Modified Garden Balsan Optimization Based Machine Learning for Intrusion Detection

The Internet of Things (IoT) environment plays a crucial role in the design of smart environments. Security and privacy are the major challenging problems that exist in the design of IoT-enabled real-time environments. Security susceptibilities in IoT-based systems pose security threats which affect smart environment applications. Intrusion detection systems (IDS) can be used for IoT environments to mitigate IoT-related security attacks which use few security vulnerabilities. This paper introduces a modified garden balsan optimization-based machine learning model for intrusion detection (MGBO-MLID) in the IoT cloud environment. The presented MGBO-MLID technique focuses on the identification and classification of intrusions in the IoT cloud atmosphere. Initially, the presented MGBO-MLID model applies min-max normalization that can be utilized for scaling the features in a uniform format. In addition, the MGBO-MLID model exploits the MGBO algorithm to choose the optimal subset of features. Moreover, the attention-based bidirectional long short-term (ABiLSTM) method can be utilized for the detection and classification of intrusions. At the final level, the Aquila optimization (AO) algorithm is applied as a hyperparameter optimizer to fine-tune the ABiLSTM methods. The experimental validation of the MGBO-MLID method is tested using a benchmark dataset. The extensive comparative study reported the betterment of the MGBO-MLID algorithm over recent approaches.     

Large distance flow-slide at Jono-Oge due to the 2018 Sulawesi Earthquake,Indonesia

There was a shallow earthquake in the Central Sulawesi province of Sulawesi island of Indonesia with a moment magnitude (Mw) 7.5 on 28th September 2018 at 18:02:44 local time. The event was preceded by major foreshocks and followed by aftershocks of significant magnitude. The epicenter of the main shock was in the Donggala regency of Minahasa peninsula of Central Sulawesi, approximately 70 km from the provincial capital of Palu. The earthquake was caused by the tectonic movement of the left lateral Palu- Koro fault within the Molucca Sea microplate, triggering major geotechnical failure and structural damage in Palu city and Sigi regency. Thousands of people died or are still unaccounted for, and countless others were injured. Balaroa, Petobo, Jono-Oge and Sibalaya were the worst hit mainly due to large-scale flow-slides and mud flows. It was the first time that such large-scale flow failures were triggered by an earthquake, and that the failure of very gentle sloping ground swept away whole localities. The objective of this research was to provide insight into the scale of ground failure and other infrastructural damage caused by the event, especially in Jono-Oge area, where the flow distance was longest. The authors performed preliminary and detailed surveys in the area twice by conducting Portable Dynamics Cone Penetration Test (PDCPT), collecting disturbed and undisturbed samples and using aerial drone (UAV) photography. The findings of the reconnaissance survey are described here along with subsequent data interpretation. Finally, the mechanism of the flow-slides is discussed.     

Regional Flood Frequency Analysis of the Seven Sites of Punjab, Pakistan, Using L-Moments

L-moments based regional flood frequency analysis has been carried out on the seven sites of Punjab, Pakistan. Discordancy measure in terms of L-moments has been used to screen the data on each of the seven sites. Homogeneity of the region has been tested using the L-moments based heterogeneity measure (H). H has been calculated using four parameter Kappa distribution with 500 simulations. In order to find the most suitable distribution for quantile estimates, a number of L-moments based frequency distributions, such as, generalized logistic (GLO), generalized extreme-value (GEV), generalized normal (GNO), Pearson type III (PE3), generalized Pareto (GPA) and five parameter Wakeby (WAK) distribution, have been used. Based on the L-moment ratio diagram and Z ^DIST statistic, three distributions; GNO, GPA and GEV have been identified as the suitable candidates for regional distribution. Accuracy measures for the estimated regional growth curves and quantiles have been calculated for the three candidate distributions, using Monte Carlo simulations. Simulations study showed that GNO distribution is the robust distribution with GPA as suitable alternative but GEV is not an appropriate distribution for the study area.     

Investigating Energy Flow in Water-Energy Storage for Hydropower Generation in Water Distribution Systems

Quantifying excess energy using an energy balance model is the key to designing and operating an energy-efficient water distribution system (WDS). Excess energy, which can be recovered instantly or stored in a water-energy storage is the basis to estimate hydropower potential in the system. For a given WDS with its demand, how the excess energy can be managed efficiently to design a water-energy storage to maximize hydropower generation is the focus of this paper. A single-objective optimization model has been developed to optimize the dimensions for up to six water-energy storages for maximizing hydropower generation while minimizing the pumping energy. While the ratio of total energy recovered to total pumping energy is found to be about 40% for all water-energy configurations, the recovered specific energy ranges from 0.116 kWh/m³ to 0.121 kWh/m³ showing the potential use of WDS as an energy storage. Results show that hydropower generation increases with the increase of number of storages up to a certain number representing the constraints of constant drinking water demand and storage dimensions. In-pipe turbines with pump operation for minimizing pumping energy can offer the optimal solution for WDS energy management. A higher number of storages with in-pipe turbines offers uniformity in pressure distribution resulting increase in system robustness.

     

A Library of Thiazolidin-4-one Derivatives as Protein Tyrosine Phosphatase 1B (PTP1B) Inhibitors: An Attempt To Discover Novel Antidiabetic Agents

Protein tyrosine phosphatase 1B (PTP1B) is an important target for the treatment of diabetes. A series of thiazolidin-4-one derivatives 8 – 22 was designed, synthesized and investigated as PTP1B inhibitors. The new molecules inhibited PTP1B with IC₅₀ values in the micromolar range. 5-(Furan-2-ylmethylene)-2-(4-nitrophenylimino)thiazolidin-4-one ( 17 ) exhibited potency with a competitive type of enzyme inhibition. structure–activity relationship studies revealed various structural facets important for the potency of these analogues. The findings revealed a requirement for a nitro group-including hydrophobic heteroaryl ring for PTP1B inhibition. Molecular docking studies afforded good correlation with experimental results. H-bonding and π–π interactions were responsible for optimal binding and effective stabilization of virtual protein-ligand complexes. Furthermore, in-silico pharmacokinetic properties of test compounds predicted their drug-like characteristics for potential oral use as antidiabetic agents.Additionally, a binding site model demonstrating crucial pharmacophoric characteristics influencing potency and binding affinity of inhibitors has been proposed, which can be employed in the design of future potential PTP1B inhibitors.     

Angiotensin‐converting enzyme‐inhibitory and antithrombotic activities of soluble peptide extracts from buffalo and cow milk Cheddar cheeses

The aim of the study was to evaluate potential role of a water‐soluble peptide (WSP) extracts derived from buffalo and cow milk Cheddar cheeses with special reference to their antihypertension and antithrombotic activities. The WSP fractions collected at different stages of ripening were tested to assess their degree of proteolysis, their peptides were profiled by RP‐HPLC and in vitro assays for potential bioactivity were conducted. The peptide peak development was observed with slight differences in peaks number, area and height. Both angiotensin‐converting enzyme‐inhibitory and antithrombotic activities increased progressively during ripening. In comparison, the highest activities were observed in peptide extracts obtained from buffalo milk Cheddar cheese, in a dose‐dependent fashion.     

Ultrasound-assisted synthesis of santalbic acid and a study of triacylglycerol species inSantalum album (Linn.) seed oil

Methyl ricinoleate (1) was treated with bromine and the dibromo derivative (2) was reacted with ethanolic KOH under ultrasonic irradiation to give 12-hydroxy-octadec-9-ynoic acid upon acidification with dil. HCl. The latter compound was methylated with BF₃/methanol to give methyl 12-hydroxy-octadec-9-ynoate (3). Compound3 was treated with methanesulfonyl chloride in the presence of triethylamine in CH₂Cl₂ to give methyl 12-mesyloxy-octadec-9-ynoate (4). Reaction of methyl 12-mesyloxy-octadec-9-ynoate with aqueous KOH under ultrasonic irradiation (20 kHz) gave (11E)-octadecen-9-ynoic acid (5, santalbic acid, 40%) and (11Z)-octadecen-9-ynoic acid (6, 60%) on acidification with dil. HCl. These isomers were separated by urea fractionation. The¹³C nuclear magnetic resonance (NMR) spectroscopic properties of the methyl ester and the triacylglycerol (TAG) esters of these enynoic fatty acid isomers were studied. The carbon shifts of the unsaturated carbon nuclei of the methyl ester of theE-isomer were unambiguously assigned as 88.547 (C-9), 79.287 (C-10), 109.760 (C-11), and 143.450 (C-12) ppm while the unsaturated carbon shifts of the (Z)-enynoate isomer appeared at 94.277 (C-9), 77.561 (C-10), 109.297 (C-11), and 142.668 (C-12) ppm. In the¹³C NMR spectral analysis of the TAG molecules of type AAA containing either the (Z)-or (E)-enyne fatty acid, the C-1 to C-6 carbon atoms on the α- and β-acyl positions were differentiated. The unsaturated carbon atoms in the α- and β-acyl chains were also resolved into two signals except that of the C-11 olefinic carbon. Sandal (Santalum album) wood seed oil (a source of santalbic acid) was separated by silica chromatography into three fractions. The least polar fraction (7.2 wt%) contained TAG which had a random distribution of saturated and unsaturated fatty acids, of which oleic acid (69%) was the predominant component. The second fraction (3.8 wt%) contained santalbic acid (58%) and oleic acid (28%) together with some other normal fatty acids. Santalbic acid in this fraction was found in both the α- and β-acyl positions of the glycerol “backbone”. The most polar fraction (89 wt%) consisted of TAG containing santalbic acid only. The distribution of the various fatty acids on the glycerol “backbone” was supported by the results from the¹³C NMR spectroscopic analysis.     

Synthesis and characterization of Ni-Si mixed oxide nanocomposite as a catalyst for carbon nanotubes formation

Ni-Si mixed oxide nanocomposite was prepared by co-precipitation method with Ni(NO₃)₂ · 6H₂O and tetraethylorthosilicate (TEOS) at pH = 10.5 under reflux condition for 6 days. It was then used as a catalyst for the formation of carbon nanotubes (CNTs) by CVD procedure. Characterization of the catalyst and the CNTs was carried out using X-ray diffractometry (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy. The results showed that Ni-Si mixed oxides nanorods with the average diameter of 3 to 4 nm play a key role in CNTs formation.