context, monthly meteorological statistics from two weather stations in Malaysia were utilised for training and testing the models on the basis of climatic aspects such as maximum temperature, mean temperature, minimum temperature, wind speed, relative humidity, and solar radiation for the period of 2000-2019. For every approach, multiple models were formulated by utilising various combinations of input parameters and other model factors. The performance of models was assessed by utilising standard statistical measures. The outcomes indicated that the three machine learning models formulated outclassed empirical models and could considerably enhance the precision of monthly Ep estimate even with the same combinations of inputs. In addition, the performance assessment showed that Long Short-Term Memory Neural Network (LSTM) offered the most precise monthly Ep estimations from all the studied models for both stations. The LSTM-10 model performance measures were (R2 = 0.970, MAE = 0.135, MSE = 0.027, RMSE = 0.166, RAE = 0.173, RSE = 0.029) for Alor Setar and (R2 = 0.986, MAE = 0.058, MSE = 0.005, RMSE = 0.074, RAE = 0.120, RSE = 0.013) for Kota Bharu.

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Application of long short-term memory neural network technique for predicting monthly pan evaporation.

Background Extracellular production of fungal lipases especially the lipases obtained from the Aspergilli has gained immense interest in recent years due to its diverse biotechnological applications. In this study, we focused on determining the fermentation parameters required for the optimal lipase production. Methods A total of 256 fungal isolates were obtained from oil seeds. From each genus, one isolate was selected to evaluate lipase production using phenol red and tributyrin plate assays. Lipase activity was estimated using the spectrophotometric pNPP hydrolysis assay. The highest lipase producer isolates were identified using 18S ribosomal RNA gene sequencing. The genetic variability was determined by random amplified polymorphic DNA (RAPD) analysis and the dendrogram was constructed using the unweighted pair group method with arithmetic averages method. The isolates were examined in a submerged fermentation culture (Smf) to measure the effect of temperature, pH, incubation time, carbon source, nitrogen source, inoculum volume, and lipid source on lipase production. Results Eleven isolates belonging to the genus Aspergillus were analyzed for lipase production where they were found to be the highest lipase producers among various fungal genera. All the tested isolates were identified as A. niger using 18s rRNA sequencing. Genetic diversity was evaluated among all of the studied A. niger isolates using RAPD primers. The RAPD primers were used to amplify 285 loci, of which five were polymorphic (1.75%) and seven were monomorphic (2.45%). Thus, a high level of genetic diversity was observed among all isolates. The tributyrin test and the lipase activity assay identified five strains of A. niger as high lipase producers, and their optimal enzyme activities were 709.74, 532.54, 735.64, 794.62, and 787.69 U/ml. The optimal conditions for lipase production were as follows: 40 °C, pH 7.5, 1% fructose as the carbon source, 1% yeast extract as the nitrogen source, 2% palm oil, 2.5 × 107 spores/ml suspension, and 3 days of incubation. Conclusions The current study provides a comprehensive characterization of the optimal conditions, which are essential to enhance lipase production in five A. niger isolates.

Norah Ayad ALanazi

Papers

Application and characterization of crude fungal lipases used to degrade fat and oil wastes.

Molecular, physiological, and biochemical characterization of extracellular lipase production by Aspergillus niger using submerged fermentation.