An Optimized Novel Trust-Based Security Mechanism Using Elephant Herd Optimization

Routing strategies and security issues are the greatest challenges in Wireless Sensor Network (WSN). Cluster-based routing Low Energy adaptive Clustering Hierarchy (LEACH) decreases power consumption and increases network lifetime considerably. Securing WSN is a challenging issue faced by researchers. Trust systems are very helpful in detecting interfering nodes in WSN. Researchers have successfully applied Nature-inspired Metaheuristics Optimization Algorithms as a decision-making factor to derive an improved and effective solution for a real-time optimization problem. The metaheuristic Elephant Herding Optimizations (EHO) algorithm is formulated based on elephant herding in their clans. EHO considers two herding behaviors to solve and enhance optimization problem. Based on Elephant Herd Optimization, a trust-based security method is built in this work. The proposed routing selects routes to destination based on the trust values, thus, finding optimal secure routes for transmitting data. Experimental results have demonstrated the effectiveness of the proposed EHO based routing. The Average Packet Loss Rate of the proposed Trust Elephant Herd Optimization performs better by 35.42%, by 1.45%, and by 31.94% than LEACH, Elephant Herd Optimization, and Trust LEACH, respectively at Number of Nodes 3000. As the proposed routing is efficient in selecting secure routes, the average packet loss rate is significantly reduced, improving the network’s performance. It is also observed that the lifetime of the network is enhanced with the proposed Trust Elephant Herd Optimization.     

Synthesis and Biological Studies of Novel Aminophosphonates and Their Metal Carbonyl Complexes (Fe,Ru)

The quest to find new inhibitors of biologically relevant targets is considered an important strategy to introduce new drug candidates for the treatment of neurodegenerative diseases. A series of (aminomethyl)benzylphosphonates 8a–c and their metallocarbonyl iron 9a–c and ruthenium 10a–c complexes were designed, synthesized, and evaluated for their inhibitory potentials against acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) by determination of IC₅₀. Metallocarbonyl derivatives, in general, did not show significant inhibition activity against these enzymes, the most potent inhibitor was the (aminomethyl)benzylphosphonate 8a (IC₅₀ = 1.215 µM against AChE). Molecular docking analysis of AChE and (aminomethyl)benzylphosphonates 8a–c showed the strongest interactions of 8a and AChE compared to isomers 8b and 8c. Cytotoxicity studies of synthesized compounds towards the V79 cell line were also performed and discussed.     

Energy Efficient Clustering Scheme (EECS) for Wireless Sensor Network with Mobile Sink

The participants in the Wireless Sensor Network (WSN) are highly resource constraint in nature. The clustering approach in the WSN supports a large-scale monitoring with ease to the user. The node near the sink depletes the energy, forming energy holes in the network. The mobility of the sink creates a major challenge in reliable and energy efficient data communication towards the sink. Hence, a new energy efficient routing protocol is needed to serve the use of networks with a mobile sink. The primary objective of the proposed work is to enhance the lifetime of the network and to increase the packet delivered to mobile sink in the network. The residual energy of the node, distance, and the data overhead are taken into account for selection of cluster head in this proposed Energy Efficient Clustering Scheme (EECS). The waiting time of the mobile sink is estimated. Based on the mobility model, the role of the sensor node is realized as finite state machine and the state transition is realized through Markov model. The proposed EECS algorithm is also been compared with Modified-Low Energy Adaptive Clustering Hierarchy (MOD-LEACH) and Gateway-based Energy-Aware multi-hop Routing protocol algorithms (M-GEAR). The proposed EECS algorithm outperforms the MOD-LEACH algorithm by 1.78 times in terms of lifetime and 1.103 times in terms of throughput. The EECS algorithm promotes unequal clustering by avoiding the energy hole and the HOT SPOT issues.     

Hybrid Global Sensitivity Analysis Based Optimal Attribute Selection Using Classification Techniques by Machine Learning Algorithm

In this study, we focus on realizing channel estimation using a fully connected deep neural network. The data aided estimation approach is employed. We assume the transmission channel is Rayleigh and it is constant over the duration of a symbol plus pilot transmission. We develop and tune the deep learning model for various size of pilot data that is known to the receiver and used for channel estimation. The deep learning models are trained on the Rayleigh channel. The performance of the model is discussed for various size of pilot by providing Bit Error Rate of the model. The Bit Error Rate performance of the model is compared to theoretical upper bound which shows that the model successfully estimates the channel.

     

Important flavonoids and limonin in selected Thai citrus residues

The distributions of important flavonoids and limonin in selected Thai citrus residues were investigated in this study. The residues of interest were peels of pomelo (Citrus grandis (L.) Osbeck cv. Kao Yai and cv. Kao Nampheung), residues after juice extraction of tangerine (Citrus reticulata Blanco cv. Sainamphueng and cv. Bangmod) and peels and residues after juice extraction of kaffir lime (Citrus hystrix DC). Flavonoids were characterized and quantified in terms of flavanones, i.e., naringin and hesperidin, and polymethoxyflavones (PMFs), i.e., nobiletin, sinensetin and tangeretin. Naringin was a dominant flavanone in polmelo peels. Three PMFs were found in all samples with varying contents. Comparing the samples, residues from tangerine cv. Bangmod exhibited the highest value of each PMFs. Limonin was present in small amounts in pomelo peels and residues after juice extraction of tangerine and kaffir lime. All samples were good sources of dietary fibre, with a total dietary fibre content of more than 60 g/100 g on a dry weight basis with high proportion of soluble dietary fibre.     

Genetic analysis of subclinical mastitis in early lactation of heifers using both linear and threshold models

Subclinical mastitis (SCM) causes economic losses for dairy producers by reducing milk production and leading to higher incidence of clinical mastitis and premature culling. The prevalence of SCM in first-lactation heifers is highest during early lactation. The objective of this study was to estimate genetic parameters for SCM in early lactation in first-parity Holsteins. Somatic cell count test-day records were collected monthly in 91 Canadian herds participating in the National Cohort of Dairy Farms of the Canadian Bovine Mastitis Research Network. Only the first test-day record available between 5 and 30 d in milk was considered for analysis. The final data set contained 8,518 records from first lactation Holstein heifers. Six alternative traits were defined as indicators of SCM, using various cutoff values of SCC, ranging from 150,000 to 400,000 cells/mL. Both linear and threshold animal models were used. Overall prevalence of SCM using the 6 traits ranged from 13 to 24%. Heritability estimates (standard error) from linear and threshold models ranged from 0.037 to 0.057 (0.015 to 0.018) and from 0.040 to 0.051 (0.017 to 0.020), respectively. We found strong genetic correlations (standard error) among alternative SCC traits, ranging from 0.90 to 0.99 (0.013 to 0.069), indicating that these 6 traits were genetically similar. Despite low heritability, based on estimated breeding values (EBV) predicted from both models, we noted exploitable genetic variation among sires. Higher EBV of SCM resistance corresponded to sires with a higher percentage of daughters without SCM. Based on a linear model (all 6 traits), percentage of daughters with SCM ranged from 5 to 13% and from 19 to 33% for the top 10% and worst 10% of 69 sires with minimum 20 daughters in at least 5 herds, respectively. Spearman's rank correlations among EBV of sires predicted from linear (from 0.75 to 0.95) and threshold (from 0.74 to 0.95) models were moderate to high, respectively. Very high rank correlations (0.98 to 0.99) between EBV predicted for the same trait from linear and threshold model indicated that reranking of sires based on model used was minimal. In conclusion, despite low heritability, we found utilizable genetic variation in early lactation of heifers. Hence, genetic selection to improve genetic resistance to SCM in early lactation of heifers was deemed possible.     

Decontamination of Microorganisms and Pesticides from Fresh Fruits and Vegetables: A Comprehensive Review from Common Household Processes to Modern Techniques

Fresh fruits and vegetables are a rich source of micronutrients. However, many foodborne illnesses have been linked to the consumption of fresh fruits and vegetables as they are reported to harbor contaminants such as microorganisms and pesticides. Recently reported foodborne outbreaks have been linked to a diverse group of fruits and vegetables due to the presence of various pathogens including Salmonella, Escherichia coli, and Listeria monocytogenes. Also, the increased use of pesticides has resulted in the deposition of chemical residues on the surface of fruits and vegetables, which has led to the adverse health conditions such as cancer, birth defects, and neurodevelopmental disorders. Fresh commodities are subjected to various treatments to prevent or minimize these outbreaks, and the main targets of such treatments have been the elimination of pathogens and degradation of toxic chemical residues. Here, we have discussed various decontamination methods including simple household washing, chemical treatments, and modern technologies with their mode of action for microbial and pesticide removal. The simple household processes are not very effective in the removal of pathogenic organisms and pesticides. The use of modern techniques like cold plasma, ozone, high hydrostatic pressure, and so on, showed better efficacy in the removal of microorganisms and pesticides. However, their industrial use is limited considering high installation and maintenance cost. In this review, we suggest combined methods based on their mode of decontamination and suitability for a selected fruit or vegetable for effective decontamination of microbes and pesticide together to reduce the treatment cost and enhance food safety.     

Lactic acid bacteria isolated from raw and fermented pork products: Identification and characterization of catalase-producing Pediococcus pentosaceus

Food Science and Biotechnology - Lactic acid bacteria (LAB) from raw and fermented pork samples were screened for their inhibitory activity by an agar spot test in order to obtain a LAB strain with...     

Genetic analysis of pathogen-specific intramammary infections in dairy cows

Mastitis is one of the most common diseases in dairy cattle, causing severe economic losses to dairy farmers. Mastitis usually occurs due to intramammary infection (IMI) caused by a variety of pathogenic bacteria. Although good progress has been made in understanding genetics of pathogen-specific clinical mastitis, studies involving genetic analysis of pathogen-specific IMI are scarce. The overall objective of this study was, therefore, to assess genetic variation of overall and pathogen-specific IMI in nonclinical primiparous and multiparous cows using bacterial culture. Data and milk samples were collected over a 2-yr interval as part of the Canadian Bovine Mastitis Research Network. The final data set contained records of 46,900 quarter milk samples from 3,382 clinically healthy primiparous and multiparous Holstein cows from 84 dairy herds. For the genetic analysis, we considered the following 7 traits: overall IMI, non-aureus staphylococci (NAS) IMI, contagious pathogen IMI, environmental pathogen IMI, major pathogen IMI, minor pathogen IMI and somatic cell score (SCS). Data were analyzed at the quarter level using a threshold-probit model via Gibbs sampling in BLUPF90. Prevalence of IMI traits at the quarter level in multiparous cow from 0 to 400 DIM ranged from 6.8 to 45.5%. Posterior mean of quarter heritability estimates (on the underlying scale, posterior SD in brackets) of overall IMI and pathogen-specific IMI traits ranged from 0.017 to 0.073 (±0.009 to 0.030). Weak to strong genetic correlations [ranging from 0.18 to 0.97 (±0.01 to 0.29)] among pathogen-specific IMI traits and with overall IMI indicated that not all of these traits were genetically similar. Weak to moderate Spearman rank correlations between estimated breeding values for overall IMI and pathogen-specific IMI traits (from 0.31 to 0.87) indicated possible substantial reranking of sires. The percentage of daughters with IMI caused by various pathogen groups ranged from 13 to 80% and from 38 to 94% for the best (10% decile) and worst sires (90% decile) according to their IMI trait-specific estimated breeding values, respectively. Pathogen-specific IMI traits and overall IMI had weak to moderate positive genetic correlations [ranging from 0.11 to 0.81 (±0.11 to 0.22)] with SCS. Therefore, selection for lower SCS will improve resistance to IMI. However, based on the observed weak to moderate rank correlations (0.04 to 0.47) between pathogen-specific IMI traits and SCS, selection for lower SCC will not improve resistance to IMI from every pathogen-specific IMI group in the same manner. Therefore, despite low heritability estimates, there was sizeable genetic variation for pathogen-specific IMI traits, indicating that long-term direct genetic selection for pathogen-specific IMI can improve pathogen-specific IMI resistance.