Study on the mechanism of Na2CO3-roasting decomposition for water leach residue.

In the process of treating cerium fluorocarbon-cerium lanthanide mixed rare earth concentrates by sulfuric acid roasting method, a large amount of waste leach residue containing iron, rare earths and phosphorus produced by flood neutralization needs to be solved urgently. In this paper, sodium carbonate roasting decomposition was used to treat the water leach residue, in which iron and rare earths were transformed into oxides, and the phosphorus was transformed into sodium phosphate. The main reactions and thermodynamic mechanisms of the roasting decomposition process were investigated by thermogravimetric analysis, phase analysis and chemical analysis. When the mass ratio of sodium carbonate to water leach residue is 1.5:1, the roasting temperature is 700 °C, and the roasting time is 1.5 h, the leaching rate of phosphorus with the roasted product reaches more than 98%. Meanwhile, the phase of the roasted product after washing mainly consists of iron oxide and rare earth oxides. The combination of sodium carbonate roasting decomposition and water leaching is effective for the treatment of water leach residue, which provides an experimental and theoretical basis for solving the problem of environmental and resource waste caused by the accumulation of a large amount of water leach residue. In addition, because sodium carbonate can achieve the separation of iron and phosphorus, this method also has certain reference value for the recovery and utilization of iron phosphate in lithium iron phosphate battery waste.

Casein/ferric chloride/polyvinyl alcohol composite for specific in-syringe colorimetric detection of formaldehyde in Hevea brasiliensis latex.

A new, simple, and selective colorimetric method of determining formaldehyde in Hevea brasiliensis latex was developed by using a casein/ferric chloride/polyvinyl alcohol hydrogel composite (casein/FeCl3/PVA) in a modified Leach test. Under heating, formaldehyde reacted with 8% casein in the presence of 0.1% FeCl3 and 4.3% HCl (v/v) entrapped in a 30% PVA hydrogel packed in a syringe. A purple-colored product was formed with a maximum absorbance of 525 nm. The color change was evaluated at the color detection zone indicated on the the syringe. The %magenta values were easily evaluated by using a mobile phone application and employed to determine formaldehyde content. The casein/FeCl3/PVA composite gave a readable response in a formaldehyde detection range from 0.04 to 0.80% with a linear response between %magenta and formaldehyde concentration (R2 = 0.9955). The detection limit was 0.032%, and precisions were in the range 0.67-4.94%. The casein/FeCl3/PVA composite was applied to the analysis of ammonia-preserved latex samples, and recoveries of formaldehyde from samples spiked at 0.1, 0.3, and 0.5% ranged from 81.55 to 99.51% (RSDs ≤ 5.41%). The recoveries and precision of the proposed method were comparable with those of high-performance liquid chromatography (HPLC). The developed method was also selective, showing no interference from other latex preservatives, i.e., phenol, ammonia, or tetramethylthiuram disulfide.

Improved LEACH Protocol Based on Underwater Energy Propagation Model, Parallel Transmission, and Replication Computing for Underwater Acoustic Sensor Networks.

Underwater acoustic sensor networks (UASNs) are critical to a range of applications from oceanographic data collection to submarine surveillance. In these networks, efficient energy management is critical due to the limited power resources of underwater sensors. The LEACH protocol, a popular cluster-based protocol, has been widely used in UASNs to minimize energy consumption. Despite its widespread use, the conventional LEACH protocol faces challenges such as an unoptimized cluster number and low transmission efficiency, which hinder its performance. This paper proposes an improved LEACH protocol for cluster-based UASNs, where the cluster number is optimized with an underwater energy propagation model to reduce energy consumption, and a transmission scheduling algorithm is also employed to achieve conflict-free parallel data transmission. Replication computing is introduced to the LEACH protocol to reduce the signaling in the clustering and data transmission phases. The simulation results show that the proposed protocol outperforms several conventional methods in terms of normalized average residual energy, average number of surviving nodes, average round when the first death node occurs, and the number of packets received by the base station.

Enhancement of Biodegradability of Chicken Manure via the Addition of Zeolite in a Two-Stage Dry Anaerobic Digestion Configuration.

Leach bed reactors (LBRs) are dry anaerobic systems that can handle feedstocks with high solid content, like chicken manure, with minimal water addition. In this study, the chicken manure was mixed with zeolite, a novel addition, and packed in the LBR to improve biogas production. The resulting leachate was then processed in a continuous stirred tank reactor (CSTR), where most of the methane was produced. The supernatant of the CSTR was returned to the LBR. The batch mode operation of the LBR led to a varying methane production rate (MPR) with a peak in the beginning of each batch cycle when the leachate was rich in organic matter. Comparing the MPR in both systems, the peaks in the zeolite system were higher and more acute than in the control system, which was under stress, as indicated by the acetate accumulation at 2328 mg L-1. Moreover, the presence of zeolite in the LBR played a crucial role, increasing the overall methane yield from 0.142 (control experiment) to 0.171 NL CH4 per g of volatile solids of chicken manure entering the system at a solid retention time of 14 d. Zeolite also improved the stability of the system. The ammonia concentration increased gradually due to the little water entering the system and reached 3220 mg L-1 (control system) and 2730 mg L-1 (zeolite system) at the end of the experiment. It seems that zeolite favored the accumulation of the ammonia at a lower rate (14.0 mg L-1 d-1) compared to the control experiment (17.3 mg L-1 d-1). The microbial analysis of the CSTR fed on the leachate from the LBR amended with zeolite showed a higher relative abundance of Methanosaeta (83.6%) compared to the control experiment (69.1%). Both CSTRs established significantly different bacterial profiles from the inoculum after 120 days of operation (p < 0.05). Regarding the archaeal communities, there were no significant statistical differences between the CSTRs and the inoculum (p > 0.05).

Unsupervised Learning-Based WSN Clustering for Efficient Environmental Pollution Monitoring.

Wireless Sensor Networks (WSNs) have been adopted in various environmental pollution monitoring applications. As an important environmental field, water quality monitoring is a vital process to ensure the sustainable, important feeding of and as a life-maintaining source for many living creatures. To conduct this process efficiently, the integration of lightweight machine learning technologies can extend its efficacy and accuracy. WSNs often suffer from energy-limited devices and resource-affected operations, thus constraining WSNs' lifetime and capability. Energy-efficient clustering protocols have been introduced to tackle this challenge. The low-energy adaptive clustering hierarchy (LEACH) protocol is widely used due to its simplicity and ability to manage large datasets and prolong network lifetime. In this paper, we investigate and present a modified LEACH-based clustering algorithm in conjunction with a K-means data clustering approach to enable efficient decision making based on water-quality-monitoring-related operations. This study is operated based on the experimental measurements of lanthanide oxide nanoparticles, selected as cerium oxide nanoparticles (ceria NPs), as an active sensing host for the optical detection of hydrogen peroxide pollutants via a fluorescence quenching mechanism. A mathematical model is proposed for the K-means LEACH-based clustering algorithm for WSNs to analyze the quality monitoring process in water, where various levels of pollutants exist. The simulation results show the efficacy of our modified K-means-based hierarchical data clustering and routing in prolonging network lifetime when operated in static and dynamic contexts.

Energy-Efficient LoRa Routing for Smart Grids.

Energy-efficient routing protocols in Internet of Things (IoT) applications are always of colossal importance as they improve the network's longevity. The smart grid (SG) application of the IoT uses advanced metring infrastructure (AMI) to read and record power consumption periodically or on demand. The AMI sensor nodes in a smart grid network sense, process, and transmit information, which require energy, which is a limited resource and is an important parameter required to maintain the network for a longer duration. The present work discusses a novel energy-efficient routing criterion in an SG environment realised using LoRa nodes. Firstly, a modified LEACH protocol-cumulative low-energy adaptive clustering hierarchy (Cum_LEACH) is proposed for cluster head selection among the nodes. It uses the cumulative energy distribution of the nodes to select the cluster head. Furthermore, for test packet transmission, multiple optimal paths are created using the quadratic kernelised African-buffalo-optimisation-based LOADng (qAB_LOADng) algorithm. The best optimal path is selected from these multiple paths using a modified version of the MAX algorithm called the SMAx algorithm. This routing criterion showed an improved energy consumption profile of the nodes and the number of active nodes after running for 5000 iterations compared to standard routing protocols such as LEACH, SEP, and DEEC.

The influence of biochar position in a leach bed system anaerobically digesting chicken litter.

As a consequence of the rapidly growing poultry industry, chicken litter is becoming an abundant and problematic waste. Anaerobic digestion of chicken litter can mitigate environmental issues while producing valuable by-products. Recent studies have shown that leach bed reactor (LBR) systems are suitable for processing chicken litter and that anaerobic digestion can be enhanced using biochar. This study investigates the influence of biochar position within an LBR system on anaerobic digestion of chicken litter. Compared to a system without biochar, application of biochar in both the LBR (mixed in with the feedstock or as a layer below the feedstock) and coupled leachate tank (LT) increased methane yield by 6 to 8% at 51 days and accelerated VFA degradation and methane production. More significant differences in methane yield were observed at shorter solid retention times. Biochar mixed in feedstock in addition to a filter in the LT performed best in terms of both methane and hydrogen sulfide production, with a 77% reduction in hydrogen sulfide yield and hydrogen sulfide contents maintained below 500 ppm. The enhanced rates of VFA degradation and methane production when applying biochar in both reactors corresponds with observed differences in the methanogen population. Biochar application in both reactors increased the abundance of Methanobacteriales in digestate and Methanosarcinaceae in leachate compared to the control. Microbial attachment and activity on biochar also increased when mixed in feedstock. Increased diversity of the methanogen population throughout the system, as well as increased activity on biochar, may have facilitated the syntrophic relationship between acetogenic bacteria and methanogens, thus accelerating VFA degradation and methane production. These results suggest mixing biochar in feedstock, in addition to a biochar filter in the LT, to enhance anaerobic digestion of chicken litter in this system.

Chemical, Antioxidant and Biological Studies of Brassica incana subsp. raimondoi (Brassicaceae) Leaf Extract.

Brassica incana subsp. raimondoi is an endemic taxon present in a restricted area located on steep limestone cliffs at an altitude of about 500 m a.s.l. in eastern Sicily. In this research, for the first time, studies on the phytochemical profile, the antioxidant properties in cell-free and cell-based systems, the cytotoxicity on normal and cancer cells by 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT) assay, and on Artemia salina Leach, were performed. The total phenolic, flavonoid, and condensed tannin contents of the leaf hydroalcoholic extract were spectrophotometrically determined. Ultra-performance liquid chromatography-tandem mass spectrometer (UPLC-MS/MS) analysis highlighted the presence of several phenolic acids, flavonoids, and carotenoids, while High-Performance Liquid Chromatography with Diode-Array Detection (HPLC-DAD) identified various kaempferol and isorhamnetin derivatives. The extract exhibited different antioxidant properties according to the five in vitro methods used. Cytotoxicity by MTT assay evidenced no impact on normal human fibroblasts (HFF-1) and prostate cancer cells (DU145), and cytotoxicity accompanied by necrotic cell death for colon cancer cells (CaCo-2) and hepatoma cells (HepG2), starting from 100 µg/mL and 500 µg/mL, respectively. No cytotoxic effects were detected by the A. salina lethality bioassay. In the H2O2-induced oxidative stress cell model, the extract counteracted cellular reactive oxygen species (ROS) production and preserved non-protein thiol groups (RSH) affected by H2O2 exposure in HepG2 cells. Results suggest the potential of B. incana subsp. raimondoi as a source of bioactive molecules.

Feather chemicals contain information about the major histocompatibility complex in a highly scented seabird.

Mate choice informed by the immune genes of the major histocompatibility complex (MHC) may provide fitness benefits including offspring with increased immunocompetence. Olfactory cues are considered the primary mechanism organisms use to evaluate the MHC of potential mates, yet this idea has received limited attention in birds. Motivated by a finding of MHC-dependent mate choice in the Leach's storm-petrel (Oceanodroma leucorhoa), we examined whether the chemical profiles of this highly scented seabird contain information about MHC genes. Whereas previous studies in birds examined non-volatile compounds, we used gas chromatography-mass spectrometry to measure the volatile compounds emitted from feathers that potentially serve as olfactory infochemicals about MHC and coupled this with locus-specific genotyping of MHC IIB genes. We found that feather chemicals reflected individual MHC diversity through interactions with sex and breeding status. Furthermore, similarity in MHC genotype was correlated with similarity in chemical profiles within female-female and male-female dyads. We provide the first evidence that volatile chemicals from bird feathers can encode information about the MHC. Our findings suggest that olfaction likely aids MHC-based mate choice in this species and highlight a role for chemicals in mediating genetic mate choice in birds where this mode of communication has been largely overlooked.

A Secure LEACH-PRO Protocol Based on Blockchain.

Wireless Sensor Networks (WSNs) are becoming more popular for many applications due to their convenient services. However, sensor nodes may suffer from significant security flaws, leading researchers to propose authentication schemes to protect WSNs. Although these authentication protocols significantly fulfill the required protection, security enhancement with less energy consumption is essential to preserve the availability of resources and secure better performance. In 2020, Youssef et al. suggested a scheme called Enhanced Probabilistic Cluster Head Selection (LEACH-PRO) to extend the sensors' lifetime in WSNs. This paper introduces a new variant of the LEACH-PRO protocol by adopting the blockchain security technique to protect WSNs. The proposed protocol (SLEACH-PRO) performs a decentralized authentication mechanism by applying a blockchain to multiple base stations to avoid system and performance degradation in the event of a station failure. The security analysis of the SLEACH-PRO is performed using Burrows-Abadi-Needham (BAN) logic and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. Moreover, the SLEACH-PRO is evaluated and compared to related protocols in terms of computational cost and security level based on its resistance against several attacks. The comparison results showed that the SLEACH-PRO protocol is more secure and requires less computational cost compared to other related protocols.

Blockchain Based Authentication and Cluster Head Selection Using DDR-LEACH in Internet of Sensor Things.

This paper proposes a blockchain-based node authentication model for the Internet of sensor things (IoST). The nodes in the network are authenticated based on their credentials to make the network free from malicious nodes. In IoST, sensor nodes gather the information from the environment and send it to the cluster heads (CHs) for additional processing. CHs aggregate the sensed information. Therefore, their energy rapidly depletes due to extra workload. To solve this issue, we proposed distance, degree, and residual energy-based low-energy adaptive clustering hierarchy (DDR-LEACH) protocol. DDR-LEACH is used to replace CHs with the ordinary nodes based on maximum residual energy, degree, and minimum distance from BS. Furthermore, storing a huge amount of data in the blockchain is very costly. To tackle this issue, an external data storage, named as interplanetary file system (IPFS), is used. Furthermore, for ensuring data security in IPFS, AES 128-bit is used, which performs better than the existing encryption schemes. Moreover, a huge computational cost is required using a proof of work consensus mechanism to validate transactions. To solve this issue, proof of authority (PoA) consensus mechanism is used in the proposed model. The simulation results are carried out, which show the efficiency and effectiveness of the proposed system model. The DDR-LEACH is compared with LEACH and the simulation results show that DDR-LEACH outperforms LEACH in terms of energy consumption, throughput, and improvement in network lifetime with CH selection mechanism. Moreover, transaction cost is computed, which is reduced by PoA during data storage on IPFS and service provisioning. Furthermore, the time is calculated in the comparison of AES 128-bit scheme with existing scheme. The formal security analysis is performed to check the effectiveness of smart contract against attacks. Additionally, two different attacks, MITM and Sybil, are induced in our system to show our system model's resilience against cyber attacks.

Determination of the Phenolic Profile by Liquid Chromatography, Evaluation of Antioxidant Activity and Toxicity of Moroccan Erica multiflora, Erica scoparia, and Calluna vulgaris (Ericaceae).

This study aimed to investigate the phenolic profile and selected biological activities of the leaf and aerial extracts of three Ericaceae species, namely Erica multiflora, Erica scoparia, and Calluna vulgaris, collected from three different places in the north of Morocco. The phenolic composition of all extracts was determined by LC coupled with photodiode array and mass spectrometry detection. Among the investigated extracts, that of E. scoparia aerial parts was the richest one, with a total amount of polyphenols of 9528.93 mg/kg. Up to 59 phenolic compounds were detected: 52 were positively identified and 49 quantified-11 in C. vulgaris, 14 in E. multiflora, and 24 in E. scoparia. In terms of chemical classes, nine were phenolic acids and 43 were flavonoids, and among them, the majority belonged to the class of flavonols. The antioxidant activity of all extracts was investigated by three different in vitro methods, namely DPPH, reducing power, and Fe2+ chelating assays; E. scoparia aerial part extract was the most active, with an IC50 of 0.142 ± 0.014 mg/mL (DPPH test) and 1.898 ± 0.056 ASE/mL (reducing power assay). Further, all extracts were non-toxic against Artemia salina, thus indicating their potential safety. The findings attained in this work for such Moroccan Ericaceae species, never investigated so far, bring novelty to the field and show them to be valuable sources of phenolic compounds with interesting primary antioxidant properties.

Phenolic and Volatile Composition and Antioxidant Properties of the Leaf Extract of Brassica fruticulosa subsp. fruticulosa (Brassicaceae) Growing Wild in Sicily (Italy).

In continuation of research conducted on species of the spontaneous flora of Sicily (Italy) belonging to the Brassicaceae family, Brassica fruticulosa subsp. fruticulosa was selected. It is an edible species utilized in Sicilian traditional medicine. In this study, for the first time, the phenolic and the volatile compounds and the antioxidant properties of the hydroalcoholic extract obtained from the leaves of B. fruticulosa subsp. fruticulosa were characterized. Through HPLC-PDA/ESI-MS analysis, a total of 22 polyphenolic compounds (20 flavonoids and 2 phenolic acids) were identified, with 3-hydroxiferuloylsophoroside-7-O-glucoside (1.30 mg/g ± 0.01) and kaempferol-3-O-feruloylsophoroside-7-O-glucoside (1.28 mg/g ± 0.01) as the most abundant compounds. Through SPME-GC/MS several volatiles belonging to different chemical classes were characterized, with nitriles and aldehydes accounting for more than 54% of the whole volatile fraction. The extract of B. fruticulosa subsp. fruticulosa showed moderate activity in the DPPH assay (IC50 = 1.65 ± 0.08 mg/mL), weak reducing power (17.47 ± 0.65 ASE/mL), and good chelating properties (IC50 = 0.38 ± 0.02 mg/mL), reaching approximately 90% activity at the highest tested concentration. Lastly, the extract was non-toxic against Artemia salina, indicating its potential safety. According to the findings, it can be stated that B. fruticulosa subsp. fruticulosa represents a new valuable source of bioactive compounds.

EZ-SEP: Extended Z-SEP Routing Protocol with Hierarchical Clustering Approach for Wireless Heterogeneous Sensor Network.

Wireless sensor networks (WSN) are networks of thousands of nodes installed in a defined physical environment to sense and monitor its state condition. The viability of such a network is directly dependent and limited by the power of batteries supplying the nodes of these networks, which represents a disadvantage of such a network. To improve and extend the life of WSNs, scientists around the world regularly develop various routing protocols that minimize and optimize the energy consumption of sensor network nodes. This article, introduces a new heterogeneous-aware routing protocol well known as Extended Z-SEP Routing Protocol with Hierarchical Clustering Approach for Wireless Heterogeneous Sensor Network or EZ-SEP, where the connection of nodes to a base station (BS) is done via a hybrid method, i.e., a certain amount of nodes communicate with the base station directly, while the remaining ones form a cluster to transfer data. Parameters of the field are unknown, and the field is partitioned into zones depending on the node energy. We reviewed the Z-SEP protocol concerning the election of the cluster head (CH) and its communication with BS and presented a novel extended mechanism for the selection of the CH based on remaining residual energy. In addition, EZ-SEP is weighted up using various estimation schemes such as base station repositioning, altering the field density, and variable nodes energy for comparison with the previous parent algorithm. EZ-SEP was executed and compared to routing protocols such as Z-SEP, SEP, and LEACH. The proposed algorithm performed using the MATLAB R2016b simulator. Simulation results show that our proposed extended version performs better than Z-SEP in the stability period due to an increase in the number of active nodes by 48%, in efficiency of network by the high packet delivery coefficient by 16% and optimizes the average power consumption compared to by 34.

Feature-Selection and Mutual-Clustering Approaches to Improve DoS Detection and Maintain WSNs' Lifetime.

Wireless Sensor Networks (WSNs) continue to face two major challenges: energy and security. As a consequence, one of the WSN-related security tasks is to protect them from Denial of Service (DoS) and Distributed DoS (DDoS) attacks. Machine learning-based systems are the only viable option for these types of attacks, as traditional packet deep scan systems depend on open field inspection in transport layer security packets and the open field encryption trend. Moreover, network data traffic will become more complex due to increases in the amount of data transmitted between WSN nodes as a result of increasing usage in the future. Therefore, there is a need to use feature selection techniques with machine learning in order to determine which data in the DoS detection process are most important. This paper examined techniques for improving DoS anomalies detection along with power reservation in WSNs to balance them. A new clustering technique was introduced, called the CH_Rotations algorithm, to improve anomaly detection efficiency over a WSN's lifetime. Furthermore, the use of feature selection techniques with machine learning algorithms in examining WSN node traffic and the effect of these techniques on the lifetime of WSNs was evaluated. The evaluation results showed that the Water Cycle (WC) feature selection displayed the best average performance accuracy of 2%, 5%, 3%, and 3% greater than Particle Swarm Optimization (PSO), Simulated Annealing (SA), Harmony Search (HS), and Genetic Algorithm (GA), respectively. Moreover, the WC with Decision Tree (DT) classifier showed 100% accuracy with only one feature. In addition, the CH_Rotations algorithm improved network lifetime by 30% compared to the standard LEACH protocol. Network lifetime using the WC + DT technique was reduced by 5% compared to other WC + DT-free scenarios.

Individual Chemical Profiles in the Leach's Storm-Petrel.

Avian chemical communication, once largely overlooked, is a growing field that has revealed the important role that olfaction plays in the social lives of some birds. Leach's storm-petrels (Oceanodroma leucorhoa) have a remarkable sense of smell and a strong, musky scent. This long-lived, monogamous seabird relies on olfaction for nest relocation and foraging, but whether they use scent for communication is less well studied. They are nocturnally active at the breeding colony and yet successfully reunite with their mate despite poor night-vision, indicating an important role for non-visual communication. We investigated the chemical profiles of Leach's storm-petrels to determine whether there is socially relevant information encoded in their plumage odor. To capture the compounds comprising their strong scent, we developed a method to study the compounds present in the air surrounding their feathers using headspace stir bar sorptive extraction coupled with gas chromatography-mass spectrometry. We collected feathers from Leach's storm-petrels breeding on Bon Portage Island in Nova Scotia, Canada in both 2015 and 2016. Our method detected 142 commonly occurring compounds. We found interannual differences in chemical profiles between the two sampling years. Males and females had similar chemical profiles, while individuals had distinct chemical signatures across the two years. These findings suggest that the scent of the Leach's storm-petrel provides sociochemical information that could facilitate olfactory recognition of individuals and may inform mate choice decisions.

Optimal Cluster Head Positioning Algorithm for Wireless Sensor Networks.

Wireless sensor networks (WSNs) are increasingly gaining popularity, especially with the advent of many artificial intelligence (AI) driven applications and expert systems. Such applications require specific relevant sensors' data to be stored, processed, analyzed, and input to the expert systems. Obviously, sensor nodes (SNs) have limited energy and computation capabilities and are normally deployed remotely over an area of interest (AoI). Therefore, proposing efficient protocols for sensing and sending data is paramount to WSNs operation. Nodes' clustering is a widely used technique in WSNs, where the sensor nodes are grouped into clusters. Each cluster has a cluster head (CH) that is used to gather captured data of sensor nodes and forward it to a remote sink node for further processing and decision-making. In this paper, an optimization algorithm for adjusting the CH location with respect to the nodes within the cluster is proposed. This algorithm aims at finding the optimal CH location that minimizes the total sum of the nodes' path-loss incurred within the intra-cluster communication links between the sensor nodes and the CH. Once the optimal CH is identified, the CH moves to the optimal location. This suggestion of CH re-positioning is frequently repeated for new geometric position. Excitingly, the algorithm is extended to consider the inter-cluster communication between CH nodes belonging to different clusters and distributed over a spiral trajectory. These CH nodes form a multi-hop communication link that convey the captured data of the clusters' nodes to the sink destination node. The performance of the proposed CH positioning algorithm for the single and multi-clusters has been evaluated and compared with other related studies. The results showed the effectiveness of the proposed CH positioning algorithm.

Integrating Software Engineering Processes in the Development of Efficient Intrusion Detection Systems in Wireless Sensor Networks.

Applying Software Engineering (SE) processes is vital to critical and complex systems including security and networking systems. Nowadays, Wireless Sensor Networks (WSNs) and their applications are found in many military and civilian systems which make them attractive to security attackers. The increasing risks and system vulnerabilities of WSNs have encouraged researchers and developers to propose many security solutions including software-based Intrusion Detection Systems (IDSs). The main drawbacks of current IDSs are due to the lack of clear, structured software development processes. Unfortunately, a substantial gap has been observed between WSN and SE research communities. Integrating SE and WSNs is an emerging topic that will be expanded as technology evolves and spreads in all life aspects. Consequently, this paper highlighted the importance of Requirement Engineering, Software Design, and Testing when developing IDSs for WSNs. Three software IDS designs were proposed in this study: Scheduling, Broadcast, and Watchdog designs. The three designs were compared in terms of consumed energy and network lifetime. Although the same IDS approach was used, but, by highlighting the design phase and implementing different designs, the network lifetime was increased by 73.6% and the consumed energy was reduced by 20% in some of the designs. This is a clear indication of how following a proper SE process could affect the performance of the IDS in WSN. Moreover, conclusions were drawn in regard to applying software engineering processes to IDSs to deliver the required functionalities, with respect to operational constraints, with an improved performance, accuracy and reliability.

Brassica incana Ten. (Brassicaceae): Phenolic Constituents, Antioxidant and Cytotoxic Properties of the Leaf and Flowering Top Extracts.

Brassica incana Ten. is an edible plant belonging to the Brassicaceae family. In this work, the phenolic composition and the antioxidant and cytotoxic properties of the hydroalcoholic extracts obtained from the leaves and the flowering tops of B. incana grown wild in Sicily (Italy) were studied for the first time. A total of 17 and 20 polyphenolic compounds were identified in the leaf and in the flowering top extracts, respectively, by HPLC-PDA-ESI-MS analysis. Brassica incana extracts showed in vitro antioxidant properties; the leaf extract displayed greater radical scavenging activity in the 2,2-diphenyl-1-picrylhydrazyl (DPPH) test than the flowering top extract (IC50 = 1.306 ± 0.049 mg/mL and 2.077 ± 0.011 mg/mL), which in turn had a stronger ferrous ion chelating ability than the other (IC50 = 0.232 ± 0.002 mg/mL and 1.147 ± 0.016 mg/mL). The cytotoxicity of the extracts against human colorectal adenocarcinoma (CaCo-2) and breast cancer (MCF-7) cell lines was evaluated through the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and the lactic dehydrogenase (LDH) release determination. The extracts showed cytotoxic efficacy against Caco-2 cells, with the flowering top extract being the most effective (about 90% activity at the highest concentration tested). In the brine shrimp lethality bioassay, the extracts exhibited no toxicity, indicating their potential safety.

Development of the Visual System in a Burrow-Nesting Seabird: Leach's Storm Petrel.

Little is known about the development of vision in wild birds. It is unknown, for example, whether the ability to see can be predicted by the level of prenatal growth or whether the eyes are open at hatching in a particular species. In this study, we investigated the growth of eyes, the formation of retinal ganglion cell topography, and the appearance of simple, visually guided behaviours in chicks of a small procellariiform seabird, Leach's storm petrel (Oceanodroma leucorhoa). This semi-precocial species, which has a well-developed sense of smell, nests in underground burrows where adults provision chicks for 6-8 weeks in the dark before fledging. Retinal ganglion cell topographic maps revealed that fine-tuning of cell distribution does not happen early in development, but rather that the ganglion cell layer continues to mature throughout provisioning and probably even after fledging. While the olfactory bulbs reached adult size around 7 weeks after hatching, the eyes and telencephalon continued to grow. Optokinetic head response and artificial burrow finding experiments indicated that chicks in the 2nd week after hatching lack even the most basic visually guided behaviours and are probably blind. Thus, vision in Leach's storm petrel chicks starts to function sometime around the 3rd week after hatching, well after the eyes have opened and the olfactory system is functional.