A novel method for determination of a time period for stabilization of power generation of microbial fuel cell with effect of microorganisms

Microbial fuel cells (MFCs) are quickly gaining traction in the mainstream industry due to their capabilities in simultaneous power generation and wastewater purification. They use bacteria like Shewanella and Geobacter as primary units for the same. However, their power generation capabilities are limited by a lack of stability in certain configurations. For the development of appropriate power storage and management systems, this instability must be investigated. Therefore, the present study proposes the artificial intelligence (AI) methodology of artificial neural search (ANS) networks to predict the period for stabilization of power generation of microbial fuel cell in the presence of microorganisms. An output voltage has been measured as a function of time (approximately 1600 h). A stabilization period of power generation has been predicted from the slope obtained from the graph of voltage vs time. The analysis of the ANS model indicated that the power generation stabilization has occurred between 12th and 16th weeks. Experiments were then performed to validate the findings from the ANS model. This may serve as an indication for the development of energy management and storage systems that can account for the trends observed during this study     

A survey on analyzing encrypted network traffic of mobile devices

International Journal of Information Security - Over the years, use of smartphones has come to dominate several areas, improving our lives, offering us convenience, and reshaping our daily work...     

Adaptive reallocation of cybersecurity analysts to sensors for balancing risk between sensors

Cyber Security Operations Center (CSOC) is a service-oriented system. Analysts work in shifts, and the goal at the end of each shift is to ensure that all alerts from each sensor (client) are analyzed. The goal is often not met because the CSOC is faced with adverse conditions such as variations in alert generation rates or in the time taken to thoroughly analyze new alerts. Current practice at many CSOCs is to pre-assign analysts to sensors based on their expertise, and the alerts from the sensors are triaged, queued, and presented to analysts. Under adverse conditions, some sensors have more number of unanalyzed alerts (backlogs) than others, which results in a major security gap for the clients if left unattended. Hence, there is a need to dynamically reallocate analysts to sensors; however, there does not exist a mechanism to ensure the following objectives: (i) balancing the number of unanalyzed alerts among sensors while maximizing the number of alerts investigated by optimally reallocating analysts to sensors in a shift, (ii) ensuring desirable properties of the CSOC: minimizing the disruption to the analyst to sensor allocation made at the beginning of the shift when analysts report to work, balancing of workload among analysts, and maximizing analyst utilization. The paper presents a technical solution to achieve the objectives and answers two important research questions: (i) detection of triggers, which determines when-to reallocate, and (ii) how to optimally reallocate analysts to sensors, which enable a CSOC manager to effectively use reallocation as a decision-making tool.     

A new single-component low-cost emitter etch-back process for silicon wafer solar cells

A way of achieving lightly doped emitter is a combination of a heavy emitter diffusion and emitter etch back, which has an added advantage of phosphorous diffusion gettering. However, this chemical emitter etch-back process must fulfil some critical requirements, e.g. cost-effectiveness, near-conformal Si etching even after deep emitter etch back, controlled Si etch rate, post-etch clean Si surface and lowest safety issues in chemical handling and drainage. In this work, we report a new low-cost (less than 1 US Cents/wafer), single-chemical, non-acidic, high-throughput emitter etch-back process for tube-diffused emitters for crystalline Si wafers. This process uses only sodium hypochlorite solution at 80 °C as the Si etchant. This process is versatile with its applications on phosphorous and boron tube-diffused monocrystalline Si and phosphorous tube-diffused multicrystalline Si wafers. The preparation, usage and drainage of this highly diluted solution are easy and safe. The Si etching process leads to excellent spatial uniformity over large-area Si wafers (243 cm²). With deep etch back resulting in a change of sheet resistance by ~60 Ω/sq, the standard deviation value changes by only 2.7%. High surface conformity in the etch-back surface is evident from reflectance studies. Quasi-steady-state photoconductance and photoluminescence imaging are used to demonstrate improved electrical parameters of the etch-back wafers.     

Multipronged,strategic delivery of paclitaxel-topotecan using engineered liposomes to ovarian cancer

Context: Synergistically active combinations have been used to enhance therapeutic efficacy for ovarian cancer chemotherapy.

Objective: The synergistically active combination of paclitaxel-topotecan (Pac-Top; 20:1, w/w) were loaded into folate-anchored PEGylated liposomes (FPL-Pac-Top) for safe and effective treatment of ovarian cancer.

Materials and methods: Coupling reactions were carried out using carbodiimide chemistry and confirmed by infrared spectral analysis. These liposomes were studied for shape and physical interaction (and integrity), in vitro drug release kinetics, hemolytic toxicity, ex vivo pharmacodynamics in OVCAR-3 cell lines, and pharmacokinetics in ovarian tumor-bearing mice.

Results: The differential scanning calorimeter studies exhibited melting of liposomes (～150?nm) at ～41?°C. The drug(s) release from liposomes followed Fickian diffusion model. The hematological studies revealed insignificant toxicity to blood cells. In vivo studies showed long circulatory behavior (increased AUC_0–t and AUMC_0–t and MRT) and selective accumulation of FPL-Pac-Top in the ovaries. FPL-Pac-Top showed less necrosis and more apoptosis in flow cytometry. Kaplan–Meier survival analysis revealed the doubling of the survival time with FPL-Pac-Top in comparison to Pac-Top solution.

Discussion and conclusion: Potentiated anti-cancer activity of FPL-Pac-Top was attributed to multiple features viz. thermosensitivity, long circulatory nature and targetability. Such approach could be a paradigm chemotherapeutic approach for safe and effective targeting of cancer.     

Identifying influential nodes in weighted complex networks using an improved WVoteRank approach

Influence maximization is an important research problem in the field of network science because of its business value. It requires the strategic selection of seed nodes called “influential nodes,” such that information originating from these nodes can reach numerous nodes in the network. Many real-world networks, such as transportation, communication, and social networks, are weighted networks. Influence maximization in a weighted network is more challenging compared to that in an unweighted network. Many methods, such as weighted degree rank, weighted h-index, weighted betweenness, and weighted VoteRank techniques, have been used to order the nodes based on their spreading capabilities in weighted networks. The VoteRank method is a popular method for finding influential nodes in an unweighted network using the idea of a voting scheme. Recently, the WVoteRank method was proposed to find the seed nodes; it extends the idea of the VoteRank method by considering the edge weights. This method considers only 1-hop neighbors to calculate the voting score of every node. In this study, we propose an improved WVoteRank method based on an extended neighborhood concept, which takes the 1-hop neighbors as well as 2-hop neighbors into account for the voting process to decide influential nodes in a weighted network. We also extend our proposed approach to unweighted networks. We compare the performance of the proposed improved WVoteRank method against the popular centrality measures, weighted degree, weighted closeness, weighted betweenness, weighted h-index, and weighted VoteRank on several real-life and synthetic datasets of diverse sizes and properties. We utilize the widely used stochastic susceptible–infected–recovered information diffusion model to calculate the infection scale, the final infected scale as a function of time, and the average distance between spreaders. The simulation results reveal that the proposed method, improved WVoteRank, considerably outperforms the other methods described above, including the recent WVoteRank.

     

A wideband rectangular and circular ring‐shaped patch antenna with gap coupled meandered parasitic elements for wireless applications

A new design of a gap coupled rectangular patch antenna with meandered parasitic elements and a circular ring at the feed line has been proposed for Bluetooth, WLAN, WiMAX, C, and X band applications. Multibands at 1.26 to 1.36 GHz, 1.83 to 3.81 GHz, 7.6 to 7.85 GHz, 9.6 to 10.74 GHz, and 13.58 to 14.23 GHz with impedance bandwidth of 6.0% and 70.21%, 3.23%, 11.2%, and 4.67%, respectively, are observed. Multiple bandwidth enhancement techniques such as using symmetrical meandered parasitic patches, gap coupling, and defected ground have been employed in one design. Circular ring feed structure and meandered parasitic patches enhance the percentage impedance bandwidth from 12.11% to 70.21%.     

Information Lower Bounds via Self-Reducibility

We use self-reduction methods to prove strong information lower bounds on two of the most studied functions in the communication complexity literature: Gap Hamming Distance (GHD) and Inner Product (IP). In our first result we affirm the conjecture that the information cost of GHD is linear even under the uniform distribution, which strengthens the Ω(n) bound recently shown by Kerenidis et al. (2012), and answers an open problem from Chakrabarti et al. (2012). In our second result we prove that the information cost of IP_n is arbitrarily close to the trivial upper bound n as the permitted error tends to zero, again strengthening the Ω(n) lower bound recently proved by Braverman and Weinstein (Electronic Colloquium on Computational Complexity (ECCC) 18, 164 2011). Our proofs demonstrate that self-reducibility makes the connection between information complexity and communication complexity lower bounds a two-way connection. Whereas numerous results in the past (Chakrabarti et al. 2001; Bar-Yossef et al. J. Comput. Syst. Sci. 68(4), 702–732 2004; Barak et al. 2010) used information complexity techniques to derive new communication complexity lower bounds, we explore a generic way in which communication complexity lower bounds imply information complexity lower bounds in a black-box manner.     

A High Resolution Assessment of Water Footprint of Wheat to Understand Yield and Water Use Heterogeneity

Efficient water use remains a major challenge globally. Semi-arid regions of the eastern plains of the state of Uttar Pradesh are no different. With stagnating yields and increased input achieving homogeneity in crop yield remains the only way to increase production. Water being the main drive, its judicious use is to be encouraged. Heterogeneity in water usage resulting in yield heterogeneity has to be quantified. It explains the extent of problem. This research conducted at Samrakalwana village at Allahabad reveals that a 36.12 % heterogeneity in water usage results in wheat yield heterogeneity of 44.04 %. Based upon this, management practices can be recommended to the farmers to minimize yield gap. Water footprints for wheat were obtained. The obtained water footprints for wheat were found to vary between 9844 to 2951 l/Kg. The water productivity ranged from 3.88 to 1.01 Tonnes/m³. This huge variation also explains the large heterogeneity is present in utilizing existing water as a resource at the Samrakalwana village.